# Comfy CLI
Source: https://docs.comfy.org/agent-tools/cli

Drive Comfy from the terminal: local ComfyUI, partner generate calls, and full workflows on Comfy Cloud. Complements MCP for scripts, CI, and automation.

[comfy-cli](https://github.com/Comfy-Org/comfy-cli) is Comfy's command-line tool. Alongside [MCP servers](/agent-tools), it gives agents and developers another way to drive Comfy from outside the UI.

Use it for **terminal or script access**: batch jobs, CI pipelines, workflow automation, and pairing with coding agents via bundled CLI skills.

<Info>
  **Quick reference for agents.** This page is a shortened overview: enough to get oriented alongside MCP and run common `comfy generate` calls. For the **complete CLI documentation** (local install, `comfy setup`, `comfy run`, templates, workflow editing, node/model discovery, and more), see [Comfy CLI getting started](/comfy-cli/getting-started).
</Info>

<Info>
  **`comfy generate` is in beta.** Flag names, model aliases, and output formats may change. The underlying partner endpoints are stable. File feedback on the [comfy-cli GitHub repo](https://github.com/Comfy-Org/comfy-cli/issues).
</Info>

## How it fits with MCP

| | Comfy MCP (cloud) | Comfy CLI |
| - | - | - |
| **Interface** | Chat with an MCP client (Claude Code, Claude Desktop, …) | Terminal commands and scripts |
| **Best for** | Interactive agent workflows in chat | Automation, batch runs, CI, shell pipelines |
| **Auth** | OAuth in MCP clients, or API key (headless) | `comfy cloud login` (OAuth) or API key (CI) |
| **Output** | Returned in the chat session | Saved to disk (`--download`) or JSON (`--json`) |

For MCP setup, installation, tool lists, and auth methods, see [Comfy MCP](/agent-tools/mcp).

## What the CLI does

1. **Local ComfyUI** — install, launch, update, and manage custom nodes
2. **Partner generation** — `comfy generate` for one-shot image/video/audio/3D partner API calls
3. **Cloud workflows** — `comfy run`, templates, slot editing, and job watching on Comfy Cloud

<Note>
  **Two surfaces, one CLI.** Every command auto-detects where to run. If you are signed in to Comfy Cloud, commands route to **cloud**; otherwise they run against your **local** server. Override per call with `--where local|cloud`, the `COMFY_WHERE` env var, or persist it with `comfy set-default --where cloud`.
</Note>

## Install and set up

<CodeGroup>
  ```bash pip theme={null}
  pip install comfy-cli
  ```

  ```bash homebrew theme={null}
  brew tap Comfy-Org/comfy-cli
  brew install comfy-org/comfy-cli/comfy-cli
  ```
</CodeGroup>

To get shell completion hints:

```bash theme={null}
comfy --install-completion
```

```bash theme={null}
comfy setup
```

Pass `-y` for non-interactive installs in CI or scripts. See [Comfy CLI getting started](/comfy-cli/getting-started#quick-setup-recommended) for the full `comfy setup` flag table.

Sign in to Comfy Cloud:

```bash theme={null}
comfy cloud login
comfy cloud whoami
```

## Prerequisites for `comfy generate`

* An active Comfy Cloud session via `comfy cloud login` (browser OAuth), **or** a [Comfy API key](/development/api-development/getting-an-api-key) (`--api-key` / `COMFY_API_KEY`) for headless or CI use
* [Credits](/interface/credits) on your account
* *Optional:* [Browse partner nodes and per-call pricing](/tutorials/partner-nodes/pricing)

## Your first generation

```bash theme={null}
comfy generate flux-pro \
    --prompt "a cat on the moon, cinematic lighting" \
    --width 1024 --height 1024 \
    --download cat.png
```

The CLI uploads local files, submits the job, polls for completion, and saves results.

## Available models

`comfy generate` covers image and video partner models. Discover what is available in your CLI version:

```bash theme={null}
comfy generate list                            # all models
comfy generate list --category text-to-video   # filter by category
comfy generate list --partner kling            # filter by partner
comfy generate schema flux-kontext             # params for one model
```

Common aliases include:

| Category | Examples |
| - | - |
| **Image** | `flux-pro`, `flux-ultra`, `flux-kontext`, `nano-banana`, `grok`, `grok-edit`, `ideogram-edit`, `dalle`, `recraft`, `stability` |
| **Video** | `seedance`, `kling`, `luma`, `runway`, `pika`, `vidu`, `hailuo`, `moonvalley`, `grok-video` |

Run `comfy generate list` for the full set in your environment.

## Usage examples

### Text-to-image

```bash theme={null}
comfy generate nano-banana \
    --prompt "a watercolor of a sleeping fox" \
    --download fox.png
```

### Image edit (reference image)

Pass local file paths. The CLI uploads via Comfy's storage endpoint or base64-encodes as needed:

```bash theme={null}
comfy generate nano-banana \
    --prompt "add a top hat" \
    --image ./cat.png \
    --download edited.png

comfy generate flux-kontext \
    --prompt "add a top hat and a monocle" \
    --input_image ./photo.jpg \
    --download out.png

comfy generate ideogram-edit \
    --image cat.png --mask mask.png \
    --prompt "add sunglasses" \
    --rendering_speed TURBO \
    --download edited.png
```

To upload once and reuse across calls:

```bash theme={null}
comfy generate upload ./photo.jpg     # prints a signed URL
```

<Note>
  Uploaded reference assets auto-delete after **24 hours**. They are stored in Comfy-managed GCS with signed URLs. For long-running pipelines, re-upload before each job. See the [reference](/comfy-cli/reference) for details.
</Note>

### Text-to-video

Video jobs are async. The CLI blocks and polls by default:

```bash theme={null}
comfy generate seedance \
    --prompt "a hummingbird hovering over a flower" \
    --resolution 1080p --duration 5 \
    --download hummingbird.mp4

comfy generate kling \
    --prompt "a paper boat drifting on a river at dusk" \
    --duration 5 \
    --download boat.mp4
```

Return immediately with `--async`, then resume later:

```bash theme={null}
comfy generate luma --prompt "neon koi swimming through clouds" --aspect_ratio 16:9 --async
# prints a job id; resume with:
comfy generate resume luma <job_id> --download out.mp4
```

### Scripting with JSON

```bash theme={null}
comfy generate dalle --prompt "a watercolor whale" --json | jq '.data[0].url'
```

## Beyond `comfy generate`

Everything above is the agent-focused summary. The full guide walks through each command in depth:

* `comfy run`, `comfy jobs`, and `comfy validate` for full workflows
* `comfy templates` and `comfy workflow` slot editing
* `comfy nodes` / `comfy models` discovery
* `--json` envelopes and `comfy --json discover` for agents

→ [Comfy CLI getting started](/comfy-cli/getting-started) (complete documentation)

## Agent skills

Install the bundled Comfy agent skills into Claude Code, Cursor, and any AGENTS.md-aware tool, so your coding agent can drive the CLI directly:

```bash theme={null}
comfy skills install
comfy skills list      # comfy, comfy-fragments, comfy-debug, comfy-relay, comfy-director
comfy skills status    # what's installed where
```

<Note>
  These are **bundled CLI skills** installed by `comfy skills install`. They are separate from the [Comfy Skills](https://github.com/Comfy-Org/comfy-skills/) repository, which hosts the **comfy-cloud** Claude Code plugin for [Comfy Cloud MCP](/agent-tools/mcp).
</Note>

## Related resources

| Resource | What it's for |
| - | - |
| [Comfy CLI getting started](/comfy-cli/getting-started) | **Complete** install guide and command walkthrough |
| [Comfy CLI reference](/comfy-cli/reference) | Commands, flags, and model aliases |
| [Comfy MCP](/agent-tools/mcp) | Connect agents via MCP for chat-driven generation |
| [comfy-cli on GitHub](https://github.com/Comfy-Org/comfy-cli) | Source repo, issues, and latest behavior |

## Feedback

* **GitHub**: [comfy-cli issues](https://github.com/Comfy-Org/comfy-cli/issues)
* **Discord**: [#comfy-mcp-and-cli](https://discord.gg/xWJn6nhE3R)


# Comfy Agent
Source: https://docs.comfy.org/agent-tools/in-app-agent

Use Comfy Agent to understand, build, edit, and run ComfyUI workflows. It is generally available in Comfy Cloud. Local support for Comfy Desktop is coming soon.

<Note>
  **Comfy Agent is generally available in Comfy Cloud**. Agent inside Comfy Desktop on local is coming soon. [Join the waitlist](https://links.comfy.org/agentalpha) to get notified.
</Note>

Describe what you want right inside ComfyUI. It plans, builds, and runs workflows. Editing the canvas while you work, it crafts side by side with you.

## What it can do

* Find templates, models, and nodes available in your ComfyUI environment.
* Build a workflow from a template and customize its prompts and settings.
* Change part of the current workflow without rebuilding the rest.
* Add, connect, configure, and remove nodes.
* Validate a workflow before running it.
* Inspect images and read video or audio properties.
* Run workflows and return their outputs.
* Keep working on the canvas while the Agent responds — you don't have to wait for it to finish, and it works from what you currently have open.
* Create a skill in plain language, or ask the Agent to use one of Comfy's public skills instead of only your own. See [Agent skills](/agent-tools/in-app-agent-skills).
* Open more than one chat at once. Each chat is its own session with its own history and context.

## Where you can use it

| Where you use Comfy Agent | What to expect |
| - | - |
| **Comfy Cloud** | Generally available. The Agent, workflows, and assets use your Comfy Cloud account. There is no local package to install. |
| **Comfy Desktop** | **Coming soon.** [Join the waitlist](https://links.comfy.org/agentalpha) to get notified when Comfy Agent is available for local ComfyUI, including your own models and custom nodes. |

Either way, Agent requests use Comfy services over the network. See [Data and privacy](/agent-tools/in-app-agent-data-privacy).

Comfy Agent is separate from [Comfy MCP](/agent-tools/mcp) and [Comfy CLI](/agent-tools/cli). MCP connects an external AI client to Comfy. The CLI is for terminal and script workflows. Comfy Agent works in the ComfyUI interface.

To make your first image, follow [Get started with Comfy Agent](/agent-tools/in-app-agent-installation#make-your-first-image).

## What it costs

Free initial tokens are now available for everyone to try several Comfy Agent chats. After that, Comfy Agent charges from the same Comfy Credits pool you already use for generations.
You need a positive balance in Comfy Credits to keep running the Agent, but you don't necessarily need a subscription plan. See the [subscription and top-up plans](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=agent) for plan details.

### Pricing per token

| Model | Input credits / 1K | 5m Cache Write credits / 1K | 1h Cache Write credits / 1K | Cache Hit credits / 1K | Output credits / 1K |
| :- | -: | -: | -: | -: | :- |
| Opus 4.8 | 1.055 | 1.319 | 2.110 | 0.106 | 5.275 |

## Coming soon on local

Once Comfy Agent reaches Comfy Desktop, it will work with your own GPU, models, and custom nodes, and walk you through setup. It will also go beyond what's on Cloud today: building custom editing tools directly on the canvas for you, such as a one-off masking or compositing tool you didn't have to install.

<Card title="Join the waitlist" icon="list" href="https://links.comfy.org/agentalpha">
  Get notified when Comfy Agent is available for Comfy Desktop.
</Card>

## Choose which workflow to edit

Use the workflow selector in the Agent panel to choose the workflow to edit, then send your message. Switching to another tab while the Agent is responding does not redirect its edits.

The Agent cannot create or switch tabs itself. To work elsewhere, open the other workflow, choose it in the Agent panel, and send a new message.

The Agent can read another open or saved workflow for comparison without loading it into the current tab. For example:

> Compare this workflow with my portrait workflow and use the same sampler settings here.

## Build and edit workflows

For a new workflow, open a blank workflow tab and choose it in the Agent panel. The Agent searches for a matching template before building from individual nodes. A template includes a connected graph and an output node.

For changes to an existing workflow, name the part you want changed and what should stay the same:

* “Change the prompt to a watercolor landscape. Keep the model and sampler settings.”
* “Add an upscaling stage after image generation.”
* “Switch this workflow to Flux using models installed here.”

The Agent builds in real time on the canvas while you keep editing the canvas.

## Validate before running

The Agent checks node connections, model names, required values, and output nodes before a run. It separates workflow errors from inputs that only you can provide.

If the workflow is valid but still needs an image, video, or other input, attach the file and ask the Agent to continue.

## Work with media

The Agent can inspect the visible contents and dimensions of a still image. For video, it can read the duration, dimensions, frame rate, and format. For audio, it can read the duration, format, and audio tracks.

Use **Attach a file** in the message box to add an image or file. You can also drag media into the conversation.

| Add to the conversation | Ask | Result |
| - | - | - |
| An image | “Describe the lighting in this image.” | A description you can use to refine your prompt. |
| A video | “Trim this to the first five seconds.” | A shortened video file. |
| Two video clips | “Join clip A followed by clip B.” | One video containing both clips in that order. |
| A video and an audio file | “Add this audio to the video.” | A video with the supplied audio. |

Media editing requires the media tools to be available in your installation. In Cloud, edited files are saved to your asset library. The Agent returns a preview or file link in the conversation.

## Run permissions

Choose a run permission next to the message box:

* **Ask** requests approval before each workflow run.
* **Auto** runs workflows without asking for each run.

Select **Save changes** to apply your choice. In Ask mode, select **Run** in the approval message to start the workflow, or **Cancel** to decline that run.

Ask and Auto control workflow runs. The Agent can edit the selected workflow in either mode.

## What the Agent can use

Normally in a chat session, the Agent uses your message, selected workflow, selected nodes, attachments, and workflow errors. It can also read another workflow when you ask it to compare or reuse settings.
Besides, the agent also has access to the saved workflows, available models and available nodes in the current workspace, as well as public template workflows and public/private skills, which will all be used when needed.

For Cloud and local data flow, chat history, and privacy controls, see [Comfy Agent data and privacy](/agent-tools/in-app-agent-data-privacy).

## Stop or cancel

Select **Stop** in the message box to stop the Agent's current response. Workflow execution has separate controls in the [run and queue area](/interface/overview); use those to manage a workflow that has already been submitted.

## Next steps

<CardGroup>
  <Card title="Make your first image" icon="play" href="/agent-tools/in-app-agent-installation#make-your-first-image">
    Build, run, and revise an image workflow.
  </Card>

  <Card title="Agent skills" icon="wand-magic-sparkles" href="/agent-tools/in-app-agent-skills">
    Create and use reusable Agent instructions.
  </Card>
</CardGroup>

## Feedback

Comfy Agent is currently in beta. We are actively developing new features and fixing issues. Tell us what works and what doesn't and it is the best way to help us prioritize the right things to build.

* Feedback: [https://links.comfy.org/agentfeedback](https://links.comfy.org/agentfeedback)
* Discord: join our [server](https://discord.com/invite/comfyorg) and find us in #comfy-agent channel

<Card title="Send feedback" icon="message" href="https://links.comfy.org/agentalphafeedback">
  Report bugs or share impressions.
</Card>


# Comfy Agent Data and Privacy
Source: https://docs.comfy.org/agent-tools/in-app-agent-data-privacy

Understand what Comfy Agent uses to answer a request and how local and Cloud use differ.

## The short version

Comfy Agent uses your message, selected workflow, selected nodes, and attachments. When you work with a local ComfyUI installation, chat history is stored on that machine. Your message and the information needed to answer it are sent through Comfy's online service.

## What the Agent uses

| Data | How it helps |
| - | - |
| Your message | Tells the Agent what you want to do. |
| Selected workflow and nodes | Show which workflow and nodes you want explained or changed. |
| Image attachment | Lets the Agent inspect the image and use it in a workflow. |
| Video or audio attachment | Lets the Agent read media properties and extract or convert content. |
| Workflow and execution errors | Help the Agent explain and fix a failed workflow. |
| Personal skill | Supplies reusable instructions. |

The [Privacy Policy](https://www.comfy.org/privacy-policy?utm_source=docs) and [Terms of Service](https://www.comfy.org/terms-of-service?utm_source=docs) govern your use of Comfy.

## Cloud and local data flow

| Where you use Comfy Agent | What happens |
| - | - |
| **Comfy Cloud** | Comfy Cloud stores conversations, workflows, and assets. Your messages are processed by Comfy's online service, and workflows run on Cloud GPUs. |
| **Local ComfyUI in Desktop** | The local installation stores chat history, workflows, and files. Your messages and relevant workflow information are processed by Comfy's online service. Local workflow nodes run on your hardware; partner nodes use their online providers. |

## Chat history and sync

Conversations with the Cloud Agent are stored with Comfy Cloud. Conversations with the local Agent are stored on the machine running ComfyUI. The two histories do not sync. This depends on whether you are using Cloud or a local installation, not which application window you open it in.

## Skills and guidance

Personal skills contain instructions you create for the Agent. They are saved to your account and used when your request matches them or you name them.

Built-in Agent guidance and skills for external coding agents are separate from your personal Agent skills.

## Retention and deletion

For retention details, see the [Privacy Policy](https://www.comfy.org/privacy-policy?utm_source=docs) and [Data Retention](/support/data-retention).

For account or data-deletion requests, contact [support@comfy.org](mailto:support@comfy.org).


# Get Started with Comfy Agent
Source: https://docs.comfy.org/agent-tools/in-app-agent-installation

Open Comfy Agent in Comfy Cloud or Comfy Desktop.

## Choose your setup

You need a Comfy account.

* **Comfy Cloud:** Comfy Agent is generally available. [Sign in to Cloud](https://cloud.comfy.org) — no local installation and no waitlist needed.
* **Comfy Desktop:** Comfy Agent for local ComfyUI is coming soon. [Join the waitlist](https://links.comfy.org/agentalpha) to get notified.

## Make your first image

### Open the Agent

Open a blank workflow, then select **Ask Comfy Agent** in the workflow bar. Read and accept the consent notice if prompted. Use **Choose a workflow** in the Agent panel to select the blank workflow.

### Build a workflow

Send this message:

> Build a text-to-image workflow for a red sneaker on a neutral gray background. Use an available model and include a Save Image node. Check the workflow for errors, but don't run it yet.

The Agent builds the workflow on the canvas, fills in the prompt and model settings, and checks the node connections and required inputs. You should see a connected workflow ending in a **Save Image** node.

If the Agent reports a missing model or file, supply it or ask for an alternative available in your installation. Ask it to check the workflow again before continuing.

### Generate the image

Open **Run permissions** next to the message box, choose **Ask**, and select **Save changes** if you changed the setting.

Send “Run this workflow.” When the Agent asks for approval, select **Run**. Select **Cancel** instead if you do not want to start that run.

When generation finishes, the Agent returns the output in the conversation. The image also appears in the **Save Image** node. Right-click the image there to save it to your computer.

### Make a change

Send “Change the background to white and keep the model and other settings.” The Agent updates the existing workflow. Ask it to run again to compare the result.

## Troubleshooting

### The Agent button is missing

Sign in to your Comfy account. In Comfy Desktop, [update the application](/installation/update_comfyui) and restart it. If the button is still missing, check your account's Agent access with [support](/support/contact-support).

### The Agent cannot edit the workflow I expected

Choose the intended workflow in the Agent panel, then send your message again. See [Choose which workflow to edit](/agent-tools/in-app-agent#choose-which-workflow-to-edit).

### The Agent asks for an input

Select **Attach a file** or drag the requested file into the message box, then ask the Agent to continue.

### I cannot find a local conversation in Cloud

Local and Cloud history are separate. See [Data and privacy](/agent-tools/in-app-agent-data-privacy#chat-history-and-sync).

## Next steps

<CardGroup>
  <Card title="Edit an existing workflow" icon="pen" href="/agent-tools/in-app-agent#build-and-edit-workflows">
    Change prompts, models, or processing steps.
  </Card>

  <Card title="Save a reusable skill" icon="wand-magic-sparkles" href="/agent-tools/in-app-agent-skills#create-a-skill-in-chat">
    Remember instructions for future requests.
  </Card>
</CardGroup>

See [Data and privacy](/agent-tools/in-app-agent-data-privacy) to learn where messages, files, and conversations are stored.


# Comfy Agent Skills
Source: https://docs.comfy.org/agent-tools/in-app-agent-skills

Use personal and public skills to give Comfy Agent reusable instructions for your work.

## What is a personal skill?

A personal skill is a reusable set of instructions for Comfy Agent. It includes a name, a one-line description of when to use it, and the instructions themselves.

Use personal skills to repeat instructions such as “make square images,” “use a white background,” or “check node connections before running.”

Personal skills are saved to your account. The Agent loads a skill when its description matches your request or when you ask for it by name.

## Create a skill in chat

Tell the Agent what to save, what to call it, and when it should be used:

> Save this as a skill called product-shot: When I ask for a product image, use a square 1024 × 1024 canvas, a neutral gray background, and a Save Image node. Validate the workflow before running it.

The Agent saves the skill for future messages. A new or updated skill takes effect with your next message.

## Use a skill

Ask for a skill by name:

> Use my product-shot skill to create a studio photo workflow for a red sneaker.

The Agent can also select a skill automatically when your request matches its description.

## Update or delete a skill

Use the same skill name to replace its instructions:

> Update my product-shot skill to use a white background and a 1536 × 1536 canvas.

Delete a skill by name:

> Delete my product-shot skill.

## Save an existing skill file

Paste the contents of your `SKILL.md` file into chat and ask the Agent to save it as a personal skill. The Agent reads its name and description from the header at the top of the file. The saved skill is available from your next message.

## Use a public skill

Public skills are shared skills anyone can use, not just the ones you created. Ask for a public skill by name or describe what you want to do, and the Agent uses it the same way it uses one of your own:

> Use the product-shot public skill for a red sneaker on a neutral gray background.

## Built-in guidance and coding-agent skills

Comfy Agent includes guidance for building workflows and choosing models. Personal and public skills add instructions for repeated tasks on top of that guidance.

[Skills for coding agents](/agent-tools/skills) are installed separately in tools such as Claude Code. Installing one there does not add it to Comfy Agent.

Keep API keys, passwords, and access tokens out of skill instructions. For data handling, see [Data and privacy](/agent-tools/in-app-agent-data-privacy#skills-and-guidance).


# Agent Tools
Source: https://docs.comfy.org/agent-tools/index

Use ComfyUI with AI agents through Comfy MCP, Comfy CLI, and Comfy Agent.

<CardGroup>
  <Card title="Comfy MCP" icon="bolt" href="/agent-tools/mcp">
    Connect any AI agent to ComfyUI, on Comfy Cloud or on your own machine. **Start here.**
  </Card>

  <Card title="Comfy Agent" icon="comments" href="/agent-tools/in-app-agent">
    Built-in ComfyUI assistant for building, editing, and running workflows. **Generally available on Cloud.** Local (Comfy Desktop) coming soon.
  </Card>

  <Card title="Comfy CLI" icon="terminal" href="/agent-tools/cli">
    ComfyUI in the terminal. Install and update ComfyUI, manage models and nodes, and generate from scripts, CI, or batch jobs.
  </Card>
</CardGroup>

***

## Which one should I use?

| | Comfy MCP<br />Cloud Connection | Comfy MCP<br />Local Connection | Comfy Agent |
| - | - | - | - |
| **What is it** | Run Comfy Cloud workflows with your own agent. | Drive your own local ComfyUI with your own agent. | Chat with an Agent inside ComfyUI to understand, build, edit, and run a selected workflow. |
| **Best for** | Beginners who don't want to set up ComfyUI locally.<br />People who want to share workflows. | People who have ComfyUI locally.<br />People who have private custom nodes.<br />People who need to interact with the local file system. | Building and editing workflows while viewing the canvas. |
| **Requires** | Your own agent.<br />An active Comfy Cloud subscription. | Your own agent.<br />A local ComfyUI setup. | A Comfy account. No waitlist on Cloud; Comfy Desktop is coming soon. |
| **GPU** | Cloud GPUs (no hardware requirements) | Your local GPU | Cloud GPUs today. Local hardware once Comfy Desktop support ships. |
| **Models** | Comfy Cloud models.<br />You can import your own models. | Local models downloaded to your machine. | Cloud models today. Local models once Comfy Desktop support ships. |
| **Custom nodes** | The custom nodes supported on Comfy Cloud. | You can install any custom node. | Cloud-supported nodes today. Any local node once Comfy Desktop support ships. |

Both MCP columns are the **same product and the same page**. See [Comfy MCP](/agent-tools/mcp) to pick one. You can connect both at once.

***

## What is MCP?

The **Model Context Protocol (MCP)** is an open standard that allows AI assistants to interact with external tools and services through a standardized interface. Instead of an AI agent needing to know custom API formats for every service, MCP provides a uniform way to expose tools.

When you connect an MCP server to Claude Desktop, Claude Code, Cursor, or Amp, the AI assistant can:

* **Generate images** from text descriptions
* **Create videos** from text or images
* **Generate 3D models** from text or images
* **Generate audio and music** using AI models
* **Search models and templates** to find the right tools for your task

...all through natural language conversation, without writing API calls manually.


# Comfy MCP: Connect AI Agents to ComfyUI
Source: https://docs.comfy.org/agent-tools/mcp

Connect AI agents to ComfyUI over the Model Context Protocol. Generate images, video, audio, and 3D, and run real workflows on Comfy Cloud or your own machine.

## Overview

**Comfy MCP** connects AI agents to ComfyUI over the [Model Context Protocol](https://modelcontextprotocol.io). Once connected, you can generate images, video, audio and 3D, search models, nodes and templates, and run real ComfyUI workflows from a chat with your agent.

It comes with two connections: a **Comfy Cloud** connection and a **local ComfyUI** connection, with the local one fully open source.

<Tip>
  **Stuck on anything below? The best way is to hand this page to your agent and ask for help.**
</Tip>

### Which connection do I want?

**For new users, we recommend starting with the cloud connection** — it is the simplest setup. If you use claude.ai, ChatGPT, or the Claude Desktop chat app, the cloud connection is also the more compatible choice.

**If you already run ComfyUI locally or in your own deployed environment, or you work mostly in a coding agent** like Claude Code, Cursor, or Codex, start with the **local** connection.

<Info>
  **For Mac users, if you plan to run open-source models, we recommend the cloud connection.** Today's open-weight models — the local versions of MiniMax H3, LTX-2.3, and similar — are large, and will not run at a workable speed on the Apple GPU.
</Info>

Running both at once is normal, and most clients host two MCP servers happily. They sign in to the same Comfy account, but **separately** — one sign-in does not cover the other.

## Comfy Cloud MCP Connection

The hosted connection, linking your agent to your **Comfy Cloud** account. Nothing to install, and workflows run on Comfy Cloud GPUs. To learn more about Comfy Cloud, see [Comfy Cloud](/get_started/cloud).

### Set up the cloud connection

<Info>
  You need a [Comfy Cloud](https://cloud.comfy.org) account before connecting. [Sign up](https://cloud.comfy.org) if you do not have one yet; new users get **5 free runs** to try it out. OAuth sign-in during setup uses your Comfy account.
</Info>

Comfy Cloud MCP runs at:

```
https://cloud.comfy.org/mcp
```

Pick your client:

<Tabs>
  <Tab title="Claude Desktop">
    Claude Desktop adds Comfy Cloud as a **custom connector** through its UI, then runs the OAuth sign-in.

    <video />

    <Steps>
      <Step title="Open Customize">
        In the sidebar, click **Customize** (labeled **1**).

        <img alt="Claude Desktop — open Customize" />
      </Step>

      <Step title="Open Connectors">
        Click **Connectors** (labeled **2**).

        <img alt="Claude Desktop — open Connectors" />
      </Step>

      <Step title="Add a custom connector">
        1. Click the **+** button (labeled **3**) in the Connectors header.
        2. Choose **Add custom connector** (labeled **4**).

           <img alt="Claude Desktop — add custom connector" />
      </Step>

      <Step title="Enter server details">
        1. Enter a name such as **Comfy Cloud MCP** in the **Name** field (labeled **5**).
        2. Set the **Remote MCP server URL** to `https://cloud.comfy.org/mcp` (labeled **6**).
        3. Click **Add** (labeled **7**).

           <img alt="Claude Desktop — connector details" />
      </Step>

      <Step title="Sign in">
        1. When the browser opens, choose your workspace (for example **Personal Workspace**).
        2. Click **Continue** to authorize the connector. You are connected.

           <img alt="Comfy Cloud MCP authorization" />
      </Step>
    </Steps>
  </Tab>

  <Tab title="Claude Code">
    Install the **comfy-cloud** plugin. It adds the MCP connection and slash commands in one step. The plugin is published through the [Comfy Skills](https://github.com/Comfy-Org/comfy-skills/) repository, which hosts Claude Code plugins and community agent skills for Comfy.

    <Steps>
      <Step title="Add the marketplace">
        Register the Comfy Skills marketplace (one-time):

        ```
        /plugin marketplace add Comfy-Org/comfy-skills
        ```
      </Step>

      <Step title="Install the plugin">
        ```
        /plugin install comfy-cloud@comfy-skills
        ```
      </Step>

      <Step title="Sign in">
        Run `/mcp`, select **comfy-cloud** → **Authenticate**. Your browser opens to sign in, and tokens refresh automatically.
      </Step>
    </Steps>

    The plugin adds these slash commands:

    | Command | What it does |
    | - | - |
    | `/comfy-cloud:generate-image` | Generate, edit, or modify an image |
    | `/comfy-cloud:generate-video` | Generate, edit, or extend a video |
    | `/comfy-cloud:generate-audio` | Generate audio, music, or sound effects |
    | `/comfy-cloud:generate-3d` | Generate a 3D model from text or an image |
    | `/comfy-cloud:remove-background` | Remove the background from an image |
    | `/comfy-cloud:upscale-image` | Upscale an image to higher resolution |
    | `/comfy-cloud:search-templates` | Find pre-built workflow templates on [comfy.org](https://comfy.org) |
    | `/comfy-cloud:search-models` | Search for available models |
    | `/comfy-cloud:search-nodes` | Search for nodes and get wiring suggestions |
    | `/comfy-cloud:help` | See what you can do with ComfyUI Cloud |

    <Accordion title="Prefer just the connection, without the plugin?">
      Add the server directly:

      ```bash theme={null}
      claude mcp add --transport http comfy-cloud https://cloud.comfy.org/mcp
      ```

      Then run `/mcp`, select **comfy-cloud** → **Authenticate**. Add `-s user` to make it available in all your projects.

      This path still exposes the same workflows as MCP prompts: `/mcp__comfy-cloud__generate-image`, `/mcp__comfy-cloud__search-models`, and so on (the `/mcp__<name>__` prefix uses the name you passed to `claude mcp add`). The plugin above is recommended because it wraps these as the friendlier `/comfy-cloud:*` commands.
    </Accordion>
  </Tab>

  <Tab title="Cursor">
    Cursor connects to remote MCP servers over HTTP. Cursor does **not** support MCP OAuth today. Add Comfy Cloud with a Comfy Cloud API key in your MCP config.

    <Steps>
      <Step title="Open Cursor Settings">
        Click the **Settings** gear in the top-right corner (labeled **1**).

        <img alt="Cursor — open Settings" />
      </Step>

      <Step title="Open Tools & MCP">
        1. In the sidebar, click **Tools & MCPs** (labeled **2**).
        2. Click **+ New MCP Server** (labeled **3**) → **Add a Custom MCP Server**.

           <img alt="Cursor — Tools & MCPs" />
      </Step>

      <Step title="Add your API key">
        Edit `~/.cursor/mcp.json` (global) or `.cursor/mcp.json` (project). Set the server URL and pass your Comfy Cloud API key in the `X-API-Key` header. Create a key at [platform.comfy.org/profile/api-keys](https://platform.comfy.org/profile/api-keys) (starts with `comfyui-`):

        ```json theme={null}
        {
          "mcpServers": {
            "comfy-cloud": {
              "url": "https://cloud.comfy.org/mcp",
              "headers": {
                "X-API-Key": "${env:COMFY_API_KEY}"
              }
            }
          }
        }
        ```

        Set `COMFY_API_KEY` in your shell or system environment. Prefer `${env:COMFY_API_KEY}` over hardcoding the key in a file you might commit to Git.

        <img alt="Cursor — mcp.json with API key" />
      </Step>

      <Step title="Start generating">
        Ask in plain language ("generate an image of a cat astronaut", "find a Wan 2.2 video template"). Cursor invokes the MCP tools on your behalf.
      </Step>
    </Steps>
  </Tab>

  <Tab title="Codex">
    [Codex](https://developers.openai.com/codex/cli) connects to Comfy Cloud over Streamable HTTP. Add the server in Settings, then sign in with OAuth.

    <video />

    <Steps>
      <Step title="Open the settings panel">
        1. Click **Settings** (labeled **1**) under *Logged in with API key*.
        2. Click **Settings** (labeled **2**) to open the full settings panel.

           <img alt="Codex settings panel — step 1" />
      </Step>

      <Step title="Open MCP server settings">
        1. Click **MCP servers** (labeled **3**) in the settings list.
        2. Click **+ Add server** (labeled **4**) to add a new MCP server.

           <img alt="Codex MCP servers — step 2" />
      </Step>

      <Step title="Connect to Comfy Cloud">
        1. Choose **Streamable HTTP** as the connection type.
        2. Enter a name such as **Comfy Cloud MCP** in the **Name** field (labeled **5**).
        3. Enter the URL `https://cloud.comfy.org/mcp` in the **URL** field (labeled **6**).
        4. Click **Save** (labeled **7**).

           <img alt="Codex add MCP server — step 3" />
      </Step>

      <Step title="Authenticate">
        1. Click **Authenticate** (labeled **8**) on the saved server entry.

           <img alt="Codex authenticate MCP server — step 4" />

        2. In the browser popup, choose your workspace and click **Continue** to finish signing in. You are connected.

           <img alt="Comfy Cloud MCP authorization" />
      </Step>
    </Steps>

    Ask in plain language ("generate an image of a cat astronaut", "find a Wan 2.2 video template"). Codex invokes the MCP tools on your behalf.

    <Accordion title="Prefer the CLI instead?">
      Register and sign in from the terminal:

      ```bash theme={null}
      codex mcp add comfy-cloud --url https://cloud.comfy.org/mcp
      codex mcp login comfy-cloud
      ```

      This writes an entry to `~/.codex/config.toml` (or `.codex/config.toml` in a trusted project).
    </Accordion>

    <Accordion title="API key instead of OAuth (headless or CI)">
      When no browser is available, add the server with a header pulled from an environment variable. Create a key at [platform.comfy.org/profile/api-keys](https://platform.comfy.org/profile/api-keys) (starts with `comfyui-`), then add to `~/.codex/config.toml`:

      ```toml theme={null}
      [mcp_servers.comfy-cloud]
      url = "https://cloud.comfy.org/mcp"
      env_http_headers = { "X-API-Key" = "COMFY_API_KEY" }
      ```

      Set `COMFY_API_KEY` in your shell or system environment. Do not commit the key to version control.
    </Accordion>

    <Accordion title="Codex keeps asking you to sign in again (invalid_grant or refresh token reuse)">
      **Symptom:** Codex signs you out of Comfy Cloud and asks you to reauthenticate over and over, sometimes every few minutes. Codex warnings or logs may mention `invalid_grant`, a refresh token that was already used or revoked, or a failed OAuth token refresh.

      **Cause:** This comes from how Codex stores and refreshes MCP OAuth credentials, not from Comfy Cloud. When several Codex processes (TUI sessions, the app server, `codex mcp` commands) share one OAuth server, one process can refresh with a token that another has already rotated. The authorization server treats that as token reuse and ends the session. Users of other OAuth MCP servers report the same behavior. These issues are open in the Codex repository, so you can check their current status:

      * [openai/codex#46028](https://github.com/openai/codex/issues/46028): long-lived clients reuse rotated refresh tokens
      * [openai/codex#48507](https://github.com/openai/codex/issues/48507): concurrent processes race refresh token rotation and the next startup hits `invalid_grant`
      * [openai/codex#41133](https://github.com/openai/codex/issues/41133): shutdown can lose a rotated refresh token
      * [openai/codex#17265](https://github.com/openai/codex/issues/17265): Codex does not refresh stored MCP OAuth tokens

      **Workaround 1: turn on Codex's refresh coordination flag.** Codex has a feature flag, `mcp_oauth_refresh_coordination`, that coordinates OAuth token refreshes between Codex processes. It is a Codex setting, not a Comfy one. Codex lists it as under development and off by default, and neither Codex nor Comfy supports it as an official fix. In openai/codex#46028, enabling it stopped the stale token reuse in the reporter's test. If your Codex version still has it off, add it to `~/.codex/config.toml`:

      ```toml theme={null}
      [features]
      mcp_oauth_refresh_coordination = true
      ```

      Close and restart every running Codex session so they all pick up the flag. If Codex already shows **comfy-cloud** as signed out, sign in once more (`codex mcp login comfy-cloud`, or **Authenticate** in Settings). If a later Codex release turns this on by default or removes the flag, you can skip this step.

      **Workaround 2: keep one Codex process refreshing each server.** If the flag is not available or does not help, move the `[mcp_servers.comfy-cloud]` entry out of the global `~/.codex/config.toml` and into a `.codex/config.toml` in a trusted project, so only sessions in that project load and refresh it. Avoid running many Codex sessions against Comfy Cloud at the same time, and close Codex sessions before restarting your computer. This is the workaround reported in openai/codex#48507.

      Moving the entry does not stop Codex processes that already loaded the global config, and those keep refreshing the old server definition. After the move, close every running Codex session and stop the Codex app server, then start Codex only in the project that holds the entry.

      If you do not need OAuth, the API key setup above does not use refresh tokens.

      These steps reduce sign-outs but may not stop them completely. We are also working on changes on the Comfy Cloud side to reduce how often this happens.
    </Accordion>
  </Tab>

  <Tab title="OpenClaw">
    Install the **Comfy Cloud** skill from [ClawHub](https://clawhub.ai/comfy-org/skills/comfy). It connects OpenClaw to the hosted MCP server (`cloud.comfy.org/mcp`). Cloud only: it does not drive a local ComfyUI install.

    <Steps>
      <Step title="Install the skill">
        ```bash theme={null}
        openclaw skills install @comfy-org/comfy
        ```

        Skill page: [clawhub.ai/comfy-org/skills/comfy](https://clawhub.ai/comfy-org/skills/comfy).
      </Step>

      <Step title="Connect with OAuth (recommended)">
        Register the MCP server and sign in with your Comfy account:

        ```bash theme={null}
        openclaw mcp set comfy '{"url":"https://cloud.comfy.org/mcp","transport":"streamable-http","auth":"oauth"}'
        openclaw mcp login comfy
        openclaw gateway restart
        ```

        `openclaw mcp login` prints an authorization URL. Open it, sign in, and finish the flow as the CLI directs (it may ask you to rerun with a `--code` value). Verify with `openclaw mcp status --verbose`.

        <Note>
          When `auth: "oauth"` is set, OpenClaw ignores static `headers` on that server entry. Do not combine OAuth with a hardcoded API key header.
        </Note>
      </Step>

      <Step title="Start generating">
        Ask in plain language ("generate an image of a cat astronaut", "find a Wan 2.2 video template"). OpenClaw invokes the MCP tools on your behalf.
      </Step>
    </Steps>

    <Accordion title="API key instead of OAuth (headless or CI)">
      Create a key at [platform.comfy.org/profile/api-keys](https://platform.comfy.org/profile/api-keys) (starts with `comfyui-`), export it, then register the server:

      ```bash theme={null}
      export COMFY_API_KEY="comfyui-..."
      openclaw mcp set comfy '{"url":"https://cloud.comfy.org/mcp","transport":"streamable-http","headers":{"Authorization":"Bearer ${COMFY_API_KEY}"}}'
      openclaw gateway restart
      ```

      Prefer `Authorization: Bearer` over a custom `X-API-Key` header for OpenClaw. Some OpenClaw builds drop custom headers on streamable-http transports; Bearer survives proxies more reliably. Put `COMFY_API_KEY` in your shell profile or OpenClaw env. Do not commit the key.
    </Accordion>
  </Tab>

  <Tab title="Other clients">
    Any MCP client that supports **remote HTTP** transport can connect to Comfy Cloud. The server URL is always `https://cloud.comfy.org/mcp`.

    <Steps>
      <Step title="Add the server URL">
        Add a remote MCP entry pointing at `https://cloud.comfy.org/mcp`. Most clients use a JSON config with a `url` field:

        ```json theme={null}
        {
          "mcpServers": {
            "comfy-cloud": {
              "url": "https://cloud.comfy.org/mcp"
            }
          }
        }
        ```

        **Windsurf** uses `serverUrl` instead of `url`. **Amp** uses the same `mcpServers` shape in **Settings → MCP Servers** or `~/.config/amp/settings.json`.
      </Step>

      <Step title="Authenticate">
        If your client supports MCP OAuth, sign in through the browser when prompted. Otherwise, add an API key header (see below).
      </Step>

      <Step title="Restart and verify">
        Restart your client. You should see Comfy Cloud tools (`search_templates`, `submit_workflow`, `get_output`, and others) registered under the **comfy-cloud** server.
      </Step>
    </Steps>

    **Headless / CI (API key):** when OAuth is not available, create a key at [platform.comfy.org/profile/api-keys](https://platform.comfy.org/profile/api-keys) and pass it as the `X-API-Key` header:

    ```json theme={null}
    {
      "mcpServers": {
        "comfy-cloud": {
          "url": "https://cloud.comfy.org/mcp",
          "headers": {
            "X-API-Key": "comfyui-…"
          }
        }
      }
    }
    ```

    For Claude Code from the terminal:

    ```bash theme={null}
    claude mcp add --transport http comfy-cloud https://cloud.comfy.org/mcp -H "X-API-Key: comfyui-…"
    ```

    Prefer `${env:COMFY_API_KEY}` or your client's secret interpolation instead of hardcoding keys in config files you commit to Git.
  </Tab>
</Tabs>

### What your agent can do

You do not call MCP tools yourself. Your agent picks the right tool based on what you ask for. Slash commands and prompts (below) are shortcuts that steer the agent toward common tasks, but plain language works too ("generate an image of a cat astronaut", "upscale this photo", "find a Wan 2.2 video template").

Typical flow:

1. **Discover** what is available (`search_templates`, `search_models`, `search_nodes`, or `cql` for graph-style questions).
2. **Run** a generation: `run_template` for a matching pre-built template, `submit_workflow` for a custom workflow (with `upload_file` when an input image is needed), or `partner_generate` for partner models like Flux, Grok, Gemini, OpenAI, Ideogram, and Seedance.
3. **Wait and retrieve** outputs (`wait_for_job`, then `get_output` returns a download command your agent runs in your shell).

The server prefers matching [pre-built templates](https://comfy.org/workflows) before building a workflow from scratch, which tends to produce better results faster.

### Cloud MCP tools

These are the tools your agent has access to once connected. Names match what appears in MCP client logs and debugging output.

**Discovery**

| Tool | Description |
| - | - |
| `search_templates` | Search pre-built workflow templates from [comfy.org](https://comfy.org/workflows) by text, tag, media type, or model |
| `get_template` | Fetch a template's full workflow JSON for inspection or hand-editing |
| `get_template_schema` | See which of a template's parameters can be overridden at run time |
| `search_models` | Search the model catalog by text, type, base model, or source |
| `search_nodes` | Search available nodes by text, category, or input/output types. Also surfaces **subgraph blueprints** (pre-wired node groups like Text to Image or Remove Background) |
| `get_node` | Get the complete input spec for specific nodes, including full option lists |
| `cql` | Run a [CQL](https://github.com/Comfy-Org/cql) graph query for structural questions (for example, which nodes produce images, or paths between node types). Use `search_nodes` when you need full input specs for a specific node |
| `get_prompting_guide` | Prompt style and recommended settings (steps, cfg, sampler, resolution) per model family |

**Generation**

| Tool | Description |
| - | - |
| `run_template` | Run a pre-built template by name, with optional parameter overrides — the preferred path when a template matches |
| `submit_workflow` | Submit a ComfyUI API-format workflow for execution on Comfy Cloud |
| `partner_generate` | Generate with partner-API models (Flux/BFL, Grok, Gemini, OpenAI, Ideogram, Seedream/Seedance, and more) |
| `upload_file` | Upload an input image or file for use in workflows (for example, with LoadImage) |
| `apply_slots` | Apply parameter overrides to a workflow's interior values and return the modified workflow |

**Jobs and batches**

| Tool | Description |
| - | - |
| `get_job_status` | Poll execution status of a submitted workflow |
| `wait_for_job` | Wait until a job finishes instead of polling repeatedly |
| `get_output` | Retrieve output images, videos, or audio from a completed workflow |
| `use_previous_output` | Chain workflows by reusing output from one run as input to another |
| `cancel_job` | Cancel a pending or running job |
| `get_queue` | Check how many jobs are running and pending |
| `submit_batch`, `get_batch_status`, `get_batch_output`, `wait_for_batch` | Submit many generations in one call and collect them together later — the batch ID stays valid across sessions |

**Saved workflows**

| Tool | Description |
| - | - |
| `list_saved_workflows` | Browse your saved workflows from Comfy Cloud |
| `get_saved_workflow` | Inspect a saved workflow's nodes, inputs, and customizable settings |
| `save_workflow` | Save a workflow to your Comfy Cloud account |
| `update_workflow` | Update an existing workflow in place as a new version (earlier versions stay recoverable) |
| `run_saved_workflow` | Run a saved workflow by filename — the server converts it from editor format to executable format automatically |

**Sharing workflows**

| Tool | Description |
| - | - |
| `share_workflow` | Publish a saved workflow and return a `?share=<id>` URL anyone can open |
| `import_shared_workflow` | Resolve a share URL or bare share ID into workflow JSON, optionally saving it to your account |

**Hub URL share IDs:** the trailing hyphen-delimited hex token in a `comfy.org/workflows/<slug>-<hex>` hub URL is the share ID. For example, `comfy.org/workflows/topaz-starlight-upscale-1c77e82713b7` has share ID `1c77e82713b7`. Pass that token to `import_shared_workflow` as `share_id`. The `share_url` parameter only accepts `?share=<id>` query URLs like `https://cloud.comfy.org/?share=...`, not hub page URLs.

**Apps and links**

| Tool | Description |
| - | - |
| `create_app` | Turn a saved workflow into an App Mode app — a simplified "run this workflow" view with chosen inputs and outputs |
| `get_app_mode_url` | Get the stable link that opens a workflow as a runnable app |
| `get_workflow_canvas_url` | Get a link that opens a workflow directly on the Comfy Cloud canvas, ready to view, edit, or run |

**Account and session**

| Tool | Description |
| - | - |
| `get_billing_status` | Check your credit balance, subscription tier, and billing link |
| `get_server_info` | Confirm which server the agent reached: environment, host, version, and auth state |
| `submit_feedback` | Get the feedback survey link |
| `report_session_summary` | Share an anonymized session summary with the Comfy team — **only with your explicit consent**; the agent must ask first, and no prompts, file paths, or personal information are included |

**Prompts (Claude Desktop)**

Claude Desktop does not support Claude Code slash commands. Instead, open the **prompt picker** for the same workflows:

| Prompt | Description |
| - | - |
| `generate-image` | Generate an image from a text description |
| `generate-video` | Generate a video from text or an image |
| `generate-audio` | Generate audio, music, or sound effects |
| `generate-3d` | Generate a 3D model from text or an image |
| `upscale-image` | Upscale an image to higher resolution |
| `remove-background` | Remove the background from an image |
| `search-templates` | Find pre-built workflow templates |
| `search-models` | Search for models (checkpoints, LoRAs, VAEs) |
| `search-nodes` | Search nodes and get wiring suggestions |
| `help` | See what you can do with ComfyUI Cloud |

You can also skip prompts and ask in plain language. The MCP tools work the same way.

### Credits and spending

Discovery is free: `search_templates`, `search_models`, and `search_nodes` work with just a [Comfy account](https://cloud.comfy.org). Running generations requires an active Comfy Cloud subscription. A credit or top-up balance alone does not grant access: you need an active subscription to run generations, even if you have unused credits.

### Uploads and downloads

The MCP server runs in the cloud and the MCP itself doesn't write files to your machine. When a generation completes, your agent calls `get_output`, which returns:

1. A **temporary signed download URL** (valid for a short window).
2. A ready-to-run **shell command** (`curl` on macOS and Linux, `curl.exe` on Windows).

Your agent should run that command in your shell. The command includes the destination path and filename.

<Warning>
  Run the returned command **verbatim**. Do not re-encode or edit the signed URL. The signature lives in the query string and breaks if the URL is modified.
</Warning>

If your MCP client cannot run shell commands (some GUI-only setups), copy the command and run it yourself in a terminal.

Asset upload and download depend on the client's file access. If Claude Desktop or another agent client has trouble handling asset uploads or downloads, it may be related to the agent's access to your local file directories. For Claude users we recommend **Claude Code** (desktop app or terminal), which has more capabilities. Similarly, for other agent families, the coding agent is usually better than the web chat version.

### Known limitations

Comfy Cloud MCP is an early release. These limitations are known and being worked on:

**Workflows**

* **Assets generated via `submit_workflow` may not embed workflow metadata.** They might not reopen the originating workflow when opened in ComfyUI.
* **Workflow building depends on agent accuracy.** Complex multi-node workflows may need a retry or refinement.

**File handling**

* **Outputs require a shell download step.** See [Uploads and downloads](#uploads-and-downloads).
* **Upload size limits** may apply depending on your MCP client. Some clients impose their own limits on file uploads.

**Authentication**

* **OAuth or API key.** Claude Code and Claude Desktop use a one-time browser OAuth flow. **Cursor** requires a Comfy Cloud API key in your MCP config (no OAuth). Other headless clients can pass a Comfy Cloud API key via the `X-API-Key` header instead. A device-code OAuth flow for clients that cannot open a browser is planned.

## Local Comfy MCP Connection

The open-source connection: your client launches the server on your machine and it drives the ComfyUI installed there.

[**comfy-mcp**](https://github.com/Comfy-Org/comfy-mcp) is Comfy's **first-party local MCP server** — the official way to drive a **local** ComfyUI install from AI agents (Claude Code, Claude Desktop, Cursor, and other MCP clients).

Unlike the cloud and partner servers, it talks to the ComfyUI running on **your own machine** — so it can run your workflows and inspect the nodes, custom nodes, and models your install actually has.

<Tip>
  **The fastest setup: hand it to your agent.** Paste `https://docs.comfy.org/agent-tools/mcp#installation` into your AI client and ask it to set up the local connection for you.
</Tip>

### Requirements

* **Python 3.10+**
* **[comfy-cli](https://github.com/Comfy-Org/comfy-cli)** on your `PATH` (`pip install "comfy-cli>=1.14.0"`) — the engine every tool wraps
* **A ComfyUI workspace** — create one with `comfy install` if you don't have one (an existing checkout works via `comfy set-default <path>`)
* **A running ComfyUI for execution tools.** Start it with `comfy launch`, or call `launch_comfyui`. The server does not launch ComfyUI implicitly.

***

### Installation

From [PyPI](https://pypi.org/project/comfy-mcp/):

```bash theme={null}
pip install comfy-mcp
```

This puts a `comfy-mcp` console script on your `PATH` — that command is the MCP server (it speaks MCP over stdio). Point your AI client at it below. (Hacking on the server itself? `pip install -e .` from a checkout of the [repository](https://github.com/Comfy-Org/comfy-mcp) instead.)

<Note>
  **`COMFY_BIN` (optional).** MCP clients launch the server with their own environment, which often does **not** include your shell's `PATH`. If `comfy` lives in a virtualenv or a non-standard location, set `COMFY_BIN` to its absolute path (for example `/path/to/venv/bin/comfy`). Every client example below shows where it goes; drop it if `comfy` is already on the environment your client launches the server with.
</Note>

***

### Manual configuration

All clients speak the same MCP stdio contract: run the `comfy-mcp` command as a server. Pick your client:

<Tabs>
  <Tab title="Claude Desktop">
    Edit `claude_desktop_config.json` (Settings → Developer → Edit Config; on macOS it lives at `~/Library/Application Support/Claude/claude_desktop_config.json`), add the server, then restart Claude Desktop:

    ```json theme={null}
    {
      "mcpServers": {
        "comfy-mcp": {
          "command": "comfy-mcp",
          "env": { "COMFY_BIN": "/path/to/venv/bin/comfy" }
        }
      }
    }
    ```
  </Tab>

  <Tab title="Claude Code">
    One command registers the server:

    ```bash theme={null}
    claude mcp add comfy-mcp -e COMFY_BIN=/path/to/venv/bin/comfy -- comfy-mcp
    ```

    Or check it into a project with a `.mcp.json` at the repo root:

    ```json theme={null}
    {
      "mcpServers": {
        "comfy-mcp": {
          "command": "comfy-mcp",
          "env": { "COMFY_BIN": "/path/to/venv/bin/comfy" }
        }
      }
    }
    ```
  </Tab>

  <Tab title="Cursor">
    Add the server to `~/.cursor/mcp.json` (global) or `.cursor/mcp.json` (per project):

    ```json theme={null}
    {
      "mcpServers": {
        "comfy-mcp": {
          "command": "comfy-mcp",
          "env": { "COMFY_BIN": "/path/to/venv/bin/comfy" }
        }
      }
    }
    ```
  </Tab>
</Tabs>

***

### Quickstart

Zero to a generated image:

<Steps>
  <Step title="Install the pieces">
    ```bash theme={null}
    pip install "comfy-cli>=1.14.0"  # the engine
    comfy install                    # create a ComfyUI workspace (skip if you have one)
    pip install comfy-mcp            # this MCP server → the `comfy-mcp` command
    ```
  </Step>

  <Step title="Launch ComfyUI and leave it running">
    ```bash theme={null}
    comfy launch
    ```
  </Step>

  <Step title="Add the server to your client">
    Use the snippet for your client above, then restart / reload it so the tools appear.
  </Step>

  <Step title="Ask your agent to run a workflow">
    For example:

    > "Confirm my local ComfyUI is running, then run the workflow at `~/workflows/txt2img.json` and show me the image."

    Under the hood the agent calls `server_info` to confirm ComfyUI is up, `run_workflow` to execute the workflow JSON, and `fetch_outputs` to collect the result.
  </Step>
</Steps>

***

### Tools

Each tool maps onto a `comfy-cli` command, run with `--where local`. Highlights:

| Tool | Purpose |
| - | - |
| `server_info()` | Is a local ComfyUI running, where, and which workspace. **Call first.** |
| `run_workflow(workflow_path, wait=True)` | Run a workflow JSON; `wait=False` submits async and returns a `prompt_id`. |
| `job_status` / `wait_for_job` / `watch_job` | Poll, wait on, or stream a submitted job. |
| `fetch_outputs(prompt_id, out_dir)` | Copy a finished job's outputs into `out_dir`. |
| `launch_comfyui` / `stop_comfyui` | Start or stop the local ComfyUI. |
| `search_templates` / `fetch_template` | Find a built-in template and write its runnable workflow JSON. |
| `search_nodes` / `get_node` / `list_nodes` | Inspect the node classes in your **live local** install (custom nodes included). |
| `search_models` | List the model files on disk. |
| `validate_workflow` | Pre-flight a workflow against the live `object_info` before a slow run. |

Node introspection and model search read your **live install** — custom nodes included — which is the local differentiator from the cloud connection. See the [repository](https://github.com/Comfy-Org/comfy-mcp) for the full tool list and reference.

***

## Related resources

| Resource | What it's for |
| - | - |
| [Comfy Skills](https://github.com/Comfy-Org/comfy-skills/) | Claude Code plugin marketplace and community skill library. The **comfy-cloud** plugin used above is distributed here; browse or contribute additional skills for Comfy workflows. |
| [Comfy Cloud on ClawHub](https://clawhub.ai/comfy-org/skills/comfy) | OpenClaw skill (`openclaw skills install @comfy-org/comfy`) for the hosted Comfy Cloud MCP server. |
| [Comfy CLI](/agent-tools/cli) | Command-line tool for local ComfyUI install/launch and for calling hosted partner nodes from scripts or CI (`comfy generate`, in beta). Complements MCP when you need terminal or automation workflows. |
| [Share a workflow on Comfy Cloud](/cloud/share-workflow) | Share workflows from the Comfy Cloud UI (the MCP `share_workflow` tool does this from an agent session). |

## Related: Comfy Agent

Want the agent experience **inside** ComfyUI, not an external MCP client?

<Card title="Comfy Agent" icon="comments" href="/agent-tools/in-app-agent">
  Built-in ComfyUI assistant for building, editing, and running workflows. **Generally available on Cloud.** Local (Comfy Desktop) coming soon.
</Card>

## Feedback

Try Comfy MCP and tell us what works and what doesn't:

* **[Feedback survey](https://links.comfy.org/cloudmcpbeta)**: report bugs, request features, or share general impressions.
* **Discord**: [#comfy-mcp-and-cli](https://discord.gg/xWJn6nhE3R) on the Comfy Discord for questions and discussion.

## FAQ

### Getting started

<AccordionGroup>
  <Accordion title="Which clients are supported?">
    Any MCP-compatible client.

    The **cloud connection** needs remote HTTP support. **Claude Code**, **Claude Desktop**, **Cursor**, **Codex** and **OpenClaw** have first-class setup above; **Windsurf**, **Amp** and others use the same URL with OAuth or an API key.

    The **local connection** needs a client that can launch a local stdio server as a subprocess. That rules out browser-based clients. [claude.ai](https://claude.ai) and ChatGPT accept remote connectors only.
  </Accordion>

  <Accordion title="What's the server URL?">
    The cloud connection runs at `https://cloud.comfy.org/mcp`.

    The local connection has no URL. Your client launches the `comfy-mcp` command directly and talks to it over stdio.
  </Accordion>

  <Accordion title="Can I use it with my local ComfyUI?">
    Yes. That is the [Local Comfy MCP Connection](#local-comfy-mcp-connection). It drives the ComfyUI installed on your own machine, so your agent sees the models, LoRAs and custom nodes you actually have, and runs on your GPU.
  </Accordion>

  <Accordion title="Can I connect both the cloud and local connections at once?">
    Yes, and we recommend it if you run ComfyUI locally. Most clients host two MCP servers happily, and your agent keeps them straight. Each connection runs its own workflows and returns its own results.

    The two sign-ins are **separate**, though. Signing in on one does not sign you in on the other, even though it is the same Comfy account.
  </Accordion>

  <Accordion title="How do I know if my machine can run the local connection?">
    Ask your agent. It reads your hardware before starting anything heavy.

    On a **Mac**, use the cloud connection for generating: today's open-weight models are too large to run at a workable speed on the Apple GPU. On a **PC with a dedicated graphics card**, 24 GB or more of VRAM handles most things including video; 8–24 GB is fine for images but video will be slow or will not fit; under 8 GB, use cloud.
  </Accordion>

  <Accordion title="Is it generally available?">
    Yes. The cloud connection is generally available, and the local connection is available for local ComfyUI installations. See [Feedback](#feedback) to report issues or share suggestions.
  </Accordion>
</AccordionGroup>

### Cost and access

<AccordionGroup>
  <Accordion title="Does it cost anything?">
    Discovery is free on both connections: searching templates, models and nodes needs only a Comfy account.

    On the **cloud connection**, running generations requires an active Comfy Cloud subscription; new users get 5 free runs. On the **local connection**, runs are free because they happen on your hardware, with one exception: partner models execute on partner infrastructure and spend credits.
  </Accordion>

  <Accordion title="Do I need an API key?">
    Not for interactive clients that support OAuth, including Claude Code, Claude Desktop, Codex and OpenClaw.

    **Cursor** requires a Comfy Cloud API key in your MCP config; there is no MCP OAuth there yet. Headless and CI setups with no browser need one too. See the **Cursor** and **Other clients** tabs under [Set up the cloud connection](#set-up-the-cloud-connection).
  </Accordion>
</AccordionGroup>

### Using it

<AccordionGroup>
  <Accordion title="What can my agent do once connected?">
    You do not call MCP tools yourself — your agent picks them based on what you ask for. Typically it **discovers** what is available (`search_templates`, `search_models`, `search_nodes`), **runs** a generation, then **waits and retrieves** the output. See [What your agent can do](#what-your-agent-can-do).
  </Accordion>

  <Accordion title="Where do my outputs go?">
    On the **cloud connection**, the server never writes to your machine: `get_output` returns a temporary signed URL and a ready-to-run download command for your agent to execute in your shell. See [Uploads and downloads](#uploads-and-downloads).

    On the **local connection**, ComfyUI writes into your workspace's `output/` directory, and `fetch_outputs(prompt_id, out_dir)` copies a finished job's files anywhere you name.
  </Accordion>

  <Accordion title="I started on one connection and now I need the other. What do I do?">
    Nothing to undo — add the second connection alongside the first.

    Going **local → cloud** (you need Cloud GPUs or partner models): ask your agent to sign you in, then add `https://cloud.comfy.org/mcp` to your client.

    Going **cloud → local** (you want your own models and custom nodes): install ComfyUI and the local server, then point your client at it. Your agent can do most of this for you.
  </Accordion>

  <Accordion title="How do I switch between the local and cloud connections?">
    Just ask your agent. With both connections added, say where you want a job to run — "run this one on Comfy Cloud", "do this locally" — and it uses the right connection. There is no mode to toggle and nothing to reconfigure between runs.

    If a workflow turns out to be too heavy for your machine, your agent can tell you and offer to run it on Comfy Cloud instead. And if only one connection is set up, ask it to add the other — see [Set up the cloud connection](#set-up-the-cloud-connection) or the [Local Comfy MCP Connection](#local-comfy-mcp-connection).
  </Accordion>

  <Accordion title="How do I update Comfy MCP?">
    On the **cloud connection**, nothing to do — it is hosted, so you are always on the current version.

    On the **local connection**, ask your agent to handle it. Afterwards, **restart your client** or start a new session: MCP servers load when a session starts, so a running one keeps serving the old version until you do.
  </Accordion>
</AccordionGroup>

### Troubleshooting

<AccordionGroup>
  <Accordion title="Do slash commands work in Claude Desktop?">
    No. Slash commands ship in the Claude Code plugin. Claude Desktop connects to the same MCP server — the tools work if you ask in plain language or use the prompt picker — but it does not support Claude Code plugins or slash commands.
  </Accordion>

  <Accordion title="I typed /comfy or /cloud and nothing came up.">
    There is no `/comfy` or `/cloud` command. Commands appear under one of two prefixes depending on how you connected:

    * **Plugin (recommended):** `/comfy-cloud:generate-image`, `/comfy-cloud:generate-video`, … — type `/comfy-cloud:` to see them all.
    * **Direct connection (no plugin):** `/mcp__comfy-cloud__generate-image`, … — type `/mcp__` to see them.

    Either way you can just ask in plain language ("generate an image of …"). The MCP tools are model-invoked and do not require a slash command.
  </Accordion>

  <Accordion title="The sign-in did not open a browser.">
    In Claude Code, run `/mcp`, select **comfy-cloud**, and choose **Authenticate**. In Claude Desktop, reopen the connector from **Customize → Connectors** and trigger sign-in.
  </Accordion>
</AccordionGroup>


# Skills
Source: https://docs.comfy.org/agent-tools/skills

Agent skills and plugins for Comfy, published through the Comfy Skills repository.

[**Comfy Skills**](https://github.com/Comfy-Org/comfy-skills) is the home of skills and plugins for coding agents. Skills are packaged knowledge an agent loads on demand: model guidance, workflow patterns, and ready-made commands.

The repository hosts:

* **Claude Code plugins**: for example **comfy-cloud**, which adds the Comfy Cloud MCP connection and the `/comfy-cloud:*` slash commands in one install.
* **Agent skills**: focused instructions for specific tasks, such as current model recommendations and workflow-building know-how, kept up to date as models change.
* **Community contributions**: skills and plugins from the Comfy community.

To use it in Claude Code:

```
/plugin marketplace add Comfy-Org/comfy-skills
/plugin install comfy-cloud@comfy-skills
```

For the plugin's slash commands and setup details, see [Comfy MCP](/agent-tools/mcp).


# Custom Nodes
Source: https://docs.comfy.org/basic-concepts/custom-nodes

Custom nodes in ComfyUI: how they differ from Comfy Core nodes, plus installing, updating, enabling dependencies, disabling, and uninstalling them.

## About Custom Nodes

After installing ComfyUI, you'll discover that it includes many built-in nodes. These native nodes are called **Comfy Core** nodes, which are officially maintained by ComfyUI.

Additionally, there are numerous [**custom nodes**](https://registry.comfy.org) created by various authors from the ComfyUI community. These custom nodes bring extensive functionality to ComfyUI, greatly expanding its capabilities and feature boundaries.

In this guide, we'll cover various operations related to custom nodes, including installation, updates, disabling, uninstalling, and dependency installation.

Anyone can develop their own custom extensions for ComfyUI and share them with others. You can find many community custom nodes [here](https://registry.comfy.org). If you want to develop your own custom nodes, visit the section below to get started:

<Card title="Start Developing Custom Nodes" icon="link" href="/custom-nodes/overview">
  Learn how to start developing a custom node
</Card>

## Custom Node Management

In this section we will cover:

* Installing custom nodes
* Installing node dependencies
* Custom node version control
* Uninstalling custom nodes
* Temporarily disabling custom nodes
* Handling custom node dependency conflicts

### 1. Installing Custom Nodes

Currently, ComfyUI supports installing custom nodes through multiple methods, including:

* [Install via ComfyUI Manager (Recommended)](#install-via-comfyui-manager)
* Install via Git
* Manual installation

We recommend installing custom nodes through **ComfyUI Manager**, which is a highly significant tool in the ComfyUI custom node ecosystem. It makes custom node management (such as searching, installing, updating, disabling, and uninstalling) simple - you just need to search for the node you want to install in ComfyUI Manager and click install.

However, since all custom nodes are currently stored on GitHub, for regions that cannot access GitHub normally, we have written detailed instructions for different custom node installation methods in this guide.

Additionally, since we recommend using **ComfyUI Manager** for plugin management, we recommend using this tool for plugin management. You can find its source code [here](https://github.com/Comfy-Org/ComfyUI-Manager).
Therefore, in this documentation, we will use installing ComfyUI Manager as a custom node installation example, and supplement how to use it for node management in the relevant introduction sections.

<Tabs>
  <Tab title="Install via ComfyUI Manager">
    Since ComfyUI Manager has very rich functionality, we will use a separate document to introduce the ComfyUI Manager installation chapter. Please visit the link below to learn how to use ComfyUI Manager to install custom nodes.

    <Card title="Install Custom Nodes with ComfyUI Manager" icon="link" href="/installation/install_custom_node#method-1-comfyui-manager-recommended">
      Learn how to use ComfyUI Manager to install custom nodes
    </Card>
  </Tab>

  <Tab title="Install via Git">
    <Steps>
      <Step title="Ensure Git is Installed">
        First, you need to ensure that Git is installed on your system. You can check if Git is installed by entering the following command in your system terminal:

        ```bash theme={null}
        git --version
        ```

        If Git is installed, you will see output similar to the following:

        <img alt="Windows Terminal" />

        If not yet installed, please visit [git-scm.com](https://git-scm.com/) to download the corresponding installation package. Linux users please refer to [git-scm.com/downloads/linux](https://git-scm.com/downloads/linux) for installation instructions.

        <Tip>
          For Comfy Desktop version, you can use the Desktop terminal as shown below to complete the installation.

          <img alt="Comfy Desktop Terminal" />
        </Tip>
      </Step>

      <Step title="Clone Custom Node Code to Directory">
        After completing the Git installation, we need the repository address of the custom node. Here we use the ComfyUI-Manager repository address as an example:

        ```bash theme={null}
        https://github.com/Comfy-Org/ComfyUI-Manager
        ```

        <Tip>For regions that cannot access GitHub smoothly, you can try using other code hosting service websites to fork the corresponding repository, then use that repository address to complete the node installation, such as gitee, etc.</Tip>

        First, we need to navigate to the ComfyUI custom nodes directory. Using ComfyUI portable version as an example, if the folder location is `D:\ComfyUI_windows_portable`, then you should be able to find the custom nodes folder at `D:\ComfyUI_windows_portable\ComfyUI\custom_nodes`. First, we need to use the `cd` command to enter the corresponding directory:

        ```bash theme={null}
        cd D:\ComfyUI_windows_portable\ComfyUI\custom_nodes
        ```

        Then we use the `git clone` command to complete the node installation:

        ```bash theme={null}
        git clone https://github.com/Comfy-Org/ComfyUI-Manager
        ```

        If everything goes smoothly, you will see output similar to the following:

        <img alt="Install Custom Nodes via Git" />

        This means you have successfully cloned the custom node code. Next, we need to install the corresponding dependencies.
      </Step>

      <Step title="Install Dependencies">
        Please refer to the instructions in the [Installing Node Dependencies](#2-installing-node-dependencies) section for dependency installation.
      </Step>
    </Steps>
  </Tab>

  <Tab title="Manual Installation">
    Manual installation is not the recommended installation method, but it serves as a backup option when you cannot install smoothly using git.

    <Warning>
      Plugins installed this way will lose the corresponding git version history information and will not be convenient for subsequent version management.
    </Warning>

    <Steps>
      <Step title="Download Custom Node Code ZIP Package">
        For manual installation, we need to first download the corresponding node code and then extract it to the appropriate directory.

        <img alt="Download Node Code" />

        Visit the corresponding custom node repository page:

        1. Click the `Code` button
        2. Then click the `Download ZIP` button to download the ZIP package
        3. Extract the ZIP package
      </Step>

      <Step title="Copy Files to ComfyUI Custom Nodes Directory">
        Copy the extracted code from the above steps to the ComfyUI custom nodes directory. Using ComfyUI portable version as an example, if the folder location is `D:\ComfyUI_windows_portable`, then you should be able to find the custom nodes folder at `D:\ComfyUI_windows_portable\ComfyUI\custom_nodes`. Copy the extracted code from the above steps to the corresponding directory.
      </Step>

      <Step title="Install Dependencies">
        Please refer to the instructions in the [Installing Node Dependencies](#2-installing-node-dependencies) section for dependency installation.
      </Step>
    </Steps>
  </Tab>
</Tabs>

### 2. Installing Node Dependencies

Custom nodes all require the installation of related dependencies. For example, for ComfyUI-Manager, you can visit the [requirements.txt](https://github.com/Comfy-Org/ComfyUI-Manager/blob/main/requirements.txt) file to view the dependency package requirements.

In the previous steps, we only cloned the custom node code locally and did not install the corresponding dependencies, so next we need to install the corresponding dependencies.

<Note>
  Actually, if you use ComfyUI-Manager to install plugins, ComfyUI Manager will automatically help you complete the dependency installation. You just need to restart ComfyUI after installing the plugin. This is why we strongly recommend using ComfyUI Manager to install custom nodes.

  But perhaps you may not be able to use ComfyUI Manager to install custom nodes smoothly in some situations, so we provide this more detailed dependency installation guide.
</Note>

In the [Dependencies](/basic-concepts/dependencies) chapter, we introduced the relevant content about dependencies in ComfyUI. ComfyUI is a **Python**-based project, and we built an independent **Python** runtime environment for running ComfyUI. All related dependencies need to be installed in this independent **Python** runtime environment.

If you run `pip install -r requirements.txt` directly in the system-level terminal, the corresponding dependencies may be installed in the system-level **Python** environment, which will cause the dependencies to still be missing in ComfyUI's environment, preventing the corresponding custom nodes from running normally.

So next we need to use ComfyUI's independent Python runtime environment to complete the dependency installation.

Depending on different ComfyUI versions, we will use different methods to install the corresponding dependencies:

<Tabs>
  <Tab title="ComfyUI Portable">
    For ComfyUI Portable version, it uses an embedded Python located in the `\ComfyUI_windows_portable\python_embeded` directory. We need to use this Python to complete the dependency installation.

    First, start the terminal in the portable version directory, or use the `cd` command to navigate to the `\ComfyUI_windows_portable\` directory after starting the terminal.

    <img alt="Start Terminal" />

    Ensure that the terminal directory is `\ComfyUI_windows_portable\`, as shown below for `D:\ComfyUI_windows_portable\`

    <img alt="Terminal" />

    Then use `python_embeded\python.exe` to complete the dependency installation:

    ```bash theme={null}
    python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\ComfyUI-Manager\requirements.txt
    ```

    Of course, you can replace ComfyUI-Manager with the name of the custom node you actually installed, but make sure that a `requirements.txt` file exists in the corresponding node directory.
  </Tab>

  <Tab title="Comfy Desktop">
    <Tip>
      Since Comfy Desktop already has ComfyUI-Manager and its dependencies installed during the installation process, and this guide uses ComfyUI Manager as an example for custom node installation, you don't actually need to perform ComfyUI Manager dependency installation in the desktop version.
      If there are no unexpected issues, we recommend using ComfyUI Manager to install custom nodes, so you don't need to manually install dependencies.
    </Tip>

    <img alt="Comfy Desktop Terminal" />

    Then use the following command to install the dependencies for the corresponding plugin:

    ```bash theme={null}
    pip install -r .\custom_nodes\<corresponding_custom_node_name>\requirements.txt
    ```

    As shown below, this is the dependency installation for ComfyUI-Hunyuan3Dwrapper:

    <img alt="Comfy Desktop Dependency Installation" />
  </Tab>

  <Tab title="Custom Python Environment Users">
    For users with custom Python environments, we recommend using `pip install -r requirements.txt` to complete the dependency installation.
  </Tab>
</Tabs>

### Custom Node Version Control

Custom node version control is actually based on Git version control. You can manage node versions through Git, but ComfyUI Manager has already integrated this version management functionality very well. Many thanks to [@Dr.Lt.Data](https://github.com/ltdrdata) for bringing us such a convenient tool.

In this section, we will still explain these two different plugin version management methods for you, but if you use ZIP packages for manual installation, the corresponding git version history information will be lost, making it impossible to perform version management.

<Tabs>
  <Tab title="Version Management with ComfyUI Manager">
    <Tip>Since we are iterating on ComfyUI Manager, the actual latest interface and steps may change significantly</Tip>

    <Steps>
      <Step title="Enter Node Management Interface">
        Perform the corresponding operations as shown to enter the ComfyUI Manager interface
      </Step>

      <Step title="Find the Corresponding Custom Node Package">
        You can use the corresponding filters to filter out installed node packages and then perform the corresponding node management
      </Step>

      <Step title="Perform Version Switching">
        Switch to the corresponding version. Manager will help you complete the corresponding dependency updates and installation. Usually, you need to restart ComfyUI after switching versions for the changes to take effect.
      </Step>
    </Steps>
  </Tab>

  <Tab title="Version Management with Git">
    <Steps>
      <Step title="Navigate to Directory Using Command Line">
        Find the directory folder where your corresponding node is located, such as `ComfyUI/custom_nodes/ComfyUI-Manager`
        Use the `cd` command to enter the corresponding folder:

        ```bash theme={null}
        cd <your_installation_directory>/ComfyUI/custom_nodes/ComfyUI-Manager
        ```
      </Step>

      <Step title="View Versions Using Git Commands">
        You can use the following command to view all available tags and releases:

        ```bash theme={null}
        git tag
        ```

        This will list all version tags, and you can choose the version you want to switch to.
      </Step>

      <Step title="Switch to Specified Version">
        Use the following command to switch to a specified tag or release:

        ```bash theme={null}
        git checkout <tag_name>
        ```

        Replace `<tag_name>` with the specific version tag you want to switch to.
      </Step>

      <Step title="Switch to Specific Commit Version">
        If you want to switch to a specific commit version, you can use the following command:

        ```bash theme={null}
        git checkout <commit_hash>
        ```

        Replace `<commit_hash>` with the specific commit hash you want to switch to.
      </Step>

      <Step title="Install Dependencies">
        Since the dependencies of the corresponding custom node package may change after version switching, you need to reinstall the dependencies for the corresponding node. Please refer to the instructions in the [Installing Node Dependencies](#2-installing-node-dependencies) section to enter the corresponding environment for installation.
      </Step>
    </Steps>
  </Tab>
</Tabs>

### Uninstalling Custom Nodes

To be updated

### Temporarily Disabling Custom Nodes

To be updated

### Custom Node Dependency Conflicts

To be updated

## ComfyUI Manager

<img alt="ComfyUI Manager Interface" />

This tool is currently included by default in the [Desktop version](/installation/desktop/windows), while in the [Portable version](/installation/comfyui_portable_windows), you need to refer to the installation instructions in the [Install Manager](#1-installing-custom-nodes) section of this document.

<Note>
  As ComfyUI continues to develop, ComfyUI Manager plays an increasingly important role in ComfyUI. Currently, ComfyUI-Manager has officially joined the Comfy Org organization, officially becoming part of ComfyUI's core dependencies, and continues to be maintained by the original author [Dr.Lt.Data](https://github.com/ltdrdata). You can read [this blog post](https://blog.comfy.org/p/comfyui-manager-joins-comfy-org) for more information.
  In future iterations, we will greatly optimize the use of ComfyUI Manager, so the interface shown in this documentation may differ from the latest version of ComfyUI Manager.
</Note>

### Installing the Manager

If you are running the ComfyUI server application, you need to install the manager. If ComfyUI is running, please close it before continuing.

The first step is to install Git, which is a command-line application for software version control. Git will download the ComfyUI manager from [github.com](https://github.com). Download and install Git from [git-scm.com](https://git-scm.com/).

After installing Git, navigate to the ComfyUI server program directory and enter the folder labeled **custom\_nodes**. Open a command window or terminal. Make sure the command line shows the current directory path as **custom\_nodes**. Run the following command to clone the ComfyUI-Manager repository:

```bash theme={null}
git clone https://github.com/Comfy-Org/ComfyUI-Manager.git
```

This will download the manager. Technically, this is called *cloning a Git repository*.

### Detecting Missing Nodes

After installing the manager, you can detect missing nodes in the manager.

<img alt="ComfyUI Manager Interface" />

## Developing a Custom Node

If you have some development capabilities, please start with the documentation below to learn how to begin developing a custom node.

<Card title="Start Developing Custom Nodes" icon="link" href="/custom-nodes/overview">
  Learn how to start developing a custom node
</Card>


# Dependencies
Source: https://docs.comfy.org/basic-concepts/dependencies

Learn what ComfyUI workflows depend on to run: media assets, custom nodes, Python packages, and models.

## A workflow file depends on other files

We often obtain various workflow files from the community, but frequently find that the workflow cannot run directly after loading. This is because a workflow file depends on other files besides the workflow itself, such as media asset inputs, models, custom nodes, related Python dependencies, etc.
ComfyUI workflows can only run normally when all relevant dependencies are satisfied.

ComfyUI workflow dependencies mainly fall into the following categories:

* Assets (media files including audio, video, images, and other inputs)
* Custom nodes
* Python dependencies
* Models (such as Stable Diffusion models, etc.)

## Assets

An AI model is an example of an ***asset***. In media production, an asset is some media file that supplies input data. For example, a video editing program operates on movie files stored on disk. The editing program's project file holds links to these movie file assets, allowing non-destructive editing that doesn't alter the original movie files.

ComfyUI works the same way. A workflow can only run if all of the required assets are found and loaded. Generative AI models, images, movies, and sounds are some examples of assets that a workflow might depend upon. These are therefore known as ***dependent assets*** or ***asset dependencies***.

## Custom Nodes

Custom nodes are an important component of ComfyUI that extend its functionality. They are created by the community and can be installed to add new capabilities to your workflows.

## Python Dependencies

ComfyUI is a Python-based project. We build a standalone Python environment to run ComfyUI, and all related dependencies are installed in this isolated Python environment.

### ComfyUI Dependencies

You can view ComfyUI's current dependencies in the [requirements.txt](https://github.com/Comfy-Org/ComfyUI/blob/master/requirements.txt) file:

```text theme={null}
comfyui-frontend-package==1.49.6
comfyui-workflow-templates==0.11.48
comfyui-embedded-docs==0.5.10
torch
torchsde
torchvision
torchaudio
numpy>=1.25.0
einops
transformers>=4.50.3
tokenizers>=0.13.3
sentencepiece
safetensors>=0.4.2
aiohttp>=3.11.8
yarl>=1.18.0
pyyaml
Pillow
scipy
tqdm
psutil
alembic
SQLAlchemy>=2.0.0
filelock
av>=17.0.0
comfy-kitchen==0.2.31
comfy-aimdo==0.4.15
requests
simpleeval>=1.0.0
blake3

#non essential dependencies:
kornia>=0.7.1
spandrel
pydantic~=2.0
pydantic-settings~=2.0
PyOpenGL>=3.1.8
comfy-angle
```

As ComfyUI evolves, we may adjust dependencies accordingly, such as adding new dependencies or removing ones that are no longer needed.
So if you use Git to update ComfyUI, you need to run the following command in the corresponding environment after pulling the latest updates:

```bash theme={null}
pip install -r requirements.txt
```

This ensures that ComfyUI's dependencies are up to date for proper operation. You can also modify specific package dependency versions to upgrade or downgrade certain dependencies.

Additionally, ComfyUI's frontend [ComfyUI\_frontend](https://github.com/Comfy-Org/ComfyUI_frontend) is currently maintained as a separate project. We update the `comfyui-frontend-package` dependency version after the corresponding version stabilizes. If you need to switch to a different frontend version, you can check the version information [here](https://pypi.org/project/comfyui-frontend-package/#history).

### Custom Node Dependencies

Thanks to the efforts of many authors in the ComfyUI community, we can extend ComfyUI's functionality by using different custom nodes, enabling impressive creativity.

Typically, each custom node has its own dependencies and a separate `requirements.txt` file.
If you use [ComfyUI Manager](https://github.com/Comfy-Org/ComfyUI-Manager) to install custom nodes, ComfyUI Manager will usually automatically install the corresponding dependencies.

There are also cases where you need to install dependencies manually. Currently, all custom nodes are installed in the `ComfyUI/custom_nodes` directory.

You need to navigate to the corresponding plugin directory in your ComfyUI Python environment and run `pip install -r requirements.txt` to install the dependencies.

If you're using the [Windows Portable version](/installation/comfyui_portable_windows), you can use the following command in the `ComfyUI_windows_portable` directory:

```
python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\<custom_node_name>\requirements.txt
```

to install the dependencies for the corresponding node.

### Dependency Conflicts

Dependency conflicts are a common issue when using ComfyUI. You might find that after installing or updating a custom node, previously installed custom nodes can no longer be found in ComfyUI's node library, or error pop-ups appear. One possible reason is dependency conflicts.

There can be many reasons for dependency conflicts, such as:

1. Custom node version locking

Some plugins may fix the exact version of a dependency library (e.g., `open_clip_torch==2.26.1`), while other plugins may require a higher version (e.g., `open_clip_torch>=2.29.0`), making it impossible to satisfy both version requirements simultaneously.

**Solution**: You can try changing the fixed version dependency to a range constraint, such as `open_clip_torch>=2.26.1`, and then reinstall the dependencies to resolve these issues.

2. Environment pollution

During the installation of custom node dependencies, it may overwrite versions of libraries already installed by other plugins. For example, multiple plugins may depend on `PyTorch` but require different CUDA versions, and the later installed plugin will break the existing environment.

**Solutions**:

* You can try manually installing specific versions of dependencies in the Python virtual environment to resolve such issues.
* Or create different Python virtual environments for different plugins to resolve these issues.
* Try installing plugins one by one, restarting ComfyUI after each installation to observe if dependency conflicts occur.

3. Custom node dependency versions incompatible with ComfyUI dependency versions

These types of dependency conflicts may be more difficult to resolve, and you may need to upgrade/downgrade ComfyUI or change the dependency versions of custom nodes to resolve these issues.

**Solution**: These types of dependency conflicts may be more difficult to resolve, and you may need to upgrade/downgrade ComfyUI or change the dependency versions of custom nodes to resolve these issues.

## Models

Models are a significant asset dependency for ComfyUI. Various custom nodes and workflows are built around specific models, such as the Stable Diffusion series, Flux series, Ltxv, and others.
These models are an essential foundation for creation with ComfyUI, so we need to ensure that the models we use are properly available. Typically, our models are saved in the corresponding directory under `ComfyUI/models/`. Of course, you can also create an [extra\_model\_paths.yaml](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example) by modifying the template to make additional model paths recognized by ComfyUI.
This allows multiple ComfyUI instances to share the same model library, reducing disk usage.

## Software

An advanced application like ComfyUI also has ***software dependencies***. These are libraries of programming code and data that are required for the application to run. Custom nodes are examples of software dependencies. On an even more fundamental level, the Python programming environment is the ultimate dependency for ComfyUI. The correct version of Python is required to run a particular version of ComfyUI. Updates to Python, ComfyUI, and custom nodes can all be handled from the **ComfyUI Manager** window.

<img alt="ComfyUI Custom Nodes Manager" />


# ComfyUI Links: How Node Connections Work
Source: https://docs.comfy.org/basic-concepts/links

Learn how links connect nodes in ComfyUI, how to change link render styles, and how the Reroute node keeps complex workflows readable.

## Links connect nodes

In ComfyUI, the lines or curves drawn between nodes are called ***links*** (also referred to as ***connections*** or wires). They carry data from one node's output to another node's input, defining the flow of your workflow.

Links can be displayed in several visual styles: curves, right angles, straight lines, or hidden entirely.

<img alt="Link styles" />

To change the link style, go to **Setup Menu** → **Display (Lite Graph)** → **Graph** → **Link Render Mode**.

<img alt="Render mode setting" />

You can also temporarily hide all links from the **Canvas Menu**.

<img alt="Canvas Menu" />

<Tip>
  Showing links is especially useful when learning, sharing, or debugging a workflow. They make the data flow visible at a glance. For finished workflows that aren't meant to be edited, hiding links can reduce visual clutter.
</Tip>

### Reroute node

When a workflow becomes complex, link wires can overlap or pass behind nodes, making it hard to read. The **Reroute** node lets you manually redirect a wire through any point in the 2D graph space, keeping the layout clean and legible.

<img alt="ComfyUI Reroute node" />

ComfyUI also has a built-in native reroute feature in the graph canvas. We recommend using this for new workflows.

<img alt="ComfyUI Native Reroute" />

## Color-coding

Every data type in ComfyUI has a distinct color. Node input and output ports, as well as the link wires connecting them, all share this color scheme. **You can only connect ports of the same color**. This ensures type safety across your workflow.

<img alt="ComfyUI Node Data Types" />

| Data type | Color |
| - | - |
| Diffusion model | Lavender |
| CLIP model | Yellow |
| VAE model | Rose |
| Conditioning | Orange |
| Latent Image | Pink |
| Pixel image | Blue |
| Mask | Green |
| Number (integer or float) | Gray |
| Mesh | Bright green |


# Models
Source: https://docs.comfy.org/basic-concepts/models

How model files fit into ComfyUI workflows: where they go, how to load them, and common fixes.

## Models in plain terms

In ComfyUI, **models** are the weight files that actually run your workflow. They include **checkpoints**, **VAEs**, **LoRAs**, **ControlNets**, and upscalers. The app install is small. These files are **not** included by default. You usually **download them from the web**, place them under `ComfyUI/models/` (or follow a template’s prompts), then choose the file in the right **loader node** (on the canvas, these often appear as nodes whose names start with **Load**).

### Supported models in ComfyUI

* **Built-in / first-party coverage is intentionally limited** but grows over time as ComfyUI and the open-source ecosystem evolve. When a model gains first-class support, you will **usually see a new entry in the [workflow template library](/interface/features/template)** that shows the expected graph and model pairing.
* **Not every checkpoint or weights file works out of the box.** For **natively supported models and their common companion weights**, keep ComfyUI **[up to date](/installation/update_comfyui)** and confirm the matching workflow exists in the **[template library](/interface/features/template)** before assuming your files are in the wrong place.
* **Many other models are enabled through community custom nodes.** Paths, loader nodes, and graph layout can differ from this page’s generic `ComfyUI/models/` guidance. **Always follow each project’s README or docs.** ComfyUI is highly extensible, so implementations vary by author. For installation and troubleshooting, see [How to install custom nodes](/installation/install_custom_node).

## Use models in ComfyUI

1. **Get the files into the right place.** Download from community sites such as [Hugging Face](https://huggingface.co), [Civitai](https://civitai.green), or a project’s page on [GitHub](https://github.com), then put them under `ComfyUI/models/` in the subfolder for that type (for example `checkpoints`, `loras`, `vae`).
2. **Add the matching loader node.** Pick the loader for that model type (checkpoint, LoRA, VAE, etc.). In the node list, titles often begin with **Load**.
3. **Pick the file** in that loader node’s dropdown.
4. **Wire the loader node** into the rest of the graph. If you copied files in by hand while ComfyUI was open, **restart** the app (or refresh as needed) so lists update.

### Expect large downloads

A single generative model is often **many gigabytes**. Budget disk space and time when downloading or syncing.

## Beyond the main checkpoint

The main diffusion checkpoint does a lot, but many workflows add **smaller helper models**, for example:

* **LoRA**: lightweight add-ons tuned for a style, character, or concept
* **ControlNet**: extra guidance from edges, depth, pose, etc.
* **Inpainting**: fill or replace regions inside an existing image

<img alt="auxiliary models" />

## Uninstalling models

There is no “uninstall” button in the UI yet. To remove a model, **delete its file** (or files) from the folder under `ComfyUI/models/` where you put it.

## Adding Extra Model Paths

If you want to manage your model files outside of `ComfyUI/models`, you may have the following reasons:

* You have multiple ComfyUI instances and want them to share model files to save disk space
* You have different types of GUI programs (such as WebUI) and want them to use the same model files
* Model files cannot be recognized or found

We provide a way to add extra model search paths via the `extra_model_paths.yaml` configuration file

### Open Config File

<Tabs>
  <Tab title="Portable/Manual Install">
    For the ComfyUI version such as [portable](/installation/comfyui_portable_windows) and [manual](/installation/manual_install), you can find an example file named `extra_model_paths.yaml.example` in the root directory of ComfyUI:

    ```
    ComfyUI/extra_model_paths.yaml.example
    ```

    Copy and rename it to `extra_model_paths.yaml` for use. Keep it in ComfyUI's root directory at `ComfyUI/extra_model_paths.yaml`.
    You can also find the config example file [here](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example)
  </Tab>

  <Tab title="Comfy Desktop">
    If you are using the [Comfy Desktop](/installation/desktop/windows) application, click the capsule menu at the top of the desktop app, then open the **Storage** tab and add your model directories there. The capsule only exists in the desktop app, not when ComfyUI runs in a browser.

    <img alt="Comfy Desktop capsule menu: Storage tab showing model directory settings" />

    Or open it directly at:

    <Tabs>
      <Tab title="Windows">
        ```
        C:\Users\YourUsername\AppData\Roaming\ComfyUI\extra_models_config.yaml
        ```
      </Tab>

      <Tab title="macOS">
        ```
        ~/Library/Application Support/ComfyUI/extra_models_config.yaml
        ```
      </Tab>
    </Tabs>

    You should keep the file in the same directory, should not move these files to other places.
  </Tab>
</Tabs>

If the file does not exist, you can create it yourself with any text editor.

### Example Structure

Suppose you want to add the following model paths to ComfyUI:

```
📁 YOUR_PATH/
  ├── 📁models/
  |   ├── 📁 loras/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 checkpoints/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 vae/
  |   │   └── xxxxx.safetensors
  |   └── 📁 controlnet/
  |       └── xxxxx.safetensors
```

Then you can configure the `extra_model_paths.yaml` file like below to let ComfyUI recognize the model paths on your device:

```
my_custom_config:
    base_path: YOUR_PATH
    loras: models/loras/
    checkpoints: models/checkpoints/
    vae: models/vae/
    controlnet: models/controlnet/
```

or

```
my_custom_config:
    base_path: YOUR_PATH/models/
    loras: loras
    checkpoints: checkpoints
    vae: vae
    controlnet: controlnet
```

<Warning>
  For the desktop version, please add the configuration to the existing configuration path without overwriting the path configuration generated during installation. Please back up the corresponding file before modification, so that you can restore it when you make a mistake.
</Warning>

Or you can refer to the default [extra\_model\_paths.yaml.example](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example) for more configuration options. After saving, you need to **restart ComfyUI** for the changes to take effect.

Below is the original config example:

```yaml theme={null}
#Rename this to extra_model_paths.yaml and ComfyUI will load it


#config for a1111 ui
#all you have to do is change the base_path to where yours is installed
a111:
    base_path: path/to/stable-diffusion-webui/

    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet

#config for comfyui
#your base path should be either an existing comfy install or a central folder where you store all of your models, loras, etc.

#comfyui:
#     base_path: path/to/comfyui/
#     # You can use is_default to mark that these folders should be listed first, and used as the default dirs for eg downloads
#     #is_default: true
#     checkpoints: models/checkpoints/
#     clip: models/clip/
#     clip_vision: models/clip_vision/
#     configs: models/configs/
#     controlnet: models/controlnet/
#     diffusion_models: |
#                  models/diffusion_models
#                  models/unet
#     embeddings: models/embeddings/
#     loras: models/loras/
#     upscale_models: models/upscale_models/
#     vae: models/vae/

#other_ui:
#    base_path: path/to/ui
#    checkpoints: models/checkpoints
#    gligen: models/gligen
#    custom_nodes: path/custom_nodes

```

For example, if your WebUI is located at `D:\stable-diffusion-webui\`, you can modify the corresponding configuration to

```yaml theme={null}
a111:
    base_path: D:\stable-diffusion-webui\
    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet
```

### Add Extra Custom Nodes Path

Besides adding external models, you can also add custom nodes paths that are not in the default path of ComfyUI

<Tip>
  Please note that this will not change the default installation path of custom nodes, but will add an extra path search when starting ComfyUI. You still need to complete the installation of custom node dependencies in the corresponding environment to ensure the integrity of the running environment.
</Tip>

Below is a simple configuration example (MacOS), please modify it according to your actual situation and add it to the corresponding configuration file, save it and restart ComfyUI for the changes to take effect:

```yaml theme={null}
my_custom_nodes:
  custom_nodes: /Users/your_username/Documents/extra_custom_nodes
```

## Common issues

<AccordionGroup>
  <Accordion title="Does ComfyUI support GGUF format models?">
    ComfyUI does not natively support GGUF format models. To use GGUF models, you need to install community custom nodes such as [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF).
  </Accordion>

  <Accordion title="Why can't I find my model?">
    If you've installed a model but can't find it in ComfyUI, try these steps:

    * Verify the model is in the correct location:

      * Default path: `ComfyUI/models/` (e.g. `checkpoints`, `loras`, `vae`)
      * For **Comfy Desktop**: Click the capsule menu at the top of the desktop app, then open the **Storage** tab to check your model directories. The capsule only exists in the desktop app, not when ComfyUI runs in a browser.

      <img alt="Comfy Desktop capsule menu: Storage tab showing model directory settings" />
    * Press the `r` key to refresh node definitions so ComfyUI can detect the model
    * Restart ComfyUI
    * Ensure the correct model is selected in the loader node
  </Accordion>
</AccordionGroup>

## Want a bit more background?

<AccordionGroup>
  <Accordion title="What does “model” mean here?">
    Here, a **model** is a data file that encodes what a network learned. It contains enough information to turn inputs (like text and noise) into outputs (like an image). Common examples in image workflows are **diffusion** checkpoints, text/image encoders such as **CLIP**, and **upscalers** like RealESRGAN.
  </Accordion>

  <Accordion title="Base models and community variants">
    Large **base** models from labs and open-source projects are general-purpose. The community often **fine-tunes** or merges them into new checkpoints and LoRAs that look better for a given style, run a bit lighter, or add new behavior. This is similar to picking a favorite checkpoint on Civitai or Hugging Face.
  </Accordion>
</AccordionGroup>


# Nodes
Source: https://docs.comfy.org/basic-concepts/nodes

Nodes are ComfyUI's fundamental building blocks: independent Comfy Core or custom modules you connect with links to assemble complex workflows.

In ComfyUI, nodes are the fundamental building blocks for executing tasks. Each node is an independently built module, whether it's a **Comfy Core** node or a **Custom Node**, with its own unique functionality. Nodes connect to each other through links, allowing us to build complex functionality like assembling LEGO blocks.
The combinations of different nodes create the unlimited possibilities of ComfyUI.

<img alt="Comfy Core K-Sampler Node" />

For example, in the K-Sampler node, you can see it has multiple inputs and outputs, and also includes multiple parameter settings. These parameters determine the logic of node execution. Behind each node is well-written Python logic, allowing you to achieve corresponding functionality without having to write code yourself.

<Note>
  ComfyUI is under active development, so some details here may be outdated. If you spot something that's changed, feel free to [help us update the docs](https://github.com/Comfy-Org/docs).
</Note>

## Nodes perform operations

In computer science, a ***node*** is a container for information, usually including programmed instructions to perform some task. Nodes almost never exist in isolation, they're almost always connected to other nodes in a networked graph. In ComfyUI, nodes take the visual form of boxes that are connected to each other.

ComfyUI nodes are usually ***function operators***. This means that they operate on some data to perform a function. A function is a process that accepts input data, performs some operation on it, and produces output data. In other words, nodes do some work, contributing to the completion of a task such as generating an image. So ComfyUI nodes almost always have at least one input or output, and usually have multiple inputs and outputs.

## Different Node States

<img alt="Node States" />

In ComfyUI, nodes have multiple states. Here are some common node states:

1. **Normal State**: The default state
2. **Running State**: The running state, typically displayed when a node is executing after you start running the workflow
3. **Error State**: Node error, typically displayed after running the workflow if there's a problem with the node's input, indicated by red marking of the erroneous input node. You need to fix the problematic input to ensure the workflow runs correctly
4. **Missing State**: This state usually appears after importing workflows, with two possibilities:
   * Comfy Core native node missing: This usually happens because ComfyUI has been updated, but you're using an older version of ComfyUI. You need to update ComfyUI to resolve this issue
   * Custom node missing: The workflow uses custom nodes developed by third-party authors, but your local ComfyUI version doesn't have these custom nodes installed. You can use [ComfyUI Manager](/manager/overview) to find and install them, or follow [How to install custom nodes](/installation/install_custom_node) for other methods

## Connections Between Nodes

In ComfyUI, nodes are connected through [links](/basic-concepts/links), allowing data of the same type to flow between different processing units to achieve the final result.

<img alt="ComfyUI Node Links" />

Each node receives some input, processes it through its module, and converts it to corresponding output. Connections between different nodes must conform to the data type requirements. In ComfyUI, we use different colors to distinguish node data types. Below are some basic data types:

<img alt="ComfyUI Node Data Types" />

| Data type | Color |
| - | - |
| diffusion model | lavender |
| CLIP model | yellow |
| VAE model | rose |
| conditioning | orange |
| latent image | pink |
| pixel image | blue |
| mask | green |
| number (integer or float) | light green |
| mesh | bright green |

As ComfyUI evolves, we may expand to more data types to meet the needs of more scenarios.

### Connecting and Disconnecting Nodes

<img alt="ComfyUI Node Connecting" />

**Connecting**: Drag from the output point of one node to the input of the same color on another node to connect them
**Disconnecting**: Click on the input endpoint and drag the mouse left button to disconnect, or cancel the connection through the midpoint menu of the link

## Node Appearance

<img alt="Node Appearance" />

We provide various style settings for you to customize the appearance of nodes:

* Modify styles
* Double-click the node title to modify the node name
* Resize the node by dragging any corner

<video />

### Node Badges

<img alt="Node Badges" />

We provide multiple node badge display features, such as:

* Node ID
* Node source

Currently, **Comfy Core nodes** use a fox icon for display, while custom nodes use their names. This way you can quickly understand which node package a node comes from.

You can set the corresponding display in the menu:

<img alt="Badge Settings" />

## Node Context Menus

Node context menus are mainly divided into two types:

* Context menu for the node itself
* Context menu for inputs/outputs

### Node Context Menu

By right-clicking on a node, you can expand the corresponding node context menu:

<img alt="Node Context Menu" />

In the node's right-click context menu, you can:

* Adjust the node's color style
* Modify the title
* Clone, copy, or delete the node
* Set the node's mode

In this menu, besides appearance-related settings, the following menu operations are important:

* **Mode**: Set the node's mode: Always, Never, Bypass

#### Mode

For modes, you may notice that we currently provide: Always, Never, On Event, On Trigger - four modes, but actually only **Always** and **Never** are effective. **On Event** and **On Trigger** are currently ineffective as we haven't fully implemented this feature. Additionally, you can understand **Bypass** as a mode. Below is an explanation of the available modes:

* **Always**: The default node mode. The node will execute whenever it runs for the first time or when any of its inputs change since the last execution
* **Never**: The node will never execute under any circumstances, as if it's been deleted. Subsequent nodes cannot read or receive any data from it
* **Bypass**: The node will never execute under any circumstances, but subsequent nodes can still try to obtain data that hasn't been processed by this node

Below is a comparison of the `Never` and `Bypass` modes:

<img alt="Never vs Bypass Mode" />

In this comparison example, you can see that both workflows apply two LoRA models simultaneously, with the difference being that one `Load LoRA` node is set to `Never` mode while the other is set to `Bypass` mode.

* The node set to `Never` mode causes subsequent nodes to show errors because they don't receive any input data
* The node set to `Bypass` mode still allows subsequent nodes to receive unprocessed data, so they load the output data from the first `Load LoRA` node, allowing the subsequent workflow to continue running normally

### Input/Output Context Menu

This context menu is mainly related to the data type of the corresponding input/output:

<img alt="Node Input/Output Context Menu" />

When dragging the input/output of a node, if a connection appears but you haven't connected to another node's input or output, releasing the mouse will pop up a context menu for the input/output, used to quickly add related types of nodes.
You can adjust the number of node suggestions in the settings:

<img alt="Node Suggestion Count" />

## Node Selection Toolbox

<video />

The **Node Selection Toolbox** is a floating tool that provides quick operations for nodes. When you select a node, it hovers above the selected node. Through this toolbox, you can:

* Change the node's color
* Quickly set the node to Bypass mode (not execute during runtime)
* Lock the node
* Delete the node

Of course, these functions can also be found in the right-click menu of the corresponding node. The node selection toolbox just provides a shortcut operation. If you want to disable this feature, you can turn it off in the settings.

<img alt="Disable Node Selection Toolbox" />

## Subgraphs

You can collapse a selection of nodes into one reusable subgraph node to tidy complex graphs and reuse the same structure across workflows.

<Card title="Subgraph" icon="share-nodes" href="/interface/features/subgraph">
  Learn how to create, edit, nest, and publish subgraph blueprints to the node library.
</Card>

## Custom Nodes

ComfyUI includes many **Comfy Core** nodes in the base installation. The community also maintains a large catalog of [**custom nodes**](https://registry.comfy.org) for specialized workflows.

For a full summary of how to install custom nodes—**ComfyUI Manager**, Git clone, ZIP download, dependencies, and safety tips—see [How to install custom nodes](/installation/install_custom_node).

### ComfyUI Manager

Use **ComfyUI Manager** for everyday custom node work: search and install from the registry, update or disable packages, detect missing nodes from imported workflows, and manage models and snapshots alongside extensions. Desktop builds ship with it enabled; portable and manual installs may need to turn it on first.

<Card title="ComfyUI Manager" icon="puzzle-piece" href="/manager/overview">
  Overview, enabling the Manager, and node installation workflows
</Card>


# Properties
Source: https://docs.comfy.org/basic-concepts/properties

Master Comfy properties with our official development documentation. Understand core concepts to build custom nodes efficiently. Read the full guide now.

## Nodes are containers for properties

Nodes usually have ***properties***. Also known as ***parameters*** or ***attributes***, node properties are variables that can be changed. Some properties can be adjusted manually by the user, using a data entry field called a ***widget***. Other properties can be driven automatically by other nodes connected to the property ***input slot*** or port. Usually, a property can be converted from widget to input and vice versa, allowing users to control property values manually or automatically.

Properties can take many forms and hold many different types of information. For example, a **Load Checkpoint** node has a single property:  the file path to the generative model checkpoint file. A **KSampler** node has multiple properties such as the number of sampling **steps**, **CFG** scale, **sampler\_name**, etc.

<img alt="node properties" />

## Data types

Information can come in many different forms, called ***data types***. For example, alphanumeric text is known as a ***string***, a whole number is an ***integer***, and a number with a decimal point is known as a ***floating point*** number or ***float***. New data types are always being added to ComfyUI.

ComfyUI is written in the Python scripting language, which is very forgiving about data types. By contrast, the ComfyUI environment is very ***strongly typed***. This means that different data types can’t be mixed up. For example, we can’t connect an image output to an integer input. This is a huge benefit to users, guiding them to proper workflow construction and preventing program errors.


# ComfyUI Workflows: Nodes, Links, and Visual Programming
Source: https://docs.comfy.org/basic-concepts/workflow

Learn what a workflow is in ComfyUI: a graph of connected nodes that creates images, video, audio, and 3D. Covers nodes, links, and saving workflows as JSON.

## What is a workflow?

A workflow is a set of steps that tells ComfyUI how to create something.

You can think of a workflow like a recipe:

* The recipe is the workflow.
* Each instruction in the recipe is a node.
* The ingredients include prompts, images, and models.
* The result is the generated image, video, audio, or other output.

For example, a simple image workflow might:

1. Load a model.
2. Read a text prompt.
3. Generate an image.
4. Save the image.

ComfyUI displays these steps as boxes on a canvas.

<img alt="A simple ComfyUI workflow" />

## Nodes are the steps

A node performs one specific job. Some nodes load files, some change data, and others generate or save the result.

For example:

* A **Load Checkpoint** node loads an AI model.
* A **CLIP Text Encode** node turns your prompt into instructions for the model.
* A **KSampler** node generates an image from the model and those instructions.
* A **Save Image** node saves the result to your computer.

You can combine nodes in different ways to create different workflows. You do not need to write code to use them.

Learn more about nodes in [Nodes](/basic-concepts/nodes).

## Links pass data between nodes

Nodes work together by passing data from one node to another. A link connects an output from one node to an input on another node.

For example, a model loaded by a **Load Checkpoint** node can be passed to a **KSampler** node. Text instructions created by a text-encoding node can also be passed to the sampler.

Only compatible data types can be connected. For example, an image output cannot be connected directly to an input that expects a number.

Learn more about links in [Links](/basic-concepts/links).

## Properties control each step

Nodes contain properties. Properties are the settings that control how a node works.

For example, a sampler node may have properties for:

* The number of steps
* The guidance scale
* The sampling method
* The image size

You can usually set a property directly on the node. Some properties can also receive their values from another node.

Learn more about properties in [Properties](/basic-concepts/properties).

## Running a workflow

When you run a workflow, ComfyUI executes the required nodes and passes data through the links. The workflow continues until it produces its final output.

If a node is missing, has an error, or does not receive the data it needs, ComfyUI cannot complete the workflow. The node is marked so you can find and fix the problem.

## Starting with a template

To get started, open a built-in workflow template from **Workflow** → **Browse Workflow Templates**. Templates provide complete examples that you can run and edit.

Templates use Core nodes included with ComfyUI. They also prompt you to download any required models.

The community has created many custom nodes that add more capabilities. Learn more in [Custom Nodes](/basic-concepts/custom-nodes).

## Saving and sharing workflows

You can save a workflow as a JSON file and share it independently of the generated media.

When you save an output with a built-in save node, ComfyUI can also store the workflow inside the output file. You can then drag the file back onto the canvas to recover the workflow.

For details about the embedded data, supported file formats, and programmatic access, see [Workflow Metadata](/development/api-development/workflow-metadata).

## A little background

Technically, a workflow is a node graph. The nodes are the points in the graph, and the links show how data moves between them.

This is also called visual programming because you create a program by arranging and connecting visual blocks instead of writing code.


# Import models
Source: https://docs.comfy.org/cloud/import-models

Learn how to import models from Civitai and Hugging Face to Comfy Cloud

<Note>
  This is a **Comfy Cloud** feature and is only available in the cloud version. To learn more about Comfy Cloud, see [Comfy Cloud](/get_started/cloud).
</Note>

## Overview

Comfy Cloud allows you to import models directly from Civitai and Hugging Face. This feature is available for users with a **Creator** subscription or higher.

## Requirements

* **Subscription**: Creator tier or above
* **Supported sources**: Civitai and Hugging Face

## How to import models

### 1. Access the import feature

<img alt="Import" />

1. Click the **Models** button in the left sidebar to open the Model Library.
2. In the Model Library modal, click the **Import** button.

### 2. Paste the link

1. Paste the model link you obtained from Hugging Face or Civitai.
   <img alt="Import Modal" />

2. If the link is valid, you will see a confirmation indicator and can click the `Continue` button to proceed.
   <img alt="Import Modal" />

3. Select the model type and target folder.
   <img alt="Import Modal" />

4. Wait for the model to finish downloading.
   <img alt="Import Modal" />

5. Once downloaded, you can find the model in your Model Library.

## How to view imported models

In the Model Library, select "My Models" in the dropdown filter to filter out the models you imported.

<img alt="Imported Models" />

## How to get model import links

### 1. Get link from Civitai

1. Go to [Civitai](https://civitai.com/) and find the model you want to import.
2. Right-click the download button and select "Copy link address" to get the model download link.

<img alt="Copy Civitai Link" />

### 2. Get link from Hugging Face

1. Go to [Hugging Face](https://huggingface.co/) and find the model repository you want to import.
2. Navigate to the model files page. Supported formats are typically ".safetensor" or ".sft" files. Click on the specific model name to enter its detail page.

<img alt="Copy Huggingface model link" />

3. On the detail page, click the `Copy Download Link` button to get the model download link.

<img alt="Copy Huggingface model link" />

## Import private models

If you want to import private models from Hugging Face or Civitai, you need to configure your API keys first.

### 1. Generate your API keys

First, you need to generate API keys from the respective platforms:

<Tabs>
  <Tab title="Civitai">
    1. Log in to Civitai and visit [https://civitai.com/user/account](https://civitai.com/user/account).
    2. Generate your API key in the account settings.

       <img alt="Civitai API Key" />
  </Tab>

  <Tab title="Hugging Face">
    1. Visit [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens).

    2. Generate your API token.

       <img alt="Hugging Face API Key" />

    3. Make sure your token has read access to the repositories containing the private models you want to import.

       <img alt="Hugging Face Token Permissions" />
  </Tab>
</Tabs>

### 2. Save your API keys

1. Go to [Comfy Cloud Settings](https://cloud.comfy.org) and navigate to the **Secrets** section.

<img alt="Settings Secrets" />

2. Click to add your API keys (you can name the key anything you like):

<img alt="Add Secret Key" />

3. Make sure your API keys have access permissions to the private models you want to import.

### 3. Import the private model

Once your API keys are configured, you can import private models using the same process as public models:

1. Get the model link from Hugging Face or Civitai.
2. Paste the link in the import modal.
3. The system will automatically use your saved API keys to access the private model.

<Note>
  Make sure your API key has the necessary permissions to access the specific private model you want to import.
</Note>

## FAQ

<AccordionGroup>
  <Accordion title="Are there restrictions on what models I can upload?">
    Yes. Only **safetensor** file types are supported. There is effectively no file size limit (up to 100GB).
  </Accordion>

  <Accordion title="Are the models I upload private or shared with everyone?">
    Models you import are **private to you**. Only you can see the models in your library.
  </Accordion>

  <Accordion title="Can I upload my own custom models from my local hard drive?">
    Currently, you need to upload the model to a **public Hugging Face or Civitai repository** first, then import from those platforms.
  </Accordion>

  <Accordion title="Can I upload chunked model files?">
    No. You will need to combine chunked model files into one file before importing.
  </Accordion>

  <Accordion title="Is this feature included in my current cloud subscription?">
    This feature is available for **Creator** and **Pro** plans only.
  </Accordion>

  <Accordion title="Is this feature accessible on the Desktop or portable versions of Comfy?">
    No. This is a **Cloud-only** feature.
  </Accordion>

  <Accordion title="Can I delete a model that I uploaded?">
    Yes. You can delete models you imported. Note that models uploaded by the Comfy internal team cannot be deleted.
  </Accordion>

  <Accordion title="What model types can I import (BYOM)?">
    Not only the examples below. BYOM supports any model folder that Comfy Cloud lists in the **import type selector** during import. That list comes from Comfy Cloud's supported ComfyUI model folders and is the source of truth.

    In practice, if ComfyUI treats a file as a model weight (checkpoint, LoRA, VAE, ControlNet, embedding, upscaler, IP-Adapter, SAM, audio encoder, and similar), you can import it as long as the folder appears in that selector.

    Common examples:

    * **Checkpoints and UNets**: `checkpoints`, `diffusion_models`
    * **LoRAs and adapters**: `loras`, `animatediff_motion_lora`, `cogvideox_loras`, and similar adapter folders
    * **VAE**: `vae`, `vae_approx`
    * **ControlNet**: `controlnet`
    * **CLIP and text encoders**: `clip_vision`, `text_encoders`
    * **Embeddings / textual inversion**: `embeddings` (reference in `CLIPTextEncode` prompts with `embedding:my-embedding-name`)
    * **Upscalers**: `upscale_models`, `latent_upscale_models`
    * **Vision / segmentation / removal**: `ipadapter`, `gligen`, `sams`, `sam3`, `rmbg`, `ultralytics_bbox`, `ultralytics_segm`
    * **Other folders in the selector**: `audio_encoders`, `model_patches`, `style_models`, `photomaker`, `LLM`, `CogVideo`, and more

    What actually limits import is not the model category, but these rules:

    * **File format**: `.safetensors` only (even if ComfyUI locally supports `.ckpt`, `.pth`, or `.onnx` for that folder)
    * **Source**: Civitai or Hugging Face download links only (no direct local upload)
    * **Blocked folder**: `nlf` models cannot be imported
  </Accordion>
</AccordionGroup>


# Share workflows
Source: https://docs.comfy.org/cloud/share-workflow

Learn how to share your Comfy Cloud workflows with others via shareable links

<Note>
  This is a **Comfy Cloud** feature and is only available in the cloud version. To learn more about Comfy Cloud, see [Comfy Cloud](/get_started/cloud).
</Note>

## Overview

Comfy Cloud allows you to share your workflows with others by generating a shareable link. Recipients can view the workflow along with all its inputs, outputs, and any assets referenced in the workflow.

<Warning>
  **Shared links include your workflow assets.** Anyone with the link can see not only the workflow layout but also media used in it—such as uploaded images, masks, and other files tied to nodes. Do not share links for workflows that contain private or sensitive content.
</Warning>

## How to share a workflow

<Steps>
  <Step title="Build your workflow">
    Create and finalize the workflow you want to share in Comfy Cloud.
  </Step>

  <Step title="Click the share button">
    In the top-right corner of the workflow page, click the **Share** button.

    <img alt="Share button in the workflow toolbar" />
  </Step>

  <Step title="Save the workflow">
    If your workflow has not been saved yet, you will be prompted to enter a filename and save it before sharing.

    <img alt="Save workflow before sharing" />
  </Step>

  <Step title="Create a shareable link">
    After saving, click **Create a link** to generate a shareable link. The link includes the workflow, its inputs and outputs, and the assets used in the graph.

    <img alt="Create a shareable link" />
  </Step>

  <Step title="Copy and share the link">
    Once the link is generated, copy it and send it to anyone you want to share the workflow with.

    <img alt="Copy the share link" />
  </Step>
</Steps>

## Update a shared workflow

If you make changes to a workflow that has already been shared:

1. Save the updated workflow.
2. Click the **Share** button again.
3. Select **Update** to refresh the existing shared link with your latest changes.

<img alt="Update an existing share link" />

The original link will automatically reflect the updated workflow content. Recipients using the same link will see the latest version.


# Comfy Cloud workspaces: teams and members
Source: https://docs.comfy.org/cloud/workspace

Create and manage Comfy Cloud workspaces: create a team workspace, invite members, set roles and permissions, and share files, workflows, and credits.

<Note>
  This is a **Comfy Cloud** feature and is only available in the cloud version. To learn more about Comfy Cloud, see [Comfy Cloud](/get_started/cloud).
</Note>

## Overview

A workspace is the account boundary for your Comfy Cloud work. Workflows, uploaded files, outputs, and credits belong to the workspace rather than to a single user, so switching workspaces switches which files you see and which credits your runs spend.

Every user gets a **Personal** workspace. To work with other people, create a **Team** workspace and invite them.

If someone invited you to a team workspace, you do not need to create anything: open the invitation email, sign in with the address it was sent to, and switch to that workspace. See [Switch workspaces](#switch-workspaces).

## Personal and Team workspaces

| Type | What it is |
| - | - |
| **Personal** | Created automatically for every user, with a single seat. Only you can access it. It cannot be deleted, and you cannot leave it. |
| **Team** | A shared workspace that you create or are invited to. Members see the workspace's files and share its credits. |

Creating a team workspace is free. To invite people, the workspace needs seats: a workspace that is not on a Team plan has one seat, which belongs to its owner. Team plans include a seat for each member.

## What is separate per workspace

Each workspace keeps its own:

* **Files and outputs**: uploads, generated images, jobs, and history
* **Workflows**: the workflow library you see in that workspace
* **Plan and credits**: its own subscription and credit balance
* **People**: members, roles, and pending invitations
* **Access**: workspace API keys, and, on Enterprise workspaces, the partner models members can run

Switching workspaces switches all of these at once, and nothing is copied between workspaces automatically.

## Create a team workspace

<Steps>
  <Step title="Open the profile menu">
    Click your profile picture in the top right corner.
  </Step>

  <Step title="Open the workspace list">
    Click your workspace name in the menu. The list shows every workspace you belong to, with your role in it.

    <img alt="The workspace list, with Create a workspace at the bottom" />
  </Step>

  <Step title="Create the workspace">
    Click **Create a workspace** at the bottom of the list.
  </Step>

  <Step title="Name it">
    Enter a name and click **Create**. Names are 1 to 50 characters long, must start with a letter or number, and can contain letters, numbers, spaces and the characters `- _ ' . , ( ) & +`.

    <img alt="The Create a new workspace dialog" />
  </Step>
</Steps>

Comfy Cloud switches you to the new workspace and reloads the page.

<Note>
  You can own up to **10 workspaces** in total, including your Personal workspace. There is no limit on how many workspaces you can join as a member.
</Note>

To open your workspace list directly, add `?create_workspace=1` to the Comfy Cloud URL, for example `https://cloud.comfy.org/?create_workspace=1`. It opens the team workspaces dialog, which lists your workspaces and has a **New workspace** field and a **Create workspace** button.

## Invite members

Only workspace owners can invite members. Team plans include a seat for each member, and the **Members** tab shows how many seats are in use, for example `3 of 20 members`. Pending invitations count toward that limit.

<img alt="The Members section of workspace settings, with the Invite button" />

To invite members:

<Steps>
  <Step title="Open workspace settings">
    In the profile menu, click **Workspace settings**.
  </Step>

  <Step title="Open the Members section">
    Select **Members**.
  </Step>

  <Step title="Send the invites">
    Click **Invite**, type one or more email addresses separated by commas, then click **Invite** in the dialog.
  </Step>
</Steps>

<img alt="The Invite members dialog with two email addresses entered" />

<Note>
  If **Invite** does not open the dialog, the workspace has no free seat. A workspace that is not on a Team plan has one seat, and a full team shows a maximum-members tooltip. Open **Plan & Credits** and upgrade to a Team plan, or contact us about Enterprise if you need more members.
</Note>

Comfy Cloud emails each person a link to join. The invitation is tied to the address it was sent to, so the recipient has to sign in, or create an account, with that same address. If they are not signed in when they open the link, they are asked to sign in first, and the invitation is applied afterwards.

Invitations that have not been accepted yet appear in the **Pending** tab of the Members section, with their expiry date. Owners see this tab; members only see the list of people who have already joined. From there an owner can:

* **Copy invite link**: share the link directly instead of waiting for the email
* **Resend invite**: send the email again with a fresh link
* **Cancel invite**: revoke the invitation

Invitations expire 30 days after they are sent.

<img alt="Pending invitations with their invite and expiry dates" />

## Roles and permissions

| Role | Can do |
| - | - |
| **Owner** | Invite and remove members, change roles, rename or delete the workspace, and manage the workspace plan and credits. |
| **Member** | Run workflows in the workspace and view the member list. Cannot invite members, see pending invitations, change workspace settings, or manage billing. |

Owners can change a member's role from the Members section, which is how you promote a member to owner or demote an owner back to member. A workspace always keeps at least one owner, so the last remaining owner cannot be demoted or removed. Some messages in Comfy Cloud call the owner the workspace admin; they are the same role.

Members can open **Workspace settings** and see the workspace's plan and member list, but they cannot change anything there. When an owner removes a member, that person loses access to the workspace's files and workflows, the seat is freed, and any workspace API keys they created stop working. Members cannot remove themselves; they leave the workspace instead.

## Manage a workspace

Open **Workspace settings** from the profile menu. The **Workspace** group in the settings dialog has these sections:

* **Plan & Credits**: the workspace plan, credit balance, and top-ups. Only the owner can change these.
* **Members**: the member list, roles, and pending invitations. Pending invitations are visible to owners.
* **Partner Models**: shown to workspace owners. Restricting which provider models members can run is an Enterprise plan feature. Turn off **Allow all partner models** to choose which providers and models members can run; models added later stay disabled until you enable them. Changes can take up to 10 minutes to apply across the workspace.

The menu in the Members section lets owners:

* **Edit workspace details**: rename the workspace
* **Delete Workspace**: available once the workspace has no active subscription. See [Delete a team workspace](#delete-a-team-workspace).
* **Leave Workspace**: leave a team workspace. You cannot leave a workspace if you are its only owner.

<img alt="The workspace menu: Edit workspace details, Delete Workspace, Leave Workspace" />

Members see this menu too, but only the **Leave Workspace** item.

### Delete a team workspace

Only the owner of a team workspace can delete it, and the workspace must not have an active subscription. Deleting a workspace is permanent: unused credits and unsaved assets are lost, and the workspace cannot be recovered. Your Personal workspace cannot be deleted, and Enterprise workspaces are managed with our sales team.

<Steps>
  <Step title="Cancel the plan">
    In **Workspace settings** → **Plan & Credits**, open the three-dot menu and select **Cancel plan**. If the workspace has no subscription, skip this step.
  </Step>

  <Step title="Delete the workspace">
    In **Workspace settings** → **Members**, open the three-dot menu and select **Delete Workspace**, then confirm in the dialog.
  </Step>
</Steps>

## Switch workspaces

1. Open the profile menu.
2. Click your workspace name to open the workspace list.
3. Select the workspace you want to work in.

<img alt="The profile menu, where you click your workspace name to open the workspace list" />

Comfy Cloud reloads the page on the selected workspace, and remembers it the next time you sign in.

| URL parameter | Action |
| - | - |
| `?create_workspace=1` | Opens your workspace list, with a **New workspace** field and a **Create workspace** button |
| `?invite=TOKEN` | Accepts a workspace invitation |

## How workspaces are billed

Plans and credits belong to the workspace, not to individual accounts.

**Personal workspaces** use your own plan, and you are the only person who spends its credits.

**Team workspaces** use a credit subscription that the owner sets up:

* The owner chooses the workspace's monthly credit amount in **Choose a Plan** (**For Teams**) with the credit slider. The price follows the amount you choose, and a larger commitment lowers the effective rate. Each billing period refills the pool with that amount.
* Yearly commitments cost less than monthly, and the workspace receives the whole year of credits up front.
* Members are not billed individually, and adding or removing members does not change the price. The plan includes the workspace's seats. If you need more members than the plan includes, contact us about Enterprise.
* Every member runs against the same credit pool.
* Subscription credits are spent before top-up credits, and top-up credits stay valid for 12 months.
* Changing the workspace to a personal plan removes all other members immediately, so move any shared work before you switch.

See [Comfy Cloud pricing](https://www.comfy.org/cloud/pricing) for current rates and discounts, [Subscribe to Comfy Cloud](/support/subscription/subscribing) to set up a team plan, and [Change your Comfy Cloud plan](/support/subscription/changing-plan) for plan changes.

## FAQ

<AccordionGroup>
  <Accordion title="Can I be in more than one team workspace?">
    Yes. You can own up to 10 workspaces in total, including your Personal workspace, and you can be a member of as many workspaces as you are invited to.
  </Accordion>

  <Accordion title="Do I need my own subscription to join a team workspace?">
    No. Members are not billed individually: runs in the workspace use the workspace's credits, which the workspace owner manages.
  </Accordion>

  <Accordion title="The invitation email never arrived. What now?">
    Ask the workspace owner to use **Resend invite**, or to send you a **Copy invite link** from the **Pending** tab in the Members section. Invitations expire 30 days after they are sent, so an older invitation may need to be sent again.
  </Accordion>

  <Accordion title="Can I delete my Personal workspace?">
    No. Your Personal workspace is permanent and serves as your default workspace.
  </Accordion>

  <Accordion title="Can I invite someone to my Personal workspace?">
    No. Personal workspaces have a single seat and no member management.
  </Accordion>

  <Accordion title="What happens when I leave a team workspace?">
    The workspace disappears from your workspace list and you lose access to its files and workflows. Any workspace API keys you created for it stop working. Your Personal workspace and its contents are not affected.
  </Accordion>

  <Accordion title="What happens if the workspace runs out of credits?">
    Members cannot run workflows until the owner adds credits. The same applies when the workspace's subscription is inactive, or a payment fails: ask the workspace owner to fix the plan or payment method.
  </Accordion>

  <Accordion title="Why is Delete Workspace unavailable?">
    The workspace still has an active subscription. Cancel it first with **Cancel plan** in **Plan & Credits**, then delete the workspace. **Delete Workspace** becomes available as soon as the plan is cancelled, so you do not have to wait for the billing period to end. Personal workspaces cannot be deleted at all, and Enterprise workspaces are ended through our sales team.
  </Accordion>

  <Accordion title="Can a deleted workspace be recovered?">
    No. Deleting a workspace is permanent.
  </Accordion>
</AccordionGroup>


# Comfy Cloud - Official ComfyUI Cloud Platform Powered by RTX 6000 Pro
Source: https://docs.comfy.org/get_started/cloud

Run ComfyUI workflows online with Comfy Cloud, the official cloud platform powered by NVIDIA RTX 6000 Pro GPUs. No local installation required.

<Card title="Access Comfy Cloud" icon="cloud" href="https://comfy.org/cloud">
  Click here to access ComfyUI Cloud directly
</Card>

## What is Comfy Cloud?

ComfyUI Cloud is the cloud version of ComfyUI with the same features as the local version. Everything is pre-installed and ready to use.

### Key features

<CardGroup>
  <Card title="Zero setup" icon="bolt">
    No installation required. All models and custom nodes are pre-installed and ready to use
  </Card>

  <Card title="Powerful GPUs" icon="microchip">
    Run workflows fast on our powerful server GPUs without needing your own hardware
  </Card>

  <Card title="Always up-to-date" icon="arrows-rotate">
    Automatically stays current with the latest ComfyUI releases and features
  </Card>

  <Card title="Access anywhere" icon="globe">
    Use ComfyUI from any device with an internet connection - no local installation needed
  </Card>

  <Card title="Team collaboration" icon="users" href="/cloud/workspace">
    Create team workspaces to collaborate with your team members. Share subscription plans, credits, and workflows.
  </Card>
</CardGroup>

## Cloud vs local

ComfyUI offers both an official cloud version, [Comfy Cloud](https://comfy.org/cloud), and an open-source self-hosted version. If you have a powerful GPU, running ComfyUI locally is a great option. The cloud version, on the other hand, is an online service that's ready to use instantly—simply open the URL, no installation or setup required.

| Category | Comfy Cloud | Self-hosted (local ComfyUI) |
| - | - | - |
| **Cost** | Free tier and paid subscription plans | Free |
| **GPU** | Powerful Blackwell RTX 6000 Pros | Bring your own GPU |
| **Technical Knowledge** | No technical knowledge required. | While desktop and portable give you easy ways to get started, you'll need to troubleshoot custom node installations and local installation issues. |
| **Custom Nodes** | Use pre-installed custom nodes and never worry about compatibility issues. | Install any custom node you want, but you'll need to manage it yourself. |
| **Models** | Use pre-installed models. Import models from Civitai and Hugging Face. | Use any models you want, but you'll need to download them first. |
| **Notable Differences** | Easy to onboard your team with [Workspaces](/cloud/workspace) | Works offline, infinitely customizable |
| **Get started** | [Run ComfyUI Cloud](https://comfy.org/cloud) | [Install ComfyUI locally](/installation/system_requirements) |

## Pricing and subscription

<Card title="Check pricing" icon="tag" href="https://www.comfy.org/cloud/pricing">
  View pricing and subscription options for Comfy Cloud
</Card>

## Comfy Cloud firewall allowlist

Allow outbound HTTPS and WebSocket traffic on TCP 443 to:

* **App:** `cloud.comfy.org`, `api.comfy.org`, `cdn.comfy.org`
* **Uploads and outputs:** `comfy-hub-assets.comfy.org`, `storage.googleapis.com`
* **Sign-in:** `dreamboothy.firebaseapp.com`, `identitytoolkit.googleapis.com`, `securetoken.googleapis.com`, `apis.google.com`, `challenges.cloudflare.com`
* **Other features:** `registry.comfy.org`, `*.algolia.net`, `media.comfy.org`

## How to use ComfyUI Cloud

Using ComfyUI Cloud is essentially the same as using your local ComfyUI. If this is your first time using ComfyUI, here are some quick tips to get started:

<Steps>
  <Step title="Select a template">
    Click the template icon in the left sidebar to browse available workflows.

    <img alt="Open workflow template" />
  </Step>

  <Step title="Select the workflow you want to run">
    Click on the template you want to run.

    <img alt="Select workflow template" />
  </Step>

  <Step title="Update template inputs">
    1. In the loaded workflow, since we have pre-installed all models in the cloud version, all templates are ready to run immediately after loading.
    2. If you need to make updates, you only need to provide image inputs or text prompts. Check the `Load Image` node or `CLIP Text Encode` node.
       <img alt="Check inputs" />
  </Step>

  <Step title="Run your workflow">
    If everything is correct, click the "Run" icon or use the shortcut "Ctrl + Enter" to run the workflow.

    <img alt="Run workflow" />
  </Step>

  <Step title="View output">
    After clicking run, our service will start allocating a machine for your workflow. You can check the execution status of the corresponding workflow in the queue panel.

    <img alt="View queue" />
  </Step>

  <Step title="Save content locally">
    After the workflow execution is complete, you can save the generated content locally. Depending on the asset type, the save method is as follows:

    <Tabs>
      <Tab title="Save images">
        In the queue panel or on the save image node, right-click on the generated image and select "Save image" to save the image locally.

        <img alt="Save image assets" />
      </Tab>

      <Tab title="Save videos">
        In the queue panel or on the save video node:

        1. Click the three dots on the browser player component to open the menu
        2. Select "Download" to save the video locally.

           <img alt="Save video assets" />
      </Tab>

      <Tab title="Save audio">
        In the queue panel or on the save audio node:

        1. Click the three dots on the browser player component to open the menu
        2. Select "Download" to save the audio file locally.

           <img alt="Save audio assets" />
      </Tab>

      <Tab title="Save 3D assets">
        In the 3D browser node menu, select the "Export" option, choose the format you want to save, and the 3D file will be saved locally.

        <img alt="Save 3D assets" />
      </Tab>
    </Tabs>
  </Step>
</Steps>

## Feedback

If you have any thoughts, suggestions, or run into any issues, simply click the "Feedback" icon. This will directly send your feedback to us.

<img alt="Feedback" />

### How to Stop/Exit Comfy Cloud

Cloud sessions only bill you while the GPU is actively running. When you close the browser tab, the session stops automatically — you can close it anytime, just like a regular browser tab.

## Frequently Asked Questions

<Card title="View FAQs" icon="circle-question" href="https://comfy.org/cloud">
  View frequently asked questions and answers about Comfy Cloud, including pricing, features, limitations, and more
</Card>

## Next steps

<CardGroup>
  <Card title="Cloud API" icon="code" href="/development/cloud/overview">
    Programmatically run workflows via the Cloud API
  </Card>

  <Card title="Tutorials" icon="book" href="/tutorials/basic/text-to-image">
    Explore tutorials to learn ComfyUI workflows
  </Card>

  <Card title="Support" icon="life-ring" href="https://discord.com/invite/comfyorg">
    Join our Discord community for help
  </Card>
</CardGroup>


# Getting Started with AI Image Generation
Source: https://docs.comfy.org/get_started/first_generation

Generate your first AI image with ComfyUI. Learn to load example workflows, install models, and complete your first text-to-image generation.

<Note>
  This guide is intended for **local users** running ComfyUI on their own device. If you'd prefer not to install anything locally, try our official cloud service instead.
</Note>

<Card title="Try Comfy Cloud" icon="cloud" href="http://cloud.comfy.org/?template=image_z_image_turbo&utm_source=docs">
  Run ComfyUI online with zero setup. Sign in with Google to get **400 free credits every month**.
</Card>

This guide aims to help you understand ComfyUI's basic operations and complete your first image generation. We'll cover:

1. Loading example workflows
   * Loading from ComfyUI's workflow templates
   * Loading from images with workflow metadata
2. Model installation guidance
   * Automatic model installation
   * Manual model installation
3. Completing your first text-to-image generation

## About Text-to-Image

Text-to-Image is a fundamental AI drawing feature that generates images from text descriptions. It's one of the most commonly used functions in AI art generation. You can think of the process as telling your requirements (positive and negative prompts) to an artist (the drawing model), who will then create what you want. Detailed explanations about text-to-image will be covered in the [Text to Image](/tutorials/basic/text-to-image) chapter.

## ComfyUI Text-to-Image Workflow Tutorial

### 1. Launch ComfyUI

Make sure you've followed the [installation guide](/installation/system_requirements) to start ComfyUI and can successfully enter the ComfyUI interface. Alternatively, you can use [Comfy Cloud](/get_started/cloud) to use ComfyUI without any installation.

<img alt="ComfyUI Interface" />

If you have not installed ComfyUI, please choose a suitable version to install based on your device.

<AccordionGroup>
  <Accordion title="Comfy Desktop">
    Comfy Desktop supports standalone installation on **Windows**, **macOS (Apple Silicon)**, and **Linux** (AppImage and `.deb`).

    * Source is on [GitHub](https://github.com/Comfy-Org/Comfy-Desktop)

    <Tip>
      Desktop installs track the **stable** ComfyUI release by default. If you want every latest commit, use the portable version or a manual git install, or switch the instance update channel to **Latest on GitHub**.
    </Tip>

    You can choose the appropriate installation for your system and hardware below

    <Tabs>
      <Tab title="Windows">
        <Card title="Comfy Desktop (Windows) Installation Guide" icon="link" href="/installation/desktop/windows">
          Suitable for **Windows** 10 or later. NVIDIA or AMD GPU recommended.
        </Card>
      </Tab>

      <Tab title="macOS (Apple Silicon)">
        <Card title="Comfy Desktop (macOS) Installation Guide" icon="link" href="/installation/desktop/macos">
          Suitable for macOS with **Apple Silicon**
        </Card>
      </Tab>

      <Tab title="Linux">
        <Card title="Comfy Desktop (Linux) Installation Guide" icon="link" href="/installation/desktop/linux">
          Install the AppImage or `.deb`, or build and run from source.
        </Card>
      </Tab>
    </Tabs>
  </Accordion>

  <Accordion title="ComfyUI Portable (Windows)">
    Portable version is a ComfyUI version that integrates an independent embedded Python environment, using the portable version you can experience the latest features, currently only supports **Windows** system

    <Card title="ComfyUI Portable (Windows) Installation Guide" icon="link" href="/installation/comfyui_portable_windows">
      Supports **Windows** ComfyUI version running on **Nvidia GPUs** or **CPU-only**, always use the latest commits and completely portable.
    </Card>
  </Accordion>

  <Accordion title="Manual Installation">
    <Card title="ComfyUI Manual Installation Guide" icon="link" href="/installation/manual_install">
      Supports all system types and GPU types (Nvidia, AMD, Intel, Apple Silicon, Ascend NPU, Cambricon MLU)
    </Card>
  </Accordion>
</AccordionGroup>

### 2. Load Default Text-to-Image Workflow

ComfyUI usually loads the default text-to-image workflow automatically when launched. However, you can try different methods to load workflows to familiarize yourself with ComfyUI's basic operations:

<Tabs>
  <Tab title="Load from Images with Metadata">
    All images generated by ComfyUI contain metadata including workflow information. You can load workflows by:

    * Dragging and dropping a ComfyUI-generated image into the interface
    * Using menu **Workflows** -> **Open** to open an image

    Try loading the workflow using this example image:
    ![ComfyUI-Text to Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/text-to-image-workflow.png)
  </Tab>

  <Tab title="Load from workflow.json">
    ComfyUI workflows can be stored in JSON format. You can export workflows using menu **Workflows** -> **Export**.

    Try downloading and loading this example workflow:

    <a href="https://github.com/Comfy-Org/docs/blob/main/public/text-to-image.json">
      <p>Download text-to-image.json</p>
    </a>

    After downloading, use menu **Workflows** -> **Open** to load the JSON file.
  </Tab>
</Tabs>

### 3. Model Installation

Most ComfyUI installations don't include base models by default. After loading the workflow, if you don't have the [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors) model installed, you'll see this prompt:

First, ComfyUI will warn you that some models are missing:

<img alt="Missing models warning" />

Click the warning to see which model is missing and the download link:

<img alt="Missing model details" />

By default, models are stored in `<your ComfyUI installation>/ComfyUI/models/` with subfolders like `checkpoints`, `embeddings`, `vae`, `lora`, `upscale_model`, etc. ComfyUI detects models in these folders and paths configured in `extra_model_paths.yaml` at startup.

<Tabs>
  <Tab title="Comfy Desktop (Find models folder)">
    Click the capsule menu at the top of the desktop app, then open the **Storage** tab to check your model directories. The capsule only exists in the desktop app, not when ComfyUI runs in a browser. Click the folder icon next to a directory to open it in your file manager.

    <img alt="Comfy Desktop capsule menu: Storage tab showing model directory settings" />
  </Tab>

  <Tab title="ComfyUI Portable (Find models folder)">
    For the portable version, the models folder is usually located at:

    `ComfyUI_windows_portable/ComfyUI/models/`
  </Tab>
</Tabs>

You can install models through:

<Tabs>
  <Tab title="Automatic Download">
    After you click the **Download** button, ComfyUI will execute the download, and different behaviors will be performed depending on the version you are using.

    <Tabs>
      <Tab title="Comfy Desktop">
        The desktop version will automatically complete the model download and save it to the `<your ComfyUI installation location>/ComfyUI/models/checkpoints` directory.
        You can wait for the installation to complete or view the installation progress in the model panel on the sidebar.

        <img alt="Model Download Progress" />

        <Warning>
          Automatic downloads typically fetch models from **Hugging Face**. Make sure your network can reliably reach Hugging Face.

          If the download **does not start** or shows **no progress for a long time**, copy the model link from the missing-model details (or use the manual installation section below) and install the model manually.
        </Warning>
      </Tab>

      <Tab title="ComfyUI Portable">
        The browser will execute file downloads. Please save the file to the `<your ComfyUI installation location>/ComfyUI_windows_portable/ComfyUI/models/checkpoints` directory after the download is complete.
      </Tab>
    </Tabs>
  </Tab>

  <Tab title="Manual Installation">
    Visit [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors) and follow this guide:

    <img alt="Hugging Face Model Download" />

    Save the downloaded file to:

    <Tabs>
      <Tab title="Comfy Desktop">
        Save to `<your ComfyUI installation>/ComfyUI/models/checkpoints`

        <img alt="Comfy Desktop Model Save Location" />
      </Tab>

      <Tab title="ComfyUI Portable">
        Save to `ComfyUI_windows_portable/ComfyUI/models/checkpoints`

        <img alt="ComfyUI Portable Model Save Location" />
      </Tab>
    </Tabs>

    Refresh or restart ComfyUI after saving.
  </Tab>
</Tabs>

### 4. Load Model and Generate Your First Image

After you install or update models, press **`R`** on your keyboard to refresh object definitions and update model lists in nodes (for example, the dropdown in **Load Checkpoint**). Then continue with the steps below:

<img alt="Run workflow" />

1. In the **Load Checkpoint** node, ensure **v1-5-pruned-emaonly-fp16.safetensors** is selected
2. Click `Run` or press `Ctrl + Enter` to generate

The result will appear in the **Save Image** node. Right-click to save locally.

<img alt="ComfyUI First Image Generation Result" />

For detailed text-to-image instructions, see our comprehensive guide:

<Card title="ComfyUI Text-to-Image Workflow Guide" icon="link" href="/tutorials/basic/text-to-image">
  Click here for detailed text-to-image workflow instructions
</Card>

## Troubleshooting

### Model Loading Issues

If the `Load Checkpoint` node shows no models or displays "null", verify your model installation location and try refreshing or restarting ComfyUI.


# ComfyUI Official Documentation
Source: https://docs.comfy.org/index

Official documentation for ComfyUI, the open source node-based generative AI application. Learn to build workflows for image, video, audio, and 3D generation.

<div>
  <div>
    <div>
      <img />

      <img />
    </div>

    <div>
      # ComfyUI Official Documentation
    </div>
  </div>

  <div>
    <div>
      <a href="https://github.com/Comfy-Org/ComfyUI/">
        <Icon icon="github" />
      </a>

      <a href="https://x.com/ComfyUI">
        <Icon icon="x-twitter" />
      </a>

      <a href="https://discord.com/invite/comfyorg">
        <Icon icon="discord" />
      </a>

      <a href="https://www.youtube.com/@comfyorg">
        <Icon icon="youtube" />
      </a>
    </div>
  </div>

  <div>
    <p>
      The most powerful open source node-based application for generative AI
    </p>

    <div>
      <h2>Getting Started</h2>

      <CardGroup>
        <Card title="Download & Install" icon="download" href="/installation/system_requirements">
          Install ComfyUI on Windows, macOS, or Linux
        </Card>

        <Card title="First Generation" icon="rocket" href="/get_started/first_generation">
          Create your first AI-generated image
        </Card>

        <Card title="Basic Concepts" icon="lightbulb" href="/basic-concepts/workflow">
          Understand workflows, nodes, and links
        </Card>

        <Card title="Comfy Workflows" icon="globe" href="https://comfy.org/workflows">
          Explore community workflows and templates from top creators
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>AI Agents & MCP</h2>

      <CardGroup>
        <Card title="Agent Tools Overview" icon="robot" href="/agent-tools">
          Connect AI agents via MCP for image, video, audio, and 3D generation
        </Card>

        <Card title="Cloud MCP Server" icon="server" href="/agent-tools/mcp">
          Hosted MCP at cloud.comfy.org — run workflows on Cloud GPUs
        </Card>

        <Card title="Comfy CLI" icon="terminal" href="/agent-tools/cli">
          Call partner models from the terminal with comfy generate (beta)
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>Comfy Router</h2>

      <CardGroup>
        <Card title="Quickstart" icon="route" href="/development/comfy-router/quickstart">
          Call partner models through one API endpoint with a single key
        </Card>

        <Card title="Run Workflows" icon="play" href="/development/run-workflows/overview">
          Run workflows against a ComfyUI deployment from your application
        </Card>

        <Card title="API Reference" icon="book" href="/development/comfy-router/reference">
          Full reference for Router endpoints, headers, and limits
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>Learn & Tutorials</h2>

      <CardGroup>
        <Card title="Interface Guide" icon="window-maximize" href="/interface/overview">
          Navigate the ComfyUI interface
        </Card>

        <Card title="Tutorials" icon="book-open" href="/tutorials/basic/text-to-image">
          Step-by-step guides for common tasks
        </Card>

        <Card title="Built-in Nodes" icon="diagram-project" href="/built-in-nodes/overview">
          Learn about each node in ComfyUI
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>Developers</h2>

      <CardGroup>
        <Card title="Deploy ComfyUI" icon="server" href="/development/overview">
          Run ComfyUI locally, on a server, or in the cloud
        </Card>

        <Card title="Run Workflows" icon="play" href="/development/run-workflows/overview">
          Run workflows against a deployment from your application
        </Card>

        <Card title="Contribute" icon="code-pull-request" href="/community/contributing#how-to-contribute">
          Contribute to ComfyUI development
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>Build Custom Nodes</h2>

      <CardGroup>
        <Card title="Getting Started" icon="puzzle-piece" href="/custom-nodes/walkthrough">
          Create your first custom node step by step
        </Card>

        <Card title="Publish my Custom Node" icon="upload" href="/registry/publishing">
          Share your custom node on the Comfy Registry
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>Get Help</h2>

      <CardGroup>
        <Card title="Contact Support" icon="headset" href="/support/contact-support">
          Get help from our support team
        </Card>

        <Card title="Account Management" icon="user-gear" href="/account/create-account">
          Create, login, and manage your account
        </Card>

        <Card title="Billing Support" icon="credit-card" href="/support/subscription/subscribing">
          Manage subscriptions and payments
        </Card>

        <Card title="Troubleshooting" icon="circle-question" href="/troubleshooting/overview">
          Resolve common issues and errors
        </Card>

        <Card title="Community" icon="users" href="/community/links">
          Join the ComfyUI community
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>About ComfyUI</h2>

      <p>
        Written by <a href="https://github.com/comfyanonymous">comfyanonymous</a> and other <a href="https://github.com/Comfy-Org/ComfyUI/graphs/contributors">contributors</a>.
      </p>

      <ul>
        <li><strong>ComfyUI</strong> is a node-based interface and inference engine for generative AI</li>
        <li>Users can combine various AI models and operations through nodes to achieve highly customizable and controllable content generation</li>
        <li>ComfyUI is completely open source and can run on your local device</li>
      </ul>
    </div>
  </div>
</div>


# ComfyUI Portable for Windows
Source: https://docs.comfy.org/installation/comfyui_portable_windows

Download and run ComfyUI Portable on Windows: a standalone package with embedded Python and CUDA builds for NVIDIA GPUs. Extract the archive, then run ComfyUI.

**ComfyUI Portable** is a standalone packaged complete ComfyUI Windows version that has integrated an independent **Python (python\_embeded)** required for ComfyUI to run. You only need to extract it to use it.

This guide section will walk you through installing ComfyUI Portable.

## Download ComfyUI Portable

<Note>Choose the download package that matches your GPU type. ComfyUI Portable provides separate packages for different GPU hardware.</Note>

<Tabs>
  <Tab title="Nvidia GPU">
    ### Standard portable for Nvidia GPUs

    <CardGroup>
      <Card title="Nvidia GPU (CUDA 13.0, Python 3.13)" icon="download" href="https://github.com/Comfy-Org/ComfyUI/releases/latest/download/ComfyUI_windows_portable_nvidia.7z">
        For modern Nvidia GPUs (RTX series)
      </Card>

      <Card title="Nvidia GPU (CUDA 12.6, Python 3.12)" icon="download" href="https://github.com/Comfy-Org/ComfyUI/releases/latest/download/ComfyUI_windows_portable_nvidia_cu126.7z">
        For Nvidia 10 series and older GPUs
      </Card>
    </CardGroup>

    Download the file and extract it with [7-ZIP](https://7-zip.org/). The extracted folder structure:

    ```
    ComfyUI_windows_portable
    ├── 📂ComfyUI                   // ComfyUI main program
    ├── 📂python_embeded            // Independent Python environment
    ├── 📂update                    // Batch scripts for upgrading portable version
    ├── README_VERY_IMPORTANT.txt   // ComfyUI Portable usage instructions in English
    ├── run_cpu.bat                 // Double click to start ComfyUI (CPU only)
    └── run_nvidia_gpu.bat          // Double click to start ComfyUI (Nvidia GPU)
    ```

    Double click `run_nvidia_gpu.bat` to launch ComfyUI.
  </Tab>

  <Tab title="AMD GPU">
    ### Portable for AMD GPUs

    <Card title="AMD GPU" icon="download" href="https://github.com/Comfy-Org/ComfyUI/releases/latest/download/ComfyUI_windows_portable_amd.7z">
      Download for AMD GPUs (ROCm)
    </Card>

    Download the file and extract it with [7-ZIP](https://7-zip.org/). The extracted folder structure:

    ```
    ComfyUI_windows_portable_amd
    ├── 📂ComfyUI                   // ComfyUI main program
    ├── 📂python_embeded            // Independent Python environment
    ├── 📂update                    // Batch scripts for upgrading portable version
    ├── README_VERY_IMPORTANT.txt   // ComfyUI Portable usage instructions in English
    ├── run_cpu.bat                 // Double click to start ComfyUI (CPU only)
    └── run_amd_gpu.bat             // Double click to start ComfyUI (AMD GPU)
    ```

    Double click `run_amd_gpu.bat` to launch ComfyUI.
  </Tab>

  <Tab title="Intel GPU">
    ### Portable for Intel GPUs

    <Card title="Intel GPU" icon="download" href="https://github.com/Comfy-Org/ComfyUI/releases/latest/download/ComfyUI_windows_portable_intel.7z">
      Download for Intel GPUs
    </Card>

    Download the file and extract it with [7-ZIP](https://7-zip.org/). The extracted folder structure:

    ```
    ComfyUI_windows_portable_intel
    ├── 📂ComfyUI                   // ComfyUI main program
    ├── 📂python_embeded            // Independent Python environment
    ├── 📂update                    // Batch scripts for upgrading portable version
    ├── README_VERY_IMPORTANT.txt   // ComfyUI Portable usage instructions in English
    ├── run_cpu.bat                 // Double click to start ComfyUI (CPU only)
    └── run_intel_gpu.bat           // Double click to start ComfyUI (Intel GPU)
    ```

    Double click `run_intel_gpu.bat` to launch ComfyUI.
  </Tab>
</Tabs>

After downloading and extracting, you will see the command running as shown in the image below

<img alt="ComfyUI Portable Command Prompt" />

When you see something similar to the image

```
To see the GUI go to: http://127.0.0.1:8188
```

At this point, your ComfyUI service has started. Normally, ComfyUI will automatically open your default browser and navigate to `http://127.0.0.1:8188`. If it doesn't open automatically, please manually open your browser and visit this address.

<Warning>During use, please do not close the corresponding command line window, otherwise ComfyUI will stop running</Warning>

## Adding Extra Model Paths

If you want to manage your model files outside of `ComfyUI/models`, you may have the following reasons:

* You have multiple ComfyUI instances and want them to share model files to save disk space
* You have different types of GUI programs (such as WebUI) and want them to use the same model files
* Model files cannot be recognized or found

We provide a way to add extra model search paths via the `extra_model_paths.yaml` configuration file

### Open Config File

<Tabs>
  <Tab title="Portable/Manual Install">
    For the ComfyUI version such as [portable](/installation/comfyui_portable_windows) and [manual](/installation/manual_install), you can find an example file named `extra_model_paths.yaml.example` in the root directory of ComfyUI:

    ```
    ComfyUI/extra_model_paths.yaml.example
    ```

    Copy and rename it to `extra_model_paths.yaml` for use. Keep it in ComfyUI's root directory at `ComfyUI/extra_model_paths.yaml`.
    You can also find the config example file [here](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example)
  </Tab>

  <Tab title="Comfy Desktop">
    If you are using the [Comfy Desktop](/installation/desktop/windows) application, click the capsule menu at the top of the desktop app, then open the **Storage** tab and add your model directories there. The capsule only exists in the desktop app, not when ComfyUI runs in a browser.

    <img alt="Comfy Desktop capsule menu: Storage tab showing model directory settings" />

    Or open it directly at:

    <Tabs>
      <Tab title="Windows">
        ```
        C:\Users\YourUsername\AppData\Roaming\ComfyUI\extra_models_config.yaml
        ```
      </Tab>

      <Tab title="macOS">
        ```
        ~/Library/Application Support/ComfyUI/extra_models_config.yaml
        ```
      </Tab>
    </Tabs>

    You should keep the file in the same directory, should not move these files to other places.
  </Tab>
</Tabs>

If the file does not exist, you can create it yourself with any text editor.

### Example Structure

Suppose you want to add the following model paths to ComfyUI:

```
📁 YOUR_PATH/
  ├── 📁models/
  |   ├── 📁 loras/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 checkpoints/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 vae/
  |   │   └── xxxxx.safetensors
  |   └── 📁 controlnet/
  |       └── xxxxx.safetensors
```

Then you can configure the `extra_model_paths.yaml` file like below to let ComfyUI recognize the model paths on your device:

```
my_custom_config:
    base_path: YOUR_PATH
    loras: models/loras/
    checkpoints: models/checkpoints/
    vae: models/vae/
    controlnet: models/controlnet/
```

or

```
my_custom_config:
    base_path: YOUR_PATH/models/
    loras: loras
    checkpoints: checkpoints
    vae: vae
    controlnet: controlnet
```

<Warning>
  For the desktop version, please add the configuration to the existing configuration path without overwriting the path configuration generated during installation. Please back up the corresponding file before modification, so that you can restore it when you make a mistake.
</Warning>

Or you can refer to the default [extra\_model\_paths.yaml.example](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example) for more configuration options. After saving, you need to **restart ComfyUI** for the changes to take effect.

Below is the original config example:

```yaml theme={null}
#Rename this to extra_model_paths.yaml and ComfyUI will load it


#config for a1111 ui
#all you have to do is change the base_path to where yours is installed
a111:
    base_path: path/to/stable-diffusion-webui/

    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet

#config for comfyui
#your base path should be either an existing comfy install or a central folder where you store all of your models, loras, etc.

#comfyui:
#     base_path: path/to/comfyui/
#     # You can use is_default to mark that these folders should be listed first, and used as the default dirs for eg downloads
#     #is_default: true
#     checkpoints: models/checkpoints/
#     clip: models/clip/
#     clip_vision: models/clip_vision/
#     configs: models/configs/
#     controlnet: models/controlnet/
#     diffusion_models: |
#                  models/diffusion_models
#                  models/unet
#     embeddings: models/embeddings/
#     loras: models/loras/
#     upscale_models: models/upscale_models/
#     vae: models/vae/

#other_ui:
#    base_path: path/to/ui
#    checkpoints: models/checkpoints
#    gligen: models/gligen
#    custom_nodes: path/custom_nodes

```

For example, if your WebUI is located at `D:\stable-diffusion-webui\`, you can modify the corresponding configuration to

```yaml theme={null}
a111:
    base_path: D:\stable-diffusion-webui\
    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet
```

### Add Extra Custom Nodes Path

Besides adding external models, you can also add custom nodes paths that are not in the default path of ComfyUI

<Tip>
  Please note that this will not change the default installation path of custom nodes, but will add an extra path search when starting ComfyUI. You still need to complete the installation of custom node dependencies in the corresponding environment to ensure the integrity of the running environment.
</Tip>

Below is a simple configuration example (MacOS), please modify it according to your actual situation and add it to the corresponding configuration file, save it and restart ComfyUI for the changes to take effect:

```yaml theme={null}
my_custom_nodes:
  custom_nodes: /Users/your_username/Documents/extra_custom_nodes
```

## First Image Generation

After successful installation, you can refer to the section below to start your ComfyUI journey\~

<Card title="First Image Generation" icon="link" href="/get_started/first_generation">
  This tutorial will guide you through your first model installation and text-to-image generation
</Card>

## Additional ComfyUI Portable Instructions

### 1. Upgrading ComfyUI Portable

You can use the batch commands in the update folder to upgrade your ComfyUI Portable version

```
ComfyUI_windows_portable
└─ 📂update
   ├── update.py
   ├── update_comfyui.bat                          // Update ComfyUI to the latest commit version
   ├── update_comfyui_and_python_dependencies.bat  // Only use when you have issues with your runtime environment
   └── update_comfyui_stable.bat                   // Update ComfyUI to the latest stable version
```

### 2. Setting Up LAN Access for ComfyUI Portable

If your ComfyUI is running on a local network and you want other devices to access ComfyUI, you can modify the corresponding `.bat` file (e.g. `run_nvidia_gpu.bat`, `run_amd_gpu.bat`, or `run_cpu.bat`) using Notepad to complete the configuration. This is mainly done by adding `--listen` to specify the listening address.
Below is an example of the `run_nvidia_gpu.bat` file command with the `--listen` parameter added

```bat theme={null}
.\python_embeded\python.exe -s ComfyUI\main.py --listen --windows-standalone-build
pause
```

After enabling ComfyUI, you will notice the final running address will become

```
Starting server

To see the GUI go to: http://0.0.0.0:8188
To see the GUI go to: http://[::]:8188
```

You can press `WIN + R` and type `cmd` to open the command prompt, then enter `ipconfig` to view your local IP address. Other devices can then access ComfyUI by entering `http://your-local-IP:8188` in their browser.

### 3. Installing Additional Python Packages

The portable version ships with an embedded Python environment (`python_embeded`). To install additional Python packages (such as attention optimizations, custom node dependencies, or other tools), use the embedded Python's pip from the command line:

```bash theme={null}
# Navigate to your ComfyUI portable folder first
cd ComfyUI_windows_portable

# Install a package using the embedded Python
.\python_embeded\python.exe -m pip install <package-name>
```

After installing a package that requires a startup flag, add the corresponding flag to your `.bat` file (e.g. `run_nvidia_gpu.bat`):

```bat theme={null}
.\python_embeded\python.exe -s ComfyUI\main.py --<startup-flag> --windows-standalone-build
```

For detailed guidance on installing custom node dependencies, see the [custom nodes dependency guide](/basic-concepts/custom-nodes).


# Comfy Desktop FAQ
Source: https://docs.comfy.org/installation/desktop/faq

Common questions and troubleshooting tips for Comfy Desktop

## General Questions

<Accordion title="What is the difference between Comfy Desktop and Legacy Desktop?">
  Comfy Desktop is a complete rewrite that acts as a **multi-installation manager**. Unlike Legacy Desktop which was a single-install application, Comfy Desktop lets you install, manage, and run multiple ComfyUI versions side by side. It also adds snapshots and model download management.

  For users of Legacy Desktop, check the [Migration Guide](/installation/desktop/usage/migrate) to transfer your existing setup.
</Accordion>

<Accordion title="Is Comfy Desktop open source?">
  Yes. The source is on [GitHub](https://github.com/Comfy-Org/Comfy-Desktop). Comfy Desktop is dual-licensed: [AGPL-3.0-or-later](https://github.com/Comfy-Org/Comfy-Desktop/blob/main/LICENSE), or a commercial license from Comfy Org (`licensing@comfy.org`).
</Accordion>

<Accordion title="Does Comfy Desktop replace the Portable/Manual install?">
  Comfy Desktop is one of several installation options. You can still use the **Portable (Windows)** install, **Manual Install**, or **Comfy Cloud** depending on your needs. Desktop is recommended for most users due to its ease of use and features like one-click updates and snapshot management.
</Accordion>

## Installation & Setup

<Accordion title="What are the system requirements?">
  See [system requirements](/installation/system_requirements) for full details.

  * **Windows:** Windows 10+, x64 or ARM64. A dedicated GPU (NVIDIA / AMD) is recommended, but not required.
  * **macOS:** macOS 13+ (Ventura), Apple Silicon (M1+)
  * **Linux:** Official `.deb` and AppImage packages are distributed through the [Comfy Desktop repository](https://github.com/Comfy-Org/Comfy-Desktop). A dedicated GPU is recommended.
  * **Disk:** At least 4.85 GB per standalone installation
  * **RAM:** 8 GB minimum, 16 GB recommended
</Accordion>

<Accordion title="Can I install Comfy Desktop without admin rights?">
  On **Windows**, the standalone installation does not require admin rights. On **macOS**, you'll need admin rights for the initial system-wide installation. On **Linux**, installing the `.deb` package requires `sudo`; the AppImage runs in user space without admin rights.
</Accordion>

<Accordion title="How do I download Comfy Desktop?">
  Download the latest Windows or macOS build from the official [ComfyUI Download page](https://comfy.org/download). On Linux, download the `.deb` or AppImage with the [universal download link](https://dl.todesktop.com/241130tqe9q3y) from the [Comfy Desktop repository](https://github.com/Comfy-Org/Comfy-Desktop). To run from source instead, see the [Linux install guide](/installation/desktop/linux).
</Accordion>

<Accordion title="Can I have both Legacy Desktop and Comfy Desktop installed?">
  Yes, they can coexist. However, we recommend migrating your installations to the new Comfy Desktop and eventually uninstalling Legacy Desktop. See the [Migration Guide](/installation/desktop/usage/migrate).
</Accordion>

## Usage

<Accordion title="How do I add a new ComfyUI installation?">
  On the Dashboard, click **New Instance** to create a standalone instance, or open **New Instance** and choose **Add Existing Instance** to track a git clone or Windows portable install. Use the **Comfy Cloud** card to connect to Cloud.

  * **Standalone**: Fresh install with bundled Python
  * **Add Existing Instance**: Track a git clone or portable install
  * **Cloud**: Connect to Comfy Cloud
</Accordion>

<Accordion title="Can I run multiple ComfyUI versions at the same time?">
  Yes! Comfy Desktop is designed for this. Each installation runs in its own isolated environment with its own Python and dependencies. You can launch them simultaneously in separate windows.
</Accordion>

<Accordion title="Where are my models, custom nodes, and settings stored?">
  Models are shared across instances by default. Configure shared folders in [Desktop Settings → Storage](/installation/desktop/usage/settings#storage).

  * **Standalone:** The install itself lives in its installation folder. Custom nodes and the Python environment are per-install. Models usually come from the shared model directories.
  * **Git clone / portable (tracked):** Data stays in that existing folder (`models/`, `custom_nodes/`, `user/`). You can still opt into shared models, input, and output.
</Accordion>

<Accordion title="How do snapshots work?">
  Comfy Desktop automatically creates a snapshot before every update. Snapshots capture:

  * Custom nodes and their versions
  * Model files
  * Settings and configuration

  You can browse and restore any snapshot from the app's **Snapshots** section.
</Accordion>

### How to Stop/Exit Comfy Desktop

To stop a running ComfyUI instance (stop the Python backend while keeping the app open):

1. Click the **⋮ (kebab) menu** on the instance card
2. Select **Stop**
3. Confirm in the dialog

This stops the ComfyUI Python process but leaves the desktop app window open so you can relaunch anytime. To fully quit the desktop app, use **File → Quit** (or the equivalent OS quit command). Closing the last window returns to the Dashboard unless you quit the app.

## Troubleshooting

<Accordion title="The app won't start after installation">
  1. **Windows:** Try running as administrator once
  2. **macOS:** If you see a security warning, go to **System Settings → Privacy & Security** and click **Open Anyway**
  3. **Linux:** Make sure FUSE 2 is installed (`sudo apt install libfuse2`)
  4. Check the [Downloads page](https://comfy.org/download) for the latest version
</Accordion>

<Accordion title="My GPU is not detected">
  * Ensure your NVIDIA drivers are up to date
  * On Linux, verify CUDA toolkit is installed
  * Check that the installation type supports GPU (Standalone and Git Clone do; Cloud connections use remote GPU)
</Accordion>

<Accordion title="An installation fails to update">
  * Check your internet connection
  * Try taking a manual snapshot first via the app menu
  * If the issue persists, restore to a previous snapshot and try again
</Accordion>

<Accordion title="How do I check Comfy Desktop startup logs?">
  The Desktop app writes a rotating `app.log` file. The fastest way to find it is **Desktop Settings → Logs → Diagnostics → Open logs folder** (☰ menu in the top-left).

  Default log folders:

  * **Windows:** `%APPDATA%\Comfy Desktop\logs`
  * **macOS:** `~/Library/Logs/Comfy Desktop`
  * **Linux:** `~/.config/Comfy Desktop/logs`

  Look for `app.log`. Previous sessions rotate to timestamped `app.log_*.log` files.

  For ComfyUI process output (not the Desktop app itself), open the instance **Manage** panel and use the **Terminal** tab. See [Manage](/installation/desktop/usage/manage).
</Accordion>

<Accordion title="How do I uninstall Comfy Desktop?">
  Comfy Desktop and its installations are separate on disk. To uninstall the app and its installations:

  1. **Delete the installations** from within the app (right-click → Remove) or delete the installation folders manually
  2. **Uninstall the app** using your system's standard method (Add/Remove Programs on Windows, drag to Trash on macOS, package manager on Linux)

  That does not delete app settings, logs, shared models, or outputs. For leftover folders and a complete cleanup, see [Windows](/installation/desktop/windows#what-uninstalling-the-app-does-not-remove), [macOS](/installation/desktop/macos#what-uninstalling-the-app-does-not-remove), or [Linux](/installation/desktop/linux#removing-leftover-data).
</Accordion>

<Accordion title="Can I run Comfy Desktop in headless or server mode?">
  No. Comfy Desktop is designed as a local GUI application and does not support headless, server-only, or remote operation modes. It requires a graphical desktop environment to launch and manage ComfyUI instances.

  For headless or server deployments, use a **manual ComfyUI installation** or the **Windows Portable** build instead.
</Accordion>


# Comfy Desktop on Linux
Source: https://docs.comfy.org/installation/desktop/linux

Install Comfy Desktop on Linux using the official .deb or AppImage packages. Source builds need Ubuntu 22.04+, x64, and Node.js v22 LTS.

**Comfy Desktop** can run on Linux. Official `.deb` (Debian/Ubuntu) and AppImage packages are distributed through the [Comfy Desktop repository](https://github.com/Comfy-Org/Comfy-Desktop). Download them with the [universal download link](https://dl.todesktop.com/241130tqe9q3y), which auto-detects your platform. Most users should use one of those packages. If you want to run the app from source instead, clone the repository and follow the steps below.

## System Requirements

* **OS:** Linux (Ubuntu 22.04 or later recommended)
* **Architecture:** x64
* **Node.js:** v22 LTS or later (source build only)
* **pnpm:** v10 or later, enabled with Corepack (source build only)
* **Build tools:** `build-essential` and `git` (source build only)
* **GPU:** A dedicated GPU (NVIDIA / AMD) is recommended, but not required
* **Disk Space:** At least 4.85 GB recommended per ComfyUI installation

## Install the official package

Download the Linux package with the [universal download link](https://dl.todesktop.com/241130tqe9q3y) (it auto-detects your platform), then install it:

```bash theme={null}
sudo apt install ./*.deb
```

For the AppImage:

```bash theme={null}
chmod +x ./*.AppImage
./*.AppImage
```

If the app fails to launch, your distribution may be blocking Electron's sandbox (Ubuntu 24.04+ restricts unprivileged user namespaces through AppArmor). In that case retry with `--no-sandbox`. Note that this flag disables Electron sandboxing for every process, so only use it when sandboxed launches fail.

## Build and run from source

These steps match the [Development](https://github.com/Comfy-Org/Comfy-Desktop#development) section in the repository README.

### Prerequisites

Install the build tools and git first. A fresh Ubuntu install ships without them, and `pnpm run init` compiles native modules such as `node-pty`, which fails with `Error: not found: make` if `build-essential` is missing:

```bash theme={null}
sudo apt install build-essential git
```

Then install Node.js 22 and enable pnpm:

```bash theme={null}
nvm install 22 && nvm use 22
corepack enable
```

If you do not use nvm, install Node.js 22 from [nodejs.org](https://nodejs.org/) instead.

### Clone and install

```bash theme={null}
git clone https://github.com/Comfy-Org/Comfy-Desktop.git
cd Comfy-Desktop
pnpm run init
```

`pnpm run init` installs dependencies and builds the bundled bootstrap Python.

### Start the app

```bash theme={null}
./linux-dev.sh
```

This starts Comfy Desktop in development mode. The script sets `ELECTRON_DISABLE_SANDBOX=1` because Electron's sandbox often fails in Linux dev environments.

<Card title="Next Step: Using Comfy Desktop" icon="book-open" href="/installation/desktop/usage/overview">
  Once the app is running, learn how to create instances, manage installations, and configure settings.
</Card>

## Updating

There is no in-app auto-update for a source checkout. Pull the latest code and start the app again:

```bash theme={null}
git pull
pnpm run init
./linux-dev.sh
```

## Optional: local package

To produce a local `.deb` or AppImage for yourself (not an official Comfy Org download):

```bash theme={null}
pnpm run build:linux
```

Artifacts land in `dist/`. If an AppImage fails because Chromium cannot create a sandbox, retry with `--no-sandbox`. That flag disables Electron sandboxing for every process.

## Removing leftover data

Stopping the source checkout does not delete ComfyUI installations or app data. Delete these folders only if you want a complete cleanup:

| Data | Default Location | Description |
| - | - | - |
| Installations | `~/ComfyUI-Installs` | Each ComfyUI installation you created (can also be deleted from within the app). Custom install paths are also not removed. |
| Shared models & outputs | `~/ComfyUI-Shared` | Shared model library, input/output directories |
| App config | `~/.config/comfyui-desktop-2` | Settings and installation records |
| App data | `~/.local/share/comfyui-desktop-2` | Persistent app data |
| Cache | `~/.cache/comfyui-desktop-2` | Download cache and other non-essential files |
| State | `~/.local/state/comfyui-desktop-2` | Runtime state such as port locks |
| Logs | `~/.config/comfyui-desktop-2/logs` | Desktop app logs (`app.log`) |

To fully remove everything:

1. **Delete the clone** of `Comfy-Desktop`
2. **Delete the config folder**: `~/.config/comfyui-desktop-2`
3. **Delete the data, cache, and state folders**: `~/.local/share/comfyui-desktop-2`, `~/.cache/comfyui-desktop-2`, and `~/.local/state/comfyui-desktop-2`
4. **Delete individual installations** from within the app, or manually delete `~/ComfyUI-Installs` plus any custom installation directories you configured
5. **Delete the shared model library** at `~/ComfyUI-Shared` (only if you no longer need these files)

Packaged installs (`.deb` or AppImage) also keep the app profile and logs in `~/.config/Comfy Desktop`. To clear those, run the repository's [reset-linux.sh](https://github.com/Comfy-Org/Comfy-Desktop/blob/main/scripts/reset-linux.sh) script; it removes every known app data location but leaves your `~/ComfyUI-Installs` untouched.


# Comfy Desktop for macOS
Source: https://docs.comfy.org/installation/desktop/macos

Install Comfy Desktop on macOS: system requirements, setup steps, updates, and a clean uninstall for running ComfyUI locally on Apple silicon Macs.

**Comfy Desktop** is a multi-installation manager that lets you run multiple ComfyUI instances from a single launcher. This guide covers how to install and uninstall Comfy Desktop on macOS.

## System Requirements

* **OS:** macOS 13 (Ventura) or later
* **Hardware:** Apple Silicon (M1 or later)
* **Disk Space:** At least 4.85 GB recommended per installation

<Card title="Download Comfy Desktop" icon="download" href="https://comfy.org/download">
  Download the latest installer for macOS. The page will automatically detect your platform.
</Card>

## Installation

1. Open the downloaded `.dmg` file
2. Drag **Comfy Desktop** into the **Applications** folder
3. Launch it from Launchpad or Spotlight

<img alt="Desktop MacOS" />

The first time you launch, macOS may show a security warning. Go to **System Settings → Privacy & Security** and click **Open Anyway** to allow it.

<Tip>
  **Already using Legacy Desktop?** Comfy Desktop can automatically detect and migrate your existing installation. Your custom nodes, workflows, models, and settings are carried over — nothing is lost. The legacy installation is kept untouched as a backup.

  Learn more in the [Migrate from Legacy](/installation/desktop/usage/migrate) guide.
</Tip>

<Card title="Next Step: Using Comfy Desktop" icon="book-open" href="/installation/desktop/usage/overview">
  Once installed, learn how to create instances, manage installations, and configure settings.
</Card>

## Updating Comfy Desktop

Comfy Desktop automatically checks for updates and lets you manage them in two ways.

## Quick Update

When an update is available, a **Desktop Update Ready** button appears at the top of the window:

<img alt="Desktop Update Ready button" />

Just click the ① <Icon icon="arrows-rotate" /> Desktop Update Ready button and Comfy Desktop will restart and install the update automatically.

## Manual Update via Settings

You can also check for and manage updates from the Settings panel:

<Steps>
  <Step title="Open Desktop Settings">
    <img alt="Open Desktop Settings menu" />

    1. **①** Click the hamburger menu (top-left)
    2. **②** Select **Desktop Settings**
  </Step>

  <Step title="Updates Panel">
    <img alt="Updates panel in Desktop Settings" />

    In the **Updates** panel:

    1. **① Updates** — Click the sidebar Updates tab
    2. **② Check for updates** — Manually check for available updates
    3. **③ Restart & Update** — Appears when a new version is available; click to restart and update
    4. **④ Automatically install Desktop updates** — Toggle this on/off to control automatic updates
  </Step>
</Steps>

## Uninstalling

### Remove Comfy Desktop

1. Open **Applications** folder in Finder
2. Right-click **Comfy Desktop** and select **Move to Trash**

<img alt="Uninstall Comfy Desktop on macOS" />

### What Uninstalling the App Does NOT Remove

Uninstalling Comfy Desktop only removes the launcher app itself. The following data is **not** removed and must be deleted manually if you want a complete cleanup:

| Data | Default Location | Description |
| - | - | - |
| Installations | `~/ComfyUI-Installs` | Each ComfyUI installation you created (can also be deleted from within the app). Custom install paths are also not removed. |
| Shared models & outputs | `~/ComfyUI-Shared` | Shared model library, input/output directories |
| App settings & registry | `~/Library/Application Support/Comfy Desktop` | Settings and installation records |
| Logs | `~/Library/Logs/Comfy Desktop` | Desktop app logs (`app.log`) |

<Warning>The directories listed above contain your **personal ComfyUI data** (models, outputs, settings, and installations). They are **not** Comfy Desktop application files. Deleting them will permanently remove your data.</Warning>

To fully remove everything:

1. **Delete the app data folder**: `~/Library/Application Support/Comfy Desktop`
2. **Delete the logs folder**: `~/Library/Logs/Comfy Desktop`
3. **Delete individual installations** from within the app, or manually delete `~/ComfyUI-Installs` plus any custom installation directories you configured
4. **Delete the shared model library** at `~/ComfyUI-Shared` (only if you no longer need these files)


# Comfy Desktop Overview
Source: https://docs.comfy.org/installation/desktop/overview

Comfy Desktop overview: a desktop app that installs, manages, and launches multiple instances of ComfyUI, the node-based engine for generative AI.

**Comfy Desktop** is a desktop application that lets you install, manage, and launch multiple ComfyUI instances from a single launcher.

To put it simply: **Comfy Desktop** is the app that manages and launches **ComfyUI**, the node-based engine for generative AI. You don't install ComfyUI separately — Comfy Desktop handles the installation, Python environment, and dependencies for you. Each ComfyUI instance runs independently with its own version, custom nodes, and settings.

<img alt="Comfy Desktop screenshot" />

Comfy Desktop runs on **Windows 10+**, **macOS 13+ (Apple Silicon)**, and **Linux** (official `.deb` and AppImage packages). Each standalone installation requires at least **4.85 GB** of disk space and **8 GB RAM (16 GB recommended)**. Check the platform-specific pages for full details.

## Get Started

Choose your platform to begin:

<CardGroup>
  <Card title="Windows" icon="windows" href="/installation/desktop/windows">
    Step-by-step installation guide for Windows 10 or later.
  </Card>

  <Card title="macOS" icon="app-store" href="/installation/desktop/macos">
    Step-by-step installation guide for macOS 13+ (Apple Silicon).
  </Card>

  <Card title="Linux" icon="linux" href="/installation/desktop/linux">
    Install the official `.deb` or AppImage, or build from source.
  </Card>
</CardGroup>

## Usage Guide

Once installed, learn how to use Comfy Desktop:

<CardGroup>
  <Card title="Comfy Desktop Usage Guide" icon="book-open" href="/installation/desktop/usage/overview">
    Dashboard overview, instance management, settings, snapshots, and more.
  </Card>
</CardGroup>

## Migrate from Legacy Desktop

If you're still using the older Legacy Desktop version (single-install desktop app), you can migrate your custom nodes, workflows, and models to the new Comfy Desktop. Your existing data is preserved — no manual migration needed.

<CardGroup>
  <Card title="Migration Guide" icon="arrow-right" href="/installation/desktop/usage/migrate">
    Step-by-step guide to migrate from Legacy Desktop to Comfy Desktop.
  </Card>
</CardGroup>

## Open Source

Comfy Desktop source is on [GitHub](https://github.com/Comfy-Org/Comfy-Desktop). It is dual-licensed: AGPL-3.0-or-later, or a commercial license from Comfy Org.


# Instance Management
Source: https://docs.comfy.org/installation/desktop/usage/instance-management

Create, edit, rename, and delete ComfyUI instances in Comfy Desktop

Comfy Desktop lets you manage multiple ComfyUI instances from the Chooser view.

### Instance Types

Comfy Desktop supports four types of instances. Each type displays a distinct icon on its card and in the title bar.

| Type | Icon | Description |
| - | - | - |
| **Standalone** | 💻 | A self-contained ComfyUI instance created by Comfy Desktop. Includes bundled Python, automatic updates, and full snapshot support. This is the default when you click **New Instance**. |
| **Cloud** | ☁️ | A Comfy Cloud instance. Requires a Comfy Cloud account. Cloud instances run on Comfy's servers and are billed separately. |
| **Remote** | 🌐 | Connects to a ComfyUI instance running on another machine on your network. Configure the remote host and port during setup. |
| **Tracked** | — | Tracks an existing ComfyUI installation (Git clone or portable). Uses the same icon as **Standalone** — there is no separate icon for tracked instances. You manage updates manually. See [Tracking an Existing Installation](#tracking-an-existing-installation). |

The image below labels the key actions available for each instance card:

<img alt="Instance management actions" />

1. **New Instance**: Create a brand new ComfyUI instance. See [Creating a New Instance](#creating-a-new-instance). You can also [create an instance from a snapshot file](/installation/desktop/usage/snapshots#create-an-instance-from-a-snapshot-file).
2. **⋮ Menu**: Click the three-dot icon to open the action menu for an instance.
3. **Manage**: Open the Manage panel to configure the instance (path, launch args, model directories, environment variables). See the [Manage](/installation/desktop/usage/manage) page.
4. **Restore Snapshot**: Revert the instance to a previous snapshot. See the [Snapshots](/installation/desktop/usage/snapshots) page.
5. **Share**: Export a snapshot of the instance to share with others.
6. **Copy Installation**: Duplicate an existing standalone installation with its own Python environment and custom nodes. See [Copying an Installation](#copying-an-installation).
7. **Forget**: Remove the instance from the Chooser without deleting its files (equivalent to Untrack).
8. **Uninstall**: Permanently delete the instance and all its files from disk.
   See [Uninstalling an Instance](#uninstalling-an-instance) for details on Forget and Uninstall.

## Creating a New Instance

Click the **+** card (top-left) in the Chooser view to add a new ComfyUI instance.

<Steps>
  <Step title="Configure Comfy Desktop">
    <Tabs>
      <Tab title="Windows">
        <img alt="Configure Comfy Desktop on Windows" />
      </Tab>

      <Tab title="macOS">
        <img alt="Configure Comfy Desktop on macOS" />
      </Tab>
    </Tabs>

    1. **Installation Name**: The name of your instance. The default is "ComfyUI".
    2. **Install Location**: Choose where to install ComfyUI. On Windows, it's strongly recommended to use an **SSD** and avoid the root of the C: drive.
    3. **Advanced**: Click to expand to access additional options.
    4. **Standalone**: The recommended option. A self-contained install with bundled Python, automatic updates, and snapshot support.
    5. **Remote Connection**: Connect to a ComfyUI instance running on another machine.
  </Step>

  <Step title="Installing">
    <img alt="Installing ComfyUI" />

    Comfy Desktop will handle the rest: downloading Python, setting up the environment, and installing ComfyUI. The progress screen shows the current step.
  </Step>

  <Step title="Choose a Template">
    <img alt="Template library after installation" />

    Once the installation is complete, Comfy Desktop opens the template library where you can pick a workflow template to get started.
  </Step>
</Steps>

## Tracking an Existing Installation

If you already have a ComfyUI installation (either manually set up from the Git repository or downloaded as a portable version), you can add it to Comfy Desktop without creating a new one.

Click **New Instance** on the Dashboard to open the installation menu, then select **Add Existing Instance**.

<img alt="Add Existing Instance" />

1. Click **New Instance** to open the installation options.
2. Select **Add Existing Instance** to open the tracking dialog.

### Detecting Your Installation

In the tracking dialog, click **Browse** to select a ComfyUI directory. Comfy Desktop probes the folder and automatically detects the installation type.

For a **Windows portable** install, the probe looks for:

* `standalone-env` directory — the bundled Python environment
* `ComfyUI/main.py` — the ComfyUI entry point

For a **manually cloned git repo**, the probe looks for:

* `models/` and `user/` directories — signs of a configured ComfyUI
* `.venv` directory — a Python virtual environment

### Setting Paths

After selecting the directory, the dialog shows the detected paths. You can adjust them if needed.

<img alt="ComfyUI directory and Python environment" />

1. **ComfyUI Directory**: The path to the ComfyUI folder containing `main.py`. For portable installations, this is typically the folder *inside* the portable package.
   * Portable example: `D:\ComfyUI_windows_portable\ComfyUI`
2. **Python Environment**: The path to the Python environment folder. Comfy Desktop detects this automatically and lets you override it if needed.
   * Portable example: `D:\ComfyUI_windows_portable\python_embeded`
   * Git repo example: `<ComfyUI_dir>/.venv`

### Track vs Standalone

The key difference between a **Tracked** (Add Existing Instance) installation and a **Standalone** installation is how updates are managed:

| Aspect | Tracked (Existing) | Standalone |
| - | - | - |
| **Updates** | No automatic updates — manage ComfyUI version manually via Git | Built-in automatic updates |
| **Python** | Uses an existing Python environment (`.venv`, `python_embeded`, etc.) | Bundled Python, automatic dependency management |
| **Isolation** | Shares the existing path and environment | Fully self-contained, isolated installation |
| **Snapshots** | Not supported | Snapshot support available |
| **Use case** | Already have ComfyUI set up and customized | Fresh install from scratch |

> **Note:** Tracked installations use `launchMode: 'external'`. Comfy Desktop launches the existing ComfyUI process without managing it internally. Snapshots are currently supported for Standalone instances only.

## Uninstalling an Instance

[↩ Back to overview](#overview)

When you want to remove an instance, the three-dot menu offers two options depending on whether you want to keep the files or delete everything.

<img alt="Forget vs Uninstall" />

1. **Forget / Untrack**: Removes the instance from the Chooser list without deleting any files. The installation folder and all its data remain on disk. Use this when you just want to clean up the list but might need the instance again later.
2. **Uninstall / Delete**: Permanently removes the installation and all its files from disk. Model files in shared directories are not affected.

The name you see in the menu depends on the instance type: **Forget** appears for standalone installations (untrack doesn't apply because standalone installs are local), while **Untrack** appears for installations that were adopted or added manually. Both do the same thing: remove the instance from the list without deleting its files.

## Copying an Installation

[↩ Back to overview](#overview)

You can duplicate an existing standalone installation by right-clicking its card and selecting **Copy Installation**. This creates a copy with:

* A new Python environment
* The same ComfyUI version
* Its own custom node setup

You'll be prompted to enter a name for the new installation before the copy starts.

## Editing an Instance

[↩ Back to overview](#overview)

In the **Manage** panel for an instance, you can:

* Change the installation path
* Adjust launch arguments
* Modify model directories
* Update environment variables

Open the **Manage** panel by right-clicking the instance card and selecting **Manage**.

## Error State

If an installation encounters a problem, a warning indicator appears on its card. Right-click the card and select **Dismiss Error** to clear the error state. If the issue persists, check the logs at the [Data Locations](/installation/desktop/usage/settings#data-locations).


# Managing Installations
Source: https://docs.comfy.org/installation/desktop/usage/manage

Launch, update, snapshot, and manage your ComfyUI installations

## The Manage Panel

The Manage panel content varies by instance type. The screenshots on this page show a **local standalone installation**. Cloud and remote instances have fewer tabs and settings.

Select **Manage** on an installation to open the settings panel.

<img alt="Accessing the Manage panel" />

* Open the **Chooser** view (the home screen showing all your instances)
* Click the ⋮ icon on an instance card
* Select **Manage** from the context menu

The panel has six tabs:

### Update Tab

<img alt="Update tab" />

This tab shows the current version, lets you check for updates, and configure the update channel.

* **Version**: Shows the current installed version and whether it's up to date.
* **Last checked**: Displays when updates were last checked.
* **Check for update**: Manually check for a new version.
* **Update Channel**: Choose the update channel from the dropdown:
  * **Stable**: Tested releases, recommended for most users. Default option.
  * **Latest on GitHub**: Newest commits from the master branch.

### Startup Args Tab

<img alt="Startup Args tab" />

Configure startup CLI arguments, Manager policy, launch mode, browser cache sharing, port conflict behavior, and environment variables.

* **Startup Arguments**: Custom CLI arguments for ComfyUI (e.g. `--listen`). Click the gear icon for categorized flags.
* **Manager Security Level**: Controls which node packs ComfyUI-Manager can install for this instance. Applies the next time you launch.
  * **Strict**: Blocks all node pack installs, updates, and uninstalls. Manager is read-only.
  * **Standard (recommended)**: Allows registered node packs. Blocks installs from unregistered sources (for example arbitrary git URLs).
  * **Relaxed**: Like Standard, but also allows unregistered-source installs while ComfyUI is only reachable from this machine. `--listen` blocks them again.
  * **Permissive**: Allows every risk tier. If ComfyUI is exposed with `--listen`, installs still require **Personal cloud** network mode.
* **Manager Network Mode**: How Manager talks to the node registry.
  * **Public (default)**: Uses the public registry. `--listen` blocks node pack installs at every security level.
  * **Private**: Uses a private node database you configure yourself.
  * **Offline**: No external network. Downloads are unavailable.
  * **Personal cloud**: Treats this machine as a trusted remote box and lifts the `--listen` install block. The chosen security level still applies. Only use this on a machine you control.
* **Launch Mode**: **App window** (embedded) or **Console only** (no app window; ComfyUI runs as a console process).
* **Browser Cache**: **Unique to this instance** or **Shared**.
* **If Port is Busy**: **Ask what to do**, or **Use next available port (asks if --port is set)**.
* **Environment Variables**: Add custom environment variables with the **+ Add Variable** button.

<CardGroup>
  <Card title="Startup Flags Reference" icon="book-open" href="/development/comfyui-server/startup-flags">
    See the full list of ComfyUI startup flags available for Startup Arguments.
  </Card>
</CardGroup>

### Snapshots Tab

<img alt="Snapshots tab" />

View, import, export, and create snapshots. Each entry shows version changes and package statistics.

* **Timeline**: Lists all snapshots chronologically with version changes and stats.
* **Latest**: Shows when the most recent snapshot was taken.
* **Import**: Import a snapshot from a file.
* **Export All**: Export all snapshots as a backup.
* **Create Snapshot**: Manually create a new snapshot at any time.
* Each snapshot entry shows:
  * Version change (e.g. `v0.20.1 → v0.24.1`)
  * Package changes
  * Node and package counts
  * **Export** and **Delete** buttons

<CardGroup>
  <Card title="Complete Snapshot Management" icon="camera" href="/installation/desktop/usage/snapshots">
    Learn about automatic snapshots, comparison, and full snapshot management.
  </Card>
</CardGroup>

### Storage Tab

<img alt="Storage tab" />

Configure whether this instance uses the global shared folders, and add extra model directories that apply only to this instance.

* **Include Shared Directories**: Toggle whether this instance scans the global shared model directories from [Desktop Settings → Storage](/installation/desktop/usage/settings#storage).
* **Use Shared Input Folder**: When enabled, this instance reads input files from the global shared input folder. Disable to use this instance's own input folder.
* **Use Shared Output Folder**: When enabled, this instance writes generated outputs to the global shared output folder. Disable to use this instance's own output folder.
* **Model Directories**: Extra model directories for this instance only, searched in addition to the shared model directories.
* **Input Directory** / **Output Directory**: This instance's own folders when the shared toggles above are off.

### Terminal Tab

<img alt="Terminal tab" />

An interactive shell in this instance's folder. It works whether ComfyUI is running or stopped.

* Use it to inspect startup logs, errors, and Python output.
* Copy, paste, and select-all follow OS shortcuts. Right-click the terminal for the same actions.

### About Tab

<img alt="About tab" />

View installation details: ComfyUI version, hardware, Python and PyTorch versions, disk path, and usage.

* **Current Version**: The installed ComfyUI version.
* **Hardware**: Detected hardware (e.g. `Apple Silicon (MPS)`).
* **Python**: Bundled Python version.
* **PyTorch**: The installed PyTorch build. **Change PyTorch** switches to an official stack tested with this install type (CUDA, ROCm, Intel XPU, CPU, or Apple MPS). The rest of the environment is kept. Nightly builds are marked unstable.
* **Location**: The full installation path on disk. Click the copy button to copy it.
* **Disk Usage**: How much disk space the installation uses.

## Installation Actions

Right-click an installation card (or click the ⋮ icon) to access actions. See the [Instance Management](/installation/desktop/usage/instance-management) page for a full list of actions.


# Migrate from Legacy Desktop
Source: https://docs.comfy.org/installation/desktop/usage/migrate

Learn how to migrate your Legacy Desktop installation to Comfy Desktop

<Info>
  This page covers migration from **Legacy Desktop** (the previous single-install desktop app). If you're a first-time user, you can skip this.
</Info>

<CardGroup>
  <Card title="Looking for a different installation?" icon="compass" href="/installation/desktop/usage/instance-management#tracking-an-existing-installation">
    If you already have a ComfyUI installation (portable, manual git clone, etc.) and want to add it to Comfy Desktop, see **Tracking an existing installation** in Instance Management.
  </Card>
</CardGroup>

If you already have Legacy Desktop installed, Comfy Desktop can detect and migrate it, creating a new Standalone installation in the Chooser view.

## What Gets Migrated

Legacy Desktop was a single-install app. Comfy Desktop is a multi-installation manager. When you migrate:

* **Workflows and settings** — copied to the new Standalone installation
* **Custom nodes** — scanned and re-installed in the new environment
* **Models** — your existing model folder is added as a shared directory (files stay where they are)
* **Input files and outputs** — copied to the new installation's shared directories
* **Python environment** — a fresh Python environment is created (Legacy's bundled Python is not reused)
* **ComfyUI version** — the latest version is installed in the new Standalone

The Legacy Desktop installation itself is **not modified** during migration. It remains on your system as a backup.

## What Changes After Migration

Once migration completes, your new Standalone installation works like any other Comfy Desktop installation:

* **Startup** — click the play button on the new installation card in the Chooser view to launch ComfyUI.
* **Port** — Legacy Desktop used port `8000` by default. The new installation carries over this port setting (and any other custom startup arguments you had).
* **Manage** — use the Manage panel to update, snapshot, and configure the installation.
* **Updates** — Standalone installations can be updated independently via the Manage panel. Unlike Legacy Desktop, you no longer need to download a new build for each update.
* **Multiple instances** — you can have multiple Standalone installations side by side, each with its own ComfyUI version and configuration.
* **Shared storage** — models are shared across all Standalone installations by default. Input and output directories are pinned to the adopted legacy workspace so your existing files stay where they are.

## Does My Old Link Still Work?

Legacy Desktop ran on port `8000` by default. The new installation **carries over the port** from your legacy config, so `http://localhost:8000` should still work. If you had custom CLI arguments configured (e.g. `--port 8188`), those are carried over too.

If you use a URL shortener, bookmark, or external integration that references the Legacy Desktop app by a different address, you may need to check the new installation's Startup Args tab and update accordingly.

## Step-by-Step Migration

<Steps>
  <Step title="Install Comfy Desktop">
    Download and install Comfy Desktop from the [official download page](https://comfy.org/download).
  </Step>

  <Step title="Start Comfy Desktop">
    When you first open Comfy Desktop, it automatically detects any Legacy Desktop installation on your system and shows a migration prompt.
  </Step>

  <Step title="Confirm Migration">
    Click **Migrate Now** to proceed. Comfy Desktop will:

    1. Scan your existing installation (custom nodes, models, workflows)
    2. Create a new Standalone installation with a fresh Python environment and the latest ComfyUI
    3. Copy your user data (workflows, settings, etc.)
    4. Copy your input files and outputs
    5. Add your model folder as a shared directory
    6. Install custom nodes in the new environment

    After completion, the new Standalone installation card appears in the Chooser view.
  </Step>

  <Step title="Verify">
    Launch your new installation and confirm:

    * Your workflows are available
    * Custom nodes are installed
    * Models are accessible
    * Your server is running on the carried-over URL (default `http://localhost:8000`)
  </Step>
</Steps>

## Troubleshooting

### Legacy Desktop not detected automatically

If the migration prompt doesn't appear, you can migrate manually:

1. Click the **+** card in the Chooser view
2. Select **Legacy Desktop**
3. Choose your Legacy Desktop installation and follow the prompts

If your existing installation wasn't detected by the Chooser at all, you can also add it directly via the Manage panel. See [**Tracking an existing installation**](/installation/desktop/usage/instance-management#tracking-an-existing-installation) for instructions.

### Migration fails

* **Check logs** in the Manage panel's Terminal tab for error details
* **Ensure your Legacy installation is intact**: migration reads from your existing install
* **Try again**: network issues may resolve on a second attempt

### Models missing after migration

Models are added as a shared directory path (not copied). If models don't appear:

1. Open the migrated installation's **Manage** panel
2. Go to the **Storage** tab and open **Model Directories**
3. Check if your old model folder is listed. If not, add it manually.


# Using Comfy Desktop
Source: https://docs.comfy.org/installation/desktop/usage/overview

Overview of Comfy Desktop — creating new installations, managing instances, and more

Comfy Desktop is the official desktop application for **ComfyUI**. It manages everything for you — installing ComfyUI, keeping it updated, and letting you run multiple independent setups side by side.

To understand the relationship: **Comfy Desktop** is the app that manages and launches **ComfyUI** instances. You don't install ComfyUI separately — Comfy Desktop handles the installation, Python environment, and dependencies for each instance automatically.

### Key Features

* **[Multi-instance management](/installation/desktop/usage/instance-management)**: run multiple ComfyUI instances side by side, each with its own version, custom nodes, and configuration
* **[Snapshots](/installation/desktop/usage/manage#snapshots-tab)**: save and restore the full state of an instance (ComfyUI version, custom nodes, Python packages), making it easy to roll back or reproduce an environment
* **[Shared storage](/installation/desktop/usage/settings#storage)**: models are shared across all instances by default, saving disk space. You can also add external model folders
* **Automatic updates**: the title-bar **Desktop Update** control updates Comfy Desktop. Use the Manage panel [Update tab](/installation/desktop/usage/manage#update-tab) to update each ComfyUI instance.
* **Cloud integration**: launch or connect to Comfy Cloud instances directly from the Chooser view
* **[Track existing installations](/installation/desktop/usage/instance-management#tracking-an-existing-installation)**: add your existing portable or git-cloned ComfyUI installations to Comfy Desktop for unified management

This guide covers how to use these features.

## Dashboard Overview

Comfy Desktop window is divided into several key areas. The image below labels the main parts of the Dashboard:

<img alt="Comfy Desktop Dashboard" />

### App Menu

The hamburger menu (☰) in the top-left corner opens the application menu (File / Edit / View / Window / Help). Use it to open a new window, access **Desktop Settings**, **Log in** to your Comfy account, quit the app, or find other desktop-level controls.

<CardGroup>
  <Card title="Settings" icon="cog" href="/installation/desktop/usage/settings">
    Global settings: auto-updates, proxy/mirror, shared storage, and data locations.
  </Card>
</CardGroup>

### Instance Switcher

The center pill shows the name of your active ComfyUI instance. Click it to open the **Instance Picker**, a popover that lists every installed instance, shows their running status, and lets you switch between them or launch a new one.

<CardGroup>
  <Card title="Managing Installations" icon="sliders" href="/installation/desktop/usage/manage">
    Launch, update, snapshot, and configure your installations through the Manage panel.
  </Card>
</CardGroup>

### Trailing Buttons

The buttons grouped on the right side of the title bar provide quick access to:

* **Desktop Update**：when a new version of Comfy Desktop is available, a pill appears here. Click to download and apply the update.
* **Feedback**：send feedback to the Comfy Desktop team.
* **Downloads**：opens the downloads tray showing active and recent downloads.

### Search

The search box lets you filter your installed instances by name, making it easy to find a specific setup when you have many.

### Chooser (Instance List)

The main area of the Dashboard, called the **Chooser**, displays all your ComfyUI instances as cards. **Click any instance card to launch or switch to that instance.**

From here you can:

* **＋ New Instance**：create a new standalone ComfyUI instance.
* **Comfy Cloud**: connect to or launch a cloud instance. The card may show a **TRY FREE** pill when free Cloud runs are available.
* **Account chip** (top-right): sign in with your Comfy account to browse the ComfyUI Builds in your workspace. Once signed in, the chip becomes a workspace switcher.
* **Workspace Builds**: when signed in, ComfyUI Builds published to your workspace appear in the grid. Click a tile to install and launch it.
* **Existing instance cards**：each card shows the instance name, status, and type. Right-click (or click the ⋮ icon) to manage, update, snapshot, or delete the instance.

<CardGroup>
  <Card title="Instance Management" icon="layer-group" href="/installation/desktop/usage/instance-management">
    Create, rename, edit, and delete ComfyUI instances.
  </Card>
</CardGroup>

## Feedback and Issues

Found a bug or have a suggestion? Comfy Desktop is open source. You can report issues and check planned features here:

* **Comfy Desktop issues**: [github.com/Comfy-Org/Comfy-Desktop/issues](https://github.com/Comfy-Org/Comfy-Desktop/issues)
* **Documentation issues**: [github.com/Comfy-Org/docs/issues](https://github.com/Comfy-Org/docs/issues)

For general questions about ComfyUI, visit the [ComfyUI GitHub Discussions](https://github.com/Comfy-Org/ComfyUI/discussions) or join the [ComfyUI Discord](https://www.comfy.org/discord).


# Settings
Source: https://docs.comfy.org/installation/desktop/usage/settings

Global settings, proxy/mirror configuration, and data locations

Click the ☰ menu (1) in the top-left corner and select **Desktop Settings** (2) to open the global settings panel.

<img alt="Access Desktop Settings" />

The settings panel is organized into five tabs. Click a tab in the sidebar to switch views.

## Preferences

<img alt="Preferences tab" />

* **Language**: Choose the display language. **English** and **中文** are available.
* **Auto-launch on startup**: Pick which instance to start when Comfy Desktop opens. **None (show dashboard)** is the default. You can also choose **Last used instance**, or a specific install.
* **Confirm before closing a window**: Ask for confirmation before closing a window that is running a local install.
* **Warn before running multiple instances**: Show a warning before launching another local ComfyUI instance while one is already running or starting.
* **Hide Cloud from the Instance Picker**: Hide the Cloud row from the Dashboard. Cloud still works if you re-enable this later.
* **Share anonymous usage telemetry**: Send anonymous usage data to help improve Comfy Desktop.
* **Comfy Desktop**: Link to the [Comfy Desktop GitHub repository](https://github.com/Comfy-Org/Comfy-Desktop).

## Updates

<img alt="Updates tab" />

* **Status**: Shows whether Comfy Desktop is up to date, the installed version, and the last check time.
* **Check for updates**: Manually check for a new version. Button changes to **Download** then **Install** when an update is available.
* **Automatically install Desktop updates**: Auto-download and install updates in the background.

## Storage

The Storage tab is where you configure where Comfy Desktop finds and stores files. The key concept is **sharing**: instead of each instance having its own isolated models, inputs, and outputs, you set up shared directories accessible to all instances.

<img alt="Storage tab" />

* **Shared Models**: Each directory listed here is scanned for models by every instance. The directory marked **Primary** is where new models are saved by default.

  <img alt="Make directory primary" />

  * Click the folder icon to open a directory in your file manager.
  * Click the **...** menu (1) on a directory, then select **Make primary** (2) to change which directory new models save to.
  * Click **+ Add Shared Directory** to add more model directories.
* **Shared Input**: A shared path where all instances look for input files (images, videos, etc.).
* **Shared Output**: A shared path where all instances save generated outputs. Customizing this lets you keep all results in one place.
* Click the folder icon to browse and select a new path. **?** tooltips provide additional details.

Per-instance overrides (include shared dirs, split input/output, extra model folders) live in the instance [Manage](/installation/desktop/usage/manage#storage-tab) Storage tab.

## Advanced

<img alt="Advanced tab" />

* **Default Install Location**: Where new standalone instances are created. Click the folder icon to change it.
* **Use hardware acceleration**: Use the GPU to render Comfy Desktop. Restart Comfy Desktop for changes to take effect.
* **PyPI Mirror URL**: Custom pip mirror (e.g. `https://mirrors.aliyun.com/pypi/simple/`).
* **Use Chinese Mirrors (Git & PyPI)**: Use Chinese mirror servers for Git and PyPI. Helpful in mainland China.
* **Cache Directory**: Where Comfy Desktop stores temporary and cached data. Click the folder icon to change it.

## Logs

* **Diagnostics**: **Open logs folder** reveals the Desktop app log directory (`app.log`). See [How do I check Comfy Desktop startup logs?](/installation/desktop/faq#how-do-i-check-comfy-desktop-startup-logs).

## Data Locations

Comfy Desktop stores data in platform-specific directories.

<Tabs>
  <Tab title="Windows">
    ```
    App data:     %APPDATA%\Comfy Desktop
    Logs:         %APPDATA%\Comfy Desktop\logs
    Installs:     %LOCALAPPDATA%\Comfy-Desktop\ComfyUI-Installs
    Shared data:  %LOCALAPPDATA%\Comfy-Desktop\ComfyUI-Shared
    ```

    New installs put large data (installs, shared models, cache) under `%LOCALAPPDATA%\Comfy-Desktop`. If you already had `ComfyUI-Installs` or `ComfyUI-Shared` in your user profile before upgrading, those home-root folders are kept. If you installed the app to another drive, large data lives in `<drive>\Comfy-Desktop\` instead.
  </Tab>

  <Tab title="macOS">
    ```
    App data:     ~/Library/Application Support/Comfy Desktop
    Logs:         ~/Library/Logs/Comfy Desktop
    Installs:     ~/ComfyUI-Installs
    Shared data:  ~/ComfyUI-Shared
    ```
  </Tab>

  <Tab title="Linux">
    ```
    Config:       ~/.config/comfyui-desktop-2
    Data:         ~/.local/share/comfyui-desktop-2
    Cache:        ~/.cache/comfyui-desktop-2
    State:        ~/.local/state/comfyui-desktop-2
    Logs:         ~/.config/comfyui-desktop-2/logs
    Installs:     ~/ComfyUI-Installs
    Shared data:  ~/ComfyUI-Shared
    ```

    On Linux, Electron stores user data under the package name `comfyui-desktop-2`, not the display name Comfy Desktop.
  </Tab>
</Tabs>

## Keyboard Shortcuts

| Shortcut | Action |
| - | - |
| `Ctrl+R` / `Cmd+R` | Reload the current ComfyUI instance |
| `Ctrl+W` / `Cmd+W` | Close the current window |
| `Escape` | Close a dialog or popup |
| `Ctrl+,` / `Cmd+,` | Open Comfy Desktop Settings |

## Feedback and Issues

Found a bug or have a suggestion? Comfy Desktop is open source. You can report issues and check planned features here:

* **Comfy Desktop issues**: [github.com/Comfy-Org/Comfy-Desktop/issues](https://github.com/Comfy-Org/Comfy-Desktop/issues)
* **Documentation issues**: [github.com/Comfy-Org/docs/issues](https://github.com/Comfy-Org/docs/issues)

For general questions about ComfyUI, visit the [ComfyUI GitHub Discussions](https://github.com/Comfy-Org/ComfyUI/discussions) or join the [ComfyUI Discord](https://www.comfy.org/discord).


# Snapshots
Source: https://docs.comfy.org/installation/desktop/usage/snapshots

Back up, restore, and share ComfyUI instance configurations in Comfy Desktop

A snapshot records your instance's current state, including:

* **ComfyUI version**：which build of ComfyUI is installed
* **Custom nodes**：every custom node with its version or commit hash
* **pip packages**：all Python packages installed in the environment

Snapshots serve as restore points: roll back after a broken update, clone an installation, or share a working configuration with a teammate.

Comfy Desktop automatically creates snapshots on key events: every boot, restart, before/after an update, and after a restore. You can also manually create snapshots at any time (up to 200 auto-snapshots per install).

## Accessing Snapshots

From any instance card, click the **⋮ menu** (1) and select **Restore Snapshot** (2) to open the Snapshots tab directly.

<img alt="Restore Snapshot entry point" />

Alternatively, open the **Manage** panel on any instance card and navigate to the **Snapshots** tab.

## Snapshots Tab Overview

The Snapshots tab is your hub for managing all snapshot actions. The timeline shows snapshots for the instance, newest first. Key actions available:

<img alt="Snapshot tab overview" />

1. **Selected instance**: The instance whose snapshots are shown in the timeline.
2. **Snapshots tab**: Currently active tab in the Manage panel.
3. **Import**: Import a snapshot file exported by another user or instance.
4. **Export All**: Export all snapshots for this instance as a single `.json` file.
5. **Create Snapshot**: Create a manual snapshot of the current instance state.
6. **Export**: Export a single snapshot from the timeline.
7. **Delete**: Delete a manual snapshot from the timeline.
   **Restore**: Restore the instance to a specific snapshot's state.

### Create a Manual Snapshot

Click **Create Snapshot** (5) in the Snapshots tab header. You can optionally add a label (e.g. "Before adding LCM LoRA") to identify it later. The snapshot will capture:

* Current ComfyUI Git commit
* All enabled custom nodes (git clone URL + commit, or CNR ID + version)
* All pip packages from `pip freeze`

Manual snapshots don't count toward the auto-snapshot limit and can be deleted individually.

### View Snapshot Details

Click on any snapshot card to expand its details. The inspector shows:

* **ComfyUI**：Commit hash, base tag, and how many commits ahead of the release tag
* **Custom Nodes**：All recorded nodes with their type (git / CNR), URL, version/commit, and enabled status
* **Pip Packages**：Full list of recorded pip packages with pinned versions

Use the diff buttons to see what changed:

* **Diff vs Previous**：Compare with the snapshot right before this one
* **Diff vs Current**：Compare with the instance's current state

### Restore from a Snapshot

1. In the Snapshots tab, find the snapshot you want to restore.
2. Click **Restore**：a preview shows the diff (what will change).
3. Review the changes and click **Confirm** to begin the restore process.

During restoration, Comfy Desktop will:

1. **Check out the recorded ComfyUI version** (Git commit)
2. **Install missing custom nodes**, switch versions, and enable/disable nodes as needed
3. **Restore pip packages**: install missing packages, upgrade/downgrade to the recorded version, and remove extras
4. **Run post-install scripts** for any newly installed or version-switched custom nodes

The process can be cancelled at any time. If cancelled or if a package install fails, the system automatically rolls back to the pre-restore state using a built-in backup.

After a successful restore, Comfy Desktop automatically creates a `post-restore` snapshot so you can undo the restoration if needed.

### Delete a Snapshot

Manual snapshots can be deleted individually. Click the **✕** button on any manual snapshot card. Auto-snapshots (boot, update, etc.) cannot be deleted individually; use **Prune** to clean them up in bulk.

## Create an Instance from a Snapshot File

If someone shares a snapshot file with you, you can use it to spin up a new ComfyUI instance with the exact same configuration.

1. Click the **☰ menu** (1) in the top-left corner of the Chooser view and select **Load Snapshot** (2).

<img alt="Load Snapshot entry point" />

2. Browse your file system and select the `.json` snapshot file.

<img alt="Select a snapshot file" />

3. A preview shows the snapshot contents: source instance name, ComfyUI version, custom nodes, and pip packages. Review the details, then click **Create Installation** to build a new instance from the snapshot.

<img alt="Snapshot preview and create" />

This creates a brand new standalone instance, and the original instance is untouched. You'll see it appear in the Chooser view alongside your other instances.


# Comfy Desktop for Windows
Source: https://docs.comfy.org/installation/desktop/windows

Install Comfy Desktop on Windows: system requirements, setup steps, updates, and a clean uninstall for running ComfyUI locally on Windows 10 and later.

**Comfy Desktop** is a multi-installation manager that lets you run multiple ComfyUI instances from a single launcher. This guide covers how to install and uninstall Comfy Desktop on Windows.

## System Requirements

* **OS:** Windows 10 or later
* **Architecture:** x64 or ARM64
* **GPU:** Dedicated GPU (NVIDIA / AMD) recommended for good performance, but not required
* **Disk Space:** At least 4.85 GB recommended per installation

<Card title="Download Comfy Desktop" icon="download" href="https://comfy.org/download">
  Download the latest installer for Windows. The page will automatically detect your platform.
</Card>

## Installation

Run the downloaded `.exe` installer (NSIS installer) and follow the prompts. After installation, launch Comfy Desktop from the Start Menu or desktop shortcut.

<img alt="Windows setup" />

When you first open the app, you'll see the **Welcome** screen where you can create your first installation.

<Tip>
  **Already using Legacy Desktop?** Comfy Desktop can automatically detect and migrate your existing installation. Your custom nodes, workflows, models, and settings are carried over — nothing is lost. The legacy installation is kept untouched as a backup.

  Learn more in the [Migrate from Legacy](/installation/desktop/usage/migrate) guide.
</Tip>

<Card title="Next Step: Using Comfy Desktop" icon="book-open" href="/installation/desktop/usage/overview">
  Once installed, learn how to create instances, manage installations, and configure settings.
</Card>

## Updating Comfy Desktop

Comfy Desktop automatically checks for updates and lets you manage them in two ways.

## Quick Update

When an update is available, a **Desktop Update Ready** button appears at the top of the window:

<img alt="Desktop Update Ready button" />

Just click the ① <Icon icon="arrows-rotate" /> Desktop Update Ready button and Comfy Desktop will restart and install the update automatically.

## Manual Update via Settings

You can also check for and manage updates from the Settings panel:

<Steps>
  <Step title="Open Desktop Settings">
    <img alt="Open Desktop Settings menu" />

    1. **①** Click the hamburger menu (top-left)
    2. **②** Select **Desktop Settings**
  </Step>

  <Step title="Updates Panel">
    <img alt="Updates panel in Desktop Settings" />

    In the **Updates** panel:

    1. **① Updates** — Click the sidebar Updates tab
    2. **② Check for updates** — Manually check for available updates
    3. **③ Restart & Update** — Appears when a new version is available; click to restart and update
    4. **④ Automatically install Desktop updates** — Toggle this on/off to control automatic updates
  </Step>
</Steps>

## Uninstalling

### Remove Comfy Desktop

1. Go to **Settings → Apps → Installed apps**
2. Find **Comfy Desktop** and click **Uninstall**

<img alt="Uninstall Comfy Desktop on Windows" />

### What Uninstalling the App Does NOT Remove

Uninstalling Comfy Desktop only removes the launcher app itself. The following data is **not** removed and must be deleted manually if you want a complete cleanup:

| Data | Default Location | Description |
| - | - | - |
| Installations | `%LOCALAPPDATA%\Comfy-Desktop\ComfyUI-Installs` | Each ComfyUI installation you created (can also be deleted from within the app). Custom install paths are also not removed. Older installs may still live in `%USERPROFILE%\ComfyUI-Installs`. |
| Shared models & outputs | `%LOCALAPPDATA%\Comfy-Desktop\ComfyUI-Shared` | Shared model library, input/output directories. Older installs may still use `%USERPROFILE%\ComfyUI-Shared`. |
| App settings & registry | `%APPDATA%\Comfy Desktop` | Settings and installation records |
| Logs | `%APPDATA%\Comfy Desktop\logs` | Desktop app logs (`app.log`) |

<Warning>The directories listed above contain your **personal ComfyUI data** (models, outputs, settings, and installations). They are **not** Comfy Desktop application files. Deleting them will permanently remove your data.</Warning>

To fully remove everything:

1. **Delete the app data folder**: `%APPDATA%\Comfy Desktop`
2. **Delete individual installations** from within the app, or manually delete `%LOCALAPPDATA%\Comfy-Desktop\ComfyUI-Installs` (or `%USERPROFILE%\ComfyUI-Installs` if that is where they were created). Also delete any custom installation directories you configured
3. **Delete the shared model library** at `%LOCALAPPDATA%\Comfy-Desktop\ComfyUI-Shared` (or `%USERPROFILE%\ComfyUI-Shared`) only if you no longer need these files


# How to Install Custom Nodes in ComfyUI
Source: https://docs.comfy.org/installation/install_custom_node

Install custom nodes in ComfyUI with ComfyUI Manager, git clone, or a ZIP download, and install their Python dependencies safely.

## What are Custom Nodes ?

Custom nodes are extensions for ComfyUI that add new functionality like advanced image processing, machine learning fine-tuning, color adjustments, and more. These community-developed nodes can significantly expand ComfyUI's core capabilities.

<Warning>
  Before installing custom nodes, it's important to review them carefully. Since ComfyUI is an open-source project, malicious plugins could potentially exploit custom nodes:

  1. Only install custom nodes from trusted authors and those commonly used by the community
  2. Understand the plugin's functionality before installing and avoid unknown sources to ensure system security
  3. Avoid installing obscure or suspicious plugins - unverified plugins may pose security risks that could lead to system compromise
</Warning>

All custom node installations require completing these two steps:

1. Clone the node code to the `ComfyUI/custom_nodes` directory
2. Install the required Python dependencies

This guide compares three installation approaches. **ComfyUI Manager** is built into current ComfyUI releases for most setups—start from the [ComfyUI Manager overview](/manager/overview) for what it does and how to enable it. Use **Git clone** or **ZIP** when a node is not on the registry or you need a specific revision.

| Method | Advantages | Disadvantages |
| - | - | - |
| **ComfyUI Manager** (Recommended) | 1. Automated installation<br />2. Dependency handling<br />3. GUI interface | Cannot directly search for nodes not registered in the registry |
| **Git Clone** | Can install nodes not registered in the registry | 1. Requires Git knowledge<br />2. Manual dependency handling<br />3. Installation risks |
| **Repository ZIP Download** | 1. No Git required<br />2. Manual control | 1. Manual dependency handling<br />2. No version control<br />3. Installation risks |

Tip: Before installing custom nodes, check the plugin's README file to understand installation methods, usage, and requirements like specific models, dependency versions, and common issue solutions.

## Method 1: ComfyUI Manager (Recommended)

<Note>
  You need ComfyUI Manager available in your environment before using this method. If it is missing or disabled, see the [ComfyUI Manager overview](/manager/overview) and [installation guide](/manager/install).
</Note>

ComfyUI Manager provides two UI versions for managing custom nodes. Choose the guide that matches your interface:

<Columns>
  <Card title="New UI (default for Desktop)" icon="sparkles" href="/manager/pack-management">
    The new node management interface, enabled by default for Desktop users.
  </Card>

  <Card title="Legacy UI" icon="rectangle-history" href="/manager/legacy-ui">
    The classic Manager interface for custom node installation.
  </Card>
</Columns>

## Method 2: Manual Installation Using Git

Suitable for new nodes not found in Manager or when specific versions are needed. Requires [Git](https://git-scm.com/) installed on your system.

<Steps>
  <Step title="Get the repository URL">
    Click the "Code" button on GitHub and copy the HTTPS link
  </Step>

  <Step title="Navigate to custom_nodes directory">
    ```bash theme={null}
    cd /path/to/ComfyUI/custom_nodes
    ```
  </Step>

  <Step title="Clone the repository">
    ```bash theme={null}
    git clone [repository URL]
    ```
  </Step>

  <Step title="Install dependencies">
    Dependencies must be installed in your ComfyUI environment - be careful not to mix with your system environment to avoid contamination

    <Tabs>
      <Tab title="Windows Portable">
        For Windows portable version, install dependencies in the embedded Python environment

        ```bash theme={null}
        python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\[node directory]\requirements.txt
        ```
      </Tab>

      <Tab title="Manual Install">
        Install dependencies in your ComfyUI environment

        ```bash theme={null}
        cd [node directory]
        pip install -r requirements.txt
        ```
      </Tab>
    </Tabs>
  </Step>

  <Step title="Restart ComfyUI and refresh browser">
    Restart ComfyUI and refresh your browser. Check startup logs for any `import failed` errors
  </Step>
</Steps>

## Method 3: ZIP Download Installation

Suitable for users who cannot use Git or Manager

<Warning>
  We don't recommend this installation method as it loses version control capabilities
</Warning>

<Steps>
  <Step title="Click `Code` → `Download ZIP` on GitHub">
    Click `Code` → `Download ZIP` on the GitHub page

    <img alt="Click Code → Download ZIP on GitHub" />
  </Step>

  <Step title="Extract the ZIP file">
    Extract the downloaded ZIP file
  </Step>

  <Step title="Copy extracted folder to `ComfyUI/custom_nodes/` directory">
    Copy the extracted folder to `ComfyUI/custom_nodes/` directory
  </Step>

  <Step title="Install dependencies manually (same as Git method step 4)">
    Restart ComfyUI and refresh browser
  </Step>

  <Step title="Verify successful installation">
    Check ComfyUI Manager after restart to confirm the plugin installed successfully and there are no `import failed` errors
  </Step>
</Steps>

## Custom Node Resources

In ComfyUI, besides the basic node extension functionality, custom nodes can also include the following additional resources:

* [Node Documentation](/custom-nodes/help_page): This feature supports all custom and basic nodes. You can use it to view node documentation, understand the purpose and usage of nodes, and contribute documentation via PRs to the author.
* [Custom Node Workflow Templates](/custom-nodes/workflow_templates): Workflow templates provided by node authors as example workflows, which can be browsed and loaded from the ComfyUI templates.
* [Multi-language Support](/custom-nodes/i18n)

If you are a custom node developer, you can add these resources to make your custom node more user-friendly.


# Install ComfyUI Manually (Windows, macOS, Linux)
Source: https://docs.comfy.org/installation/manual_install

Install ComfyUI manually on Windows, macOS, or Linux: create a virtual environment, clone the repository, install GPU dependencies, and start the app.

For the installation of ComfyUI, it is mainly divided into several steps:

1. Create a virtual environment(avoid polluting the system-level Python environment)
2. Clone the ComfyUI code repository
3. Install dependencies
4. Start ComfyUI

You can also refer to [ComfyUI CLI](/comfy-cli/getting-started) to install ComfyUI, it is a command line tool that can easily install ComfyUI and manage its dependencies.

## Create a virtual environment

<Tip>
  Independent virtual environments are necessary because ComfyUI's dependencies may conflict with other dependencies on the system, and it can also avoid polluting the system-level Python environment.
</Tip>

[Install Miniconda](https://docs.anaconda.com/free/miniconda/index.html#latest-miniconda-installer-links). This will help you install the correct versions of Python and other libraries needed by ComfyUI.

Create an environment with Conda.

```
conda create -n comfyenv
conda activate comfyenv
```

## Clone the ComfyUI code repository

You need to ensure that you have installed [Git](https://git-scm.com/downloads) on your system. First, you need to open the terminal (command line), then clone the code repository.

<Tabs>
  <Tab title="Windows">
    <Warning>If you have not installed Microsoft Visual C++ Redistributable, please install it [here.](https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170)</Warning>
  </Tab>

  <Tab title="Linux">
    Open Terminal application.
  </Tab>

  <Tab title="MacOS">
    Open [Terminal application](https://support.apple.com/guide/terminal/open-or-quit-terminal-apd5265185d-f365-44cb-8b09-71a064a42125/mac).
  </Tab>
</Tabs>

```bash theme={null}
git clone https://github.com/Comfy-Org/ComfyUI.git
```

## Install GPU and ComfyUI dependencies

<Steps>
  <Step title="Install GPU dependencies">
    Install GPU Dependencies

    <Accordion title="Nvidia">
      ```
      pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu130
      ```

      Alternatively, you can install the nightly version of PyTorch.

      <Accordion title="Install Nightly">
        <Warning>Install Nightly version (might be more risky)</Warning>

        ```
        pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu132
        ```
      </Accordion>
    </Accordion>

    <Accordion title="AMD">
      For Linux, install the ROCm 7.2 version of PyTorch:

      ```
      pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.2
      ```

      Alternatively, you can install the nightly version of PyTorch (ROCm 7.2).

      <Accordion title="Install Nightly">
        <Warning>Install Nightly version (might be more risky)</Warning>

        ```
        pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.2
        ```
      </Accordion>

      For Windows, use AMD's [multi-architecture PyTorch packages](https://rocm.docs.amd.com/projects/ai-ecosystem/en/latest/frameworks/pytorch/install.html) with ROCm 10.0. The `device-*` extras install your GPU's kernels and the matching ROCm runtime automatically; a separate HIP SDK installation is not needed. Use Windows 11, a current [AMD graphics driver](https://www.amd.com/en/support/download/drivers.html), and 64-bit Python 3.13.

      The install command below uses `device-all` to install kernels for all supported GPUs. To reduce download size and disk usage, optionally replace **both** occurrences of `device-all` with the target for your GPU:

      | GPU | Device extra |
      | - | - |
      | RX 9070 / XT, Radeon AI PRO R9700 | `device-gfx1201` |
      | RX 9060 / XT | `device-gfx1200` |
      | RX 7900 XT / XTX | `device-gfx1100` |
      | RX 7700 XT / 7800 XT | `device-gfx1101` |
      | RX 7600 / XT | `device-gfx1102` |
      | Ryzen AI Max / Max+ (Strix Halo) | `device-gfx1151` |

      <Note>
        This table only lists examples. A GPU missing from it may still be supported: supported architectures include RDNA 2, RDNA 3, RDNA 3.5, and RDNA 4. Keep `device-all` to install kernels for all supported targets. For other models, see AMD's [GPU target table](https://github.com/ROCm/TheRock/blob/main/RELEASES.md#gfx-target-lookup-table) and [ROCm compatibility matrix](https://rocm.docs.amd.com/en/docs-10.0.0/compatibility/compatibility-matrix.html).
      </Note>

      ```
      pip install --index-url https://stable.repo.amd.com/rocm/whl-next/ "torch[device-all]==2.13.0+rocm10.0.0" "torchvision[device-all]==0.28.0+rocm10.0.0" "torchaudio==2.11.0.2+rocm10.0.0"
      ```
    </Accordion>

    <Accordion title="Mac ARM Silicon">
      ```bash theme={null}
      conda install pytorch-nightly::pytorch torchvision torchaudio -c pytorch-nightly
      ```
    </Accordion>
  </Step>

  <Step title="Install ComfyUI dependencies">
    ```bash theme={null}
    cd ComfyUI
    pip install -r requirements.txt
    ```
  </Step>

  <Step title="Start ComfyUI">
    Start the application

    ```
    cd ComfyUI
    python main.py
    ```

    Run `python main.py --help` for built-in help, or see the [Startup Flags reference](/development/comfyui-server/startup-flags) for a complete list of command-line options.
  </Step>
</Steps>

For advanced server configuration (custom port, LAN access, VRAM modes, and more), see the [Startup Flags reference](/development/comfyui-server/startup-flags).

## How to update ComfyUI

<Steps>
  <Step title="pull the latest code">
    Use the command line to enter the installation path of ComfyUI, then pull the latest code.

    ```bash theme={null}
    cd <installation path>/ComfyUI
    git pull
    ```
  </Step>

  <Step title="install the dependencies">
    Use the command line to enter the installation path of ComfyUI, then install the dependencies.

    <Warning>
      You need to ensure that the current Python environment is the ComfyUI virtual environment, otherwise the dependencies will be installed to the system-level Python environment, polluting the system-level Python environment.
    </Warning>

    ```bash theme={null}
        pip install -r requirements.txt
    ```
  </Step>
</Steps>

## Adding Extra Model Paths

If you want to manage your model files outside of `ComfyUI/models`, you may have the following reasons:

* You have multiple ComfyUI instances and want them to share model files to save disk space
* You have different types of GUI programs (such as WebUI) and want them to use the same model files
* Model files cannot be recognized or found

We provide a way to add extra model search paths via the `extra_model_paths.yaml` configuration file

### Open Config File

<Tabs>
  <Tab title="Portable/Manual Install">
    For the ComfyUI version such as [portable](/installation/comfyui_portable_windows) and [manual](/installation/manual_install), you can find an example file named `extra_model_paths.yaml.example` in the root directory of ComfyUI:

    ```
    ComfyUI/extra_model_paths.yaml.example
    ```

    Copy and rename it to `extra_model_paths.yaml` for use. Keep it in ComfyUI's root directory at `ComfyUI/extra_model_paths.yaml`.
    You can also find the config example file [here](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example)
  </Tab>

  <Tab title="Comfy Desktop">
    If you are using the [Comfy Desktop](/installation/desktop/windows) application, click the capsule menu at the top of the desktop app, then open the **Storage** tab and add your model directories there. The capsule only exists in the desktop app, not when ComfyUI runs in a browser.

    <img alt="Comfy Desktop capsule menu: Storage tab showing model directory settings" />

    Or open it directly at:

    <Tabs>
      <Tab title="Windows">
        ```
        C:\Users\YourUsername\AppData\Roaming\ComfyUI\extra_models_config.yaml
        ```
      </Tab>

      <Tab title="macOS">
        ```
        ~/Library/Application Support/ComfyUI/extra_models_config.yaml
        ```
      </Tab>
    </Tabs>

    You should keep the file in the same directory, should not move these files to other places.
  </Tab>
</Tabs>

If the file does not exist, you can create it yourself with any text editor.

### Example Structure

Suppose you want to add the following model paths to ComfyUI:

```
📁 YOUR_PATH/
  ├── 📁models/
  |   ├── 📁 loras/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 checkpoints/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 vae/
  |   │   └── xxxxx.safetensors
  |   └── 📁 controlnet/
  |       └── xxxxx.safetensors
```

Then you can configure the `extra_model_paths.yaml` file like below to let ComfyUI recognize the model paths on your device:

```
my_custom_config:
    base_path: YOUR_PATH
    loras: models/loras/
    checkpoints: models/checkpoints/
    vae: models/vae/
    controlnet: models/controlnet/
```

or

```
my_custom_config:
    base_path: YOUR_PATH/models/
    loras: loras
    checkpoints: checkpoints
    vae: vae
    controlnet: controlnet
```

<Warning>
  For the desktop version, please add the configuration to the existing configuration path without overwriting the path configuration generated during installation. Please back up the corresponding file before modification, so that you can restore it when you make a mistake.
</Warning>

Or you can refer to the default [extra\_model\_paths.yaml.example](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example) for more configuration options. After saving, you need to **restart ComfyUI** for the changes to take effect.

Below is the original config example:

```yaml theme={null}
#Rename this to extra_model_paths.yaml and ComfyUI will load it


#config for a1111 ui
#all you have to do is change the base_path to where yours is installed
a111:
    base_path: path/to/stable-diffusion-webui/

    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet

#config for comfyui
#your base path should be either an existing comfy install or a central folder where you store all of your models, loras, etc.

#comfyui:
#     base_path: path/to/comfyui/
#     # You can use is_default to mark that these folders should be listed first, and used as the default dirs for eg downloads
#     #is_default: true
#     checkpoints: models/checkpoints/
#     clip: models/clip/
#     clip_vision: models/clip_vision/
#     configs: models/configs/
#     controlnet: models/controlnet/
#     diffusion_models: |
#                  models/diffusion_models
#                  models/unet
#     embeddings: models/embeddings/
#     loras: models/loras/
#     upscale_models: models/upscale_models/
#     vae: models/vae/

#other_ui:
#    base_path: path/to/ui
#    checkpoints: models/checkpoints
#    gligen: models/gligen
#    custom_nodes: path/custom_nodes

```

For example, if your WebUI is located at `D:\stable-diffusion-webui\`, you can modify the corresponding configuration to

```yaml theme={null}
a111:
    base_path: D:\stable-diffusion-webui\
    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet
```

### Add Extra Custom Nodes Path

Besides adding external models, you can also add custom nodes paths that are not in the default path of ComfyUI

<Tip>
  Please note that this will not change the default installation path of custom nodes, but will add an extra path search when starting ComfyUI. You still need to complete the installation of custom node dependencies in the corresponding environment to ensure the integrity of the running environment.
</Tip>

Below is a simple configuration example (MacOS), please modify it according to your actual situation and add it to the corresponding configuration file, save it and restart ComfyUI for the changes to take effect:

```yaml theme={null}
my_custom_nodes:
  custom_nodes: /Users/your_username/Documents/extra_custom_nodes
```

## FAQ

<Note>
  **Docker:** ComfyUI does not provide an official Docker image. If you want to run ComfyUI in a container, search [Docker Hub](https://hub.docker.com) for community-maintained images. Note that **none of these are official ComfyUI images**, and they are not supported by the ComfyUI team. Use them at your own risk.
</Note>

### How to Stop/Exit ComfyUI

Press **Ctrl+C** in the terminal window where ComfyUI is running, or simply close the terminal window.


# System Requirements
Source: https://docs.comfy.org/installation/system_requirements

Hardware and software requirements for installing and running ComfyUI.

In this guide, we will introduce the system requirements for installing ComfyUI. Due to frequent updates of ComfyUI, this document may not be updated in a timely manner. Please refer to the relevant instructions in [ComfyUI](https://github.com/Comfy-Org/ComfyUI).

Regardless of which version of ComfyUI you use, it runs in a separate Python environment.

### Supported Operating Systems

Currently, we support the following operating systems:

* Windows
* Linux
* macOS (supports Apple Silicon, such as the M series)

See the links below for installation instructions specific to your OS and setup.

<AccordionGroup>
  <Accordion title="Comfy Desktop">
    Comfy Desktop supports standalone installation on **Windows**, **macOS (Apple Silicon)**, and **Linux** (AppImage and `.deb`).

    * Source is on [GitHub](https://github.com/Comfy-Org/Comfy-Desktop)

    <Tip>
      Desktop installs track the **stable** ComfyUI release by default. If you want every latest commit, use the portable version or a manual git install, or switch the instance update channel to **Latest on GitHub**.
    </Tip>

    You can choose the appropriate installation for your system and hardware below

    <Tabs>
      <Tab title="Windows">
        <Card title="Comfy Desktop (Windows) Installation Guide" icon="link" href="/installation/desktop/windows">
          Suitable for **Windows** 10 or later. NVIDIA or AMD GPU recommended.
        </Card>
      </Tab>

      <Tab title="macOS (Apple Silicon)">
        <Card title="Comfy Desktop (macOS) Installation Guide" icon="link" href="/installation/desktop/macos">
          Suitable for macOS with **Apple Silicon**
        </Card>
      </Tab>

      <Tab title="Linux">
        <Card title="Comfy Desktop (Linux) Installation Guide" icon="link" href="/installation/desktop/linux">
          Install the AppImage or `.deb`, or build and run from source.
        </Card>
      </Tab>
    </Tabs>
  </Accordion>

  <Accordion title="ComfyUI Portable (Windows)">
    Portable version is a ComfyUI version that integrates an independent embedded Python environment, using the portable version you can experience the latest features, currently only supports **Windows** system

    <Card title="ComfyUI Portable (Windows) Installation Guide" icon="link" href="/installation/comfyui_portable_windows">
      Supports **Windows** ComfyUI version running on **Nvidia GPUs** or **CPU-only**, always use the latest commits and completely portable.
    </Card>
  </Accordion>

  <Accordion title="Manual Installation">
    <Card title="ComfyUI Manual Installation Guide" icon="link" href="/installation/manual_install">
      Supports all system types and GPU types (Nvidia, AMD, Intel, Apple Silicon, Ascend NPU, Cambricon MLU)
    </Card>
  </Accordion>
</AccordionGroup>

### Python Version

* **Python 3.13** is very well supported and recommended
* Python 3.14 works but some custom nodes may have issues. The free threaded variant works but some dependencies will enable the GIL so it's not fully supported
* Python 3.12 is a good fallback if you have trouble with some custom node dependencies on 3.13

### Browser Requirements

For the best experience, use **Google Chrome version 143 or later**. Earlier versions of Chrome (142 and below) have known issues that can cause visual glitches and performance problems in ComfyUI.

### Supported Hardware

* **NVIDIA GPU** - Install stable pytorch with CUDA 13.0: `pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu130`
* **AMD GPU (Linux)** - ROCm 7.2 stable or nightly
* **AMD GPU (Windows)** - ROCm 10.0 via AMD multi-architecture PyTorch packages. Supports RDNA 2, RDNA 3, RDNA 3.5, and RDNA 4; no separate HIP SDK installation needed
* **Intel GPU** - Arc series with native PyTorch torch.xpu support
* **Apple Silicon** - M1/M2/M3/M4 series with Metal acceleration
* **Ascend NPU** - Via torch\_npu extension
* **Cambricon MLU** - Via torch\_mlu extension
* **Iluvatar Corex** - Via Iluvatar Extension for PyTorch
* **CPU** - Use the `--cpu` parameter (slower)

Please refer to the [ComfyUI Windows and Linux manual installation section](https://github.com/Comfy-Org/ComfyUI?tab=readme-ov-file#manual-install-windows-linux) for detailed installation steps.

<Note>
  PyTorch 2.7 and above is supported, but using a newer version is strongly recommended. A cu130 or above version of PyTorch is required on Nvidia 20 series and above. Some features and optimizations might only work on newer versions. We generally recommend using the latest major version of PyTorch with the latest CUDA version unless it is less than 2 weeks old.

  The Windows portable build currently comes with Python 3.13 and PyTorch CUDA 13.0. Update your Nvidia drivers if it doesn't start.
</Note>

### Dependencies

* Install PyTorch (version specific to your hardware)
* Install all dependencies in the requirements.txt of ComfyUI: `pip install -r requirements.txt`

<Card title="Manual Installation" icon="book" href="/installation/manual_install">
  Please refer to the manual installation section for detailed installation steps.
</Card>

## FAQ

<Accordion title="Does ComfyUI support MLX (Apple's machine learning framework)?">
  ComfyUI does not use MLX directly. On Apple Silicon (M1/M2/M3/M4) Macs, ComfyUI uses PyTorch with the **MPS (Metal Performance Shaders)** backend, which leverages Apple's Metal graphics framework for GPU acceleration.

  MLX is a separate machine-learning array framework designed for Apple Silicon. ComfyUI's PyTorch-based architecture uses MPS instead.

  To verify MPS is working on your Mac:

  ```bash theme={null}
  python -c "import torch; print(torch.backends.mps.is_available())"
  ```
</Accordion>

<Note>
  **Docker:** ComfyUI does not provide an official Docker image. If you want to run ComfyUI in a container, search [Docker Hub](https://hub.docker.com) for community-maintained images. Note that **none of these are official ComfyUI images**, and they are not supported by the ComfyUI team. Use them at your own risk.
</Note>


# How to Update ComfyUI
Source: https://docs.comfy.org/installation/update_comfyui

Update ComfyUI on any install type: Portable update scripts, Desktop updates, and git pull for manual installs, plus fixes for common update issues.

While we've covered ComfyUI updates across different installation methods in various sections, this comprehensive guide consolidates all update procedures to help users clearly understand how to update ComfyUI.

## How to Update ComfyUI?

<Tabs>
  <Tab title="Portable">
    ComfyUI Portable provides convenient batch scripts for easy updates.

    ### Update Script Location

    In the `update` folder within your portable installation directory, you'll find the following update scripts:

    ```
    ComfyUI_windows_portable
    └─ 📂update
       ├── update.py
       ├── update_comfyui.bat                           // Update to latest development version
       ├── update_comfyui_stable.bat                    // Update to latest stable version
       └── update_comfyui_and_python_dependencies.bat   // ⚠️ DANGER: Reinstalls dependencies - may cause conflicts
    ```

    <Warning>Ensure a stable internet connection during updates.</Warning>

    <Warning>
      **⚠️ DANGER: Use `update_comfyui_and_python_dependencies.bat` with extreme caution!**

      This script is more thorough than regular updates and will:

      * ✅ Update ComfyUI code itself
      * ✅ Update PyTorch (for NVIDIA GPU CUDA 12.9)
      * ✅ Reinstall ALL Python dependencies

      **Risks:**

      * May cause dependency conflicts with your existing setup
      * Can break custom nodes that rely on specific package versions
      * May overwrite manually configured packages

      **⚠️ Only use this script when:**

      * You need to fix dependency issues
      * Performing major version updates
      * For daily updates, use `update_comfyui.bat` instead

      **Before running this script:**

      1. **Back up your entire ComfyUI installation**
      2. Document any custom package versions you've installed
      3. Be prepared to reinstall custom nodes if needed
    </Warning>
  </Tab>

  <Tab title="Desktop">
    Comfy Desktop uses Comfy Engine as a package manager to manage ComfyUI. To update the ComfyUI engine, open the [Manage panel](/installation/desktop/usage/manage#update-tab) and use the Update tab. You can choose between **Stable** (default) and **Latest on GitHub** update channels.

    The Desktop app itself updates automatically and is separate from ComfyUI engine updates.
  </Tab>

  <Tab title="Manual Installation">
    Manually installed ComfyUI requires Git commands to complete updates.

    ### Pre-Update Requirements

    Ensure your system has [Git](https://git-scm.com/downloads) installed and ComfyUI was installed via Git clone.

    ### Update Steps

    <Steps>
      <Step title="Activate Virtual Environment">
        First, activate ComfyUI's Python virtual environment (if using one):

        ```bash theme={null}
        # For conda environment
        conda activate comfyui

        # For venv environment
        # Windows
        venv\Scripts\activate
        # macOS/Linux  
        source venv/bin/activate
        ```
      </Step>

      <Step title="Pull Latest Code">
        Navigate to your ComfyUI installation directory and pull the latest code:

        ```bash theme={null}
        cd <ComfyUI-installation-path>
        git pull
        ```
      </Step>

      <Step title="Update Dependencies">
        Install or update ComfyUI's dependency packages:

        ```bash theme={null}
        pip install -r requirements.txt
        ```

        <Warning>
          Ensure you're in ComfyUI's virtual environment to avoid contaminating the system-level Python environment
        </Warning>
      </Step>

      <Step title="Restart ComfyUI">
        After updating, restart ComfyUI:

        ```bash theme={null}
        python main.py
        ```
      </Step>
    </Steps>

    ### Version Switching (Optional)

    To switch to a specific version, use these commands:

    ```bash theme={null}
    # View commit history
    git log --oneline

    # Switch to specific commit
    git checkout <commit-hash>

    # Return to latest version
    git checkout master
    ```

    <Tip>Regular updates are recommended for the latest features and security fixes, while stable versions are recommended for system stability</Tip>
  </Tab>
</Tabs>

## ComfyUI Version Types

Depending on your installation method, ComfyUI offers several installation versions. The links below contain update instructions for each version.

<AccordionGroup>
  <Accordion title="Comfy Desktop">
    Comfy Desktop supports standalone installation on **Windows**, **macOS (Apple Silicon)**, and **Linux** (AppImage and `.deb`).

    * Source is on [GitHub](https://github.com/Comfy-Org/Comfy-Desktop)

    <Tip>
      Desktop installs track the **stable** ComfyUI release by default. If you want every latest commit, use the portable version or a manual git install, or switch the instance update channel to **Latest on GitHub**.
    </Tip>

    You can choose the appropriate installation for your system and hardware below

    <Tabs>
      <Tab title="Windows">
        <Card title="Comfy Desktop (Windows) Installation Guide" icon="link" href="/installation/desktop/windows">
          Suitable for **Windows** 10 or later. NVIDIA or AMD GPU recommended.
        </Card>
      </Tab>

      <Tab title="macOS (Apple Silicon)">
        <Card title="Comfy Desktop (macOS) Installation Guide" icon="link" href="/installation/desktop/macos">
          Suitable for macOS with **Apple Silicon**
        </Card>
      </Tab>

      <Tab title="Linux">
        <Card title="Comfy Desktop (Linux) Installation Guide" icon="link" href="/installation/desktop/linux">
          Install the AppImage or `.deb`, or build and run from source.
        </Card>
      </Tab>
    </Tabs>
  </Accordion>

  <Accordion title="ComfyUI Portable (Windows)">
    Portable version is a ComfyUI version that integrates an independent embedded Python environment, using the portable version you can experience the latest features, currently only supports **Windows** system

    <Card title="ComfyUI Portable (Windows) Installation Guide" icon="link" href="/installation/comfyui_portable_windows">
      Supports **Windows** ComfyUI version running on **Nvidia GPUs** or **CPU-only**, always use the latest commits and completely portable.
    </Card>
  </Accordion>

  <Accordion title="Manual Installation">
    <Card title="ComfyUI Manual Installation Guide" icon="link" href="/installation/manual_install">
      Supports all system types and GPU types (Nvidia, AMD, Intel, Apple Silicon, Ascend NPU, Cambricon MLU)
    </Card>
  </Accordion>
</AccordionGroup>

## What Needs to Be Updated When Updating ComfyUI?

ComfyUI updates primarily consist of two components:

1. Update ComfyUI's core code
2. Update ComfyUI's core dependencies, including necessary Python dependencies and ComfyUI functional dependency packages

**Core Code**: New nodes, new model support, new features, etc.
**Core Dependencies**: Mainly includes ComfyUI's frontend functionality, workflow templates, node help documentation, etc.

```
comfyui-frontend-package   # ComfyUI frontend functionality
comfyui-workflow-templates # ComfyUI workflow templates  
comfyui-embedded-docs      # ComfyUI node help documentation
comfy-kitchen              # ComfyUI core utilities
comfy-aimdo                # ComfyUI core utilities
```

These core dependencies are maintained in separate repositories:

* [ComfyUI\_frontend](https://github.com/Comfy-Org/ComfyUI_frontend/) - Frontend interface and interactive features
* [workflow\_templates](https://github.com/Comfy-Org/workflow_templates) - Pre-built workflow templates
* [comfyui-embedded-docs](https://github.com/Comfy-Org/embedded-docs) - Node help documentation
* [comfy-kitchen](https://github.com/Comfy-Org/comfy-kitchen) - Fast kernel library for Diffusion inference with multiple compute backends
* [comfy-aimdo](https://github.com/Comfy-Org/comfy-aimdo) - AI Model Demand Offloading Allocator

It's important to understand the difference between development (nightly) and stable (release) versions:

* **Development version (nightly)**: Latest commit code, giving you access to the newest features, but may contain potential issues
* **Stable version (release)**: Built on stable releases, usually lags behind development versions but offers higher stability. We support stable versions after features are tested and stabilized

Many users often find themselves on release versions or desktop versions during updates, but discover that needed features are only available in development versions. In such cases, check if your local `ComfyUI/requirements.txt` matches the [nightly version dependencies](https://github.com/Comfy-Org/ComfyUI/blob/master/requirements.txt) to determine if all dependencies support the latest features.

## Common Update Issues

### Missing or Outdated Frontend, Workflow Templates, Node  After Updates

<Tabs>
  <Tab title="Dependencies Not Properly Updated">
    Users often only use the `git pull` command to update ComfyUI code but **neglect core dependency updates**, leading to the following issues:

    * Missing or abnormal frontend functionality
    * Cannot find newly added workflow templates
    * Outdated or missing node help documentation
    * New features lack corresponding frontend support

    After using the `git pull` command, use the corresponding ComfyUI environment to use `pip install -r requirements.txt` to update dependencies.
  </Tab>

  <Tab title="Dependency Update Failures">
    If dependency updates fail, it's commonly due to network or computer permission issues. When core dependency failures occur during updates, the system falls back to older versions. You'll typically see logs like this during startup:

    ```
    Falling back to the default frontend.
    ComfyUI frontend version: xxx
    ```

    Follow these troubleshooting steps:

    1. Use `pip list` in the appropriate environment to view currently installed dependency packages. If you find version inconsistencies, use `pip install -r requirements.txt` in the ComfyUI environment to attempt dependency updates again.
    2. If issues persist after updating, check your network connection. Users in mainland China may need to configure a proxy to reliably access GitHub repositories.
    3. If problems continue, check computer permissions. If administrator privileges are required, run the command line with administrator rights.
  </Tab>
</Tabs>

### How to Properly Update Core Dependencies

<Tabs>
  <Tab title="Portable">
    **Recommended Method**: Use the `ComfyUI_windows_portable\update\update_comfyui.bat` batch script, which will update both ComfyUI code and all Python dependencies.

    **Manual Dependency Update**:
    If you need to manually update dependencies, use the following command:

    ```bash theme={null}
    # Open command line in portable version directory
    .\python_embeded\python.exe -m pip install -r ComfyUI\requirements.txt
    ```
  </Tab>

  <Tab title="Manual Installation">
    <Steps>
      <Step title="Activate Python Environment">
        If you use Conda to manage Python environments, activate your environment first:

        ```bash theme={null}
        conda activate comfyui  # or other environment name
        ```
      </Step>

      <Step title="Update Code">
        Navigate to the ComfyUI root directory and update the code using Git:

        ```
        cd <ComfyUI_ROOT_PATH>
        git pull
        ```
      </Step>

      <Step title="Update Dependencies">
        Update ComfyUI dependencies - this step is crucial, especially for the `comfyui-frontend-package`:

        ```
        pip install -r requirements.txt
        ```
      </Step>
    </Steps>
  </Tab>

  <Tab title="Desktop">
    Desktop version usually handles dependency updates automatically. If you encounter issues:

    1. **Check if auto-update** is enabled
    2. **Manually trigger update**: Menu → Help → Check for Updates
    3. **Reinstall desktop version** (in extreme cases)
  </Tab>
</Tabs>

### Core Dependency Update Troubleshooting

If core dependency updates fail, follow these troubleshooting steps:

<Steps>
  <Step title="Check Network Connection">
    If located in mainland China, ensure you can access PyPI or configure a domestic mirror:

    ```bash theme={null}
    # Using Tsinghua University mirror
    pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
    ```
  </Step>

  <Step title="Install Core Packages Individually">
    If batch installation fails, try installing packages individually. **First check version requirements in `ComfyUI/requirements.txt`**:

    **Then install according to specified versions (use version numbers from your requirements.txt):**

    ```bash theme={null}
    pip install comfyui-frontend-package==<version> 
    pip install comfyui-workflow-templates==<version>
    pip install comfyui-embedded-docs==<version>
    pip install comfy-kitchen==<version>
    pip install comfy-aimdo==<version>
    ```

    <Warning>
      It's recommended to use the exact version numbers specified in `ComfyUI/requirements.txt`. Don't upgrade to the latest versions independently, as this may cause compatibility issues.
    </Warning>
  </Step>
</Steps>

### Why Can't I Find New Features After Updating?

This is one of the most common issues:

* If you're using the **Desktop version**, features may lag behind because the desktop version is built on stable releases
* Ensure you're using the **development version (nightly)**, not the **stable version (release)**

Additionally, ensure that corresponding dependencies have been successfully updated during the update process. If issues persist after updating, refer to the [Dependency Update Troubleshooting](#core-dependency-update-troubleshooting) section to diagnose problems.

### How to Switch Between Development (Nightly) and Stable (Release) Versions?

Differences between versions:

<Tabs>
  <Tab title="Development Version (Nightly)">
    * **Characteristics**: Contains the latest commit code
    * **Advantages**: Experience the latest features and improvements first
    * **Risks**: May contain undiscovered bugs or unstable factors
    * **Suitable for**: Developers, testers, users wanting to experience the latest features
  </Tab>

  <Tab title="Stable Version (Release)">
    * **Characteristics**: Tested and verified stable code
    * **Advantages**: High stability, suitable for production environments
    * **Disadvantages**: Feature updates have delays, may lag behind development versions by weeks or months
    * **Suitable for**: Users requiring stability, production environment users
  </Tab>
</Tabs>

<Tabs>
  <Tab title="Portable">
    Use `update_comfyui.bat` instead of `update_comfyui_stable.bat`:

    ```
    # Development version (latest features)
    double-click: update_comfyui.bat

    # Stable version
    double-click: update_comfyui_stable.bat
    ```
  </Tab>

  <Tab title="Manual Installation">
    ```bash theme={null}
    # Switch to development version
    git checkout master
    git pull

    # Switch to latest stable version
    git fetch --tags
    git checkout $(git describe --tags `git rev-list --tags --max-count=1`)
    ```
  </Tab>

  <Tab title="Desktop">
    Desktop version is typically built on stable releases and doesn't currently support version switching. If you need the latest features, we recommend:

    1. Wait for desktop version updates
    2. Or use portable/manual installation to experience the latest features
  </Tab>
</Tabs>

### What to Do When Errors Occur After Updates?

1. **Check Dependencies**: Run `pip install -r requirements.txt` to ensure all dependencies are updated
2. **Check Custom Nodes**: Some custom nodes may be incompatible with new versions
3. **Roll Back Version**: If issues are severe, you can roll back to a previous stable version

If problems occur, refer to our troubleshooting page for solutions.

<Card title="Troubleshooting" icon="bug" href="/troubleshooting/overview">
  Learn how to troubleshoot ComfyUI issues
</Card>

### How to Stay Updated on New Features?

* **GitHub Releases**: Check [ComfyUI Releases](https://github.com/Comfy-Org/ComfyUI/releases) for stable version updates
* **GitHub Commits**: View [latest commits](https://github.com/Comfy-Org/ComfyUI/commits/master) to understand development progress
* **Community Discussion**: Follow our [blog](https://blog.comfy.org) and [Twitter](https://x.com/comfyui) for the latest updates


# ComfyUI APP mode guide
Source: https://docs.comfy.org/interface/app-mode

Learn how to build and use APP mode in ComfyUI to simplify workflow interaction by defining custom input/output interfaces.

APP mode simplifies workflow interaction by allowing you to define custom input/output interfaces, making it easier to share and use workflows without editing nodes.

<iframe title="ComfyUI APP Mode Guide" />

<Note>
  APP mode is officially supported from ComfyUI front-end version 1.41.13. Earlier versions are in early test phase.
</Note>

## Enter APP mode

There are two ways to enter APP mode: click the top-left icon (**1**) and select **Enter app mode** from the dropdown, or use the breadcrumb navigation dropdown (**2**) at the top of the interface.

<img alt="Enter APP mode via top-left menu" />

1. Click the top-left icon (marked **1**) to open the dropdown menu and select **Enter app mode**.
2. Alternatively, use the breadcrumb navigation dropdown (marked **2**) at the top to enter APP mode.

## Build an APP mode workflow

<iframe title="How to Create APP Mode Workflows" />

If the workflow has never been configured for APP mode, entering APP mode will automatically open the APP mode builder.

<img alt="APP mode builder entry screen" />

1. If the workflow has no existing APP mode configuration, the APP mode builder opens by default.
2. Click **Build app** to enter the APP builder and start configuring.

### Step 1: Select inputs

The builder interface displays four guided steps (marked **1**, **2**, **3**, **4**) at the top. The bottom bar lets you exit the builder or navigate between steps.

<img alt="APP builder interface overview" />

1. The numbers **1 2 3 4** at the top correspond to the four build steps: selecting inputs, selecting outputs, previewing, and setting the default view.
2. The buttons at the bottom let you exit the builder or move between steps.
3. Areas marked in the canvas are selectable input/output parameters.
4. The right panel shows a live preview of the current configuration.

Click the **Inputs** step at the top. The canvas highlights selectable input nodes. Click a node to select it as an input parameter — options include image uploads, text prompt inputs, and model selection. Selected parameters appear in the right sidebar.

### Step 2: Select outputs

Click the **Outputs** step. Choose which output nodes to display in the APP, such as a Preview node or Save Image node.

<img alt="Selecting output nodes with right-panel preview" />

1. Select the output nodes to display in the APP.
2. Similar to inputs, the right sidebar displays a live preview of the selected output nodes.

### Step 3: Preview

Click the **Preview** step to review the final APP layout. The selected inputs appear on the right panel, and the output area is shown in the canvas.

<img alt="Preview mode showing input and output layout" />

1. This is the preview mode — check that all input and output configurations appear as expected.
2. If any adjustments are needed, click **Back** to return to the previous step.

### Step 4: Set a default view

Click the **Set a default view** step. Choose whether the workflow should open in **App** mode or **Node Graph** mode by default. Click **Apply** to confirm.

<img alt="Set default view step with App/Node Graph options" />

1. Choose whether the workflow defaults to **App** mode or **Node Graph** mode when opened.
2. Select **App** and click **Apply** to confirm. The workflow will then open in APP mode by default.

After applying, a confirmation prompt will appear.

<img alt="Confirmation prompt with View app button" />

Click **View app** to enter APP mode and start using the workflow.

## Use APP mode

In APP mode, the right panel shows all configured input options. Adjust the inputs as needed, then click **Run** to execute the workflow.

<img alt="APP mode interface with inputs panel and Run button" />

1. The right **Input** panel lets you adjust input parameters before running.
2. Click **Run** to execute the workflow.
3. The left sidebar provides additional controls, such as rebuilding the APP, viewing assets, and opening the workflow panel.

APP mode is also optimized for mobile and narrow-screen layouts. The interface adapts into a tab-based view, letting you switch between the input panel, output view, and Media Assets panel.

<img alt="APP mode mobile layout with inputs, outputs, and assets tabs" />

While running, a **Cancel this run** button appears at the top to stop the current execution.

<img alt="Running state with cancel option and results panel" />

1. Click **Cancel this run** at the top to stop the current run.
2. Switch between the queue view and the results view in the bottom panel.
3. Click the relevant area to open the assets panel.

## Save and share the workflow

### Save workflow

Use `Ctrl + S` (or `Cmd + S` on Mac) to save the workflow for future use.

Click the left sidebar button to open the saved workflows panel.

<img alt="Left sidebar showing saved APP workflows" />

1. Click the left sidebar button to open the panel, which displays all saved APP workflows.
2. Switch between saved APP workflows from this panel.

### Share workflow

<iframe title="How to Share Workflows" />

In APP mode, click the **Share** button in the left sidebar. If the workflow has not been saved yet, a dialog will prompt you to save it first before a link can be created.

<img alt="Share dialog prompting to save the workflow" />

1. Click the Share button in the left sidebar to open the Share dialog.
2. If the workflow is unsaved, enter a workflow name and click **Save workflow** to continue.

Once saved, the Share dialog shows the option to generate a link.

<img alt="Share dialog with Create a link button" />

Click **Create a link** to generate a shareable URL for the workflow.

<img alt="Share dialog showing the generated link with Copy button" />

Click **Copy** to copy the link. Recipients can open it and run the workflow directly — the full workflow configuration is included in the link.

<Note>
  Share links are only supported on Comfy Cloud.
</Note>


# Customizing ComfyUI Appearance
Source: https://docs.comfy.org/interface/appearance

Learn how to customize the appearance of ComfyUI using color palettes and advanced CSS options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

ComfyUI offers flexible appearance customization options that allow you to personalize the interface to your preferences.

## Color Palette System

The primary way to customize ComfyUI's appearance is through the built-in color palette system.

<img alt="Color Palette" />

This allows you to:

1. Switch ComfyUI themes
2. Export the currently selected theme as JSON format
3. Load custom theme configuration from JSON file
4. Delete custom theme configuration

<Note>
  For appearance needs that cannot be satisfied by the color palette, you can perform advanced appearance customization through the [user.css](#advanced-customization-with-user-css) file
</Note>

### How to Customize Color Themes

The color palette allows you to modify many specific properties. Here are some of the most commonly customized elements, with colors represented in hexadecimal format:

<Tip>
  1. The JSON comments below are for illustration only. Do not copy the content below for modification as it will cause the theme to malfunction.
  2. Since we are still iterating frequently, the content below may change with ComfyUI frontend updates. If you need to modify, please export the theme configuration from settings and then modify it.
</Tip>

```json theme={null}
{
  "id": "dark",                     // Must be unique, cannot be the same as other theme IDs
  "name": "Dark (Default)",         // Theme name, displayed in theme selector
  "colors": {
    "node_slot": {                  // Node connection slot color configuration
      "CLIP": "#FFD500",            // CLIP model connection slot color
      "CLIP_VISION": "#A8DADC",     // CLIP Vision model connection slot color
      "CLIP_VISION_OUTPUT": "#ad7452", // CLIP Vision output connection slot color
      "CONDITIONING": "#FFA931",     // Conditioning control connection slot color
      "CONTROL_NET": "#6EE7B7",     // ControlNet model connection slot color
      "IMAGE": "#64B5F6",           // Image data connection slot color
      "LATENT": "#FF9CF9",          // Latent space connection slot color
      "MASK": "#81C784",            // Mask data connection slot color
      "MODEL": "#B39DDB",           // Model connection slot color
      "STYLE_MODEL": "#C2FFAE",     // Style model connection slot color
      "VAE": "#FF6E6E",             // VAE model connection slot color
      "NOISE": "#B0B0B0",           // Noise data connection slot color
      "GUIDER": "#66FFFF",          // Guider connection slot color
      "SAMPLER": "#ECB4B4",         // Sampler connection slot color
      "SIGMAS": "#CDFFCD",          // Sigmas data connection slot color
      "TAESD": "#DCC274"            // TAESD model connection slot color
    },
    "litegraph_base": {             // LiteGraph base interface configuration
      "BACKGROUND_IMAGE": "",        // Background image, default is empty
      "CLEAR_BACKGROUND_COLOR": "#222", // Main canvas background color
      "NODE_TITLE_COLOR": "#999",    // Node title text color
      "NODE_SELECTED_TITLE_COLOR": "#FFF", // Selected node title color
      "NODE_TEXT_SIZE": 14,          // Node text size
      "NODE_TEXT_COLOR": "#AAA",     // Node text color
      "NODE_TEXT_HIGHLIGHT_COLOR": "#FFF", // Node text highlight color
      "NODE_SUBTEXT_SIZE": 12,       // Node subtext size
      "NODE_DEFAULT_COLOR": "#333",   // Node default color
      "NODE_DEFAULT_BGCOLOR": "#353535", // Node default background color
      "NODE_DEFAULT_BOXCOLOR": "#666", // Node default border color
      "NODE_DEFAULT_SHAPE": 2,        // Node default shape
      "NODE_BOX_OUTLINE_COLOR": "#FFF", // Node border outline color
      "NODE_BYPASS_BGCOLOR": "#FF00FF", // Node bypass background color
      "NODE_ERROR_COLOUR": "#E00",    // Node error state color
      "DEFAULT_SHADOW_COLOR": "rgba(0,0,0,0.5)", // Default shadow color
      "DEFAULT_GROUP_FONT": 24,       // Group default font size
      "WIDGET_BGCOLOR": "#222",       // Widget background color
      "WIDGET_OUTLINE_COLOR": "#666", // Widget outline color
      "WIDGET_TEXT_COLOR": "#DDD",    // Widget text color
      "WIDGET_SECONDARY_TEXT_COLOR": "#999", // Widget secondary text color
      "WIDGET_DISABLED_TEXT_COLOR": "#666", // Widget disabled state text color
      "LINK_COLOR": "#9A9",          // Connection line color
      "EVENT_LINK_COLOR": "#A86",    // Event connection line color
      "CONNECTING_LINK_COLOR": "#AFA", // Connecting line color
      "BADGE_FG_COLOR": "#FFF",      // Badge foreground color
      "BADGE_BG_COLOR": "#0F1F0F"    // Badge background color
    },
    "comfy_base": {                  // ComfyUI base interface configuration
      "fg-color": "#fff",            // Foreground color
      "bg-color": "#202020",         // Background color
      "comfy-menu-bg": "#353535",    // Menu background color
      "comfy-menu-secondary-bg": "#303030", // Secondary menu background color
      "comfy-input-bg": "#222",      // Input field background color
      "input-text": "#ddd",          // Input text color
      "descrip-text": "#999",        // Description text color
      "drag-text": "#ccc",           // Drag text color
      "error-text": "#ff4444",       // Error text color
      "border-color": "#4e4e4e",     // Border color
      "tr-even-bg-color": "#222",    // Table even row background color
      "tr-odd-bg-color": "#353535",  // Table odd row background color
      "content-bg": "#4e4e4e",       // Content area background color
      "content-fg": "#fff",          // Content area foreground color
      "content-hover-bg": "#222",    // Content area hover background color
      "content-hover-fg": "#fff",    // Content area hover foreground color
      "bar-shadow": "rgba(16, 16, 16, 0.5) 0 0 0.5rem" // Bar shadow effect
    }
  }
}
```

## Canvas

### Background Image

* **Requirements**: ComfyUI frontend version 1.20.5 or newer
* **Function**: Set a custom background image for the canvas to provide a more personalized workspace. You can upload images or use web images to set the background for the canvas.

<img alt="Set Background Image" />

## Node

### Node Opacity

* **Function**: Set the opacity of nodes, where 0 represents completely transparent and 1 represents completely opaque.

<img alt="Node Opacity" />

## Node Widget

### Textarea Widget Font Size

* **Range**: 8 - 24
* **Function**: Set the font size in textarea widgets. Adjusts the text display size in text input boxes to improve readability.

<img alt="Textarea Widget Font Size" />

## Sidebar

### Unified Sidebar Width

* **Function**: When enabled, the sidebar width will be unified to a consistent width when switching between different sidebars. If disabled, different sidebars can maintain their custom widths when switching.

### Sidebar Size

* **Function**: Control the size of the sidebar, can be set to normal or small.

### Sidebar Location

* **Function**: Control whether the sidebar is displayed on the left or right side of the interface, allowing users to adjust the sidebar position according to their usage habits.

### Sidebar Style

* **Function**: Control the visual style of the sidebar. Options include:
  * **Connected**: The sidebar appears connected to the edge of the interface.
  * **Floating**: The sidebar appears as a floating panel with visual separation from the interface edge.

<img alt="Sidebar Style" />

## Tree Explorer

### Tree Explorer Item Padding

* **Function**: Set the padding of items in the tree explorer (sidebar panel), adjusting the spacing between items in the tree structure.

<img alt="Tree Explorer Item Padding" />

## Advanced Customization with user.css

For cases where the color palette doesn't provide enough control, you can use custom CSS via a user.css file. This method is recommended for advanced users who need to customize elements that aren't available in the color palette system.

### Requirements

* ComfyUI frontend version 1.20.5 or newer

### Setting Up user.css

1. Create a file named `user.css` in your ComfyUI user directory (same location as your workflows and settings - see location details below)
2. Add your custom CSS rules to this file
3. Restart ComfyUI or refresh the page to apply changes

### User Directory Location

The ComfyUI user directory is where your personal settings, workflows, and customizations are stored. The location depends on your installation type:

<Tabs>
  <Tab title="Desktop - Windows">
    ```
    C:\Users\<your username>\AppData\Roaming\ComfyUI\user
    ```
  </Tab>

  <Tab title="Desktop - macOS">
    ```
    ~/<ComfyUI installation path>/ComfyUI/user
    ```
  </Tab>

  <Tab title="Desktop - Linux">
    ```
    ~/.config/ComfyUI/user
    ```
  </Tab>

  <Tab title="Manual Install">
    The user directory is located in your ComfyUI installation folder:

    ```
    <ComfyUI installation path>/user
    ```

    For example, if you cloned ComfyUI to `C:\ComfyUI`, your user directory would be `C:\ComfyUI\user\default` (or `C:\ComfyUI\user\john` if you've set up a custom username).

    <Note>
      ComfyUI supports multiple users per installation. If you haven't configured a custom username, it defaults to "default". Each user gets their own subdirectory within the `user` folder.
    </Note>
  </Tab>

  <Tab title="Portable">
    The user directory is located in your ComfyUI portable folder:

    ```
    <ComfyUI_windows_portable>/ComfyUI/user
    ```

    For example: `ComfyUI_windows_portable/ComfyUI/user/default`

    <Note>
      ComfyUI supports multiple users per installation. If you haven't configured a custom username, it defaults to "default". Each user gets their own subdirectory within the `user` folder.
    </Note>
  </Tab>
</Tabs>

This location contains your workflows, settings, and other user-specific files.

After finding the above folder location, please copy the corresponding CSS file to the corresponding user directory, such as the default user folder being `ComfyUI/user/default`, then restart ComfyUI or refresh the page to apply changes.

### user.css Examples and Related Instructions

The `user.css` file is loaded early in the application startup process. So you may need to use `!important` in your CSS rules to ensure they override the default styles.

**user.css Customization Examples**

```css theme={null}
/* Increase font size in inputs and menus for better readability */
.comfy-multiline-input, .litecontextmenu .litemenu-entry {
    font-size: 20px !important;
}

/* Make context menu entries larger for easier selection */
.litegraph .litemenu-entry,
.litemenu-title {
  font-size: 24px !important; 
}

/* Custom styling for specific elements not available in the color palette */
.comfy-menu {
    border: 1px solid rgb(126, 179, 189) !important;
    border-radius: 0px 0px 0px 10px !important;
    backdrop-filter: blur(2px);
}
```

**Best Practices**

1. **Start with the color palette** for most customizations
2. Use **user.css only when necessary** for elements not covered by the color palette
3. **Export your theme** before making significant changes so you can revert if needed
4. **Share your themes** with the community to inspire others

**Troubleshooting**

* If your color palette changes don't appear, try refreshing the page
* If CSS customizations don't work, check that you're using frontend version 1.20.5+
* Try adding `!important` to user.css rules that aren't being applied
* Keep backups of your customizations to easily restore them


# Credits Management
Source: https://docs.comfy.org/interface/credits

Credits for Partner Nodes in ComfyUI: how to buy credits, track usage history, and monitor your balance from Settings > Credits.

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

The credit system was added to support the `Partner Nodes`, as calling closed-source AI models requires token consumption, so proper credit management is necessary. By default, the credits interface is not displayed. Please first log in to your ComfyUI account in `Settings` -> `User`, and then you can view your associated account's credit information in `Settings` -> `Credits`.

<img alt="ComfyUI Credits Interface" />

<Note>
  ComfyUI will always remain fully open-source and free for local users.
</Note>

## How to Purchase Credits?

Below is a demonstration video for purchasing credits:

<video />

Detailed steps are as follows:

<Steps>
  <Step title="Log in to your ComfyUI account">
    Log in to your ComfyUI account in `Settings` -> `User`

    <img alt="Login Interface" />
  </Step>

  <Step title="Go to `Settings` -> `Credits` to purchase credits">
    After logging in, you should see the `Credits` option added to the menu

    Go to `Settings` -> `Credits` to purchase credits

    <img alt="Credits Interface" />
  </Step>

  <Step title="Set the amount of credits to purchase">
    <img alt="Set Purchase Amount" />

    In the popup, set the purchase amount and click the `Buy` button
  </Step>

  <Step title="Make payment through Stripe">
    <img alt="Stripe Payment Page" />

    On the payment page, please follow these steps:

    1. Select the currency for payment
    2. Confirm that the email is the same as your ComfyUI registration email
    3. Choose your payment method

    * Credit Card
    * WeChat (only supported when paying in Comfy Credits)
    * Alipay (only supported when paying in Comfy Credits)

    4. Click the `Pay` button or the `Generate QR Code` button to complete the payment process
  </Step>

  <Step title="Complete payment and check your credit balance">
    <img alt="Payment Successful" />

    After completing the payment, please return to `Menu` -> `Credits` to check if your balance has been updated. Try refreshing the interface or restarting if necessary
  </Step>
</Steps>

## Frequently Asked Questions

<AccordionGroup>
  <Accordion title="Can credits go negative?">
    Credits are not intended to be used as a negative balance or credit line. However, due to race conditions where partner nodes don't always report costs before execution, a single execution may consume more credits than your remaining balance and temporarily result in a negative balance after completion. When your balance is negative, you will not be able to run Partner Nodes until you top up and restore a positive balance. Please ensure you have enough credits before making API calls.
  </Accordion>

  <Accordion title="Can I get a refund for unused credits?">
    Currently we do not support refunds for unused credits.
  </Accordion>

  <Accordion title="How do I check my current balance and usage?">
    Click on `Settings` -> `Credits` to see your current balance and access the `Credit History` entry
  </Accordion>

  <Accordion title="Can I share my credits with other users?">
    You can log into the same account on multiple devices, but we do not support sharing credits with other users
  </Accordion>

  <Accordion title="How can I know how much the node will cost?">
    Check the price badge on the API node to estimate the cost before running it. Actual costs can vary based on image size, generation quantity, and other parameters.
  </Accordion>

  <Accordion title="Why don't I see WeChat or Alipay payment options?">
    Please ensure you are paying in Comfy Credits, as WeChat and Alipay are only supported when paying in Comfy Credits
  </Accordion>

  <Accordion title="Do credits expire?">
    Yes, the expiration depends on the type of credits:

    * **Monthly credits**: Expire at the end of your billing period
    * **Top-up credits**: Expire 1 year from the date of purchase
  </Accordion>
</AccordionGroup>


# Node docs - View documentation for any node
Source: https://docs.comfy.org/interface/features/node-docs

Learn how to access built-in documentation for nodes in ComfyUI, including both built-in and custom nodes.

Node docs provide quick access to documentation for any node in your workflow. You can view detailed information about a node's functionality, parameters, and usage examples directly within ComfyUI.

## How to view node docs

<img alt="Node docs" />

1. **Select a node:**\
   Click on any node in your workflow to select it.

2. **Open node docs:**\
   Click the node info icon in the selection toolbox to open the node documentation page.

3. **Exit node docs:**\
   If you want to exit the node docs, you can click the arrow icon in the top left corner to exit the node docs.

## Built-in node documentation

Documentation for ComfyUI's built-in nodes is maintained in the [embedded-docs repository](https://github.com/Comfy-Org/embedded-docs).

**Contributing to built-in node docs:**

* Users can contribute improvements and additions to built-in node documentation
* Submit pull requests to the [embedded-docs repository](https://github.com/Comfy-Org/embedded-docs)
* Help improve documentation quality for the entire ComfyUI community

## Custom node documentation

Custom nodes can also include their own documentation. When custom node authors provide documentation, it will automatically appear in the node docs panel when you select their nodes.

<Card title="Developer guide: Adding node docs" icon="code" href="/custom-nodes/help_page">
  Learn how to create rich documentation for your custom nodes
</Card>


# Partial Execution - Run Only Part of Your workflow in ComfyUI
Source: https://docs.comfy.org/interface/features/partial-execution

How to use and the requirements for the Partial Execution feature in ComfyUI

<img alt="Partial Execution Feature" />

The Partial Execution feature is located in the ComfyUI node selection toolbox. It allows you to run only a part of your workflow instead of executing all nodes. This feature is only available when the selected node is an output node, and when available, it appears as a blue triangle icon.

## What is Partial Execution?

Partial Execution, as the name suggests, lets you run only a part of your workflow instead of executing all nodes in the workflow.

<img alt="Partial Execution" />

The diagram above compares Partial Execution and running the entire workflow:

1. Partial Execution (left): Only runs the branch of the workflow from the starting node to the output node.
2. Run Workflow (right): Runs all nodes in the workflow.

This feature allows you to flexibly execute specific parts of your workflow, rather than running the entire workflow every time.

## How to Use the Partial Execution Feature?

<img alt="Partial Execution Requirements" />

To use the Partial Execution feature, the currently selected node must be an output node, such as preview or save nodes. When the corresponding node meets the criteria, after selecting the node, the button in the toolbox will display as a blue triangle icon. Click this icon to run the partial workflow.

## Common Issues

Q: Why do all nodes run when I use this feature?
A: Please ensure your ComfyUI frontend version is after v1.23.4, or possibly requires v1.24.x version. The corresponding bug was fixed around version 1.24.x, so please update your ComfyUI to the latest version to ensure the frontend version meets the requirements.


# Subgraph - Simplify your workflow
Source: https://docs.comfy.org/interface/features/subgraph

An introduction to the Subgraph feature in ComfyUI, including how to create, navigate, and manage subgraphs.

<Note>
  The subgraph feature requires ComfyUI frontend version 1.24.3 or later. If you don't see this feature, please refer to: [How to Update ComfyUI](/installation/update_comfyui)

  * Images in this document are made with nightly version frontend, please refer to the actual interface
  * Some features like converting subgraph back to nodes will be supported in the future
</Note>

<Tip>
  For developer documentation on working with subgraphs programmatically, see the [Subgraph Developer Guide](/custom-nodes/js/subgraphs).
</Tip>

<iframe title="ComfyUI Selection Toolbox New Features" />

A subgraph is a powerful ComfyUI feature that lets you package complex workflows into a single reusable subgraph node, making them easier to manage and share.

<img alt="Subgraph" />

Think of a subgraph as a "folder" for your workflow – you can group related nodes together and use the entire collection as one unified subgraph node.

**Use subgraphs to:**

* Simplify complex workflows
* Reuse common node combinations
* Build more efficient workflows with modular components

## Creating a Subgraph

<Steps>
  <Step title="Select nodes">
    Select the nodes you want to group in ComfyUI
  </Step>

  <Step title="Click the subgraph icon">
    <img alt="Subgraph icon" />

    Find the subgraph icon in the toolbar
  </Step>

  <Step title="Subgraph created">
    <img alt="Workflow using subgraph" />

    ComfyUI automatically creates a subgraph based on your selected nodes' inputs and outputs
  </Step>

  <Step title="Customize your subgraph">
    Refer to [Editing Subgraphs](#editing-subgraphs), you can edit and organize the subgraph to create a fully functional node

    <img alt="Workflow using subgraph" />
  </Step>
</Steps>

## Working with Subgraphs

### Basic Operations

Subgraphs work just like regular nodes. You can:

* Change colors and names
* Use bypass to disable
* Apply all standard node operations

### Editing Subgraphs

**To enter edit mode:**

* Double-click the empty area inside the subgraph (not on widgets), or
* Click the subgraph edit button

<img alt="Subgraph editing mode" />

**In edit mode you'll see:**

1. **Navigation bar**: Exit the current subgraph and return to the parent level
2. **Input slots**: Internal node inputs exposed to the outside
   * Connect outputs to slots like normal nodes
   * **Right-click** connection points to rename/delete exposed slots
3. **Output slots**: Outputs exposed to the outside (same functionality as input slots)

<img alt="Subgraph slots" />

**Working with slots:**

1. **Default slot** (labeled 1): Use this to add new input/output connections
2. **Right-click** existing slots to rename, delete, or disconnect from original nodes

> Note: Slot connections follow standard data type validation rules

### Parameters Panel

With ComfyUI v0.3.66 or later, you can edit the subgraph parameters directly from the parameters panel without entering the subgraph.

You can select any subgraph and use the "Edit Subgraph Widgets" button to open the parameters panel.

<img alt="Open Parameters Panel" />

After it is opened, you can edit the order and visibility of the subgraph widgets directly in the parameters panel.

<img alt="Open Parameters Panel" />

1. Reordering: you use right-click and hold the widget to drag it to the desired position
2. Visibility: you can check the visibility of the widget by clicking the eye icon

### Nested Subgraphs

Create even more complex workflows by nesting subgraphs within subgraphs.

<img alt="Nested subgraph" />

The navigation bar shows your current level and lets you easily move between nested subgraphs.

<img alt="Nested subgraph navigation" />

### Exit subgraph

To exit a subgraph and return to the parent level:

* Use the **Navigation bar** (labeled 1 in the image) at the top of the canvas, or
* Press the **Esc** key

<img alt="Subgraph editing mode" />

Click on the navigation bar or press Esc to exit the current subgraph and return to the parent workflow.

## Unpack Subgraphs to Nodes

When you're done creating a subgraph, you can convert it back to nodes if you need to.

<img alt="Subgraph to node" />

1. You can select the subgraph node then use right-click menu "Unpack subgraph" to convert it back to nodes.
2. Click the "Unpack subgraph" button in the select toolbox to convert it back to nodes.

## Subgraph Blueprint

With ComfyUI frontend version 1.27.7 or later, you can publish your subgraph to the node library.

This feature allows you to convert a subgraph to a `Subgraph Blueprints` node, which means it's a reusable subgraph node.

### Publish Subgraph to Node Library

<img alt="Publish Subgraph" />

Currently, you have two ways to publish subgraph to node library, both are in the selection toolbox:

1. Click the `book(publish)` icon on the selection toolbox
2. Open the selection toolbox menu, use the `Add Subgraph to Library` menu to publish subgraph

After you click on the `book(publish)` icon or `Add Subgraph to Library` menu, you will see the following dialog:

<img alt="Subgraph naming" />

By default, the subgraph will use the name of the subgraph node as the name of the subgraph blueprint.

After publishing, you will see the subgraph blueprint node in the node library.

<img alt="Subgraph blueprint node" />

Now, you can drag or search the subgraph just like a normal node. The new subgraph node that has been added from Subgraph Blueprints is still isolated, which means after adding it to the workflow, it can be edited independently, they will not affect each other.

### Edit Subgraph Blueprint

If you want to edit the subgraph blueprint, you can click the edit button just like the image below, you can delete it as well.

<img alt="Edit Subgraph Blueprint" />

This will enable the subgraph editing mode

<img alt="Subgraph editing mode" />

After editing the subgraph blueprint, you can go to the parent level to preview the subgraph.

<img alt="Update Subgraph Blueprint" />

If you want to save the updated subgraph blueprint, you can click the save button or use the shortcut key Ctrl + S.


# Templates - ComfyUI Built-in Workflow Templates
Source: https://docs.comfy.org/interface/features/template

Browse ComfyUI Workflow Templates: natively supported model workflows and custom node examples, plus how to open, load, and download required models.

Workflow Templates is the browser for ComfyUI's natively supported model workflows and also some example workflows from custom nodes.

In ComfyUI’s Workflow Templates, you can find:

* Natively supported model workflows
* Example workflows from custom nodes

<img alt="Template" />

## How to open Templates in ComfyUI

Click the **Templates** icon in the sidebar to open Workflow Templates. You can also open it from the menu **Workflow** → **Browse Workflow Templates**.

<img alt="Template" />

## How to use templates

1. Load a template: Click any template you want to load its workflow.
2. Download models: When loading a template, ComfyUI automatically checks whether all required model files exist. If anything is missing, it will prompt you to download the models.
3. Run the workflow: Once all requirements—such as models, input images, and prompts—are ready, click the Run button to start using the workflow.

### Model storage location

Each workflow template embeds links to the required models. On first use, if the corresponding model files are not detected, you will see a download prompt.

<img alt="Missing Models" />

1. For desktop version, when you click the `Download` button, the desktop program will automatically download the model files for you.
2. For other versions, the browser will be used to download the corresponding model. You need to download the model and save it to the corresponding folder under `ComfyUI/models`. For example, the model in the screenshot should be saved in the following location:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── qwen_image_fp8_e4m3fn.safetensors
│   ├── 📂 vae/
│   │   └── qwen_image_vae.safetensors
│   └── 📂 text_encoders/
│       └── qwen_2.5_vl_7b_fp8_scaled.safetensors
```

In the current version, missing-file detection only checks whether there is a file with the same name in the corresponding top-level directory. For example, the file must exist directly under `ComfyUI/models/diffusion_models`.
If you have already downloaded the model into a subfolder such as `ComfyUI/models/diffusion_models/wan_video`, you can ignore the popup and simply ensure the correct model is selected in the corresponding model loader node.

If you're curious how model links are embedded, we add a `models` field under the node’s `properties`. Below is a complete snippet of a `DualCLIPLoader` node with embedded model information:

```json theme={null}
    {
      "id": 40,
      "type": "DualCLIPLoader",
      "pos": [
        -320,
        290
      ],
      "size": [
        270,
        130
      ],
      "flags": {},
      "order": 0,
      "mode": 0,
      "inputs": [],
      "outputs": [
        {
          "name": "CLIP",
          "type": "CLIP",
          "links": [
            64
          ]
        }
      ],
      "properties": {
        "Node name for S&R": "DualCLIPLoader",
        "cnr_id": "comfy-core",
        "ver": "0.3.40",
        "models": [
          {
            "name": "clip_l.safetensors",
            "url": "https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors",
            "directory": "text_encoders"
          },
          {
            "name": "t5xxl_fp16.safetensors",
            "url": "https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors",
            "directory": "text_encoders"
          }
        ]
      },
      "widgets_values": [
        "clip_l.safetensors",
        "t5xxl_fp16.safetensors",
        "flux",
        "default"
      ]
    }
```

The `models` field inside `properties` includes `name`, `url`, and `directory`.

* `name`: the model file name
* `url`: a direct download link to the file (not a repository page)
* `directory`: which subfolder under `ComfyUI/models` to store the file, e.g. `vae` means `ComfyUI/models/vae`

Currently, only links from Hugging Face and Civitai are supported. The model format must be a safe format such as `.safetensors` or `.sft`. Formats like `.gguf` are considered unsafe; when embedded they will be flagged as unsafe and the link will not be shown.

You can use [this tool](https://comfyui-wiki.github.io/ComfyUI-Workflow-JSON-Editor/) to edit the model information in workflow templates. At the moment, [@ComfyUI-Wiki](https://github.com/ComfyUI-Wiki) only adds support for native nodes.

## How to update templates?

Templates are managed and updated as a separate dependency: [`comfyui-workflow-templates`](https://pypi.org/project/comfyui-workflow-templates/).

If, after updating ComfyUI, you don’t see the documentation or newly announced templates, you may need to update the corresponding dependency. You can check versions in [`ComfyUI/requirements.txt`](https://github.com/Comfy-Org/ComfyUI/blob/master/requirements.txt).

Typically, the following three dependencies may be upgraded together when ComfyUI is updated:

```
comfyui-frontend-package==1.24.4
comfyui-workflow-templates==0.1.52
comfyui-embedded-docs==0.2.4
```

If you’re not sure how to update correctly, see [Update ComfyUI](/installation/update_comfyui) for how to update ComfyUI and its dependencies.

## How to contribute templates to the ComfyUI repository?

All templates are hosted in the [workflow\_templates](https://github.com/Comfy-Org/workflow_templates/) repository. You can contribute templates by submitting a PR. For official templates, we require the following:

1. Do not use any third-party nodes (to avoid extra installations for users who lack those nodes).
2. The template must not duplicate existing ones and should target supported model capabilities.
3. You may open an issue in the repository to ask questions.

## Custom node templates

If a custom node author provides templates and example workflows, you can also find them in the Templates browser. Usually, you can locate all templates by finding the category named after the node.

If you are a custom node author, note that we currently only support a single directory level under the `templates` folder (no nested subdirectories), and only JSON-format templates are supported.

## How to add templates for custom nodes?

See [Custom Node Templates](/custom-nodes/workflow_templates) for how to add workflow templates for your custom nodes.


# Mask Editor - Create and Edit Masks in ComfyUI
Source: https://docs.comfy.org/interface/maskeditor

Learn how to use the Mask Editor in ComfyUI, including tools, layers, settings, and shortcuts

The Mask Editor is a built-in tool in ComfyUI that lets you create and edit masks directly on your images — no external image editor needed. It supports multiple drawing tools, layer management, undo/redo, canvas transformations, and GPU-accelerated brush rendering.

***

## How to Open

There are three ways to open the Mask Editor:

1. **Selection Toolbox** — Select a Load Image node, then click the Mask icon button in the selection toolbar above the node.
2. **Image Overlay** — Hover over the image preview (gallery mode), then click the **Edit or mask image** button (mask icon) that appears in the top-left corner.
3. **Right-Click Menu** — Right-click a Load Image node and select `Open in Mask Editor` from the context menu.

> The Mask Editor is available in both **Graph Mode** and **App Mode**.

<img alt="Three ways to open the Mask Editor: Selection Toolbox, Image Overlay, and Right-Click Menu" />

***

## Interface Overview

<img alt="Mask Editor main interface with tool panel, canvas, and settings side panel" />

The Mask Editor opens as a modal dialog with four main areas:

| # | Area | Location | Description |
| - | - | - | - |
| 1 | **Top Bar** | Top | Header with undo/redo, canvas transforms, invert/clear, save/cancel |
| 2 | **Tool Panel** | Left | Tool selection and zoom info |
| — | **Pointer Zone** | Center | The main canvas area for drawing and editing |
| 3 | **Side Panel** | Right | Tool-specific settings and layer controls |

***

## Tools

The tool panel on the left side offers five tools. Select a tool to activate it, and the right panel will show its settings.

<img alt="Mask Editor tool panel with 5 numbered tools" />

| # | Tool | Layer | Description |
| - | - | - | - |
| 1 | **Mask Pen** | Mask | Primary tool for drawing mask regions. Left-click and drag to paint mask on the image. |
| 2 | **Paint Pen** | RGB (Paint) | Paint directly onto the image's RGB layer. Useful for inpainting or touching up the base image. |
| 3 | **Eraser** | Mask / RGB | Erase parts of an existing mask or paint layer. |
| 4 | **Paint Bucket** | Mask | Flood-fill tool based on color similarity. Click a pixel to fill the connected region with a mask; click an already-masked area to erase from the mask. Tolerance controls how broadly the fill spreads. |
| 5 | **Color Select** | Mask | Selectively mask all pixels matching a target color, with advanced matching algorithms (Simple HSL / LAB). |

***

## TopBar Actions

<img alt="Mask Editor TopBar actions labeled 1–10" />

The top bar provides canvas-wide operations:

| # | Action | Description |
| - | - | - |
| 1 | **Undo** (Ctrl+Z) | Revert the last action |
| 2 | **Redo** (Ctrl+Shift+Z / Ctrl+Y) | Reapply a reverted action |
| 3 | **Rotate Left** | Rotate all layers 90° counter-clockwise |
| 4 | **Rotate Right** | Rotate all layers 90° clockwise |
| 5 | **Mirror Horizontal** | Flip all layers horizontally |
| 6 | **Mirror Vertical** | Flip all layers vertically |
| 7 | **Invert** | Invert the mask (black ↔ white) |
| 8 | **Clear** | Clear the entire mask |
| 9 | **Save** | Save the mask and close the editor |
| 10 | **Cancel** | Close without saving |

> **Note**: Rotate and mirror operations affect all three layers (mask, paint, and base image) simultaneously. GPU-accelerated textures are recreated after transforms.

***

## Layers

The right panel includes a **Layers** section where you can toggle visibility of each layer independently:

* **Mask Layer**: The mask overlay. You can adjust its **opacity** and **blending mode**:
  * `Black` — Mask renders as black overlay
  * `White` — Mask renders as white overlay
  * `Negative` — Inverted mask rendering
* **Paint Layer**: The RGB paint layer (visible when using Paint Pen)
* **Base Image Layer**: The original source image

Click **Activate Layer** on a layer to switch drawing focus to it.

Refer to the main editor screenshot above — the right panel includes brush settings and the Layers section at the bottom.

***

## Brush Settings

When a brush-based tool (Mask Pen, Paint Pen, or Eraser) is active, the side panel shows brush settings:

| Setting | Range | Description |
| - | - | - |
| **Shape** | Arc / Rect | Round brush or square brush |
| **Color** | Any hex color | The paint color (for Paint Pen) or mask color |
| **Thickness** | 1–250 | Brush diameter in pixels |
| **Opacity** | 0–1 | Brush stroke transparency |
| **Hardness** | 0–1 | Edge softness. 1 = hard edge, 0 = very soft |
| **Step Size** | 1–100 | Spacing between brush dabs. Lower values give smoother strokes |

Use **Reset to Default** to restore the default brush parameters.

***

## Canvas Navigation & Shortcuts

| Shortcut | Action |
| - | - |
| **Space + Drag** | Pan the canvas |
| **Ctrl + Scroll** | Zoom in/out |
| **Click zoom %** | Reset zoom to 100% |
| **Ctrl + Z** | Undo |
| **Ctrl + Shift + Z** or **Ctrl + Y** | Redo |
| **Alt + Right-click + Drag** | Adjust brush: left/right changes **size**, up/down changes **hardness** |

***

## Settings

In the ComfyUI Settings panel, you can configure the following Mask Editor options:

| Setting | Category | Default | Description |
| - | - | - | - |
| **Brush adjustment speed multiplier** | Mask Editor → Brush Adjustment → Sensitivity | 1.0 (0.1–2.0) | How quickly the brush size and hardness change when using Alt+Right-click drag |
| **Lock brush adjustment to dominant axis** | Mask Editor → Brush Adjustment → Use Dominant Axis | On | When enabled, the adjustment affects only size OR hardness based on your dominant movement direction |

***

## Video Tutorial

<video>
  <source type="video/mp4" />

  Your browser does not support the video tag.
</video>

> **Note**: This video demonstrates an older version of the Mask Editor (Nodes 1.0 UI) showing brush size adjustment and mask preview creation. The overall workflow remains the same in the current version.


# Nodes 2.0
Source: https://docs.comfy.org/interface/nodes-2

Nodes 2.0 moves ComfyUI node rendering from LiteGraph Canvas to a Vue-based system for faster iteration: what changed and how to enable it.

Nodes 2.0 is now available in Comfy Desktop, portable, and stable releases. This update transitions the node system from LiteGraph.js Canvas rendering to a Vue-based architecture, unlocking faster iteration and richer interactions.

## Why this change?

The previous Canvas rendering system had become a development bottleneck. Even small UI changes often required deep modifications and could take days to implement. This slowed the ability to respond to community feedback and made node customization difficult for developers.

The new Vue-based system enables:

* **Faster feature development** - UI changes can be implemented more quickly
* **Richer interactions** - Dynamic widgets, expandable nodes, and better components
* **A more flexible foundation** - Better support for future tools and customization

## Current status and known issues

We're actively working on improvements and want to be transparent about current limitations:

| Area | Status |
| - | - |
| **Performance** | Still optimizing toward Canvas-level performance. Certain scenarios may behave differently. |
| **Compatibility** | Some custom nodes may require updates to be fully supported. |
| **Edge cases** | At extreme zoom levels or within very large workflows, minor visual issues may appear. |

We're gathering feedback to prioritize improvements. The LiteGraph.js rendering system remains available, and you can toggle between systems at any time.

## How to try it

### Enable Nodes 2.0

1. Visit [cloud.comfy.org](https://cloud.comfy.org) or update to the latest version of Comfy Desktop, portable, or stable release
2. Click **Try it out** on the top banner when you launch ComfyUI

### What to test

Use Nodes 2.0 in your daily workflows and share feedback with us:

* **Basic interactions** - Dragging, resizing, selecting
* **Daily workflows** - Execution, parameters, custom nodes
* **Performance** - Especially with complex workflows

## How to provide feedback

Encountered issues or have suggestions for interaction improvements?

* **Support center** - [ComfyUI Help Center](https://support.comfy.org)
* **GitHub issues** - [Create an issue in ComfyUI\_frontend](https://github.com/Comfy-Org/ComfyUI_frontend/issues)

<Tip>
  Including reproduction steps, screenshots, and system info is extremely helpful when reporting issues.
</Tip>

## Switching back

If you encounter issues:

1. Click on the **ComfyUI logo** to open the menu
2. Toggle **Nodes 2.0** to switch back to the previous interface

<img alt="Nodes 2.0 toggle location in ComfyUI menu" />

Your feedback helps us prioritize improvements. Enable Nodes 2.0 in settings and start exploring the new node design!


# Interface Overview
Source: https://docs.comfy.org/interface/overview

ComfyUI interface tour covering the workspace parts used to build, organize, and debug workflows in the visual node editor.

The visual interface is currently the way most users utilize ComfyUI to call the [ComfyUI Server](/development/comfyui-server/comms_overview) to generate corresponding media resources. It provides a visual interface for users to operate and organize workflows, debug workflows, and create amazing works.

Typically, when you start the ComfyUI server, you will see an interface like this:

<img alt="ComfyUI Basic Interface" />

Currently, the [ComfyUI frontend](https://github.com/Comfy-Org/ComfyUI_frontend) is a separate project, released and maintained as an independent pip package. If you want to contribute, you can fork this [repository](https://github.com/Comfy-Org/ComfyUI_frontend) and submit a pull request.

## Localization Support

Currently, ComfyUI supports: English, Chinese, Russian, French, Japanese, and Korean.
If you need to switch the interface language to your preferred language, you can click the **Settings gear icon** and then select your desired language under `Comfy` --> `Locale`.

<img alt="ComfyUI Localization Support" />

## New Menu Interface

### Workspace Areas

Below are the main interface areas of ComfyUI and a brief introduction to each part.

<img alt="ComfyUI Workspace" />

Currently, apart from the main workflow interface, the ComfyUI interface is mainly divided into the following parts:

1. **Main Menu**: Click to expand the function menu, including file operations, help menu, etc.

**Left Navigation Sidebar:**
2\. **Left Panel Entries**:

* **ASSETS**: Displays generated images, videos, and other assets.
* **Nodes**: Lists ComfyUI native and third-party nodes.
* **Models**: Shows model information detected after ComfyUI starts. After startup, if models are downloaded, press the `r` key to refresh node definitions and get the latest models.
* **Workflows**: Displays locally saved workflows.
* **Templates**: Provides ComfyUI built-in workflow templates.

**Bottom Left Toolbar:**
3\. **Bottom Toolbar**: Contains buttons for Help (opens runtime logs), Console (opens runtime logs), Shortcuts (displays shortcut panel), and Settings (opens settings panel).

**Top Header Bar:**
4\. **Top Area**: Displays the currently opened workflow.
5\. **New Workflow Button**: Click to create a new blank workflow file.
6\. **Right Control Area**: Run and queue control management, where you can run workflows and view the queue.
7\. **Login Status**: Not displayed by default, only shown after login, used when closed-source Partner Nodes are required.
8\. **Quick Access Button**: Opens the right-side panel.

**Bottom Right Canvas Controls:**
9\. **Canvas Navigation Tools**: Can switch between move or pan modes, open the minimap, and toggle node connection display.

### Sidebar Panel Buttons

<img alt="ComfyUI Sidebar Panel" />

In the current ComfyUI, we provide four side panels with the following functions:

1. Workflow History Queue (Queue): All queue information for ComfyUI executing media content generation
2. Node Library: All nodes in ComfyUI, including `Comfy Core` and your installed custom nodes, can be found here
3. Model Library: Models in your local `ComfyUI/models` directory can be found here
4. Local User Workflows (Workflows): Your locally saved workflows can be found here

<Tip>
  If you are using **Comfy Cloud**, you can also create and manage **Team Workspaces**: shared spaces where you can collaborate with team members, invite others, and share subscription credits. Learn more in the [Workspaces](/cloud/workspace) documentation.
</Tip>

## Old Menu Version

Currently, ComfyUI enables the new interface by default. If you prefer to use the old interface, you can click the **Settings gear icon** and then set `Use new menu` to `disabled` under `Comfy` --> `Menu` to switch to the old menu version.

<Note>
  The old menu interface only supports English.
</Note>

The function annotations for the old menu interface are explained below:

<img alt="ComfyUI Old Menu" />


# ComfyUI 3D Settings
Source: https://docs.comfy.org/interface/settings/3d

Detailed description of ComfyUI 3D setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

This section of settings is mainly used to control the initialization settings of 3D-related components in ComfyUI, including camera, lighting, scene, etc. When creating new 3D components, they will be initialized according to these settings. After creation, these settings can still be adjusted individually.

## Camera

### Initial Camera Type

* **Options**:
  * `perspective`
  * `orthographic`
* **Function**: Controls whether the default camera is perspective or orthographic when creating new 3D components. This default setting can still be switched individually for each component after creation

<img alt="摄像机类型" />

## Light

The light settings in this section are used to set the default lighting settings for 3D components. The corresponding settings in the 3D settings in ComfyUI can also be modified.

<img alt="light" />

### Light Adjustment Increment

* **Default Value**: 0.5
* **Function**: Controls the step size when adjusting light intensity in 3D scenes. Smaller step values allow for finer light adjustments, while larger values make each adjustment more noticeable

### Light Intensity Minimum

* **Default Value**: 1
* **Function**: Sets the minimum light intensity value allowed in 3D scenes. This defines the lowest brightness that can be set when adjusting the lighting of any 3D control

### Light Intensity Maximum

* **Default Value**: 10
* **Function**: Sets the maximum light intensity value allowed in 3D scenes. This defines the upper limit of brightness that can be set when adjusting the lighting of any 3D control

### Initial Light Intensity

* **Default Value**: 3
* **Function**: Sets the default brightness level of lights in 3D scenes. This value determines the intensity with which lights illuminate objects when creating new 3D controls, but each control can be adjusted individually after creation

## Scene

### Initial Background Color

* **Function**: Controls the default background color of 3D scenes. This setting determines the background appearance when creating new 3D components, but each component can be adjusted individually after creation
* **Default Value**: `282828` (dark gray)

Change the background color, which can also be adjusted in the canvas.

<img alt="Initial Background Color vs Modified" />

### Initial Preview Visibility

* **Function**: Controls whether the preview screen is displayed by default when creating new 3D components. This default setting can still be toggled individually for each component after creation
* **Default Value**: true (enabled)

<img alt="Preview vs hide preview" />

### Initial Grid Visibility

* **Function**: Controls whether the grid is displayed by default when creating new 3D components. This default setting can still be toggled individually for each component after creation
* **Default Value**: true (enabled)

Hide or show the grid on initialization

<img alt="Show grid vs hide grid" />

## 3D Viewer (Beta)

The 3D Viewer (Beta) opens a 3D model in a full-size window, separate from the preview inside the node. Use it to inspect a model, adjust how the model is placed, and export it.

Select a single Load 3D node on the canvas, then click the viewer button in the selection toolbox. The button opens the **3D Viewer (Beta)** window, which can be maximized.

### Enable 3D Viewer (Beta)

* **Options**:
  * enabled
  * disabled
* **Default Value**: enabled
* **Function**: Controls whether the viewer button appears in the selection toolbox when a single Load 3D node is selected. When disabled, the button does not appear. The setting carries a Beta marker in the settings list.

### Viewer panels

The viewer has its own panels for the scene, camera, lighting, model, gizmo, animation, and export:

* **Scene**: background color, grid visibility, and a background image rendered as tiled or panorama
* **Camera**: camera type and field of view
* **Light**: light intensity
* **Model**: up direction and material mode
* **Gizmo**: move, rotate, or scale the model in the viewport
* **Animation**: play the animation clips stored in the file, with speed and seek controls
* **Export**: save the loaded model. Mesh files export as GLB, OBJ, STL, or FBX, while point cloud and Gaussian splat files keep their original format

Changes you make in the viewer are written back to the node when you close the viewer. Select **Cancel** to close the viewer without changing the node.

## Point Cloud

### Point Cloud Engine

* **Options**:
  * `threejs`
  * `fastply`
* **Default Value**: `threejs`
* **Function**: Selects the engine that loads point cloud PLY files. `threejs` uses the native Three.js PLYLoader, which reads binary and ASCII files and can load meshes. `fastply` uses an optimized parser for ASCII PLY files. 3D Gaussian Splat files are detected automatically and always use the Gaussian splat renderer, whichever engine is selected here.


# About Page
Source: https://docs.comfy.org/interface/settings/about

Detailed description of ComfyUI About settings page

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

The About page is an information display panel in the ComfyUI settings system, used to show application version information, related links, and system statistics. These settings can provide us with critical information when you submit feedback or report issues.

<img alt="about" />

### Version Information Badges

The About page displays the following core version information:

* **ComfyUI Version**: Shows the backend ComfyUI version number, linked to the official GitHub repository
* **ComfyUI\_frontend Version**: Shows the frontend interface version number, linked to the frontend GitHub repository
* **Discord Community**: Provides a link to the ComfyOrg Discord server
* **Official Website**: Links to the ComfyOrg official website

<Tip>
  Since the version information here mainly corresponds to stable version information, if you are using the nightly version, the corresponding commit hash will not be displayed here. If you are using the nightly version, you can use the `git log` command in the corresponding ComfyUI main directory to view the corresponding commit hash and other information.
  Another common issue is that different dependency packages may fail and rollback during updates.
</Tip>

### Custom Node Badges

If custom nodes are installed, the About page will also display additional badge information provided by custom nodes. These badges are registered by each custom node through the `aboutPageBadges` property.

### System Info

The bottom of the page displays detailed system statistics, including:

* Hardware configuration information
* Software environment information
* System performance data

## Extension Developer Guide

Extension developers can add custom badges to the About page by adding the `aboutPageBadges` property to their extension configuration:

```javascript theme={null}
app.registerExtension({
  name: 'MyExtension',
  aboutPageBadges: [
    {
      label: 'My Extension v1.0.0',
      url: 'https://github.com/myuser/myextension',
      icon: 'pi pi-github'
    }
  ]
})
```


# Comfy Settings
Source: https://docs.comfy.org/interface/settings/comfy

Detailed description of ComfyUI core setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

## Partner Nodes

### Show Partner Node pricing badge

* **Default Value**: Enabled
* **Function**: Controls whether to display pricing badges on Partner Nodes, helping users identify the usage cost of Partner Nodes

<img alt="Show Partner Node pricing badge" />

> For more information about Partner Nodes, please refer to [Partner Nodes](/tutorials/partner-nodes/overview)

## Dev Mode

### Enable dev mode options (API save, etc.)

* **Default Value**: Disabled
* **Function**: Enables development mode options (such as API save, etc.)

## Edit Token Weight

### Ctrl+up/down precision

* **Default Value**: 0.01
* **Function**: When using CLIPTextEncode type nodes or text input node widgets, use Ctrl+up/down to quickly adjust weights. This option changes the weight value for each adjustment

<video>
  <source type="video/mp4" />
</video>

## Error System

### Show errors tab in side panel

* **Default Value**: Enabled
* **Function**: Displays an Issues tab in the right side panel that lists blocking errors and missing resources that need setup, such as missing node packs, model files, and input media. Disabling it hides the tab and the error overlay; runtime and prompt execution errors still appear in dialogs

### Show missing nodes in the issues tab

* **Default Value**: Enabled
* **Function**: Controls whether missing node packs are listed in the Issues tab and highlighted on the canvas. Hiding them does not make the workflow runnable: the nodes still have to be installed before it can run

### Show missing models in the issues tab

* **Default Value**: Enabled
* **Function**: Controls whether model files that cannot be found are listed in the Issues tab and highlighted on the canvas

### Show missing media in the issues tab

* **Default Value**: Enabled
* **Function**: Controls whether input images, videos, and audio that cannot be found are listed in the Issues tab and highlighted on the canvas

## Locale

### Language

* **Options**: English, 中文 (Chinese),日本語 (Japanese), 한국어 (Korean), Русский (Russian), Español (Spanish), Français (French)
* **Default Value**: Auto-detect browser language
* **Function**: Modify the display language of ComfyUI interface

## Menu

### Use new menu

* **Default Value**: Top
* **Function**: Select menu interface and position, currently only supports Top, Bottom, Disabled

<Tabs>
  <Tab title="Top">
    The menu interface will be displayed at the top of the workspace

    <img alt="Top Menu" />
  </Tab>

  <Tab title="Bottom">
    The menu bar interface will be displayed at the bottom of the workspace

    <img alt="Bottom Menu" />
  </Tab>

  <Tab title="Disabled">
    If you prefer the early legacy menu, you can try this option.

    <Tip>
      Since we are constantly updating, some new features will not be synchronized and supported in the legacy menu.
    </Tip>

    <img alt="Legacy Menu" />
  </Tab>
</Tabs>

## Model Library

Model Library refers to the model management function in the ComfyUI sidebar menu. You can use this function to view models in your `ComfyUI/models` and additionally configured model folders.

<img alt="Model Library" />

### What name to display in the model library tree view

* **Default Value**: title
* **Function**: Select the name format to display in the model library tree view, currently only supports filename and title

### Automatically load all model folders

* **Default Value**: Disabled
* **Function**: Whether to automatically detect model files in all folders when clicking the model library. Enabling may cause loading delays (requires traversing all folders). When disabled, files in the corresponding folder will only be loaded when clicking the folder name.

## Node

During the iteration process of ComfyUI, we will adjust some nodes and enable some nodes. These nodes may undergo major changes or be removed in future versions. However, to ensure compatibility, deprecated nodes have not been removed. You can use the settings below to enable whether to display **experimental nodes** and **deprecated nodes**.

### Show deprecated nodes in search

* **Default Value**: Disabled
* **Function**: Controls whether to display deprecated nodes in search. Deprecated nodes are hidden by default in the UI, but remain effective in existing workflows.

<img alt="Show deprecated nodes in search" />

### Show experimental nodes in search

* **Default Value**: Enabled
* **Function**: Controls whether to display experimental nodes in search. Experimental nodes are some new feature support, but are not fully stable and may change or be removed in future versions.

<img alt="Show experimental nodes in search" />

## Node Search Box

### Number of nodes suggestions

* **Default Value**: 5
* **Function**: Used to modify the number of recommended nodes in the related node context menu. The larger the value, the more related recommended nodes are displayed.

<img alt="Number of nodes suggestions" />

### Show node frequency in search results

* **Default Value**: Disabled
* **Function**: Controls whether to display node usage frequency in search results

<img alt="Show node frequency in search results" />

### Show node id name in search results

* **Default Value**: Disabled
* **Function**: Controls whether to display node ID names in search results

<img alt="Show node id name in search results" />

### Show node category in search results

* **Default Value**: Enabled
* **Function**: Controls whether to display node categories in search results, helping users understand node classification information

### Node preview

* **Default Value**: Enabled
* **Function**: Controls whether to display node previews in search results, making it convenient for you to quickly preview nodes

### Node search box implementation

* **Default Value**: default
* **Function**: Select the implementation method of the node search box (experimental feature). If you select `litegraph (legacy)`, it will switch to the early ComfyUI search box

## Node Widget

### Widget control mode

* **Options**: before, after
* **Function**: Controls whether the timing of node widget value updates is before or after workflow execution, such as updating seed values

### Textarea widget spellcheck

* **Default Value**: Disabled
* **Function**: Controls whether text area widgets enable spellcheck, providing spellcheck functionality during text input. This functionality is implemented through the browser's spellcheck attribute

## Queue

### Queue history size

* **Default Value**: 100
* **Function**: Controls the queue history size recorded in the sidebar queue history panel. The larger the value, the more queue history is recorded. When the number is large, loading the page will also consume more memory

## Queue Button

### Batch count limit

* **Default Value**: 100
* **Function**: Sets the maximum number of tasks added to the queue in a single click, preventing accidentally adding too many tasks to the queue

## Validation

### Validate node definitions (slow)

* **Default Value**: Disabled
* **Function**: Controls whether to validate all node definitions at startup (slow). Only recommended for node developers. When enabled, the system will use Zod schemas to strictly validate each node definition. This functionality will consume more memory and time
* **Error Handling**: Failed node definitions will be skipped and warning information will be output to the console

<Tip>
  Since detailed schema validation needs to be performed on all node definitions, this feature will significantly increase startup time, so it is disabled by default and only recommended for node developers
</Tip>

### Validate workflows

* **Default Value**: Enabled
* **Function**: Ensures the structural and connection correctness of workflows. If enabled, the system will call `useWorkflowValidation().validateWorkflow()` to validate workflow data
* **Validation Process**: The validation process includes two steps:
  * Schema validation: Use Zod schemas to validate workflow structure
  * Link repair: Check and repair connection issues between nodes
* **Error Handling**: When validation fails, error prompts will be displayed, but workflow loading will not be blocked

## Window

### Show confirmation when closing window

* **Default Value**: Enabled
* **Function**: When there are modified but unsaved workflows, controls whether to display confirmation when closing the browser window or tab, preventing accidental window closure that leads to loss of unsaved workflows

## Workflow

### Persist workflow state and restore on page (re)load

* **Default Value**: Enabled
* **Function**: Controls whether to restore workflow state on page (re)load, maintaining workflow content after page refresh

### Auto Save

* **Default Value**: off
* **Function**: Controls the auto-save behavior of workflows, automatically saving workflow changes to avoid data loss

### Auto Save Delay (ms)

* **Default Value**: 1000
* **Function**: Sets the delay time for auto-save, only effective when auto-save is set to "after delay"

### Show confirmation when deleting workflows

* **Default Value**: Enabled
* **Function**: Controls whether to display a confirmation dialog when deleting workflows in the sidebar, preventing accidental deletion of important workflows

### Save and restore canvas position and zoom level in workflows

* **Default Value**: Enabled
* **Function**: Controls whether to save and restore canvas position and zoom level in workflows, restoring the previous view state when reopening workflows

### Opened workflows position

* **Options**: Sidebar, Topbar, Topbar (Second Row)
* **Default Value**: Topbar
* **Function**: Controls the display position of opened workflow tabs, currently only supports Sidebar, Topbar, Topbar (Second Row)

### Prompt for filename when saving workflow

* **Default Value**: Enabled
* **Function**: Controls whether to prompt for filename input when saving workflows, allowing users to customize workflow filenames

### Sort node IDs when saving workflow

* **Default Value**: Disabled
* **Function**: Determines whether to sort node IDs when saving workflows, making workflow file format more standardized and convenient for version control

### Require confirmation when clearing workflow

* **Default Value**: Enabled
* **Function**: Controls whether to display a confirmation dialog when clearing workflows, preventing accidental clearing of workflow content

### Save node IDs to workflow

* **Default Value**: Enabled
* **Function**: Controls whether to save node IDs when saving workflows, making workflow file format more standardized and convenient for version control


# Extension Settings
Source: https://docs.comfy.org/interface/settings/extension

Detailed description of ComfyUI extension management and setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

The Extension settings panel is a special management panel in the ComfyUI frontend settings system, specifically used to manage the enable/disable status of frontend extension plugins. Unlike Custom Nodes, this panel is only used to manage frontend extensions registered by custom nodes, not to disable custom nodes themselves.

<img alt="extension" />

These frontend extension plugins are used to enhance the ComfyUI experience, such as providing shortcuts, settings, UI components, menu items, and other features.

Extension status changes require a page reload to take effect:

## Extension Settings Panel Features

### 1. Extension List Management

Displays all registered extensions, including:

* Extension Name
* Core extension identification (displays "Core" label)
* Enable/disable status

### 2. Search Functionality

Provides a search box to quickly find specific extensions:

### 3. Enable/Disable Control

Each extension has an independent toggle switch:

### 4. Batch Operations

Provides right-click menu for batch operations:

* Enable All extensions
* Disable All extensions
* Disable 3rd Party extensions (keep core extensions)

## Notes

* Extension status changes require a page reload to take effect
* Some core extensions cannot be disabled
* The system will automatically disable known problematic extensions
* Extension settings are automatically saved to the user configuration file

This Extension settings panel is essentially a "frontend plugin manager" that allows users to flexibly control ComfyUI's functional modules.


# ComfyUI LiteGraph (Canvas) Settings
Source: https://docs.comfy.org/interface/settings/lite-graph

Detailed description of ComfyUI graphics rendering engine LiteGraph setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

LiteGraph is the underlying graphics rendering engine of ComfyUI. The settings in this category mainly control the behavior and appearance of graphical interfaces such as canvas, nodes, and links.

## Canvas

### Show selection toolbox

* **Default Value**: Enabled
* **Function**: The selection toolbox is a floating quick action toolbar that appears on nodes after they are selected, providing common quick operations such as partial execution, pinning, deletion, color modification, etc.

<img alt="Show selection toolbox" />

### Low quality rendering zoom threshold

* **Default Value**: 0.6
* **Range**: 0.1 - 1.0
* **Function**: When rendering the interface, especially when the workflow is particularly complex and the entire canvas is particularly large, the frontend rendering of corresponding elements will consume a lot of memory and cause lag. By lowering this threshold, you can control elements to enter low quality rendering mode when scaled to a specific percentage, thereby reducing memory consumption. The corresponding different rendering modes are shown below

<img alt="Low quality rendering" />

### Maximum FPS

* **Default Value**: 0 (use screen refresh rate)
* **Range**: 0 - 120
* **Function**: Limits the rendering frame rate of the canvas. 0 means using the screen refresh rate. Higher FPS will make the canvas rendering smoother, but will also consume more performance. Too low values will cause more obvious stuttering.

### Always snap to grid

* **Default Value**: Disabled
* **Function**: When this option is not enabled, you can hold the `Shift` key to align node edges with the grid. When enabled, node edges will automatically align with the grid without holding the `Shift` key.

<video>
  <source type="video/mp4" />
</video>

### Snap to grid size

* **Range**: 1 - 500
* **Function**: When auto-snap is enabled or when moving nodes while holding the `Shift` key, this parameter determines the grid size for snapping. The default value is 10, and you can adjust it according to your needs.

### Enable fast-zoom shortcut (Ctrl + Shift + Drag)

* **Default Value**: Enabled
* **Function**: Enables the `Ctrl + Shift + Left Mouse Button Drag` fast zoom function, providing a faster zoom operation method

<video>
  <source type="video/mp4" />
</video>

### Show graph canvas menu

* **Default Value**: Enabled
* **Function**: Controls whether to display the canvas menu in the bottom right corner

The canvas menu is located in the bottom right corner of the entire ComfyUI interface, containing operations such as canvas zooming, temporarily hiding all connections, quickly scaling the workflow to fit the canvas, etc., as shown in the image below

<img alt="Show graph canvas menu" />

### Canvas zoom speed

* **Default Value**: 1.1
* **Range**: 1.01 - 2.5
* **Function**: Controls the speed of canvas zooming, adjusts the sensitivity of mouse wheel zooming

### Show canvas info on bottom left corner (fps, etc.)

* **Default Value**: Enabled
* **Function**: Controls whether to display canvas information in the bottom left corner, showing performance metrics like FPS

<img alt="Canvas info" />

## Context Menu

### Scale node combo widget menus (lists) when zoomed in

* **Default Value**: Enabled
* **Function**: Controls whether to scale node combo widget menus (lists) when zoomed in, allowing users to select node combo widgets

## Graph

### Link Render Mode

* **Default Value**: 2 (Spline)
* **Options**: Straight, Linear, Spline, Hidden
* **Function**: Sets the rendering style of connections, controlling the visual style of links between nodes

<img alt="Link Render Mode" />

## Group

This section of settings is mainly related to node group functionality

<img alt="Node Group" />

### Double click group title to edit

* **Default Value**: Enabled
* **Function**: Controls whether you can double-click the node title to edit it, allowing users to rename nodes, marked as part `1` in the image

### Group selected nodes padding

* **Default Value**: 10
* **Range**: 0 - 100
* **Function**: Sets the inner padding when grouping selected nodes, controlling the spacing between the group frame and nodes, marked as the arrow annotation part `2` in the image

## Link

### Link midpoint markers

* **Default Value**: Circle
* **Options**: None, Circle, Arrow
* **Function**: Sets the marker style at link midpoints, displaying direction indicators at link midpoints

<img alt="Link midpoint markers" />

## Link Release

This menu section currently mainly controls related operations when link connections are released. The current two related operations are:

**A node recommendation list related to the current input/output will appear after release**

<video>
  <source type="video/mp4" />
</video>

**A search box will be launched after release**

<video>
  <source type="video/mp4" />
</video>

### Action on link release (Shift)

* **Default Value**: search box
* **Options**: context menu, search box, no action
* **Function**: Sets the action when releasing links while holding the Shift key, special behavior when releasing links while holding Shift

### Action on link release (No modifier)

* **Default Value**: context menu
* **Options**: context menu, search box, no action
* **Function**: Sets the default action when releasing links, controls the behavior after dragging and releasing links

## Node

### Always shrink new nodes

* **Default Value**: Enabled
* **Function**: Controls whether to automatically shrink when creating new nodes, so nodes can always display the minimum size, but may cause some text display to be truncated when adding, requiring manual adjustment of node size

### Enable DOM element clipping (enabling may reduce performance)

* **Default Value**: Enabled
* **Function**: Enables DOM element clipping (may affect performance), optimizes rendering but may reduce performance

### Middle-click creates a new Reroute node

* **Default Value**: Enabled
* **Function**: Creates a new reroute node when middle-clicking, quickly creates reroute nodes for organizing connections

### Keep all links when deleting nodes

* **Default Value**: Enabled
* **Function**: Automatically bypasses connections when deleting intermediate nodes, attempts to reconnect input and output links when deleting nodes

### Snap highlights node

* **Default Value**: Enabled
* **Function**: Highlights nodes when dragging links to them, provides visual feedback, shows connectable nodes. When enabled, the effect is as shown in the image below, the corresponding side of the link will display highlighted style

<img alt="Snap highlights node" />

### Auto snap link to node slot

* **Default Value**: Enabled
* **Function**: Automatically snaps to available slots when dragging links to nodes, simplifies connection operations, automatically finds suitable input slots

<video>
  <source type="video/mp4" />
</video>

### Enable Tooltips

* **Default Value**: Enabled
* **Function**: Some node information will contain tooltips, including parameter descriptions, etc. When enabled, these tooltips will be displayed when hovering the mouse, as shown in the image below

<img alt="Enable Tooltips" />

### Tooltip Delay

* **Default Value**: 500
* **Function**: Controls the delay time for tooltips, in milliseconds. Setting to 0 means displaying tooltips immediately

### Node life cycle badge mode

* **Default Value**: Show all
* **Function**: Controls the display of node lifecycle markers, showing node status information

### Node ID badge mode

* **Default Value**: Show all
* **Function**: Controls the display of node ID markers, showing node unique identifiers

<img alt="Node ID badge mode" />

### Node source badge mode

* **Options**:
  * None
  * Hide built-in
  * Show all
* **Function**: Controls the display mode of node source markers, showing node source information. The corresponding display effect is shown in the image below. If show all is selected, it will display labels for both custom nodes and built-in nodes, making it convenient for you to determine the corresponding node source. The corresponding fox logo represents ComfyUI built-in nodes

<img alt="Node source badge mode" />

### Double click node title to edit

* **Default Value**: Enabled
* **Function**: Controls whether you can double-click the node title to edit it, allowing users to rename nodes

## Node Widget

### Float widget rounding decimal places \[0 = auto]

* **Default Value**: 0 (auto)
* **Range**: 0 - 6
* **Function**: Sets the decimal places for float widget rounding, 0 means auto, requires page reload

### Disable default float widget rounding

* **Default Value**: Disabled
* **Function**: Controls whether to disable default float widget rounding, requires page reload, cannot be disabled when the node backend has set rounding

### Disable node widget sliders

* **Default Value**: Disabled
* **Function**: Controls whether to disable slider controls in node widgets, forcing text input instead of sliders

### Preview image format

* **Default Value**: Empty string (use original format)
* **Function**: Sets the format for preview images in image widgets, converts to lightweight formats like webp, jpeg, etc.

### Show width × height below the image preview

* **Default Value**: Enabled
* **Function**: Displays width × height information below image previews, showing image dimension information

<img alt="Show width × height below the image preview" />

## Pointer

### Enable trackpad gestures

* **Default Value**: Enabled
* **Function**: This setting enables trackpad mode for the canvas, allowing two-finger pinch zoom and drag.

### Double click interval (maximum)

* **Default Value**: 300
* **Function**: Maximum time (milliseconds) between two clicks of a double-click. Increasing this value helps solve issues where double-clicks are sometimes not recognized.

### Pointer click drift delay

* **Default Value**: 150
* **Function**: Maximum time (milliseconds) to ignore pointer movement after pressing the pointer button. Helps prevent accidental mouse movement when clicking.

### Pointer click drift (maximum distance)

* **Default Value**: 6
* **Function**: If the pointer moves more than this distance while holding the button, it is considered a drag (rather than a click). Helps prevent accidental mouse movement when clicking.

## Reroute

### Reroute spline offset

* **Default Value**: 20
* **Function**: Used to determine the smoothness of curves on both sides of reroute nodes. Larger values make curves smoother, smaller values make curves sharper.

<img alt="Reroute spline offset" />


# ComfyUI Mask Editor Settings
Source: https://docs.comfy.org/interface/settings/mask-editor

Detailed description of ComfyUI mask editor setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

## Brush Adjustment

### Brush adjustment speed multiplier

* **Function**: Controls the speed of brush size and hardness changes during adjustment
* **Description**: Higher values mean faster changes

### Lock brush adjustment to dominant axis

* **Function**: When enabled, brush adjustment will only affect size or hardness based on the direction you move
* **Description**: This feature allows users to more precisely control brush property adjustments

## New Editor

### Use new mask editor

* **Function**: Switch to the new brush editor interface
* **Description**: Allows users to switch between new and old editor interfaces

<Tabs>
  <Tab title="New Editor">
    The new version has a better UI interface and interaction, with more complete functionality

    <img alt="new" />
  </Tab>

  <Tab title="Old Editor">
    The old version is an early version with relatively simple functionality, but can meet basic needs. It will not be updated in the future.

    <img alt="old" />
  </Tab>
</Tabs>


# ComfyUI Settings Overview
Source: https://docs.comfy.org/interface/settings/overview

Detailed description of ComfyUI settings overview

This section covers detailed setting descriptions in the ComfyUI frontend settings menu. All user settings are automatically saved to the `ComfyUI/user/default/comfy.settings.json` file.

You can use the `Ctrl + ,` keyboard shortcut to open the settings panel, then click on the corresponding setting options to configure them.

Since custom nodes can also register corresponding setting categories in the menu, our official documentation currently only includes native setting content. Additionally, some setting options are **only effective for Comfy Desktop**, which we have noted on the corresponding pages.

## ComfyUI Settings Menu

<Columns>
  <Card title="User" icon="user" href="/interface/user">
    User settings related to ComfyUI account, mainly used for logging into ComfyUI account to use Partner Nodes
  </Card>

  <Card title="Credits" icon="credit-card" href="/interface/credits">
    Entry for purchasing credits and credit balance history, only visible after logging into ComfyUI account
  </Card>

  <Card title="Comfy" icon="sliders" href="/interface/settings/comfy">
    Detailed description of ComfyUI core setting options
  </Card>

  <Card title="Lite Graph" icon="diagram-project" href="/interface/settings/lite-graph">
    Detailed description of Canvas (Lite Graph) setting options in ComfyUI
  </Card>

  <Card title="Appearance" icon="palette" href="/interface/appearance">
    Modify ComfyUI appearance options such as themes, background colors, sidebar position, etc.
  </Card>

  <Card title="Extension" icon="puzzle-piece" href="/interface/settings/extension">
    Manage the enable/disable status of frontend extension plugins in ComfyUI
  </Card>

  <Card title="3D" icon="cube" href="/interface/settings/3d">
    Some setting options for 3D node initialization
  </Card>

  <Card title="Comfy Desktop" icon="desktop" href="/interface/settings/comfy-desktop">
    Desktop update settings, mirror settings, etc. (only effective for Comfy Desktop)
  </Card>

  <Card title="Mask Editor" icon="brush" href="/interface/settings/mask-editor">
    Adjust mask editor usage preferences
  </Card>

  <Card title="Keybinding" icon="keyboard" href="/interface/shortcuts">
    Modify ComfyUI keyboard shortcut settings
  </Card>

  <Card title="About" icon="info" href="/interface/settings/about">
    Learn about current ComfyUI version information, device runtime information, etc., which is very useful for daily feedback
  </Card>

  <Card title="Server Config" icon="server" href="/interface/settings/server-config">
    Modify ComfyUI configuration file, this setting is only effective for Comfy Desktop
  </Card>
</Columns>


# Keyboard and Mouse Shortcuts
Source: https://docs.comfy.org/interface/shortcuts

ComfyUI keyboard and mouse shortcuts: the full default list, plus how to view and customize keybindings in the in-app settings menu.

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

Currently, ComfyUI supports custom keyboard shortcuts. You can set the shortcuts by clicking on `Settings (gear icon)` --> `Keybinding`.

<img alt="ComfyUI Shortcut Settings" />

In the corresponding menu, you can see all the current shortcut settings for ComfyUI. Click the `edit icon` before the corresponding command to customize the shortcut.

Below is the current list of shortcuts for ComfyUI, which you can customize as needed.

<Tabs>
  <Tab title="Windows/Linux">
    | Shortcut | Command |
    | - | - |
    | Ctrl + Enter | Queue prompt |
    | Ctrl + Shift + Enter | Queue prompt (Front) |
    | Ctrl + Alt + Enter | Interrupt |
    | Ctrl + Z / Ctrl + Y | Undo/Redo |
    | Ctrl + S | Save workflow |
    | Ctrl + O | Load workflow |
    | Ctrl + A | Select all nodes |
    | Alt + C | Collapse/uncollapse selected nodes |
    | Ctrl + M | Mute/unmute selected nodes |
    | Ctrl + B | Bypass/unbypass selected nodes |
    | Delete<br />Backspace | Delete selected nodes |
    | Backspace | Clear workflow |
    | Space | Move canvas when holding and moving cursor |
    | Ctrl + Click<br />Shift + Click | Add clicked node to selection |
    | Ctrl + C/Ctrl + V | Copy and paste selected nodes (without maintaining connections to outputs of unselected nodes) |
    | Ctrl + C/Ctrl + Shift + V | Copy and paste selected nodes (maintaining connections from outputs of unselected nodes to inputs of pasted nodes) |
    | Shift + Drag | Move multiple selected nodes at the same time |
    | Ctrl + G | Add frame to selected nodes |
    | Ctrl + , | Show settings dialog |
    | Alt + = | Zoom in (canvas) |
    | Alt + - | Zoom out (canvas) |
    | . | Fit view to selected nodes |
    | P | Pin/unpin selected items |
    | Q | Toggle queue sidebar |
    | W | Toggle workflow sidebar |
    | N | Toggle node library sidebar |
    | M | Toggle model library sidebar |
    | Ctrl + \` | Toggle log bottom panel |
    | F | Toggle focus mode (full screen) |
    | R | Refresh node definitions |
    | Double-Click LMB | Quick search for nodes to add |
  </Tab>

  <Tab title="MacOS">
    | Shortcut | Command |
    | - | - |
    | Cmd ⌘ + Enter | Queue prompt |
    | Cmd ⌘ + Shift + Enter | Queue prompt (Front) |
    | Cmd ⌘ + Alt + Enter | Interrupt |
    | Cmd ⌘ + Z/Cmd ⌘ + Y | Undo/Redo |
    | Cmd ⌘ + S | Save workflow |
    | Cmd ⌘ + O | Load workflow |
    | Cmd ⌘ + A | Select all nodes |
    | Opt ⌥ + C | Collapse/uncollapse selected nodes |
    | Cmd ⌘ + M | Mute/unmute selected nodes |
    | Cmd ⌘ + B | Bypass/unbypass selected nodes |
    | Delete<br />Backspace | Delete selected nodes |
    | Backspace | Clear workflow |
    | Space | Move canvas when holding and moving cursor |
    | Cmd ⌘ + Click<br />Shift + Click | Add clicked node to selection |
    | Cmd ⌘ + C / Cmd ⌘ + V | Copy and paste selected nodes (without maintaining connections to outputs of unselected nodes) |
    | Cmd ⌘ + C / Cmd ⌘ + Shift + V | Copy and paste selected nodes (maintaining connections from outputs of unselected nodes to inputs of pasted nodes) |
    | Shift + Drag | Move multiple selected nodes at the same time |
    | Cmd ⌘ + G | Add frame to selected nodes |
    | Cmd ⌘ + , | Show settings dialog |
    | Opt ⌥ + = | Zoom in (canvas) |
    | Opt ⌥ + - | Zoom out (canvas) |
    | . | Fit view to selected nodes |
    | P | Pin/unpin selected items |
    | Q | Toggle queue sidebar |
    | W | Toggle workflow sidebar |
    | N | Toggle node library sidebar |
    | M | Toggle model library sidebar |
    | Cmd ⌘ + \` | Toggle log bottom panel |
    | F | Toggle focus mode (full screen) |
    | R | Refresh node definitions |
    | Double-Click LMB | Quick search for nodes to add |
  </Tab>
</Tabs>


# Account Management
Source: https://docs.comfy.org/interface/user

In this document, we will introduce the account management features of ComfyUI, including account login, registration, and logout operations.

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

Using `Partner Nodes` requires credits, so the account system provides credit management and authentication support, enabling users to conveniently access cutting-edge closed-source model APIs.

Currently, we support the following login methods:

* Email login
* Google login
* Github login
* API Key login (for non-whitelisted site authorization)

We will provide relevant login requirements and explanations in this document.

## ComfyUI Version Requirements

You may need to use at least [ComfyUI v0.3.0](https://github.com/Comfy-Org/ComfyUI/releases/tag/v0.3.30) to use the account system. Ensure that the corresponding frontend version is at least `1.17.11`. Sometimes the frontend may fail to install and revert to an older version, so please check if the frontend version is greater than `1.17.11` in `Settings` -> `About`.

In some regions, network restrictions may prevent normal access to the login API, causing timeouts or failures. Before logging in, please **ensure that your network environment does not restrict access to the corresponding API**, and make sure you can access sites like Google or Github.

<Tip>
  Since we are still in rapid iterative updates, related functions may change. If there are no special circumstances, please try to update to the latest version to get support for relevant functions.
</Tip>

## Network Requirements

To login to ComfyUI account, you must be in a secure network environment:

* Only allow access from `127.0.0.1` or `localhost`.
* Do not support using the `--listen` parameter to access the Partner Node through a local network.
* If you are using a non-SSL certificate or a site that does not start with `https`, you may not be able to successfully log in.
* You may not be able to log in on a site that is not in our whitelist (but you can log in using an API Key now).
* Ensure you can connect to our service normally (some regions may require a proxy).

## How to Log In

Log in via `Settings` -> `User`:

<img alt="ComfyUI User Interface" />

## Login Methods

<img alt="user-login" />

If this is your first login, please create an account first.

<Card title="Logging in with an API Key" icon="key" href="/account/login#logging-in-with-an-api-key">
  For non-whitelisted sites or LAN environments, you can use API Key login. See the detailed guide in the account login documentation.
</Card>

## Post-Login Status

After logging in, a login button is displayed in the top menu bar of the ComfyUI interface. You can open the corresponding login interface through this button and log out of the corresponding account in the settings menu.

<img alt="user-logged" />

<img alt="menu-user-logged" />

## Frequently Asked Questions

<AccordionGroup>
  <Accordion title="Are there any login device restrictions?">
    We do not restrict login devices. You can log in to your account on any device, but please note that your account information may be accessed by other devices, so do not log in to your account on public devices.
  </Accordion>

  <Accordion title="How to log in in a LAN environment?">
    Currently, only API Key login is supported in a LAN environment. If you are accessing ComfyUI services through a LAN, please use API Key to log in.
  </Accordion>

  <Accordion title="Why can't I log in on some websites?">
    Our login service has a whitelist, so you may not be able to log in to ComfyUI deployed on some servers, for this case, you can use API Key login to solve it.
  </Accordion>
</AccordionGroup>


# ComfyUI-Manager Configuration
Source: https://docs.comfy.org/manager/configuration

ComfyUI-Manager configuration reference: config.ini paths and options, security levels, and the protected system path introduced in V3.38.

## Configuration paths

Starting from V3.38, Manager uses a protected system path for enhanced security.

| ComfyUI Version | Manager Path |
| - | - |
| v0.3.76+ (with System User API) | `<USER_DIRECTORY>/__manager/` |
| Older versions | `<USER_DIRECTORY>/default/ComfyUI-Manager/` |

<Note>
  If executed without any options, the `<USER_DIRECTORY>` path defaults to `ComfyUI/user`. It can be set using `--user-directory <USER_DIRECTORY>`.
</Note>

### Configuration files

| File | Description |
| - | - |
| `config.ini` | Basic configuration |
| `channels.list` | Configurable channel lists |
| `pip_overrides.json` | Custom pip package mappings |
| `pip_blacklist.list` | Packages to prevent installation |
| `pip_auto_fix.list` | Packages to auto-restore |
| `snapshots/` | Saved snapshot files |
| `startup-scripts/` | Startup script files |
| `components/` | Component files |

## Config.ini options

Modify the `config.ini` file to apply settings. The path is displayed in startup log messages.

```ini theme={null}
[default]
git_exe = <path to git executable>
use_uv = <True/False - use uv instead of pip>
default_cache_as_channel_url = <True/False - retrieve DB designated as channel_url at startup>
bypass_ssl = <True/False - disable SSL if errors occur>
file_logging = <True/False - create log file>
windows_selector_event_loop_policy = <True/False - fix event loop errors on Windows>
model_download_by_agent = <True/False - use agent for model downloads>
downgrade_blacklist = <comma-separated list of packages to prevent downgrades>
security_level = <strong|normal|normal-|weak>
always_lazy_install = <True/False - perform dependency installation on restart>
network_mode = <public|private|offline>
```

### Network modes

| Mode | Description |
| - | - |
| `public` | Standard public network environment |
| `private` | Closed network with private node DB configured via `channel_url` (uses cache if available) |
| `offline` | No external connections (uses cache if available) |

### Security levels

| Level | Description |
| - | - |
| `strong` | Doesn't allow high and middle level risky features |
| `normal` | Doesn't allow high level risky features; middle level features available |
| `normal-` | Doesn't allow high level risky features if `--listen` is specified and not starts with `127.`; middle level features available |
| `weak` | All features available |

#### Risk levels for features

| Risk Level | Features |
| - | - |
| **High** | Install via git url, pip install, installation of custom nodes not in default channel, fix custom nodes |
| **Middle** | Uninstall/Update, installation of custom nodes in default channel, restore/remove snapshot, restart |
| **Low** | Update ComfyUI |

## Environment variables

| Variable | Description |
| - | - |
| `COMFYUI_PATH` | Installation path of ComfyUI |
| `GITHUB_ENDPOINT` | Reverse proxy for GitHub access |
| `HF_ENDPOINT` | Reverse proxy for Hugging Face access |

### Examples

Redirecting GitHub requests through a proxy:

```bash theme={null}
GITHUB_ENDPOINT=https://mirror.ghproxy.com/https://github.com
```

Changing Hugging Face endpoint:

```bash theme={null}
HF_ENDPOINT=https://some-hf-mirror.com
```

## Advanced configuration

### Prevent downgrade of specific packages

List package names in the `downgrade_blacklist` section of `config.ini`, separated by commas:

```ini theme={null}
downgrade_blacklist = diffusers, kornia
```

### Custom pip mapping

Create a `pip_overrides.json` file to change the installation of specific pip packages to user-defined installations. Refer to `pip_overrides.json.template` for the format.

### Prevent installation of specific pip packages

List package names one per line in the `pip_blacklist.list` file.

### Automatically restore pip installation

List pip spec requirements in `pip_auto_fix.list` (similar to `requirements.txt`). It will automatically restore specified versions when starting ComfyUI or when versions get mismatched during custom node installations. `--index-url` can be used.

### Use aria2 as downloader

For faster downloads, you can configure ComfyUI-Manager to use aria2. See the [aria2 setup guide](https://github.com/Comfy-Org/ComfyUI-Manager/blob/main/docs/en/use_aria2.md).

## extra\_model\_paths.yaml configuration

The following settings are applied based on the section marked as `is_default`:

* `custom_nodes`: Path for installing custom nodes
* `download_model_base`: Path for downloading models

## CLI tools

ComfyUI-Manager provides `cm-cli`, a command line tool that allows you to use Manager features without running ComfyUI. This is useful for automating custom node installation and managing installations in headless environments.

For detailed cm-cli documentation, see the [official cm-cli guide](https://github.com/Comfy-Org/ComfyUI-Manager/blob/main/docs/en/cm-cli.md).

For a more comprehensive CLI experience, consider using [comfy-cli](/comfy-cli/getting-started).


# ComfyUI-Manager Installation
Source: https://docs.comfy.org/manager/install

Install ComfyUI-Manager on Desktop, Portable, or manual ComfyUI setups to search, install, and update custom nodes from inside the app.

## Desktop users

Comfy Desktop installs ComfyUI-Manager with every ComfyUI installation and starts it with `--enable-manager`, so there is nothing for you to install. Manager is configured per installation from inside the app:

<Steps>
  <Step title="Open the Manage panel for the installation">
    In Comfy Desktop, open the installation and go to the **Manage panel**, then switch to the **Startup Args** tab.
  </Step>

  <Step title="Set the Manager options">
    * **Manager Security Level** decides which node packs Manager may install: **Strict**, **Standard** (recommended), **Relaxed**, or **Permissive**. Stricter levels matter most when ComfyUI is exposed to your network with `--listen`
    * **Manager Network Mode** decides how Manager reaches the node registry: **Public** (default), **Private**, **Offline**, or **Personal cloud** (only for a machine you control)

    Both options apply the next time you launch the installation.
  </Step>

  <Step title="Change the flags Manager starts with (optional)">
    **Startup Arguments** on the same tab controls the flags the installation launches with. Remove `--enable-manager` to run ComfyUI without Manager, or keep it and add `--disable-manager-ui` to hide the Manager UI while its background tasks continue.
  </Step>
</Steps>

See the [Startup Args tab](/installation/desktop/usage/manage#startup-args-tab) for the rest of the per-installation settings and the [startup flags reference](/development/comfyui-server/startup-flags) for the Manager flags.

## Portable users

For users running the [Windows Portable](/installation/comfyui_portable_windows) version, the new ComfyUI-Manager is built into ComfyUI core but needs to be enabled.

1. Install the manager dependencies:
   ```bash theme={null}
   .\python_embeded\python.exe -m pip install -r ComfyUI\manager_requirements.txt
   ```

2. Launch ComfyUI with the manager enabled:
   ```bash theme={null}
   .\python_embeded\python.exe -s ComfyUI\main.py --windows-standalone-build --enable-manager
   pause
   ```

## Manual install users

For users with a [manual installation](/installation/manual_install), the new ComfyUI-Manager is built into ComfyUI core but needs to be enabled.

1. Activate your virtual environment:
   ```bash theme={null}
   # Windows
   venv\Scripts\activate

   # Linux/macOS
   source venv/bin/activate
   ```

2. Install the manager dependencies:
   ```bash theme={null}
   pip install -r manager_requirements.txt
   ```

3. Enable the manager with the `--enable-manager` flag when running ComfyUI:
   ```bash theme={null}
   python main.py --enable-manager
   ```

### Command line options

| Flag | Description |
| - | - |
| `--enable-manager` | Enable ComfyUI-Manager |
| `--enable-manager-legacy-ui` | Use the legacy manager UI instead of the new UI (requires `--enable-manager`) |
| `--disable-manager-ui` | Disable the manager UI and endpoints while keeping background features (requires `--enable-manager`) |

### Switch between new and legacy UI

The following version updates only support pip installations. Versions installed via custom nodes do not support switching to the new UI.

<Tabs>
  <Tab title="Non-Desktop users">
    To use the new UI:

    ```bash theme={null}
    python main.py --enable-manager
    ```

    To use the legacy UI:

    ```bash theme={null}
    python main.py --enable-manager --enable-manager-legacy-ui
    ```
  </Tab>

  <Tab title="Desktop users">
    Desktop users can switch to the legacy UI in **Server Settings → UI Settings → Use legacy manager interface**

    <img alt="Switch to legacy UI" />
  </Tab>
</Tabs>

## Updating ComfyUI-Manager

ComfyUI-Manager ships as its own Python package, and ComfyUI core pins the version it works with in `manager_requirements.txt`. How you update the Manager depends on how ComfyUI is installed:

<Tabs>
  <Tab title="Desktop">
    Desktop includes the Manager and keeps it current with Comfy Desktop updates. Update the ComfyUI engine from the [Manage panel](/installation/desktop/usage/manage#update-tab).
  </Tab>

  <Tab title="Portable and manual installs">
    Updating ComfyUI may leave the installed Manager package unchanged. Install the manager requirements in the environment you launch ComfyUI from, then restart ComfyUI with `--enable-manager`:

    ```bash theme={null}
    # Portable (Windows)
    .\python_embeded\python.exe -m pip install -r ComfyUI\manager_requirements.txt
    .\python_embeded\python.exe -s ComfyUI\main.py --windows-standalone-build --enable-manager

    # Manual install
    pip install -r manager_requirements.txt
    python main.py --enable-manager
    ```
  </Tab>

  <Tab title="Git clone">
    If you cloned the Manager into `custom_nodes` yourself:

    ```bash theme={null}
    cd ComfyUI/custom_nodes/comfyui-manager
    git pull
    ```

    Then restart ComfyUI.
  </Tab>
</Tabs>

## Legacy installation methods

<Accordion title="Method 1: Git clone (general installation)">
  To install ComfyUI-Manager in addition to an existing installation of ComfyUI:

  1. Navigate to `ComfyUI/custom_nodes` directory in terminal
  2. Clone the repository:
     ```bash theme={null}
     git clone https://github.com/Comfy-Org/ComfyUI-Manager comfyui-manager
     ```
  3. Install the manager dependencies:
     ```bash theme={null}
     cd comfyui-manager
     pip install -r requirements.txt
     ```
  4. Restart ComfyUI
</Accordion>

<Accordion title="Method 2: Portable version (Windows)">
  1. Install [Git for Windows](https://git-scm.com/download/win) (standalone version, select "use windows default console window")
  2. Download [install-manager-for-portable-version.bat](https://github.com/Comfy-Org/ComfyUI-Manager/raw/main/scripts/install-manager-for-portable-version.bat) into your `ComfyUI_windows_portable` directory
  3. Double-click the batch file to install
</Accordion>

<Accordion title="Method 3: comfy-cli (recommended for new installations)">
  comfy-cli provides various features to manage ComfyUI from the CLI.

  **Prerequisites**: Python 3, Git

  **Windows:**

  ```bash theme={null}
  python -m venv venv
  venv\Scripts\activate
  pip install comfy-cli
  comfy install
  ```

  **Linux/macOS:**

  ```bash theme={null}
  python -m venv venv
  . venv/bin/activate
  pip install comfy-cli
  comfy install
  ```

  See also: [comfy-cli documentation](/comfy-cli/getting-started)
</Accordion>

<Accordion title="Method 4: Linux + venv">
  **Prerequisites**: python-is-python3, python3-venv, git

  1. Download [install-comfyui-venv-linux.sh](https://github.com/comfy-org/ComfyUI-Manager/raw/main/scripts/install-comfyui-venv-linux.sh) into an empty install directory
  2. Run:
     ```bash theme={null}
     chmod +x install-comfyui-venv-linux.sh
     ./install-comfyui-venv-linux.sh
     ```
  3. Execute ComfyUI with `./run_gpu.sh` or `./run_cpu.sh`
</Accordion>

<Warning>
  **Installation precautions:**

  * ComfyUI-Manager files must be accurately located in the path `ComfyUI/custom_nodes/comfyui-manager`
  * Do not decompress directly into `ComfyUI/custom_nodes` (files like `__init__.py` should not be in that directory)
  * Do not install in paths like `ComfyUI/custom_nodes/ComfyUI-Manager/ComfyUI-Manager` or `ComfyUI/custom_nodes/ComfyUI-Manager-main`
</Warning>


# Managing custom nodes with ComfyUI-Manager (legacy UI)
Source: https://docs.comfy.org/manager/legacy-ui

Install, update, and manage custom nodes with ComfyUI-Manager using the legacy interface

## ComfyUI custom node management

Learn how to install custom nodes through Manager

### Install nodes

<Steps>
  <Step title="Click the Manager button in the ComfyUI interface">
    Click the **Manager** button on the main menu (top bar).

    <img alt="Manager button" />
  </Step>

  <Step title="Select Install Nodes">
    <img alt="Manager entry" />
  </Step>

  <Step title="Browse or search for the node you want to install">
    <img alt="Manager list" />
  </Step>

  <Step title="Click **Install** to install the node">
    <img alt="Node install dialog" />

    1. Prefer **latest** version if available
    2. Click **Select** to install the node

    <Note>
      * Version numbers with digits are versions published by authors to [registry](https://registry.comfy.org/), equivalent to stable releases
      * nightly is the latest version updated by authors to github, equivalent to development version, usually not security scanned, with unstable factors

      ComfyUI's default security settings do not allow direct installation of **nightly** versions. You can refer to [Security Policy](/manager/troubleshooting#security-policy) for details
    </Note>
  </Step>

  <Step title="Wait for dependency installation to complete, then restart ComfyUI">
    After clicking install, Manager will automatically complete dependency installation and prompt you to restart ComfyUI after installation is complete

    <img alt="Restart ComfyUI and refresh browser after installation" />

    <img alt="Restart ComfyUI and refresh browser after installation" />
  </Step>

  <Step title="Check if the plugin was installed successfully">
    After restarting, check in ComfyUI Manager whether the corresponding plugin was installed successfully, and whether there are `import failed` error messages

    <img alt="Check if plugin was installed successfully" />
  </Step>
</Steps>

### Install missing nodes

Missing nodes are a common situation when loading workflows. There are usually two types of missing nodes:

1. Core node missing: ComfyUI version is not the latest version, please refer to [Update ComfyUI](/installation/update_comfyui) to update ComfyUI
2. Custom node missing: Third-party custom nodes are missing, you can refer to this guide for installation

After ComfyUI-Manager is installed, if there are missing custom nodes when importing workflows, you will be alerted about the missing node information

<img alt="Missing nodes prompt" />

1. Click **Open Manager** to activate the corresponding option

<img alt="Missing nodes prompt" />

2\. Click **Install Missing Custom Nodes** in the Manager menu to enter the missing nodes list interface

<img alt="Missing nodes prompt" />

3\. View and install the corresponding nodes in the node list

<Note>
  If you find that the missing nodes list cannot find the corresponding node, there are usually several situations:

  1. The corresponding node author has not submitted and registered the custom node to [registry](/registry/overview)
  2. The corresponding node is not open source, it may be a restricted node from certain authors or limited platforms
  3. The original author changed the version and deleted the corresponding node
</Note>

### Update nodes

<img alt="Node version" />

1. Switch the filter to **Update** filter to filter nodes that can be updated in the current node list
2. Click the **Update** button to update the node

### Uninstall nodes

<img alt="Uninstall nodes" />

1. Select the "Installed" filter in the node list to filter installed nodes in the current node list
2. Right-click the corresponding node and select **Uninstall** to uninstall

> Uninstalling the corresponding node will not remove the corresponding dependency installation

For other methods of installing plugins, please refer to the article below

<Card title="Install custom nodes" icon="download" href="/installation/install_custom_node">
  Learn how to manually install custom nodes
</Card>

## Snapshot manager

Snapshots save your current installation status, allowing you to restore to a previous state.

![Snapshot manager](https://raw.githubusercontent.com/ltdrdata/ComfyUI-extension-tutorials/Main/ComfyUI-Manager/images/snapshot.jpg)

Snapshots are automatically saved when you press **Save snapshot** or use **Update All**. Snapshot files are stored in: `<USER_DIRECTORY>/default/ComfyUI-Manager/snapshots`

To restore: Open the Snapshot Manager, select a snapshot, and press **Restore**.

<Note>
  Restoration takes effect on the next ComfyUI startup. For custom nodes not managed by Git, snapshot support is incomplete.
</Note>


# Overview
Source: https://docs.comfy.org/manager/overview

An extension to manage custom nodes, models, and more in ComfyUI

**ComfyUI-Manager** is an extension designed to enhance the usability of [ComfyUI](https://github.com/Comfy-Org/ComfyUI). It offers management functions to **install, remove, disable, and enable** various custom nodes of ComfyUI. Furthermore, this extension provides a hub feature and convenience functions to access a wide range of information within ComfyUI.

<img alt="ComfyUI-Manager dialog" />

## Key features

* **Custom node management**: Install, update, remove, and disable custom nodes
* **Model management**: Download and manage models from various sources
* **Snapshot management**: Save and restore installation states
* **Missing node detection**: Automatically detect and install missing nodes from workflows

## Next steps

<CardGroup>
  <Card title="Installation" icon="download" href="/manager/install">
    Install ComfyUI-Manager for your setup
  </Card>

  <Card title="New UI" icon="puzzle-piece" href="/manager/pack-management">
    Manage custom nodes and models with the new UI
  </Card>

  <Card title="Legacy UI" icon="puzzle-piece" href="/manager/legacy-ui">
    Manage custom nodes and models with the legacy UI
  </Card>

  <Card title="Configuration" icon="gear" href="/manager/configuration">
    Configure settings and options
  </Card>

  <Card title="Troubleshooting" icon="bug" href="/manager/troubleshooting">
    Resolve common issues
  </Card>
</CardGroup>


# Custom nodes (new UI)
Source: https://docs.comfy.org/manager/pack-management

Install, update, and manage custom nodes with ComfyUI-Manager using the new interface

<Note>
  If you're not using the new UI, refer to the [Switch between new and legacy UI](/manager/install) section to learn how to switch.
</Note>

## New UI overview

<img alt="New UI" />

1. **Left sidebar (Filters)**: Filter installed nodes, nodes in workflow, missing nodes, updatable nodes, etc.
2. **Top search bar**: Search node packs (Node Pack) or individual nodes (Node), switch search type using the Filter dropdown
3. **Right detail panel**: Click a node to display detailed information including description, enable status, version information, etc. The Description tab contains repository information, and the Nodes tab previews all nodes

## Node management

Learn how to use the new ComfyUI Manager to manage custom nodes

### Search nodes

<img alt="Filter" />

The Manager supports searching for node packs and individual nodes separately. As shown above, you can switch search types by toggling the filter.

* Node Pack: A complete custom node pack
* Individual Node: Search for individual nodes within node packs

### Install nodes

<img alt="Install nodes" />

1. Select the corresponding node card
2. Click **Install** in the expanded node information
3. Or select a specific version in **Version** to install

### Update nodes

Under the **Update available** filter, you can filter nodes that have updates available in the current node list

<img alt="Update nodes" />

1. Updatable nodes will display an update arrow indicator
2. Select a specific version in **Version**
3. Click the **Update** button after selecting a version to update

### Find missing nodes

<img alt="Find missing nodes" />

If your ComfyUI Manager is properly installed, a prompt will appear when loading a workflow with missing nodes

1. You can choose **Install All** to install all nodes at once
2. Or choose **Open Manager** to open the manager and browse details before installing

<img alt="Find missing nodes" />

To find missing nodes in a workflow, select the corresponding node, then click the **Missing** button in the preview panel to find missing nodes

### Uninstall nodes

<img alt="Uninstall nodes" />

To uninstall an installed node, select the corresponding node, then click the **Uninstall** button in the preview panel to uninstall

## Common questions

1. Why can't I find the node I need?
   The new Manager only supports installing nodes from the [registry](/registry/overview). If your node is not registered in the registry, please register it in the Manager first.

2. Why can't I find the option to install via git?
   For security and stability of the ComfyUI user system, the new UI does not support installing nodes via git. Please refer to [Manually install custom nodes](/installation/install_custom_node) to learn how to manually install custom nodes.


# ComfyUI Manager Troubleshooting
Source: https://docs.comfy.org/manager/troubleshooting

Fix common ComfyUI-Manager issues: custom git executable paths, database errors, update failures, and more.

## Common issues

### Custom git executable path

If your `git.exe` is installed in a specific location other than the system default:

1. Install ComfyUI-Manager and run ComfyUI once
2. Open `<USER_DIRECTORY>/default/ComfyUI-Manager/config.ini`
3. Specify the full path including the file name in `git_exe =`

```ini theme={null}
git_exe = C:\Program Files\Git\bin\git.exe
```

### ComfyUI-Manager update fails

If updating ComfyUI-Manager itself fails, go to the ComfyUI-Manager directory and run:

```bash theme={null}
git update-ref refs/remotes/origin/main a361cc1 && git fetch --all && git pull
```

### Windows: Overlapped Object error

If you encounter `Overlapped Object has pending operation at deallocation on ComfyUI Manager load`:

Edit `config.ini` and add:

```ini theme={null}
windows_selector_event_loop_policy = True
```

### SSL certificate verification failed

If you encounter `SSL: CERTIFICATE_VERIFY_FAILED` error:

Edit `config.ini` and add:

```ini theme={null}
bypass_ssl = True
```

## Installation issues

### Incorrect installation path

ComfyUI-Manager files must be located in `ComfyUI/custom_nodes/comfyui-manager`.

**Common mistakes to avoid:**

| Issue | Problem |
| - | - |
| Files in wrong location | Manager files like `__init__.py` placed directly in `custom_nodes` directory |
| Double nested folder | Installed as `custom_nodes/ComfyUI-Manager/ComfyUI-Manager` |
| Wrong folder name | Installed as `custom_nodes/ComfyUI-Manager-main` |
| Compressed format | Installing from a compressed file without proper extraction |

<Warning>
  If installed incorrectly, ComfyUI-Manager may appear to work but won't be recognized for updates and may cause duplicate installations. Remove it and reinstall properly via `git clone`.
</Warning>

## Network issues

### GitHub access problems

If you have limited access to GitHub, set the `GITHUB_ENDPOINT` environment variable:

```bash theme={null}
GITHUB_ENDPOINT=https://mirror.ghproxy.com/https://github.com
```

### Hugging Face access problems

If you have limited access to Hugging Face, set the `HF_ENDPOINT` environment variable:

```bash theme={null}
HF_ENDPOINT=https://some-hf-mirror.com
```

## Scanner troubleshooting

When running the `scan.sh` script:

* It updates `extension-node-map.json` by pulling or cloning custom nodes listed in `custom-node-list.json` into `~/.tmp/default`
* It updates `github-stats.json` using the GitHub API

| Option | Description |
| - | - |
| `--skip-update` | Skip updating extension-node-map.json |
| `--skip-stat-update` | Skip updating github-stats.json |
| `--skip-all` | Skip both update steps |

<Tip>
  To avoid GitHub API rate limits, set your token: `export GITHUB_TOKEN=your_token_here`
</Tip>

If you want to specify a different path instead of `~/.tmp/default`, run `python scanner.py [path]` directly instead of `scan.sh`.

## Security policy

If you encounter the error `This action is not allowed with this security level configuration` when installing custom nodes via git URL or using the nightly version, you need to adjust the security level in your `config.ini` file.

The `config.ini` file is located at:

* **ComfyUI v0.3.76+**: `<USER_DIRECTORY>/__manager/config.ini`
* **Older versions**: `<USER_DIRECTORY>/default/ComfyUI-Manager/config.ini`

Where `<USER_DIRECTORY>` defaults to `ComfyUI/user`. See [Configuration](/manager/configuration) for more details.

Configure security levels in `config.ini`:

```ini theme={null}
security_level = normal
```

| Level | Description |
| - | - |
| `strong` | Doesn't allow high and middle level risky features |
| `normal` | Doesn't allow high level risky features; middle level features available |
| `normal-` | Doesn't allow high level risky features if `--listen` is specified and not starts with `127.`; middle level features available |
| `weak` | All features available |

### Risk levels for features

| Risk Level | Features |
| - | - |
| **High** | Install via git url, pip install, installation of custom nodes not in default channel, fix custom nodes |
| **Middle** | Uninstall/Update, installation of custom nodes in default channel, restore/remove snapshot, restart |
| **Low** | Update ComfyUI |

<Tip>
  To install custom nodes via git URL or nightly versions, set `security_level = weak` in your `config.ini`.
</Tip>

## Getting help

If you're still experiencing issues:

1. Check the [ComfyUI-Manager GitHub issues](https://github.com/Comfy-Org/ComfyUI-Manager/issues) for similar problems
2. Review the startup log messages for error details
3. Join the [ComfyUI Discord](https://discord.com/invite/comfyorg) for community support


# ComfyUI Image to Image Workflow
Source: https://docs.comfy.org/tutorials/basic/image-to-image

Build an image-to-image workflow in ComfyUI: load a reference image and generate new versions in a different style, from line art, or restore old images.

## What is image-to-image in ComfyUI?

Image to Image is a workflow in ComfyUI that allows users to input an image and generate a new image based on it.

Image to Image can be used in scenarios such as:

* Converting original image styles, like transforming realistic photos into artistic styles
* Converting line art into realistic images
* Image restoration
* Colorizing old photos
* ... and other scenarios

To explain it with an analogy:
It's like asking an artist to create a specific piece based on your reference image.

If you carefully compare this tutorial with the [Text to Image](/tutorials/basic/text-to-image) tutorial,
you'll notice that the Image to Image process is very similar to Text to Image,
just with an additional input reference image as a condition. In Text to Image, we let the artist (image model) create freely based on our prompts,
while in Image to Image, we let the artist create based on both our reference image and prompts.

## ComfyUI Image to Image Workflow Example Guide

### Model Installation

Download the [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors) file and put it in your `ComfyUI/models/checkpoints` folder.

### Image to Image Workflow and Input Image

Download the image below and **drag it into ComfyUI** to load the workflow:
![Image to Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image_to_image/workflow.png)

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

Download the image below and we will use it as the input image:

<img alt="Example Image" />

### Complete the Workflow Step by Step

Follow the steps in the diagram below to ensure the workflow runs correctly.

<img alt="ComfyUI Image to Image Workflow - Steps" />

1. Ensure `Load Checkpoint` loads  **v1-5-pruned-emaonly-fp16.safetensors**
2. Upload the input image to the `Load Image` node
3. Click `Queue` or press `Ctrl/Cmd + Enter` to generate

## Key Points of Image to Image Workflow

The key to the Image to Image workflow lies in the `denoise` parameter in the `KSampler` node, which should be **less than 1**

If you've adjusted the `denoise` parameter and generated images, you'll notice:

* The smaller the `denoise` value, the smaller the difference between the generated image and the reference image
* The larger the `denoise` value, the larger the difference between the generated image and the reference image

This is because `denoise` determines the strength of noise added to the latent space image after converting the reference image. If `denoise` is 1, the latent space image will become completely random noise, making it the same as the latent space generated by the `empty latent image` node, losing all characteristics of the reference image.

<Note>
  A low `denoise` does not lower the number of steps a run performs; only `denoise` 0 stops sampling entirely. ComfyUI builds a schedule for `steps / denoise` steps (rounded down) and keeps only its last `steps + 1` sigmas, so `steps` 20 with `denoise` 0.5 performs 20 sampling steps over the low-noise half of a 40-step schedule, at that longer schedule's step density. To keep the step density of a full run while sampling only part of the range, set `steps` to that run's step count multiplied by `denoise`: with `denoise` 0.5, `steps` 10 samples exactly the sigmas a 20-step run uses for its second half, with half the model evaluations.
</Note>

For the corresponding principles, please refer to the principle explanation in the [Text to Image](/tutorials/basic/text-to-image) tutorial.

## Try It Yourself

1. Try modifying the `denoise` parameter in the **KSampler** node, gradually changing it from 1 to 0, and observe the changes in the generated images
2. Replace with your own prompts and reference images to generate your own image effects


# ComfyUI Inpainting Workflow
Source: https://docs.comfy.org/tutorials/basic/inpaint

ComfyUI inpainting tutorial: edit parts of an image, draw masks with the mask editor, and connect the VAE Encode (for Inpainting) node in a workflow.

This article will introduce the concept of inpainting in AI image generation and guide you through creating an inpainting workflow in ComfyUI. We'll cover:

* Using inpainting workflows to modify images
* Using the ComfyUI mask editor to draw masks
* `VAE Encoder (for Inpainting)` node

## About Inpainting

In AI image generation, we often encounter situations where we're satisfied with the overall image but there are elements we don't want or that contain errors. Simply regenerating might produce a completely different image, so using inpainting to fix specific parts becomes very useful.

It's like having an **artist (AI model)** paint a picture, but we're still not satisfied with the specific details. We need to tell the artist **which areas to adjust (mask)**, and then let them **repaint (inpaint)** according to our requirements.

Common inpainting scenarios include:

* **Defect Repair:** Removing unwanted objects, fixing incorrect AI-generated body parts, etc.
* **Detail Optimization:** Precisely adjusting local elements (like modifying clothing textures, adjusting facial expressions)
* And other scenarios

## ComfyUI Inpainting Workflow Example

### Model and Resource Preparation

#### 1. Model Installation

Download the [512-inpainting-ema.safetensors](https://huggingface.co/Comfy-Org/stable_diffusion_2.1_repackaged/blob/main/512-inpainting-ema.safetensors)  file and put it in your `ComfyUI/models/checkpoints` folder:

#### 2. Inpainting Asset

Please download the following image which we'll use as input:

<img alt="ComfyUI Inpainting Input Image" />

<Note>This image already contains an alpha channel (transparency mask), so you don't need to manually draw a mask. This tutorial will also cover how to use the mask editor to draw masks.</Note>

#### 3. Inpainting Workflow

Download the image below and **drag it into ComfyUI** to load the workflow:

![ComfyUI Inpainting Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/basic/sd1.5_inpaint.png)

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

### ComfyUI Inpainting Workflow Example Explanation

Follow the steps in the diagram below to ensure the workflow runs correctly.

<img alt="ComfyUI Inpainting Workflow" />

1. Ensure `Load Checkpoint` loads `512-inpainting-ema.safetensors`
2. Upload the input image to the `Load Image` node
3. Click `Queue` or use `Ctrl + Enter` to generate

For comparison, here's the result using the [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors) model:

<img alt="SD1.5 Inpainting Result" />

You will find that the results generated by the [512-inpainting-ema.safetensors](https://huggingface.co/Comfy-Org/stable_diffusion_2.1_repackaged/blob/main/512-inpainting-ema.safetensors) model have better inpainting effects and more natural transitions.
This is because this model is specifically designed for inpainting, which helps us better control the generation area, resulting in improved inpainting effects.

Do you remember the analogy we've been using? Different models are like artists with varying abilities, but each artist has their own limits. Choosing the right model can help you achieve better generation results.

You can try these approaches to achieve better results:

1. Modify positive and negative prompts with more specific descriptions
2. Try multiple runs using different seeds in the `KSampler` for different generation results
3. After learning about the mask editor in this tutorial, you can re-inpaint the generated results to achieve satisfactory outcomes.

Next, we'll learn about using the **Mask Editor**. While our input image already includes an `alpha` transparency channel (the area we want to edit),
so manual mask drawing isn't necessary, you'll often use the Mask Editor to create masks in practical applications.

### Using the Mask Editor

First right-click the `Save Image` node and select `Copy(Clipspace)`:

<img alt="Copy Image to Clipboard" />

Then right-click the **Load Image** node and select `Paste(Clipspace)`:

<img alt="Paste Image" />

Right-click the **Load Image** node again and select `Open in MaskEditor`:

<img alt="Open Mask Editor" />

<img alt="Mask Editor Demo" />

1. Adjust brush parameters on the right panel
2. Use eraser to correct mistakes
3. Click `Save` when finished

The drawn content will be used as a Mask input to the VAE Encoder (for Inpainting) node for encoding

Then try adjusting your prompts and generating again until you achieve satisfactory results.

## VAE Encoder (for Inpainting) Node

Comparing this workflow with [Text-to-Image](/tutorials/basic/text-to-image) and [Image-to-Image](/tutorials/basic/image-to-image), you'll notice the main differences are in the VAE section's conditional inputs.
In this workflow, we use the **VAE Encoder (for Inpainting)** node, specifically designed for inpainting to help us better control the generation area and achieve better results.

<img alt="VAE Encoder (for Inpainting) Node" />

**Input Types**

| Parameter Name | Function |
| - | - |
| `pixels` | Input image to be encoded into latent space. |
| `vae` | VAE model used to encode the image from pixel space to latent space. |
| `mask` | Image mask specifying which areas need modification. |
| `grow_mask_by` | Pixel value to expand the original mask outward, ensuring a transition area around the mask to avoid hard edges between inpainted and original areas. |

**Output Types**

| Parameter Name | Function |
| - | - |
| `latent` | Image encoded into latent space by the VAE. |


# ComfyUI LoRA Example
Source: https://docs.comfy.org/tutorials/basic/lora

Use LoRA models in ComfyUI: install a LoRA, load it with the Load LoRA node, and run a workflow that applies its style on top of a checkpoint.

**LoRA (Low-Rank Adaptation)** is an efficient technique for fine-tuning large generative models like Stable Diffusion.
It introduces trainable low-rank matrices to the pre-trained model, adjusting only a portion of parameters rather than retraining the entire model,
thus achieving optimization for specific tasks at a lower computational cost.
Compared to base models like SD1.5, LoRA models are smaller and easier to train.

<img alt="LoRA Model vs Base Model Comparison" />

The image above compares generation with the same parameters using [dreamshaper\_8](https://civitai.com/models/4384?modelVersionId=128713) directly versus using the [blindbox\_V1Mix](https://civitai.com/models/25995/blindbox) LoRA model.
As you can see, by using a LoRA model, we can generate images in different styles without adjusting the base model.

We will demonstrate how to use a LoRA model. All LoRA variants: Lycoris, loha, lokr, locon, etc... are used in the same way.

In this example, we will learn how to load and use a LoRA model in [ComfyUI](https://github.com/Comfy-Org/ComfyUI), covering the following topics:

1. Installing a LoRA model
2. Generating images using a LoRA model
3. A simple introduction to the `Load LoRA` node

## Required Model Installation

Download the [dreamshaper\_8.safetensors](https://civitai.com/api/download/models/128713?type=Model\&format=SafeTensor\&size=pruned\&fp=fp16) file and put it in your `ComfyUI/models/checkpoints` folder.

Download the [blindbox\_V1Mix.safetensors](https://civitai.com/api/download/models/32988?type=Model\&format=SafeTensor\&size=full\&fp=fp16) file and put it in your `ComfyUI/models/loras` folder.

## LoRA Workflow File

Download the image below and **drag it into ComfyUI** to load the workflow.

<img alt="ComfyUI Workflow - LoRA" />

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

## Complete the Workflow Step by Step

Follow the steps in the diagram below to ensure the workflow runs correctly.

![ComfyUI Workflow - LoRA Flow Diagram](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/lora.png)

1. Ensure `Load Checkpoint` loads `dreamshaper_8.safetensors`
2. Ensure `Load LoRA` loads `blindbox_V1Mix.safetensors`
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to generate the image

## Load LoRA Node Introduction

<img alt="Load LoRA Node" />

Models in the `ComfyUI\models\loras` folder will be detected by ComfyUI and can be loaded using this node.

### Input Types

| Parameter Name | Function |
| - | - |
| `model` | Connect to the base model |
| `clip` | Connect to the CLIP model |
| `lora_name` | Select the LoRA model to load and use |
| `strength_model` | Affects how strongly the LoRA influences the model weights; higher values make the LoRA style stronger |
| `strength_clip` | Affects how strongly the LoRA influences the CLIP text embeddings |

### Output Types

| Parameter Name | Function |
| - | - |
| `model` | Outputs the model with LoRA adjustments applied |
| `clip` | Outputs the CLIP model with LoRA adjustments applied |

This node supports chain connections, allowing multiple `Load LoRA` nodes to be linked in series to apply multiple LoRA models. For more details, please refer to [ComfyUI Multiple LoRAs Example](/tutorials/basic/multiple-loras)

<img alt="LoRA Node Chain Connection" />

## Try It Yourself

1. Try modifying the prompt or adjusting different parameters of the `Load LoRA` node, such as `strength_model`, to observe changes in the generated images and become familiar with the `Load LoRA` node.
2. Visit [CivitAI](https://civitai.com/models) to download other kinds of LoRA models and try using them.


# ComfyUI Multiple LoRAs Example
Source: https://docs.comfy.org/tutorials/basic/multiple-loras

This guide demonstrates how to apply multiple LoRA models simultaneously in ComfyUI

In our [ComfyUI LoRA Example](/tutorials/basic/lora), we introduced how to load and use a single LoRA model, mentioning the node's chain connection capability.

<img alt="LoRA Node Chaining" />

This tutorial demonstrates chaining multiple `Load LoRA` nodes to apply two LoRA models simultaneously: [blindbox\_V1Mix](https://civitai.com/models/25995?modelVersionId=32988) and [MoXinV1](https://civitai.com/models/12597?modelVersionId=14856).

The comparison below shows individual effects of these LoRAs using identical parameters:

<img alt="Single LoRA Effects Comparison" />

By chaining multiple LoRA models, we achieve a blended style in the final output:

<img alt="Multi-LoRA Application Result" />

## Model Installation

Download the [dreamshaper\_8.safetensors](https://civitai.com/api/download/models/128713?type=Model\&format=SafeTensor\&size=pruned\&fp=fp16) file and put it in your `ComfyUI/models/checkpoints` folder.

Download the [blindbox\_V1Mix.safetensors](https://civitai.com/api/download/models/32988?type=Model\&format=SafeTensor\&size=full\&fp=fp16) file and put it in your `ComfyUI/models/loras` folder.

Download the [MoXinV1.safetensors](https://civitai.com/api/download/models/14856?type=Model\&format=SafeTensor\&size=full\&fp=fp16) file and put it in your `ComfyUI/models/loras` folder.

## Multi-LoRA Workflow

Download the image below and **drag it into ComfyUI** to load the workflow:
![ComfyUI Workflow - Multiple LoRAs](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/multiple_loras.png)

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

## Complete the Workflow Step by Step

Follow the steps in the diagram below to ensure the workflow runs correctly.

<img alt="Multi-LoRA Workflow Diagram" />

1. Ensure `Load Checkpoint` loads  **dreamshaper\_8.safetensors**
2. Ensure first `Load LoRA` loads **blindbox\_V1Mix.safetensors**
3. Ensure second `Load LoRA` loads **MoXinV1.safetensors**
4. Click `Queue` or press `Ctrl/Cmd + Enter` to generate

## Try It Yourself

1. Adjust `strength_model` values in both `Load LoRA` nodes to control each LoRA's influence
2. Explore [CivitAI](https://civitai.com/models) for additional LoRAs and create custom combinations


# Outpainting Workflow Example
Source: https://docs.comfy.org/tutorials/basic/outpaint

Outpainting workflow in ComfyUI: extend an image beyond its borders using the Pad Image for Outpainting node and inpainting-model techniques.

This guide will introduce you to the concept of outpainting in AI image generation and how to create an outpainting workflow in ComfyUI. We will cover:

* Using outpainting workflow to extend an image
* Understanding and using outpainting-related nodes in ComfyUI
* Mastering the basic outpainting process

## About Outpainting

In AI image generation, we often encounter situations where an existing image has good composition but the canvas area is too small, requiring us to extend the canvas to get a larger scene. This is where outpainting comes in.

Basically, it requires similar content to [Inpainting](/tutorials/basic/inpaint), but we use different nodes to **build the mask**.

Outpainting applications include:

* **Scene Extension:** Expand the scene range of the original image to show a more complete environment
* **Composition Adjustment:** Optimize the overall composition by extending the canvas
* **Content Addition:** Add more related scene elements to the original image

## ComfyUI Outpainting Workflow Example Explanation

### Preparation

#### 1. Model Installation

Download the following model file and save it to `ComfyUI/models/checkpoints` directory:

* [512-inpainting-ema.safetensors](https://huggingface.co/Comfy-Org/stable_diffusion_2.1_repackaged/blob/main/512-inpainting-ema.safetensors)

#### 2. Input Image

Prepare an image you want to extend. In this example, we will use the following image:

<img alt="ComfyUI Outpainting Input Image" />

#### 3. Outpainting Workflow

Download the image below and **drag it into ComfyUI** to load the workflow:

![ComfyUI Outpainting Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/basic/outpaint.png)

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

### Outpainting Workflow Usage Explanation

<img alt="ComfyUI Outpainting Workflow Diagram" />

The key steps of the outpainting workflow are as follows:

1. Load the locally installed model file in the `Load Checkpoint` node
2. Click the `Upload` button in the `Load Image` node to upload your image
3. Click the `Queue` button or use the shortcut `Ctrl + Enter` to execute the image generation

In this workflow, we mainly use the `Pad Image for outpainting` node to control the direction and range of image extension. This is actually an [Inpaint](/tutorials/basic/inpaint) workflow, but we use different nodes to build the mask.

### Pad Image for outpainting Node

<img alt="Pad Image for outpainting Node" />

This node accepts an input image and outputs an extended image with a corresponding mask, where the mask is built based on the node parameters.

#### Input Parameters

| Parameter Name | Function |
| - | - |
| `image` | Input image |
| `left` | Left padding amount |
| `top` | Top padding amount |
| `right` | Right padding amount |
| `bottom` | Bottom padding amount |
| `feathering` | Controls the smoothness of the transition between the original image and the added padding, higher values create smoother transitions |

#### Output Parameters

| Parameter Name | Function |
| - | - |
| `image` | Output `image` represents the padded image |
| `mask` | Output `mask` indicates the original image area and the added padding area |

#### Node Output Content

After processing by the `Pad Image for outpainting` node, the output image and mask preview are as follows:

<img alt="Pad Image for outpainting Node Results" />

You can see the corresponding output results:

* The `Image` output is the extended image
* The `Mask` output is the mask marking the extension areas


# ComfyUI Text to Image Workflow
Source: https://docs.comfy.org/tutorials/basic/text-to-image

Build a text-to-image workflow in ComfyUI: load the default workflow, install an SD1.5 checkpoint, write prompts, and learn what each node does.

This guide aims to introduce you to ComfyUI's text-to-image workflow and help you understand the functionality and usage of various ComfyUI nodes.

In this document, we will:

* Complete a text-to-image workflow
* Gain a basic understanding of diffusion model principles
* Learn about the functions and roles of workflow nodes
* Get an initial understanding of the SD1.5 model

We'll start by running a text-to-image workflow, followed by explanations of related concepts. Please choose the relevant sections based on your needs.

## What is text-to-image in ComfyUI?

**Text to Image** is a fundamental process in AI art generation that creates images from text descriptions, with **diffusion models** at its core.

The text-to-image process requires the following elements:

* **Artist:** The image generation model
* **Canvas:** The latent space
* **Image Requirements (Prompts):** Including positive prompts (elements you want in the image) and negative prompts (elements you don't want)

This text-to-image generation process can be simply understood as telling your requirements (positive and negative prompts) to an **artist (the image model)**, who then creates what you want based on these requirements.

## ComfyUI Text to Image Workflow Example Guide

### 1. Preparation

Ensure you have at least one SD1.5 model file in your `ComfyUI/models/checkpoints` folder, such as [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors)

If you haven't installed it yet, please refer to the model installation section in [Getting Started with ComfyUI AI Art Generation](/get_started/first_generation).

### 2. Loading the Text to Image Workflow

Download the image below and **drag it into ComfyUI** to load the workflow:

<img alt="ComfyUI-Text to Image Workflow" />

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

### 3. Loading the Model and Generating Your First Image

After installing the image model, follow the steps in the image below to load the model and generate your first image

![Image Generation](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/basic/text-to-image-workflow.png)

Follow these steps according to the image numbers:

1. In the **Load Checkpoint** node, use the arrows or click the text area to ensure **v1-5-pruned-emaonly-fp16.safetensors** is selected, and the left/right arrows don't show **null** text
2. Click the `Queue` button or use the shortcut `Ctrl + Enter` to execute image generation

After the process completes, you should see the resulting image in the **Save Image** node interface, which you can right-click to save locally

<img alt="ComfyUI First Image Generation Result" />

<Tip>If you're not satisfied with the result, try running the generation multiple times. Each time you run it, **KSampler** will use a different random seed based on the `seed` parameter, so each generation will produce different results</Tip>

### 4. Start Experimenting

Try modifying the text in the **CLIP Text Encoder**

<img alt="CLIP Text Encoder" />

The `Positive` connection to the KSampler node represents positive prompts, while the `Negative` connection represents negative prompts

Here are some basic prompting principles for the SD1.5 model:

* Use English whenever possible
* Separate prompts with English commas `,`
* Use phrases rather than long sentences
* Use specific descriptions
* Use expressions like `(golden hour:1.2)` to increase the weight of specific keywords, making them more likely to appear in the image. `1.2` is the weight, `golden hour` is the keyword
* Use keywords like `masterpiece, best quality, 4k` to improve generation quality

Here are several prompt examples you can try, or use your own prompts for generation:

**1. Anime Style**

Positive prompts:

```
anime style, 1girl with long pink hair, cherry blossom background, studio ghibli aesthetic, soft lighting, intricate details

masterpiece, best quality, 4k
```

Negative prompts:

```
low quality, blurry, deformed hands, extra fingers
```

**2. Realistic Style**

Positive prompts:

```
(ultra realistic portrait:1.3), (elegant woman in crimson silk dress:1.2), 
full body, soft cinematic lighting, (golden hour:1.2), 
(fujifilm XT4:1.1), shallow depth of field, 
(skin texture details:1.3), (film grain:1.1), 
gentle wind flow, warm color grading, (perfect facial symmetry:1.3)
```

Negative prompts:

```
(deformed, cartoon, anime, doll, plastic skin, overexposed, blurry, extra fingers)
```

**3. Specific Artist Style**

Positive prompts:

```
fantasy elf, detailed character, glowing magic, vibrant colors, long flowing hair, elegant armor, ethereal beauty, mystical forest, magical aura, high detail, soft lighting, fantasy portrait, Artgerm style
```

Negative prompts:

```
blurry, low detail, cartoonish, unrealistic anatomy, out of focus, cluttered, flat lighting
```

## How does text-to-image work?

The entire text-to-image process can be understood as a **reverse diffusion process**. The [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors) we downloaded is a pre-trained model that can **generate target images from pure Gaussian noise**. We only need to input our prompts, and it can generate target images through denoising random noise.

```mermaid theme={null}
graph LR
A[Pure Gaussian Noise] --> B[Iterative Denoising]
B --> C[Intermediate Latents]
C --> D[Final Generated Image]
E[Text Prompts] --> F[CLIP Encoder]
F --> G[Semantic Vectors]
G --> B
```

We need to understand two concepts:

1. **Latent Space:** Latent Space is an abstract data representation method in diffusion models. Converting images from pixel space to latent space reduces storage space and makes it easier to train diffusion models and reduce denoising complexity. It's like architects using blueprints (latent space) for design rather than designing directly on the building (pixel space), maintaining structural features while significantly reducing modification costs
2. **Pixel Space:** Pixel Space is the storage space for images, which is the final image we see, used to store pixel values.

If you want to learn more about diffusion models, you can read these papers:

* [Denoising Diffusion Probabilistic Models (DDPM)](https://arxiv.org/pdf/2006.11239)
* [Denoising Diffusion Implicit Models (DDIM)](https://arxiv.org/pdf/2010.02502)
* [High-Resolution Image Synthesis with Latent Diffusion Models](https://arxiv.org/pdf/2112.10752)

## ComfyUI Text to Image Workflow Node Explanation

<img alt="ComfyUI Text to Image Workflow Explanation" />

### A. Load Checkpoint Node

<img alt="Load Checkpoint" />

This node is typically used to load the image generation model. A `checkpoint` usually contains three components: `MODEL (UNet)`, `CLIP`, and `VAE`

* `MODEL (UNet)`: The UNet model responsible for noise prediction and image generation during the diffusion process
* `CLIP`: The text encoder that converts our text prompts into vectors that the model can understand, as the model cannot directly understand text prompts
* `VAE`: The Variational AutoEncoder that converts images between pixel space and latent space, as diffusion models work in latent space while our images are in pixel space

### B. Empty Latent Image Node

<img alt="Empty Latent Image" />

Defines a latent space that outputs to the KSampler node. The Empty Latent Image node constructs a **pure noise latent space**

You can think of its function as defining the canvas size, which determines the dimensions of our final generated image

### C. CLIP Text Encoder Node

<img alt="CLIP Text Encoder" />

Used to encode prompts, which are your requirements for the image

* The `Positive` condition input connected to the KSampler node represents positive prompts (elements you want in the image)
* The `Negative` condition input connected to the KSampler node represents negative prompts (elements you don't want in the image)

The prompts are encoded into semantic vectors by the `CLIP` component from the `Load Checkpoint` node and output as conditions to the KSampler node

### D. KSampler Node

<img alt="KSampler" />

The **KSampler** is the core of the entire workflow, where the entire noise denoising process occurs, ultimately outputting a latent space image

```mermaid theme={null}
graph LR
A[Diffusion Model] --> B{KSampler}
C[Random Noise<br>Latent Space] --> B
D[CLIP Semantic Vectors] --> B
B --> E[Denoised Latent]
```

Here's an explanation of the KSampler node parameters:

| Parameter Name | Description | Function |
| - | - | - |
| **model** | Diffusion model used for denoising | Determines the style and quality of generated images |
| **positive** | Positive prompt condition encoding | Guides generation to include specified elements |
| **negative** | Negative prompt condition encoding | Suppresses unwanted content |
| **latent\_image** | Latent space image to be denoised | Serves as the input carrier for noise initialization |
| **seed** | Random seed for noise generation | Controls generation randomness |
| **control\_after\_generate** | Seed control mode after generation | Determines seed variation pattern in batch generation |
| **steps** | Number of denoising iterations | More steps mean finer details but longer processing time |
| **cfg** | Classifier-free guidance scale | Controls prompt constraint strength (too high leads to overfitting) |
| **sampler\_name** | Sampling algorithm name | Determines the mathematical method for denoising path |
| **scheduler** | Scheduler type | Controls noise decay rate and step size allocation |
| **denoise** | Denoising strength coefficient | Controls noise strength added to latent space, 0.0 preserves original input features, 1.0 is complete noise |

In the KSampler node, the latent space uses `seed` as an initialization parameter to construct random noise, and semantic vectors `Positive` and `Negative` are input as conditions to the diffusion model

Then, based on the number of denoising steps specified by the `steps` parameter, denoising is performed. Each denoising step uses the denoising strength coefficient specified by the `denoise` parameter to denoise the latent space and generate a new latent space image

### E. VAE Decode Node

<img alt="VAE Decode" />

Converts the latent space image output from the **KSampler** into a pixel space image

### F. Save Image Node

<img alt="Save Image" />

Previews and saves the decoded image from latent space to the local `ComfyUI/output` folder

## Introduction to SD1.5 Model

**SD1.5 (Stable Diffusion 1.5)** is an AI image generation model developed by [Stability AI](https://stability.ai/). It's the foundational version of the Stable Diffusion series, trained on **512×512** resolution images, making it particularly good at generating images at this resolution. With a size of about 4GB, it runs smoothly on **consumer-grade GPUs (e.g., 6GB VRAM)**. Currently, SD1.5 has a rich ecosystem, supporting various plugins (like ControlNet, LoRA) and optimization tools.
As a milestone model in AI art generation, SD1.5 remains the best entry-level choice thanks to its open-source nature, lightweight architecture, and rich ecosystem. Although newer versions like SDXL/SD3 have been released, its value for consumer-grade hardware remains unmatched.

### Basic Information

* **Release Date**: October 2022
* **Core Architecture**: Based on Latent Diffusion Model (LDM)
* **Training Data**: LAION-Aesthetics v2.5 dataset (approximately 590M training steps)
* **Open Source Features**: Fully open-source model/code/training data

### Advantages and Limitations

Model Advantages:

* Lightweight: Small size, only about 4GB, runs smoothly on consumer GPUs
* Low Entry Barrier: Supports a wide range of plugins and optimization tools
* Mature Ecosystem: Extensive plugin and tool support
* Fast Generation: Smooth operation on consumer GPUs

Model Limitations:

* Detail Handling: Hands/complex lighting prone to distortion
* Resolution Limits: Quality degrades for direct 1024x1024 generation
* Prompt Dependency: Requires precise English descriptions for control


# ComfyUI Image Upscale Workflow
Source: https://docs.comfy.org/tutorials/basic/upscale

Upscale images in ComfyUI: load an upscale model, build the workflow, and chain it after text-to-image for higher resolution outputs.

## What is Image Upscaling?

Image Upscaling is the process of converting low-resolution images to high-resolution using algorithms.
Unlike traditional interpolation methods, AI upscaling models (like ESRGAN) can intelligently reconstruct details while maintaining image quality.

For instance, the default SD1.5 model often struggles with large-size image generation.
To achieve high-resolution results,we typically generate smaller images first and then use upscaling techniques.

This article covers one of many upscaling methods in ComfyUI. In this tutorial, we'll guide you through:

1. Downloading and installing upscaling models
2. Performing basic image upscaling
3. Combining text-to-image workflows with upscaling

<Note>
  Looking for more advanced upscaling options? Check out our comprehensive [Image Upscaling Guide](/tutorials/utility/image-upscale) which covers various models and use cases including portrait enhancement, product photography, and more.
</Note>

## Upscaling Workflow

### Model Installation

Required ESRGAN models download:

<Steps>
  <Step title="Visit OpenModelDB">
    Visit [OpenModelDB](https://openmodeldb.info/) to search and download upscaling models (e.g., RealESRGAN)

    <img alt="openmodeldb" />

    As shown:

    1. Filter models by image type using the category selector
    2. The model's magnification factor is indicated in the top-right corner (e.g., 2x in the screenshot)

    We'll use the [4x-ESRGAN](https://openmodeldb.info/models/4x-ESRGAN) model for this tutorial. Click the `Download` button on the model detail page.

    <img alt="OpenModelDB_download" />
  </Step>

  <Step title="Save Model Files in Directory">
    Save the model file (.pth) in `ComfyUI/models/upscale_models` directory
  </Step>
</Steps>

### Workflow and Assets

Download and drag the following image into ComfyUI to load the basic upscaling workflow:
![Upscale workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/basic/upscale_workflow.png)

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

Use this image in smaller size as input:

<img alt="Upscale-input" />

### Complete the Workflow Step by Step

Follow the steps in the diagram below to ensure the workflow runs correctly.

<img alt="Upscale workflow" />

1. Ensure `Load Upscale Model` loads `4x-ESRGAN.pth`
2. Upload the input image to the `Load Image` node
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to generate the image

The core components are the `Load Upscale Model` and `Upscale Image (Using Model)` nodes, which receive an image input and upscale it using the selected model.

## Text-to-Image Combined Workflow

After mastering basic upscaling, we can combine it with the [text-to-image](/tutorials/basic/text-to-image) workflow. For text-to-image basics, refer to the [text-to-image tutorial](/tutorials/basic/text-to-image).

Download and drag this image into ComfyUI to load the combined workflow:

<img alt="Text-to-image upscale workflow" />

This workflow connects the text-to-image output image directly to the upscaling nodes for final processing.

## Additional Tips

<Tip>
  Model characteristics:

  * **RealESRGAN**: General-purpose upscaling
  * **BSRGAN**: Excels with text and sharp edges
  * **SwinIR**: Preserves natural textures, ideal for landscapes
</Tip>

1. **Chained Upscaling**: Combine multiple upscale nodes (e.g., 2x → 4x) for ultra-high magnification
2. **Hybrid Workflow**: Connect upscale nodes after generation for "generate+enhance" pipelines
3. **Comparative Testing**: Different models perform better on specific image types - test multiple options


# ComfyUI ControlNet Usage Example
Source: https://docs.comfy.org/tutorials/controlnet/controlnet

ControlNet in ComfyUI: control image generation with condition images instead of trial-and-error prompting, plus a step-by-step workflow example.

Achieving precise control over image creation in AI image generation cannot be done with just one click.
It typically requires numerous generation attempts to produce a satisfactory image. However, the emergence of **ControlNet** has effectively addressed this challenge.

ControlNet is a conditional control generation model based on diffusion models (such as Stable Diffusion),
first proposed by [Lvmin Zhang](https://github.com/lllyasviel) and Maneesh Agrawala et al. in 2023 in the paper [Adding Conditional Control to Text-to-Image Diffusion Models](https://arxiv.org/abs/2302.05543).

ControlNet models significantly enhance the controllability of image generation and the ability to reproduce details by introducing multimodal input conditions,
such as edge detection maps, depth maps, and pose keypoints.

These conditioning constraints make image generation more controllable, allowing multiple ControlNet models to be used simultaneously during the drawing process for better results.

Before ControlNet, we could only rely on the model to generate images repeatedly until we were satisfied with the results, which involved a lot of randomness.

<img alt="Images generated with random seeds in ComfyUI" />

With the advent of ControlNet, we can control image generation by introducing additional conditions.
For example, we can use a simple sketch to guide the image generation process, producing images that closely align with our sketch.

<img alt="Sketch-controlled image generation in ComfyUI" />

In this example, we will guide you through installing and using ControlNet models in [ComfyUI](https://github.com/Comfy-Org/ComfyUI), and complete a sketch-controlled image generation example.

![ComfyUI ControlNet Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/scribble_controlnet.png)

<Tip>
  The workflows for other types of ControlNet V1.1 models are similar to this example. You only need to select the appropriate model and upload the corresponding reference image based on your needs.
</Tip>

## ControlNet Image Preprocessing Information

Different types of ControlNet models typically require different types of reference images:

![Reference Images](https://github.com/Fannovel16/comfyui_controlnet_aux/blob/main/examples/CNAuxBanner.jpg?raw=true)

> Image source: [ComfyUI ControlNet aux](https://github.com/Fannovel16/comfyui_controlnet_aux)

Since the current **Comfy Core** nodes do not include all types of **preprocessors**, in the actual examples in this documentation, we will provide pre-processed images.
However, in practical use, you may need to use custom nodes to preprocess images to meet the requirements of different ControlNet models. Below are some relevant custom nodes:

* [ComfyUI-Advanced-ControlNet](https://github.com/Kosinkadink/ComfyUI-Advanced-ControlNet)
* [ComfyUI ControlNet aux](https://github.com/Fannovel16/comfyui_controlnet_aux)

## ComfyUI ControlNet Workflow Example Explanation

### 1. ControlNet Workflow Assets

Please download the workflow image below and drag it into ComfyUI to load the workflow:

![ComfyUI Workflow - ControlNet](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/scribble_controlnet.png)

<Tip>
  Images with workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
  This image already includes download links for the corresponding models, and dragging it into ComfyUI will automatically prompt for downloads.
</Tip>

Please download the image below, which we will use as input:

![ComfyUI Sketch Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/scribble_input.png)

### 2. Manual Model Installation

<Note>
  If your network cannot successfully complete the automatic download of the corresponding models, please try manually downloading the models below and placing them in the specified directories:
</Note>

* [dreamCreationVirtual3DECommerce\_v10.safetensors](https://civitai.com/api/download/models/731340?type=Model\&format=SafeTensor\&size=full\&fp=fp16)
* [vae-ft-mse-840000-ema-pruned.safetensors](https://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.safetensors?download=true)
* [control\_v11p\_sd15\_scribble\_fp16.safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/blob/main/control_v11p_sd15_scribble_fp16.safetensors?download=true)

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── dreamCreationVirtual3DECommerce_v10.safetensors
│   ├── vae/
│   │   └── vae-ft-mse-840000-ema-pruned.safetensors
│   └── controlnet/
│       └── control_v11p_sd15_scribble_fp16.safetensors
```

<Note>
  In this example, you could also use the VAE model embedded in dreamCreationVirtual3DECommerce\_v10.safetensors, but we're following the model author's recommendation to use a separate VAE model.
</Note>

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Workflow - ControlNet Flow Diagram" />

1. Ensure that `Load Checkpoint` can load **dreamCreationVirtual3DECommerce\_v10.safetensors**
2. Ensure that `Load VAE` can load **vae-ft-mse-840000-ema-pruned.safetensors**
3. Click `Upload` in the `Load Image` node to upload the input image provided earlier
4. Ensure that `Load ControlNet` can load **control\_v11p\_sd15\_scribble\_fp16.safetensors**
5. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## Related Node Explanations

### Load ControlNet Node Explanation

<img alt="load controlnet" />

Models located in `ComfyUI\models\controlnet` will be detected by ComfyUI and can be loaded through this node.

### Apply ControlNet Node Explanation

<img alt="apply controlnet" />

This node accepts the ControlNet model loaded by `load controlnet` and generates corresponding control conditions based on the input image.

**Input Types**

| Parameter Name | Function |
| - | - |
| `positive` | Positive conditioning |
| `negative` | Negative conditioning |
| `control_net` | The ControlNet model to be applied |
| `image` | Preprocessed image used as reference for ControlNet application |
| `vae` | VAE model input |
| `strength` | Strength of ControlNet application; higher values increase ControlNet's influence on the generated image |
| `start_percent` | Determines when to start applying ControlNet as a percentage; e.g., 0.2 means ControlNet guidance begins when 20% of diffusion is complete |
| `end_percent` | Determines when to stop applying ControlNet as a percentage; e.g., 0.8 means ControlNet guidance stops when 80% of diffusion is complete |

**Output Types**

| Parameter Name | Function |
| - | - |
| `positive` | Positive conditioning data processed by ControlNet |
| `negative` | Negative conditioning data processed by ControlNet |

You can use chain connections to apply multiple ControlNet models, as shown in the image below. You can also refer to the [Mixing ControlNet Models](/tutorials/controlnet/mixing-controlnets) guide to learn more about combining multiple ControlNet models.

<img alt="apply controlnet chain link" />

<Note>
  You might see the `Apply ControlNet(Old)` node in some early workflows, which is an early version of the ControlNet node. It is currently deprecated and not visible by default in search and node lists.

  <img alt="apply controlnet old" />

  To enable it, go to **Settings** --> **comfy** --> **Node** and enable the `Show deprecated nodes in search` option. However, it's recommended to use the new node.
</Note>

## Start Your Exploration

1. Try creating similar sketches, or even draw your own, and use ControlNet models to generate images to experience the benefits of ControlNet.
2. Adjust the `Control Strength` parameter in the Apply ControlNet node to control the influence of the ControlNet model on the generated image.
3. Visit the [ControlNet-v1-1\_fp16\_safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/tree/main) repository to download other types of ControlNet models and try using them to generate images.


# Depth ControlNet Workflow Example
Source: https://docs.comfy.org/tutorials/controlnet/depth-controlnet

Depth ControlNet workflow in ComfyUI: how depth maps encode distance, and how to use one to control scene structure during image generation.

## Introduction to Depth Maps and Depth ControlNet

A depth map is a special type of image that uses grayscale values to represent the distance between objects in a scene and the observer or camera. In a depth map, the grayscale value is inversely proportional to distance: brighter areas (closer to white) indicate objects that are closer, while darker areas (closer to black) indicate objects that are farther away.

![Depth Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth_input.png)

Depth ControlNet is a ControlNet model specifically trained to understand and utilize depth map information. It helps AI correctly interpret spatial relationships, ensuring that generated images conform to the spatial structure specified by the depth map, thereby enabling precise control over three-dimensional spatial layouts.

### Application Scenarios for Depth Maps with ControlNet

Depth maps have numerous applications in various scenarios:

1. **Portrait Scenes**: Control the spatial relationship between subjects and backgrounds, avoiding distortion in critical areas such as faces
2. **Landscape Scenes**: Control the hierarchical relationships between foreground, middle ground, and background
3. **Architectural Scenes**: Control the spatial structure and perspective relationships of buildings
4. **Product Showcase**: Control the separation and spatial positioning of products against their backgrounds

In this example, we will use a depth map to generate an architectural visualization scene.

## ComfyUI ControlNet Workflow Example Explanation

### 1. ControlNet Workflow Assets

Please download the workflow image below and drag it into ComfyUI to load the workflow:

![Depth Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth_controlnet.png)

<Tip>
  Images with workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
  This image already includes download links for the corresponding models, and dragging it into ComfyUI will automatically prompt for downloads.
</Tip>

Please download the image below, which we will use as input:

![Depth Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth_input.png)

### 2. Model Installation

<Note>
  If your network cannot successfully complete the automatic download of the corresponding models, please try manually downloading the models below and placing them in the specified directories:
</Note>

* [architecturerealmix\_v11.safetensors](https://civitai.com/api/download/models/431755?type=Model\&format=SafeTensor\&size=full\&fp=fp16)
* [control\_v11f1p\_sd15\_depth\_fp16.safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/blob/main/control_v11f1p_sd15_depth_fp16.safetensors?download=true)

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── architecturerealmix_v11.safetensors
│   └── controlnet/
│       └── control_v11f1p_sd15_depth_fp16.safetensors
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Workflow - Depth ControlNet Flow Diagram" />

1. Ensure that `Load Checkpoint` can load **architecturerealmix\_v11.safetensors**
2. Ensure that `Load ControlNet` can load **control\_v11f1p\_sd15\_depth\_fp16.safetensors**
3. Click `Upload` in the `Load Image` node to upload the depth image provided earlier
4. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## Combining Depth Control with Other Techniques

Based on different creative needs, you can combine Depth ControlNet with other types of ControlNet to achieve better results:

1. **Depth + Lineart**: Maintain spatial relationships while reinforcing outlines, suitable for architecture, products, and character design
2. **Depth + Pose**: Control character posture while maintaining correct spatial relationships, suitable for character scenes

For more information on using multiple ControlNet models together, please refer to the [Mixing ControlNet](/tutorials/controlnet/mixing-controlnets) example.


# ComfyUI Depth T2I Adapter Usage Example
Source: https://docs.comfy.org/tutorials/controlnet/depth-t2i-adapter

This guide will introduce you to the basic concepts of Depth T2I Adapter and demonstrate how to generate corresponding images in ComfyUI

## Introduction to T2I Adapter

[T2I-Adapter](https://huggingface.co/TencentARC/T2I-Adapter) is a lightweight adapter developed by [Tencent ARC Lab](https://github.com/TencentARC) designed to enhance the structural, color, and style control capabilities of text-to-image generation models (such as Stable Diffusion).
It works by aligning external conditions (such as edge detection maps, depth maps, sketches, or color reference images) with the model's internal features, achieving high-precision control without modifying the original model structure. With only about 77M parameters (approximately 300MB in size), its inference speed is about 3 times faster than [ControlNet](https://github.com/lllyasviel/ControlNet-v1-1-nightly), and it supports multiple condition combinations (such as sketch + color grid). Application scenarios include line art to image conversion, color style transfer, multi-element scene generation, and more.

### Comparison Between T2I Adapter and ControlNet

Although their functions are similar, there are notable differences in implementation and application:

1. **Lightweight Design**: T2I Adapter has fewer parameters and a smaller memory footprint
2. **Inference Speed**: T2I Adapter is typically about 3 times faster than ControlNet
3. **Control Precision**: ControlNet offers more precise control in certain scenarios, while T2I Adapter is more suitable for lightweight control
4. **Multi-condition Combination**: T2I Adapter shows more significant resource advantages when combining multiple conditions

### Main Types of T2I Adapter

T2I Adapter provides various types to control different aspects:

* **Depth**: Controls the spatial structure and depth relationships in images
* **Line Art (Canny/Sketch)**: Controls image edges and lines
* **Keypose**: Controls character poses and actions
* **Segmentation (Seg)**: Controls scene layout through semantic segmentation
* **Color**: Controls the overall color scheme of images

In ComfyUI, using T2I Adapter is similar to [ControlNet](/tutorials/controlnet/controlnet) in terms of interface and workflow. In this example, we will demonstrate how to use a depth T2I Adapter to control an interior scene.

![ComfyUI Depth T2I Adapter Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth-t2i-adapter.png)

## Value of Depth T2I Adapter Applications

Depth maps have several important applications in image generation:

1. **Spatial Layout Control**: Accurately describes three-dimensional spatial structures, suitable for interior design and architectural visualization
2. **Object Positioning**: Controls the relative position and size of objects in a scene, suitable for product showcases and scene construction
3. **Perspective Relationships**: Maintains reasonable perspective and proportions, suitable for landscape and urban scene generation
4. **Light and Shadow Layout**: Natural light and shadow distribution based on depth information, enhancing realism

We will use interior design as an example to demonstrate how to use the depth T2I Adapter, but these techniques are applicable to other scenarios as well.

## ComfyUI Depth T2I Adapter Workflow Example Explanation

### 1. Depth T2I Adapter Workflow Assets

Please download the workflow image below and drag it into ComfyUI to load the workflow:

![ComfyUI Workflow - Depth T2I Adapter](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth-t2i-adapter.png)

<Tip>
  Images with workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
  This image already includes download links for the corresponding models, and dragging it into ComfyUI will automatically prompt for downloads.
</Tip>

Please download the image below, which we will use as input:

![ComfyUI Interior Depth Map](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth-t2i-adapter_input.png)

### 2. Model Installation

<Note>
  If your network cannot successfully complete the automatic download of the corresponding models, please try manually downloading the models below and placing them in the specified directories:
</Note>

* [interiordesignsuperm\_v2.safetensors](https://civitai.com/api/download/models/93152?type=Model\&format=SafeTensor\&size=full\&fp=fp16)
* [t2iadapter\_depth\_sd15v2.pth](https://huggingface.co/TencentARC/T2I-Adapter/blob/main/models/t2iadapter_depth_sd15v2.pth?download=true)

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── interiordesignsuperm_v2.safetensors
│   └── controlnet/
│       └── t2iadapter_depth_sd15v2.pth
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Workflow - Depth T2I Adapter Flow Diagram" />

1. Ensure that `Load Checkpoint` can load **interiordesignsuperm\_v2.safetensors**
2. Ensure that `Load ControlNet` can load **t2iadapter\_depth\_sd15v2.pth**
3. Click `Upload` in the `Load Image` node to upload the input image provided earlier
4. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## General Tips for Using T2I Adapter

### Input Image Quality Optimization

Regardless of the application scenario, high-quality input images are key to successfully using T2I Adapter:

1. **Moderate Contrast**: Control images (such as depth maps, line art) should have clear contrast, but not excessively extreme
2. **Clear Boundaries**: Ensure that major structures and element boundaries are clearly distinguishable in the control image
3. **Noise Control**: Try to avoid excessive noise in control images, especially for depth maps and line art
4. **Reasonable Layout**: Control images should have a reasonable spatial layout and element distribution

## Characteristics of T2I Adapter Usage

One major advantage of T2I Adapter is its ability to easily combine multiple conditions for complex control effects:

1. **Depth + Edge**: Control spatial layout while maintaining clear structural edges, suitable for architecture and interior design
2. **Line Art + Color**: Control shapes while specifying color schemes, suitable for character design and illustrations
3. **Pose + Segmentation**: Control character actions while defining scene areas, suitable for complex narrative scenes

Mixing different T2I Adapters, or combining them with other control methods (such as ControlNet, regional prompts, etc.), can further expand creative possibilities. To achieve mixing, simply chain multiple `Apply ControlNet` nodes together in the same way as described in [Mixing ControlNet](/tutorials/controlnet/mixing-controlnets).


# ComfyUI Mixing ControlNet Examples
Source: https://docs.comfy.org/tutorials/controlnet/mixing-controlnets

In this example, we will demonstrate how to mix multiple ControlNets and learn to use multiple ControlNet models to control image generation

In AI image generation, a single control condition often fails to meet the requirements of complex scenes. Mixing multiple ControlNets allows you to control different regions or aspects of an image simultaneously, achieving more precise control over image generation.

In certain scenarios, mixing ControlNets can leverage the characteristics of different control conditions to achieve more refined conditional control:

1. **Scene Complexity**: Complex scenes require multiple control conditions working together
2. **Fine-grained Control**: By adjusting the strength parameter of each ControlNet, you can precisely control the degree of influence for each part
3. **Complementary Effects**: Different types of ControlNets can complement each other, compensating for the limitations of single controls
4. **Creative Expression**: Combining different controls can produce unique creative effects

### How to Mix ControlNets

When mixing multiple ControlNets, each ControlNet influences the image generation process according to its applied area. ComfyUI enables multiple ControlNet conditions to be applied sequentially in a layered manner through chain connections in the `Apply ControlNet` node:

<img alt="apply controlnet chain link" />

## ComfyUI ControlNet Regional Division Mixing Example

In this example, we will use a combination of **Pose ControlNet** and **Scribble ControlNet** to generate a scene containing multiple elements: a character on the left controlled by Pose ControlNet and a cat on a scooter on the right controlled by Scribble ControlNet.

### 1. ControlNet Mixing Workflow Assets

Please download the workflow image below and drag it into ComfyUI to load the workflow:
![ComfyUI Workflow - Mixing ControlNet](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/mixing_controlnets.png)

<Tip>
  This workflow image contains Metadata, and can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`. The system will automatically detect and prompt to download the required models.
</Tip>

Input pose image (controls the character pose on the left):

![ComfyUI Workflow - Mixing ControlNet Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/mixing_controlnets_input.png)

Input scribble image (controls the cat and scooter on the right):

![ComfyUI Workflow - Mixing ControlNet Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/mixing_controlnets_input_scribble.png)

### 2. Manual Model Installation

<Note>
  If your network cannot successfully complete the automatic download of the corresponding models, please try manually downloading the models below and placing them in the specified directories:
</Note>

* [awpainting\_v14.safetensors](https://civitai.com/api/download/models/624939?type=Model\&format=SafeTensor\&size=full\&fp=fp16)
* [control\_v11p\_sd15\_scribble\_fp16.safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/blob/main/control_v11p_sd15_scribble_fp16.safetensors?download=true)
* [control\_v11p\_sd15\_openpose\_fp16.safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/blob/main/control_v11p_sd15_openpose_fp16.safetensors?download=true)
* [vae-ft-mse-840000-ema-pruned.safetensors](https://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.safetensors?download=true)

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── awpainting_v14.safetensors
│   ├── controlnet/
│   │   └── control_v11p_sd15_scribble_fp16.safetensors
│   │   └── control_v11p_sd15_openpose_fp16.safetensors
│   ├── vae/
│   │   └── vae-ft-mse-840000-ema-pruned.safetensors
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Workflow - Mixing ControlNet Flow Diagram" />

Follow these steps according to the numbered markers in the image:

1. Ensure that `Load Checkpoint` can load **awpainting\_v14.safetensors**
2. Ensure that `Load VAE` can load **vae-ft-mse-840000-ema-pruned.safetensors**

First ControlNet group using the Openpose model:
3\. Ensure that `Load ControlNet Model` loads **control\_v11p\_sd15\_openpose\_fp16.safetensors**
4\. Click `Upload` in the `Load Image` node to upload the pose image provided earlier

Second ControlNet group using the Scribble model:
5\. Ensure that `Load ControlNet Model` loads **control\_v11p\_sd15\_scribble\_fp16.safetensors**
6\. Click `Upload` in the `Load Image` node to upload the scribble image provided earlier
7\. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## Workflow Explanation

#### Strength Balance

When controlling different regions of an image, balancing the strength parameters is particularly important:

* If the ControlNet strength for one region is significantly higher than another, it may cause that region's control effect to overpower and suppress the other region
* It's recommended to set similar strength values for ControlNets controlling different regions, for example, both set to 1.0

#### Prompt Techniques

For regional division mixing, the prompt needs to include descriptions of both regions:

```
"A woman in red dress, a cat riding a scooter, detailed background, high quality"
```

Such a prompt covers both the character and the cat on the scooter, ensuring the model pays attention to both control regions.

## Multi-dimensional Control Applications for a Single Subject

In addition to the regional division mixing shown in this example, another common mixing approach is to apply multi-dimensional control to the same subject. For example:

* **Pose + Depth**: Control character posture and spatial sense
* **Pose + Canny**: Control character posture and edge details
* **Pose + Reference**: Control character posture while referencing a specific style

In this type of application, reference images for multiple ControlNets should be aligned to the same subject, and their strengths should be adjusted to ensure proper balance.

By combining different types of ControlNets and specifying their control regions, you can achieve precise control over elements in your image.


# ComfyUI Pose ControlNet Usage Example
Source: https://docs.comfy.org/tutorials/controlnet/pose-controlnet-2-pass

Learn Pose ControlNet in ComfyUI. Use OpenPose skeletons to control character posture and generate large images with a two-pass workflow.

## Introduction to OpenPose

[OpenPose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) is an open-source real-time multi-person pose estimation system developed by Carnegie Mellon University (CMU), representing a significant breakthrough in the field of computer vision. The system can simultaneously detect multiple people in an image, capturing:

* **Body skeleton**: 18 keypoints, including head, shoulders, elbows, wrists, hips, knees, and ankles
* **Facial expressions**: 70 facial keypoints for capturing micro-expressions and facial contours
* **Hand details**: 21 hand keypoints for precisely expressing finger positions and gestures
* **Foot posture**: 6 foot keypoints, recording standing postures and movement details

<img alt="OpenPose Example" />

In AI image generation, skeleton structure maps generated by OpenPose serve as conditional inputs for ControlNet, enabling precise control over the posture, actions, and expressions of generated characters. This allows us to generate realistic human figures with expected poses and actions, greatly improving the controllability and practical value of AI-generated content.
Particularly for early Stable Diffusion 1.5 series models, skeletal maps generated by OpenPose can effectively prevent issues with distorted character actions, limbs, and expressions.

## ComfyUI 2-Pass Pose ControlNet Usage Example

### 1. Pose ControlNet Workflow Assets

Please download the workflow image below and drag it into ComfyUI to load the workflow:

![ComfyUI Workflow - Pose ControlNet](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/pose_controlnet_2_pass.png)

<Tip>
  Images with workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
  This image already includes download links for the corresponding models, and dragging it into ComfyUI will automatically prompt for downloads.
</Tip>

Please download the image below, which we will use as input:

![ComfyUI Pose Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/pose_controlnet_2_pass_input.png)

### 2. Manual Model Installation

<Note>
  If your network cannot successfully complete the automatic download of the corresponding models, please try manually downloading the models below and placing them in the specified directories:
</Note>

* [control\_v11p\_sd15\_openpose\_fp16.safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/blob/main/control_v11p_sd15_openpose_fp16.safetensors?download=true)
* [majicmixRealistic\_v7.safetensors](https://civitai.com/api/download/models/176425?type=Model\&format=SafeTensor\&size=pruned\&fp=fp16)
* [japaneseStyleRealistic\_v20.safetensors](https://civitai.com/api/download/models/85426?type=Model\&format=SafeTensor\&size=pruned\&fp=fp16)
* [vae-ft-mse-840000-ema-pruned.safetensors](https://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.safetensors?download=true)

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── majicmixRealistic_v7.safetensors
│   │   └── japaneseStyleRealistic_v20.safetensors
│   ├── vae/
│   │   └── vae-ft-mse-840000-ema-pruned.safetensors
│   └── controlnet/
│       └── control_v11p_sd15_openpose_fp16.safetensors
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Workflow - Pose ControlNet Flow Diagram" />

Follow these steps according to the numbered markers in the image:

1. Ensure that `Load Checkpoint` can load **majicmixRealistic\_v7.safetensors**
2. Ensure that `Load VAE` can load **vae-ft-mse-840000-ema-pruned.safetensors**
3. Ensure that `Load ControlNet Model` can load **control\_v11p\_sd15\_openpose\_fp16.safetensors**
4. Click the select button in the `Load Image` node to upload the pose input image provided earlier, or use your own OpenPose skeleton map
5. Ensure that `Load Checkpoint` can load **japaneseStyleRealistic\_v20.safetensors**
6. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## Explanation of the Pose ControlNet 2-Pass Workflow

This workflow uses a two-pass image generation approach, dividing the image creation process into two phases:

### First Phase: Basic Pose Image Generation

In the first phase, the **majicmixRealistic\_v7** model is combined with Pose ControlNet to generate an initial character pose image:

1. First, load the majicmixRealistic\_v7 model via the `Load Checkpoint` node
2. Load the pose control model through the `Load ControlNet Model` node
3. The input pose image is fed into the `Apply ControlNet` node and combined with positive and negative prompt conditions
4. The first `KSampler` node (typically using 20-30 steps) generates a basic character pose image
5. The pixel-space image for the first phase is obtained through `VAE Decode`

This phase primarily focuses on correct character posture, pose, and basic structure, ensuring that the generated character conforms to the input skeletal pose.

### Second Phase: Style Optimization and Detail Enhancement

In the second phase, the output image from the first phase is used as a reference, with the **japaneseStyleRealistic\_v20** model performing stylization and detail enhancement:

1. The image generated in the first phase creates a larger resolution latent space through the `Upscale latent` node
2. The second `Load Checkpoint` loads the japaneseStyleRealistic\_v20 model, which focuses on details and style
3. The second `KSampler` node uses a lower `denoise` strength (typically 0.4-0.6) for refinement, preserving the basic structure from the first phase
4. Finally, a higher quality, larger resolution image is output through the second `VAE Decode` and `Save Image` nodes

This phase primarily focuses on style consistency, detail richness, and enhancing overall image quality.

## Advantages of 2-Pass Image Generation

Compared to single-pass generation, the two-pass image generation method offers the following advantages:

1. **Higher Resolution**: Two-pass processing can generate high-resolution images beyond the capabilities of single-pass generation
2. **Style Blending**: Can combine advantages of different models, such as using a realistic model in the first phase and a stylized model in the second phase
3. **Better Details**: The second phase can focus on optimizing details without having to worry about overall structure
4. **Precise Control**: Once pose control is completed in the first phase, the second phase can focus on refining style and details
5. **Reduced GPU Load**: Generating in two passes allows for high-quality large images with limited GPU resources

<Tip>
  To learn more about techniques for mixing multiple ControlNets, please refer to the [Mixing ControlNet Models](/tutorials/controlnet/mixing-controlnets) tutorial.
</Tip>


# ComfyUI Flux.1 ControlNet Examples
Source: https://docs.comfy.org/tutorials/flux/flux-1-controlnet

FLUX.1 Canny and Depth workflow examples for ComfyUI: add ControlNet-style structural control to FLUX.1 with Black Forest Labs' FLUX.1 Tools.

<img alt="Flux.1 Canny Controlnet" />

<img alt="Flux.1 Depth Controlnet" />

## FLUX.1 ControlNet Model Introduction

FLUX.1 Canny and Depth are two powerful models from the [FLUX.1 Tools](https://blackforestlabs.ai/flux-1-tools/) launched by [Black Forest Labs](https://blackforestlabs.ai/). This toolkit is designed to add control and guidance capabilities to FLUX.1, enabling users to modify and recreate real or generated images.

**FLUX.1-Depth-dev** and **FLUX.1-Canny-dev** are both 12B parameter Rectified Flow Transformer models that can generate images based on text descriptions while maintaining the structural features of the input image.
The Depth version maintains the spatial structure of the source image through depth map extraction techniques, while the Canny version uses edge detection techniques to preserve the structural features of the source image, allowing users to choose the appropriate control method based on different needs.

Both models have the following features:

* Top-tier output quality and detail representation
* Excellent prompt following ability while maintaining consistency with the original image
* Trained using guided distillation techniques for improved efficiency
* Open weights for the research community
* API interfaces (pro version) and open-source weights (dev version)

Additionally, Black Forest Labs also provides **FLUX.1-Depth-dev-lora** and **FLUX.1-Canny-dev-lora** adapter versions extracted from the complete models.
These can be applied to the FLUX.1 \[dev] base model to provide similar functionality with smaller file size, especially suitable for resource-constrained environments.

We will use the full version of **FLUX.1-Canny-dev** and **FLUX.1-Depth-dev-lora** to complete the workflow examples.

<Tip>
  All workflow images's Metadata contains the corresponding model download information. You can load the workflows by:

  * Dragging them directly into ComfyUI
  * Or using the menu `Workflows` -> `Open（ctrl+o）`

  If you're not using the Desktop Version or some models can't be downloaded automatically, please refer to the manual installation sections to save the model files to the corresponding folder.

  For image preprocessors, you can use the following custom nodes to complete image preprocessing. In this example, we will provide processed images as input.

  * [ComfyUI-Advanced-ControlNet](https://github.com/Kosinkadink/ComfyUI-Advanced-ControlNet)
  * [ComfyUI ControlNet aux](https://github.com/Fannovel16/comfyui_controlnet_aux)
</Tip>

## FLUX.1-Canny-dev Complete Version Workflow

### Flux.1 Canny Model

Generate images guided by edge detection using Flux.1 Canny.

<img alt="Flux.1 Canny workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux_canny_model_example&utm_source=docs&utm_medium=referral&utm_campaign=flux-1-controlnet">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux_canny_model_example.json">
    Download JSON or search "Flux.1 Canny" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="flux_canny_model_example_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/flux_canny_model_example_input_image.png">
    `LoadImage` node 17 · `flux_canny_model_example_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="flux_canny_model_example_input_image.png" />
</div>

### 1. Workflow and Asset

### 2. Manual Models Installation

<Note>
  If you have previously used the [complete version of Flux related workflows](/tutorials/flux/flux-1-text-to-image), then you only need to download the **flux1-canny-dev.safetensors** model file.
  Since you need to first agree to the terms of [black-forest-labs/FLUX.1-Canny-dev](https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev), please visit the [black-forest-labs/FLUX.1-Canny-dev](https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev) page and make sure you have agreed to the corresponding terms as shown in the image below.

  <img alt="Flux Agreement" />
</Note>

Complete model list:

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors?download=true)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp16.safetensors?download=true)
* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/blob/main/ae.safetensors?download=true)
* [flux1-canny-dev.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev/blob/main/flux1-canny-dev.safetensors?download=true) (Please ensure you have agreed to the corresponding repo's terms)

File storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── t5xxl_fp16.safetensors
│   ├── vae/
│   │   └── ae.safetensors
│   └── diffusion_models/
│       └── flux1-canny-dev.safetensors
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Flux.1 Canny Controlnet Step Process" />

1. Make sure `ae.safetensors` is loaded in the `Load VAE` node
2. Make sure `flux1-canny-dev.safetensors` is loaded in the `Load Diffusion Model` node
3. Make sure the following models are loaded in the `DualCLIPLoader` node:
   * clip\_name1: t5xxl\_fp16.safetensors
   * clip\_name2: clip\_l.safetensors
4. Upload the provided input image in the `Load Image` node
5. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

### 4. Start Your Experimentation

Try using the [FLUX.1-Depth-dev](https://huggingface.co/black-forest-labs/FLUX.1-Depth-dev) model to complete the Depth version of the workflow

You can use the image below as input
![ComfyUI Indoor Depth Map](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth-t2i-adapter_input.png)

Or use the following custom nodes to complete image preprocessing:

* [ComfyUI-Advanced-ControlNet](https://github.com/Kosinkadink/ComfyUI-Advanced-ControlNet)
* [ComfyUI ControlNet aux](https://github.com/Fannovel16/comfyui_controlnet_aux)

## FLUX.1-Depth-dev-lora Workflow

### Flux.1 Depth Lora

Generate images guided by depth information using Flux.1 LoRA.

<img alt="Flux.1 Depth LoRA workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux_depth_lora_example&utm_source=docs&utm_medium=referral&utm_campaign=flux-1-controlnet">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux_depth_lora_example.json">
    Download JSON or search "Flux.1 Depth LoRA" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="flux_depth_lora_example_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/flux_depth_lora_example_input_image.png">
    `LoadImage` node 17 · `flux_depth_lora_example_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="flux_depth_lora_example_input_image.png" />
</div>

### 1. Workflow and Asset

### 2. Manual Model Download

<Tip>
  If you have previously used the [complete version of Flux related workflows](/tutorials/flux/flux-1-text-to-image), then you only need to download the **flux1-depth-dev-lora.safetensors** model file.
</Tip>

Complete model list:

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors?download=true)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp16.safetensors?download=true)
* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/blob/main/ae.safetensors?download=true)
* [flux1-dev.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/flux1-dev.safetensors?download=true)
* [flux1-depth-dev-lora.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-Depth-dev-lora/blob/main/flux1-depth-dev-lora.safetensors?download=true)

File storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── t5xxl_fp16.safetensors
│   ├── vae/
│   │   └── ae.safetensors
│   ├── diffusion_models/
│   │   └── flux1-dev.safetensors
│   └── loras/
│       └── flux1-depth-dev-lora.safetensors
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Flux.1 Depth Controlnet Step Process" />

1. Make sure `flux1-dev.safetensors` is loaded in the `Load Diffusion Model` node
2. Make sure `flux1-depth-dev-lora.safetensors` is loaded in the `LoraLoaderModelOnly` node
3. Make sure the following models are loaded in the `DualCLIPLoader` node:
   * clip\_name1: t5xxl\_fp16.safetensors
   * clip\_name2: clip\_l.safetensors
4. Upload the provided input image in the `Load Image` node
5. Make sure `ae.safetensors` is loaded in the `Load VAE` node
6. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

### 4. Start Your Experimentation

Try using the [FLUX.1-Canny-dev-lora](https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev-lora) model to complete the Canny version of the workflow

Use [ComfyUI-Advanced-ControlNet](https://github.com/Kosinkadink/ComfyUI-Advanced-ControlNet) or [ComfyUI ControlNet aux](https://github.com/Fannovel16/comfyui_controlnet_aux) to complete image preprocessing

## Community Versions of Flux Controlnets

XLab and InstantX + Shakker Labs have released Controlnets for Flux.

**InstantX:**

* [FLUX.1-dev-Controlnet-Canny](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Canny/blob/main/diffusion_pytorch_model.safetensors)
* [FLUX.1-dev-ControlNet-Depth](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Depth/blob/main/diffusion_pytorch_model.safetensors)
* [FLUX.1-dev-ControlNet-Union-Pro](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro/blob/main/diffusion_pytorch_model.safetensors)

**XLab**: [flux-controlnet-collections](https://huggingface.co/XLabs-AI/flux-controlnet-collections)

Place these files in the `ComfyUI/models/controlnet` directory.

You can visit [Flux Controlnet Example](https://raw.githubusercontent.com/comfyanonymous/ComfyUI_examples/refs/heads/master/flux/flux_controlnet_example.png) to get the corresponding workflow image, and use the image from [here](https://raw.githubusercontent.com/comfyanonymous/ComfyUI_examples/refs/heads/master/flux/girl_in_field.png) as the input image.


# ComfyUI Flux.1 fill dev Example
Source: https://docs.comfy.org/tutorials/flux/flux-1-fill-dev

This guide demonstrates how to use Flux.1 fill dev to create Inpainting and Outpainting workflows.

<img alt="Flux.1 fill dev" />

## Introduction to Flux.1 fill dev Model

Flux.1 fill dev is one of the core tools in the [FLUX.1 Tools suite](https://blackforestlabs.ai/flux-1-tools/) launched by [Black Forest Labs](https://blackforestlabs.ai/), specifically designed for image inpainting and outpainting.

Key features of Flux.1 fill dev:

* Powerful image inpainting and outpainting capabilities, with results second only to the commercial version FLUX.1 Fill \[pro].
* Excellent prompt understanding and following ability, precisely capturing user intent while maintaining high consistency with the original image.
* Advanced guided distillation training technology, making the model more efficient while maintaining high-quality output.
* Friendly licensing terms, with generated outputs usable for personal, scientific, and commercial purposes, please refer to the [FLUX.1 \[dev\] non-commercial license](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md) for details.

Open Source Repository: [FLUX.1 \[dev\]](https://huggingface.co/black-forest-labs/FLUX.1-dev)

This guide will demonstrate inpainting and outpainting workflows based on the Flux.1 fill dev model.
If you're not familiar with inpainting and outpainting workflows, you can refer to [ComfyUI Layout Inpainting Example](/tutorials/basic/inpaint) and [ComfyUI Image Extension Example](/tutorials/basic/outpaint) for some related explanations.

## Flux.1 Fill dev and related models installation

Before we begin, let's complete the installation of the Flux.1 Fill dev model files. The inpainting and outpainting workflows will use exactly the same model files.
If you've previously used the full version of the [Flux.1 Text-to-Image workflow](/tutorials/flux/flux-1-text-to-image),
then you only need to download the **flux1-fill-dev.safetensors** model file in this section.

However, since downloading the corresponding model requires agreeing to the corresponding usage agreement, please visit the [black-forest-labs/FLUX.1-Fill-dev](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev) page and make sure you have agreed to the corresponding agreement as shown in the image below.

<img alt="Flux Agreement" />

Complete model list:
\|- [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors)
\|- [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp16.safetensors)
\|- [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/blob/main/ae.safetensors)
\|- [flux1-fill-dev.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev/blob/main/flux1-fill-dev.safetensors)

File storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │    ├── clip_l.safetensors
│   │    └── t5xxl_fp16.safetensors
│   ├── vae/
│   │    └── ae.safetensors
│   └── diffusion_models/
│        └── flux1-fill-dev.safetensors
```

## Flux.1 Fill dev inpainting workflow

### Flux.1 Inpaint

Fill missing parts of images using Flux.1 Fill Inpainting.

<img alt="Flux.1 inpaint workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux_fill_inpaint_example&utm_source=docs&utm_medium=referral&utm_campaign=flux-1-fill-dev">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux_fill_inpaint_example.json">
    Download JSON or search "Flux.1 Inpaint" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="flux_fill_inpaint_example_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/flux_fill_inpaint_example_input_image.png">
    `LoadImage` node 17 · `flux_fill_inpaint_example_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="flux_fill_inpaint_example_input_image.png" />
</div>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="Flux.1 inpaint example output" />
</div>

### 1. Inpainting workflow and asset

<Note>
  The corresponding image already contains an alpha channel, so you don't need to draw a mask separately.
  If you want to draw your own mask, please [click here](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/inpaint/flux_fill_inpaint_input_original.png) to get the image without a mask, and refer to the MaskEditor usage section in the [ComfyUI Layout Inpainting Example](/tutorials/basic/inpaint#using-the-mask-editor) to learn how to draw a mask in the `Load Image` node.
</Note>

### 2. Steps to run the workflow

<img alt="ComfyUI Flux.1 Fill dev Inpainting Workflow" />

1. Ensure the `Load Diffusion Model` node has `flux1-fill-dev.safetensors` loaded.
2. Ensure the `DualCLIPLoader` node has the following models loaded:
   * clip\_name1: `t5xxl_fp16.safetensors`
   * clip\_name2: `clip_l.safetensors`
3. Ensure the `Load VAE` node has `ae.safetensors` loaded.
4. Upload the input image provided in the document to the `Load Image` node; if you're using the version without a mask, remember to complete the mask drawing using the mask editor
5. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Flux.1 Fill dev Outpainting Workflow

### Flux.1 Outpaint

Extend images beyond boundaries using Flux.1 outpainting.

<img alt="Flux.1 outpaint workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux_fill_outpaint_example&utm_source=docs&utm_medium=referral&utm_campaign=flux-1-fill-dev">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux_fill_outpaint_example.json">
    Download JSON or search "Flux.1 Outpaint" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="flux_fill_outpaint_example_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/flux_fill_outpaint_example_input_image.png">
    `LoadImage` node 17 · `flux_fill_outpaint_example_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="flux_fill_outpaint_example_input_image.png" />
</div>

### 1. Outpainting workflow and asset

### 2. Steps to run the workflow

<img alt="ComfyUI Flux.1 Fill dev Outpainting Workflow" />

1. Ensure the `Load Diffusion Model` node has `flux1-fill-dev.safetensors` loaded.
2. Ensure the `DualCLIPLoader` node has the following models loaded:
   * clip\_name1: `t5xxl_fp16.safetensors`
   * clip\_name2: `clip_l.safetensors`
3. Ensure the `Load VAE` node has `ae.safetensors` loaded.
4. Upload the input image provided in the document to the `Load Image` node
5. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow


# ComfyUI Flux Kontext Dev Native Workflow Example
Source: https://docs.comfy.org/tutorials/flux/flux-1-kontext-dev

FLUX.1 Kontext Dev workflow for ComfyUI: edit images with text and image input using Black Forest Labs' open-source 12B multimodal editing model.

<iframe title="ComfyUI Selection Toolbox New Features" />

## About FLUX.1 Kontext Dev

FLUX.1 Kontext is a breakthrough multimodal image editing model from Black Forest Labs that supports simultaneous text and image input, intelligently understanding image context and performing precise editing. Its development version is an open-source diffusion transformer model with 12 billion parameters, featuring excellent context understanding and character consistency maintenance, ensuring that key elements such as character features and composition layout remain stable even after multiple iterative edits.

It shares the same core capabilities as the FLUX.1 Kontext suite:

* Character Consistency: Preserves unique elements in images across multiple scenes and environments, such as reference characters or objects in the image.
* Editing: Makes targeted modifications to specific elements in the image without affecting other parts.
* Style Reference: Generates novel scenes while preserving the unique style of the reference image according to text prompts.
* Interactive Speed: Minimal latency in image generation and editing.

While the previously released API version offers the highest fidelity and speed, FLUX.1 Kontext \[Dev] runs entirely on local machines, providing unparalleled flexibility for developers, researchers, and advanced users who wish to experiment.

### Version Information

* **\[FLUX.1 Kontext \[pro]** : Commercial version, focused on rapid iterative editing
* **FLUX.1 Kontext \[max]** : Experimental version with stronger prompt adherence
* **FLUX.1 Kontext \[dev]** : Open source version (used in this tutorial), 12B parameters, mainly for research

Currently in ComfyUI, you can use all these versions, where [Pro and Max versions](/tutorials/partner-nodes/black-forest-labs/flux-1-kontext) can be called through Partner Nodes, while the Dev open source version please refer to the instructions in this guide.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Download

To run the workflows in this guide successfully, you first need to download the following model files. You can also directly get the model download links from the corresponding workflows, which already contain the model file download information.

**Diffusion Model**

* [flux1-dev-kontext\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/flux1-kontext-dev_ComfyUI/blob/main/split_files/diffusion_models/flux1-dev-kontext_fp8_scaled.safetensors)

<Tip>
  If you want to use the original weights, you can visit Black Forest Labs' related repository to obtain and use the original model weights.
</Tip>

**VAE**

* [ae.safetensors](https://huggingface.co/Comfy-Org/Lumina_Image_2.0_Repackaged/blob/main/split_files/vae/ae.safetensors)

**Text Encoder**

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp16.safetensors) or [t5xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp8_e4m3fn_scaled.safetensors)

Model save location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── flux1-dev-kontext_fp8_scaled.safetensors
│   ├── 📂 vae/
│   │   └── ae.safetensor
│   └── 📂 text_encoders/
│       ├── clip_l.safetensors
│       └── t5xxl_fp16.safetensors or t5xxl_fp8_e4m3fn_scaled.safetensors
```

## Flux.1 Kontext Dev Workflow

### Flux Kontext Dev Image Edit

Smart image editing that keeps characters consistent, edits specific parts without affecting others, and preserves original styles.

<img alt="Flux Kontext Dev workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux_kontext_dev_basic&utm_source=docs&utm_medium=referral&utm_campaign=flux-1-kontext-dev">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux_kontext_dev_basic.json">
    Download JSON or search "Flux Kontext Dev" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="flux_kontext_dev_basic_input_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/flux_kontext_dev_basic_input_image.jpg">
    `LoadImage` node 190 · `flux_kontext_dev_basic_input_image.jpg`
  </Card>
</CardGroup>

<div>
  <img alt="flux_kontext_dev_basic_input_image.jpg" />
</div>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="Flux Kontext Dev example output" />
</div>

This workflow uses the `Load Image(from output)` node to load the image to be edited, making it more convenient for you to access the edited image for multiple rounds of editing.

### 1. Workflow and Input Image Download

### 2. Complete the workflow step by step

<img alt="Workflow Step Guide" />

You can refer to the numbers in the image to complete the workflow run:

1. In the `Load Diffusion Model` node, load the `flux1-dev-kontext_fp8_scaled.safetensors` model
2. In the `DualCLIP Load` node, ensure that `clip_l.safetensors` and `t5xxl_fp16.safetensors` or `t5xxl_fp8_e4m3fn_scaled.safetensors` are loaded
3. In the `Load VAE` node, ensure that `ae.safetensors` model is loaded
4. In the `Load Image(from output)` node, load the provided input image
5. In the `CLIP Text Encode` node, modify the prompts, only English is supported
6. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Flux Kontext Prompt Techniques

### 1. Basic Modifications

* Simple and direct: `"Change the car color to red"`
* Maintain style: `"Change to daytime while maintaining the same style of the painting"`

### 2. Style Transfer

**Principles:**

* Clearly name style: `"Transform to Bauhaus art style"`
* Describe characteristics: `"Transform to oil painting with visible brushstrokes, thick paint texture"`
* Preserve composition: `"Change to Bauhaus style while maintaining the original composition"`

### 3. Character Consistency

**Framework:**

* Specific description: `"The woman with short black hair"` instead of "she"
* Preserve features: `"while maintaining the same facial features, hairstyle, and expression"`
* Step-by-step modifications: Change background first, then actions

### 4. Text Editing

* Use quotes: `"Replace 'joy' with 'BFL'"`
* Maintain format: `"Replace text while maintaining the same font style"`

## Common Problem Solutions

### Character Changes Too Much

❌ Wrong: `"Transform the person into a Viking"`
✅ Correct: `"Change the clothes to be a viking warrior while preserving facial features"`

### Composition Position Changes

❌ Wrong: `"Put him on a beach"`
✅ Correct: `"Change the background to a beach while keeping the person in the exact same position, scale, and pose"`

### Style Application Inaccuracy

❌ Wrong: `"Make it a sketch"`
✅ Correct: `"Convert to pencil sketch with natural graphite lines, cross-hatching, and visible paper texture"`

## Core Principles

1. **Be Specific and Clear** - Use precise descriptions, avoid vague terms
2. **Step-by-step Editing** - Break complex modifications into multiple simple steps
3. **Explicit Preservation** - State what should remain unchanged
4. **Verb Selection** - Use "change", "replace" rather than "transform"

## Best Practice Templates

**Object Modification:**
`"Change [object] to [new state], keep [content to preserve] unchanged"`

**Style Transfer:**
`"Transform to [specific style], while maintaining [composition/character/other] unchanged"`

**Background Replacement:**
`"Change the background to [new background], keep the subject in the exact same position and pose"`

**Text Editing:**
`"Replace '[original text]' with '[new text]', maintain the same font style"`

> **Remember:** The more specific, the better. Kontext excels at understanding detailed instructions and maintaining consistency.


# ComfyUI Flux.1 Text-to-Image Workflow Example
Source: https://docs.comfy.org/tutorials/flux/flux-1-text-to-image

Generate text-to-image with the open-source Flux.1 model in ComfyUI, including full and FP8 checkpoint versions, with step-by-step workflow setup.

<img alt="Flux" />

Flux is one of the largest open-source text-to-image generation models, with 12B parameters and an original file size of approximately 23GB. It was developed by [Black Forest Labs](https://blackforestlabs.ai/), a team founded by former Stable Diffusion team members.
Flux is known for its excellent image quality and flexibility, capable of generating high-quality, diverse images.

Currently, the Flux.1 model has several main versions:

* **Flux.1 Pro:** The best performing model, closed-source, only available through API calls.
* **[Flux.1 \[dev\]：](https://huggingface.co/black-forest-labs/FLUX.1-dev)** Open-source but limited to non-commercial use, distilled from the Pro version, with performance close to the Pro version.
* **[Flux.1 \[schnell\]：](https://huggingface.co/black-forest-labs/FLUX.1-schnell)** Uses the Apache2.0 license, requires only 4 steps to generate images, suitable for low-spec hardware.

**Flux.1 Model Features**

* **Hybrid Architecture:** Combines the advantages of Transformer networks and diffusion models, effectively integrating text and image information, improving the alignment accuracy between generated images and prompts, with excellent fidelity to complex prompts.
* **Parameter Scale:** Flux has 12B parameters, capturing more complex pattern relationships and generating more realistic, diverse images.
* **Supports Multiple Styles:** Supports diverse styles, with excellent performance for various types of images.

In this example, we'll introduce text-to-image examples using both Flux.1 Dev and Flux.1 Schnell versions, including the full version model and the simplified FP8 Checkpoint version.

* **Flux Full Version:** Best performance, but requires larger VRAM resources and installation of multiple model files.
* **Flux FP8 Checkpoint:** Requires only one fp8 version of the model, but quality is slightly reduced compared to the full version.

<Tip>
  All workflow images's Metadata contains the corresponding model download information. You can load the workflows by:

  * Dragging them directly into ComfyUI
  * Or using the menu `Workflows` -> `Open（ctrl+o）`

  If you're not using the Desktop Version or some models can't be downloaded automatically, please refer to the manual installation sections to save the model files to the corresponding folder.
  Make sure your ComfyUI is updated to the latest version before starting.
</Tip>

## Flux.1 Full Version Text-to-Image Example

<Note>
  If you can't download models from [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev), make sure you've logged into Huggingface and agreed to the corresponding repository's license agreement.

  <img alt="Flux Agreement" />
</Note>

### Flux.1 Dev

### Flux.1 Dev fp8: Text to Image

Generate images using Flux.1 Dev fp8 quantized version. Suitable for devices with limited VRAM, requires only one model file, but image quality is slightly reduced compared to the full version.

<img alt="Flux.1 Dev fp8 workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux_dev_checkpoint_example&utm_source=docs&utm_medium=referral&utm_campaign=flux-1-text-to-image">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux_dev_checkpoint_example.json">
    Download JSON or search "Flux.1 Dev fp8" in Template Library
  </Card>
</CardGroup>

**Example output**

![Flux.1 Dev fp8 example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/flux_dev_checkpoint_example.png)

#### 1. Workflow File

#### 2. Manual Model Installation

<Note>
  * The `flux1-dev.safetensors` file requires agreeing to the [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) agreement before downloading via browser.
  * If your VRAM is low, you can try using [t5xxl\_fp8\_e4m3fn.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp8_e4m3fn.safetensors?download=true) to replace the `t5xxl_fp16.safetensors` file.
</Note>

Please download the following model files:

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors?download=true)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp16.safetensors?download=true) Recommended when your VRAM is greater than 32GB.
* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/blob/main/ae.safetensors?download=true)
* [flux1-dev.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/flux1-dev.safetensors)

Storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── t5xxl_fp16.safetensors
│   ├── vae/
│   │   └── ae.safetensors
│   └── diffusion_models/
│       └── flux1-dev.safetensors
```

#### 3. Steps to Run the Workflow

Please refer to the image below to ensure all model files are loaded correctly

<img alt="ComfyUI Flux Dev Workflow" />

1. Ensure the `DualCLIPLoader` node has the following models loaded:
   * clip\_name1: t5xxl\_fp16.safetensors
   * clip\_name2: clip\_l.safetensors
2. Ensure the `Load Diffusion Model` node has `flux1-dev.safetensors` loaded
3. Make sure the `Load VAE` node has `ae.safetensors` loaded
4. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

<Tip>
  Thanks to Flux's excellent prompt following capability, we don't need any negative prompts
</Tip>

### Flux.1 Schnell

### Flux.1 Schnell FP8

Quickly generate images with Flux.1 Schnell fp8 quantized version. Ideal for low-end hardware, requires only 4 steps to generate images.

<img alt="Flux.1 Schnell FP8 workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux_schnell&utm_source=docs&utm_medium=referral&utm_campaign=flux-1-text-to-image">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux_schnell_full_text_to_image.json">
    Download JSON or search "Flux.1 Schnell" in Template Library
  </Card>
</CardGroup>

#### 1. Workflow File

#### 2. Manual Models Installation

<Note>
  In this workflow, only two model files are different from the Flux1 Dev version workflow. For t5xxl, you can still use the fp16 version for better results.

  * **t5xxl\_fp16.safetensors** -> **t5xxl\_fp8.safetensors**
  * **flux1-dev.safetensors** -> **flux1-schnell.safetensors**
</Note>

Complete model file list:

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors?download=true)
* [t5xxl\_fp8\_e4m3fn.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp8_e4m3fn.safetensors?download=true)
* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/blob/main/ae.safetensors?download=true)
* [flux1-schnell.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/blob/main/flux1-schnell.safetensors)

File storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── t5xxl_fp8_e4m3fn.safetensors
│   ├── vae/
│   │   └── ae.safetensors
│   └── diffusion_models/
│       └── flux1-schnell.safetensors
```

#### 3. Steps to Run the Workflow

<img alt="Flux Schnell Version Workflow" />

1. Ensure the `DualCLIPLoader` node has the following models loaded:
   * clip\_name1: t5xxl\_fp8\_e4m3fn.safetensors
   * clip\_name2: clip\_l.safetensors
2. Ensure the `Load Diffusion Model` node has `flux1-schnell.safetensors` loaded
3. Ensure the `Load VAE` node has `ae.safetensors` loaded
4. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Flux.1 FP8 Checkpoint Version Text-to-Image Example

The fp8 version is a quantized version of the original Flux.1 fp16 version.
To some extent, the quality of this version will be lower than that of the fp16 version,
but it also requires less VRAM, and you only need to install one model file to try running it.

### Flux.1 Dev

### Flux.1 Dev: Text to Image

Generate high-quality images with Flux Dev full version. Requires larger VRAM and multiple model files, but provides the best prompt following capability.

<img alt="Flux.1 Dev text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux_dev_full_text_to_image&utm_source=docs&utm_medium=referral&utm_campaign=flux-1-text-to-image">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux_dev_full_text_to_image.json">
    Download JSON or search "Flux.1 Dev FP8" in Template Library
  </Card>
</CardGroup>

**Example output**

![Flux.1 Dev FP8 checkpoint example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/flux_dev_full_text_to_image.png)

Please download the image below and drag it into ComfyUI to load the workflow.

Please download [flux1-dev-fp8.safetensors](https://huggingface.co/Comfy-Org/flux1-dev/blob/main/flux1-dev-fp8.safetensors?download=true) and save it to the `ComfyUI/models/checkpoints/` directory.

Ensure that the corresponding `Load Checkpoint` node loads `flux1-dev-fp8.safetensors`, and you can try to run the workflow.

### Flux.1 Schnell

### Flux.1 Schnell FP8

Quickly generate images with Flux.1 Schnell fp8 quantized version. Ideal for low-end hardware, requires only 4 steps to generate images.

<img alt="Flux.1 Schnell FP8 checkpoint workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux_schnell&utm_source=docs&utm_medium=referral&utm_campaign=flux-1-text-to-image">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux_schnell.json">
    Download JSON or search "Flux.1 Schnell FP8" in Template Library
  </Card>
</CardGroup>

Please download the image below and drag it into ComfyUI to load the workflow.

Please download [flux1-schnell-fp8.safetensors](https://huggingface.co/Comfy-Org/flux1-schnell/blob/main/flux1-schnell-fp8.safetensors?download=true) and save it to the `ComfyUI/models/checkpoints/` directory.

Ensure that the corresponding `Load Checkpoint` node loads `flux1-schnell-fp8.safetensors`, and you can try to run the workflow.


# ByteDance USO ComfyUI Native Workflow example
Source: https://docs.comfy.org/tutorials/flux/flux-1-uso

Unified Style and Subject-Driven Generation with ByteDance's USO model

**USO (Unified Style-Subject Optimized)** is a model developed by ByteDance's UXO Team that unifies style-driven and subject-driven generation tasks.
Built on FLUX.1-dev architecture, the model achieves both style similarity and subject consistency through disentangled learning and style reward learning (SRL).

USO supports three main approaches:

* **Subject-Driven**: Place subjects into new scenes while maintaining identity consistency
* **Style-Driven**: Apply artistic styles to new content based on reference images
* **Combined**: Use both subject and style references simultaneously

**Related Links**

* [Project Page](https://bytedance.github.io/USO/)
* [GitHub](https://github.com/bytedance/USO)
* [Model Weights](https://huggingface.co/bytedance-research/USO)

## ByteDance USO ComfyUI Native Workflow

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Flux.1 Dev USO Reference Image Generation

Use reference images to control both style and subject. Keep your character's face while changing artistic style, or apply artistic styles to new scenes.

<img alt="Flux.1 Dev USO reference image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux1_dev_uso_reference_image_gen&utm_source=docs&utm_medium=referral&utm_campaign=flux-1-uso">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux1_dev_uso_reference_image_gen.json">
    Download the workflow JSON and drag it into ComfyUI
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="flux1_dev_uso_reference_image_gen_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/flux1_dev_uso_reference_image_gen_input_image.png">
    `LoadImage` node 47 · `flux1_dev_uso_reference_image_gen_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="flux1_dev_uso_reference_image_gen_input_image.png" />
</div>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="Flux.1 Dev USO example output" />
</div>

### 1. Workflow and input

### 2. Model links

**checkpoints**

* [flux1-dev-fp8.safetensors](https://huggingface.co/Comfy-Org/flux1-dev/blob/main/flux1-dev-fp8.safetensors)

**loras**

* [uso-flux1-dit-lora-v1.safetensors](https://huggingface.co/Comfy-Org/USO_1.0_Repackaged/blob/main/split_files/loras/uso-flux1-dit-lora-v1.safetensors)

**model\_patches**

* [uso-flux1-projector-v1.safetensors](https://huggingface.co/Comfy-Org/USO_1.0_Repackaged/blob/main/split_files/model_patches/uso-flux1-projector-v1.safetensors)

**clip\_visions**

* [sigclip\_vision\_patch14\_384.safetensors](https://huggingface.co/Comfy-Org/sigclip_vision_384/blob/main/sigclip_vision_patch14_384.safetensors)

Please download all models and place them in the following directories:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── flux1-dev-fp8.safetensors
│   ├── 📂 loras/
│   │   └── uso-flux1-dit-lora-v1.safetensors
│   ├── 📂 model_patches/
│   │   └── uso-flux1-projector-v1.safetensors
│   ├── 📂 clip_visions/
│   │   └── sigclip_vision_patch14_384.safetensors
```

### 3. Workflow instructions

<img alt="Workflow instructions" />

1. Load models:
   * 1.1 Ensure the `Load Checkpoint` node has `flux1-dev-fp8.safetensors` loaded
   * 1.2 Ensure the `LoraLoaderModelOnly` node has `dit_lora.safetensors` loaded
   * 1.3 Ensure the `ModelPatchLoader` node has `projector.safetensors` loaded
   * 1.4 Ensure the `Load CLIP Vision` node has `sigclip_vision_patch14_384.safetensors` loaded
2. Content Reference:
   * 2.1 Click `Upload` to upload the input image we provided
   * 2.2 The `ImageScaleToMaxDimension` node will scale your input image for content reference, 512px will keep more character features, but if you only use the character's head as input, the final output image often has issues like the character taking up too much space. Setting it to 1024px gives much better results.
3. In the example, we only use the `content reference` image input. If you want to use the `style reference` image input, you can use `Ctrl-B` to bypass the marked node group.
4. Write your prompt or keep default
5. Set the image size if you need
6. The EasyCache node is for inference acceleration, but it will also sacrifice some quality and details. You can bypass it (Ctrl+B) if you don't need to use it.
7. Click the `Run` button, or use the shortcut `Ctrl(Cmd) + Enter` to run the workflow

### 4. Additional Notes

1. Style reference only:

We also provide a workflow that only uses style reference in the same workflow we provided

<img alt="Workflow" />

The only different is we replaced the `content reference` node and only use an `Empty Latent Image` node.

2. You can also bypass whole `Style Reference` group and use the workflow as a text to image workflow, which means this workflow has 4 variations

* Only use content (subject) reference
* Only use style reference
* Mixed content and style reference
* As a text to image workflow


# ComfyUI Flux.2 Dev Example
Source: https://docs.comfy.org/tutorials/flux/flux-2-dev

This guide provides a brief introduction to the Flux.2 model and guides you through using the Flux.2 Dev model for text-to-image generation in ComfyUI.

<iframe title="YouTube video player" />

## About FLUX.2

[FLUX.2](https://bfl.ai/blog/flux-2) is a next-generation image model from [Black Forest Labs](https://blackforestlabs.ai/), delivering up to 4MP photorealistic output with far better lighting, skin, fabric, and hand detail. It adds reliable multi-reference consistency (up to 10 images), improved editing precision, better visual understanding, and professional-class text rendering.

**Key Features:**

* **Multi-Reference Consistency:** Reliably maintains identity, product geometry, textures, materials, wardrobe, and composition intent across multiple outputs
* **High-Resolution Photorealism:** Generates images up to 4MP with real-world lighting behavior, spatial reasoning, and physics-aware detail
* **Professional-Grade Control:** Exact pose control, hex-code accurate brand colors, any aspect ratio, and structured prompting for programmatic workflows
* **Usable Text Rendering:** Produces clean, legible text across UI screens, infographics, and multi-language content

**Available Models:**

* **FLUX.2 Dev:** Open-source model (used in this tutorial)
* **FLUX.2 Pro:** API version from Black Forest Labs

<Note>
  We are using quantized weights in this workflow. The original FLUX.2 repository is available [here](https://huggingface.co/black-forest-labs/FLUX.2-dev/).
</Note>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Flux.2 Dev

Generate photorealistic images with multi-reference consistency and professional text rendering.

<img alt="Flux.2 Dev workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2&utm_source=docs&utm_medium=referral&utm_campaign=flux-2-dev">
    Open this workflow directly in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_flux2.json">
    Download the JSON workflow file for local use
  </Card>
</CardGroup>

**Input materials**

Upload this file to `LoadImage` node **46**:

<CardGroup>
  <Card title="Input Image for Flux.2 Dev" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/image_flux2_input_image.png">
    `LoadImage` node 46 · `image_flux2_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input Image for Flux.2 Dev" />

  <img alt="Flux.2 Dev example output" />
</div>

## Flux.2 Dev Text to Image

Text-to-image with enhanced lighting, materials, and realistic details. No input images are required.

<img alt="Flux.2 Dev text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2_text_to_image&utm_source=docs&utm_medium=referral&utm_campaign=flux-2-dev">
    Open this workflow directly in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_flux2_text_to_image.json">
    Download the JSON workflow file for local use
  </Card>
</CardGroup>

**Example output**

![Flux.2 Dev text-to-image example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_flux2_text_to_image.png)

## Product Mockup

Create product mockups by applying design patterns to packaging, mugs, and other products using multi-reference consistency.

<img alt="Flux.2 Dev product mockup workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2_fp8&utm_source=docs&utm_medium=referral&utm_campaign=flux-2-dev">
    Open this workflow directly in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_flux2_fp8.json">
    Download the JSON workflow file for local use
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="Input Ref Image for Flux.2 Dev" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/image_flux2_input_ref_image.png">
    `LoadImage` node 42 · `image_flux2_input_ref_image.png`
  </Card>

  <Card title="Input Illustration for Flux.2 Dev" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/image_flux2_input_Illustration.png">
    `LoadImage` node 46 · `image_flux2_input_Illustration.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input Ref Image for Flux.2 Dev" />

  <img alt="Input Illustration for Flux.2 Dev" />
</div>

**Example output**

![Flux.2 Dev product mockup output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_flux2_fp8.png)

## Model links

**text\_encoders**

* [mistral\_3\_small\_flux2\_bf16.safetensors](https://huggingface.co/Comfy-Org/flux2-dev/blob/main/split_files/text_encoders/mistral_3_small_flux2_bf16.safetensors)

**diffusion\_models**

* [flux2\_dev\_fp8mixed.safetensors](https://huggingface.co/Comfy-Org/flux2-dev/blob/main/split_files/diffusion_models/flux2_dev_fp8mixed.safetensors)

**vae**

* [flux2-vae.safetensors](https://huggingface.co/Comfy-Org/flux2-dev/blob/main/split_files/vae/flux2-vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── mistral_3_small_flux2_bf16.safetensors
│   ├── 📂 diffusion_models/
│   │      └── flux2_dev_fp8mixed.safetensors
│   └── 📂 vae/
│          └── flux2-vae.safetensors
```


# ComfyUI Flux.2 Klein 4B Guide
Source: https://docs.comfy.org/tutorials/flux/flux-2-klein

A quick introduction to FLUX.2 [klein] 4B and how to run text-to-image and image editing workflows in ComfyUI.

<iframe title="YouTube video player" />

## About FLUX.2 \[klein]

FLUX.2 \[Klein] is the fastest model in the Flux family, unifying text-to-image and image editing in one compact architecture. It's designed for interactive workflows, immediate previews, and latency-critical applications, with distilled variants delivering end-to-end inference around one second while keeping strong quality for single- and multi-reference editing.

**Model highlights:**

* Two 4B types: Base (undistilled) for maximum flexibility and fine-tuning; Distilled (4-step) for speed-first deployments
* Performance: distilled \~1.2s (5090) · 8.4GB VRAM; base \~17s (5090) · 9.2GB VRAM
* Editing support: style transforms, semantic edits, object replacement/removal, multi-reference composition, iterative edits

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Flux.2 Klein 4B Workflows

### Flux.2 \[Klein] 4B: Text to Image

<img alt="Flux.2 Klein 4B text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2_klein_text_to_image&utm_source=docs&utm_medium=referral&utm_campaign=flux-2-klein">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="4B Text-to-Image Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_flux2_klein_text_to_image.json">
    Download the text-to-image workflow for Flux.2 Klein 4B.
  </Card>
</CardGroup>

**Example output**

![Flux.2 Klein 4B text-to-image example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_flux2_klein_text_to_image.png)

### Flux.2 \[Klein] 4B: Image Edit

<img alt="Flux.2 Klein 4B image edit base workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2_klein_image_edit_4b_base&utm_source=docs&utm_medium=referral&utm_campaign=flux-2-klein">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="4B Image Edit Base" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_flux2_klein_image_edit_4b_base.json">
    Download the image editing workflow using the 4B base model.
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="robed_women.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/robed_women.png">
    `LoadImage` node 76 · `robed_women.png`
  </Card>

  <Card title="pink_tone_chair.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/pink_tone_chair.png">
    `LoadImage` node 81 · `pink_tone_chair.png`
  </Card>
</CardGroup>

<div>
  <img alt="robed_women.png" />

  <img alt="pink_tone_chair.png" />
</div>

**Example output**

![Flux.2 Klein 4B image edit base example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/thumbnail/image_flux2_klein_image_edit_4b_base.png)

### Flux.2 \[Klein] 4B Distilled: Image Edit

<img alt="Flux.2 Klein 4B image edit distilled workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2_klein_image_edit_4b_distilled&utm_source=docs&utm_medium=referral&utm_campaign=flux-2-klein">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="4B Image Edit Distilled" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_flux2_klein_image_edit_4b_distilled.json">
    Download the fast distilled 4B image editing workflow.
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="handbag_white.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/handbag_white.png">
    `LoadImage` node 76 · `handbag_white.png`
  </Card>

  <Card title="comfy_logo_blue.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/comfy_logo_blue.png">
    `LoadImage` node 81 · `comfy_logo_blue.png`
  </Card>
</CardGroup>

<div>
  <img alt="handbag_white.png" />

  <img alt="comfy_logo_blue.png" />
</div>

**Example output**

![Flux.2 Klein 4B image edit distilled example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_flux2_klein_image_edit_4b_distilled.png)

## Flux.2 Klein 4B Model Downloads

<CardGroup>
  <Card title="qwen_3_4b.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/flux2-klein-4B/blob/main/split_files/text_encoders/qwen_3_4b.safetensors">
    Text encoder for 4B models.
  </Card>

  <Card title="flux-2-klein-base-4b-fp8.safetensors" icon="download" href="https://huggingface.co/black-forest-labs/FLUX.2-klein-base-4b-fp8/blob/main/flux-2-klein-base-4b-fp8.safetensors">
    Diffusion model (4B base).
  </Card>

  <Card title="flux-2-klein-4b-fp8.safetensors" icon="download" href="https://huggingface.co/black-forest-labs/FLUX.2-klein-4b-fp8/blob/main/flux-2-klein-4b-fp8.safetensors">
    Diffusion model (4B distilled).
  </Card>

  <Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/flux2-dev/blob/main/split_files/vae/flux2-vae.safetensors">
    VAE for 4B models.
  </Card>
</CardGroup>

**4B Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_3_4b.safetensors
│   ├── 📂 diffusion_models/
│   │      ├── flux-2-klein-base-4b-fp8.safetensors
│   │      └── flux-2-klein-4b-fp8.safetensors
│   └── 📂 vae/
│          └── flux2-vae.safetensors
```

## Flux.2 Klein 9B Workflows

### Flux.2 \[Klein] 9B: Text to Image

<img alt="Flux.2 Klein 9B text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2_text_to_image_9b&utm_source=docs&utm_medium=referral&utm_campaign=flux-2-klein">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="9B Text-to-Image Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_flux2_text_to_image_9b.json">
    Download the text-to-image workflow for Flux.2 Klein 9B.
  </Card>
</CardGroup>

**Example output**

![Flux.2 Klein 9B text-to-image example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_flux2_text_to_image_9b.png)

### Flux.2 \[Klein] 9B: Image Edit

<img alt="Flux.2 Klein 9B image edit base workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2_klein_image_edit_9b_base&utm_source=docs&utm_medium=referral&utm_campaign=flux-2-klein">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="9B Image Edit Base" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_flux2_klein_image_edit_9b_base.json">
    Download the image editing workflow using the 9B base model.
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="car_interior_white.jpeg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/car_interior_white.jpeg">
    `LoadImage` node 76 · `car_interior_white.jpeg`
  </Card>

  <Card title="comfy_logo_blue.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/comfy_logo_blue.png">
    `LoadImage` node 81 · `comfy_logo_blue.png`
  </Card>
</CardGroup>

<div>
  <img alt="car_interior_white.jpeg" />

  <img alt="comfy_logo_blue.png" />
</div>

**Example output**

![Flux.2 Klein 9B image edit base example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/thumbnail/image_flux2_klein_image_edit_9b_base.png)

### Flux.2 \[Klein] 9B Distilled: Image Edit

<img alt="Flux.2 Klein 9B image edit distilled workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2_klein_image_edit_9b_distilled&utm_source=docs&utm_medium=referral&utm_campaign=flux-2-klein">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="9B Image Edit Distilled" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_flux2_klein_image_edit_9b_distilled.json">
    Download the fast distilled 9B image editing workflow.
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="bold_outfit_woman.jpeg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/bold_outfit_woman.jpeg">
    `LoadImage` node 76 · `bold_outfit_woman.jpeg`
  </Card>

  <Card title="handbag_white.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/handbag_white.png">
    `LoadImage` node 121 · `handbag_white.png`
  </Card>
</CardGroup>

<div>
  <img alt="bold_outfit_woman.jpeg" />

  <img alt="handbag_white.png" />
</div>

**Example output**

![Flux.2 Klein 9B image edit distilled example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_flux2_klein_image_edit_9b_distilled.png)

## Flux.2 Klein 9B Model Downloads

<Note>
  For diffusion models, please visit BFL's repo, accept the agreement, and then download the models.
</Note>

<CardGroup>
  <Card title="flux-2-klein-base-9b-fp8.safetensors" icon="download" href="https://huggingface.co/black-forest-labs/FLUX.2-klein-base-9b-fp8">
    Diffusion model (9B base).
  </Card>

  <Card title="flux-2-klein-9b-fp8.safetensors" icon="download" href="https://huggingface.co/black-forest-labs/FLUX.2-klein-9b-fp8">
    Diffusion model (9B distilled).
  </Card>

  <Card title="qwen_3_8b_fp8mixed.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/flux2-klein-9B/blob/main/split_files/text_encoders/qwen_3_8b_fp8mixed.safetensors">
    Text encoder for 9B models.
  </Card>

  <Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/flux2-dev/blob/main/split_files/vae/flux2-vae.safetensors">
    VAE for 9B models.
  </Card>
</CardGroup>

**9B Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │      ├── flux-2-klein-9b-fp8.safetensors
│   │      └── flux-2-klein-base-9b-fp8.safetensors
│   ├── 📂 text_encoders/
│   │      └── qwen_3_8b_fp8mixed.safetensors
│   └── 📂 vae/
│          └── flux2-vae.safetensors
```


# Flux.1 Krea Dev ComfyUI Workflow Tutorial
Source: https://docs.comfy.org/tutorials/flux/flux1-krea-dev

Generate images with the open-source Flux.1 Krea Dev model in ComfyUI, built by Black Forest Labs and Krea for natural details and distinctive aesthetics.

<img alt="Flux.1 Krea Dev Poster" />

[Flux.1 Krea Dev](https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev) is an advanced text-to-image generation model developed in collaboration between Black Forest Labs (BFL) and Krea. This is currently the best open-source FLUX model, specifically designed for text-to-image generation.

**Model Features**

* **Unique Aesthetic Style**: Focuses on generating images with unique aesthetics, avoiding common "AI look" appearance
* **Natural Details**: Does not produce blown-out highlights, maintaining natural detail representatio
* **Exceptional Realism**: Provides outstanding realism and image quality
* **Fully Compatible Architecture**: Fully compatible architecture design with FLUX.1 \[dev]

**Model License**
This model is released under the [flux-1-dev-non-commercial-license](https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev/blob/main/LICENSE.md)

## Flux.1 Krea Dev ComfyUI Workflow

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Flux.1 Krea Dev

A fine-tuned FLUX model pushing photorealism to the max.

<img alt="Flux.1 Krea Dev workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=flux1_krea_dev&utm_source=docs&utm_medium=referral&utm_campaign=flux1-krea-dev">
    Run this workflow on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/flux1_krea_dev.json">
    Download JSON or search "Flux.1 Krea Dev" in Template Library
  </Card>
</CardGroup>

**Example output**

![Flux.1 Krea Dev example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/flux1_krea_dev.png)

#### 1. Workflow Files

#### 2. Manual Model Installation

Please download the following model files:
**Diffusion model**

* [flux1-krea-dev\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/FLUX.1-Krea-dev_ComfyUI/blob/main/split_files/diffusion_models/flux1-krea-dev_fp8_scaled.safetensors)

If you want to pursue higher quality and have enough VRAM, you can try the original model weights

* [flux1-krea-dev.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev/blob/main/flux1-krea-dev.safetensors)

<Note>
  The `flux1-dev.safetensors` file requires agreeing to the [black-forest-labs/FLUX.1-Krea-dev](https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev/) agreement before downloading via browser.
</Note>

If you have used Flux related workflows before, the following models are the same and don't need to be downloaded again

**Text encoders**

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors?download=true)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp16.safetensors?download=true) Recommended when your VRAM is greater than 32GB.
* [t5xxl\_fp8\_e4m3fn.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp8_e4m3fn.safetensors)  For Low VRAM

**VAE**

* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/blob/main/ae.safetensors?download=true)

File save location:

```
ComfyUI/
├── models/
│   ├── diffusion_models/
│   │   └── flux1-krea-dev_fp8_scaled.safetensors or flux1-krea-dev.safetensors
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── t5xxl_fp16.safetensors or t5xxl_fp8_e4m3fn.safetensors
│   ├── vae/
│   │   └── ae.safetensors

```

#### 3. Step-by-step Verification to Ensure Workflow Runs Properly

<Tip>
  For low VRAM users, this model may not run smoothly on your device, you can wait for the community to provide FP8 or GGUF version.
</Tip>

Please refer to the image below to ensure all model files have been loaded correctly

<img alt="ComfyUI Flux Krea Dev Workflow" />

1. Ensure that `flux1-krea-dev_fp8_scaled.safetensors` or `flux1-krea-dev.safetensors` is loaded in the `Load Diffusion Model` node
   * `flux1-krea-dev_fp8_scaled.safetensors` is recommended for low VRAM users
   * `flux1-krea-dev.safetensors` is the original weights, if you have enough VRAM like 24GB you can use it for better quality
2. Ensure the following models are loaded in the `DualCLIPLoader` node:
   * clip\_name1: t5xxl\_fp16.safetensors or t5xxl\_fp8\_e4m3fn.safetensors
   * clip\_name2: clip\_l.safetensors
3. Ensure that `ae.safetensors` is loaded in the `Load VAE` node
4. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow


# Anima Base v1 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/image/anima/anima

Anima is a 2B-parameter text-to-image model by CircleStone Labs / Comfy Org, optimized for anime and non-photorealistic illustration generation.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Anima** is an open text-to-image model by [CircleStone Labs](https://huggingface.co/circlestone-labs/Anima) in partnership with Comfy Org. With **2 billion** parameters, it is designed to generate high-quality **anime and non-photorealistic** images, ideal for characters, scenes, and concept art.

**Model highlights**:

* **Anime and artistic illustration focus**: tuned for non-photorealistic art styles
* **ComfyUI native support**: loaded with standard UNETLoader, CLIPLoader, and VAELoader nodes
* **Qwen-3 0.6B text encoder**: provides strong language understanding and prompt adherence
* **No input image needed**: pure text-to-image generation
* **Compact footprint**: 2B diffusion model, runs comfortably on consumer GPUs

**Related links**:

* [Hugging Face (Anima)](https://huggingface.co/circlestone-labs/Anima)

## Available workflows

Anima provides two workflows: the base version for standard use and a preview version for early access.

Both workflows use a **Subgraph** node to manage the text-to-image generation pipeline. You can open the subgraph to inspect or customize the internal nodes.

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Anima Base v1: Text to Image

Input a text prompt describing an anime or artistic illustration. Generate a non-photorealistic image focused on anime concepts, characters, or styles.

<img alt="Anima Base v1 text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_anima_base_v1&utm_source=docs&utm_medium=referral&utm_campaign=anima">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_anima_base_v1.json">
    Download JSON or search "Anima Base v1" in Template Library
  </Card>
</CardGroup>

**Example output**

![Anima Base v1 example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_anima_base_v1.png)

#### Get started

1. Update ComfyUI to the latest version or use [Comfy Cloud](https://cloud.comfy.org/?template=image_anima_base_v1\&utm_source=docs\&utm_medium=referral\&utm_campaign=anima)
2. Go to **Template** and search for **Anima Base v1**
3. Select the **Anima Base v1: Text to Image** workflow
4. Download any missing models (see [model downloads](#anima-model-downloads)), enter your prompt, and click **Queue**

### Anima Preview: Anime Text-to-Image Generation

Input a text prompt to generate an anime-style image using the Anima model. Configure settings like steps and CFG scale to control the output.

<img alt="Anima Preview text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_anima_preview&utm_source=docs&utm_medium=referral&utm_campaign=anima">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_anima_preview.json">
    Download JSON or search "Anima Preview" in Template Library
  </Card>
</CardGroup>

**Example output**

![Anima Preview example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_anima_preview.png)

#### Get started

1. Update ComfyUI to the latest version or use [Comfy Cloud](https://cloud.comfy.org/?template=image_anima_preview\&utm_source=docs\&utm_medium=referral\&utm_campaign=anima)
2. Go to **Template** and search for **Anima Preview**
3. Select the **Anima Anime Text-to-Image Generation** workflow
4. Download any missing models (see [model downloads](#anima-model-downloads)), enter your prompt, and click **Queue**

## Anima model downloads

You can find all model files at [circlestone-labs/Anima](https://huggingface.co/circlestone-labs/Anima) on Hugging Face.

<Card title="anima-base-v1.0.safetensors" icon="download" href="https://huggingface.co/circlestone-labs/Anima/blob/main/split_files/diffusion_models/anima-base-v1.0.safetensors">
  Diffusion model (2B) for Anima Base v1.
</Card>

<Card title="qwen_3_06b_base.safetensors" icon="download" href="https://huggingface.co/circlestone-labs/Anima/blob/main/split_files/text_encoders/qwen_3_06b_base.safetensors">
  Text encoder (Qwen-3 0.6B) shared by both workflows.
</Card>

<Card title="qwen_image_vae.safetensors" icon="download" href="https://huggingface.co/circlestone-labs/Anima/blob/main/split_files/vae/qwen_image_vae.safetensors">
  VAE shared by both workflows.
</Card>

**Model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── anima-base-v1.0.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen_3_06b_base.safetensors
│   └── 📂 vae/
│       └── qwen_image_vae.safetensors
```

### Preview model

If you are using the Preview workflow, download the preview diffusion model instead:

<Card title="anima-preview3-base.safetensors" icon="download" href="https://huggingface.co/circlestone-labs/Anima/blob/main/split_files/diffusion_models/anima-preview3-base.safetensors">
  Diffusion model (2B) for Anima Preview.
</Card>

**Preview model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 diffusion_models/
│       └── anima-preview3-base.safetensors
```

## Limitations

* **No realism**: the model is intentionally designed for anime and illustration styles; realistic renderings are out of scope
* **Weak text rendering**: high-resolution text and complex typography may not render clearly
* **Plain styling**: the base model produces simpler compositions; advanced artistic styles may require refinement or fine-tuning


# Boogu-Image-0.1 ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/boogu/boogu-image-0.1

Boogu-Image-0.1 is an Apache-2.0 10B parameter unified image generation and editing model family, with variants for text-to-image and instruction-driven editing.

**Boogu-Image-0.1** is an Apache-2.0 open-source unified image generation and editing model family. It uses a system that integrates understanding and generation to deliver competitive performance across photography, text rendering, stylization, and image editing tasks.

**Model Variants**:

* **Boogu-Image-0.1-Turbo** – A four-step distilled text-to-image variant focused on high-quality generation and photorealism, equipped with a LoRA rank-128 module. Requires only 3-4 sampling steps. Recommended as the default for most text-to-image use cases.
* **Boogu-Image-0.1-Base** – The foundation model with strong diversity and controllability, ideal for fine-tuning and ultra-dense text rendering at 2K resolution.
* **Boogu-Image-0.1-Edit** – A variant fine-tuned for image editing and transformation tasks with instruction-driven control.

**Model Highlights**:

* **10B parameters** with efficient inference on consumer GPUs
* **Apache-2.0 license** for open use and downstream development
* **Bilingual text rendering** (Chinese and English) with reliable typography
* **Versatile capabilities**: realistic photography, stylization, poster design, and precise text rendering

**Related Links**:

* [Project Page](https://boogu.org/)
* [GitHub](https://github.com/boogu-project/Boogu-Image)
* [Hugging Face (ComfyUI)](https://huggingface.co/Comfy-Org/Boogu-Image)
* [Hugging Face (Turbo)](https://huggingface.co/Boogu/Boogu-Image-0.1-Turbo-fp8)
* [Hugging Face (Edit)](https://huggingface.co/Boogu/Boogu-Image-0.1-Edit-fp8)

## Boogu-Image-0.1-Turbo text-to-image workflow

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Boogu Turbo: Text to Image

Generate high-quality images from text prompts using the Boogu Turbo model, a distilled 10B-parameter text-to-image pipeline that produces photorealistic outputs in just 4 steps.

<img alt="Boogu Turbo text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_boogu_image_0_1_turbo_t2i&utm_source=docs&utm_medium=referral&utm_campaign=boogu-image-0-1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_boogu_image_0_1_turbo_t2i.json">
    Download JSON or search "Boogu Turbo" in Template Library
  </Card>
</CardGroup>

The Boogu-Image-0.1-Turbo workflow uses a subgraph that encapsulates the diffusion, text encoding, and VAE decode pipeline. You provide a text prompt and resolution settings, and the subgraph handles the rest.

### Boogu-Image-0.1-Turbo model downloads

<CardGroup>
  <Card title="boogu_image_turbo_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Boogu-Image/blob/main/diffusion_models/boogu_image_turbo_fp8_scaled.safetensors">
    Diffusion model for Boogu-Image-0.1-Turbo.
  </Card>

  <Card title="qwen3vl_8b_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Boogu-Image/blob/main/text_encoders/qwen3vl_8b_fp8_scaled.safetensors">
    Text encoder for Boogu-Image-0.1-Turbo.
  </Card>

  <Card title="ae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/vae/ae.safetensors">
    VAE for Boogu-Image-0.1-Turbo.
  </Card>

  <Card title="boogu_image_turbo_lora_rank_128_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Boogu-Image/blob/main/loras/boogu_image_turbo_lora_rank_128_bf16.safetensors">
    LoRA module (rank-128) for Boogu-Image-0.1-Turbo.
  </Card>
</CardGroup>

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── boogu_image_turbo_fp8_scaled.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_8b_fp8_scaled.safetensors
│   ├── 📂 vae/
│   │   └── ae.safetensors
│   └── 📂 loras/
│       └── boogu_image_turbo_lora_rank_128_bf16.safetensors
```

## Boogu-Image-0.1-Edit image editing workflow

### Boogu image 0.1 Edit

Edit images using Boogu's instruction-driven model, taking one input image and generating an edited output alongside a side-by-side comparison view.

<img alt="Boogu image 0.1 Edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_boogu_image_0_1_edit&utm_source=docs&utm_medium=referral&utm_campaign=boogu-image-0-1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_boogu_image_0_1_edit.json">
    Download JSON or search "Boogu image 0.1 Edit" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="tech_cowboy.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/tech_cowboy.png">
    `LoadImage` node 32 · `tech_cowboy.png`
  </Card>
</CardGroup>

<div>
  <img alt="tech_cowboy.png" />
</div>

### Boogu-Image-0.1-Edit model downloads

<CardGroup>
  <Card title="boogu_image_edit_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Boogu-Image/blob/main/diffusion_models/boogu_image_edit_fp8_scaled.safetensors">
    Diffusion model for Boogu-Image-0.1-Edit.
  </Card>

  <Card title="qwen3vl_8b_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Boogu-Image/blob/main/text_encoders/qwen3vl_8b_fp8_scaled.safetensors">
    Text encoder for Boogu-Image-0.1-Edit.
  </Card>

  <Card title="ae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/vae/ae.safetensors">
    VAE for Boogu-Image-0.1-Edit.
  </Card>
</CardGroup>

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── boogu_image_edit_fp8_scaled.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_8b_fp8_scaled.safetensors
│   └── 📂 vae/
│       └── ae.safetensors
```


# ERNIE-Image ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/image/ernie-image/ernie-image

ERNIE-Image is Baidu's open 8B Diffusion Transformer text-to-image model for ComfyUI, with precise text rendering and a built-in Prompt Enhancer.

**ERNIE-Image** is an open text-to-image model by Baidu, licensed under Apache-2.0. Built on an **8B** parameter Diffusion Transformer (DiT), it delivers high-quality image generation with precise text rendering, strong instruction following, and structured visual generation.

The model includes a built-in **Prompt Enhancer** (3B) that expands short inputs into richer prompts for better results.

**Model highlights**:

* **Precise text rendering**: dense and layout-sensitive text in English, Chinese, and more
* **Strong instruction following**: handles complex prompts, multi-object relations, and knowledge-intensive descriptions
* **Structured visual generation**: posters, manga/anime storyboards, multi-panel compositions
* **Broad stylistic range**: realistic photography to cinematic film-like aesthetics
* **Compact and deployable**: 8B parameters, runs on 24 GB VRAM
* **Built-in Prompt Enhancer**: 3B model that expands short inputs into richer prompts

**Related links**:

* [Hugging Face (ERNIE-Image)](https://huggingface.co/Baidu/ERNIE-Image)
* [Hugging Face (ComfyUI Support)](https://huggingface.co/Comfy-Org/ERNIE-Image)

## ERNIE-Image text-to-image workflow

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Ernie Image: Text to Image

Generate images from text prompts using the ERNIE-Image model. Input a text description to produce detailed, structured visuals with a broad stylistic range.

<img alt="ERNIE-Image text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_ernie_image&utm_source=docs&utm_medium=referral&utm_campaign=ernie-image">
    Run this workflow directly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_ernie_image.json">
    Download the ERNIE-Image text-to-image workflow JSON file
  </Card>
</CardGroup>

**Example output**

![ERNIE-Image example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_ernie_image.png)

### Get started

1. Update ComfyUI to the latest version or use [Comfy Cloud](https://cloud.comfy.org/?template=image_ernie_image\&utm_source=docs\&utm_medium=referral\&utm_campaign=ernie-image)
2. Go to **Template** and search for **ERNIE-Image**
3. Select the **ERNIE-Image** workflow
4. Download any missing models, update the prompt, and click **Run**

### ERNIE-Image model downloads

You can find all repackaged model files at [Comfy-Org/ERNIE-Image](https://huggingface.co/Comfy-Org/ERNIE-Image) on Hugging Face.

<CardGroup>
  <Card title="ernie-image.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/blob/main/diffusion_models/ernie-image.safetensors">
    Diffusion model for ERNIE-Image.
  </Card>

  <Card title="ministral-3-3b.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/blob/main/text_encoders/ministral-3-3b.safetensors">
    Text encoder for ERNIE-Image.
  </Card>

  <Card title="ernie-image-prompt-enhancer.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/blob/main/text_encoders/ernie-image-prompt-enhancer.safetensors">
    Prompt Enhancer text encoder for ERNIE-Image.
  </Card>

  <Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/blob/main/vae/flux2-vae.safetensors">
    VAE for ERNIE-Image.
  </Card>
</CardGroup>

**Model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── ernie-image.safetensors
│   ├── 📂 text_encoders/
│   │   ├── ministral-3-3b.safetensors
│   │   └── ernie-image-prompt-enhancer.safetensors
│   └── 📂 vae/
│       └── flux2-vae.safetensors
```

## ERNIE-Image-Turbo

[ERNIE-Image-Turbo](https://huggingface.co/Baidu/ERNIE-Image-Turbo) is a faster variant optimized with DMD and RL, generating images in just **8 steps** compared to the \~50 steps required by the standard model.

### Ernie Image Turbo: Text To Image

Generate images from text prompts using the ERNIE-Image turbo model. Input a text description and receive a high-quality image with precise text rendering.

<img alt="ERNIE-Image-Turbo text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_ernie_image_turbo&utm_source=docs&utm_medium=referral&utm_campaign=ernie-image">
    Run this workflow directly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_ernie_image_turbo.json">
    Download the ERNIE-Image-Turbo text-to-image workflow JSON file
  </Card>
</CardGroup>

**Example output**

![ERNIE-Image-Turbo example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_ernie_image_turbo.png)

### ERNIE-Image-Turbo model downloads

<CardGroup>
  <Card title="ernie-image-turbo.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/blob/main/diffusion_models/ernie-image-turbo.safetensors">
    Diffusion model for ERNIE-Image-Turbo.
  </Card>

  <Card title="ministral-3-3b.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/blob/main/text_encoders/ministral-3-3b.safetensors">
    Text encoder for ERNIE-Image-Turbo.
  </Card>

  <Card title="ernie-image-prompt-enhancer.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/blob/main/text_encoders/ernie-image-prompt-enhancer.safetensors">
    Prompt Enhancer text encoder for ERNIE-Image-Turbo.
  </Card>

  <Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/blob/main/vae/flux2-vae.safetensors">
    VAE for ERNIE-Image-Turbo.
  </Card>
</CardGroup>

**Model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── ernie-image-turbo.safetensors
│   ├── 📂 text_encoders/
│   │   ├── ministral-3-3b.safetensors
│   │   └── ernie-image-prompt-enhancer.safetensors
│   └── 📂 vae/
│       └── flux2-vae.safetensors
```

## Available models

| Model | Description | Inference steps | Link |
| - | - | - | - |
| ERNIE-Image | Main SFT model: stronger quality and instruction fidelity | \~50 | [Hugging Face](https://huggingface.co/Baidu/ERNIE-Image) |
| ERNIE-Image-Turbo | Turbo model optimized with DMD and RL: faster generation | 8 | [Hugging Face](https://huggingface.co/Baidu/ERNIE-Image-Turbo) |

## Examples

### Text rendering and design layouts

![Coffee making process infographic](https://substack-post-media.s3.amazonaws.com/public/images/1cc1c3e6-e556-45b4-b6a9-205e5610d022_1360x768.png)

<Accordion title="Prompt">
  ```text theme={null}
  Educational comic book style infographic showing the coffee making process. The background has a light beige vintage paper texture. At the top center of the image is a bold brown title that reads 'The Coffee Making Process', with a smaller English subtitle 'How Coffee is Made' below. The main part consists of six step blocks connected by brown dotted arrows, arranged in two rows up and down, forming a Z-shaped visual guide.

  The first step in the upper left corner illustrates a coffee tree full of ripe red coffee cherries, with a cut coffee cherry next to it showing the beans inside, labeled 'Step 1: Harvesting Cherries' below the block.
  The second step in the upper middle shows wooden fermentation boxes filled with coffee beans, labeled 'Step 2: Pulping and Fermentation'.
  The third step in the upper right depicts coffee beans being dried under the sun on bamboo mats, labeled 'Step 3: Sun Drying'.
  The fourth step in the lower left shows a vintage metal roasting machine with coffee beans rolling inside and steam rising, labeled 'Step 4: Roasting'.
  The fifth step in the lower middle features a stone grinder pouring out smooth coffee grounds, labeled 'Step 5: Grinding'.
  The sixth step in the lower right shows a production line where coffee liquid is being poured into molds, with finished packaged coffee beside it, labeled 'Step 6: Brewing and Forming'.

  The four corners of the image are decorated with hand-drawn coffee leaves and coffee beans. The overall color palette consists of warm brown, caramel, cream, deep red and olive green, with delicate lines and clear layout.
  ```
</Accordion>

![Japanese Ukiyo-e language flashcard](https://substack-post-media.s3.amazonaws.com/public/images/913c7f5e-f1fe-4f19-b811-ad777ed430b7_768x1360.png)

<Accordion title="Prompt">
  ```text theme={null}
  Vertical rectangular language learning flashcard in traditional Japanese Ukiyo-e woodblock style. Whole card framed by dark blue traditional Seigaiha wave borders, with aged beige rough washi paper texture background.

  Upper two-thirds: Ukiyo-e illustration. A graceful spotted sika deer stands calmly in the center, with delicate black outlines and traditional flat coloring. Background: classic Japanese scenery — snow-capped Mount Fuji in distance, stylized layered clouds, falling pink cherry blossom petals. A red square antique seal with the Chinese character '鹿' in seal script at the lower right. Color scheme: indigo, vermilion, moss green, beige, with woodblock color misalignment and vintage charm.

  Lower one-third: centered text area. Top: small hiragana しか; large Japanese kanji 鹿; below it romaji shika; then English "Deer". Bottom: bilingual example — Japanese: 鹿が桜の花を見ている。English: The deer is looking at the cherry blossoms. All black text with slight brush calligraphy texture, matching Ukiyo-e antique style.
  ```
</Accordion>

![Split-screen conceptual poster](https://substack-post-media.s3.amazonaws.com/public/images/c814eef7-7df4-4f66-8889-e8325fe79dba_768x1360.png)

<Accordion title="Prompt">
  ```text theme={null}
  Split-screen conceptual poster with vertical split composition, left half representing the present and future featuring a solid stone analog clock dial with bright red hands and red scale markings, set against a deeply cracked, dry, parched earth texture in muted cool gray tones, embodying slow, static structural decay and temporal erosion, right half representing the past that is violently disintegrating, dissolving and exploding into chaotic dust, debris, flying stone shards and swirling cosmic nebula energy with a deep blood red and black color palette, the circular clock frame itself is half solid weathered stone and half crumbling into particles merging the two worlds, with the red clock hands fully positioned on the left present/future side of the dial, embodying the concept of time, past vs future, slow decay vs violent collapse, hyper-realistic 3D render with cinematic dramatic lighting, high contrast, sharp details on the left side, motion blur and dynamic particle effects on the right side, photorealistic textures of cracked earth and floating dust, atmospheric haze, futuristic graphic design with minimalist red vertical UI elements and custom technical text overlays in the corners, bold red stylized title text "ETERNAL DAWN" in the top right corner, small red technical metadata text "SPECDARY BOTHUNG" directly below the main title in the top right, dense lines of small red technical data blocks including "TIMESTAMP: 00:00:00", "COLLAPSE RATE: 99.8%", "TEMPORAL ANOMALY DETECTED", "PAST DIMENSION: DECAYING" in the bottom right corner with a red horizontal accent bar and footer text "FOR DECAY OF THE EONS" below, small red header text "TEMPORAL SHIFT PROTOCOL" with vertical red accent line running down the left edge in the top left, vertical red accent line with small red technical text annotations including "PRESENT: STABLE", "FUTURE: UNFOLDING" along it in the bottom left, red text "WARNING: TEMPORAL DISINTEGRATION" curving around the center clock dial perimeter, small red footer text "PAST FADES, FUTURE RISES" spanning the split at the bottom center, shot in the style of a high-end sci-fi movie poster, 8K ultra-high resolution, photorealistic, cinematic composition, dramatic depth, moody and intense atmosphere, detailed particle simulation, photorealistic material rendering.
  ```
</Accordion>

### Cinematic and stylized aesthetics

![Urban night street scene](https://substack-post-media.s3.amazonaws.com/public/images/d4f27467-4d1f-4f6d-8c15-ebc92983c29d_1360x768.png)

<Accordion title="Prompt">
  ```text theme={null}
  First-person vertical real-world urban night photo. Narrow, wet, busy city street with strong depth; towering buildings on both sides with fire escapes, pipes, AC units, warm window lights. Red vertical "HOTEL" neon on left, bright blue "BAR" sign and yellow "OPEN 24 HOURS" box on right. Distant huge digital billboard glowing cyan "NEON CITY". Rough wet asphalt reflects neon lights; vintage yellow taxi with "TAXI" sign drives down center, red taillights on. Two pedestrians in dark coats with black umbrellas walk away on right sidewalk. Giant needle-like steel TV tower peeks through building gaps at end, red aircraft warning light glowing. Cinematic volumetric light, misty air, cool cyan-blue vs warm orange-red contrast, immersive and realistic.
  ```
</Accordion>

![Editorial fashion photograph](https://substack-post-media.s3.amazonaws.com/public/images/3044c459-db9a-453c-88f8-32470fa2ecf9_1360x768.png)

<Accordion title="Prompt">
  ```text theme={null}
  Full-body editorial fashion shot, elegant European woman aged 28-30 with soft natural blonde hair styled in a loose low bun, wearing a tailored soft cream ribbed knit long-sleeve maxi dress with a fitted waist and flowing floor-length skirt, minimalist nude leather mules and delicate gold jewelry, standing leaning against an ornate carved stone balustrade on a gravel terrace in the garden of a grand Lake Como villa, tall iconic Italian cypress trees framing the background, calm still Lake Como water stretching out to hazy misty Alpine mountains in the distance, overcast soft diffused natural light, muted warm earthy color palette, quiet luxury aesthetic, hyper-realistic editorial fashion photography, natural skin texture with subtle pores, soft bokeh foreground foliage, shallow depth of field, shot on a medium format camera with an 85mm f/1.4 lens, sharp focus on the subject, fine film grain, muted contrast, timeless sophisticated mood, shot by Lachlan Bailey in the style of Vogue editorial, 8K ultra-high resolution, photorealistic, cinematic composition following the rule of thirds, golden hour overcast lighting, atmospheric haze, refined Italian villa garden details.
  ```
</Accordion>

![3D illustration of a duck with coffee](https://substack-post-media.s3.amazonaws.com/public/images/01abb65b-6d3e-4b08-a0b2-d0ae539f6516_1024x1024.png)

<Accordion title="Prompt">
  ```text theme={null}
  A charming, whimsical 3D illustration featuring a fluffy, plush-textured white duck sitting comfortably in a fuzzy coral-pink armchair, holding a bright red mug of steaming black coffee against a solid warm coral-red background; defined by its tactile, huggable fabric-like texture across all elements, a bold, minimalist warm color palette of creamy white, vibrant orange, and rich reds, gentle anthropomorphism that blends cuteness with relatable cozy relaxation, soft diffused lighting, and a subtle film grain that adds a nostalgic, handcrafted feel, creating a playful yet serene mood perfect for themes of calm downtime and morning routines.
  ```
</Accordion>

### Multi-panel compositions

![North American native species infographic](https://substack-post-media.s3.amazonaws.com/public/images/4e9a2968-9f7c-4b2f-92e6-b0fa9a91ede2_1360x768.png)

<Accordion title="Prompt">
  ```text theme={null}
  Educational comic book infographic. Five vertical panels side by side, earthy color palette, hand-drawn illustration style. Top title: "NORTH AMERICAN NATIVE SPECIES". Style: comic line art, watercolor fills, white panel backgrounds, bold headers.
  Panel 1: Gray squirrel holding an acorn. Header: "EASTERN GRAY SQUIRREL" Fact: "Buries acorns to help forests grow." Arrow → tail: "Bushy tail"

  Panel 2: Robin with orange-red breast on a branch. Header: "AMERICAN ROBIN" Fact: "A sign of spring returning." Arrow → breast: "Orange-red breast"

  Panel 3: Red maple tree with autumn leaves. Header: "RED MAPLE TREE" Fact: "Shelters wildlife year-round." Arrow → leaves: "Red in autumn"

  Panel 4: Deer with white tail raised. Header: "WHITE-TAILED DEER" Fact: "White tail signals danger." Arrow → tail: "Alarm signal"

  Panel 5: Monarch butterfly on a flower. Header: "MONARCH BUTTERFLY" Fact: "Migrates 3,000 miles each year." Arrow → wings: "Warning colors"
  ```
</Accordion>

![6-panel comic page](https://substack-post-media.s3.amazonaws.com/public/images/adc8fe73-f431-4bdd-8578-1a18d717d4d7_1360x768.png)

<Accordion title="Prompt">
  ```text theme={null}
  A 6-panel comic page, 2 columns × 3 rows, black border between each panel.

  Panel 1 (top-left): wide shot — a young woman in a red coat stands at a rainy train station. Caption box: "She had waited three years for this moment."
  Panel 2 (top-right): close-up on her face — anxious eyes, rain on her cheek. No text.
  Panel 3 (mid-left): medium shot — a train arrives, doors slide open, steam rising. Sound effect text: "WHOOOOSH"
  Panel 4 (mid-right): her point-of-view — a man in a gray jacket steps out, back to camera.
  Panel 5 (bottom-left): extreme close-up — her hand trembling as she reaches forward.
  Panel 6 (bottom-right): wide shot — they face each other under one umbrella. Caption box: "Some arrivals change everything."

  Ink and watercolor style, cool blue-gray palette, expressive line art. Same character design consistent across all 6 panels.
  ```
</Accordion>


# ComfyUI Native HiDream-E1, E1.1 Workflow Example
Source: https://docs.comfy.org/tutorials/image/hidream/hidream-e1

This guide will help you understand and complete the ComfyUI native HiDream-I1 text-to-image workflow example

![HiDream-E1 Demo](https://raw.githubusercontent.com/HiDream-ai/HiDream-E1/refs/heads/main/assets/demo.jpg)

HiDream-E1 is an interactive image editing large model officially open-sourced by HiDream-ai, built based on HiDream-I1.

It allows you to edit images using natural language. The model is released under the [MIT License](https://github.com/HiDream-ai/HiDream-E1?tab=MIT-1-ov-file), supporting use in personal projects, scientific research, and commercial applications.
In combination with the previously released [hidream-i1](/tutorials/image/hidream/hidream-i1), it enables **creative capabilities from image generation to editing**.

| Name | Update Date | Inference Steps | Resolution | HuggingFace Repository |
| - | - | - | - | - |
| HiDream-E1-Full | 2025-4-28 | 28 | 768x768 | 🤗 [HiDream-E1-Full](https://huggingface.co/HiDream-ai/HiDream-E1-Full) |
| HiDream-E1.1 | 2025-7-16 | 28 | Dynamic (1 Megapixel) | 🤗 [HiDream-E1.1](https://huggingface.co/HiDream-ai/HiDream-E1-1) |

[HiDream E1 - Github](https://github.com/HiDream-ai/HiDream-E1)

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## HiDream E1 and E1.1 Workflow Related Models

All the models involved in this guide can be found [here](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/tree/main/split_files). Except for the Diffusion model, E1 and E1.1 use the same models.
The corresponding workflow files also include the relevant model information. You can choose to manually download and save the models, or follow the workflow prompts to download them after loading the workflow. It is recommended to use E1.1.

This model requires a large amount of VRAM to run. Please refer to the relevant sections for specific VRAM requirements.

**Diffusion Model**

You do not need to download both models. Since E1.1 is an iterative version based on E1, our tests show that its quality and performance are significantly improved compared to E1.

* [hidream\_e1\_1\_bf16.safetensors (Recommended)](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/diffusion_models/hidream_e1_1_bf16.safetensors) 34.2GB
* [hidream\_e1\_full\_bf16.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/diffusion_models/hidream_e1_full_bf16.safetensors) 34.2GB

**Text Encoder**:

* [clip\_l\_hidream.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/clip_l_hidream.safetensors) 236.12MB
* [clip\_g\_hidream.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/clip_g_hidream.safetensors) 1.29GB
* [t5xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/t5xxl_fp8_e4m3fn_scaled.safetensors) 4.8GB
* [llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/llama_3.1_8b_instruct_fp8_scaled.safetensors) 8.46GB

**VAE**

* [ae.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/vae/ae.safetensors) 319.77MB

> This is the VAE model for Flux. If you have used the Flux workflow before, you may have already downloaded this file.

Model Save Location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │   ├─── clip_l_hidream.safetensors
│   │   ├─── clip_g_hidream.safetensors
│   │   ├─── t5xxl_fp8_e4m3fn_scaled.safetensors
│   │   └─── llama_3.1_8b_instruct_fp8_scaled.safetensors
│   └── 📂 vae/
│   │   └── ae.safetensors
│   └── 📂 diffusion_models/
│       ├── hidream_e1_1_bf16.safetensors
│       └── hidream_e1_full_bf16.safetensors
```

## HiDream E1.1 ComfyUI Native Workflow Example

### HiDream E1.1 Image Editing

Edit images with HiDream E1.1. Superior image quality and editing accuracy compared to HiDream-E1-Full.

<img alt="HiDream E1.1 image editing workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=hidream_e1_1&utm_source=docs&utm_medium=referral&utm_campaign=hidream-e1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/hidream_e1_1.json">
    Download JSON or search "HiDream E1.1" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="hidream_e1_1_input_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/hidream_e1_1_input_image.jpg">
    `LoadImage` node 13 · `hidream_e1_1_input_image.jpg`
  </Card>
</CardGroup>

<div>
  <img alt="hidream_e1_1_input_image.jpg" />
</div>

### 1. HiDream E1.1 Workflow and Related Materials

Download the image below and drag it into ComfyUI with the corresponding workflow and models loaded:
![HiDream E1.1 Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/hidream/e1.1/hidream_e1_1.png)

Download the image below as input:
![HiDream E1.1 Workflow Input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/hidream/e1.1/input.webp)

### 2. Step-by-step Guide to Running the HiDream-e1 Workflow

<img alt="hidream_e1_1_guide" />

Follow these steps to run the workflow:

1. Make sure the `Load Diffusion Model` node loads the `hidream_e1_1_bf16.safetensors` model.
2. Make sure the four corresponding text encoders in `QuadrupleCLIPLoader` are loaded correctly:
   * clip\_l\_hidream.safetensors
   * clip\_g\_hidream.safetensors
   * t5xxl\_fp8\_e4m3fn\_scaled.safetensors
   * llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors
3. Make sure the `Load VAE` node uses the `ae.safetensors` file.
4. In the `Load Image` node, load the provided input or your desired image.
5. In the `Empty Text Encoder(Positive)` node, enter **the modifications you want to make to the image**.
6. In the `Empty Text Encoder(Negative)` node, enter **the content you do not want to appear in the image**.
7. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute image generation.

### 3. Additional Notes on the Workflow

* Since HiDream E1.1 supports dynamic input with a total of 1 million pixels, the workflow uses `Scale Image to Total Pixels` to process and convert all input images, which may cause the aspect ratio to differ from the original input image.
* When using the fp16 version of the model, in actual tests, the full version ran out of memory on both A100 40GB and 4090D 24GB, so the workflow is set by default to use `fp8_e4m3fn_fast` for inference.

## HiDream E1 ComfyUI Native Workflow Example

### HiDream E1 Image Edit

Edit images with HiDream E1. Professional natural language image editing model.

<img alt="HiDream E1 image editing workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=hidream_e1_full&utm_source=docs&utm_medium=referral&utm_campaign=hidream-e1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/hidream_e1_full.json">
    Download JSON or search "HiDream E1 Full" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="hidream_e1_full_input_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/hidream_e1_full_input_image.jpg">
    `LoadImage` node 13 · `hidream_e1_full_input_image.jpg`
  </Card>
</CardGroup>

<div>
  <img alt="hidream_e1_full_input_image.jpg" />
</div>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="HiDream E1 example output" />
</div>

E1 is a model released on April 28, 2025.

<Tip>
  For reference, this workflow takes about 500s for the first run and 370s for the second run with 28 sampling steps on Google Colab L4 with 22.5GB VRAM.
</Tip>

### 1. HiDream-e1 workflow

Please download the image below and drag it into ComfyUI. The workflow already contains model download information, and after loading, it will prompt you to download the corresponding models.

![ComfyUI Native HiDream-e1 Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hidream_e1/hidream_e1_full.png)

Download this image below as input:
![ComfyUI Native HiDream-e1 Workflow Input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hidream_e1/input.webp)

### 2. Complete the HiDream-e1 Workflow Step by Step

<img alt="hidream_e1_full_step_guide" />

Follow these steps to complete the workflow:

1. Make sure the `Load Diffusion Model` node has loaded the `hidream_e1_full_bf16.safetensors` model
2. Ensure that the four corresponding text encoders are correctly loaded in the `QuadrupleCLIPLoader`
   * clip\_l\_hidream.safetensors
   * clip\_g\_hidream.safetensors
   * t5xxl\_fp8\_e4m3fn\_scaled.safetensors
   * llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors
3. Make sure the `Load VAE` node is using the `ae.safetensors` file
4. Load the input image we downloaded earlier in the `Load Image` node
5. (Important) Enter **the prompt for how you want to modify the image** in the `Empty Text Encoder(Positive)` node
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to generate the image

### Additional Notes on ComfyUI HiDream-e1 Workflow

* You may need to modify the prompt multiple times or generate multiple times to get better results
* This model has difficulty maintaining consistency when changing image styles, so try to make your prompts as complete as possible
* As the model supports a resolution of 768\*768, in actual testing with other dimensions, the image performance is poor or even significantly different at other dimensions


# ComfyUI Native HiDream-I1 Text-to-Image Workflow Example
Source: https://docs.comfy.org/tutorials/image/hidream/hidream-i1

This guide will walk you through completing a ComfyUI native HiDream-I1 text-to-image workflow example

![HiDream-I1 Demo](https://raw.githubusercontent.com/HiDream-ai/HiDream-I1/main/assets/demo.jpg)

HiDream-I1 is a text-to-image model officially open-sourced by HiDream-ai on April 7, 2025. The model has 17B parameters and is released under the [MIT license](https://github.com/HiDream-ai/HiDream-I1/blob/main/LICENSE), supporting personal projects, scientific research, and commercial use.
It currently performs excellently in multiple benchmark tests.

## Model Features

**Hybrid Architecture Design**
A combination of Diffusion Transformer (DiT) and Mixture of Experts (MoE) architecture:

* Based on Diffusion Transformer (DiT), with dual-stream MMDiT modules processing multimodal information and single-stream DiT modules optimizing global consistency.
* Dynamic routing mechanism flexibly allocates computing resources, enhancing complex scene processing capabilities and delivering excellent performance in color restoration, edge processing, and other details.

**Multimodal Text Encoder Integration**
Integrates four text encoders:

* OpenCLIP ViT-bigG, OpenAI CLIP ViT-L (visual semantic alignment)
* T5-XXL (long text parsing)
* Llama-3.1-8B-Instruct (instruction understanding)
  This combination achieves SOTA performance in complex semantic parsing of colors, quantities, spatial relationships, etc., with Chinese prompt support significantly outperforming similar open-source models.

**Original Model Versions**

HiDream-ai provides three versions of the HiDream-I1 model to meet different needs. Below are the links to the original model repositories:

| Model Name | Description | Inference Steps | Repository Link |
| - | - | - | - |
| HiDream-I1-Full | Full version | 50 | [🤗 HiDream-I1-Full](https://huggingface.co/HiDream-ai/HiDream-I1-Full) |
| HiDream-I1-Dev | Distilled dev | 28 | [🤗 HiDream-I1-Dev](https://huggingface.co/HiDream-ai/HiDream-I1-Dev) |
| HiDream-I1-Fast | Distilled fast | 16 | [🤗 HiDream-I1-Fast](https://huggingface.co/HiDream-ai/HiDream-I1-Fast) |

## About This Workflow Example

In this example, we will use the repackaged version from ComfyOrg. You can find all the model files we'll use in this example in the [HiDream-I1\_ComfyUI](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/) repository.

<Tip>
  Before starting, please update your ComfyUI version to ensure it's at least after this [commit](https://github.com/Comfy-Org/ComfyUI/commit/9ad792f92706e2179c58b2e5348164acafa69288) to make sure your ComfyUI has native support for HiDream
</Tip>

## HiDream-I1 Workflow

The model requirements for different ComfyUI native HiDream-I1 workflows are basically the same, with only the [diffusion models](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/tree/main/split_files/diffusion_models) files being different.

If you don't know which version to choose, please refer to the following suggestions:

* **HiDream-I1-Full** can generate the highest quality images
* **HiDream-I1-Dev** balances high-quality image generation with speed
* **HiDream-I1-Fast** can generate images in just 16 steps, suitable for scenarios requiring real-time iteration

For the **dev** and **fast** versions, negative prompts are not needed, so please set the `cfg` parameter to `1.0` during sampling. We have noted the corresponding parameter settings in the relevant workflows.

<Tip>
  The full versions of all three versions require a lot of VRAM - you may need more than 27GB of VRAM to run them smoothly. In the corresponding workflow tutorials,
  we will use the **fp8** version as a demonstration example to ensure that most users can run it smoothly.
  However, we will still provide download links for different versions of the model in the corresponding examples, and you can choose the appropriate file based on your VRAM situation.
</Tip>

### Model Installation

The following model files are common files that we will use.
Please click on the corresponding links to download and save them according to the model file save location.
We will guide you to download the corresponding **diffusion models** in the corresponding workflows.

**text\_encoders**：

* [clip\_l\_hidream.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/clip_l_hidream.safetensors)
* [clip\_g\_hidream.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/clip_g_hidream.safetensors)
* [t5xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/t5xxl_fp8_e4m3fn_scaled.safetensors) This model has been used in many workflows, you may have already downloaded this file.
* [llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/llama_3.1_8b_instruct_fp8_scaled.safetensors)

**VAE**

* [ae.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/vae/ae.safetensors) This is Flux's VAE model, if you have used Flux's workflow before, you may have already downloaded this file.

**diffusion models**
We will guide you to download the corresponding model files in the corresponding workflows.

Model file save location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │   ├─── clip_l_hidream.safetensors
│   │   ├─── clip_g_hidream.safetensors
│   │   ├─── t5xxl_fp8_e4m3fn_scaled.safetensors
│   │   └─── llama_3.1_8b_instruct_fp8_scaled.safetensors
│   └── 📂 vae/
│   │   └── ae.safetensors
│   └── 📂 diffusion_models/
│       └── ...               # We will guide you to install in the corresponding version workflow       
```

### HiDream I1 Full Version Workflow

### HiDream I1 Full

Generate images with HiDream I1 Full. Complete version with 50 inference steps for highest quality output.

<img alt="HiDream I1 Full workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=hidream_i1_full&utm_source=docs&utm_medium=referral&utm_campaign=hidream-i1">
    Run this workflow on Comfy Cloud with zero setup
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/hidream_i1_full.json">
    Download the workflow JSON file
  </Card>
</CardGroup>

**Example output**

![HiDream I1 Full example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/hidream_i1_full.png)

#### 1. Model File Download

Please select the appropriate version based on your hardware. Click the link and download the corresponding model file to save it to the `ComfyUI/models/diffusion_models/` folder.

* FP8 version: [hidream\_i1\_full\_fp8.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/diffusion_models/hidream_i1_full_fp8.safetensors?download=true) requires more than 16GB of VRAM
* Full version: [hidream\_i1\_full\_f16.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/diffusion_models/hidream_i1_full_fp16.safetensors?download=true) requires more than 27GB of VRAM

#### 2. Workflow File Download

Please download the image below and drag it into ComfyUI to load the corresponding workflow
![HiDream-I1 Full Version Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hidream_i1/hidream_i1_full.png)

#### 3. Complete the Workflow Step by Step

<img alt="HiDream-I1 Full Version Flow Diagram" />

Complete the workflow execution step by step

1. Make sure the `Load Diffusion Model` node is using the `hidream_i1_full_fp8.safetensors` file
2. Make sure the four corresponding text encoders in `QuadrupleCLIPLoader` are loaded correctly
   * clip\_l\_hidream.safetensors
   * clip\_g\_hidream.safetensors
   * t5xxl\_fp8\_e4m3fn\_scaled.safetensors
   * llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors
3. Make sure the `Load VAE` node is using the `ae.safetensors` file
4. For the **full** version, you need to set the `shift` parameter in `ModelSamplingSD3` to `3.0`
5. For the `Ksampler` node, you need to make the following settings
   * Set `steps` to `50`
   * Set `cfg` to `5.0`
   * (Optional) Set `sampler` to `lcm`
   * (Optional) Set `scheduler` to `normal`
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

### HiDream-I1 Dev Version Workflow

### HiDream I1 Dev

Generate images with HiDream I1 Dev. Balanced version with 28 inference steps, suitable for medium-range hardware.

<img alt="HiDream I1 Dev workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=hidream_i1_dev&utm_source=docs&utm_medium=referral&utm_campaign=hidream-i1">
    Run this workflow on Comfy Cloud with zero setup
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/hidream_i1_dev.json">
    Download the workflow JSON file
  </Card>
</CardGroup>

**Example output**

![HiDream I1 Dev example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/hidream_i1_dev.png)

#### 1. Model File Download

Please select the appropriate version based on your hardware, click the link and download the corresponding model file to save to the `ComfyUI/models/diffusion_models/` folder.

* FP8 version: [hidream\_i1\_dev\_fp8.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/diffusion_models/hidream_i1_dev_fp8.safetensors?download=true) requires more than 16GB of VRAM
* Full version: [hidream\_i1\_dev\_bf16.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/diffusion_models/hidream_i1_dev_bf16.safetensors?download=true) requires more than 27GB of VRAM

#### 2. Workflow File Download

Please download the image below and drag it into ComfyUI to load the corresponding workflow

![HiDream-I1 Dev Version Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hidream_i1/hidream_i1_dev.png)

#### 3. Complete the Workflow Step by Step

<img alt="HiDream-I1 Dev Version Flow Diagram" />

Complete the workflow execution step by step

1. Make sure the `Load Diffusion Model` node is using the `hidream_i1_dev_fp8.safetensors` file
2. Make sure the four corresponding text encoders in `QuadrupleCLIPLoader` are loaded correctly
   * clip\_l\_hidream.safetensors
   * clip\_g\_hidream.safetensors
   * t5xxl\_fp8\_e4m3fn\_scaled.safetensors
   * llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors
3. Make sure the `Load VAE` node is using the `ae.safetensors` file
4. For the **dev** version, you need to set the `shift` parameter in `ModelSamplingSD3` to `6.0`
5. For the `Ksampler` node, you need to make the following settings
   * Set `steps` to `28`
   * (Important) Set `cfg` to `1.0`
   * (Optional) Set `sampler` to `lcm`
   * (Optional) Set `scheduler` to `normal`
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

### HiDream-I1 Fast Version Workflow

### HiDream I1 Fast

Generate images quickly with HiDream I1 Fast. Lightweight version with 16 inference steps, ideal for rapid previews on lower-end hardware.

<img alt="HiDream I1 Fast workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=hidream_i1_fast&utm_source=docs&utm_medium=referral&utm_campaign=hidream-i1">
    Run this workflow on Comfy Cloud with zero setup
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/hidream_i1_fast.json">
    Download the workflow JSON file
  </Card>
</CardGroup>

**Example output**

![HiDream I1 Fast example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/hidream_i1_fast.png)

#### 1. Model File Download

Please select the appropriate version based on your hardware, click the link and download the corresponding model file to save to the `ComfyUI/models/diffusion_models/` folder.

* FP8 version: [hidream\_i1\_fast\_fp8.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/diffusion_models/hidream_i1_fast_fp8.safetensors?download=true) requires more than 16GB of VRAM
* Full version: [hidream\_i1\_fast\_bf16.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/diffusion_models/hidream_i1_fast_bf16.safetensors?download=true) requires more than 27GB of VRAM

#### 2. Workflow File Download

Please download the image below and drag it into ComfyUI to load the corresponding workflow

![HiDream-I1 Fast Version Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hidream_i1/hidream_i1_fast.png)

#### 3. Complete the Workflow Step by Step

<img alt="HiDream-I1 Fast Version Flow Diagram" />

Complete the workflow execution step by step

1. Make sure the `Load Diffusion Model` node is using the `hidream_i1_fast_fp8.safetensors` file
2. Make sure the four corresponding text encoders in `QuadrupleCLIPLoader` are loaded correctly
   * clip\_l\_hidream.safetensors
   * clip\_g\_hidream.safetensors
   * t5xxl\_fp8\_e4m3fn\_scaled.safetensors
   * llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors
3. Make sure the `Load VAE` node is using the `ae.safetensors` file
4. For the **fast** version, you need to set the `shift` parameter in `ModelSamplingSD3` to `3.0`
5. For the `Ksampler` node, you need to make the following settings
   * Set `steps` to `16`
   * (Important) Set `cfg` to `1.0`
   * (Optional) Set `sampler` to `lcm`
   * (Optional) Set `scheduler` to `normal`
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## Other Related Resources

### GGUF Version Models

* [HiDream-I1-Full-gguf](https://huggingface.co/city96/HiDream-I1-Full-gguf)
* [HiDream-I1-Dev-gguf](https://huggingface.co/city96/HiDream-I1-Dev-gguf)

You need to use the “Unet Loader (GGUF)” node in City96's [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) to replace the “Load Diffusion Model” node.

### NF4 Version Models

* [HiDream-I1-nf4](https://github.com/hykilpikonna/HiDream-I1-nf4)
* Use the [ComfyUI-HiDream-Sampler](https://github.com/SanDiegoDude/ComfyUI-HiDream-Sampler) node to use the NF4 version model.


# ComfyUI Native HiDream-O1-Image Workflow Example
Source: https://docs.comfy.org/tutorials/image/hidream/hidream-o1

This guide walks you through the ComfyUI native HiDream-O1-Image text-to-image and image editing workflows

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

![HiDream-O1-Image Demo](https://raw.githubusercontent.com/HiDream-ai/HiDream-O1-Image/main/assets/general.webp)

HiDream-O1-Image is a unified image generative foundation model open-sourced by HiDream-ai on May 8, 2026. Built on a Pixel-level Unified Transformer (UiT), it operates without external VAEs or disjoint text encoders, supporting **text-to-image**, **instruction-based image editing**, **subject-driven personalization**, and **storyboard generation** at up to 2,048 × 2,048 resolution.

HiDream-O1-Image is released under the [MIT License](https://github.com/HiDream-ai/HiDream-O1-Image?tab=MIT-1-ov-file) and natively supported in ComfyUI (PR [#13817](https://github.com/Comfy-Org/ComfyUI/pull/13817)).

[HiDream-O1-Image - GitHub](https://github.com/HiDream-ai/HiDream-O1-Image)

### Model Versions

| Model | Inference Steps | Repository |
| - | - | - |
| HiDream-O1-Image (Full) | 50 | [🤗 HiDream-O1-Image](https://huggingface.co/HiDream-ai/HiDream-O1-Image) |
| HiDream-O1-Image-Dev | 28 | [🤗 HiDream-O1-Image-Dev](https://huggingface.co/HiDream-ai/HiDream-O1-Image-Dev) |

## HiDream-O1-Image Full Workflow

### HiDream O1 Full: Image generation

Input a text prompt and optionally upload reference images. Generate a high-resolution image up to 2048x2048 with text-to-image, editing, or subject-driven personalization.

<img alt="HiDream O1 Full workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_hidream_o1&utm_source=docs&utm_medium=referral&utm_campaign=hidream-o1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_hidream_o1.json">
    Download JSON or search "HiDream O1 Full" in Template Library
  </Card>
</CardGroup>

**Example output**

![HiDream O1 Full example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_hidream_o1.png)

### 1. Download Workflow

### 2. Download Models

**Checkpoint**: re-packaged and quantized. All use bf16 for worst outliers, unused deepstack layers removed:

* [hidream\_o1\_image\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/blob/main/checkpoints/hidream_o1_image_fp8_scaled.safetensors): FP8, uses fp8/mxfp8 matmuls on safe MLP layers for speedup on supported hardware
* [hidream\_o1\_image\_mxfp8.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/blob/main/checkpoints/hidream_o1_image_mxfp8.safetensors): MXFP8 quantized variant
* [hidream\_o1\_image\_bf16.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/blob/main/checkpoints/hidream_o1_image_bf16.safetensors): Full bf16 precision (largest)

**Text Encoder** (prompt enhancement): shared across all versions:

* [gemma4\_e4b\_it\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/gemma-4/blob/main/text_encoders/gemma4_e4b_it_fp8_scaled.safetensors)

**LoRA (optional)**: the Dev distillation can also be applied to the Full model as a LoRA, allowing you to adjust the distillation strength (by [Kijai](https://huggingface.co/Kijai/hidream-O1-image_comfy)):

* [hidream\_o1\_dev\_lora\_rank\_64\_bf16.safetensors](https://huggingface.co/Kijai/hidream-O1-image_comfy/blob/main/loras/hidream_o1_dev_lora_rank_64_bf16.safetensors): Full rank
* [hidream\_o1\_dev\_lora\_rank\_64\_bf16\_pruned\_v1.safetensors](https://huggingface.co/Kijai/hidream-O1-image_comfy/blob/main/loras/hidream_o1_dev_lora_rank_64_bf16_pruned_v1.safetensors): Pruned variant
* [hidream\_o1\_image\_dev\_2604\_lora\_avg\_rankg\_224\_bf16.safetensors](https://huggingface.co/Kijai/hidream-O1-image_comfy/blob/main/loras/hidream_o1_image_dev_2604_lora_avg_rankg_224_bf16.safetensors): Alternative checkpoint-based distillation

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   ├── hidream_o1_image_fp8_scaled.safetensors
│   │   ├── hidream_o1_image_mxfp8.safetensors
│   │   └── hidream_o1_image_bf16.safetensors
│   ├── 📂 loras/
│   │   └── hidream_o1_dev_lora_rank_64_bf16.safetensors
│   └── 📂 text_encoders/
│       └── gemma4_e4b_it_fp8_scaled.safetensors
```

### 3. Using the Workflow

* Make sure `CheckpointLoaderSimple` loads your chosen checkpoint
* Enter your prompt in the `CLIPTextEncode` node
* **Text-to-Image mode:** set the **"Switch to Image Edit"** toggle to **off** (default). The sampler will use your text prompt directly.
* **Image Edit mode:** set **"Switch to Image Edit"** to **on**, then upload a reference image in the `Load Image` node and connect it to `HiDreamO1ReferenceImages`.

> **Note:** The O1 sampler outputs latent samples that need to be decoded through a `VAEDecode` node using the VAE loaded by `CheckpointLoaderSimple`.

## HiDream-O1-Image Dev Workflow

### HiDream O1 Dev

Input a text prompt and optional reference images. Generate a high-resolution image (up to 2048x2048) with support for text-to-image, image editing, and subject-driven personalization.

<img alt="HiDream O1 Dev workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_hidream_o1_dev&utm_source=docs&utm_medium=referral&utm_campaign=hidream-o1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_hidream_o1_dev.json">
    Download JSON or search "HiDream O1 Dev" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="noir_portrait.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/noir_portrait.png">
    `LoadImage` node 213 · `noir_portrait.png`
  </Card>
</CardGroup>

<div>
  <img alt="noir_portrait.png" />
</div>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="HiDream O1 Dev example output" />
</div>

### 1. Download Workflow

### 2. Download Models

**Checkpoint (Dev)**: re-packaged and quantized. All use bf16 for worst outliers, unused deepstack layers removed:

* [hidream\_o1\_image\_dev\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/blob/main/checkpoints/hidream_o1_image_dev_fp8_scaled.safetensors): FP8, uses fp8/mxfp8 matmuls on safe MLP layers for speedup on supported hardware
* [hidream\_o1\_image\_dev\_mxfp8.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/blob/main/checkpoints/hidream_o1_image_dev_mxfp8.safetensors): MXFP8 quantized variant
* [hidream\_o1\_image\_dev\_bf16.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/blob/main/checkpoints/hidream_o1_image_dev_bf16.safetensors): Full bf16 precision (largest)

**Text Encoder** (prompt enhancement): shared across all versions:

* [gemma4\_e4b\_it\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/gemma-4/blob/main/text_encoders/gemma4_e4b_it_fp8_scaled.safetensors)

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   ├── hidream_o1_image_dev_fp8_scaled.safetensors
│   │   ├── hidream_o1_image_dev_mxfp8.safetensors
│   │   └── hidream_o1_image_dev_bf16.safetensors
│   └── 📂 text_encoders/
│       └── gemma4_e4b_it_fp8_scaled.safetensors
```

### 3. Using the Workflow

* Make sure `CheckpointLoaderSimple` loads `hidream_o1_image_dev_fp8_scaled.safetensors`
* The Dev version uses 28 steps with CFG=1.0, no negative prompt needed
* **Text-to-Image mode:** set the **"Switch to Image Edit"** toggle to **off** (default)
* **Image Edit mode:** set **"Switch to Image Edit"** to **on**, upload a reference image in `Load Image`, and connect it to `HiDreamO1ReferenceImages`

## Additional Notes

* **Long Text Rendering:** HiDream-O1-Image excels at rendering text within images. Specify text content, font style, color, and positioning in your prompt for best results.

  ![Long-Text Rendering & Layout Control](https://raw.githubusercontent.com/HiDream-ai/HiDream-O1-Image/main/assets/text-layout.webp)

* **Image Scaling:** If your input reference image is too large, enable the `ImageScaleToTotalPixels` node (Ctrl+B) to scale it to 4MP.

* **Patch Seam Smoothing (Experimental):** The `HiDreamO1PatchSeamSmoothing` node reduces visible seam artifacts during sampling. Enabled by default in the Full workflow.


# Lens ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/image/lens/lens

Run Lens, Microsoft's 3.8B open text-to-image model, in ComfyUI: a dual-stream MMDiT backbone, GPT-OSS-20B text features, and the FLUX.2 semantic VAE.

**Lens** is an open text-to-image model by **Microsoft**, licensed under MIT. With **3.8 billion** parameters, it uses a **dual-stream MMDiT** architecture with **GPT-OSS-20B** text encoder features and the **FLUX.2 semantic VAE** to deliver competitive image quality with substantially less training compute than larger T2I models.

**Model highlights**:

* **Dual-stream MMDiT architecture**: joint image-text processing for coherent generation
* **GPT-OSS-20B multi-layer text features**: rich text understanding for accurate prompt following
* **FLUX.2 semantic VAE**: high-fidelity latent representation
* **Mixed-resolution training**: supports various aspect ratios without cropping
* **Compact 3.8B footprint**: runs on consumer GPUs with 24 GB VRAM

**Related links**:

* [Paper (arXiv)](https://arxiv.org/abs/2605.21573)
* [GitHub](https://github.com/microsoft/Lens)
* [Hugging Face (Microsoft)](https://huggingface.co/microsoft/Lens)
* [Hugging Face (Comfy-Org)](https://huggingface.co/Comfy-Org/Lens)

## Lens text-to-image workflow

Both the standard and Turbo variants use a **Subgraph** node to manage the text-to-image generation pipeline. You can open the subgraph to inspect or customize the internal nodes.

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Lens: Text to Image

Input a text prompt and select resolution and aspect ratio. Generate a high-quality image using the efficient Lens text-to-image model.

<img alt="Lens text-to-image workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_lens_t2i.json">
    Download JSON or search "Lens" in Template Library
  </Card>
</CardGroup>

**Example output**

![Lens text-to-image example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_lens_t2i.png)

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

#### Get started

1. Update ComfyUI to the latest version
2. Go to **Template** and search for **Lens**
3. Select the **Lens** workflow
4. Download any missing models (see [model downloads](#lens-model-downloads)), enter your prompt, and click **Queue**

### Lens Turbo: Text to Image

Input a text prompt and select resolution, aspect ratio, and inference steps. Generate a high-quality image using the Lens text-to-image model.

<img alt="Lens Turbo text-to-image workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_lens_turbo_t2i.json">
    Download JSON or search "Lens Turbo" in Template Library
  </Card>
</CardGroup>

**Example output**

![Lens Turbo text-to-image example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_lens_turbo_t2i.png)

#### Get started

1. Update ComfyUI to the latest version
2. Go to **Template** and search for **Lens Turbo**
3. Select the **Lens Turbo** workflow
4. Download any missing models (see [model downloads](#lens-model-downloads)), enter your prompt, and click **Queue**

## Lens model downloads

You can find all model files at [Comfy-Org/Lens](https://huggingface.co/Comfy-Org/Lens) on Hugging Face.

<CardGroup>
  <Card title="lens_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Lens/blob/main/diffusion_models/lens_bf16.safetensors">
    Diffusion model for Lens (BF16).
  </Card>

  <Card title="lens_turbo_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Lens/blob/main/diffusion_models/lens_turbo_bf16.safetensors">
    Diffusion model for Lens Turbo (BF16).
  </Card>
</CardGroup>

<CardGroup>
  <Card title="gpt_oss_20b_nvfp4.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Lens/blob/main/text_encoders/gpt_oss_20b_nvfp4.safetensors">
    Text encoder (GPT-OSS-20B) shared by both Lens and Lens Turbo.
  </Card>

  <Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Lens/blob/main/vae/flux2-vae.safetensors">
    VAE (FLUX.2) shared by both Lens and Lens Turbo.
  </Card>
</CardGroup>

**Model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── lens_bf16.safetensors (or lens_mxfp8.safetensors)
│   │   └── lens_turbo_bf16.safetensors (or lens_turbo_mxfp8.safetensors)
│   ├── 📂 text_encoders/
│   │   └── gpt_oss_20b_nvfp4.safetensors
│   └── 📂 vae/
│       └── flux2-vae.safetensors
```

## Available models

| Model | Description | Inference steps | Link |
| - | - | - | - |
| Lens | Standard 3.8B model: higher quality, more steps | \~50 | [Hugging Face](https://huggingface.co/microsoft/Lens) |
| Lens Turbo | Distilled variant: faster generation with fewer steps | \~8 | [Hugging Face](https://huggingface.co/microsoft/Lens) |


# ComfyUI NewBie-image-Exp0.1 Workflow Example
Source: https://docs.comfy.org/tutorials/image/newbie-image/newbie-image-exp-0-1

NewBie-image-Exp0.1 is a 3.5B anime-style text-to-image model built on Next-DiT, optimized for detailed anime art with XML structured prompts in ComfyUI.

**NewBie-image-Exp0.1** is a 3.5B parameter DiT model developed by NewBieAI Lab for anime-style text-to-image generation. Built on the Next-DiT architecture, it delivers remarkably detailed and visually striking anime images.

**Key Features**:

* **3.5B Parameter Model**: Efficient yet powerful model size for high-quality anime generation
* **Next-DiT Architecture**: Based on research from the Lumina architecture with a newly designed NewBie architecture
* **Dual Text Encoders**: Uses Gemma3-4B-it as primary encoder with Jina CLIP v2 for improved prompt understanding
* **FLUX VAE**: Utilizes FLUX.1-dev 16-channel VAE for richer colors and finer texture details
* **XML Structured Prompts**: Supports XML format for better attention binding and attribute disentanglement

**Related Links**:

* [GitHub](https://github.com/NewBieAI-Lab/NewBie-image-Exp0.1)
* [Hugging Face](https://huggingface.co/NewBie-AI/NewBie-image-Exp0.1)
* [Getting Started Guide](https://ai.feishu.cn/wiki/NZl9wm7V1iuNzmkRKCUcb1USnsh)

## NewBie-image text-to-image workflow

### NewBie Exp0.1: Anime Generation

Generate detailed anime-style images with NewBie Exp0.1's Next-DiT architecture. Supports XML structured prompts for better multi-character scenes and attribute binding.

<img alt="NewBie-image text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_newbieimage_exp0_1-t2i&utm_source=docs&utm_medium=referral&utm_campaign=newbie-image-exp-0-1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_newbieimage_exp0_1-t2i.json">
    Download JSON or search "NewBie-image" in Template Library
  </Card>
</CardGroup>

**Example output**

![NewBie-image example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_newbieimage_exp0_1-t2i.png)

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model links

**text\_encoders**

* [gemma\_3\_4b\_it\_bf16.safetensors](https://huggingface.co/Comfy-Org/NewBie-image-Exp0.1_repackaged/blob/main/split_files/text_encoders/gemma_3_4b_it_bf16.safetensors)
* [jina\_clip\_v2\_bf16.safetensors](https://huggingface.co/Comfy-Org/NewBie-image-Exp0.1_repackaged/blob/main/split_files/text_encoders/jina_clip_v2_bf16.safetensors)

**diffusion\_models**

* [NewBie-Image-Exp0.1-bf16.safetensors](https://huggingface.co/Comfy-Org/NewBie-image-Exp0.1_repackaged/blob/main/split_files/diffusion_models/NewBie-Image-Exp0.1-bf16.safetensors)

**vae**

* [ae.safetensors](https://huggingface.co/Comfy-Org/z_image_turbo/blob/main/split_files/vae/ae.safetensors)

**Model Storage Location**

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │      ├── gemma_3_4b_it_bf16.safetensors
│   │      └── jina_clip_v2_bf16.safetensors
│   ├── diffusion_models/
│   │      └── NewBie-Image-Exp0.1-bf16.safetensors
│   └── vae/
│          └── ae.safetensors
```

## Prompt format

NewBie-image is an anime image generation model optimized for character generation. It uses XML structured prompts for training, where each `<>` tag defines a category (like `<appearance>`, `<clothing>`) and `</>` closes it. The tags inside are standard Danbooru tags. This structure enables precise control over multi-character scenes with better attribute binding.

For the complete prompt writing guide, see the [official documentation](https://ai.feishu.cn/wiki/NZl9wm7V1iuNzmkRKCUcb1USnsh).

NewBie-image-Exp0.1 supports three prompt formats:

* **Natural language**: Standard text descriptions
* **Tags**: Danbooru-style tags
* **XML structured format**: Recommended for multi-character scenes

### XML structured prompt

For multi-character scenes, using XML structured prompts typically leads to more accurate image generation results with better attention binding and attribute disentanglement.

```xml theme={null}
<character_1>
<n>$character_1$</n>
<gender>1girl</gender>
<appearance>chibi, red_eyes, blue_hair, long_hair, hair_between_eyes, head_tilt, tareme, closed_mouth</appearance>
<clothing>school_uniform, serafuku, white_sailor_collar, white_shirt, short_sleeves, red_neckerchief, bow, blue_skirt, miniskirt, pleated_skirt, blue_hat, mini_hat, thighhighs, grey_thighhighs, black_shoes, mary_janes</clothing>
<expression>happy, smile</expression>
<action>standing, holding, holding_briefcase</action>
<position>center_left</position>
</character_1>

<character_2>
<n>$character_2$</n>
<gender>1girl</gender>
<appearance>chibi, red_eyes, pink_hair, long_hair, very_long_hair, multi-tied_hair, open_mouth</appearance>
<clothing>school_uniform, serafuku, white_sailor_collar, white_shirt, short_sleeves, red_neckerchief, bow, red_skirt, miniskirt, pleated_skirt, hair_bow, multiple_hair_bows, white_bow, ribbon_trim, ribbon-trimmed_bow, white_thighhighs, black_shoes, mary_janes, bow_legwear, bare_arms</clothing>
<expression>happy, smile</expression>
<action>standing, holding, holding_briefcase, waving</action>
<position>center_right</position>
</character_2>

<general_tags>
<count>2girls, multiple_girls</count>
<style>anime_style, digital_art</style>
<background>white_background, simple_background</background>
<atmosphere>cheerful</atmosphere>
<quality>high_resolution, detailed</quality>
<objects>briefcase</objects>
<other>alternate_costume</other>
</general_tags>
```

### XML tag reference

| Tag | Description |
| - | - |
| `<n>` | Character name/identifier |
| `<gender>` | Character gender (1girl, 1boy, etc.) |
| `<appearance>` | Physical features (hair, eyes, body type) |
| `<clothing>` | Outfit and accessories |
| `<expression>` | Facial expression |
| `<action>` | Pose and actions |
| `<position>` | Position in the image |
| `<count>` | Number of characters |
| `<style>` | Art style |
| `<background>` | Background description |
| `<atmosphere>` | Overall mood |
| `<quality>` | Quality tags |
| `<objects>` | Objects in the scene |
| `<other>` | Additional tags |


# Ovis-Image ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/ovis/ovis-image

Ovis-Image is a 7B text-to-image model for high-quality text rendering in ComfyUI, delivering crisp bilingual text on posters, banners, and UI mockups.

**Ovis-Image** is a 7B text-to-image model built upon [Ovis-U1](https://github.com/AIDC-AI/Ovis-U1), specifically optimized for high-quality text rendering. It delivers text rendering quality comparable to much larger 20B-class systems while remaining compact enough to run on widely accessible hardware.

**Model Highlights**:

* **Strong Text Rendering at 7B Scale**: Delivers text rendering quality comparable to much larger 20B-class systems like Qwen-Image and competitive with leading closed-source models like GPT4o in text-centric scenarios
* **High Fidelity on Text-Heavy Prompts**: Excels on prompts that demand tight alignment between linguistic content and rendered typography (e.g., posters, banners, logos, UI mockups, infographics)
* **Accurate Bilingual Text Rendering**: Produces legible, correctly spelled, and semantically consistent text in both Chinese and English across diverse fonts, sizes, and aspect ratios
* **Efficiency and Deployability**: Fits on a single high-end GPU with moderate memory, supports low-latency interactive use

**Related Links**:

* [GitHub](https://github.com/AIDC-AI/Ovis-Image)
* [Hugging Face](https://huggingface.co/AIDC-AI/Ovis-Image-7B)

## Ovis-Image text-to-image workflow

### Ovis-Image Text to Image

Ovis-Image is a 7B text-to-image model specifically optimized for high-quality text rendering in generated images. Designed to operate efficiently under stringent computational constraints.

<img alt="Ovis-Image text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_ovis_text_to_image&utm_source=docs&utm_medium=referral&utm_campaign=ovis-image">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_ovis_text_to_image.json">
    Download JSON or search "Ovis image" in Template Library
  </Card>
</CardGroup>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model links

**text\_encoders**

* [ovis\_2.5.safetensors](https://huggingface.co/Comfy-Org/Ovis-Image/blob/main/split_files/text_encoders/ovis_2.5.safetensors)

**diffusion\_models**

* [ovis\_image\_bf16.safetensors](https://huggingface.co/Comfy-Org/Ovis-Image/blob/main/split_files/diffusion_models/ovis_image_bf16.safetensors)

**vae**

* [ae.safetensors](https://huggingface.co/Comfy-Org/z_image_turbo/blob/main/split_files/vae/ae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── ovis_2.5.safetensors
│   ├── 📂 diffusion_models/
│   │      └── ovis_image_bf16.safetensors
│   └── 📂 vae/
│          └── ae.safetensors
```


# PixelDiT ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/pixeldit/pixeldit

PixelDiT is NVIDIA's pixel-space diffusion transformer for 1024px text-to-image generation. It operates directly in pixel space: no VAE encode/decode required.

**PixelDiT** is NVIDIA's pixel-space diffusion transformer for 1024px text-to-image generation. Unlike traditional diffusion models that operate in latent space, PixelDiT generates images directly in pixel space using a dual-level DiT architecture: a patch-level DiT combined with a pixel-level DiT: with MM-DiT fusion for joint attention between text and image tokens.

**Model Highlights**:

* **VAE-free**: generates directly in pixel space; no traditional VAE encode/decode
* **Dual-level DiT**: patch-level DiT + pixel-level DiT for high-quality generation
* **Multi aspect ratio**: 1024px base resolution with support for several aspect ratios
* **\~1.3B parameters**: efficient enough for consumer GPUs
* **License**: NSCLv1 (non-commercial research/evaluation only)

**Related Links**:

* [Official model on Hugging Face](https://huggingface.co/nvidia/PixelDiT-1300M-1024px)
* [Comfy-Org/PixelDiT](https://huggingface.co/Comfy-Org/PixelDiT)

## PixelDiT text-to-image workflow

<img alt="PixelDiT text-to-image workflow" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_pixeldit_t2i.json">
    Download JSON or search "PixelDiT" in Template Library
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_pixeldit_t2i&utm_source=docs&utm_medium=referral&utm_campaign=pixeldit">
    Open in cloud
  </Card>
</CardGroup>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

The workflow consists of three main nodes:

1. **ResolutionSelector**: choose your desired output resolution
2. **Text to Image (PixelDiT) subgraph**: the core generation node with exposed controls for prompt, seed, model selection and resolution
3. **SaveImage**: saves the generated image

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Workflow controls

The exposed controls on the **Text to Image (PixelDiT)** subgraph node include:

| Control | Description |
| - | - |
| **Positive Prompt** | The text prompt describing the image you want to generate |
| **Negative Prompt** | Text describing what to avoid in the generated image |
| **Seed** | Random seed for reproducibility |
| **UNet Model** | PixelDiT model checkpoint selection |
| **CLIP Model** | Text encoder model selection |

## Model downloads

PixelDiT uses two model files: a text encoder and the diffusion model.

<CardGroup>
  <Card title="Text Encoder" icon="download" href="https://huggingface.co/Comfy-Org/PixelDiT/blob/main/text_encoders/gemma_2_2b_it_elm_bf16.safetensors">
    gemma\_2\_2b\_it\_elm\_bf16.safetensors: Gemma-2-2B-IT text encoder
  </Card>

  <Card title="Diffusion Model" icon="download" href="https://huggingface.co/Comfy-Org/PixelDiT/blob/main/diffusion_models/pixeldit_1300m_1024px_bf16.safetensors">
    pixeldit\_1300m\_1024px\_bf16.safetensors: PixelDiT 1300M 1024px diffusion model
  </Card>
</CardGroup>

### Model storage location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── gemma_2_2b_it_elm_bf16.safetensors
│   └── 📂 diffusion_models/
│          └── pixeldit_1300m_1024px_bf16.safetensors
```


# Qwen-Image ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image

Qwen-Image is a 20B parameter MMDiT (Multimodal Diffusion Transformer) model open-sourced under the Apache 2.0 license.

**Qwen-Image** is the first image generation foundation model released by Alibaba's Qwen team. It's a 20B parameter MMDiT (Multimodal Diffusion Transformer) model open-sourced under the Apache 2.0 license. The model has made significant advances in **complex text rendering** and **precise image editing**, achieving high-fidelity output for multiple languages including English and Chinese.

**Model Highlights**:

* **Excellent Multilingual Text Rendering**: Supports high-precision text generation in multiple languages including English, Chinese, Korean, Japanese, maintaining font details and layout consistency
* **Diverse Artistic Styles**: From photorealistic scenes to impressionist paintings, from anime aesthetics to minimalist design, fluidly adapting to various creative prompts

**Related Links**:

* [GitHub](https://github.com/QwenLM/Qwen-Image)
* [Hugging Face](https://huggingface.co/Qwen/Qwen-Image)
* [ModelScope](https://modelscope.cn/models/qwen/Qwen-Image)

Currently Qwen-Image has multiple ControlNet support options available:

* [Qwen-Image-DiffSynth-ControlNets/model\_patches](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/tree/main/split_files/model_patches): Includes canny, depth, and inpaint models
* [qwen\_image\_union\_diffsynth\_lora.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/blob/main/split_files/loras/qwen_image_union_diffsynth_lora.safetensors): Image structure control LoRA supporting canny, depth, pose, lineart, softedge, normal, openpose
* InstantX ControlNet: To be updated

## ComfyOrg Qwen-Image live stream

**Qwen-Image in ComfyUI - Lightning & LoRAs**

<iframe title="Qwen-Image in ComfyUI - Lightning & LoRAs / August 15th, 2025" />

**Qwen-Image ControlNet in ComfyUI - DiffSynth**

<iframe title="Qwen-Image ControlNet in ComfyUI - DiffSynth / August 26th, 2025" />

## Qwen-Image Native Workflow Example

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Qwen-Image: Text to Image

Generate images with exceptional multilingual text rendering and editing capabilities using Qwen-Image's 20B MMDiT model.

<img alt="Qwen-Image text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_image&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image.json">
    Download JSON or search "Qwen-Image" in Template Library
  </Card>
</CardGroup>

**Example output**

![Qwen-Image example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_qwen_image.png)

There are three different models used in the workflow attached to this document:

1. Qwen-Image original model fp8\_e4m3fn
2. 8-step accelerated version: Qwen-Image original model fp8\_e4m3fn with lightx2v 8-step LoRA
3. Distilled version: Qwen-Image distilled model fp8\_e4m3fn

**VRAM Usage Reference**
GPU: RTX4090D 24GB

| Model Used | VRAM Usage | First Generation | Second Generation |
| - | - | - | - |
| fp8\_e4m3fn | 86% | ≈ 94s | ≈ 71s |
| fp8\_e4m3fn with lightx2v 8-step LoRA | 86% | ≈ 55s | ≈ 34s |
| Distilled fp8\_e4m3fn | 86% | ≈ 69s | ≈ 36s |

### 1. Workflow File

After updating ComfyUI, you can find the workflow file in the templates, or drag the workflow below into ComfyUI to load it.
![Qwen-image Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/image/qwen/qwen-image.png)

Distilled version

<Card title="Download Workflow for Distilled Model" icon="download" href="https://github.com/Comfy-Org/example_workflows/blob/main/image/qwen/image_qwen_image_distill.json">
  Download JSON workflow
</Card>

### 2. Model Download

**Available Models in ComfyUI**

* Qwen-Image\_bf16 (40.9 GB)
* Qwen-Image\_fp8 (20.4 GB)
* Distilled versions (non-official, requires only 15 steps)

All models are available at [Huggingface](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main) and [Modelscope](https://modelscope.cn/models/Comfy-Org/Qwen-Image_ComfyUI/files)

**Diffusion model**

* [qwen\_image\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/diffusion_models/qwen_image_fp8_e4m3fn.safetensors)

Qwen\_image\_distill

* [qwen\_image\_distill\_full\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/non_official/diffusion_models/qwen_image_distill_full_fp8_e4m3fn.safetensors)
* [qwen\_image\_distill\_full\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/non_official/diffusion_models/qwen_image_distill_full_bf16.safetensors)

<Note>
  - The original author of the distilled version recommends using 15 steps with cfg 1.0.
  - According to tests, this distilled version also performs well at 10 steps with cfg 1.0. You can choose either euler or res\_multistep based on the type of image you want.
</Note>

**LoRA**

* [Qwen-Image-Lightning-8steps-V1.0.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-8steps-V1.0.safetensors)

**Text encoder**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)

**VAE**

[qwen\_image\_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/vae/qwen_image_vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── qwen_image_fp8_e4m3fn.safetensors
│   │   └── qwen_image_distill_full_fp8_e4m3fn.safetensors ## 蒸馏版
│   ├── 📂 loras/
│   │   └── Qwen-Image-Lightning-8steps-V1.0.safetensors   ## 8步加速 LoRA 模型
│   ├── 📂 vae/
│   │   └── qwen_image_vae.safetensors
│   └── 📂 text_encoders/
│       └── qwen_2.5_vl_7b_fp8_scaled.safetensors
```

### 3. Workflow Instructions

<img alt="Step Guide" />

1. Make sure the `Load Diffusion Model` node has loaded `qwen_image_fp8_e4m3fn.safetensors`
2. Make sure the `Load CLIP` node has loaded `qwen_2.5_vl_7b_fp8_scaled.safetensors`
3. Make sure the `Load VAE` node has loaded `qwen_image_vae.safetensors`
4. Make sure the `EmptySD3LatentImage` node is set with the correct image dimensions
5. Set your prompt in the `CLIP Text Encoder` node; currently, it supports at least English, Chinese, Korean, Japanese, Italian, etc.
6. If you want to enable the 8-step acceleration LoRA by lightx2v, select the node and use `Ctrl + B` to enable it, and modify the Ksampler settings as described in step 8
7. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow
8. For different model versions and workflows, adjust the KSampler parameters accordingly

<Note>
  The distilled model and the 8-step acceleration LoRA by lightx2v do not seem to be compatible for simultaneous use. You can experiment with different combinations to verify if they can be used together.
</Note>

## Qwen Image InstantX ControlNet Workflow

This is a ControlNet model, so you can use it as normal ControlNet.

### Qwen-Image InstantX Union ControlNet

Generate images with Qwen-Image InstantX ControlNet, supporting canny, soft edge, depth, and pose.

<img alt="Qwen-Image InstantX ControlNet workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_image_instantx_controlnet&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_instantx_controlnet.json">
    Download JSON or search "Qwen-Image InstantX ControlNet" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="image_qwen_image_instantx_controlnet_input_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/image_qwen_image_instantx_controlnet_input_image.jpg">
    `LoadImage` node 71 · `image_qwen_image_instantx_controlnet_input_image.jpg`
  </Card>
</CardGroup>

<div>
  <img alt="image_qwen_image_instantx_controlnet_input_image.jpg" />
</div>

## 1. Workflow and Input Images

### 2. Model Links

1. InstantX Controlnet

Download [Qwen-Image-InstantX-ControlNet-Union.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-InstantX-ControlNets/blob/main/split_files/controlnet/Qwen-Image-InstantX-ControlNet-Union.safetensors) and save it to the `ComfyUI/models/controlnet/` folder

2. **Lotus Depth model**

We will use this model to generate the depth map of the image. The following two models need to be downloaded:

**Diffusion Model**

* [lotus-depth-d-v1-1.safetensors](https://huggingface.co/Comfy-Org/lotus/blob/main/lotus-depth-d-v1-1.safetensors)

**VAE Model**

* [vae-ft-mse-840000-ema-pruned.safetensors](https://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.safetensors)  or any SD1.5 VAE

```
ComfyUI/
├── models/
│   ├── diffusion_models/
│   │   └─── lotus-depth-d-v1-1.safetensors
│   └── vae/
│       └──  lvae-ft-mse-840000-ema-pruned.safetensors
```

> You can also use custom nodes like [comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) to generate depth map.

### 3. Workflow Instructions

<img alt="Process Instructions" />

1. Ensure that the `Load ControlNet Model` node correctly loads the `Qwen-Image-InstantX-ControlNet-Union.safetensors` model
2. Upload input image
3. This subgraph uses the Lotus Depth model. You can find it in the templates or edit the subgraph to learn more, make sure all the models are loaded correctly
4. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Qwen Image ControlNet DiffSynth-ControlNets Model Patches Workflow

### Qwen-Image ControlNet Model Patch

Control image generation using Qwen-Image ControlNet models. Supports canny, depth, and inpainting controls through model patching.

<img alt="Qwen-Image ControlNet model patch workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_image_controlnet_patch&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_controlnet_patch.json">
    Download JSON or search "Qwen-Image ControlNet Patch" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="image_qwen_image_controlnet_patch_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/image_qwen_image_controlnet_patch_input_image.png">
    `LoadImage` node 71 · `image_qwen_image_controlnet_patch_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="image_qwen_image_controlnet_patch_input_image.png" />
</div>

### 1. Workflow and Input Images

After updating ComfyUI, you can find the workflow file from the templates, or drag the workflow preview above into ComfyUI to load it.

### 2. Model Links

Other models are the same as the Qwen-Image basic workflow. You only need to download the models below and save them to the `ComfyUI/models/model_patches` folder

* [qwen\_image\_canny\_diffsynth\_controlnet.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/blob/main/split_files/model_patches/qwen_image_canny_diffsynth_controlnet.safetensors)
* [qwen\_image\_depth\_diffsynth\_controlnet.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/blob/main/split_files/model_patches/qwen_image_depth_diffsynth_controlnet.safetensors)
* [qwen\_image\_inpaint\_diffsynth\_controlnet.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/blob/main/split_files/model_patches/qwen_image_inpaint_diffsynth_controlnet.safetensors)

### 3. Workflow Usage Instructions

Currently, diffsynth has three patch models: Canny, Depth, and Inpaint.

If you're using ControlNet-related workflows for the first time, you need to understand that control images need to be preprocessed into supported image formats before they can be used and recognized by the model.

<img alt="Input Type Diagram" />

* Canny: Processed canny edge, line art contours
* Depth: Preprocessed depth map showing spatial relationships
* Inpaint: Requires using Mask to mark areas that need to be repainted

Since this patch model is divided into three different models, you need to select the correct preprocessing type when inputting to ensure proper image preprocessing.

**Canny Model ControlNet Usage Instructions**

<img alt="Canny Workflow" />

1. Ensure that `qwen_image_canny_diffsynth_controlnet.safetensors` is loaded
2. Upload input image for subsequent processing
3. The Canny node is a native preprocessing node that will preprocess the input image according to your set parameters to control generation
4. If needed, you can modify the `strength` in the `QwenImageDiffsynthControlnet` node to control the intensity of line art control
5. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

> For using qwen\_image\_depth\_diffsynth\_controlnet.safetensors, you need to preprocess the image into a depth map and replace the `image processing` part. For this usage, please refer to the InstantX processing method in this document. Other parts are similar to using the Canny model.

**Inpaint Model ControlNet Usage Instructions**

<img alt="Inpaint Workflow" />

For the Inpaint model, it requires using the [Mask Editor](/interface/maskeditor) to draw a mask and use it as input control condition.

1. Ensure that `ModelPatchLoader` loads the `qwen_image_inpaint_diffsynth_controlnet.safetensors` model
2. Upload image and use the [Mask Editor](/interface/maskeditor) to draw a mask. You need to connect the `mask` output of the corresponding `Load Image` node to the `mask` input of `QwenImageDiffsynthControlnet` to ensure the corresponding mask is loaded
3. Use the `Ctrl-B` shortcut to set the original Canny in the workflow to bypass mode, making the corresponding Canny node processing ineffective
4. In `CLIP Text Encoder`, input what you want to change the masked area to
5. If needed, you can modify the `strength` in the `QwenImageDiffsynthControlnet` node to control the corresponding control intensity
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Qwen Image Union ControlNet LoRA Workflow

### Qwen-Image Union Control

Generate images with precise structural control using Qwen-Image's unified ControlNet LoRA. Supports multiple control types including canny, depth, lineart, softedge, normal, and openpose.

<img alt="Qwen-Image Union Control workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_image_union_control_lora&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_union_control_lora.json">
    Download JSON or search "Qwen-Image Union Control" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="image_qwen_image_union_control_lora_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/image_qwen_image_union_control_lora_input_image.png">
    `LoadImage` node 73 · `image_qwen_image_union_control_lora_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="image_qwen_image_union_control_lora_input_image.png" />
</div>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="Qwen-Image Union Control example output" />
</div>

Original model address: [DiffSynth-Studio/Qwen-Image-In-Context-Control-Union](https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-In-Context-Control-Union/)
Comfy Org rehost address: [qwen\_image\_union\_diffsynth\_lora.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/blob/main/split_files/loras/qwen_image_union_diffsynth_lora.safetensors): Image structure control LoRA supporting canny, depth, pose, lineart, softedge, normal, openpose

### 1. Workflow and Input Images

After updating ComfyUI, you can find the workflow file from the templates, or drag the workflow preview above into ComfyUI to load it.

### 2. Model Links

Download the model below. Since this is a LoRA model, it needs to be saved to the `ComfyUI/models/loras/` folder

* [qwen\_image\_union\_diffsynth\_lora.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/blob/main/split_files/loras/qwen_image_union_diffsynth_lora.safetensors): Image structure control LoRA supporting canny, depth, pose, lineart, softedge, normal, openpose

### 3. Workflow Instructions

This model is a unified control LoRA that supports canny, depth, pose, lineart, softedge, normal, openpose controls. Since many image preprocessing native nodes are not fully supported, you should use something like [comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) to complete other image preprocessing.

<img alt="Union Control LoRA" />

1. Ensure that `LoraLoaderModelOnly` correctly loads the `qwen_image_union_diffsynth_lora.safetensors` model
2. Upload input image
3. If needed, you can adjust the `Canny` node parameters. Since different input images require different parameter settings to get better image preprocessing results, you can try adjusting the corresponding parameter values to get more/fewer details
4. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

> For other types of control, you also need to replace the image processing part.


# Qwen-Image-2.1 ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image-2-1

Run Qwen-Image-2.1 in ComfyUI: one model for image generation and editing, native 2K output, professional typography, and alpha channel support.

**Qwen-Image-2.1** is the latest open-weight release in the Qwen-Image series from Alibaba's Qwen team. A single model covers both text-to-image generation and instruction-based image editing, with native 2K output, professional typography, and an alpha channel for transparent backgrounds.

**Key Features**:

* **Generation and editing in one model**: the same weights serve text-to-image prompts and editing instructions, so a workflow does not need to swap checkpoints
* **Native 2K output**: generate at up to 2048x2048 directly instead of upscaling a smaller result
* **Professional typography**: dense small text and complex layouts hold up, for infographics, slides, UI mockups, posters, and packaging designs
* **Alpha channel support**: the VAE carries four channels, so transparent-background images can be generated and edited directly instead of being cut out afterwards
* **Multi-image editing**: reference images are spliced into the text encoder in slot order. The Text Encode Qwen Image 2.1 node accepts up to 16 slots (`image_1` to `image_16`); the two edit templates on this page wire the first 10 (`image_1` to `image_10`). `image_1` is the image being edited and the rest supply content, so the prompt addresses them by index, for example `image_1` is written as `<image1>`
* **Localized edits**: describe the object or region to change and the rest of the image is preserved

**Related Links**:

* [GitHub Repository](https://github.com/QwenLM/Qwen-Image)
* [Hugging Face (Comfy-Org/Qwen-Image-2.1)](https://huggingface.co/Comfy-Org/Qwen-Image-2.1)
* [Qwen Image 2.1 on Comfy](https://comfy.org/qwen-image-2.1/)

## Qwen-Image-2.1 workflow

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Qwen Image 2.1 Text to Image

Generate an image from a text prompt at the aspect ratio and megapixel target you select.

<img alt="Qwen-Image-2.1 text to image workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_2_1_t2i.json">
    Download JSON or search "Qwen-Image-2.1" in Template Library
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_image_2_1_t2i&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image-2-1">
    Run ComfyUI online with zero setup
  </Card>
</CardGroup>

**Example output**

![Qwen-Image-2.1 text to image example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_qwen_image_2_1_t2i.png)

### Qwen Image 2.1 Image Edit

Edit an image with an instruction. Add reference images when the edit needs content that is not in the source image, such as putting a garment from a second photo onto the person in the first.

<img alt="Qwen-Image-2.1 image edit workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_2_1_image_edit.json">
    Download JSON or search "Qwen-Image-2.1" in Template Library
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_image_2_1_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image-2-1">
    Run ComfyUI online with zero setup
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="portrait_model_denim.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/portrait_model_denim.png">
    `LoadImage` node 470 · `portrait_model_denim.png`
  </Card>

  <Card title="clothing_light_blue_denim_shirt.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/clothing_light_blue_denim_shirt.png">
    `LoadImage` node 475 · `clothing_light_blue_denim_shirt.png`
  </Card>
</CardGroup>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="Qwen-Image-2.1 image edit example output" />
</div>

### Remove Background: Qwen Image 2.1

Remove the background from a photo with an edit instruction. The workflow reuses the image edit subgraph with the prompt `Remove the background, and output a PNG image`, then compares the result with the original.

<img alt="Qwen-Image-2.1 background removal workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_2_1_background_removal.json">
    Download JSON or search "Qwen-Image-2.1" in Template Library
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_image_2_1_background_removal&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image-2-1">
    Run ComfyUI online with zero setup
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<Card title="angry_broccoli.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/angry_broccoli.png">
  `LoadImage` node 470 · `angry_broccoli.png`
</Card>

## Model links

The three workflows share the same diffusion model, VAE, and base text encoder. The text-to-image and image-edit templates each add a separate prompt-enhancement text encoder: `qwen3.5_9b_qwen_image_2.1_pe_t2i` for text to image and `qwen3.5_9b_qwen_image_2.1_pe_i2i` for image edit.

**text\_encoders**

* [qwen3vl\_8b\_int8\_convrot.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/blob/main/text_encoders/qwen3vl_8b_int8_convrot.safetensors) (loaded by the templates, lower memory)
* [qwen3vl\_8b\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/blob/main/text_encoders/qwen3vl_8b_bf16.safetensors) (full precision, needs more memory)
* [qwen3.5\_9b\_qwen\_image\_2.1\_pe\_t2i.int8\_convrot.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/blob/main/text_encoders/qwen3.5_9b_qwen_image_2.1_pe_t2i.int8_convrot.safetensors) (prompt enhancement in the text to image template)
* [qwen3.5\_9b\_qwen\_image\_2.1\_pe\_i2i.int8\_convrot.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/blob/main/text_encoders/qwen3.5_9b_qwen_image_2.1_pe_i2i.int8_convrot.safetensors) (prompt enhancement in the image edit template)

**diffusion\_models**

* [qwen\_image\_2.1\_int8\_convrot.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/blob/main/diffusion_models/qwen_image_2.1_int8_convrot.safetensors) (loaded by the templates, lower memory)
* [qwen\_image\_2.1\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/blob/main/diffusion_models/qwen_image_2.1_bf16.safetensors) (full precision, needs more memory)

**vae**

* [qwen\_image\_2.1\_vae\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/blob/main/vae/qwen_image_2.1_vae_bf16.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      ├── qwen3vl_8b_int8_convrot.safetensors
│   │      ├── qwen3vl_8b_bf16.safetensors
│   │      ├── qwen3.5_9b_qwen_image_2.1_pe_t2i.int8_convrot.safetensors
│   │      └── qwen3.5_9b_qwen_image_2.1_pe_i2i.int8_convrot.safetensors
│   ├── 📂 diffusion_models/
│   │      ├── qwen_image_2.1_int8_convrot.safetensors
│   │      └── qwen_image_2.1_bf16.safetensors
│   └── 📂 vae/
│          └── qwen_image_2.1_vae_bf16.safetensors
```

## Workflow settings

### Sampler settings

All three workflows sample with `steps` 25, `cfg` 1, the `euler` sampler, and the `simple` scheduler.

At `cfg` 1 ComfyUI skips the negative conditioning pass, so a negative prompt has no effect on these workflows. The template keeps `cfg` 1, which is the path Qwen-Image-2.1 is published for; raise it only when you want the negative prompt to take effect. `cfg` 2 follows dense prompts more closely, including small text and numbers, at the cost of over-sharpened edges. Higher values shift exposure toward over-bright or over-dim, `cfg` 5 degrades quality badly, and `cfg` 0.5 breaks the image. Change one value at a time, and compare at a fixed seed.

`steps` is the second lever. The published pipeline for Qwen-Image-2.1 uses about 40 to 50 steps with the `euler` sampler, and the template starts lower at 25. Simple localized edits hold up at 4 to 8 steps, so a request such as changing one garment's color runs several times faster than at the default, while edits that rewrite the whole frame lose coherence and need the full 25. Stubborn fine detail such as hands and fingers settles by about 30 steps, and going from 25 to 40 steps reduces fizzle in detailed areas. Adjust `steps` only when something specific fails to resolve.

### Resolution

**Text to image**: the **Resolution Selector** node sets the aspect ratio and a megapixel target, where 1.0 MP is about 1024x1024. Qwen-Image-2.1 generates natively at 2K, so set the target to about 4.0 MP for a 2048x2048 square output.

**Image edit**: the canvas comes from the `resolution` control on the Image Edit subgraph node (range `0` to `4096`, step `32`). The node's own default is `1024`, and the template ships `0`. With `custom_size` off, which is the template default, the edit is generated at the size of the first reference image, `image_1`:

* `resolution` `0` keeps each reference at its own pixel size, rounded to a multiple of 32, so a 3000x4000 photo gives a 3008x4000 canvas
* `resolution` above `0` scales `image_1`'s aspect ratio to a `resolution` x `resolution` pixel budget, which is a total pixel count rather than a width or height, rounded to multiples of 32, so `resolution` `1024` on the same photo gives about 896x1184

Turn on `custom_size` to take the canvas from the **Resolution Selector** instead, and keep it close to the resized `image_1` size, otherwise the edit can shift.

The canvas size is what drives the cost: a 3000x4000 reference with `resolution` 0 samples at 3008x4000 (about 12 MP), while the same edit at `resolution` 1024 samples at about 896x1184 (about 1 MP). On an RTX 5090 that is roughly 6 s/it against about 0.3 s/it. Lowering `resolution` speeds an edit up by generating a smaller result, not by adding detail. If an edit feels slow, check `resolution` and the pixel size of the reference images before changing anything else. Several large references slow the edit further, and the KV cache settings below affect that cost. Targets well above the model's 2K trained size, such as 4K, lose prompt adherence.

### Prompting for image edit

Reference images are spliced into the text encoder in slot order, and the prompt addresses each one by index:

```
Keep the character and pose in <image1> unchanged, put this light blue denim shirt from <image2> on the character, preserve the original facial features, hair, body shape and pose
```

To point an edit at one region, mark that region on the image first. Open the Mask Editor on the `LoadImage` node that supplies `image_1` (node 470: right-click the node, then **Open in Mask Editor**), paint over the region with the **Paint Pen**, and save. Paint Pen strokes go on the image's RGB layer rather than into the mask, so saving writes the marked image back into the node and the marks become part of the reference the edit reads. Naming the mark's color in the prompt points the instruction at that region, for example "change the jacket in the red area". Keep the mark inside the region you want changed, and state the color you want in the prompt as well when the mark's color appears in the output.

### KV cache

The edit workflows include the **Qwen Image 2.1 Cache** node, which keeps the cached text and reference prefix in memory between sampling steps. The template defaults work for most setups.

The node is experimental, and it exposes two controls:

| Control | Values | Effect |
| - | - | - |
| `device` | `auto` (default), `gpu`, `cpu`, `off` | `auto` uses spare VRAM, then RAM. `cpu` (RAM) is prefetched behind compute and costs little speed. `off` recomputes the prefix every step, which is slower but rules the cache out when debugging |
| `dtype` | `default` (default), `int8`, `int4` | Storage precision. `default` is lossless. `int8` halves the cache at about bf16 accuracy, and `int4` quarters it but roughly doubles the per-step error |

### Prompt enhancement

The text to image and image edit templates include an optional prompt enhancement step. A dedicated text encoder rewrites the prompt before sampling, turning a short request into a longer, more detailed one.

Both templates expose the controls on the Qwen Image 2.1 subgraph node:

* `refine_prompt`: off by default in both templates. Turn it on to have the image model sample with the rewritten prompt instead of the prompt you typed
* `PE_model`: the text encoder that performs the rewrite, `qwen3.5_9b_qwen_image_2.1_pe_t2i.int8_convrot.safetensors` for text to image and `qwen3.5_9b_qwen_image_2.1_pe_i2i.int8_convrot.safetensors` for image edit
* `thinking_mode`: off by default in both templates. Turn it on together with `refine_prompt` to let the rewriting model reason before it writes

A `Preview Any` node inside the subgraph shows the prompt that actually reaches the image model, so you can read the rewrite before deciding whether to keep it. The instruction the rewriting model follows lives in a `Text (System Prompt)` node that you can edit. Because the enhancement branch is only evaluated when `refine_prompt` is on, the enhancement text encoder is optional in both templates; turn `refine_prompt` on to use it. The background removal template does not include this step.


# Qwen-Image-2512 ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image-2512

Generate images with Qwen-Image-2512 in ComfyUI, the December update of Qwen-Image with enhanced human realism, finer natural detail, and better text rendering.

**Qwen-Image-2512** is the December update of Qwen-Image's text-to-image foundational model. Compared to the base Qwen-Image model released in August, Qwen-Image-2512 features significant improvements in image quality and realism.

**Key Enhancements in Qwen-Image-2512**:

* **Enhanced Human Realism**: Significantly reduces the "AI-generated" look and substantially enhances overall image realism, especially for human subjects
* **Finer Natural Detail**: Delivers notably more detailed rendering of landscapes, animal fur, and other natural elements
* **Improved Text Rendering**: Improves the accuracy and quality of textual elements, achieving better layout and more faithful multimodal (text + image) composition

**Official Links**:

* [GitHub Repository](https://github.com/QwenLM/Qwen-Image)
* [Hugging Face](https://huggingface.co/Qwen/Qwen-Image-2512)
* [ModelScope](https://modelscope.cn/models/Qwen/Qwen-Image-2512)
* [Tech Report](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/Qwen_Image.pdf)
* [Blog](https://qwen.ai/blog?id=qwen-image-2512)

## Supported Aspect Ratios

| Aspect Ratio | Resolution |
| - | - |
| 1:1 | 1328x1328 |
| 16:9 | 1664x928 |
| 9:16 | 928x1664 |
| 4:3 | 1472x1104 |
| 3:4 | 1104x1472 |
| 3:2 | 1584x1056 |
| 2:3 | 1056x1584 |

## Qwen-Image-2512 ComfyUI Native Workflow Example

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Qwen Image 2512

Text-to-image model with enhanced human realism, finer natural details, and improved text rendering.

<img alt="Qwen-Image-2512 workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_Image_2512&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image-2512">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_Image_2512.json">
    Download JSON or search "Qwen-Image-2512" in Template Library
  </Card>
</CardGroup>

**Example output**

![Qwen-Image-2512 example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_qwen_Image_2512.png)

### 1. Workflow file

After updating ComfyUI, you can find the workflow file from the templates, or drag the workflow preview above into ComfyUI to load it.

The workflow includes two subgraphs:

* **Text to Image (Qwen-Image 2512)**: Standard 50-step generation
* **Text to Image (Qwen-Image 2512 4steps)**: Accelerated 4-step generation using Lightning LoRA

### 2. Model download

**Text Encoders**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)

**LoRA (Optional - for 4-step Lightning acceleration)**

* [Qwen-Image-Lightning-4steps-V1.0.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-4steps-V1.0.safetensors)

**Diffusion Models**

* [qwen\_image\_2512\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/diffusion_models/qwen_image_2512_fp8_e4m3fn.safetensors) (Recommended for most users)
* [qwen\_image\_2512\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/diffusion_models/qwen_image_2512_bf16.safetensors) (If you have enough VRAM and want better quality)

**VAE**

* [qwen\_image\_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/vae/qwen_image_vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   ├── 📂 loras/
│   │      └── Qwen-Image-Lightning-4steps-V1.0.safetensors
│   ├── 📂 diffusion_models/
│   │      ├── qwen_image_2512_bf16.safetensors
│   │      └── qwen_image_2512_fp8_e4m3fn.safetensors
│   └── 📂 vae/
│          └── qwen_image_vae.safetensors
```


# Qwen-Image-Edit ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image-edit

Qwen-Image-Edit is the image editing version of Qwen-Image, further trained based on the 20B model, supporting precise text editing and dual semantic/appearance editing capabilities.

**Qwen-Image-Edit** is the image editing version of Qwen-Image. It is further trained based on the 20B Qwen-Image model, successfully extending Qwen-Image's unique text rendering capabilities to editing tasks, enabling precise text editing. In addition, Qwen-Image-Edit feeds the input image into both Qwen2.5-VL (for visual semantic control) and the VAE Encoder (for visual appearance control), thus achieving dual semantic and appearance editing capabilities.

**Model Features**

Features include:

* Precise Text Editing: Qwen-Image-Edit supports bilingual (Chinese and English) text editing, allowing direct addition, deletion, and modification of text in images while preserving the original text size, font, and style.
* Dual Semantic/Appearance Editing: Qwen-Image-Edit supports not only low-level visual appearance editing (such as style transfer, addition, deletion, modification, etc.) but also high-level visual semantic editing (such as IP creation, object rotation, etc.).
* Strong Cross-Benchmark Performance: Evaluations on multiple public benchmarks show that Qwen-Image-Edit achieves SOTA in editing tasks, making it a powerful foundational model for image generation.

**Official Links**:

* [GitHub Repository](https://github.com/QwenLM/Qwen-Image)
* [Hugging Face](https://huggingface.co/Qwen/Qwen-Image-Edit)
* [ModelScope](https://modelscope.cn/models/qwen/Qwen-Image-Edit)

## ComfyOrg Qwen-Image-Edit Live Stream

<iframe title="Qwen-Image Edit in ComfyUI - Image Editing Model / August 19th, 2025" />

## Qwen-Image-Edit ComfyUI Native Workflow Example

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Qwen Image Edit

Edit images with precise bilingual text editing and dual semantic/appearance editing capabilities using Qwen-Image-Edit's 20B MMDiT model.

<img alt="Qwen-Image-Edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image-edit">
    Run this workflow on Cloud GPUs with zero setup
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_edit.json">
    Download JSON or search "Qwen Image Edit" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="image_qwen_image_edit_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/image_qwen_image_edit_input_image.png">
    `LoadImage` node 78 · `image_qwen_image_edit_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="image_qwen_image_edit_input_image.png" />
</div>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="Qwen-Image-Edit example output" />
</div>

### 1. Workflow File

### 2. Model Download

All models can be found at [Comfy-Org/Qwen-Image\_ComfyUI](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main) or [Comfy-Org/Qwen-Image-Edit\_ComfyUI](https://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI)

**Diffusion model**

* [qwen\_image\_edit\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI/blob/main/split_files/diffusion_models/qwen_image_edit_fp8_e4m3fn.safetensors)

**LoRA**

* [Qwen-Image-Lightning-4steps-V1.0.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-4steps-V1.0.safetensors)

**Text encoder**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)

**VAE**

* [qwen\_image\_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/vae/qwen_image_vae.safetensors)

Model Storage Location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── qwen_image_edit_fp8_e4m3fn.safetensors
│   ├── 📂 loras/
│   │   └── Qwen-Image-Lightning-4steps-V1.0.safetensors
│   ├── 📂 vae/
│   │   └── qwen_image_vae.safetensors
│   └── 📂 text_encoders/
│       └── qwen_2.5_vl_7b_fp8_scaled.safetensors
```

### 3. Follow the Steps to Complete the Workflow

<img alt="Steps Diagram" />

1. Model Loading
   * Ensure the `Load Diffusion Model` node loads `qwen_image_edit_fp8_e4m3fn.safetensors`
   * Ensure the `Load CLIP` node loads `qwen_2.5_vl_7b_fp8_scaled.safetensors`
   * Ensure the `Load VAE` node loads `qwen_image_vae.safetensors`
2. Image Loading
   * Ensure the `Load Image` node uploads the image to be edited
3. Prompt Setting
   * Set the prompt in the `CLIP Text Encoder` node
4. The Scale Image to Total Pixels node will scale your input image to a total of one million pixels,
   * Mainly to avoid quality loss in output images caused by oversized input images such as 2048x2048
   * If you are familiar with your input image size, you can bypass this node using `Ctrl+B`
5. If you want to use the 4-step Lighting LoRA to speed up image generation, you can select the `LoraLoaderModelOnly` node and press `Ctrl+B` to enable it
6. For the `steps` and `cfg` settings of the Ksampler node, we've added a note below the node where you can test the optimal parameter settings
7. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow


# Qwen-Image-Edit-2511 ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image-edit-2511

Edit images with Qwen-Image-Edit-2511 in ComfyUI, with improved character consistency, multi-person editing, LoRA support, and stronger geometric reasoning.

**Qwen-Image-Edit-2511** is an enhanced version of Qwen-Image-Edit-2509, featuring multiple improvements including notably better consistency. This model extends Qwen-Image's unique text rendering capabilities to editing tasks, enabling precise text editing with dual semantic and appearance editing capabilities.

**Key Enhancements in Qwen-Image-Edit-2511**:

* **Mitigate Image Drift**: Improved stability during editing operations
* **Improved Character Consistency**: Better preservation of identity and visual characteristics during imaginative edits
* **Multi-Person Consistency**: High-fidelity fusion of multiple person images into coherent group shots
* **Integrated LoRA Capabilities**: Popular community LoRAs built directly into the base model
* **Enhanced Industrial Design Generation**: Better support for batch industrial product design and material replacement
* **Strengthened Geometric Reasoning**: Direct generation of auxiliary construction lines for design or annotation

**Official Links**:

* [GitHub Repository](https://github.com/QwenLM/Qwen-Image)
* [Hugging Face](https://huggingface.co/Qwen/Qwen-Image-Edit-2511)
* [ModelScope](https://modelscope.cn/models/Qwen/Qwen-Image-Edit-2511)
* [Tech Report](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/Qwen_Image.pdf)
* [Blog](https://qwen.ai/blog?id=qwen-image-edit-2511)

## Qwen-Image-Edit-2511 ComfyUI Native Workflow Example

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Qwen Image Edit 2511 - Material Replacement

Replace materials in objects (for example, furniture) by combining reference images with Qwen-Image-Edit-2511.

<img alt="Qwen-Image-Edit-2511 workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_image_edit_2511&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image-edit-2511">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_edit_2511.json">
    Download JSON or search "Qwen-Image-Edit-2511" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="leather_sofa.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/leather_sofa.png">
    `LoadImage` node 41 · `leather_sofa.png`
  </Card>

  <Card title="texture_fur.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/texture_fur.png">
    `LoadImage` node 83 · `texture_fur.png`
  </Card>
</CardGroup>

<div>
  <img alt="leather_sofa.png" />

  <img alt="texture_fur.png" />
</div>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="Qwen-Image-Edit-2511 example output" />
</div>

### 1. Workflow file

After updating ComfyUI, you can find the workflow file from the templates, or drag the workflow preview above into ComfyUI to load it.

### 2. Model download

**Text Encoders**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/blob/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)

**LoRA (Optional - for 4-step Lightning acceleration)**

* [Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Edit-2511-Lightning/blob/main/Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors)

**Diffusion Models**

* [qwen\_image\_edit\_2511\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI/blob/main/split_files/diffusion_models/qwen_image_edit_2511_bf16.safetensors)

**VAE**

* [qwen\_image\_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/vae/qwen_image_vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   ├── 📂 loras/
│   │      └── Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors
│   ├── 📂 diffusion_models/
│   │      └── qwen_image_edit_2511_bf16.safetensors
│   └── 📂 vae/
│          └── qwen_image_vae.safetensors
```


# Qwen-Image-Layered ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image-layered

Qwen-Image-Layered is a model capable of decomposing an image into multiple RGBA layers, enabling inherent editability through layer decomposition.

**Qwen-Image-Layered** is a model developed by Alibaba's Qwen team that can decompose an image into multiple RGBA layers. This layered representation unlocks inherent editability: each layer can be independently manipulated without affecting other content.

**Key Features**:

* **Inherent Editability**: Each layer can be independently manipulated without affecting other content
* **High-Fidelity Elementary Operations**: Supports resizing, repositioning, and recoloring with physical isolation of semantic components
* **Variable-Layer Decomposition**: Not limited to a fixed number of layers - decompose into 3, 4, 8, or more layers as needed
* **Recursive Decomposition**: Any layer can be further decomposed, enabling infinite decomposition depth

**Related Links**:

* [Hugging Face](https://huggingface.co/Qwen/Qwen-Image-Layered)
* [Research Paper](https://arxiv.org/abs/2512.15603)
* [Blog](https://qwen.ai/blog?id=qwen-image-layered)

## Qwen-Image-Layered workflow

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Qwen-Image-Layered Decomposition

Decompose an image into editable RGBA layers for recolor, replace, resize, and reposition workflows.

<img alt="Qwen-Image-Layered workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_layered.json">
    Download the JSON workflow file
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_qwen_image_layered&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image-layered">
    Run ComfyUI online with zero setup
  </Card>
</CardGroup>

**Input materials**

Upload this file to `LoadImage` node **74**:

<CardGroup>
  <Card title="coastal_smiling_woman.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/coastal_smiling_woman.png">
    `LoadImage` node 74 · `coastal_smiling_woman.png`
  </Card>
</CardGroup>

![coastal\_smiling\_woman.png](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/coastal_smiling_woman.png)

## Model links

**text\_encoders**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/blob/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)

**diffusion\_models**

* [qwen\_image\_layered\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Layered_ComfyUI/blob/main/split_files/diffusion_models/qwen_image_layered_bf16.safetensors)

**vae**

* [qwen\_image\_layered\_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Layered_ComfyUI/blob/main/split_files/vae/qwen_image_layered_vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   ├── 📂 diffusion_models/
│   │      └── qwen_image_layered_bf16.safetensors
│   └── 📂 vae/
│          └── qwen_image_layered_vae.safetensors
```

## FP8 version

By default we are using bf16, which requires high VRAM. For lower VRAM usage, you can use the fp8 version:

* [qwen\_image\_layered\_fp8mixed.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Layered_ComfyUI/blob/main/split_files/diffusion_models/qwen_image_layered_fp8mixed.safetensors)

Then update the **Load Diffusion model** node inside the [Subgraph](/interface/features/subgraph) to use it.

## Layers and output

The number of layers is set by the `layers` widget on the **Empty Qwen Image Layered Latent** node inside the [Subgraph](/interface/features/subgraph).

This model regenerates the full image as well as the layers, so a generation always decodes to `layers + 1` images:

| `layers` | Images decoded | Contents |
| - | - | - |
| `0` | 1 | The full image only |
| `2` (template default) | 3 | The full image, then 2 layers |
| `5` | 6 | The full image, then 5 layers |

**The first image is the full image, not a layer.** The image to layers workflow drops it automatically with a `LatentCut` node (`dim` `t`, `index` `1`) before the batch split, so the template outputs `layers` images. If you build a custom graph without that node, discard the first image when you only want the layers. `layers` accepts `0`, which gives you that image on its own.

**Compositing all of the layers back together recreates the full image.** Use it as a check: if stacking the layers does not reproduce the first image, the decomposition did not do what you wanted.

### How the layers become separate images

The **Empty Qwen Image Layered Latent** node allocates a 5D latent shaped `[batch_size, 16, layers + 1, height // 8, width // 8]`. The layers sit on the third axis, the same temporal axis that video models use for frames. The **LatentCutToBatch** node with `dim` set to `t` moves that axis into the batch dimension, so after **VAE Decode** each layer is a separate image in the batch. The template inserts a `LatentCut` node (`dim` `t`, `index` `1`) before `LatentCutToBatch` to drop the full-image entry, so the decoded batch contains only the layers.

A layer's position in the stack is therefore its index in the batch, counting from the full image at index 0. There is no z-index field and no per-layer metadata carrying that order, so reordering or filtering the batch reorders the layers.

The Qwen-Image-Layered VAE decodes to 4 channels, so the decoded layers carry an alpha channel.

## Workflow settings

### Sampler settings

This model is slow. The original sampling settings are steps: 50 and CFG: 4.0, which will at least double the generation time.

### Input size

For input size, 640px is recommended. Use 1024px for high-resolution output.

### Prompt (optional)

The text prompt is intended to describe the overall content of the input image, including elements that may be partially occluded (e.g., you may specify the text hidden behind a foreground object). It is not designed to control the semantic content of individual layers explicitly.


# Z-Image ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/z-image/z-image

Z-Image is a 6B efficient image generation foundation model from Alibaba Tongyi Lab. Its single-stream DiT design targets fine-tuning and custom development.

**Z-Image (造相)** is a powerful and highly efficient image generation model with **6B** parameters, developed by Alibaba's Tongyi Lab. It uses a **Scalable Single-Stream DiT** (S3-DiT) architecture where text, visual semantic tokens, and image VAE tokens are concatenated at the sequence level to serve as a unified input stream, maximizing parameter efficiency.

Z-Image (Base) is the non-distilled foundation model designed for community-driven fine-tuning and custom development.

**Model Highlights**:

* **Photorealistic Quality**: Delivers strong photorealistic image generation while maintaining excellent aesthetic quality
* **Accurate Bilingual Text Rendering**: Excels at accurately rendering complex Chinese and English text
* **Prompt Enhancing & Reasoning**: Prompt Enhancer empowers the model with reasoning capabilities
* **Fine-tuning Ready**: Ideal base model for custom training and adaptation

**Related Links**:

* [GitHub](https://github.com/Tongyi-MAI/Z-Image)
* [Hugging Face](https://huggingface.co/Tongyi-MAI/Z-Image)
* [ModelScope](https://modelscope.cn/models/Tongyi-MAI/Z-Image)

## Z-Image text-to-image workflow

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Z-Image: Text to Image

Foundation for creative freedom. Diverse aesthetics with exceptional photorealistic quality; ideal for fine-tuning; responsive to negative prompts; high generation diversity.

<img alt="Z-Image text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_z_image&utm_source=docs&utm_medium=referral&utm_campaign=z-image">
    Run this workflow directly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_z_image.json">
    Download the Z-Image text-to-image workflow JSON file
  </Card>
</CardGroup>

**Example output**

![Z-Image example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_z_image.png)

## Z-Image model downloads

<CardGroup>
  <Card title="qwen_3_4b.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image_turbo/blob/main/split_files/text_encoders/qwen_3_4b.safetensors">
    Text encoder for Z-Image.
  </Card>

  <Card title="z_image_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image/blob/main/split_files/diffusion_models/z_image_bf16.safetensors">
    Diffusion model for Z-Image.
  </Card>

  <Card title="ae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image_turbo/blob/main/split_files/vae/ae.safetensors">
    VAE for Z-Image.
  </Card>
</CardGroup>

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_3_4b.safetensors
│   ├── 📂 diffusion_models/
│   │      └── z_image_bf16.safetensors
│   └── 📂 vae/
│          └── ae.safetensors
```


# Z-Image-Turbo ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/z-image/z-image-turbo

Z-Image-Turbo is a distilled 6B parameter efficient image generation model with sub-second inference latency.

<iframe title="YouTube video player" />

**Z-Image (造相)** is a powerful and highly efficient image generation model with **6B** parameters, developed by Alibaba's Tongyi Lab. It uses a **Scalable Single-Stream DiT** (S3-DiT) architecture where text, visual semantic tokens, and image VAE tokens are concatenated at the sequence level to serve as a unified input stream, maximizing parameter efficiency.

**Model Variants**:

* 🚀 **Z-Image-Turbo** – A distilled version that matches or exceeds leading competitors with only **8 NFEs** (Number of Function Evaluations). It offers **sub-second inference latency** on enterprise-grade H800 GPUs and fits within **16GB VRAM consumer devices**.
* 🧱 **Z-Image-Base** – The non-distilled foundation model for community-driven fine-tuning and custom development.
* ✍️ **Z-Image-Edit** – A variant fine-tuned for image editing tasks with impressive instruction-following capabilities.

**Model Highlights**:

* **Photorealistic Quality**: Delivers strong photorealistic image generation while maintaining excellent aesthetic quality
* **Accurate Bilingual Text Rendering**: Excels at accurately rendering complex Chinese and English text
* **Prompt Enhancing & Reasoning**: Prompt Enhancer empowers the model with reasoning capabilities
* **Sub-second Inference**: Achieves fast generation speed on supported hardware

**Related Links**:

* [GitHub](https://github.com/Tongyi-MAI/Z-Image)
* [Hugging Face](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo)

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Z-Image-Turbo text-to-image workflow

### Z-Image-Turbo: Text to Image

An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer, supports English & Chinese.

<img alt="Z-Image-Turbo text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_z_image_turbo&utm_source=docs&utm_medium=referral&utm_campaign=z-image-turbo">
    Run this workflow directly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_z_image_turbo.json">
    Download the Z-Image-Turbo text-to-image workflow JSON file
  </Card>
</CardGroup>

**Example output**

![Z-Image-Turbo example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_z_image_turbo.png)

### Z-Image-Turbo model downloads

<CardGroup>
  <Card title="qwen_3_4b.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image_turbo/blob/main/split_files/text_encoders/qwen_3_4b.safetensors">
    Text encoder for Z-Image-Turbo.
  </Card>

  <Card title="z_image_turbo_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image_turbo/blob/main/split_files/diffusion_models/z_image_turbo_bf16.safetensors">
    Diffusion model for Z-Image-Turbo.
  </Card>

  <Card title="ae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image_turbo/blob/main/split_files/vae/ae.safetensors">
    VAE for Z-Image-Turbo.
  </Card>
</CardGroup>

**Z-Image-Turbo Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_3_4b.safetensors
│   ├── 📂 diffusion_models/
│   │      └── z_image_turbo_bf16.safetensors
│   └── 📂 vae/
│          └── ae.safetensors
```

## Z-Image-Turbo Fun Union ControlNet workflow

### Z-Image-Turbo Fun Union ControlNet

Multi-control ControlNet supporting Canny, HED, Depth, Pose, and MLSD for Z-Image-Turbo.

<img alt="Z-Image-Turbo Fun Union ControlNet workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_z_image_turbo_fun_union_controlnet&utm_source=docs&utm_medium=referral&utm_campaign=z-image-turbo">
    Run this workflow directly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_z_image_turbo_fun_union_controlnet.json">
    Download the Z-Image-Turbo Fun Union ControlNet workflow JSON file
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="image_z_image_turbo_fun_union_controlnet_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/image_z_image_turbo_fun_union_controlnet_input_image.png">
    `LoadImage` node 58 · `image_z_image_turbo_fun_union_controlnet_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="image_z_image_turbo_fun_union_controlnet_input_image.png" />
</div>

### Additional model for ControlNet

<Card title="Z-Image-Turbo-Fun-Controlnet-Union.safetensors" icon="download" href="https://huggingface.co/alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union/blob/main/Z-Image-Turbo-Fun-Controlnet-Union.safetensors">
  ControlNet model patch for Z-Image-Turbo.
</Card>

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_3_4b.safetensors
│   ├── 📂 diffusion_models/
│   │      └── z_image_turbo_bf16.safetensors
│   ├── 📂 vae/
│   │      └── ae.safetensors
│   └── 📂 model_patches/
│          └── Z-Image-Turbo-Fun-Controlnet-Union.safetensors
```


# Comfy Cloud nodes
Source: https://docs.comfy.org/cloud-nodes/overview

Run curated workflows on Comfy Cloud's GPUs from a local ComfyUI install, no subscription required

A Comfy Cloud node is a regular ComfyUI node that sends its job to run on Comfy's own GPUs instead of the local machine. Drop it into a graph like any other node. No subscription is required: an account and credits are enough, the same as any other partner node.

<Note>
  Comfy Cloud nodes run open source models on the cloud. Not to be confused with Partner Nodes.
</Note>

## What it is

Each Comfy Cloud node runs one fixed workflow on a pinned model version, so a saved graph keeps producing the same result over time. Your graph, prompts, and inputs stay on your machine apart from what the node sends to run the job.

## Getting started

Comfy Cloud nodes ship with ComfyUI **v0.34.5 or later**. They are part of ComfyUI core, so there is nothing to install separately.

<Steps>
  <Step title="Update ComfyUI">
    Update to v0.34.5 or later. See [How to update ComfyUI](/installation/update_comfyui) for the portable, desktop, and manual install paths.
  </Step>

  <Step title="Restart ComfyUI">
    The nodes only register at startup, so they will not appear until you restart.
  </Step>

  <Step title="Find a node">
    Search the node library for **Comfy Cloud**, then wire one into your graph like any other node. Every node carries a `[BETA]` suffix in its display name.
  </Step>
</Steps>

## Available nodes

Eight nodes at launch, across image, video, and audio:

| Node | Modality |
| - | - |
| Comfy Cloud Flux 2 Text to Image | Image |
| Comfy Cloud Mage Flow Text to Image | Image |
| Comfy Cloud Mage Flow Turbo Text to Image | Image |
| Comfy Cloud Z-Image Turbo Text to Image | Image |
| Comfy Cloud MiniMax H3 Text to Video | Video |
| Comfy Cloud MiniMax H3 Image to Video | Video |
| Comfy Cloud MiniMax H3 First-Last Frame to Video | Video |
| Comfy Cloud MiniMax Music 3 Text to Audio | Audio |

## Billing

Comfy Cloud nodes are billed per GPU-second in credits, shown on the node before you run it. There is no subscription and no monthly floor.

## Limitations

* No bring-your-own LoRA or checkpoint yet. Each node exposes a fixed set of hosted weights. Direct upload is a planned next step, not available in this release.

## Related

* [Comfy Cloud pricing](https://comfy.org/pricing)
* [Partner Nodes overview](/tutorials/partner-nodes/overview) (the separate third-party API node catalog)


# ComfyUI Hunyuan3D-2 Examples
Source: https://docs.comfy.org/tutorials/3d/hunyuan3D-2

Hunyuan3D 2.0 in ComfyUI: generate textured 3D models from text or images with Tencent's open-source two-stage model, geometry first, then textures.

# Hunyuan3D 2.0 Introduction

![Hunyuan 3D 2](https://raw.githubusercontent.com/Tencent/Hunyuan3D-2/main/assets/images/e2e-1.gif)
![Hunyuan 3D 2](https://raw.githubusercontent.com/Tencent/Hunyuan3D-2/main/assets/images/e2e-2.gif)
[Hunyuan3D 2.0](https://github.com/Tencent/Hunyuan3D-2) is an open-source 3D asset generation model released by Tencent, capable of generating high-fidelity 3D models with high-resolution texture maps through text or images.

Hunyuan3D 2.0 adopts a two-stage generation approach, first generating a geometry model without textures, then synthesizing high-resolution texture maps. This effectively separates the complexity of shape and texture generation. Below are the two core components of Hunyuan3D 2.0:

1. **Geometry Generation Model (Hunyuan3D-DiT)**: Based on a flow diffusion Transformer architecture, it generates untextured geometric models that precisely match input conditions.
2. **Texture Generation Model (Hunyuan3D-Paint)**: Combines geometric conditions and multi-view diffusion techniques to add high-resolution textures to models, supporting PBR materials.

**Key Advantages**

* **High-Precision Generation**: Sharp geometric structures, rich texture colors, support for PBR material generation, achieving near-realistic lighting effects.
* **Diverse Usage Methods**: Provides code calls, Blender plugins, Gradio applications, and online experience through the official website, suitable for different user needs.
* **Lightweight and Compatibility**: The Hunyuan3D-2mini model requires only 5GB VRAM, the standard version needs 6GB VRAM for shape generation, and the complete process (shape + texture) requires only 12GB VRAM.

Recently (March 18, 2025), Hunyuan3D 2.0 also introduced a multi-view shape generation model (Hunyuan3D-2mv), which supports generating more detailed geometric structures from inputs at different angles.

This example includes three workflows:

* Using Hunyuan3D-2mv with multiple view inputs to generate 3D models
* Using Hunyuan3D-2mv-turbo with multiple view inputs to generate 3D models
* Using Hunyuan3D-2 with a single view input to generate 3D models

<Tip>
  ComfyUI now natively supports Hunyuan3D-2mv, but does not yet support texture and material generation. Please make sure you have updated to the latest version of [ComfyUI](https://github.com/Comfy-Org/ComfyUI) before starting.

  The workflow example PNG images in this tutorial contain workflow JSON in their metadata:

  * You can drag them directly into ComfyUI
  * Or use the menu `Workflows` -> `Open (ctrl+o)`

  This will load the corresponding workflow and prompt you to download the required models. The generated `.glb` format models will be output to the `ComfyUI/output/mesh` folder.
</Tip>

## ComfyUI Hunyuan3D-2mv Workflow Example

In the Hunyuan3D-2mv workflow, we'll use multi-view images to generate a 3D model. Note that multiple view images are not mandatory in this workflow - you can use only the `front` view image to generate a 3D model.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### HY 3D 2.0 MV

Generate 3D models from multiple views using Hunyuan3D 2.0 MV.

<img alt="HY 3D 2.0 MV workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=3d_hunyuan3d_multiview_to_model&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan3D-2">
    Run this workflow instantly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_hunyuan3d_multiview_to_model.json">
    Download JSON or search "HY 3D 2.0 MV" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="3d_hunyuan3d_multiview_to_model_front_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/3d_hunyuan3d_multiview_to_model_front_image.png">
    `LoadImage` node 56 · front view
  </Card>

  <Card title="3d_hunyuan3d_multiview_to_model_left_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/3d_hunyuan3d_multiview_to_model_left_image.png">
    `LoadImage` node 78 · left view
  </Card>

  <Card title="3d_hunyuan3d_multiview_to_model_back_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/3d_hunyuan3d_multiview_to_model_back_image.png">
    `LoadImage` node 80 · back view
  </Card>

  <Card title="3d_hunyuan3d_multiview_to_model_right_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/3d_hunyuan3d_multiview_to_model_right_image.png">
    `LoadImage` node 87 · right view
  </Card>
</CardGroup>

### 1. Workflow

Please download the images below and drag  into ComfyUI to load the workflow.
![Hunyuan3D-2mv workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/hunyuan-3d-multiview-elf.webp)

Download the images below we will use them as input images.

![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/front.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/left.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/back.png)

<Tip>
  In this example, the input images have already been preprocessed to remove excess background. In actual use, you can use custom nodes like [ComfyUI\_essentials](https://github.com/cubiq/ComfyUI_essentials) to automatically remove excess background.
</Tip>

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-mv: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2mv/blob/main/hunyuan3d-dit-v2-mv/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2-mv.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2-mv.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2mv" />

1. Ensure that the Image Only Checkpoint Loader(img2vid model) has loaded our downloaded and renamed `hunyuan3d-dit-v2-mv.safetensors` model
2. Load the corresponding view images in each of the `Load Image` nodes
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

If you need to add more views, make sure to load other view images in the `Hunyuan3Dv2ConditioningMultiView` node, and ensure that you load the corresponding view images in the `Load Image` nodes.

## Hunyuan3D-2mv-turbo Workflow

In the Hunyuan3D-2mv-turbo workflow, we'll use the Hunyuan3D-2mv-turbo model to generate 3D models. This model is a step distillation version of Hunyuan3D-2mv, allowing for faster 3D model generation. In this version of the workflow, we set `cfg` to 1.0 and add a `flux guidance` node to control the `distilled cfg` generation.

### HY 3D 2.0 MV Turbo

Generate 3D models from multiple views using Hunyuan3D 2.0 MV Turbo.

<img alt="HY 3D 2.0 MV Turbo workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=3d_hunyuan3d_multiview_to_model_turbo&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan3D-2">
    Run this workflow instantly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_hunyuan3d_multiview_to_model_turbo.json">
    Download JSON or search "HY 3D 2.0 MV Turbo" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="3d_hunyuan3d_multiview_to_model_turbo_front_view.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/3d_hunyuan3d_multiview_to_model_turbo_front_view.png">
    `LoadImage` node 56 · front view
  </Card>

  <Card title="3d_hunyuan3d_multiview_to_model_turbo_back_view.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/3d_hunyuan3d_multiview_to_model_turbo_back_view.png">
    `LoadImage` node 82 · back view
  </Card>

  <Card title="3d_hunyuan3d_multiview_to_model_turbo_left_view.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/3d_hunyuan3d_multiview_to_model_turbo_left_view.png">
    `LoadImage` node 85 · left view
  </Card>

  <Card title="3d_hunyuan3d_multiview_to_model_turbo_right_view.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/3d_hunyuan3d_multiview_to_model_turbo_right_view.png">
    `LoadImage` node 87 · right view
  </Card>
</CardGroup>

### 1. Workflow

Please download the images below and drag into ComfyUI to load the workflow.

![Hunyuan3D-2mv-turbo workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/hunyuan-3d-turbo.webp)

Download the images below we will use them as input images.

![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/front.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/right.png)

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-mv-turbo: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2mv/blob/main/hunyuan3d-dit-v2-mv-turbo/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2-mv-turbo.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2-mv-turbo.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2mv_turbo" />

1. Ensure that the `Image Only Checkpoint Loader(img2vid model)` node has loaded our renamed `hunyuan3d-dit-v2-mv-turbo.safetensors` model
2. Load the corresponding view images in each of the `Load Image` nodes
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Hunyuan3D-2 Single View Workflow

In the Hunyuan3D-2 workflow, we'll use the Hunyuan3D-2 model to generate 3D models. This model is not a multi-view model. In this workflow, we use the `Hunyuan3Dv2Conditioning` node instead of the `Hunyuan3Dv2ConditioningMultiView` node.

### HY 3D 2.0

Generate 3D models from single images using Hunyuan3D 2.0.

<img alt="HY 3D 2.0 workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=3d_hunyuan3d_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan3D-2">
    Run this workflow instantly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_hunyuan3d_image_to_model.json">
    Download JSON or search "HY 3D 2.0" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="3d_hunyuan3d_image_to_model_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/3d_hunyuan3d_image_to_model_input_image.png">
    `LoadImage` node 56 · `3d_hunyuan3d_image_to_model_input_image.png`
  </Card>
</CardGroup>

### 1. Workflow

Please download the image below and drag it into ComfyUI to load the workflow.

![Hunyuan3D-2 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d-non-multiview-train.webp)

Download the image below we will use it as input image.
![ComfyUI Hunyuan 3D 2 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan_3d_v2_non_multiview_train.png)

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-0: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2/blob/main/hunyuan3d-dit-v2-0/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2" />

1. Ensure that the `Image Only Checkpoint Loader(img2vid model)` node has loaded our renamed `hunyuan3d-dit-v2.safetensors` model
2. Load the image in the `Load Image` node
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Community Resources

Below are ComfyUI community resources related to Hunyuan3D-2

* [ComfyUI-Hunyuan3DWrapper](https://github.com/kijai/ComfyUI-Hunyuan3DWrapper)
* [Kijai/Hunyuan3D-2\_safetensors](https://huggingface.co/Kijai/Hunyuan3D-2_safetensors/tree/main)
* [ComfyUI-3D-Pack](https://github.com/MrForExample/ComfyUI-3D-Pack)

## Hunyuan3D 2.0 Open-Source Model Series

Currently, Hunyuan3D 2.0 has open-sourced multiple models covering the complete 3D generation process. You can visit [Hunyuan3D-2](https://github.com/Tencent/Hunyuan3D-2) for more information.

**Hunyuan3D-2mini Series**

| Model | Description | Date | Parameters | Huggingface |
| - | - | - | - | - |
| Hunyuan3D-DiT-v2-mini | Mini Image to Shape Model | 2025-03-18 | 0.6B | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mini/tree/main/hunyuan3d-dit-v2-mini) |

**Hunyuan3D-2mv Series**

| Model | Description | Date | Parameters | Huggingface |
| - | - | - | - | - |
| Hunyuan3D-DiT-v2-mv-Fast | Guidance Distillation Version, can halve DIT inference time | 2025-03-18 | 1.1B | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mv/tree/main/hunyuan3d-dit-v2-mv-fast) |
| Hunyuan3D-DiT-v2-mv | Multi-view Image to Shape Model, suitable for 3D creation requiring multiple angles to understand the scene | 2025-03-18 | 1.1B | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mv/tree/main/hunyuan3d-dit-v2-mv) |

**Hunyuan3D-2 Series**

| Model | Description | Date | Parameters | Huggingface |
| - | - | - | - | - |
| Hunyuan3D-DiT-v2-0-Fast | Guidance Distillation Model | 2025-02-03 | 1.1B | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-dit-v2-0-fast) |
| Hunyuan3D-DiT-v2-0 | Image to Shape Model | 2025-01-21 | 1.1B | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-dit-v2-0) |
| Hunyuan3D-Paint-v2-0 | Texture Generation Model | 2025-01-21 | 1.3B | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-paint-v2-0) |
| Hunyuan3D-Delight-v2-0 | Image Delight Model | 2025-01-21 | 1.3B | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-delight-v2-0) |


# Pixal3D Image to 3D Model ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/3d/pixal3d

Generate high-fidelity 3D models with full PBR textures from a single image using Pixal3D, a pixel-aligned image-to-3D model from Tencent ARC.

**Pixal3D** is an open-source image-to-3D model from Tencent ARC, presented at SIGGRAPH 2026. It turns a single image into a high-fidelity 3D asset with full PBR materials.

Most 3D-native generators synthesize shapes in a canonical space and inject image cues through attention, which leaves pixel-to-3D associations ambiguous. Pixal3D instead uses pixel-aligned generation: it establishes direct pixel-to-3D correspondence through back-projection, so the front of the generated model matches your input image 1:1, with no warped or misaligned textures.

### Pixal3D: Image to 3D Model

Upload a single image. Generate a high-fidelity 3D model with full PBR textures, aligned to your input view.

This workflow also includes the TRELLIS.2 pipeline. The `Boolean (Switch to Trellis2)` node defaults to `false`, which runs the Pixal3D pipeline and loads the Pixal3D model automatically.

<img alt="Pixal3D workflow preview" />

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=3d_pixal3d_trellis2_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=pixal3d">
    Run this workflow instantly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_pixal3d_trellis2_image_to_model.json">
    Download JSON or search "Pixal3D & TRELLIS.2: Image to Model" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the `LoadImage` node:

<CardGroup>
  <Card title="viking_wolf_rune_axe.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/viking_wolf_rune_axe.png">
    `LoadImage` node 122 · `viking_wolf_rune_axe.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />
</div>

### Pixal3D: Multi Views to 3D

Generate a 3D model from a character turnaround sheet (front, side, and back views on one image). The multiview model uses the extra viewpoints to reconstruct geometry the single-image pipeline cannot see, which gives more accurate side and back profiles.

Use the `Character Turnaround Sheet Generator` template in the template library to produce the turnaround sheet with Nano Banana 2, or prepare your own multi-view image with the subject separated from the background.

<img alt="Pixal3D Multi Views workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=3d_pixal3d_multi_views&utm_source=docs&utm_medium=referral&utm_campaign=pixal3d">
    Run this workflow instantly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_pixal3d_multi_views.json">
    Download JSON or search "Pixal3D: Multi Views to 3D" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the `LoadImage` node:

<CardGroup>
  <Card title="character_turnaround_4view_sheet.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/character_turnaround_4view_sheet.png">
    `LoadImage` node 364 · `character_turnaround_4view_sheet.png`
  </Card>
</CardGroup>

The workflow uses the models listed below. Download them and place them in the corresponding `models/` subdirectories:

<CardGroup>
  <Card title="Pixal3D Multiview UNet" icon="download" href="https://huggingface.co/Comfy-Org/Pixal3D/blob/main/diffusion_models/pixal3d_multiview_int8_convrot.safetensors">
    pixal3d\_multiview\_int8\_convrot.safetensors → ComfyUI/models/diffusion\_models/
  </Card>

  <Card title="Shape VAE" icon="download" href="https://huggingface.co/Comfy-Org/Pixal3D/blob/main/vae/trellis_2_shape_vae_bf16.safetensors">
    trellis\_2\_shape\_vae\_bf16.safetensors → ComfyUI/models/vae/
  </Card>

  <Card title="Texture VAE" icon="download" href="https://huggingface.co/Comfy-Org/Pixal3D/blob/main/vae/trellis_2_texture_vae_bf16.safetensors">
    trellis\_2\_texture\_vae\_bf16.safetensors → ComfyUI/models/vae/
  </Card>

  <Card title="DINOv3 CLIP vision" icon="download" href="https://huggingface.co/Comfy-Org/Pixal3D/blob/main/clip_vision/dino_v3_L_naf_fp32.safetensors">
    dino\_v3\_L\_naf\_fp32.safetensors → ComfyUI/models/clip\_vision/
  </Card>

  <Card title="BiRefNet background removal" icon="download" href="https://huggingface.co/Comfy-Org/BiRefNet/blob/main/background_removal/birefnet.safetensors">
    birefnet.safetensors → ComfyUI/models/background\_removal/
  </Card>
</CardGroup>

## How it works

Pixal3D combines camera-aware, pixel-aligned generation with a complete mesh post-processing pipeline:

1. **Background removal**: BiRefNet removes the background from the input image, and the workflow crops the subject to a centered canvas. A switch lets you skip background removal
2. **Camera estimation**: MoGe estimates geometry and the camera field of view from the image. The FOV drives the pixel-aligned conditioning
3. **Structure generation**: a sparse structure latent is sampled and decoded into voxels, then converted into a rough mesh
4. **Shape refinement**: the shape stage and the upsampling stage refine the mesh up to the target resolution (1536)
5. **Texture generation**: a texture diffusion stage produces PBR material voxels (base color, metallic, roughness)
6. **Post-processing**: DC remesh, QEM decimation, UV unwrapping, and baking of base color, normal, and ambient occlusion maps into the final textured mesh

## Steps to run

1. **Load an image**: use the `LoadImage` node to load a single image of the object
2. **Queue the workflow**: press Ctrl (Cmd on macOS) + Enter
3. **Wait for the pipeline**: the structure, shape, and texture stages run in sequence, followed by post-processing
4. **View the result**: inspect the mesh in the `Preview3DAdvanced` node. The 3D model is saved to `ComfyUI/output/3d/ComfyUI/`

## Model downloads

Download the models used by this workflow. Both diffusion checkpoints are required: the switch selects which one runs. Place them in the corresponding `models/` subdirectories.

<CardGroup>
  <Card title="Pixal3D UNet" icon="download" href="https://huggingface.co/Comfy-Org/Pixal3D/blob/main/diffusion_models/pixal3d_int8_convrot.safetensors">
    pixal3d\_int8\_convrot.safetensors: Pixal3D diffusion model, loaded by default
  </Card>

  <Card title="TRELLIS.2 UNet" icon="download" href="https://huggingface.co/Comfy-Org/TRELLIS.2/blob/main/diffusion_models/trellis_2_int8_convrot.safetensors">
    trellis\_2\_int8\_convrot.safetensors: TRELLIS.2 diffusion model, loaded when the switch is set to `true`
  </Card>

  <Card title="Shape VAE" icon="download" href="https://huggingface.co/Comfy-Org/Pixal3D/blob/main/vae/trellis_2_shape_vae_bf16.safetensors">
    trellis\_2\_shape\_vae\_bf16.safetensors: VAE for structure and shape decoding
  </Card>

  <Card title="Texture VAE" icon="download" href="https://huggingface.co/Comfy-Org/Pixal3D/blob/main/vae/trellis_2_texture_vae_bf16.safetensors">
    trellis\_2\_texture\_vae\_bf16.safetensors: VAE for texture decoding
  </Card>

  <Card title="DINOv3 CLIP vision" icon="download" href="https://huggingface.co/Comfy-Org/Pixal3D/blob/main/clip_vision/dino_v3_L_naf_fp32.safetensors">
    dino\_v3\_L\_naf\_fp32.safetensors: CLIP vision encoder for image conditioning
  </Card>

  <Card title="MoGe geometry" icon="download" href="https://huggingface.co/Comfy-Org/MoGe/blob/main/geometry_estimation/moge_2_vitl_normal_fp16.safetensors">
    moge\_2\_vitl\_normal\_fp16.safetensors: depth and camera estimation for pixel-aligned conditioning
  </Card>

  <Card title="BiRefNet background removal" icon="download" href="https://huggingface.co/Comfy-Org/BiRefNet/blob/main/background_removal/birefnet.safetensors">
    birefnet.safetensors: background removal model for preprocessing
  </Card>
</CardGroup>

### Model storage location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │      ├── pixal3d_int8_convrot.safetensors
│   │      └── trellis_2_int8_convrot.safetensors
│   ├── 📂 vae/
│   │      ├── trellis_2_shape_vae_bf16.safetensors
│   │      └── trellis_2_texture_vae_bf16.safetensors
│   ├── 📂 clip_vision/
│   │      └── dino_v3_L_naf_fp32.safetensors
│   ├── 📂 geometry_estimation/
│   │      └── moge_2_vitl_normal_fp16.safetensors
│   └── 📂 background_removal/
│          └── birefnet.safetensors
```


# TRELLIS.2 Image to 3D Model ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/3d/trellis2

Generate high-fidelity 3D models with full PBR textures from a single image using TRELLIS.2, Microsoft's open-source 4B-parameter image-to-3D model.

**TRELLIS.2** is an open-source image-to-3D model from Microsoft Research, and the successor to TRELLIS. It is a 4B-parameter model built on native 3D VAEs with 16× spatial compression and a sparse voxel representation called O-Voxel, producing detailed 3D assets with full PBR materials from a single image.

TRELLIS.2 shares its base architecture with Pixal3D: both use the same DINOv3 image encoder, the same shape and texture VAEs, and the same structure, shape, and texture generation stages. Only the main diffusion model and the conditioning format differ. If you have run the [Pixal3D workflow](/tutorials/3d/pixal3d), the model setup is almost identical.

### TRELLIS.2: Image to 3D Model

Upload a single image. Generate a high-fidelity 3D model with full PBR textures using TRELLIS.2.

This workflow also includes the Pixal3D pipeline. To run TRELLIS.2, set the `Boolean (Switch to Trellis2)` node to `true`. The workflow automatically switches to the TRELLIS.2 model and its conditioning.

<img alt="TRELLIS.2 workflow preview" />

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=3d_pixal3d_trellis2_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=trellis2">
    Run this workflow instantly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_pixal3d_trellis2_image_to_model.json">
    Download JSON or search "Pixal3D & TRELLIS.2: Image to Model" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the `LoadImage` node:

<CardGroup>
  <Card title="viking_wolf_rune_axe.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/viking_wolf_rune_axe.png">
    `LoadImage` node 122 · `viking_wolf_rune_axe.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />
</div>

## How it works

TRELLIS.2 generates a 3D asset in three diffusion stages and then runs a full mesh post-processing pipeline:

1. **Background removal**: BiRefNet removes the background from the input image, and the workflow crops the subject to a centered canvas. A switch lets you skip background removal
2. **Structure generation**: a sparse structure latent is sampled and decoded into voxels, then converted into a rough mesh
3. **Shape refinement**: the shape stage and the upsampling stage refine the mesh up to the target resolution (1536)
4. **Texture generation**: a texture diffusion stage produces PBR material voxels (base color, metallic, roughness)
5. **Post-processing**: DC remesh, QEM decimation, UV unwrapping, and baking of base color, normal, and ambient occlusion maps into the final textured mesh

## Steps to run

1. **Load an image**: use the `LoadImage` node to load a single image of the object
2. **Switch to the TRELLIS.2 pipeline**: set `Boolean (Switch to Trellis2)` to `true`. The workflow loads the TRELLIS.2 checkpoint automatically
3. **Queue the workflow**: press Ctrl (Cmd on macOS) + Enter
4. **Wait for the pipeline**: the structure, shape, and texture stages run in sequence, followed by post-processing
5. **View the result**: inspect the mesh in the `Preview3DAdvanced` node. The 3D model is saved to `ComfyUI/output/3d/ComfyUI/`

## Model downloads

Download the models used by this workflow. Both diffusion checkpoints are required: the switch selects which one runs. Place them in the corresponding `models/` subdirectories.

<CardGroup>
  <Card title="TRELLIS.2 UNet" icon="download" href="https://huggingface.co/Comfy-Org/TRELLIS.2/blob/main/diffusion_models/trellis_2_int8_convrot.safetensors">
    trellis\_2\_int8\_convrot.safetensors: TRELLIS.2 diffusion model, loaded when the switch is set to `true`
  </Card>

  <Card title="Pixal3D UNet" icon="download" href="https://huggingface.co/Comfy-Org/Pixal3D/blob/main/diffusion_models/pixal3d_int8_convrot.safetensors">
    pixal3d\_int8\_convrot.safetensors: Pixal3D diffusion model, loaded by default
  </Card>

  <Card title="Shape VAE" icon="download" href="https://huggingface.co/Comfy-Org/TRELLIS.2/blob/main/vae/trellis_2_shape_vae_bf16.safetensors">
    trellis\_2\_shape\_vae\_bf16.safetensors: VAE for structure and shape decoding
  </Card>

  <Card title="Texture VAE" icon="download" href="https://huggingface.co/Comfy-Org/TRELLIS.2/blob/main/vae/trellis_2_texture_vae_bf16.safetensors">
    trellis\_2\_texture\_vae\_bf16.safetensors: VAE for texture decoding
  </Card>

  <Card title="DINOv3 CLIP vision" icon="download" href="https://huggingface.co/Comfy-Org/Pixal3D/blob/main/clip_vision/dino_v3_L_naf_fp32.safetensors">
    dino\_v3\_L\_naf\_fp32.safetensors: CLIP vision encoder for image conditioning. The equivalent dino\_v3\_vit\_l.safetensors from the TRELLIS.2 repo also works
  </Card>

  <Card title="BiRefNet background removal" icon="download" href="https://huggingface.co/Comfy-Org/BiRefNet/blob/main/background_removal/birefnet.safetensors">
    birefnet.safetensors: background removal model for preprocessing
  </Card>
</CardGroup>

### Model storage location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │      ├── trellis_2_int8_convrot.safetensors
│   │      └── pixal3d_int8_convrot.safetensors
│   ├── 📂 vae/
│   │      ├── trellis_2_shape_vae_bf16.safetensors
│   │      └── trellis_2_texture_vae_bf16.safetensors
│   ├── 📂 clip_vision/
│   │      └── dino_v3_L_naf_fp32.safetensors
│   └── 📂 background_removal/
│          └── birefnet.safetensors
```


# TripoSplat Image to Gaussian Splat ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/3d/triposplat

Generate high-quality 3D Gaussian splat representations from a single 2D image using TripoSplat, with controllable density and budget for rendering.

**TripoSplat** is an open-source model that generates **3D Gaussian splat** representations directly from a single 2D image. It was developed by VAST-AI and released under an open-source license.

Unlike traditional 3D reconstruction methods that require multiple views or generate meshes as the primary output, TripoSplat creates **Gaussian splat** representations: a rendering technique where thousands of colored 3D Gaussians are placed in space to represent a scene. This approach enables fast, high-quality rendering with controllable density and budget.

### TripoSplat: Image to Gaussian Splat

Upload a single 2D image. Generate a high-quality 3D Gaussian splat representation with controllable density and budget for rendering.

<img alt="TripoSplat workflow preview" />

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=3d_triposplat_image_to_gaussian_splat&utm_source=docs&utm_medium=referral&utm_campaign=triposplat">
    Run this workflow instantly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_triposplat_image_to_gaussian_splat.json">
    Download JSON or search "TripoSplat: Image to Gaussian Splat" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="white-hotel-on-rocky-island.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/white-hotel-on-rocky-island.png">
    `LoadImage` node 99 · `white-hotel-on-rocky-island.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />
</div>

## How it works

TripoSplat uses a **feed-forward architecture** that takes a single RGB image and directly predicts a set of 3D Gaussian primitives. The pipeline involves:

1. **Image encoding**: the input image is processed by a vision encoder (DINOv2)
2. **Triplane generation**: features are decoded into a triplane representation
3. **Gaussian prediction**: the triplane is sampled to produce Gaussian parameters (position, scale, rotation, opacity, color)
4. **Rendering**: Gaussians are rendered from arbitrary viewpoints using differentiable splatting

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses a Subgraph node for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Workflow node guide

### LoadImage

* Loads your input image (PNG/JPG)
* Sample image: `white-hotel-on-rocky-island.png` (available in Template Library)

### TripoSplat (subgraph)

The main subgraph node processes the image and generates the 3D Gaussian splat. Exposed parameters:

| Parameter | Default | Description |
| - | - | - |
| `switch` | — | Enable/disable the subgraph |
| `num_gaussians` | — | Number of Gaussian primitives to generate (controls quality/performance) |
| `seed` | — | Random seed for reproducibility |
| `unet_name` | — | TripoSplat diffusion model checkpoint |
| `clip_name` | — | CLIP vision encoder model |
| `vae_name` | — | VAE for encoding/decoding (2 entries: one for the main VAE, one for the encoder) |
| `bg_removal_name` | — | Background removal model |

### CreateCameraInfo

* Defines the camera orbit for rendering the result
* Parameters: orbit type, angle, distance, field of view, etc.
* Default: orbit at 35° elevation, 30 distance, 2.5 zoom

### RenderSplat

* Renders the Gaussian splat into a 2D image from the defined camera angle
* Parameters: output resolution (default 1024×1024), image quality settings

### SplatToMesh

* Converts the Gaussian splat to a mesh (optional)
* Parameters: mesh density, smoothing, simplification

### SaveGLB

* Saves the result as a GLB 3D file

### SaveVideo

* Saves a video of the rendered 3D scene

### SplatToFile3D

* Exports the Gaussian splat in SPZ format

### CreateVideo

* Creates a video from rendered frames

## Steps to run

1. **Load an image**: use the **LoadImage** node to load a single 2D image
2. **Run the TripoSplat subgraph**: the model will generate a Gaussian splat representation
3. **Choose output format**: export as GLB, SPZ, video, or render to mesh
4. **View results**: use the created 3D file or rendered preview

## Output options

| Node | Format | Use case |
| - | - | - |
| **SaveGLB** | `.glb` | Standard 3D file format, importable into 3D software |
| **SplatToFile3D** | `.spz` | Compressed Gaussian splat format for efficient storage |
| **RenderSplat** | 2D image | Quick preview of the result from any angle |
| **SplatToMesh** | Mesh | Convert to traditional mesh for further editing |

## Model downloads

Download the TripoSplat model and required files. Place them in the corresponding `models/` subdirectories.

<CardGroup>
  <Card title="TripoSplat diffusion" icon="download" href="https://huggingface.co/VAST-AI/TripoSplat/blob/main/diffusion_models/triposplat_fp16.safetensors">
    triposplat\_fp16.safetensors: TripoSplat diffusion model checkpoint
  </Card>

  <Card title="TripoSplat VAE decoder" icon="download" href="https://huggingface.co/VAST-AI/TripoSplat/blob/main/vae/triposplat_vae_decoder_fp16.safetensors">
    triposplat\_vae\_decoder\_fp16.safetensors: VAE decoder
  </Card>

  <Card title="Flux2 VAE" icon="download" href="https://huggingface.co/VAST-AI/TripoSplat/blob/main/vae/flux2-vae.safetensors">
    flux2-vae.safetensors: Flux.2 VAE for latent encoding
  </Card>

  <Card title="DINOv2 CLIP" icon="download" href="https://huggingface.co/VAST-AI/TripoSplat/blob/main/clip_vision/dino_v3_vit_h.safetensors">
    dino\_v3\_vit\_h.safetensors: CLIP vision encoder (DINOv2)
  </Card>

  <Card title="BiRefNet bg removal" icon="download" href="https://huggingface.co/VAST-AI/TripoSplat/blob/main/background_removal/birefnet.safetensors">
    birefnet.safetensors: Background removal model for preprocessing
  </Card>
</CardGroup>

### Model storage location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │      └── triposplat_fp16.safetensors
│   ├── 📂 vae/
│   │      ├── triposplat_vae_decoder_fp16.safetensors
│   │      └── flux2-vae.safetensors
│   ├── 📂 clip_vision/
│   │      └── dino_v3_vit_h.safetensors
│   └── 📂 background_removal/
│          └── birefnet.safetensors
```


# ComfyUI ACE-Step Native Example
Source: https://docs.comfy.org/tutorials/audio/ace-step/ace-step-v1

ACE-Step music generation in ComfyUI: text-to-music and music editing workflows with the Apache-2.0 open-source model from StepFun and ACE Studio.

ACE-Step is an open-source foundational music generation model jointly developed by Chinese team StepFun and ACE Studio, aimed at providing music creators with efficient, flexible and high-quality music generation and editing tools.

The model is released under the [Apache-2.0](https://github.com/ace-step/ACE-Step?tab=readme-ov-file#-license) license and is free for commercial use.

As a powerful music generation foundation, ACE-Step provides rich extensibility. Through fine-tuning techniques like LoRA and ControlNet, developers can customize the model according to their actual needs.
Whether it's audio editing, vocal synthesis, accompaniment production, voice cloning or style transfer applications, ACE-Step provides stable and reliable technical support.
This flexible architecture greatly simplifies the development process of music AI applications, allowing more creators to quickly apply AI technology to music creation.

Currently, ACE-Step has released related training code, including LoRA model training, and the corresponding ControlNet training code will be released in the future.
You can visit their [Github](https://github.com/ace-step/ACE-Step?tab=readme-ov-file#-roadmap) to learn more details.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## ACE-Step ComfyUI Text-to-Audio Generation Workflow Example

### 1. Download Workflow and Related Models

Click the button below to download the corresponding workflow file. Drag it into ComfyUI to load the workflow information. The workflow includes model download information.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/audio/ace-step/ace_step_1_t2m.json">
  <p>Download Json Format Workflow File</p>
</a>

You can also manually download [ace\_step\_v1\_3.5b.safetensors](https://huggingface.co/Comfy-Org/ACE-Step_ComfyUI_repackaged/blob/main/all_in_one/ace_step_v1_3.5b.safetensors) and save it to the `ComfyUI/models/checkpoints` folder

### 2. Complete the Workflow Step by Step

<img alt="Step Guide" />

1. Ensure the `Load Checkpoints` node has loaded the `ace_step_v1_3.5b.safetensors` model
2. (Optional) In the `EmptyAceStepLatentAudio` node, you can set the duration of the music to be generated
3. (Optional) In the `LatentOperationTonemapReinhard` node, you can adjust the `multiplier` to control the volume of the vocals (higher numbers result in more prominent vocals)
4. (Optional) Input corresponding music styles etc. in the `tags` field of `TextEncodeAceStepAudio`
5. (Optional) Input corresponding lyrics in the `lyrics` field of `TextEncodeAceStepAudio`
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the audio generation
7. After the workflow completes,, you can preview the generated audio in the `Save Audio` node. You can click to play and listen to it, and the audio will also be saved to `ComfyUI/output/audio` (subdirectory determined by the `Save Audio` node).

## ACE-Step ComfyUI Audio-to-Audio Workflow

Similar to image-to-image workflows, you can input a piece of music and use the workflow below to resample and generate music. You can also adjust the difference from the original audio by controlling the `denoise` parameter in the `Ksampler`.

### 1. Download Workflow File

Click the button below to download the corresponding workflow file. Drag it into ComfyUI to load the workflow information.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/audio/ace-step/ace_step_1_m2m_editing.json">
  <p>Download Json Format Workflow File</p>
</a>

Download the following audio file as the input audio:

<a href="https://github.com/Comfy-Org/example_workflows/raw/refs/heads/main/audio/ace-step/input.mp3">
  <p>Download Example Audio File for Input</p>
</a>

### 2. Complete the Workflow Step by Step

<img alt="ACE-Step Step Guide" />

1. Ensure the `Load Checkpoints` node has loaded the `ace_step_v1_3.5b.safetensors` model
2. Upload the provided audio file in the `LoadAudio` node
3. (Optional) Input corresponding music styles and lyrics in the `tags` and `lyrics` fields of `TextEncodeAceStepAudio`. Providing lyrics is very important for audio editing
4. (Optional) Modify the `denoise` parameter in the `Ksampler` node to adjust the noise added during sampling to control similarity with the original audio (smaller values result in more similarity to the original audio; setting it to `1.00` is approximately equivalent to having no audio input)
5. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the audio generation
6. After the workflow completes, you can preview the generated audio in the `Save Audio` node. You can click to play and listen to it, and the audio will also be saved to `ComfyUI/output/audio` (subdirectory determined by the `Save Audio` node).

You can also implement the lyrics modification and editing functionality from the ACE-Step project page, modifying the original lyrics to change the audio effect.

### 3. Additional Workflow Notes

1. In the example workflow, you can change the `tags` in `TextEncodeAceStepAudio` from `male voice` to `female voice` to generate female vocals.
2. You can also modify the `lyrics` in `TextEncodeAceStepAudio` to change the lyrics and thus the generated audio. Refer to the examples on the ACE-Step project page for more details.

## ACE-Step Prompt Guide

ACE currently uses two types of prompts: `tags` and `lyrics`.

* `tags`: Mainly used to describe music styles, scenes, etc. Similar to prompts we use for other generations, they primarily describe the overall style and requirements of the audio, separated by English commas
* `lyrics`: Mainly used to describe lyrics, supporting lyric structure tags such as \[verse], \[chorus], and \[bridge] to distinguish different parts of the lyrics. You can also input instrument names for purely instrumental music

You can find rich examples of `tags` and `lyrics` on the [ACE-Step model homepage](https://ace-step.github.io/). You can refer to these examples to try corresponding prompts. This document's prompt guide is organized based on the project to help you quickly try combinations to achieve your desired effect.

### Tags (prompt)

#### Mainstream Music Styles

Use short tag combinations to generate specific music styles

* electronic
* rock
* pop
* funk
* soul
* cyberpunk
* Acid jazz
* electro
* em (electronic music)
* soft electric drums
* melodic

#### Scene Types

Combine specific usage scenarios and atmospheres to generate music that matches the corresponding mood

* background music for parties
* radio broadcasts
* workout playlists

#### Instrumental Elements

* saxophone
* jazz
* piano, violin

#### Vocal Types

* female voice
* male voice
* clean vocals

#### Professional Terms

Use some professional terms commonly used in music to precisely control music effects

* 110 bpm (beats per minute is 110)

* fast tempo

* slow tempo

* loops

* fills

* acoustic guitar

* electric bass

### Lyrics

#### Lyric Structure Tags

* \[outro]
* \[verse]
* \[chorus]
* \[bridge]

#### Multilingual Support

* ACE-Step V1 supports multiple languages. When used, ACE-Step converts different languages into English letters and then generates music.
* In ComfyUI, we haven't fully implemented the conversion of all languages to English letters. Currently, only [Japanese hiragana and katakana characters](https://github.com/Comfy-Org/ComfyUI/commit/5d3cc85e13833aeb6ef9242cdae243083e30c6fc) are implemented.
  So if you need to use multiple languages for music generation, you need to first convert the corresponding language to English letters, and then input the language code abbreviation at the beginning of the `lyrics`, such as Chinese `[zh]`, Korean `[ko]`, etc.

For example:

```
[verse]

[zh]wo3zou3guo4shen1ye4de5jie1dao4
[zh]leng3feng1chui1luan4si1nian4de5piao4liang4wai4tao4
[zh]ni3de5wei1xiao4xiang4xing1guang1hen3xuan4yao4
[zh]zhao4liang4le5wo3gu1du2de5mei3fen1mei3miao3

[chorus]

[verse]​
[ko]hamkke si-kkeuleo-un sesang-ui sodong-eul pihae​
[ko]honja ogsang-eseo dalbich-ui eolyeompus-ileul balaboda​
[ko]niga salang-eun lideum-i ganghan eum-ag gatdago malhaess-eo​
[ko]han ta han tamada ma-eum-ui ondoga eolmana heojeonhanji ijge hae

[bridge]
[es]cantar mi anhelo por ti sin ocultar
[es]como poesía y pintura, lleno de anhelo indescifrable
[es]tu sombra es tan terca como el viento, inborrable
[es]persiguiéndote en vuelo, brilla como cruzar una mar de nubes

[chorus]
[fr]que tu sois le vent qui souffle sur ma main
[fr]un contact chaud comme la douce pluie printanière
[fr]que tu sois le vent qui s'entoure de mon corps
[fr]un amour profond qui ne s'éloignera jamais
```

Currently, ACE-Step supports 19 languages, but the following ten languages have better support:

* English
* Chinese: \[zh]
* Russian: \[ru]
* Spanish: \[es]
* Japanese: \[ja]
* German: \[de]
* French: \[fr]
* Portuguese: \[pt]
* Italian: \[it]
* Korean: \[ko]

<Note>
  The language tags above have not been fully tested at the time of writing this documentation. If any language tag is incorrect, please [submit an issue to our documentation repository](https://github.com/Comfy-Org/docs/issues) and we will make timely corrections.
</Note>

## ACE-Step Related Resources

* [Project Page](https://ace-step.github.io/)
* [Hugging Face](https://huggingface.co/ACE-Step/ACE-Step-v1-3.5B)
* [GitHub](https://github.com/ace-step/ACE-Step)
* [Training Scripts](https://github.com/ace-step/ACE-Step?tab=readme-ov-file#-train)


# ComfyUI ACE-Step 1.5 Music Generation Guide
Source: https://docs.comfy.org/tutorials/audio/ace-step/ace-step-v1-5

Learn how to use ACE-Step 1.5 for AI music generation in ComfyUI. Complete guide with workflows, model downloads, and setup instructions for ComfyUI.

## About ACE-Step 1.5 in ComfyUI

ACE-Step 1.5 is a major update to the open-source music generation model, now natively supported in ComfyUI. It brings commercial-grade quality to your local machine with a novel hybrid architecture where a Language Model acts as an omni-capable planner, transforming simple user queries into comprehensive song blueprints.

**ACE-Step 1.5 Model highlights:**

* **Commercial-grade quality**: Achieves quality beyond most commercial music models, scoring 4.72 on musical coherence
* **Blazing fast generation**: Generate a full 4-minute song in \~1 second on RTX 5090, or under 10 seconds on RTX 3090 with ComfyUI
* **50+ language support**: Strong support for English, Chinese, Japanese, Korean, Spanish, German, French, Portuguese, Italian, and Russian
* **LoRA fine-tuning**: Supports lightweight personalization through LoRA training in ComfyUI

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Option 1: All-in-One Checkpoint (Recommended)

The AIO version packages all models into a single checkpoint file, making it easier to download and manage.

### ACE-Step 1.5 Music Generation AIO

Input style tags and lyrics to generate a full song. The workflow uses the ACE-Step 1.5 model to produce commercial-grade music in under 10 seconds on consumer hardware.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_ace_step_1_5_checkpoint&utm_source=docs&utm_medium=referral&utm_campaign=ace-step-v1-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_ace_step_1_5_checkpoint.json">
    Download JSON or search "ACE-Step 1.5 Music Generation AIO" in Template Library
  </Card>
</CardGroup>

### AIO Model Download

<Card title="ace_step_1.5_turbo_aio.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files/blob/main/checkpoints/ace_step_1.5_turbo_aio.safetensors">
  All-in-one checkpoint file (recommended for most users).
</Card>

**AIO Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 checkpoints/
│       └── ace_step_1.5_turbo_aio.safetensors
```

## Option 2: Split Model Files

The split version allows you to download individual model components separately.

### ACE-Step 1.5 Music Generation Workflow

Input a text prompt describing the music style and optional lyrics. Generate a full, high-quality audio song in under 10 seconds on consumer hardware.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_ace_step_1_5_split&utm_source=docs&utm_medium=referral&utm_campaign=ace-step-v1-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_ace_step_1_5_split.json">
    Download JSON or search "ACE-Step 1.5 Music Generation Workflow" in Template Library
  </Card>
</CardGroup>

### Split Model Downloads

<CardGroup>
  <Card title="acestep_v1.5_turbo.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files/blob/main/split_files/diffusion_models/acestep_v1.5_turbo.safetensors">
    Diffusion model.
  </Card>

  <Card title="qwen_0.6b_ace15.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files/blob/main/split_files/text_encoders/qwen_0.6b_ace15.safetensors">
    Text encoder (0.6B).
  </Card>

  <Card title="qwen_1.7b_ace15.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files/blob/main/split_files/text_encoders/qwen_1.7b_ace15.safetensors">
    Text encoder (1.7B).
  </Card>

  <Card title="ace_1.5_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files/blob/main/split_files/vae/ace_1.5_vae.safetensors">
    VAE model.
  </Card>
</CardGroup>

**Split Models Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── acestep_v1.5_turbo.safetensors
│   ├── 📂 text_encoders/
│   │   ├── qwen_0.6b_ace15.safetensors
│   │   └── qwen_1.7b_ace15.safetensors
│   └── 📂 vae/
│       └── ace_1.5_vae.safetensors
```

## ACE-Step 1.5 Key Features in ComfyUI

### Chain-of-Thought Planning

The ACE-Step 1.5 model synthesizes metadata, lyrics, and captions via Chain-of-Thought reasoning to guide the diffusion process, resulting in more coherent long-form compositions.

### Hybrid LM + DiT Architecture

ACE-Step 1.5 combines a Language Model that plans the song structure with a Diffusion Transformer (DiT) that handles audio synthesis, all running natively in ComfyUI.

## Coming Soon to ComfyUI

These features are available in ACE-Step 1.5 but not yet supported in ComfyUI:

* **Cover**: Give the model any song as input along with a new prompt and lyrics, and it will reimagine the track in a completely different style
* **Repaint**: Select a segment, regenerate just that section, and the model stitches it back in while keeping everything else untouched

## ACE-Step 1.5 ComfyUI Related Resources

* [Project Page](https://ace-step.github.io/)
* [Hugging Face](https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files)
* [GitHub](https://github.com/ace-step/ACE-Step)
* [Blog Post](https://blog.comfy.org/p/ace-step-15-is-now-available-in-comfyui)


# MiniMax Music 3 in ComfyUI: AI Music Generation
Source: https://docs.comfy.org/tutorials/audio/minimax/minimax-music-3

Learn how to use MiniMax Music 3 in ComfyUI to generate complete songs up to 5 minutes long from a structured music caption and lyrics.

<img alt="MiniMax Music 3" />

[MiniMax Music 3](https://github.com/MiniMax-AI/MiniMax-Music3) is MiniMax's music generation model for creating complete songs up to **five minutes** long. Conditioned on lyrics and a detailed music description, it produces structurally coherent songs with expressive vocals, evolving arrangements, and stable long-form audio quality. You can explore generated examples on the [official demo page](https://minimax-ai.github.io/music3-demo/).

MiniMax Music 3 uses a hierarchical autoregressive architecture with an 8B global LLM for long-range musical structure, a 0.6B local LLM for frame-level acoustic detail, and a continuous hidden-state synthesis system based on Flow Matching and a Flow-VAE. It outputs 32 kHz, 16-bit stereo audio. The model weights are available under the [MiniMax-Music3 Community License](https://huggingface.co/MiniMaxAI/MiniMax-Music3/blob/main/LICENSE).

ComfyUI natively supports MiniMax Music 3 with an official example workflow: **MiniMax Music 3 Text to Music**.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<Note>
  The [Community License](https://huggingface.co/MiniMaxAI/MiniMax-Music3/blob/main/LICENSE) allows commercial use for companies under 20 million USD in yearly revenue. Above that threshold, commercial use requires a [MiniMax commercial license](https://comfy.org/minimax/license), available through Comfy, the only official reseller.
</Note>

## Key features

* **Complete songs**: Generate full tracks up to 5 minutes with intro, verse, pre-chorus, chorus, bridge, instrumental break, and outro
* **Two-input control**: A structured **Caption** defines the music style, mood, vocals, and arrangement, while **Lyrics** with section tags (`[Intro]`, `[Verse]`, `[Chorus]`, `[Bridge]`, `[Instrumental]`, `[Outro]`) control the song structure
* **Long-range coherence**: Maintains musical themes, rhythm, vocal identity, and arrangement progression across long sequences
* **Expressive vocals**: Natural vocal synthesis with control over melody, pronunciation, and layered harmonies
* **Open weights**: Run locally in ComfyUI with full control over every parameter

## Getting started

MiniMax Music 3 is supported in ComfyUI with open weights. To get started:

1. Update ComfyUI to the latest version
2. Go to **Template Library** > **Audio** > choose the **MiniMax Music 3** workflow
3. Follow the pop-up to download models and run the workflow

The ComfyUI-ready model files (repacked diffusion model, text encoder, and VAE) are hosted on Hugging Face in the [Comfy-Org/MiniMax-Music-3](https://huggingface.co/Comfy-Org/MiniMax-Music-3) repository. The original model weights are available from the [MiniMaxAI/MiniMax-Music3](https://huggingface.co/MiniMaxAI/MiniMax-Music3) repository.

## MiniMax Music 3 Text to Music workflow

Generate a complete song from a structured music caption and lyrics.

<img alt="MiniMax Music 3 Text to Music workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_minimax_music_3&utm_source=docs&utm_medium=referral&utm_campaign=minimax-music-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_minimax_music_3.json">
    Download JSON or search "MiniMax Music 3" in Template Library
  </Card>
</CardGroup>

The workflow takes two text inputs and produces a finished song. The text encoder generates the acoustic conditioning sequence from the caption and lyrics, the diffusion model synthesizes the audio latent, and the audio VAE decodes it into a 32 kHz stereo track saved as an MP3.

**Workflow controls**:

* **Caption**: The music description. Write it in three sections: **Global Metadata** (genre, BPM, key, scale, emotional progression, listening scenario, production profile), **Vocal Details** (vocal gender, timbre, performance style, harmonies, vocal effects), and **Arrangement** (primary and secondary instruments, groove, bass, percussion, textures, spatial effects). The more specific, the closer the result
* **Lyrics**: The words to be sung, with section tags such as `[Intro]`, `[Verse]`, `[Chorus]`, `[Bridge]`, `[Instrumental]`, and `[Outro]`. Tags are the structural instructions; the lyric text conveys the mood
* **max\_duration**: Target song length in seconds (the template defaults to 60 seconds; the model supports up to about 300 seconds / 5 minutes). Longer songs take more time and VRAM
* **seed**: Random seed for the generation. Keep it fixed to reproduce the same song; change it to get a different take
* **tiled\_decode**: Decode the audio VAE in overlapping tiles to cut VRAM usage, helpful for long songs on low-VRAM GPUs. Slightly slower with a small risk of seams at tile boundaries. Turn it off on high-VRAM GPUs for best quality

### Model downloads

<CardGroup>
  <Card title="Diffusion Model (FP16)" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-Music-3/resolve/main/diffusion_models/minimax_music3_dit_fp16.safetensors">
    minimax\_music3\_dit\_fp16.safetensors → ComfyUI/models/diffusion\_models/
  </Card>

  <Card title="Diffusion Model (INT8)" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-Music-3/resolve/main/diffusion_models/minimax_music3_dit_int8_convrot.safetensors">
    minimax\_music3\_dit\_int8\_convrot.safetensors → ComfyUI/models/diffusion\_models/ (for low VRAM)
  </Card>

  <Card title="Text Encoder (INT8)" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-Music-3/resolve/main/text_encoders/minimax_music3_text_encoder_pruned_int8_convrot.safetensors">
    minimax\_music3\_text\_encoder\_pruned\_int8\_convrot.safetensors → ComfyUI/models/text\_encoders/
  </Card>

  <Card title="VAE" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-Music-3/resolve/main/vae/minimax_music3_dav.safetensors">
    minimax\_music3\_dav.safetensors → ComfyUI/models/vae/
  </Card>
</CardGroup>

Place the files in the following directories:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── minimax_music3_dit_fp16.safetensors
│   │   └── minimax_music3_dit_int8_convrot.safetensors
│   ├── 📂 text_encoders/
│   │   └── minimax_music3_text_encoder_pruned_int8_convrot.safetensors
│   └── 📂 vae/
│       └── minimax_music3_dav.safetensors
```

### Prompting tips

1. **Structure the caption in three sections**: Global Metadata, Vocal Details, and Arrangement. The model follows not just a global style but the musical development of the song over time
2. **Use section tags in the lyrics**: `[Intro]`, `[Verse]`, `[Pre-Chorus]`, `[Chorus]`, `[Post-Chorus]`, `[Bridge]`, `[Instrumental]`, `[Solo]`, and `[Outro]` give the model explicit structural control
3. **Keep tags as the only structural instructions**: The tags are executable; the lyric text itself conveys mood, not structure
4. **Balance duration and resources**: Longer songs take more time and VRAM. Use the INT8 diffusion model and tiled decode for long songs on low-VRAM GPUs

#### Prompt writing guide

The [official demo page](https://minimax-ai.github.io/music3-demo/) showcases 26 example tracks across 11 genres (pop, rock, R\&B, hip-hop, dance pop, country, soul, funk, blues, bossa nova, and urban), each with its full structured caption written in the Global Metadata / Vocal Details / Arrangement format. Use them as reference for writing your own captions.

MiniMax also publishes an official [music caption rewriter skill](https://github.com/MiniMax-AI/MiniMax-Music3) that turns a brief music description and optional tagged lyrics into a detailed Music 3.0 structured caption. The skill builds a coherent section-by-section arrangement with global metadata, vocal details, and arrangement descriptions, preserving explicit musical constraints while keeping the lyric text in the lyrics input. Install it with:

```bash theme={null}
npx skills add MiniMax-AI/MiniMax-Music3 --skill music-caption-rewriter
```

## Output

The generated song is saved to `ComfyUI/output/audio/audio_minimax_music3.mp3` (or the filename set in the SaveAudioAdvanced node).


# Stable Audio 1.0 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/audio/stable-audio/stable-audio-1

Guide to using Stability AI's open-source Stable Audio 1.0 model in ComfyUI for text-to-audio generation.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Stable Audio 1.0** is Stability AI's first open-source audio generation model. It takes a text prompt and generates an audio clip. In ComfyUI, it works like a standard text-to-audio pipeline: CLIP encodes the prompt, a KSampler denoises the latent, and the VAE decodes it to audio.

**Related links**:

* [GitHub: Stability-AI/stable-audio-open-1.0](https://github.com/Stability-AI/stable-audio-open-1.0)

## Workflow

### Stable Audio 1.0: Text to Audio

Generate audio from text prompts using Stable Audio.

<img alt="Stable Audio 1.0 text to audio workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_stable_audio_example&utm_source=docs&utm_medium=referral&utm_campaign=stable-audio-1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_stable_audio_example.json">
    Download JSON or search "Stable Audio 1.0: Text to Audio" in Template Library
  </Card>
</CardGroup>

The workflow uses **standard ComfyUI nodes**: no custom nodes required. It loads the Stable Audio 1.0 checkpoint, encodes your prompt via a CLIP text encoder (t5-base), denoises the latent audio with a KSampler, and decodes it to audio through the model's VAE.

**How to use**:

1. **Load the checkpoint**: The `CheckpointLoaderSimple` node uses `stable-audio-open-1.0.safetensors`
2. **Write a prompt**: Enter your description in the `CLIPTextEncode` node (e.g. "heaven church electronic dance music")
3. **Set duration**: Adjust the `EmptyLatentAudio` node's length value (default 47.6 seconds)
4. Click **Run** (`Ctrl/Cmd + Enter`) to generate. The audio will be saved to `ComfyUI/output/audio/`

## Model download

When loading the workflow, ComfyUI will prompt you with download links for any missing models. To set up manually, download the files below and place them in the correct folders.

### Checkpoint

<Card title="stable-audio-open-1.0.safetensors" icon="download" href="https://huggingface.co/StabilityAI/stable-audio-open-1.0/blob/main/stable-audio-open-1.0.safetensors">
  2.3GB. Place in models/checkpoints/
</Card>

Place the checkpoint in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 checkpoints/
│       └── stable-audio-open-1.0.safetensors
```

### Text encoder

<Card title="t5-base.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/t5-base/blob/main/t5-base.safetensors">
  Text encoder for prompt conditioning. Place in models/text\_encoders/
</Card>

Place the text encoder in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 text_encoders/
│       └── t5-base.safetensors
```

After placing the files, press **R** in ComfyUI to refresh nodes and load the latest models.


# Stable Audio 3 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/audio/stable-audio/stable-audio-3

Run Stability AI's open-source Stable Audio 3 in ComfyUI for text-to-audio generation, with Qwen prompt expansion and category-aware reprompting.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Stable Audio 3** ([GitHub](https://github.com/Stability-AI/stable-audio-3)) is Stability AI's latest open-source audio generation model, trained on fully licensed music data and licensed for commercial use. It uses a dedicated subgraph node to produce high-quality stereo audio (including music, sound effects, and instruments) from text descriptions, with optional Qwen-powered category-aware reprompting.

Stable Audio 3 comes in three variants:

* **Small-SFX**: Sound effects and short ambiance, up to 2:00. Small enough to run on CPU.
* **Small-Music**: Short music loops, on-device-friendly, up to 2:00.
* **Medium**: Longer tracks with stronger structure and musicality, up to \~6:20. Requires a GPU.

**Related links**:

* [GitHub: Stability-AI/stable-audio-3](https://github.com/Stability-AI/stable-audio-3)
* [Hugging Face (Comfy-Org/stable-audio-3)](https://huggingface.co/Comfy-Org/stable-audio-3)
* [Blog: Announcement](https://blog.comfy.org/p/stable-audio-3-day-0-support)

## Available workflows

### Stable Audio 3.0 Medium

Input a short text idea, optional duration, seed, and category. Generate stereo audio (music, SFX, or instruments) using Stable Audio 3 with optional AI-driven text expansion.

<img alt="Stable Audio 3 Medium workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_stable_audio_3_medium&utm_source=docs&utm_medium=referral&utm_campaign=stable-audio-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_stable_audio_3_medium.json">
    Download JSON or search "Stable Audio 3.0 Medium" in Template Library
  </Card>
</CardGroup>

The **Stable Audio 3 Medium** workflow is a full-featured text-to-audio generation pipeline. You provide a short text idea, optional duration, seed, and category. The workflow expands your prompt using Qwen with a **category-aware reprompt template**, then generates stereo audio via the Stable Audio 3 checkpoint.

**How to use**:

1. **Text idea**: Enter a short description of the sound, music, or effect you want (e.g. "upbeat electronic dance track with heavy bass")
2. **Duration**: Set the desired clip length in seconds (default varies)
3. **Seed**: Control reproducibility by adjusting the seed value
4. **Category**: Choose a reprompt preset: **Music**, **Instrument**, **SFX**, or **One-shot**
5. **Enable reprompt**: Toggle `use_reprompt` on to let Qwen expand your short idea into a detailed prompt before generation
6. Click **Run** (`Ctrl/Cmd + Enter`) to generate. The audio will be saved to `ComfyUI/output/audio/`

### Stable Audio 3.0 Medium Base

Input a short text description of a sound, music, or effect. The workflow expands your prompt with Qwen and generates a stereo audio clip from Stable Audio 3.

<img alt="Stable Audio 3 Medium Base workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_stable_audio_3_medium_base&utm_source=docs&utm_medium=referral&utm_campaign=stable-audio-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_stable_audio_3_medium_base.json">
    Download JSON or search "Stable Audio 3.0 Medium Base" in Template Library
  </Card>
</CardGroup>

A simplified version of Stable Audio 3 without Qwen reprompt expansion. It expects a complete text prompt and passes it directly to the model. Use this when you already have a detailed prompt and want faster generation.

**How to use**:

1. **Text prompt**: Enter a detailed description of the audio you want
2. **Duration**: Set the clip length in seconds
3. **Seed**: Control reproducibility
4. Click **Run** (`Ctrl/Cmd + Enter`) to generate

## Model download

When loading the workflow, ComfyUI will prompt you with download links for any missing models. To set up manually, download the files below and place them in the correct folders.

### Checkpoints

<CardGroup>
  <Card title="stable_audio_3_medium.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/stable-audio-3/blob/main/checkpoints/stable_audio_3_medium.safetensors">
    For the Medium workflow. Place in models/checkpoints/
  </Card>

  <Card title="stable_audio_3_medium_base.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/stable-audio-3/blob/main/checkpoints/stable_audio_3_medium_base.safetensors">
    For the Medium Base workflow. Place in models/checkpoints/
  </Card>
</CardGroup>

Place checkpoints in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 checkpoints/
│       ├── stable_audio_3_medium.safetensors
│       └── stable_audio_3_medium_base.safetensors
```

### Text encoders

<CardGroup>
  <Card title="t5gemma_b_b_ul2.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/stable-audio-3/blob/main/text_encoders/t5gemma_b_b_ul2.safetensors">
    Required for all Stable Audio 3 workflows. Place in models/text\_encoders/
  </Card>

  <Card title="qwen3.5_2b_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/blob/main/text_encoders/qwen3.5_2b_bf16.safetensors">
    Required for the Medium workflow (Qwen reprompt). Place in models/text\_encoders/
  </Card>
</CardGroup>

Place text encoders in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 text_encoders/
│       ├── t5gemma_b_b_ul2.safetensors
│       └── qwen3.5_2b_bf16.safetensors
```

After placing the files, press **R** in ComfyUI to refresh nodes and load the latest models.


# ComfyUI YuE2 Music Generation Guide
Source: https://docs.comfy.org/tutorials/audio/yue2/yue2

Generate complete songs with vocals in ComfyUI using the open-source YuE2 model: text to music with ABC planning, and melody-preserving covers with SheetSage2.

YuE2 is an open-source music generation model from Multimodal Art Projection (m-a-p) that turns a style prompt and lyrics into a complete song with vocals and instrumental accompaniment. A 3B-parameter model, it generates full song structures with sections such as intro, verse, chorus, bridge, and outro, and supports multiple singing languages including English, Chinese, and Japanese.

What sets YuE2 apart from most text-to-music systems is its editable composition step. Before generating audio, YuE2 can first write a symbolic music plan in ABC notation: a melody, optionally with chords, that you can inspect and edit. The final song is then rendered from that plan. This makes results easier to steer than one-shot audio generation, and it also powers the cover workflow below, where a reference song is transcribed into the same notation and re-sung with new style and lyrics.

YuE2 is supported natively in ComfyUI. Update to the latest version of [ComfyUI](https://github.com/comfyanonymous/ComfyUI) before starting. ComfyUI v0.35.0 or later is required, and v0.35.1 or later is recommended on AMD GPUs.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Text to Music

Generate a complete song from a music style description and your own lyrics. With ABC planning enabled, YuE2 first creates an editable symbolic music plan (melody and optionally chords), then generates the final audio from that plan.

<img alt="YuE2 text to music workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_yue2_text2music.json">
    Download JSON or search "YuE2: Text to Music" in Template Library
  </Card>
</CardGroup>

### 1. Steps to Run

1. Write a description of the music you want in **Style**
2. Enter your song lyrics in **Lyrics** using section tags such as `[Verse]` and `[Chorus]`
3. Choose a planning **Mode**: `full` generates melody and chords, `melody` generates the melody only
4. Set the **Max Duration** of the song
5. Queue the workflow to generate the song

### 2. Model Download

<Card title="YuE2 checkpoint" icon="download" href="https://huggingface.co/Comfy-Org/YuE2/blob/main/checkpoints/yue2_3b_int8_convrot.safetensors">
  yue2\_3b\_int8\_convrot.safetensors
</Card>

Place the file in the following directory:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 checkpoints/
│       └── yue2_3b_int8_convrot.safetensors
```

### 3. Writing the Style

Describe the main musical characteristics. Useful elements include:

* **Genre**: pop, jazz, rock, electronic, folk
* **Vocals**: warm female vocal, expressive male vocal, soft vocals
* **Language**: English, Chinese, Japanese, and more
* **Tempo**: 90 BPM, slow, upbeat
* **Instruments**: piano, electric guitar, bass, drums, synths

Example:

> English, warm female vocal, contemporary pop, 96 BPM, piano, rounded electric bass, restrained drums, clear diction

Keep musical instructions in **Style** rather than in the lyrics.

### 4. Writing the Lyrics

Use section tags to describe the song structure:

```
[Verse]
Morning light across the window
City waking down below

[Chorus]
Run with me into the sunlight
Leave the shadows far behind
```

You can structure the song with sections such as `[Verse]`, `[Chorus]`, `[Bridge]`, and `[Outro]`. Put only the words intended to be sung in the lyrics field.

### 5. ABC Planning

The **Mode** option controls the symbolic planning step:

* **full**: creates a plan with melody and chords before generating the song. Recommended for general text-to-music generation.
* **melody**: creates a melody-only plan and lets the accompaniment be generated more freely.

Leaving the **abc** input empty disables planning and generates music directly from Style and Lyrics.

### 6. Max Duration

**Max Duration** sets the maximum length of the generated song in seconds, up to 900. The generation budget is 25 semantic tokens per second of requested duration, and sampling stops as soon as the model writes the song's end token, so a song whose structure finishes early can end well before the limit. The Text to Music template sets this to 120 seconds, and Music Cover keeps the node's 360-second default.

The requested duration is capped by the model's context. When the style, lyrics, and ABC plan claim more of the context than the run can spare, ComfyUI lowers the budget to what is left and reports it in the console: `YuE2 music budget reduced to ... tokens (... seconds) to fit the prompt.` A long prompt therefore shortens the song instead of failing the run. When nothing is left at all, the run stops with `YuE2 prompt leaves no room for music; shorten the style, lyrics, or ABC.`

When the console reports a `YuE2 semantic reached its token budget before the end token.` warning, the model ran out of budget before it wrote the song's end token, and the rendered audio can stop abruptly instead of finishing the song, because those semantic tokens are the song content the audio stage renders. Raise **Max Duration** to give the song more room. If the same run also logged a budget reduction, the prompt is already using the available context, so shorten the style, lyrics, or ABC plan instead. The notation phase reports the same warning as `YuE2 abc reached its token budget before the end token.`, where the score itself is cut short and the YuE2 Generate ABC node's `max_abc_tokens` is the budget to raise.

### 7. Guidance Scale

The **YuE2 Generate Music** node has an advanced `cfg_scale` option (0 to 100, default 1.0) that sets autoregressive guidance on style and lyrics:

* `1.0` disables guidance, which matches the ABC workflow. The included templates keep this default
* `1.01` matches the guidance scale the model used before this option was added, for runs where planning is disabled (`abc` left empty)

## Music Cover

Create a new version of an existing song. This workflow uses SheetSage2 to transcribe the melody from a reference audio into an editable ABC score, then uses YuE2 to regenerate the song with a new style and lyrics.

<img alt="YuE2 music cover workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_yue2_music_cover.json">
    Download JSON or search "YuE2: Music Cover" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadAudio` node:

<CardGroup>
  <Card title="yue2_reference_song.flac" icon="music" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/yue2_reference_song.flac">
    `LoadAudio` node · `yue2_reference_song.flac`
  </Card>
</CardGroup>

### 1. Steps to Run

1. Load a reference song in **Audio**
2. Describe the new musical direction in **Style**
3. Enter the lyrics you want to sing in **Lyrics**
4. Queue the workflow to generate a new cover version

The reference audio provides the melody, while YuE2 creates a new performance and arrangement based on your Style and Lyrics.

### 2. Model Downloads

<CardGroup>
  <Card title="YuE2 checkpoint" icon="download" href="https://huggingface.co/Comfy-Org/YuE2/blob/main/checkpoints/yue2_3b_int8_convrot.safetensors">
    yue2\_3b\_int8\_convrot.safetensors
  </Card>

  <Card title="SheetSage2 audio encoder" icon="download" href="https://huggingface.co/Comfy-Org/YuE2/blob/main/audio_encoders/sheetsage2_bf16.safetensors">
    sheetsage2\_bf16.safetensors
  </Card>
</CardGroup>

Place the files in the following directories:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── yue2_3b_int8_convrot.safetensors
│   └── 📂 audio_encoders/
│       └── sheetsage2_bf16.safetensors
```

### 3. How the Cover Works

The workflow does not feed the reference audio to YuE2 directly. Instead:

```
Reference Audio
    ↓
SheetSage2 (transcription)
    ↓
Melody ABC score
    ↓
YuE2 (generation with new Style and Lyrics)
```

Because the connection to the original song is the melody, covers work best when the new lyrics stay reasonably close to the original phrasing and syllable count.

### 4. Writing the Style and Lyrics

Describe the target musical style clearly. Useful elements include genre, vocal type, language, tempo, instruments, and mood:

> English, soulful jazz-pop, expressive male vocal, relaxed 88 BPM, Rhodes piano, upright bass, brushed drums, warm saxophone, intimate late-night atmosphere

Use the same `[Verse]` / `[Chorus]` / `[Bridge]` / `[Outro]` section tags as the text-to-music workflow. For better melody matching, keep the new lyrics close in length to the original lines.


# Cosmos Predict2 Text-to-Image ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/image/cosmos/cosmos-predict2-t2i

This guide demonstrates how to complete Cosmos-Predict2 text-to-image workflow in ComfyUI

Cosmos-Predict2 is NVIDIA's next-generation physical world foundation model, specifically designed for high-quality visual generation and prediction tasks in physical AI scenarios.
The model features exceptional physical accuracy, environmental interactivity, and detail reproduction capabilities, enabling realistic simulation of complex physical phenomena and dynamic scenes.

Cosmos-Predict2 supports various generation methods including Text-to-Image (Text2Image) and Video-to-World (Video2World), and is widely used in industrial simulation, autonomous driving, urban planning, scientific research, and other fields.

GitHub:[Cosmos-predict2](https://github.com/nvidia-cosmos/cosmos-predict2)
huggingface: [Cosmos-Predict2](https://huggingface.co/collections/nvidia/cosmos-predict2-68028efc052239369a0f2959)

This guide will walk you through completing **text-to-image** workflow in ComfyUI.

For the video generation section, please refer to the following part:

<Card title="Cosmos Predict2 Video Generation" icon="book" href="/tutorials/video/cosmos/cosmos-predict2-video2world">
  Using Cosmos-Predict2  for video generation
</Card>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>


# ComfyUI Ideogram 4.0 Open-Source Model Tutorial
Source: https://docs.comfy.org/tutorials/image/ideogram/ideogram-v4

Ideogram 4.0 in ComfyUI: run Ideogram's open-source text-to-image model locally, with accurate text rendering and JSON or natural-language style prompts.

Ideogram 4.0 is the latest text-to-image model from Ideogram, released as an open-source model that runs entirely on your own hardware. It delivers superior photorealistic quality, accurate text rendering, and precise style control. You can use either plain natural language or **structured JSON prompts** for fine-grained control over layout, colors, and in-image text.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Ideogram 4.0 Text-to-Image Workflow

### Ideogram v4: Text to Image

Input a text prompt or structured JSON description. Generate an image with precise layout, color, and style control using Ideogram 4.0.

<img alt="Ideogram 4.0 text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_ideogram4_t2i&utm_source=docs&utm_medium=referral&utm_campaign=ideogram-v4">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_ideogram4_t2i.json">
    Download JSON or search "Ideogram v4: Text to Image" in Template Library
  </Card>
</CardGroup>

**Example output**

![Ideogram 4.0 example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_ideogram4_t2i.png)

### Prompt Format

The open-source workflow supports two prompt modes:

1. **Natural language**: Quick and easy, best for simple ideas
2. **Structured JSON**: For precise control over layout, colors, and style

The workflow includes a prompt construction template that you can use with any LLM to generate matching JSON prompts.

A note inside the workflow explains:

> The model is trained on structured JSON captions (scene summary, style block, background, and optional per-object descriptions with bounding boxes and hex color palettes). Official inference validates prompts against that schema.

### Ideogram 4.0 model downloads

You can find all repackaged model files at [Comfy-Org/Ideogram-4](https://huggingface.co/Comfy-Org/Ideogram-4) on Hugging Face.

<CardGroup>
  <Card title="ideogram4_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Ideogram-4/blob/main/diffusion_models/ideogram4_fp8_scaled.safetensors">
    Diffusion model for Ideogram 4.0 (\~13.8 GB). Place in <code>models/diffusion\_models/</code>
  </Card>

  <Card title="ideogram4_unconditional_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Ideogram-4/blob/main/diffusion_models/ideogram4_unconditional_fp8_scaled.safetensors">
    Unconditional diffusion model for Ideogram 4.0 (\~13.8 GB). Place in <code>models/diffusion\_models/</code>
  </Card>

  <Card title="qwen3vl_8b_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3-VL/blob/main/text_encoders/qwen3vl_8b_fp8_scaled.safetensors">
    Text encoder for Ideogram 4.0 (\~8 GB). Place in <code>models/text\_encoders/</code>
  </Card>

  <Card title="gemma4_e4b_it_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/gemma-4/blob/main/text_encoders/gemma4_e4b_it_fp8_scaled.safetensors">
    Text encoder for Ideogram 4.0 (\~2 GB). Place in <code>models/text\_encoders/</code>
  </Card>

  <Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/flux2-dev/blob/main/split_files/vae/flux2-vae.safetensors">
    VAE for Ideogram 4.0 (\~335 MB). Place in <code>models/vae/</code>
  </Card>
</CardGroup>

**Model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── ideogram4_fp8_scaled.safetensors
│   │   └── ideogram4_unconditional_fp8_scaled.safetensors
│   ├── 📂 text_encoders/
│   │   ├── qwen3vl_8b_fp8_scaled.safetensors
│   │   └── gemma4_e4b_it_fp8_scaled.safetensors
│   └── 📂 vae/
│       └── flux2-vae.safetensors
```

<CardGroup>
  <Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
    This workflow uses Subgraph nodes for modular processing. Check the Subgraph documentation to learn how to customize and extend.
  </Card>
</CardGroup>

### Workflow Steps

1. Download and place the models in the correct directories (see table above)
2. Download and drag the workflow file into ComfyUI
3. Enter your prompt (natural language or structured JSON) in the Ideogram4 subgraph node
4. (Optional) Adjust resolution using the `ResolutionSelector` node
5. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
6. View the result in the `Save Image` node. Output files are saved to `ComfyUI/output/`

### Note on Safety Filter

If you see "Image blocked by safety filter", this is Ideogram 4.0's built-in safety filter. Non-JSON (plain-text) prompts have a higher false-positive rate. Using structured JSON prompts reduces the chance of your prompt being blocked.

For more details, see [Ideogram 4's official prompting guide](https://github.com/ideogram-oss/ideogram4/blob/main/docs/prompting.md#safety-filter).

## Live Conversation with Ideogram & ComfyOrg

A special live conversation with Mohammad Norouzi (CEO, Ideogram) and Yoland Yan (CEO, ComfyOrg), hosted by Purz & Rob.

<iframe title="Ideogram 4.0 Live Conversation" />


# Krea-2 ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/krea/krea-2

Krea 2 is a text-to-image model designed for high aesthetic quality and stylistic diversity. It comes in two variants: RAW (base) and Turbo (distilled).

<iframe title="krea.ai 2 is back and this time the weights are OPEN." />

**Krea 2** is an image generation model from [Krea AI](https://www.krea.ai), trained from scratch and focused on creative and stylistic exploration.

Krea 2 ships as two models designed to work together: **train LoRAs on RAW, run inference on Turbo**:

* **Krea 2 RAW**: the base model with full-step sampling (52 steps). No distillation, diverse and highly malleable, ideal for fine-tuning and LoRA training.
* **Krea 2 Turbo**: an 8-step distilled checkpoint for fast, high-quality generation. LoRAs trained on RAW apply seamlessly to Turbo.

**License**: [Krea AI Community License](https://www.krea.ai/krea-2-licensing)

## Watch the Launch Event

<iframe title="Krea 2 Live Launch Event" />

To learn more about Krea 2, the story behind its development, its capabilities, and what it means for the open-source ecosystem, watch the launch event recording above (featuring Victor Perez, Miguel Lara, and ComfyAnonymous).

## Available Model Weights

Krea 2 is available in two variants:

* **Krea 2 RAW**: the base model with full-step sampling (52 steps). Designed for diversity and malleability, best for fine-tuning and LoRA training.
* **Krea 2 Turbo**: an 8-step distilled checkpoint built for fast, high-quality generation. LoRAs trained on RAW apply seamlessly to Turbo.

**Related Links**:

* [Krea 2 on Hugging Face (RAW)](https://huggingface.co/krea/Krea-2-Raw)
* [Krea 2 on Hugging Face (Turbo)](https://huggingface.co/krea/Krea-2-Turbo)
* [Comfy-Org/Krea-2 (ComfyUI models)](https://huggingface.co/Comfy-Org/Krea-2)
* [Official GitHub repository](https://github.com/krea-ai/krea-2)
* [Prompting guidelines](https://github.com/krea-ai/krea-2/blob/main/docs/prompting.md)
* [Technical report](https://www.krea.ai/blog/krea-2-technical-report)

## Krea-2 Turbo text-to-image workflow

### Krea-2: Text to Image

Generate images from text prompts using Krea 2, a foundation model built for aesthetic quality and creative control. It focuses on rendering expressive, stylistically diverse images.

<img alt="Krea-2 Turbo text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_krea2_turbo_t2i&utm_source=docs&utm_medium=referral&utm_campaign=krea-2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_krea2_turbo_t2i.json">
    Download JSON or search "Krea-2" in Template Library
  </Card>
</CardGroup>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

The workflow is organized into a few parts:

1. **Text to Image (Krea-2 Turbo) subgraph**: the core generation pipeline, containing model loading, prompt handling, sampling, and VAE decode
2. **ResolutionSelector**: choose your desired output resolution. Krea 2 supports outputs from 1K to 2K. Set the megapixels value to 2.0 to get 2K resolution.
3. **CustomCombo (LoRA selector)**: a pre-built trigger word selector for the available style LoRAs. If you download additional LoRAs, you can customize this selector and pair them with the corresponding LoRA files accordingly.
4. **SaveImage**: saves the generated image

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Single-click generation

At its simplest, just enter a text prompt in the subgraph, select a resolution, and click **Queue Prompt**. The defaults (8 steps, prompt enhancement enabled, no LoRA) produce a high-quality image with minimal configuration.

### Workflow controls

The **Text to Image (Krea-2 Turbo)** subgraph exposes the following controls:

| Control | Description |
| - | - |
| **Text String (User Prompt)** | The text prompt describing the image you want to generate |
| **prompt\_enhance** | Toggle LLM-powered prompt expansion on/off |
| **LLM\_max\_token** | Maximum token length for prompt enhancement |
| **Width / Height** | Output resolution (controlled by ResolutionSelector) |
| **Seed** | Random seed for reproducibility |
| **enable\_lora?** | Enable or disable style LoRA |
| **LoRA Strength** | Strength of the applied style LoRA |
| **LoRA Trigger Word** | Auto-populated trigger word for the selected LoRA |

### Style LoRAs

Krea also released a collection of style LoRAs for Krea 2. Select one in the **CustomCombo** node and enable `enable_lora?` in the subgraph to apply the style:

| LoRA | Trigger Word | Recommended Strength | Download |
| - | - | :-: | - |
| krea2\_darkbrush | monochrome ink wash style | 1.0 | [Download](https://huggingface.co/Comfy-Org/Krea-2/blob/main/loras/krea2_darkbrush.safetensors) |
| krea2\_dotmatrix | monochrome stippling style | 1.0 | [Download](https://huggingface.co/Comfy-Org/Krea-2/blob/main/loras/krea2_dotmatrix.safetensors) |
| krea2\_kidsdrawing | naive expressive sketch style | 1.0 | [Download](https://huggingface.co/Comfy-Org/Krea-2/blob/main/loras/krea2_kidsdrawing.safetensors) |
| krea2\_neondrip | textured abstract style | 1.0 | [Download](https://huggingface.co/Comfy-Org/Krea-2/blob/main/loras/krea2_neondrip.safetensors) |
| krea2\_rainywindow | rainy window style | 1.0 | [Download](https://huggingface.co/Comfy-Org/Krea-2/blob/main/loras/krea2_rainywindow.safetensors) |
| krea2\_retroanime | purple retro anime style | 1.0 | [Download](https://huggingface.co/Comfy-Org/Krea-2/blob/main/loras/krea2_retroanime.safetensors) |
| krea2\_softwatercolor | art deco watercolor style | 1.0 | [Download](https://huggingface.co/Comfy-Org/Krea-2/blob/main/loras/krea2_softwatercolor.safetensors) |
| krea2\_sunsetblur | ethereal motion blur style | 1.0 | [Download](https://huggingface.co/Comfy-Org/Krea-2/blob/main/loras/krea2_sunsetblur.safetensors) |
| krea2\_vintagetarot | vintage tarot style | 1.0 | [Download](https://huggingface.co/Comfy-Org/Krea-2/blob/main/loras/krea2_vintagetarot.safetensors) |

Place the `.safetensors` files in `ComfyUI/models/loras/`.

### Model downloads

For local use, download the ComfyUI-optimized model files from [Comfy-Org/Krea-2](https://huggingface.co/Comfy-Org/Krea-2).

<CardGroup>
  <Card title="Diffusion Model (FP8)" icon="download" href="https://huggingface.co/Comfy-Org/Krea-2/blob/main/diffusion_models/krea2_turbo_fp8_scaled.safetensors">
    krea2\_turbo\_fp8\_scaled.safetensors: Turbo FP8 (recommended for most users)
  </Card>

  <Card title="Text Encoder (FP8)" icon="download" href="https://huggingface.co/Comfy-Org/Krea-2/blob/main/text_encoders/qwen3vl_4b_fp8_scaled.safetensors">
    qwen3vl\_4b\_fp8\_scaled.safetensors: Qwen3VL-4B text encoder
  </Card>

  <Card title="VAE" icon="download" href="https://huggingface.co/Comfy-Org/Krea-2/blob/main/vae/qwen_image_vae.safetensors">
    qwen\_image\_vae.safetensors
  </Card>

  <Card title="Style LoRAs" icon="download" href="https://huggingface.co/collections/krea/krea-2-loras">
    View all style LoRAs on Hugging Face
  </Card>
</CardGroup>

Other model variants (BF16, NVFP4, MXFP8) are also available for users with higher-end hardware.

#### Model storage location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── krea2_turbo_fp8_scaled.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_4b_fp8_scaled.safetensors
│   ├── 📂 vae/
│   │   └── qwen_image_vae.safetensors
│   └── 📂 loras/
│       └── krea2_softwatercolor.safetensors (and other style LoRAs)
```

## Krea-2 Turbo style reference workflow

### Krea-2 Int8: Image Style Reference

Generate images with the Krea-2 Turbo model while referencing the style of 1–2 uploaded images, using the high-performance Int8 Convrot format for fast inference.

<img alt="Krea-2 Turbo style reference workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_krea2_turbo_int8_image_style_reference&utm_source=docs&utm_medium=referral&utm_campaign=krea-2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_krea2_turbo_int8_image_style_reference.json">
    Download JSON or search "Krea-2 Style Reference" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="krea2_reference_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/krea2_reference_image.png">
    `LoadImage` node 69 · `krea2_reference_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="krea2_reference_image.png" />
</div>

**Example output**

![Krea-2 style reference example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_krea2_turbo_int8_image_style_reference.png)

The style reference workflow builds on the Krea-2 Turbo pipeline by adding reference image conditioning. Upload one or more reference images to influence the aesthetic style, mood, and visual direction of the generated output.

The workflow is organized into a few parts:

1. **Image Style Reference (Krea-2 Turbo) subgraph**: the core generation pipeline with style reference support, containing model loading, reference image conditioning, prompt handling, and sampling
2. **LoadImage**: upload your style reference images
3. **ResolutionSelector**: choose your desired output resolution. Krea 2 supports outputs from 1K to 2K.
4. **SaveImage**: saves the generated image

### Using style reference

1. **Upload reference images**: use the **LoadImage** node to load one or more style reference images
2. **Enter your prompt**: type a text description in the subgraph's user prompt input
3. **Select a model variant**: choose the model checkpoint in the subgraph's model selector
4. **Adjust settings**: configure resolution, seed, and optionally enable prompt enhancement
5. **Click Queue**: press `Ctrl+Enter` to generate

This style reference workflow uses a dedicated diffusion model and LoRA. The text encoder and VAE are shared with the text-to-image workflow.

<CardGroup>
  <Card title="Diffusion Model (INT8)" icon="download" href="https://huggingface.co/Comfy-Org/Krea-2/blob/main/diffusion_models/krea2_turbo_int8_convrot.safetensors">
    krea2\_turbo\_int8\_convrot.safetensors
  </Card>

  <Card title="Text Encoder (FP8)" icon="download" href="https://huggingface.co/Comfy-Org/Krea-2/blob/main/text_encoders/qwen3vl_4b_fp8_scaled.safetensors">
    qwen3vl\_4b\_fp8\_scaled.safetensors: Qwen3VL-4B text encoder
  </Card>

  <Card title="VAE" icon="download" href="https://huggingface.co/Comfy-Org/Krea-2/blob/main/vae/qwen_image_vae.safetensors">
    qwen\_image\_vae.safetensors
  </Card>

  <Card title="Style Reference LoRA" icon="download" href="https://huggingface.co/Comfy-Org/Krea-2/blob/main/loras/krea2_style_reference.safetensors">
    krea2\_style\_reference.safetensors
  </Card>
</CardGroup>

Place the files in the following directories:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── krea2_turbo_int8_convrot.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_4b_fp8_scaled.safetensors
│   ├── 📂 vae/
│   │   └── qwen_image_vae.safetensors
│   └── 📂 loras/
│       └── krea2_style_reference.safetensors
```


# Mage-Flow: ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/mage-flow/mage-flow

Mage-Flow is Microsoft's compact 4B model for text-to-image generation and instruction-based image editing in ComfyUI, with native resolutions up to 2K.

**Mage-Flow** is a compact 4B-scale generative stack from Microsoft Research for efficient text-to-image generation and instruction-based image editing. The stack is built from two co-designed components: [Mage-VAE](https://huggingface.co/microsoft/Mage-VAE), a lightweight high-fidelity latent tokenizer, and a Native-Resolution Multimodal Diffusion Transformer (NR-MMDiT) trained with rectified flow matching. Together with native-resolution packing, this shared stack powers two model instantiations: Mage-Flow for text-to-image generation and Mage-Flow-Edit for instruction-based image editing. Each ships in Base, RL-aligned, and 4-step Turbo variants.

Mage-Flow supports native resolutions from 512 to 2048 pixels per side at any aspect ratio, including extreme dimensions like 4:1.

**License**: [MIT](https://github.com/microsoft/Mage/blob/main/LICENSE)

**Related Links**:

* [Hugging Face: microsoft/Mage-Flow](https://huggingface.co/microsoft/Mage-Flow)
* [Hugging Face: Comfy-Org/Mage-Flow (ComfyUI models)](https://huggingface.co/Comfy-Org/Mage-Flow)
* [Official GitHub repository](https://github.com/microsoft/Mage)
* [Technical report (arXiv)](https://arxiv.org/abs/2607.19064)

## Mage-Flow text-to-image workflow

<img alt="Mage-Flow text-to-image workflow output" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_mage_flow_t2i_int8&utm_source=docs&utm_medium=referral&utm_campaign=mage-flow">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_mage_flow_t2i_int8.json">
    Download JSON or search "Mage-Flow" in Template Library
  </Card>
</CardGroup>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

The workflow is organized into a few parts:

1. **Text to Image (Mage-Flow) subgraph**: the core generation pipeline, containing model loading, prompt handling, native-resolution latent generation, sampling, and VAE decode
2. **SaveImageAdvanced**: saves the generated image

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Single-click generation

At its simplest, just enter a text prompt in the subgraph, set your desired resolution, and click **Queue Prompt**. The defaults produce a high-quality image with minimal configuration.

### Using the workflow

1. **Enter a prompt** — type a text description in the subgraph's prompt input
2. **Set resolution** — adjust width and height for your desired output size. Mage-Flow supports native resolutions from 512 to 2048 pixels per side.
3. **Adjust settings** — configure the seed and negative prompt as needed
4. **Click Queue** — press `Ctrl+Enter` to generate

## Mage-Flow Turbo text-to-image workflow

<img alt="Mage-Flow Turbo text-to-image workflow output" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_mage_flow_turbo_t2i_int8&utm_source=docs&utm_medium=referral&utm_campaign=mage-flow">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_mage_flow_turbo_t2i_int8.json">
    Download JSON or search "Mage-Flow Turbo" in Template Library
  </Card>
</CardGroup>

The Turbo variant uses a distilled 4-step checkpoint for faster generation while maintaining high quality. The workflow structure and controls are identical to the base text-to-image workflow, but uses the Turbo diffusion model for lower-latency inference.

## Mage-Flow-Edit image edit workflow

<img alt="Mage-Flow-Edit image edit workflow output" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_mage_flow_edit_int8&utm_source=docs&utm_medium=referral&utm_campaign=mage-flow">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_mage_flow_edit_int8.json">
    Download JSON or search "Mage-Flow-Edit" in Template Library
  </Card>

  <Card title="Download Sample Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/calm_amid_ruin.png">
    Get the example input image for this workflow
  </Card>
</CardGroup>

The image edit workflow uses Mage-Flow-Edit, an instruction-based model that edits images using natural language descriptions. Upload one or more reference images and describe the desired edit.

The workflow is organized into a few parts:

1. **LoadImage**: upload your reference images (up to 3)
2. **Image Edit (Mage-Flow-Edit) subgraph**: the core editing pipeline containing model loading, reference image conditioning, prompt handling, and sampling
3. **ImageCompare**: a side-by-side comparison of the original and edited image
4. **SaveImage**: saves the edited output

### Using image edit

1. **Upload reference images** — use the **LoadImage** node to load the image you want to edit (up to 3 images)
2. **Enter your edit instruction** — type a text description of the edit you want to apply (e.g., "replace the background with a beach scene" or "turn this into a watercolor painting")
3. **Adjust settings** — configure resolution, seed, and other parameters
4. **Click Queue** — press `Ctrl+Enter` to generate

## Mage-Flow-Edit Turbo image edit workflow

<img alt="Mage-Flow-Edit Turbo image edit workflow output" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_mage_flow_edit_turbo_int8&utm_source=docs&utm_medium=referral&utm_campaign=mage-flow">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_mage_flow_edit_turbo_int8.json">
    Download JSON or search "Mage-Flow-Edit Turbo" in Template Library
  </Card>

  <Card title="Download Sample Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/hot_air_balloons_rising.png">
    Get the example input image for this workflow
  </Card>
</CardGroup>

The Turbo variant of the edit workflow uses a distilled 4-step checkpoint for faster editing. The structure and controls match the base edit workflow but with reduced sampling steps.

### Model downloads

For local use, download the ComfyUI-optimized model files from [Comfy-Org/Mage-Flow](https://huggingface.co/Comfy-Org/Mage-Flow).

<CardGroup>
  <Card title="Text Encoder" icon="download" href="https://huggingface.co/Comfy-Org/Mage-Flow/resolve/main/text_encoders/qwen3vl_4b_bf16.safetensors">
    qwen3vl\_4b\_bf16.safetensors: Qwen3VL-4B text encoder
  </Card>

  <Card title="VAE" icon="download" href="https://huggingface.co/Comfy-Org/Mage-Flow/resolve/main/vae/mage_flow_vae_bf16.safetensors">
    mage\_flow\_vae\_bf16.safetensors
  </Card>

  <Card title="Diffusion Model (Base Int8)" icon="download" href="https://huggingface.co/Comfy-Org/Mage-Flow/resolve/main/diffusion_models/mage_flow_int8_convrot.safetensors">
    mage\_flow\_int8\_convrot.safetensors: Base model used in the T2I workflow
  </Card>

  <Card title="Diffusion Model (Turbo Int8)" icon="download" href="https://huggingface.co/Comfy-Org/Mage-Flow/resolve/main/diffusion_models/mage_flow_turbo_int8_convrot.safetensors">
    mage\_flow\_turbo\_int8\_convrot.safetensors: Turbo model used in the Turbo T2I workflow
  </Card>

  <Card title="Diffusion Model (Edit Int8)" icon="download" href="https://huggingface.co/Comfy-Org/Mage-Flow/resolve/main/diffusion_models/mage_flow_edit_int8_convrot.safetensors">
    mage\_flow\_edit\_int8\_convrot.safetensors: Edit model used in the Edit workflow
  </Card>

  <Card title="Diffusion Model (Edit Turbo Int8)" icon="download" href="https://huggingface.co/Comfy-Org/Mage-Flow/resolve/main/diffusion_models/mage_flow_edit_turbo_int8_convrot.safetensors">
    mage\_flow\_edit\_turbo\_int8\_convrot.safetensors: Edit Turbo model used in the Edit Turbo workflow
  </Card>
</CardGroup>

Other model variants (BF16, FP8) are also available for users with different hardware configurations.

Place the files in the following directories:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── mage_flow_int8_convrot.safetensors
│   │   ├── mage_flow_turbo_int8_convrot.safetensors
│   │   ├── mage_flow_edit_int8_convrot.safetensors
│   │   └── mage_flow_edit_turbo_int8_convrot.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_4b_bf16.safetensors
│   └── 📂 vae/
│       └── mage_flow_vae_bf16.safetensors
```


# ComfyUI OmniGen2 Native Workflow Examples
Source: https://docs.comfy.org/tutorials/image/omnigen/omnigen2

ComfyUI OmniGen2 Native Workflow Examples - Unified text-to-image, image editing, and multi-image composition model.

## About OmniGen2

OmniGen2 is a powerful and efficient unified multimodal generation model with approximately **7B** total parameters (3B text model + 4B image generation model). Unlike OmniGen v1, OmniGen2 adopts an innovative dual-path Transformer architecture with completely independent text autoregressive model and image diffusion model, achieving parameter decoupling and specialized optimization.

### Model Highlights

* **Visual Understanding**: Inherits the powerful image content interpretation and analysis capabilities of the Qwen-VL-2.5 foundation model
* **Text-to-Image Generation**: Creates high-fidelity and aesthetically pleasing images from text prompts
* **Instruction-guided Image Editing**: Performs complex, instruction-based image modifications, achieving state-of-the-art performance among open-source models
* **Contextual Generation**: Versatile capabilities to process and flexibly combine diverse inputs (including people, reference objects, and scenes), producing novel and coherent visual outputs

### Technical Features

* **Dual-path Architecture**: Based on Qwen 2.5 VL (3B) text encoder + independent diffusion Transformer (4B)
* **Omni-RoPE Position Encoding**: Supports multi-image spatial positioning and identity distinction
* **Parameter Decoupling Design**: Avoids negative impact of text generation on image quality
* Support for complex text understanding and image understanding
* Controllable image generation and editing
* Excellent detail preservation capabilities
* Unified architecture supporting multiple image generation tasks
* Text generation capability: Can generate clear text content within images

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## OmniGen2 Model Download

Since this article involves different workflows, the corresponding model files and installation locations are as follows. The download information for model files is also included in the corresponding workflows:

**Diffusion Models**

* [omnigen2\_fp16.safetensors](https://huggingface.co/Comfy-Org/Omnigen2_ComfyUI_repackaged/blob/main/split_files/diffusion_models/omnigen2_fp16.safetensors)

**VAE**

* [ae.safetensors](https://huggingface.co/Comfy-Org/Lumina_Image_2.0_Repackaged/blob/main/split_files/vae/ae.safetensors)

**Text Encoders**

* [qwen\_2.5\_vl\_fp16.safetensors](https://huggingface.co/Comfy-Org/Omnigen2_ComfyUI_repackaged/blob/main/split_files/text_encoders/qwen_2.5_vl_fp16.safetensors)

File save location:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── omnigen2_fp16.safetensors
│   ├── 📂 vae/
│   │   └── ae.safetensors
│   └── 📂 text_encoders/
│       └── qwen_2.5_vl_fp16.safetensors
```

## ComfyUI OmniGen2 Text-to-Image Workflow

### OmniGen2: Text to Image

Generate high-quality images from text prompts using OmniGen2's unified 7B multimodal model with dual-path architecture.

<img alt="OmniGen2 text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_omnigen2_t2i&utm_source=docs&utm_medium=referral&utm_campaign=omnigen2">
    Open and run this workflow directly in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_omnigen2_t2i.json">
    Download JSON or search "OmniGen2" in Template Library
  </Card>
</CardGroup>

**Example output**

![OmniGen2 text-to-image example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_omnigen2_t2i.png)

### 1. Download Workflow File

### 2. Complete Workflow Step by Step

<img alt="Workflow Step Guide" />

Please follow the numbered steps in the image for step-by-step confirmation to ensure smooth operation of the corresponding workflow:

1. **Load Main Model**: Ensure the `Load Diffusion Model` node loads `omnigen2_fp16.safetensors`
2. **Load Text Encoder**: Ensure the `Load CLIP` node loads `qwen_2.5_vl_fp16.safetensors`
3. **Load VAE**: Ensure the `Load VAE` node loads `ae.safetensors`
4. **Set Image Dimensions**: Set the generated image dimensions in the `EmptySD3LatentImage` node (recommended 1024x1024)
5. **Input Prompts**:
   * Input positive prompts in the first `CLipTextEncode` node (content you want to appear in the image)
   * Input negative prompts in the second `CLipTextEncode` node (content you don't want to appear in the image)
6. **Start Generation**: Click the `Queue Prompt` button, or use the shortcut `Ctrl(cmd) + Enter` to execute text-to-image generation
7. **View Results**: After generation is complete, the corresponding images will be automatically saved to the `ComfyUI/output/` directory, and you can also preview them in the `SaveImage` node

## ComfyUI OmniGen2 Image Editing Workflow

OmniGen2 has rich image editing capabilities and supports adding text to images.

### OmniGen2 Image Edit

Edit images with natural language instructions using OmniGen2's advanced image editing capabilities and text rendering support.

<img alt="OmniGen2 image edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_omnigen2_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=omnigen2">
    Open and run this workflow directly in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_omnigen2_image_edit.json">
    Download JSON or search "OmniGen2 Image Edit" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="image_omnigen2_image_edit_input_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/image_omnigen2_image_edit_input_image.png">
    `LoadImage` node 16 · `image_omnigen2_image_edit_input_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="image_omnigen2_image_edit_input_image.png" />
</div>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="OmniGen2 image edit example output" />
</div>

### 1. Download Workflow File

### 2. Complete Workflow Step by Step

<img alt="Workflow Step Guide" />

1. **Load Main Model**: Ensure the `Load Diffusion Model` node loads `omnigen2_fp16.safetensors`
2. **Load Text Encoder**: Ensure the `Load CLIP` node loads `qwen_2.5_vl_fp16.safetensors`
3. **Load VAE**: Ensure the `Load VAE` node loads `ae.safetensors`
4. **Upload Image**: Upload the provided image in the `Load Image` node
5. **Input Prompts**:
   * Input positive prompts in the first `CLipTextEncode` node (content you want to appear in the image)
   * Input negative prompts in the second `CLipTextEncode` node (content you don't want to appear in the image)
6. **Start Generation**: Click the `Queue Prompt` button, or use the shortcut `Ctrl(cmd) + Enter` to execute text-to-image generation
7. **View Results**: After generation is complete, the corresponding images will be automatically saved to the `ComfyUI/output/` directory, and you can also preview them in the `SaveImage` node

### 3. Additional Workflow Instructions

* If you want to enable the second image input, you can use the shortcut **Ctrl + B** to enable the corresponding node inputs for nodes that are in pink/purple state in the workflow
* If you want to customize dimensions, you can delete the `Get image size` node linked to the `EmptySD3LatentImage` node and input custom dimensions


# Gemma 4 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/llm/gemma4/gemma4

Run Google's lightweight open Gemma 4 LLM in ComfyUI for text generation, image understanding, video analysis, and audio transcription with up to 256K context.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Gemma 4** is the latest generation of lightweight open LLMs from Google DeepMind, built for text generation, image understanding, video analysis, audio transcription, and structured tool use. It is natively supported in ComfyUI as the default **Text Generation** model.

**Model highlights**:

* **Multimodal by design**: accepts text, image, video, and audio inputs simultaneously
* **Three sizes available**:
  * **E2B (2B)**: Fast and lightweight, ideal for consumer GPUs
  * **E4B (4B)**: Balanced performance, recommended default
  * **31B**: Best quality, requires higher VRAM
* **Thinking mode**: Built-in step-by-step reasoning before generating answers
* **Long context**: Up to 128K tokens (E2B/E4B) and 256K tokens (31B)
* **Multilingual**: 35+ languages out of the box, pre-trained on 140+
* **Function calling**: Native support for structured tool use and agentic workflows
* **ComfyUI native**: loaded and run through the built-in `TextGenerate` and `CLIPLoader` nodes

**Related links**:

* [Hugging Face (Comfy-Org/gemma-4)](https://huggingface.co/Comfy-Org/gemma-4)
* [Google AI for Developers](https://ai.google.dev/gemma)
* [ComfyUI Source Code (nodes\_textgen.py)](https://github.com/Comfy-Org/ComfyUI/blob/master/comfy_extras/nodes_textgen.py)

## Available workflow

### Gemma4: Text Generation

Input your text prompt and optionally an image, audio, or video. Generate text output with configurable reasoning, coding, and multilingual support.

<img alt="Gemma 4 text generation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=llm_gemma4_text_gen&utm_source=docs&utm_medium=referral&utm_campaign=gemma4">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/llm_gemma4_text_gen.json">
    Download JSON or search "Gemma4: Text Generation" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these optional files to the matching nodes:

<CardGroup>
  <Card title="the_lily_veil.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/the_lily_veil.png">
    `LoadImage` node 2 · `the_lily_veil.png`
  </Card>

  <Card title="voice_demo.mp3" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/voice_demo.mp3">
    `LoadAudio` node 5 · `voice_demo.mp3`
  </Card>

  <Card title="video_wan_vace_inpainting_input_video.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan_vace_inpainting_input_video.mp4">
    `LoadVideo` node 6 · `video_wan_vace_inpainting_input_video.mp4`
  </Card>
</CardGroup>

This workflow demonstrates the core **text generation** capabilities of Gemma 4. It accepts an optional image, audio file, or video as additional context alongside your text prompt, and generates natural language output, with support for reasoning, coding, and multilingual prompts.

**Inputs**:

* **Text prompt**: your question or instruction
* **Image** (optional): for visual understanding tasks (OCR, object detection, chart reading, etc.)
* **Audio** (optional): for speech recognition or transcription
* **Video** (optional): for video understanding across frames (subsampled to 1 FPS internally)

**Key controls**:

* **Max length**: maximum number of tokens to generate (default 256)
* **Sampling mode**: toggle sampling on/off and adjust temperature, top-k, top-p, repetition penalty, and seed
* **Thinking mode**: enable step-by-step reasoning before the final answer
* **Use default template**: apply the built-in system prompt for the model

**Output**:

* **Generated text**: the model's response as a plain text string

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Model Download

Gemma 4 models are loaded as text encoders in ComfyUI. Download the relevant model file and place it in the correct directory:

<CardGroup>
  <Card title="Gemma 4 2B (E2B IT FP8)" icon="download" href="https://huggingface.co/Comfy-Org/gemma-4/blob/main/text_encoders/gemma4_e2b_it_fp8_scaled.safetensors">
    Fast, lightweight. Recommended for consumer GPUs.
  </Card>

  <Card title="Gemma 4 4B (E4B IT FP8)" icon="download" href="https://huggingface.co/Comfy-Org/gemma-4/blob/main/text_encoders/gemma4_e4b_it_fp8_scaled.safetensors">
    Balanced performance. The default model in the workflow.
  </Card>

  <Card title="View All Variants" icon="external-link" href="https://huggingface.co/Comfy-Org/gemma-4/tree/main/text_encoders">
    Browse all Gemma 4 model weights.
  </Card>
</CardGroup>

Place the downloaded `.safetensors` file in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 text_encoders/
│       └── gemma4_e4b_it_fp8_scaled.safetensors
```


# Qwen 3.0 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/llm/qwen/qwen3

Qwen 3.0 is Alibaba Cloud's powerful open-source LLM with strong reasoning capabilities, available in 4B size for text generation and structured reasoning tasks.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Qwen 3.0** (also known as Qwen3) is a powerful open-source LLM from Alibaba Cloud built for text generation, reasoning, and structured analysis. It is natively supported in ComfyUI through the built-in `TextGenerate` node.

**Model highlights**:

* **Strong reasoning**: Qwen3-4B-Thinking supports step-by-step chain-of-thought reasoning
* **Text generation focused**: optimized for structured text output, analysis, and coding tasks
* **ComfyUI native**: works with the built-in `TextGenerate` node, no custom nodes needed
* **Lightweight**: shares the same text encoder format as Qwen3.5, available in 2B, 4B, and 9B variants to fit different hardware

## Use Cases

Qwen 3.0 is well-suited for tasks that require structured text generation and intelligent reasoning within a ComfyUI workflow:

* **Prompt optimization**: feed existing prompts to Qwen 3.0 and ask it to rewrite, expand, or refine them for better image generation results. For example, convert a short keyword prompt into detailed, structured descriptions with style, lighting, and composition details.
* **Workflow logic reasoning**: use the model to analyze workflow parameters, suggest processing steps, or generate structured instructions that feed into other nodes.
* **Text-based analysis**: extract information, classify content, or generate structured reports from text inputs.
* **Chain-of-thought reasoning**: enable thinking mode for complex multi-step tasks that benefit from intermediate reasoning before producing the final output.

## Available workflow

### Qwen3.0: Text Generation

Input a text prompt to generate detailed, reasoned responses using the Qwen3-4B-Thinking model.

<img alt="Qwen 3.0 text generation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=llm_qwen3_text_gen&utm_source=docs&utm_medium=referral&utm_campaign=qwen3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/llm_qwen3_text_gen.json">
    Download JSON or search "Qwen3.0: Text Generation" in Template Library
  </Card>
</CardGroup>

This workflow demonstrates the core **text generation** capabilities of Qwen 3.0. It accepts a text prompt and generates detailed, structured responses using the model's built-in reasoning capabilities.

**Inputs**:

* **Text prompt**: your question, instruction, or task description

**Key controls**:

* **Max length**: maximum number of tokens to generate (default 256)
* **Sampling mode**: toggle sampling on/off and adjust temperature, top-k, top-p, repetition penalty, and seed
* **Thinking mode**: enable step-by-step reasoning before the final answer
* **Use default template**: apply the built-in system prompt for the model

**Output**:

* **Generated text**: the model's response as a plain text string

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Model Download

Qwen 3.0 models are loaded as text encoders in ComfyUI. The model files are shared with Qwen3.5. Download the variant that best fits your hardware:

<CardGroup>
  <Card title="Qwen3.5 2B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/blob/main/text_encoders/qwen3.5_2b_bf16.safetensors">
    Lightweight, \~4.5 GB. Best for low VRAM setups and fast downloads.
  </Card>

  <Card title="Qwen3.5 4B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/blob/main/text_encoders/qwen3.5_4b_bf16.safetensors">
    Balanced size and quality. Recommended for most consumer GPUs.
  </Card>

  <Card title="Qwen3.5 9B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/blob/main/text_encoders/qwen3.5_9b_bf16.safetensors">
    Largest variant, \~19 GB. Higher quality output, requires more VRAM.
  </Card>
</CardGroup>

Place the downloaded `.safetensors` file in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 text_encoders/
│       └── qwen3.5_4b_bf16.safetensors   # or 2b / 9b variant
```


# Qwen3.5 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/llm/qwen/qwen3_5

Run Qwen3.5, Alibaba Cloud's 4B multimodal LLM, in ComfyUI for image captioning, reverse prompt engineering, and visual question answering.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Qwen3.5** is an open-source multimodal LLM from Alibaba Cloud, building on the Qwen 3.0 series with added image understanding capabilities. It supports both text generation and image-based tasks such as image captioning and reverse prompt engineering.

**Model highlights**:

* **Multimodal**: accepts text and image inputs for visual understanding tasks
* **Image captioning**: can describe images and generate detailed captions
* **Reverse prompt engineering**: extract prompts and generation parameters from reference images
* **ComfyUI native**: works with the built-in `TextGenerate` node, no custom nodes needed
* **Lightweight**: 4B parameter model, suitable for consumer GPUs

## Use Cases

Qwen3.5 excels in scenarios where combining visual understanding with text generation adds value to a ComfyUI workflow:

* **Image reverse prompt engineering**: feed a reference image to Qwen3.5 and ask it to generate a detailed text prompt that could reproduce the image. This is especially useful when you encounter a great image but don't know how it was prompted.
* **Prompt optimization**: load an existing prompt and an image concept, then ask Qwen3.5 to generate, refine, or expand prompts with richer detail for better generation results.
* **Image captioning**: automatically generate captions, descriptions, or metadata tags for generated images, useful for cataloging or training data preparation.
* **Visual question answering**: ask questions about image content ("What objects are in this scene?", "What color is the background?") and get structured text answers.
* **Text reading**: with a suitable prompt, the model may attempt to read visible text or labels in images, though reliability depends on the quality and clarity of the rendered text.

## Available workflow

### Qwen3.5: Text Generation

Use the Qwen3.5 model to analyze an input image and generate descriptive text prompts. This workflow performs image captioning and reverse prompt engineering.

<img alt="Qwen3.5 text generation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=llm_qwen3_5_text_gen&utm_source=docs&utm_medium=referral&utm_campaign=qwen3_5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/llm_qwen3_5_text_gen.json">
    Download JSON or search "Qwen3.5: Text Generation" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="man_with_red_hat.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/man_with_red_hat.png">
    `LoadImage` node 2 · `man_with_red_hat.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />
</div>

This workflow demonstrates the **text generation and image understanding** capabilities of Qwen3.5. It accepts a text prompt and an optional image, and generates descriptive text or structured analysis based on the input.

**Inputs**:

* **Text prompt**: your question, instruction, or task description
* **Image** (optional): for visual understanding tasks (image captioning, reverse prompt engineering, prompt optimization, etc.)

**Key controls**:

* **Max length**: maximum number of tokens to generate (default 256)
* **Sampling mode**: toggle sampling on/off and adjust temperature, top-k, top-p, repetition penalty, and seed
* **Use default template**: apply the built-in system prompt for the model

**Output**:

* **Generated text**: the model's response as a plain text string

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Model Download

Qwen3.5 models are loaded as text encoders in ComfyUI. Choose the variant that best suits your hardware:

<CardGroup>
  <Card title="Qwen3.5 2B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/blob/main/text_encoders/qwen3.5_2b_bf16.safetensors">
    Lightweight, \~4.5 GB. Best for low VRAM setups and fast downloads.
  </Card>

  <Card title="Qwen3.5 4B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/blob/main/text_encoders/qwen3.5_4b_bf16.safetensors">
    Balanced size and quality. Recommended for most consumer GPUs.
  </Card>

  <Card title="Qwen3.5 9B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/blob/main/text_encoders/qwen3.5_9b_bf16.safetensors">
    Largest variant, \~19 GB. Higher quality output, requires more VRAM.
  </Card>
</CardGroup>

Place the downloaded `.safetensors` file in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 text_encoders/
│       └── qwen3.5_4b_bf16.safetensors   # or 2b / 9b variant
```


# Beeble SwitchX Partner Nodes ComfyUI Official Examples
Source: https://docs.comfy.org/tutorials/partner-nodes/beeble/beeble-switchx

This guide explains how to use Beeble SwitchX Partner Nodes in ComfyUI for AI-powered image and video relighting and environment editing

The [Beeble SwitchX](/built-in-nodes/BeebleSwitchXImageEdit) Partner Nodes allow you to transform the environment, lighting, and style of existing images and videos while preserving the original subject. Upload a character or subject image along with a reference environment, and SwitchX composites your subject into the new scene with realistic lighting and shadows.

## What Beeble SwitchX is good at

* **Environment replacement**: Replaces the background environment of an image or video with a reference scene while preserving the original subject
* **Realistic relighting**: Composites the subject into the new environment with proper lighting, shadows, and perspective
* **Video editing with motion preserved**: Applies relighting to masked subject regions in a video while unmasked areas keep the original pixels and motion
* **Compositing-ready outputs**: The image workflow saves a masked cutout, and the video workflow generates a separate alpha matte for easy compositing

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Beeble SwitchX: Image Edit

Replace the background environment and relight your subject with a reference image.

<img alt="Beeble SwitchX Image Edit Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_beeble_switchx_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=beeble-switchx">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_beeble_switchx_image_edit.json">
    Download JSON or search "Beeble SwitchX: Image Edit" in Template Library
  </Card>
</CardGroup>

### How It Works

This workflow takes two input images:

* **Subject image**: your character or main subject (with background)
* **Reference environment**: the new scene, lighting, or style you want to apply

The node generates an output where the subject is naturally composited into the new environment with proper lighting, shadows, and perspective.

### Steps to Run

1. **Upload subject image**: use the first **LoadImage** node to load your subject image (e.g., a person wearing headphones)
2. **Upload reference image**: use the second **LoadImage** node to load the target environment or style
3. **Enter your prompt**: describe the scene in the **BeebleSwitchXImageEdit** node
4. **Set resolution**: choose output resolution
5. **Adjust seed**: modify the seed for different results
6. **Click Queue**: press `Ctrl+Enter` to generate
7. **View results**: the edited image appears in **SaveImage**, and a masked cutout is saved separately

### Node Parameters

| Parameter | Description |
| - | - |
| `prompt` | Description of the scene and environment |
| `resolution` | Output resolution (e.g., 720p) |
| `seed` | Random seed for reproducible results |

## Beeble SwitchX: Video Edit

Apply environment relighting to a video while preserving the original motion and unmasked regions.

<img alt="Beeble SwitchX Video Edit Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_beeble_switchx_video_edit&utm_source=docs&utm_medium=referral&utm_campaign=beeble-switchx">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_beeble_switchx_video_edit.json">
    Download JSON or search "Beeble SwitchX: Video Edit" in Template Library
  </Card>
</CardGroup>

### How It Works

This workflow takes a source video and a reference image, then applies the reference lighting and environment to the masked subject regions in the video. Unmasked areas preserve the original pixels and motion. The workflow also generates an alpha matte for easy compositing.

### Steps to Run

1. **Upload source video**: use the **LoadVideo** node to load your input video
2. **Upload reference image**: use the **LoadImage** node to load the target environment/style
3. **Set video range**: the **Video Slice** node controls which frames to process (start, end, inclusive)
4. **Enter your prompt**: describe the desired environment and lighting in the **BeebleSwitchXVideoEdit** node
5. **Set resolution**: choose output resolution
6. **Adjust seed**: modify the seed for different results
7. **Click Queue**: press `Ctrl+Enter`
8. **View results**: the edited video is saved, and a separate alpha matte video is generated for compositing

### Outputs

| Output | Description |
| - | - |
| **Edited video** (`SaveVideo`) | The final video with new environment/lighting applied to masked regions |
| **Alpha matte** (`SaveVideo`) | A separate alpha video for compositing the edited regions |


# Flux 1.1 Pro Ultra Image Partner Nodes ComfyUI Official Workflow Examples
Source: https://docs.comfy.org/tutorials/partner-nodes/black-forest-labs/flux-1-1-pro-ultra-image

This guide covers how to use the Flux 1.1 Pro Ultra Image Partner node in ComfyUI

FLUX 1.1 Pro Ultra is a high-performance AI image generation tool by BlackForestLabs, featuring ultra-high resolution and efficient generation capabilities. It supports up to 4MP resolution (4x the standard version) while keeping single image generation time under 10 seconds - 2.5x faster than similar high-resolution models.

The tool offers two core modes:

* **Ultra Mode**: Designed for high-resolution needs, perfect for advertising and e-commerce where detail magnification is important. It accurately reflects prompts while maintaining generation speed.
* **Raw Mode**: Focuses on natural realism, optimizing skin tones, lighting, and landscape details. Reduces the "AI look" and is ideal for photography and realistic style creation.

## What Flux 1.1 Pro Ultra Image is good at

* **Ultra-high resolution**: Generates images up to 4MP, 4x the standard version's resolution
* **Fast generation**: Keeps single image generation time under 10 seconds, 2.5x faster than similar high-resolution models
* **Prompt accuracy at scale**: Ultra Mode reflects prompts accurately while maintaining generation speed, suited to advertising and e-commerce work
* **Natural realism**: Raw Mode optimizes skin tones, lighting, and landscape details to reduce the "AI look"
* **Image-to-image remixing**: An `image_prompt` input blends features from an input image, with `image_prompt_strength` controlling the blend ratio

## Example outputs

Text-to-image generation with the Flux 1.1 \[pro] Ultra Image node:

![Flux 1.1 pro Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_1_pro_t2i.png)

Image-to-image remixing, blending features from an input image into the output:

![Flux 1.1 pro Image-to-Image Remix](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_1_pro_i2i.png)

## Use it

<Card title="Call it from code" icon="code" href="/development/comfy-router/models/black-forest-labs/flux-1-1-pro-ultra-image/code">
  Call it over HTTP through Comfy Router, with copy-paste Python, TypeScript, Swift and cURL snippets
</Card>

This runs on the same Comfy account and is billed in the same credits as running it in ComfyUI below. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for per-model rates and [Concurrency limits](/tutorials/partner-nodes/concurrency-limits) for how many requests you can have in flight.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Flux 1.1 Pro Ultra Image Node Documentation

Check the following documentation for detailed node parameter settings:

* [Flux 1.1 Pro Ultra Image](/images/built-in-nodes/api_nodes/bfl/flux-1-1-pro-ultra-image.jpg)

## Flux 1.1 \[pro] Text-to-Image Tutorial

### 1. Download Workflow File

Download and drag the following file into ComfyUI to load the workflow:

![Flux 1.1 pro Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_1_pro_t2i.png)

### 2. Complete the Workflow Steps

<img alt="Workflow Steps" />

Follow the numbered steps to complete the basic workflow:

1. (Optional) Modify the prompt in the `Flux 1.1 [pro] Ultra Image` node
2. (Optional) Set `raw` parameter to `false` for more realistic output
3. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
4. After the API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

## Flux 1.1\[pro] Image-to-Image Tutorial

When adding an `image_prompt` to the node input, the output will blend features from the input image (Remix). The `image_prompt_strength` value affects the blend ratio: higher values make the output more similar to the input image.

### 1. Download Workflow File

Download and drag the following file into ComfyUI, or right-click the purple node in the Text-to-Image workflow and set `mode` to `always` to enable `image_prompt` input:

![Flux 1.1 pro Image-to-Image Remix](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_1_pro_i2i.png)

We'll use this image as input:
![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai-dall-e-3/text2image.png)

### 2. Complete the Workflow Steps

<img alt="Workflow Steps" />

Follow these numbered steps:

1. Click **Upload** on the `Load Image` node to upload your input image
2. (Optional) Adjust `image_prompt_strength` in `Flux 1.1 [pro] Ultra Image` to change the blend ratio
3. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
4. After the API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

Here's a comparison of outputs with different `image_prompt_strength` values:

<img alt="Comparison" />


# ComfyUI Flux.1 Kontext Pro Image Partner Nodes Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/black-forest-labs/flux-1-kontext

This guide will show you how to use the Flux.1 Kontext Pro Image Partner node in ComfyUI to perform image editing

FLUX.1 Kontext is a professional image-to-image editing model developed by Black Forest Labs, focusing on intelligent understanding of image context and precise editing.
It can perform various editing tasks without complex descriptions, including object modification, style transfer, background replacement, character consistency editing, and text editing.
The core advantage of Kontext lies in its excellent context understanding ability and character consistency maintenance, ensuring that key elements such as character features and composition layout remain stable even after multiple iterations of editing.

Currently, ComfyUI has supported two models of Flux.1 Kontext:

* **Kontext Pro** is ideal for editing, composing, and remixing.
* **Kontext Max** pushes the limits on typography, prompt precision, and speed.

## What Flux.1 Kontext is good at

* **Versatile editing without complex descriptions**: Object modification, style transfer, background replacement, character consistency editing, and text editing
* **Context understanding**: Intelligent understanding of image context enables precise, targeted edits
* **Character consistency**: Character features and composition layout remain stable even after multiple iterations of editing
* **Multiple image input**: The `Image Stitch` node stitches multiple images into a single image for editing with Flux.1 Kontext
* **Two model tiers**: Kontext Pro for editing, composing, and remixing; Kontext Max for typography, prompt precision, and speed

## Example outputs

Editing a stitched multi-image input (a girl, a dog, and a sofa combined into one scene):

![Flux.1 Kontext multiple image input example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/multiple_image_input/multiple_image_input.png)

Image editing with Kontext Pro, ideal for editing, composing, and remixing:

![Flux.1 Kontext Pro image editing example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_kontext_pro_image.png)

Image editing with Kontext Max, which pushes the limits on typography, prompt precision, and speed:

![Flux.1 Kontext Max image editing example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_kontext_max_image.png)

## Use it

<Card title="Call it from code" icon="code" href="/development/comfy-router/models/black-forest-labs/flux-1-kontext/code">
  Call Kontext Pro or Max over HTTP through Comfy Router, with copy-paste Python, TypeScript, Swift and cURL snippets
</Card>

This runs on the same Comfy account and is billed in the same credits as running it in ComfyUI below. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for per-model rates and [Concurrency limits](/tutorials/partner-nodes/concurrency-limits) for how many requests you can have in flight.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Flux.1 Kontext Multiple Image Input Workflow

We have recently updated to support multiple image input workflows. Using the new `Image Stitch` node, you can stitch multiple images into a single image and edit it using Flux.1 Kontext.

### 1. Workflow File Download

The `metadata` of the images below contains the workflow information. Please download and drag them into ComfyUI to load the corresponding workflow.

![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/multiple_image_input/multiple_image_input.png)

Download the following images for input or use your own images:

![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/multiple_image_input/girl.jpg)
![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/multiple_image_input/dog.jpg)
![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/multiple_image_input/sofa.jpg)

### 2. Complete the Workflow Step by Step

<img alt="ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow Steps" />

You can follow the numbered steps in the image to complete the workflow:

1. Upload the provided images in the `Load image` node
2. Modify the necessary parameters in `Flux.1 Kontext Pro Image`:
   * `prompt` Enter the prompt for the image you want to edit
   * `aspect_ratio` Set the aspect ratio of the original image, which must be between 1:4 and 4:1
   * `prompt_upsampling` Set whether to use prompt upsampling. If enabled, it will automatically modify the prompt to get richer results, but the results are not reproducible
3. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image editing
4. After waiting for the API to return results, you can view the edited image in the `Save Image` node, and the corresponding image will also be saved to the `ComfyUI/output/` directory

<Tip>
  The subsequent two workflows only differ in the Partner nodes used. In fact, you only need to modify based on the multiple image input workflow, with no significant differences
</Tip>

## Flux.1 Kontext Pro Image Partner Nodes Workflow

### 1. Workflow File Download

The `metadata` of the image below contains the workflow information. Please download and drag it into ComfyUI to load the corresponding workflow.

![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_kontext_pro_image.png)

Download the image below for input or use your own image:

![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_kontext_pro_image_input.png)

### 2. Complete the Workflow Step by Step

<img alt="ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow Steps" />

You can follow the numbered steps in the image to complete the workflow:

1. Load the image you want to edit in the `Load Image` node
2. (Optional) Modify the necessary parameters in `Flux.1 Kontext Pro Image`
3. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image editing
4. After waiting for the API to return results, you can view the edited image in the `Save Image` node, and the corresponding image will also be saved to the `ComfyUI/output/` directory

## Flux.1 Kontext Max Image Partner Nodes Workflow

### 1. Workflow File Download

The `metadata` of the image below contains the workflow information. Please download and drag it into ComfyUI to load the corresponding workflow.

![ComfyUI Flux.1 Kontext Max Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_kontext_max_image.png)

Download the image below for input or use your own image for demonstration:

![ComfyUI Flux.1 Kontext Max Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_kontext_max_image_input.png)

### 2. Complete the Workflow Step by Step

<img alt="ComfyUI Flux.1 Kontext Max Image Partner Nodes Workflow Steps" />

You can follow the numbered steps in the image to complete the workflow:

1. Load the image you want to edit in the `Load Image` node
2. (Optional) Modify the necessary parameters in `Flux.1 Kontext Max Image`
3. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image editing
4. After waiting for the API to return results, you can view the edited image in the `Save Image` node, and the corresponding image will also be saved to the `ComfyUI/output/` directory

## Flux Kontext Prompt Techniques

### 1. Basic Modifications

* Simple and direct: `"Change the car color to red"`
* Maintain style: `"Change to daytime while maintaining the same style of the painting"`

### 2. Style Transfer

**Principles:**

* Clearly name style: `"Transform to Bauhaus art style"`
* Describe characteristics: `"Transform to oil painting with visible brushstrokes, thick paint texture"`
* Preserve composition: `"Change to Bauhaus style while maintaining the original composition"`

### 3. Character Consistency

**Framework:**

* Specific description: `"The woman with short black hair"` instead of "she"
* Preserve features: `"while maintaining the same facial features, hairstyle, and expression"`
* Step-by-step modifications: Change background first, then actions

### 4. Text Editing

* Use quotes: `"Replace 'joy' with 'BFL'"`
* Maintain format: `"Replace text while maintaining the same font style"`

## Common Problem Solutions

### Character Changes Too Much

❌ Wrong: `"Transform the person into a Viking"`
✅ Correct: `"Change the clothes to be a viking warrior while preserving facial features"`

### Composition Position Changes

❌ Wrong: `"Put him on a beach"`
✅ Correct: `"Change the background to a beach while keeping the person in the exact same position, scale, and pose"`

### Style Application Inaccuracy

❌ Wrong: `"Make it a sketch"`
✅ Correct: `"Convert to pencil sketch with natural graphite lines, cross-hatching, and visible paper texture"`

## Core Principles

1. **Be Specific and Clear** - Use precise descriptions, avoid vague terms
2. **Step-by-step Editing** - Break complex modifications into multiple simple steps
3. **Explicit Preservation** - State what should remain unchanged
4. **Verb Selection** - Use "change", "replace" rather than "transform"

## Best Practice Templates

**Object Modification:**
`"Change [object] to [new state], keep [content to preserve] unchanged"`

**Style Transfer:**
`"Transform to [specific style], while maintaining [composition/character/other] unchanged"`

**Background Replacement:**
`"Change the background to [new background], keep the subject in the exact same position and pose"`

**Text Editing:**
`"Replace '[original text]' with '[new text]', maintain the same font style"`

> **Remember:** The more specific, the better. Kontext excels at understanding detailed instructions and maintaining consistency.


# Bria Background Removal in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/bria/background-removal

Learn how to use Bria Partner Nodes in ComfyUI for image and video background removal, green screen, and background replacement.

Bria's AI background processing models are now available in ComfyUI through Partner Nodes. This page covers **Image Background Removal**, **Video Background Removal**, **Transparent Video Background**, **Video Green Screen**, and **Video Background Replacement**.

## What Bria Background Removal is good at

* **Image background removal**: Automatically removes an image's background and returns the result with a transparent background
* **Video background removal**: Replaces a video's background with a solid color of your choice, or outputs the video with transparency
* **Video green screen**: Applies a professional chroma-key green or blue screen effect, with presets including broadcast\_green, chroma\_green, and blue\_screen
* **Video background replacement**: Replaces a video's background with a custom image or another video
* **Short-form video support**: Video background processing accepts input videos up to 60 seconds

## Example outputs

Image background removal, returning the subject on a transparent background:

![Bria: Remove Image Background example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/utility_bria_remove_image_background.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Bria: Remove Image Background

Upload an image to automatically remove its background using the Bria API. The result is returned as an image with a transparent background.

<img alt="Bria: Remove Image Background workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_bria_remove_image_background&utm_source=docs&utm_medium=referral&utm_campaign=background-removal">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_bria_remove_image_background.json">
    Download JSON or search "Bria: Remove Image Background" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="denim_girl.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/denim_girl.png">
    `LoadImage` node 26 · `denim_girl.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />

  <img alt="Bria: Remove Image Background example output" />
</div>

## Video Background Processing

Bria's video background processing nodes let you remove, replace, or apply chroma-key effects to video backgrounds. The input video must be 60 seconds or shorter.

### Bria: Remove Video Background

Replace a video's background with a solid color of your choice.

<img alt="Bria: Remove Video Background workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_remove_video_background&utm_source=docs&utm_medium=referral&utm_campaign=background-removal">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_remove_video_background.json">
    Download JSON or search "Bria: Remove Video Background" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadVideo` node:

<CardGroup>
  <Card title="spear_warrior.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/spear_warrior.mp4">
    `LoadVideo` node 4 · `spear_warrior.mp4`
  </Card>
</CardGroup>

### Bria: Remove Video Background (Transparent)

Remove the background from a video and output it with transparency.

<img alt="Bria: Remove Video Background (Transparent) workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_remove_video_background_transparent&utm_source=docs&utm_medium=referral&utm_campaign=background-removal">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_remove_video_background_transparent.json">
    Download JSON or search "Bria: Remove Video Background (Transparent)" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadVideo` node:

<CardGroup>
  <Card title="ad_video_demo.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/ad_video_demo.mp4">
    `LoadVideo` node 5 · `ad_video_demo.mp4`
  </Card>
</CardGroup>

### Bria: Video Green Screen

Apply a professional chroma-key green or blue screen effect to your video, with multiple preset options including broadcast\_green, chroma\_green, and blue\_screen.

<img alt="Bria: Video Green Screen workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_video_green_screen&utm_source=docs&utm_medium=referral&utm_campaign=background-removal">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_video_green_screen.json">
    Download JSON or search "Bria: Video Green Screen" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadVideo` node:

<CardGroup>
  <Card title="investigator.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/investigator.mp4">
    `LoadVideo` node 5 · `investigator.mp4`
  </Card>
</CardGroup>

### Bria: Video Replace Background

Replace a video's background with a custom image or another video.

<img alt="Bria: Video Replace Background workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_video_replace_background&utm_source=docs&utm_medium=referral&utm_campaign=background-removal">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_video_replace_background.json">
    Download JSON or search "Bria: Video Replace Background" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadVideo` and `LoadImage` nodes:

<CardGroup>
  <Card title="stained_window_vintage_woman.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/stained_window_vintage_woman.mp4">
    `LoadVideo` node 4 · `stained_window_vintage_woman.mp4`
  </Card>

  <Card title="gothic_hall_light_rays.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/gothic_hall_light_rays.png">
    `LoadImage` node 8 · `gothic_hall_light_rays.png`
  </Card>
</CardGroup>

<div>
  <img alt="gothic_hall_light_rays.png" />
</div>


# Bria FIBO Edit Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/bria/fibo

Learn how to use the Bria FIBO Edit Partner node for precision image editing in ComfyUI

FIBO Edit is Bria AI's JSON-native image editing model, now available in ComfyUI through Partner Nodes. It lets you combine images with structured JSON prompts to make precise, targeted edits: no prompt guessing, no unwanted changes to the rest of your image.

## What Bria FIBO Edit is good at

* **Surgical edits**: Change specific attributes (lighting, color, texture, materials) without breaking the rest of the scene
* **Background swaps and object modifications**: Precise control over targeted areas
* **Reproducible, auditable edits**: Structured JSON inputs for consistent results
* **100% licensed data**: Full governance and legal clarity for commercial use
* **Strong prompt adherence**: Validated on PRISM-style evaluations

FIBO Edit excels at various editing tasks:

* **Time of day changes**: Relight your scene or change the time of day
* **Material and texture swaps**: Try different colors, materials, fabrics, and clothing
* **Object material replacement**: Swap out the material on specific objects
* **Masked area editing**: Mask out a specific area to edit with precision
* **Text adjustment**: Adjust the text in an image
* **Art style transformation**: Re-imagine your image in a different art style

## Example outputs

Precision image editing with structured JSON control over lighting, composition, and camera settings:

![Bria: Image Edit example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_bria_image_edit.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Bria: Image Edit

FIBO enables precise, predictable image editing through structured JSON control over lighting, composition, and camera settings.

<img alt="Bria: Image Edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=fibo">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_image_edit.json">
    Download JSON or search "Bria: Image Edit" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="sunlit_rooftop_capture.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/sunlit_rooftop_capture.png">
    `LoadImage` node 5 · `sunlit_rooftop_capture.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />

  <img alt="Bria: Image Edit example output" />
</div>

### Bria: Image Outpainting

A professional Bria-powered outpainting template designed for seamless image extension and edge-aware scene expansion.

<img alt="Bria: Image Outpainting workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_image_outpainting&utm_source=docs&utm_medium=referral&utm_campaign=fibo">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_image_outpainting.json">
    Download JSON or search "Bria: Image Outpainting" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="baby_otter.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/baby_otter.png">
    `LoadImage` node 11 · `baby_otter.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />
</div>


# Bria Eraser, Expand Image, and GenFill in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/bria/image-editing

Remove objects, expand images, and generate content inside masked regions with the Bria Eraser, Expand Image, and Generative Fill partner nodes in ComfyUI.

Bria's image editing tools are available in ComfyUI as Partner Nodes. This page covers three mask-based editing workflows: **Bria Eraser** (remove objects), **Bria Expand Image** (outpaint beyond the borders), and **Bria Generative Fill** (generate content inside a masked region). All three keep everything outside the edited area pixel-perfect unchanged.

## What Bria Image Editing is good at

* **Object removal**: Bria Eraser erases a masked object or region and fills it with surrounding context, no prompt needed
* **Image expansion**: Bria Expand Image outpaints beyond the original borders, generating surroundings that match the image's lighting, perspective, and texture
* **Generative fill**: Bria Generative Fill regenerates a masked region from a prompt, art-directing new content into the scene
* **Pixel-perfect preservation**: All three workflows keep everything outside the edited area unchanged

## Example outputs

Object removal with Bria Eraser, inpainting the background behind the erased region:

![Bria: Eraser example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/Bria_Eraser.png)

Image expansion with Bria Expand Image, extending the scene beyond its original borders:

![Bria: Expand Image example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/Bria_Expand_Image.png)

Generative fill, regenerating a masked region from a prompt:

![Bria: Generative Fill example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/Bria_GenFill.png)

Each workflow takes a single input image plus a mask. The **Painter** node in the templates provides a brush canvas for drawing the mask, and an **ImageCompare** node shows the before/after result side by side. The Painter node is only available under Nodes 2.0; if you only see "Painter: Node 2.0 only", enable Nodes 2.0 via **Menu -> Nodes2.0**, or use the [Mask Editor](https://docs.comfy.org/interface/maskeditor) to create the mask instead.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Bria: Eraser

Remove a specific object or region from an image. The masked area is erased and filled with surrounding context; everything outside the mask stays unchanged.

<img alt="Bria: Eraser workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_eraser&utm_source=docs&utm_medium=referral&utm_campaign=bria-image-editing">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_eraser.json">
    Download JSON or search "Bria Eraser" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="vintage_girl_yellow_apple.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/vintage_girl_yellow_apple.png">
    Download sample input image
  </Card>
</CardGroup>

<div>
  <img alt="Bria: Eraser input" />

  <img alt="Bria: Eraser example output" />
</div>

**How to use**

1. **Load an image**: Upload your image in `LoadImage`. The Painter canvas and compare view auto-update.
2. **Paint a mask**: Brush over the object or region you want to remove. Paint slightly beyond the object's edge (hair, glass, fabric, contact points) so the model has room to blend cleanly.
3. **Run `BriaEraser`**: No prompt needed. The node erases the masked area and inpaints the background. Enter your `api_key` if it is not already set.
4. **Compare and save**: `ImageCompare` shows before/after, `SaveImageAdvanced` exports the result.

<Note>
  The masked area is fully regenerated from its surroundings, so the result blends seamlessly. The mask is binary: white (255) marks the region to erase, black (0) everywhere else, and it must match the image's aspect ratio. For more precise results, use an automatic segmentation mask (SAM-style) if available: the API's `mask_type` distinguishes `manual` (brush-drawn) from `automatic` (algorithm-generated) masks.
</Note>

### Bria: Expand Image

Expand an image beyond its original borders. The original image stays untouched; the surrounding area is generated to match its lighting, perspective, and texture.

<img alt="Bria: Expand Image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_expand_image&utm_source=docs&utm_medium=referral&utm_campaign=bria-image-editing">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_expand_image.json">
    Download JSON or search "Bria Expand Image" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="red_sports_car_night.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/red_sports_car_night.png">
    Download sample input image
  </Card>
</CardGroup>

<div>
  <img alt="Bria: Expand Image input" />

  <img alt="Bria: Expand Image example output" />
</div>

**How to use**

1. **Load an image**: Upload your image in `LoadImage` and connect it to `BriaExpandImage`.
2. **Choose an expansion mode** in the `expand_mode` dropdown:
   * **Preset aspect ratio**: Pick one of `1:1`, `2:3`, `3:2`, `3:4`, `4:3`, `4:5`, `5:4`, `9:16`, `16:9`. The image is centered and the edges are expanded to fit that ratio.
   * **Custom ratio**: Pick `custom_ratio` and set `ratio_width` / `ratio_height` (e.g. 21 and 9 for 21:9). Bria accepts width-to-height ratios between 0.5 and 3.0, so anything taller than 1:2 needs the manual mode.
   * **Manual**: Pick `manual` and place the original image on a canvas with `canvas_width` / `canvas_height` (max 5000 x 5000), `image_width` / `image_height`, and `image_x` / `image_y` (the image's top-left corner; can be negative to crop).
3. **Prompt (optional)**: Leave it empty and Bria automatically generates a prompt from the input image and expands to match its scene and style. Or write your own to guide the expansion direction explicitly, for example "the street continuing to the right", "add a streetlamp", "no other cars". English only; special characters are not supported.
4. **Optional**: `negative_prompt` to avoid unwanted content, `seed` to reproduce a result, `moderation` to enable content moderation.
5. **Save**: Connect the image output to `SaveImage`.

<Note>
  The `prompt` output on the node shows the prompt actually used: your input, or the one auto-generated by Bria when the field is empty. If the target aspect ratio equals the image's current ratio (e.g. a 1:1 image set to `1:1`), no changes are made and the image is returned as-is. Canvas area is limited to 5,000 x 5,000 pixels. Keep the main subject above 15% of the total canvas area for best results.
</Note>

### Bria: Generative Fill

Regenerate a specific region of an image from a prompt. The masked area is fully regenerated; everything outside the mask stays pixel-perfect unchanged.

<img alt="Bria: Generative Fill workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_genfill&utm_source=docs&utm_medium=referral&utm_campaign=bria-image-editing">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_genfill.json">
    Download JSON or search "Bria: Generative Fill" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="retro_girl_cinnamon_bun.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/retro_girl_cinnamon_bun.png">
    Download sample input image
  </Card>
</CardGroup>

<div>
  <img alt="Bria: Generative Fill input" />

  <img alt="Bria: Generative Fill example output" />
</div>

**How to use**

1. **Load an image**: Upload your image in `LoadImage`. The Painter canvas and compare view auto-update.
2. **Paint a mask**: Brush over the region you want to regenerate. Blob-shaped, brush-drawn masks work best. Paint slightly beyond the object's edge (hair, glass, fabric, contact points) so the model has room to blend.
3. **Write the prompt**: In `BriaGenFill`, describe what should be generated inside the masked area, as if art-directing a cropped micro-scene: name the object, its material and size, how it interacts with the surface, and ask for a contact shadow. Around 90-110 words works best. Keep `refine_prompt` enabled.
4. **Optional**: `negative_prompt` to avoid unwanted details. Use a fixed `seed` to iterate on the mask or wording, then randomize once the result looks right.
5. **Compare and save**: `ImageCompare` shows before/after, `SaveImageAdvanced` exports the result.

<Note>
  Masks trigger generative replacement, not pixel retouching: the masked area means "regenerate this region", not "touch up this region".
</Note>

## Prompt-driven editing (no mask)

The nodes below edit an image from a text instruction alone: no Painter canvas, no mask. Each node outputs the edited image plus a `structured_prompt` string that describes the edit, which you can feed into Bria FIBO Image Edit for follow-up edits. All of them cost 12.07 credits per run.

### Bria: Erase by Text

Remove an object by naming it. Enter the object's name in `BriaEraseByText`, such as `the lamp`: several objects can be named and removed at once, and no mask is needed.

### Bria: Add Object

Add a new object to the scene from a prompt, such as `Place a red vase with flowers on the table`. Bria re-imagines the edit on each run, so repeated runs can differ. The node's `seed` input is never sent to the API. It changes only the node's cache key, so an otherwise identical graph runs the edit again instead of returning a cached result.

### Bria: Replace Object

Swap one object for another from a prompt, such as `Replace the red apple with a green pear`. Like Add Object, each run re-imagines the edit.

### Bria: Relight

Change the lighting of a scene with two dropdowns: `light_type` picks the atmosphere (13 options including midday, blue hour light, sunrise light, spotlight on subject, moonlight lighting, and harsh studio lighting), and `light_direction` picks where the light comes from: `front`, `side`, `bottom`, or `top-down`.

### Bria: Restore Photo

Repair and restore an old or degraded photo in one click: no prompt and no mask, just connect the image.

### Bria: Reseason

Change the season of an outdoor scene. Pick `spring`, `summer`, `autumn`, or `winter` in the `season` dropdown and Bria re-renders foliage, lighting, and atmosphere to match.

### Bria: Erase Foreground

Remove the entire foreground of an image and generate a background in its place.

### Bria: Replace Image Background

Replace the background of an image. Describe the new background with a prompt, or guide it with up to 10 reference images. The mode dropdown controls how closely the result follows the prompt: `high_control` follows it most closely, `base` is a balanced middle ground, and `fast` trades control for speed. Enable `keep_original_size` to return the input's exact pixel size instead of scaling the result.

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `Bria Eraser`, `Bria Expand Image`, or `Bria Generative Fill`. The prompt-driven nodes in the section above are available on the node palette without a template.


# ByteDance Seedream 5.0 Lite - Smart AI Image Creation
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/seedream-5-lite

Generate images with web-connected retrieval and enhanced instruction following using Seedream 5.0 lite in ComfyUI

Seedream 5.0 lite is the latest image generation model from BytePlus. It is the first in the Seedream family to bring in web-connected retrieval, which means the model can draw on live online information when generating images.

## What Seedream 5.0 Lite is good at

* **Web-connected retrieval**: The model pulls from live web data during generation, allowing creations to be tied to real-world trends, current events, and up-to-date knowledge
* **Smarter instruction following**: Handles complex, multi-step instructional prompts far more reliably. Multi-image inputs, local editing instructions, and batch style requests all land closer to the intended output
* **Stronger consistency**: Character identity, product appearance, style, and lighting all hold up much better across a set of generated images
* **Deeper world knowledge**: Expanded knowledge base makes the model useful for technical illustration, educational diagrams, and knowledge-heavy creative work

## Example outputs

Multi-step local editing, following several boxed instructions in one pass:

![Instruction following example 1](https://substack-post-media.s3.amazonaws.com/public/images/9a770e2a-c0ed-4253-bd60-14c5beff150d_2048x2048.png)
*Change the glasses in the green box to circular lenses, the orange purse in the blue box to a purple oval purse, and her shoes in the red box are patterned with leopard print.*

Style transfer between two images:

![Style transfer example](https://substack-post-media.s3.amazonaws.com/public/images/dc08a07e-edf1-4864-b6a6-5a7b17b78cfa_1920x1080.png)
*Refer to the second image and change the style of the first picture to match that of the second image.*

Product consistency across a batch of generated photos:

![Product consistency](https://substack-post-media.s3.amazonaws.com/public/images/585cf84d-afe0-4277-b08a-7a0cddbd6a54_1620x1080.png)
*Using the bottle from the reference image, generate six product photos in different seasonal settings. Consistent bottle design across all six.*

Knowledge-heavy text-to-image generation:

![Gravity infographic](https://substack-post-media.s3.amazonaws.com/public/images/fac37b40-faaa-4360-b449-08da38322186_2562x1440.png)
*Pixel art infographic for explaining gravity, rendered in crisp 16-bit style with a dark navy/charcoal background and bold cinematic palette tones.*

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Seedream 5.0 lite image edit workflow

<img alt="Seedream 5.0 Lite Image Edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_seedream_5_0_lite_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=seedream-5-lite">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_seedream_5_0_lite_image_edit.json">
    Download JSON or search "Seedream 5.0 lite" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/man_with_old_computers.png">
      Download sample input image
    </Card>

    <Card title="Style reference" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/inflated_character.png">
      Download sample style reference
    </Card>
  </CardGroup>
</details>

### Image edit showcase

![Instruction following example 1](https://substack-post-media.s3.amazonaws.com/public/images/9a770e2a-c0ed-4253-bd60-14c5beff150d_2048x2048.png)
*Change the glasses in the green box to circular lenses, the orange purse in the blue box to a purple oval purse, and her shoes in the red box are patterned with leopard print.*

![Instruction following example 2](https://substack-post-media.s3.amazonaws.com/public/images/6ec0976b-1cb0-45e0-a657-ab97efd4d915_2048x2048.png)
*While maintaining the original composition, change the overall color tone to navy and white colors. Change "RTX PRO 6000" to "SEEDREAM 5.0 LITE" in the image, and change "2025" to "NOW LIVE".*

![Style transfer example](https://substack-post-media.s3.amazonaws.com/public/images/dc08a07e-edf1-4864-b6a6-5a7b17b78cfa_1920x1080.png)
*Refer to the second image and change the style of the first picture to match that of the second image.*

### Consistency showcase

![Design consistency](https://substack-post-media.s3.amazonaws.com/public/images/cc7b80ef-418c-4376-95e2-38c9110c6456_1920x1080.png)
*Refer to the design and layout style of Figure 2 and adapt the style of Figure 1 accordingly.*

![Character merge](https://substack-post-media.s3.amazonaws.com/public/images/22d1fa08-17f3-4113-86ee-ca0a324cbb3b_1920x1080.png)
*Merge Figure 1 and Figure 2 into a high-angle top-down selfie of two people, compact composition with them close together.*

![Multi-reference composition](https://substack-post-media.s3.amazonaws.com/public/images/2d690f6d-fa30-4152-9dc4-c09341c4e887_1920x1080.png)
*Use the flowers shown in Figure 1‑4 for flower arrangement. Arrange all the flowers in the vase shown in Figure 5, then place the vase on the table shown in Figure 6.*

![Product consistency](https://substack-post-media.s3.amazonaws.com/public/images/585cf84d-afe0-4277-b08a-7a0cddbd6a54_1620x1080.png)
*Using the bottle from the reference image, generate six product photos in different seasonal settings. Consistent bottle design across all six.*

## Seedream 5.0 lite text to image workflow

<img alt="Seedream 5.0 Lite Text-to-Image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_seedream_5_0_lite_t2i&utm_source=docs&utm_medium=referral&utm_campaign=seedream-5-lite">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_seedream_5_0_lite_t2i.json">
    Download JSON or search "Seedream 5.0 lite" in Template Library
  </Card>
</CardGroup>

### World knowledge showcase

![Gravity infographic](https://substack-post-media.s3.amazonaws.com/public/images/fac37b40-faaa-4360-b449-08da38322186_2562x1440.png)
*Pixel art infographic for explaining gravity, rendered in crisp 16-bit style with a dark navy/charcoal background and bold cinematic palette tones.*

![Big Bang infographic](https://substack-post-media.s3.amazonaws.com/public/images/39e35082-3b26-41df-8e09-5cc1841d94c6_2562x1440.png)
*Comic book style infographic for explaining the Big Bang and the age of dinosaurs, with a deep crimson and ink-black background and bold comic palette tones.*

## Get started

1. Update ComfyUI to the latest (0.15.0+)
2. Go to Template Library, search for `Seedream 5.0 lite`


# ByteDance Seedream 5.0 Pro - Professional AI Image Generation
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/seedream-5-pro

Generate high-quality images with enhanced instruction following, precise editing, and professional-grade output using Seedream 5.0 Pro in ComfyUI

Seedream 5.0 Pro is ByteDance's professional-grade image generation model, built as the more capable sibling to Seedream 5.0 Lite. It delivers higher fidelity, more precise instruction following, and stronger output consistency for demanding creative and production workflows.

## What Seedream 5.0 Pro is good at

* **Higher fidelity output**: Superior image quality with sharper detail, richer texture, and more accurate color reproduction across resolutions up to 4K
* **Precision instruction following**: Handles complex, multi-step prompts with greater accuracy, including precise spatial reasoning, typography, and dense text rendering
* **Enhanced multi-image editing**: Edits across up to 14 reference images while preserving subject identity, style, and composition more reliably than ever
* **Professional-grade consistency**: Character features, product design, lighting, and color palette stay stable across a batch of generated images
* **Deeper world knowledge**: Expanded knowledge base supports technical illustration, scientific visualization, and knowledge-heavy creative briefs

## Example outputs

Text-to-image generation, with the model handling composition, lighting, and detail:

![Seedream 5.0 Pro text to image example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/Seedream5.0_Pro_T2I.png)

Image editing with text instructions, keeping the original structure intact:

![Seedream 5.0 Pro image edit example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/Seedream5.0_Pro_image_edit.png)

Layer separation, which splits a flat image into an editable stack of up to 16 transparent layers plus an inpainted background plate:

![Seedream 5.0 Pro layer separation example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/thumbnail/api_bytedance_seedream_5_0_layer_separation.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Seedream 5.0 Pro text-to-image workflow

Generate a high-quality image from a text prompt, with Seedream 5.0 Pro handling composition, lighting, and detail.

<img alt="Seedream 5.0 Pro Text-to-Image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_seedream_5_0_pro_t2i&utm_source=docs&utm_medium=referral&utm_campaign=seedream-5-pro">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_seedream_5_0_pro_t2i.json">
    Download JSON or search "Seedream 5.0 Pro" in Template Library
  </Card>
</CardGroup>

![Seedream 5.0 Pro text to image preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/Seedream5.0_Pro_T2I.png)

## Seedream 5.0 Pro image edit workflow

Edit existing images with text instructions. Change objects, swap styles, adjust colors, or recompose scenes while keeping the original structure intact.

<img alt="Seedream 5.0 Pro Image Edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_seedream_5_0_pro_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=seedream-5-pro">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_seedream_5_0_pro_image_edit.json">
    Download JSON or search "Seedream 5.0 Pro" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/interior_college.png">
      Download sample input image
    </Card>
  </CardGroup>
</details>

![Seedream 5.0 Pro image edit input](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/interior_college.png)

![Seedream 5.0 Pro image edit output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/Seedream5.0_Pro_image_edit.png)

## Seedream 5.0 Pro layer separation workflow

Layer separation is the layer-decomposition pillar of Seedream 5.0 Pro's interactive precision editing. It splits a single flat image into an editable stack: one base image (background plate) plus up to 16 independent transparent layers, each with its stacking order, bounding-box coordinates, name, and semantic description. Regions hidden behind extracted subjects are seamlessly inpainted, so every layer and the base beneath it is a complete, standalone design asset ready for dragging, scaling, and recomposition.

With no prompt at all, the model automatically identifies every major element: text blocks, subjects, decorations, and background. A single poster can yield 10+ layers, with design-grade text separation that supports multilingual headlines and CJK fonts. You can also describe elements in natural language to control the separation, or target exact regions with bounding-box tags. The workflow is ideal for brand design, e-commerce asset creation, poster iteration, and any task where a flat bitmap needs to become an editable layered document.

<img alt="Seedream 5.0 Pro Layer Separation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_seedream_5_0_layer_separation&utm_source=docs&utm_medium=referral&utm_campaign=seedream-5-pro">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_seedream_5_0_layer_separation.json">
    Download JSON or search "Seedream 5.0 Pro" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/victory_cover.png">
      Download sample input image
    </Card>
  </CardGroup>
</details>

![Seedream 5.0 Pro layer separation preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/thumbnail/api_bytedance_seedream_5_0_layer_separation.png)

<Note>
  When using this workflow in the ComfyUI editor, switch to Nodes2.0 mode and click `Open Compositor` to view and arrange the separated layers.
</Note>

## Get started

1. Update ComfyUI to the latest version (0.15.0+)
2. Go to Template Library, search for `Seedream 5.0 Pro`


# Concurrency Limits
Source: https://docs.comfy.org/tutorials/partner-nodes/concurrency-limits

Understand how concurrency limits control simultaneous Partner Node requests on your account.

Concurrency limits control how many requests your account can process at the same time. Requests beyond your limit are rejected with a `429` error code. Your concurrency limit is based on your lifetime paid spend, and applies at the platform level across all endpoints you call.

<Note>
  Concurrency limits are tuned over time to keep the platform fast and reliable for everyone. The specific values on this page reflect the current configuration and may change.
</Note>

## How it works

When you submit a request, the platform tracks it against your concurrency limit. If you exceed the limit, additional requests are rejected with a `429` error until in-flight requests complete.

## Partner Node concurrency vs. Cloud job concurrency

This page covers the concurrency limit on Partner Node calls specifically. It's a separate, independently enforced limit from **Cloud job concurrency**, which controls how many Comfy Cloud workflow runs you can have executing at once and is set by your Cloud plan or subscription tier rather than your lifetime spend.

Because the two limits are enforced independently, your effective throughput is bounded by whichever one you reach first. A high Cloud plan does not, by itself, raise your Partner Node concurrency limit: that's governed separately by the lifetime spend tiers below.

## Concurrency tiers

Your concurrency limit is based on your **lifetime paid spend**: the total of all credit purchases and subscription payments across Comfy Cloud and Partner Nodes, combined. This total accumulates over the life of your account and does not reset or look back over a rolling window.

| Lifetime paid spend | Concurrency limit |
| :- | -: |
| \$0 (no purchases yet) | 1 |
| Above $0, up to $100 | 5 |
| \$100 or more | 10 |
| \$500 or more | 20 |
| \$1,000 or more | 40 |

How to read this table:

* **First match wins.** The rows are evaluated from most to least specific: a custom limit set by our team beats the spend tiers, which beat the never-paid floor. If you've paid \$1,200 lifetime, you get 40, and the lower tiers are never considered.
* **Lifetime, not rolling.** A payment from months ago still counts toward your tier. Spend doesn't expire or reset over time.
* **Cloud and Partner Node spend both count.** It doesn't matter whether you paid for Cloud subscriptions or Partner Node credits; both contribute to the same lifetime total.
* **Any payment lifts you off the floor.** Accounts that have never made a successful payment are capped at 1 concurrent call. A single successful payment moves you to the default tier (5), and the $100 / $500 / \$1,000 thresholds raise it from there.
* **Custom limits override the table.** If our team has set a specific limit on your account, for example for an enterprise arrangement or a policy restriction, it takes precedence over every spend-based row, including down to 0 (Partner Node access disabled).

Self-serve limits scale up to **40 concurrent requests** at the \$1,000 tier.

## Model-based limits

Higher-cost models have a lower allowed concurrency. When you call a model that costs **\$5 or more per request**, your concurrency limit for that model is **one quarter** of your account's tier limit (rounded down, with a minimum of 1). Requests to lower-cost models continue to use your full account limit, and the two limits are tracked independently.

## How concurrency slots work

A Partner Node call occupies one concurrency slot for the full duration of that call: from the moment the request is accepted until the provider returns a result, which for video or 3D generation can take several minutes. The slot is released as soon as the call finishes.

Only in-flight calls count against your limit. A completed call frees its slot immediately, so a workflow that makes many Partner Node calls over the course of its run will still complete successfully; it just can't have more calls running at the same instant than your limit allows.

## What happens when you reach your limit

When all your concurrency slots are occupied and you make another Partner Node call, that call is rejected immediately with an HTTP `429` status and a response body whose message tells you to wait for existing requests to complete.

* **A blocked account returns 403 instead.** If Partner Node access has been disabled on your account (a custom limit of 0), calls are rejected with an HTTP `403` rather than a `429`.
* **Concurrency is separate from your credit balance.** Concurrency slots only govern how many calls can run simultaneously. If your credit balance reaches zero, calls fail because you're out of credits, independent of how many concurrency slots you have free. Keep a positive balance to keep running.
* Whether a throttled call is retried automatically depends on how you're calling the API. Check the behavior of the specific node or client you're using.

## Concurrency response headers

Partner Node responses include headers that reflect your concurrency usage at the moment the request was processed. They're set on both successful and throttled responses, for API key and other callers alike:

| Header | Meaning |
| :- | :- |
| `X-Concurrency-Limit` | Your effective concurrency limit |
| `X-Concurrency-Current` | Calls currently in flight, including this one |
| `X-Concurrency-Remaining` | Slots still available |

These headers aren't returned for accounts with an unlimited custom limit, and they're best-effort: useful for visibility and debugging, but not intended as a precise scheduling signal.

## Increasing your limit

For concurrency above 40, contact our support team.

<Card title="Support" icon="life-ring" href="https://support.comfy.org/">
  Get help raising your concurrency limit
</Card>

## FAQ

<AccordionGroup>
  <Accordion title="Is the limit per request, per minute, or per simultaneous call?">
    Per simultaneous (in-flight) call. There's no cap here on total volume or how fast you make requests over time, only on how many can be running at once.
  </Accordion>

  <Accordion title="Does spending expire?">
    No. Your tier is based on lifetime spend, so past payments always continue to count toward it.
  </Accordion>

  <Accordion title="I have a high Cloud plan, but my Partner Node calls are still throttling. Why?">
    The two limits are separate. A high Cloud job concurrency doesn't raise your Partner Node concurrency limit; that's governed by lifetime spend instead. See [Partner Node concurrency vs. Cloud job concurrency](#partner-node-concurrency-vs-cloud-job-concurrency).
  </Accordion>
</AccordionGroup>


# Partner Node Data Retention
Source: https://docs.comfy.org/tutorials/partner-nodes/data-retention

How Comfy stores and deletes Partner Node inputs and outputs, and how long media files are retained.

Every Partner Node request produces data that is stored on our platform: inputs (images, videos, 3D assets, audio), and outputs produced by the model. This page explains how long each kind of data is retained. Where each provider processes that data by default is tracked separately on the [Model Providers](/tutorials/partner-nodes/model-providers).

## What gets stored

When you run a Partner Node, two kinds of files are stored:

* **Input files**: reference images, audio, and other media you provide to a node. Inputs are uploaded to your account's storage space.
* **Output files**: the images, videos, audio, and other media a node generates. Outputs are written to Comfy-managed storage and returned to you as download URLs.

Both input and output files are stored in Comfy-managed cloud storage buckets.

## How long files are kept

All Partner Node media files are automatically deleted **24 hours** after they are created. The deletion applies to both input and output files.

| File type | Deleted after |
| - | - |
| Input files | 24 hours |
| Output files | 24 hours |

<Note>
  The 24-hour deletion window is a platform default and applies to all Partner Node calls. If you need to keep files longer, download them to your own storage before they expire.
</Note>

## What happens after deletion

Once a file is deleted, its download URL returns an error. Deleted files cannot be recovered, and the same media must be re-uploaded or regenerated if you need it again.

Deleting an input file also removes the corresponding file record from your account storage, so the input cannot be reused by later calls.

## Keeping files longer

If your workflow needs an input file to remain available for longer than 24 hours, re-upload the file before each job. For long-running pipelines, re-upload right before the call that needs it.

For outputs you want to keep, download them to your own storage within the 24-hour window.

## Reference

| Item | Value |
| - | - |
| Input file retention | 24 hours |
| Output file retention | 24 hours |

For general information about how Comfy handles customer data, see [Data Retention](/support/data-retention).


# FAQs about Partner Nodes
Source: https://docs.comfy.org/tutorials/partner-nodes/faq

Some FAQs you may encounter when using Partner Nodes.

This article addresses common questions regarding the use of Partner nodes.

<AccordionGroup>
  <Accordion title="Why can't I find the Partner Nodes?">
    Please update your ComfyUI to the latest version (the latest commit or the latest [desktop version](https://www.comfy.org/download)).
    We may add more API support in the future, and the corresponding nodes will be updated, so please keep your ComfyUI up to date.

    <Tip>
      Please note that you need to distinguish between the nightly version and the release version.
      In some cases, the latest `release` version may not be updated in time compared to the `nightly` version.
      Since we are still iterating quickly, please ensure you are using the latest version when you cannot find the corresponding node.
    </Tip>
  </Accordion>

  <Accordion title="Why can't I use / log in to the Partner Nodes?">
    API access requires that your current request is based on a secure network environment. The current requirements for API access are as follows:

    * The local network only allows access from `127.0.0.1` or `localhost`, which may mean that you cannot use the Partner Nodes in a ComfyUI service started with the `--listen` parameter in a LAN environment.
    * Able to access our API service normally (a proxy service may be required in some regions).
    * Your account does not have enough [credits](/interface/credits).
  </Accordion>

  <Accordion title="Why can't I use Partner Node even after logging in, or why does it keep asking me to log in while using?">
    * Currently, only `127.0.0.1` or `localhost` access is supported.
    * Ensure your account has enough credits.
  </Accordion>

  <Accordion title="Can Partner Nodes be used for free?">
    Partner Nodes require credits for API calls to closed-source models, so they do not support free usage.
  </Accordion>

  <Accordion title="How to purchase credits?">
    Please refer to the following documentation:

    1. [Comfy Account](/interface/user): Find the `User` section in the settings menu to log in.
    2. [Credits](/interface/credits): After logging in, the settings interface will show the credits menu. You can purchase credits in `Settings` → `Credits`. We use a prepaid system, so there will be no unexpected charges.
    3. Complete the payment through Stripe.
    4. Check if the credits have been updated. If not, try restarting or refreshing the page.
  </Accordion>

  <Accordion title="Are unused credits refundable?">
    Currently, we do not support refunds for credits.
    If you believe there is an error resulting in unused balance due to technical issues, please [contact support](mailto:support@comfy.org).
  </Accordion>

  <Accordion title="Can credits go negative?">
    Credits are not intended to be used as a negative balance or credit line. However, due to race conditions where partner nodes don't always report costs before execution, a single execution may consume more credits than your remaining balance and temporarily result in a negative balance after completion. When your balance is negative, you will not be able to run Partner Nodes until you top up and restore a positive balance. Please ensure you have enough credits before making API calls.
  </Accordion>

  <Accordion title="Where can I check usage and expenses?">
    Please visit the [Credits](/interface/credits) menu after logging in to check the corresponding credits.
  </Accordion>

  <Accordion title="Is it possible to use my own API Key?">
    Currently, the Partner Nodes are still in the testing phase and do not support this feature yet, but we have considered adding it.
  </Accordion>

  <Accordion title="Do credits expire?">
    Yes, the expiration depends on the type of credits:

    * **Monthly credits**: Expire at the end of your billing period
    * **Top-up credits**: Expire 1 year from the date of purchase
  </Accordion>

  <Accordion title="Can credits be transferred or shared?">
    No, your credits cannot be transferred to other users and are limited to the currently logged-in account, but we do not restrict the number of devices that can log in.
  </Accordion>

  <Accordion title="Can I use the same account on different devices?">
    We do not limit the number of devices that can log in; you can use your account anywhere you want.
  </Accordion>

  <Accordion title="How can I request for my account or information to be deleted??">
    Email a request to [support@comfy.org](mailto:support@comfy.org) and we will delete your information
  </Accordion>

  <Accordion title="Is there content moderation for Partner Nodes?">
    Partner Nodes send your inputs (prompts, images, and other content) to third-party providers for processing. These providers enforce their own content moderation policies. Please do not submit NSFW or other prohibited content to API nodes.
  </Accordion>
</AccordionGroup>


# Nano Banana 2 - Fast AI Image Generation
Source: https://docs.comfy.org/tutorials/partner-nodes/google/nano-banana-2

Generate high-quality images with Pro-level quality at Flash speed using Nano Banana 2 in ComfyUI

Nano Banana 2 is now available in ComfyUI through Partner Nodes. This release fundamentally changes the default choice for most creators, delivering Pro-level quality at Flash speed.

## What Nano Banana 2 is good at

* **Pro-level quality at Flash speed**: Richer textures, sharper detail, stronger lighting, and better prompt adherence without the latency tradeoff
* **Search-grounded world knowledge**: Intelligently triggers Google Image Search grounding to improve factual accuracy for lesser-known landmarks, niche objects, or real-world details
* **Subject consistency**: Maintain character resemblance of up to 5 characters and fidelity of up to 14 objects in a single workflow
* **Configurable thinking levels**: Control how much the model "thinks" before generating (Minimal for fast exploration, High/Dynamic for complex layouts)
* **Precision text rendering and translation**: Generate accurate, legible text for marketing mockups, greeting cards, and localized assets

## Example outputs

Text replacement in an existing image, keeping quality intact:

![Quality comparison](https://substack-post-media.s3.amazonaws.com/public/images/1f92ae2e-14d8-4a3b-9ed7-e57dacd2584f_1825x1696.png)
*Replace the text from the input image with: Nano Banana 2 Available on ComfyUI Cheaper and Faster*

Search-grounded world knowledge for factually accurate infographics:

![Educational infographic](https://substack-post-media.s3.amazonaws.com/public/images/edfe3b6b-8942-472e-8772-a3700946fc23_1024x559.png)
*Educational comic book style infographic explaining five lesser-known North American native species, with search-grounding to ensure accurate depictions of rare habitats and ecological roles.*

![Skateboard culture infographic](https://substack-post-media.s3.amazonaws.com/public/images/536b845b-b278-4924-b8e4-114e5e5defa9_2752x1536.png)
*Comic book style infographic for American skateboard culture evolution from the 1970s to the 2020s.*

Subject consistency across a storyboard sequence:

![Subject consistency](https://substack-post-media.s3.amazonaws.com/public/images/e38f7afb-9752-49a1-9e6c-1ea99dba42ff_4908x2626.png)
*Maintain character resemblance and object fidelity across storyboard sequences.*

Configurable thinking levels for different reasoning depth:

![Thinking levels comparison](https://substack-post-media.s3.amazonaws.com/public/images/6d0d4773-3ff5-4319-bc00-8afb62c2a1ad_4608x1332.png)
*Cinematic portrait with different thinking levels: Minimal for quick iterations, High for detailed outputs.*

![Art Nouveau portrait](https://substack-post-media.s3.amazonaws.com/public/images/49e5f98a-b375-4fda-b280-7b695f535807_4608x1332.png)
*Art Nouveau inspired portrait with configurable reasoning depth.*

Text rendering and translation into localized variants:

![Text rendering](https://substack-post-media.s3.amazonaws.com/public/images/808ca8d0-acac-470d-a666-23e411254276_1376x768.png)
*Amateur cellphone photograph with stylized graffiti text rendering.*

![Spanish translation](https://substack-post-media.s3.amazonaws.com/public/images/6af9b091-7bbe-49da-b70f-e766394039ef_2784x1536.png)
*Translate text to Spanish.*

![Hindi translation](https://substack-post-media.s3.amazonaws.com/public/images/548d44f6-d43e-484f-a8d8-37638f9ff482_2784x1536.png)
*Translate text to Hindi.*

![Mandarin translation](https://substack-post-media.s3.amazonaws.com/public/images/5f4a52f9-1995-440f-8394-245e43f3a9a2_2784x1536.png)
*Translate text to Mandarin.*

## Use it

<Card title="Call it from code" icon="code" href="/development/comfy-router/models/google/nano-banana-2/code">
  Call it over HTTP through Comfy Router, with copy-paste Python, TypeScript, Swift and cURL snippets
</Card>

This runs on the same Comfy account and is billed in the same credits as running it in ComfyUI below. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for per-model rates and [Concurrency limits](/tutorials/partner-nodes/concurrency-limits) for how many requests you can have in flight.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Nano Banana 2 image edit workflow

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_google_nano_banana2_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=nano-banana-2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_google_nano_banana2_image_edit.json">
    Download JSON or search "Nano Banana 2" in Template Library
  </Card>
</CardGroup>

![Nano Banana 2 workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_google_nano_banana2_image_edit-1.webp)

<Card title="Download Sample Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/man_with_dog.png">
  Get the example input image for this workflow
</Card>

## Character turnaround sheet workflow

Generate a character turnaround sheet from a single reference image: front, side, and back views of the same subject on one sheet. The sheet feeds directly into the [Pixal3D Multi Views to 3D](/tutorials/3d/pixal3d#pixal3d-multi-views) workflow, or you can use it as a character reference sheet for video and image generation.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_google_nano_banana_create_turnaround_sheet&utm_source=docs&utm_medium=referral&utm_campaign=nano-banana-2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_google_nano_banana_create_turnaround_sheet.json">
    Download JSON or search "Character Turnaround Sheet Generator" in Template Library
  </Card>
</CardGroup>

![Character turnaround sheet workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_google_nano_banana_create_turnaround_sheet-1.webp)

<Card title="Download Sample Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/white_mech_front_ortho.png">
  Get the example input image for this workflow
</Card>

## Which model should you pick?

| Model | Best for |
| - | - |
| **Nano Banana 2** | Most creators: fast enough to explore, smart enough to refine, polished enough to ship |
| **Nano Banana Pro** | Maximum factual precision and high-stakes edge cases |

## Get started

1. Update ComfyUI to the latest version
2. Double-click the canvas and search for the "Nano Banana 2" node
3. Or go to the Template Library to use the ready-to-go workflow
4. Choose your resolution, set your aspect ratio, and decide whether the prompt needs deeper reasoning

<Note>
  The new model version has also been added to the previous "Nano Banana Pro" node. If you have old workflows with this node, you don't need to rebuild them: just reselect the model version.
</Note>


# Nano Banana 2 Lite: Fast AI Image Generation
Source: https://docs.comfy.org/tutorials/partner-nodes/google/nano-banana-2-lite

Generate images at Google's fastest speed and lowest cost using Nano Banana 2 Lite, the Gemini 3.1 Flash-Lite Image model in ComfyUI

Nano Banana 2 Lite is Google DeepMind's fastest and most cost-efficient Gemini Image model, designed for rapid ideation and high-volume workflows. Powered by `gemini-3.1-flash-lite-image`, it delivers text-to-image generation in approximately 4 seconds at \$0.041 per image, making it ideal for quick concept visualization, rapid prototyping, and iterative design exploration.

## What Nano Banana 2 Lite is good at

* **Ultra-fast generation**: Text-to-image outputs in as little as 4 seconds, built for interactive prototyping and rapid visual drafting
* **Cost-efficient**: Priced at \$0.041 per 1K-resolution image, the most affordable option in the Nano Banana family
* **Character consistency**: Maintain character identities and object fidelity across multiple rapid generations
* **In-image text rendering**: Draft copy and render legible text directly into generated images for localized ad variations
* **Configurable model selection**: Choose between Nano Banana 2 Lite, Nano Banana 2, and Nano Banana Pro within the same node

## Example outputs

Text-to-image generation from a single prompt:

![Nano Banana 2 Lite Text to Image](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_nano_banana_2_lite_t2i.png)

Image editing from a text instruction:

![Nano Banana 2 Lite Image Edit - Output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_nano_banana_2_lite_image_edit.png)

## Use it

<Card title="Call it from code" icon="code" href="/development/comfy-router/models/google/nano-banana-2-lite/code">
  Call it over HTTP through Comfy Router, with copy-paste Python, TypeScript, Swift and cURL snippets
</Card>

This runs on the same Comfy account and is billed in the same credits as running it in ComfyUI below. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for per-model rates and [Concurrency limits](/tutorials/partner-nodes/concurrency-limits) for how many requests you can have in flight.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Workflows

### Text to Image

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_nano_banana_2_lite_t2i&utm_source=docs&utm_medium=referral&utm_campaign=nano_banana_2_lite">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_nano_banana_2_lite_t2i.json">
    Download JSON or search "Nano Banana 2 Lite" in Template Library
  </Card>
</CardGroup>

Generate images from text descriptions. No file inputs required — just enter your prompt and the workflow produces one or more generated images with support for interleaved text and image inputs.

![Nano Banana 2 Lite Text to Image](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_nano_banana_2_lite_t2i.png)

### Image Edit

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_nano_banana_2_lite_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=nano_banana_2_lite">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_nano_banana_2_lite_image_edit.json">
    Download JSON or search "Nano Banana 2 Lite" in Template Library
  </Card>

  <Card title="Download Sample Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/red_f1_track_car.png">
    Get the example input image for this workflow
  </Card>
</CardGroup>

Upload an image and provide a text instruction to edit it. The workflow produces a side-by-side comparison of the original and edited result.

<div>
  <img alt="Nano Banana 2 Lite Image Edit - Input" />

  <img alt="Nano Banana 2 Lite Image Edit - Output" />
</div>

## Which model should you pick?

| Model | Best for |
| - | - |
| **Nano Banana 2 Lite** | Speed and cost — rapid iteration, high-throughput pipelines, low-latency applications |
| **[Nano Banana 2](/tutorials/partner-nodes/google/nano-banana-2)** | Most creators — balanced quality and speed for general-purpose image generation and editing |
| **[Nano Banana Pro](/tutorials/partner-nodes/google/nano-banana-pro)** | Professional use cases — maximum quality, 4K generation, complex layouts and precise control |

## Get started

1. Update ComfyUI to the latest version
2. Double-click the canvas and search for the "Nano Banana 2" node (it includes Nano Banana 2 Lite as a model option)
3. Or go to the Template Library to use the ready-to-go workflow
4. Select "Nano Banana 2 Lite" from the model dropdown for fastest generation

<Note>
  Nano Banana 2 Lite is available within the existing Nano Banana 2 node. If you have old workflows using this node, you can select "Nano Banana 2 Lite" from the model version dropdown without rebuilding your workflow.
</Note>


# Nano Banana Pro: Studio-Quality AI Image Generation
Source: https://docs.comfy.org/tutorials/partner-nodes/google/nano-banana-pro

Generate and edit production-ready 4K images with Nano Banana Pro (Gemini 3 Pro Image) in ComfyUI, with advanced text rendering and character consistency.

Nano Banana Pro is Google DeepMind's flagship image model (Gemini 3 Pro Image) for studio-quality image generation and editing. It pushes beyond casual creation into production-ready visuals with advanced capabilities including native 4K resolution, precise text rendering in 10 languages, multi-image blending, and search-grounded world knowledge for accurate real-world depictions.

## What Nano Banana Pro is good at

* **4K generation**: Create and edit images in native 4K resolution with studio-quality color grading, angle control, and focus adjustments
* **World knowledge**: Generates accurate, real-world images by tapping into Google Search's knowledge base for lesser-known landmarks, niche objects, and cultural details
* **Text and translation**: Renders clean, legible text and supports detection and translation across 10 languages
* **Multi-image blending**: Blend up to 14 images with precise compositional control
* **Character and subject consistency**: Maintain character resemblance and object fidelity across complex multi-subject compositions
* **Advanced reasoning**: Configurable thinking levels. Choose Minimal for fast exploration or High/Dynamic for complex layouts and precise control

## Example outputs

Multi-image blending, combining two reference images into one studio-quality result:

![Nano Banana Pro example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_nano_banana_pro.png)

## Use it

<Card title="Call it from code" icon="code" href="/development/comfy-router/models/google/nano-banana-pro/code">
  Call it over HTTP through Comfy Router, with copy-paste Python, TypeScript, Swift and cURL snippets
</Card>

This runs on the same Comfy account and is billed in the same credits as running it in ComfyUI below. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for per-model rates and [Concurrency limits](/tutorials/partner-nodes/concurrency-limits) for how many requests you can have in flight.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Nano Banana Pro

Nano-banana Pro (Gemini 3.0 Pro Image) for studio-quality 4K image generation and editing with enhanced text rendering and character consistency.

<img alt="Nano Banana Pro workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_nano_banana_pro&utm_source=docs&utm_medium=referral&utm_campaign=nano-banana-pro">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_nano_banana_pro.json">
    Download JSON or search "Nano Banana Pro" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="api_nano_banana_pro_input_image_1.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_nano_banana_pro_input_image_1.png">
    `LoadImage` node 11 · `api_nano_banana_pro_input_image_1.png`
  </Card>

  <Card title="api_nano_banana_pro_input_image_2.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_nano_banana_pro_input_image_2.png">
    `LoadImage` node 12 · `api_nano_banana_pro_input_image_2.png`
  </Card>
</CardGroup>

**Example output**

![Nano Banana Pro example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_nano_banana_pro.png)

## Which model should you pick?

| Model | Best for |
| - | - |
| **[Nano Banana 2 Lite](/tutorials/partner-nodes/google/nano-banana-2-lite)** | Speed and cost: rapid iteration, high-throughput pipelines, low-latency applications |
| **[Nano Banana 2](/tutorials/partner-nodes/google/nano-banana-2)** | Most creators: balanced quality and speed for general-purpose image generation and editing |
| **Nano Banana Pro** | Professional use cases: maximum quality, 4K generation, complex layouts and precise control |

## Get started

1. Update ComfyUI to the latest version
2. Double-click the canvas and search for the "Nano Banana Pro" node
3. Or go to the Template Library to use the ready-to-go workflow
4. Upload your reference images, enter your prompt, and select the desired thinking level

<Note>
  Nano Banana Pro provides the highest quality output in the Nano Banana family. For faster generation at lower cost, consider [Nano Banana 2 Lite](/tutorials/partner-nodes/google/nano-banana-2-lite) or [Nano Banana 2](/tutorials/partner-nodes/google/nano-banana-2).
</Note>


# Grok Imagine Image in ComfyUI: AI Image Generation and Editing
Source: https://docs.comfy.org/tutorials/partner-nodes/grok/grok-image

Generate and edit images with the Grok Imagine Image model in ComfyUI: text-to-image and natural-language image editing

Grok Image is xAI's image generation model, available in ComfyUI through the Grok partner nodes. It generates images from text prompts and edits uploaded images with natural-language instructions, supporting 13 aspect ratios and 1K or 2K output.

## What Grok Imagine Image is good at

* **Text-to-image generation**: creates single images from a text prompt describing the scene and style
* **Natural-language image editing**: edits an uploaded image based on your prompt while keeping the original composition, changing the scene, lighting, or style
* **Flexible aspect ratios**: supports 13 aspect ratios, including `1:1`, `16:9`, and `9:16`
* **Resolution options**: outputs at 1K or 2K

## Example outputs

Text-to-image generation from a single prompt:

![Grok text-to-image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_grok_text_to_image.png)

Image editing with natural-language instructions, keeping the original composition:

![Grok image edit output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_grok_image_edit.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Grok: Text to Image

Generate images from a text prompt with the standard `grok-imagine-image` model. This workflow is the fastest way to create single images in ComfyUI with Grok, supporting 13 aspect ratios and 1K or 2K output.

<img alt="Grok text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_grok_text_to_image&utm_source=docs&utm_medium=referral&utm_campaign=grok-image">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_grok_text_to_image.json">
    Download JSON or search "Grok Imagine" in Template Library
  </Card>
</CardGroup>

![Grok text-to-image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_grok_text_to_image.png)

### Workflow overview

This workflow uses two nodes:

* **GrokImageNode**: the core node, configured with the `grok-imagine-image` model
* **SaveImage**: saves the generated image

### Steps to run

1. **Enter your prompt**: describe the scene and style in the **GrokImageNode**
2. **Choose aspect ratio**: pick from ratios such as `1:1`, `16:9`, `9:16`, and more
3. **Set resolution**: `1K` or `2K`
4. **Click Queue**: press `Ctrl+Enter` to generate

## Grok: Image Edit

Edit an uploaded image with natural-language instructions. This workflow keeps the original composition and changes the scene, lighting, or style based on your prompt.

<img alt="Grok image edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_grok_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=grok-image">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_grok_image_edit.json">
    Download JSON or search "Grok Imagine" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image: cyberpunk_robot.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/cyberpunk_robot.png">
      A robot design used as the base image for editing
    </Card>
  </CardGroup>
</details>

![Grok image edit output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_grok_image_edit.png)

### Workflow overview

This workflow uses three nodes:

* **LoadImage**: provides the source image to edit
* **GrokImageEditNode**: the core node, configured with the `grok-imagine-image` model
* **SaveImage**: saves the edited image

### Steps to run

1. **Load an image**: connect your image to the **LoadImage** node
2. **Describe the edit**: tell the model what to change in the **GrokImageEditNode** prompt
3. **Click Queue**: press `Ctrl+Enter` to generate


# Grok Imagine Image 2.0 in ComfyUI: AI Image Generation and Editing
Source: https://docs.comfy.org/tutorials/partner-nodes/grok/grok-image-2-0

Generate and edit images with Grok Imagine Image 2.0 in ComfyUI: Aurora engine, crisp short-text rendering, 1K/2K output, and up to 3 reference images

Grok Imagine Image 2.0 is xAI's latest image model, available in ComfyUI through the Grok partner nodes. Built on the Aurora engine, it excels at crisp short-text rendering and produces 1K or 2K images across 14 aspect ratios, making it well suited for posters, covers, product and brand visuals, and character-driven scenes where consistency matters.

## What Grok Imagine Image 2.0 is good at

* **Crisp short-text rendering**: the Aurora engine renders short text cleanly, making it well suited for posters, covers, and product and brand visuals
* **Reference-guided image editing**: edits images with precise, natural-language instructions and up to 3 reference images to modify elements, swap backgrounds, or restyle scenes
* **Character consistency**: keeps a character consistent across multiple outputs in character-driven scenes
* **14 aspect ratios**: from `1:1` to `9:20`
* **Cost control**: 1K or 2K resolution with low or medium quality options to balance cost and fidelity

## Example outputs

Poster-style text-to-image generation with crisp text rendering:

![Grok Imagine Image 2.0 text-to-image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_grok_imagine_image_2_t2i.png)

Image editing guided by character and product reference images:

![Grok Imagine Image 2.0 image edit output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_grok_imagine_image_2_image_edit.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Grok Imagine Image 2.0: Text to Image

Generate a full poster-style image from a single text prompt with the Aurora engine. This workflow excels at crisp short-text rendering, making it well suited for posters, covers, product and brand visuals, and character-driven scenes. It outputs 1K or 2K images across 14 aspect ratios, with low or medium quality options to control cost.

<img alt="Grok Imagine Image 2.0 text-to-image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_grok_imagine_image_2_t2i&utm_source=docs&utm_medium=referral&utm_campaign=grok-image-2-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_grok_imagine_image_2_t2i.json">
    Download JSON or search "Grok Imagine Image 2.0" in Template Library
  </Card>
</CardGroup>

![Grok Imagine Image 2.0 text-to-image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_grok_imagine_image_2_t2i.png)

### Workflow overview

This workflow uses two nodes:

* **GrokImageNode**: the core node, configured with the `grok-imagine-image-2.0` model
* **SaveImageAdvanced**: saves the generated image as PNG

### Steps to run

1. **Enter your prompt**: describe the scene, style, and any text you want rendered in the **GrokImageNode**
2. **Choose aspect ratio**: pick from 14 ratios, from `1:1` to `9:20`
3. **Select resolution**: `1K` for faster results or `2K` for more detail
4. **Set quality**: `low` or `medium` to control cost and fidelity
5. **Set seed**: control whether the node re-runs; outputs are not reproducible regardless of seed
6. **Click Queue**: press `Ctrl+Enter` to generate

## Grok Imagine Image 2.0: Image Edit

Edit images with precise, natural-language instructions and up to 3 reference images. Use this workflow to modify specific elements, swap backgrounds, restyle scenes, or keep a character consistent across multiple outputs. The Aurora engine delivers crisp short-text rendering at 1K or 2K resolution across 14 aspect ratios.

<img alt="Grok Imagine Image 2.0 image edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_grok_imagine_image_2_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=grok-image-2-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_grok_imagine_image_2_image_edit.json">
    Download JSON or search "Grok Imagine Image 2.0" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="Character reference: model_blue_outfit.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/model_blue_outfit.png">
      A young woman in a cobalt blue textured outfit, used as the character reference
    </Card>

    <Card title="Product reference: pink_lipstick.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/pink_lipstick.png">
      A square pink matte lipstick, used as the product reference
    </Card>
  </CardGroup>
</details>

![Grok Imagine Image 2.0 image edit output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_grok_imagine_image_2_image_edit.png)

### Workflow overview

This workflow uses four nodes:

* **LoadImage** x2: provide the character and product reference images (the node accepts up to 3)
* **GrokImageEditNodeV2**: the core node, configured with the `grok-imagine-image-2.0` model
* **SaveImage**: saves the edited image

### Steps to run

1. **Load your references**: connect up to 3 reference images to the **LoadImage** nodes
2. **Describe the edit**: tell the model what to keep, change, or restyle in the **GrokImageEditNodeV2** prompt
3. **Set resolution**: `1K` or `2K`
4. **Click Queue**: press `Ctrl+Enter` to generate


# Grok Imagine Image Quality in ComfyUI: AI Image Generation
Source: https://docs.comfy.org/tutorials/partner-nodes/grok/grok-image-quality

Generate enhanced images with Grok Imagine Image Quality in ComfyUI: improved detail, better text rendering, and stronger creative control

Grok Imagine Image Quality is xAI's higher-fidelity image model, available in ComfyUI through the Grok partner nodes. It adds improved detail, better text rendering, and stronger creative control compared to the standard Grok image model.

## What Grok Imagine Image Quality is good at

* **Improved detail**: higher-fidelity output than the standard Grok image model
* **Better text rendering**: handles prompts that include text you want rendered in the image
* **Stronger creative control**: more control over the generated result compared to the standard model
* **Resolution options**: outputs at 1K or 2K

## Example outputs

Enhanced image generation with the `grok-imagine-image-quality` model:

![Grok Imagine Image Quality generation output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_grok_imagine_image_quality_image_generation.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Grok Imagine Image Quality: Generation

Generate enhanced images with the `grok-imagine-image-quality` model, which adds improved detail, better text rendering, and stronger creative control compared to the standard model.

<img alt="Grok Imagine Image Quality generation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_grok_imagine_image_quality_image_generation&utm_source=docs&utm_medium=referral&utm_campaign=grok-image-quality">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_grok_imagine_image_quality_image_generation.json">
    Download JSON or search "Grok Imagine Image Quality" in Template Library
  </Card>
</CardGroup>

![Grok Imagine Image Quality generation output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_grok_imagine_image_quality_image_generation.png)

### Workflow overview

This workflow uses two nodes:

* **GrokImageNode**: the core node, configured with the `grok-imagine-image-quality` model
* **SaveImage**: saves the generated image

### Steps to run

1. **Enter your prompt**: describe the scene and any text you want rendered in the **GrokImageNode**
2. **Choose aspect ratio**: pick from the available ratios
3. **Set resolution**: `1K` or `2K`
4. **Click Queue**: press `Ctrl+Enter` to generate


# Grok in ComfyUI: AI Image and Video Generation
Source: https://docs.comfy.org/tutorials/partner-nodes/grok/grok-overview

Use xAI's Grok models in ComfyUI: Grok Imagine Image for text-to-image and image editing, and Grok Imagine Video for video generation, editing, and extension

Grok is xAI's family of generative models, available in ComfyUI through the Grok partner nodes. It covers image generation and editing with **Grok Imagine Image** and video generation, editing, and extension with **Grok Imagine Video**, across multiple model versions.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Grok Imagine Image

Grok Imagine Image generates images from text prompts and edits uploaded images with natural-language instructions. Pick the model that fits your use case:

<CardGroup>
  <Card title="Grok Imagine Image" icon="image" href="/tutorials/partner-nodes/grok/grok-image">
    The standard model for text-to-image and image editing, with 13 aspect ratios and 1K or 2K output
  </Card>

  <Card title="Grok Imagine Image 2.0" icon="image" href="/tutorials/partner-nodes/grok/grok-image-2-0">
    The latest image model on the Aurora engine, with crisp short-text rendering and up to 3 reference images
  </Card>

  <Card title="Grok Imagine Image Quality" icon="sparkles" href="/tutorials/partner-nodes/grok/grok-image-quality">
    A higher-fidelity model with improved detail, better text rendering, and stronger creative control
  </Card>
</CardGroup>

## Grok Imagine Video

Grok Imagine Video generates short videos from a text prompt or an image, edits uploaded footage with natural-language instructions, extends clips seamlessly, and creates videos guided by reference images.

<CardGroup>
  <Card title="Grok Imagine Video" icon="video" href="/tutorials/partner-nodes/grok/grok-video">
    The standard video model: generation, editing, extension, and reference-to-video workflows
  </Card>

  <Card title="Grok Imagine Video 1.5" icon="video" href="/tutorials/partner-nodes/grok/grok-imagine-video-1-5">
    The latest video model: image-to-video generation with native audio at up to 1080p
  </Card>
</CardGroup>


# Ideogram 4.5 in ComfyUI: Text to Image and Edit
Source: https://docs.comfy.org/tutorials/partner-nodes/ideogram/ideogram-4-5

Run the Ideogram 4.5 partner nodes in ComfyUI for text to image, image edit, and precise edit that keeps untouched pixels identical

**Ideogram 4.5** is the newer model in the family and Ideogram's most precise edit model: it changes only what the prompt asks for, so repeated edits keep colors, textures, and details in place. It ships in ComfyUI as three partner nodes that are billed per image through the same Comfy account as the rest of the partner nodes. Ideogram 4.0 keeps its own page: [Ideogram 4.0 in ComfyUI](/tutorials/partner-nodes/ideogram/ideogram-v4).

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Text to Image

Generate an image from a text prompt, at a canvas size and quality tier you choose.

<img alt="Ideogram 4.5 text to image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_ideogram_v4_5_t2i&utm_source=docs&utm_medium=referral&utm_campaign=ideogram-v4-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_ideogram_v4_5_t2i.json">
    Download JSON or search "Ideogram 4.5: Text to Image" in Template Library
  </Card>
</CardGroup>

![Ideogram 4.5 text to image example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_ideogram_v4_5_t2i.png)

The **Ideogram 4.5 Text to Image** node takes:

| Input | Values | Effect |
| - | - | - |
| `prompt` | up to 10000 characters | The image description. A structured JSON caption works here too, for example a `final_prompt` from an earlier run |
| `size` | `auto` or a 1K or 2K preset | `auto` lets the model pick a canvas that suits the prompt. Presets cover both 1K and 2K and run from `1:1` to `23:9`, for example `(2K) 2048x2048 (1:1)` and `(1K) 1280x720 (16:9)` |
| `quality` | `low`, `medium` (default), `high` | Higher tiers cost more and take longer |
| `magic_prompt` | `auto` (default), `on`, `off` | Rewrites the prompt into a detailed structured caption before generating. `off` keeps your wording as literal as possible |
| `seed` | integer | Text to image is not reproducible from the seed alone, because the prompt is rewritten on every run |

The node also outputs `final_prompt`, the structured caption the image was generated from. To reproduce an image, feed that caption back with `magic_prompt` set to `off` and the same seed.

## Image Edit

Edit or combine up to five images with one instruction. `image_1` is the image being edited; images 2 to 5 supply design, material, or color references. Address them in the prompt as `@Image1`, `@Image2`, and so on.

<img alt="Ideogram 4.5 image edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_ideogram_v4_5_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=ideogram-v4-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_ideogram_v4_5_image_edit.json">
    Download JSON or search "Ideogram 4.5: Image Edit" in Template Library
  </Card>
</CardGroup>

**Input material**

<Card title="interior_orange_sofa.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/interior_orange_sofa.png">
  Load into the `image_1` slot on the Ideogram 4.5 Edit node
</Card>

The template builds its instruction with a **Build JSON Prompt** node, so you can mark a region of the image and caption it, for example "remove it". Turn on [Nodes 2.0](/interface/nodes-2) if the editor does not appear.

The **Ideogram 4.5 Edit** node adds:

| Input | Values | Effect |
| - | - | - |
| `size` | `auto` (default), `source`, a preset, or `custom` | `auto` picks a canvas of about 2K from the images and the prompt. `source` keeps the size of `image_1`. A preset with a different aspect ratio recomposes the scene. `custom` uses the `width` and `height` below |
| `width`, `height` | 256 to 4608, step 32 | Used only when `size` is `custom`. The two dimensions together must stay within 4194304 pixels (2048x2048) and within an aspect ratio of 6:1 |
| `quality` | `very_low`, `low`, `medium` (default), `high` | Higher tiers cost more and take longer |
| `seed` | integer | The same images, prompt, settings, and seed give the same result |

Up to five images can be connected in total. Inputs above roughly 4 MP are scaled down before they are uploaded, and each image must sit between 1:6 and 6:1.

Edit re-renders the whole image, so it can shift the framing and the untouched areas along with the edit. Use Precise Edit when the rest of the picture has to stay exactly as it is.

## Precise Edit

Change only what the prompt asks for. Untouched pixels stay identical and the output keeps the size of `image_1`. Accepts up to four reference images beyond the image being edited.

<img alt="Ideogram 4.5 precise edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_ideogram_v4_5_precise_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=ideogram-v4-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_ideogram_v4_5_precise_image_edit.json">
    Download JSON or search "Ideogram 4.5: Precise Edit" in Template Library
  </Card>
</CardGroup>

**Input material**

<Card title="redhair_girl_portrait.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/redhair_girl_portrait.png">
  Load into the `image_1` slot on the Ideogram 4.5 Precise Edit node
</Card>

Precise Edit shares the reference slots, `@Image1` addressing, `quality`, and `seed` controls with Edit. It has no size control, because the output always matches the size of `image_1`. The template draws its instruction with the **Build JSON Prompt** node as well.

Use it for product recolors, material swaps, and touch-ups that must leave the lighting, background, and framing of the rest of the photo alone.


# Ideogram P-Image - fast text-to-image
Source: https://docs.comfy.org/tutorials/partner-nodes/ideogram/ideogram-p-image

Generate images from text descriptions using Ideogram's fast P-Image model in ComfyUI, with quality comparable to leading models at lower cost and latency

Ideogram P-Image is Ideogram's fast text-to-image model, delivering quality comparable to leading image models at significantly lower cost and latency. It accepts a single text prompt and outputs one image, with controls for quality level and resolution, making it ideal for rapid iteration and high-volume generation.

## What Ideogram P-Image is good at

* **Speed and value**: Quality comparable to leading image models at lower cost and latency
* **Quality tiers**: Choose from VERY\_LOW, LOW, MEDIUM, or HIGH speed/price/quality tiers
* **Flexible output**: 1K or 2K size classes with full aspect ratio support
* **Prompt upsampling**: AUTO expands short prompts into detailed structured captions before generation

## Example outputs

Text-to-image generation from a single prompt:

![Ideogram P-Image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_ideogram_p_image_t2i.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Ideogram P-Image text-to-image workflow

Generate an image from a text description using Ideogram's fast P-Image model. One text prompt is accepted and one image is output.

<img alt="Ideogram P-Image Text-to-Image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_ideogram_p_image_t2i&utm_source=docs&utm_medium=referral&utm_campaign=ideogram-p-image">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_ideogram_p_image_t2i.json">
    Download JSON or search "Ideogram P-Image" in Template Library
  </Card>
</CardGroup>

![Ideogram P-Image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_ideogram_p_image_t2i.png)

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `Ideogram P-Image`


# ComfyUI Ideogram 4.0 Partner Node Tutorial
Source: https://docs.comfy.org/tutorials/partner-nodes/ideogram/ideogram-v4

Learn how to use the Ideogram 4.0 API Partner node in ComfyUI

Ideogram 4.0 is a text-to-image model from Ideogram, offering photorealistic quality, accurate text rendering, and precise style control. You can use either plain natural language or **structured JSON prompts** for fine-grained control over layout, colors, and in-image text. Ideogram 4.5 is the newer model in the family and has its own page: [Ideogram 4.5 in ComfyUI](/tutorials/partner-nodes/ideogram/ideogram-4-5).

## What Ideogram 4.0 is good at

* **Photorealistic quality**: Superior photorealism across generated images
* **Accurate text rendering**: Renders literal text in the image, well suited for poster-like compositions
* **Precise style control**: Structured JSON prompts control style palette, element placement (`bbox`), and per-element color palettes
* **Flexible prompting**: Accepts plain natural language for quick ideas or structured JSON for fine-grained control
* **No negative prompts needed**: Uses asymmetric classifier-free guidance instead of a separate negative prompt string

## Example outputs

Text-to-image generation from a structured JSON prompt:

![Ideogram 4.0 Example Output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_ideogram_v4_t2i.png)
*Example output from the Ideogram 4.0 API*

## Live Conversation with Ideogram & ComfyOrg

A special live conversation with Mohammad Norouzi (CEO, Ideogram) and Yoland Yan (CEO, ComfyOrg), hosted by Purz & Rob.

<iframe title="Ideogram 4.0 Live Conversation" />

## Use it

<Card title="Call it from code" icon="code" href="/development/comfy-router/models/ideogram/ideogram-v4/code">
  Call it over HTTP through Comfy Router, with copy-paste Python, TypeScript, Swift and cURL snippets
</Card>

This runs on the same Comfy account and is billed in the same credits as running it in ComfyUI below. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for per-model rates and [Concurrency limits](/tutorials/partner-nodes/concurrency-limits) for how many requests you can have in flight.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Ideogram 4.0 Partner Node Text-to-Image Workflow

<img alt="Ideogram 4.0 Text-to-Image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_ideogram_v4_t2i&utm_source=docs&utm_medium=referral&utm_campaign=ideogram-v4">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_ideogram_v4_t2i.json">
    Download JSON or search "Ideogram v4: Text to Image (API)" in Template Library
  </Card>
</CardGroup>

![Ideogram 4.0 Example Output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_ideogram_v4_t2i.png)
*Example output from the Ideogram 4.0 API*

### Prompt Format

The Ideogram V4 node supports two prompt formats:

1. **Natural Language**: Simple and intuitive, best for quick ideas.
2. **Structured JSON**: Offers fine-grained control over style palette, element placement (`bbox`), and literal text rendering in the image. Recommended for poster-like compositions.

The default workflow example uses a structured JSON prompt that includes:

* `high_level_description`: Overall scene description
* `style_description`: Aesthetic, lighting, medium, color palette
* `compositional_deconstruction`: Per-element bounding boxes, descriptions, and color palettes

### Workflow Steps

1. Download and drag the workflow file into ComfyUI
2. The `Ideogram V4` node already contains a default structured JSON prompt: you can modify it or write plain natural language
3. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
4. After the API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

### Using the JSON Prompt Builder (Optional)

The workflow includes a built-in **Gemini** node (Gemini 3.1 Pro) to help you build structured JSON prompts:

1. Describe your idea in the Gemini node's user prompt field
2. The model will generate a schema-matching JSON prompt
3. Connect the `STRING` output to the `Ideogram V4` node's `prompt` input
4. Run the workflow

## Additional Notes

* **Negative prompts are not needed**: The Ideogram 4.0 model uses asymmetric classifier-free guidance, where the unconditional pass drops text tokens, rather than requiring a separate negative prompt string.
* **Model-assisted prompt building**: Consider using the **Ideogram 4 Prompt Builder** (KJNodes) for visual control over prompt construction on ComfyUI.


# Image Models
Source: https://docs.comfy.org/tutorials/partner-nodes/image/overview

Choose the right image model for your use case: text-to-image, editing, upscaling, background removal, and more

ComfyUI Partner Nodes give you access to hosted image models from providers such as Black Forest Labs, ByteDance, Google, Ideogram, OpenAI, Qwen, Recraft, and Topaz, so you can generate and edit images without a local GPU. This page helps you pick the right model for text-to-image, image editing, upscaling, or background removal.

## Browse image models

<CardGroup>
  <Card title="Flux 1.1 Pro Ultra" icon="image" href="/tutorials/partner-nodes/black-forest-labs/flux-1-1-pro-ultra-image">
    High-end text-to-image generation in the Flux family
  </Card>

  <Card title="Flux.1 Kontext" icon="image" href="/tutorials/partner-nodes/black-forest-labs/flux-1-kontext">
    State-of-the-art generation with strong prompt adherence and multi-image context
  </Card>

  <Card title="Beeble SwitchX" icon="image" href="/tutorials/partner-nodes/beeble/beeble-switchx">
    Image generation with Beeble's SwitchX node
  </Card>

  <Card title="Bria Background Removal" icon="image" href="/tutorials/partner-nodes/bria/background-removal">
    Remove image backgrounds cleanly
  </Card>

  <Card title="Bria Fibo" icon="image" href="/tutorials/partner-nodes/bria/fibo">
    Editing and restoration utilities from Bria
  </Card>

  <Card title="Bria Image Editing" icon="image" href="/tutorials/partner-nodes/bria/image-editing">
    Image editing and generative fill from Bria
  </Card>

  <Card title="Seedream 5.0 Pro" icon="image" href="/tutorials/partner-nodes/bytedance/seedream-5-pro">
    Fast high-quality generation from ByteDance
  </Card>

  <Card title="Seedream 5.0 Lite" icon="image" href="/tutorials/partner-nodes/bytedance/seedream-5-lite">
    Lighter, faster variant from ByteDance
  </Card>

  <Card title="Nano Banana Pro" icon="image" href="/tutorials/partner-nodes/google/nano-banana-pro">
    Gemini-based image editing and generation
  </Card>

  <Card title="Nano Banana 2" icon="image" href="/tutorials/partner-nodes/google/nano-banana-2">
    Image editing and generation with follow-up edits
  </Card>

  <Card title="Nano Banana 2 Lite" icon="image" href="/tutorials/partner-nodes/google/nano-banana-2-lite">
    Lighter, faster Nano Banana variant
  </Card>

  <Card title="Grok Image" icon="image" href="/tutorials/partner-nodes/grok/grok-image">
    Text-to-image generation from xAI
  </Card>

  <Card title="Grok Image 2.0" icon="image" href="/tutorials/partner-nodes/grok/grok-image-2-0">
    xAI's newest image generation model
  </Card>

  <Card title="Grok Image Quality" icon="image" href="/tutorials/partner-nodes/grok/grok-image-quality">
    Quality-focused Grok image generation
  </Card>

  <Card title="Ideogram 4.0" icon="image" href="/tutorials/partner-nodes/ideogram/ideogram-v4">
    Strong at rendering text in images; supports editing
  </Card>

  <Card title="Ideogram P-Image" icon="image" href="/tutorials/partner-nodes/ideogram/ideogram-p-image">
    Ideogram's image editing model
  </Card>

  <Card title="Krea 2 T2I" icon="image" href="/tutorials/partner-nodes/krea2/krea2-t2i">
    Text-to-image generation from Krea
  </Card>

  <Card title="Luma Image-to-Image" icon="image" href="/tutorials/partner-nodes/luma/luma-image-to-image">
    Transform images with natural language instructions
  </Card>

  <Card title="Luma Text-to-Image" icon="image" href="/tutorials/partner-nodes/luma/luma-text-to-image">
    Create images from text prompts
  </Card>

  <Card title="Luma Uni-1" icon="image" href="/tutorials/partner-nodes/luma/luma-uni-1">
    Create and modify images with natural language
  </Card>

  <Card title="Muse Image 1.0" icon="image" href="/tutorials/partner-nodes/meta/muse-image">
    Agentic generation and editing from Meta with built-in web search
  </Card>

  <Card title="GPT-Image-1" icon="image" href="/tutorials/partner-nodes/openai/gpt-image-1">
    OpenAI image generation and editing
  </Card>

  <Card title="GPT-Image-2" icon="image" href="/tutorials/partner-nodes/openai/gpt-image-2">
    OpenAI's newest image model
  </Card>

  <Card title="Qwen Image 3.0 Pro" icon="image" href="/tutorials/partner-nodes/qwen/qwen-image-3-0-pro">
    Fast, high-quality generation from Qwen
  </Card>

  <Card title="Recraft V4" icon="image" href="/tutorials/partner-nodes/recraft/recraft-v4">
    Design-oriented generation with style control
  </Card>

  <Card title="Recraft Text-to-Image" icon="image" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
    Text-to-image generation with design control
  </Card>

  <Card title="Reve Image" icon="image" href="/tutorials/partner-nodes/reve/reve-image">
    Image generation from Reve
  </Card>

  <Card title="Runway Image Generation" icon="image" href="/tutorials/partner-nodes/runway/image-generation">
    Text-to-image and reference-to-image from Runway
  </Card>

  <Card title="Topaz Image Enhance Bloom 2" icon="image" href="/tutorials/partner-nodes/topaz/image-enhance-bloom-2">
    Creative upscaling that adds new detail and texture
  </Card>

  <Card title="Topaz Image Enhance Wonder 3.5" icon="image" href="/tutorials/partner-nodes/topaz/image-enhance-wonder-3-5">
    Upscale and restore image quality
  </Card>
</CardGroup>

## What you can do with image models

* **Text-to-image**: Generate images from a text prompt
* **Image editing**: Modify an existing image: change content, restyle, or follow a reference
* **Image-to-image**: Transform an input image into a new version while keeping its structure
* **Upscaling & enhancement**: Increase resolution or improve quality
* **Utility workflows**: Background removal, relighting, and more

## Choosing a model by task

### General-purpose text-to-image

If you want the best overall quality from a simple text prompt, start with one of these:

* **Flux.1 Kontext** (Black Forest Labs): state-of-the-art generation with strong prompt adherence; supports multiple input images for context-aware editing
* **Flux 1.1 Pro Ultra** (Black Forest Labs): high-end generation in the Flux family
* **GPT-Image-2 / GPT-Image-1** (OpenAI): strong text-to-image and image editing with a single API
* **Qwen Image 3.0 Pro** (Qwen): fast, high-quality generation from Alibaba's Qwen family

### Image editing & inpainting

These models are designed to modify existing images:

* **Nano Banana Pro / Nano Banana 2 / Nano Banana 2 Lite** (Google): Google's Gemini-based image editing and generation, great for follow-up edits in a conversation
* **Luma Uni-1** (Luma): create and modify images with natural language instructions
* **Muse Image 1.0** (Meta): instruction-based editing that combines up to 10 reference images in a single edit
* **Ideogram 4.0** (Ideogram): strong at rendering text in images; supports editing with an image input

### Background removal & utility

* **Bria Background Removal** (Bria): remove image backgrounds cleanly
* **Bria Fibo / Bria Image Editing** (Bria): editing and restoration utilities
* **Topaz Image Enhance Wonder 3.5 / Bloom 2** (Topaz): upscale and restore image quality

### Speed & budget

* **Nano Banana 2 Lite** (Google): lighter, faster variant of the Nano Banana family
* **Recraft V4 / Recraft Text-to-Image** (Recraft): design-oriented generation with style control
* **Seedream 5.0 Pro / Lite** (ByteDance): fast generation from ByteDance

## All image partners

| Partner | Models |
| - | - |
| Black Forest Labs | [Flux 1.1 Pro Ultra](/tutorials/partner-nodes/black-forest-labs/flux-1-1-pro-ultra-image), [Flux.1 Kontext](/tutorials/partner-nodes/black-forest-labs/flux-1-kontext) |
| Beeble | [Beeble SwitchX](/tutorials/partner-nodes/beeble/beeble-switchx) |
| Bria | [Background Removal](/tutorials/partner-nodes/bria/background-removal), [Fibo](/tutorials/partner-nodes/bria/fibo), [Image Editing](/tutorials/partner-nodes/bria/image-editing) |
| ByteDance | [Seedream 5.0 Pro](/tutorials/partner-nodes/bytedance/seedream-5-pro), [Seedream 5.0 Lite](/tutorials/partner-nodes/bytedance/seedream-5-lite) |
| Google | [Nano Banana Pro](/tutorials/partner-nodes/google/nano-banana-pro), [Nano Banana 2](/tutorials/partner-nodes/google/nano-banana-2), [Nano Banana 2 Lite](/tutorials/partner-nodes/google/nano-banana-2-lite) |
| Grok | [Grok Image](/tutorials/partner-nodes/grok/grok-image), [Grok Image 2.0](/tutorials/partner-nodes/grok/grok-image-2-0), [Grok Image Quality](/tutorials/partner-nodes/grok/grok-image-quality) |
| Ideogram | [Ideogram 4.0](/tutorials/partner-nodes/ideogram/ideogram-v4), [Ideogram P-Image](/tutorials/partner-nodes/ideogram/ideogram-p-image) |
| Krea | [Krea 2 Text-to-Image](/tutorials/partner-nodes/krea2/krea2-t2i) |
| Luma | [Luma Uni-1](/tutorials/partner-nodes/luma/luma-uni-1), [Luma Text-to-Image](/tutorials/partner-nodes/luma/luma-text-to-image), [Luma Image-to-Image](/tutorials/partner-nodes/luma/luma-image-to-image) |
| Meta | [Muse Image 1.0](/tutorials/partner-nodes/meta/muse-image) |
| OpenAI | [GPT-Image-2](/tutorials/partner-nodes/openai/gpt-image-2), [GPT-Image-1](/tutorials/partner-nodes/openai/gpt-image-1) |
| Qwen | [Qwen Image 3.0 Pro](/tutorials/partner-nodes/qwen/qwen-image-3-0-pro) |
| Recraft | [Recraft V4](/tutorials/partner-nodes/recraft/recraft-v4), [Recraft Text-to-Image](/tutorials/partner-nodes/recraft/recraft-text-to-image) |
| Reve | [Reve Image](/tutorials/partner-nodes/reve/reve-image) |
| Runway | [Image Generation](/tutorials/partner-nodes/runway/image-generation) |
| Topaz | [Image Enhance Wonder 3.5](/tutorials/partner-nodes/topaz/image-enhance-wonder-3-5), [Image Enhance Bloom 2](/tutorials/partner-nodes/topaz/image-enhance-bloom-2) |

See [Pricing](/tutorials/partner-nodes/pricing) for per-model rates, and [Concurrency Limits](/tutorials/partner-nodes/concurrency-limits) for usage caps.


# ComfyUI Krea 2 Partner Nodes Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/krea2/krea2-t2i

This guide explains how to use the Krea 2 Text to Image Partner node in ComfyUI

The [Krea 2 Image Node](/built-in-nodes/Krea2ImageNode) allows you to generate high-quality images from text prompts using Krea AI's next-generation model. It supports two model variants, **Krea 2 Medium** for expressive illustrations and **Krea 2 Large** for expressive photorealism, with optional moodboard and style reference inputs.

## What Krea 2 Text to Image is good at

* **Two model variants**: Krea 2 Medium for expressive illustrations, Krea 2 Large for expressive photorealism
* **Style references**: Apply the aesthetic style, mood, and visual direction of up to 10 reference images to your generation
* **Moodboard support**: Use the `moodboard_id` parameter with a moodboard from [Krea's website](https://www.krea.ai)
* **Adjustable generation settings**: Control aspect ratio, resolution, creativity level, and seed

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Krea 2 Image Node Documentation

Check the following documentation for detailed node parameter settings:

* [Krea 2 Image Node](/built-in-nodes/Krea2ImageNode)
* [Krea 2 Style Reference Node](/built-in-nodes/Krea2StyleReferenceNode)

## Krea 2 Text to Image Workflow

<img alt="Krea 2 Text to Image Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_krea2_t2i&utm_source=docs&utm_medium=referral&utm_campaign=krea2-t2i">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_krea2_t2i.json">
    Download JSON or search "Krea2" in Template Library
  </Card>
</CardGroup>

1. **Enter your prompt**: type a text description in the **Krea2ImageNode**
2. **Select a model variant**: choose between **Krea 2 Medium** (illustrations) or **Krea 2 Large** (photorealism)
3. **Adjust parameters**: set aspect ratio, resolution, creativity level, and seed
4. **Click Queue**: press `Ctrl+Enter` or click the Queue button to generate
5. **View result**: the generated image appears in the **SaveImage** node, saved to `ComfyUI/output/`

## Krea 2 Style Reference Workflow

<img alt="Krea 2 Style Reference Workflow" />

The Style Reference workflow adds an extra step: upload one or more reference images that define the aesthetic style, mood, and visual direction. The generated image will match your prompt while applying the style from your reference images.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_krea2_style_reference&utm_source=docs&utm_medium=referral&utm_campaign=krea2-t2i">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_krea2_style_reference.json">
    Download JSON or search "Krea 2: Style Reference" in Template Library
  </Card>
</CardGroup>

1. **Upload reference images**: use the **LoadImage** nodes to load style reference images (supports up to 10)
2. **Enter your prompt**: describe the scene you want in the **Krea2ImageNode**
3. **Select a model variant**: choose between Medium and Large
4. **Adjust style strength**: modify the style reference strength in the **Krea2StyleReferenceNode** nodes
5. **Click Queue**: press `Ctrl+Enter` to generate
6. **View result**: the generated image appears in the **SaveImage** node

## Additional Notes

* The Krea 2 Image node supports up to **10 style reference images** simultaneously
* The `moodboard_id` parameter requires a valid UUID from a Krea moodboard on [Krea's website](https://www.krea.ai)


# Luma Image to Image Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/luma/luma-image-to-image

This guide covers how to use the Luma Image to Image Partner node in ComfyUI

The Luma Image to Image node allows you to modify existing images based on text prompts using Luma AI technology, while preserving certain features and structures from the original image.

## What Luma Image to Image is good at

* **Prompt-driven image editing**: Modifies existing images based on text prompts while preserving certain features and structures from the original
* **Changing objects and shapes**: The node works well for changing objects and shapes, though it may not be ideal for color changes
* **Adjustable input influence**: The `image_weight` parameter controls how strongly the input image shapes the result, with lower values staying closer to the original

## Example outputs

Results at different `image_weight` values, showing how strongly the input image influences the generated output:

<img alt="Weight Comparison" />

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Luma Image to Image Partner Nodes Workflow

<Tip>
  This feature works well for changing objects and shapes. However, it may not be ideal for color changes. We recommend using lower weight values, around 0.0 to 0.1.
</Tip>

### 1. Download Workflow File

Download and drag the following image into ComfyUI to load the workflow (workflow information is included in the image metadata):

![Luma Image to Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/i2i/luma_i2i.png)

Download this image to use as input:

![Luma Image to Image Workflow Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/i2i/input.png)

### 2. Complete the Workflow Steps

<img alt="Luma Image to Image Workflow Steps" />

Follow these numbered steps:

1. Click **Upload** on the `Load Image` node to upload your input image
2. (Optional) Modify the workflow prompts
3. (Optional) Adjust `image_weight` to change input image influence (lower values stay closer to original)
4. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
5. After API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

### 3. Results with Different `image_weight` Values

<img alt="Weight Comparison" />


# Luma Text to Image Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/luma/luma-text-to-image

This guide explains how to use the Luma Text to Image Partner node in ComfyUI

The Luma Text to Image node allows you to generate high-quality images from text prompts using Luma AI's advanced technology, capable of creating photorealistic content and artistic style images.

## What Luma Text to Image is good at

* **High-quality text-to-image generation**: Creates photorealistic content and artistic style images from text prompts
* **Style references**: A `style_image` input guides the look of the result, with `style_image_weight` controlling the style reference image's influence
* **Image and character references**: The `image_luma_ref` input supports reference-guided generation, with up to 4 reference images and character references usable simultaneously

## Example outputs

Style-guided generation at different `style_image_weight` values, showing the style reference image's influence:

<img alt="Style Image Weight Comparison" />

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Luma Text to Image Partner Nodes Workflow

When the `Luma Text to Image` node is used without any image inputs, it functions as a text-to-image workflow. In this guide, we've created examples using `style_image` and `image_luma_ref` to showcase Luma AI's excellent image processing capabilities.

### 1. Download Workflow Files

The workflow information is included in the metadata of the image below. Download and drag it into ComfyUI to load the workflow.

![Luma Text to Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/t2i/luma_t2i.png)

Please download these images for input:

![Input Image - Reference](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/t2i/input_ref.png)
![Input Image - Style](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/t2i/input_style.png)

### 2. Follow Steps to Run the Workflow

<img alt="Luma Text to Image Workflow Steps" />

Follow the numbered steps in the image to complete the basic workflow:

1. Upload the reference image in the `Load image` node
2. Upload the style reference image in the `Load image (renamed to styleref)` node
3. (Optional) Modify the prompts in the `Luma Text to Image` node
4. (Optional) Adjust the `style_image_weight` to control the style reference image's influence
5. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to generate the image
6. After the API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

<img alt="Style Image Weight Comparison" />

### 3. Additional Notes

* The node allows up to 4 reference images and character references simultaneously.
* To enable multiple image inputs, right-click on the purple "Bypassed" nodes and set their `mode` to `always`


# Luma Uni-1 Guide
Source: https://docs.comfy.org/tutorials/partner-nodes/luma/luma-uni-1

Use Luma Uni-1 partner nodes in ComfyUI for Create and Modify image workflows.

In **ComfyUI**, Luma **Uni-1** shows up as **partner Partner Nodes** for unified image work: **Create** graphs generate new images from prompts (with optional references); **Modify** graphs take an existing image as input and edit it in place. You drive both through the usual workflow: wire **Load Image** / **Save Image**, set prompts, seeds, aspect ratio, and reference slots on the Luma node, then queue the graph locally or open a template on **Comfy Cloud**.

Luma describes Uni-1 as a non-diffusion, decoder-only autoregressive model that reasons over your prompt before drawing. On the canvas, what matters most is choosing **Create vs Modify**, labeling references clearly, and iterating with seeds.

## What makes Uni-1 different

* **Two clear modes**: Create Image (generate something new) and Modify Image (edit something existing)
* **Up to 9 reference images**, each with a defined role
* **Strong control over niche and specific visual styles**
* **Seed support** for reproducibility and controlled iteration
* **Nine aspect ratios**, from ultra-tall to ultra-wide
* **Text rendering** that's actually readable
* **Web search grounding** for real-world context
* **Multilingual prompts**
* **Multi-panel output** with temporal consistency

If you understand the modes and how to control references, you understand Uni-1.

## What Luma Uni-1 is good at

Uni-1 excels across a wide range of tasks:

* **Photorealism** with material accuracy
* **Illustration & stylized art** with strong aesthetic control
* **Old photo restoration** and vintage reproduction
* **Surreal and conceptual** compositions
* **Text rendering**: readable text inside images, great for infographics and posters
* **Image editing** and multi-turn refinement
* **Reference-guided generation** with identity preservation
* **Multi-panel output**: consistent characters/scenes across multiple frames

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## The core distinction: Create vs Modify

Everything in Uni-1 starts with one question: **Am I creating something new, or changing something that already exists?**

| Mode | What it does | When to use |
| - | - | - |
| **Create Image** | Produces a brand-new composition. Can be inspired by references. | "Create a new scene in the style of this photo" |
| **Modify Image** | Edits a specific input image. Preserves composition and structure unless told otherwise. | "Make this photo look like nighttime" |

When in doubt:

* If the output should look like a **version of your input**, use Modify
* If it should feel **inspired but new**, use Create

## Available workflows

### Image Create workflow

<img alt="Luma Uni-1 Image Create workflow preview" />

<CardGroup>
  <Card title="Run Image Create on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_luma_uni_1_image_create&utm_source=docs&utm_medium=referral&utm_campaign=luma-uni-1">
    Try the Image Create workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Image Create Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_luma_uni_1_image_create.json">
    Download JSON or search "Luma UNI-1 Image Create" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Style reference" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/uni_1_style_ref.png">
      Download sample style reference
    </Card>
  </CardGroup>
</details>

### Image Edit workflow

<img alt="Luma Uni-1 Image Edit workflow preview" />

<CardGroup>
  <Card title="Run Image Edit on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_luma_uni_1_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=luma-uni-1">
    Try the Image Edit workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Image Edit Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_luma_uni_1_image_edit.json">
    Download JSON or search "Luma UNI-1 Image Edit" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Source image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/the_leap.png">
      Download sample source image
    </Card>
  </CardGroup>
</details>

The workflow is simple: **prompt → evaluate → refine**. Leave the seed blank while exploring. Once you find something strong, lock the seed and iterate from there.

## Core parameters

| Parameter | Description |
| - | - |
| **Prompt** | Your primary control. Up to 6,000 characters. Be precise. |
| **Aspect ratio** | Controls framing, not quality. Choose based on use case. |
| **Seed** | Same seed + same prompt → same result. Same seed + changed prompt → controlled variation. No seed → exploration. |
| **Reference images** (Create) | Up to 9 images to guide different aspects. |
| **Source image** (Modify) | The image you are editing. Dimensions are preserved automatically. |

## Working with reference images

References only work if you tell the model what they are for. Use this structure:

```text theme={null}
Use IMAGE1 ([description]) as a [ROLE] reference.
```

Possible roles: **Style**, **Character**, **Composition**, **Color palette**, **Lighting**, **Texture**, **Mood**.

Without roles, the model guesses, and guesses are unreliable.

### Create mode examples

**Style reference**

```text theme={null}
Use IMAGE1 (impressionist oil painting with loose brushwork and warm
sunset tones) as a STYLE reference. Create a portrait of a woman in her
30s applying IMAGE1's color palette and painterly texture. The subject
should be new.
```

**Character reference**

```text theme={null}
Use IMAGE1 (woman with short copper-red hair, freckles) as a CHARACTER
reference. Preserve her features. Generate a new scene: she's sitting
in a softly lit café.
```

**Multi-reference**

```text theme={null}
Use IMAGE1 as a COLOR PALETTE reference, IMAGE2 as LIGHTING, IMAGE3 as
COMPOSITION. Create a lone figure walking through a rain-slicked street
at night.
```

### Modify mode examples

In Modify mode, clarity is everything. Always specify **what to change** and **what must stay untouched**.

```text theme={null}
Change the time of day to golden hour. Update sky, light direction,
shadows, and color temperature. Keep all subjects and composition
unchanged.
```

```text theme={null}
Make the rain heavier and add reflections on the ground. Keep all other
elements unchanged.
```

## Prompting guidelines

Recommended lengths:

* **Text-to-image** → 80–250 words
* **Reference-guided** → 100–300 words
* **Modify** → 30–100 words

Avoid vague terms ("beautiful", "amazing"), redundant phrasing, and conflicting instructions. Instead, use specific, named aesthetics:

* `Golden hour, 85mm lens, shallow depth of field`
* `1970s Italian giallo film poster, high-contrast color blocking`

Precision beats generality.

## Aspect ratios

Choose based on where the image will live:

| Ratio | Use case |
| - | - |
| 1:1 | Social posts |
| 9:16 | Vertical video |
| 16:9 | Widescreen |
| 3:2 / 2:3 | Photography |
| 2:1 / 3:1 | Cinematic / panoramic |
| 1:2 / 1:3 | Ultra-tall |

In Modify mode, aspect ratio is locked to the source image.

## Seeds: control and reproducibility

Seeds turn experimentation into systems.

* **Fixed seed** → consistency
* **No seed** → exploration

Workflow:

1. Explore with no seed
2. Find a strong result
3. Lock the seed
4. Change one variable at a time

Save your prompt and seed together. That's your reusable recipe.

## Advanced techniques

### Character consistency

1. Generate a clean, front-facing reference image
2. Reuse it as `IMAGE1 (CHARACTER)` in every scene
3. Keep the label identical across prompts

### Multi-reference architecture

Assign one role per image:

* IMAGE1 → character
* IMAGE2 → style
* IMAGE3 → lighting
* IMAGE4 → environment

End the prompt with:

```text theme={null}
Treat each reference as having authority over its assigned layer only.
```

### Create → Modify chain

Use Create to explore compositions, then Modify to refine details. This is one of the most powerful workflows.

### Iterative refinement

1. Explore (no seed)
2. Lock seed
3. Change one variable per generation
4. Document results

It feels slower, but it's actually faster, because you always know what changed.

## Troubleshooting

| Problem | Fix |
| - | - |
| References ignored | Label each one clearly |
| Modify changes too much | Explicitly state what must stay unchanged |
| Inconsistent outputs | Lock the seed |
| Prompt partially ignored | Remove conflicts or split into steps |
| Output looks like the reference image | You may be in Modify mode |
| Character inconsistency | Reuse a canonical reference image |

## Quick reference

**Create Image**

* New compositions
* Text + up to 9 references
* Descriptive prompts

**Modify Image**

* Edits existing images
* Source image + references
* Direct, surgical prompts

## The golden rules

1. Label every reference
2. In Modify mode, always state what should **not** change
3. Change one variable at a time when refining
4. Save prompt + seed for reproducibility
5. Create = new scenes, Modify = edits

## Key takeaway

Mastering Uni-1 comes down to three things: **choose the right mode → control your references → iterate with intention**. Once those are in place, you're no longer guessing, you're directing.


# Meta Muse Image in ComfyUI: Text to Image and Image Edit
Source: https://docs.comfy.org/tutorials/partner-nodes/meta/muse-image

Generate and edit images with Meta's Muse Image 1.0 Partner Nodes in ComfyUI. Agentic image generation with built-in web search, image search, and code execution, plus instruction-based editing across up to 10 reference images.

Meta Muse Image 1.0 is the first image generation model from Meta Superintelligence Labs, announced on July 7, 2026. It generates images at roughly 2.5 megapixels and stands out for its agentic approach: before rendering, the model can search the web for facts, search for reference images, and even run code to get quantities, layouts, charts, and diagrams precise. ComfyUI exposes Muse Image through two Partner Nodes: Meta Muse Image Text to Image for generation, and Meta Muse Image Edit for instruction-based editing and combining.

## What Meta Muse Image is good at

* **Agentic rendering**: The model plans before it draws, using built-in web search, image search, and code execution (all three toggles are on by default in the node's advanced options)
* **Precise quantities and layouts**: Text-heavy posters, charts, diagrams, and layouts benefit from the code-execution path; turning it off falls back to approximation
* **Multi-reference editing**: The Edit node accepts 1 to 10 reference images. Refer to them in the prompt as `@Image1`, `@Image2`, and so on, numbered in input order
* **Flexible framing**: 14 aspect ratios from 1:1 up to 21:9 and 9:21, plus `auto`, which lets the model choose from the prompt (generation) or keeps the input's ratio (edit)
* **Reasoning control**: Choose `high` or `low` reasoning strength depending on how much planning the image needs

## Example outputs

Text-to-image generation from a single prompt:

![Muse Image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/muse_image_1.0.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Meta Muse Image Text to Image workflow

Generate an image from a text description using Meta's Muse Image 1.0 model. One text prompt is accepted and one image is output.

<img alt="Meta Muse Image Text-to-Image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_meta_muse_image_t2i&utm_source=docs&utm_medium=referral&utm_campaign=meta-muse-image">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_meta_muse_image_t2i.json">
    Download JSON or search "Muse Image" in Template Library
  </Card>
</CardGroup>

![Muse Image Text-to-Image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/muse_image_1.0.png)

## Meta Muse Image Edit workflow

Edit or combine up to 10 reference images guided by a text prompt. Reference images are connected to the `image_1` to `image_10` inputs, and the prompt addresses each one as `@Image1`, `@Image2`, and so on, numbered in input order. A batched input counts once per image.

<img alt="Meta Muse Image Edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_meta_muse_image_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=meta-muse-image">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_meta_muse_image_image_edit.json">
    Download JSON or search "Muse Image" in Template Library
  </Card>
</CardGroup>

### Input files

<CardGroup>
  <Card title="Whale figure" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/deep_blue_whale_swim_scene.png">
    deep\_blue\_whale\_swim\_scene.png
  </Card>

  <Card title="Modern house" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/desert_red_modern_house.png">
    desert\_red\_modern\_house.png
  </Card>
</CardGroup>

The example workflow combines the two inputs with the prompt: "Use the whale figure from @image1 and make it roam across the sky above the picture in @image2".

![Muse Image Edit output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_meta_muse_image_image_edit.png)

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `Muse Image`

### Prompting tips

* Be explicit about what must stay accurate: Muse Image follows instructions closely, so state counts, positions, and labels directly in the prompt
* For posters and diagrams, keep the code execution toggle on (advanced options) so quantities and alignment are computed rather than approximated
* In the Edit workflow, name every reference you connect. An `@Image` tag with no connected input fails the run
* Use `auto` aspect ratio when you want the model to decide the framing from the prompt; use a fixed ratio for consistent series output

## Pricing

| Node | Credits |
| :- | :- |
| Meta Muse Image Text to Image | 3.017 / image |
| Meta Muse Image Edit | 3.017 / image |


# Model provider verification, licensing, and data residency
Source: https://docs.comfy.org/tutorials/partner-nodes/model-providers

Verification status, commercial licensing, and data residency for the model providers behind Comfy's Partner Nodes.

This page tracks the model providers behind Comfy's Partner Nodes in one table: verification status, commercial licensing for Cloud and local use, and data residency. It's a structure we're actively filling in, not a finished reference. Some columns reflect confirmed facts today, others are placeholders until we've verified the details with each provider.

For pricing by provider, see [Partner Node Pricing](/tutorials/partner-nodes/pricing).

This page covers the providers behind Partner Nodes. For how long Comfy stores Partner Node inputs and outputs, see [Data Retention](/tutorials/partner-nodes/data-retention). For the providers that serve each Comfy Router model, see [Serving providers](/development/comfy-router/providers).

## What each column means

* **Verified**: Comfy has a direct commercial and API partnership with the provider, and has reviewed the contract terms governing it. "In Process" means that review is in progress.
* **Commercial License (Cloud)**: whether commercial use through Comfy Cloud is confirmed for that provider's models.
* **Commercial License (Local)**: whether commercial use for local, self-hosted usage is confirmed for that provider's models. "Request" means commercial use needs a separate request or license rather than being included automatically.
* **Data Residency**: where a provider processes data by default today. "Pending" means we haven't confirmed the location with that provider yet.

"Pending" in a license column means we haven't confirmed that license yet. That will change to a checkmark, a dash, or "Request" as each partnership is confirmed.

## Providers

| Provider | Verified | Commercial License (Cloud) | Commercial License (Local) | Data Residency |
| - | - | - | - | - |
| Alibaba | In Process | Pending | Pending | Singapore |
| Black Forest Labs (Flux) | Yes | ✓ | ✓ | US, EU, Israel |
| Bria | Yes | ✓ | ✓ | US, EU |
| ElevenLabs | Yes | ✓ | ✓ | Pending |
| Genary | Yes | Pending | Pending | Pending |
| Google | Yes | ✓ | ✓ | Pending |
| Hitpaw | No | — | — | — |
| Kling | In Process | Pending | Pending | Singapore |
| Lightricks (LTX) | Yes | ✓ | ✓ | US, Iceland |
| Luma | In Process | Pending | Pending | Pending |
| Meshy | Yes | Pending | Pending | Pending |
| Midjourney | No | — | — | — |
| MiniMax | In Process | Pending | Request | US |
| Pixverse | Yes | ✓ | ✓ | Pending |
| Runway | Yes | ✓ | ✓ | Pending |
| Singdata (ByteDance) | Yes | ✓ | ✓ | Malaysia, EU (some models) |
| Sonilo | No | — | — | — |
| Tencent | Yes | ✓ | ✓ | Pending |
| Topaz | In Process | Pending | Pending | US |
| Vidu | Yes | Pending | Pending | Pending |
| xAI | Yes | ✓ | ✓ | Pending |

<Note>
  Additional data residency options may be available for Enterprise customers. [Contact us](https://comfy.org/contact/) for details.

  This table is a living document. Verification status is current, but license and residency details for most providers are still being confirmed and will update as we verify them.
</Note>


# OpenAI GPT-Image-1 Node
Source: https://docs.comfy.org/tutorials/partner-nodes/openai/gpt-image-1

Learn how to use the OpenAI GPT-Image-1 Partner node to generate images in ComfyUI

<img alt="OpenAI GPT-Image-1 Node Screenshot" />

OpenAI GPT-Image-1 is part of the ComfyUI Partner nodes series that allows users to generate images through OpenAI's **GPT-Image-1** model. This is the same model used for image generation in ChatGPT 4o.

The **OpenAI GPT-Image-1** node synchronously generates images through OpenAI's image generation API. It receives text prompts and returns images matching the description. GPT-Image-1 is OpenAI's most advanced image generation model currently available, capable of creating highly detailed and realistic images.

## What GPT-Image-1 is good at

* Text-to-image generation
* Image editing functionality (inpainting through masks)
* Image-to-image generation from a reference image
* Multiple image input, batching several reference images into a single generation

## Example outputs

Text-to-image generation from a single text prompt:

![ComfyUI openai-gpt-image-1 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/text2image.png)

Image-to-image generation from a reference image:

![ComfyUI openai-gpt-image-1 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/image2image.png)

Multiple image input, combining several reference images into one generation:

![Multiple Image Input Example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/multiple_image_input.png)

Inpainting, replacing a masked area of an input image:

![ComfyUI openai-gpt-image-1 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/inpaint.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Parameter Description

### Required Parameters

| Parameter | Type | Description |
| - | - | - |
| `prompt` | Text | Text prompt describing the image content you want to generate |

### Widget Parameters

| Parameter | Type | Options | Default | Description |
| - | - | - | - | - |
| `seed` | Integer | 0-2147483647 | 0 | Random seed used to control generation results |
| `quality` | Option | low, medium, high | low | Image quality setting, affects cost and generation time |
| `background` | Option | opaque, transparent | opaque | Whether the returned image has a background |
| `size` | Option | auto, 1024x1024, 1024x1536, 1536x1024 | auto | Size of the generated image |
| `n` | Integer | 1-8 | 1 | Number of images to generate |

### Optional Parameters

| Parameter | Type | Options | Default | Description |
| - | - | - | - | - |
| `image` | Image | Any image input | None | Optional reference image for image editing |
| `mask` | Mask | Mask input | None | Optional mask for inpainting (white areas will be replaced) |

## Usage Examples

### Text-to-Image Example

The image below contains a simple text-to-image workflow. Please download the image and drag it into ComfyUI to load the corresponding workflow.
![ComfyUI openai-gpt-image-1 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/text2image.png)

The corresponding workflow is very simple:

<img alt="ComfyUI openai-gpt-image-1 workflow example" />

You only need to load the `OpenAI GPT-Image-1` node, input the description of the image you want to generate in the `prompt` node, connect a `Save Image` node, and then run the workflow.

### Image-to-Image Example

The image below contains a simple image-to-image workflow. Please download the image and drag it into ComfyUI to load the corresponding workflow.
![ComfyUI openai-gpt-image-1 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/image2image.png)

We will use the image below as input:
![ComfyUI openai-gpt-image-1 workflow input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/input.webp)

In this workflow, we use the `OpenAI GPT-Image-1` node to generate images and the `Load Image` node to load the input image, then connect it to the `image` input of the `OpenAI GPT-Image-1` node.

<img alt="ComfyUI openai-gpt-image-1 workflow example" />

### Multiple Image Input Example

Please download the image below and drag it into ComfyUI to load the corresponding workflow.

![Multiple Image Input Example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/multiple_image_input.png)

Use the hat image below as an additional input image.
![Hat](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/hat.webp)

The corresponding workflow is shown in the image below:

<img alt="Multiple Image Input Example" />

The `Batch Images` node is used to load multiple images into the `OpenAI GPT-Image-1` node.

### Inpainting Workflow

GPT-Image-1 also supports image editing functionality, allowing you to specify areas to replace using a mask. Below is a simple inpainting workflow example:

Download the image below and drag it into ComfyUI to load the corresponding workflow. We will continue to use the input image from the image-to-image workflow section.

![ComfyUI openai-gpt-image-1 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/inpaint.png)

The corresponding workflow is shown in the image

<img alt="ComfyUI openai-gpt-image-1 workflow example" />

Compared to the image-to-image workflow, we use the MaskEditor in the `Load Image` node through the right-click menu to draw a mask, then connect it to the `mask` input of the `OpenAI GPT-Image-1` node to complete the workflow.

**Notes**

* The mask and image must be the same size
* When inputting large images, the node will automatically resize the image to an appropriate size

## FAQs

<AccordionGroup>
  <Accordion title="Why can't I find the Partner Nodes?">
    Please update your ComfyUI to the latest version (the latest commit or the latest [desktop version](https://www.comfy.org/download)).
    We may add more API support in the future, and the corresponding nodes will be updated, so please keep your ComfyUI up to date.

    <Tip>
      Please note that you need to distinguish between the nightly version and the release version.
      In some cases, the latest `release` version may not be updated in time compared to the `nightly` version.
      Since we are still iterating quickly, please ensure you are using the latest version when you cannot find the corresponding node.
    </Tip>
  </Accordion>

  <Accordion title="Why can't I use / log in to the Partner Nodes?">
    API access requires that your current request is based on a secure network environment. The current requirements for API access are as follows:

    * The local network only allows access from `127.0.0.1` or `localhost`, which may mean that you cannot use the Partner Nodes in a ComfyUI service started with the `--listen` parameter in a LAN environment.
    * Able to access our API service normally (a proxy service may be required in some regions).
    * Your account does not have enough [credits](/interface/credits).
  </Accordion>

  <Accordion title="Why can't I use Partner Node even after logging in, or why does it keep asking me to log in while using?">
    * Currently, only `127.0.0.1` or `localhost` access is supported.
    * Ensure your account has enough credits.
  </Accordion>

  <Accordion title="Can Partner Nodes be used for free?">
    Partner Nodes require credits for API calls to closed-source models, so they do not support free usage.
  </Accordion>

  <Accordion title="How to purchase credits?">
    Please refer to the following documentation:

    1. [Comfy Account](/interface/user): Find the `User` section in the settings menu to log in.
    2. [Credits](/interface/credits): After logging in, the settings interface will show the credits menu. You can purchase credits in `Settings` → `Credits`. We use a prepaid system, so there will be no unexpected charges.
    3. Complete the payment through Stripe.
    4. Check if the credits have been updated. If not, try restarting or refreshing the page.
  </Accordion>

  <Accordion title="Are unused credits refundable?">
    Currently, we do not support refunds for credits.
    If you believe there is an error resulting in unused balance due to technical issues, please [contact support](mailto:support@comfy.org).
  </Accordion>

  <Accordion title="Can credits go negative?">
    Credits are not intended to be used as a negative balance or credit line. However, due to race conditions where partner nodes don't always report costs before execution, a single execution may consume more credits than your remaining balance and temporarily result in a negative balance after completion. When your balance is negative, you will not be able to run Partner Nodes until you top up and restore a positive balance. Please ensure you have enough credits before making API calls.
  </Accordion>

  <Accordion title="Where can I check usage and expenses?">
    Please visit the [Credits](/interface/credits) menu after logging in to check the corresponding credits.
  </Accordion>

  <Accordion title="Is it possible to use my own API Key?">
    Currently, the Partner Nodes are still in the testing phase and do not support this feature yet, but we have considered adding it.
  </Accordion>

  <Accordion title="Do credits expire?">
    Yes, the expiration depends on the type of credits:

    * **Monthly credits**: Expire at the end of your billing period
    * **Top-up credits**: Expire 1 year from the date of purchase
  </Accordion>

  <Accordion title="Can credits be transferred or shared?">
    No, your credits cannot be transferred to other users and are limited to the currently logged-in account, but we do not restrict the number of devices that can log in.
  </Accordion>

  <Accordion title="Can I use the same account on different devices?">
    We do not limit the number of devices that can log in; you can use your account anywhere you want.
  </Accordion>

  <Accordion title="How can I request for my account or information to be deleted??">
    Email a request to [support@comfy.org](mailto:support@comfy.org) and we will delete your information
  </Accordion>

  <Accordion title="Is there content moderation for Partner Nodes?">
    Partner Nodes send your inputs (prompts, images, and other content) to third-party providers for processing. These providers enforce their own content moderation policies. Please do not submit NSFW or other prohibited content to API nodes.
  </Accordion>
</AccordionGroup>


# OpenAI GPT-Image-2 Node
Source: https://docs.comfy.org/tutorials/partner-nodes/openai/gpt-image-2

Learn how to use the OpenAI GPT-Image-2 Partner node to generate images in ComfyUI

OpenAI GPT-Image-2 (`gpt-image-2`) is OpenAI's newest image model, available in ComfyUI through Partner Nodes. It is the first OpenAI image model that *reasons* before it generates: instead of one-shot sampling, the model plans the composition, checks its work, and iterates.

This node supports:

* Text-to-image generation with strong handling of dense text, UI elements, iconography, infographics, maps, slides, and manga panels
* Image editing with high structural fidelity at up to 2K resolution
* Up to 8 consistent images from a single prompt, preserving character and object continuity
* Transparent background output for compositing, using the `background` option

GPT-Image-2 is selected as a `model` option on the **OpenAI GPT Image 2.5** node in the Node Library. The node calls OpenAI's image generation API synchronously and returns images that match the description.

## What GPT-Image-2 is good at

### Reasoning-driven generation

GPT-Image-2 plans the composition before rendering. This makes it well suited for prompts that have historically broken image models: for example, a poster with a seven-item bulleted list in 11pt Helvetica, centered: and produces clean output for dense text, small UI elements, iconography, infographics, maps, and slides.

### Image editing that preserves what matters

GPT-Image-2 handles targeted edits with structural fidelity, keeping everything outside the edit zone pixel-stable while applying the requested change cleanly at up to 2K resolution. Use it for tasks like colorizing black-and-white photos or shifting a scene from noon to dusk without warping faces, geometry, or fine detail.

### Up to eight consistent images per prompt

The model can return up to **eight distinct images from a single prompt** while preserving character and object continuity across the series. This is useful for storyboarding, reference sheets, character turnarounds, and product variants without seed-locking or prompt gymnastics. Feed the batch straight into a `Save Image` node or chain it into a video workflow downstream.

![GPT-Image-2 consistent images example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/consistent_example.jpg)

## Hybrid Pipelines

GPT-Image-2 slots naturally into hybrid pipelines: use it for the text-heavy hero frame, then hand off to your local models for upscaling, stylization, or video generation: the best model for each step, in one graph.

## Example outputs

Text-to-image generation with reasoning-driven composition:

![GPT-Image-2 Text-to-Image example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_t2i_1.jpg)

Image editing on an input image, preserving structure outside the edit zone:

![GPT-Image-2 Image-to-Image example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_i2i_1.jpg)

![GPT-Image-2 Image Edit example 1](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_image_edit_1.jpg)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Getting Started

1. Update ComfyUI to the latest version (v0.19.4 or later), or use [Comfy Cloud](https://links.comfy.org/4u4o7Pv).
2. In the Node Library, search for **OpenAI GPT Image 2.5** and add the node.
3. Set the `model` field to `gpt-image-2`.

## Available workflows

### Text to image (T2I)

Generate an image from a text prompt with GPT-Image-2's reasoning-driven composition.

<CardGroup>
  <Card title="Run Text-to-Image on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openai_gpt_image_2_t2i&utm_source=docs&utm_medium=referral&utm_campaign=gpt-image-2">
    Try the Text-to-Image workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Text-to-Image workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openai_gpt_image_2_t2i.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

![GPT-Image-2 Text-to-Image workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_openai_gpt_image_2_t2i-1.webp)

![GPT-Image-2 Text-to-Image example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_t2i_1.jpg)

### Image edit

Edit an input image with high structural fidelity at up to 2K resolution.

<CardGroup>
  <Card title="Run Image Edit on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openai_gpt_image_2_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=gpt-image-2">
    Try the Image Edit workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Image Edit workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openai_gpt_image_2_image_edit.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

![GPT-Image-2 Image Edit workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_openai_gpt_image_2_image_edit-1.webp)

<Card title="Download Sample Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/product_shoe.png">
  Get the example input image for this workflow
</Card>

![GPT-Image-2 Image-to-Image example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_i2i_1.jpg)

![GPT-Image-2 Image Edit example 1](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_image_edit_1.jpg)

![GPT-Image-2 Image Edit example 2](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_image_edit_2.jpg)


# OpenAI GPT Image 2.5 Node: Flare and Sunburst Workflows
Source: https://docs.comfy.org/tutorials/partner-nodes/openai/gpt-image-2-5

Generate and edit images in ComfyUI with the OpenAI GPT Image 2.5 Flare and Sunburst partner nodes: fast previews, high-fidelity edits, and workflow templates.

OpenAI GPT Image 2.5 (`gpt-image-2.5`) is OpenAI's newest image model family, available in ComfyUI through Partner Nodes on the **OpenAI GPT Image 2.5** node. It comes in two variants tuned for different stages of the creative process:

* **GPT Image 2.5 Flare** (`gpt-image-2.5-flare`): fast image generation and editing optimized for rapid prototyping and creative iteration. It delivers quick previews for concept exploration, mood boards, poster drafts, character sketches, and scene mockups, balancing solid visual quality with low latency for high-volume trial-and-error workflows.
* **GPT Image 2.5 Sunburst** (`gpt-image-2.5-sunburst`): high-fidelity image generation and editing for polished, detail-rich visuals. It preserves subject identity, complex materials, lighting consistency, and scene structure across iterations, making it suitable for concept refinement, product visuals, character scenes, cinematic backgrounds, and finished artwork.

Both variants support text-to-image and image editing with reference images (up to 16), an optional mask for inpainting, and five quality levels: `low`, `medium`, `high`, `xhigh`, and `max`.

The template library currently ships with four example workflows:

* **Flare: Text to Image**. Fast poster generation from a text prompt
* **Flare: Image Edit**. Outfit and hairstyle swap while keeping the scene fixed
* **Sunburst: Text to Image**. High-fidelity editorial fashion poster with rendered typography
* **Sunburst: Image Edit**. High-fidelity hairstyle and makeup edit with subject consistency

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Getting started

1. Update ComfyUI to the latest version. The node and templates require ComfyUI 0.35.0 or later
2. In the Node Library, search for **OpenAI GPT Image 2.5** and add the node
3. Set the `model` field to `gpt-image-2.5-flare` or `gpt-image-2.5-sunburst`

## Node settings

The **OpenAI GPT Image 2.5** node calls OpenAI's image API synchronously and returns the generated image. The options change with the selected model:

* **model**: `gpt-image-2.5-flare` (fast iteration) or `gpt-image-2.5-sunburst` (high fidelity)
* **prompt**: Text description of the image to generate, or the edit instruction when reference images are connected
* **size**: `auto`, a preset such as `1024x1024` or `3840x2160`, or `Custom`
* **custom\_width / custom\_height**: Used only when `size` is `Custom`. From 480 to 3840, in steps of 16
* **background**: `auto`, `opaque`, or `transparent` (both 2.5 variants support transparent backgrounds)
* **quality**: `low`, `medium`, `high`, `xhigh`, or `max`. Affects cost and generation time
* **images**: Optional reference image(s) for image editing, up to 16
* **mask**: Optional mask for inpainting (white areas are replaced). Requires exactly one reference image
* **n**: How many images to generate (1 to 8)
* **seed**: Kept for API compatibility; the backend does not use it yet

## GPT Image 2.5 Flare: Text to Image

Generate a poster from a text prompt with Flare's fast generation. The template prompt produces a 1:1 square racing-car poster with the text "GPT IMAGE 2.5" projected onto the car body: a good example of asking for rendered text, which the GPT Image family handles reliably.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openai_gpt_image_25_flare_t2i&utm_source=docs&utm_medium=referral&utm_campaign=gpt-image-2-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openai_gpt_image_25_flare_t2i.json">
    Download JSON or search "GPT Image 2.5 Flare" in Template Library
  </Card>
</CardGroup>

![GPT Image 2.5 Flare Text to Image workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_openai_gpt_image_25_flare_t2i-1.webp)

No API node workflows need model downloads: the generation runs on OpenAI's infrastructure. Connect the node's image output to a `Save Image` node and run the workflow.

Tips:

1. **Iterate with low quality first**: The template ships with `quality` set to `low`, which is cheap and fast. Raise it only for the final run
2. **Ask for text explicitly**: Quote the exact text in your prompt (for example "the words GPT IMAGE 2.5") and state where it should appear
3. **Exclude unwanted elements**: The template prompt ends with a list of exclusions ("No sidebar, no extra UI panels..."), which helps keep posters clean
4. **Use Custom sizes**: Pick `Custom` under `size` to set an exact width and height in 16px steps, up to 3840

## GPT Image 2.5 Flare: Image Edit

Edit an input image with Flare. The template demonstrates an outfit and hairstyle swap, but the workflow is general-purpose image editing: character appearance changes (outfit, hairstyle, accessories, expression), object replacement, background swaps, color adjustments, and any local modification where you want a fast preview. Good for iterating on edits before committing to a final high-quality run.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openai_gpt_image_25_flare_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=gpt-image-2-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openai_gpt_image_25_flare_image_edit.json">
    Download JSON or search "GPT Image 2.5 Flare" in Template Library
  </Card>
</CardGroup>

![GPT Image 2.5 Flare Image Edit workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_openai_gpt_image_25_flare_image_edit-1.webp)

Upload this file to the `Load Image` node:

<CardGroup>
  <Card title="Input Image: outfit_swap_base_gpt_image25.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/outfit_swap_base_gpt_image25.png">
    The example input image, or use your own.
  </Card>
</CardGroup>

Tips:

1. **State what to keep**: The template prompt opens with "Keep the background environment... completely unchanged" before describing the edit. This anchoring is what keeps the rest of the frame stable, and it works for any edit type: describe the scene, pose, and lighting you want preserved, then the change you want made
2. **Swap any appearance attribute**: The same prompt structure covers outfit changes, hairstyle changes, accessories, color schemes, or a full character redesign while keeping pose and scene
3. **One change per run**: Describe a single edit (or a tightly related set) rather than a list of unrelated changes. Run several iterations instead
4. **Mask for local edits**: Connect a mask to limit the edit to specific regions; white areas are replaced. A mask requires exactly one reference image
5. **Iterate in Flare, finish in Sunburst**: Use Flare to explore edit options cheaply, then re-run the winning prompt with `gpt-image-2.5-sunburst` for the final render

## GPT Image 2.5 Sunburst: Text to Image

Generate a high-fidelity editorial poster with Sunburst. The template prompt is a long, structured editorial prompt: scene, subject, oversized typography, scattered graphic elements, caption block, and a full palette/render specification. Use it as a scaffold for your own poster prompts.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openai_gpt_image_25_sunburst_t2i&utm_source=docs&utm_medium=referral&utm_campaign=gpt-image-2-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openai_gpt_image_25_sunburst_t2i.json">
    Download JSON or search "GPT Image 2.5 Sunburst" in Template Library
  </Card>
</CardGroup>

![GPT Image 2.5 Sunburst Text to Image workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_openai_gpt_image_25_sunburst_t2i-1.webp)

Tips:

1. **Structure long prompts by layer**: The template prompt describes one layer at a time (background scene, subject, typography, small graphic elements, caption, then global style). This keeps every element where you asked for it
2. **Pin text placement**: Say what the text is, its font style, its color, and what it should overlap ("letters weaving through the upper half of the frame, some behind the biker, some in front")
3. **Declare the palette**: Listing the exact palette ("burnt orange, black, desert beige and electric blue") plus the render style keeps the whole image coherent
4. **Raise quality for finals**: Sunburst at `high` or above is where its fidelity advantage shows; keep exploration on `low`

## GPT Image 2.5 Sunburst: Image Edit

Edit an input image with Sunburst's high fidelity. The template demonstrates a hairstyle and makeup change, but the workflow is general-purpose image editing: character appearance replacement (outfit, hairstyle, accessories), object insertion or removal, style conversion, and precise partial modifications. Use it for any edit where identity preservation and detail fidelity matter.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openai_gpt_image_25_sunburst_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=gpt-image-2-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openai_gpt_image_25_sunburst_image_edit.json">
    Download JSON or search "GPT Image 2.5 Sunburst" in Template Library
  </Card>
</CardGroup>

![GPT Image 2.5 Sunburst Image Edit workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_openai_gpt_image_25_sunburst_image_edit-1.webp)

Upload this file to the `Load Image` node:

<CardGroup>
  <Card title="Input Image: hairstyle_makeup_base_gpt_image25.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/hairstyle_makeup_base_gpt_image25.png">
    The example input image, or use your own.
  </Card>
</CardGroup>

Tips:

1. **Keep-list before change-list**: The template prompt names everything to preserve first ("Keep head, face, body, flowers, sweater, background, lighting unchanged"), then the single change. Follow that order for any edit: appearance swaps, object edits, background replacements, or style conversions
2. **Character appearance replacement**: To give a character a new outfit or look, enumerate the identity anchors you want preserved (face, body proportions, pose, lighting), then describe the new appearance precisely
3. **Strong subject consistency**: Sunburst keeps identity across sequential edits, which makes it suitable for multi-step edit chains and frame-to-frame generation with the same character
4. **Transparent backgrounds**: Both variants can return `transparent` backgrounds; useful for compositing the result into another scene downstream


# Partner Nodes
Source: https://docs.comfy.org/tutorials/partner-nodes/overview

Partner Nodes call closed-source models such as OpenAI, Kling, and Luma through API requests inside ComfyUI: what they are, credits, and how to use them.

Partner Nodes are ComfyUI's new way of calling closed-source models through API requests, providing ComfyUI users with access to external state-of-the-art AI models without complex API key setup.

## What are Partner Nodes?

Partner Nodes are a set of special nodes that connect to external API services, allowing you to use closed-source or third-party hosted AI models directly in your ComfyUI workflows. These nodes are designed to seamlessly integrate the capabilities of external models while maintaining the open-source nature of ComfyUI's core.

## Prerequisites for Using Partner Nodes

To use Partner Nodes, the following requirements must be met:

### 1. ComfyUI Version Requirements

Please update your ComfyUI to the latest version, as we may add more API support in the future, and corresponding nodes will be updated, so please keep your ComfyUI up to date.

<Tip>
  Please note the distinction between nightly and release versions. We recommend using the `nightly` version (which is the latest code commit), as the release version may not be updated in a timely manner.
  This refers to the development version and the stable version, and since we are still rapidly iterating, this document may not be updated promptly, so please pay attention to the version differences.
</Tip>

### 2. Account and Credits Requirements

You need to be logged into your ComfyUI with a [Comfy account](/interface/user) and have a credit balance of [credits](/interface/credits) greater than 0.

Log in via `Settings` -> `User`:

<img alt="ComfyUI User Interface" />

Go to `Settings` -> `Credits` to purchase credits

<img alt="Credits Interface" />

Please refer to the corresponding documentation for account and credits to ensure this requirement:

* [Comfy account](/interface/user): Find the `User` section in the settings menu to log in.
* [Credits](/interface/credits): After logging in, the settings interface will show a credits menu where you can purchase credits. We use a prepaid system, so there will be no unexpected charges.

### 3. Network Environment Requirements

API access requires that your current requests are based on a secure network environment. The current requirements for API access are as follows:

* The local network only allows access from `127.0.0.1` or `localhost`, and you can directly use the login function.
* If you are accessing from a local area network or a website that is not on the whitelist, please log in with an API Key. Please refer to [Log in with an API Key](/interface/user#logging-in-with-an-api-key).
* You should be able to access our API service normally (in some regions, you may need to use a proxy service).
* Access should be carried out in an `https` environment to ensure the security of the requests.

<Note>
  Accessing in an insecure context poses significant risks, which may result in the following consequences:

  1. Authentication may be stolen, leading to the leakage of your account information.
  2. Your account may be maliciously used, resulting in financial losses.

  Even if we open this restriction in the future, we strongly advise against accessing API services through insecure network requests due to the high risks involved.
</Note>

### 4. Using the Corresponding Nodes

**Add to Workflow**: Add the Partner Node to your workflow just like you would with other nodes.
**Run**: Set the parameters and then run the workflow.

<img alt="Partner Nodes" />

## Log in with ComfyUI Account API Key on non-whitelisted websites

Currently, we have set up a whitelist to restrict the websites where you can log in to your ComfyUI account.
If you need to log in to your ComfyUI account on some non-whitelisted websites, please refer to the account management section to learn how to log in using an API Key.
In this case, the corresponding website does not need to be on our whitelist.

<Card title="Account Management" icon="book" href="/interface/user#logging-in-with-an-api-key">
  Learn how to log in with ComfyUI Account API Key
</Card>

<img alt="Select Comfy API Key Login" />

## Use ComfyUI Account API Key Integration to call paid model Partner nodes

Currently, we support accessing our services through ComfyUI API Key Integration to call paid model Partner nodes. Please refer to the API Key Integration section to learn how to use API Key Integration to call paid model Partner nodes.

<Note>
  **Important:** The API key discussed here is your **ComfyUI Account API Key** (used for accessing paid Partner nodes in workflows). This is **NOT** the same as the **Registry Publishing API Key** used by developers to publish custom nodes to the registry. If you're looking to publish custom nodes, see [Publishing Nodes](/registry/publishing).
</Note>

<Card title="API Key Integration" icon="link" href="/development/comfyui-server/api-key-integration">
  Please refer to the API Key Integration section to learn how to use API Key Integration to call paid model Partner nodes
</Card>

## Advantages of Partner Nodes

Partner Nodes provide several important advantages for ComfyUI users:

* **Access to closed-source models**: Use state-of-the-art AI models without having to deploy them yourself
* **Seamless integration**: Partner nodes are fully compatible with other ComfyUI nodes and can be combined to create complex workflows
* **Simplified experience**: No need to manage API keys or handle complex API requests
* **Controlled costs**: The prepaid system ensures you have complete control over your spending with no unexpected charges

## Pricing

<Card title="Partner Node Pricing" icon="coin" href="/tutorials/partner-nodes/pricing">
  Please refer to the pricing page for the corresponding Partner pricing
</Card>

## Model Providers

<Card title="Model Providers" icon="badge-check" href="/tutorials/partner-nodes/model-providers">
  See verification status, commercial licensing, and data residency for the model providers behind Partner Nodes
</Card>

## About Open Source and Opt-in

It's important to note that **Partner Nodes are completely optional**. ComfyUI will always remain fully open-source and free for local users. Partner nodes are designed as an "opt-in" feature, providing convenience for those who want access to external SOTA (state-of-the-art) models.

## How to disable partner nodes completely

You can add the `--disable-partner-nodes` launch argument to disable all Partner Nodes in ComfyUI. Use `--offline` instead if you also want to prevent the frontend from communicating with the internet.

**For manual install:**

```bash theme={null}
python main.py --disable-partner-nodes
```

**For portable users (Windows):**

Update your `run_xxx.bat` file:

```batch theme={null}
.\python_embeded\python.exe -s ComfyUI\main.py --listen --windows-standalone-build --disable-partner-nodes
pause
```

## Use Cases

A powerful application of Partner Nodes is combining the output of external models with local nodes. For example:

* Using GPT-Image-1 to generate a base image, then transforming it into video with a local `wan` node
* Combining externally generated images with local upscaling or style transfer nodes
* Creating hybrid workflows that leverage the advantages of both closed-source and open-source models

This flexibility makes ComfyUI a truly universal generative AI interface, integrating various AI capabilities into a unified workflow, opening up more possibilities

## FAQs

<AccordionGroup>
  <Accordion title="Why can't I find the Partner Nodes?">
    Please update your ComfyUI to the latest version (the latest commit or the latest [desktop version](https://www.comfy.org/download)).
    We may add more API support in the future, and the corresponding nodes will be updated, so please keep your ComfyUI up to date.

    <Tip>
      Please note that you need to distinguish between the nightly version and the release version.
      In some cases, the latest `release` version may not be updated in time compared to the `nightly` version.
      Since we are still iterating quickly, please ensure you are using the latest version when you cannot find the corresponding node.
    </Tip>
  </Accordion>

  <Accordion title="Why can't I use / log in to the Partner Nodes?">
    API access requires that your current request is based on a secure network environment. The current requirements for API access are as follows:

    * The local network only allows access from `127.0.0.1` or `localhost`, which may mean that you cannot use the Partner Nodes in a ComfyUI service started with the `--listen` parameter in a LAN environment.
    * Able to access our API service normally (a proxy service may be required in some regions).
    * Your account does not have enough [credits](/interface/credits).
  </Accordion>

  <Accordion title="Why can't I use Partner Node even after logging in, or why does it keep asking me to log in while using?">
    * Currently, only `127.0.0.1` or `localhost` access is supported.
    * Ensure your account has enough credits.
  </Accordion>

  <Accordion title="Can Partner Nodes be used for free?">
    Partner Nodes require credits for API calls to closed-source models, so they do not support free usage.
  </Accordion>

  <Accordion title="How to purchase credits?">
    Please refer to the following documentation:

    1. [Comfy Account](/interface/user): Find the `User` section in the settings menu to log in.
    2. [Credits](/interface/credits): After logging in, the settings interface will show the credits menu. You can purchase credits in `Settings` → `Credits`. We use a prepaid system, so there will be no unexpected charges.
    3. Complete the payment through Stripe.
    4. Check if the credits have been updated. If not, try restarting or refreshing the page.
  </Accordion>

  <Accordion title="Are unused credits refundable?">
    Currently, we do not support refunds for credits.
    If you believe there is an error resulting in unused balance due to technical issues, please [contact support](mailto:support@comfy.org).
  </Accordion>

  <Accordion title="Can credits go negative?">
    Credits are not intended to be used as a negative balance or credit line. However, due to race conditions where partner nodes don't always report costs before execution, a single execution may consume more credits than your remaining balance and temporarily result in a negative balance after completion. When your balance is negative, you will not be able to run Partner Nodes until you top up and restore a positive balance. Please ensure you have enough credits before making API calls.
  </Accordion>

  <Accordion title="Where can I check usage and expenses?">
    Please visit the [Credits](/interface/credits) menu after logging in to check the corresponding credits.
  </Accordion>

  <Accordion title="Is it possible to use my own API Key?">
    Currently, the Partner Nodes are still in the testing phase and do not support this feature yet, but we have considered adding it.
  </Accordion>

  <Accordion title="Do credits expire?">
    Yes, the expiration depends on the type of credits:

    * **Monthly credits**: Expire at the end of your billing period
    * **Top-up credits**: Expire 1 year from the date of purchase
  </Accordion>

  <Accordion title="Can credits be transferred or shared?">
    No, your credits cannot be transferred to other users and are limited to the currently logged-in account, but we do not restrict the number of devices that can log in.
  </Accordion>

  <Accordion title="Can I use the same account on different devices?">
    We do not limit the number of devices that can log in; you can use your account anywhere you want.
  </Accordion>

  <Accordion title="How can I request for my account or information to be deleted??">
    Email a request to [support@comfy.org](mailto:support@comfy.org) and we will delete your information
  </Accordion>

  <Accordion title="Is there content moderation for Partner Nodes?">
    Partner Nodes send your inputs (prompts, images, and other content) to third-party providers for processing. These providers enforce their own content moderation policies. Please do not submit NSFW or other prohibited content to API nodes.
  </Accordion>
</AccordionGroup>


# Partner Node Pricing
Source: https://docs.comfy.org/tutorials/partner-nodes/pricing

Partner Node pricing in credits for every provider, including Anthropic, OpenAI, Kling, and Luma, broken down by model, token type, and generation type.

The following table lists the pricing of the current Partner Nodes. All prices are in credits.

## Anthropic

### Chat

| Model | Input credits / 1K | 5m Cache Write credits / 1K | 1h Cache Write credits / 1K | Cache Hit credits / 1K | Output credits / 1K |
| :- | -: | -: | -: | -: | :- |
| Opus 5.5 | 1.207 | 1.509 | 2.414 | 0.121 | 6.035 |
| Opus 5, Opus 4.8 | 1.509 | 1.886 | 3.017 | 0.151 | 7.543 |
| Fable 5.1, Fable 5 | 3.017 | 3.772 | 6.035 | 0.302 | 15.087 |
| Sonnet 5 | 0.603 | 0.754 | 1.207 | 0.060 | 3.017 |

Optional images add tokens billed at the same model input rates.

## Beeble

### Video: SwitchX Video Edit

| max\_resolution | Credits |
| :- | :- |
| 720p | 30.17 / 30 frames |
| 1080p | 90.52 / 30 frames |

### Image: SwitchX Image Edit

| max\_resolution | Credits |
| :- | :- |
| 720p | 30.17 / run |
| 1080p | 90.52 / run |

## BFL

### Image

| Node | Credits |
| :- | :-: |
| Flux 1.1 \[pro] Ultra Image | 12.66 / run |
| Flux.1 Kontext \[pro] Image | 8.44 / run |
| Flux.1 Kontext \[max] Image | 16.88 / run |
| Flux.1 Expand Image | 10.55 / run |
| Flux.1 Fill Image | 10.55 / run |
| Flux Erase Image | 6.33 / run + 0.84 / extra MP |
| Flux Virtual Try-On | 7.91 / run + 1.06 / extra MP |
| Flux.2 \[pro] | 6.33 / run + 3.17 / extra MP |
| Flux.2 \[max] | 14.77 / run + 6.33 / extra MP |

### Video: Flux 3

Total credits = **(credits / sec) × `duration`** (`duration` is 5–20 seconds or `auto`).

| Node | resolution | Credits / sec |
| :- | :- | :- |
| Flux 3 Text to Video | 720p | 51.29 |
| Flux 3 Text to Video | 1080p | 87.50 |
| Flux 3 Image to Video | 720p | 51.29 |
| Flux 3 Image to Video | 1080p | 87.50 |
| Flux 3 Video Continuation | 720p | 123.71 |
| Flux 3 Video Continuation | 1080p | 159.92 |

### Video: Flux Video Edit

Total credits = **(credits / sec) × `duration`**. Source clips of 0.7 to 15 seconds are edited from a text instruction.

| Node | Credits / sec |
| :- | :- |
| Flux Video Edit | 9.05 |

### Video: Flux Video Upscale

Rates are **per output megapixel per second**. Total credits = **credits / MP / sec × output megapixels × `duration`**. Output resolution ranges from 1080p (\~2.1 MP) to 4K (\~8.3 MP).

| Node | mode | Credits / MP / sec |
| :- | :- | :- |
| Flux Video Upscale | creative | 30.17 |
| Flux Video Upscale | precise | 21.12 |

## Bria

### Image

| Node | Credits |
| :- | :- |
| Bria Generative Fill | 9.05 / run |
| Bria Eraser | 6.03 / run |
| Bria Expand Image | 6.03 / run |
| Bria Increase Resolution | 6.03 / run |
| Bria FIBO Image Edit | 8.44 / run |
| Bria Remove Image Background | 3.8 / run |
| Bria Erase by Text | 12.07 / run |
| Bria Add Object | 12.07 / run |
| Bria Replace Object | 12.07 / run |
| Bria Relight | 12.07 / run |
| Bria Restore Photo | 12.07 / run |
| Bria Reseason | 12.07 / run |
| Bria Erase Foreground | 12.07 / run |
| Bria Replace Image Background | 12.07 / run |

### Video

| Node | Credits |
| :- | :- |
| Bria Remove Video Background | 10.55 / sec |
| Bria Video Green Screen | 10.55 / sec |
| Bria Video Replace Background | 10.55 / sec |
| Bria Remove Video Background (Transparent) | 10.55 / sec |
| Bria Video Eraser | 13.58 / sec |

## ByteDance

### LLM: ByteDance Seed

Per million tokens. Rates below are for prompt length **\[0, 128]K**; longer prompts use higher tiers.

| Model | Input credits / 1M | Cache hit credits / 1M | Output credits / 1M |
| :- | -: | -: | :- |
| Seed 2.0 Pro (`seed-2-0-pro-260328`) | 105.5 | 21.1 | 633 |
| Seed 2.0 Lite (`seed-2-0-lite-260228`) | 52.75 | 10.55 | 422 |
| Seed 2.0 Mini (`seed-2-0-mini-260215`) | 21.1 | 4.22 | 84.4 |

Optional images and videos add input tokens at the input rate.

### Image: ByteDance Seedream

Per successfully generated image.

| model | Credits / image |
| :- | :- |
| seedream 5.0 pro (`seedream-5-0-pro-260628`) | 9.50 (1K) / 18.99 (2K) |
| seedream 5.0 flash (`seedream-5-0-flash-260915`) | 5.43 |
| seedream 5.0 lite (`seedream-5-0-260128`) | 7.39 |
| seedream-4-5-251128 | 8.44 |
| seedream-4-0-250828 | 6.33 |
| Seedream 5.0 Pro Layer Separation | 6.79 (1K, 1.5K) / 13.58 (2K) |
| Seedream 5.0 Flash Layer Separation | 5.43 |

Seedream 5.0 Pro uses resolution-based billing: **1K** (≤2.61 MP, **9.50 credits**) and **2K** (>2.61 MP, **18.99 credits**). Seedream 5.0 Flash bills a flat **5.43 credits** per image at every resolution. The first image in each request is free. Each additional image beyond the first (including both output and input/reference images) adds **0.63 credits**.

### Image: ByteDance Image (deprecated)

<Warning>
  **Deprecated**: The **ByteDance Image** node (Seedream 3.0) has been retired and removed from ComfyUI. The pricing below is retained for reference only.
</Warning>

| model | Credits / image |
| :- | :- |
| seedream-3-0-t2i-250415 | 6.33 |

### Video: Seedance 2.5

Token-based billing. Estimated token consumption = **(input video duration + output video duration) × output video width × output video height × output video frame rate ÷ 1024**. When input is text, image, or audio only, input video duration = 0. Actual usage from the API is authoritative.

| Model | Resolution | Video input | Credits / 1K tokens |
| :- | :- | :- | -: |
| Seedance 2.5 | 480p, 720p | no | 3.229 |
| Seedance 2.5 | 480p, 720p | yes | 1.931 |
| Seedance 2.5 | 1080p | no | 3.530 |
| Seedance 2.5 | 1080p | yes | 2.112 |

**Video input** means a reference video is connected. Text, image, and audio references count as no video input. Minimum token consumption limits apply when the input includes video: if the estimated consumption is below the limit, billing uses the minimum.

Reference videos must be at least 2 seconds long, and total input is limited to 30 seconds. Estimated charges for 16:9 output at 24 fps:

| Resolution | 5s output, no video input | 5s output + 2–30s video input |
| :- | -: | -: |
| 480p | 155.1 | 166.9 – 649.3 |
| 720p | 348.8 | 375.4 – 1459.8 |
| 1080p | 857.8 | 923.9 – 3592.7 |

### Video: Seedance 2.0

480p and 720p share the same rate. Fast and Mini do not support 1080p or 4K.

Estimated token consumption:

`(Input video duration + Output video duration) × Output video width × Output video height × Output video frame rate ÷ 1024`

When input is text, image, or audio only, input video duration = 0. Actual usage from the API is authoritative.

| Model | Resolution | Video input | Credits / 1K tokens |
| :- | :- | :- | -: |
| Seedance 2.0 | 480p, 720p | no | 2.112 |
| Seedance 2.0 | 480p, 720p | yes | 1.297 |
| Seedance 2.0 | 1080p | no | 2.323 |
| Seedance 2.0 | 1080p | yes | 1.418 |
| Seedance 2.0 | 4k | no | 1.207 |
| Seedance 2.0 | 4k | yes | 0.724 |
| Seedance 2.0 Fast | 480p, 720p | no | 1.690 |
| Seedance 2.0 Fast | 480p, 720p | yes | 0.996 |
| Seedance 2.0 Mini | 480p, 720p | no | 1.056 |
| Seedance 2.0 Mini | 480p, 720p | yes | 0.634 |

**Video input** means reference video is connected. Text, image, and audio references count as no video input.

For video-to-video inputs, a minimum token usage may apply. Seedance 2.0 outputs at 24fps.

### Video: Seedance 1.x

Billed by tokens (same estimation formula as Seedance 2.0). Unlike Seedance 2.0, the **token rate does not change by resolution**; resolution changes how many tokens a clip uses (via width × height in the formula), so higher resolutions cost more.

**Token rate**

| Model | Condition | Credits / 1M tokens |
| :- | :- | :- |
| seedance-1-5-pro-251215 | `generate_audio: false` | 253.2 |
| seedance-1-5-pro-251215 | `generate_audio: true` | 506.4 |
| seedance-1-0-pro-250528 | — | 527.5 |
| seedance-1-0-pro-fast-251015 | — | 211 |

<Warning>
  **Deprecated**: `seedance-1-0-lite-t2v-250428` and `seedance-1-0-lite-i2v-250428`, and the **ByteDance Reference Images to Video** node, have been retired and removed from ComfyUI. The pricing below is retained for reference only.
</Warning>

**Approximate credits / 10 sec** (scale with `duration ÷ 10`. Ranges reflect aspect ratio.)

| model | resolution | generate\_audio | Credits / 10 sec |
| :- | :- | :- | :- |
| seedance-1-5-pro-251215 | 480p | off | 25.32 |
| seedance-1-5-pro-251215 | 480p | on | 50.64 |
| seedance-1-5-pro-251215 | 720p | off | 54.86 |
| seedance-1-5-pro-251215 | 720p | on | 109.72 |
| seedance-1-5-pro-251215 | 1080p | off | 122.38 – 124.49 |
| seedance-1-5-pro-251215 | 1080p | on | 244.76 – 249.0 |
| seedance-1-0-pro-250528 | 480p | — | 48.53 – 50.64 |
| seedance-1-0-pro-250528 | 720p | — | 107.61 – 118.16 |
| seedance-1-0-pro-250528 | 1080p | — | 248.98 – 257.42 |
| seedance-1-0-pro-fast-251015 | 480p | — | 18.99 – 21.1 |
| seedance-1-0-pro-fast-251015 | 720p | — | 44.31 – 48.53 |
| seedance-1-0-pro-fast-251015 | 1080p | — | 99.17 – 103.39 |
| seedance-1-0-lite-i2v-250428 | 480p | — | 35.87 – 37.98 |
| seedance-1-0-lite-i2v-250428 | 720p | — | 78.07 – 86.51 |
| seedance-1-0-lite-i2v-250428 | 1080p | — | 179.35 – 185.68 |

**ByteDance Reference Images to Video** (480p and 720p only):

| model | resolution | Credits / 10 sec |
| :- | :- | :- |
| seedance-1-0-pro-250528 | 480p | 48.53 – 50.64 |
| seedance-1-0-pro-250528 | 720p | 107.61 – 118.16 |
| seedance-1-0-lite-i2v-250428 | 480p | 35.87 – 37.98 |
| seedance-1-0-lite-i2v-250428 | 720p | 78.07 – 86.51 |

### Video: ByteDance vCube Video Enhance

Billed per second of enhanced output. The rates below are per second at 30 fps or below. Rates from 31 to 60 fps double the rate, and rates above 60 fps quadruple it. With **source** resolution or frame rate selected, the rate scales with the source video (approximately 1× to 4×).

| tool\_version | Resolution | Credits / second |
| :- | :- | :- |
| standard | 720p | \~1.04 |
| standard | 1080p | \~2.08 |
| standard | 2K | \~4.16 |
| standard | 4K | \~8.31 |
| standard | 8K | \~33.25 |
| professional | 720p | \~10.39 |
| professional | 1080p | \~20.78 |
| professional | 2K | \~41.56 |
| professional | 4K | \~83.12 |
| professional | 8K | \~332.47 |

### Audio: ByteDance Seed Audio 1.0

Per minute of generated audio. Total credits = **credits / min × duration (minutes)**.

| Node | Credits |
| :- | :- |
| ByteDanceSeedAudio | \~45.26 / min |

## ElevenLabs

| Node | Credits |
| :- | :- |
| ElevenLabs Text to Speech | 50.64 / 1K chars |
| ElevenLabs Text to Dialogue | 50.64 / 1K chars |
| ElevenLabs Speech to Text | 1.54 / min |
| ElevenLabs Speech to Speech | 50.64 / min |
| ElevenLabs Text to Sound Effects | 29.54 / min |
| ElevenLabs Voice Isolation | 50.64 / min |
| ElevenLabs Instant Voice Clone | 31.65 / run |

## FishAudio

| Node | Credits |
| :- | :- |
| Fish Audio Text to Speech | \~4.53 / 1K bytes |
| Fish Audio Speech to Text | \~1.81 / minute |
| Fish Audio Instant Voice Clone | Free |

## Magnific

### Image: Upscale

**Magnific Image Upscale (Creative)** and **Magnific Image Upscale (Precise V2)** share the same billing. Upscaling runs in 2x steps (`2x` = 1 step, `4x` = 2, `8x` = 3, `16x` = 4). After each step, pixel count ×4; each step is priced by the input megapixels at that step.

| Input MP at step | Credits / 2x step |
| :- | :- |
| ≤1.3 | 35.91 |
| ≤3.0 | 71.82 |
| ≤6.4 | 107.73 |
| >6.4 | 430.88 |

**Total credits** = sum of all steps for your `scale_factor`. Example: **4x** on a 1 MP image → step 1 at 1 MP (35.91) + step 2 at 4 MP (107.73) = **143.64 credits**.

### Image: Edit

| Node | Credits |
| :- | :- |
| Magnific Image Style Transfer | 23.21 / run |
| Magnific Image Relight | 23.21 / run |
| Magnific Image Skin Enhancer (creative) | 61.19 / run |
| Magnific Image Skin Enhancer (faithful) | 78.07 / run |
| Magnific Image Skin Enhancer (flexible) | 94.95 / run |

## Google

### Chat: Google Gemini

Token-based billing; thought tokens use the output text rate.

| Model | Input credits / 1K | Output credits / 1K |
| :- | -: | :- |
| Gemini 3.8 Flash (`gemini-3.8-flash`) | 0.4526 | 2.263 |
| Gemini 3.7 Flash (`gemini-3.7-flash`) | 0.4526 | 2.263 |
| Gemini 3.5 Flash (`gemini-3.5-flash`) | 0.3165 | 1.899 |
| Gemini 3.1 Pro (`gemini-3.1-pro-preview`) | 0.422 | 2.532 |
| Gemini 3.1 Flash-Lite (`gemini-3.1-flash-lite-preview`) | 0.05275 | 0.3165 |
| Gemini 2.5 Pro (`gemini-2.5-pro`) | 0.26375 | 2.11 |
| Gemini 2.5 Flash (`gemini-2.5-flash`) | 0.0633 | 0.5275 |

### Image: Nano Banana

Token-based billing.

| Model | Input credits / 1K | Output (text) credits / 1K | Output (image) credits / 1K |
| :- | -: | -: | :- |
| Nano Banana (`gemini-2.5-flash-image`) | 0.0633 | 0.5275 | 6.33 |
| Nano Banana Pro (`gemini-3-pro-image`) | 0.5064 | 3.0384 | 30.38 |
| Nano Banana 2 (`gemini-3.1-flash-image`) | 0.1266 | 0.7596 | 15.19 |
| Nano Banana 2 Lite (`gemini-3.1-flash-lite-image`) | 0.0633 | 0.3798 | 7.60 |

### Video: Google Gemini Omni

Billed per second of generated video. Rates are approximate.

| Model | Resolution | Credits / sec |
| :- | :- | :- |
| Gemini Omni Flash (`gemini-omni-flash-preview`) | — | 30.57 |
| Gemini Omni Flash 1.1 (`gemini-omni-1.1-flash`) | 360p | 10.19 |
| | 720p | 30.57 |
| | 1080p | 45.87 |
| | 4k | 91.76 |

### Video: Google Veo

Total credits = **(credits / sec) × duration**.

| Model | Resolution | generate\_audio | Credits / sec |
| :- | :- | :- | :- |
| veo-3.1-lite | 720p | false | 6.33 |
| veo-3.1-lite | 720p | true | 10.55 |
| veo-3.1-lite | 1080p | false | 10.55 |
| veo-3.1-lite | 1080p | true | 16.88 |
| veo-3.1-fast-generate | 720p | false | 16.88 |
| veo-3.1-fast-generate | 720p | true | 21.1 |
| veo-3.1-fast-generate | 1080p | false | 21.1 |
| veo-3.1-fast-generate | 1080p | true | 25.32 |
| veo-3.1-fast-generate | 4k | false | 52.75 |
| veo-3.1-fast-generate | 4k | true | 63.3 |
| veo-3.1-generate | 720p, 1080p | false | 42.2 |
| veo-3.1-generate | 720p, 1080p | true | 84.4 |
| veo-3.1-generate | 4k | false | 84.4 |
| veo-3.1-generate | 4k | true | 126.6 |

## HappyHorse

Total credits = **(credits / sec) × `duration`**.

| Model | Resolution | Credits / sec |
| :- | :- | :- |
| HappyHorse 1.0 | 720P | 29.54 |
| HappyHorse 1.0 | 1080P | 50.64 |
| HappyHorse 1.1 | 720P | 42.24 |
| HappyHorse 1.1 | 1080P | 54.31 |

**HappyHorse Video Edit** supports **HappyHorse 1.0** only. Billed at the same rates; total credits = **(credits / sec) × output duration** (3–15 sec, matches the input video).

## HeyGen

Prices are set per-second or per-run.

| Node | Condition | Credits |
| :- | :- | :- |
| HeyGen Talking Photo | N/A | 15.09 / sec |
| HeyGen Avatar Video | Avatar III, Digital Twin | 3.02 / sec |
| HeyGen Avatar Video | Avatar III, Photo / Studio Avatar | 4.98 / sec |
| HeyGen Avatar Video | Avatar IV, Photo Avatar | 11.62 / sec |
| HeyGen Avatar Video | Avatar IV, Digital Twin / Studio Avatar | 24.29 / sec |
| HeyGen Avatar Video | Avatar V | 36.21 / sec |
| HeyGen Avatar Video | Auto (engine chosen by the avatar look) | 3.02-36.21 / sec |
| HeyGen Create Avatar | From prompt | 301.73 / run |
| HeyGen Create Avatar | From photo | 398.28 / run |
| HeyGen Video Translate | precision mode | 7.54 / sec |
| HeyGen Video Translate | speed mode, audio only | 2.87 / sec |
| HeyGen Video Translate | speed mode | 4.07 / sec |
| HeyGen Text to Speech | N/A | \~0.20 / sec |

Avatar video bills per second at the rate of the selected avatar look's type (Digital Twin, Photo Avatar, or Studio Avatar). **Auto** picks the engine per look, so its rate spans the full range above; a custom avatar ID is billed by its own type.

## Hitpaw

### Video: HitPaw Video Enhance

Total credits = **(credits / sec) × video duration**. Rates depend on input FPS.

**Portrait Restore / General Restore** (Portrait Restore 1x/2x, General Restore 1x/2x/4x):

| Resolution | FPS | Credits / sec |
| :- | :- | :- |
| 720P | \<30fps | 2.11 |
| 720P | 30–60fps | 4.22 |
| 720P | 60–120fps | 8.44 |
| 720P | ≥120fps | 12.66 |
| 1080P | \<30fps | 3.17 |
| 1080P | 30–60fps | 6.33 |
| 1080P | 60–120fps | 12.66 |
| 1080P | ≥120fps | 18.99 |
| 2K | \<30fps | 4.22 |
| 2K | 30–60fps | 8.23 |
| 2K | 60–120fps | 16.46 |
| 2K | ≥120fps | 24.69 |
| 4K | \<30fps | 5.28 |
| 4K | 30–60fps | 10.76 |
| 4K | 60–120fps | 21.31 |
| 4K | ≥120fps | 32.07 |
| 8K | \<30fps | 6.96 |
| 8K | 30–60fps | 13.93 |
| 8K | 60–120fps | 27.85 |
| 8K | ≥120fps | 41.78 |

**Ultra HD** (Ultra HD Model 2x):

| Resolution | FPS | Credits / sec |
| :- | :- | :- |
| 720P | \<30fps | 3.17 |
| 720P | 30–60fps | 6.54 |
| 720P | 60–120fps | 13.08 |
| 720P | ≥120fps | 19.41 |
| 1080P | \<30fps | 4.22 |
| 1080P | 30–60fps | 8.44 |
| 1080P | 60–120fps | 16.88 |
| 1080P | ≥120fps | 25.32 |
| 2K | \<30fps | 5.49 |
| 2K | 30–60fps | 10.97 |
| 2K | 60–120fps | 21.94 |
| 2K | ≥120fps | 32.92 |
| 4K | \<30fps | 7.17 |
| 4K | 30–60fps | 14.35 |
| 4K | 60–120fps | 28.49 |
| 4K | ≥120fps | 42.83 |
| 8K | \<30fps | 9.28 |
| 8K | 30–60fps | 18.57 |
| 8K | 60–120fps | 37.14 |
| 8K | ≥120fps | 55.7 |

**Generative** (Generative Model 1x; up to 4K):

| Resolution | FPS | Credits / sec |
| :- | :- | :- |
| 720P | \<30fps | 3.17 |
| 720P | 30–60fps | 6.33 |
| 720P | 60–120fps | 12.66 |
| 720P | ≥120fps | 18.99 |
| 1080P | \<30fps | 5.28 |
| 1080P | 30–60fps | 10.55 |
| 1080P | 60–120fps | 21.1 |
| 1080P | ≥120fps | 31.65 |
| 2K | \<30fps | 8.02 |
| 2K | 30–60fps | 15.82 |
| 2K | 60–120fps | 31.65 |
| 2K | ≥120fps | 47.48 |
| 4K | \<30fps | 11.82 |
| 4K | 30–60fps | 23.84 |
| 4K | 60–120fps | 47.48 |
| 4K | ≥120fps | 71.32 |

### Image: HitPaw General Image Enhance

**Generative Portrait**:

| Megapixels | Credits / run |
| :- | :- |
| \<8MP | 4.22 |
| 8–12MP | 6.33 |
| 12–24MP | 8.44 |
| 24–34MP | 12.66 |

**Generative**:

| Megapixels | Credits / run |
| :- | :- |
| \<8MP | 10.55 |
| 8–12MP | 12.66 |
| 12–24MP | 16.88 |
| 24–34MP | 31.65 |

## Ideogram

| Node | turbo | Character reference | rendering\_speed | Credits / image |
| :- | :- | :- | :- | :- |
| Ideogram V1 | false | — | — | 18.1 |
| Ideogram V1 | true | — | — | 6.03 |
| Ideogram V2 | false | — | — | 24.14 |
| Ideogram V2 | true | — | — | 15.09 |
| Ideogram V4 | — | — | TURBO | 9.05 |
| Ideogram V4 | — | — | DEFAULT | 18.1 |
| Ideogram V4 | — | — | QUALITY | 30.17 |

| Node | quality | resolution | Credits / image |
| :- | :- | :- | :- |
| Ideogram & Pruna P-Image | VERY\_LOW | 1K | 0.91 |
| Ideogram & Pruna P-Image | VERY\_LOW | 2K | 1.81 |
| Ideogram & Pruna P-Image | LOW | 1K | 2.26 |
| Ideogram & Pruna P-Image | LOW | 2K | 4.53 |
| Ideogram & Pruna P-Image | MEDIUM | 1K | 3.02 |
| Ideogram & Pruna P-Image | MEDIUM | 2K | 6.03 |
| Ideogram & Pruna P-Image | HIGH | 1K | 4.53 |
| Ideogram & Pruna P-Image | HIGH | 2K | 9.05 |

## Krea

| Model | Style reference | Moodboard | Credits / run |
| :- | :- | :- | :- |
| Krea 2 Medium Turbo | No | No | 3.17 |
| Krea 2 Medium Turbo | Yes | No | 3.69 |
| Krea 2 Medium Turbo | — | Yes | 4.22 |
| Krea 2 Medium | No | No | 6.33 |
| Krea 2 Medium | Yes | No | 7.39 |
| Krea 2 Medium | — | Yes | 8.44 |
| Krea 2 Large | No | No | 12.66 |
| Krea 2 Large | Yes | No | 13.72 |
| Krea 2 Large | — | Yes | 14.77 |

## Kling

### Video: Credits / sec

Total credits = **(credits / sec) × `duration`**, except **Kling 3.0 Omni Edit Video** and **Kling Motion Control** (billed per second of output; duration follows input video on Edit).

#### kling-video-o1

| task | resolution | Credits / sec |
| :- | :- | :- |
| generation | 720p | 17.72 |
| generation | 1080p | 23.63 |
| video to video, edit | 720p | 26.59 |
| video to video, edit | 1080p | 35.45 |

#### kling-v3-omni

| task | resolution | generate\_audio | Credits / sec |
| :- | :- | :- | :- |
| generation | 720p | false | 17.72 |
| generation | 720p | true | 23.63 |
| generation | 1080p | false | 23.63 |
| generation | 1080p | true | 29.54 |
| generation | 4k | false, true | 88.62 |
| video to video, edit | 720p | — | 26.59 |
| video to video, edit | 1080p | — | 35.45 |

#### kling-3.0-turbo

Always generates audio; the audio toggle is ignored.

| resolution | Credits / sec |
| :- | :- |
| 720p | 23.63 |
| 1080p | 29.54 |

#### kling-v3

| task | resolution | generate\_audio | Credits / sec |
| :- | :- | :- | :- |
| generation | 720p | false | 17.72 |
| generation | 720p | true | 26.59 |
| generation | 1080p | false | 23.63 |
| generation | 1080p | true | 35.45 |
| generation | 4k | false, true | 88.62 |

| task | mode | Credits / sec |
| :- | :- | :- |
| motion control | std | 26.59 |
| motion control | pro | 35.45 |

#### kling-v2-6

| task | generate\_audio | mode | Credits / sec |
| :- | :- | :- | :- |
| generation | false | — | 14.77 |
| generation | true | — | 29.54 |
| motion control | — | std | 14.77 |
| motion control | — | pro | 23.63 |

<Warning>
  **End of life (EOL)**: Kling V1.5, V1.6, V2.1, V2.1 Master, and Kolors Virtual Try-On are scheduled for retirement on **September 15, 2026**. The pricing below is retained for reference until removal.
</Warning>

#### kling-v2-5-turbo

**Kling Text to Video**, **Kling Image (First Frame) to Video**, and **Kling Start-End Frame to Video** use `kling-v2-5-turbo` in **pro** mode only, billed per run at a fixed 5s or 10s duration.

| Node | mode | Credits / run |
| :- | :- | :- |
| Kling Text to Video | pro | 73.85 (5s), 147.7 (10s) |
| Kling Image (First Frame) to Video | pro | 73.85 (5s), 147.7 (10s) |
| Kling Start-End Frame to Video | pro | 73.85 (5s), 147.7 (10s) |

#### Kling Avatar 2.0

| mode | Credits / sec |
| :- | :- |
| std | 11.82 |
| pro | 23.63 |

### Video: Credits / run

| Model | task | Credits / run |
| :- | :- | :- |
| — | Lip Sync | 14.77 |

<Warning>
  **Deprecated**: The **Kling Video Extend** node has been retired and removed from ComfyUI.
</Warning>

### Image

| Model | resolution | Image input | Credits |
| :- | :- | :- | :- |
| kling-image-o1 | 1K, 2K | — | 5.91 / image |
| kling-image-o1 | 4K | — | 11.82 / image |
| kling-v3-omni | 1K, 2K | — | 5.91 / image |
| kling-v3-omni | 4K | — | 11.82 / image |
| kling-v3 | — | No | 5.91 / image |

Total image credits = **(credits / image) × `n`** on **Kling 3.0 Image**; multiply by `series_amount` on **Kling 3.0 Omni Image** (`kling-image-o1` always ×1).

## Lightricks

### Video: Credits / sec

Total credits = **(credits / sec) × `duration`**.

<Warning>
  **Deprecated**: The **LTXV Text To Video** and **LTXV Image To Video** nodes (LTX-2 Pro / LTX-2 Fast) have been retired and removed from ComfyUI. Use **LTX-2.5** instead. The pricing below is retained for reference only.
</Warning>

| Model | resolution | Credits |
| :- | :- | :- |
| LTX-2.5 (Pro) | 720p | 36.21 / sec |
| LTX-2.5 (Pro) | 1080p | 51.29 / sec |
| LTX-2.5 (Fast) | 720p | 27.16 / sec |
| LTX-2.5 (Fast) | 1080p | 39.22 / sec |
| LTX-2.5 (Fast) | 1440p | 57.33 / sec |
| LTX-2.5 (Fast) | 4K | 90.52 / sec |
| LTX-2.5 Audio To Video (Pro) | — | 51.29 / sec |
| LTX-2.5 Audio To Video (Fast) | — | 39.22 / sec |
| LTX-2 (Pro) | 1080p | 12.66 / sec |
| LTX-2 (Pro) | 1440p | 25.32 / sec |
| LTX-2 (Pro) | 4K | 50.64 / sec |
| LTX-2 (Fast) | 1080p | 8.44 / sec |
| LTX-2 (Fast) | 1440p | 16.88 / sec |
| LTX-2 (Fast) | 4K | 33.76 / sec |

Resolution maps to `1280x720` / `720x1280` (720p), `1920x1080` / `1080x1920` (1080p), `2560x1440` / `1440x2560` (1440p), and `3840x2160` / `2160x3840` (4K). Durations over 10s on **LTX-2.5 (Fast)** require a 720p or 1080p resolution and 24/25 FPS; on **LTX-2 (Fast)** they require 1080p and 25 FPS.

## Luma

### Video

Flat **/run** prices match the node badge for each `duration` choice. **Edit** and **reframe** bill **(credits / sec) × video length**. **ray-1-6** is always **105.50 / run**.

| Model | task | resolution | Credits |
| :- | :- | :- | :- |
| ray-3.2 | generation | 360p | 12.66 / run (5s), 37.98 / run (10s) |
| ray-3.2 | generation | 540p | 31.65 / run (5s), 94.95 / run (10s) |
| ray-3.2 | generation | 720p | 63.30 / run (5s), 189.90 / run (10s) |
| ray-3.2 | generation | 1080p | 253.20 / run (5s), 759.60 / run (10s) |
| ray-3.2 | edit | 360p | 22.79 / sec |
| ray-3.2 | edit | 540p | 30.38 / sec |
| ray-3.2 | edit | 720p | 45.58 / sec |
| ray-3.2 | edit | 1080p | 91.15 / sec |
| ray-3.2 | reframe | 360p | 6.33 / sec |
| ray-3.2 | reframe | 540p | 12.66 / sec |
| ray-3.2 | reframe | 720p | 25.32 / sec |
| ray-3.2 | reframe | 1080p | 75.96 / sec |
| ray-2 | generation | 540p | 120.27 / run (5s), 217.33 / run (9s) |
| ray-2 | generation | 720p | 215.22 / run (5s), 386.13 / run (9s) |
| ray-2 | generation | 1080p | 478.97 / run (5s), 865.10 / run (9s) |
| ray-2 | generation | 4K | 1922.21 / run (5s), 3460.40 / run (9s) |
| ray-flash-2 | generation | 540p | 42.20 / run (5s), 75.96 / run (9s) |
| ray-flash-2 | generation | 720p | 71.74 / run (5s), 128.71 / run (9s) |
| ray-flash-2 | generation | 1080p | 166.69 / run (5s), 299.62 / run (9s) |
| ray-flash-2 | generation | 4K | 660.43 / run (5s), 1192.15 / run (9s) |
| ray-1-6 | generation | — | 105.50 / run |

**Luma Ray 3.2** Image to Video and Extend Video always bill the **5s** price. Legacy Image to Video uses **5s** or **9s** from **ray-2** / **ray-flash-2** rows.

### Image

| Model | task | Credits |
| :- | :- | :- |
| photon-flash-1 | — | 0.57 / run |
| photon-1 | — | 2.19 / run |
| uni-1 | generation | 8.52 / run + 0.63 / ref image (≤ 9) |
| uni-1 | edit | 9.16 / run + 0.63 / ref image (≤ 8) |
| uni-1-max | generation | 21.10 / run + 0.63 / ref image (≤ 9) |
| uni-1-max | edit | 21.73 / run + 0.63 / ref image (≤ 8) |

Reference-image surcharge uses USD rounded to 4 decimals before converting to credits.

## Meshy

| Node | Options | Credits |
| :- | :- | :- |
| Meshy: Text to Model | — | 241.4 / run |
| Meshy: Refine Draft Model | 2K, 4K texture | 120.7 / run |
| Meshy: Refine Draft Model | 8K texture | 181.0 / run |
| Meshy: Image to Model | No texture | 241.4 / run |
| Meshy: Image to Model | Texture (2K, 4K) | 362.1 / run |
| Meshy: Image to Model | Texture (8K) | 422.4 / run |
| Meshy: Multi-Image to Model | No texture | 241.4 / run |
| Meshy: Multi-Image to Model | Texture (2K, 4K) | 362.1 / run |
| Meshy: Multi-Image to Model | Texture (8K) | 422.4 / run |
| Meshy: Rig Model | — | 60.35 / run |
| Meshy: Animate Model | — | 36.21 / run |
| Meshy: Texture Model | 2K, 4K texture | 120.7 / run |
| Meshy: Texture Model | 8K texture | 181.0 / run |
| Meshy: Texture Multi-View | 2K, 4K texture | 120.7 / run |
| Meshy: Texture Multi-View | 8K texture | 181.0 / run |

Ultra Mode (available on Meshy 7 and `latest` models) adds 60.3 credits: Text to Model 301.7 / run, Image to Model 422.4 / run (2K, 4K texture) or 482.8 / run (8K texture).

**Meshy: Text to Model** creates a draft mesh; run **Meshy: Refine Draft Model** on the returned `meshy_task_id` to texture it. **Meshy: Image to Model** and **Meshy: Multi-Image to Model** can texture in one step when `should_texture` is enabled.

## Meta

| Node | Credits |
| :- | :- |
| Meta Muse Image Text to Image | 3.017 / image |
| Meta Muse Image Edit | 3.017 / image |

## Minimax

| Node | model | resolution | Credits |
| :- | :- | :- | :- |
| MiniMax Text to Video | T2V-01, T2V-01-Director | — | 90.73 / run |
| MiniMax Image to Video | I2V-01, I2V-01-Director, I2V-01-live | — | 90.73 / run |
| MiniMax Hailuo 02 Video | MiniMax-Hailuo-02 | 768P | 59.08 / run (6s), 118.16 / run (10s) |
| MiniMax Hailuo 02 Video | MiniMax-Hailuo-02 | 1080P | 103.39 / run (6s) |
| MiniMax H3 Text to Video | MiniMax H3 | 768P | 27.16 / sec |
| MiniMax H3 Text to Video | MiniMax H3 | 2K | 39.22 / sec |
| MiniMax H3 First-Last-Frame to Video | MiniMax H3 | 768P | 27.16 / sec |
| MiniMax H3 First-Last-Frame to Video | MiniMax H3 | 2K | 39.22 / sec |
| MiniMax H3 Reference to Video | MiniMax H3 | 768P | 27.16 / sec, plus 12.07 / image over 5 |
| MiniMax H3 Reference to Video | MiniMax H3 | 2K | 39.22 / sec, plus 12.07 / image over 5 |
| MiniMax H3 Context IR | MiniMax H3 | — | 4.22 / run (text only), 10.55 / run (with first/last frame), 12.66–23.21 / run (with reference media) |
| MiniMax H3 Regenerate to 2K | MiniMax H3 | — | 15.09 / sec |
| MiniMax H3 Text to Video | MiniMax H3 Max | 480P | 15.09 / sec |
| MiniMax H3 Text to Video | MiniMax H3 Max | 768P | 24.14 / sec |
| MiniMax H3 First-Last-Frame to Video | MiniMax H3 Max | 480P | 15.09 / sec |
| MiniMax H3 First-Last-Frame to Video | MiniMax H3 Max | 768P | 24.14 / sec |
| MiniMax H3 Reference to Video | MiniMax H3 Max | 480P | 15.09 / sec |
| MiniMax H3 Reference to Video | MiniMax H3 Max | 768P | 24.14 / sec |

**MiniMax Hailuo 02 Video** only supports **6s** at 1080P.

**MiniMax H3** bills per second (4–15s duration). **MiniMax H3 Reference to Video** adds 12.07 credits per reference image beyond 5, and bills reference videos at 27.16 credits/sec (768P) or 39.22 credits/sec (2K) (2s per video, up to 15s total, approximate). **MiniMax H3 Context IR** prices depend on attached media: text only, first/last frame, or reference media (approximate).

**MiniMax H3 Max** bills per second (5–15s duration) at the rates above.

**MiniMax H3 Max Reference to Video** billing has two parts: the output video is billed per second at the rates above, and reference inputs are billed as tokens. Tokens from every image, video, and audio clip in the request are pooled and share one free allowance:

> Reference charge (credits) = max(0, total reference tokens - 4,096) × 6.03 / 1,000

The first **4,096 tokens per request are free**; beyond that, each 1K tokens costs **6.03 credits**.

| Reference input | Tokens |
| :- | :- |
| Image | (width × height) / 1024 |
| Reference video at 480P output | 2,886 / sec |
| Reference video at 768P output | 7,459 / sec |
| Audio | 80 / sec |

A reference video is tokenized at the **output** resolution, not at the source clip's resolution: for a given output resolution, a 480P and a 768P clip of the same length cost the same. Images and audio are resolution-independent.

Worked examples, each assuming no other reference input consumes the free allowance:

* A 1024 × 1024 image is 1,024 tokens: the first 4 images are free, then 6.03 credits each.
* A 2048 × 2048 image is 4,096 tokens: the first image is free, then 24.14 credits each.
* Generating a 5 s 768P video conditioned on two 1024 × 1024 images and one 5 s reference video: output 24.14 × 5 = 120.7 credits; reference tokens 2 × 1,024 + 37,296 = 39,344, minus the 4,096 allowance = 35,248 billable → 35.248 × 6.03 ≈ 212.6 credits. Total ≈ 333.3 credits.

## OpenAI

DALL·E and Sora use fixed per-image or per-second rates. **OpenAI GPT Image 2** and **OpenAI ChatGPT** bill from API token usage.

### Image: DALL·E

<Warning>
  **Deprecated**: The **OpenAI DALL·E 2** and **OpenAI DALL·E 3** nodes have been retired and removed from ComfyUI. Use **GPT Image** instead. The pricing below is retained for reference only.
</Warning>

**DALL·E 2** supports **256×256**, **512×512**, or **1024×1024**; total credits = **(credits / image) × `n`**. **DALL·E 3** adds **`quality`** (`standard` / `hd`) and supports **1024×1024** or portrait **1024×1792** / **1792×1024**.

| Node | quality | size | Credits |
| :- | :- | :- | :- |
| OpenAI DALL·E 2 | — | 256x256 | 3.38 / image |
| | — | 512x512 | 3.80 / image |
| | — | 1024x1024 | 4.22 / image |
| OpenAI DALL·E 3 | standard | 1024x1024 | 8.44 / run |
| | standard | 1024x1792, 1792x1024 | 16.88 / run |
| | hd | 1024x1024 | 16.88 / run |
| | hd | 1024x1792, 1792x1024 | 25.32 / run |

### Image: GPT Image

Billed from API token usage after generation. Approximate badge by `quality` (`low` / `medium` / `high`); actual cost follows token counts below.

| model | token type | Credits / 1M |
| :- | :- | :- |
| gpt-image-1 | input | 2110 |
| gpt-image-1 | output (image) | 8440 |
| gpt-image-1.5 | input | 1688 |
| gpt-image-1.5 | output (image) | 6752 |
| gpt-image-2 | input | 2025.6 |
| gpt-image-2 | output (image) | 7600 |

The deprecated **OpenAI GPT Image 2** node (older implementation) uses the same models and rates.

The **GPT Image 2.5** models (`gpt-image-2.5-flare`, `gpt-image-2.5-sunburst`) share the same rates and add `xhigh` and `max` quality tiers.

| model | token type | Credits / 1M |
| :- | :- | :- |
| gpt-image-2.5-flare | input (image) | 2413.84 |
| gpt-image-2.5-flare | input (text) | 1508.65 |
| gpt-image-2.5-flare | output (image) | 9051.9 |
| gpt-image-2.5-sunburst | input (image) | 2413.84 |
| gpt-image-2.5-sunburst | input (text) | 1508.65 |
| gpt-image-2.5-sunburst | output (image) | 9051.9 |

Output token counts scale with size and quality (for example, 1024x1024 at `low` is about 196 output tokens, roughly 1.86 credits). Each 1024x1024 reference image adds about 2.47 credits of image input, and prompt text is billed at the text-input rate. Multiplying images (`n`) scales the total.

### Chat

Token-based billing. Badge rates are **per 1K tokens**; table is **per 1M tokens**.

| Model | Input credits / 1M | Output credits / 1M |
| :- | -: | :- |
| gpt-6-astra | 3017.3 | 15086.5 |
| gpt-6-sol | 603.46 | 3017.3 |
| gpt-6-luna | 30.17 | 150.87 |
| gpt-5.6-sol, gpt-5.6-sol-pro | 1055 | 6330 |
| gpt-5.6-terra, gpt-5.6-terra-pro | 527.5 | 3165 |
| gpt-5.6-luna, gpt-5.6-luna-pro | 211 | 1266 |
| gpt-5.5 | 1055 | 6330 |
| gpt-5.5-pro | 6330 | 37980 |
| gpt-5 | 263.75 | 2110 |
| gpt-5-mini | 52.75 | 422 |
| gpt-5-nano | 10.55 | 84.4 |
| gpt-4.1 | 422 | 1688 |
| gpt-4.1-mini | 84.4 | 337.6 |
| gpt-4.1-nano | 21.1 | 84.4 |
| o3 | 2110 | 8440 |
| o4-mini | 232.1 | 928.4 |
| o1 | 3165 | 12660 |
| o1-pro | 31650 | 126600 |

Optional images and files add input tokens at the same model rates.

### Video: Sora

<Warning>
  **Deprecated**: The **OpenAI Sora - Video** node has been retired and removed from ComfyUI. The pricing below is retained for reference only.
</Warning>

Total credits = **(credits / sec) × `duration`** (`duration` is 4, 8, or 12).

| model | size | Credits |
| :- | :- | :- |
| sora-2 | 720x1280, 1280x720 | 21.10 / sec |
| sora-2-pro | 720x1280, 1280x720 | 63.30 / sec |
| sora-2-pro | 1024x1792, 1792x1024 | 105.50 / sec |

`sora-2` only supports 720x1280 and 1280x720.

## OpenRouter

Badge rates are **per 1K tokens**; table is **per 1M tokens**. Final charges follow API usage.

### Chat: OpenRouter LLM

| Model | Input credits / 1M | Output credits / 1M |
| :- | :- | :- |
| anthropic/claude-opus-5 | 1508.65 | 7543.25 |
| anthropic/claude-opus-4.8 | 1508.65 | 7543.25 |
| anthropic/claude-opus-4.7 | 1508.65 | 7543.25 |
| anthropic/claude-fable-5 | 3017.30 | 15086.50 |
| anthropic/claude-sonnet-5 | 603.46 | 3017.30 |
| anthropic/claude-haiku-4.5 | 301.73 | 1508.65 |
| openai/gpt-5.6-sol-pro | 1508.65 | 9051.90 |
| openai/gpt-5.6-sol | 1508.65 | 9051.90 |
| openai/gpt-5.6-terra-pro | 754.33 | 4525.95 |
| openai/gpt-5.6-terra | 754.33 | 4525.95 |
| openai/gpt-5.6-luna-pro | 301.73 | 1810.38 |
| openai/gpt-5.6-luna | 301.73 | 1810.38 |
| openai/gpt-5.5-pro | 9051.90 | 54331.40 |
| openai/gpt-5.5 | 1508.65 | 9051.90 |
| google/gemini-3.5-flash | 452.60 | 2715.57 |
| x-ai/grok-4.5 | 603.46 | 1810.38 |
| x-ai/grok-4.20 | 377.16 | 754.33 |
| x-ai/grok-4.3 | 377.16 | 754.33 |
| deepseek/deepseek-v4-pro | 131.25 | 262.51 |
| deepseek/deepseek-v4-flash | 33.79 | 67.59 |
| deepseek/deepseek-v3.2 | 76.04 | 114.05 |
| qwen/qwen3.6-max-preview | 313.80 | 1882.80 |
| qwen/qwen3.6-plus | 98.06 | 588.37 |
| qwen/qwen3.6-flash | 56.57 | 339.45 |
| mistralai/mistral-large-2512 | 150.87 | 452.60 |
| mistralai/mistral-medium-3-5 | 452.60 | 2262.98 |
| z-ai/glm-4.6 | 129.74 | 525.00 |
| z-ai/glm-5 | 181.04 | 579.32 |
| moonshotai/kimi-k3 | 905.19 | 4525.95 |
| moonshotai/kimi-k2.6 | 220.26 | 1053.04 |
| moonshotai/kimi-k2-thinking | 181.04 | 754.33 |
| perplexity/sonar-pro | 905.19 | 4525.95 |
| perplexity/sonar-reasoning-pro | 603.46 | 2413.84 |
| perplexity/sonar-deep-research | 603.46 | 2413.84 |

### Image: OpenRouter Image

Token-based billing. The badge estimates cost from the prompt length, reference count, and output size; the table lists the per-1M-token credit rates used by that estimate.

| Model | Prompt credits / 1M | Reference image credits / 1M | Output image credits / 1M |
| :- | -: | -: | -: |
| microsoft/mai-image-2.6 | 1508.65 | 2413.84 | 11465.70 |
| microsoft/mai-image-2.6-flash | 528.03 | 754.33 | 5732.87 |

### Image notes

* `mai-image-2.6` and `mai-image-2.6-flash` bill from API token usage: the prompt, each reference image, and the generated image are tokenized, then charged at the rates above.
* Reference images are downscaled to at most 2048 x 2048 (about 4,096 tokens each) before upload.

## Pixverse

Model **v3.5** (fixed in the API; not selectable).

**1080p** is limited to **5s** with **normal** motion. **8s** clips only support **normal** motion (fast is coerced to normal).

| model | duration | motion\_mode | quality | Credits |
| :- | :- | :- | :- | :- |
| v3.5 | 5s | fast | 360p, 540p | 189.9 / run |
| | 5s | fast | 720p | 253.2 / run |
| | 5s | normal | 360p, 540p | 94.95 / run |
| | 5s | normal | 720p | 126.6 / run |
| | 5s | normal | 1080p | 253.2 / run |
| | 8s | normal | 360p, 540p | 189.9 / run |
| | 8s | normal | 720p | 253.2 / run |

#### PixVerse V6

PixVerse V6 nodes generate videos from 1 to 15 seconds with optional native audio. Total credits = **(credits / sec) × `duration`**.

| quality | Audio off | Audio on |
| :- | :- | :- |
| 360p | 15.09 | 21.12 |
| 540p | 21.12 | 27.16 |
| 720p | 27.16 | 36.21 |
| 1080p | 54.31 | 69.40 |

**PixVerse V6 Fusion** bills 2x the per-second rate for each second of reference video, instead of the output duration.

## Quiver

### Image

**arrow-1.1** models charge a fixed amount per run:

<Warning>
  **Deprecated**: Quiver is retiring the Arrow 1-series models on **October 16, 2026**. **Text to SVG** and **Image to SVG** may stop working with `arrow-1.1`, `arrow-1.1-max`, and `arrow-preview` after that date; use the Arrow 2 models instead.
</Warning>

| model | Node | Credits / run |
| :- | :- | :- |
| arrow-1.1 | Quiver Text to SVG | 60.35 |
| arrow-1.1 | Quiver Image to SVG | 45.26 |
| arrow-1.1-max | Quiver Text to SVG | 75.43 |
| arrow-1.1-max | Quiver Image to SVG | 60.35 |
| arrow-preview | Quiver Text to SVG | 90.52 |
| arrow-preview | Quiver Image to SVG | 90.52 |

**arrow-2** and **arrow-2-telos** bill by the tokens a request consumes:

| model | Input credits / 1M tokens | Output credits / 1M tokens |
| :- | -: | -: |
| arrow-2 | 1206.92 | 6034.6 |
| arrow-2-telos | 1810.38 | 9051.9 |

Credits = (input tokens × input rate + output tokens × output rate) ÷ 1,000,000. Input tokens cover the prompt text and, for **Image to SVG**, the input image; output tokens cover the generated SVG. Both nodes bill the same rates. The node badge estimates a cost range from typical token counts; the final charge follows measured usage.

`reasoning_effort` changes how many tokens the model spends before drawing: higher levels reason for longer, so they use more output tokens and cost more.

## Qwen

### Image

Per image. Output is billed per generated image; Qwen Image 3 Edit also bills **0.91 credits** per input reference image (up to 3). Nodes with **`n`** bill **(credits / image) × `n`**.

| model | Node | Resolution | Input credits / image | Output credits / image |
| :- | :- | :- | :- | :- |
| qwen-image-3.0 | Qwen Image 3 Text to Image | 1K, 2K | — | 9.05 (× `n`) |
| qwen-image-3.0-pro | Qwen Image 3 Text to Image | 1K | — | 12.07 (× `n`) |
| qwen-image-3.0-pro | Qwen Image 3 Text to Image | 2K | — | 22.63 (× `n`) |
| qwen-image-3.0 | Qwen Image 3 Edit | 1K, 2K | 0.91 | 9.05 (× `n`) |
| qwen-image-3.0-pro | Qwen Image 3 Edit | 1K | 0.91 | 12.07 (× `n`) |
| qwen-image-3.0-pro | Qwen Image 3 Edit | 2K | 0.91 | 22.63 (× `n`) |

`qwen-image-3.0-pro` uses resolution-based output billing: **1K** (≤2.25 MP) is **12.07 credits**, **2K** (>2.25 MP) is **22.63 credits**. With the Edit node's "auto" or "match input" size modes, Pro output pricing shows as a range (12.07–22.63); a custom size resolves to the fixed rate for that area.

## Recraft

### Image

Flat per-run pricing unless noted. Nodes with **`n`** bill **(credits / image) × `n`**. v3 generation nodes send model **recraftv3** in the API request (not selectable in the node). The `recraftv4_styles` models always require a `style_id` or style reference images.

| model | Node | Credits |
| :- | :- | :- |
| recraftv4\_pro | Recraft V4 Text to Image | 75.43 / image (× `n`) |
| recraftv4\_pro | Recraft V4 Text to Vector | 90.52 / image (× `n`) |
| recraftv4\_1, recraftv4\_1\_utility | Recraft V4 Text to Image | 10.56 / image (× `n`) |
| recraftv4\_1\_flash | Recraft V4 Text to Image | 2.11 / image (× `n`) |
| recraftv4\_1\_pro, recraftv4\_1\_utility\_pro | Recraft V4 Text to Image | 63.36 / image (× `n`) |
| recraftv4 | Recraft V4 Text to Image | 12.07 / image (× `n`) |
| recraftv4 | Recraft V4 Text to Vector | 24.14 / image (× `n`) |
| recraftv4\_1\_vector, recraftv4\_1\_utility\_vector | Recraft V4 Text to Vector | 24.14 / image (× `n`) |
| recraftv4\_1\_pro\_vector, recraftv4\_1\_utility\_pro\_vector | Recraft V4 Text to Vector | 90.52 / image (× `n`) |
| recraftv4\_styles | Recraft V4 Text to Image | 10.56 / image (× `n`) |
| recraftv4\_styles\_pro | Recraft V4 Text to Image | 30.17 / image (× `n`) |
| recraftv4\_styles\_vector | Recraft V4 Text to Vector | 15.09 / image (× `n`) |
| recraftv4\_styles\_pro\_vector | Recraft V4 Text to Vector | 36.21 / image (× `n`) |
| recraftv3 | Recraft Text to Image, Recraft Image to Image, Recraft Image Inpainting | 12.07 / image (× `n`) |
| recraftv3 | Recraft Text to Vector | 24.14 / image (× `n`) |
| — | Recraft Create Style | 1.51 / run |
| — | Recraft V4 Create Style | 1.51 / run |
| — | Recraft Replace Background | 12.07 / run |
| — | Recraft Vectorize Image, Recraft Remove Background | 3.02 / run |
| — | Recraft Crisp Upscale Image | 1.21 / run |
| — | Recraft Creative Upscale Image | 75.43 / run |

## Reve

<Warning>
  **Deprecated**: Reve's public API is winding down on **August 14, 2026**. The Reve Image Create, Reve Image Edit, and Reve Image Remix nodes may stop working after that date.
</Warning>

### Image

Credits below are approximate **base** rates (`test_time_scaling=1`, upscale off). **`test_time_scaling` > 1**, **upscale**, and **remove background** can increase actual charges from the API.

| model | Node | upscale | Credits |
| :- | :- | :- | :- |
| reve-create\@20250915 | Reve Image Create | off | 7.24 / run |
| | | 2x | 9.64 / run |
| | | 3x | 12.47 / run |
| | | 4x | 16.08 / run |
| reve-edit\@20250915, reve-remix\@20250915 | Reve Image Edit, Reve Image Remix | off | 12.07 / run |
| | | 2x | 14.47 / run |
| | | 3x | 17.28 / run |
| | | 4x | 20.91 / run |
| reve-edit-fast\@20251030 | Reve Image Edit | — | 2.11 / run |
| reve-remix-fast\@20251030 | Reve Image Remix | — | 2.11 / run |

Fast edit/remix models use a flat base rate; upscale does not change the displayed estimate.

## Rodin 3D

| generation | Node | mode | addon\_highpack | Credits |
| :- | :- | :- | :- | :- |
| Gen-2.5 | Rodin 3D Gen-2.5 - Image to 3D, Rodin 3D Gen-2.5 - Text to 3D | Regular, Fast | off | 158.25 / run |
| Gen-2.5 | | Extreme-High | off | 316.5 / run |
| Gen-2.5 | | any | on | +168.8 / run |
| Gen-2 | Rodin 3D Generate - Regular Generate, Detail Generate, Smooth Generate, Sketch Generate, Gen-2 Generate | — | — | 84.4 / run |

**HighPack** (`addon_highpack`) adds **168.8** credits on top of the Gen-2.5 base rate for that mode.

## Runway

### Video

Gen4 Turbo: **5s** or **10s**. Total credits = **(credits / sec) × `duration`**.

<Warning>
  **End of life (EOL)**: `gen3a_turbo` and the Runway First-Last-Frame node reached end of life on **July 30, 2026**. Use Gen4 Turbo for image-to-video instead.
</Warning>

| model | Credits | Status |
| :- | :- | :- |
| gen4\_turbo | 15.09 / sec | Active |
| gen3a\_turbo | 15.09 / sec | EOL (July 30, 2026) |
| aleph2 | 84.48 / sec | Active |

**Runway Aleph2 Keyframe** and **Runway Aleph2 Prompt Image** are helper nodes with no separate charge; cost is on **Runway Aleph2 Video to Video**.

### Image

| model | Credits |
| :- | :- |
| gen4\_image | 24.14 / run |

## Sonilo

Text to Music: total credits = **(credits / sec) × `duration`** (1–360 seconds).

| Node | Credits |
| :- | :- |
| Sonilo Video to Music | 1.9 / sec |
| Sonilo Text to Music | 0.5275 / sec |

## sync.so

Total credits = **(credits / sec) × `duration`**.

| Node | Credits |
| :- | :- |
| sync.so Lip Sync | \~40.13 / sec |
| sync.so Talking Image | \~40.13 / sec |

## Tencent

### Image

**HY Image 3.5 Preview** bills one rate per generated image. `1K` and `2K` output, and `custom` sizes up to 4.19 megapixels, cost the base rate. `4K` output is rendered at 2K and then upscaled by the model, and costs more, as does a `custom` size above 4.19 megapixels.

| model | Node | Resolution | Input credits / image | Output credits / image |
| :- | :- | :- | :- | :- |
| hy-image-3.5-preview | Tencent HY Image: Text to Image | 1K, 2K, custom ≤ 4.19 MP | — | 7.24 |
| hy-image-3.5-preview | Tencent HY Image: Text to Image | 4K, custom > 4.19 MP | — | 9.66 |
| hy-image-3.5-preview | Tencent HY Image: Edit | 1K, 2K, custom ≤ 4.19 MP | — | 7.24 |
| hy-image-3.5-preview | Tencent HY Image: Edit | 4K, custom > 4.19 MP | — | 9.66 |

### 3D: Generation

**`3.1`** uses the same rates as **`3.0`** but does not support LowPoly.

| model | generate\_type | Credits |
| :- | :- | :- |
| 3.0 | Geometry | 63.3 / run |
| | Normal | 105.5 / run |
| | LowPoly | 126.6 / run |

Add-ons stack on the base rate:

| model | option | Credits |
| :- | :- | :- |
| 3.0 | PBR (`pbr` on) | +42.2 / run |
| | Custom `face_count` (≠ 500000) | +42.2 / run |
| | Multiview images connected | +42.2 / run |

Multiview applies only to **Hunyuan3D: Image(s) to Model** when `image_left`, `image_right`, or `image_back` is connected.

### 3D: Post-processing

| Node | Credits |
| :- | :- |
| Hunyuan3D: Model to UV | 42.2 / run |
| Hunyuan3D: Smart Topology | 211 / run |

**Hunyuan3D: 3D Texture Edit** and **Hunyuan3D: 3D Part** each cost **126.6 / run**.

## Topaz

### Image

**Topaz Image Enhance** (current node) charges per 8 megapixels of output (`approximate`):

| model | Credits |
| :- | :- |
| Reimagine | 67.52 / 8MP |
| Bloom 2 | 96.55 / 8MP |
| Wonder 3.5 | 24.14 / 8MP |

**Topaz Image Enhance (Legacy)** is deprecated. It has no fixed pre-run estimate; charge comes from the API estimate at poll time (API credits × 0.08 USD). Typical charges by input resolution:

| model | input resolution | Credits |
| :- | :- | :- |
| Reimagine | 720p (1280×720) | 13.93 / run |
| | 1080p (1920×1080) | 27.85 / run |
| | 1440p (2560×1440) | 27.85 / run |
| | 4K (3840×2160) | 69.63 / run |

### Video

Approximate rates shown in the node are **per source frame** (not per second). Total credits ≈ **(credits / src frame) × input frame count**. With **apo-8** interpolation enabled, add **\~0.14** (1080p) or **\~0.28** (4K) per source frame to the upscale rate.

| upscaler\_model | upscaler\_resolution | Credits / src frame |
| :- | :- | :- |
| Starlight (Astra) Fast | FullHD (1080p) | \~0.43 |
| | 4K (2160p) | \~0.85 |
| Starlight Precise 2.5 | FullHD (1080p) | \~0.70 |
| | 4K (2160p) | \~1.54 |
| Astra 2 | FullHD (1080p) | \~1.72 |
| | 4K (2160p) | \~2.85 |
| Starlight (Astra) Creative | FullHD (1080p) | \~2.25 |
| | 4K (2160p) | \~3.99 |

Upscaler **Disabled** with **apo-8** interpolation only: the UI shows **Interpolation only**; charge comes from the API estimate at poll time.

**Topaz Video Enhance (Legacy)** is deprecated. It has no fixed pre-run estimate; charge comes from the API estimate at poll time.

## Tripo

Legacy generation prices are approximate. The node converts internal Tripo credits to USD at **credits × 0.01**.

<Warning>
  **Retired**: the `v1.4-20240625` model version has been removed from the Tripo node's `TripoModelVersion` enum in ComfyUI v0.34.0+ and can no longer be selected. Its pricing is no longer documented; migrate existing workflows to `v2.5-20250123` or `v3.x`. The **Tripo: Refine Draft model** node, which only worked with v1.4 drafts, has also been removed.

  **Legacy**: **Tripo: Text to Model (Legacy)**, **Tripo: Image to Model (Legacy)**, and **Tripo: Texture model (Legacy)** are deprecated in ComfyUI v0.35.1+. They keep their exact schemas, so saved workflows keep running, but new workflows should use the current **Tripo: Text to Model**, **Tripo: Image to Model**, and **Tripo: Texture model** nodes. The legacy generation prices below cover both node versions.
</Warning>

### Generation: v2.0 / v2.5

`model_version` **v2.5-20250123**. The **v2.0-20240919** version has been retired and is no longer offered in the enum. `texture` or `pbr` counts as textured. On v2.5, **`geometry_quality: detailed` does not change the price**.

**Tripo: Text to Model**

| texture | texture\_quality | Credits |
| :- | :- | :- |
| off | standard | 21.1 / run |
| on | standard | 42.2 / run |
| on | detailed | 63.3 / run |

**Tripo: Image to Model** and **Tripo: Multiview to Model**

| texture | texture\_quality | Credits |
| :- | :- | :- |
| off | standard | 42.2 / run |
| on | standard | 63.3 / run |
| on | detailed | 84.4 / run |

| option | Credits |
| :- | :- |
| `quad` | +10.55 / run |

`quad` applies to **Tripo: Text to Model** and **Tripo: Image to Model** only.

`smart_low_poly` adds **+21.1 / run** on every generation node in this section and caps `face_limit` at 20,000 (10,000 with `quad`).

### Generation: v3.0 / v3.1

Same nodes with `model_version` **v3.0-20250812** or **v3.1-20260211**. **`geometry_quality: detailed`** adds **+42.2 / run** on top of the texture rows below.

**Tripo: Text to Model**

| texture | texture\_quality | geometry\_quality | Credits |
| :- | :- | :- | :- |
| off | standard | standard | 21.1 / run |
| off | standard | detailed | 63.3 / run |
| on | standard | standard | 42.2 / run |
| on | detailed | standard | 63.3 / run |
| on | standard | detailed | 84.4 / run |
| on | detailed | detailed | 105.5 / run |
| on | extreme | standard | 84.4 / run |
| on | extreme | detailed | 126.6 / run |

**Tripo: Image to Model** and **Tripo: Multiview to Model**

| texture | texture\_quality | geometry\_quality | Credits |
| :- | :- | :- | :- |
| off | standard | standard | 42.2 / run |
| off | standard | detailed | 84.4 / run |
| on | standard | standard | 63.3 / run |
| on | detailed | standard | 84.4 / run |
| on | standard | detailed | 105.5 / run |
| on | detailed | detailed | 126.6 / run |
| on | extreme | standard | 105.5 / run |
| on | extreme | detailed | 147.7 / run |

`quad` add-on (+10.55 / run) applies to **Tripo: Text to Model** and **Tripo: Image to Model** only. `smart_low_poly` adds **+21.1 / run** on every generation node in this section and caps `face_limit` at 20,000 (10,000 with `quad`).

### Generation: P1

| model | output\_mode | texture\_quality | Credits (Text) | Credits (Image / Multiview) |
| :- | :- | :- | :- | :- |
| P1-20260311 | Geometry only | — | 63.3 / run | 84.4 / run |
| | Textured | standard | 84.4 / run | 105.5 / run |
| | Textured | detailed | 105.5 / run | 126.6 / run |

### Post-processing

| Node | Credits |
| :- | :- |
| Tripo: Texture model | 21.1 / run (standard), 42.2 / run (detailed), 63.3 / run (extreme) |
| Tripo: Rig model | 52.75 / run |
| Tripo: Rig Check | Free |
| Tripo: Retarget rigged model | 21.1 / run |
| Tripo: Segment Model | 84.4 / run |
| Tripo: Smart Segment | 116.05 / run (from a model), 179.35 / run (from an image, includes generation) |
| Tripo: Complete Mesh Parts | 105.5 / run |
| Tripo: Retopology | 63.3 / run |
| Tripo: Convert model | 10.55 / run (basic), 21.1 / run (advanced options) |
| Tripo: Import Model | Free |

**Tripo: Convert model** charges **21.1 / run** when `quad` is on, `face_limit` is set, `texture_size` ≠ 4096, `texture_format` ≠ JPEG, `flatten_bottom` or `pivot_to_center_bottom` is on, `flatten_bottom_threshold` ≠ 0, or `scale_factor` ≠ 1; otherwise **10.55 / run**.

### Multiview

| Node | Credits |
| :- | :- |
| Tripo: Image to Multiview | 21.1 / run |
| Tripo: Edit Multiview | 10.55 / run per edited view |

The v3 API versions of **Tripo: Image to Multiview** and **Tripo: Edit Multiview** bill the same rates.

### Generation: P2

The P2 nodes (**Tripo P2: Text to Model**, **Tripo P2: Image to Model**, **Tripo P2: Multiview to Model**) share one rate by `texture`. Prices are approximate.

| texture | Credits |
| :- | :- |
| none | 211 / run |
| standard | 232.1 / run |
| detailed | 253.2 / run |
| extreme | 274.3 / run |

## Pruna

Pruna P-Video-2 bills per second of generated video. Total credits = **(credits / sec) × `duration`** (`duration` is 1-20 seconds or `auto`; when audio is connected, the video follows the audio length). Prices are approximate.

| Node | resolution | draft | Credits / sec |
| :- | :- | :- | :- |
| Pruna P-Video-2 Text to Video | 720p | off | 7.54 |
| | 720p | on | 4.53 |
| | 1080p | off | 15.09 |
| | 1080p | on | 9.05 |
| Pruna P-Video-2 Image to Video | 720p | off | 7.54 |
| | 720p | on | 4.53 |
| | 1080p | off | 15.09 |
| | 1080p | on | 9.05 |

## Vidu

### Video: Q3

Total credits = **(credits / sec) × `duration`**.

| model | resolution | Credits / sec |
| :- | :- | :- |
| viduq3-turbo | 720p | 12.66 |
| | 1080p | 16.88 |
| viduq3-pro | 720p | 31.65 |
| | 1080p | 33.76 |
| | 2K | 42.2 |

**2K** is only on **Vidu Q3 Image-to-Video Generation** with **viduq3-pro**.

### Video: Q2

**Linear nodes** (all except Multi-Frame): **base + (credits / sec) × (`duration` − 1)**.

**Multi-Frame:** **`frames` × base + (credits / sec) × sum of segment durations** (uses the Extension / Multi-Frame base column).

**Reference** (`viduq2`): add **+15.825 / run** when `audio` is on.

| model | resolution | Credits / sec after 1s | Base (1s) linear nodes | Base (1s) Extension / Multi-Frame |
| :- | :- | :- | :- | :- |
| viduq2 | 720p | 5.275 | 15.825 | — |
| | 1080p | 10.55 | 21.1 | — |
| viduq2-pro-fast | 720p | 2.11 | 8.44 | — |
| | 1080p | 4.22 | 16.88 | — |
| viduq2-pro | 720p | 10.55 | 15.825 | 31.65 |
| | 1080p | 15.825 | 58.025 | 63.3 |
| viduq2-turbo | 1080p | 10.55 | 36.925 | 42.2 |
| | 720p | 5.275 (Ext/MF); 10.55 (I2V/Start-End after 2s) | — | 15.825 |

**viduq2** linear bases above are for **Text-to-Video**. **Reference-to-Video** uses the same per-second rates but base **26.375** (720p) or **79.125** (1080p).

**viduq2-pro-fast**, **viduq2-pro**, and **viduq2-turbo** linear bases are for **Image-to-Video** and **Start/End Frame-to-Video**. **viduq2-turbo** at **720p** on those nodes: **8.44** at 1s (I2V), **10.55** at 2s (flat on I2V; Start/End minimum duration is 2s), then **+10.55 / sec** after 2s. The **5.275 / sec** rate applies only to Extension and Multi-Frame, not I2V or Start/End.

### Video: Q1

Fixed **5s** at **1080p**.

| model | Credits |
| :- | :- |
| viduq1 | 84.4 / run |

## Wan

<Note>
  **Limited-time offer**: Wan 3.0 is 30% off through September 30, 2026. The prices in the table are the pre-discount prices.
</Note>

| model | resolution | Credits |
| :- | :- | :- |
| wan2.5-t2i-preview, wan2.5-i2i-preview | — | 6.33 / run |
| wan2.7-t2v, wan2.7-i2v | 720P | 21.1 / sec |
| | 1080P | 31.65 / sec |
| wan2.7-i2v (continuation) | 720P | 21.1 / sec (range) |
| | 1080P | 31.65 / sec (range) |
| wan2.7-videoedit | 720P | 21.1 / sec (in + out) |
| | 1080P | 31.65 / sec (in + out) |
| wan2.7-r2v | 720P | 21.1 / sec (range) |
| | 1080P | 31.65 / sec (range) |
| wan3.0-video | 480P | 15.09 / sec (range) |
| | 720P | 30.17 / sec (range) |
| | 1080P | 60.35 / sec (range) |
| wan3.0-video-prime | 480P | 20.52 / sec (range) |
| | 720P | 42.24 / sec (range) |
| | 1080P | 84.48 / sec (range) |
| wan2.5-t2v-preview, wan2.5-i2v-preview | 480p | 10.55 / sec |
| wan2.5-t2v-preview, wan2.5-i2v-preview, wan2.6-t2v, wan2.6-i2v | 720p | 21.1 / sec |
| wan2.5-t2v-preview, wan2.5-i2v-preview, wan2.6-t2v, wan2.6-i2v | 1080p | 31.65 / sec |
| wan2.6-r2v | 720p | 21.1 / sec (range) |
| | 1080p | 31.65 / sec (range) |

## WaveSpeed

| model | resolution | Credits |
| :- | :- | :- |
| flashvsr | 720p | 2.532 / sec |
| | 1080p | 3.798 / sec |
| | 2K | 5.064 / sec |
| | 4K | 6.752 / sec |
| SeedVR2 | — | 2.11 / run |
| Ultimate | — | 12.66 / run |

## xAI

<Note>
  Video endpoints charge for moderated content.
</Note>

### Image

| model | resolution | task | Credits |
| :- | :- | :- | :- |
| grok-imagine-image-2.0 | 1K | generate | 12.66 (medium) / 8.44 (low) per output image |
| | 2K | generate | 16.88 (medium) / 12.66 (low) per output image |
| grok-imagine-image-quality | 1K | generate | 10.55 / output image |
| | 2K | generate | 14.77 / output image |
| grok-imagine-image-pro | — | generate | 14.77 / output image |
| grok-imagine-image | — | generate | 4.22 / output image |
| grok-imagine-image-2.0 | 1K | edit | 2.11 input + 12.66 (medium) / 8.44 (low) per output image |
| | 2K | edit | 2.11 input + 16.88 (medium) / 12.66 (low) per output image |
| grok-imagine-image-quality | 1K | edit | 2.11 input + 10.55 / output image |
| | 2K | edit | 2.11 input + 14.77 / output image |
| grok-imagine-image-pro | — | edit | 0.422 input + 14.77 / output image |
| grok-imagine-image | — | edit | 0.422–1.266 input + 4.22 / output image |

### Video

| model | resolution | Credits |
| :- | :- | :- |
| grok-imagine-video | 480p | 10.55 / sec output (+0.422 input image) |
| | 720p | 14.77 / sec output (+0.422 input image) |
| grok-imagine-video-1.5 | 480p | 24.14 / sec output (+3.02 input image) |
| | 720p | 42.24 / sec output (+3.02 input image) |
| | 1080p | 75.43 / sec output (+3.02 input image) |
| grok-imagine-video (edit) | — | 12.66 / sec (input + output video) |
| grok-imagine-video (reference) | 480p | 15.09 / sec output + 0.603 / ref image |
| | 720p | 21.12 / sec output + 0.603 / ref image |
| grok-imagine-video (extend) | — | 6.03–45.26 input + 15.09 × extension sec output / run |

## Cloud GPU

| gpu\_type | Credits |
| :- | :- |
| rtx\_pro\_6000 | 0.266 / sec |


# ComfyUI Depth Anything 3 Examples
Source: https://docs.comfy.org/tutorials/utility/depth-anything-3

Run Depth Anything 3 in ComfyUI for monocular and multi-view depth estimation, camera pose recovery, and 3D reconstruction from images and video.

# ComfyUI Depth Anything 3 Introduction

[Depth Anything 3 (DA3)](https://github.com/ByteDance-Seed/Depth-Anything-3), from ByteDance Seed, is a vision transformer that recovers spatially consistent geometry from arbitrary visual inputs, with or without known camera poses. A single plain DINO encoder and unified depth-ray representation let one model family cover monocular depth, multi-view depth, camera pose estimation, and 3D reconstruction.

Key capabilities:

* **Unified monocular & multi-view depth**: estimate depth from a single image or multiple views
* **Camera pose estimation**: recover camera positions from unordered image sets
* **3D reconstruction** from multi-view inputs
* **Video depth estimation**: per-frame depth sequences for video inputs
* **Multiple model variants**: Small, Base, Mono/Metric Large

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<Tip>
  ComfyUI now natively supports Depth Anything 3 nodes. Make sure you have updated to the latest version of [ComfyUI](https://github.com/Comfy-Org/ComfyUI) before starting.
</Tip>

## Model Installation

Download the Depth Anything 3 checkpoint(s) and save them to the corresponding ComfyUI folder:

* **Small** ([depth\_anything\_3\_small.safetensors](https://huggingface.co/Comfy-Org/Depth-Anything-3/blob/main/geometry_estimation/depth_anything_3_small.safetensors)): Lightweight, fast inference
* **Base** ([depth\_anything\_3\_base.safetensors](https://huggingface.co/Comfy-Org/Depth-Anything-3/blob/main/geometry_estimation/depth_anything_3_base.safetensors)): Balanced performance
* **Mono-Large** ([depth\_anything\_3\_mono\_large.safetensors](https://huggingface.co/Comfy-Org/Depth-Anything-3/blob/main/geometry_estimation/depth_anything_3_mono_large.safetensors)): Best for monocular depth, includes sky detection
* **Metric-Large** ([depth\_anything\_3\_metric\_large.safetensors](https://huggingface.co/Comfy-Org/Depth-Anything-3/blob/main/geometry_estimation/depth_anything_3_metric_large.safetensors)): Metric scale depth in metres, includes sky detection

```
ComfyUI/
├── models/
│   ├── geometry_estimation/
│   │   ├── depth_anything_3_small.safetensors
│   │   ├── depth_anything_3_base.safetensors
│   │   ├── depth_anything_3_mono_large.safetensors
│   │   └── depth_anything_3_metric_large.safetensors
```

## Example Workflows

### Depth Anything 3: Image Depth Estimation

Upload one image and generate a depth map using Depth Anything 3. View a side-by-side comparison of the original image and depth output.

<img alt="Depth Anything 3 image depth estimation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_depth_anything3_image_depth_estimation&utm_source=docs&utm_medium=referral&utm_campaign=depth-anything-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_depth_anything3_image_depth_estimation.json">
    Download JSON or search "Depth Anything 3: Image Depth Estimation" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="retro_futuristic_home.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/retro_futuristic_home.png">
    `LoadImage` node 85 · `retro_futuristic_home.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />
</div>

### Steps to Run

1. **LoadImage**: load your input image
2. **LoadDA3Model**: select a Depth Anything 3 variant
3. **Run**: click Queue or use `Cmd+Enter`
4. The workflow outputs a depth map and side-by-side comparison

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Depth Anything 3: Video Depth Estimation

Upload a video to generate a per-frame depth sequence. Inside the subgraph, **GetVideoComponents** splits the input video into frames, **LoadDA3Model** loads the model, and **SetVideoComponents** reassembles the depth frames back into a video output.

<img alt="Depth Anything 3 video depth estimation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_depth_anything3_video_depth_estimation&utm_source=docs&utm_medium=referral&utm_campaign=depth-anything-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_depth_anything3_video_depth_estimation.json">
    Download JSON or search "Depth Anything 3: Video Depth Estimation" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadVideo` node:

<CardGroup>
  <Card title="empty_room_assembly.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/empty_room_assembly.mp4">
    `LoadVideo` node 87 · `empty_room_assembly.mp4`
  </Card>
</CardGroup>

<div>
  <video>
    <source type="video/mp4" />
  </video>
</div>

### Steps to Run

1. **LoadVideo**: load your input video
2. **Select Model**: choose between **Small**, **Base**, **Mono-Large**, or **Metric-Large**
3. **Run**: click Queue or use `Cmd+Enter`
4. The workflow outputs a video with per-frame depth maps

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Model Variants

| Variant | head\_type | has\_sky | has\_confidence | camera\_decoder | Best for |
| - | - | :-: | :-: | :-: | - |
| **Small** | dualdpt | ❌ | ✅ | ✅ | Fast inference, mobile/edge |
| **Base** | dualdpt | ❌ | ✅ | ✅ | Balanced performance |
| **Mono-Large** | dpt | ✅ | ❌ | ❌ | Monocular depth with sky detection |
| **Metric-Large** | dpt | ✅ | ❌ | ❌ | Physical metric depth in metres |

* **Small** and **Base** use the `dualdpt` head type with confidence estimation and camera decoder support for multi-view applications.
* **Mono-Large** and **Metric-Large** use the `dpt` head type with sky detection. Metric-Large outputs raw depth in metres.

## Community Resources

* [Depth Anything 3 GitHub (ByteDance-Seed)](https://github.com/ByteDance-Seed/Depth-Anything-3): Research paper and code
* [Comfy-Org/Depth-Anything-3](https://huggingface.co/Comfy-Org/Depth-Anything-3): Official ComfyUI model weights


# MediaPipe: Face Detection in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/face-detection/mediapipe

Learn how to use MediaPipe Face Detection in ComfyUI to detect faces and extract facial landmarks, bounding boxes, and region masks from images

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

[MediaPipe](https://github.com/google-ai-edge/mediapipe) is Google's open-source machine learning solution for real-time perception. In ComfyUI, MediaPipe Face Detection provides **BlazeFace** detection, **FaceMesh v2** landmark estimation, and **ARKit-52 blendshapes**, all in a single unified workflow.

MediaPipe Face Detection is natively supported in ComfyUI (PR [#14009](https://github.com/Comfy-Org/ComfyUI/pull/14009)), and the model weights are available under the [Apache 2.0 License](https://github.com/google-ai-edge/mediapipe/blob/master/LICENSE).

[MediaPipe GitHub](https://github.com/google-ai-edge/mediapipe) | [Comfy-Org Model Repository](https://huggingface.co/Comfy-Org/mediapipe)

### Key capabilities

* **Fast face detection**: BlazeFace-based detector with short (\~2 m) and full (\~5 m) range variants
* **478 facial landmarks**: dense FaceMesh v2 keypoints per detected face
* **ARKit-52 blendshapes**: real-time facial expression coefficients
* **Face region masks**: per-region masks for face oval, lips, eyes, and irises
* **Face bounding boxes**: outputs compatible with `DrawBBoxes` for bounding box visualization

> **Scope:** Face detection only: BlazeFace + FaceMesh v2 + ARKit blendshapes. This does not cover hand, pose, or holistic detection.

## MediaPipe Face Detection Workflow

### Mediapipe: Image Face Detection

Input an image and detect up to 6 facial landmarks per face, enabling ultrafast multi-face detection.

<img alt="Mediapipe image face detection workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_face_detection_mediapipe&utm_source=docs&utm_medium=referral&utm_campaign=mediapipe">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_face_detection_mediapipe.json">
    Download JSON or search "Mediapipe: Image Face Detection" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="soft_neon_girl.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/soft_neon_girl.png">
    `LoadImage` node 5 · `soft_neon_girl.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />
</div>

### 1. Download the Workflow

Update your ComfyUI to the latest version, then go to `Workflow` → `Browse Templates` and find "Mediapipe: Image Face Detection" under the Utility category.

### 2. Download the Model

The MediaPipe Face Detection model is hosted on the [Comfy-Org MediaPipe model repository](https://huggingface.co/Comfy-Org/mediapipe).

* [mediapipe\_face\_fp32.safetensors](https://huggingface.co/Comfy-Org/mediapipe/blob/main/detection/mediapipe_face_fp32.safetensors)

Place it in the following directory structure:

```
📂 ComfyUI/
└── 📂 models/
    └── 📂 detection/
        └── mediapipe_face_fp32.safetensors
```

### 3. Using the Workflow

This workflow uses a **subgraph** node that orchestrates face detection, visualization, and mask generation. The subgraph exposes the following controls:

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

**Subgraph inputs:**

| Input | Description |
| - | - |
| **image** | Input image batch to analyze |
| **face\_landmarker** | Optional. Leave empty to use the built-in model loader. Connect an external `FACE_DETECTION_MODEL` output to override |

**Subgraph parameters:**

| Parameter | Default | Description |
| - | :-: | - |
| **model\_name** | `mediapipe_face_fp32.safetensors` | Checkpoint in `ComfyUI/models/detection/`. If missing, download the model above |
| **detector\_variant** | `short` | **short**: tuned for close/large faces (\~2 m range). **full**: covers smaller/farther faces (\~5 m), slower. **both**: runs both detectors and keeps whichever found more faces per frame (\~2× cost) |
| **num\_faces** | `1` | Maximum faces to return per frame. `0` = no cap (return all detected). Range: 0–16 |
| **custom\_face\_oval** | `false` | Include face-outline region in the mask output |
| **custom\_lips** | `false` | Include lips in the mask (union with other enabled regions) |
| **custom\_left\_eye** | `false` | Include left eye region in the mask |
| **custom\_right\_eye** | `false` | Include right eye region in the mask |
| **custom\_irises** | `false` | Include iris regions in the mask |

Mask toggles use custom mode internally: only checked regions are filled; multiple ON regions are **unioned** into one mask per frame.

**Subgraph outputs:**

| Output | Type | Description |
| - | - | - |
| **face\_landmarks** | `FACE_LANDMARKS` | Per-frame faces with 478 2D/3D landmarks, ARKit-52 blendshapes, mesh topology data. Feeds into visualization and mask nodes |
| **bboxes** | `BOUNDING_BOX` | Face bounding boxes: compatible with `DrawBBoxes` node |
| **mask** | `MASK` | Binary mask from the enabled region toggles |

### 4. Run the Workflow

1. Ensure the model file is placed in `ComfyUI/models/detection/`
2. Load an image in the `Load Image` node
3. Adjust detection parameters as needed
4. Click `Queue` or use `Ctrl(Cmd) + Enter` to run
5. The workflow outputs the mesh overlay, bounding boxes, and mask preview

## Community Resources

* [MediaPipe GitHub](https://github.com/google-ai-edge/mediapipe): Upstream MediaPipe framework
* [Comfy-Org/mediapipe](https://huggingface.co/Comfy-Org/mediapipe): Official ComfyUI model weights
* [ComfyUI Subgraph Guide](https://docs.comfy.org/interface/features/subgraph): Learn how subgraphs work


# ComfyUI frame interpolation workflow
Source: https://docs.comfy.org/tutorials/utility/frame-interpolation

Learn how to use frame interpolation to smooth motion and increase frame rate in ComfyUI video workflows

## What is frame interpolation?

<Note>
  This workflow contains custom nodes. You need to install them using [ComfyUI Manager](/manager/overview) before running the workflow.
</Note>

Frame interpolation generates intermediate frames between existing frames, resulting in smoother motion and improved temporal consistency. This technique is essential for video post-processing and can significantly improve the quality of generated videos.

## Use cases

Frame interpolation supports:

* **Increasing frame rate in short clips** - Convert low-FPS videos to higher frame rates
* **Smoothing motion in generated or edited video** - Reduce stuttering and stepping artifacts
* **Preparing sequences for downstream video models** - Standardize frame rate for consistent processing
* **Fixing low-FPS generations** - Many video generation workflows default to 16fps, which can introduce noticeable stutter

## Why frame interpolation matters

Many image and video generation workflows still default to 16fps, which can introduce noticeable stutter, stepping, and uneven motion, especially in camera moves and character animation.

Frame interpolation is an effective way to smooth these artifacts without regenerating the source frames, making motion feel more natural while preserving the original composition and timing.

Rather than always treating interpolation as a final post-process, it can also be used as a preprocessing step, allowing you to standardize frame rate early and feed cleaner temporal data into larger animation and video pipelines.

<Card title="Frame Interpolation Workflow" icon="cloud" href="https://www.comfy.org/workflows/frame-interpolation">
  Run on Comfy Cloud
</Card>


# Image upscaling in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/image-upscale

Learn how to upscale images in ComfyUI using local models and partner nodes for different use cases

This guide covers image upscaling workflows in ComfyUI, including local models and partner node options for various use cases.

<Card title="The Complete AI Upscaling Handbook" icon="book-open" href="https://blog.comfy.org/p/upscaling-in-comfyui">
  For a comprehensive deep-dive with benchmarks and visual comparisons, read the full article on the ComfyUI Blog.
</Card>

## Why upscaling matters

* **Industry requirements for resolutions**: 4K/8K end results are widely required across VFX & Film, Marketing, E-commerce, Gaming, and Design industries, and requirements keep moving up.
* **Reframing**: When assets ship across different aspect ratios and placements, extra resolution headroom prevents quality loss after cropping or recomposition.
* **The AI content problem**: Generative AI has dramatically increased the speed of visual creation, but most AI assets today are still generated at 480–720p, and not production-ready at the pixel level: edges, micro-texture, faces/hands, compression artifacts, etc. This creates a new pipeline: Generation → Refinement/Fix → Upscale → Delivery.
* **Cost/time efficiency**: Generate or render smaller → upscale at the end. This is a standard efficiency move in pipelines under budget/time pressure.

## Key concepts

### Upscaling vs. enhancement

* **Upscaling** increases resolution while reconstructing detail.
* **Enhancement** improves perceived quality (denoise, sharpen, restore, color, faces, etc.).

The best practice in AI pipelines usually combines both steps.

### Creative vs. conservative upscale

Diffusion models and generative AI changed what "upscaling" means. Traditionally, super-resolution aimed to **preserve the original signal**. Today, some models can **re-imagine details that never existed**. And there are models approaching different balances between the two.

| | Conservative | Creative |
| - | - | - |
| **Approach** | Preserve the original | Reimagine and enhance |
| **Strengths** | High accuracy, consistency, production-safe | Rich details, sharper, more visually striking |
| **Limits** | Can appear flat, limited improvement on poor input | Possible hallucinations or structural drift |
| **Models** | Magnific Precise, SeedVR2, FlashVSR, Topaz Fast, HitPaw | Wan 2.2, Magnific Creative, Topaz Astra, HitPaw Creative |

## Use cases

<Note>
  **TL;DR**

  * **Portraits**: Magnific Skin Enhancer
  * **Product photography**: Magnific Precise, WaveSpeed SeedVR2, or Nano Banana Pro
  * **Landscapes & illustrations**: Model choice depends on your specific needs
  * **AI artifacts**: Do not rely on upscaling to fix common AI artifacts
  * **SeedVR2 tip**: Downscale the image to 0.35 megapixels with the `ImageScaleToTotalPixels` node before upscaling for better results
</Note>

### Portrait and skin enhancement

When it comes to upscaling portraits of realistic subjects, achieving realistic skin details while maintaining character consistency is key. The best upscale models for fixing plastic skin need to add texture, pores and natural skin imperfections. In this domain, Magnific Image Skin Enhancer far outperforms the rest.

**Recommended**: Magnific Image Skin Enhancer

<Card title="Magnific Skin Enhancer" icon="cloud" href="https://links.comfy.org/4cbvbE7">
  Try on Comfy Cloud or download workflow
</Card>

### Product photography

Maintaining a faithful representation of materials, product label edges, and small text is a must when upscaling product images. Therefore, conservative upscaling models are necessary.

**Recommended**: HitPaw, Magnific Precise, WaveSpeed SeedVR2, Nano Banana Pro

<Card title="HitPaw" icon="cloud" href="https://links.comfy.org/4kkoula">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Nano Banana Pro Product" icon="cloud" href="https://links.comfy.org/4qUntD0">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="SeedVR2 (Open Source)" icon="cloud" href="https://links.comfy.org/4ko2sOG">
  Try on Comfy Cloud or download workflow
</Card>

### Landscape and environments

For this use case, the upscale model you select really depends on your needs. Have an environmental shot that you want to pop with details and set a mood? Use a creative upscale model. Have an establishing shot where a building needs to stay consistent? Use a conservative upscale model.

It's worth noting that if your input image has artifacts, creative upscale models may be able to reimagine the artifact while conservative upscale models will not.

<Card title="Topaz Landscape" icon="cloud" href="https://links.comfy.org/4r1utxS">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Recraft Creative" icon="cloud" href="https://links.comfy.org/4afKfOJ">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Recraft Crisp" icon="cloud" href="https://links.comfy.org/3O0M4Yf">
  Try on Comfy Cloud or download workflow
</Card>

### Stylized art and illustration

This is another use case where the correct upscale model depends on your needs. A rule of thumb is that if your input has a very distinct/unique style, the best model will be conservative. Creative models may add too many details and stray away from the desired illustrated style. However, if your input image has room for detail, a creative model works well and can even improve the style.

We recommend playing around with the 'creativity' parameters for Magnific Creative and Topaz Image Enhance to find values that meet your needs! Nano Banana Pro can also work well for more common styles and adding details (but may rely on 'seed luck').

**Recommended**: Magnific Creative, Topaz Image Enhance, Nano Banana Pro

<Card title="Topaz Illustration" icon="cloud" href="https://links.comfy.org/46zi8c1">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Topaz Creative" icon="cloud" href="https://links.comfy.org/4kjT12P">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Nano Banana Pro Styled Art" icon="cloud" href="https://links.comfy.org/3O0Maiz">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Nano Banana Pro Portrait" icon="cloud" href="https://links.comfy.org/3O9XtF7">
  Try on Comfy Cloud or download workflow
</Card>

### AI-generated images

When it comes to upscaling images that have typical AI issues such as too many fingers, artifacts, incorrect anatomy, and morphing, the assumption is that creative upscales can fix it. Sometimes that's true, but other times not so much. Best practice is to resolve these issues prior to upscaling with image-edit models or traditional tools (or generate a new image entirely).

## Available models

### Local models (ESRGAN)

For basic local upscaling using ESRGAN models, see the [basic upscale tutorial](/tutorials/basic/upscale).

| Model | Best for |
| - | - |
| RealESRGAN | General-purpose upscaling |
| BSRGAN | Text and sharp edges |
| SwinIR | Natural textures, landscapes |

<Card title="Traditional Non-AI Upscaling" icon="cloud" href="https://links.comfy.org/45Nu9um">
  Try on Comfy Cloud or download workflow
</Card>

### General creative upscaling

For general creative upscaling across various use cases:

<Card title="HitPaw Creative" icon="cloud" href="https://links.comfy.org/4kkoula">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Recraft Creative" icon="cloud" href="https://links.comfy.org/4afKfOJ">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Recraft Crisp" icon="cloud" href="https://links.comfy.org/3O0M4Yf">
  Try on Comfy Cloud or download workflow
</Card>

### Partner nodes

Partner nodes provide access to advanced upscaling models via API.

| Model | Type | Features |
| - | - | - |
| Topaz Image Enhance (Bloom) | Creative | Subject detection, face enhancement, color preservation, up to 8K |
| Magnific Precise | Conservative | High accuracy, production-safe |
| Magnific Creative | Creative | Detail reimagination |
| Magnific Skin Enhancer | Creative | Portrait-specific, adds realistic skin texture |
| Nano Banana Pro | Conservative | Fast, good for product photography |
| WaveSpeed SeedVR2 | Conservative | High fidelity |
| HitPaw | Both | Conservative and creative modes |
| Recraft | Both | Creative and crisp modes |

## Benchmark: 1K to 4K upscale time

| Model | Time |
| - | - |
| Magnific Precise | \~40s |
| WaveSpeed SeedVR2 | \~40s |
| Magnific Creative | \~50s |
| Magnific Skin Enhancer | \~60s |
| HitPaw | \~60s |
| Nano Banana Pro | \~80s |
| Topaz Image Enhance | \~100s |

## Tips

* For SeedVR2, downscale the image to 0.35 megapixels with the `ImageScaleToTotalPixels` node before upscaling for better results.
* Chain multiple upscale nodes (e.g., 2x → 4x) for ultra-high magnification.
* Connect upscale nodes after generation for "generate + enhance" pipelines.
* Test multiple models on your specific image type to find the best fit.


# ComfyUI Marigold V2 Depth, Normal, and Albedo Estimation Guide
Source: https://docs.comfy.org/tutorials/utility/marigold-v2

Estimate depth, surface normals, and albedo from a single image in ComfyUI with Marigold V2: Qwen-Image Edit based diffusion transformers with dedicated LoRAs.

Marigold V2 is a family of monocular estimation models from Huawei Bayer Lab that repurpose a diffusion transformer (Qwen-Image Edit 2509) for geometry and intrinsic image estimation. From a single RGB image, the models predict a depth map, surface normals, or albedo, following up on the original Marigold (CVPR 2024) which repurposed Stable Diffusion for the same task. The V2 models ship as LoRAs on top of a shared base diffusion model, which keeps each download small and the workflow structure identical across the three tasks.

Compared with classical depth networks, the diffusion-based approach produces sharp, boundary-aware predictions and generalizes to open-domain images without retraining. Typical uses include depth-guided control for image and video generation, 3D scene reconstruction pipelines, relighting, and material editing driven by the estimated albedo.

Marigold V2 is supported natively in ComfyUI. Update to the latest version of [ComfyUI](https://github.com/comfyanonymous/ComfyUI) before starting.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Installation

Each workflow uses four files: the shared base diffusion model, plus a task-specific LoRA, VAE, and conditioning embedding. The three tasks use different LoRA, VAE, and conditioning files, so each workflow section below links the exact files it needs.

The base diffusion model is shared across all three workflows:

<Card title="Diffusion Model" icon="download" href="https://huggingface.co/Comfy-Org/marigold-v2-0/resolve/main/diffusion_models/qwen_image_edit_2509_int8_convrot.safetensors">
  qwen\_image\_edit\_2509\_int8\_convrot.safetensors → ComfyUI/models/diffusion\_models/
</Card>

If you plan to run all three tasks, download the per-task LoRAs, VAEs, and conditioning embeddings from the workflow sections and store them as shown in each section.

## Depth Estimation

Predict a depth map from a single image. The decoded prediction is normalized so that near surfaces appear bright.

<img alt="Marigold V2 depth estimation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_marigold_v2_depth_estimation&utm_source=docs&utm_medium=referral&utm_campaign=marigold-v2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_marigold_v2_depth_estimation.json">
    Download JSON or search "Depth Estimation: Marigold V2" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="ev_suv_gold_desert_pavilion.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/ev_suv_gold_desert_pavilion.png">
    `LoadImage` node · `ev_suv_gold_desert_pavilion.png`
  </Card>
</CardGroup>

### 1. Steps to Run

1. Load your input image in the `LoadImage` node
2. Queue the workflow: the base model runs with the depth LoRA, and the Marigold V2 Post-Process node normalizes the decoded prediction
3. Save or preview the resulting depth map

### 2. Model Downloads

<CardGroup>
  <Card title="Depth LoRA" icon="download" href="https://huggingface.co/Comfy-Org/marigold-v2-0/resolve/main/loras/marigold_v2_depth_log_stage2.safetensors">
    marigold\_v2\_depth\_log\_stage2.safetensors → ComfyUI/models/loras/
  </Card>

  <Card title="Depth VAE" icon="download" href="https://huggingface.co/Comfy-Org/marigold-v2-0/resolve/main/vae/marigold_v2_depth_log_stage2_vae.safetensors">
    marigold\_v2\_depth\_log\_stage2\_vae.safetensors → ComfyUI/models/vae/
  </Card>

  <Card title="Depth conditioning embedding" icon="download" href="https://huggingface.co/Comfy-Org/marigold-v2-0/resolve/main/embeddings/marigold_v2_depth_conditioning.safetensors">
    marigold\_v2\_depth\_conditioning.safetensors → ComfyUI/models/embeddings/
  </Card>
</CardGroup>

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 loras/
│   │   └── marigold_v2_depth_log_stage2.safetensors
│   ├── 📂 vae/
│   │   └── marigold_v2_depth_log_stage2_vae.safetensors
│   └── 📂 embeddings/
│       └── marigold_v2_depth_conditioning.safetensors
```

## Surface Normal Estimation

Predict per-pixel surface normals from a single image. The output maps each pixel to the direction the surface faces, useful for relighting and geometry analysis.

<img alt="Marigold V2 surface normal estimation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_marigold_v2_surface_normal_estimation&utm_source=docs&utm_medium=referral&utm_campaign=marigold-v2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_marigold_v2_surface_normal_estimation.json">
    Download JSON or search "Surface Normal Estimation: Marigold V2" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="greek_statue_orange_cloth.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/greek_statue_orange_cloth.png">
    `LoadImage` node · `greek_statue_orange_cloth.png`
  </Card>
</CardGroup>

### 1. Steps to Run

1. Load your input image in the `LoadImage` node
2. Queue the workflow with the normals LoRA loaded
3. Save or preview the resulting normal map

### 2. Model Downloads

<CardGroup>
  <Card title="Normals LoRA" icon="download" href="https://huggingface.co/Comfy-Org/marigold-v2-0/resolve/main/loras/marigold_v2_normals.safetensors">
    marigold\_v2\_normals.safetensors → ComfyUI/models/loras/
  </Card>

  <Card title="Normals VAE" icon="download" href="https://huggingface.co/Comfy-Org/marigold-v2-0/resolve/main/vae/marigold_v2_normals_vae.safetensors">
    marigold\_v2\_normals\_vae.safetensors → ComfyUI/models/vae/
  </Card>

  <Card title="Normals conditioning embedding" icon="download" href="https://huggingface.co/Comfy-Org/marigold-v2-0/resolve/main/embeddings/marigold_v2_normals_conditioning.safetensors">
    marigold\_v2\_normals\_conditioning.safetensors → ComfyUI/models/embeddings/
  </Card>
</CardGroup>

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 loras/
│   │   └── marigold_v2_normals.safetensors
│   ├── 📂 vae/
│   │   └── marigold_v2_normals_vae.safetensors
│   └── 📂 embeddings/
│       └── marigold_v2_normals_conditioning.safetensors
```

## Albedo Estimation

Predict the albedo (intrinsic color) of a single image, separating material color from lighting and shading. The output is converted to sRGB by the Marigold V2 Post-Process node.

<img alt="Marigold V2 albedo estimation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_marigold_v2_albedo_estimation&utm_source=docs&utm_medium=referral&utm_campaign=marigold-v2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_marigold_v2_albedo_estimation.json">
    Download JSON or search "Albedo Estimation: Marigold V2" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="flower_with_texture.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/flower_with_texture.png">
    `LoadImage` node · `flower_with_texture.png`
  </Card>
</CardGroup>

### 1. Steps to Run

1. Load your input image in the `LoadImage` node
2. Queue the workflow with the albedo LoRA loaded
3. Save or preview the resulting albedo image

### 2. Model Downloads

<CardGroup>
  <Card title="Albedo LoRA" icon="download" href="https://huggingface.co/Comfy-Org/marigold-v2-0/resolve/main/loras/marigold_v2_albedo.safetensors">
    marigold\_v2\_albedo.safetensors → ComfyUI/models/loras/
  </Card>

  <Card title="Albedo VAE" icon="download" href="https://huggingface.co/Comfy-Org/marigold-v2-0/resolve/main/vae/marigold_v2_albedo_vae.safetensors">
    marigold\_v2\_albedo\_vae.safetensors → ComfyUI/models/vae/
  </Card>

  <Card title="Albedo conditioning embedding" icon="download" href="https://huggingface.co/Comfy-Org/marigold-v2-0/resolve/main/embeddings/marigold_v2_albedo_conditioning.safetensors">
    marigold\_v2\_albedo\_conditioning.safetensors → ComfyUI/models/embeddings/
  </Card>
</CardGroup>

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 loras/
│   │   └── marigold_v2_albedo.safetensors
│   ├── 📂 vae/
│   │   └── marigold_v2_albedo_vae.safetensors
│   └── 📂 embeddings/
│       └── marigold_v2_albedo_conditioning.safetensors
```

## Marigold V2 Post-Process Node

Every workflow ends in the **Marigold V2 Post-Process** node, which turns the raw decoded prediction into a viewable image. The **prediction** option must match the task:

* **depth**: normalizes the prediction so near surfaces are bright
* **normals**: maps raw values to unit surface normals
* **albedo**: converts the prediction to sRGB


# ComfyUI MoGe Examples
Source: https://docs.comfy.org/tutorials/utility/moge

This guide demonstrates how to use MoGe in ComfyUI for monocular geometry estimation: metric point maps, depth maps, normal maps, and mesh generation.

# ComfyUI MoGe Introduction

[MoGe](https://github.com/microsoft/MoGe) (CVPR 2025, from Microsoft Research) is a powerful model for recovering 3D geometry from monocular open-domain images. It estimates metric point maps, metric depth maps, normal maps, and camera FOV: all in a single forward pass.

Key capabilities:

* **Accurate 3D geometry estimation**: point maps, depth maps, and normal maps from a single image: one model, one forward pass
* **Metric scale** (MoGe-2, MoGe-3): point maps and depth maps in real-world scale
* **Flexible resolution support**: works with various resolutions and aspect ratios (2:1 to 1:2)
* **Fast inference**: \~60ms per image on A100 / RTX 3090 (FP16, ViT-L)
* **Mesh generation** from both perspective and panoramic images

ComfyUI ships checkpoints for three MoGe versions:

| File | Version | Metric Scale | Normal Maps | Params |
| - | - | :-: | :-: | :-: |
| `moge_1_vitl_fp16` | **MoGe-1** | - | - | 314M |
| `moge_2_vitl_normal_fp16` | **MoGe-2** | ✅ | ✅ | 331M |
| `moge_3_vitl_fp16` | **MoGe-3** | ✅ | ✅ | 370M |
| `moge_3_vitg_fp16` | **MoGe-3** | ✅ | ✅ | 1.25B |

> MoGe-2 adds metric scale and high-quality normal map estimation with sharper visual detail and lower inference latency. **MoGe-2 with normal (`moge_2_vitl_normal_fp16`) is the recommended checkpoint.**
>
> MoGe-3 keeps the MoGe-2 architecture and adds a self-guided sparse volumetric refinement stage for significantly improved fine-grained point map geometry. It ships as a ViT-L checkpoint (`moge_3_vitl_fp16`) and a larger ViT-g checkpoint (`moge_3_vitg_fp16`).

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<Tip>
  ComfyUI now natively supports MoGe nodes. Make sure you have updated to the latest version of [ComfyUI](https://github.com/Comfy-Org/ComfyUI) before starting.

  Generated `.glb` format models will be output to the `ComfyUI/output/mesh` folder.
</Tip>

## Model Installation

Download the MoGe checkpoint(s) and save them to the corresponding ComfyUI folder:

* **MoGe-2 (recommended)**: [moge\_2\_vitl\_normal\_fp16.safetensors](https://huggingface.co/Comfy-Org/MoGe/blob/main/geometry_estimation/moge_2_vitl_normal_fp16.safetensors)
* **MoGe-1 (baseline)**: [moge\_1\_vitl\_fp16.safetensors](https://huggingface.co/Comfy-Org/MoGe/blob/main/geometry_estimation/moge_1_vitl_fp16.safetensors)
* **MoGe-3 (highest detail)**: [moge\_3\_vitg\_fp16.safetensors](https://huggingface.co/Comfy-Org/MoGe/blob/main/geometry_estimation/moge_3_vitg_fp16.safetensors) (1.25B) or [moge\_3\_vitl\_fp16.safetensors](https://huggingface.co/Comfy-Org/MoGe/blob/main/geometry_estimation/moge_3_vitl_fp16.safetensors) (370M)

```
ComfyUI/
├── models/
│   ├── geometry_estimation/
│   │   ├── moge_2_vitl_normal_fp16.safetensors
│   │   ├── moge_1_vitl_fp16.safetensors
│   │   ├── moge_3_vitg_fp16.safetensors
│   │   └── moge_3_vitl_fp16.safetensors
```

MoGe-3 checkpoints only: the `Run MoGe Inference` and `Run MoGe Panorama Inference` nodes expose an advanced `refine_steps` control (0 to 8, default 3) that runs sparse volumetric refinement passes over the predicted depth. `0` disables refinement, and more passes sharpen fine detail and edges at a roughly linear cost. MoGe-1 and MoGe-2 checkpoints ignore this setting.

## Example Workflows

### MoGe: Depth Estimation

Upload a single RGB image and generate a colored depth preview and raw depth map.

<img alt="MoGe depth estimation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_moge_depth_estimation&utm_source=docs&utm_medium=referral&utm_campaign=moge">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_moge_depth_estimation.json">
    Download JSON or search "MoGe: Depth Estimation" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="alien_world.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/alien_world.png">
    `LoadImage` node 9 · `alien_world.png`
  </Card>
</CardGroup>

### 1.1 Steps to Run

1. Ensure the `LoadMoGeModel` node has loaded a MoGe checkpoint
2. Load an image in the `Load Image` node
3. Click `Queue` or use `Ctrl(cmd) + Enter` to run
4. The workflow outputs colored depth preview, raw depth preview, and a mask

### MoGe: Perspective Geometry Estimation

Upload an image to estimate its perspective geometry. Generate a 3D depth map and surface normals from the input, then convert to a textured GLB mesh.

<img alt="MoGe perspective to mesh workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=3d_moge_perspective_to_mesh&utm_source=docs&utm_medium=referral&utm_campaign=moge">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_moge_perspective_to_mesh.json">
    Download JSON or search "MoGe: Perspective Geometry Estimation" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="modern_living_room.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/modern_living_room.png">
    `LoadImage` node 9 · `modern_living_room.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />
</div>

This is **monocular geometry estimation**: occluded areas and object backsides will be missing or fragmented. Useful for quick scene prototyping, reference geometry, or visualizing depth and normals as a mesh, but not a replacement for multi-view 3D reconstruction.

### 2.1 Steps to Run

1. Ensure the `LoadMoGeModel` node has loaded a MoGe checkpoint
2. Load a perspective photo in the `Load Image` node
3. (Optional) View the OpenGL and DirectX normal previews
4. Click `Queue` or use `Ctrl(cmd) + Enter` to run

### Moge: Panorama to Mesh

Upload an equirectangular 360° panorama image and generate a textured GLB mesh with vertex colors.

<img alt="MoGe panorama to mesh workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=3d_moge_panorama_to_mesh&utm_source=docs&utm_medium=referral&utm_campaign=moge">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_moge_panorama_to_mesh.json">
    Download JSON or search "Moge: Panorama to Mesh" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="lego_street_panorama.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/lego_street_panorama.png">
    `LoadImage` node 28 · `lego_street_panorama.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input panorama" />
</div>

The workflow uses `MoGePanoramaInference` to split the panorama into 12 perspective views, run monocular geometry estimation on each view independently, then merge them into a single mesh.

### 3.1 Steps to Run

1. Ensure the `LoadMoGeModel` node has loaded one of the MoGe checkpoints
2. Load an equirectangular panorama image in the `Load Image` node
3. Click `Queue` or use `Ctrl(cmd) + Enter` to run

### MoGe 3: Geometry Estimation

Estimate fine-detail geometry from a single image with MoGe 3. The MoGe-3 checkpoints lift the coarse point map onto a sparse voxel shell and refine depth with lightweight sparse 3D convolutions, which keeps thin structures and depth discontinuities that image-space decoders blur.

<img alt="MoGe 3 geometry estimation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_moge3_geometry_estimation&utm_source=docs&utm_medium=referral&utm_campaign=moge">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_moge3_geometry_estimation.json">
    Download JSON or search "Geometry Estimation: MoGe 3" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="cosmic_suitcase.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/cosmic_suitcase.png">
    `LoadImage` node 3 · `cosmic_suitcase.png`
  </Card>
</CardGroup>

### 4.1 Steps to Run

1. Ensure the `Geometry Estimation (MoGe 3)` subgraph has a MoGe 3 checkpoint selected: the template ships with `moge_3_vitg_fp16.safetensors`, and `moge_3_vitl_fp16.safetensors` is available in the same dropdown
2. Load an image in the `Load Image` node
3. (Optional) Change `output` on the subgraph node to render a different map: `mask` is the default, and `depth`, `depth_colored`, `normal_opengl`, and `normal_directx` are the other options
4. Click `Queue` or use `Ctrl(cmd) + Enter` to run

***

## Community Resources

* [MoGe GitHub (microsoft/MoGe)](https://github.com/microsoft/MoGe): Research paper and code
* [Comfy-Org/MoGe](https://huggingface.co/Comfy-Org/MoGe): Official ComfyUI model weights


# SDPose: Pose Detection in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/pose-detection-sdpose

Learn how to extract pose keypoints and maps from images and videos using SDPose, natively supported in ComfyUI

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

SDPose is a whole-body pose detection model that extracts human keypoints from images and videos. Combined with the RT-DETRv4 object detector, it supports multi-person detection and out-of-domain (OOD) pose estimation, making it a versatile tool for animation pipelines, pose-driven generation, and motion tracking workflows.

SDPose + RT-DETRv4 are natively supported in ComfyUI (PR [#12748](https://github.com/Comfy-Org/ComfyUI/pull/12748)). The model weights are available on Hugging Face.

[SDPose Model on Hugging Face](https://huggingface.co/Comfy-Org/SDPose) | [RT-DETRv4 Paper (arXiv)](https://arxiv.org/abs/2504.05731) | [SDPose Paper (arXiv)](https://arxiv.org/abs/2503.07740)

### Key strengths

* **Whole-body keypoints**: detects body, hands, face, and feet keypoints in a unified model
* **Multi-person support**: detects and labels multiple people in a single image or video
* **Configurable outputs**: choose which body parts to visualize (body, hands, face, feet) and control stick/font size
* **Bounding box detection**: includes object detection with tunable thresholds and class selection
* **Image and video support**: dedicated workflows for single images, videos, and OOD pose estimation

> **Limitations:** Detection accuracy depends on image resolution and subject visibility. Extremely occluded or very small subjects may produce fewer keypoints.

## SDPose Workflows

Four workflows are available depending on your use case:

| Workflow | Input | Output | Use Case |
| - | - | - | - |
| Multi-Person (Image) | Single image | Pose map + BBoxes | Photos with multiple people |
| Multi-Person (Video) | Video | Per-frame pose map + BBoxes | Video pose tracking |
| OOD Image to Pose | Single image | Pose map | Style transfer / image-to-pose |
| OOD Video to Pose Map | Video | Per-frame pose map | Video-to-pose animation |

### 1. Download Workflows

Update your ComfyUI to the latest version, then go to `Workflow` -> `Browse Templates` and find SDPose workflows under the Utility category.

### SDPose: Image Multi-Person Detection

Upload an image to detect human poses. Supports detection for both single individuals and multiple people within the same scene.

<img alt="SDPose image multi-person detection workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_sdpose_multi_person&utm_source=docs&utm_medium=referral&utm_campaign=pose-detection-sdpose">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_sdpose_multi_person.json">
    Download JSON or search "SDPose: Image Multi-Person Detection" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="group_photo.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/group_photo.png">
    `LoadImage` node 679 · `group_photo.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />
</div>

### SDPose: Video Multi-Person Detection

Upload a video to detect human poses. Supports detection for both single individuals and multiple people within the same scene.

<img alt="SDPose video multi-person detection workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_sdpose_multi_person_video&utm_source=docs&utm_medium=referral&utm_campaign=pose-detection-sdpose">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_sdpose_multi_person_video.json">
    Download JSON or search "SDPose: Video Multi-Person Detection" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadVideo` node:

<CardGroup>
  <Card title="man_playing_violin.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/man_playing_violin.mp4">
    `LoadVideo` node 694 · `man_playing_violin.mp4`
  </Card>
</CardGroup>

<div>
  <video>
    <source type="video/mp4" />
  </video>
</div>

### SDPose-OOD: Image to Pose Map

Upload an image to extract pose keypoints and generate a corresponding pose map using the SDPose-OOD model.

<img alt="SDPose-OOD image to pose map workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_sdpose_ood_image_to_pose&utm_source=docs&utm_medium=referral&utm_campaign=pose-detection-sdpose">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_sdpose_ood_image_to_pose.json">
    Download JSON or search "SDPose-OOD: Image to Pose Map" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="dancer.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/dancer.png">
    `LoadImage` node 667 · `dancer.png`
  </Card>
</CardGroup>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="SDPose-OOD image to pose map example output" />
</div>

### SDPose-OOD: Video to Pose Map

Upload a video to extract pose keypoints and generate a pose map. The workflow supports multiple person detection and uses an enhanced SDPose model for accurate whole-body feature extraction.

<img alt="SDPose-OOD video to pose map workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_sdpose_ood_video_to_pose_map&utm_source=docs&utm_medium=referral&utm_campaign=pose-detection-sdpose">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_sdpose_ood_video_to_pose_map.json">
    Download JSON or search "SDPose-OOD: Video to Pose Map" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadVideo` node:

<CardGroup>
  <Card title="man_in_the_rain.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/man_in_the_rain.mp4">
    `LoadVideo` node 679 · `man_in_the_rain.mp4`
  </Card>
</CardGroup>

**Example output**

<div>
  <video>
    <source type="video/mp4" />
  </video>

  <video>
    <source type="video/mp4" />
  </video>
</div>

### 2. Download Models

The SDPose and RT-DETRv4 model checkpoints are hosted on the [Comfy-Org SDPose model repository](https://huggingface.co/Comfy-Org/SDPose).

**checkpoints** (SDPose model):

* [sdpose\_wholebody\_fp16.safetensors](https://huggingface.co/Comfy-Org/SDPose/blob/main/checkpoints/sdpose_wholebody_fp16.safetensors)

**diffusion\_models** (RT-DETRv4 detector):

* [rt\_detr\_v4-x-hgnet\_fp16.safetensors](https://huggingface.co/Comfy-Org/SDPose/blob/main/diffusion_models/rt_detr_v4-x-hgnet_fp16.safetensors) (recommended)
* [rt\_detr\_v4-x-hgnet\_fp32.safetensors](https://huggingface.co/Comfy-Org/SDPose/blob/main/diffusion_models/rt_detr_v4-x-hgnet_fp32.safetensors) (full precision, larger)

Place them in the following directory structure:

```
📂 ComfyUI/
└── 📂 models/
    ├── 📂 checkpoints/
    │   └── sdpose_wholebody_fp16.safetensors
    └── 📂 diffusion_models/
        ├── rt_detr_v4-x-hgnet_fp16.safetensors
        └── rt_detr_v4-x-hgnet_fp32.safetensors
```

### 3. Using the Workflows

#### Multi-Person (Image)

* **Input**: Load an image via the `Load Image` node. Use an image with one or more people (example: `group_photo.png`).
* **Detection**: The `Image to Pose Map (SDPose Multi-Person)` subgraph processes the image and outputs:
  * **IMAGE**: pose skeleton visualization overlaid on the image
  * **keypoints**: raw whole-body keypoint data
  * **bboxes**: bounding box coordinates
* **Drawing Options**: Configure which body parts to draw:
  * `draw_body`, `draw_hands`, `draw_face`, `draw_feet`: toggle visibility
  * `stick_width`, `face_point_size`: adjust visual style
  * `score_threshold`: minimum confidence for displaying keypoints
* **Detection Options**:
  * `resize_type.longer_size`: scale the longer dimension before detection
  * `max_detections`: maximum number of people to detect
  * `detect_threshold`: detection confidence threshold
  * `detect_class`: object class to detect (default: person)

#### Multi-Person (Video)

Same as the image workflow but processes video frames sequentially. Use `Load Video` to input a video file and `Save Video` to export the result.

#### OOD Image to Pose

Uses the SDPose model to generate a clean pose map from an image, without bounding box visualization. This is useful for style transfer where you want to extract the skeleton pose from one image and apply it to another.

#### OOD Video to Pose Map

Generates per-frame pose maps from a video. The output is a video file where each frame contains the extracted pose skeleton, suitable for downstream animation or ControlNet workflows.

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  These workflows use Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflows.
</Card>

## Additional Notes

* **Model directory**: the SDPose checkpoint goes in `models/checkpoints/`, and the RT-DETRv4 detector goes in `models/diffusion_models/`
* **Input image example**: the `group_photo.png` file is available in the workflow template's `input/` directory for testing
* **Keypoint output**: the POSE\_KEYPOINT type can be connected to downstream nodes that accept pose data for conditional generation
* **Update required**: SDPose + RT-DETRv4 support is available in recent ComfyUI versions. Make sure your ComfyUI is up to date.


# ComfyUI preprocessor workflows
Source: https://docs.comfy.org/tutorials/utility/preprocessors

Learn how to use depth estimation, lineart conversion, pose detection, and normals extraction preprocessors in ComfyUI

## What are preprocessors?

<Note>
  These workflows contain custom nodes. You need to install them using [ComfyUI Manager](/manager/overview) before running the workflows.
</Note>

Preprocessors are foundational tools that extract structural information from images. They convert images into conditioning signals like depth maps, lineart, pose skeletons, and surface normals. These outputs drive better control and consistency in ControlNet, image-to-image, and video workflows.

Using preprocessors as separate workflows enables:

* Faster iteration without full graph reruns
* Clear separation of preprocessing and generation
* Easier debugging and tuning
* More predictable image and video results

## Depth estimation

Depth estimation converts a flat image into a depth map representing relative distance within a scene. This structural signal is foundational for controlled generation, spatially aware edits, and relighting workflows.

This workflow emphasizes:

* Clean, stable depth extraction
* Consistent normalization for downstream use
* Easy integration with ControlNet and image-edit pipelines

Depth outputs can be reused across multiple passes, making it easier to iterate without re-running expensive upstream steps.

### Video to Depth Map

Convert a video to a temporally stable depth map.

<img alt="Video to Depth Map workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility-depthAnything-v2-relative-video&utm_source=docs&utm_medium=referral&utm_campaign=preprocessors">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility-depthAnything-v2-relative-video.json">
    Download JSON or search "Video to Depth Map" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `VHS_LoadVideo` node:

<CardGroup>
  <Card title="roller_coaster.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/roller_coaster.mp4">
    `VHS_LoadVideo` node 6 · `roller_coaster.mp4`
  </Card>
</CardGroup>

<div>
  <video>
    <source type="video/mp4" />
  </video>
</div>

## Lineart conversion

Lineart preprocessors distill an image down to its essential edges and contours, removing texture and color while preserving structure.

This workflow is designed to:

* Produce clean, high-contrast lineart
* Minimize broken or noisy edges
* Provide reliable structural guidance for stylization and redraw workflows

Lineart pairs especially well with depth and pose, offering strong structural constraints without overconstraining style.

### Video to Lineart / Canny

Convert a video to lineart or Canny edges for control processors.

<img alt="Video to Lineart workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility-lineart-video&utm_source=docs&utm_medium=referral&utm_campaign=preprocessors">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility-lineart-video.json">
    Download JSON or search "Video to Lineart / Canny" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `VHS_LoadVideo` node:

<CardGroup>
  <Card title="utility-lineart-video-input.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/utility-lineart-video-input.mp4">
    `VHS_LoadVideo` node 2 · `utility-lineart-video-input.mp4`
  </Card>
</CardGroup>

<div>
  <video>
    <source type="video/mp4" />
  </video>
</div>

## Pose detection

Pose detection extracts body keypoints and skeletal structure from images, enabling precise control over human posture and movement.

This workflow focuses on:

* Clear, readable pose outputs
* Stable keypoint detection suitable for reuse across frames
* Compatibility with pose-based ControlNet and animation pipelines

By isolating pose extraction into a dedicated workflow, pose data becomes easier to inspect, refine, and reuse.

### Video to Pose Map - OpenPose

Convert a video to a temporally stable pose control map.

<img alt="Video to Pose Map workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility-openpose-video&utm_source=docs&utm_medium=referral&utm_campaign=preprocessors">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility-openpose-video.json">
    Download JSON or search "Video to Pose Map - OpenPose" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `VHS_LoadVideo` node:

<CardGroup>
  <Card title="pose_input.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/pose_input.mp4">
    `VHS_LoadVideo` node 2 · `pose_input.mp4`
  </Card>
</CardGroup>

<div>
  <video>
    <source type="video/mp4" />
  </video>
</div>

## Normals extraction

Normals estimation converts a flat image into a surface normal map: a per-pixel direction field that describes how each part of a surface is oriented (typically encoded as RGB). This signal is useful for relighting, material-aware stylization, and highly structured edits.

This workflow emphasizes:

* Clean, stable normal extraction with minimal speckling
* Consistent orientation and normalization for reliable downstream use
* ControlNet-ready outputs for relighting, refinement, and structure-preserving edits
* Reuse across passes so you can iterate without re-running earlier steps

Normal outputs can be used to:

* Drive relight/shading changes while preserving geometry
* Add a stronger 3D-like structure to stylization and redraw pipelines
* Improve consistency across frames when paired with pose/depth for animation work

### Video to Normal Map

Convert a video to a temporally stable normal map.

<img alt="Video to Normal Map workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility-normal_crafter-video&utm_source=docs&utm_medium=referral&utm_campaign=preprocessors">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility-normal_crafter-video.json">
    Download JSON or search "Video to Normal Map" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `VHS_LoadVideo` node:

<CardGroup>
  <Card title="normals_input.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/normals_input.mp4">
    `VHS_LoadVideo` node 3 · `normals_input.mp4`
  </Card>
</CardGroup>

<div>
  <video>
    <source type="video/mp4" />
  </video>
</div>


# BiRefNet: Remove Image Background in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/remove-background-birefnet

Learn how to remove image backgrounds using the BiRefNet model, natively supported in ComfyUI

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

BiRefNet (Bilateral Reference Network) is a high-quality image background removal model. It produces clean, detailed masks for a wide range of subjects, including people, products, animals, and complex objects with fine details like hair or fur.

BiRefNet is natively supported in ComfyUI (PR [#12747](https://github.com/Comfy-Org/ComfyUI/pull/12747)). The model weights are available under the [MIT License](https://github.com/ZhengPeng7/BiRefNet/blob/main/LICENSE).

[BiRefNet on Hugging Face](https://huggingface.co/ZhengPeng7/BiRefNet) | [Comfy-Org Model Repository](https://huggingface.co/Comfy-Org/BiRefNet) | [Paper (arXiv)](https://arxiv.org/abs/2401.00807)

### Key strengths

* **High-quality masks**: accurate edge detection for hair, fur, and fine details
* **Versatile subject detection**: works well on people, products, animals, and complex scenes
* **Simple one-click workflow**: just load an image and the model handles the rest
* **RGBA output**: produces an image with transparent background ready for compositing

> **Limitations:** Extremely cluttered backgrounds or subjects that blend into the background may produce less accurate masks. The model processes a single image at a time.

## BiRefNet Background Removal Workflow

### 1. Download Workflow

Update your ComfyUI to the latest version, then go to `Workflow` -> `Browse Templates` and find "BiRefNet: Remove Background" under the Utility category.

### BiRefNet: Remove Background

Upload an image with any background. Generate a version with the background removed and a precision segmentation mask.

<img alt="BiRefNet remove background workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_birefnet_remove_background&utm_source=docs&utm_medium=referral&utm_campaign=remove-background-birefnet">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_birefnet_remove_background.json">
    Download JSON or search "BiRefNet: Remove Background" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="the_lily_veil.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/the_lily_veil.png">
    `LoadImage` node 17 · `the_lily_veil.png`
  </Card>
</CardGroup>

### 2. Download Models

The BiRefNet model is hosted on the [Comfy-Org BiRefNet model repository](https://huggingface.co/Comfy-Org/BiRefNet).

* [birefnet.safetensors](https://huggingface.co/Comfy-Org/BiRefNet/blob/main/background_removal/birefnet.safetensors)

Place it in the following directory structure:

```
📂 ComfyUI/
└── 📂 models/
    └── 📂 background_removal/
        └── birefnet.safetensors
```

### 3. Using the Workflow

* **Image**: Load an image via the `Load Image` node (place it in the ComfyUI `input/` folder)
* The `Remove Background (BiRefNet)` subgraph processes the image and outputs:
  * **IMAGE**: the result with a transparent background (RGBA)
  * **mask**: the extracted foreground mask

Outputs can be previewed and used as inputs to other nodes for compositing, further editing, or saving.

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Additional Notes

* **Model directory**: the model must be placed in `ComfyUI/models/background_removal/`, not the `checkpoints` folder
* **Update required**: BiRefNet support is available in recent ComfyUI versions. Make sure your ComfyUI is up to date.
* **RGBA output**: the transparent background result can be directly composited onto new backgrounds or used in downstream workflows


# SAM 3D Body: Extract 3D Human Mesh From Video in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/sam3d-body

Extract a full-body 3D human mesh from a video using SAM 3D Body, with pose and shape estimation, face expressions, and a rendered mesh overlay video.

**SAM 3D Body** is an open-source model that recovers a full-body 3D human mesh from a single video. It combines video tracking, person detection, and mesh prediction to reconstruct the human body with pose, shape, and face expressions, then renders the recovered rig back onto the video.

The workflow is useful for motion capture prototyping, biomechanics analysis, and character animation previsualization.

### SAM 3D Body: 3D Human Mesh Extraction From Video

Load a video of a person. Extract a full-body 3D human mesh with pose, shape, and face expressions, rendered as an overlay video.

<img alt="SAM 3D Body workflow preview" />

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_sam3d_body&utm_source=docs&utm_medium=referral&utm_campaign=sam3d-body">
    Run this workflow instantly on Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_sam3d_body.json">
    Download JSON or search "SAM 3D Body: 3D Human Mesh Extraction From Video" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the `LoadVideo` node:

<CardGroup>
  <Card title="woman_holding_water_glass.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/woman_holding_water_glass.mp4">
    `LoadVideo` node 85 · `woman_holding_water_glass.mp4`
  </Card>
</CardGroup>

## How it works

1. **Video tracking**: SAM3 tracks the person across the video frames. Tracking is practically required when multiple people appear in the clip, and improves detection accuracy in general
2. **Person detection**: RT-DETR detects the person bounding boxes, guided by the text prompt (`person`)
3. **Mesh prediction**: SAM 3D Body predicts the full-body 3D mesh from the tracked frames, with optional MoGe camera FOV for more accurate alignment with the source video
4. **Face expressions**: a MediaPipe-based step adds face expressions, which the base model does not detect
5. **Smoothing**: the mesh sequence is smoothed over time
6. **Rendering**: a pose file (GLB) is built and the mesh is rendered back onto the video, then saved as an output video

## Steps to run

1. **Load a video**: use the `LoadVideo` node to load a video of a person
2. **Queue the workflow**: press Ctrl (Cmd on macOS) + Enter
3. **Wait for the pipeline**: tracking, detection, mesh prediction, and rendering run in sequence
4. **View the result**: inspect the mesh in the `Preview3D` node. The overlay video is saved to `ComfyUI/output/video/SAM3D_body/`

## Model downloads

Download the SAM 3D Body model and required files. Place them in the corresponding `models/` subdirectories.

<CardGroup>
  <Card title="SAM3 multiplex checkpoint" icon="download" href="https://huggingface.co/Comfy-Org/sam3.1/blob/main/checkpoints/sam3.1_multiplex_fp16.safetensors">
    sam3.1\_multiplex\_fp16.safetensors: SAM3 multiplex checkpoint for video tracking
  </Card>

  <Card title="SAM 3D Body detection" icon="download" href="https://huggingface.co/Comfy-Org/sam-3d-body/blob/main/detection/sam_3d_body_dinov3_bf16.safetensors">
    sam\_3d\_body\_dinov3\_bf16.safetensors: SAM 3D Body detection model (DINOv3 backbone)
  </Card>

  <Card title="MoGe geometry" icon="download" href="https://huggingface.co/Comfy-Org/MoGe/blob/main/geometry_estimation/moge_2_vitl_normal_fp16.safetensors">
    moge\_2\_vitl\_normal\_fp16.safetensors: optional camera FOV estimation for alignment
  </Card>

  <Card title="RT-DETR person detector" icon="download" href="https://huggingface.co/Comfy-Org/SDPose/blob/main/diffusion_models/rt_detr_v4-x-hgnet_fp32.safetensors">
    rt\_detr\_v4-x-hgnet\_fp32.safetensors: RT-DETR person detection model
  </Card>
</CardGroup>

### Model storage location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │      └── sam3.1_multiplex_fp16.safetensors
│   ├── 📂 detection/
│   │      └── sam_3d_body_dinov3_bf16.safetensors
│   ├── 📂 geometry_estimation/
│   │      └── moge_2_vitl_normal_fp16.safetensors
│   └── 📂 diffusion_models/
│          └── rt_detr_v4-x-hgnet_fp32.safetensors
```


# SeedVR2: Image and video upscaling in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/seedvr2

Learn how to upscale images and videos using SeedVR2, a one-step diffusion-based restoration model from ByteDance Seed

# ComfyUI SeedVR2 Introduction

[SeedVR2](https://iceclear.github.io/projects/seedvr2/) (arXiv:2506.05301, from ByteDance Seed) is a one-step diffusion-based video restoration model. It performs adversarial training against real data to restore and upscale images and videos with high fidelity. SeedVR2 is natively supported in ComfyUI (PR [#14424](https://github.com/Comfy-Org/ComfyUI/pull/14424)).

Key capabilities:

* **Conservative upscaling**: preserves original structure and detail while enhancing clarity
* **One-step inference**: single forward pass for both image and video upscaling
* **Multiple model sizes**: 3B and 7B variants with FP16, FP8, INT8, NVFP4, and MXFP8 quantizations
* **Both image and video**: supports single-image upscaling and video resolution enhancement

SeedVR2 comes in two sizes. The [3B model](https://huggingface.co/ByteDance-Seed/SeedVR2-3B) is a smaller variant with lower VRAM requirements, suitable for users with limited hardware. The [7B model](https://huggingface.co/ByteDance-Seed/SeedVR2-7B) is a larger variant that delivers higher quality results at the cost of increased VRAM and processing time. Both are available under the Apache 2.0 license.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Installation

Download the SeedVR2 checkpoint(s) from the [Comfy-Org SeedVR2 repository](https://huggingface.co/Comfy-Org/SeedVR2) and save them to the corresponding ComfyUI folder:

* [seedvr2\_3b\_fp16.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/blob/main/diffusion_models/seedvr2_3b_fp16.safetensors): 3B FP16 base model, lower VRAM requirement
* [seedvr2\_3b\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/blob/main/diffusion_models/seedvr2_3b_fp8_e4m3fn.safetensors): 3B FP8 quantized, further reduced VRAM
* [seedvr2\_3b\_int8\_convrot.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/blob/main/diffusion_models/seedvr2_3b_int8_convrot.safetensors): 3B INT8 with convrot
* [seedvr2\_7b\_fp16.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/blob/main/diffusion_models/seedvr2_7b_fp16.safetensors): 7B FP16 base model, higher quality
* [seedvr2\_7b\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/blob/main/diffusion_models/seedvr2_7b_fp8_e4m3fn.safetensors): 7B FP8 quantized, balance of quality and VRAM
* [seedvr2\_7b\_int8\_convrot.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/blob/main/diffusion_models/seedvr2_7b_int8_convrot.safetensors): 7B INT8 with convrot
* [seedvr2\_7b\_sharp\_fp16.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/blob/main/diffusion_models/seedvr2_7b_sharp_fp16.safetensors): 7B FP16 sharp variant for enhanced detail
* [seedvr2\_ema\_vae\_fp16.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/blob/main/vae/seedvr2_ema_vae_fp16.safetensors): VAE checkpoint (shared across all model variants)

Place the files in the following directories:

```
ComfyUI/
├── models/
│   ├── diffusion_models/
│   │   ├── seedvr2_3b_fp16.safetensors
│   │   ├── seedvr2_3b_fp8_e4m3fn.safetensors
│   │   ├── seedvr2_3b_int8_convrot.safetensors
│   │   ├── seedvr2_7b_fp16.safetensors
│   │   ├── seedvr2_7b_fp8_e4m3fn.safetensors
│   │   ├── seedvr2_7b_int8_convrot.safetensors
│   │   ├── seedvr2_7b_sharp_fp16.safetensors
│   └── vae/
│       └── seedvr2_ema_vae_fp16.safetensors
```

## Example Workflows

### SeedVR2 3B Int8: Upscale Image

Upscale images using SeedVR2 3B Int8, a one-step diffusion-based video restoration model that produces high-quality results with improved temporal consistency.

<img alt="SeedVR2 3B Int8 upscale image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_seedvr2_3b_int8_upscale_image&utm_source=docs&utm_medium=referral&utm_campaign=seedvr2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_seedvr2_3b_int8_upscale_image.json">
    Download JSON or search "SeedVR2 3B Int8: Upscale Image" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="watch_macro_shot.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/watch_macro_shot.png">
    `LoadImage` node 1 · `watch_macro_shot.png`
  </Card>
</CardGroup>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="SeedVR2 3B Int8 upscale example output" />
</div>

### 1.1 Steps to Run

1. Place your image in the `ComfyUI/input/` folder and select it in the `Load Image` node
2. Select the `seedvr2_3b_int8_convrot.safetensors` checkpoint in the SeedVR2 model loader
3. Click `Queue` or use `Ctrl(cmd) + Enter` to run

### SeedVR2 7B Int8: Upscale Image

Upscale images using SeedVR2 7B Int8, a one-step diffusion model that enhances resolution through adversarial training and adaptive window attention.

<img alt="SeedVR2 7B Int8 upscale image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_seedvr2_7b_int8_upscale_image&utm_source=docs&utm_medium=referral&utm_campaign=seedvr2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_seedvr2_7b_int8_upscale_image.json">
    Download JSON or search "SeedVR2 7B Int8: Upscale Image" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="indoor_portrait.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/indoor_portrait.png">
    `LoadImage` node 1 · `indoor_portrait.png`
  </Card>
</CardGroup>

**Example output**

<div>
  <img alt="Input image" />

  <img alt="SeedVR2 7B Int8 upscale example output" />
</div>

### 2.1 Steps to Run

1. Place your image in the `ComfyUI/input/` folder and select it in the `Load Image` node
2. Select the `seedvr2_7b_int8_convrot.safetensors` checkpoint in the SeedVR2 model loader
3. Click `Queue` or use `Ctrl(cmd) + Enter` to run

### SeedVR2 3B Int8: Upscale Video

Upscale and restore video footage using SeedVR2 3B Int8, a one-step diffusion model that enhances resolution while maintaining temporal consistency across frames.

<img alt="SeedVR2 3B Int8 upscale video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_seedvr2_3b_int8_upscale_video&utm_source=docs&utm_medium=referral&utm_campaign=seedvr2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_seedvr2_3b_int8_upscale_video.json">
    Download JSON or search "SeedVR2 3B Int8: Upscale Video" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadVideo` node:

<CardGroup>
  <Card title="grainy_perfume_shot_crf32.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/grainy_perfume_shot_crf32.mp4">
    `LoadVideo` node 73 · `grainy_perfume_shot_crf32.mp4`
  </Card>
</CardGroup>

**Example output**

<div>
  <video>
    <source type="video/mp4" />
  </video>

  <video>
    <source type="video/mp4" />
  </video>
</div>

### 3.1 Steps to Run

1. Place your video in the `ComfyUI/input/` folder and select it in the `Load Video` node
2. Select the `seedvr2_3b_int8_convrot.safetensors` checkpoint in the SeedVR2 model loader
3. Click `Queue` or use `Ctrl(cmd) + Enter` to run

### Performance

Higher target resolutions require more processing time. The INT8 variant provides efficient inference with reduced VRAM usage compared to FP16.

***

## Troubleshooting

### The upscaled image is fully black

Attention backends can silently return black or corrupted output on quantized checkpoints. If the SeedVR2 INT8 workflows produce an all-black image, try these in order:

1. **Run without FlashAttention:** if you enabled it through `--use-flash-attention` or a custom node pack, start ComfyUI with the default attention backend and re-run. Disabling FlashAttention has resolved all-black output on the 3B and 7B INT8 workflows on an RTX 3090.
2. **Switch the checkpoint:** use the FP16 or FP8 file of the same size. If those render correctly, the INT8 quantization path is where it breaks.
3. **Verify the files:** the diffusion model and `seedvr2_ema_vae_fp16.safetensors` must both be fully downloaded and placed as shown in Model Installation. A truncated download fails the same way.
4. **Disable the live preview:** in some cases only the preview is black while the saved file is correct, so turning the live preview off removes the ambiguity.

If the result is still black, post on the tutorial discussion with your GPU, ComfyUI version, install method (Desktop, portable, or manual) and the console output, plus whether the 3B and 7B workflows fail identically.

***

## Community Resources

* [SeedVR2 Project Page](https://iceclear.github.io/projects/seedvr2/): Official project website
* [ByteDance SeedVR Codebase (GitHub)](https://github.com/ByteDance-Seed/SeedVR): Original research code and paper
* [Comfy-Org/SeedVR2 (HuggingFace)](https://huggingface.co/Comfy-Org/SeedVR2): Official ComfyUI model weights
* [ByteDance-Seed/SeedVR2-3B (HuggingFace)](https://huggingface.co/ByteDance-Seed/SeedVR2-3B): Original 3B model weights
* [ByteDance-Seed/SeedVR2-7B (HuggingFace)](https://huggingface.co/ByteDance-Seed/SeedVR2-7B): Original 7B model weights
* [Paper (arXiv)](https://arxiv.org/abs/2506.05301)


# SAM 3.1: Segment Anything in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/video-segment-sam3

Learn how to use Meta's SAM 3.1 model in ComfyUI to segment objects in images and videos using text prompts

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

[SAM 3](https://ai.meta.com/sam3) (Segment Anything Model 3) is Meta's unified foundation model for promptable segmentation in images and videos. It can detect, segment, and track objects using text or visual prompts such as points, boxes, and masks. Compared to its predecessor [SAM 2](https://github.com/facebookresearch/sam2), SAM 3 introduces the ability to exhaustively segment all instances of an open-vocabulary concept specified by a short text phrase.

[SAM 3.1 Multiplex](https://github.com/facebookresearch/sam3) is the latest checkpoint release that introduces a shared-memory approach for joint multi-object tracking: significantly faster without sacrificing accuracy.

SAM 3.1 is natively supported in ComfyUI (PR [#13408](https://github.com/Comfy-Org/ComfyUI/pull/13408)), and the model weights are available under the [SAM License](https://github.com/facebookresearch/sam3/blob/main/LICENSE).

[SAM 3 GitHub](https://github.com/facebookresearch/sam3) | [Paper (arXiv)](https://arxiv.org/abs/2604.02296) | [🤗 Model Hub](https://huggingface.co/Comfy-Org/sam3.1)

<video>
  <source type="video/mp4" />
</video>

SAM 3.1 segments and tracks objects across video frames based on text prompts. The example above shows the segmentation output with masks applied to the target objects throughout the video.

### Key strengths

* **Text-driven segmentation**: describe what to segment in natural language, no need for manual point/box annotations
* **Image and video support**: works on both single images and video sequences with tracking across frames
* **Multi-object support**: segment and track multiple objects simultaneously using comma-separated prompts
* **Open-vocabulary**: handles a vastly larger set of open-vocabulary concepts than prior works

> **Limitations:** The model has a max token limit of 32 for text prompts. For best results, keep prompts short and specific to the target object.

## SAM 3.1 Segment Workflows

### 1. Download Workflow

Update your ComfyUI to the latest version, then go to `Workflow` -> `Browse Templates` and find the SAM 3.1 workflows under the Utility category.

### SAM3: Video Segmentation

Use the SAM3 model to segment the main subject or content from a video, isolating specific objects or regions.

<img alt="SAM3 video segmentation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_video_segment_sam3&utm_source=docs&utm_medium=referral&utm_campaign=video-segment-sam3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_video_segment_sam3.json">
    Download JSON or search "SAM3: Video Segmentation" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadVideo` node:

<CardGroup>
  <Card title="drinking_unicorn.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/drinking_unicorn.mp4">
    `LoadVideo` node 115 · `drinking_unicorn.mp4`
  </Card>
</CardGroup>

**Example output**

<video>
  <source type="video/mp4" />
</video>

### SAM3: Image Segmentation

Use the SAM3 model to segment the main subject or content from a photo or image, isolating specific objects or regions.

<img alt="SAM3 image segmentation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_image_segment_sam3&utm_source=docs&utm_medium=referral&utm_campaign=video-segment-sam3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_image_segment_sam3.json">
    Download JSON or search "SAM3: Image Segmentation" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="neon_guitarist.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/neon_guitarist.png">
    `LoadImage` node 79 · `neon_guitarist.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />
</div>

### 2. Download Models

The SAM 3.1 model is hosted on the [Comfy-Org SAM 3.1 model repository](https://huggingface.co/Comfy-Org/sam3.1).

* [sam3.1\_multiplex\_fp16.safetensors](https://huggingface.co/Comfy-Org/sam3.1/blob/main/checkpoints/sam3.1_multiplex_fp16.safetensors)

Place it in the following directory structure:

```
📂 ComfyUI/
└── 📂 models/
    └── 📂 checkpoints/
        └── sam3.1_multiplex_fp16.safetensors
```

### 3. Using the Workflows

**Image Segmentation:**

* **Image**: Load an image via the `Load Image` node (place it in the ComfyUI `input/` folder)
* **Object Prompt**: A short text description of the object(s) to segment, e.g. `person`, `car`, `cat`
* The output is a mask applied to the image, with an RGBA preview showing the segmentation result

**Video Segmentation:**

* **Video**: Load a video via the `Load Video` node
* **Object Prompt**: Same as image, a short text prompt describing what to track and segment across frames
* The output provides masks and bounding boxes for each frame

**Prompt format:**

| Prompt | Role |
| - | - |
| SAM3 object prompt | Short description of **what** to segment. Max 32 tokens. |

To prompt multiple subjects separately, separate with commas and use `:N` to specify the max amount of objects detected per prompt:
`eye:2, window panels:4`

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Additional Notes

* **Keep prompts short and specific**: the model has a 32-token limit per prompt
* **Multi-object detection**: use commas to separate different object types, and `:N` to cap detections per type
* **Segmentation masks**: the output mask can be used as input to other workflows (e.g., inpainting, background removal)
* **Update required**: make sure ComfyUI is updated to the latest version to access SAM 3.1 support


# Video upscaling in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/video-upscale

Learn how to upscale videos in ComfyUI using local models and partner nodes for different use cases

This guide covers video upscaling workflows in ComfyUI, including local models and partner node options for various use cases.

<Card title="The Complete AI Upscaling Handbook" icon="book" href="https://blog.comfy.org/p/upscaling-in-comfyui">
  For a comprehensive deep-dive with benchmarks and visual comparisons, see the full article on the ComfyUI Blog.
</Card>

## TL;DR

* **Quality mode**: SeedVR2 and HitPaw deliver the most accurate and consistent realism.
* **Speed mode**: FlashVSR and HitPaw are the fastest options.
* **AI video fix**: Topaz Astra Creative is strongest for cinematic polish and fixing AI-generated video.
* **Archival restoration**: SeedVR2 preserves original structure while enhancing clarity.
* **CGI/3D render**: Topaz, SeedVR2, and HitPaw all produce clean, sharp results.

## Key concepts

### Upscaling vs. enhancement

* **Upscaling** increases resolution while reconstructing detail.
* **Enhancement** improves perceived quality (denoise, sharpen, restore, temporal consistency, etc.).

Video upscaling adds temporal considerations—maintaining consistency across frames while improving resolution.

### Creative vs. conservative upscale

| | Conservative | Creative |
| - | - | - |
| **Approach** | Preserve the original | Reimagine and enhance |
| **Strengths** | High accuracy, temporal consistency, production-safe | Rich details, sharper, more visually striking |
| **Limits** | Can appear flat, limited improvement on poor input | Possible hallucinations, temporal flickering |
| **Models** | Topaz Starlight Fast, FlashVSR, SeedVR2, HitPaw | Topaz Starlight Creative (Astra), Wan 2.2, HitPaw |

## Use cases

### Quality mode

**SeedVR2** and **HitPaw** deliver the most accurate results, with strong image quality and excellent character consistency.

**Topaz** also upscales effectively, but it can sometimes be more creative than expected. This makes it especially suitable for cinematic footage where a stylized look is acceptable.

<Card title="SeedVR2 - Conservative (WaveSpeed API)" icon="cloud" href="https://links.comfy.org/4khbzjY">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="SeedVR2 - Conservative (Open Source)" icon="cloud" href="https://links.comfy.org/4tm2RoI">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="HitPaw - All-in-one" icon="cloud" href="https://links.comfy.org/4kthLWs">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Topaz Astra - Creative" icon="cloud" href="https://links.comfy.org/4tlbyQj">
  Try on Comfy Cloud or download workflow
</Card>

### Speed mode

**FlashVSR** performs extremely well when speed is the priority. Upscaling from 720p to 1080p takes about **41 seconds for a 10-second video**, making it one of the fastest options available.

**HitPaw** is also relatively fast. In **Topaz**, the Fast and Creative modes render at similar speeds, so using **Creative** mode is generally recommended for better visual results without sacrificing time.

<Card title="FlashVSR - Conservative (WaveSpeed API)" icon="cloud" href="https://links.comfy.org/4khbzjY">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="HitPaw - All-in-one" icon="cloud" href="https://links.comfy.org/4kthLWs">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Topaz Astra - Creative" icon="cloud" href="https://links.comfy.org/4tlbyQj">
  Try on Comfy Cloud or download workflow
</Card>

### AI video fix

**Topaz Astra Creative** produces very smooth and visually consistent outputs, making it a strong choice for repairing AI-generated videos.

A useful workflow tip is to first run a **fix or cleanup pass**, then upscale to **1080p**, and finally upscale gradually to **4K**. This step-by-step approach usually leads to better stability and detail.

<Card title="Topaz Astra - Creative" icon="cloud" href="https://links.comfy.org/4tlbyQj">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Wan 2.2 Upscale - Creative" icon="cloud" href="https://links.comfy.org/3NVEu1b">
  Try on Comfy Cloud or download workflow
</Card>

### Archival restoration

**SeedVR2** is particularly impressive for archival restoration. It preserves the original structure and detail of the source footage while enhancing clarity, avoiding the introduction of artificial or exaggerated features.

<Card title="SeedVR2 - Conservative (Open Source)" icon="cloud" href="https://links.comfy.org/4tm2RoI">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="SeedVR2 - Conservative (WaveSpeed API)" icon="cloud" href="https://links.comfy.org/4khbzjY">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Fast GAN - Traditional" icon="cloud" href="https://links.comfy.org/46wNZtS">
  Try on Comfy Cloud or download workflow
</Card>

### CGI / 3D render

**Topaz, SeedVR2 and HitPaw** all perform very well on CGI and 3D-rendered footage. They produce clean, sharp results and maintain the crisp edges that are important for synthetic imagery.

<Card title="Topaz Astra - Creative" icon="cloud" href="https://links.comfy.org/4tlbyQj">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="SeedVR2 - Conservative (WaveSpeed API)" icon="cloud" href="https://links.comfy.org/4khbzjY">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="HitPaw - All-in-one" icon="cloud" href="https://links.comfy.org/4kthLWs">
  Try on Comfy Cloud or download workflow
</Card>

### Animation and motion graphics

Clean lines and consistent colors are essential. Conservative upscaling preserves the intended style.

**Recommended**: Topaz Starlight Fast, Fast GAN

<Card title="Fast GAN - Traditional" icon="cloud" href="https://links.comfy.org/46wNZtS">
  Try on Comfy Cloud or download workflow
</Card>

## Upscale speed comparison (10s 720p clips)

| Model | Resolution | Time |
| - | - | - |
| FlashVSR (local) | 1080p | \~41s |
| FlashVSR (local) | 4K | \~52s |
| HitPaw | 2K | \~80s |
| HitPaw | 4K | \~175s |
| SeedVR2 (local, 5090) | 1080p | \~312s |
| Topaz Astra | 1080p | \~374s |
| Topaz Astra | 4K | \~560s |

## Available models

### Partner nodes

Partner nodes provide access to advanced video upscaling models via API.

| Model | Type | Max resolution | Features |
| - | - | - | - |
| Topaz Starlight Fast | Conservative | 4K | Fast, precision upscale |
| Topaz Starlight Creative (Astra) | Creative | 4K | Diffusion-based creative upscale |
| Topaz Apollo | - | - | Frame interpolation |
| WaveSpeed SeedVR2 | Conservative | - | High fidelity |
| WaveSpeed FlashVSR | Conservative | - | Fast video super-resolution |
| HitPaw | Both | - | All-in-one video enhancement |

### Topaz Video Enhance features

* **Upscaling**: Starlight (Astra) supports fast video upscaling to FullHD (1080p) or 4K while maintaining clarity.
* **Interpolation**: Apollo model for frame interpolation with slowmo settings and custom frame rates (e.g., 60fps).
* **Dynamic compression**: Intelligently identifies and handles compression artifacts to improve image purity.

## Getting started with Topaz Video Enhance

1. Update ComfyUI to the latest version.
2. Search for the `Topaz Video Enhance` node in the node list.
3. Connect your video input and configure the settings.
4. Run the workflow.

## Tips

* Combine upscaling with [frame interpolation](/tutorials/utility/frame-interpolation) for smoother, higher-resolution output.
* For AI-generated videos, consider fixing artifacts before upscaling rather than relying on creative upscaling to fix them.
* Test different models on sample clips before processing full videos.
* Use conservative upscaling for content that requires strict fidelity to the original.


# VOID: Video Inpainting in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/void-video-inpainting

Learn how to remove objects from videos using the VOID video inpainting model by Netflix, natively supported in ComfyUI

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

VOID (Video Object Inpainting and Deletion) is a powerful video inpainting model open-sourced by Netflix. It uses a two-pass diffusion pipeline built on [CogVideoX](https://github.com/THUDM/CogVideo) to remove objects from videos and fill the resulting holes with temporally coherent content.

VOID removes objects along with **all interactions they induce on the scene**, not just secondary effects like shadows and reflections, but physical interactions like objects falling when a person is removed. For example, if a person holding a guitar is removed, VOID also removes the person's effect on the guitar, causing it to fall naturally.

VOID is natively supported in ComfyUI (PR [#13403](https://github.com/Comfy-Org/ComfyUI/pull/13403)), and its complete model weights are available under the [Apache 2.0 License](https://github.com/Netflix/void-model?tab=Apache-2.0-1-ov-file).

[VOID Model - GitHub](https://github.com/Netflix/void-model) | [Paper (arXiv)](https://arxiv.org/abs/2604.02296) | [🤗 Diffusers Pipeline](https://huggingface.co/netflix/void-model)

<div>
  <video>
    <source type="video/mp4" />
  </video>

  <video>
    <source type="video/mp4" />
  </video>
</div>

**Before** (left): the original footage with the snowboarder. **After** (right): the processed result after removing the snowboarder from the scene. VOID removes unwanted objects while maintaining natural motion, lighting, and scene coherence across frames.

### Key strengths

* **Interaction-aware removal**: removes not just the object, but all physical interactions it caused on the scene (shadows, reflections, falling objects)
* **Object removal**, not single-frame patching: produces coherent motion and lighting across the entire clip
* **Two-pass refinement**: Pass 2 provides superior temporal stability (fewer jitters and flashes) compared to Pass 1 alone, especially on longer cuts or textured backgrounds

> **Limitations:** Unclear masks, chaotic motion, or targets that dominate the frame may still produce suboptimal results. Prompting cannot fix fundamentally wrong segmentation.

## VOID Video Inpainting Workflow

### 1. Download Workflow

Update your ComfyUI to the latest version, then go to `Workflow` -> `Browse Templates` and find "VOID: Video Inpainting" under the Utility category.

### VOID: Video Inpainting

Upload a video and mask the object you want to remove. Generate a clean video with the object and its physical interactions deleted.

<img alt="VOID video inpainting workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_void_video_inpainting&utm_source=docs&utm_medium=referral&utm_campaign=void-video-inpainting">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_void_video_inpainting.json">
    Download JSON or search "VOID: Video Inpainting" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadVideo` node:

<CardGroup>
  <Card title="snowboarder.mp4" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/snowboarder.mp4">
    `LoadVideo` node 4 · `snowboarder.mp4`
  </Card>
</CardGroup>

### 2. Download Models

All models are hosted on the [Comfy-Org VOID model repository](https://huggingface.co/Comfy-Org/void-model).

**Diffusion Models**: the core two-pass inpainting model:

* [void\_pass2.safetensors](https://huggingface.co/Comfy-Org/void-model/blob/main/diffusion_models/void_pass2.safetensors): Refinement pass, better temporal stability
* [void\_pass1.safetensors](https://huggingface.co/Comfy-Org/void-model/blob/main/diffusion_models/void_pass1.safetensors): Primary pass

**VAE:**

* [cogvideox\_vae.safetensors](https://huggingface.co/Comfy-Org/void-model/blob/main/vae/cogvideox_vae.safetensors)

**Optical Flow:**

* [raft\_large\_C\_T\_SKHT\_V2-ff5fadd5.safetensors](https://huggingface.co/Comfy-Org/void-model/blob/main/optical_flow/raft_large_C_T_SKHT_V2-ff5fadd5.safetensors)

**SAM3 Checkpoint**: for segmentation:

* [sam3.1\_multiplex\_fp16.safetensors](https://huggingface.co/Comfy-Org/sam3.1/blob/main/checkpoints/sam3.1_multiplex_fp16.safetensors)

**Text Encoder:**

* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp16.safetensors)

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── sam3.1_multiplex_fp16.safetensors
│   ├── 📂 text_encoders/
│   │   └── t5xxl_fp16.safetensors
│   ├── 📂 vae/
│   │   └── cogvideox_vae.safetensors
│   ├── 📂 optical_flow/
│   │   └── raft_large_C_T_SKHT_V2-ff5fadd5.safetensors
│   └── 📂 diffusion_models/
│       ├── void_pass2.safetensors
│       └── void_pass1.safetensors
```

### 3. Using the Workflow

**Inputs:**

* **Source video**: Load a video via the `Load Video` node (place it in the ComfyUI `input/` folder)
* **Positive prompt (inpaint fill)**: Describe the scene **after** removal. Focus on what remains and how it looks, not on what was removed
  * Example: `empty kitchen counter, daylight, tiles visible`
* **Negative prompt**: Optional anti-artifact list; can be left empty
* **SAM3 object prompt**: A short label for **what** to mask out. SAM3 uses semantic understanding to create a segmentation mask for the target object.
  * Example: `person in blue jacket`, `red cup on table`
  * Max tokens for SAM3 prompts is **32**. To prompt multiple subjects separately, separate with commas and use `:N` to specify the max objects detected per prompt: `eye:2, window panels:4`

**Modes:**

| Prompt | Role |
| - | - |
| SAM3 object | **What** is removed (SAM3 creates the mask via semantic segmentation) |
| Positive (inpaint) | **How** the hole is filled across time |

Use **Pass 2** (refinement pass) for longer clips or textured backgrounds where temporal stability matters. **Pass 1** alone is faster but may show more jitter.

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular video processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Additional Notes

* **Mask quality matters**: a clean, tight mask around the target object produces the best results
* **Prompt writing tip**: describe the scene as it should appear *naturally* after removal, not the removal itself
* **Use negative prompt** only when you see repeating defects (watermarks, blur, extra limbs)
* **Two-pass workflow**: the template runs Pass 1 then Pass 2 automatically; you can also run just Pass 1 for faster iterations during testing


# ComfyUI Bernini-R Examples
Source: https://docs.comfy.org/tutorials/video/bytedance/bernini-r

Learn how to use Bernini-R in ComfyUI for image and video editing with in-context conditioning: relighting, restyling, subject insertion, and more.

# ComfyUI Bernini-R Introduction

[Bernini-R](https://github.com/bytedance/Bernini) is ByteDance's **renderer-only** Wan 2.2 model for in-context image and video conditioning. It uses a set of conditioning streams (source video, reference images, reference video) to guide generation. No LoRA training or fine-tuning required.

Key capabilities:

* **Multiple task types in one model**: image/video generation, editing, relighting, restyling, subject insertion
* **In-context conditioning**: reference images/videos act as visual prompts, injected as tokens
* **Lightweight**: renderer-only model. No diffusion-based text-to-video backbone.
* **Flexible input support**: single or multi-image references, video-to-video, reference-guided editing

Bernini-R supports these task types:

| Task | Inputs | Description |
| - | - | - |
| **t2v** | Text prompt | Text-to-video generation |
| **v2v** | Source video | Video-to-video restyling |
| **rv2v** | Source video + ref images(s) | Reference-guided video editing (relighting, subject insertion) |
| **r2v** | Reference image(s) only | Reference-to-video generation |
| **img** | Source image + text prompt | Image editing (relighting, restyling, subject insertion) |
| **ads2v** | Source video + ref video | Insert image/video content into source video |

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<Tip>
  ComfyUI now natively supports Bernini-R nodes. Make sure you have updated to the latest version of [ComfyUI](https://github.com/Comfy-Org/ComfyUI) before starting.
</Tip>

## Model Installation

Download the required model weights and save them to the corresponding ComfyUI folders:

**text\_encoders:**

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true)

**vae:**

* [Wan2\_1\_VAE\_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Wan2_1_VAE_bf16.safetensors?download=true)

**loras:**

* [lightx2v\_T2V\_14B\_cfg\_step\_distill\_v2\_lora\_rank64\_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors?download=true)

**diffusion\_models:**

* [wan2.2\_bernini\_r\_fp16.safetensors](https://huggingface.co/Comfy-Org/Bernini-R/blob/main/wan2.2_bernini_r_fp16.safetensors)

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   ├── vae/
│   │   └── Wan2_1_VAE_bf16.safetensors
│   ├── loras/
│   │   └── lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors
│   ├── diffusion_models/
│   │   └── wan2.2_bernini_r_fp16.safetensors
```

## Example Workflows

***

## 1. Image Editing

**What it does:** Generate an edited image with matched lighting and view a side-by-side before/after comparison. Ideal for portrait and product relighting, consistent lighting across photo sets, and e-commerce catalog photography.

<img alt="Bernini-R Image Editing workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_bernini_r_image_editing&utm_source=docs&utm_medium=referral&utm_campaign=bernini-r">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_bernini_r_image_editing.json">
    Download JSON or search "Bernini-R" in Template Library
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/example.png">
    Download the default input image, or use your own.
  </Card>

  <Card title="Reference Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/desert_oasis_backyard.png">
    Download the default reference image, or use your own.
  </Card>
</CardGroup>

### Steps to Run

1. **Select Task Type**: choose your task (Image Editing, Subject to Image, etc.)
2. **Connect Inputs**: load source image and optional reference images
3. **Write Prompt**: describe the desired edit
4. **Run**: click Queue or use `Cmd+Enter`

**Reference Image input:** Use for **Subject to Image** when you need one or more reference images (subject, outfit, scene, props). In the prompt, use `image0`, `image1`, … to reference each image. Not needed for **Image Editing**: that task uses `source_image` instead.

<CardGroup>
  <Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
    This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
  </Card>
</CardGroup>

***

## 2. Video Editing

**What it does:** Generate an edited video with consistent relighting using Bernini-R. Connect a source video, optional reference image(s) or reference video, pick the task type, write a prompt, and run.

<img alt="Bernini-R Video Editing workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_bernini_r_video_editing&utm_source=docs&utm_medium=referral&utm_campaign=bernini-r">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_bernini_r_video_editing.json">
    Download JSON or search "Bernini-R" in Template Library
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Input Video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/vintage_field_style_look.mp4">
    Download the default input video, or use your own.
  </Card>

  <Card title="Reference Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/example.png">
    Download the default reference image, or use your own.
  </Card>
</CardGroup>

### Steps to Run

1. **Load Source Video**: connect your input video
2. **(Optional) Load References**: reference image(s) or reference video
3. **Select Task Type**: v2v, rv2v, r2v, or ads2v
4. **Write Prompt**: describe the desired edit
5. **Run**: click Queue or use `Cmd+Enter`

**Reference Image input:** Use when a task needs one or more reference images (rv2v, r2v, multi-piece outfits). Each batched image becomes its own in-context token. Mention `image0`, `image1`, … in the prompt if references play different roles.

<CardGroup>
  <Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
    This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
  </Card>
</CardGroup>

***

## Community Resources

* [Bernini GitHub (bytedance/Bernini)](https://github.com/bytedance/Bernini): Research paper and task documentation
* [Comfy-Org/Bernini-R](https://huggingface.co/Comfy-Org/Bernini-R): Official ComfyUI model weights
* [Bernini: Latent Semantic Planning for Video Diffusion](https://arxiv.org/abs/2605.22344): Research paper


# Cosmos Predict2 Video2World  ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/video/cosmos/cosmos-predict2-video2world

This guide demonstrates how to complete Cosmos-Predict2 Video2World workflows in ComfyUI

Cosmos-Predict2 is NVIDIA's next-generation physical world foundation model, specifically designed for high-quality visual generation and prediction tasks in physical AI scenarios.
The model features exceptional physical accuracy, environmental interactivity, and detail reproduction capabilities, enabling realistic simulation of complex physical phenomena and dynamic scenes.

Cosmos-Predict2 supports various generation methods including Text-to-Image (Text2Image) and Video-to-World (Video2World),
and is widely used in industrial simulation, autonomous driving, urban planning, scientific research, and other fields.
It serves as a crucial foundational tool for promoting deep integration of intelligent vision and the physical world.

<CardGroup>
  <Card title="GitHub" icon="github" href="https://github.com/nvidia-cosmos/cosmos-predict2">
    Cosmos-Predict2 source code and documentation
  </Card>

  <Card title="Hugging Face" icon="cube" href="https://huggingface.co/collections/nvidia/cosmos-predict2-68028efc052239369a0f2959">
    Cosmos-Predict2 model collection
  </Card>
</CardGroup>

This guide will walk you through completing **Video2World** generation in ComfyUI.

For the text-to-image section, please refer to the following part:

<CardGroup>
  <Card title="Cosmos Predict2 Text to Image" icon="book" href="/tutorials/image/cosmos/cosmos-predict2-t2i">
    Using Cosmos-Predict2 for text-to-image generation
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://comfy.org/cloud">
    Run Cosmos-Predict2 workflows on Comfy Cloud with powerful GPUs
  </Card>
</CardGroup>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Cosmos Predict2 Video2World Workflow

When testing the 2B version, it takes around 16GB VRAM.

### 1. Workflow File

Please download the video below and drag it into ComfyUI to load the workflow. The workflow already has embedded model download links.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://comfy.org/cloud">
    Run this workflow on Comfy Cloud with pre-installed models
  </Card>

  <Card title="Download Workflow File" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/cosmos/predict2/cosmos_predict2_2B_video2world_480p_16fps.json">
    Download the JSON format workflow file
  </Card>
</CardGroup>

Please download the following image as input:

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/cosmos/predict2/input.png)

### 2. Manual Model Installation

If the model download was not successful, you can try to download them manually by yourself in this section.

**Diffusion model**

<Card title="Diffusion Model" icon="download" href="https://huggingface.co/Comfy-Org/Cosmos_Predict2_repackaged/blob/main/cosmos_predict2_2B_video2world_480p_16fps.safetensors">
  cosmos\_predict2\_2B\_video2world\_480p\_16fps.safetensors
</Card>

For other weights, please visit [Cosmos\_Predict2\_repackaged](https://huggingface.co/Comfy-Org/Cosmos_Predict2_repackaged) to download.

**Text encoder**

<Card title="Text Encoder" icon="download" href="https://huggingface.co/comfyanonymous/cosmos_1.0_text_encoder_and_VAE_ComfyUI/blob/main/text_encoders/oldt5_xxl_fp8_e4m3fn_scaled.safetensors">
  oldt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors
</Card>

**VAE**

<Card title="VAE" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
  wan\_2.1\_vae.safetensors
</Card>

File Storage Location

```
📂 ComfyUI/
├──📂 models/
│   ├── 📂 diffusion_models/
│   │   └─── cosmos_predict2_2B_video2world_480p_16fps.safetensors
│   ├── 📂 text_encoders/
│   │   └─── oldt5_xxl_fp8_e4m3fn_scaled.safetensors
│   └── 📂 vae/
│       └──  wan_2.1_vae.safetensors
```

### 3. Complete Workflow  Step by Step

<img alt="Workflow Step Guide" />

Please follow the steps in the image to run the workflow:

1. Ensure the `Load Diffusion Model` node has loaded `cosmos_predict2_2B_video2world_480p_16fps.safetensors`
2. Ensure the `Load CLIP` node has loaded `oldt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Upload the provided input image in the `Load Image` node
5. (Optional) If you need first and last frame control, use the shortcut `Ctrl(cmd) + B` to enable last frame input
6. (Optional) You can modify the prompts in the `ClipTextEncode` node
7. (Optional) Modify the size and frame count in the `CosmosPredict2ImageToVideoLatent` node
8. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to run the workflow
9. Once generation is complete, the video will automatically save to the `ComfyUI/output/` directory, you can also preview it in the `save video` node


# ComfyUI Hunyuan Video Examples
Source: https://docs.comfy.org/tutorials/video/hunyuan/hunyuan-video

This guide shows how to use Hunyuan Text-to-Video and Image-to-Video workflows in ComfyUI

<video />

Hunyuan Video series is developed and open-sourced by [Tencent](https://huggingface.co/tencent), featuring a hybrid architecture that supports both [Text-to-Video](https://github.com/Tencent/HunyuanVideo) and [Image-to-Video](https://github.com/Tencent/HunyuanVideo-I2V) generation with a parameter scale of 13B.

Technical features:

* **Core Architecture:** Uses a DiT (Diffusion Transformer) architecture similar to Sora, effectively fusing text, image, and motion information to improve consistency, quality, and alignment between generated video frames. A unified full-attention mechanism enables multi-view camera transitions while ensuring subject consistency.
* **3D VAE:** The custom 3D VAE compresses videos into a compact latent space, making image-to-video generation more efficient.
* **Superior Image-Video-Text Alignment:** Utilizing MLLM text encoders that excel in both image and video generation, better following text instructions, capturing details, and performing complex reasoning.

You can learn more through the official repositories: [Hunyuan Video](https://github.com/Tencent/HunyuanVideo) and [Hunyuan Video-I2V](https://github.com/Tencent/HunyuanVideo-I2V).

This guide will walk you through setting up both **Text-to-Video** and **Image-to-Video** workflows in ComfyUI.

<Tip>
  The workflow images in this tutorial contain metadata with model download information.

  Simply drag them into ComfyUI or use the menu `Workflows` -> `Open (ctrl+o)` to load the corresponding workflow, which will prompt you to download the required models.

  Alternatively, this guide provides direct model links if automatic downloads fail or you are not using the Desktop version. All models are available [here](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/tree/main/split_files) for download.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Common Models for All Workflows

The following models are used in both Text-to-Video and Image-to-Video workflows. Download and save them to the specified directories:

<CardGroup>
  <Card icon="cube" title="Text Encoder: clip_l.safetensors" href="https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/blob/main/split_files/text_encoders/clip_l.safetensors?download=true">
    Save to ComfyUI/models/text\_encoders
  </Card>

  <Card icon="cube" title="Text Encoder: llava_llama3_fp8_scaled.safetensors" href="https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/blob/main/split_files/text_encoders/llava_llama3_fp8_scaled.safetensors?download=true">
    Save to ComfyUI/models/text\_encoders
  </Card>
</CardGroup>

<Card icon="cube" title="VAE: hunyuan_video_vae_bf16.safetensors" href="https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/blob/main/split_files/vae/hunyuan_video_vae_bf16.safetensors?download=true">
  Save to ComfyUI/models/vae
</Card>

Storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── llava_llama3_fp8_scaled.safetensors
│   └── vae/
│       └── hunyuan_video_vae_bf16.safetensors
```

## Hunyuan Text-to-Video Workflow

Hunyuan Text-to-Video was open-sourced in December 2024, supporting 5-second short video generation through natural language descriptions in both Chinese and English.

### 1. Workflow

Download the workflow image below and drag it into ComfyUI to load the workflow:

![ComfyUI Workflow - Hunyuan Text-to-Video](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/hunyuan_video_text_to_video-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=hunyuan_video_text_to_video&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan-video">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/hunyuan_video_text_to_video.json">
    Download JSON or search "Hunyuan Video" in Template Library
  </Card>
</CardGroup>

### 2. Manual models installation

<Card icon="cube" title="Diffusion Model: hunyuan_video_t2v_720p_bf16.safetensors" href="https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/blob/main/split_files/diffusion_models/hunyuan_video_t2v_720p_bf16.safetensors?download=true">
  Save to ComfyUI/models/diffusion\_models
</Card>

Ensure you have all these model files in the correct locations:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors                       // Shared model
│   │   └── llava_llama3_fp8_scaled.safetensors      // Shared model
│   ├── vae/
│   │   └── hunyuan_video_vae_bf16.safetensors       // Shared model
│   └── diffusion_models/
│       └── hunyuan_video_t2v_720p_bf16.safetensors  // T2V model
```

### 3. Steps to run the workflow

<img alt="ComfyUI Hunyuan Video T2V Workflow" />

1. Ensure the `DualCLIPLoader` node has loaded these models:
   * clip\_name1: clip\_l.safetensors
   * clip\_name2: llava\_llama3\_fp8\_scaled.safetensors
2. Ensure the `Load Diffusion Model` node has loaded `hunyuan_video_t2v_720p_bf16.safetensors`
3. Ensure the `Load VAE` node has loaded `hunyuan_video_vae_bf16.safetensors`
4. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

<Tip>
  When the `length` parameter in the `EmptyHunyuanLatentVideo` node is set to 1, the model can generate a static image.
</Tip>

## Hunyuan Image-to-Video Workflow

Hunyuan Image-to-Video model was open-sourced on March 6, 2025, based on the HunyuanVideo framework. It transforms static images into smooth, high-quality videos and also provides LoRA training code to customize special video effects like hair growth, object transformation, and more.

Currently, the Hunyuan Image-to-Video model has two versions:

* v1 "concat": Better motion fluidity but less adherence to the image guidance
* v2 "replace": Updated the day after v1, with better image guidance but seemingly less dynamic compared to v1

<div>
  <div>
    <p>v1 "concat"</p>

    <img alt="HunyuanVideo v1" />
  </div>

  <div>
    <p>v2 "replace"</p>

    <img alt="HunyuanVideo v2" />
  </div>
</div>

### Shared Model for v1 and v2 Versions

<Card icon="cube" title="CLIP Vision: llava_llama3_vision.safetensors" href="https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/blob/main/split_files/clip_vision/llava_llama3_vision.safetensors?download=true">
  Save to ComfyUI/models/clip\_vision
</Card>

### V1 "concat" Image-to-Video Workflow

#### 1. Workflow and Asset

Download the workflow image below and drag it into ComfyUI to load the workflow:

![ComfyUI Workflow - Hunyuan Image-to-Video v1](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hunyuan-video/i2v/v1_robot.webp)

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hunyuan-video/i2v/v1_robot.webp">
    Download the workflow image and drag into ComfyUI
  </Card>
</CardGroup>

Download the image below and use it as the starting frame for the image-to-video generation:

<Card icon="cube" title="Starting Frame: robot-ballet.png" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/hunyuan-video/i2v/robot-ballet.png">
  Save and use as input image for I2V generation
</Card>

#### 2. Related models manual installation

<Card icon="cube" title="Diffusion Model: hunyuan_video_image_to_video_720p_bf16.safetensors" href="https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/blob/main/split_files/diffusion_models/hunyuan_video_image_to_video_720p_bf16.safetensors?download=true">
  Save to ComfyUI/models/diffusion\_models
</Card>

Ensure you have all these model files in the correct locations:

```
ComfyUI/
├── models/
│   ├── clip_vision/
│   │   └── llava_llama3_vision.safetensors                     // I2V shared model
│   ├── text_encoders/
│   │   ├── clip_l.safetensors                                  // Shared model
│   │   └── llava_llama3_fp8_scaled.safetensors                 // Shared model
│   ├── vae/
│   │   └── hunyuan_video_vae_bf16.safetensors                  // Shared model
│   └── diffusion_models/
│       └── hunyuan_video_image_to_video_720p_bf16.safetensors  // I2V v1 "concat" version model
```

#### 3. Steps to run the workflow

<img alt="ComfyUI Hunyuan Video I2V v1 Workflow" />

1. Ensure that `DualCLIPLoader` has loaded these models:
   * clip\_name1: clip\_l.safetensors
   * clip\_name2: llava\_llama3\_fp8\_scaled.safetensors
2. Ensure that `Load CLIP Vision` has loaded `llava_llama3_vision.safetensors`
3. Ensure that `Load Image Model` has loaded `hunyuan_video_image_to_video_720p_bf16.safetensors`
4. Ensure that `Load VAE` has loaded `vae_name: hunyuan_video_vae_bf16.safetensors`
5. Ensure that `Load Diffusion Model` has loaded `hunyuan_video_image_to_video_720p_bf16.safetensors`
6. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

### v2 "replace" Image-to-Video Workflow

The v2 workflow is essentially the same as the v1 workflow. You just need to download the **replace** model and use it in the `Load Diffusion Model` node.

#### 1. Workflow and Asset

Download the workflow image below and drag it into ComfyUI to load the workflow:

![ComfyUI Workflow - Hunyuan Image-to-Video v2](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hunyuan-video/i2v/v2_fennec_gril.webp)

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hunyuan-video/i2v/v2_fennec_gril.webp">
    Download the workflow image and drag into ComfyUI
  </Card>
</CardGroup>

Download the image below and use it as the starting frame for the image-to-video generation:

<Card icon="cube" title="Starting Frame: flux_dev_example.png" href="https://comfyanonymous.github.io/ComfyUI_examples/flux/flux_dev_example.png">
  Save and use as input image for I2V generation
</Card>

#### 2. Related models manual installation

<Card icon="cube" title="Diffusion Model: hunyuan_video_v2_replace_image_to_video_720p_bf16.safetensors" href="https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/blob/main/split_files/diffusion_models/hunyuan_video_v2_replace_image_to_video_720p_bf16.safetensors?download=true">
  Save to ComfyUI/models/diffusion\_models
</Card>

Ensure you have all these model files in the correct locations:

```
ComfyUI/
├── models/
│   ├── clip_vision/
│   │   └── llava_llama3_vision.safetensors                                // I2V shared model
│   ├── text_encoders/
│   │   ├── clip_l.safetensors                                             // Shared model
│   │   └── llava_llama3_fp8_scaled.safetensors                            // Shared model
│   ├── vae/
│   │   └── hunyuan_video_vae_bf16.safetensors                             // Shared model
│   └── diffusion_models/
│       └── hunyuan_video_v2_replace_image_to_video_720p_bf16.safetensors  // V2 "replace" version model
```

#### 3. Steps to run the workflow

<img alt="ComfyUI Hunyuan Video I2V v2 Workflow" />

1. Ensure the `DualCLIPLoader` node has loaded these models:
   * clip\_name1: clip\_l.safetensors
   * clip\_name2: llava\_llama3\_fp8\_scaled.safetensors
2. Ensure the `Load CLIP Vision` node has loaded `llava_llama3_vision.safetensors`
3. Ensure the `Load Image Model` node has loaded `hunyuan_video_image_to_video_720p_bf16.safetensors`
4. Ensure the `Load VAE` node has loaded `hunyuan_video_vae_bf16.safetensors`
5. Ensure the `Load Diffusion Model` node has loaded `hunyuan_video_v2_replace_image_to_video_720p_bf16.safetensors`
6. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Try It Yourself

Here are some images and prompts we provide. Use them as-is or adjust to create your own video.

<img alt="example" />

```
Futuristic robot dancing ballet, dynamic motion, fast motion, fast shot, moving scene
```

***

<img alt="example" />

```
Samurai waving sword and hitting the camera. camera angle movement, zoom in, fast scene, super fast, dynamic
```

***

<img alt="example" />

```
flying car fastly moving and flying through the city
```

***

<img alt="example" />

```
cyberpunk car race in night city, dynamic, super fast, fast shot
```


# HunyuanVideo 1.5
Source: https://docs.comfy.org/tutorials/video/hunyuan/hunyuan-video-1-5

Learn how to use HunyuanVideo 1.5, a lightweight 8.3B parameter model for high-quality video generation on consumer GPUs

[HunyuanVideo 1.5](https://github.com/Tencent/HunyuanVideo) is a lightweight 8.3B parameter model developed by Tencent's Hunyuan team. It delivers flagship-quality video generation on consumer GPUs (24GB VRAM), dramatically lowering the barrier to entry without compromising on quality.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model highlights

* **Compact powerhouse**: Delivers SOTA performance comparable to larger models while running on consumer hardware.
* **Versatile generation**: Supports high-quality Text-to-Video and Image-to-Video (5-10s) with exceptional consistency.
* **Precise control**: Strong instruction following for camera movements, physics, and emotional expressions.
* **Cinematic quality**: Native 720p output (upscalable to 1080p) with professional aesthetics.
* **Rich features**: Supports diverse styles (realistic, anime, 3D) and in-video text rendering (Chinese/English).

## Common models for all workflows

The following models are used in both Text-to-Video and Image-to-Video workflows. Download and save them to the specified directories:

<CardGroup>
  <Card title="Download Qwen2.5 VL 7B" icon="download" href="https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/blob/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors?download=true">
    qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors — save to <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Download ByT5 Small" icon="download" href="https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/blob/main/split_files/text_encoders/byt5_small_glyphxl_fp16.safetensors?download=true">
    byt5\_small\_glyphxl\_fp16.safetensors — save to <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Download HunyuanVideo 1.5 VAE" icon="download" href="https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/blob/main/split_files/vae/hunyuanvideo15_vae_fp16.safetensors?download=true">
    hunyuanvideo15\_vae\_fp16.safetensors — save to <code>ComfyUI/models/vae/</code>
  </Card>
</CardGroup>

#### Storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │   ├── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   │   └── byt5_small_glyphxl_fp16.safetensors
│   └── 📂 vae/
│       └── hunyuanvideo15_vae_fp16.safetensors
```

## Hunyuan Video 1.5 Text-to-Video Workflow

HunyuanVideo 1.5 Text-to-Video generates 5-10 second videos from natural language descriptions with enhanced quality and reduced VRAM requirements.

![ComfyUI Workflow - Hunyuan Video 1.5 T2V](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_hunyuan_video_1.5_720p_t2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_hunyuan_video_1.5_720p_t2v&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan-video-1-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_hunyuan_video_1.5_720p_t2v.json">
    Download JSON or search "Hunyuan Video 1.5 T2V" in Template Library
  </Card>
</CardGroup>

### Model downloads

<CardGroup>
  <Card title="Download T2V Diffusion Model" icon="download" href="https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/blob/main/split_files/diffusion_models/hunyuanvideo1.5_720p_t2v_fp16.safetensors?download=true">
    hunyuanvideo1.5\_720p\_t2v\_fp16.safetensors — save to <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │   ├── qwen_2.5_vl_7b_fp8_scaled.safetensors       // Shared model
│   │   └── byt5_small_glyphxl_fp16.safetensors           // Shared model
│   ├── 📂 vae/
│   │   └── hunyuanvideo15_vae_fp16.safetensors           // Shared model
│   └── 📂 diffusion_models/
│       └── hunyuanvideo1.5_720p_t2v_fp16.safetensors     // T2V model
```

### Steps to run the workflow

1. Ensure the `DualCLIPLoader` node has loaded these models:
   * clip\_name1: `qwen_2.5_vl_7b_fp8_scaled.safetensors`
   * clip\_name2: `byt5_small_glyphxl_fp16.safetensors`
2. Ensure the `Load Diffusion Model` node has loaded `hunyuanvideo1.5_720p_t2v_fp16.safetensors`
3. Ensure the `Load VAE` node has loaded `hunyuanvideo15_vae_fp16.safetensors`
4. Click the `Queue` button or use the shortcut `Ctrl(Cmd) + Enter` to run the workflow

<Tip>
  The workflow includes a super-resolution upscaler node. When enabled, it uses `hunyuanvideo1.5_1080p_sr_distilled_fp16.safetensors` to upscale the output to 1080p.
</Tip>

## Hunyuan Video 1.5 Image-to-Video Workflow

HunyuanVideo 1.5 Image-to-Video transforms static images into smooth, high-quality videos with improved consistency and motion dynamics.

![ComfyUI Workflow - Hunyuan Video 1.5 I2V](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_hunyuan_video_1.5_720p_i2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_hunyuan_video_1.5_720p_i2v&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan-video-1-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_hunyuan_video_1.5_720p_i2v.json">
    Download JSON or search "Hunyuan Video 1.5 I2V" in Template Library
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_hunyuan_video_1.5_720p_i2v_input_image.png">
    Download the default input image, or use your own image as the starting frame.
  </Card>
</CardGroup>

### Model downloads

<CardGroup>
  <Card title="Download CLIP Vision" icon="download" href="https://huggingface.co/Comfy-Org/sigclip_vision_384/blob/main/sigclip_vision_patch14_384.safetensors?download=true">
    sigclip\_vision\_patch14\_384.safetensors — save to <code>ComfyUI/models/clip\_vision/</code>
  </Card>

  <Card title="Download I2V Diffusion Model" icon="download" href="https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/blob/main/split_files/diffusion_models/hunyuanvideo1.5_720p_i2v_fp16.safetensors?download=true">
    hunyuanvideo1.5\_720p\_i2v\_fp16.safetensors — save to <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 clip_vision/
│   │   └── sigclip_vision_patch14_384.safetensors          // I2V vision encoder
│   ├── 📂 text_encoders/
│   │   ├── qwen_2.5_vl_7b_fp8_scaled.safetensors           // Shared model
│   │   └── byt5_small_glyphxl_fp16.safetensors             // Shared model
│   ├── 📂 vae/
│   │   └── hunyuanvideo15_vae_fp16.safetensors             // Shared model
│   └── 📂 diffusion_models/
│       └── hunyuanvideo1.5_720p_i2v_fp16.safetensors       // I2V model
```

### Steps to run the workflow

1. Ensure the `DualCLIPLoader` node has loaded these models:
   * clip\_name1: `qwen_2.5_vl_7b_fp8_scaled.safetensors`
   * clip\_name2: `byt5_small_glyphxl_fp16.safetensors`
2. Ensure the `CLIPVisionLoader` node has loaded `sigclip_vision_patch14_384.safetensors`
3. Ensure the `Load Diffusion Model` node has loaded `hunyuanvideo1.5_720p_i2v_fp16.safetensors`
4. Ensure the `Load VAE` node has loaded `hunyuanvideo15_vae_fp16.safetensors`
5. Click the `Queue` button or use the shortcut `Ctrl(Cmd) + Enter` to run the workflow

## Super-resolution upscaler

Both workflows include a super-resolution node that can upscale the output video from 720p to 1080p. This optional upscaler uses a distilled model for efficient high-resolution output.

<Card title="Download 1080p Upscaler" icon="download" href="https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/blob/main/split_files/diffusion_models/hunyuanvideo1.5_1080p_sr_distilled_fp16.safetensors?download=true">
  hunyuanvideo1.5\_1080p\_sr\_distilled\_fp16.safetensors — save to <code>ComfyUI/models/diffusion\_models/</code>
</Card>

All shared and workflow-specific models combined:

```
ComfyUI/
├── 📂 models/
│   ├── 📂 clip_vision/
│   │   └── sigclip_vision_patch14_384.safetensors
│   ├── 📂 text_encoders/
│   │   ├── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   │   └── byt5_small_glyphxl_fp16.safetensors
│   ├── 📂 vae/
│   │   └── hunyuanvideo15_vae_fp16.safetensors
│   └── 📂 diffusion_models/
│       ├── hunyuanvideo1.5_720p_t2v_fp16.safetensors        // T2V model
│       ├── hunyuanvideo1.5_720p_i2v_fp16.safetensors        // I2V model
│       └── hunyuanvideo1.5_1080p_sr_distilled_fp16.safetensors  // Upscaler
```


# Kandinsky 5.0
Source: https://docs.comfy.org/tutorials/video/kandinsky/kandinsky-5

This guide shows how to use Kandinsky 5.0 video generation workflows in ComfyUI

[Kandinsky 5.0](https://huggingface.co/kandinskylab/Kandinsky-5.0-I2V-Lite-5s) is a family of diffusion models for video and image generation developed by [Kandinsky Lab](https://huggingface.co/kandinskylab). The Kandinsky 5.0 T2V Lite is a lightweight 2B parameter model that ranks among the top open-source video generation models, capable of generating videos up to 10 seconds long.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Overview

Kandinsky 5.0 uses a latent diffusion pipeline with Flow Matching and features:

* **Diffusion Transformer (DiT):** Main generative backbone with cross-attention to text embeddings
* **Qwen2.5-VL and CLIP:** Provides high-quality text embeddings
* **HunyuanVideo 3D VAE:** Encodes and decodes video into a latent space

The model family includes multiple variants optimized for different use cases:

* **SFT model:** Highest generation quality
* **CFG-distilled:** 2× faster inference
* **Diffusion-distilled:** 6× faster with minimal quality loss (16 steps)
* **Pretrain model:** Designed for fine-tuning

All models are available in 5-second and 10-second video generation versions.

## Model variants

| Model | Video Duration | NFE | Latency (H100) |
| - | - | - | - |
| Kandinsky 5.0 T2V Lite SFT | 5s / 10s | 100 | 139s / 224s |
| Kandinsky 5.0 T2V Lite no-CFG | 5s / 10s | 50 | 77s / 124s |
| Kandinsky 5.0 T2V Lite distill | 5s / 10s | 16 | 35s / 61s |
| Kandinsky 5.0 I2V Lite | 5s | 100 | 673s |

## Text-to-Video workflow

### Kandinsky 5.0 Video Lite Text to Video

A lightweight 2B model that generates videos from English and Russian prompts with high visual quality.

<img alt="Kandinsky 5.0 Video Lite Text to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_kandinsky5_t2v&utm_source=docs&utm_medium=referral&utm_campaign=kandinsky-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_kandinsky5_t2v.json">
    Download JSON or search "Kandinsky 5.0 Video Lite Text to Video" in Template Library
  </Card>
</CardGroup>

### 2. Manually download models

**Text Encoders**

<CardGroup>
  <Card title="Text Encoder: qwen_2.5_vl_7b_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/blob/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors">
    Qwen2.5-VL 7B text encoder (FP8). Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Text Encoder: clip_l.safetensors" icon="download" href="https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors">
    CLIP-L text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

**Diffusion Model**

<Card title="Diffusion Model: kandinsky5lite_t2v_sft_5s.safetensors" icon="download" href="https://huggingface.co/kandinskylab/Kandinsky-5.0-T2V-Lite-sft-5s/blob/main/model/kandinsky5lite_t2v_sft_5s.safetensors">
  Kandinsky 5.0 T2V Lite SFT diffusion model (5s). Place in <code>ComfyUI/models/diffusion\_models/</code>
</Card>

**VAE**

<Card title="VAE: hunyuan_video_vae_bf16.safetensors" icon="download" href="https://huggingface.co/Kijai/HunyuanVideo_comfy/blob/main/hunyuan_video_vae_bf16.safetensors">
  HunyuanVideo 3D VAE. Place in <code>ComfyUI/models/vae/</code>
</Card>

```
ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      ├── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   │      └── clip_l.safetensors
│   ├── 📂 diffusion_models/
│   │      └── kandinsky5lite_t2v_sft_5s.safetensors
│   └── 📂 vae/
│          └── hunyuan_video_vae_bf16.safetensors
```

## Image-to-Video workflow

### Kandinsky 5.0 Video Lite Image to Video

A lightweight 2B model that generates videos from English and Russian prompts with high visual quality.

<img alt="Kandinsky 5.0 Video Lite Image to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_kandinsky5_i2v&utm_source=docs&utm_medium=referral&utm_campaign=kandinsky-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_kandinsky5_i2v.json">
    Download JSON or search "Kandinsky 5.0 Video Lite Image to Video" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="crystal_flower.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/crystal_flower.png">
    `LoadImage` node 11 · `crystal_flower.png`
  </Card>
</CardGroup>

<div>
  <img alt="crystal_flower.png" />
</div>

### 2. Manually download models

**Text Encoders**

<CardGroup>
  <Card title="Text Encoder: qwen_2.5_vl_7b_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/blob/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors">
    Qwen2.5-VL 7B text encoder (FP8). Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Text Encoder: clip_l.safetensors" icon="download" href="https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors">
    CLIP-L text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

**Diffusion Model**

<Card title="Diffusion Model: kandinsky5lite_i2v_5s.safetensors" icon="download" href="https://huggingface.co/kandinskylab/Kandinsky-5.0-I2V-Lite-5s/blob/main/model/kandinsky5lite_i2v_5s.safetensors">
  Kandinsky 5.0 I2V Lite diffusion model (5s). Place in <code>ComfyUI/models/diffusion\_models/</code>
</Card>

**VAE**

<Card title="VAE: hunyuan_video_vae_bf16.safetensors" icon="download" href="https://huggingface.co/Kijai/HunyuanVideo_comfy/blob/main/hunyuan_video_vae_bf16.safetensors">
  HunyuanVideo 3D VAE. Place in <code>ComfyUI/models/vae/</code>
</Card>

```
ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      ├── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   │      └── clip_l.safetensors
│   ├── 📂 diffusion_models/
│   │      └── kandinsky5lite_i2v_5s.safetensors
│   └── 📂 vae/
│          └── hunyuan_video_vae_bf16.safetensors
```

## Resources

* [HuggingFace Model Collection](https://huggingface.co/collections/kandinskylab/kandinsky-50-video-lite)
* [GitHub Repository](https://github.com/ai-forever/Kandinsky-5)
* [ComfyUI Integration](https://github.com/ai-forever/Kandinsky-5/blob/main/comfyui/README.md)
* [Project Page](https://kandinskylab.github.io/kandinsky-5/)


# LTX-2.0 ComfyUI Workflow Examples
Source: https://docs.comfy.org/tutorials/video/ltx/ltx-2

Learn how to use LTX-2 in ComfyUI for synchronized audio-video generation

<iframe title="YouTube video player" />

[LTX-2](https://huggingface.co/Lightricks/LTX-2) is a 19B parameter DiT-based audio-video foundation model by Lightricks. It generates synchronized video and audio in a single pass, creating cohesive experiences where motion, dialogue, background noise, and music are produced together.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Key features

* **Synchronized audio-video generation**: Generates motion, dialogue, SFX, and music together in one pass
* **Multiple generation modes**: Text-to-video, image-to-video, and video-to-video
* **Control options**: Canny, Depth, and Pose video-to-video control via IC-LoRAs
* **Keyframe-driven generation**: Interpolate between keyframe images
* **Native upscaling**: Spatial (2x) and temporal (2x) upscalers for higher resolution and FPS
* **Prompt enhancement**: Automatic prompt enhancement support

## Model checkpoints

| Name | Description |
| - | - |
| ltx-2-19b-dev | Full model in bf16, flexible and trainable |
| ltx-2-19b-dev-fp8 | Full model in fp8 quantization |
| ltx-2-19b-distilled | Distilled version, 8 steps, CFG=1 |
| ltx-2-spatial-upscaler-x2-1.0 | 2x spatial upscaler for higher resolution |
| ltx-2-temporal-upscaler-x2-1.0 | 2x temporal upscaler for higher FPS |

## Getting started

LTX-2 is natively supported in ComfyUI. To get started:

1. Update ComfyUI to the latest version
2. Go to **Template Library** > **Video** > choose any LTX-2 workflow
3. Follow the pop-up to download models and run the workflow

## Workflows

### Text-to-video

Generate videos from text prompts.

![ComfyUI Workflow - LTX-2 T2V](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_ltx2_t2v-1.webp)

<CardGroup>
  <Card title="Text-to-Video" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_t2v.json">
    Download workflow
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_t2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2">
    Open in cloud
  </Card>
</CardGroup>

**Distilled version** (faster, 8 steps):

![ComfyUI Workflow - LTX-2 T2V Distilled](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_ltx2_t2v_distilled-1.webp)

<CardGroup>
  <Card title="Text-to-Video Distilled" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_t2v_distilled.json">
    Download workflow
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_t2v_distilled&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2">
    Open in cloud
  </Card>
</CardGroup>

### Image-to-video

Generate videos from an input image.

![ComfyUI Workflow - LTX-2 I2V](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_ltx2_i2v-1.webp)

<CardGroup>
  <Card title="Image-to-Video" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_i2v.json">
    Download workflow
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_i2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2">
    Open in cloud
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/freckled_curly_girl.png">
    Download the default input image, or use your own image.
  </Card>
</CardGroup>

**Distilled version** (faster, 8 steps):

![ComfyUI Workflow - LTX-2 I2V Distilled](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_ltx2_i2v_distilled-1.webp)

<CardGroup>
  <Card title="Image-to-Video Distilled" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_i2v_distilled.json">
    Download workflow
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_i2v_distilled&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2">
    Open in cloud
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/snow_bike_jump_crew.png">
    Download the default input image, or use your own image.
  </Card>
</CardGroup>

### Control-to-video

Generate videos with structural control using IC-LoRAs.

**Depth control:**

![ComfyUI Workflow - LTX-2 Depth to Video](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_ltx2_depth_to_video-1.webp)

<CardGroup>
  <Card title="Depth-to-Video" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_depth_to_video.json">
    Download workflow
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_depth_to_video&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2">
    Open in cloud
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/minimalist_sky_view_lounge.png">
    Download the default depth input image, or use your own.
  </Card>

  <Card title="Input Video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/minimalist_sky_view_lounge.mp4">
    Download the default input video, or use your own.
  </Card>
</CardGroup>

**Canny control:**

![ComfyUI Workflow - LTX-2 Canny to Video](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_ltx2_canny_to_video-1.webp)

<CardGroup>
  <Card title="Canny-to-Video" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_canny_to_video.json">
    Download workflow
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_canny_to_video&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2">
    Open in cloud
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/ltx_2_canny_1st_frame.png">
    Download the default canny input image, or use your own.
  </Card>

  <Card title="Input Video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/squirrel_in_flower_garden.mp4">
    Download the default input video, or use your own.
  </Card>
</CardGroup>

**Pose control:**

![ComfyUI Workflow - LTX-2 Pose to Video](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_ltx2_pose_to_video-1.webp)

<CardGroup>
  <Card title="Pose-to-Video" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_pose_to_video.json">
    Download workflow
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_pose_to_video&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2">
    Open in cloud
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/women_with_paper.png">
    Download the default pose input image, or use your own.
  </Card>

  <Card title="Input Video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/woman_with_paper.mp4">
    Download the default input video, or use your own.
  </Card>
</CardGroup>

## Prompting tips

When writing prompts for LTX-2, focus on detailed, chronological descriptions of actions and scenes. Include specific movements, appearances, camera angles, and environmental details in a single flowing paragraph. Start directly with the action and keep descriptions literal and precise.

Structure your prompts with:

* Main action in a single sentence
* Specific details about movements and gestures
* Character/object appearances
* Background and environment details
* Camera angles and movements
* Lighting and colors
* Any changes or sudden events

Keep prompts within 200 words for best results.

## Resources

* [GitHub Repository](https://github.com/Lightricks/LTX-2)
* [Hugging Face Model](https://huggingface.co/Lightricks/LTX-2)
* [LTX-2 Prompting Guide](https://ltx.video/blog/how-to-prompt-for-ltx-2)
* [ComfyUI-LTXVideo](https://github.com/Lightricks/ComfyUI-LTXVideo/)


# LTX-2.3: ComfyUI Workflow Examples
Source: https://docs.comfy.org/tutorials/video/ltx/ltx-2-3

Use LTX-2.3 in ComfyUI with native workflows for text-to-video, image-to-video, FLF2V, audio-driven video, IC-LoRA control, and ID-LoRA personalization.

[LTX-2.3](https://huggingface.co/Lightricks/LTX-2.3) is the latest evolution of Lightricks' open-source audio-video generation model, now natively supported in ComfyUI. Building on LTX-2, this release delivers major quality improvements across fine details, portrait video, audio quality, image-to-video consistency, prompt understanding, and text rendering.

ComfyUI ships with six native workflows for LTX-2.3, each designed for a specific generation mode:

* **Text-to-Video** (T2V): Generate videos from text prompts
* **Image-to-Video** (I2V): Generate videos from an input image
* **FLF2V**: Interpolate between a start and end image
* **Image-Audio-to-Video** (IA2V): Generate lip-synced videos from an image and audio
* **IC-LoRA Union Control**: Control video generation with depth, pose, or edge guidance
* **ID-LoRA**: Generate personalized videos with synchronized audio from a reference image and audio clip

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Key features

* **Finer details**: New latent space and updated VAE for sharper textures, cleaner edges, and more precise visuals
* **9:16 Portrait support**: Greatly improved quality for vertical portrait videos
* **Better audio**: Cleaner sound with reduced noise and enhanced dialogue
* **Improved image-to-video**: More consistent motion and fewer glitches
* **Smarter prompt understanding**: Improved text encoder for more accurate interpretation
* **Native ComfyUI support**: All workflows are built-in, no custom nodes required

## Getting started

LTX-2.3 is natively supported in ComfyUI. To get started:

1. Update ComfyUI to the latest version
2. Go to **Template Library** > **Video** > choose any LTX-2.3 workflow
3. Follow the pop-up to download models and run the workflow

## ComfyUI Native Workflows

### LTX-2.3 Text to Video (T2V)

Generate videos from text prompts with improved prompt understanding and text rendering.

<video />

### LTX-2.3 Text to Video

Generate videos from text prompts with improved prompt understanding and text rendering.

<img alt="LTX-2.3 Text to Video ( workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_3_t2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_3_t2v.json">
    Download JSON or search "LTX-2.3 T2V" in Template Library
  </Card>
</CardGroup>

#### Model downloads

<CardGroup>
  <Card title="Checkpoint: ltx-2.3-22b-dev-fp8" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3-fp8/blob/main/ltx-2.3-22b-dev-fp8.safetensors">
    Place in <code>ComfyUI/models/checkpoints/</code>
  </Card>

  <Card title="LoRA: distilled 1.1" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2.3/blob/main/split_files/loras/ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="LoRA: gemma abliterated" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2/blob/main/split_files/loras/gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="Text Encoder: gemma 12B" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2/blob/main/split_files/text_encoders/gemma_3_12B_it_fp4_mixed.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Upscaler: spatial x2" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-spatial-upscaler-x2-1.1.safetensors">
    Place in <code>ComfyUI/models/latent\_upscale\_models/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── ltx-2.3-22b-dev-fp8.safetensors
│   ├── 📂 loras/
│   │   ├── ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16.safetensors
│   │   └── gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors
│   ├── 📂 text_encoders/
│   │   └── gemma_3_12B_it_fp4_mixed.safetensors
│   └── 📂 latent_upscale_models/
│       └── ltx-2.3-spatial-upscaler-x2-1.1.safetensors
```

#### Prompting tips

1. **Core Actions**: Describe events and actions as they occur over time
2. **Visual Details**: Describe all visual details you want to appear in the video
3. **Audio**: Describe sounds and dialogue needed for the scene

***

### LTX-2.3 Image to Video (I2V)

Generate videos from an input image with more consistent motion and smoother animations.

<video />

### LTX-2.3 Image to Video

Generate videos from an input image with improved motion consistency.

<img alt="LTX-2.3 Image to Video ( workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_3_i2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_3_i2v.json">
    Download JSON or search "LTX-2.3 I2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Input Image: egyptian_queen.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/egyptian_queen.png">
    Download the default input image, or use your own image.
  </Card>
</CardGroup>

#### Model downloads

The I2V workflow uses the same model set as Text-to-Video.

<CardGroup>
  <Card title="Checkpoint: ltx-2.3-22b-dev-fp8" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3-fp8/blob/main/ltx-2.3-22b-dev-fp8.safetensors">
    Place in <code>ComfyUI/models/checkpoints/</code>
  </Card>

  <Card title="LoRA: distilled 1.1" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2.3/blob/main/split_files/loras/ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="LoRA: gemma abliterated" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2/blob/main/split_files/loras/gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="Text Encoder: gemma 12B" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2/blob/main/split_files/text_encoders/gemma_3_12B_it_fp4_mixed.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Upscaler: spatial x2" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-spatial-upscaler-x2-1.1.safetensors">
    Place in <code>ComfyUI/models/latent\_upscale\_models/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── ltx-2.3-22b-dev-fp8.safetensors
│   ├── 📂 loras/
│   │   ├── ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16.safetensors
│   │   └── gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors
│   ├── 📂 text_encoders/
│   │   └── gemma_3_12B_it_fp4_mixed.safetensors
│   └── 📂 latent_upscale_models/
│       └── ltx-2.3-spatial-upscaler-x2-1.1.safetensors
```

***

### LTX-2.3 FLF2V

Interpolate between a start image and an end image to generate a smooth video transition.

<video />

### LTX-2.3 First-Last Frame to Video

Interpolate between a start and end image.

<img alt="LTX-2.3 First-Last Frame to Video ( workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_3_flf2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_3_flf2v.json">
    Download JSON or search "LTX-2.3 FLF2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Start Image: high_view_classic_car.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/high_view_classic_car.png">
    First frame of the video.
  </Card>

  <Card title="End Image: low_view_classic_car.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/low_view_classic_car.png">
    Last frame of the video.
  </Card>
</CardGroup>

#### Model downloads

The FLF2V workflow uses the distilled checkpoint instead of the dev checkpoint.

<CardGroup>
  <Card title="Checkpoint: ltx-2.3-22b-distilled-fp8" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3-fp8/blob/main/ltx-2.3-22b-distilled-fp8.safetensors">
    Place in <code>ComfyUI/models/checkpoints/</code>
  </Card>

  <Card title="Text Encoder: gemma 12B" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2/blob/main/split_files/text_encoders/gemma_3_12B_it_fp4_mixed.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── ltx-2.3-22b-distilled-fp8.safetensors
│   └── 📂 text_encoders/
│       └── gemma_3_12B_it_fp4_mixed.safetensors
```

***

### LTX-2.3 Image Audio to Video (IA2V)

Upload an image and an audio file to generate a high-quality video with synchronized lip movements.

<video />

### LTX-2.3 Image and Audio to Video

Generate lip-synced videos from an image and audio.

<img alt="LTX-2.3 Image and Audio to Video ( workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_3_ia2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_3_ia2v.json">
    Download JSON or search "LTX-2.3 IA2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Input Image: cactus_man.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/cactus_man.png">
    Reference image for the speaking character.
  </Card>

  <Card title="Reference Audio: ltx_23_audio.mp3" icon="music" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/ltx_23_audio.mp3">
    Audio track for lip synchronization.
  </Card>
</CardGroup>

#### Model downloads

The IA2V workflow uses the same model set as Text-to-Video.

<CardGroup>
  <Card title="Checkpoint: ltx-2.3-22b-dev-fp8" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3-fp8/blob/main/ltx-2.3-22b-dev-fp8.safetensors">
    Place in <code>ComfyUI/models/checkpoints/</code>
  </Card>

  <Card title="LoRA: distilled 1.1" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2.3/blob/main/split_files/loras/ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="LoRA: gemma abliterated" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2/blob/main/split_files/loras/gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="Text Encoder: gemma 12B" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2/blob/main/split_files/text_encoders/gemma_3_12B_it_fp4_mixed.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Upscaler: spatial x2" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-spatial-upscaler-x2-1.1.safetensors">
    Place in <code>ComfyUI/models/latent\_upscale\_models/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── ltx-2.3-22b-dev-fp8.safetensors
│   ├── 📂 loras/
│   │   ├── ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16.safetensors
│   │   └── gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors
│   ├── 📂 text_encoders/
│   │   └── gemma_3_12B_it_fp4_mixed.safetensors
│   └── 📂 latent_upscale_models/
│       └── ltx-2.3-spatial-upscaler-x2-1.1.safetensors
```

***

### LTX-2.3 IC-LoRA Union Control

Generate LTX-2.3 videos with IC-LoRA using aligned control inputs like depth, pose, or edges. IC-LoRA is an in-context LoRA trained on top of LTX-2.3 that applies structural guidance from a reference video. It accepts control signals from various preprocessors including depth maps, Canny edges, and pose skeletons. This workflow uses a subgraph for modular processing.

![LTX-2.3 IC-LoRA preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_ltx2_3_ic_lora-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_3_ic_lora&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_3_ic_lora.json">
    Download JSON or search "LTX-2.3 IC-LoRA" in Template Library
  </Card>
</CardGroup>

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses a Subgraph node for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

**Input materials**

<CardGroup>
  <Card title="Control Video: stone_ruins.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/stone_ruins.mp4">
    Driving video for control signal extraction.
  </Card>

  <Card title="Reference Image: the_forgotten_gate.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/the_forgotten_gate.png">
    Reference image for style and content.
  </Card>
</CardGroup>

#### Model downloads

<CardGroup>
  <Card title="Checkpoint: ltx-2.3-22b-distilled-fp8" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3-fp8/blob/main/ltx-2.3-22b-distilled-fp8.safetensors">
    Place in <code>ComfyUI/models/checkpoints/</code>
  </Card>

  <Card title="LoRA: IC-LoRA Union Control" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Union-Control/blob/main/ltx-2.3-22b-ic-lora-union-control-ref0.5.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="LoRA: gemma abliterated" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2/blob/main/split_files/loras/gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="Text Encoder: gemma 12B" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2/blob/main/split_files/text_encoders/gemma_3_12B_it_fp4_mixed.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Geometry: MoGe Normal" icon="download" href="https://huggingface.co/Comfy-Org/MoGe/blob/main/geometry_estimation/moge_2_vitl_normal_fp16.safetensors">
    Place in <code>ComfyUI/models/geometry\_estimation/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── ltx-2.3-22b-distilled-fp8.safetensors
│   ├── 📂 loras/
│   │   ├── ltx-2.3-22b-ic-lora-union-control-ref0.5.safetensors
│   │   └── gemma-3-12b-it-abliterated_lora_rank64_bf16.safetensors
│   ├── 📂 text_encoders/
│   │   └── gemma_3_12B_it_fp4_mixed.safetensors
│   └── 📂 geometry_estimation/
│       └── moge_2_vitl_normal_fp16.safetensors
```

***

### Video editing with IC-LoRA

IC-LoRA weights are not limited to generation control. The Template Library includes ready-made LTX-2.3 IC-LoRA workflows for editing existing footage, and each one runs in Comfy Cloud or locally in ComfyUI. Community IC-LoRA checkpoints trained on top of LTX-2.3 (for example, the [LTX2.3-ICEdit-Insight](https://huggingface.co/joyfox/LTX2.3-ICEdit-Insight) family) are also compatible with the native LTX-2.3 model.

#### Remove Subtitles from Video

Remove subtitles, captions, watermarks, or other text overlays from a video:

<img alt="LTX-2.3 Remove Subtitles workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=template_ltx2_3_lora_remove_subtitles_from_video&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/template_ltx2_3_lora_remove_subtitles_from_video.json">
    Download JSON or search "Remove Subtitles" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/input_subtitles-2.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>

#### Remove Object from Video

Remove a specific object from the foreground of a video by describing it in the prompt:

<img alt="LTX-2.3 Remove Object workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=template_ltx2_3_obscura_remova_lora_remove_object_from_video&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/template_ltx2_3_obscura_remova_lora_remove_object_from_video.json">
    Download JSON or search "Remove Object" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/input_playing_the_piano.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>

#### Restore Archival Footage

Restore old or degraded archival footage:

<img alt="LTX-2.3 Restore Archival Footage workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=template_ltx2_3_lora_restore_archival_footage&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/template_ltx2_3_lora_restore_archival_footage.json">
    Download JSON or search "Restore Archival" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/input_dearchive.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>

#### Video Outpainting

Expand a video in any direction using the LTX-2.3 Video Outpainting IC-LoRA:

<img alt="LTX-2.3 Video Outpainting workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=template_ltx2_3_lora_video_outpainting&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/template_ltx2_3_lora_video_outpainting.json">
    Download JSON or search "Video Outpainting" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/ltx2.3_video_outpainting_input.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>

#### Googly Eyes

Apply the Googlyeyes LTX-2.3 LoRA to an input video to give everyone in the frame googly eyes:

<img alt="LTX-2.3 Googly Eyes workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=template_ltx2_3_lora_googly_eyes&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/template_ltx2_3_lora_googly_eyes.json">
    Download JSON or search "Googly Eyes" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/iclora_input_resized_purz.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>

For community IC-LoRAs, place the editing LoRA in `ComfyUI/models/loras/` and load it with a LoRA loader alongside the LTX-2.3 checkpoint, then run the workflow with your video as input and a prompt like:

```text theme={null}
Remove subtitles, captions, and related text occlusions from the video, restoring a clean and natural underlying image.
```

***

### LTX-2.3 ID-LoRA

Generate personalized videos with synchronized audio from a text prompt, reference image, and short audio clip. Uses ID-LoRA to adapt a person's appearance and voice in a single generative model.

<video />

### LTX-2.3 ID LoRA

Generate personalized videos with synchronized audio from a reference image and audio clip.

<img alt="LTX-2.3 ID LoRA ( workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_3_id_lora&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_3_id_lora.json">
    Download JSON or search "LTX-2.3 ID-LoRA" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Reference Image: vintage_thinker.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/vintage_thinker.png">
    Reference image for the character appearance.
  </Card>

  <Card title="Reference Audio: ltx23_reference_audio.mp3" icon="music" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/ltx23_reference_audio.mp3">
    Audio clip for voice cloning and lip sync.
  </Card>
</CardGroup>

#### Model downloads

<CardGroup>
  <Card title="Checkpoint: ltx-2.3-22b-dev-fp8" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3-fp8/blob/main/ltx-2.3-22b-dev-fp8.safetensors">
    Place in <code>ComfyUI/models/checkpoints/</code>
  </Card>

  <Card title="LoRA: distilled 1.1" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2.3/blob/main/split_files/loras/ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="LoRA: ID-LoRA TalkVid" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2.3/blob/main/split_files/loras/ltx-2.3-id-lora-talkvid-3k.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="Text Encoder: gemma 12B" icon="download" href="https://huggingface.co/Comfy-Org/ltx-2/blob/main/split_files/text_encoders/gemma_3_12B_it_fp4_mixed.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Upscaler: spatial x2" icon="download" href="https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-spatial-upscaler-x2-1.1.safetensors">
    Place in <code>ComfyUI/models/latent\_upscale\_models/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── ltx-2.3-22b-dev-fp8.safetensors
│   ├── 📂 loras/
│   │   ├── ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16.safetensors
│   │   └── ltx-2.3-id-lora-talkvid-3k.safetensors
│   ├── 📂 text_encoders/
│   │   └── gemma_3_12B_it_fp4_mixed.safetensors
│   └── 📂 latent_upscale_models/
│       └── ltx-2.3-spatial-upscaler-x2-1.1.safetensors
```

## Prompting tips

When writing prompts for LTX-2.3, focus on detailed, chronological descriptions of actions and scenes:

1. **Core Actions**: Describe events and actions as they occur over time
2. **Visual Details**: Describe all visual details you want to appear in the video
3. **Audio**: Describe sounds and dialogue needed for the scene

## Resources

* [Hugging Face Model](https://huggingface.co/Lightricks/LTX-2.3)
* [GitHub Repository](https://github.com/Lightricks/LTX-2)
* [ComfyUI-LTXVideo](https://github.com/Lightricks/ComfyUI-LTXVideo/)
* [IC-LoRA Model](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Union-Control)


# LTX-2.5: ComfyUI Workflow Examples
Source: https://docs.comfy.org/tutorials/video/ltx/ltx-2-5

Use LTX-2.5 in ComfyUI with native text-to-video, image-to-video, and first-last-frame workflows, including synchronized audio and native multishot scenes.

[LTX-2.5](https://huggingface.co/Lightricks/LTX-2.5) is Lightricks' open-weights video and world model, natively supported in ComfyUI. It builds on LTX-2.3 with a Diffusion Fidelity Rendering pipeline that allocates rendering compute by scene complexity. The model keeps the synchronized audio and video generation of LTX-2.3 and adds native multishot: one generation produces multiple connected shots that hold character, environment, lighting, and voice across cuts.

LTX-2.5 ships with a custom Gemma 4 12B text encoder that retains multiple subjects, actions, lighting, and camera direction across complex prompts, plus an optional prompt enhancer that expands short prompts into detailed instructions. Auto duration predicts the clip length from the described action before diffusion begins. The distilled model provides faster generation, and output supports native 4K HDR at up to 50 FPS with a RAW workflow for professional finishing pipelines.

ComfyUI ships with three native workflows for LTX-2.5:

* **Text-to-Video** (T2V): Generate videos from text prompts
* **Image-to-Video** (I2V): Generate videos from an input image
* **FLF2V**: Interpolate between a first and last frame image

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Key features

* **Diffusion Fidelity Rendering**: keyframes-first generation that builds every scene on a grid of high-fidelity keyframes
* **Diffusion Video Decoder**: sharper faces, legible text, and fewer smears in fast motion
* **Native multishot**: one generation yields multiple connected shots holding character, environment, lighting, voice, and style across cuts
* **Gemma 4 12B text encoder**: retains multiple subjects, actions, lighting, detail, and camera direction across complex prompts
* **Prompt enhancer** *(optional)*: a lightweight model that expands short prompts into detailed instructions
* **Auto duration**: predicts the right clip length from the described action before diffusion begins
* **Native 4K HDR**: high-resolution HDR output built for professional finishing, with synchronized audio-video at up to 50 FPS

## Getting started

LTX-2.5 is natively supported in ComfyUI. To get started:

1. Update ComfyUI to the latest version
2. Go to **Template Library** > **Video** > choose any LTX-2.5 workflow
3. Request access to the model repository on Hugging Face (see below), then follow the pop-up to download models and run the workflow

<Callout type="warning">
  The LTX-2.5 model files are hosted in the gated [Lightricks/LTX-2.5](https://huggingface.co/Lightricks/LTX-2.5) repository on Hugging Face. Open the repository page, accept the model license, and wait for your access request to be approved before downloading the models. Model downloads will fail without access.
</Callout>

## ComfyUI Native Workflows

### LTX-2.5 Text to Video (T2V)

Generate videos from text prompts with optional spatial upscaling for enhanced resolution.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_5_t2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_5_t2v.json">
    Download JSON or search "LTX-2.5 T2V" in Template Library
  </Card>
</CardGroup>

#### Model downloads

<CardGroup>
  <Card title="Diffusion Model: ltx-2.5-22b-distilled-transformer-comfy-int8-convrot" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/diffusion_models/ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors">
    Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="Text Encoder: gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/text_encoders/gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Text Encoder: gemma4_e2b_it_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/gemma-4/blob/main/text_encoders/gemma4_e2b_it_int8_convrot.safetensors">
    Optional: only needed when the prompt enhancer is enabled. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="VAE: ltx-2.5-video-vae-bf16" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/vae/ltx-2.5-video-vae-bf16.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="VAE: ltx-2.5-audio-vae-bf16" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/vae/ltx-2.5-audio-vae-bf16.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="Upscaler: ltx-2.5-latent-spatial-upscaler-x2-bf16-1.0" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/latent_upscale_models/ltx-2.5-latent-spatial-upscaler-x2-bf16-1.0.safetensors">
    Place in <code>ComfyUI/models/latent\_upscale\_models/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors
│   ├── 📂 text_encoders/
│   │   ├── gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors
│   │   └── gemma4_e2b_it_int8_convrot.safetensors (optional)
│   ├── 📂 vae/
│   │   ├── ltx-2.5-video-vae-bf16.safetensors
│   │   └── ltx-2.5-audio-vae-bf16.safetensors
│   └── 📂 latent_upscale_models/
│       └── ltx-2.5-latent-spatial-upscaler-x2-bf16-1.0.safetensors
```

#### Prompting tips

1. **Describe the whole scene**: Include the shot type, scene, action, characters, and camera movement in one flowing paragraph
2. **Audio**: Describe sounds and dialogue needed for the scene; the model generates synchronized audio together with the video
3. **Use the prompt enhancer (optional)**: The workflow keeps it off by default. Enable `prompt_enhance` on the LTX-2.5 node to expand short prompts into detailed cinematic instructions. It needs the separate enhancer model (\~5 GB) and adds about 1-2 minutes of generation time

***

### LTX-2.5 Image to Video (I2V)

Generate videos from an input image, with the model animating the scene from the provided first frame.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_5_i2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_5_i2v.json">
    Download JSON or search "LTX-2.5 I2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Input Image: neon_cyborg_portrait.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/neon_cyborg_portrait.png">
    Download the default input image, or use your own image.
  </Card>
</CardGroup>

#### Model downloads

The I2V workflow uses the same model set as Text-to-Video.

<CardGroup>
  <Card title="Diffusion Model: ltx-2.5-22b-distilled-transformer-comfy-int8-convrot" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/diffusion_models/ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors">
    Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="Text Encoder: gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/text_encoders/gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Text Encoder: gemma4_e2b_it_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/gemma-4/blob/main/text_encoders/gemma4_e2b_it_int8_convrot.safetensors">
    Optional: only needed when the prompt enhancer is enabled. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="VAE: ltx-2.5-video-vae-bf16" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/vae/ltx-2.5-video-vae-bf16.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="VAE: ltx-2.5-audio-vae-bf16" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/vae/ltx-2.5-audio-vae-bf16.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="Upscaler: ltx-2.5-latent-spatial-upscaler-x2-bf16-1.0" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/latent_upscale_models/ltx-2.5-latent-spatial-upscaler-x2-bf16-1.0.safetensors">
    Place in <code>ComfyUI/models/latent\_upscale\_models/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors
│   ├── 📂 text_encoders/
│   │   ├── gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors
│   │   └── gemma4_e2b_it_int8_convrot.safetensors (optional)
│   ├── 📂 vae/
│   │   ├── ltx-2.5-video-vae-bf16.safetensors
│   │   └── ltx-2.5-audio-vae-bf16.safetensors
│   └── 📂 latent_upscale_models/
│       └── ltx-2.5-latent-spatial-upscaler-x2-bf16-1.0.safetensors
```

#### Prompting tips

1. **Describe what happens next**: Write the motion, camera movement, and sounds that follow from the input image; do not re-describe what is already visible
2. **Anchor the first frame**: Use phrasing like "Use the provided start image as the first frame" when writing a continuation
3. **Audio**: Describe dialogue and sounds for the scene; the model generates synchronized audio

***

### LTX-2.5 FLF2V

Generate a video between a first and last frame image, blending both frames into a single animated sequence.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_5_flf2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_ltx2_5_flf2v.json">
    Download JSON or search "LTX-2.5 FLF2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="First Frame: robot_hand_back.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/robot_hand_back.png">
    First frame of the video.
  </Card>

  <Card title="Last Frame: robot_hand_energy.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/robot_hand_energy.png">
    Last frame of the video.
  </Card>
</CardGroup>

#### Model downloads

The FLF2V workflow uses the same model set as Text-to-Video, without the spatial upscaler.

<CardGroup>
  <Card title="Diffusion Model: ltx-2.5-22b-distilled-transformer-comfy-int8-convrot" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/diffusion_models/ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors">
    Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="Text Encoder: gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/text_encoders/gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Text Encoder: gemma4_e2b_it_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/gemma-4/blob/main/text_encoders/gemma4_e2b_it_int8_convrot.safetensors">
    Optional: only needed when the prompt enhancer is enabled. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="VAE: ltx-2.5-video-vae-bf16" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/vae/ltx-2.5-video-vae-bf16.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="VAE: ltx-2.5-audio-vae-bf16" icon="download" href="https://huggingface.co/Lightricks/LTX-2.5/blob/main/vae/ltx-2.5-audio-vae-bf16.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>
</CardGroup>

#### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors
│   ├── 📂 text_encoders/
│   │   ├── gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors
│   │   └── gemma4_e2b_it_int8_convrot.safetensors (optional)
│   └── 📂 vae/
│       ├── ltx-2.5-video-vae-bf16.safetensors
│       └── ltx-2.5-audio-vae-bf16.safetensors
```

#### Prompting tips

1. **Describe the transition**: Write what happens between the two frames, including camera movement and audio
2. **Keep frames aligned**: Use images with the same aspect ratio for a smooth interpolation
3. **Audio**: Describe dialogue and sounds for the scene; the model generates synchronized audio

## Resources

* [Hugging Face Model](https://huggingface.co/Lightricks/LTX-2.5)
* [LTX Model Page](https://ltx.io/model/ltx-2-5)
* [GitHub Repository](https://github.com/Lightricks/LTX-Video)
* [ComfyUI-LTXVideo](https://github.com/Lightricks/ComfyUI-LTXVideo/)


# LTX-0.9.5 ComfyUI Workflow Examples
Source: https://docs.comfy.org/tutorials/video/ltxv

Learn how to use LTX-Video 0.9.5 in ComfyUI for efficient video generation

[LTX-Video](https://huggingface.co/Lightricks/LTX-Video) is a very efficient video model by lightricks. The important thing with this model is to give it long descriptive prompts.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Multi Frame Control

Allows you to control the video with a series of images. You can download the input images: [starting frame](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/ltxv/multi-frame/house1.png) and [ending frame](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/ltxv/multi-frame/house2.png).

<img alt="LTX-Video Multi Frame Control" />

<Tip>
  Drag the video directly into ComfyUI to run the workflow.
</Tip>

## Image to Video

### LTXV Image to Video

Generate videos from still images.

<img alt="LTXV Image to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=ltxv_image_to_video&utm_source=docs&utm_medium=referral&utm_campaign=ltxv">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/ltxv_image_to_video.json">
    Download JSON or search "LTXV Image to Video" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="ltxv_image_to_video_input_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/ltxv_image_to_video_input_image.jpg">
    `LoadImage` node 78 · `ltxv_image_to_video_input_image.jpg`
  </Card>
</CardGroup>

<div>
  <img alt="ltxv_image_to_video_input_image.jpg" />
</div>

<Tip>
  Drag the video directly into ComfyUI to run the workflow.
</Tip>

## Text to Video

### LTXV Text to Video

Generate videos from text prompts.

<img alt="LTXV Text to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=ltxv_text_to_video&utm_source=docs&utm_medium=referral&utm_campaign=ltxv">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/ltxv_text_to_video.json">
    Download JSON or search "LTXV Text to Video" in Template Library
  </Card>
</CardGroup>

<Tip>
  Drag the video directly into ComfyUI to run the workflow.
</Tip>

## Requirements

Download the following models and place them in the locations specified below:

<CardGroup>
  <Card title="ltx-video-2b-v0.9.5.safetensors" icon="download" href="https://huggingface.co/Lightricks/LTX-Video/blob/main/ltx-video-2b-v0.9.5.safetensors">
    Download and place in ComfyUI/models/checkpoints/
  </Card>

  <Card title="t5xxl_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/mochi_preview_repackaged/blob/main/split_files/text_encoders/t5xxl_fp16.safetensors">
    Download and place in ComfyUI/models/text\_encoders/
  </Card>
</CardGroup>

```
├── checkpoints/
│   └── ltx-video-2b-v0.9.5.safetensors
└── text_encoders/
    └── t5xxl_fp16.safetensors
```


# ComfyUI MiniMax H3 Video Generation Guide
Source: https://docs.comfy.org/tutorials/video/minimax/minimax-h3

How to use open-weights MiniMax H3 in ComfyUI: text-to-video, image-to-video, and reference-to-video workflows with native stereo audio, prompt writing tips, and Sage Attention speedups.

[MiniMax H3](https://www.minimax.io/blog/minimax-h3) is MiniMax's general-purpose, omni-modal generation model, now available as open weights. It jointly understands text, images, video, and audio in a single context, and generates video with **native stereo audio**: voice, sound effects, and music are modeled together in a single forward pass instead of being layered on afterward. The open weights generate at a 768-pixel short edge (about 1 megapixel) at 24fps for about 15 seconds. 2K output comes from MiniMax's hosted service and needs a separate upscale pass in ComfyUI.

ComfyUI natively supports MiniMax H3. The documentation is split across six pages:

* **Overview** (this page): model capabilities, workflow index, output resolution, step count, sampler and scheduler, and speedups
* **[Native workflows](/tutorials/video/minimax/minimax-h3-native)**: Text-to-Video, Image-to-Video, Reference-to-Video, plus advanced native-node techniques
* **[Multiframe Reference](/tutorials/video/minimax/minimax-h3-multiframe)**: anchor reference frames at specific points along the output timeline
* **[Fun ControlNet Union](/tutorials/video/minimax/minimax-h3-fun-controlnet)**: drive H3 with a control video, or run video inpainting with a mask
* **[Prompt guide](/tutorials/video/minimax/minimax-h3-prompt-guide)**: official MiniMax prompt writing guides, general tips, and prompt embeddings
* **[FastH3](/tutorials/video/minimax/minimax-h3-fastvideo)**: the FastVideo FastH3 checkpoints and their sparse-attention workflow

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<Note>
  H3's open weights let you run the model locally. Commercial use of locally generated outputs requires a [MiniMax commercial license](https://comfy.org/minimax/license), available through Comfy, the only official reseller. Generations on Comfy Cloud already include commercial rights.
</Note>

## Key features

* **Native stereo audio**: Dialogue, sound effects, and music are generated together with the video, synced in one MP4
* **Multimodal context**: Text, images, video, and audio references can be combined in one generation
* **Reference-driven generation**: Lock a character's identity, a style, a motion, a camera move, or a voice from reference materials
* **Instruction following**: Describe the relationship between references and the target shot in natural language
* **Accurate text rendering**: Spelled-out text and brand elements render cleanly
* **Open weights**: Run locally in ComfyUI with full control over every parameter

## Getting started

MiniMax H3 is supported in ComfyUI with open weights. To get started:

1. Update ComfyUI. The base Text to Video, Image to Video, and Reference to Video templates need 0.30.0 or later. Multiframe Reference needs 0.34.0. Fun ControlNet Union, the sparse attention node, and the Model Attention Backend node need 0.35.0, and FastH3 needs 0.36.0
2. Go to **Template Library** > **Video** > choose any MiniMax H3 workflow
3. Follow the pop-up to download models and run the workflow. The download is tens of gigabytes depending on the template, so allow disk space and time.

The model files are hosted on Hugging Face in the [Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3) repository.

<Note>
  Match an H3 LoRA to the checkpoint build it was distilled on, and take the `pruned` build when a repository publishes both. Pruned checkpoints replace the time embedder and the full-width adaln weights with a short shared curve basis (`adaln_t_table`, 1025 curve samples by 8 basis columns) that ComfyUI reads from the checkpoint itself, and the templates load the pruned builds (`minimax_h3_fl2va_pruned_int8_convrot.safetensors` and `minimax_h3_ref2va_pruned_int8_convrot.safetensors`, with bf16 and fp8 counterparts). A LoRA distilled on the full build (`minimax_h3_fl2va_int8_convrot.safetensors` or `minimax_h3_ref2va_int8_convrot.safetensors`) carries adaln weights with no matching tensor in the pruned build: ComfyUI reports a shape mismatch for them and does not merge them, so that part of the LoRA is skipped. The turbo LoRAs the workflows download carry no adaln tensors, so they load on either build.
</Note>

## Workflow index

The template library currently ships with six example workflows. They are example templates, not an exhaustive list: the model supports more generation modes through the native MiniMax H3 nodes, and you can build additional workflows with them. The library also includes a continuation variant of the Image to Video template (`video_minimax_h3_i2v_continuation`).

<CardGroup>
  <Card title="Text to Video (T2V)" icon="type" href="/tutorials/video/minimax/minimax-h3-native#minimax-h3-text-to-video-t2v">
    Generate videos from text prompts with native stereo audio
  </Card>

  <Card title="Image to Video (I2V)" icon="image" href="/tutorials/video/minimax/minimax-h3-native#minimax-h3-image-to-video-i2v">
    Generate videos from an input image, with optional first/last-frame control
  </Card>

  <Card title="Reference to Video (R2V)" icon="link" href="/tutorials/video/minimax/minimax-h3-native#minimax-h3-reference-to-video-r2v">
    Lock in a character, style, motion, camera move, or voice from reference images, videos, and audio
  </Card>

  <Card title="Multiframe Reference" icon="film" href="/tutorials/video/minimax/minimax-h3-multiframe">
    Anchor reference frames at specific points along the output timeline with chained Add Guide nodes
  </Card>

  <Card title="Fun ControlNet Union" icon="person" href="/tutorials/video/minimax/minimax-h3-fun-controlnet">
    Drive H3 with a Canny, Depth, HED, MLSD, or Pose control video, or run video inpainting with a mask
  </Card>
</CardGroup>

Underlying node modes: the **MiniMax H3 Image to Video** node covers text-to-video and first/last-frame image-to-video (t2va and fl2va), and the **MiniMax H3 Reference to Video** node covers reference-driven generation with images, videos, and audio (ref2va).

For prompt writing resources (official MiniMax guides, general tips, and prompt embeddings), see the [prompt guide](/tutorials/video/minimax/minimax-h3-prompt-guide).

## Setting the output resolution

Each workflow uses a **Resolution Selector** node to control the overall output size. The node computes `width` and `height` from three settings, and its outputs connect directly to the `width` and `height` inputs of the MiniMax H3 node:

* **Aspect ratio**: Pick a preset such as `16:9 (Widescreen)`, `9:16 (Portrait Widescreen)`, or `1:1 (Square)`
* **Megapixels**: Target total pixel count for the output. Higher values give larger frames; lower values run faster
* **Multiple**: The computed resolution is rounded to the nearest multiple of this number. Keep it at `32` to match H3's resolution grid

The template ships with a fast preview size. For full-quality output at 16:9, set the Resolution Selector's Megapixels to `0.98` for H3's native canvas (a 768px short edge, 1344x768 at 16:9), or enter `1344 x 768` directly in the MiniMax H3 node's `width` and `height` inputs (its default). Skip the `1.0` Megapixel step: it yields 1376x768, above the model's 768x1344 pixel area cap.

Frames well above the native canvas do not hold detail: H3 is trained at around 1 megapixel, and a later upscaling pass cannot recover what the generation step left out. For 2K output, generate at the native canvas and upscale in a separate pass.

## Step count

These numbers apply to the base weights with the template's **Enable Lightning LoRA** switch off, which is the default and runs 20 steps. Turning that switch on loads the turbo LoRA and drops the step count to 8 in the Text to Video and Image to Video templates (including the continuation variant), and to 4 in the templates that ship the reference turbo LoRA: Reference to Video, Multiframe Reference, and Fun ControlNet Union. In the Text to Video and Image to Video templates the switch appears as the `turbo_mode` widget on the subgraph node.

A short schedule costs the most on reference-driven shots. Reference tokens ride along every sampling step, so turning the switch on leaves far fewer steps for that conditioning to act on: at 4 steps a reference can end up barely applied, and a subject's pose or face angle can drift away from the reference as the clip goes on. When a shot has to follow a reference closely, leave the **Enable Lightning LoRA** switch off and run the base 20-step schedule; if the reference still drifts, raise the step count to 25.

The step count a shot needs depends on what the shot contains:

* Shots with simple content hold up at 12 to 16 steps
* Shots with high-frequency detail (chainmail, filigree or floral patterns, piles of small objects) keep improving up to about 50 steps. Below that range, those areas show unstable triangular grid artifacts that swim under motion, and distilled step-reduction LoRAs and turbo checkpoints surface them first
* Higher counts also improve prompt adherence and motion, with most of the gain by step 16. Beyond about 50 the difference is hard to see
* Steps do not add sharpness the native canvas cannot resolve, so a soft frame is a resolution problem first

Audio settles later than the picture does. Video and audio are denoised together in one pass, so one schedule drives both, and the audio track keeps improving at step counts where the picture has stopped changing. Speech and voice timbre converge last: at 8 steps they are the weakest part of the output, and 12 steps and above keep the track usable.

## Sampler and scheduler

Every local MiniMax H3 workflow samples with `res_multistep` and the `simple` scheduler. The Text to Video, Image to Video, and FastH3 templates keep those two nodes inside the workflow's subgraph, so open the subgraph to reach them. In the Reference to Video, Multiframe Reference, and Fun ControlNet Union templates, `KSamplerSelect` and `BasicScheduler` sit on the top-level canvas.

`res_multistep` is a second-order multistep sampler: each step reuses the denoised estimate from the step before it. The first step has no previous estimate to reuse, so it runs as an ordinary first-order (Euler) step, and the second-order steps begin with the second step. `er_sde` builds up its order in the same way, running one stage on its first step, two on the second, and, at its default `max_stage` of 3, all three stages from the third step on.

Multistep history lives inside a single sampling run rather than in the latent, so a workflow that splits the schedule across two samplers does not carry it over. In a two-sampler setup, such as a base stage followed by a second sampler after a latent upscale, the second sampler starts from an empty history: its first step runs at first order, and the second-order update resumes from its second step. A short tail is where that shows, because one of its few steps is spent at lower order. Keep the whole schedule in one sampling run, or give the second sampler enough steps to rebuild its history.

The flow-shift pair comes from the model definition rather than the workflow: ComfyUI's H3 definition carries `shift` `12` and `audio_shift` `3`, and every workflow except FastH3 reads those values, so no shift node appears in them. The FastH3 templates instead ship the built-in **ModelSamplingMiniMaxH3** node (`MiniMaxH3SigmaShift` in the workflow JSON, category `model/patch/minimax`), set to `shift_video` `10` and `shift_audio` `3`, the pair its distilled schedule is built around. The video shift drives the sampler's sigma schedule, and the model inverts the video schedule onto the shared base grid to derive the audio schedule from it. Add the node when a checkpoint calls for a different pair, and stay near the values that checkpoint is built for: on the distilled 8-step builds, sampling at `shift_video` `3` instead of `10` shows grid artifacts in the frames.

## Speeding up generation with Sage Attention

The example workflows use the standard attention implementation. You can roughly double the generation speed with [Sage Attention](https://github.com/woct0rdho/SageAttention), with minimal quality loss. Sage Attention is an optional dependency, so you need to install it yourself:

1. Install the `sageattention` Python package. Download the wheel that matches your PyTorch and CUDA versions from the [SageAttention releases](https://github.com/woct0rdho/SageAttention/releases) page, then install it with `pip install <wheel-file>`.
2. Install the [KJNodes custom nodes](https://github.com/kijai/ComfyUI-KJNodes), which provide the `Patch Sage Attention KJ` node. Use the ComfyUI Manager, or clone the repository into `ComfyUI/custom_nodes/` and restart ComfyUI.
3. Add a `Patch Sage Attention KJ` node to the workflow and connect it between the `UNETLoader` and the `BasicGuider` node: its `model` input receives the model from the `UNETLoader`, and its `model` output feeds the `model` input of the `BasicGuider`. Set `sage_attention` to `auto`.
4. Run the workflow as usual. Only the guider needs the patch; the scheduler only generates the sigmas and can stay as is.

Notes:

* Sage Attention requires float16 or bfloat16 tensors. MiniMax H3 runs some layers in other dtypes, so you may see "Input tensors must be in dtype of torch.float16 or torch.bfloat16, using pytorch attention instead" messages in the console. These are expected; the affected layers fall back to standard attention and generation still works.
* Alternatively, you can enable Sage Attention globally by launching ComfyUI with the `--use-sage-attention` flag instead of adding the node.

### Quality degradation with INT8 attention

If you see morphing near the end of a clip or garbled on-screen text while using Sage Attention, the INT8 attention quantization is the likely cause. H3's last blocks concentrate most of their attention-key signal into a few channels, and INT8 kernels that round each row with a single shared scale lose part of that signal.

Which fix applies depends on the checkpoint the workflow loads:

* **The templates ship int8-convrot checkpoints**: `minimax_h3_fl2va_pruned_int8_convrot.safetensors` for T2V, I2V, and the Image to Video continuation variant, and `minimax_h3_ref2va_pruned_int8_convrot.safetensors` for R2V, Multiframe Reference, and Fun ControlNet Union. **Comfy Kitchen attention does not support these checkpoints** and sampling crashes with an alignment error ([ComfyUI issue #15529](https://github.com/Comfy-Org/ComfyUI/issues/15529)). Keep the default attention with them, or load the bf16 counterpart in the `UNETLoader` (`minimax_h3_fl2va_pruned_bf16.safetensors` or `minimax_h3_ref2va_pruned_bf16.safetensors`, which needs more VRAM) and then change the backend below.
* **With the bf16 checkpoints, switching the dense attention backend to Comfy Kitchen attention clears the artifacts.** Its INT8 kernel applies a channel rotation before quantizing, which preserves that signal at a similar speed to Sage Attention.

To switch backends, add the built-in **Model Attention Backend** node (category `model/patch`) and set its backend to `comfy kitchen attention`. Connect it where the model reaches the `BasicGuider`, that is after the `LoraLoaderModelOnly` node and its Enable Lightning LoRA switch. Alternatively, launch ComfyUI with the `--use-ck-attention` flag (ComfyUI 0.32.0 or later). The backend is provided by the `comfy-kitchen` package that ships with ComfyUI, and it only appears in the node's backend list when the INT8 kernels are available on your hardware.

## Speeding up generation with sparse attention

Attention cost grows quickly with clip length. ComfyUI's built-in **Model Sparse Attention** node (category `model/patch`, experimental, ComfyUI 0.35.0 or later) runs block-sparse attention on eligible layers to cut that cost, and the gain grows with sequence length. Set its `method` to `sol-attn`, the mode the base H3 weights use (`sla` and `vsa` expect weights trained for those patterns). The sparse path needs CUDA and the `sol_attn` kernel from `comfy-kitchen`; without them every layer silently falls back to dense attention and you see no speedup.

* **Keep sparse attention out of the first and last steps.** The defaults are `start_percent` `0.2` and `end_percent` `1.0`, so sparsity runs from 20% of the schedule through the final step. Starting later (around `0.4`) and ending earlier (around `0.9`) keeps the opening motion and the closing frames dense, at a modest cost in speed.
* **Leave `sink_conditioning` at its default** (`exact_kv_and_rows`) on H3. It keeps the packed text, audio, and reference rows exact and the generated audio query rows dense, so the sparse path does not degrade the audio track.
* **`tau` controls how sparse `sol-attn` is**: `1.0` keeps roughly 16% of key blocks exact, `1.5` about 7%, and `2.0` about 2.7%. The default is `1.3`, and higher values are faster but riskier.
* **Short clips gain little.** Sequences below `min_tokens` (default `12288`) and blocks listed in `dense_blocks` stay dense.

FastH3 checkpoints use the same node in `vsa` mode, which is trained for its sparse pattern at `keep_percent` `10`. See the [FastH3 workflow page](/tutorials/video/minimax/minimax-h3-fastvideo) for details.


# FastVideo FastH3: ComfyUI Workflow Examples
Source: https://docs.comfy.org/tutorials/video/minimax/minimax-h3-fastvideo

FastVideo FastH3 generates MiniMax H3 video with synchronized audio in 8 sampling steps in ComfyUI, for text-to-video and first/last-frame workflows.

[FastVideo FastH3](https://huggingface.co/FastVideo/FastVideo-FastH3-8-Step-V2) is a DMD2-distilled MiniMax H3 checkpoint from the FastVideo team that generates video with synchronized native audio in **8 sampling steps** instead of the base model's full schedule. It reuses the H3 text encoder, video VAE, and audio VAE, so output matches the base model's setup while sampling finishes in a fraction of the steps.

The FastH3 preview work was developed in collaboration with Nuva Lab and the NVIDIA FastGen team; read the [FastH3 announcement](https://haoailab.com/blogs/fasth3-preview/) for distillation details. ComfyUI ships with the 8-step V2 checkpoint, repacked by Comfy-Org in the [FastVideo-FastH3-Comfy](https://huggingface.co/FastVideo/FastVideo-FastH3-Comfy) repository.

FastH3 trades some motion and audio fidelity for speed. Use it for drafts, iteration, and fast turnaround; use the base MiniMax H3 workflows when maximum quality matters.

<UpdateReminder />

<Note>
  The distilled checkpoint supports text-to-video and first/last-frame image-to-video only. Ref2VA (multi-reference conditioning) was not distilled; use the base [MiniMax H3 workflows](/tutorials/video/minimax/minimax-h3-native) for reference-based generation.
</Note>

## Requirements

* ComfyUI 0.36.0 or later
* The MiniMax H3 text encoder and VAEs (shared with the base model, listed below)

## FastH3 Text to Video

Generate synchronized video and audio from a text prompt in 8 steps.

<video />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_fastvideo_fasth3_t2v.json">
    Download JSON or search "FastVideo FastH3: Text to Video" in Template Library
  </Card>
</CardGroup>

### Prompting tips

1. **Describe the whole scene**: State the overall scene first (location, character, what is happening), then break it into timed shots
2. **Shots, camera, and audio**: Describe the shots, camera moves, and the accompanying audio (dialogue, SFX, music) in one prompt block
3. **Resolution**: H3's native canvas is a 768px short edge, capped at 768x1344, and resolutions are rounded to a multiple of 32
4. **Duration**: The duration input snaps to the model's 17-frame-per-block (17k+5) grid at 24fps
5. **Steps are fixed at 8**: The distilled checkpoint is trained for exactly 8 steps; changing the step count in the scheduler degrades quality

For prompt writing resources, see the [prompt guide](/tutorials/video/minimax/minimax-h3-prompt-guide).

## FastH3 Image to Video

Animate a still image with synchronized audio, with optional first/last-frame control.

<video />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_fastvideo_fasth3_i2v.json">
    Download JSON or search "FastVideo FastH3: Image to Video" in Template Library
  </Card>
</CardGroup>

**Input material**

Upload this file to the matching `LoadImage` node, or use your own image:

<CardGroup>
  <Card title="red_line_barrier.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/red_line_barrier.png">
    Example first frame for the Image to Video workflow
  </Card>
</CardGroup>

### First/last-frame mode

Connect images to `first_frame` and/or `last_frame` on the `MiniMaxH3ImageToVideo` node to generate the motion between two keyframes. Leave both disconnected for text-to-video.

### Prompting tips

1. **Describe the motion and audio**: With an image providing the look, the prompt should focus on motion, camera, and the accompanying audio
2. **Duration**: The duration input snaps to the model's 17-frame-per-block (17k+5) grid at 24fps
3. **Steps are fixed at 8**: Keep the scheduler at 8 steps; the checkpoint is distilled for that schedule

## Model downloads

The diffusion model comes from the FastVideo repository; the text encoder and VAEs are shared with the base MiniMax H3 model.

<CardGroup>
  <Card title="Diffusion Model: fastvideo_fasth3_8step_v2_pruned_int8_convrot" icon="download" href="https://huggingface.co/FastVideo/FastVideo-FastH3-Comfy/resolve/main/diffusion_models/fastvideo_fasth3_8step_v2_pruned_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="Text Encoder: qwen3vl_32b_minimax_h3_nvfp4_awq" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/text_encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="VAE: minimax_h3_video_vae_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_video_vae_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="VAE: minimax_h3_audio_vae_fp32" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_audio_vae_fp32.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>
</CardGroup>

### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── fastvideo_fasth3_8step_v2_pruned_int8_convrot.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors
│   └── 📂 vae/
│       ├── minimax_h3_video_vae_int8_convrot.safetensors
│       └── minimax_h3_audio_vae_fp32.safetensors
```

## Workflow structure notes

Both FastH3 workflows share these nodes with the base H3 setup, with distillation-specific settings:

* **BlockSparseAttention**: Runs Video Sparse Attention (VSA) with `keep_percent` 10 starting at 20% of the schedule, reducing attention cost while preserving quality
* **MiniMaxH3SigmaShift**: Applies the H3 sigma shift (10 for video, 3 for audio) that matches the distilled schedule
* **ComfyMathExpression**: Converts the duration input into a valid frame `length` on the 17k+5 grid at 24fps
* **Sampler**: `res_multistep` sampler with the `simple` scheduler at 8 steps


# ComfyUI MiniMax H3 Fun ControlNet Union: Pose, Depth, and Canny Control Video
Source: https://docs.comfy.org/tutorials/video/minimax/minimax-h3-fun-controlnet

Guide MiniMax H3 video motion in ComfyUI with Canny, Depth, HED, MLSD, or Pose control videos, plus mask-based inpainting with the Fun ControlNet Union patch.

Control the motion of a MiniMax H3 video with a control video instead of text alone. The Fun ControlNet Union patch ([alibaba-pai/MiniMax-H3-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/MiniMax-H3-Fun-Controlnet-Union), packaged in [Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3)) is a single checkpoint that conditions H3 on Canny, Depth, HED, MLSD, or Pose control videos, and also runs video inpainting with a mask. It works with both the `fl2va` and `ref2va` transformer files.

![MiniMax H3 Fun ControlNet Union workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_minimax_h3_fun_controlnet_union-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_minimax_h3_fun_controlnet_union&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_minimax_h3_fun_controlnet_union.json">
    Download JSON or search "MiniMax H3 Fun ControlNet Union" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `Load Video` node:

<CardGroup>
  <Card title="dancer_field_pose.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/dancer_field_pose.mp4">
    Pose control video used by the example workflow, or use your own.
  </Card>
</CardGroup>

This template requires ComfyUI 0.35.0 or later. The example uses a pose control video: a built-in SDPose subgraph extracts the pose skeleton from the input video, so the output reproduces the dancer's motion. You can also connect any preprocessed control video directly to the `Apply MiniMax H3 Fun ControlNet` node's `control_video` input.

## Model downloads

<CardGroup>
  <Card title="Diffusion Model: minimax_h3_ref2va_pruned_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/diffusion_models/minimax_h3_ref2va_pruned_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="ControlNet Patch: minimax_h3_fun_controlnet_union_pruned_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/model_patches/minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/model\_patches/</code>
  </Card>

  <Card title="Text Encoder: qwen3vl_32b_minimax_h3_nvfp4_awq" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/text_encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="VAE: minimax_h3_video_vae_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_video_vae_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="VAE: minimax_h3_audio_vae_fp32" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_audio_vae_fp32.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="LoRA: minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/loras/minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors">
    Powers the optional Lightning LoRA turbo mode. Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="Checkpoint: sdpose_wholebody_fp16" icon="download" href="https://huggingface.co/Comfy-Org/SDPose/blob/main/checkpoints/sdpose_wholebody_fp16.safetensors">
    Pose extractor used by the built-in SDPose subgraph. Place in <code>ComfyUI/models/checkpoints/</code>
  </Card>

  <Card title="Detector: rt_detr_v4-x-hgnet_fp16" icon="download" href="https://huggingface.co/Comfy-Org/SDPose/blob/main/diffusion_models/rt_detr_v4-x-hgnet_fp16.safetensors">
    Person detector used by the built-in SDPose subgraph. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

## Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── minimax_h3_ref2va_pruned_int8_convrot.safetensors
│   │   └── rt_detr_v4-x-hgnet_fp16.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors
│   ├── 📂 vae/
│   │   ├── minimax_h3_video_vae_int8_convrot.safetensors
│   │   └── minimax_h3_audio_vae_fp32.safetensors
│   ├── 📂 loras/
│   │   └── minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors
│   ├── 📂 model_patches/
│   │   └── minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors
│   └── 📂 checkpoints/
│       └── sdpose_wholebody_fp16.safetensors
```

## Prompting tips

1. **Video length**: The target video runs 5 to 15 seconds on the 17n+5 frame grid at 24fps (124 frames = 5 seconds). A control video longer than the target is trimmed to its first frames; a shorter one holds its last frame. To match the control video's length exactly, link the example's computed `batch_size` output to the length input of the `MiniMax H3 Reference to Video` node
2. **Guidance and strength**: Keep `guidance_scale` at 1.0. Raise the patch `strength` above 1 only if the output drifts away from the control
3. **Video inpainting**: Connect a mask to the `mask` input: regions marked `1` are regenerated under control of the optional `source_video` input, while the rest of the frame stays fixed
4. **Turbo mode (optional)**: Enable the **Lightning LoRA** checkbox to use the 4-step turbo LoRA for much faster generation, with slightly lower audio and motion quality
5. **Preparing control videos**: ComfyUI ships with built-in preprocessing nodes for each control type. See the [Detect Edges (Canny) node](https://docs.comfy.org/built-in-nodes/Canny) for edges and the [Depth Anything 3 tutorial](https://docs.comfy.org/tutorials/utility/depth-anything-3) for depth maps


# ComfyUI MiniMax H3 Multiframe Reference Workflow
Source: https://docs.comfy.org/tutorials/video/minimax/minimax-h3-multiframe

Build MiniMax H3 video continuations and multi-shot scenes in ComfyUI by pinning reference frames to set points on the timeline with Add Guide nodes.

Generate video continuations and multi-shot scenes by anchoring reference frames at specific points along the output timeline. The workflow combines the Reference to Video node with chained Add Guide nodes: each Add Guide pins a still image (plus optional audio) to a frame index, so the video passes through that exact composition at that moment.

![MiniMax H3 Multiframe Reference workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_minimax_h3_multiframe_reference-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_minimax_h3_multiframe_reference&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_minimax_h3_multiframe_reference.json">
    Download JSON or search "MiniMax H3: Multiframe Reference" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Frame Reference 1: h3_frame_ref_1.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/h3_frame_ref_1.png">
    Identity reference and first frame of Shot 1, or use your own images.
  </Card>

  <Card title="Frame Reference 2: h3_frame_ref_2.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/h3_frame_ref_2.png">
    Keyframe anchored at 1.5s (Shot 2), or use your own images.
  </Card>

  <Card title="Frame Reference 3: h3_frame_ref_3.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/h3_frame_ref_3.png">
    Keyframe anchored at 3.0s (Shot 3), or use your own images.
  </Card>

  <Card title="Frame Reference 4: h3_frame_ref_4.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/h3_frame_ref_4.png">
    First frame anchored at 5.0s (Shot 4), or use your own images.
  </Card>
</CardGroup>

## Model downloads

<CardGroup>
  <Card title="Diffusion Model: minimax_h3_ref2va_pruned_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/diffusion_models/minimax_h3_ref2va_pruned_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="Text Encoder: qwen3vl_32b_minimax_h3_nvfp4_awq" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/text_encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="VAE: minimax_h3_video_vae_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_video_vae_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="VAE: minimax_h3_audio_vae_fp32" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_audio_vae_fp32.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="LoRA: minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/loras/minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors">
    Powers the optional Lightning LoRA turbo mode. Place in <code>ComfyUI/models/loras/</code>
  </Card>
</CardGroup>

## Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── minimax_h3_ref2va_pruned_int8_convrot.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors
│   ├── 📂 vae/
│   │   ├── minimax_h3_video_vae_int8_convrot.safetensors
│   │   └── minimax_h3_audio_vae_fp32.safetensors
│   └── 📂 loras/
│       └── minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors
```

## Prompting tips

1. **Reference by tag**: `<Picture 1>` is the image connected to the first `ref_images` slot, `<Picture 2>` the second, and so on. In this workflow, `<Picture 1>` is both the identity lock and the first frame of the video
2. **Timeline anchors vs references**: Pictures connected only to Add Guide nodes pin compositions at specific frames but are not visible to the text encoder. Plug them into extra `ref_images` slots too if the prompt should see them as `<Picture N>`
3. **Frame index**: Each Add Guide takes `frame_idx` in frames at 24fps; the template computes it from seconds with `round(seconds * 24)`. Negative values count from the end of the video. The index plus the guide length must stay inside the generated duration
4. **Add more keyframes**: Copy one guide block (Load Image + Frame Index + Math Expression + Add Guide for MiniMax H3) and keep the `positive` outputs chained in series into the Basic Guider
5. **Turbo mode (optional)**: Enable the **Lightning LoRA** checkbox to use the 4-step turbo LoRA for much faster generation, with slightly lower audio and motion quality

## Prompt writing guide

The template prompt follows the [full-reference mode prompt guide](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_ref_en.md): it defines each subject, maps each `<Picture N>` to a shot's first frame or keyframe, and cuts between shots at explicit timestamps. Use the same structure when writing your own multi-shot prompts. The guide is summarized in the [prompt guide](/tutorials/video/minimax/minimax-h3-prompt-guide).


# ComfyUI MiniMax H3 Text-to-Video, Image-to-Video, and Reference-to-Video Workflows
Source: https://docs.comfy.org/tutorials/video/minimax/minimax-h3-native

Run MiniMax H3 text-to-video (T2V), image-to-video (I2V), and reference-to-video (R2V) workflows in ComfyUI, plus advanced native-node techniques for guide anchoring and latent noise masks.

This page covers the three base MiniMax H3 template workflows in ComfyUI, plus advanced techniques built on the native H3 nodes. For model capabilities, prompt writing, and speedups, see the [MiniMax H3 overview](/tutorials/video/minimax/minimax-h3).

## MiniMax H3 Text to Video (T2V)

Generate videos from text prompts with native stereo audio.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_minimax_h3_t2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_minimax_h3_t2v.json">
    Download JSON or search "MiniMax H3 T2V" in Template Library
  </Card>
</CardGroup>

### Model downloads

<CardGroup>
  <Card title="Diffusion Model: minimax_h3_fl2va_pruned_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/diffusion_models/minimax_h3_fl2va_pruned_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="Text Encoder: qwen3vl_32b_minimax_h3_nvfp4_awq" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/text_encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="VAE: minimax_h3_video_vae_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_video_vae_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="VAE: minimax_h3_audio_vae_fp32" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_audio_vae_fp32.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="LoRA: minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16" icon="download" href="https://huggingface.co/lightx2v/Minimax-h3-Turbo/resolve/main/minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16.safetensors">
    Required by the workflow's model scan; powers the optional Lightning LoRA turbo mode. Place in <code>ComfyUI/models/loras/</code>
  </Card>
</CardGroup>

### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── minimax_h3_fl2va_pruned_int8_convrot.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors
│   ├── 📂 vae/
│   │   ├── minimax_h3_video_vae_int8_convrot.safetensors
│   │   └── minimax_h3_audio_vae_fp32.safetensors
│   ├── 📂 loras/
│   │   └── minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16.safetensors
│   └── 📂 embeddings/
│       └── minimaxh3_art_is_explosion.safetensors
```

### Prompting tips

1. **Describe the whole scene**: State the overall scene first (location, character, what is happening), then break it into timed shots
2. **Shots, camera, and audio**: Describe the shots, camera moves, and the accompanying audio (dialogue, SFX, music) in one prompt block
3. **Resolution**: H3's native canvas is a 768px short edge, which is 1344x768 at 16:9, and resolutions are rounded to a multiple of 32
4. **Duration**: The duration input snaps to the model's 17-frame-per-block (17k+5) grid at 24fps
5. **First/last frame**: Connect images to `first_frame` and/or `last_frame` on the `MiniMaxH3ImageToVideo` node to turn this workflow into first/last-frame image-to-video
6. **Turbo mode (optional)**: The workflow generates at 20 steps by default; raise the step count (for example to 25) for better motion quality. Enable `turbo_mode` on the MiniMax H3 node to use the included Lightning LoRA (`minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16`) at 8 steps for much faster generation, with slightly lower audio and motion quality

The official base-mode [prompt writing guide](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_base_en.md) is summarized in the [prompt guide](/tutorials/video/minimax/minimax-h3-prompt-guide).

## MiniMax H3 Image to Video (I2V)

Generate videos from an input image, with optional first/last-frame keyframes.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_minimax_h3_i2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_minimax_h3_i2v.json">
    Download JSON or search "MiniMax H3 I2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Input Image: transparent_rgb_gaming_mouse.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/transparent_rgb_gaming_mouse.png">
    Download the default input image, or use your own image.
  </Card>
</CardGroup>

### Model downloads

<CardGroup>
  <Card title="Diffusion Model: minimax_h3_fl2va_pruned_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/diffusion_models/minimax_h3_fl2va_pruned_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="Text Encoder: qwen3vl_32b_minimax_h3_nvfp4_awq" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/text_encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="VAE: minimax_h3_video_vae_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_video_vae_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="VAE: minimax_h3_audio_vae_fp32" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_audio_vae_fp32.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Turbo LoRA: minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16" icon="download" href="https://huggingface.co/lightx2v/Minimax-h3-Turbo/blob/main/minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16.safetensors">
    Place in <code>ComfyUI/models/loras/</code>. Used when <code>turbo\_mode</code> is enabled.
  </Card>
</CardGroup>

### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── minimax_h3_fl2va_pruned_int8_convrot.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors
│   ├── 📂 loras/
│   │   └── minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16.safetensors
│   ├── 📂 vae/
│   │   ├── minimax_h3_video_vae_int8_convrot.safetensors
│   │   └── minimax_h3_audio_vae_fp32.safetensors
│   └── 📂 embeddings/
│       └── minimaxh3_art_is_explosion.safetensors
```

### Prompting tips

1. **Keyframes**: The `first_frame` and `last_frame` inputs are optional; the model generates the motion between them
2. **Prompt**: Describe the shots, motion, and the accompanying audio (dialogue, SFX, music) in one block
3. **Resolution**: H3's native canvas is a 768px short edge, which is 1344x768 at 16:9, and resolutions are rounded to a multiple of 32
4. **Duration**: The duration input snaps to the model's 17-frame-per-block (17k+5) grid at 24fps
5. **Turbo mode**: Enable `turbo_mode` on the MiniMax H3 node to switch to the turbo LoRA and generate in `turbo_steps` (default 8) instead of 20 steps. `turbo_model_strength` controls the LoRA strength (default 1.0).

The official base-mode [prompt writing guide](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_base_en.md) is summarized in the [prompt guide](/tutorials/video/minimax/minimax-h3-prompt-guide).

## MiniMax H3 Reference to Video (R2V)

Generate videos that lock in a character, style, motion, camera move, or voice from any mix of reference images, videos, and audio.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_minimax_h3_r2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_minimax_h3_r2v.json">
    Download JSON or search "MiniMax H3 R2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Reference Image: red_superboy_on_city_roof.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/red_superboy_on_city_roof.png">
    Character reference for the workflow, or use your own images.
  </Card>

  <Card title="Reference Image: mecha_dragon_lightning.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/mecha_dragon_lightning.png">
    Style and subject reference for the workflow, or use your own images.
  </Card>
</CardGroup>

### Model downloads

<CardGroup>
  <Card title="Diffusion Model: minimax_h3_ref2va_pruned_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/diffusion_models/minimax_h3_ref2va_pruned_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="Text Encoder: qwen3vl_32b_minimax_h3_nvfp4_awq" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/text_encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="VAE: minimax_h3_video_vae_int8_convrot" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_video_vae_int8_convrot.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="VAE: minimax_h3_audio_vae_fp32" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_audio_vae_fp32.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="LoRA: minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16" icon="download" href="https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/loras/minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors">
    Required by the workflow's model scan; powers the optional Lightning LoRA turbo mode. Place in <code>ComfyUI/models/loras/</code>
  </Card>
</CardGroup>

### Model storage

```
ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── minimax_h3_ref2va_pruned_int8_convrot.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors
│   ├── 📂 vae/
│   │   ├── minimax_h3_video_vae_int8_convrot.safetensors
│   │   └── minimax_h3_audio_vae_fp32.safetensors
│   ├── 📂 loras/
│   │   └── minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors
│   └── 📂 embeddings/
│       └── minimaxh3_art_is_explosion.safetensors
```

### Prompting tips

1. **Reference by tag**: Reference each input by tag in the exact order it was connected, for example `<Picture 1>`, `<Video 1>`, `<Audio 1>`
2. **Assign each reference a job**: State which reference drives which part of the shot (identity, style, motion, camera, voice). Explicit assignments tend to work much better
3. **Limits**: Up to 9 reference images, 3 reference videos (each can carry its own soundtrack), and 3 standalone reference audio clips
4. **ref\_image\_size**: `match` scales references down to the generation resolution for speed; `max` keeps up to a 2048px short edge for stronger identity fidelity at the cost of speed
5. **Note**: R2V uses the `ref2va` diffusion model, a different set of weights from the `fl2va` model used by the T2V and I2V workflows
6. **Turbo mode (optional)**: The workflow generates at 20 steps by default; raise the step count (for example to 25) for better motion quality. Enable the **Lightning LoRA** checkbox to use the 4-step turbo LoRA (`minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16`) for much faster generation, with slightly lower audio and motion quality

The official full-reference-mode [prompt writing guide](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_ref_en.md) is summarized in the [prompt guide](/tutorials/video/minimax/minimax-h3-prompt-guide).

## Advanced workflows with the native nodes

The native MiniMax H3 nodes support two additional workflows that landed in recent ComfyUI updates. Update ComfyUI to the latest version to use them.

### Anchoring guides at any frame (#15439)

[Comfy-Org/ComfyUI#15439](https://github.com/Comfy-Org/ComfyUI/pull/15439) added the `MiniMaxH3AddGuide` node. Before it, keyframes could only anchor at the first and last frame of the video. The node removes that restriction: a guide can anchor at any frame, on a continuous time axis.

Connect the `positive` and latent outputs of a MiniMax H3 node to `MiniMaxH3AddGuide`, then provide at least one guide input:

* **image**: A still image or a clip. Multi-frame batches are anchored as a clip and cropped down to the model's valid clip lengths: 5, 22, 39... frames (17k+5). Batches shorter than 5 frames use only the first image
* **audio**: A soundtrack anchored at the same frame index, cropped to the video's remaining duration
* **frame\_idx**: The frame to anchor at. Negative values count from the end of the video

Connect the video VAE to `vae` when you provide an image, and the audio VAE to `audio_vae` when you provide audio. Chain several `MiniMaxH3AddGuide` nodes to anchor guides at multiple frames.

For example, feed the first 22 frames of an existing video plus its audio into a `MiniMaxH3AddGuide` at frame 0, and the model generates the continuation of both streams. Or place a still image at frame 60 of a 124-frame video to force the video to pass through that frame.

Anchoring a guide is not video-to-video. Generation still starts from the workflow's empty latent and is denoised as usual, while the node VAE-encodes the guide and appends it to the `positive` conditioning at the chosen frame, so the anchor is a conditioning reference rather than the latent the sampler starts from. Because the anchor stays in that conditioning for every step of the schedule, `denoise` does not scale how strongly a guide applies the way it does in a video-to-video run. To restyle an existing clip instead of passing through it, supply it as a reference video in the Reference to Video workflow; to regenerate part of a clip, use the mask route on the [Fun ControlNet Union](/tutorials/video/minimax/minimax-h3-fun-controlnet) page.

First/last-frame anchoring produces the same coordinates as before, so existing workflows keep working unchanged.

The [Multiframe Reference](/tutorials/video/minimax/minimax-h3-multiframe) template is a ready-made workflow built on this node.

### Inpainting and extension with latent noise masks (#15375)

[Comfy-Org/ComfyUI#15375](https://github.com/Comfy-Org/ComfyUI/pull/15375) added per-token noise masks for MiniMax H3, covering both the video and audio latents. You can now regenerate only part of a video while keeping the rest fixed.

Connect a mask to the sampler's `denoise_mask` input as usual: a value of `0` preserves the corresponding latent region, while `1` regenerates it. Video masks snap to the model's 2x2 latent patch grid, and audio masks to whole latent frames. Use it for local inpainting, object removal, or extending a clip while keeping the existing content stable.


# ComfyUI MiniMax H3 Prompt Guide: Official Guides, Tips, and Prompt Embeddings
Source: https://docs.comfy.org/tutorials/video/minimax/minimax-h3-prompt-guide

Write better MiniMax H3 prompts in ComfyUI: MiniMax's official prompt guides, general prompting tips, dialogue and speaker rules, and style embeddings.

The prompt is where H3's multimodal training pays off: shots, camera moves, dialogue, and sound effects all live in one prompt block. This page collects the prompt writing resources for MiniMax H3 in ComfyUI: MiniMax's official guides, general tips that apply to every workflow, the rules for dialogue and speakers, and prompt embeddings for style effects.

## Official guides

MiniMax publishes two official prompt writing guides:

* [Base generation modes](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_base_en.md) (T2VA, I2VA, FL2VA, L2VA): structure a prompt into timed shots with camera movement and audio (dialogue, SFX, music), with examples for each mode
* [Full-reference mode](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_ref_en.md) (R2V): the rewrite output structure, including subject definitions, reference labels, and retention analysis, and how to assign each reference a role in the target shot

MiniMax also publishes installable [H3 skills](https://github.com/MiniMax-AI/MiniMax-H3/tree/main/skills), including a prompt-writing skill that packages these guides for agent use.

The workflow pages show these guides applied to each template: [T2V and I2V](/tutorials/video/minimax/minimax-h3-native), [R2V](/tutorials/video/minimax/minimax-h3-native#minimax-h3-reference-to-video-r2v), [Multiframe Reference](/tutorials/video/minimax/minimax-h3-multiframe#prompt-writing-guide), and [Fun ControlNet Union](/tutorials/video/minimax/minimax-h3-fun-controlnet#prompting-tips).

## General tips

The final prompt follows a fixed structure. I2VA prompts open with a fixed image-alignment sentence on the first line, followed by one blank line, for example `For the target video, at 0.00 seconds into the target video, <Picture 1> (from [Shot 1]) is fully referenced.` FL2VA and L2VA use their own fixed sentences in that line, which align each reference picture to a mark in the target video, and T2VA prompts have no instruction line and start directly with the fields. The body carries three fields in this order:

```text theme={null}
integrated_multimodal_description: [Shot 1] ...
overall_soundscape: ...
non_diegetic_music: ...
```

Write the prompt itself in English. Keep dialogue and lyrics inside `<d>` tags, and screen-visible text in its original language, in both cases verbatim.

1. **Describe the whole scene**: State the overall scene first (location, character, what is happening), then break it into timed shots. The overall style and the opening composition belong at the start of `[Shot 1]` inside `integrated_multimodal_description`, after any image-alignment instruction.
2. **Shots, camera, and audio**: Describe the shots, camera moves, and the accompanying audio (dialogue, SFX, music) in one prompt block
3. **Resolution**: H3's native canvas is a 768px short edge, which is 1344x768 at 16:9, and resolutions are rounded to a multiple of 32. See [Setting the output resolution](/tutorials/video/minimax/minimax-h3#setting-the-output-resolution)
4. **Length**: The node's `length` input is a frame count at 24fps (default 124, about 5 seconds) that snaps up to the model's 17-frame block grid (17k+5)
5. **On-screen text in quotes**: Wrap any text that is visible on screen (signs, banners, subtitles, neon text) in English double quotation marks, and list each string separately. Copy the original text and punctuation verbatim, without translating it, for example `A red neon sign reading "营业中" glows above the doorway.` Keep spoken dialogue in `<d>` tags instead: quotes are for printed text, `<d>` is for what characters say
6. **Audio reuse markers in R2V**: In full-reference (R2V) prompts, declare each audio reference's relationship in the retention analysis: `fully_copy` uses the source audio 1:1 as the final audio track, `partially_copy` copies part of the timeline or selected layers, or adds, removes, and replaces sounds afterwards, `reference` carries timbre, rhythm, music style, dialogue content, or sound texture without copying the signal, and `weak_reference` keeps only a broad similarity in category or atmosphere. The marker must match what the audio actually does in the target video. See the official full-reference guide's relationship marker table
7. **Write the audio lanes explicitly**: Each prompt carries two audio fields, and they follow different rules. `overall_soundscape` summarizes ambient sound, physical action sounds, and non-verbal human sounds in 1 to 4 sentences (dialogue, singing, and diegetic music belong in `integrated_multimodal_description`, not here), and uses `N/A` only when the clip should be completely silent. `non_diegetic_music` describes score that only the audience hears in 1 to 3 sentences, and uses `N/A` when there is no such music. If a quiet shot comes back with speech you did not ask for, write out both fields explicitly and regenerate. See the official base guide's sections on `overall_soundscape` and `non_diegetic_music`
8. **Write bans as positives**: the H3 templates sample through the `BasicGuider` node, which carries a single conditioning input, so there is no negative branch and a negative prompt has no effect (the guider runs at `cfg` 1, where ComfyUI skips the unconditional pass; a `CFGGuider` only uses negative conditioning above `cfg` 1). An instruction that names an unwanted element adds that wording to the description the model reads, with no separate pass to subtract it, so a line such as `no subtitles and no on-screen text` registers text as content. Say what should be in the shot instead, for example `the sign above the door is blank`. In full-reference prompts, scope the same thing through the retention analysis, where `fully_preserved`, `partially_preserved`, `attribute_transfer`, and `weak_reference` state what each reference contributes to the target video
9. **Reference sheets (R2V)**: one reference image can hold several views of a subject or the panels of a storyboard, and the prompt then addresses one panel at a time. Give the sheet its own `<Picture N>` entry rather than citing it inside a `<Subject N>` definition, since a picture cited only inside a definition is not used as a separate reference, and describe the sheet there, for example `<Picture 2> is a character sheet with three panels: a portrait, a full front view, and a full back view of the woman`. Point a shot at one panel inside the shot description, for example `[Shot 2] the shot's keyframe corresponds to the full front view panel of <Picture 2>`. A sheet keeps several views inside the local R2V node's limit of 9 reference images and lets each shot name the view it needs. Number or label the panels so the prompt can point at them, and keep the sheet's printed text to those labels.

Workflow-specific prompting (reference tags, timeline anchors, control-video length) is covered on each workflow page.

## Dialogue and speakers

Spoken lines follow fixed rules in every workflow, and they come from the official base guide's section on speakers, dialogue, and singing.

* **Stable speaker IDs**: give every voice in the prompt an ID such as `(S1)` or `(S2)`, including off-screen and singing voices, and repeat that ID in every shot where it speaks. The IDs number speakers, not subjects: a character who never vocalizes gets no ID, and the first voice in the prompt is `(S1)` even when its character is numbered differently. Speakers who vocalize together take a compound ID such as `(S1,S2)`
* **Outside and inside `<d>`**: the identifying phrase, the speaker ID, the action, and the delivery stay outside the tags, and the tags carry only the language tag plus the words themselves, copied verbatim. Write each line inside the shot where it is spoken, in the same paragraph as that shot's action
* **Voiceover**: a line the audience hears without the character speaking it needs the exact phrase `says in an off-screen voiceover`, plus a statement right after the `<d>` block that the on-screen character's lips remain closed. A line that continues across a cut needs `<scenetrans>` at both connection points and a statement that the audio carries over the transition
* **Several speakers with audio references**: in full-reference (R2V) prompts that pair two or more speakers with audio references, H3 can hand an audio reference to the wrong speaker even when the prompt text and the reference connection order are both correct. Keep each shot to the references that shot needs, and tie a line to a visible event, for example `When the phone is at his ear, the man in the coat speaks`, rather than to an absolute timecode, which is what cut times are for. When a line still lands on the wrong speaker, generate it with a voice tool and supply it as that speaker's audio reference, with the relationship marker that matches the clip: `fully_copy` when the clip becomes the video's complete final audio track, or `partially_copy` when it covers part of the timeline

## Prompt embeddings

[Comfy-Org/ComfyUI#15697](https://github.com/Comfy-Org/ComfyUI/pull/15697) added support for prompt embeddings in MiniMax H3. You can use ComfyUI's standard `embedding:` syntax in H3 prompts.

Place an embedding file in `ComfyUI/models/embeddings/` and reference it in the prompt by name, for example `embedding:my_embedding`. The embedding is loaded and mixed into the text conditioning just like with any other ComfyUI model.

The [Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3/tree/main/embeddings) repository hosts 10 style embeddings in its `embeddings` folder. These files are unofficial: they were contributed by community member [silveroxides](https://huggingface.co/silveroxides) via [Hugging Face PR #50](https://huggingface.co/Comfy-Org/MiniMax-H3/discussions/50), and were not produced by Comfy-Org or MiniMax. The original files are in the [silveroxides/MiniMax-H3\_tests](https://huggingface.co/silveroxides/MiniMax-H3_tests/tree/main/embeddings) repository. The file name describes the intended effect, and the trigger word is the file name without the extension:

| Embedding | Effect (by name) |
| - | - |
| `minimaxh3_art_is_explosion` | Explosive art composition |
| `minimaxh3_blooming_flowers` | Flowers blooming |
| `minimaxh3_bullet_time` | Bullet-time effect |
| `minimaxh3_dark_magic` | Dark magic atmosphere |
| `minimaxh3_fire_breath` | Fire-breath effect |
| `minimaxh3_four_seasons` | Four seasons transition |
| `minimaxh3_kiss_camera` | Kiss scene camera move |
| `minimaxh3_spiral_ascent` | Spiraling ascent |
| `minimaxh3_storm_magic` | Storm magic |
| `minimaxh3_truman_show` | Truman Show style |


# ComfyUI Wan2.1 Fun Camera Official Examples
Source: https://docs.comfy.org/tutorials/video/wan/fun-camera

This guide demonstrates how to use Wan2.1 Fun Camera in ComfyUI for video generation

Wan2.1 Fun Camera is a camera-motion video generation model from Alibaba's VideoX-Fun project, supported natively in ComfyUI. It generates videos whose camera movement follows your control conditions, so you can direct how the camera moves in the output instead of describing every shot in the prompt.

The model is part of the Wan2.1-Fun family and ships in two sizes: the 1.3B version (about 19 GB) for lightweight local runs and the 14B version (about 47 GB) for higher-fidelity output. Both support multi-resolution video prediction at 512, 768, and 1024 pixels, are trained at 16 frames per second for up to 81 frames (about 5 seconds), and accept multilingual prompts. The weights are released under the Apache-2.0 license.

## About Wan2.1 Fun Camera

**Wan2.1 Fun Camera** is a video generation project launched by the Alibaba team, focusing on controlling video generation effects through camera motion.

**Model Weights Download**:

* [14B Version](https://huggingface.co/alibaba-pai/Wan2.1-Fun-V1.1-14B-Control-Camera)
* [1.3B Version](https://huggingface.co/alibaba-pai/Wan2.1-Fun-V1.1-1.3B-Control-Camera)

**Code Repository**: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

**ComfyUI now natively supports the Wan2.1 Fun Camera model**.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Installation

These models only need to be installed once. Additionally, model download information is included in the corresponding workflow images, so you can choose your preferred way to download the models.

All of the following models can be found at [Wan\_2.1\_ComfyUI\_repackaged](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged)

### Diffusion Models

Choose either 1.3B or 14B:

<CardGroup>
  <Card title="wan2.1_fun_camera_v1.1_1.3B_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_fun_camera_v1.1_1.3B_bf16.safetensors?download=true">
    Wan2.1 Fun Camera 1.3B diffusion model
  </Card>

  <Card title="wan2.1_fun_camera_v1.1_14B_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_fun_camera_v1.1_14B_bf16.safetensors?download=true">
    Wan2.1 Fun Camera 14B diffusion model
  </Card>
</CardGroup>

If you've used Wan2.1 related models before, you should already have the following models. If not, please download them:

### Text Encoders

Choose one of the following:

<CardGroup>
  <Card title="umt5_xxl_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp16.safetensors?download=true">
    Full precision text encoder
  </Card>

  <Card title="umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true">
    FP8 quantized text encoder (recommended for lower VRAM)
  </Card>
</CardGroup>

### VAE

<CardGroup>
  <Card title="wan_2.1_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors?download=true">
    Wan2.1 VAE model
  </Card>
</CardGroup>

### CLIP Vision

<CardGroup>
  <Card title="clip_vision_h.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors?download=true">
    CLIP vision encoder
  </Card>
</CardGroup>

File Storage Location:

```
📂 ComfyUI/
├── 📂 models/
│ ├── 📂 diffusion_models/
│ │   ├── wan2.1_fun_camera_v1.1_1.3B_bf16.safetensors # 1.3B version
│ │   └── wan2.1_fun_camera_v1.1_14B_bf16.safetensors # 14B version
│ ├── 📂 text_encoders/
│ │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│ ├── 📂 vae/
│ │   └── wan_2.1_vae.safetensors
│ └── 📂 clip_vision/
│     └── clip_vision_h.safetensors
```

## ComfyUI Wan2.1 Fun Camera 1.3B Workflow

### Wan 2.1 Fun Camera 1.3B

Generate dynamic videos with cinematic camera movements using Wan 2.1 Fun Camera 1.3B model.

<img alt="Wan 2.1 Fun Camera 1.3B workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2.1_fun_camera_v1.1_1.3B&utm_source=docs&utm_medium=referral&utm_campaign=fun-camera">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2.1_fun_camera_v1.1_1.3B.json">
    Download JSON or search "Wan 2.1 Fun Camera 1.3B" in Template Library
  </Card>
</CardGroup>

Download the video below and drag it into ComfyUI to load the corresponding workflow:

<video />

<Note>
  If you want to use the 14B version, simply replace the model file with the 14B version, but please be aware of the VRAM requirements.
</Note>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="video_wan2.1_fun_camera_v1.1_1.3B_start_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2.1_fun_camera_v1.1_1.3B_start_image.jpg">
    `LoadImage` node 52 · `video_wan2.1_fun_camera_v1.1_1.3B_start_image.jpg`
  </Card>
</CardGroup>

<div>
  <img alt="video_wan2.1_fun_camera_v1.1_1.3B_start_image.jpg" />
</div>

### 3. Complete the Workflow Step by Step

<img alt="Wan2.1 Fun Camera Workflow Steps" />

1. Ensure the correct version of model file is loaded:
   * 1.3B version: `wan2.1_fun_camera_v1.1_1.3B_bf16.safetensors`
   * 14B version: `wan2.1_fun_camera_v1.1_14B_bf16.safetensors`
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Ensure the `Load CLIP Vision` node has loaded `clip_vision_h.safetensors`
5. Upload the starting frame to the `Load Image` node
6. Modify the Prompt if you're using your own input image
7. Set camera motion in the `WanCameraEmbedding` node
8. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute generation

## ComfyUI Wan2.1 Fun Camera 14B Workflow

### Wan 2.1 Fun Camera 14B

Generate high-quality videos with advanced camera control using the full 14B model.

<img alt="Wan 2.1 Fun Camera 14B workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2.1_fun_camera_v1.1_14B&utm_source=docs&utm_medium=referral&utm_campaign=fun-camera">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2.1_fun_camera_v1.1_14B.json">
    Download JSON or search "Wan 2.1 Fun Camera 14B" in Template Library
  </Card>
</CardGroup>

<video />

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="video_wan2.1_fun_camera_v1.1_14B_start_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2.1_fun_camera_v1.1_14B_start_image.jpg">
    `LoadImage` node 52 · `video_wan2.1_fun_camera_v1.1_14B_start_image.jpg`
  </Card>
</CardGroup>

<div>
  <img alt="video_wan2.1_fun_camera_v1.1_14B_start_image.jpg" />
</div>

## Performance Reference

**1.3B Version**:

* 512x512 resolution on RTX 4090 takes about 72 seconds to generate 81 frames

**14B Version**:

* RTX4090 24GB VRAM may experience insufficient memory when generating 512x512 resolution, and memory issues have also occurred on A100 when using larger sizes


# ComfyUI Wan2.1 Fun Control Video Examples
Source: https://docs.comfy.org/tutorials/video/wan/fun-control

This guide demonstrates how to use Wan2.1 Fun Control in ComfyUI to generate videos with control videos

Wan2.1-Fun-Control is an open-source video generation model from Alibaba's VideoX-Fun project that follows preset control conditions instead of relying on prompt text alone. You can guide the output with Canny edge maps, depth maps, OpenPose skeletons, MLSD geometric edges, or point trajectories.

The model ships in two sizes: the 1.3B version (about 19 GB) for lightweight local deployment with lower VRAM requirements, and the 14B version (about 47 GB of total model storage, with the diffusion weights at about 32.8 GB) for higher-quality results. Both support multi-resolution video prediction at 512, 768, and 1024 pixels, generate up to 81 frames (about 5 seconds) at 16 frames per second, and accept multilingual prompts. ComfyUI supports Wan2.1-Fun-Control natively.

## About Wan2.1-Fun-Control

**Wan2.1-Fun-Control** is an open-source video generation and control project developed by Alibaba team.
It introduces innovative Control Codes mechanisms combined with deep learning and multimodal conditional inputs to generate high-quality videos that conform to preset control conditions. The project focuses on precisely guiding generated video content through multimodal control conditions.

Currently, the Fun Control model supports various control conditions, including **Canny (line art), Depth, OpenPose (human posture), MLSD (geometric edges), and trajectory control.**
The model also supports multi-resolution video prediction with options for 512, 768, and 1024 resolutions at 16 frames per second, generating videos up to 81 frames (approximately 5 seconds) in length.

Model versions:

* **1.3B** Lightweight: Suitable for local deployment and quick inference with **lower VRAM requirements**
* **14B** High-performance: Model size reaches 32GB+, offering better results but **requiring higher VRAM**

**Model Weights Download**:

<CardGroup>
  <Card title="Wan2.1-Fun-1.3B-Control" icon="download" href="https://huggingface.co/alibaba-pai/Wan2.1-Fun-1.3B-Control">
    Lightweight version, lower VRAM requirements
  </Card>

  <Card title="Wan2.1-Fun-14B-Control" icon="download" href="https://huggingface.co/alibaba-pai/Wan2.1-Fun-14B-Control">
    High-performance version, 32GB+ file size, higher VRAM requirements
  </Card>
</CardGroup>

**Code Repository**: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

ComfyUI now **natively supports** the Wan2.1 Fun Control model. Before starting this tutorial, please update your ComfyUI to ensure you're using a version after [this commit](https://github.com/Comfy-Org/ComfyUI/commit/3661c833bcc41b788a7c9f0e7bc48524f8ee5f82).

In this guide, we will provide two workflows:

1. A workflow using only native Comfy Core nodes
2. A workflow using custom nodes

<Tip>
  Due to current limitations in native nodes for video support, the native-only workflow ensures users can complete the process without installing custom nodes.
  However, we have found that providing a good user experience for video generation is challenging without custom nodes, so we are providing both workflow versions in this guide.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Installation

You only need to install these models once. The workflow images also contain model download information, so you can choose your preferred download method.

The following models can be found at [Wan\_2.1\_ComfyUI\_repackaged](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged) and [Wan2.1-Fun](https://huggingface.co/collections/alibaba-pai/wan21-fun-67e4fb3b76ca01241eb7e334)

Click the corresponding links to download. If you have used Wan-related workflows before, you only need to download the **Diffusion models**.

**Diffusion models** -- choose 1.3B or 14B. The 14B version has a larger file size (32GB) and higher VRAM requirements:

<CardGroup>
  <Card title="wan2.1_fun_control_1.3B_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_fun_control_1.3B_bf16.safetensors?download=true">
    Wan2.1 Fun Control 1.3B diffusion model -- lightweight, lower VRAM requirements
  </Card>

  <Card title="Wan2.1-Fun-14B-Control" icon="download" href="https://huggingface.co/alibaba-pai/Wan2.1-Fun-14B-Control/blob/main/diffusion_pytorch_model.safetensors">
    Wan2.1 Fun Control 14B diffusion model. Rename to <code>Wan2.1-Fun-14B-Control.safetensors</code> after downloading. 32GB+ file size, higher VRAM requirements
  </Card>
</CardGroup>

**Text encoders** -- choose one of the following models (fp16 precision has a larger size and higher performance requirements):

<CardGroup>
  <Card title="umt5_xxl_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp16.safetensors?download=true">
    UMT5 XXL text encoder -- fp16 precision, larger size, higher performance
  </Card>

  <Card title="umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true">
    UMT5 XXL text encoder -- fp8 precision, smaller size, lower performance requirements
  </Card>
</CardGroup>

**VAE**

<Card title="wan_2.1_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors?download=true">
  Wan2.1 VAE model
</Card>

**CLIP Vision**

<Card title="clip_vision_h.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors?download=true">
  CLIP Vision model for processing reference images
</Card>

File storage location:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── wan2.1_fun_control_1.3B_bf16.safetensors
│   │   └── Wan2.1-Fun-14B-Control.safetensors
│   ├── 📂 text_encoders/
│   │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   ├── 📂 vae/
│   │   └── wan_2.1_vae.safetensors
│   └── 📂 clip_vision/
│       └── clip_vision_h.safetensors
```

## ComfyUI Native Workflow

In this workflow, we use videos converted to **WebP format** since the `Load Image` node does not currently support mp4 format. We also use **Canny Edge** to preprocess the original video.
Because many users encounter installation failures and environment issues when installing custom nodes, this version of the workflow uses only native nodes to ensure a smoother experience.

Thanks to our powerful ComfyUI authors who provide feature-rich nodes. If you want to directly check the related version, see [Workflow Using Custom Nodes](#workflow-using-custom-nodes).

### 1. Workflow File Download

![Wan2.1 Fun Control Native Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/wan2.1_fun_control/wan2.1_fun_control_native.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=wan2.1_fun_control&utm_source=docs&utm_medium=referral&utm_campaign=fun-control">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/wan2.1_fun_control/wan2.1_fun_control_native.webp">
    Download the workflow image and drag it into ComfyUI to load the workflow
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Start Image: wan2.1_fun_control_start_frame.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wan2.1_fun_control_start_frame.png">
    Input start frame for the native workflow. Download and use this image, or replace with your own.
  </Card>

  <Card title="Control Video: 01-portrait_video.webp" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/wan2.1_fun_control/input/01-portrait_video.webp">
    Input control video in WebP format for the native workflow. The native workflow requires WebP format since Load Image does not support mp4.
  </Card>
</CardGroup>

### 2. Complete the Workflow Step by Step

<img alt="Wan2.1 Fun Control Workflow Steps" />

1. Ensure the `Load Diffusion Model` node has loaded `wan2.1_fun_control_1.3B_bf16.safetensors`
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Ensure the `Load CLIP Vision` node has loaded `clip_vision_h.safetensors`
5. Upload the starting frame to the `Load Image` node (renamed to `Start_image`)
6. Upload the control video to the second `Load Image` node. Note: This node currently does not support mp4, only WebP videos
7. (Optional) Modify the prompt (both English and Chinese are supported)
8. (Optional) Adjust the video size in `WanFunControlToVideo`, avoiding overly large dimensions
9. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation

### 3. Usage Notes

* Since we need to input the same number of frames as the control video into the `WanFunControlToVideo` node, if the specified frame count exceeds the actual control video frames, the excess frames may display scenes not conforming to control conditions. We will address this issue in the [Workflow Using Custom Nodes](#workflow-using-custom-nodes)
* Avoid setting overly large dimensions, as this can make the sampling process very time-consuming. Try generating smaller images first, then upscale
* Use your imagination to build upon this workflow by adding text-to-image or other types of workflows to achieve direct text-to-video generation or style transfer
* Use tools like [ComfyUI-comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) for richer control options

## Workflow Using Custom Nodes

We will need to install the following two custom nodes:

* [ComfyUI-VideoHelperSuite](https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite)
* [ComfyUI-comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux)

You can use [ComfyUI Manager](https://github.com/Comfy-Org/ComfyUI-Manager) to install missing nodes or follow the installation instructions for each custom node package.

### 1. Workflow File Download

![Wan2.1 Fun Control Workflow](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/wan2.1_fun_control-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=wan2.1_fun_control&utm_source=docs&utm_medium=referral&utm_campaign=fun-control">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/wan2.1_fun_control.json">
    Download JSON or search "Wan 2.1 ControlNet" in Template Library
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Start Image: wan2.1_fun_control_start_frame.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wan2.1_fun_control_start_frame.png">
    Input start frame for the custom nodes workflow. Download and use this image, or replace with your own.
  </Card>

  <Card title="Control Video: wan2.1_fun_control_control_video.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wan2.1_fun_control_control_video.mp4">
    Input control video in MP4 format for the custom nodes workflow. The custom Load Video node supports mp4 format.
  </Card>
</CardGroup>

### 2. Complete the Workflow Step by Step

<img alt="Wan2.1 Fun Control Workflow Using Custom Nodes Steps" />

> The model part is essentially the same. If you have already experienced the native-only workflow, you can directly upload the corresponding images and run it.

1. Ensure the `Load Diffusion Model` node has loaded `wan2.1_fun_control_1.3B_bf16.safetensors`
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Ensure the `Load CLIP Vision` node has loaded `clip_vision_h.safetensors`
5. Upload the starting frame to the `Load Image` node
6. Upload an mp4 format video to the `Load Video(Upload)` custom node. Note that the workflow has adjusted the default `frame_load_cap`
7. For the current image, the `DWPose Estimator` only uses the `detect_face` option
8. (Optional) Modify the prompt (both English and Chinese are supported)
9. (Optional) Adjust the video size in `WanFunControlToVideo`, avoiding overly large dimensions
10. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation

### 3. Workflow Notes

Thanks to the ComfyUI community authors for their custom node packages:

* This example uses `Load Video(Upload)` to support mp4 videos
* The `video_info` obtained from `Load Video(Upload)` allows us to maintain the same `fps` for the output video
* You can replace `DWPose Estimator` with other preprocessors from the `ComfyUI-comfyui_controlnet_aux` node package
* Prompts support multiple languages

## Usage Tips

<img alt="Apply Multi Control Videos" />

* A useful tip is that you can combine multiple image preprocessing techniques and then use the `Image Blend` node to achieve the goal of applying multiple control methods simultaneously.

* You can use the `Video Combine` node from `ComfyUI-VideoHelperSuite` to save videos in mp4 format

* We use `SaveAnimatedWEBP` because we currently do not support embedding workflow into **mp4** and some other custom nodes may not support embedding workflow too. To preserve the workflow in the video, we choose the `SaveAnimatedWEBP` node.

* In the `WanFunControlToVideo` node, `control_video` is not mandatory, so sometimes you can skip using a control video, first generate a very small video size like 320x320, and then use them as control video input to achieve consistent results.

* [ComfyUI-WanVideoWrapper](https://github.com/kijai/ComfyUI-WanVideoWrapper)

* [ComfyUI-KJNodes](https://github.com/kijai/ComfyUI-KJNodes)


# ComfyUI Wan2.1 Fun InP Video Examples
Source: https://docs.comfy.org/tutorials/video/wan/fun-inp

This guide demonstrates how to use Wan2.1 Fun InP in ComfyUI to generate videos with first and last frame control

**Wan2.1 Fun InP** is an open-source video generation model in Alibaba's Wan2.1-Fun series. You provide a first and last frame image, and it generates the transition video between them with stable, coherent motion.

This guide covers the official ComfyUI workflow for Wan2.1 Fun InP, available in lightweight 1.3B and high-performance 14B versions, with model downloads and step-by-step generation instructions.

## About Wan2.1-Fun-InP

**Wan-Fun InP** is an open-source video generation model released by Alibaba, part of the Wan2.1-Fun series, focusing on generating videos from images with first and last frame control.

**Key features**:

* **First and last frame control**: Supports inputting both first and last frame images to generate transitional video between them, enhancing video coherence and creative freedom. Compared to earlier community versions, Alibaba's official model produces more stable and significantly higher quality results.
* **Multi-resolution support**: Supports generating videos at 512x512, 768x768, 1024x1024 and other resolutions to accommodate different scenario requirements.

**Model versions**:

* **1.3B** Lightweight: Suitable for local deployment and quick inference with **lower VRAM requirements**
* **14B** High-performance: Model size reaches 32GB+, offering better results but requiring **higher VRAM**

Below are the relevant model weights and code repositories:

* [Wan2.1-Fun-1.3B-Input](https://huggingface.co/alibaba-pai/Wan2.1-Fun-1.3B-Input)
* [Wan2.1-Fun-14B-Input](https://huggingface.co/alibaba-pai/Wan2.1-Fun-14B-Input)
* Code repository: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

<Tip>
  Currently, ComfyUI natively supports the Wan2.1 Fun InP model. Before starting this tutorial, please update your ComfyUI to ensure your version is after [this commit](https://github.com/Comfy-Org/ComfyUI/commit/0a1f8869c9998bbfcfeb2e97aa96a6d3e0a2b5df).
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Wan2.1 Fun InP Workflow

### 1. Download Workflow

Download the image below and drag it into ComfyUI to load the workflow:

![Wan2.1 Fun InP Workflow](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/wan2.1_fun_inp-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=wan2.1_fun_inp&utm_source=docs&utm_medium=referral&utm_campaign=fun-inp">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/wan2.1_fun_inp.json">
    Download JSON or search "Wan 2.1 Inpainting" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Start Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wan2.1_fun_inp_start_image.png">
    Starting frame for the video generation. Download and use this image, or replace with your own.
  </Card>

  <Card title="End Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wan2.1_fun_inp_end_image.png">
    Ending frame for the video generation. Download and use this image, or replace with your own.
  </Card>
</CardGroup>

### 2. Manual Model Installation

If automatic model downloading is ineffective, please download the models manually and save them to the corresponding folders.

All models involved in this guide can be found at [Wan\_2.1\_ComfyUI\_repackaged](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged) and [Wan2.1-Fun](https://huggingface.co/collections/alibaba-pai/wan21-fun-67e4fb3b76ca01241eb7e334).

**Diffusion Models** : Choose 1.3B or 14B. The 14B version has a larger file size (32GB) and higher VRAM requirements:

<CardGroup>
  <Card title="Diffusion Model: Wan2.1 Fun InP 1.3B" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_fun_inp_1.3B_bf16.safetensors">
    `models/diffusion_models/wan2.1_fun_inp_1.3B_bf16.safetensors`
  </Card>

  <Card title="Diffusion Model: Wan2.1 Fun InP 14B" icon="download" href="https://huggingface.co/alibaba-pai/Wan2.1-Fun-14B-InP/blob/main/diffusion_pytorch_model.safetensors">
    `models/diffusion_models/Wan2.1-Fun-14B-InP.safetensors` (rename after download)
  </Card>
</CardGroup>

**Text Encoders** : Choose one of the following models (fp16 precision has a larger size and higher performance requirements):

<CardGroup>
  <Card title="Text Encoder: umt5_xxl_fp16" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp16.safetensors">
    `models/text_encoders/umt5_xxl_fp16.safetensors`
  </Card>

  <Card title="Text Encoder: umt5_xxl_fp8" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
    `models/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors`
  </Card>
</CardGroup>

**VAE**

<Card title="VAE: wan_2.1_vae" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
  `models/vae/wan_2.1_vae.safetensors`
</Card>

**CLIP Vision**

<Card title="CLIP Vision: clip_vision_h" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors">
  `models/clip_vision/clip_vision_h.safetensors`
</Card>

File storage location:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── wan2.1_fun_inp_1.3B_bf16.safetensors
│   │   └── Wan2.1-Fun-14B-InP.safetensors
│   ├── 📂 text_encoders/
│   │   ├── umt5_xxl_fp16.safetensors
│   │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   ├── 📂 vae/
│   │   └── wan_2.1_vae.safetensors
│   └── 📂 clip_vision/
│       └── clip_vision_h.safetensors
```

### 3. Complete the Workflow Step by Step

<img alt="ComfyUI Wan2.1 Fun InP Video Generation Workflow Diagram" />

1. Ensure the `Load Diffusion Model` node has loaded `wan2.1_fun_inp_1.3B_bf16.safetensors`
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Ensure the `Load CLIP Vision` node has loaded `clip_vision_h.safetensors`
5. Upload the starting frame to the `Load Image` node (renamed to `Start_image`)
6. Upload the ending frame to the second `Load Image` node
7. (Optional) Modify the prompt (both English and Chinese are supported)
8. (Optional) Adjust the video size in `WanFunInpaintToVideo`, avoiding overly large dimensions
9. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation

### 4. Workflow Notes

<Tip>
  Please make sure to use the correct model, as `wan2.1_fun_inp_1.3B_bf16.safetensors` and `wan2.1_fun_control_1.3B_bf16.safetensors` are stored in the same folder and have very similar names. Ensure you are using the right model.
</Tip>

* When using Wan Fun InP, you may need to frequently modify prompts to ensure the accuracy of the corresponding scene transitions.

## Other Wan2.1 Fun InP or video-related custom node packages

* [ComfyUI-VideoHelperSuite](https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite)
* [ComfyUI-WanVideoWrapper](https://github.com/kijai/ComfyUI-WanVideoWrapper)
* [ComfyUI-KJNodes](https://github.com/kijai/ComfyUI-KJNodes)


# ComfyUI Wan2.1 VACE Video Examples
Source: https://docs.comfy.org/tutorials/video/wan/vace

This article introduces how to complete Wan VACE video generation examples in ComfyUI

<Warning>
  As we have made adjustments to the template and added related usage and instructions for CausVid LoRA, this document needs to be updated and requires some preparation time. Until then, please refer to the notes in the template for usage.
</Warning>

## About VACE

VACE 14B is an open-source unified video editing model launched by the Alibaba Tongyi Wanxiang team. Through integrating multi-task capabilities, supporting high-resolution processing and flexible multi-modal input mechanisms, this model significantly improves the efficiency and quality of video creation.

The model is open-sourced under the [Apache-2.0](https://github.com/ali-vilab/VACE?tab=Apache-2.0-1-ov-file) license and can be used for personal or commercial purposes.

Here is a comprehensive analysis of its core features and technical highlights:

* Multi-modal input: supports multiple input forms including text, images, video, masks, and control signals
* Unified architecture: single model supports multiple tasks with freely combinable functions
* Motion transfer: generates coherent actions based on reference videos
* Local replacement: replaces specific areas in videos through masks
* Video extension: completes actions or extends backgrounds
* Background replacement: preserves subjects while changing environmental backgrounds

Currently VACE has released two versions: 1.3B and 14B. Compared to the 1.3B version, the 14B version supports 720P resolution output with better image details and stability.

| Model | 480P | 720P |
| - | - | - |
| [VACE-1.3B](https://huggingface.co/Wan-AI/Wan2.1-VACE-1.3B) | ✅ | ❌ |
| [VACE-14B](https://huggingface.co/Wan-AI/Wan2.1-VACE-14B) | ✅ | ✅ |

Related model weights and code repositories:

<CardGroup>
  <Card title="VACE-1.3B" icon="download" href="https://huggingface.co/Wan-AI/Wan2.1-VACE-1.3B">
    1.3B model weights on Hugging Face
  </Card>

  <Card title="VACE-14B" icon="download" href="https://huggingface.co/Wan-AI/Wan2.1-VACE-14B">
    14B model weights on Hugging Face
  </Card>

  <Card title="GitHub Repository" icon="github" href="https://github.com/ali-vilab/VACE">
    VACE source code and documentation
  </Card>

  <Card title="VACE Project Page" icon="globe" href="https://ali-vilab.github.io/VACE-Page/">
    Official project homepage with examples
  </Card>
</CardGroup>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Download and Loading in Workflows

Since the workflows covered in this document all use the same workflow template, we can first complete the model download and loading information introduction, then enable or disable different inputs through bypassing different nodes to achieve different workflows.
The model download information is already embedded in the workflow information in specific examples, so you can also complete the model download when downloading specific example workflows.

### Model Download

**Diffusion Models**

<CardGroup>
  <Card title="wan2.1_vace_14B_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_vace_14B_fp16.safetensors">
    VACE 14B diffusion model (recommended, \~32GB). Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="wan2.1_vace_1.3B_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_vace_1.3B_fp16.safetensors">
    VACE 1.3B diffusion model (lighter, \~7GB). Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

<Tip>
  If you have used Wan Video related workflows before, you have already downloaded the following model files.
</Tip>

**VAE**

<CardGroup>
  <Card title="wan_2.1_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
    Wan VAE model. Place in <code>ComfyUI/models/vae/</code>
  </Card>
</CardGroup>

**Text Encoders** (choose one version)

<CardGroup>
  <Card title="umt5_xxl_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp16.safetensors">
    Full precision text encoder (higher quality, larger size). Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
    FP8 text encoder (lower VRAM usage). Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

File save location:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └─── wan2.1_vace_14B_fp16.safetensors
│   ├── 📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors # or umt5_xxl_fp16.safetensors
│   └── 📂 vae/
│       └──  wan_2.1_vae.safetensors
```

### Model Loading

Since the models used in the workflows covered in this document are consistent, the workflows are also the same, and only the nodes are bypassed to enable or disable different inputs. Please refer to the following image to ensure that the corresponding models are correctly loaded in different workflows.

<img alt="Wan2.1 VACE Model Loading" />

1. Make sure the `Load Diffusion Model` node has loaded `wan2.1_vace_14B_fp16.safetensors`
2. Make sure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors` or `umt5_xxl_fp16.safetensors`
3. Make sure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`

### How to toggle Node Bypass Status

When a node is set to Bypass status, data passing through the node will not be affected by the node and will be output directly. We often set nodes to Bypass status when we don't need them.
Here are three ways to toggle a node's Bypass status:

<img alt="Toggle Bypass" />

1. After selecting the node, click the arrow in the indicator section of the selection toolbox to quickly toggle the node's Bypass status
2. After selecting the node, right-click the node and select `Mode` -> `Always` to switch to Always mode
3. After selecting the node, right-click the node and select the `Bypass` option to toggle the Bypass status

***

## 1. VACE Text-to-Video

**What it does:** Transform text descriptions into high-quality videos using the Wan2.1 VACE 14B model. Supports both 480p and 720p resolution.

### Wan2.1 VACE Text to Video

Transform text descriptions into high-quality videos. Supports both 480p and 720p with VACE-14B model.

<img alt="Wan2.1 VACE Text to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan_vace_14B_t2v&utm_source=docs&utm_medium=referral&utm_campaign=vace">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan_vace_14B_t2v.json">
    Download JSON or search "Wan2.1 VACE Text to Video" in Template Library
  </Card>
</CardGroup>

<video />

<Tip>
  If you cannot load the workflow from mp4 file, please ensure that your ComfyUI front-end version is up to date version in [requirements.txt](https://github.com/Comfy-Org/ComfyUI/blob/master/requirements.txt), make sure you can load the workflow from mp4 file.

  Currently 1.19.9 is the latest ComfyUI front-end version in the requirements.txt file.
</Tip>

### Steps to Run

<img alt="image" />

Please follow the numbered steps in the image to ensure smooth workflow execution:

1. Enter positive prompts in the `CLIP Text Encode (Positive Prompt)` node
2. Enter negative prompts in the `CLIP Text Encode (Negative Prompt)` node
3. Set the image dimensions (640x640 resolution recommended for first run) and frame count (video duration) in `WanVaceToVideo`
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation
5. Once generated, the video will automatically save to `ComfyUI/output/video` directory (subfolder location depends on `save video` node settings)

<Tip>
  During testing with a 4090 GPU:

  * 720x1280 resolution, generating 81 frames takes about 40 minutes
  * 640x640 resolution, generating 49 frames takes about 7 minutes

  However, 720P video quality is better.
</Tip>

***

## 2. VACE Image-to-Video

**What it does:** Generate videos that match the style and content of a reference image. Perfect for style-consistent video generation.

You can continue using the workflow above, just unbypass the `Load image` node in **Load reference image** and input your image. You can also use the image below. In this file we have already set up the corresponding parameters.

### Wan2.1 VACE Reference to Video

Create videos that match the style and content of a reference image. Perfect for style-consistent video generation.

<img alt="Wan2.1 VACE Reference to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan_vace_14B_ref2v&utm_source=docs&utm_medium=referral&utm_campaign=vace">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan_vace_14B_ref2v.json">
    Download JSON or search "Wan2.1 VACE Reference to Video" in Template Library
  </Card>
</CardGroup>

<video />

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="video_wan_vace_14B_ref2v_reference_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan_vace_14B_ref2v_reference_image.jpg">
    `LoadImage` node 73 · `video_wan_vace_14B_ref2v_reference_image.jpg`
  </Card>
</CardGroup>

<div>
  <img alt="video_wan_vace_14B_ref2v_reference_image.jpg" />
</div>

### Steps to Run

<img alt="Workflow Steps" />

Please follow the numbered steps in the image to ensure smooth workflow execution:

1. Input the corresponding image in the `Load image` node
2. You can modify and edit prompts like in the text-to-video workflow
3. Set the image dimensions (640x640 resolution recommended for first run) and frame count (video duration) in `WanVaceToVideo`
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation
5. Once generated, the video will automatically save to `ComfyUI/output/video` directory (subfolder location depends on `save video` node settings)

<Tip>
  You may want to use nodes like getting image dimensions to set the resolution, but due to width and height step requirements of the corresponding nodes, you may get error messages if your image dimensions are not divisible by 16.
</Tip>

### Additional Notes

VACE also supports inputting multiple reference images in a single image to generate corresponding videos. You can see related examples on the VACE project [page](https://ali-vilab.github.io/VACE-Page/).

***

## 3. VACE Video-to-Video

**What it does:** Generate videos by controlling input videos and reference images using Wan VACE. Control video style and motion through reference materials.

### Wan2.1 VACE Control Video

Generate videos by controlling input videos and reference images using Wan VACE.

<img alt="Wan2.1 VACE Control Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan_vace_14B_v2v&utm_source=docs&utm_medium=referral&utm_campaign=vace">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan_vace_14B_v2v.json">
    Download JSON or search "Wan2.1 VACE Control Video" in Template Library
  </Card>
</CardGroup>

<video />

We will use the following materials as input:

<CardGroup>
  <Card title="Reference Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/video_wan_vace_14B_v2v_reference_image.jpg">
    Input reference image for style and content.
  </Card>

  <Card title="Control Video (Preprocessed)" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/video_wan_vace_14B_v2v_reference_image_control_video.mp4">
    Preprocessed control video (depth). Use directly in <code>Load Video</code> under <strong>Load control video</strong>.
  </Card>
</CardGroup>

1. Input image for reference:

![v2v-input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/vace/v2v/input.jpg)

2. The video below has been preprocessed and will be used to control video generation:

<video />

3. The video below is the original video. You can download these materials and use preprocessing nodes like [comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) to preprocess the images:

<video />

### Steps to Run

<img alt="Workflow Steps" />

Please follow the numbered steps in the image to ensure smooth workflow execution:

1. Input the reference image in the `Load Image` node under **Load reference image**
2. Input the control video in the `Load Video` node under **Load control video**. Since the provided video is preprocessed, no additional processing is needed
3. If you need to preprocess the original video yourself, you can modify the **Image preprocessing** group or use `comfyui_controlnet_aux` nodes to complete the preprocessing
4. Modify prompts
5. Set the image dimensions (640x640 resolution recommended for first run) and frame count (video duration) in `WanVaceToVideo`
6. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation
7. Once generated, the video will automatically save to `ComfyUI/output/video` directory (subfolder location depends on `save video` node settings)

***

## 4. VACE Inpainting

**What it does:** Edit specific regions in videos while preserving surrounding content. Great for object removal or replacement.

### Wan2.1 VACE Inpainting

Edit specific regions in videos while preserving surrounding content. Great for object removal or replacement.

<img alt="Wan2.1 VACE Inpainting workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan_vace_inpainting&utm_source=docs&utm_medium=referral&utm_campaign=vace">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan_vace_inpainting.json">
    Download JSON or search "Wan2.1 VACE Inpainting" in Template Library
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Input Video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/video_wan_vace_inpainting_input_video.mp4">
    Input video for inpainting. Load in the <code>Load Video</code> node.
  </Card>

  <Card title="First Frame & Mask" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/video_wan_vace_inpainting_1st_frame_and_mask.png">
    First frame with mask overlay for inpainting region.
  </Card>

  <Card title="Reference Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/video_wan_vace_inpainting_reference_image.jpg">
    Reference image for inpainting content.
  </Card>
</CardGroup>

\[To be updated]

***

## 5. VACE Video Outpainting

**What it does:** Generate extended videos by expanding video size using Wan VACE outpainting.

### Wan2.1 VACE Outpainting

Generate extended videos by expanding video size using Wan VACE outpainting.

<img alt="Wan2.1 VACE Outpainting workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan_vace_outpainting&utm_source=docs&utm_medium=referral&utm_campaign=vace">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan_vace_outpainting.json">
    Download JSON or search "Wan2.1 VACE Outpainting" in Template Library
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Input Video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/video_wan_vace_outpainting_input_video.mp4">
    Input video for outpainting. Load in the <code>Load Video</code> node.
  </Card>
</CardGroup>

\[To be updated]

***

## 6. VACE First-Last Frame Video Generation

**What it does:** Generate smooth video transitions by defining start and end frames. Supports custom keyframe sequences.

### Wan2.1 VACE First-Last Frame

Generate smooth video transitions by defining start and end frames. Supports custom keyframe sequences.

<img alt="Wan2.1 VACE First-Last Frame workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan_vace_flf2v&utm_source=docs&utm_medium=referral&utm_campaign=vace">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan_vace_flf2v.json">
    Download JSON or search "Wan2.1 VACE First-Last Frame" in Template Library
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Start Frame" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/video_wan_vace_flf2v_start_image.png">
    Starting frame image. Load in the <code>Load Image</code> node.
  </Card>

  <Card title="End Frame" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/video_wan_vace_flf2v_end_image.png">
    Ending frame image. Load in the <code>Load Image</code> node.
  </Card>
</CardGroup>

To ensure that the first and last frames are effective, the video `length` setting must satisfy that `length-1` is divisible by 4.

The corresponding `Batch_size` setting must satisfy `Batch_size = length - 2`.

\[To be updated]


# Wan-Alpha Tutorial
Source: https://docs.comfy.org/tutorials/video/wan/wan-alpha

Learn how to generate videos with alpha channel transparency using Wan-Alpha in ComfyUI

Wan-Alpha is a specialized text-to-video model that generates high-quality videos with alpha channel transparency. Built on the Wan2.1-14B-T2V base model, it creates videos with transparent backgrounds and semi-transparent objects, perfect for compositing workflows.

The model excels at generating transparent backgrounds, semi-transparent objects (bubbles, glass, water), glowing effects, and fine details with proper alpha channels (hair, smoke, particles).

# Video tutorial

<iframe title="YouTube video player" />

## Resources

* [Wan-Alpha GitHub](https://github.com/WeChatCV/Wan-Alpha)
* [Hugging Face Model](https://huggingface.co/htdong/Wan-Alpha)
* [ComfyUI Version](https://huggingface.co/htdong/Wan-Alpha_ComfyUI)
* [Research Paper](https://arxiv.org/pdf/2509.24979)

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Wan-Alpha Text-to-Video Workflow (14B)

### 1. Download the Workflow

Update your ComfyUI to the latest version, then download and drag the workflow file into ComfyUI, or find "Wan 2.1 Alpha T2V 14B" in the Template Library under `Workflow` → `Browse Templates` → `Video`.

<img alt="Wan-Alpha T2V workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2.1_alpha_t2v_14B&utm_source=docs&utm_medium=referral&utm_campaign=wan-alpha">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2.1_alpha_t2v_14B.json">
    Download JSON or search "Wan 2.1 Alpha T2V 14B" in Template Library
  </Card>
</CardGroup>

### 2. Install Models

All models mentioned can be found at [Wan\_2.1\_ComfyUI\_repackaged](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged).

**Diffusion Models** : Choose one version:

<CardGroup>
  <Card title="wan2.1_t2v_14B_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_t2v_14B_fp8_scaled.safetensors?download=true">
    FP8 scaled diffusion model. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="wan2.1_t2v_14B_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_t2v_14B_bf16.safetensors?download=true">
    BF16 diffusion model. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

**Text Encoder**

<CardGroup>
  <Card title="umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true">
    FP8 text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

**VAE Models**

<CardGroup>
  <Card title="wan_alpha_2.1_vae_rgb_channel.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_alpha_2.1_vae_rgb_channel.safetensors?download=true">
    RGB channel VAE. Place in <code>ComfyUI/models/vae/</code>
  </Card>

  <Card title="wan_alpha_2.1_vae_alpha_channel.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_alpha_2.1_vae_alpha_channel.safetensors?download=true">
    Alpha channel VAE. Place in <code>ComfyUI/models/vae/</code>
  </Card>
</CardGroup>

**LoRA Models**

<CardGroup>
  <Card title="wan_alpha_2.1_rgba_lora.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/loras/wan_alpha_2.1_rgba_lora.safetensors?download=true">
    Alpha generation LoRA. Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors" icon="download" href="https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Lightx2v/lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors?download=true">
    Lightning LoRA for fast inference. Place in <code>ComfyUI/models/loras/</code>
  </Card>
</CardGroup>

File storage locations:

```
ComfyUI/
├── models/
│   ├── diffusion_models/
│   │   ├── wan2.1_t2v_14B_fp8_scaled.safetensors
│   │   └── wan2.1_t2v_14B_bf16.safetensors
│   ├── text_encoders/
│   │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   ├── vae/
│   │   ├── wan_alpha_2.1_vae_rgb_channel.safetensors
│   │   └── wan_alpha_2.1_vae_alpha_channel.safetensors
│   └── loras/
│       ├── wan_alpha_2.1_rgba_lora.safetensors
│       └── lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors
```

### 3. Complete the Workflow Step by Step

1. Ensure the correct diffusion model is loaded in the `Load Diffusion Model` node
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node for RGB has loaded `wan_alpha_2.1_vae_rgb_channel.safetensors`
4. Ensure the second `Load VAE` node for Alpha has loaded `wan_alpha_2.1_vae_alpha_channel.safetensors`
5. Ensure the `LoRA Loader` node has loaded `wan_alpha_2.1_rgba_lora.safetensors`
6. (Optional) Load `lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors` in the Lightning LoRA node for faster generation
7. Set your positive prompt in the `CLIP Text Encode (Positive Prompt)` node
8. (Optional) Modify video dimensions in the `EmptyHunyuanLatentVideo` node
9. Click the `Run` button or use `Ctrl(Cmd) + Enter` to execute generation


# Wan Animate 2: Motion Transfer
Source: https://docs.comfy.org/tutorials/video/wan/wan-animate-2

Animate a still character with Wan Animate 2 in ComfyUI: transfer motion from a driving video directly, with no pose extraction or skeleton preprocessing.

Wan Animate 2 is an end-to-end character animation framework from the Wan team that directly consumes driving videos in a redesigned Diffusion Transformer. It achieves high-fidelity motion generation and strong identity preservation by eliminating intermediate motion extractors: no pose extraction or skeleton preprocessing is needed.

The model also adds text-driven viewpoint control, decoupling the output camera perspective from the driving video. This lets you animate a still character using a driving video while controlling the camera independently, and even generate a fresh background from your text prompt.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Highlights

* **Direct motion transfer**: Animates a still character from a driving video without pose extraction or skeleton preprocessing
* **Identity preservation**: Keeps the reference character's identity, appearance, and details intact
* **Text-driven camera control**: Decouples output camera perspective from the driving video
* **Fresh backgrounds**: Generates a new background from your text prompt instead of copying the driving video's background
* **High-fidelity motion**: Replicates complex motions and expressions from the driving video

## Wan Animate 2 workflow

Animate a still character using a driving video, transferring motion directly from video frames. The output preserves the reference character's identity while generating a fresh background and camera movement from your text prompt.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan_animate2&utm_source=docs&utm_medium=referral&utm_campaign=wan-animate-2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan_animate2.json">
    Download JSON or search "Wan Animate 2" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching nodes:

<CardGroup>
  <Card title="Reference image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/pink_hair_mech_arms_ref.png">
    `LoadImage` node: pink\_hair\_mech\_arms\_ref.png (the character to animate)
  </Card>

  <Card title="Driving video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/street_dance_drive.mp4">
    `LoadVideo` node: street\_dance\_drive.mp4 (the motion source)
  </Card>
</CardGroup>

### Model downloads

This workflow uses the `wan_animate_2_int8_convrot.safetensors` diffusion model. The repository also ships BF16 and distilled variants; if you want to use those instead, change the model selection in the `UNETLoader` node. All files are available in the [Comfy-Org/Wan-Animate-2](https://huggingface.co/Comfy-Org/Wan-Animate-2) repository:

<CardGroup>
  <Card title="Diffusion Model (INT8, required)" icon="download" href="https://huggingface.co/Comfy-Org/Wan-Animate-2/blob/main/diffusion_models/wan_animate_2_int8_convrot.safetensors">
    wan\_animate\_2\_int8\_convrot.safetensors: INT8 convrot quantized diffusion model used by this workflow
  </Card>

  <Card title="Diffusion Model (BF16, optional)" icon="download" href="https://huggingface.co/Comfy-Org/Wan-Animate-2/blob/main/diffusion_models/wan_animate_2_bf16.safetensors">
    wan\_animate\_2\_bf16.safetensors: Full-precision base model. Requires changing the UNETLoader model selection.
  </Card>

  <Card title="Diffusion Model (Distill INT8, optional)" icon="download" href="https://huggingface.co/Comfy-Org/Wan-Animate-2/blob/main/diffusion_models/wan_animate_2_distill_int8_convrot.safetensors">
    wan\_animate\_2\_distill\_int8\_convrot.safetensors: Distilled INT8 variant. Requires changing the UNETLoader model selection.
  </Card>

  <Card title="Diffusion Model (Distill BF16, optional)" icon="download" href="https://huggingface.co/Comfy-Org/Wan-Animate-2/blob/main/diffusion_models/wan_animate_2_distill_bf16.safetensors">
    wan\_animate\_2\_distill\_bf16.safetensors: Distilled BF16 variant. Requires changing the UNETLoader model selection.
  </Card>

  <Card title="LoRA" icon="download" href="https://huggingface.co/Comfy-Org/Wan-Animate-2/blob/main/loras/lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors">
    lightx2v\_I2V\_14B\_480p\_cfg\_step\_distill\_rank64\_bf16.safetensors: LightX2V acceleration LoRA
  </Card>

  <Card title="Text Encoder" icon="download" href="https://huggingface.co/Comfy-Org/Wan-Animate-2/blob/main/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
    umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors: UMT5-XXL FP8 text encoder
  </Card>

  <Card title="CLIP Vision" icon="download" href="https://huggingface.co/Comfy-Org/Wan-Animate-2/blob/main/clip_vision/clip_vision_h.safetensors">
    clip\_vision\_h.safetensors: CLIP Vision encoder
  </Card>

  <Card title="VAE" icon="download" href="https://huggingface.co/Comfy-Org/Wan-Animate-2/blob/main/vae/Wan2_1_VAE_bf16.safetensors">
    Wan2\_1\_VAE\_bf16.safetensors: Wan2.1 VAE for encoding and decoding
  </Card>
</CardGroup>

Place the files in the following directories:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── wan_animate_2_bf16.safetensors
│   │   ├── wan_animate_2_distill_bf16.safetensors
│   │   ├── wan_animate_2_distill_int8_convrot.safetensors
│   │   └── wan_animate_2_int8_convrot.safetensors
│   ├── 📂 loras/
│   │   └── lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors
│   ├── 📂 text_encoders/
│   │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   ├── 📂 clip_vision/
│   │   └── clip_vision_h.safetensors
│   └── 📂 vae/
│       └── Wan2_1_VAE_bf16.safetensors
```

### Workflow instructions

1. Make sure all the models are loaded correctly
2. Upload the reference image: the character in this image is the target character to animate
3. Upload the driving video: its motion is transferred to the reference character
4. Update the prompt to describe the scene, background, and camera movement you want
5. Click `Run` or use the shortcut `Ctrl(cmd) + Enter` to generate the video


# Wan ATI Native Workflow
Source: https://docs.comfy.org/tutorials/video/wan/wan-ati

Wan ATI trajectory control in ComfyUI: draw trajectories to direct object, region, and camera motion in generated video, built on Wan2.1.

**ATI (Any Trajectory Instruction)** is a controllable video generation framework proposed by the ByteDance team. ATI is implemented based on Wan2.1 and supports unified control of objects, local regions, and camera motion in videos through arbitrary trajectory instructions.

<CardGroup>
  <Card title="Project Repository" icon="github" href="https://github.com/bytedance/ATI">
    ATI source code and documentation on GitHub
  </Card>

  <Card title="Online Trajectory Editing Tool" icon="pencil" href="https://comfyui-wiki.github.io/Trajectory-Annotation-Tool/">
    Visual tool to draw and edit motion trajectories on images
  </Card>
</CardGroup>

## Key Features

* **Unified Motion Control**: Supports trajectory control for multiple motion types including objects, local regions, and camera movements.
* **Interactive Trajectory Editor**: Visual tool that allows users to freely draw and edit motion trajectories on images.
* **Wan2.1 Compatible**: Based on the official Wan2.1 implementation, compatible with environments and model structures.
* **Rich Visualization Tools**: Supports visualization of input trajectories, output videos, and trajectory overlays.

## WAN ATI Trajectory Control Workflow Example

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### 1. Workflow Download

Update your ComfyUI to the latest version, then download and drag the workflow file into ComfyUI, or find "Wan2.1 ATI" in the Template Library under `Workflow` → `Browse Templates` → `Video`.

![Wan2.1 ATI Workflow Preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_wan_ati-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan_ati&utm_source=docs&utm_medium=referral&utm_campaign=wan-ati">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan_ati.json">
    Download JSON or search "Wan2.1 ATI" in Template Library
  </Card>
</CardGroup>

<video />

We will use the following image as input:

<CardGroup>
  <Card title="Input Image: video_wan_ati_input_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan_ati_input_image.jpg">
    Download the default input image, or use your own image as the starting frame.
  </Card>
</CardGroup>

<video />

### 2. Manual Model Installation

All models involved in this guide can be found [here](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files).

**Diffusion Model** : Choose one version:

<CardGroup>
  <Card title="Diffusion Model: Wan2_1-I2V-ATI-14B_fp8_e4m3fn.safetensors" icon="download" href="https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Wan2_1-I2V-ATI-14B_fp8_e4m3fn.safetensors">
    Wan2.1 I2V ATI 14B diffusion model (fp8 precision). Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

**Text Encoders** : Choose one version:

<CardGroup>
  <Card title="Text Encoder: umt5_xxl_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp16.safetensors">
    Full precision text encoder (higher quality, larger size). Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Text Encoder: umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
    FP8 text encoder (lower VRAM usage). Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

**VAE**

<Card title="VAE: wan_2.1_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
  Wan2.1 VAE model. Place in <code>ComfyUI/models/vae/</code>
</Card>

**CLIP Vision**

<Card title="CLIP Vision: clip_vision_h.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors">
  CLIP Vision model for processing reference images. Place in <code>ComfyUI/models/clip\_vision/</code>
</Card>

**File Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── Wan2_1-I2V-ATI-14B_fp8_e4m3fn.safetensors
│   ├── 📂 text_encoders/
│   │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors  # or your chosen version
│   ├── 📂 clip_vision/
│   │   └── clip_vision_h.safetensors
│   └── 📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Complete the Workflow Execution Step by Step

<img alt="Workflow step diagram" />

Please follow the numbered steps in the image to ensure smooth execution of the corresponding workflow.

1. Ensure the `Load Diffusion Model` node has loaded the `Wan2_1-I2V-ATI-14B_fp8_e4m3fn.safetensors` model
2. Ensure the `Load CLIP` node has loaded the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
3. Ensure the `Load VAE` node has loaded the `wan_2.1_vae.safetensors` model
4. Ensure the `Load CLIP Vision` node has loaded the `clip_vision_h.safetensors` model
5. Upload the provided input image in the `Load Image` node
6. Trajectory editing: Currently there is no corresponding trajectory editor in ComfyUI yet. You can use the following link to complete trajectory editing.
   * [Online Trajectory Editing Tool](https://comfyui-wiki.github.io/Trajectory-Annotation-Tool/)
7. If you need to modify the prompts (positive and negative), please make changes in the `CLIP Text Encoder` node numbered `5`
8. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation


# Causal Forcing I2V ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/video/wan/wan-causal-forcing

Generate videos from images using Causal Forcing or Causal Forcing++ with Wan2.1. Achieves smooth, temporally consistent video in as few as 1 inference step.

**Causal Forcing** is a video generation technique that applies **recurrent conditioning** during inference, where each generated frame is fed back into the model to predict the next frame. This produces smooth, temporally consistent videos from a single start image in as few as **1 to 4 inference steps**.

This workflow uses **Wan2.1** and supports both **Causal Forcing** (standard) and **Causal Forcing++** (enhanced) modes.

<img alt="Causal Forcing I2V workflow" />

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_causal_forcing_i2v&utm_source=docs&utm_medium=referral&utm_campaign=wan-causal-forcing">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_causal_forcing_i2v.json">
    Download JSON or search "Causal Forcing" in Template Library
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="girl_riding_a_wolf.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/girl_riding_a_wolf.png">
    Input image for the first frame. Download and use this image, or replace with your own.
  </Card>
</CardGroup>

## How it works

Unlike standard video generation which processes all frames in parallel, Causal Forcing treats video generation as a **sequential process**:

1. The model takes an input image as the **first frame**
2. It generates the next frame conditioned on the previous one
3. Each new frame becomes the input for the next prediction
4. This repeats for the desired number of frames

This recurrent approach creates **strong temporal consistency**: each frame naturally follows from the one before it. This can produce high-quality results with very few inference steps (1 to 4).

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses a Subgraph node for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Causal Forcing vs Causal Forcing++

| Mode | Description |
| - | - |
| **Causal Forcing** | Standard recurrent conditioning. Good quality with 2–4 steps. |
| **Causal Forcing++** | Enhanced mode that applies additional conditioning for better temporal coherence. Works well with just 1–2 steps. |

## Using the workflow

### Inputs

The workflow accepts a single input image (the first frame) and a text prompt describing the desired video content (optional).

| Setting | Description |
| - | - |
| **first\_frame** (required) | The starting image for the video. Load a PNG/JPG via the **LoadImage** node. |
| **positive\_prompt** (optional) | A text description of the desired video content. Leave empty for no conditioning. |
| **duration** (optional) | The number of frames to generate. Default: number of frames in the model's expected output. |

### WAN I2V subgraph parameters

These are exposed as controls on the blueprint subgraph node:

\| Parameter | Default | Description |
||---|---|---|
\| `unet_name` | - | The Wan2.1 I2V model checkpoint to use |
\| `clip_name` | - | The CLIP / text encoder model for the prompt |
\| `vae_name` | - | The VAE model for encoding/decoding |
\| `width` | - | Output video width |
\| `height` | - | Output video height |
\| `noise_seed` | - | Seed for reproducibility |

## Steps to run

1. **Load an image**: use the **LoadImage** node to load your starting frame
2. **Write a prompt** (optional): describe the desired video content
3. **Set duration**: how many frames to generate
4. **Select models**: choose Wan2.1 I2V checkpoint, CLIP, and VAE
5. **Choose mode**: Causal Forcing or Causal Forcing++ (set via the subgraph's internal configuration or a Causal Forcing-specific input if available)
6. **Run**: frames will be generated sequentially and saved to `ComfyUI/output/`

## Model downloads

Download the Wan2.1 I2V model and required files. Place them in the corresponding `models/` subdirectories.

### Wan2.1 I2V

<CardGroup>
  <Card title="Wan2.1 I2V 14B" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_i2v_480p_14B_fp16.safetensors?download=true">
    wan2.1\_i2v\_480p\_14B\_fp16.safetensors - Wan2.1 I2V 14B checkpoint
  </Card>

  <Card title="Wan2.1 I2V 1.3B" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_t2v_1.3B_fp16.safetensors?download=true">
    wan2.1\_t2v\_1.3B\_fp16.safetensors - Wan2.1 1.3B checkpoint (8GB VRAM minimum)
  </Card>
</CardGroup>

### CLIP and VAE

<CardGroup>
  <Card title="CLIP (google-bert)" icon="download" href="https://huggingface.co/google-bert/bert-base-uncased/blob/main/model.safetensors">
    google-bert/bert-base-uncased - CLIP text encoder
  </Card>

  <Card title="VAE (Wan2.1)" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/Wan2.1_VAE_bf16.safetensors?download=true">
    Wan2.1\_VAE\_bf16.safetensors - Wan2.1 VAE
  </Card>
</CardGroup>

### Model storage location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │      └── wan2.1_i2v_480p_14B_fp16.safetensors (or 1.3B variant)
│   ├── 📂 text_encoders/
│   │      └── bert-base-uncased (folder with model.safetensors)
│   └── 📂 vae/
│          └── Wan2.1_VAE_bf16.safetensors
```


# Wan Dancer: Music to Dance Video Generation
Source: https://docs.comfy.org/tutorials/video/wan/wan-dancer

Create synchronized dance videos from music with Wan Dancer in ComfyUI. Use a reference image and audio to generate coherent, expressive dance motion.

Wan Dancer is an audio-driven dance video generation model built on the Wan 2.2 architecture. It uses a hierarchical framework with global and local expert models to generate coherent, expressive dance videos synchronized to input music.

Given a reference image of a character and an audio track, Wan Dancer produces a dance video where the character performs movements that match the rhythm and style of the music. The global model captures overall dance structure and body coordination, while the local model refines fine-grained motion details for natural, high-quality output.

## Model Highlights

* **Audio-driven dance generation**: Generates dance movements directly from music without manual keyframing or motion capture
* **Hierarchical framework**: Two-stage architecture (global + local) for coherent body motion and detailed movement refinement
* **Music-synchronized output**: Dance motions are naturally aligned to the input audio's rhythm and tempo
* **Style control**: Configurable dance style and motion amplitude for creative direction
* **Minute-scale generation**: Produces long-form, coherent dance videos with temporal consistency across the full duration

## Workflow Overview

The Wan Dancer workflow takes two inputs: a reference image of the character and an audio file. It generates two video outputs: a global output preview showing the overall dance structure, and a final refined output with enhanced motion details.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Wan Dancer Workflow

### Wan Dancer: Music to Dance

Generate minute-scale coherent dance videos from music using a hierarchical Wan Dancer framework. Input a music file and reference image to produce synchronized dance videos.

<img alt="Wan Dancer: Music to Dance workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan_dancer&utm_source=docs&utm_medium=referral&utm_campaign=wan-dancer">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan_dancer.json">
    Download JSON or search "Wan Dancer" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching nodes:

<CardGroup>
  <Card title="blue_dancer.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/blue_dancer.png">
    `LoadImage` node 547 · `blue_dancer.png`
  </Card>

  <Card title="wan_dancer_reference_audio.mp3" icon="music" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wan_dancer_reference_audio.mp3">
    `LoadAudio` node 548 · `wan_dancer_reference_audio.mp3`
  </Card>
</CardGroup>

<div>
  <img alt="blue_dancer.png" />
</div>

### 3. Manually Download Models

**Diffusion Models**

* [wan2.2\_dancer\_14b\_global\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan-Dancer/blob/main/diffusion_models/wan2.2_dancer_14b_global_fp8_scaled.safetensors)
* [wan2.2\_dancer\_14b\_local\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan-Dancer/blob/main/diffusion_models/wan2.2_dancer_14b_local_fp8_scaled.safetensors)

**LoRA**

* [lightx2v\_I2V\_14B\_480p\_cfg\_step\_distill\_rank64\_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors)

**Text Encoder**

* [umt5\_xxl\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp16.safetensors)

**CLIP Vision**

* [clip\_vision\_h.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors)

**VAE**

* [Wan2\_1\_VAE\_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Wan2_1_VAE_bf16.safetensors)

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_dancer_14b_global_fp8_scaled.safetensors
│   │   └─── wan2.2_dancer_14b_local_fp8_scaled.safetensors
│   ├───📂 loras/
│   │   └─── lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp16.safetensors
│   ├───📂 clip_vision/
│   │   └─── clip_vision_h.safetensors
│   └───📂 vae/
│       └── Wan2_1_VAE_bf16.safetensors
```

### 4. Workflow Instructions

<Tip>
  Wan Dancer samples 149 frames at once and requires significant VRAM. The default workflow outputs a 5-second video. Make sure you have a GPU with sufficient VRAM before running this workflow.
</Tip>

1. **Load the reference image**: Use the `Load Image` node to upload your character image. The default input uses `blue_dancer.png`.

2. **Load the audio file**: Use the `Load Audio` node to upload your music or audio track. The default input uses `wan_dancer_reference_audio.mp3`.

3. **Configure dance parameters**:
   * `dance_style`: Select the dance style for the output video
   * `motion_amplitude`: Control the intensity of dance movements
   * `audio_duration`: Set to match the duration of your input audio
   * `final_duration`: Choose the final output video duration

4. **Configure output dimensions**:
   * `width` and `height`: Set the resolution of the output video. Choose values appropriate for your GPU's available VRAM.

5. **Verify model paths**: Make sure the model selector widgets point to the correct model files:
   * `global_model`: Should load `wan2.2_dancer_14b_global_fp8_scaled.safetensors`
   * `local_model`: Should load `wan2.2_dancer_14b_local_fp8_scaled.safetensors`
   * `lightning_lora`: Should load `lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors`
   * `clip_vision`: Should load `clip_vision_h.safetensors`

6. **Run generation**: Click the `Run` button or use the shortcut `Ctrl(Cmd) + Enter` to execute video generation.

### 5. Output

The workflow produces two video outputs:

* **Global output preview**: Shows the overall dance structure generated by the global model
* **Final output**: The refined dance video after local model enhancement

Both outputs are saved automatically via the `SaveVideo` nodes.

## Model Information

Wan Dancer is an open source model released under the Apache 2.0 license. The model weights are available on Hugging Face:

* [Comfy-Org/Wan-Dancer](https://huggingface.co/Comfy-Org/Wan-Dancer): Global and local diffusion models

## Report Issues

If you encounter runtime errors or unexpected behavior:

* Ensure ComfyUI is updated to the latest version
* Check that all required models are downloaded and placed in the correct directories
* For Desktop/Cloud users: updates follow stable releases, so nightly-supported models may not be available immediately

Report issues to: [ComfyUI/issues](https://github.com/Comfy-Org/ComfyUI/issues)


# ComfyUI Wan2.1 FLF2V Native Example
Source: https://docs.comfy.org/tutorials/video/wan/wan-flf

This guide explains how to complete Wan2.1 FLF2V video generation examples in ComfyUI

Wan FLF2V (First-Last Frame Video Generation) is an open-source video generation model developed by the Alibaba Tongyi Wanxiang team. Its open-source license is [Apache 2.0](https://github.com/Wan-Video/Wan2.1?tab=Apache-2.0-1-ov-file).
Users only need to provide two images as the starting and ending frames, and the model automatically generates intermediate transition frames, outputting a logically coherent and naturally flowing 720p high-definition video.

**Core Technical Highlights**

1. **Precise First-Last Frame Control**: The matching rate of first and last frames reaches 98%, defining video boundaries through starting and ending scenes, intelligently filling intermediate dynamic changes to achieve scene transitions and object morphing effects.
2. **Stable and Smooth Video Generation**: Using CLIP semantic features and cross-attention mechanisms, the video jitter rate is reduced by 37% compared to similar models, ensuring natural and smooth transitions.
3. **Multi-functional Creative Capabilities**: Supports dynamic embedding of Chinese and English subtitles, generation of anime/realistic/fantasy and other styles, adapting to different creative needs.
4. **720p HD Output**: Directly generates 1280x720 resolution videos without post-processing, suitable for social media and commercial applications.
5. **Open-source Ecosystem Support**: Model weights, code, and training framework are fully open-sourced, supporting deployment on mainstream AI platforms.

**Technical Principles and Architecture**

1. **DiT Architecture**: Based on diffusion models and Diffusion Transformer architecture, combined with Full Attention mechanism to optimize spatiotemporal dependency modeling, ensuring video coherence.
2. **3D Causal Variational Encoder**: Wan-VAE technology compresses HD frames to 1/128 size while retaining subtle dynamic details, significantly reducing memory requirements.
3. **Three-stage Training Strategy**: Starting from 480P resolution pre-training, gradually upgrading to 720P, balancing generation quality and computational efficiency through phased optimization.

**Related Links**

* **GitHub Repository**: [GitHub](https://github.com/Wan-Video/Wan2.1)
* **Hugging Face Model Page**: [Hugging Face](https://huggingface.co/Wan-AI/Wan2.1-FLF2V-14B-720P)
* **ModelScope Community**: [ModelScope](https://www.modelscope.cn/models/Wan-AI/Wan2.1-FLF2V-14B-720P)

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Wan2.1 FLF2V 720P ComfyUI Native Workflow Example

### 1. Download Workflow Files and Related Input Files

<Tip>
  Since this model is trained on high-resolution images, using smaller sizes may not yield good results. In the example, we use a size of 720 \* 1280, which may cause users with lower VRAM hard to run smoothly and will take a long time to generate.
  If needed, please adjust the video generation size for testing. A small generation size may not produce good output with this model, please notice that.
</Tip>

Update your ComfyUI to the latest version, then download and drag the workflow file into ComfyUI, or find "Wan2.1 FLF2V 720P" in the Template Library under `Workflow` → `Browse Templates` → `Video`.

![Wan2.1 FLF2V 720P Workflow Preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/wan2.1_flf2v_720_f16-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=wan2.1_flf2v_720_f16&utm_source=docs&utm_medium=referral&utm_campaign=wan-flf">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/wan2.1_flf2v_720_f16.json">
    Download JSON or search "Wan2.1 FLF2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Start Image: wan2.1_flf2v_720_f16_start_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wan2.1_flf2v_720_f16_start_image.png">
    Starting frame for the video generation (LoadImage node 52). Download and use this image, or replace with your own.
  </Card>

  <Card title="End Image: wan2.1_flf2v_720_f16_end_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wan2.1_flf2v_720_f16_end_image.png">
    Ending frame for the video generation (LoadImage node 72). Download and use this image, or replace with your own.
  </Card>
</CardGroup>

### 2. Manual Model Installation

All models involved in this guide can be found [here](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files).

**Diffusion Models** : Choose one version based on your hardware

<CardGroup>
  <Card title="Diffusion Model: Wan2.1 FLF2V 14B FP16" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_flf2v_720p_14B_fp16.safetensors">
    wan2.1\_flf2v\_720p\_14B\_fp16.safetensors : Full precision, requires more VRAM. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="Diffusion Model: Wan2.1 FLF2V 14B FP8" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_flf2v_720p_14B_fp8_e4m3fn.safetensors">
    wan2.1\_flf2v\_720p\_14B\_fp8\_e4m3fn.safetensors : Quantized version, lower VRAM usage. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

<Tip>
  If you have previously tried Wan Video related workflows, you may already have the following files.
</Tip>

**Text Encoders** : Choose one version

<CardGroup>
  <Card title="Text Encoder: UMT5 XXL FP16" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp16.safetensors">
    umt5\_xxl\_fp16.safetensors : Full precision text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="Text Encoder: UMT5 XXL FP8" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
    umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors : Quantized text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

**VAE**

<Card title="VAE: Wan2.1 VAE" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
  wan\_2.1\_vae.safetensors : Wan2.1 VAE for encoding/decoding. Place in <code>ComfyUI/models/vae/</code>
</Card>

**CLIP Vision**

<Card title="CLIP Vision: CLIP Vision H" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors">
  clip\_vision\_h.safetensors : CLIP Vision encoder. Place in <code>ComfyUI/models/clip\_vision/</code>
</Card>

File Storage Location

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   └─── wan2.1_flf2v_720p_14B_fp16.safetensors           # or FP8 version
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors           # or your chosen version
│   ├───📂 vae/
│   │   └─── wan_2.1_vae.safetensors
│   └───📂 clip_vision/
│       └─── clip_vision_h.safetensors   
```

### 3. Complete Workflow Execution Step by Step

<img alt="Wan2.1 FLF2V 720P Native Workflow Steps" />

1. Ensure the `Load Diffusion Model` node has loaded `wan2.1_flf2v_720p_14B_fp16.safetensors` or `wan2.1_flf2v_720p_14B_fp8_e4m3fn.safetensors`
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Ensure the `Load CLIP Vision` node has loaded `clip_vision_h.safetensors`
5. Upload the starting frame to the `Start_image` node
6. Upload the ending frame to the `End_image` node
7. (Optional) Modify the positive and negative prompts, both Chinese and English are supported
8. (**Important**) In `WanFirstLastFrameToVideo` we use 720*1280 as default size.because it's a 720P model, so using a small size will not yield good output. Please use size around 720*1280 for good generation.
9. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation


# ComfyUI Wan-Move Workflow Example
Source: https://docs.comfy.org/tutorials/video/wan/wan-move

Generate motion-controllable video with Wan-Move in ComfyUI: guide object motion with point trajectories for precise image-to-video generation.

**Wan-Move** is a motion-controllable video generation framework developed by Alibaba's Tongyi Lab. It enables users to control object motion in generated videos by specifying point trajectories on the input image, making image-to-video generation more precise and controllable.

**Key Features**:

* **High-Quality 5s 480p Motion Control**: Generates 5-second, 480p videos with fine-grained motion controllability
* **Latent Trajectory Guidance**: Represents motion conditions by propagating first frame features along trajectories
* **Fine-grained Point-level Control**: Object motions are represented with dense point trajectories, enabling precise region-level control
* **No Architecture Changes**: Seamlessly integrates into Wan-I2V-14B without extra motion modules

**Related Links**:

* [GitHub](https://github.com/ali-vilab/Wan-Move)
* [Hugging Face](https://huggingface.co/Ruihang/Wan-Move-14B-480P)
* [Paper](https://arxiv.org/abs/2512.08765)

## Wan-Move image-to-video workflow

Preview the workflow output:

![Wan-Move preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_wanmove_480p-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wanmove_480p&utm_source=docs&utm_medium=referral&utm_campaign=wan-move">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wanmove_480p.json">
    Download JSON or search "Wan-Move Motion-Control" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="snowboard_rush.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/snowboard_rush.png">
    `LoadImage` node · `snowboard_rush.png`
  </Card>
</CardGroup>

<div>
  <img alt="snowboard_rush.png" />
</div>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model links

<CardGroup>
  <Card title="Checkpoint: Wan21-WanMove" icon="download" href="https://huggingface.co/Kijai/WanVideo_comfy_fp8_scaled/blob/main/WanMove/Wan21-WanMove_fp8_scaled_e4m3fn_KJ.safetensors">
    Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="LoRA: LightX2V Distilled" icon="download" href="https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors">
    Place in <code>ComfyUI/models/loras/</code>
  </Card>

  <Card title="Text Encoder: umt5" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
    Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="CLIP Vision: clip_vision_h" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors">
    Place in <code>ComfyUI/models/clip\_vision/</code>
  </Card>

  <Card title="VAE: wan_2.1_vae" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
    Place in <code>ComfyUI/models/vae/</code>
  </Card>
</CardGroup>

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   ├── 📂 clip_vision/
│   │      └── clip_vision_h.safetensors
│   ├── 📂 loras/
│   │      └── lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors
│   ├── 📂 diffusion_models/
│   │      └── Wan21-WanMove_fp8_scaled_e4m3fn_KJ.safetensors
│   └── 📂 vae/
│          └── wan_2.1_vae.safetensors
```


# ComfyUI Wan2.1 Video Examples
Source: https://docs.comfy.org/tutorials/video/wan/wan-video

Run Wan2.1 video workflows in ComfyUI: text-to-video with the 1.3B model and image-to-video with the 14B model, including model installation.

Wan2.1 Video series is a video generation model open-sourced by Alibaba in February 2025 under the [Apache 2.0 license](https://github.com/Wan-Video/Wan2.1?tab=Apache-2.0-1-ov-file).
It offers two versions:

* 14B (14 billion parameters)
* 1.3B (1.3 billion parameters)
  Covering multiple tasks including text-to-video (T2V) and image-to-video (I2V).
  The model not only outperforms existing open-source models in performance but more importantly, its lightweight version requires only 8GB of VRAM to run, significantly lowering the barrier to entry.

<video>
  <source type="video/mp4" />
</video>

* [Wan2.1 Code Repository](https://github.com/Wan-Video/Wan2.1)
* [Wan2.1 Model Repository](https://huggingface.co/Wan-AI)

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Wan2.1 ComfyUI Native Workflow Examples

<Tip>
  Please update ComfyUI to the latest version before starting the examples to make sure you have native Wan Video support.
</Tip>

## Model Installation

All models mentioned in this guide can be found [here](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files). Below are the common models you'll need for the examples in this guide, which you can download in advance:

Choose one version from **Text encoders** to download:

<CardGroup>
  <Card title="umt5_xxl_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp16.safetensors?download=true">
    FP16 precision text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>

  <Card title="umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true">
    FP8 scaled text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

**VAE**

<Card title="wan_2.1_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors?download=true">
  Wan2.1 VAE model. Place in <code>ComfyUI/models/vae/</code>
</Card>

**CLIP Vision**

<Card title="clip_vision_h.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors?download=true">
  CLIP Vision model for image conditioning. Place in <code>ComfyUI/models/clip\_vision/</code>
</Card>

File storage locations:

```
ComfyUI/
├── models/
│   ├── diffusion_models/
│   │   └── ... (download per workflow below)
│   ├── text_encoders/
│   │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   ├── vae/
│   │   └── wan_2.1_vae.safetensors
│   └── clip_vision/
│       └── clip_vision_h.safetensors
```

<Note>
  For diffusion models, we'll use the fp16 precision models in this guide because we've found that they perform better than the bf16 versions. If you need other precision versions, please visit [here](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/diffusion_models) to download them.
</Note>

## Wan2.1 Text-to-Video Workflow (1.3B)

### Wan 2.1 Text to Video

Generate videos from text prompts using Wan 2.1.

<img alt="Wan 2.1 Text to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=text_to_video_wan&utm_source=docs&utm_medium=referral&utm_campaign=wan-video">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/text_to_video_wan.json">
    Download JSON or search "Wan 2.1 Text to Video" in Template Library
  </Card>
</CardGroup>

### Model Downloads

<Card title="wan2.1_t2v_1.3B_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_t2v_1.3B_fp16.safetensors?download=true">
  Diffusion model for Wan2.1 Text-to-Video. Place in <code>ComfyUI/models/diffusion\_models/</code>
</Card>

> If you need other t2v precision versions, please visit [here](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/diffusion_models) to download them.

### Steps to Run

<img alt="ComfyUI Wan2.1 Workflow Steps" />

1. Make sure the `Load Diffusion Model` node has loaded the `wan2.1_t2v_1.3B_fp16.safetensors` model
2. Make sure the `Load CLIP` node has loaded the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
3. Make sure the `Load VAE` node has loaded the `wan_2.1_vae.safetensors` model
4. (Optional) You can modify the video dimensions in the `EmptyHunyuanLatentVideo` node if needed
5. (Optional) If you need to modify the prompts (positive and negative), make changes in the `CLIP Text Encoder` node at number `5`
6. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the video generation

## Wan2.1 Image-to-Video Workflow (14B)

**Since Wan Video separates the 480P and 720P models**, we'll need to provide examples for both resolutions in this guide. In addition to using different models, they also have slight parameter differences.

### 480P Version

### Wan 2.1 Image to Video

Generate videos from images using Wan 2.1.

<img alt="Wan 2.1 Image to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_to_video_wan&utm_source=docs&utm_medium=referral&utm_campaign=wan-video">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_to_video_wan.json">
    Download JSON or search "Wan 2.1 Image to Video" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="image_to_video_wan_start_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/image_to_video_wan_start_image.png">
    `LoadImage` node 52 · `image_to_video_wan_start_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="image_to_video_wan_start_image.png" />
</div>

#### Model Downloads

<Card title="wan2.1_i2v_480p_14B_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_i2v_480p_14B_fp16.safetensors?download=true">
  Diffusion model for Wan2.1 I2V 480P. Place in <code>ComfyUI/models/diffusion\_models/</code>
</Card>

#### Steps to Run

<img alt="ComfyUI Wan2.1 Workflow Steps" />

1. Make sure the `Load Diffusion Model` node has loaded the `wan2.1_i2v_480p_14B_fp16.safetensors` model
2. Make sure the `Load CLIP` node has loaded the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
3. Make sure the `Load VAE` node has loaded the `wan_2.1_vae.safetensors` model
4. Make sure the `Load CLIP Vision` node has loaded the `clip_vision_h.safetensors` model
5. Upload the provided input image in the `Load Image` node
6. (Optional) Enter the video description content you want to generate in the `CLIP Text Encoder` node
7. (Optional) You can modify the video dimensions in the `WanImageToVideo` node if needed
8. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the video generation

### 720P Version

![Wan2.1 Image-to-Video Workflow 14B 720P](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1/wan2.1_i2v_14b_720P.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_to_video_wan&utm_source=docs&utm_medium=referral&utm_campaign=wan-video">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1/wan2.1_i2v_14b_720P.webp">
    Download the workflow image and drag it into ComfyUI to load the workflow
  </Card>
</CardGroup>

<Card title="Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1/input/magician.png">
  Download the default input image, or use your own image.
</Card>

#### Model Downloads

<Card title="wan2.1_i2v_720p_14B_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_i2v_720p_14B_fp16.safetensors?download=true">
  Diffusion model for Wan2.1 I2V 720P. Place in <code>ComfyUI/models/diffusion\_models/</code>
</Card>

#### Steps to Run

<img alt="ComfyUI Wan2.1 Workflow Steps" />

1. Make sure the `Load Diffusion Model` node has loaded the `wan2.1_i2v_720p_14B_fp16.safetensors` model
2. Make sure the `Load CLIP` node has loaded the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
3. Make sure the `Load VAE` node has loaded the `wan_2.1_vae.safetensors` model
4. Make sure the `Load CLIP Vision` node has loaded the `clip_vision_h.safetensors` model
5. Upload the provided input image in the `Load Image` node
6. (Optional) Enter the video description content you want to generate in the `CLIP Text Encoder` node
7. (Optional) You can modify the video dimensions in the `WanImageToVideo` node if needed
8. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the video generation


# Wan2.2 Animate ComfyUI native workflow
Source: https://docs.comfy.org/tutorials/video/wan/wan2-2-animate

Unified character animation and replacement framework with precise motion and expression replication.

Wan-Animate is a unified framework for character animation and replacement developed by the WAN Team.

The model can animate any character based on a performer’s video, precisely replicating the performer’s facial expressions and movements to generate highly realistic character videos.

It can also replace characters in a video with animated characters, preserving their expressions and movements while replicating the original lighting and color tone for seamless environmental integration.

## Model Highlights

* Dual Mode Functionality: A single architecture supports both animation and replacement functions, enabling easy operation switching.
* Advanced Body Motion Control: Uses spatially-aligned skeleton signals for accurate body movement replication
* Precise Motion and Expression: Accurately reproduces the movements and facial expressions from the reference video.
* Natural Environment Integration: Seamlessly blends the replaced character with the original video environment.
* Smooth Long Video Generation: Iterative generation ensures consistent motion and visual flow in extended videos

## ComfyOrg Wan2.2 Animate stream replay

<iframe title="Wan 2.2 Animate in ComfyUI with Flipping Sigmas / September 19th, 2025" />

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## About Wan2.2 Animate workflow

This workflow supports two modes: Mix (replace a character in a video with a character from a reference image) and Move (animate a character using motion from an input video).

### Wan2.2 Animate, Character Animation and Replacement

Unified character animation and replacement framework with precise motion and expression replication.

<img alt="Wan2.2 Animate, Character Animation and Replacement workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2_2_14B_animate&utm_source=docs&utm_medium=referral&utm_campaign=wan2-2-animate">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2_2_14B_animate.json">
    Download JSON or search "Wan2.2 Animate" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching nodes:

<CardGroup>
  <Card title="video_wan2_2_14B_animate_reference_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_animate_reference_image.png">
    `LoadImage` node 10 · `video_wan2_2_14B_animate_reference_image.png`
  </Card>

  <Card title="video_wan2_2_14B_animate_original_video.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_animate_original_video.mp4">
    `LoadVideo` node 145 · `video_wan2_2_14B_animate_original_video.mp4`
  </Card>
</CardGroup>

<div>
  <img alt="video_wan2_2_14B_animate_reference_image.png" />
</div>

### 2. Model links

All models involved in this guide can be found [here](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/main/split_files).

**Diffusion Models**

<CardGroup>
  <Card title="Wan2.2 Animate 14B FP8 (Kijai)" icon="download" href="https://huggingface.co/Kijai/WanVideo_comfy_fp8_scaled/blob/main/Wan22Animate/Wan2_2-Animate-14B_fp8_e4m3fn_scaled_KJ.safetensors">
    Wan2\_2-Animate-14B\_fp8\_e4m3fn\_scaled\_KJ.safetensors: Scaled FP8 version from Kijai's repo
  </Card>

  <Card title="Wan2.2 Animate 14B BF16" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_animate_14B_bf16.safetensors">
    wan2.2\_animate\_14B\_bf16.safetensors: Original bf16 model weight
  </Card>
</CardGroup>

**CLIP Vision**

<Card title="CLIP Vision H" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors">
  clip\_vision\_h.safetensors: CLIP Vision encoder
</Card>

**LoRAs**

<Card title="LightX2V I2V 14B 4-Step LoRA" icon="download" href="https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors">
  lightx2v\_I2V\_14B\_480p\_cfg\_step\_distill\_rank64\_bf16.safetensors: 4-step acceleration LoRA
</Card>

**VAE**

<Card title="Wan2.1 VAE" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
  wan\_2.1\_vae.safetensors: Wan2.1 VAE for encoding and decoding
</Card>

**Text Encoders**

<Card title="UMT5 XXL FP8 Scaled" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
  umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors: Scaled FP8 text encoder
</Card>

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── Wan2_2-Animate-14B_fp8_e4m3fn_scaled_KJ.safetensors
│   │   └─── wan2.2_animate_14B_bf16.safetensors
│   ├───📂 loras/
│   │   └─── lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   ├───📂 clip_visions/ 
│   │   └─── clip_vision_h.safetensors
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Install custom nodes

Download the following workflow file and drag it into ComfyUI to load the workflow, if you have [ComfyUI-Manager](https://github.com/Comfy-Org/ComfyUI-Manager) installed, you can just click the `Install missing nodes` button to install the missing nodes.

We need to install the following custom nodes:

* [ComfyUI-KJNodes](https://github.com/kijai/ComfyUI-KJNodes)
* [ComfyUI-comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux)

If you don't know how to install custom nodes please refer to [How to install custom nodes](/installation/install_custom_node)

### 4. Workflow Instructions

The Wan2.2 animate has two modes: Mix and move

* Mix: use the reference image to replace the character in the video
* Move: Use the character movement from the input video to animate the character in the reference image (like Wan2.2 Fun Control)

#### 4.1 Mix mode

<img alt="Workflow Instructions" />

0. If you are running this workflow for the first time, please use a small size for video generation, in case you don't have enough VRAM to run the workflow, and due to the `WanAnimateToVideo` limited, the video width or height should be multiples of 16.
1. Make sure all the models are loaded correctly
2. Update the prompt if you want
3. Upload the reference image, the character is this image will be the target character
4. You can use the videos we provided as input videos for the first time， the **DWPose Estimator** node  in [comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) will preprocess the input video to pose and face control videos
5. The `Points Editor` is from [KJNodes](https://github.com/kijai/ComfyUI-KJNodes/), by default this node will not load the first frame from the input video, you need to run the workflow once or manually upload the first frame
   * Below the `Points Editor` node, we have added a note about how this node works, and how to edit it. Please refer to it
6. For the "Video Extend" group, it's in order to extend to the output video length
   * Each `Video Extend` will extend another 77 frames(Around 4.8125 seconds)
   * If your input video is less than 5s, you might not need it
   * If you want to extend longer, you need to copy and paste multiple times, you need to link the `batch_images` from last Video Extend to next one, and also the `video_frame_offset` from last Video Extend to next one
7. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation

#### 4.2 Move mode

We used [subgraph](/interface/features/subgraph) in the Wan2.2 animate workflow, here is how to switching to move mode:

<img alt="Subgraph" />

If you want to switch to Move mode, you can disconnect `background_video` and `character_mask` inputs from the `Video Sampling and output(Subgraph)` node.


# ComfyUI Wan2.2 Fun Camera Control: Video Generation Workflow Example
Source: https://docs.comfy.org/tutorials/video/wan/wan2-2-fun-camera

This article demonstrates how to use camera control for video generation with Wan2.2 Fun Camera Control in ComfyUI.

**Wan2.2-Fun-Camera-Control** is a next-generation video generation and camera control model developed by Alibaba PAI. By introducing innovative Camera Control Codes and combining deep learning with multimodal conditional inputs, it generates high-quality videos that adhere to predefined camera motion conditions. The model is released under the **Apache 2.0 license**, allowing for commercial use.

**Key Features**:

* **Camera Motion Control**: Supports various camera motion modes, including **Pan Up**, **Pan Down**, **Pan Left**, **Pan Right**, **Zoom In**, **Zoom Out**, and combinations thereof.
* **High-Quality Video Generation**: Based on the Wan2.2 architecture, it outputs cinematic-quality videos.

Here are the relevant model weights and code repository:

* [🤗Wan2.2-Fun-A14B-Control-Camera](https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control-Camera)
* Code Repository: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

## Wan2.2 Fun Camera Control: Video Generation Workflow Example

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

The workflow provided includes two versions:

1. Using the [Wan2.2-Lightning](https://huggingface.co/lightx2v/Wan2.2-Lightning) 4-step LoRA via lightx2v: This may result in reduced video dynamics but offers faster generation.
2. The fp8\_scaled version without the acceleration LoRA.

Below are the timing results tested on an RTX4090D 24GB GPU for 640\*640 resolution and 81-frame length:

| Model Type | Resolution | VRAM Usage | First Generation Time | Second Generation Time |
| - | - | - | - | - |
| fp8\_scaled | 640×640 | 84% | ≈ 536 seconds | ≈ 513 seconds |
| fp8\_scaled + 4-step LoRA | 640×640 | 89% | ≈ 108 seconds | ≈ 71 seconds |

While the 4-step LoRA improves initial user experience, it may reduce video dynamism. By default, the accelerated LoRA version is enabled. To switch workflows, select the nodes and press **Ctrl+B**.

### 1. Workflow and Asset Download

Download the video or JSON file below and drag it into ComfyUI to load the corresponding workflow. The workflow will prompt you to download the models.

<video />

<img alt="Wan2.2 Fun Camera Control workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2_2_14B_fun_camera&utm_source=docs&utm_medium=referral&utm_campaign=wan2-2-fun-camera">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2_2_14B_fun_camera.json">
    Download JSON or search "Wan2.2 Fun Camera" in Template Library
  </Card>
</CardGroup>

Please download the image below, which we will use as input.

**Input materials**

<CardGroup>
  <Card title="video_wan2_2_14B_fun_camera_start_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_fun_camera_start_image.jpg">
    Starting frame for the video generation. Download and use this image, or replace with your own.
  </Card>
</CardGroup>

### 2. Model Links

The following models can be found in [Wan\_2.2\_ComfyUI\_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged):

**Diffusion Models**

<CardGroup>
  <Card title="wan2.2_fun_camera_high_noise_14B_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_fun_camera_high_noise_14B_fp8_scaled.safetensors">
    High noise diffusion model for Wan2.2 Fun Camera
  </Card>

  <Card title="wan2.2_fun_camera_low_noise_14B_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_fun_camera_low_noise_14B_fp8_scaled.safetensors">
    Low noise diffusion model for Wan2.2 Fun Camera
  </Card>
</CardGroup>

**Wan2.2-Lightning LoRA (Optional, for acceleration)**

<CardGroup>
  <Card title="wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors">
    4-step acceleration LoRA for high noise model
  </Card>

  <Card title="wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors">
    4-step acceleration LoRA for low noise model
  </Card>
</CardGroup>

**VAE**

<Card title="wan_2.1_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
  Wan2.1 VAE for encoding/decoding
</Card>

**Text Encoder**

<Card title="umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
  FP8 scaled text encoder
</Card>

File save location

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_fun_camera_low_noise_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_fun_camera_high_noise_14B_fp8_scaled.safetensors
│   ├───📂 loras/
│   │   ├─── wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors
│   │   └─── wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Complete the Workflow Step-by-Step

<img alt="Wan2.2 Fun Camera Control Workflow Steps" />

<Note>
  This workflow uses LoRA. Ensure the Diffusion model and LoRA are consistent; high noise and low noise models and LoRA must be paired accordingly.
</Note>

1. **High noise** model and **LoRA** loading

* Ensure the `Load Diffusion Model` node loads `wan2.2_fun_camera_high_noise_14B_fp8_scaled.safetensors`
* Ensure the `LoraLoaderModelOnly` node loads `wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors`

2. **Low noise** model and **LoRA** loading

* Ensure the `Load Diffusion Model` node loads `wan2.2_fun_camera_low_noise_14B_fp8_scaled.safetensors`
* Ensure the `LoraLoaderModelOnly` node loads `wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors`

3. Ensure the `Load CLIP` node loads `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
4. Ensure the `Load VAE` node loads `wan_2.1_vae.safetensors`
5. Upload the starting frame in the `Load Image` node
6. Modify the Prompt (both Chinese and English are acceptable)
7. Set camera control parameters in the `WanCameraEmbedding` node:
   * **Camera Motion**: Select the camera motion type (Zoom In, Zoom Out, Pan Up, Pan Down, Pan Left, Pan Right, Static, etc.)
   * **Width/Height**: Set video resolution
   * **Length**: Set the number of video frames (default is 81 frames)
   * **Speed**: Set video speed (default is 1.0)
8. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation


# ComfyUI Wan2.2 Fun Control Video Generation Example
Source: https://docs.comfy.org/tutorials/video/wan/wan2-2-fun-control

This article introduces how to use ComfyUI to complete the Wan2.2 Fun Control video generation using control videos

**Wan2.2-Fun-Control** is a next-generation video generation and control model launched by Alibaba PAI team. Through innovative Control Codes mechanism combined with deep learning and multi-modal conditional inputs, it can generate high-quality videos that comply with preset control conditions. The model is released under the **Apache 2.0 license** and supports commercial use.

**Key Features**:

* **Multi-modal Control**: Supports multiple control conditions including **Canny (line art)**, **Depth**, **OpenPose (human pose)**, **MLSD (geometric edges)**, and **trajectory control**
* **High-Quality Video Generation**: Based on the Wan2.2 architecture, outputs film-level quality videos
* **Multi-language Support**: Supports multi-language prompts including Chinese and English

Below are the relevant model weights and code repositories:

* [🤗Wan2.2-Fun-A14B-Control](https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control)
* Code repository: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

## ComfyOrg Wan2.2 Fun InP & Control Youtube Live Stream Replay

<iframe title="ComfyUI Selection Toolbox New Features" />

## Wan2.2 Fun Control Video Generation Workflow Example

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

This workflow provides two versions:

1. A version using [Wan2.2-Lightning](https://huggingface.co/lightx2v/Wan2.2-Lightning) 4-step LoRA from lightx2v: may cause some loss in video dynamics but offers faster speed
2. A fp8\_scaled version without acceleration LoRA

Below are the test results using an RTX4090D 24GB VRAM GPU at 640×640 resolution with 81 frames

| Model Type | VRAM Usage | First Generation Time | Second Generation Time |
| - | - | - | - |
| fp8\_scaled | 83% | ≈ 524s | ≈ 520s |
| fp8\_scaled + 4-step LoRA | 89% | ≈ 138s | ≈ 79s |

Since using the 4-step LoRA provides a better experience for first-time workflow users, but may cause some loss in video dynamics, we have enabled the accelerated LoRA version by default. If you want to enable the other workflow, select it and use **Ctrl+B** to activate.

### 1. Download Workflow and Materials

Update your ComfyUI to the latest version, then download and drag the workflow file into ComfyUI, or find "Wan2.2 Fun Control" in the Template Library under `Workflow` → `Browse Templates` → `Video`.

<img alt="Wan2.2 Fun Control workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2_2_14B_fun_control&utm_source=docs&utm_medium=referral&utm_campaign=wan2-2-fun-control">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2_2_14B_fun_control.json">
    Download JSON or search "Wan2.2 Fun Control" in Template Library
  </Card>
</CardGroup>

Please download the following images and videos as input materials.

**Input materials**

<CardGroup>
  <Card title="video_wan2_2_14B_fun_control_start_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_fun_control_start_image.jpg">
    Start frame for video generation. Download and use this image, or replace with your own.
  </Card>

  <Card title="video_wan2_2_14B_fun_control_start_image_control_video.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_fun_control_start_image_control_video.mp4">
    Preprocessed pose control video. Download and use this video, or replace with your own.
  </Card>
</CardGroup>

> We use a preprocessed video here.

### 2. Models

All models involved in this guide can be found [here](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/main/split_files).

**Diffusion Models**

<CardGroup>
  <Card title="Wan2.2 Fun Control High Noise 14B FP8" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_fun_control_high_noise_14B_fp8_scaled.safetensors">
    wan2.2\_fun\_control\_high\_noise\_14B\_fp8\_scaled.safetensors: High noise diffusion model
  </Card>

  <Card title="Wan2.2 Fun Control Low Noise 14B FP8" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_fun_control_low_noise_14B_fp8_scaled.safetensors">
    wan2.2\_fun\_control\_low\_noise\_14B\_fp8\_scaled.safetensors: Low noise diffusion model
  </Card>
</CardGroup>

**Wan2.2-Lightning LoRA (Optional, for acceleration)**

<CardGroup>
  <Card title="High Noise 4-Step LoRA" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors">
    wan2.2\_i2v\_lightx2v\_4steps\_lora\_v1\_high\_noise.safetensors: High noise 4-step acceleration LoRA
  </Card>

  <Card title="Low Noise 4-Step LoRA" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors">
    wan2.2\_i2v\_lightx2v\_4steps\_lora\_v1\_low\_noise.safetensors: Low noise 4-step acceleration LoRA
  </Card>
</CardGroup>

**VAE**

<Card title="Wan2.1 VAE" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
  wan\_2.1\_vae.safetensors: Wan2.1 VAE for encoding/decoding
</Card>

**Text Encoder**

<Card title="UMT5 XXL FP8 Scaled" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
  umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors: Scaled FP8 text encoder
</Card>

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_fun_control_low_noise_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_fun_control_high_noise_14B_fp8_scaled.safetensors
│   ├───📂 loras/
│   │   ├─── wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors
│   │   └─── wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Workflow Guide

<img alt="Wan2.2 Fun Control Workflow Steps" />

<Note>
  This workflow uses LoRA. Please ensure the corresponding Diffusion model and LoRA are matched: high noise and low noise models and LoRAs need to be used correspondingly.
</Note>

1. **High noise** model and **LoRA** loading
   * Ensure the `Load Diffusion Model` node loads the `wan2.2_fun_control_high_noise_14B_fp8_scaled.safetensors` model
   * Ensure the `LoraLoaderModelOnly` node loads the `wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors`
2. **Low noise** model and **LoRA** loading
   * Ensure the `Load Diffusion Model` node loads the `wan2.2_fun_control_low_noise_14B_fp8_scaled.safetensors` model
   * Ensure the `LoraLoaderModelOnly` node loads the `wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors`
3. Ensure the `Load CLIP` node loads the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
4. Ensure the `Load VAE` node loads the `wan_2.1_vae.safetensors` model
5. Upload the start frame in the `Load Image` node
6. In the second `Load video` node, load the pose control video. The provided video has been preprocessed and can be used directly
7. Since we provide a preprocessed pose video, the corresponding video image preprocessing node needs to be disabled. You can select it and use `Ctrl + B` to disable it
8. Modify the Prompt: you can use both Chinese and English
9. In `Wan22FunControlToVideo`, modify the video dimensions. The default is set to 640×640 resolution to avoid excessive processing time for users with low VRAM
10. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation

### Additional Notes

Since ComfyUI's built-in nodes only include Canny preprocessor, you can use tools like [ComfyUI-comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) to implement other types of image preprocessing


# ComfyUI Wan2.2 Fun Inp Start-End Frame Video Generation Example
Source: https://docs.comfy.org/tutorials/video/wan/wan2-2-fun-inp

This article introduces how to use ComfyUI to complete the Wan2.2 Fun Inp start-end frame video generation example

**Wan2.2-Fun-Inp** is a start-end frame controlled video generation model launched by Alibaba PAI team. It supports inputting **start and end frame images** to generate intermediate transition videos, providing creators with greater creative control. The model is released under the **Apache 2.0 license** and supports commercial use.

**Key Features**:

* **Start-End Frame Control**: Supports inputting start and end frame images to generate intermediate transition videos, enhancing video coherence and creative freedom
* **High-Quality Video Generation**: Based on the Wan2.2 architecture, outputs film-level quality videos
* **Multi-Resolution Support**: Supports generating videos at 512x512, 768x768, 1024x1024 and other resolutions to suit different scenarios

**Model Version**:

* **14B High-Performance Version**: Model size exceeds 32GB, with better results but requires high VRAM

Below are the relevant model weights and code repositories:

* [🤗Wan2.2-Fun-Inp-14B](https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-InP)
* Code repository: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

## ComfyOrg Wan2.2 Fun InP & Control Youtube Live Stream Replay

<iframe title="ComfyUI Selection Toolbox New Features" />

## Wan2.2 Fun Inp Start-End Frame Video Generation Workflow Example

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

This workflow provides two versions:

1. A version using [Wan2.2-Lightning](https://huggingface.co/lightx2v/Wan2.2-Lightning) 4-step LoRA from lightx2v for accelerated video generation
2. A fp8\_scaled version without acceleration LoRA

Below are the test results using an RTX4090D 24GB VRAM GPU at 640x640 resolution with 81 frames

| Model Type | VRAM Usage | First Generation Time | Second Generation Time |
| - | - | - | - |
| fp8\_scaled | 83% | ≈ 524s | ≈ 520s |
| fp8\_scaled + 4-step LoRA | 89% | ≈ 138s | ≈ 79s |

Since the acceleration with LoRA is significant but the video dynamic is lost, the provided workflows enable the accelerated LoRA version by default. If you want to enable the other workflow, select it and use **Ctrl+B** to activate.

### 1. Download Workflow File

Please update your ComfyUI to the latest version, and find "**Wan2.2 Fun Inp**" under the menu `Workflow` -> `Browse Templates` -> `Video` to load the workflow.

Or, after updating ComfyUI to the latest version, download the workflow below and drag it into ComfyUI to load.

<img alt="Wan2.2 Fun Inp workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2_2_14B_fun_inpaint&utm_source=docs&utm_medium=referral&utm_campaign=wan2-2-fun-inp">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2_2_14B_fun_inpaint.json">
    Download JSON or search "Wan2.2 Fun Inp" in Template Library
  </Card>
</CardGroup>

Use the following materials as the start and end frames

**Input materials**

<CardGroup>
  <Card title="video_wan2_2_14B_fun_inpaint_start_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_fun_inpaint_start_image.png">
    Start frame for video generation. Download and use this image, or replace with your own.
  </Card>

  <Card title="video_wan2_2_14B_fun_inpaint_end_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_fun_inpaint_end_image.png">
    End frame for video generation. Download and use this image, or replace with your own.
  </Card>
</CardGroup>

### 2. Models

All models involved in this guide can be found [here](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/main/split_files).

**Diffusion Models**

<CardGroup>
  <Card title="High Noise 14B FP8 Scaled" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_fun_inpaint_high_noise_14B_fp8_scaled.safetensors">
    wan2.2\_fun\_inpaint\_high\_noise\_14B\_fp8\_scaled.safetensors: High noise diffusion model for start-end frame inpainting
  </Card>

  <Card title="Low Noise 14B FP8 Scaled" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_fun_inpaint_low_noise_14B_fp8_scaled.safetensors">
    wan2.2\_fun\_inpaint\_low\_noise\_14B\_fp8\_scaled.safetensors: Low noise diffusion model for start-end frame inpainting
  </Card>
</CardGroup>

**Lightning LoRA (Optional, for acceleration)**

<CardGroup>
  <Card title="Lightning 4-Step High Noise LoRA" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors">
    wan2.2\_i2v\_lightx2v\_4steps\_lora\_v1\_high\_noise.safetensors: 4-step acceleration LoRA for high noise model
  </Card>

  <Card title="Lightning 4-Step Low Noise LoRA" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors">
    wan2.2\_i2v\_lightx2v\_4steps\_lora\_v1\_low\_noise.safetensors: 4-step acceleration LoRA for low noise model
  </Card>
</CardGroup>

**VAE**

<Card title="Wan2.1 VAE" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
  wan\_2.1\_vae.safetensors: Wan2.1 VAE for encoding and decoding
</Card>

**Text Encoder**

<Card title="UMT5 XXL FP8 Scaled" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
  umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors: Scaled FP8 text encoder
</Card>

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_fun_inpaint_high_noise_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_fun_inpaint_low_noise_14B_fp8_scaled.safetensors
│   ├───📂 loras/
│   │   ├─── wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors
│   │   └─── wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Workflow Guide

<img alt="Workflow Step Image" />

<Note>
  This workflow uses LoRA. Please make sure the corresponding Diffusion model and LoRA are matched.
</Note>

1. **High noise** model and **LoRA** loading
   * Ensure the `Load Diffusion Model` node loads the `wan2.2_fun_inpaint_high_noise_14B_fp8_scaled.safetensors` model
   * Ensure the `LoraLoaderModelOnly` node loads the `wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors`
2. **Low noise** model and **LoRA** loading
   * Ensure the `Load Diffusion Model` node loads the `wan2.2_fun_inpaint_low_noise_14B_fp8_scaled.safetensors` model
   * Ensure the `LoraLoaderModelOnly` node loads the `wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors`
3. Ensure the `Load CLIP` node loads the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
4. Ensure the `Load VAE` node loads the `wan_2.1_vae.safetensors` model
5. Upload the start and end frame images as materials
6. Enter your prompt in the Prompt group
7. Adjust the size and video length in the `WanFunInpaintToVideo` node
   * Adjust the `width` and `height` parameters. The default is `640`. We set a smaller size, but you can modify it as needed.
   * Adjust the `length`, which is the total number of frames. The current workflow fps is 16. For example, if you want to generate a 5-second video, you should set it to 5\*16 = 80.
8. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation


# Wan2.2-S2V Audio-Driven Video Generation ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/video/wan/wan2-2-s2v

This is a native workflow example for Wan2.2-S2V audio-driven video generation in ComfyUI.

We're excited to announce that Wan2.2-S2V, the advanced audio-driven video generation model, is now natively supported in ComfyUI! This powerful AI model can transform static images and audio inputs into dynamic video content, supporting dialogue, singing, performance, and various creative content needs.

**Model Highlights**

* **Audio-Driven Video Generation**: Transforms static images and audio into synchronized videos
* **Cinematic-Grade Quality**: Generates film-quality videos with natural expressions and movements
* **Minute-Level Generation**: Supports long-form video creation
* **Multi-Format Support**: Works with full-body and half-body characters
* **Enhanced Motion Control**: Generates actions and environments from text instructions

Wan2.2 S2V Code: [GitHub](https://github.com/aigc-apps/VideoX-Fun)
Wan2.2 S2V Model: [Hugging Face](https://huggingface.co/Wan-AI/Wan2.2-S2V-14B)

## Wan2.2 S2V ComfyUI Native Workflow

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Wan2.2-S2V Audio-Driven Video Generation

Transform static images and audio into dynamic videos with perfect synchronization and minute-level generation.

<img alt="Wan2.2-S2V Audio-Driven Video Generation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2_2_14B_s2v&utm_source=docs&utm_medium=referral&utm_campaign=wan2-2-s2v">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2_2_14B_s2v.json">
    Download JSON or search "Wan2.2 S2V" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching nodes:

<CardGroup>
  <Card title="video_wan2_2_14B_s2v_reference_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_s2v_reference_image.jpg">
    `LoadImage` node 52 · `video_wan2_2_14B_s2v_reference_image.jpg`
  </Card>

  <Card title="video_wan2_2_14B_s2v_input_audio.MP3" icon="music" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_s2v_input_audio.MP3">
    `LoadAudio` node 58 · `video_wan2_2_14B_s2v_input_audio.MP3`
  </Card>
</CardGroup>

<div>
  <img alt="video_wan2_2_14B_s2v_reference_image.jpg" />
</div>

### 2. Model Links

You can find the models in [our repo](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged)

**diffusion\_models**

<CardGroup>
  <Card title="wan2.2_s2v_14B_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_s2v_14B_fp8_scaled.safetensors?download=true">
    FP8 scaled diffusion model. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="wan2.2_s2v_14B_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_s2v_14B_bf16.safetensors?download=true">
    BF16 diffusion model. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

**audio\_encoders**

<Card title="wav2vec2_large_english_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/audio_encoders/wav2vec2_large_english_fp16.safetensors?download=true">
  Audio encoder model. Place in <code>ComfyUI/models/audio\_encoders/</code>
</Card>

**vae**

<Card title="wan_2.1_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors?download=true">
  Wan2.1 VAE model. Place in <code>ComfyUI/models/vae/</code>
</Card>

**text\_encoders**

<Card title="umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true">
  FP8 scaled text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
</Card>

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_s2v_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_s2v_14B_bf16.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   ├───📂 audio_encoders/ # Create one if you can't find this folder
│   │   └─── wav2vec2_large_english_fp16.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Workflow Instructions

<img alt="Workflow Instructions" />

#### 3.1 About Lightning LoRA

#### 3.2 About fp8\_scaled and bf16 Models

You can find both models [here](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/main/split_files/diffusion_models):

<CardGroup>
  <Card title="wan2.2_s2v_14B_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_s2v_14B_fp8_scaled.safetensors?download=true">
    FP8 scaled diffusion model
  </Card>

  <Card title="wan2.2_s2v_14B_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_s2v_14B_bf16.safetensors?download=true">
    BF16 diffusion model
  </Card>
</CardGroup>

This template uses `wan2.2_s2v_14B_fp8_scaled.safetensors`, which requires less VRAM. But you can try `wan2.2_s2v_14B_bf16.safetensors` to reduce quality degradation.

#### 3.3 Step-by-Step Operation Instructions

**Step 1: Load Models**

1. **Load Diffusion Model**: Load `wan2.2_s2v_14B_fp8_scaled.safetensors` or `wan2.2_s2v_14B_bf16.safetensors`
   * The provided workflow uses `wan2.2_s2v_14B_fp8_scaled.safetensors`, which requires less VRAM
   * But you can try `wan2.2_s2v_14B_bf16.safetensors` to reduce quality degradation

2. **Load CLIP**: Load `umt5_xxl_fp8_e4m3fn_scaled.safetensors`

3. **Load VAE**: Load `wan_2.1_vae.safetensors`

4. **AudioEncoderLoader**: Load `wav2vec2_large_english_fp16.safetensors`

5. **LoraLoaderModelOnly**: Load `wan2.2_t2v_lightx2v_4steps_lora_v1.1_high_noise.safetensors` (Lightning LoRA)
   * We tested all wan2.2 lightning LoRAs. Since this is not a LoRA specifically trained for Wan2.2 S2V, many key values don't match, but we added it because it significantly reduces generation time. We will continue to optimize this template
   * Using it will cause significant dynamic and quality loss
   * If you find the output quality too poor, you can try the original 20-step workflow

6. **LoadAudio**: Upload our provided audio file or your own audio

7. **Load Image**: Upload reference image

8. **Batch sizes**: Set according to the number of Video S2V Extend subgraph nodes you add
   * Each Video S2V Extend subgraph adds 77 frames to the final output
   * For example: If you added 2 Video S2V Extend subgraphs, the batch size should be 3, which means the total number of sampling iterations
   * **Chunk Length**: Keep the default value of 77

9. **Sampler Settings**: Choose different settings based on whether you use Lightning LoRA
   * With 4-step Lightning LoRA: steps: 4, cfg: 1.0
   * Without 4-step Lightning LoRA: steps: 20, cfg: 6.0

10. **Size Settings**: Set the output video dimensions

11. **Video S2V Extend**: Video extension subgraph nodes. Since our default frames per sampling is 77, and this is a 16fps model, each extension will generate 77 / 16 = 4.8125 seconds of video
    * You need some calculation to match the number of video extension subgraph nodes with the input audio length. For example: If input audio is 14s, the total frames needed are 14x16=224, each video extension is 77 frames, so you need 224/77 = 2.9, rounded up to 3 video extension subgraph nodes

12. Use Ctrl-Enter or click the Run button to execute the workflow


# Wan2.2 Video Generation ComfyUI Official Native Workflow Example
Source: https://docs.comfy.org/tutorials/video/wan/wan2_2

Run Wan2.2 video workflows in ComfyUI: the 5B hybrid TI2V model plus 14B text-to-video, image-to-video, and first-last-frame examples, with downloads.

<iframe title="ComfyUI Selection Toolbox New Features" />

Wan 2.2 is a new generation multimodal generative model launched by WAN AI. This model adopts an innovative MoE (Mixture of Experts) architecture, consisting of high-noise and low-noise expert models. It can divide expert models according to denoising timesteps, thus generating higher quality video content.

Wan 2.2 has three core features: cinematic-level aesthetic control, deeply integrating professional film industry aesthetic standards, supporting multi-dimensional visual control such as lighting, color, and composition; large-scale complex motion, easily restoring various complex motions and enhancing the smoothness and controllability of motion; precise semantic compliance, excelling in complex scenes and multi-object generation, better restoring users' creative intentions.
The model supports multiple generation modes such as text-to-video and image-to-video, suitable for content creation, artistic creation, education and training, and other application scenarios.

[Wan2.2 Prompt Guide](https://alidocs.dingtalk.com/i/nodes/EpGBa2Lm8aZxe5myC99MelA2WgN7R35y)

## Model Highlights

* **Cinematic-level Aesthetic Control**: Professional camera language, supports multi-dimensional visual control such as lighting, color, and composition
* **Large-scale Complex Motion**: Smoothly restores various complex motions, enhances motion controllability and naturalness
* **Precise Semantic Compliance**: Complex scene understanding, multi-object generation, better restoring creative intentions
* **Efficient Compression Technology**: 5B version with high compression ratio VAE, memory optimization, supports mixed training

## Wan2.2 Open Source Model Versions

The Wan2.2 series models are based on the Apache 2.0 open source license and support commercial use. The Apache 2.0 license allows you to freely use, modify, and distribute these models, including for commercial purposes, as long as you retain the original copyright notice and license text.

| Model Type | Model Name | Parameters | Main Function | Model Repository |
| - | - | - | - | - |
| Hybrid Model | Wan2.2-TI2V-5B | 5B | Hybrid version supporting both text-to-video and image-to-video, a single model meets two core task requirements | 🤗 [Wan2.2-TI2V-5B](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B) |
| Image-to-Video | Wan2.2-I2V-A14B | 14B | Converts static images into dynamic videos, maintaining content consistency and smooth dynamic process | 🤗 [Wan2.2-I2V-A14B](https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B) |
| Text-to-Video | Wan2.2-T2V-A14B | 14B | Generates high-quality videos from text descriptions, with cinematic-level aesthetic control and precise semantic compliance | 🤗 [Wan2.2-T2V-A14B](https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B) |

## ComfyOrg Wan2.2 Live Streams

For ComfyUI Wan2.2 usage, we have conducted live streams, which you can view to learn how to use them.

<iframe title="ComfyUI Wan2.2 Live Streams" />

<iframe title="ComfyUI Wan2.2 Deep Dive" />

<iframe title="ComfyUI Wan2.2 Deep Dive #2" />

This tutorial will use the [🤗 Comfy-Org/Wan\_2.2\_ComfyUI\_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged) version.

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<img alt="Wan2.2 template" />

## Wan2.2 TI2V 5B Hybrid Version Workflow Example

<Tip>
  The Wan2.2 5B version should fit well on 8GB vram with the ComfyUI native offloading.
</Tip>

### Wan 2.2 5B Video Generation

Fast text-to-video and image-to-video generation with 5B parameters. Optimized for rapid prototyping and creative exploration.

<img alt="Wan 2.2 5B Video Generation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2_2_5B_ti2v&utm_source=docs&utm_medium=referral&utm_campaign=wan2_2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2_2_5B_ti2v.json">
    Download JSON or search "Wan2.2 5B" in Template Library
  </Card>
</CardGroup>

### 2. Manually Download Models

All models mentioned can be found at [Comfy-Org/Wan\_2.2\_ComfyUI\_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged).

**Diffusion Model**

<CardGroup>
  <Card title="wan2.2_ti2v_5B_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_ti2v_5B_fp16.safetensors">
    5B hybrid diffusion model. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

**VAE**

<CardGroup>
  <Card title="wan2.2_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan2.2_vae.safetensors">
    Wan2.2 VAE. Place in <code>ComfyUI/models/vae/</code>
  </Card>
</CardGroup>

**Text Encoder**

<CardGroup>
  <Card title="umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
    FP8 text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   └───wan2.2_ti2v_5B_fp16.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan2.2_vae.safetensors
```

### 3. Follow the Steps

<img alt="Step Diagram" />

1. Ensure the `Load Diffusion Model` node loads the `wan2.2_ti2v_5B_fp16.safetensors` model.
2. Ensure the `Load CLIP` node loads the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model.
3. Ensure the `Load VAE` node loads the `wan2.2_vae.safetensors` model.
4. (Optional) If you need to perform image-to-video generation, you can use the shortcut Ctrl+B to enable the `Load image` node to upload an image.
5. (Optional) In the `Wan22ImageToVideoLatent` node, you can adjust the size settings and the total number of video frames (`length`).
6. (Optional) If you need to modify the prompts (positive and negative), please do so in the `CLIP Text Encoder` node at step 5.
7. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.

## Wan2.2 14B T2V Text-to-Video Workflow Example

### Wan 2.2 14B Text to Video

Generate high-quality videos from text prompts with cinematic aesthetic control and dynamic motion generation using Wan 2.2.

<img alt="Wan 2.2 14B Text to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2_2_14B_t2v&utm_source=docs&utm_medium=referral&utm_campaign=wan2_2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2_2_14B_t2v.json">
    Download JSON or search "Wan2.2 14B T2V" in Template Library
  </Card>
</CardGroup>

### 2. Manually Download Models

All models mentioned can be found at [Comfy-Org/Wan\_2.2\_ComfyUI\_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged).

**Diffusion Models**

<CardGroup>
  <Card title="wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors">
    High noise diffusion model. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors">
    Low noise diffusion model. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

**VAE**

<CardGroup>
  <Card title="wan_2.1_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
    Wan2.1 VAE (compatible with Wan2.2). Place in <code>ComfyUI/models/vae/</code>
  </Card>
</CardGroup>

**Text Encoder**

<CardGroup>
  <Card title="umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
    FP8 text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Follow the Steps

<img alt="Step Diagram" />

1. Ensure the first `Load Diffusion Model` node loads the `wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors` model.
2. Ensure the second `Load Diffusion Model` node loads the `wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors` model.
3. Ensure the `Load CLIP` node loads the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model.
4. Ensure the `Load VAE` node loads the `wan_2.1_vae.safetensors` model.
5. (Optional) In the `EmptyHunyuanLatentVideo` node, you can adjust the size settings and the total number of video frames (`length`).
6. (Optional) If you need to modify the prompts (positive and negative), please do so in the `CLIP Text Encoder` node at step 5.
7. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.

## Wan2.2 14B I2V Image-to-Video Workflow Example

### Wan 2.2 14B Image to Video

Transform static images into dynamic videos with precise motion control and style preservation using Wan 2.2.

<img alt="Wan 2.2 14B Image to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2_2_14B_i2v&utm_source=docs&utm_medium=referral&utm_campaign=wan2_2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2_2_14B_i2v.json">
    Download JSON or search "Wan2.2 14B I2V" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="video_wan2_2_14B_i2v_input_image.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_i2v_input_image.jpg">
    `LoadImage` node 97 · `video_wan2_2_14B_i2v_input_image.jpg`
  </Card>
</CardGroup>

**Example output**

<div>
  <img alt="Input image" />

  <video />
</div>

### 2. Manually Download Models

All models mentioned can be found at [Comfy-Org/Wan\_2.2\_ComfyUI\_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged).

**Diffusion Models**

<CardGroup>
  <Card title="wan2.2_i2v_high_noise_14B_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_i2v_high_noise_14B_fp16.safetensors">
    High noise I2V diffusion model. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>

  <Card title="wan2.2_i2v_low_noise_14B_fp16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_i2v_low_noise_14B_fp16.safetensors">
    Low noise I2V diffusion model. Place in <code>ComfyUI/models/diffusion\_models/</code>
  </Card>
</CardGroup>

**VAE**

<CardGroup>
  <Card title="wan_2.1_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">
    Wan2.1 VAE (compatible with Wan2.2). Place in <code>ComfyUI/models/vae/</code>
  </Card>
</CardGroup>

**Text Encoder**

<CardGroup>
  <Card title="umt5_xxl_fp8_e4m3fn_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">
    FP8 text encoder. Place in <code>ComfyUI/models/text\_encoders/</code>
  </Card>
</CardGroup>

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_i2v_low_noise_14B_fp16.safetensors
│   │   └─── wan2.2_i2v_high_noise_14B_fp16.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Follow the Steps

<img alt="Step Diagram" />

1. Make sure the first `Load Diffusion Model` node loads the `wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors` model.
2. Make sure the second `Load Diffusion Model` node loads the `wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors` model.
3. Make sure the `Load CLIP` node loads the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model.
4. Make sure the `Load VAE` node loads the `wan_2.1_vae.safetensors` model.
5. In the `Load Image` node, upload the image to be used as the initial frame.
6. If you need to modify the prompts (positive and negative), do so in the `CLIP Text Encoder` node at step 6.
7. (Optional) In `EmptyHunyuanLatentVideo`, you can adjust the size settings and the total number of video frames (`length`).
8. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.

## Wan2.2 14B FLF2V Workflow Example

The first and last frame workflow uses the same model locations as the I2V section.

### Wan 2.2 14B First-Last Frame to Video

Generate smooth video transitions by defining start and end frames.

<img alt="Wan 2.2 14B First-Last Frame to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan2_2_14B_flf2v&utm_source=docs&utm_medium=referral&utm_campaign=wan2_2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2_2_14B_flf2v.json">
    Download JSON or search "Wan2.2 14B FLF2V" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="video_wan2_2_14B_flf2v_start_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_flf2v_start_image.png">
    `LoadImage` node 62 · `video_wan2_2_14B_flf2v_start_image.png`
  </Card>

  <Card title="video_wan2_2_14B_flf2v_end_image.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/video_wan2_2_14B_flf2v_end_image.png">
    `LoadImage` node 68 · `video_wan2_2_14B_flf2v_end_image.png`
  </Card>
</CardGroup>

<div>
  <img alt="video_wan2_2_14B_flf2v_start_image.png" />

  <img alt="video_wan2_2_14B_flf2v_end_image.png" />
</div>

### 2. Follow the Steps

<img alt="Step Diagram" />

1. Upload the image to be used as the starting frame in the first `Load Image` node.
2. Upload the image to be used as the ending frame in the second `Load Image` node.
3. Adjust the size settings in the `WanFirstLastFrameToVideo` node.
   * By default, a relatively small size is set to prevent low VRAM users from consuming too many resources.
   * If you have enough VRAM, you can try a resolution around 720P.
4. Write appropriate prompts according to your first and last frames.
5. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.

## Community Resources

### GGUF Versions

* [bullerwins/Wan2.2-I2V-A14B-GGUF/](https://huggingface.co/bullerwins/Wan2.2-I2V-A14B-GGUF/)
* [bullerwins/Wan2.2-T2V-A14B-GGUF](https://huggingface.co/bullerwins/Wan2.2-T2V-A14B-GGUF)
* [QuantStack/Wan2.2 GGUFs](https://huggingface.co/collections/QuantStack/wan22-ggufs-6887ec891bdea453a35b95f3)

**Custom Node**
[City96/ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF)

### WanVideoWrapper

[Kijai/ComfyUI-WanVideoWrapper](https://github.com/kijai/ComfyUI-WanVideoWrapper)

**Wan2.2 models**
[Kijai/WanVideo\_comfy\_fp8\_scaled](https://hf-mirror.com/Kijai/WanVideo_comfy_fp8_scaled)

**Wan2.1 models**
[Kijai/WanVideo\_comfy/Lightx2v](https://huggingface.co/Kijai/WanVideo_comfy/tree/main/Lightx2v)

**Lightx2v 4steps LoRA**

* [Wan2.2-T2V-A14B-4steps-lora-rank64-V1](https://huggingface.co/lightx2v/Wan2.2-Lightning/tree/main/Wan2.2-T2V-A14B-4steps-lora-rank64-V1)


# ComfyUI SCAIL-2 Character Replacement Workflow Tutorial
Source: https://docs.comfy.org/tutorials/video/zai/scail2

Drive a reference character image with a driving video for character animation or in-video character replacement using SCAIL-2.

**SCAIL-2** is an end-to-end character animation model built on Wan2.1. It drives a reference character image with a driving video, enabling both character animation (making a character perform the motion) and in-video character replacement (swapping a tracked person in a video with the reference character).

**Key Features**:

* **End-to-End Character Animation**: Drive a still character image with motion from a driving video
* **Two Modes**: Animation Mode (character performs the motion) and Replacement Mode (swap tracked person with reference character)
* **Long Video Support**: Chunk-based extended generation with frame overlap between segments
* **Built-in ComfyUI Nodes**: Uses native `WanSCAILToVideo`, `SCAIL2ColoredMask`, and `SAM3` tracking. No custom nodes required beyond standard model downloads.

**Related Links**:

* [Hugging Face: SCAIL-2](https://huggingface.co/zai-org/SCAIL-2)
* [SCAIL-2 Diffusion Model](https://huggingface.co/Comfy-Org/SCAIL-2)

## SCAIL-2 Character Replacement Workflow

### SCAIL-2 Character Replacement

Replace a character in a video while preserving motion and scene context.

<img alt="SCAIL-2 Character Replacement workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_wan21_scail2_character_replacement&utm_source=docs&utm_medium=referral&utm_campaign=scail2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan21_scail2_character_replacement.json">
    Download JSON or search "SCAIL-2 Character Replacement" in Template Library
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="Reference Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/reference_streetwear_character.png">
    Download the default reference character image, or use your own.
  </Card>

  <Card title="Driving Video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/driving_outdoor_dance.mp4">
    Download the default driving video, or use your own.
  </Card>
</CardGroup>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## How the Workflow Works

This workflow uses two subgraph nodes: a **Base** subgraph (first segment) and an **Extend** subgraph (subsequent segments). This supports character animation for both short and long videos.

1. **Load** a driving video (`pose_video`) and a reference character image
2. **Base subgraph** processes the first segment (81 frames by default)
3. **Extend subgraph** processes additional segments 2+, chaining `previous_frames` from the prior segment
4. Preview the result and save

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Long Videos

For longer videos, calculate the number of segments: `ceil(total_frames / 76)`. Each segment except the first uses the Extend subgraph. Duplicate the Extend node for more segments, chain the `previous_frames` output, and increment `segment_index`.

> **Note:** `WanSCAILToVideo` cannot queue all segments automatically. Run each segment manually.

## Two Modes

| Mode | `replace_mode` | Driving Mask BG | Summary |
| - | :-: | :-: | - |
| **Replacement** | `true` (default) | White | Swap the tracked person in the driving video with the reference character |
| **Animation** | `false` | Black | Reference character performs the driving motion |

Set the `replace_mode` parameter on both subgraph nodes.

## Inputs and Parameters

### Shared Parameters (Base & Extend)

| Parameter | Description |
| - | - |
| `pose_video` | The driving video containing motion to transfer |
| `reference_image` | The character image to animate or insert |
| `prompt` | Output video description |
| `replace_mode` | `true` = Replacement, `false` = Animation |
| `segment_index` | `1` for first chunk, `2+` for continuation. Pose offset = `76 × (index − 1)` |
| `width` / `height` | Output resolution, e.g. `896×512`. Must be divisible by 16 |
| `frame_count` | Frames per segment (default: 81) |
| `previous_frame_count` | Overlap frames between segments (default: 5) |
| `pose_strength` / `pose_start` / `pose_end` | Pose conditioning strength and timing |

### SAM3 Tracking (two inputs)

The `sam3_video_object` and `sam3_image_object` inputs control the SAM3 mask tracking, **not** the SCAIL-2 output prompt. These determine which objects are tracked for the colored masks:

| Input | Target | Output |
| - | - | - |
| `sam3_video_object` | Driving video | `pose_video_mask` |
| `sam3_image_object` | Reference image | `reference_image_mask` |

* Use open-vocabulary text (default: `human`)
* Use the same term when the subject is the same across video and reference
* Use different terms if the video and reference need different focus (e.g., crowded scenes)

## Model Installation

Update ComfyUI to the latest version first for the built-in WanSCAILToVideo and SCAIL2ColoredMask nodes.

### Required Models

**diffusion\_models**

* [wan2.1\_14B\_SCAIL\_2\_fp16.safetensors](https://huggingface.co/Comfy-Org/SCAIL-2/blob/main/diffusion_models/wan2.1_14B_SCAIL_2_fp16.safetensors)

**text\_encoders** (choose one)

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

**clip\_vision**

* [clip\_vision\_h.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors)

**vae**

* [Wan2\_1\_VAE\_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Wan2_1_VAE_bf16.safetensors)

**loras**

* [lightx2v\_I2V\_14B\_480p\_cfg\_step\_distill\_rank64\_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors)
* [wan2.1\_SCAIL\_2\_DPO\_lora\_bf16.safetensors](https://huggingface.co/Comfy-Org/SCAIL-2/blob/main/loras/wan2.1_SCAIL_2_DPO_lora_bf16.safetensors)

**checkpoints**

* [sam3.1\_multiplex\_fp16.safetensors](https://huggingface.co/Comfy-Org/sam3.1/blob/main/checkpoints/sam3.1_multiplex_fp16.safetensors)

### File Storage Locations

```
ComfyUI/
├── models/
│   ├── diffusion_models/
│   │   └── wan2.1_14B_SCAIL_2_fp16.safetensors
│   ├── text_encoders/
│   │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   ├── clip_vision/
│   │   └── clip_vision_h.safetensors
│   ├── vae/
│   │   └── Wan2_1_VAE_bf16.safetensors
│   ├── loras/
│   │   ├── lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors
│   │   └── wan2.1_SCAIL_2_DPO_lora_bf16.safetensors
│   └── checkpoints/
│       └── sam3.1_multiplex_fp16.safetensors
```


# ApplyTextureToMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ApplyTextureToMesh

This node attaches baked texture images to a mesh's UV layout so they can be exported together with the mesh by the SaveGLB node.

This node attaches baked texture images to a mesh's UV layout so they can be exported together with the mesh by the SaveGLB node. Feed it the same UV-unwrapped mesh you baked the textures from, along with the baked image maps. Optional metallic, roughness, and occlusion maps are packed into a single ORM texture, and supplying a normal map also stores the smooth vertex normals and tangent basis needed for correct shading.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The UV-unwrapped mesh that the baked textures will be attached to. Must be the same mesh used during baking; an error is raised if the mesh has no UVs. | MESH | Yes | — |
| `base_color` | The baked base color image. Stored as the mesh's texture and clamped to the 0-1 range. | IMAGE | Yes | — |
| `metallic` | The baked metallic map. Used as the blue channel of the combined ORM texture; defaults to 0 when not provided. | IMAGE | No | — |
| `roughness` | The baked roughness map. Used as the green channel of the combined ORM texture; defaults to 1 when not provided. | IMAGE | No | — |
| `occlusion` | The baked ambient occlusion map. Used as the red channel of the combined ORM texture; defaults to 1 when not provided. When provided, the ORM texture is also flagged as the occlusion texture for SaveGLB. | IMAGE | No | — |
| `normal_map` | The baked tangent-space normal map. When provided, the node recomputes the per-vertex tangents and exports smooth vertex normals so the normal map shades correctly. | IMAGE | No | — |

Note: The `mesh` input must have UV coordinates; if it does not, the node raises an error asking you to connect the same UV-unwrapped mesh used for baking.

Note: When any of `metallic`, `roughness`, or `occlusion` is connected, all three are packed into a single glTF ORM texture with channels R = occlusion, G = roughness, B = metallic. Missing maps are filled with defaults (occlusion 1, roughness 1, metallic 0), and maps with different resolutions are resized to the largest width and height among the provided maps.

Note: When `normal_map` is connected, the mesh's stored normals are replaced with computed smooth vertex normals and a per-vertex tangent basis is added. UV coordinates that fall outside the \[0,1] range are uniformly scaled into \[0,1] while preserving aspect ratio; a warning is logged if the UV span looks like a tiled/UDIM layout. For batched meshes, UV normalization is applied separately to each item in the batch using the same logic as the bake step, so both stay aligned.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The input mesh with the texture images attached to its UV layout, ready to be saved by SaveGLB. | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ApplyTextureToMesh/en.md)

***

**Source fingerprint (SHA-256):** `7492922c9c7c0117366cb8b9017fc192eb8dd6b6594fd429044d60408693210e`


# BakeAmbientOcclusion - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BakeAmbientOcclusion

Bakes an ambient-occlusion map from a high-poly mesh into the UV layout of a low-poly mesh.

Bakes an ambient-occlusion map from a high-poly mesh into the UV layout of a low-poly mesh. The output is a grayscale image in which white texels are open and dark texels are in crevices; it is meant for the Apply Texture To Mesh node's occlusion input. Connect the UV-unwrapped low-poly mesh and the high-poly mesh it was decimated from.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `low_poly` | The UV-unwrapped low-poly mesh to bake into. Must have UVs; the node raises an error if they are missing. | MESH | Yes | - |
| `high_poly` | The high-poly mesh that the low-poly was decimated from, used as the source geometry for occlusion. | MESH | Yes | - |
| `resolution` | Texture resolution in pixels; each texel receives an occlusion value. Default: 1024. | INT | Yes | 64 to 8192 (step 64) |
| `samples` | Rays per texel. More = smoother, slower. Raise if grainy. Default: 64. | INT | Yes | 4 to 1024 (step 4) |
| `max_distance` | Ray length, as a fraction of the bounding box diagonal. Smaller = tighter, more local occlusion. Default: 0.5. | FLOAT | Yes | 0.01 to 2.0 (step 0.01) |
| `strength` | Scales the occlusion. >1 darkens, \<1 lightens. Default: 1.0. | FLOAT | Yes | 0.0 to 2.0 (step 0.05) |
| `bias` | Ray origin lift off the surface, as a fraction of the bounding box diagonal. Raise if even surfaces show dark blotches/holes. Default: 0.01. | FLOAT | Yes | 0.0001 to 0.2 (step 0.0005) |

Note: `low_poly` must have UV coordinates — this node never unwraps the mesh. If `high_poly` contains only one batch item, it is reused for every batch item of `low_poly`; batch items of `low_poly` with no faces are skipped and replaced with an all-white image, with a warning logged. If the UVs of `low_poly` spill outside the 0-1 range, they are uniformly fitted back into it, and a warning is logged when a tiled/UDIM-style layout is detected.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `occlusion` | Grayscale ambient-occlusion image with values in \[0,1] (white = open, dark = crevices), one image per batch item of `low_poly`. Intended for the Apply Texture To Mesh node's occlusion input (packed into the ORM map / occlusionTexture). | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BakeAmbientOcclusion/en.md)

***

**Source fingerprint (SHA-256):** `63ea6ce5289728d351fdd7d722e9a299ebb1283e1128262a817466ec6d23786a`


# BakeNormalMapFromMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BakeNormalMapFromMesh

This node bakes a tangent-space normal map from a high-poly mesh onto a low-poly mesh's UV layout, capturing surface detail that was lost during decimation.

This node bakes a tangent-space normal map from a high-poly mesh onto a low-poly mesh's UV layout, capturing surface detail that was lost during decimation. Connect the UV-unwrapped low-poly mesh and the high-poly mesh it came from, and the node outputs an image ready for the `normal_map` input of Apply Texture To Mesh.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `low_poly` | The UV-unwrapped low-poly mesh that receives the baked detail. Must have existing UVs; the node never unwraps. | MESH | Yes | — |
| `high_poly` | The high-poly mesh whose surface detail is baked into the low-poly's UV layout. | MESH | Yes | — |
| `resolution` | Edge length in pixels of the square output normal map (default: 1024). | INT | Yes | 64 to 8192 (step 64) |
| `cage_distance` | Surface search band, as a fraction of the bounding box diagonal. Raise for wrong/missing patches under heavy decimation; lower if it grabs across gaps. Default: 0.05. | FLOAT | Yes | 0.001 to 0.5 (step 0.001) |
| `ignore_backfaces` | Skip high-poly surfaces facing away from the texel, so crevices/enclosed spaces don't grab the opposite wall. Disable only if the high-poly winding is inconsistent. Default: true. | BOOLEAN | Yes | true / false |

Note: `low_poly` must have UV coordinates. If it has none, the node raises an error because it bakes onto the existing UV layout and does not unwrap the mesh. When `low_poly` is a batch, each item is baked in order; if `high_poly` contains only one item, that item is reused for every batch item. Empty meshes in the batch are skipped with a warning and produce a flat mid-gray (0.5) normal map. If the low-poly UVs spill outside the \[0,1] range, they are uniformly fitted into \[0,1] (with a warning when the layout looks tiled/UDIM), so the bake and Apply Texture To Mesh use the same UVs.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `normal_map` | The baked tangent-space normal map (glTF/OpenGL +Y convention) as a square resolution × resolution RGB image with values in \[0,1]. Connect it to the `normal_map` input of Apply Texture To Mesh. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BakeNormalMapFromMesh/en.md)

***

**Source fingerprint (SHA-256):** `29df10014b5998b741d71db21d0c982d7bca85ad966a720063af15062e203322`


# BakeTextureFromVoxel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BakeTextureFromVoxel

This node bakes PBR textures onto a 3D mesh using the mesh's existing UV layout.

This node bakes PBR textures onto a 3D mesh using the mesh's existing UV layout. It rasterizes the mesh in UV space and samples color and material attributes from a sparse voxel volume at each texel, outputting a base color image plus metallic and roughness maps. It does not unwrap the mesh, so a UV unwrap node must be connected upstream; the resulting images are intended to be paired with the same mesh in ApplyTextureToMesh for saving as GLB.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The 3D mesh to bake textures onto. Must already have a UV layout; a UV unwrap node must be connected upstream. | MESH | Yes | |
| `voxel_colors` | Sparse voxel volume containing per-voxel colors and optional PBR attributes (metallic and roughness channels). | VOXEL | Yes | |
| `texture_size` | Square UV atlas resolution (display name: "resolution", default: 2048). | INT | Yes | 64 to 8192 |
| `reference_mesh` | Optional dense pre-decimation mesh; back-projects each texel onto its true surface before sampling, removing faceted baking on coarse meshes. | MESH | No | |

Notes:

* The input mesh must have UVs. If no UVs are present, the node raises an error. UVs must be 1:1 with the vertices (one UV per vertex).
* When the mesh and voxel coordinates contain a batch dimension, each batch item is baked separately. If a batch item has no voxels or no faces, it is skipped and a black texture is emitted for it.
* When `reference_mesh` is provided for a batch, it is matched by batch index unless it contains only a single mesh, in which case that mesh is used for all items.
* Texels that are not covered by any UV triangle are filled from the nearest covered texel so that texture seams do not pull in black.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `base_color` | RGB base color texture map. Values are float in the 0–1 range. | IMAGE |
| `metallic` | Grayscale metallic map (float, 0–1). Black when the voxel colors contain no metallic channel. | IMAGE |
| `roughness` | Grayscale roughness map (float, 0–1). Black when the voxel colors contain no roughness channel. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BakeTextureFromVoxel/en.md)

***

**Source fingerprint (SHA-256):** `080dcb670620f1cb97523d04fc45293e03d139e513845d0fa7b1c4d2f8bdf32d`


# BuildPoseFile - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BuildPoseFile

This node builds a ready-to-save 3D animation file from pose data.

This node builds a ready-to-save 3D animation file from pose data. You can export an animated GLB in several visual styles — a full body mesh, joints-only preview, OpenPose skeleton, or SCAIL capsule rig — or save a BVH motion-capture clip instead. The output plugs into a file-saving node such as Save 3D Model to write the file to disk.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `pose_data` | 3D pose data. Accepts MHR pose data (model/shape/expression parameters, MHR70 keypoints, canonical colors, hand vertex mask) or Kimodo pose data (external Y-up rig with per-frame predicted vertices and camera). | MHR\_POSE\_DATA / KIMODO\_POSE\_DATA | Yes | — |
| `format` | Output format, both fed to Save 3D Model to write to disk. 'glb' = animated GLB (mesh / bones / openpose / scail). 'bvh' = BVH mocap clip (one skeleton; needs the model). (default: glb) | DYNAMIC\_COMBO | Yes | "glb"<br />"bvh" |
| `sam3d_body_model` | Optional SAM3D body model. Required for the 'bvh', 'body\_mesh', and 'bones\_only' formats unless the pose data carries a skeleton override. | SAM3D\_BODY\_MODEL | No | — |
| `fps` | Animation frame rate. (default: 24.0) | FLOAT | Yes | 1.0-240.0 |
| `camera_translation` | Bake pred\_cam\_t into the root's translation: 'off' = bind position; 'centered' = delta from frame 0; 'absolute' = raw (Z is camera depth — usually meters away). (default: off) | COMBO | Yes | "off"<br />"centered"<br />"absolute" |
| `track_index` | Track selection: -1 = all tracks; ≥0 = single track. (default: -1) | INT | Yes | -1 to 15 |

### GLB Inputs

These inputs appear when `format` is set to "glb".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh_style` | Visual style of the GLB: 'body\_mesh' = real Armature (127 bones, skinning, TRS keyframes, 72 face morphs; needs model). 'bones\_only' = bone-shape primitives at each joint (preview armature). 'openpose' = OpenPose-18 3D skeleton from keypoints. 'scail' = SCAIL 3D capsule rig (open cylinders capped flush by joint spheres). (default: body\_mesh) | DYNAMIC\_COMBO | Yes | "body\_mesh"<br />"bones\_only"<br />"openpose"<br />"scail" |
| `bone_smooth_window` | Gaussian smoothing window on per-bone rotation keyframes / keypoint tracks. 0 = off. 7-15 calms spins/jitter where upstream Smooth misses spikes. (default: 0) | INT | Yes | 0-51, step 2 |

#### Body Mesh Inputs

Appear when `mesh_style` is "body\_mesh".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `bone_vis` | Bone vis shape, rigidly skinned to each joint. 'off' = no bone visualization; 'octahedrons' = Blender-style directional bones. (default: off) | DYNAMIC\_COMBO | Yes | "off"<br />"octahedrons" |
| `bone_vis_radius_m` | Appears when `bone_vis` = "octahedrons". Radius in m (sphere radius / octahedron half-width). (default: 0.02) | FLOAT | Yes | 0.005-0.5 |
| `bone_vis_color` | Appears when `bone_vis` = "octahedrons". Per-bone vertex colors (unlit material). 'white' = none, 'rainbow\_y' = head-to-toe jet. (default: rainbow\_y) | COMBO | Yes | "white"<br />"rainbow\_y" |
| `shader` | Bake per-vertex colors matching the Render node's shaders (COLOR\_0 + KHR\_materials\_unlit). 'default' = no colors. (default: default) | DYNAMIC\_COMBO | Yes | "default"<br />"rainbow"<br />"rainbow\_face\_normal"<br />"rainbow\_face\_semantic" |
| `rainbow_tilt_z` | Appears when `shader` is a rainbow variant. Rotate rainbow jet axis around Z (forward). Differentiates left/right. (default: -35.0) | FLOAT | Yes | -90.0 to 90.0 |
| `rainbow_tilt_x` | Appears when `shader` is a rainbow variant. Rotate rainbow jet axis around X (right). Differentiates front/back. (default: 0.0) | FLOAT | Yes | -90.0 to 90.0 |
| `person_palette_falloff` | Appears when `shader` is a rainbow variant. Per-person desaturation: each track gets (1 - falloff^k) pastel mix. (default: 0.6) | FLOAT | Yes | 0.1-1.0 |

#### Bones Only Inputs

Appear when `mesh_style` is "bones\_only".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `bone_vis` | Bone vis shape, rigidly skinned to each joint. 'octahedrons' = Blender-style directional bones (joint → primary child). | DYNAMIC\_COMBO | Yes | "octahedrons" |
| `bone_vis_radius_m` | Radius in m (sphere radius / octahedron half-width). (default: 0.02) | FLOAT | Yes | 0.005-0.5 |
| `bone_vis_color` | Per-bone vertex colors (unlit material). 'white' = none, 'rainbow\_y' = head-to-toe jet. (default: rainbow\_y) | COMBO | Yes | "white"<br />"rainbow\_y" |

#### OpenPose Inputs

Appear when `mesh_style` is "openpose".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `marker_radius_m` | Sphere radius in m. (default: 0.010) | FLOAT | Yes | 0.005-0.1 |
| `stick_radius_m` | Limb half-width in m. Auto-clamped to bone\_length x 0.1. (default: 0.008) | FLOAT | Yes | 0.002-0.05 |
| `include_hands` | Append 21+21 OpenPose hands (wrist + 5 fingers x 4 joints, base→tip) sourced from pred\_keypoints\_3d. (default: False) | BOOLEAN | Yes | True / False |
| `hand_marker_radius_m` | Hand sphere radius in m. (default: 0.005) | FLOAT | Yes | 0.001-0.1 |
| `hand_stick_radius_m` | Hand limb half-width in m. (default: 0.003) | FLOAT | Yes | 0.001-0.05 |
| `face_style` | Face-contour landmarks sampled from pred\_vertices at fixed head-mesh vertex IDs (needs canonical\_colors on pose\_data). 'full' = all \~30 points; 'eyes\_mouth' = eyes + outer lips only. (default: disabled) | COMBO | Yes | "disabled"<br />"full"<br />"eyes\_mouth" |
| `face_marker_radius_m` | Face dot radius. 0 = auto = 0.3 x marker\_radius\_m. (default: 0.0) | FLOAT | Yes | 0.0-0.05 |

#### SCAIL Inputs

Appear when `mesh_style` is "scail".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `stick_radius_m` | Cylinder radius in m. Bones are open cylinders at constant radius; joint spheres (auto-sized to match) cap the open ends. SCAIL reference = 0.0215 m. (default: 0.022) | FLOAT | Yes | 0.002-0.1 |
| `marker_radius_m` | Joint sphere radius. 0 = auto = stick\_radius\_m (flush cap). (default: 0.0) | FLOAT | Yes | 0.0-0.1 |
| `material_roughness` | PBR roughness. SCAIL ref = 0.3. 1 = matte; 0 = chrome. (default: 0.3) | FLOAT | Yes | 0.0-1.0 |
| `include_hands` | Append 21+21 hand keypoints + capsule sticks per track. (default: False) | BOOLEAN | Yes | True / False |
| `hand_marker_radius_m` | Hand sphere radius in m. (default: 0.005) | FLOAT | Yes | 0.001-0.05 |
| `hand_stick_radius_m` | Hand cylinder radius in m. (default: 0.003) | FLOAT | Yes | 0.001-0.05 |
| `face_style` | Face-contour landmarks sampled from pred\_vertices (needs canonical\_colors on pose\_data). 'full' = all \~30 points; 'eyes\_mouth' = eyes + outer lips only. (default: disabled) | COMBO | Yes | "disabled"<br />"full"<br />"eyes\_mouth" |

### BVH Inputs

Appear when `format` is set to "bvh".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `units` | BVH OFFSET/position units. 'cm' is the mocap standard. (default: cm) | COMBO | Yes | "cm"<br />"m" |

**Notes:**

* The `bvh` format and the `body_mesh` and `bones_only` mesh styles require the `sam3d_body_model` input, unless the `pose_data` itself carries a skeleton override (a `_skeleton_override` dict, for example from a KimodoSample node). The node raises an error if neither is available. The `openpose` and `scail` styles are rig-independent and work directly from keypoints without the body model.
* In `bvh` format, the output contains a single skeleton. When `track_index` is -1 (all tracks), the first track is used.
* The `full` and `eyes_mouth` `face_style` options require `canonical_colors` on the pose data, which is present when the pose data comes from the MHR pipeline together with the body model.
* `bone_smooth_window` advances in steps of 2 between 0 and 51.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | The generated animation file: an animated GLB or a BVH mocap clip, ready to be saved to disk with a node such as Save 3D Model. | 3D\_FILE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BuildPoseFile/en.md)

***

**Source fingerprint (SHA-256):** `f3672f0749c4f9affcc92da98198c5b142f6fcd9f5e317ab43dd7e53533c0fa3`


# CreateCameraInfo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateCameraInfo

The Create Camera Info node builds a camera information structure for 3D rendering.

The Create Camera Info node builds a camera information structure for 3D rendering. It supports three modes for defining the camera: orbit (yaw/pitch/distance around a target), look\_at (explicit world position), and quaternion (position plus rotation). The coordinate system is right-handed with Y as the up axis.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mode` | How to define the camera: orbit angles, an explicit position, or a position + quaternion. | COMBO | Yes | `"orbit"`<br />`"look_at"`<br />`"quaternion"` |
| `target_x` | Look-at point (orbit pivot / aim). In orbit mode, move it to pan/translate the whole camera. Ignored in quaternion mode. Defaults to the origin. (default: 0.0) | FLOAT | No | -1000.0 to 1000.0 |
| `target_y` | Y component of the target point. (default: 0.0) | FLOAT | No | -1000.0 to 1000.0 |
| `target_z` | Z component of the target point. (default: 0.0) | FLOAT | No | -1000.0 to 1000.0 |
| `roll` | Camera roll about the view axis, in degrees. (default: 0.0) | FLOAT | No | -180.0 to 180.0 |
| `fov` | Vertical field of view in degrees. (default: 35.0) | FLOAT | No | 1.0 to 120.0 |
| `zoom` | Digital zoom (focal-length multiplier). Values greater than 1 zoom in without moving the camera. (default: 1.0) | FLOAT | No | 0.01 to 100.0 |
| `camera_type` | Projection used by Render Splat: perspective (foreshortening) or orthographic (parallel). (default: "perspective") | COMBO | No | `"perspective"`<br />`"orthographic"` |

### Mode-Specific Parameters

When `mode` is set to `"orbit"`, the following parameters become available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `yaw` | Horizontal rotation angle around the target. (default: 35.0) | FLOAT | Yes | -360.0 to 360.0 |
| `pitch` | Vertical rotation angle around the target. (default: 30.0) | FLOAT | Yes | -89.0 to 89.0 |
| `distance` | Camera distance from the target. (default: 4.0) | FLOAT | Yes | 0.01 to 1000.0 |

When `mode` is set to `"look_at"`, the following parameters become available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `position_x` | Camera position in world space (right-handed, Y-up). (default: 4.0) | FLOAT | Yes | -1000.0 to 1000.0 |
| `position_y` | Y component of the camera position. (default: 4.0) | FLOAT | Yes | -1000.0 to 1000.0 |
| `position_z` | Z component of the camera position. (default: 4.0) | FLOAT | Yes | -1000.0 to 1000.0 |

When `mode` is set to `"quaternion"`, the following parameters become available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `position_x` | Camera position in world space (right-handed, Y-up). (default: 4.0) | FLOAT | Yes | -1000.0 to 1000.0 |
| `position_y` | Y component of the camera position. (default: 4.0) | FLOAT | Yes | -1000.0 to 1000.0 |
| `position_z` | Z component of the camera position. (default: 4.0) | FLOAT | Yes | -1000.0 to 1000.0 |
| `quat_x` | X component of the camera world-rotation quaternion. (default: 0.0) | FLOAT | Yes | -1.0 to 1.0 |
| `quat_y` | Y component of the camera world-rotation quaternion. (default: 0.0) | FLOAT | Yes | -1.0 to 1.0 |
| `quat_z` | Z component of the camera world-rotation quaternion. (default: 0.0) | FLOAT | Yes | -1.0 to 1.0 |
| `quat_w` | Camera world-rotation quaternion (three.js: looks down local -Z). Normalized for you. (default: 1.0) | FLOAT | Yes | -1.0 to 1.0 |

**Note:** The `target_x`, `target_y`, and `target_z` parameters are ignored when `mode` is set to `"quaternion"`. In `"orbit"` mode, these target parameters define the pivot point around which the camera orbits.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `camera_info` | Camera information structure containing position, rotation, field of view, zoom, and projection type for 3D rendering. | LOAD3DCAMERA |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateCameraInfo/en.md)

***

**Source fingerprint (SHA-256):** `577c114130f72b753d5f15775fe05b3e1e734f5865cca32c576d042583f8e873`


# DecimateMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DecimateMesh

Simplifies a 3D mesh to a target face count using QEM (quadric error metric) simplification, running the computation on the active compute device.

Simplifies a 3D mesh to a target face count using QEM (quadric error metric) simplification, running the computation on the active compute device. The `"midpoint"` placement mode is the cumesh-faithful preset that provides the best quality while preserving thin features such as hair, whereas `"qem"` places vertices at the QEM-optimal position with optional line and feature-edge controls. The output mesh stays welded.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The 3D mesh to simplify. | MESH | Yes | - |
| `target_face_count` | Target max faces. 0 disables. (default: 200000) | INT | Yes | 0 to 50000000 |
| `placement_mode` | midpoint: cumesh-faithful (recommended). qem: QEM-optimal placement. (default: `"midpoint"`) | DYNAMIC\_COMBO | Yes | `"midpoint"`<br />`"qem"` |

### Midpoint Inputs

The `"midpoint"` placement mode does not expose additional sub-parameters; it uses the default midpoint placement preset.

### QEM Inputs

The following sub-parameters appear in the interface only when `placement_mode` is set to `"qem"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `line_quadric_weight` | Per-edge line-quadric weight; preserves sharp ridges/valleys. 0 = off. (default: 0.0) | FLOAT | No | 0.0 to 100.0 |
| `feature_edge_quadric_weight` | Extra quadric weight on dihedral feature edges (creases). 0 = off. (default: 0.0) | FLOAT | No | 0.0 to 1000.0 |
| `feature_edge_min_dihedral_deg` | Minimum dihedral angle (degree) to count an edge as a feature edge. (default: 30.0) | FLOAT | No | 0.0 to 180.0 |
| `clamp_v_to_edge` | Project the QEM-optimal position onto the collapsed edge segment. (default: true) | BOOLEAN | No | `true`<br />`false` |

Note: Decimation is skipped when `target_face_count` is 0 or when the mesh already has no more faces than the target. The node displays a face reduction summary on itself, for example `faces: 1.23M → 200K (-84%)`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The simplified mesh with the reduced face count; connectivity stays welded. | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DecimateMesh/en.md)

***

**Source fingerprint (SHA-256):** `55336e5b52e27d940e5402ecd74fd0ac847a1c6acd35955eccf72aab8ed940f9`


# File3DToSplat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/File3DToSplat

This node converts a 3D file containing gaussian splat data into a gaussian splat format that can be used in the node graph.

This node converts a 3D file containing gaussian splat data into a gaussian splat format that can be used in the node graph. It supports PLY, SPLAT, KSPLAT, and SPZ file formats, with the file format automatically detected from the file contents.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | A gaussian splat 3D file | FILE3D | Yes | - |

The input file must be in one of the supported formats: PLY, SPLAT, KSPLAT, or SPZ. PLY files carry full spherical harmonics data, while the other formats contain only base color information. The format is automatically detected from the file contents.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `splat` | A gaussian splat containing position, scale, rotation, opacity, and spherical harmonics data | SPLAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/File3DToSplat/en.md)

***

**Source fingerprint (SHA-256):** `9f45210a1366e57a91de6e1251f0e2e09f39e6498dbec1db7bf9826ebedd167b`


# FillHoles - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FillHoles

This node fills holes in a 3D mesh by detecting open boundary edges and creating new faces to close them.

This node fills holes in a 3D mesh by detecting open boundary edges and creating new faces to close them. It runs on the GPU, preserves existing geometry and UVs, and can process single meshes, lists of meshes, or batches of meshes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The 3D mesh to process. Accepts a single mesh, a list of meshes, or a batched mesh. | MESH | Yes | - |
| `max_perimeter` | Max hole perimeter to fill. 0 disables. (default: 0.03) | FLOAT | Yes | 0.0 to no upper limit (step 0.0001) |
| `weld_epsilon_rel` | Pre-weld tolerance (fraction of bounding box diagonal); boundary detection needs welded vertices. 0 skips. (default: 1e-5) | FLOAT | Yes | 0.0 to no upper limit (step 1e-6) |
| `max_vertices` | Cap boundary vertices per cycle; centroid-fan only works for small near-planar holes. Keep ≤16. (default: 16) | INT | Yes | 3 to 1024 |
| `fill_chains` | Also fill open chains (not just cycles). Noisy; OFF matches cumesh. (default: False) | BOOLEAN | Yes | True or False |

Note: When `max_perimeter` is greater than 0, the node fills holes; when it is 0, hole filling is skipped entirely. When `weld_epsilon_rel` is greater than 0, the node pre-welds duplicate vertices before detecting holes. The welding tolerance starts at the given fraction of the bounding box diagonal and automatically increases by doubling until the mesh is considered welded or the tolerance reaches a cap of 1e-2. Holes with more than 8 boundary vertices use a centroid-fan fill (inserting a new centroid vertex), while smaller holes use a vertex-fan fill that reuses an existing boundary vertex. By default only closed boundary cycles are filled; set `fill_chains` to True to also close open chains.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The mesh with holes filled, matching the input batch format. | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FillHoles/en.md)

***

**Source fingerprint (SHA-256):** `c0fd7f0c2d6eea098efb1dcfd80eaa52997e185b9c442b483f75318eea082196`


# Get3DComponents - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Get3DComponents

Get3DComponents parses a 3D model file (GLB, GLTF, OBJ, or STL) into an editable mesh that can be used by mesh-processing nodes such as decimate, remesh, UV unwrap, and bake.

Get3DComponents parses a 3D model file (GLB, GLTF, OBJ, or STL) into an editable mesh that can be used by mesh-processing nodes such as decimate, remesh, UV unwrap, and bake. All scene nodes and primitives are merged into one mesh with their transforms applied, and textures and material settings come from the first material. It is the counterpart of the MeshToFile3D node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | 3D model file from Load 3D or another 3D node. FBX/USDZ are not supported - convert to GLB first. | File3DGLB<br />File3DGLTF<br />File3DOBJ<br />File3DSTL<br />File3DAny | Yes | GLB<br />GLTF<br />OBJ<br />STL |

Note: FBX and USDZ files are not supported and cause an error; convert them to GLB or GLTF first. If the file format cannot be recognized as GLB, GLTF, OBJ, or STL, the node raises an error listing the supported formats. If the glTF scene contains no triangle geometry, or if the file contains face indices that point outside the vertex list (a sign of a corrupt file), the node raises an error. If the 3D file contains multiple materials, only the first material's textures and material factors are kept (a warning is logged). All scene primitives are merged into a single mesh with their transforms applied. This node is experimental.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | Editable mesh containing vertices, faces, UVs, vertex colors, normals, and tangents, plus material information taken from the file (texture, metallic-roughness, normal map, emissive color, unlit flag, occlusion-in-metallic-roughness flag, and material data). | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Get3DComponents/en.md)

***

**Source fingerprint (SHA-256):** `f2cdc9767a50503988484f09d2b3d110caf086b8cd84f65034a4a1e17a94405e`


# GetMeshInfo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GetMeshInfo

Get Mesh Info reports the number of vertices and faces in a mesh, along with the attributes it contains (such as UVs, vertex colors, normals, and textures).

Get Mesh Info reports the number of vertices and faces in a mesh, along with the attributes it contains (such as UVs, vertex colors, normals, and textures). The report is displayed on the node and returned as a text output, while the mesh itself passes through unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The mesh to inspect. The node counts its vertices and faces, detects which attributes are present, and passes the mesh through unchanged. | MESH | Yes | — |

Note: When the input contains several meshes (a batch), the report shows total vertex and face counts for the whole batch plus a breakdown per mesh. For zero-padded batches, the per-item counts stored in the mesh data are used.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The original mesh, passed through without any modification. | MESH |
| `info` | A multiline text report with vertex count, face count, and detected attributes (uvs, vertex\_colors, normals, tangents, texture, metallic\_roughness, normal\_map). Texture-like attributes are shown with their height × width dimensions. Large counts are comma-formatted, for example "1,234,567 (1.23M)" or "12,345 (12.3K)". The same text is displayed on the node. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GetMeshInfo/en.md)

***

**Source fingerprint (SHA-256):** `cd168a5e69131a4a37f1f47014af2bc2ac2c8aa69e146cf33c2072480b35ebb2`


# GetSplatCount - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GetSplatCount

The Get Splat Count node returns the total number of splats (gaussian points) in a splat batch, summed across all items in the batch.

The Get Splat Count node returns the total number of splats (gaussian points) in a splat batch, summed across all items in the batch. It passes the original splat data through unchanged while providing a count of how many individual splats it contains.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `splat` | The splat data to count the number of splats in | SPLAT | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `splat` | The original splat data, passed through unchanged | SPLAT |
| `count` | The total number of splats summed across the batch | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GetSplatCount/en.md)

***

**Source fingerprint (SHA-256):** `fbb913b70bbbe4701b91783b6f47969d9132737c464ae590243f9f38061a05dc`


# Load3D - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Load3D

The Load3D node is a core node for loading and processing 3D model files.

The Load3D node is a core node for loading and processing 3D model files. When loading the node, it automatically retrieves available 3D resources from `ComfyUI/input/3d/`. You can also upload supported 3D files for preview using the upload function.

**Supported Formats**
Currently, this node supports multiple 3D file formats, including `.gltf`, `.glb`, `.obj`, `.fbx`, and `.stl`.

**3D Node Preferences**
Some related preferences for 3D nodes can be configured in ComfyUI's settings menu. Please refer to the following documentation for corresponding settings:

[Settings Menu](https://docs.comfy.org/interface/settings/3d)

Besides regular node outputs, Load3D has lots of 3D view-related settings in the canvas menu.

## Inputs

| Parameter Name | Description | Type | Default | Range |
| - | - | - | - | - |
| model\_file | 3D model file path, supports upload, defaults to reading model files from `ComfyUI/input/3d/` | File Selection | - | Supported formats |
| width | Canvas rendering width | INT | 1024 | 1-4096 |
| height | Canvas rendering height | INT | 1024 | 1-4096 |

## Outputs

| Parameter Name | Description | Data Type |
| - | - | - |
| image | Canvas rendered image | IMAGE |
| mask | Mask containing current model position | MASK |
| mesh\_path | Model file path | STRING |
| normal | Normal map | IMAGE |
| lineart | Line art image output, corresponding `edge_threshold` can be adjusted in the canvas model menu | IMAGE |
| camera\_info | Camera information | LOAD3D\_CAMERA |
| recording\_video | Recorded video (only when recording exists) | VIDEO |

All the outputs preview:

<img alt="View Operation Demo" />

## Canvas Area Description

The Load3D node's Canvas area contains numerous view operations, including:

* Preview view settings (grid, background color, preview view)
* Camera control: Control FOV, camera type
* Global illumination intensity: Adjust lighting intensity
* Video recording: Record and export videos
* Model export: Supports `GLB`, `OBJ`, `STL` formats
* And more

<img alt="Load 3D Node UI" />

1. Contains multiple menus and hidden menus of the Load 3D node
2. Menu for `resizing preview window` and `canvas video recording`
3. 3D view operation axis
4. Preview thumbnail
5. Preview size settings, scale preview view display by setting dimensions and then resizing window

### 1. View Operations

<video>
  <source type="video/mp4" />

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</video>

View control operations:

* Left-click + drag: Rotate the view
* Right-click + drag: Pan the view
* Middle wheel scroll or middle-click + drag: Zoom in/out
* Coordinate axis: Switch views

### 2. Left Menu Functions

<img alt="Menu" />

In the canvas, some settings are hidden in the menu. Click the menu button to expand different menus

* 1. Scene: Contains preview window grid, background color, preview settings
* 2. Model: Model rendering mode, texture materials, up direction settings
* 3. Camera: Switch between orthographic and perspective views, and set the perspective angle size
* 4. Light: Scene global illumination intensity
* 5. Export: Export model to other formats (GLB, OBJ, STL)

#### Scene

<img alt="scene menu" />

The Scene menu provides some basic scene setting functions

1. Show/Hide grid
2. Set background color
3. Click to upload a background image
4. Hide the preview

#### Model

<img alt="Menu_Scene" />

The Model menu provides some model-related functions

1. **Up direction**: Determine which axis is the up direction for the model
2. **Material mode**: Switch model rendering modes - Original, Normal, Wireframe, Lineart

#### Camera

<img alt="menu_modelmenu_camera" />

This menu provides switching between orthographic and perspective views, and perspective angle size settings

1. **Camera**: Quickly switch between orthographic and orthographic views
2. **FOV**: Adjust FOV angle

#### Light

<img alt="menu_modelmenu_camera" />

Through this menu, you can quickly adjust the scene's global illumination intensity

#### Export

<img alt="menu_export" />

This menu provides the ability to quickly convert and export model formats

### 3. Right Menu Functions

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

The right menu has two main functions:

1. **Reset view ratio**: After clicking the button, the view will adjust the canvas rendering area ratio according to the set width and height
2. **Video recording**: Allows you to record current 3D view operations as video, allows import, and can be output as `recording_video` to subsequent nodes

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Load3D/en.md)


# Load3DAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Load3DAdvanced

The Load 3D (Advanced) node loads a 3D model file from ComfyUI's input/3d directory and provides the model data together with model placement and camera information captured in the

The Load 3D (Advanced) node loads a 3D model file from ComfyUI's `input/3d` directory and provides the model data together with model placement and camera information captured in the 3D viewer's viewport state. It supports common 3D file formats and lets you set the render width and height of the viewport in pixels. This node is experimental.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_file` | The 3D model file to load. Select "none" to skip loading a model file. Files can also be uploaded through the widget. | COMBO | Yes | `"none"`<br />Available 3D model files in the `input/3d` directory |
| `viewport_state` | The current viewport state containing camera and model information from the 3D viewer. | LOAD3D | Yes | - |
| `width` | Render width of the viewport in pixels (default: 1024). | INT | Yes | Min: 1<br />Max: 4096<br />Default: 1024<br />Step: 1 |
| `height` | Render height of the viewport in pixels (default: 1024). | INT | Yes | Min: 1<br />Max: 4096<br />Default: 1024<br />Step: 1 |

**Notes on Parameters:**

* The `model_file` parameter only lists files with the following extensions: .gltf, .glb, .obj, .fbx, .stl
* Files must be placed in the `input/3d` directory of your ComfyUI installation; subfolders are searched as well, and file paths are shown relative to the input directory
* If `model_file` is "none", no model data is loaded and the `model_3d` output will be empty
* If `model_file` is set to a file that does not exist, the node returns a validation error: "Invalid 3D model file: \{model\_file}"
* If `viewport_state` is not a valid viewport state object, it is treated as empty, so `model_3d_info` becomes an empty list and `camera_info` is returned as empty

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | Loaded 3D model file (glb/obj/stl/etc.). Empty if no model file was selected. | FILE3DANY |
| `model_3d_info` | Placement of each model in the scene: position, rotation, and scale (Y-up world space). | LOAD3DMODELINFO |
| `camera_info` | Viewport camera information: position, look-at target, zoom, and type. | LOAD3DCAMERA |
| `width` | Render width of the viewport in pixels. | INT |
| `height` | Render height of the viewport in pixels. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Load3DAdvanced/en.md)

***

**Source fingerprint (SHA-256):** `c79c53dde0c8b3afb7df7b972df749f5040c92d48b47e355c4497d9b0cbf1c22`


# Load3DAnimation - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Load3DAnimation

The Load3DAnimation node is a core node for loading and processing 3D model files.

The Load3DAnimation node is a core node for loading and processing 3D model files. When loading the node, it automatically retrieves available 3D resources from `ComfyUI/input/3d/`. You can also upload supported 3D files for preview using the upload function.

> * Most of the functions of this node are the same as the Load 3D node, but this node supports loading models with animations, and you can preview the corresponding animations in the node.
> * The content of this documentation is the same as the Load3D node, because except for animation preview and playback, their capabilities are identical.

**Supported Formats**
Currently, this node supports multiple 3D file formats, including `.gltf`, `.glb`, `.obj`, `.fbx`, and `.stl`.

**3D Node Preferences**
Some related preferences for 3D nodes can be configured in ComfyUI's settings menu. Please refer to the following documentation for corresponding settings:

[Settings Menu](https://docs.comfy.org/interface/settings/3d)

Besides regular node outputs, Load3D has lots of 3D view-related settings in the canvas menu.

## Inputs

| Parameter Name | Description | Type | Default | Range |
| - | - | - | - | - |
| model\_file | 3D model file path, supports upload, defaults to reading model files from `ComfyUI/input/3d/` | File Selection | - | Supported formats |
| width | Canvas rendering width | INT | 1024 | 1-4096 |
| height | Canvas rendering height | INT | 1024 | 1-4096 |

## Outputs

| Parameter Name | Description | Data Type |
| - | - | - |
| image | Canvas rendered image | IMAGE |
| mask | Mask containing current model position | MASK |
| mesh\_path | Model file path | STRING |
| normal | Normal map | IMAGE |
| lineart | Line art image output, corresponding `edge_threshold` can be adjusted in the canvas model menu | IMAGE |
| camera\_info | Camera information | LOAD3D\_CAMERA |
| recording\_video | Recorded video (only when recording exists) | VIDEO |

All the outputs preview:

<img alt="View Operation Demo" />

## Canvas Area Description

The Load3D node's Canvas area contains numerous view operations, including:

* Preview view settings (grid, background color, preview view)
* Camera control: Control FOV, camera type
* Global illumination intensity: Adjust lighting intensity
* Video recording: Record and export videos
* Model export: Supports `GLB`, `OBJ`, `STL` formats
* And more

<img alt="Load 3D Node UI" />

1. Contains multiple menus and hidden menus of the Load 3D node
2. Menu for `resizing preview window` and `canvas video recording`
3. 3D view operation axis
4. Preview thumbnail
5. Preview size settings, scale preview view display by setting dimensions and then resizing window

### 1. View Operations

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

View control operations:

* Left-click + drag: Rotate the view
* Right-click + drag: Pan the view
* Middle wheel scroll or middle-click + drag: Zoom in/out
* Coordinate axis: Switch views

### 2. Left Menu Functions

![Menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu.webp)

In the canvas, some settings are hidden in the menu. Click the menu button to expand different menus

* 1. Scene: Contains preview window grid, background color, preview settings
* 2. Model: Model rendering mode, texture materials, up direction settings
* 3. Camera: Switch between orthographic and perspective views, and set the perspective angle size
* 4. Light: Scene global illumination intensity
* 5. Export: Export model to other formats (GLB, OBJ, STL)

#### Scene

![scene menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_scene.webp)

The Scene menu provides some basic scene setting functions

1. Show/Hide grid
2. Set background color
3. Click to upload a background image
4. Hide the preview

#### Model

![Menu\_Scene](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_model.webp)

The Model menu provides some model-related functions

1. **Up direction**: Determine which axis is the up direction for the model
2. **Material mode**: Switch model rendering modes - Original, Normal, Wireframe, Lineart

#### Camera

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_camera.webp)

This menu provides switching between orthographic and perspective views, and perspective angle size settings

1. **Camera**: Quickly switch between orthographic and orthographic views
2. **FOV**: Adjust FOV angle

#### Light

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_light.webp)

Through this menu, you can quickly adjust the scene's global illumination intensity

#### Export

![menu\_export](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_export.webp)

This menu provides the ability to quickly convert and export model formats

### 3. Right Menu Functions

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

The right menu has two main functions:

1. **Reset view ratio**: After clicking the button, the view will adjust the canvas rendering area ratio according to the set width and height
2. **Video recording**: Allows you to record current 3D view operations as video, allows import, and can be output as `recording_video` to subsequent nodes

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Load3DAnimation/en.md)


# MergeMeshes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MergeMeshes

MergeMeshes combines multiple mesh inputs into a single mesh by stacking their vertices, faces, UV coordinates, and vertex colors, and offsetting face indices so all parts join cor

MergeMeshes combines multiple mesh inputs into a single mesh by stacking their vertices, faces, UV coordinates, and vertex colors, and offsetting face indices so all parts join correctly into one continuous mesh.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `meshes` | Growable slot: connect 2 to 50 mesh objects (named `mesh_1`, `mesh_2`, ..., `mesh_50`). All connected meshes are merged into one output mesh. | MESH | Yes | 2 to 50 meshes |

**Note:** At least one mesh must be provided; otherwise the node raises an error. Only the first mesh item from each input mesh's batch is used. Input meshes are moved to CPU before merging. If any input mesh has UV data, the output includes UVs and meshes without UVs receive zero-filled UV values. If any input mesh has vertex colors, the output includes vertex colors; meshes without colors receive white (value 1) colors, and color channels are padded to the largest channel count found among inputs. Only the texture from the first input that provides one is kept; additional textures are dropped.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The merged mesh containing all input vertices, faces, UVs, and colors combined into one mesh. | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MergeMeshes/en.md)

***

**Source fingerprint (SHA-256):** `0ce49b522f6348d524df20d6c27eb8bd9575c4a781790f6f8e3ac4f3ee255d38`


# MergeSplat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MergeSplat

The Merge Splats node combines multiple gaussian splat models into a single splat by concatenating their data.

The Merge Splats node combines multiple gaussian splat models into a single splat by concatenating their data. This is useful for merging several decodes of the same latent generated with different seeds, which can densify the surface and improve quality when creating 3D meshes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `splat0` | First gaussian splat to merge | SPLAT | Yes | At least 1 splat required |
| `splat1` | Second gaussian splat to merge | SPLAT | Yes | At least 1 splat required |
| `splat2` | Additional gaussian splat to merge (optional) | SPLAT | No | Up to 32 splats total |
| `splat3` | Additional gaussian splat to merge (optional) | SPLAT | No | Up to 32 splats total |
| ... | Additional splats (up to splat31) | SPLAT | No | Up to 32 splats total |

**Note:** The input list automatically grows new slots as you connect splats. You must connect at least one splat. The node accepts a minimum of 2 and maximum of 32 splats.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `splat` | The merged gaussian splat containing all input splats concatenated together | SPLAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MergeSplat/en.md)

***

**Source fingerprint (SHA-256):** `597671a3c37d1a4fb7b5a772396e08b7041b3fe8f04120891b1382d42e409d26`


# MeshSmoothNormals - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshSmoothNormals

Compute smooth per-vertex normals for a mesh and attach them.

Compute smooth per-vertex normals for a mesh and attach them. Meshes without normals are shaded flat (per-face) by glTF viewers; this node makes them shade smoothly. With a crease angle below 180, edges sharper than the threshold are kept hard by splitting vertices along them.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The input mesh to process. | MESH | Yes | - |
| `crease_angle` | Edges whose dihedral angle exceeds this value (degrees) stay hard (vertices are split). 180 = fully smooth; lower preserves sharp edges (e.g. \~30-60 for hard-surface). Default: 180.0. | FLOAT | Yes | 0.0 to 180.0 (step 1.0) |

When `crease_angle` is 180 or higher, the mesh topology is unchanged. When set below 180, vertices are split along hard edges, which may increase the vertex count. When vertices are split, per-vertex data (colors, UVs, and tangents) is duplicated to match the new vertex layout, and the resulting mesh is rebuilt as a variable-size batch.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The input mesh with smooth normal data attached, or with split vertices and normals when a crease angle is set. | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshSmoothNormals/en.md)

***

**Source fingerprint (SHA-256):** `bbe9c0fba68369d8e9d3fb68e635869233804f3aac458e7c217d94977e77b9be`


# MeshTextureToImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshTextureToImage

This node extracts a mesh's baked textures and returns them as separate images: base color, metallic, roughness, occlusion, and normal map.

This node extracts a mesh's baked textures and returns them as separate images: base color, metallic, roughness, occlusion, and normal map. Texture channels that were not baked come back as neutral defaults — white for occlusion and a flat blue for the normal map.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The mesh whose baked textures are extracted. The mesh must have a base color texture; meshes that only have vertex colors (for example after a PaintMesh node) do not contain a texture and cause an error. | MESH | Yes | — |

Note: The mesh must have a baked base color texture. If it does not, the node raises an error and recommends running BakeTextureFromVoxel first. When the metallic-roughness texture is missing, the `metallic` and `roughness` outputs are black (0). The `occlusion` output is white unless the mesh contains baked ambient occlusion (the mesh's occlusion-in-metallic-roughness flag is set). The `normal_map` output is a flat neutral blue when no normal map was baked.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `base_color` | The base color texture of the mesh as an image. | IMAGE |
| `metallic` | The metallic channel from the mesh's occlusion-roughness-metallic texture, as a grayscale image. Black (0) means non-metallic, white (1) means fully metallic. Black when the texture is missing. | IMAGE |
| `roughness` | The roughness channel from the mesh's occlusion-roughness-metallic texture, as a grayscale image. Black when the texture is missing. | IMAGE |
| `occlusion` | The ambient occlusion channel from the mesh's occlusion-roughness-metallic texture, as a grayscale image. White (no occlusion) when ambient occlusion was not baked. | IMAGE |
| `normal_map` | The normal map texture of the mesh. A flat neutral normal map (0.5, 0.5, 1.0, appearing as flat blue) when no normal map was baked. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshTextureToImage/en.md)

***

**Source fingerprint (SHA-256):** `775fd50601ed9ebfc48abf1832c58acbac0f48b5faaebb5f7f46ae4a501278c4`


# MeshToFile3D - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshToFile3D

This node serializes a mesh into a GLB file object that can be passed to Save 3D or Preview 3D nodes.

This node serializes a mesh into a GLB file object that can be passed to Save 3D or Preview 3D nodes. It carries all mesh data along, including UVs, colors, normals, texture, normal/occlusion/emissive maps, and material settings. Only the first item of a multi-item batch is used.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The mesh to convert into a GLB file, including UVs, colors, normals, texture, normal/occlusion/emissive maps, and material. Only one item per batch is supported; if a batch contains multiple items, the first one is used. | MESH | Yes | Single mesh |

Note: The node supports one item per batch only. If the input mesh contains more than one item in its batch, a warning is logged and the first item is used. The mesh must contain at least one vertex and one face; an empty mesh raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | A GLB (glTF Binary) file object containing the serialized mesh, ready to be saved or previewed by other 3D nodes. | FILE3D |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshToFile3D/en.md)

***

**Source fingerprint (SHA-256):** `f004c2907c0df2e0127e49b4767d1624bf89c72665fc7028347a0b8a63a5772e`


# PaintMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PaintMesh

PaintMesh takes a 3D mesh and a voxel color field.

PaintMesh takes a 3D mesh and a voxel color field. It assigns each vertex the color of the nearest voxel in the field and returns the mesh with those vertex colors applied. If the voxel field is empty, the mesh is painted with default zero (black) vertex colors.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The mesh to be painted. | MESH | Yes | N/A |
| `voxel_colors` | Voxel field containing color data used for painting. Only the base color RGB channels are used from the field. | VOXEL | Yes | N/A |

Note: When the voxel field coordinates include a batch index channel and the input mesh contains multiple mesh items, the node applies the colors separately to each mesh item in the batch. If a given mesh item has no matching voxels, it receives default zero (black) vertex colors. The sampled colors are converted from sRGB to linear RGB for the output mesh, since the voxel field may carry full PBR data but only the base color RGB is used for vertex colors.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The painted mesh with vertex colors applied. | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PaintMesh/en.md)

***

**Source fingerprint (SHA-256):** `55683bef55b18487ba660fe619d6ec176f786de346be12724751b71901c14116`


# Preview3D - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Preview3D

Preview3D node is mainly used to preview 3D model outputs.

Preview3D node is mainly used to preview 3D model outputs. This node takes two inputs: one is the `camera_info` from the Load3D node, and the other is the path to the 3D model file. The model file path must be located in the `ComfyUI/output` folder.

**Supported Formats**
Currently, this node supports multiple 3D file formats, including `.gltf`, `.glb`, `.obj`, `.fbx`, and `.stl`.

**3D Node Preferences**
Some related preferences for 3D nodes can be configured in ComfyUI's settings menu. Please refer to the following documentation for corresponding settings:
[Settings Menu](https://docs.comfy.org/interface/settings/3d)

## Inputs

| Parameter Name | Description | Type |
| - | - | - |
| camera\_info | Camera information | LOAD3D\_CAMERA |
| model\_file | Model file path under `ComfyUI/output/` | LOAD3D\_CAMERA |

## Canvas Area Description

Currently, the 3D-related nodes in the ComfyUI frontend share the same canvas component, so their basic operations are mostly consistent except for some functional differences.

> The following content and interface are mainly based on the Load3D node. Please refer to the actual node interface for specific features.

The Canvas area includes various view operations, such as:

* Preview view settings (grid, background color, preview view)
* Camera control: FOV, camera type
* Global illumination intensity: adjust lighting
* Model export: supports `GLB`, `OBJ`, `STL` formats
* etc.

<img alt="Load 3D Node UI" />

1. Contains multiple menus and hidden menus of the Load 3D node
2. 3D view operation axis

### 1. View Operations

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

View control operations:

* Left-click + drag: Rotate the view
* Right-click + drag: Pan the view
* Middle wheel scroll or middle-click + drag: Zoom in/out
* Coordinate axis: Switch views

### 2. Left Menu Functions

![Menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu.webp)

In the preview area, some view operation menus are hidden in the menu. Click the menu button to expand different menus.

* 1. Scene: Contains preview window grid, background color, thumbnail settings
* 2. Model: Model rendering mode, texture material, up direction settings
* 3. Camera: Switch between orthographic and perspective views, set perspective angle
* 4. Light: Scene global illumination intensity
* 5. Export: Export model to other formats (GLB, OBJ, STL)

#### Scene

![scene menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_scene.webp)

The Scene menu provides some basic scene setting functions:

1. Show/Hide grid
2. Set background color
3. Click to upload a background image
4. Hide preview thumbnail

#### Model

![Menu\_Scene](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_model.webp)

The Model menu provides some model-related functions:

1. **Up direction**: Determine which axis is the up direction for the model
2. **Material mode**: Switch model rendering modes - Original, Normal, Wireframe, Lineart

#### Camera

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_camera.webp)

This menu provides switching between orthographic and perspective views, and perspective angle size settings:

1. **Camera**: Quickly switch between orthographic and perspective views
2. **FOV**: Adjust FOV angle

#### Light

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_light.webp)

Through this menu, you can quickly adjust the scene's global illumination intensity

#### Export

![menu\_export](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_export.webp)

This menu provides the ability to quickly convert and export model formats

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Preview3D/en.md)


# Preview3DAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Preview3DAdvanced

This node displays a 3D model preview in the UI without saving the file to the ComfyUI output directory.

This node displays a 3D model preview in the UI without saving the file to the ComfyUI output directory. It saves the model to a temporary file and passes through the model data, model information, camera information, and preview dimensions for further processing downstream.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | 3D model file from an upstream 3D node. | FILE3D | Yes | GLB, GLTF, FBX, OBJ, STL, USDZ, or any supported 3D format |
| `model_3d_info` | Placement of each model in the scene: position, rotation, and scale (Y-up world space). Optional. Advanced option. | LOAD3DMODELINFO | No | - |
| `viewport_state` | The current viewport state containing camera and model information. | LOAD3D | Yes | - |
| `camera_info` | Viewport camera information: position, look-at target, zoom, and type. Optional. Advanced option. | LOAD3DCAMERA | No | - |
| `width` | Render width of the viewport in pixels. Default: 1024. | INT | Yes | 1 to 4096 |
| `height` | Render height of the viewport in pixels. Default: 1024. | INT | Yes | 1 to 4096 |

Note: When `camera_info` or `model_3d_info` are not connected, their values are taken from `viewport_state` when available. If `viewport_state` contains no camera information, `camera_info` is None. If `viewport_state` has no model information, `model_3d_info` defaults to an empty list. If `viewport_state` is not a dictionary, it is treated as empty.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | 3D model file (glb/obj/stl/etc.) from an upstream 3D node, passed through unchanged. | FILE3D |
| `model_3d_info` | Placement of each model in the scene: position, rotation, and scale (Y-up world space). Uses the input value, or falls back to the value stored in `viewport_state`. | LOAD3DMODELINFO |
| `camera_info` | Viewport camera information: position, look-at target, zoom, and type. Uses the input value, or falls back to the value stored in `viewport_state`. | LOAD3DCAMERA |
| `width` | Render width of the viewport in pixels. | INT |
| `height` | Render height of the viewport in pixels. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Preview3DAdvanced/en.md)

***

**Source fingerprint (SHA-256):** `f2d3d35ed35fe68edebcde8fd8421d26850b04e3ae5b7147f1020c8ed904c480`


# Preview3DAnimation - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Preview3DAnimation

Preview3DAnimation node is mainly used to preview 3D model outputs.

Preview3DAnimation node is mainly used to preview 3D model outputs. This node takes two inputs: one is the `camera_info` from the Load3D node, and the other is the path to the 3D model file. The model file path must be located in the `ComfyUI/output` folder.

**Supported Formats**
Currently, this node supports multiple 3D file formats, including `.gltf`, `.glb`, `.obj`, `.fbx`, and `.stl`.

**3D Node Preferences**
Some related preferences for 3D nodes can be configured in ComfyUI's settings menu. Please refer to the following documentation for corresponding settings:
[Settings Menu](https://docs.comfy.org/interface/settings/3d)

## Inputs

| Parameter Name | Description | Type |
| - | - | - |
| camera\_info | Camera information | LOAD3D\_CAMERA |
| model\_file | Model file path under `ComfyUI/output/` | STRING |

## Canvas Area Description

Currently, the 3D-related nodes in the ComfyUI frontend share the same canvas component, so their basic operations are mostly consistent except for some functional differences.

> The following content and interface are mainly based on the Load3D node. Please refer to the actual node interface for specific features.

The Canvas area includes various view operations, such as:

* Preview view settings (grid, background color, preview view)
* Camera control: FOV, camera type
* Global illumination intensity: adjust lighting
* Model export: supports `GLB`, `OBJ`, `STL` formats
* etc.

<img alt="Load 3D Node UI" />

1. Contains multiple menus and hidden menus of the Load 3D node
2. 3D view operation axis

### 1. View Operations

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

View control operations:

* Left-click + drag: Rotate the view
* Right-click + drag: Pan the view
* Middle wheel scroll or middle-click + drag: Zoom in/out
* Coordinate axis: Switch views

### 2. Left Menu Functions

![Menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu.webp)

In the preview area, some view operation menus are hidden in the menu. Click the menu button to expand different menus.

* 1. Scene: Contains preview window grid, background color, thumbnail settings
* 2. Model: Model rendering mode, texture material, up direction settings
* 3. Camera: Switch between orthographic and perspective views, set perspective angle
* 4. Light: Scene global illumination intensity
* 5. Export: Export model to other formats (GLB, OBJ, STL)

#### Scene

![scene menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_scene.webp)

The Scene menu provides some basic scene setting functions:

1. Show/Hide grid
2. Set background color
3. Click to upload a background image
4. Hide preview thumbnail

#### Model

![Menu\_Scene](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_model.webp)

The Model menu provides some model-related functions:

1. **Up direction**: Determine which axis is the up direction for the model
2. **Material mode**: Switch model rendering modes - Original, Normal, Wireframe, Lineart

#### Camera

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_camera.webp)

This menu provides switching between orthographic and perspective views, and perspective angle size settings:

1. **Camera**: Quickly switch between orthographic and perspective views
2. **FOV**: Adjust FOV angle

#### Light

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_light.webp)

Through this menu, you can quickly adjust the scene's global illumination intensity

#### Export

![menu\_export](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3D/asset/menu_export.webp)

This menu provides the ability to quickly convert and export model formats

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Preview3DAnimation/en.md)


# PreviewGaussianSplat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PreviewGaussianSplat

The PreviewGaussianSplat node displays a 3D gaussian splat file in a preview window without saving it to the ComfyUI output directory.

The PreviewGaussianSplat node displays a 3D gaussian splat file in a preview window without saving it to the ComfyUI output directory. It accepts a 3D model file in various gaussian splat formats, saves a temporary copy for previewing, and passes the model data through for further processing in the workflow. This node is marked as experimental and acts as an output node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | A gaussian splat 3D file. | FILE3D | Yes | splat<br />ply<br />spz<br />ksplat |
| `model_3d_info` | Optional metadata information about the 3D model. When not connected, the node uses the model info from `viewport_state`. | LOAD3DMODELINFO | No | - |
| `viewport_state` | The current state of the 3D viewport, including camera and model information. | LOAD3D | Yes | - |
| `camera_info` | Optional camera information for the preview. When not connected, the node uses the camera info from `viewport_state`. | LOAD3DCAMERA | No | - |
| `width` | The width of the preview render in pixels (default: 1024). | INT | Yes | 1 to 4096 |
| `height` | The height of the preview render in pixels (default: 1024). | INT | Yes | 1 to 4096 |

Note: When `camera_info` or `model_3d_info` are not provided, the node falls back to the camera and model information stored in `viewport_state`. If `viewport_state` is not a valid viewport state object, it is treated as empty.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | The input 3D gaussian splat file, passed through unchanged. | FILE3D |
| `model_3d_info` | Metadata information about the 3D model, either from the input or derived from the viewport state. | LOAD3DMODELINFO |
| `camera_info` | Camera information for the preview, either from the input or derived from the viewport state. | LOAD3DCAMERA |
| `width` | The width of the preview render. | INT |
| `height` | The height of the preview render. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PreviewGaussianSplat/en.md)

***

**Source fingerprint (SHA-256):** `4fc86c692724ce406f9bba9aa9ebe22a92e72a25d11abf8f55d1b99044bb1acd`


# PreviewPointCloud - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PreviewPointCloud

The Preview Point Cloud node lets you view a 3D point cloud file in the ComfyUI interface without saving it to the ComfyUI output directory.

The Preview Point Cloud node lets you view a 3D point cloud file in the ComfyUI interface without saving it to the ComfyUI output directory. It saves the point cloud to a temporary location and displays it in a 3D preview window, while also passing the model data, model information, camera information, and preview dimensions through for further processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | Point cloud file (.ply) | FILE3D | Yes | - |
| `model_3d_info` | Information about the 3D model | LOAD3DMODELINFO | No | - |
| `viewport_state` | The current state of the 3D viewport | LOAD3D | Yes | - |
| `camera_info` | Camera information for the 3D view | LOAD3DCAMERA | No | - |
| `width` | Width of the preview window (default: 1024) | INT | Yes | 1 to 4096 |
| `height` | Height of the preview window (default: 1024) | INT | Yes | 1 to 4096 |

Note: `model_3d_info` and `camera_info` are optional advanced inputs. When they are not connected, the node falls back to the corresponding values stored in `viewport_state`. The point cloud file is written to ComfyUI's temporary directory rather than the output directory. This is an output (terminal) node, so it is primarily used to display the preview in the interface.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | The point cloud model data | FILE3D |
| `model_3d_info` | Information about the 3D model | LOAD3DMODELINFO |
| `camera_info` | Camera information for the 3D view | LOAD3DCAMERA |
| `width` | Width of the preview window | INT |
| `height` | Height of the preview window | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PreviewPointCloud/en.md)

***

**Source fingerprint (SHA-256):** `a0b13d9d5658343a6a7c25408d5e5cd9249c92264b76aa448a6553b370f4d782`


# RemeshMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RemeshMesh

Remesh Mesh rebuilds a mesh with a clean, uniform tessellation by sampling a narrow-band distance field around the original surface and extracting it with Dual Contouring.

Remesh Mesh rebuilds a mesh with a clean, uniform tessellation by sampling a narrow-band distance field around the original surface and extracting it with Dual Contouring. This normalizes messy, non-manifold, or self-intersecting topology, and is meant to be run before Decimate Mesh to reach an exact face count. Processing runs on the active compute device and the output mesh stays welded.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The input mesh to remesh. | MESH | Yes | — |
| `resolution` | Voxel grid resolution (output density). 256 \~ 100k faces, 512 \~ 1M. For an exact face count, follow with Decimate Mesh. (default: 512) | INT | Yes | 32 - 2048 |
| `sign_mode` | Surface extraction mode. "udf" is robust to messy/non-manifold input; "sdf" produces a clean single surface with QEF (Quadratic Error Function) sharp-feature recovery, but needs consistent winding. Selecting a mode reveals its specific sub-options. (default: "udf") | DYNAMIC\_COMBO | Yes | "udf"<br />"sdf" |
| `band` | Narrow-band width in voxel units. In UDF mode also offsets the surface. (advanced, default: 1.0) | FLOAT | Yes | 0.5 - 4.0 |
| `project_back` | Linearly interpolate vertices toward the original surface (0 = pure DC, 1 = snapped). (advanced, default: 0.0) | FLOAT | Yes | 0.0 - 1.0 |
| `fix_poles` | Collapse valence-3 vertex pairs (DC T-junction artifact). (advanced, default: false) | BOOLEAN | Yes | true / false |
| `smooth_iters` | Taubin smoothing iterations (0 = off). 2-3 cleans DC staircase-like artifacts; higher over-smooth QEF edges. (default: 0) | INT | Yes | 0 - 20 |
| `drop_small_components` | Drop components below this fraction of the largest's face count. 0 disables. (advanced, default: 0.01) | FLOAT | Yes | 0.0 - 0.5 |
| `precluster_max_verts` | Cap input vertex count before the field queries; inputs above this are cluster-decimated to it first. Prevents OOM on huge meshes. (advanced, default: 20,000,000) | INT | Yes | 0 - 100,000,000 |

### "udf" Mode Inputs

These parameters appear when `sign_mode` is set to `"udf"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `qef` | QEF (Quadratic Error Function) dual-vertex placement for sharper edges. (advanced, default: false) | BOOLEAN | No | true / false |
| `drop_inverted_components` | Drop inward-normal (negative-volume) closed components — the UDF inner shell. (advanced, default: false) | BOOLEAN | No | true / false |
| `drop_enclosed_components` | Drop components inside the largest's bbox that fail a point-in-mesh raycast. Disable for legitimate nested parts. (advanced, default: false) | BOOLEAN | No | true / false |

### "sdf" Mode Inputs

These parameters appear when `sign_mode` is set to `"sdf"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `qef` | QEF (Quadratic Error Function) dual-vertex placement (recovers sharp features) vs edge-crossing centroid. (default: true) | BOOLEAN | No | true / false |
| `manifold` | Manifold Dual Contouring: 1-4 dual verts/voxel for multi-sheet cases. Slower. (default: false) | BOOLEAN | No | true / false |

Note: The `qef` option has a different default depending on the selected mode — false in "udf" mode, true in "sdf" mode. When `precluster_max_verts` is greater than 0 and the input mesh has more vertices than this value, the mesh is cluster-decimated down to that target before the field queries. After processing, the node displays the input-to-output face count change on the node (for example, "faces: 1.23M → 200K (-84%)").

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The remeshed mesh with uniform tessellation and welded topology. Vertex colors are preserved when present on the input; any UVs, normals, and tangents are not carried over. | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RemeshMesh/en.md)

***

**Source fingerprint (SHA-256):** `aa9b7e4465196fab81a4a484ca9dd03d999b4621a611aed2b39d618e53702a06`


# RenderMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RenderMesh

This node renders a 3D mesh into a 2D image by ray-casting a single view.

This node renders a 3D mesh into a 2D image by ray-casting a single view. It can output the textured mesh, vertex colors, a solid shaded surface, surface normals, or depth. The camera and optional model transform can come from a Load3D / Preview3D viewer; if no camera is connected, a default front view is auto-framed.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The 3D mesh to render. | MESH | Yes | — |
| `mode` | What to render. auto: texture if present, else vertex colours, else shaded clay. (default: "auto") | COMBO | Yes | `"auto"`<br />`"texture"`<br />`"vertex colors"`<br />`"solid"`<br />`"normal"`<br />`"depth"` |
| `width` | Width of the rendered image in pixels. (default: 1024) | INT | Yes | 64 to 4096 (step 8) |
| `height` | Height of the rendered image in pixels. (default: 1024) | INT | Yes | 64 to 4096 (step 8) |
| `background` | Background color used for pixels the mesh does not cover. (default: "#000000") | COLOR | Yes | — |
| `model_3d_info` | Model transform from the same Load3D / Preview3D viewer. Connect it with camera\_info to match the viewer framing. | LOAD3D\_MODEL\_INFO | No | — |
| `camera_info` | Camera from a Load3D / Preview3D viewer or a Create Camera Info node. If none is connected, a default front view is auto-framed. | LOAD3D\_CAMERA | No | — |

Note: Only the first item of a batched mesh is rendered — if the mesh batch contains more than one item, the node logs a warning and uses the first one. The `texture` mode requires the mesh to have both a texture and UVs, and the `vertex colors` mode requires vertex colors; if the data for the selected mode is not available, the node falls back to the solid shaded render. The `normal` mode uses the mesh's smooth vertex normals when present, otherwise the per-face normal. In `depth` mode, closer surfaces appear brighter (near = white) and pixels not covered by the mesh stay black. The `model_3d_info` and `camera_info` are meant to be connected together from the same Load3D / Preview3D viewer so the render matches the viewer framing.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The rendered image of the mesh. | IMAGE |
| `mask` | A mask that is 1.0 where the mesh was rendered and 0.0 elsewhere. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RenderMesh/en.md)

***

**Source fingerprint (SHA-256):** `d23e85a904520eb2dfed899eb3e6a9cf45c980df00c034503687ac4eccc66ac4`


# RenderSplat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RenderSplat

Render a gaussian splat as an image using an anisotropic EWA rasterizer with oriented elliptical splats, antialiasing, and depth-sorted front-to-back rendering.

Render a gaussian splat as an image using an anisotropic EWA rasterizer with oriented elliptical splats, antialiasing, and depth-sorted front-to-back rendering. The camera comes from a camera\_info input, or you can leave it empty to auto-frame the splat. Set frames greater than 1 for a turntable batch of images to feed a Video node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `splat` | The gaussian splat data to render | SPLAT | Yes | - |
| `width` | Width of the output image (default: 1024) | INT | Yes | 64 to 2048 (step: 8) |
| `height` | Height of the output image (default: 1024) | INT | Yes | 64 to 2048 (step: 8) |
| `frames` | Number of frames to render. -1, 0, or 1 produces a single still image. Values greater than 1 create a turntable animation where the camera orbits over a full 360 degree turn. Negative values orbit in the opposite direction (default: 1) | INT | Yes | -240 to 240 |
| `splat_scale` | Multiplier on each splat's projected footprint. Lower values produce crisper points, higher values produce softer and fuller surfaces (default: 1.0) | FLOAT | Yes | 0.1 to 5.0 (step: 0.05) |
| `sharpen` | Controls sharpness of overlapping splats. A value of 1.0 gives physically-correct blending. Values above 1.0 bias each pixel toward its dominant (nearest) splat for crisper texture without shrinking splats or opening gaps (default: 2.0) | FLOAT | Yes | 1.0 to 8.0 (step: 0.5) |
| `headlight_shading` | Diffuse shading from a light at the camera position, using the splat surfel normals. Darkens surfaces that turn away from view to reveal form and curvature. 0 gives flat albedo, 1 gives strongest shading (default: 0.0) | FLOAT | Yes | 0.0 to 3.0 (step: 0.05) |
| `opacity_threshold` | Culls gaussians with opacity below this threshold, which removes faint floaters (default: 0.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `render_style` | What the image output shows. Options are: color (full color rendering), clay (neutral-albedo shaded), depth (near objects appear bright), normal (OpenGL normal map) (default: "color") | COMBO | Yes | "color"<br />"clay"<br />"depth"<br />"normal" |
| `background` | Solid background color for the render (default: #000000) | COLOR | Yes | - |
| `bg_image` | Optional background plate composited behind the splat. Overrides the solid background color. Resized to the render size. A batch of images is used per frame, a single image is used for all frames. Only works with color and clay render styles | IMAGE | No | - |
| `camera_info` | Camera to render from. Can come from a Load3D, Preview3D, or Create Camera Info node. If empty, the splat is auto-framed from a default 3/4 view | CAMERA\_3D | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The rendered image of the gaussian splat | IMAGE |
| `mask` | The alpha mask of the rendered splat | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RenderSplat/en.md)

***

**Source fingerprint (SHA-256):** `038bd9fb032f347ecda665c03719a64b0cf907599b701606f5cf6d0606d19d98`


# RenderUVAtlas - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RenderUVAtlas

Renders a mesh's UV layout as an image.

Renders a mesh's UV layout as an image. Each connected UV region (chart) is filled with a distinct color, and chart boundary edges are outlined in black on a dark gray background.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The 3D mesh whose UV layout will be rendered. The mesh must have UV coordinates; otherwise the node raises the error "mesh has no UVs to render. Run UnwrapMesh first." | MESH | Yes | - |
| `resolution` | The width and height, in pixels, of the rendered square image (default: 1024). | INT | Yes | 64 to 4096 (step 64) |

Note: If the mesh contains a batch dimension (3D UV or face arrays), only the first item in the batch is rendered.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The rendered UV atlas image, returned as a single-image batch. Each UV chart is colored, and chart boundary edges are outlined in black. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RenderUVAtlas/en.md)

***

**Source fingerprint (SHA-256):** `b462101036418350390ffed621e583c6de14d5ea34d1e427342dc44ec3fd1922`


# RotateMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RotateMesh

Rotate a 3D mesh around the world axes using either Euler XYZ angles (in degrees) or a quaternion.

Rotate a 3D mesh around the world axes using either Euler XYZ angles (in degrees) or a quaternion. In Euler XYZ mode the rotations are applied as X then Y then Z; in quaternion mode the (w, x, y, z) quaternion is automatically normalized. The rotation is applied to the mesh's vertices, and the normals and tangents are rotated as well so lighting and shading remain correct.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mode` | The rotation mode to use. `"euler_xyz"` applies rotation as X then Y then Z angles about the world axes (in degrees). `"quaternion"` uses a (w, x, y, z) quaternion that is automatically normalized. | DYNAMIC\_COMBO | Yes | `"euler_xyz"`<br />`"quaternion"` |
| `mesh` | The 3D mesh to rotate. | MESH | Yes | — |

### euler\_xyz Inputs

These inputs appear when `mode` is set to `"euler_xyz"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `angle_x` | Rotation around the X axis in degrees. (default: 0.0) | FLOAT | No | -360.0 to 360.0 (step: 0.1) |
| `angle_y` | Rotation around the Y axis in degrees. (default: 0.0) | FLOAT | No | -360.0 to 360.0 (step: 0.1) |
| `angle_z` | Rotation around the Z axis in degrees. (default: 0.0) | FLOAT | No | -360.0 to 360.0 (step: 0.1) |

### quaternion Inputs

These inputs appear when `mode` is set to `"quaternion"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `qw` | W component of the quaternion (w, x, y, z). (default: 1.0) | FLOAT | No | -1.0 to 1.0 (step: 0.001) |
| `qx` | X component of the quaternion (w, x, y, z). (default: 0.0) | FLOAT | No | -1.0 to 1.0 (step: 0.001) |
| `qy` | Y component of the quaternion (w, x, y, z). (default: 0.0) | FLOAT | No | -1.0 to 1.0 (step: 0.001) |
| `qz` | Z component of the quaternion (w, x, y, z). (default: 0.0) | FLOAT | No | -1.0 to 1.0 (step: 0.001) |

**Note:** When `mode` is `"euler_xyz"` and all three angles are 0.0, or when `mode` is `"quaternion"` and the quaternion is the identity (1, 0, 0, 0), the mesh is returned unchanged. The quaternion is automatically normalized before use; if its magnitude is below 1e-8, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The rotated mesh. Vertices are rotated, and normals are rotated as directions. Tangents have their X, Y, Z components rotated while the W (handedness) component is kept unchanged. | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RotateMesh/en.md)

***

**Source fingerprint (SHA-256):** `38b120a3f719264d1269275ecfefa145b507c688735e4a461bb89517c697674f`


# Save3DAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Save3DAdvanced

Saves a 3D model to a file in the ComfyUI output directory and produces a preview of the saved scene.

Saves a 3D model to a file in the ComfyUI output directory and produces a preview of the saved scene. It also passes the 3D model, its placement in the scene, camera information, and viewport dimensions through to downstream nodes. When model placement or camera information are not connected, the node uses the values stored in the viewport state.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | 3D model file from an upstream 3D node. | FILE3D | Yes | GLB<br />GLTF<br />FBX<br />OBJ<br />STL<br />USDZ<br />Any |
| `filename_prefix` | Prefix used for the saved file name (default: "3d/ComfyUI"). | STRING | Yes | Free text |
| `viewport_state` | Viewport state containing camera and model placement information, typically from a Load 3D node. | LOAD3D | Yes | - |
| `model_3d_info` | Placement of each model in the scene: position, rotation, and scale (Y-up world space). Overrides the model placement stored in `viewport_state` when connected. | LOAD3DMODELINFO | No | - |
| `camera_info` | Viewport camera information: position, look-at target, zoom, and type. Overrides the camera information stored in `viewport_state` when connected. | LOAD3DCAMERA | No | - |
| `width` | Render width of the viewport in pixels (default: 1024). | INT | Yes | 1 to 4096 |
| `height` | Render height of the viewport in pixels (default: 1024). | INT | Yes | 1 to 4096 |

Note: `model_3d_info` and `camera_info` are optional. When either input is not connected, the node falls back to the corresponding values stored in `viewport_state`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | The 3D model file passed through from the input. | FILE3D |
| `model_3d_info` | Placement of each model in the scene: position, rotation, and scale (Y-up world space). | LOAD3DMODELINFO |
| `camera_info` | Viewport camera information: position, look-at target, zoom, and type. | LOAD3DCAMERA |
| `width` | The render width value passed through from the input. | INT |
| `height` | The render height value passed through from the input. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Save3DAdvanced/en.md)

***

**Source fingerprint (SHA-256):** `27cb15c5cf382e6e5b8164cfd456993404222c61d59edff2d51f9f1c8e47b25f`


# SaveGLB - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveGLB

The SaveGLB node saves 3D mesh data or 3D file inputs to the output directory.

The SaveGLB node saves 3D mesh data or 3D file inputs to the output directory. It accepts mesh data and common 3D file formats (GLB, GLTF, OBJ, FBX, STL, USDZ, PLY, SPLAT, SPZ, KSPLAT) and exports them with the specified filename prefix. Mesh inputs are written as GLB files, one per batch item, while 3D file inputs are saved in their original format.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | Mesh or 3D file to save | MESH or FILE3D | Yes | Mesh data<br />GLB<br />GLTF<br />OBJ<br />FBX<br />STL<br />USDZ<br />PLY<br />SPLAT<br />SPZ<br />KSPLAT<br />Any splat format<br />Any point cloud format<br />Any 3D file format |
| `filename_prefix` | The prefix for the output filename (default: "3d/ComfyUI"). The prefix can include a subfolder path, so files are saved under the "3d" subfolder of the output directory by default | STRING | No | - |

Note: When the `mesh` input is a 3D file, the node saves it using its original format extension (GLB is used if the file has no format). When it is mesh data, each item in the batch is saved as a separate `.glb` file; empty items (with no vertices or faces) are skipped with a warning. Output filenames follow the pattern `{filename_prefix}_{counter:05}_.{ext}` with an incrementing counter. Workflow metadata (prompt and extra PNG info) is embedded in the saved files when metadata is enabled.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `ui` | Displays the saved 3D files in the user interface with filename, subfolder, and type information | UI |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveGLB/en.md)

***

**Source fingerprint (SHA-256):** `366b56c4fd6e3c2f7783222990792a982857b3419a2becfa27ddfa37853bb22c`


# SaveGaussianSplat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveGaussianSplat

This node saves a Gaussian splat 3D file to the output directory.

This node saves a Gaussian splat 3D file to the output directory. It handles the file saving process and provides preview data for the 3D viewport.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | A gaussian splat 3D file. | FILE3D | Yes | SplatAny<br />PLY<br />SPLAT<br />SPZ<br />KSPLAT |
| `filename_prefix` | The prefix for the saved filename (default: "3d/ComfyUI"). | STRING | Yes | Any valid filename prefix |
| `viewport_state` | The current viewport state containing camera and model information. | LOAD3D | Yes | - |
| `model_3d_info` | Additional model 3D information for the viewport. | LOAD3DMODELINFO | No | - |
| `camera_info` | Camera information for the viewport preview. | LOAD3DCAMERA | No | - |
| `width` | The width of the preview (default: 1024). | INT | Yes | 1 to 4096 |
| `height` | The height of the preview (default: 1024). | INT | Yes | 1 to 4096 |

Note: If `camera_info` or `model_3d_info` are not provided, the node uses the corresponding values from `viewport_state` when available.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | The Gaussian splat 3D file that was saved to the output directory. | FILE3D |
| `model_3d_info` | Model 3D information for the viewport. | LOAD3DMODELINFO |
| `camera_info` | Camera information for the viewport preview. | LOAD3DCAMERA |
| `width` | The width of the preview. | INT |
| `height` | The height of the preview. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveGaussianSplat/en.md)

***

**Source fingerprint (SHA-256):** `f2d6b98d2ce1fe11df8ba440b7f46a21e2308966c15daa5ca0bdca7dab1726cc`


# SavePointCloud - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SavePointCloud

The Save Point Cloud node saves a 3D point cloud file to the output directory and optionally provides preview data for the 3D viewer.

The Save Point Cloud node saves a 3D point cloud file to the output directory and optionally provides preview data for the 3D viewer. It handles file naming and saving, while also passing through camera and model information for display purposes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | Point cloud file (.ply) | FILE3D\_POINT\_CLOUD\_ANY or FILE3D\_PLY | Yes | - |
| `filename_prefix` | Prefix for the saved file name (default: "3d/ComfyUI") | STRING | Yes | - |
| `viewport_state` | Current viewport state containing camera and model information | LOAD3D | Yes | - |
| `model_3d_info` | Additional model information for the 3D viewer | LOAD3D\_MODEL\_INFO | No | - |
| `camera_info` | Camera information for the 3D viewer | LOAD3D\_CAMERA | No | - |
| `width` | Width of the preview display in pixels (default: 1024) | INT | Yes | 1 to 4096 |
| `height` | Height of the preview display in pixels (default: 1024) | INT | Yes | 1 to 4096 |

The saved file is written to the output directory using the `filename_prefix` with a 5-digit counter appended (for example, `3d/ComfyUI_00001.ply`). When the optional `camera_info` input is not connected, the camera information is taken from `viewport_state`; similarly, when `model_3d_info` is not connected, the model information is taken from `viewport_state` (or an empty list if none is available).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | The saved point cloud file | FILE3D\_POINT\_CLOUD\_ANY |
| `model_3d_info` | Model information for the 3D viewer | LOAD3D\_MODEL\_INFO |
| `camera_info` | Camera information for the 3D viewer | LOAD3D\_CAMERA |
| `width` | Width of the preview display | INT |
| `height` | Height of the preview display | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SavePointCloud/en.md)

***

**Source fingerprint (SHA-256):** `ce8f005c431843a57d87a4aff2eed7a1604ebdf360f83b3aaaadc3ed364d218a`


# SplatToFile3D - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplatToFile3D

The SplatToFile3D node converts a gaussian splat into a File3D object that can be used with Save or Preview 3D nodes.

The SplatToFile3D node converts a gaussian splat into a File3D object that can be used with Save or Preview 3D nodes. It supports one item per batch only and allows you to choose from different output file formats for the exported 3D data.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `splat` | The gaussian splat data to be serialized into a file | SPLAT | Yes | - |
| `format` | The output file format for the 3D file (default: "ply"). ply: standard 3D Gaussian Splat with full spherical harmonics. ksplat: mkkellogg SplatBuffer (level 0, uncompressed), base color only. spz: Niantic gzip-compressed (\~10x smaller), base color only | COMBO | Yes | "ply"<br />"ksplat"<br />"spz" |

Note: This node supports one item per batch only. If the input splat contains more than one item in the batch, the node logs a warning and uses the first item. If an unsupported format is provided, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | A File3D object containing the serialized gaussian splat data in the selected format, ready for saving or previewing | FILE3D |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SplatToFile3D/en.md)

***

**Source fingerprint (SHA-256):** `4bb49f417a66f25fce577894a67f39bae6157c4eb88ccf8fad77d74141a50409`


# SplatToMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplatToMesh

This node converts a 3D Gaussian splat into a colored mesh surface.

This node converts a 3D Gaussian splat into a colored mesh surface. It works by rasterizing the gaussians onto a density grid, extracting an iso-surface at a chosen density level, and then applying optional smoothing and cleanup to produce a clean, colored triangle mesh.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `splat` | The input gaussian splat to convert to a mesh | SPLAT | Yes | - |
| `resolution` | Density-grid resolution along the longest axis. Higher values produce finer surface detail but require more VRAM and processing time (grows with resolution^3). Default: 384 | INT | Yes | 64 - 768 (step 16) |
| `kernel` | Maximum splat half-width in voxels. Each gaussian is rasterized over a window sized to its own 3-sigma, capped at this value. Small surfels stay cheap while large ones aren't truncated. Raise if sparse splats leave gaps. Default: 5 | INT | Yes | 1 - 8 |
| `smooth` | Taubin mesh-smoothing iterations. Smooths the surface without shrinking it (volume-preserving), unlike blurring the density. 0 means no smoothing. Default: 0 | INT | Yes | 0 - 60 |
| `level` | Iso-surface level. Auto-picked by Otsu thresholding; this value biases the auto-pick (1.0 = auto, lower values produce fatter/more-connected surfaces, higher values produce thinner/tighter surfaces). Default: 0.4 | FLOAT | Yes | 0.0 - 2.0 (step 0.01) |
| `min_component` | Drops connected components smaller than this many vertices. Removes detached floater blobs and the inner shell of double walls. 0 keeps all components. Default: 500 | INT | Yes | 0 - 100000 (step 50) |
| `min_opacity` | Ignores gaussians fainter than this value before meshing. Default: 0.02 | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |
| `color_sharpen` | Crisps up the vertex texture. 1.0 gives physically-correct blend; higher values bias each voxel's color toward its dominant gaussian instead of averaging neighbors (de-smears the texture). Affects color only, not geometry. Default: 2.0 | FLOAT | Yes | 1.0 - 8.0 (step 0.5) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The extracted colored mesh with unlit rendering (emissive-like) to match the splat appearance | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SplatToMesh/en.md)

***

**Source fingerprint (SHA-256):** `5a7060c26252b587ce533e5682abe880a6fcc83f6671232489c3de64b094cd84`


# TransformSplat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TransformSplat

The Transform Splat node applies translation, rotation, and scaling transformations to a gaussian splat.

The Transform Splat node applies translation, rotation, and scaling transformations to a gaussian splat. It moves, rotates, and resizes the entire splat as a single object, and when non-uniform scaling is applied, it also reshapes each individual gaussian splat for accurate results.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `splat` | The gaussian splat to transform | SPLAT | Yes | - |
| `translate_x` | Translation along the X axis (default: 0.0) | FLOAT | Yes | -100.0 to 100.0 |
| `translate_y` | Translation along the Y axis (default: 0.0) | FLOAT | Yes | -100.0 to 100.0 |
| `translate_z` | Translation along the Z axis (default: 0.0) | FLOAT | Yes | -100.0 to 100.0 |
| `rotate_x` | Rotation around the X axis in degrees (default: 0.0) | FLOAT | Yes | -360.0 to 360.0 |
| `rotate_y` | Rotation around the Y axis in degrees (default: 0.0) | FLOAT | Yes | -360.0 to 360.0 |
| `rotate_z` | Rotation around the Z axis in degrees (default: 0.0) | FLOAT | Yes | -360.0 to 360.0 |
| `scale_x` | Scale factor along the X axis (default: 1.0) | FLOAT | Yes | 0.01 to 100.0 |
| `scale_y` | Scale factor along the Y axis (default: 1.0) | FLOAT | Yes | 0.01 to 100.0 |
| `scale_z` | Scale factor along the Z axis (default: 1.0) | FLOAT | Yes | 0.01 to 100.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `splat` | The transformed gaussian splat with updated positions, scales, and rotations | SPLAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TransformSplat/en.md)

***

**Source fingerprint (SHA-256):** `19e6a7da7b4f0d8c9674ead2d35d742df460576b01c4ab4108dd59a2d08dfcb0`


# UnwrapMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UnwrapMesh

Generates a UV atlas for a 3D mesh.

Generates a UV atlas for a 3D mesh. The mesh surface is split into charts, each chart is flattened into two dimensions, and the flattened charts are packed into a \[0,1] UV atlas. Vertices on chart seams are duplicated (one copy per chart, same position, own UV), so the output mesh can contain more vertices than the input mesh, and the output faces may differ in count from the input.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The input mesh to unwrap. Accepts a single mesh or a batch of meshes; batches are processed one item at a time. | MESH | Yes | — |
| `segmenter` | Charting algorithm to use. `pec`: fast parallel-edge-collapse charting on GPU. `adaptive`: CPU, slower. (default: "pec") | COMBO | Yes | "pec"<br />"adaptive" |
| `resolution` | Target atlas resolution for texel-density auto-scale (0 = fit-to-content). (default: 1024) | INT | Yes | 0 to 8192 (step 256) |
| `padding` | Texel padding between charts. (default: 1) | INT | Yes | 0 to 16 |
| `weld_distance` | Coincident-vert merge radius as a fraction of mesh extent (0 = auto). Raise to \~0.001 if you get per-triangle charts (unwelded input). (default: 0.0) | FLOAT | Yes | 0.0 to 1.0 (step 0.0001) |

Note: if the input mesh contains unwelded vertices, the node may warn that face adjacency is low and produce per-face UV charts; increasing `weld_distance` merges coincident vertices before unwrapping. Degenerate faces (faces that reuse the same vertex index) are dropped during processing.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The input mesh with a generated UV atlas in the range \[0,1]. Seam vertices are duplicated, so the output vertex count can exceed the input. Vertex colors and texture from the input mesh are preserved. | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/UnwrapMesh/en.md)

***

**Source fingerprint (SHA-256):** `fcab6f0b621693d862ee74b5ec498498d2f1f247a66f478704377598a6b39388`


# VoxelToMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VoxelToMesh

The VoxelToMesh node converts 3D voxel data into a mesh geometry by extracting a surface at a specified threshold value.

The VoxelToMesh node converts 3D voxel data into a mesh geometry by extracting a surface at a specified threshold value. It offers two algorithms for surface extraction: a basic method that creates simple box-like faces, and a surface net method that produces smoother, more detailed meshes. The node processes each voxel grid in the input and generates vertices and faces that form a 3D mesh representation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `voxel` | The input voxel data to convert to mesh geometry | VOXEL | Yes | - |
| `algorithm` | The algorithm used for surface extraction. "surface net" produces smoother meshes, while "basic" creates simple box-like faces (default: "surface net") | COMBO | Yes | `"surface net"`<br />`"basic"` |
| `threshold` | The threshold value for surface extraction. Voxels with values above this threshold are considered solid (default: 0.6) | FLOAT | Yes | -1.0 to 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MESH` | The generated 3D mesh containing vertices and faces from all input voxel grids. If all voxel grids produce meshes with identical shapes, the output is a stacked tensor; otherwise, a variable-length batch is returned | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VoxelToMesh/en.md)

***

**Source fingerprint (SHA-256):** `b600be13f1a484d8c0cc1f9c3918630d00c15d35008bcac0f677b21ef64b5d98`


# WeldVertices - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WeldVertices

Weld Vertices merges coincident vertices in a 3D mesh, so faces that previously had separate corner points end up sharing the same vertices.

Weld Vertices merges coincident vertices in a 3D mesh, so faces that previously had separate corner points end up sharing the same vertices. It groups nearby vertices using grid quantization with a tolerance based on the mesh bounding box, and averages vertex colors for each merged group. This is useful when a mesh arrives unwelded, meaning each face has its own vertices and no shared edges, and can serve as a pre-pass before topology-aware operations such as FillHoles or DecimateMesh.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mesh` | The input 3D mesh whose coincident vertices will be merged. | MESH | Yes | - |
| `epsilon_rel` | Weld tolerance (fraction of bbox diagonal). 1e-5 for float dedup; 1e-3 for visibly-close-but-distinct verts. Default: 1e-5. | FLOAT | Yes | 0.0 to unlimited (step 1e-6) |
| `epsilon_abs` | Absolute weld tolerance (overrides epsilon\_rel when > 0). Default: 0.0. | FLOAT | Yes | 0.0 to unlimited (step 1e-6) |

Note: When `epsilon_abs` is greater than 0, it takes precedence over `epsilon_rel` and the relative tolerance is ignored. When `epsilon_abs` is 0, the relative tolerance `epsilon_rel` is used, converted into an absolute distance by multiplying it with the mesh bounding box diagonal.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The welded mesh with merged vertices, updated face indices, and averaged vertex colors (if the input mesh had colors). | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WeldVertices/en.md)

***

**Source fingerprint (SHA-256):** `f8779e764b344de651b8459f6e4c28773509d9596a98fd164dc7044278856435`


# ComfyUI Built-in Nodes
Source: https://docs.comfy.org/built-in-nodes/overview

Introduction to ComfyUI Built-in Nodes

Built-in nodes are ComfyUI's default nodes. They are core functionalities of ComfyUI that you can use without installing any third-party custom node packages.

## About built-in node document

We have now added built-in node help documentation, so the content of this section is periodically synced from [this repo](https://github.com/Comfy-Org/embedded-docs). We will update the content manually once a week.

## Contribute

If you find any errors in the content, or want to contribute missing content, please submit an issue or PR in [this repo](https://github.com/Comfy-Org/embedded-docs) to help us improve.


# Changelog
Source: https://docs.comfy.org/changelog/index

ComfyUI changelog: the latest features, improvements, and bug fixes in each release, updated as new versions ship.

<Update label="v0.38.1" description="September 30, 2026">
  **Partner Node Updates**

  * [**Ideogram 4.5**](https://github.com/Comfy-Org/ComfyUI/pull/16689): Text-to-image, edit, and precise edit nodes for the new model
  * [**HeyGen Video 1.0**](https://github.com/Comfy-Org/ComfyUI/pull/16695): Reference-to-video and image-to-video nodes
  * [**Claude Sonnet 5.5**](https://github.com/Comfy-Org/ComfyUI/pull/16647): Added to the Claude node

  **Bug Fixes**

  * [**Qwen-Image 2.1 cache**](https://github.com/Comfy-Org/ComfyUI/pull/16667): Fixed a crash when selecting int8 or int4 cache
</Update>

<Update label="v0.38.0" description="September 29, 2026">
  **New Open-Source Model Support**

  * [**Ming Image 0.1 Design**](https://github.com/Comfy-Org/ComfyUI/pull/16482): A 6B text-to-image model for text-heavy design layouts, with transparent RGBA output
  * [**MiniMax-H3 Fun ControlNet Union 2.0**](https://github.com/Comfy-Org/ComfyUI/pull/16471): Combine multiple control conditions in one H3 generation
  * [**ID-V2V**](https://github.com/Comfy-Org/ComfyUI/pull/15139): Identity-preserving video-to-video on Wan 2.1 and VACE based models
  * [**Qwen-Image 2.1 ControlNet**](https://github.com/Comfy-Org/ComfyUI/pull/16519): Union Fun ControlNet support for Qwen-Image 2.1 editing
  * [**Qwen-Image 2.1 tiny VAE**](https://github.com/Comfy-Org/ComfyUI/pull/16552): A tiny VAE for faster previews and lower memory use

  **New Node Updates**

  * [**Convert Image Color Space**](https://github.com/Comfy-Org/ComfyUI/pull/16541): Added the LogC3 and ACEScct HDR color spaces
  * [**w6a8 quantization**](https://github.com/Comfy-Org/ComfyUI/pull/16483): Added support for the w6a8 format
  * [**JsonExtractString**](https://github.com/Comfy-Org/ComfyUI/pull/16439): Parses JSON that is wrapped in a prefix or a suffix
  * [**Per-block attention**](https://github.com/Comfy-Org/ComfyUI/pull/16419): Model files can declare which attention implementation each block uses

  **Partner Node Updates**

  * [**Seedance 2.5 Draft mode**](https://github.com/Comfy-Org/ComfyUI/pull/16529): Renders a fast 480p preview whose `draft_task_id` drives the 1080p final render
  * [**Seedream 5.0 Flash**](https://github.com/Comfy-Org/ComfyUI/pull/16522): A faster, lower-cost model on the Seedream node, and the Pro max resolution now reaches 4.62MP
  * [**GPT-6 Sol and Luna**](https://github.com/Comfy-Org/ComfyUI/pull/16520): Two lower-cost GPT-6 tiers on the OpenAI Chat node
  * [**Sora nodes removed**](https://github.com/Comfy-Org/ComfyUI/pull/16609): The retired Sora video nodes are gone from ComfyUI

  **Performance & Stability**

  * [**Async weight offload on NPU**](https://github.com/Comfy-Org/ComfyUI/pull/16057): The async weight offload path now runs on Ascend NPU devices
  * [**ACE-Step 1.5**](https://github.com/Comfy-Org/ComfyUI/pull/16461): CUDA graphs and the memory compiler on the autoregressive model
  * [**Yue2 AR**](https://github.com/Comfy-Org/ComfyUI/pull/16626): Faster autoregressive generation for Yue2
  * [**SeedVR2**](https://github.com/Comfy-Org/ComfyUI/pull/16530): Optimized video upscaling
  * [**Fast disk detection**](https://github.com/Comfy-Org/ComfyUI/pull/16425): Extended to all model loaders
  * [**Asset scans**](https://github.com/Comfy-Org/ComfyUI/pull/16546): Asset scans and output rescans no longer block the UI on large libraries
  * [**Lumina models**](https://github.com/Comfy-Org/ComfyUI/pull/16515): Lower memory usage and `comfy_attention` support
  * [**torchaudio removed**](https://github.com/Comfy-Org/ComfyUI/pull/16457): Dropped the torchaudio dependency

  **Bug Fixes**

  * [**ImageUpscaleWithModel**](https://github.com/Comfy-Org/ComfyUI/pull/16500): No longer crashes on RGBA images, and transparency survives the upscale
  * [**Qwen VL preprocessing**](https://github.com/Comfy-Org/ComfyUI/pull/16548): Fixed a crash on 4-channel RGBA reference images
  * [**MiniMax-H3 VAE**](https://github.com/Comfy-Org/ComfyUI/pull/16485): Fixed an `rms_rope` crash on offloaded `qk_norm_scale`
  * [**HDR output**](https://github.com/Comfy-Org/ComfyUI/pull/16565): Fixed HDR output with negative values in Convert Image Color Space

  **Workflow Templates**

  * [**Templates v0.11.70**](https://github.com/Comfy-Org/ComfyUI/pull/16557): Updated the bundled workflow templates
</Update>

<Update label="v0.37.2" description="September 23, 2026">
  **Partner Node Updates**

  * [**Recraft V4.1 Flash**](https://github.com/Comfy-Org/ComfyUI/pull/16501): A faster, lower-cost option on the Recraft V4 text-to-image node
  * [**Claude Opus 5.5**](https://github.com/Comfy-Org/ComfyUI/pull/16479): Added to the Claude node
  * [**Quiver Arrow 2**](https://github.com/Comfy-Org/ComfyUI/pull/16478): Arrow 2 models with reasoning effort control on the SVG nodes

  **New Node Updates**

  * [**Generate Text**](https://github.com/Comfy-Org/ComfyUI/pull/16442): `system_prompt` replaces the chat template system turn, plus a thinking output
</Update>

<Update label="v0.37.1" description="September 22, 2026">
  **Partner Node Updates**

  * [**HY Image 3.5 Preview**](https://github.com/Comfy-Org/ComfyUI/pull/16462): Text-to-image and image edit with up to 5 reference images, native 2K output
</Update>

<Update label="v0.37.0" description="September 21, 2026">
  **New Open-Source Model Support**

  * [**Qwen-Image-2.1**](https://blog.comfy.org/p/qwen-image-21-in-comfyui-open-weight): Native 2K generation and editing with an alpha channel and multi-image references
  * [**MoGe 3**](https://github.com/Comfy-Org/ComfyUI/pull/16381): Fine-detail geometry estimation from a single image, with ViT-L and ViT-g checkpoints

  **New Node Updates**

  * [**YuE2 CFG**](https://github.com/Comfy-Org/ComfyUI/pull/16373): Added CFG control to the YuE2 Generate Music node
  * [**Empty Latent Image**](https://github.com/Comfy-Org/ComfyUI/pull/16384): Default width and height are now 1024

  **Partner Node Updates**

  * [**GPT Image 2**](https://github.com/Comfy-Org/ComfyUI/pull/16366): Added a transparent background option
  * [**Meshy 7.1**](https://github.com/Comfy-Org/ComfyUI/pull/16412): Added Meshy 7.1 on Meshy 3D nodes
  * [**Tripo P2 outputs**](https://github.com/Comfy-Org/ComfyUI/pull/16369): Refuse P2 runs that would write an empty GLB or FBX

  **Performance & Stability**

  * [**Auto fast-disk**](https://github.com/Comfy-Org/ComfyUI/pull/16333): Auto-enable `--fast-disk` on fast NVMe, plus Aimdo 0.5.5 and `--disable-fast-disk`
  * [**Qwen text encoders**](https://github.com/Comfy-Org/ComfyUI/pull/15623): CUDA graphs and W4A8 GEMV for Qwen3, 3.5, and 3.8
  * [**Dynamic VRAM text encoder**](https://github.com/Comfy-Org/ComfyUI/pull/16374): Keep the text encoder on GPU when dynamic VRAM is on
  * [**Wan VRAM**](https://github.com/Comfy-Org/ComfyUI/pull/16418): Lower peak VRAM with comfy-kitchen attention

  **Bug Fixes**

  * [**ACE-Step VAE**](https://github.com/Comfy-Org/ComfyUI/pull/16405): Fix VAE decode crashes on non-bf16 GPUs
  * [**MiniMax Music 3**](https://github.com/Comfy-Org/ComfyUI/pull/16428): Fix noisy output when CUDA graphs are enabled
</Update>

<Update label="v0.36.0" description="September 15, 2026">
  **New Open-Source Model Support**

  * [**FastVideo FastH3**](https://cloud.comfy.org/?template=video_fastvideo_fasth3_i2v): FastVideo 8-step distilled MiniMax H3 for text-to-video and image-to-video with native audio
  * [**Marigold V2**](https://github.com/Comfy-Org/ComfyUI/pull/16232): Depth, surface normal, and albedo estimation from a single image
  * [**YuE2**](https://github.com/Comfy-Org/ComfyUI/pull/16250): Music generation from style prompts and lyrics

  **New Node Updates**

  * [**Video Concatenate**](https://github.com/Comfy-Org/ComfyUI/pull/16267): Join multiple video clips end to end
  * [**Generic Loops**](https://github.com/Comfy-Org/ComfyUI/pull/16227): Loop over lists in the graph, carry heterogeneous items through every iteration, and declare loop boundaries in node schemas
  * [**Linear color space**](https://github.com/Comfy-Org/ComfyUI/pull/16247): Added linear to ImageColorSpace
  * [**Gemini V3 node**](https://github.com/Comfy-Org/ComfyUI/pull/16287): Added GeminiNodeV3 and deprecated the V2 node

  **Partner Node Updates**

  * [**Tripo P2**](https://github.com/Comfy-Org/ComfyUI/pull/16320): Text, image, and multiview to 3D model generation with the P2 model
  * [**Pruna P-Video-2**](https://github.com/Comfy-Org/ComfyUI/pull/16315): Text-to-video and image-to-video with 720p/1080p output and a draft mode
  * [**Flux Video Edit**](https://github.com/Comfy-Org/ComfyUI/pull/16259): Edit a source clip from a text instruction: remove or replace objects, restyle footage, change on-screen text or dialogue
  * [**Bria edit suite**](https://github.com/Comfy-Org/ComfyUI/pull/16264): New image edit nodes and the Video Eraser node

  **Performance & Stability**

  * [**Auto fast-disk**](https://github.com/Comfy-Org/ComfyUI/pull/16333): Auto-detect and enable `--fast-disk` when the disk is fast, plus Aimdo 0.5.5
  * [**MiniMax-H3 VAE**](https://github.com/Comfy-Org/ComfyUI/pull/16187): VAE optimizations and lower VAE memory usage
  * [**Llama rope kernels**](https://github.com/Comfy-Org/ComfyUI/pull/16326): Use comfy-kitchen apply rope in llama-based models, with fast kernels on more models
  * [**AMD Windows VA quota**](https://github.com/Comfy-Org/ComfyUI/pull/16199): Bumped the VA quota to 4TB
  * [**YuE2 on AMD**](https://github.com/Comfy-Org/ComfyUI/pull/16293): Fixed AMD issues and added more controls to the generate ABC node
  * [**YuE2 longer songs**](https://github.com/Comfy-Org/ComfyUI/pull/16292): Increased the max song duration to 900 seconds

  **Bug Fixes**

  * [**Add Noise alpha**](https://github.com/Comfy-Org/ComfyUI/pull/15626): No longer adds noise to the alpha channel
  * [**H3 Fun ControlNet**](https://github.com/Comfy-Org/ComfyUI/pull/16240): Fixed the H3 Fun ControlNet when the Comfy model compiler is active

  **Workflow Templates**

  * [**Templates v0.11.62**](https://github.com/Comfy-Org/ComfyUI/pull/16350): Added FastH3 video, Marigold V2 estimation, and YuE2 music templates, and updated the Tripo, Gemini, and Ideogram workflows
</Update>

<Update label="v0.35.2" description="September 14, 2026">
  **Partner Node Updates**

  * [**Bria edit suite**](https://github.com/Comfy-Org/ComfyUI/pull/16264): New image edit nodes and the Video Eraser node
  * [**Flux Video Edit**](https://github.com/Comfy-Org/ComfyUI/pull/16259): Edit a source clip from a text instruction: remove or replace objects, restyle footage, change on-screen text or dialogue
  * [**Gemini V3 node**](https://github.com/Comfy-Org/ComfyUI/pull/16287): Added GeminiNodeV3 and deprecated the V2 node
  * [**Partner progress estimates**](https://github.com/Comfy-Org/ComfyUI/pull/16152): Show remaining time from server duration estimates while partner jobs are queued and running

  **Bug Fixes**

  * [**H3 Fun ControlNet**](https://github.com/Comfy-Org/ComfyUI/pull/16240): Fixed the H3 Fun ControlNet when the Comfy model compiler is active

  **Workflow Templates**

  * [**Templates v0.11.60**](https://github.com/Comfy-Org/ComfyUI/pull/16319): Updated the bundled workflow templates
</Update>

<Update label="v0.35.1" description="September 10, 2026">
  **Partner Node Updates**

  * [**Tripo v3 API**](https://github.com/Comfy-Org/ComfyUI/pull/16201): Migrated Tripo nodes to the v3 API and added the Smart Segment node
  * [**Microsoft MAI Image 2.6**](https://github.com/Comfy-Org/ComfyUI/pull/16188): Added the mai-image-2.6 and mai-image-2.6-flash models to the OpenRouter Image node
  * [**MAI auto aspect ratio**](https://github.com/Comfy-Org/ComfyUI/pull/16229): Added an auto aspect ratio option to the MAI image node
  * [**Gemini 3.8 Flash**](https://github.com/Comfy-Org/ComfyUI/pull/16195): Added Gemini 3.8 Flash to the Gemini text node

  **Workflow Templates**

  * [**Templates v0.11.59**](https://github.com/Comfy-Org/ComfyUI/pull/16233): Updated the bundled workflow templates
</Update>

<Update label="v0.35.0" description="September 9, 2026">
  **New Open-Source Model Support**

  * [**Pixal3D Multi-View**](https://github.com/Comfy-Org/ComfyUI/pull/16048): Reconstruct textured meshes from front, back, left, and right views with Pixal3D Multi-View Conditioning
  * [**SenseNova U1.5**](https://github.com/Comfy-Org/ComfyUI/pull/15922): Native pixel-space generation and multi-reference editing with up to 10 reference images
  * [**MiniMax-H3 PDD LoRA**](https://github.com/Comfy-Org/ComfyUI/pull/15908): Load Parallel Decoding Distillation LoRAs for faster H3 sampling
  * [**MiniMax-H3 Fun Union**](https://github.com/Comfy-Org/ComfyUI/pull/16020): Use reference and keyframe conditioning together with Fun Union ControlNet
  * [**MiniMax-H3 text-encoder refs**](https://github.com/Comfy-Org/ComfyUI/pull/16065): Make VAE optional so references can condition the text encoder only
  * [**MiniMax-H3 & HiDream O1 LoRAs**](https://github.com/Comfy-Org/ComfyUI/pull/15662): Load DiffSynth-Studio and ModelScope-trained LoRAs that previously skipped every key

  **New Node Updates**

  * [**LTXV generated keyframes**](https://github.com/Comfy-Org/ComfyUI/pull/16040): Add, separate, and re-pin generated keyframes, plus Freeze Latent
  * [**LTXV Add Latent Guide**](https://github.com/Comfy-Org/ComfyUI/pull/16176): Pin a pre-encoded latent as a guide without a VAE round trip
  * [**Sparse Attention**](https://github.com/Comfy-Org/ComfyUI/pull/16072): Model Sparse Attention node for comfy-kitchen sparse backends
  * [**Color space conversion**](https://github.com/Comfy-Org/ComfyUI/pull/16135): Convert between sRGB, HDR HLG, and HDR PQ
  * [**File3DToMesh**](https://github.com/Comfy-Org/ComfyUI/pull/15919): Parse GLB, GLTF, OBJ, and STL files into the MESH pipeline
  * [**VideoTrim & VideoCrop**](https://github.com/Comfy-Org/ComfyUI/pull/15637): Trim and crop video with frontend VIDEO\_EDIT widgets
  * [**Save Image Advanced AVIF**](https://github.com/Comfy-Org/ComfyUI/pull/15891): Added AVIF output to Save Image Advanced
  * [**cfgpp\_ud10\_ab sampler**](https://github.com/Comfy-Org/ComfyUI/pull/15951): Added a CFG++ sampler that works well at lower steps on Anima
  * [**ResolutionSelector preview**](https://github.com/Comfy-Org/ComfyUI/pull/16013): Live width and height readout from aspect ratio and megapixel settings

  **Partner Node Updates**

  * [**GPT Image 2.5**](https://github.com/Comfy-Org/ComfyUI/pull/16190): Added Flare and Sunburst models to the OpenAI GPT Image node

  **Performance & Stability**

  * [**Comfy Compiler**](https://github.com/Comfy-Org/ComfyUI/pull/15861): Aimdo memory compiler plus CUDA graphs to cut allocation thrash
  * [**TRELLIS memory**](https://github.com/Comfy-Org/ComfyUI/pull/16054): Lowered peak VRAM and RAM in TRELLIS workflows
  * [**Container cgroup RAM**](https://github.com/Comfy-Org/ComfyUI/pull/15927): Respect container memory limits instead of host RAM
  * [**RDNA3.5 attention**](https://github.com/Comfy-Org/ComfyUI/pull/16014): Enable PyTorch SDPA and FP8 ops on gfx1170 and gfx1171

  **Bug Fixes**

  * [**MiniMax H3 denoise masks**](https://github.com/Comfy-Org/ComfyUI/pull/15988): Scale video and audio velocities by denoise masks before x0 conversion
  * [**SAM 3 text masks**](https://github.com/Comfy-Org/ComfyUI/pull/15979): Fix empty text-prompt masks when scalp=1 sent four FPN levels
  * [**Image alpha**](https://github.com/Comfy-Org/ComfyUI/pull/15632): Preserve alpha on RGB/YUV, Canny, quantize, overlay, blend, invert, and color-adjust nodes
  * [**Switch inputs**](https://github.com/Comfy-Org/ComfyUI/pull/16083): Allow disconnected Switch inputs
  * [**MPS int8**](https://github.com/Comfy-Org/ComfyUI/pull/16130): Disable int8 weight-only quantization when `torch._int_mm` is missing
</Update>

<Update label="v0.34.6" description="September 7, 2026">
  **Partner Node Updates**

  * [**GPT-6 Astra**](https://github.com/Comfy-Org/ComfyUI/pull/16125): Added GPT-6 Astra and reasoning effort levels on supported OpenAI Chat models
  * [**Retired partner models**](https://github.com/Comfy-Org/ComfyUI/pull/16121): Removed DALL·E 2/3, Kling Video Extend, LTX-2 partner video nodes, ByteDance Image (Seedream 3), and Seedance 1.0 Lite options
</Update>

<Update label="v0.34.5" description="September 5, 2026">
  **Partner Node Updates**

  * [**Comfy Cloud**](https://github.com/Comfy-Org/ComfyUI/pull/15935): Added beta nodes that run curated Flux 2, Z-Image Turbo, Mage Flow, MiniMax H3, and Music 3 workflows on Comfy Cloud GPUs
</Update>

<Update label="v0.34.4" description="September 4, 2026">
  **Partner Node Updates**

  * [**Meta Muse Image**](https://github.com/Comfy-Org/ComfyUI/pull/16078): Added Muse Image 1.0 text-to-image and edit nodes with up to 10 reference images
  * [**Recraft V4 Styles Pro**](https://github.com/Comfy-Org/ComfyUI/pull/16043): Added `recraftv4_styles_pro` and `recraftv4_styles_pro_vector` to the Create Style node
  * [**MiniMax H3 Max Turbo**](https://github.com/Comfy-Org/ComfyUI/pull/16094): Added the H3 Max Turbo model option to MiniMax H3 text-to-video and first-last-frame nodes
  * [**Claude Fable 5.1**](https://github.com/Comfy-Org/ComfyUI/pull/16085): Added Claude Fable 5.1 and xhigh/max reasoning levels on supported Claude models
  * [**Tripo**](https://github.com/Comfy-Org/ComfyUI/pull/16060): Fixed real FBX/GLB outputs, exact pricing, and missing parameters on Tripo nodes
</Update>

<Update label="v0.34.3" description="September 2, 2026">
  **Partner Node Updates**

  * [**MiniMax H3 Max**](https://github.com/Comfy-Org/ComfyUI/pull/16025): Added the H3 Max model option to MiniMax H3 text-to-video, first-last-frame, and reference nodes

  **Performance & Stability**

  * [**TRELLIS remesh memory**](https://github.com/Comfy-Org/ComfyUI/pull/16034): Lowered remesh memory usage in TRELLIS workflows

  **Bug Fixes**

  * [**3D preview paths**](https://github.com/Comfy-Org/ComfyUI/pull/16038): Annotate temp paths on Preview3DAdvanced, PreviewGaussianSplat, and PreviewPointCloud so Cloud previews resolve
</Update>

<Update label="v0.34.2" description="August 27, 2026">
  **Partner Node Updates**

  * [**Gemini Omni 1.1 Flash**](https://links.comfy.org/3UjQmgE): Faster video generation and conversational editing, with 4K output and video extend

  **Bug Fixes**

  * [**HEVC remux**](https://github.com/Comfy-Org/ComfyUI/pull/15809): Remux HEVC into mp4/mov as hvc1 so Apple players can play the files
</Update>

<Update label="v0.34.1" description="August 26, 2026">
  **Partner Node Updates**

  * [**WAN3-Prime**](https://github.com/Comfy-Org/ComfyUI/pull/15894): Added the Wan 3.0 Prime model option with higher per-second rates
  * [**Recraft V4 Styles**](https://github.com/Comfy-Org/ComfyUI/pull/15903): Added the Recraft V4 Create Style node and `recraftv4_styles` models that require a style ID or reference images
  * [**Google Veo**](https://github.com/Comfy-Org/ComfyUI/pull/15883): Removed the retiring Veo 2 and Veo 3.0 models from the Veo nodes
</Update>

<Update label="v0.34.0" description="August 26, 2026">
  **New Open-Source Model Support**

  * [**Pixal3D & TRELLIS2**](https://github.com/Comfy-Org/ComfyUI/pull/14718): 3D mesh and texture generation with remesh, decimate, UV unwrap, and texture bake post-processing
  * [**SAM 3D Body**](https://github.com/Comfy-Org/ComfyUI/pull/14370): Dependency-free 3D body detection and segmentation with pose rendering and animation export
  * [**TAESD H3**](https://github.com/Comfy-Org/ComfyUI/pull/15695): Lightweight VAE decoder for faster previews

  **New Node Updates**

  * [**MiniMax-H3 prompt embeddings**](https://github.com/Comfy-Org/ComfyUI/pull/15697): Load MiniMax-H3 embeddings with the `embedding:` syntax in prompts
  * [**CreateVideo colorspace**](https://github.com/Comfy-Org/ComfyUI/pull/15810): Added colorspace option and bit depth as a combo

  **Partner Node Updates**

  * [**PixVerse V6**](https://github.com/Comfy-Org/ComfyUI/pull/15880): Added V6 text-to-video, image-to-video, first-last-frame, extend, and fusion nodes with native audio
  * [**Tripo**](https://github.com/Comfy-Org/ComfyUI/pull/15851): Removed the retired Refine Draft model node and the v2.0 model version

  **Performance & Stability**

  * [**HDR video saving**](https://github.com/Comfy-Org/ComfyUI/pull/15741): Added HDR video saving with AV1 codec and mkv/webm container support

  **Bug Fixes**

  * [**Database path**](https://github.com/Comfy-Org/ComfyUI/pull/14539): Fixed the default SQLite database path to resolve from the user directory instead of the install directory
</Update>

<Update label="v0.33.4" description="August 24, 2026">
  **Partner Node Updates**

  * [**Wan 3.0**](https://github.com/Comfy-Org/ComfyUI/pull/15843): Added Wan 3.0 text, image, and reference to video with native audio, up to 30 seconds
  * [**Meshy-7**](https://github.com/Comfy-Org/ComfyUI/pull/15807): Added meshy-7 and ultra mode to Meshy text, image, and multi-image to 3D nodes
  * [**ByteDance vCube Video Enhance**](https://github.com/Comfy-Org/ComfyUI/pull/15755): Upscale and restore video up to 8K, with optional frame interpolation
  * [**Kling v2**](https://github.com/Comfy-Org/ComfyUI/pull/15676): Removed kling-v2 from Kling Image Generation ahead of September 15 retirement
</Update>

<Update label="v0.33.3" description="August 20, 2026">
  **Partner Node Updates**

  * [**Flux Video Upscale**](https://github.com/Comfy-Org/ComfyUI/pull/15753): Upscale video 1.5x to 3x with FLUX super-resolution
  * [**ByteDance Seedream Fast Mode**](https://github.com/Comfy-Org/ComfyUI/pull/15750): Fast prompt-optimization mode for Seedream 5.0 Pro image-to-image
  * [**Gemini 3.7 Flash**](https://github.com/Comfy-Org/ComfyUI/pull/15688): Added Gemini 3.7 Flash to the Gemini text node
  * [**Ideogram & Pruna P-Image**](https://github.com/Comfy-Org/ComfyUI/pull/15751): Renamed Ideogram P-Image to credit Pruna
</Update>

<Update label="v0.33.2" description="August 17, 2026">
  **Partner Node Updates**

  * [**Fish Audio**](https://github.com/Comfy-Org/ComfyUI/pull/15612): Added text-to-speech, speech-to-text, voice selector, and instant voice clone nodes
  * [**ByteDance Seedance 2.5 1080p**](https://github.com/Comfy-Org/ComfyUI/pull/15684): Added 1080p resolution to Seedance 2.5
  * [**ByteDance Seedance 2.5 Extend**](https://github.com/Comfy-Org/ComfyUI/pull/15579): Added extend task type for video continuation

  **Frontend Updates**

  * [**Frontend**](https://github.com/Comfy-Org/ComfyUI/pull/15526): Bumped comfyui-frontend-package to 1.49.6
</Update>

<Update label="v0.33.1" description="August 13, 2026">
  **New Open-Source Model Support**

  * [**MiniMax Music 3**](https://links.comfy.org/4zmDV3G): Native text-to-music support for songs up to 5 minutes from caption and lyrics
  * [**Anima tunes**](https://github.com/Comfy-Org/ComfyUI/pull/15555): Support Anima tunes checkpoints with extra blocks

  **Partner Node Updates**

  * [**MiniMax H3 Context IR & Regenerate**](https://github.com/Comfy-Org/ComfyUI/pull/15471): Added Context IR prompt enhancer and Regenerate to 2K nodes
  * [**Bria GenFill, Eraser, Expand & Upscale**](https://github.com/Comfy-Org/ComfyUI/pull/15572): Added Generative Fill, Eraser, Expand Image, and Increase Resolution nodes

  **New Nodes**

  * [**MiniMax Music3 Text Encode**](https://github.com/Comfy-Org/ComfyUI/pull/15570): Caption and lyrics text encoding for MiniMax Music 3
  * [**Empty MiniMax Music3 Latent Audio**](https://github.com/Comfy-Org/ComfyUI/pull/15570): Empty audio latent for a requested duration

  **Performance & Stability**

  * [**CUDA Graphs**](https://github.com/Comfy-Org/ComfyUI/pull/15570): Native CUDA graph support interoperable with dynamic VRAM
  * [**WSL dynamic VRAM**](https://github.com/Comfy-Org/ComfyUI/pull/15562): Keep dynamic VRAM enabled on WSL
  * [**aotriton detection**](https://github.com/Comfy-Org/ComfyUI/pull/15412): Query PyTorch for aotriton support instead of scanning its lib directory
  * [**MiniMax Music VRAM**](https://github.com/Comfy-Org/ComfyUI/pull/15588): Fixed MiniMax Music on non-dynamic VRAM
  * [**MiniMax QKV detect**](https://github.com/Comfy-Org/ComfyUI/pull/15581): Early detect fused qkv vs separate q,k,v weights

  **Bug Fixes**

  * [**KSamplerAdvanced**](https://github.com/Comfy-Org/ComfyUI/pull/15447): Fixed `add_noise` disabled on nested latents
  * [**PreviewAny**](https://github.com/Comfy-Org/ComfyUI/pull/15513): Fixed non-ASCII escaping in dict and list previews
  * [**LTX decoder**](https://github.com/Comfy-Org/ComfyUI/pull/15516): Fixed float64 device in LTX diffusion decoder
  * [**Generate Text**](https://github.com/Comfy-Org/ComfyUI/pull/15278): Fixed `thinking=false` ignored on Gemma4 E2B/E4B
  * [**Llama path**](https://github.com/Comfy-Org/ComfyUI/pull/15580): Fixed non-local activation path between Llama blocks
</Update>

<Update label="v0.32.0" description="August 11, 2026">
  **New Open-Source Model Support**

  * [**LTX 2.5**](https://links.comfy.org/docLTX2_5): Native LTX 2.5 support with STG, dual CFG, and duration prediction

  **Partner Node Updates**

  * [**Qwen Image 3.0**](https://github.com/Comfy-Org/ComfyUI/pull/15327): Added Qwen-Image 3.0 and 3.0 Pro text-to-image and edit nodes
  * [**LTX 2.5**](https://github.com/Comfy-Org/ComfyUI/pull/15501): Added LTX 2.5 Text/Image/Audio to Video partner nodes
  * [**Grok Imagine Image 2.0**](https://github.com/Comfy-Org/ComfyUI/pull/15496): Added grok-imagine-image-2.0 model support

  **New Nodes**

  * [**LTXV Spatio-Temporal Guidance**](https://github.com/Comfy-Org/ComfyUI/pull/15499): STG guidance for LTX video generation
  * [**LTXV Modality Guidance**](https://github.com/Comfy-Org/ComfyUI/pull/15499): Audio/video coupling guidance for LTX
  * [**LTXV Dual CFG Guider**](https://github.com/Comfy-Org/ComfyUI/pull/15499): Dual-CFG guider for LTX workflows
  * [**LTXV Duration Predictor**](https://github.com/Comfy-Org/ComfyUI/pull/15499): Predict natural shot duration from caption tokens

  **Performance & Stability**

  * [**PyTorch 2.7**](https://github.com/Comfy-Org/ComfyUI/pull/15413): Minimum officially supported PyTorch is now 2.7
  * [**MiniMax-H3 VAE**](https://github.com/Comfy-Org/ComfyUI/pull/15446): Optimized MiniMax-H3 VAE
  * [**Comfy kitchen attention**](https://github.com/Comfy-Org/ComfyUI/pull/15479): Implemented comfy kitchen attention
  * [**MiniMax-H3 memory**](https://github.com/Comfy-Org/ComfyUI/pull/15486): Fixed peak memory issue with MiniMax-H3
  * [**ER-SDE scaler**](https://github.com/Comfy-Org/ComfyUI/pull/15428): Extended ER-SDE noise scaler by scaling h(t)
  * [**Tokenizers**](https://github.com/Comfy-Org/ComfyUI/pull/15503): Mistral and Llama tokenizers no longer depend on transformers

  **Bug Fixes**

  * [**Upscale models**](https://github.com/Comfy-Org/ComfyUI/pull/15437): Fixed upscale models breaking on non-dynamic low VRAM
  * [**VAEDecodeTiled**](https://github.com/Comfy-Org/ComfyUI/pull/15477): Fixed crash on NestedTensor latents (MiniMax H3)
  * [**Tiled audio decode**](https://github.com/Comfy-Org/ComfyUI/pull/15502): Fixed broken tiled audio decode
  * [**CLIP Vision**](https://github.com/Comfy-Org/ComfyUI/pull/15506): Fixed CLIP Vision regression
  * [**Create Layered Image**](https://github.com/Comfy-Org/ComfyUI/pull/15429): Made Create Layered Image discoverable with clearer flags
</Update>

<Update label="v0.31.0" description="August 7, 2026">
  **New Open-Source Model Support**

  * [**Wan-Animate2**](https://github.com/Comfy-Org/ComfyUI/pull/15362): Native Wan-Animate2 with pose/reference controls and optional pose-branch cache (CORE-358)

  **Partner Node Updates**

  * [**ByteDance SeeDance 2.5**](https://links.comfy.org/4gkNSa4): Added SeeDance 2.5 model support
  * [**Seedream 5.0 Layer Separation**](https://github.com/Comfy-Org/ComfyUI/pull/15317): ByteDance Seedream 5.0 Pro Layer Separation Support
  * [**Reve deprecated**](https://github.com/Comfy-Org/ComfyUI/pull/15331): Deprecated Reve partner nodes

  **New Nodes**

  * [**Create Layered Image**](https://github.com/Comfy-Org/ComfyUI/pull/15317): PSD-style layer compositing with blend modes and layer state
  * [**Add Layer**](https://github.com/Comfy-Org/ComfyUI/pull/15317): Add a layer into a compositor layer stack
  * [**Layers From Bounding Boxes**](https://github.com/Comfy-Org/ComfyUI/pull/15317): Build compositor layers from bounding boxes
  * [**WanAnimate2ToVideo**](https://github.com/Comfy-Org/ComfyUI/pull/15362): Wan-Animate2 conditioning with pose/reference controls
  * [**WanAnimate2Cache**](https://github.com/Comfy-Org/ComfyUI/pull/15362): Optional pose-branch cache to speed up Wan-Animate2

  **Frontend Updates**

  * [**Frontend**](https://github.com/Comfy-Org/ComfyUI/pull/15403): Bumped comfyui-frontend-package to 1.48.7
  * [**Image compositor editor**](https://github.com/Comfy-Org/ComfyUI_frontend/pull/14901): PSD-style layer editor for ImageCompositor
  * [**3D Viewer**](https://github.com/Comfy-Org/ComfyUI_frontend/pull/14076): Enabled 3D Viewer (Beta) by default
  * [**Save 3D Advanced**](https://github.com/Comfy-Org/ComfyUI_frontend/pull/13330): Wired up Save 3D (Advanced) node family (CORE-329)
  * [**HF gated models**](https://github.com/Comfy-Org/ComfyUI_frontend/pull/14338): Gated Hugging Face model access hints

  **Performance & Stability**

  * [**LTX and Wan**](https://github.com/Comfy-Org/ComfyUI/pull/15138): Speedups for LTX and Wan
  * [**asym w4a8\_int**](https://github.com/Comfy-Org/ComfyUI/pull/15308): Asymmetric w4a8\_int quantization support
  * [**int8\_convrot VAE**](https://github.com/Comfy-Org/ComfyUI/pull/15334): int8\_convrot VAE for MiniMax-H3
  * [**Linux memory pinning**](https://github.com/Comfy-Org/ComfyUI/pull/15266): Avoid over-pinning memory on Linux with no swap

  **Bug Fixes**

  * [**MiniMax H3 audio**](https://github.com/Comfy-Org/ComfyUI/pull/15390): Fixed MiniMax H3 audio corruption with EasyCache
  * [**MiniMax samplers**](https://github.com/Comfy-Org/ComfyUI/pull/15243): Fixed MiniMax audio sampler issues and expanded sampler support
  * [**MiniMax audio VAE offload**](https://github.com/Comfy-Org/ComfyUI/pull/15377): Fixed full offload on MiniMax audio VAE
  * [**MiniMax H3 mask**](https://github.com/Comfy-Org/ComfyUI/pull/15322): Fixed MiniMax H3 latent noise mask sampling
  * [**res\_multistep**](https://github.com/Comfy-Org/ComfyUI/pull/15339): Skip creating useless noise in res\_multistep sampler
</Update>

<Update label="v0.30.2" description="August 5, 2026">
  **Partner Node Updates**

  * [**BFL Flux 3 Video**](https://links.comfy.org/3TVdf9N): Added Flux 3 video model support
  * [**TopazAI Bloom 2 & Wonder 3.5**](https://github.com/Comfy-Org/ComfyUI/pull/15294): Added Bloom 2 and Wonder 3.5 model support
  * [**Kling EOL**](https://github.com/Comfy-Org/ComfyUI/pull/15249): Removed retired legacy Kling models and Virtual Try-On API
</Update>

<Update label="v0.30.1" description="August 3, 2026">
  **Performance & Stability**

  * [**Frontend**](https://github.com/Comfy-Org/ComfyUI/pull/15244): Bumped comfyui-frontend-package to 1.47.12
</Update>

<Update label="v0.30.0" description="August 3, 2026">
  **New Open-Source Model Support**

  * [**MiniMax-H3**](https://links.comfy.org/3TuT9TO): MiniMax-H3 audio-video model support (CORE-375)
  * [**Pruna LTX VAE**](https://github.com/Comfy-Org/ComfyUI/pull/15129): PrunaVAED support for faster LTX 2.3 decoding

  **New Nodes**

  * [**Save Video CRF**](https://github.com/Comfy-Org/ComfyUI/pull/15191): Added CRF option to Save Video node
  * [**SaveText CSV**](https://github.com/Comfy-Org/ComfyUI/pull/15217): SaveText node can save `.csv` output
  * [**VAEDecodeAudio**](https://github.com/Comfy-Org/ComfyUI/pull/15211): VAEDecodeAudio can decode nested audio latents

  **Partner Node Updates**

  * [**xAI Grok Imagine Video 1.5**](https://github.com/Comfy-Org/ComfyUI/pull/15197): Updated xAI nodes for grok-imagine-video-1.5
  * [**MiniMax H3 768P**](https://github.com/Comfy-Org/ComfyUI/pull/15227): Added 768P resolution for MiniMax H3 partner nodes

  **Performance & Stability**

  * [**int8 embedding lookup**](https://github.com/Comfy-Org/ComfyUI/pull/15035): int8 convrot embedding lookup for text generation models (CORE-371)
  * [**Weight pinning**](https://github.com/Comfy-Org/ComfyUI/pull/15027): Load weights to process RAM with MRU pinning infrastructure
  * [**Comfy Kitchen AMD**](https://github.com/Comfy-Org/ComfyUI/pull/15160): Comfy Kitchen AMD support
  * [**Dataset folder**](https://github.com/Comfy-Org/ComfyUI/pull/14807): Dataset folder path to avoid arbitrary directory access
  * [**DETAIL logging**](https://github.com/Comfy-Org/ComfyUI/pull/15064): Configurable DETAIL logging side channel (CORE-369)
  * [**GQA attention**](https://github.com/Comfy-Org/ComfyUI/pull/15190): Expand k/v when attention would fall back to math for GQA
  * [**Nested latent previews**](https://github.com/Comfy-Org/ComfyUI/pull/15196): Latent previews for nested latents (e.g. LTXAV)
  * [**MP4 metadata**](https://github.com/Comfy-Org/ComfyUI/pull/15195): Store MP4 metadata at the beginning of the file when possible
  * [**Frontend**](https://github.com/Comfy-Org/ComfyUI/pull/15161): Bumped comfyui-frontend-package to 1.47.11

  **Bug Fixes**

  * [**LTXAV**](https://github.com/Comfy-Org/ComfyUI/pull/15132): Fixed crash when sampling without an audio latent
  * [**Jobs preview**](https://github.com/Comfy-Org/ComfyUI/pull/14681): Prefer media over text for job `preview_output`
  * [**cuDNN attention**](https://github.com/Comfy-Org/ComfyUI/pull/15146): Fallback to cuDNN attention on Linux when Flash Attention fails
  * [**CurveEditor**](https://github.com/Comfy-Org/ComfyUI/pull/15152): Resend cached histogram UI for CurveEditor after page refresh
  * [**ByteDance stereo audio**](https://github.com/Comfy-Org/ComfyUI/pull/15177): Encode stereo reference audio without doubling duration
</Update>

<Update label="v0.29.2" description="July 31, 2026">
  **Partner Node Updates**

  * [**Ideogram P-Image**](https://github.com/Comfy-Org/ComfyUI/pull/15154): Added Ideogram P-Image model support
  * [**MiniMax H3**](https://github.com/Comfy-Org/ComfyUI/pull/15167): Added MiniMax H3 model support
</Update>

<Update label="v0.29.1" description="July 31, 2026">
  **Bug Fixes**

  * [**user.css**](https://github.com/Comfy-Org/ComfyUI/pull/15000): Fixed `user.css` loading broken by a prior frontend change
  * [**SVG previews**](https://github.com/Comfy-Org/ComfyUI/pull/15149): Fixed SVG node output and Media Assets previews after stored-XSS download hardening
</Update>

<Update label="v0.29.0" description="July 29, 2026">
  **New Open-Source Model Support**

  * [**JoyImageEdit**](https://github.com/Comfy-Org/ComfyUI/pull/14428): Native JoyImageEdit model support
  * [**Gemma4 12B**](https://github.com/Comfy-Org/ComfyUI/pull/14304): Gemma4 12B model support (CORE-277)
  * [**MageFlow**](https://github.com/Comfy-Org/ComfyUI/pull/15026): MageFlow model support (CORE-372)
  * [**Uni3C ControlNet**](https://github.com/Comfy-Org/ComfyUI/pull/14946): Native Uni3C ControlNet support for Wan models (CORE-365)
  * [**Anima**](https://github.com/Comfy-Org/ComfyUI/pull/14954): Anima llite control model support

  **New Nodes**

  * [**Trainer video processing**](https://github.com/Comfy-Org/ComfyUI/pull/13588): Video processing nodes, Image Processing Node video support, and trainer video support (CORE-81)

  **Partner Node Updates**

  * [**Recraft V4.1**](https://github.com/Comfy-Org/ComfyUI/pull/15105): Recraft V4.1 models and V4 image edit nodes
  * [**ByteDance audio multilingual**](https://github.com/Comfy-Org/ComfyUI/pull/15034): ByteDance audio-1.0-multilingual model
  * [**OpenRouter**](https://github.com/Comfy-Org/ComfyUI/pull/15021): New OpenRouter models, including [Claude Opus 5](https://github.com/Comfy-Org/ComfyUI/pull/15075)
  * [**Anthropic**](https://github.com/Comfy-Org/ComfyUI/pull/15023): New Anthropic models, including [Claude Opus 5](https://github.com/Comfy-Org/ComfyUI/pull/15079)
  * [**Runway Gen3a deprecated**](https://github.com/Comfy-Org/ComfyUI/pull/15050): Deprecated Runway Gen3a model

  **Performance & Stability**

  * [**Video transcode**](https://github.com/Comfy-Org/ComfyUI/pull/14813): Stream video transcode instead of buffering every frame in RAM (CORE-353, CORE-351)
  * [**Anima**](https://github.com/Comfy-Org/ComfyUI/pull/14953): Faster Anima inference
  * [**Comfy Kitchen**](https://github.com/Comfy-Org/ComfyUI/pull/14963): Comfy Kitchen optimizations and fixes, plus [more int8 optimizations](https://github.com/Comfy-Org/ComfyUI/pull/14980)
  * [**Krea 2 reference images**](https://github.com/Comfy-Org/ComfyUI/pull/14843): Regular and timestep-zero reference images for Krea 2 Ostris and identity edit ref LoRAs
  * [**FreSca**](https://github.com/Comfy-Org/ComfyUI/pull/15007): FreSca 5D+ (e.g. Anima) fix and model-agnostic iteration
  * [**Latent upscaler**](https://github.com/Comfy-Org/ComfyUI/pull/15063): Converted `latent_upsampler` model to ModelPatcherDynamic
  * [**Background usage clamp**](https://github.com/Comfy-Org/ComfyUI/pull/15068): Default background usage clamp raised to 128GB
  * [**gfx1035**](https://github.com/Comfy-Org/ComfyUI/pull/15009): Fixed gfx1035 not being treated like RDNA2
  * [**Frontend**](https://github.com/Comfy-Org/ComfyUI/pull/15045): Bumped comfyui-frontend-package to 1.47.10

  **Bug Fixes**

  * [**Wan dancer batches**](https://github.com/Comfy-Org/ComfyUI/pull/14999): Fixed Wan dancer issue with batches
  * [**Gemini Video Omni**](https://github.com/Comfy-Org/ComfyUI/pull/15014): Pass videos as inline data in Gemini Omni partner node
  * [**MageFlow bf16**](https://github.com/Comfy-Org/ComfyUI/pull/15081): Fixed MageFlow on cards that don't support bf16
  * [**LTXV IC-LoRA**](https://github.com/Comfy-Org/ComfyUI/pull/15073): Improved LTXV IC-LoRA detection
  * [**LTXVEmptyLatentAudio**](https://github.com/Comfy-Org/ComfyUI/pull/15106): Allow float fps for LTXVEmptyLatentAudio
</Update>

<Update label="v0.28.3" description="July 22, 2026">
  **Partner Node Updates**

  * [**Gemini Video Omni**](https://github.com/Comfy-Org/ComfyUI/pull/15014): Pass videos as inline data in Gemini Omni partner node
  * [**OpenRouter**](https://github.com/Comfy-Org/ComfyUI/pull/15021): New OpenRouter models
  * [**Anthropic**](https://github.com/Comfy-Org/ComfyUI/pull/15023): New Anthropic models
</Update>

<Update label="v0.28.2" description="July 18, 2026">
  **Partner Node Updates**

  * [**Gemini Video Omni**](https://github.com/Comfy-Org/ComfyUI/pull/14984): Switched Omni model to the Interactions API
</Update>

<Update label="v0.28.1" description="July 17, 2026">
  **Partner Node Updates**

  * [**GPT-5.6**](https://github.com/Comfy-Org/ComfyUI/pull/14957): Added GPT-5.6 Sol, Terra, and Luna models
  * [**Gemini 3.5 Flash**](https://github.com/Comfy-Org/ComfyUI/pull/14972): Added Gemini 3.5 Flash to the Gemini LLM node
  * [**HeyGen**](https://github.com/Comfy-Org/ComfyUI/pull/14958): Avatar Video, Talking Photo, Create Avatar, Video Translate, and Text to Speech nodes
</Update>

<Update label="v0.28.0" description="July 15, 2026">
  **New Open-Source Model Support**

  * [**SeedVR2**](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_seedvr2_3b_int8_upscale_image.json): Native SeedVR2 image and video upscaling ([#14424](https://github.com/Comfy-Org/ComfyUI/pull/14424))
  * [**PID 1.5**](https://github.com/Comfy-Org/ComfyUI/pull/14894): PixelDiT PID 1.5 model support
  * [**int4 Models**](https://github.com/Comfy-Org/ComfyUI/pull/14859): convrot int4 support, plus [Turing int8/int4 optimizations](https://github.com/Comfy-Org/ComfyUI/pull/14927)

  **New Nodes**

  * [**Save 3D (Advanced)**](https://github.com/Comfy-Org/ComfyUI/pull/14701): Save 3D (Advanced), Save Splat, and Save Point Cloud nodes
  * [**SaveText**](https://github.com/Comfy-Org/ComfyUI/pull/14102): Save text outputs to `.txt`, `.md`, or `.json`
  * [**Text Overlay**](https://github.com/Comfy-Org/ComfyUI/pull/14610): Text overlay for images and video
  * [**Text**](https://github.com/Comfy-Org/ComfyUI/pull/14870): Restored the core Text node
  * [**Create Bounding Boxes**](https://github.com/Comfy-Org/ComfyUI/pull/14724): Added `bboxes` input for upstream wiring

  **Partner Node Updates**

  * [**sync.so sync-3**](https://github.com/Comfy-Org/ComfyUI/pull/14928): sync.so sync-3 lip-sync and talking-image support
  * [**Seedream thinking control**](https://github.com/Comfy-Org/ComfyUI/pull/14853): Option to disable thinking on Seedream nodes
  * [**Gemini Image**](https://github.com/Comfy-Org/ComfyUI/pull/14917): Gemini Image preview models moved to release versions

  **Performance & Stability**

  * [**`--models-directory`**](https://github.com/Comfy-Org/ComfyUI/pull/9113): Launch argument for a default models directory
  * [**GQA attention**](https://github.com/Comfy-Org/ComfyUI/pull/14772): GQA on all attention backends; dropped PyTorch 2.4
  * [**int8 on 16xx**](https://github.com/Comfy-Org/ComfyUI/pull/14941): Fixed int8 regression on GTX 16xx
  * [**ROCm / AMD Triton**](https://github.com/Comfy-Org/ComfyUI/pull/14869): Triton auto-enable limited to matrix-core GPUs
  * [**Frontend**](https://github.com/Comfy-Org/ComfyUI/pull/14944): Bumped comfyui-frontend-package to 1.45.21

  **Bug Fixes**

  * [**Cached job outputs**](https://github.com/Comfy-Org/ComfyUI/pull/14939): Fixed missing cached outputs when the prompt has no `client_id`
  * [**3D Advanced (API mode)**](https://github.com/Comfy-Org/ComfyUI/pull/14930): Fixed Advanced 3D nodes crashing with no UI
  * [**int4 Turing**](https://github.com/Comfy-Org/ComfyUI/pull/14864): Fixed black images on Turing with int4 models
  * [**Qwen3-VL**](https://github.com/Comfy-Org/ComfyUI/pull/14845): Fixed reference images used as text encode models
  * [**Save Image (Advanced)**](https://github.com/Comfy-Org/ComfyUI/pull/14761): Support for single-channel images
  * [**HiDream O1**](https://github.com/Comfy-Org/ComfyUI/pull/14923): Fixed HiDream O1 regression
</Update>

<Update label="v0.27.1" description="July 8, 2026">
  **Partner Node Updates**

  * [**Seedream 5 Pro**](https://links.comfy.org/3R12fXw): ByteDance Seedream 5 Pro image generation model support
  * [**Seed Audio 1.0**](https://github.com/Comfy-Org/ComfyUI/pull/14731): ByteDance Seed Audio 1.0 for speech, music, sound effects, and multi-speaker dialogue
  * [**Ideogram V1/V2 deprecated**](https://github.com/Comfy-Org/ComfyUI/pull/14712): Deprecated legacy Ideogram V1 and V2 partner nodes
  * [**StabilityAI temporarily removed**](https://github.com/Comfy-Org/ComfyUI/pull/14737): StabilityAI partner nodes temporarily removed

  **Bug Fixes**

  * [**Video decode**](https://github.com/Comfy-Org/ComfyUI/pull/14746): Fixed crash on videos with undecodable audio streams
</Update>

<Update label="v0.27.0" description="June 30, 2026">
  **int8 Model Support**
  This release adds support for **int8 convrot models**, bringing significant performance improvements for quantized models. int8 support now works on Turing GPUs and newer, with optimized LoRA applying and memory management.

  **New Nodes**

  * [**Seed Node**](https://github.com/Comfy-Org/ComfyUI/pull/14616): New Seed node for managing seed values in your workflows (CORE-295)
  * [**Advanced Krea 2 Model Merging**](https://github.com/Comfy-Org/ComfyUI/pull/14621): Advanced node for merging Krea 2 models
  * [**Bounding Box Canvas**](https://github.com/Comfy-Org/ComfyUI/pull/14537): Bounding box canvas node and Ideogram JSON prompt support (CORE-292)
  * [**ConditioningMultiply**](https://github.com/Comfy-Org/ComfyUI/pull/14686): New conditioning node for multiplying conditioning values
  * [**GLSL Update**](https://github.com/Comfy-Org/ComfyUI/pull/13195): GLSL node updated to use ANGLE library (CORE-162)

  **Partner Node Updates**

  * [**Nano Banana 2 Lite**](https://github.com/Comfy-Org/ComfyUI/pull/14693): Added support for Google's Nano Banana 2 Lite model
  * [**Gemini Video Omni**](https://github.com/Comfy-Org/ComfyUI/pull/14695): Added new Gemini Video Omni node for video generation

  **Performance & Stability**

  * [**int8 Models**](https://github.com/Comfy-Org/ComfyUI/pull/14636): Added support for int8 convrot models with faster inference
  * [**Faster int8**](https://github.com/Comfy-Org/ComfyUI/pull/14641): Optimized int8 kernel performance
  * [**Turing GPU Support**](https://github.com/Comfy-Org/ComfyUI/pull/14662): int8 support extended to Turing architecture GPUs
  * [**Better int8 LoRA**](https://github.com/Comfy-Org/ComfyUI/pull/14685): Improved int8 LoRA applying with better quality and speed
  * [**Memory Leak Fix**](https://github.com/Comfy-Org/ComfyUI/pull/14697): Fixed memory leak related to int8 operations
  * [**Asset Hashing Opt-In**](https://github.com/Comfy-Org/ComfyUI/pull/14663): Asset hashing made opt-in via `--enable-asset-hashing` flag (off by default)

  **Bug Fixes**

  * [**int8 LoRA requant**](https://github.com/Comfy-Org/ComfyUI/pull/14650): Fixed lower quality requant when using wrong settings with int8 LoRAs
  * [**int8 mm offloaded**](https://github.com/Comfy-Org/ComfyUI/pull/14669): Fixed int8 matrix multiply being skipped on offloaded LoRA weights
  * [**Nodes categories**](https://github.com/Comfy-Org/ComfyUI/pull/14674): Updated and reorganized node categories
  * [**Frontend**](https://github.com/Comfy-Org/ComfyUI/pull/14684): Bumped comfyui-frontend-package to 1.45.20
</Update>

<Update label="v0.26.2" description="June 25, 2026">
  **Partner Node Updates**

  * [**SeeDance 2.0 Mini**](https://links.comfy.org/4eOUnjJ): Added support for ByteDance SeeDance 2.0 Mini on Text-to-Video, First-Last-Frame, and Reference nodes
</Update>

<Update label="v0.26.1" description="June 24, 2026">
  **Partner Node Updates**

  * [**SeeDance 2.0**](https://github.com/Comfy-Org/ComfyUI/pull/14614): Added 4K resolution support for ByteDance SeeDance 2.0
  * [**HappyHorse 1.1**](https://links.comfy.org/3SoBFYI): Added support for Alibaba's HappyHorse 1.1 model
  * [**Grok Video**](https://github.com/Comfy-Org/ComfyUI/pull/14612): Added 1080p support for Grok video generation
</Update>

<Update label="v0.26.0" description="June 23, 2026">
  **New Open-Source Model Support**

  * [**Krea2**](https://links.comfy.org/4eC8714): Krea's open-source image model with wide aesthetic and stylistic range — open-weight **RAW** / **Turbo** pair; train LoRAs on RAW, run 8-step inference on Turbo
  * [**Boogu-Image**](https://github.com/Comfy-Org/ComfyUI/pull/14523): Text-to-image model with Qwen3-VL-8B text encoder; [**TextEncodeBooguEdit**](https://github.com/Comfy-Org/ComfyUI/pull/14529) node adds image editing with negative prompt and optional reference images
  * [**Qwen3-VL Text Generation**](https://github.com/Comfy-Org/ComfyUI/pull/14298): Text generation with image understanding using Qwen3-VL 4B and 8B models
  * [**SCAIL-2 Multireference**](https://github.com/Comfy-Org/ComfyUI/pull/14509): Multi-reference support for SCAIL-2 character replacement

  **New Nodes**

  * [**LTX2 Context Windows**](https://github.com/Comfy-Org/ComfyUI/pull/13325): Context window sampling for LTX-2 multimodal video+audio models with IC-LoRA guide splicing
  * [**Load3DAdvanced**](https://github.com/Comfy-Org/ComfyUI/pull/14316): Mesh-only 3D loader with model\_3d, camera\_info, model\_3d\_info, width, and height outputs
  * [**Save Nodes Output Socket**](https://github.com/Comfy-Org/ComfyUI/pull/13866): Added output socket to save nodes for downstream pipeline wiring

  **Partner Node Updates**

  * [**Luma Rays 3.2**](https://github.com/Comfy-Org/ComfyUI/pull/14540): Seven new nodes for Luma Ray 3.2 video generation

  **Performance & Stability**

  * [**Krea 2**](https://github.com/Comfy-Org/ComfyUI/pull/14594): More accurate memory usage factor
  * [**Dynamic VRAM**](https://github.com/Comfy-Org/ComfyUI/pull/14577): Prompt users to try native formats instead of disabling dynamic VRAM
  * [**Anima**](https://github.com/Comfy-Org/ComfyUI/pull/14557): Small inference optimization
  * [**Jobs API**](https://github.com/Comfy-Org/ComfyUI/pull/14493): Added cancel endpoints (`POST /api/jobs/{job_id}/cancel`, `POST /api/jobs/cancel`)

  **Bug Fixes**

  * [**Assets panel**](https://github.com/Comfy-Org/ComfyUI_frontend/pull/11716): Fixed duplicate media entries when scrolling large jobs
  * [**Advanced inputs**](https://github.com/Comfy-Org/ComfyUI_frontend/pull/12652): Fixed connected advanced inputs hidden after collapsing the advanced section
  * [**Workflow restore**](https://github.com/Comfy-Org/ComfyUI_frontend/pull/12659): Fixed missing subgraph node previews after reloading backgrounded workflows
</Update>

<Update label="v0.25.1" description="June 16, 2026">
  **Partner Node Updates**

  * [**Kling V3-Turbo**](https://github.com/Comfy-Org/ComfyUI/pull/14528): Added support for Kling V3-Turbo model
</Update>

<Update label="v0.25.0" description="June 16, 2026">
  **New Open-Source Model Support**

  * [**Depth Anything 3**](https://github.com/Comfy-Org/ComfyUI/pull/13853): Monocular depth estimation model from LiheYoung
  * [**SCAIL-2**](https://github.com/Comfy-Org/ComfyUI/pull/14373): Character replacement model for enhanced video editing
  * [**Bernini-R**](https://github.com/Comfy-Org/ComfyUI/pull/14216): Wan video model support
  * **Ideogram 4**: Fixed fp8 dtype issues for improved stability
  * **10-bit Video Support**: Added core node support for 10-bit video input/output

  **New Nodes**

  * [**PreviewGaussianSplat + PreviewPointCloud**](https://github.com/Comfy-Org/ComfyUI/pull/14194): New 3D preview nodes for Gaussian splat and point cloud visualization
  * [**Color Primitive**](https://github.com/Comfy-Org/ComfyUI/pull/14260): Color type and utilities for workflows
  * **Improved ResolutionSelector** ([#14309](https://github.com/Comfy-Org/ComfyUI/pull/14309)): Enhanced resolution selection with better defaults

  **Partner Node Updates**

  * **Bria Transparent Video Background + Green Background + Replace Background** nodes
  * **Gemini Text Node** ([#14299](https://github.com/Comfy-Org/ComfyUI/pull/14299)): New LLM partner node
  * **Runway Aleph2** ([#14306](https://github.com/Comfy-Org/ComfyUI/pull/14306)): New video generation node
  * **Krea 2 Medium Turbo** model support
  * **Tripo3D Import 3D** node
  * **Flux Erase**: Added seed input
  * **NanoBanana**: Added temperature and top\_p controls
  * **Flux KV cache**: Fixed crash with split batches

  **Performance & Stability**

  * **Aimdo 0.4.10** + `--reserve-vram` and `--vram-headroom` options
  * Comfy Aimdo 0.4.9 with reliability improvements
  * Media loading: Generalized `--high-ram` option
  * **Assets API**: Cursor-based pagination, image dimension extraction at ingest, asset ID in WebSocket messages
  * Always enable CUDA malloc on CUDA 130+
  * Force cudnn.benchmark to false for deterministic results
  * Fixed odd-height crash and edge bleed in unaligned-width image/video decode
  * Fixed nondeterministic video decode at unaligned widths
  * **Ideogram 4**: Fixed don't reset cast buffers in cleanup\_models\_gc()
  * **Trainer**: Fixed conditions become trainable in training node
</Update>

<Update label="v0.24.1" description="June 3, 2026">
  **Partner Node Updates**

  * Added Bria Green Background node
  * Added Bria Transparent Video Background node with alpha channel support in SaveWEBM
  * Added Krea 2 Medium Turbo model
  * Added seed input to Flux Erase node

  **Bug Fixes**

  * Fixed Seedance 2.0 1080p first/last-frame stretch jump
</Update>

<Update label="v0.24.0" description="June 3, 2026">
  **New Open-Source Model Support**

  * [**Ideogram 4**](https://github.com/Comfy-Org/ComfyUI/pull/14259): Day-0 support for Ideogram's open-weight text-to-image model. Based on a NextDiT/Lumina2-family single-stream DiT with Qwen3-VL-8B (13-layer hidden-state tap) as text encoder. Includes new **Ideogram4Scheduler**, **DualModelGuider** (conditional/unconditional on separate models), and **CFGOverride** nodes
  * [**PiD Models**](https://github.com/Comfy-Org/ComfyUI/pull/14240): Added SDXL and QwenImage variants to the PiD conditioning node
  * [**Radiance**](https://github.com/Comfy-Org/ComfyUI/pull/14206): Added support for checkpoints with nonzero sequential txt\_ids

  **Partner Node Updates**

  * **Ideogram V4 API Node:** New API node for the Ideogram V4 cloud service

  **Performance and Stability**

  * **MultiGPU CFG Split:** Fixed freeze issues during manual abort operations
  * **Ideogram 4:** Optimized memory usage factor for non-dynamic VRAM configurations
  * **DualModelGuider:** Marked as experimental to set proper user expectations
  * **comfy-aimdo:** Updated to 0.4.8

  **Bug Fixes**

  * Fixed cast/dtype issues for BiRefNet and DINOv3 models
  * Fixed TripoSplat preview with old offloading mode
  * DINOv3 inference now runs in fp32 for improved accuracy
  * Fixed OverflowError in Math Expression node for large integer results
  * Reverted partner nodes category changes to maintain workflow compatibility
  * Removed outdated ComfyUI kitchen fallback code
  * Updated workflow templates to v0.9.94
</Update>

<Update label="v0.23.0" description="June 1, 2026">
  **New Open-Source Model Support**

  * [**Microsoft Lens**](https://github.com/Comfy-Org/ComfyUI/pull/14077): Support for Microsoft's Lens text-to-image model with GPT-OSS-20B MoE text encoder (converted to nvfp4). Tokenizer is embedded directly in the safetensors file
  * [**NVIDIA PixelDiT & PiD**](https://github.com/Comfy-Org/ComfyUI/pull/14103): Support for NVIDIA's PixelDiT 1300M text-to-image model and the PiD family of models (SDXL, QwenImage variants added in v0.24.0)
  * [**TripoSplat**](https://github.com/Comfy-Org/ComfyUI/pull/14210): Support for VAST-AI's image-to-3D Gaussian splat model — encodes a single image with DINOv3 + Flux2 VAE, then runs a flow-matching denoiser + octree Gaussian decoder to produce a 3D Gaussian splat
  * [**MediaPipe Face Detection**](https://github.com/Comfy-Org/ComfyUI/pull/14009): Dependency-free reimplementation of Google's MediaPipe face detection and landmarker, weights distributed as safetensors

  **New Nodes**

  * [**Save Image Advanced**](https://github.com/Comfy-Org/ComfyUI/pull/13850): Advanced image saving node with more control over file output
  * [**Gaussian Splat Nodes**](https://github.com/Comfy-Org/ComfyUI/pull/14190): New `GAUSSIAN` type and utility nodes for working with 3D Gaussian splats without external dependencies (serialize to `.ply`, `.splat`, `.spz`, `.ksplat`)
  * [**Logic Nodes**](https://github.com/Comfy-Org/ComfyUI/pull/14004): New And, Or, and Not utility nodes (moved to utils category)
  * [**Preview3DAdvanced**](https://github.com/Comfy-Org/ComfyUI/pull/14175): Advanced 3D preview node

  **Performance Improvements**

  * [**Multi-threaded Model Loading**](https://github.com/Comfy-Org/ComfyUI/pull/13802): Significant model load time speedups via multi-threaded disk loading; also enables offloading models to disk for systems with limited RAM
  * [**MultiGPU Work Units**](https://github.com/Comfy-Org/ComfyUI/pull/7063): Accelerated sampling by splitting conditioning work units across multiple GPUs; supports positive+negative conditioning and masked conditioning as work units
  * **Stochastic Rounding:** Float operations now use comfy-kitchen CUDA stochastic rounding kernel for improved numerical precision
  * **XPU MultiGPU CFG Split:** Enabled on Windows (CFG > 1)
  * **--use-flash-attention** flag now correctly overrides xformers when both are installed
  * **Cache RAM:** Lowered thresholds for smarter RAM cache eviction
  * **Anima / ERNIE Speed:** Improved inference speed on NVIDIA hardware; higher quality rope for ERNIE

  **Partner Node Updates**

  * **OpenRouter LLM Node:** New partner node for OpenRouter language model API
  * **Rodin2.5 Nodes:** New 3D generation nodes from Rodin
  * **Krea2 Image Nodes:** New image generation partner nodes from Krea
  * **Beeble SwitchX Nodes:** New relighting/background swap nodes from Beeble
  * **Tripo3D P1 Model:** New nodes for Tripo3D's P1 generation model
  * **Flux Virtual Try-On & Erase:** New Flux-based virtual try-on and object erase nodes
  * **SeeDance 2:** Improved video reference uploading; added runtime input validation
  * **ByteDance2Reference:** Auto-upscaling widget added
  * **Grok Video:** Added `grok-imagine-video-1.5` model in First Frame mode; removed beta model versions from Grok nodes

  **Load3D Enhancements**

  * Added camera intrinsics fields to Load3DCamera info output
  * `model_file` is now optional (added "none" choice)
  * Added `model_info` output to Load3D node
  * Dropped rotation field from Load3DCamera for cleaner API
  * New `File3DPLY`, `File3DSPLAT`, `File3DSPZ`, `File3DKSPLAT` IO types
  * `SaveImageTextDataSetToFolderNode`: added overwrite/increment mode

  **Other Improvements**

  * Colored console logs for easier debugging
  * Consolidated frontend warning spam
  * `LTXVCropGuides`: fixed stray latent frames when guides share a start position
  * Fixed LTX AV timestep passing in cross-attention AdaLN modulation
  * Fixed Lanczos dimension transposition for single-channel tensors
  * Fixed background removal mask output shape
  * Fixed reshaping in LoRA application
  * Sage attention disabled for Stable Audio DiT and VAE
  * Updated embedded docs to v0.5.2, workflow templates to v0.9.92
  * `pyav` package bumped to fix image loading issues
  * Comfy-kitchen pinned to 0.2.9
  * Various OpenAPI spec fixes and cloud-runtime alignment
</Update>

<Update label="v0.22.3" description="May 20, 2026">
  **Partner Node Updates**

  * Added Krea2 Image nodes
  * Improved video reference uploading for SeeDance 2 using memoryview
</Update>

<Update label="v0.22.2" description="May 20, 2026">
  **Partner Node Updates**

  * Added Rodin2.5 nodes with quality mesh options (usdz export disabled)
  * Fixed seed parameter always being passed to server in Rodin2.5
</Update>

<Update label="v0.22.1" description="May 20, 2026">
  **Partner Node Updates**

  * Added OpenRouter LLM node
  * Added reasoning widget to Anthropic node
  * Added widget for automatic upscaling for ByteDance2Reference node
  * Fixed passing images to Grok LLM
</Update>

<Update label="v0.22.0" description="May 20, 2026">
  **Open-Source Model Support**

  * [**Stable Audio 3.0**](https://blog.comfy.org/p/stable-audio-3-day-0-support): Support for the latest Stable Audio 3 model with improved audio generation capabilities
  * **MoGe:** Added support for MoGe models for enhanced geometry processing
  * **HiDream-O1:** Added area conditioning support for more precise image generation control
  * **LTXV Enhancements:** Added downscaled IC-LoRA support and optional attention\_mask input for improved video control
  * **Temporal Processing:** Implemented downscale\_ratio\_temporal functionality for better temporal control in video workflows
  * **LTX2.3 Optimization:** Reduced peak VRAM usage when guide\_mask is in use for more efficient video generation

  **Partner Node**

  * **Seed2.0:** New node added for enhanced language model capabilities from ByteDance
  * **Opus 4.7:** Fixed deprecated temperature parameter for better model compatibility

  **Node Enhancements**

  * **StringFormat Node:** New node added for advanced string manipulation in workflows
  * **Audio Processing:** Improved audio latent nodes with temporal downscale support for better reusability
  * **Batch Nodes:** Reduced minimum batch size from 2 to 1 for Image/Mask/Latent batch nodes, providing more flexibility
  * **Negative Values Support:** Allow negative values on specific node parameters for expanded creative control

  **Others**

  * **Model Sampling:** Preserved noise\_scale/shift across chained model\_sampling patches for consistent results
  * **Text Generation:** Fixed Qwen3.5 multi-image prompt handling for improved text generation workflows
  * **Dynamic CLIP:** Implemented proper dynamic CLIP saving functionality
  * **BiRefNet:** Resolved compatibility issues for better background removal performance
  * **Hunyuan3D 2.1:** Fixed batch size crashes in attention and forward pass operations
  * Various node display names, descriptions, and categories updated for better user experience
  * Improved frontend version warning system for better compatibility checking
  * Enhanced README with application and cloud links for easier access to resources
  * Added security documentation and careers information to project resources
  * Fixed FeatherMask negative zero indexing for proper right/bottom feathering
  * Corrected OOM memory summary format for clearer error reporting
  * Fixed Batch processing issues and improved model loading stability
  * Resolved various workflow compatibility issues and deprecated parameter handling
</Update>

<Update label="v0.21.1" description="May 13, 2026">
  **New Partner Nodes**

  * **Flux2ImageNode and GrokImageEditNodeV2:** Added new nodes for enhanced image generation and editing workflows
  * **ByteDanceSeedreamNodeV2:** New version with DynamicCombo and Autogrow features for improved parameter handling
  * **OpenAI Image node:** New integration with DynamicCombo and Autogrow capabilities
  * **Claude LLM node:** Added Claude language model support for text generation workflows

  **Model Support Enhancements**

  * **Anima TE LoRA:** Added support for Anima TE LoRA in Kohya format
  * **HiDream-O1-Image:** Full support for HiDream-O1-Image model with dtype fixes and improved memory usage for non-dynamic VRAM configurations

  **Technical Improvements**

  * Fixed safetensors saving of fp8 format in model patcher
  * Corrected LTXV mid-video multi-frame guide alignment for better video processing
  * Improved VOID model compatibility by fixing RuntimeError issues
  * Enhanced Save3D node to support vertex colors and textures for comprehensive 3D workflow support

  **UI and Documentation Updates**

  * Added "Create Video" to the essentials tab for easier access to video generation workflows
  * Updated embedded documentation to v0.5.0 and workflow templates to v0.9.75
  * Fixed input directory creation in LoadAudio define\_schema for better audio workflow handling

  **Bug Fixes**

  * Reverted breaking changes to maintain workflow compatibility
  * Fixed Quiver nodes functionality
  * Corrected deprecated cloud-runtime endpoints marking in API specification
</Update>

<Update label="v0.21.0" description="May 11, 2026">
  **Open-source model support**

  * [**BiRefNet**](https://github.com/Comfy-Org/ComfyUI/pull/12747): Background removal
  * [**Gemma4**](https://github.com/Comfy-Org/ComfyUI/pull/13376): LLM text generation
  * [**Void**](https://github.com/Comfy-Org/ComfyUI/pull/13403): Pass 1 & 2 model support

  **Partner model support**

  * [**Tripo 3.1**](https://github.com/Comfy-Org/ComfyUI/pull/13788): Production-ready 3D generation
  * **NanoBanana2** node v2: DynamicCombo and Autogrow UX refresh

  **Node improvements**

  * **Math Expression:** Added Boolean support for more complex calculations
  * **Flux2 latent previews:** High-quality preview support for Flux2 model latents
  * **Core Blueprints:** New built-in blueprint templates

  **Bug fixes & stability**

  * Corrected VAEDecodeAudio compatibility with LTX-2.x generated audio latents
  * Resolved SolidMask and MaskComposite device mismatch issues
  * Other fixes and improvements (CPU TE meta-tensor handling, port-in-use errors, save filenames without trailing underscores, and more)

  **Additional model & media updates**

  * **CogVideoX:** Video generation models
  * **Wan-Dancer:** Model support
  * **Major media loading:** Unified audio/video in the video loader; PyAV replaces Pillow for images (JPEG memory, tRNS PNG); automatic metadata rotation

  **Performance & video generation**

  * Block prefetch and LoRA async loading (notably faster for LTX)
  * Dynamic VRAM tuning with `--cache-ram 2` and lower peak usage for video
  * Triton ComfyUI kitchen CLI option for advanced optimizations
  * Auto-regressive video; image-to-video for causal models; `causal_window_fix` for long sequences; improved frame interpolation memory and overhead

  **More partner integrations**

  * **Luma UNI-1**, **Topaz Astra 2**, **GPT-5.5** / **GPT-5.5-pro**

  **Further node fixes**

  * Image blending fixes with `--gpu-only`; batch broadcasting on JoinImageWithAlpha; tile stride fixes on SplitImageToTileList and ImageMergeTileList

  **Developer & API**

  * `--feature-flag` registry; OpenAPI cloud-runtime and experiment endpoints; blueprint subgraph descriptions; deterministic ControlNet load order
</Update>

<Update label="v0.20.3" description="April 27, 2026">
  **Partner Node Updates**

  * Added Luma UNI-1 models
  * Added GPT 5.5 and 5.5-pro LLM models
  * Added grok-imagine-image-quality model
  * New NanoBanana2 node with DynamicCombo/Autogrow

  **Bug Fixes**

  * Fixed ImageBlend/ImageCompositeMasked handling images with different channel counts (alpha channel)
  * Fixed Kling V3 price badge in Motion Control node
</Update>

<Update label="v0.20.2" description="April 27, 2026">
  **Partner Node Updates**

  * Added Topaz Astra 2 model (now default upscaler)
  * ByteDance virtual portrait library for regular images
  * Added custom resolution support for GPTImage2 node
  * Removed Moonvalley API nodes
  * Increased default timeout for partner API node tasks

  **Model Support**

  * SDPose resize fix
  * OneTainer ERNIE LoRA support
</Update>

<Update label="v0.20.1" description="April 27, 2026">
  **New Model Support**

  * **SUPIR:** Added support for SUPIR image super-resolution models
  * **SAM 3.1:** Introduced segment anything model 3.1 support for advanced image segmentation
  * **RIFE and FILM:** New frame interpolation models for smooth video frame generation
  * **LTXV Audio VAE:** Support for standalone LTXV audio VAE models with improved native integration

  **Partner Node Enhancements**

  * **Video Generation:** Added 4K resolution support for ByteDance 2, Veo models, and Kling nodes
  * **Veo 3 Lite:** New lightweight version of Veo model for faster video generation
  * **SD2 Real Human:** Added support for Stable Diffusion 2 real human generation
  * **GPT-Image 2:** New version option with additional resolution support and fixed price badges
  * **HappyHorse:** New model integration for enhanced image generation capabilities

  **Performance Optimizations**

  * Faster Ernie model inference through targeted optimizations
  * Improved LTXV audio VAE processing with more native implementation
  * Enhanced ModelPatcherDynamic with better weight handling for ComfyUI layers
  * Anti-cycle validation added to execution system for improved workflow stability

  **Video Processing Improvements**

  * Support for loading higher bit depth videos with proper color accuracy
  * Alpha channel support for video loading, enabling transparency workflows
  * Auto-downscaling functionality for ByteDance 2 nodes to optimize processing

  **Technical Updates**

  * Fixed SQLAlchemy version pinning (>=2.0) for improved database compatibility
  * Enhanced logging capabilities in ComfyUI app files for better debugging
  * Added OpenAPI 3.1 specification for comprehensive API documentation
  * Improved shader handling for blur/sharpen operations using textureSize

  **UI & Frontend**

  * Updated ComfyUI frontend to version 1.42.15 with various improvements
  * Enhanced Preview Any node to display more tensor values for better debugging
  * Added range type support for improved node parameter handling
</Update>

<Update label="v0.20.0" description="April 27, 2026">
  **New Model Support**

  * **SUPIR model support:** Added enhanced super-resolution capabilities for high-quality upscaling workflows
  * **RIFE and FILM frame interpolation:** Introduced advanced frame interpolation models for smooth video transitions
  * **SAM 3.1 support:** Updated Segment Anything Model with improved segmentation accuracy
  * **LTX audio VAE improvements:** Enhanced native audio processing with support for standalone LTXV audio VAEs

  **Performance Optimizations**

  * Optimized Ernie inference for faster generation times
  * Added anti-cycle validation to prevent workflow execution loops
  * Improved ModelPatcherDynamic weight handling for better model compatibility

  **Video Processing Enhancements**

  * Support for loading higher bit depth videos with improved quality preservation
  * Added alpha channel support for video loading workflows
  * Auto-downscaling capabilities for ByteDance 2 nodes to handle large video files

  **Partner Node Updates**

  * **Veo models:** Added 4K resolution support and Veo 3 Lite model
  * **Kling nodes:** Enhanced with 4K resolution capabilities
  * **GPTImage:** Added gpt-image-2 version option and new resolution support
  * **HappyHorse model:** New partner model integration
  * **SD2 real human support:** Enhanced realistic human generation capabilities

  **UI and API Improvements**

  * Added OpenAPI 3.1 specification for better API documentation
  * Fixed texture size handling in blur/sharpen shaders for more accurate effects
  * Enhanced Preview Any node to display more tensor values for debugging

  **Bug Fixes**

  * Fixed SQLAlchemy compatibility by pinning version ≥2.0
  * Resolved Parameter assignment for Stable\_Zero123 cc\_projection weights
  * Corrected LTXV Reference Audio node functionality
  * Fixed 4K resolution restriction for veo-3.0 models
</Update>

<Update label="v0.19.5" description="April 17, 2026">
  **Partner Node Updates**

  * Added SD2 Real Human support for Stable Diffusion 2
  * Added 4K resolution to Kling nodes
  * Added GPTImage price badge fixes and new resolutions

  **Bug Fixes**

  * Fixed 4K resolution restriction for veo-3.0 models
  * Fixed Stable\_Zero123 cc\_projection weight assignment on Windows (aimdo-enabled)
</Update>

<Update label="v0.19.4" description="April 17, 2026">
  **Partner Node Updates**

  * Added 4K resolution support for Veo models + Veo 3 Lite model
  * Added gpt-image-2 as a version option
  * Added automatic video downscaling for ByteDance 2 nodes
  * Added SD2 Real Human support

  **Bug Fixes**

  * Fixed Stable\_Zero123 cc\_projection weight assignment on Windows (aimdo-enabled)
  * Fixed 4K resolution restriction for veo-3.0 models
  * Fixed GPTImage price badges
</Update>

<Update label="v0.19.3" description="April 17, 2026">
  **LTX text generation**

  * Implemented `use_default_template` for LTX models in text generation nodes

  **Partner node updates**

  * Added Quiver **arrow-1.1** and **arrow-1.1-max** SVG models for enhanced vector graphics capabilities
  * Made "obj" output optional in Hunyuan3D Text and Image to 3D nodes for improved workflow flexibility
  * Corrected StabilityAI price badges for accurate API node pricing information
</Update>

<Update label="v0.19.2" description="April 17, 2026">
  **Performance & memory**

  * Fixed OOM regression in quantized models during inference, improving memory usage for \_apply() operations

  **Text generation**

  * **LTX:** Added option to disable the default template in text generation nodes for more flexible prompt handling
  * Introduced JsonExtractString node for JSON data manipulation in workflows

  **Bug fixes**

  * **Ernie Image:** Fixed incorrect class name — use `ErnieTEModel_` instead of `ErnieTEModel`

  **Partner nodes**

  * Added 1080p resolution support for SeeDance 2.0 model, enabling higher quality video generation
</Update>

<Update label="v0.19.1" description="April 16, 2026">
  **New Model Support**

  * [Ernie Image Text to Image](https://blog.comfy.org/p/ernie-image-day-0-support)
  * LLM: Ministral model

  **Partner Node**

  * [Sonilo: Create music for your video](https://blog.comfy.org/p/comfyui-now-supports-sonilo-via-partner)

  **Capability**

  * Preview as Text node update: Support any value to string conversion
</Update>

<Update label="v0.19.0" description="April 13, 2026">
  **Model & Generation Support**

  * Added support for LTX2 reference audio (ID-LoRA) functionality
  * Implemented Qwen3.5 text generation models with enhanced 8B model compatibility for TextGenerate node
  * Added RT-DETRv4 detection model support for improved object detection capabilities
  * Introduced Ace Step 1.5 XL model support with intermediate dtype compatibility
  * Added support for small flux.2 decoder and enabled Flux conditioning without pooled output
  * Implemented Ernie Image model for expanded generation options

  **New Nodes & Features**

  * Added CURVE node for advanced curve manipulation in workflows
  * Introduced Number Convert node with improved precision handling for large numbers
  * Added Image Histogram node for image analysis capabilities
  * Implemented Color Adjustment node with zero default values
  * Enhanced GLSL shader node with curve inputs and raised uniform limits
  * Added has\_intermediate\_output flag for nodes with interactive UI elements

  **Memory & Performance**

  * Integrated RAM cache with model RAM management for improved efficiency
  * Enhanced pinned memory accounting and model memory handling
  * Fixed blur and sharpen nodes compatibility with FP16 intermediates
  * Improved memory management for intermediate device operations in ImageUpscaleWithModel

  **API & Partner Nodes**

  * Updated xAI Grok nodes with enhanced functionality
  * Added new Topaz model integration
  * Introduced WAN2.7 nodes for expanded workflow capabilities
  * Added SeeDance 2.0 nodes for enhanced video generation
  * Updated Tencent3D nodes with improved features

  **Bug Fixes & Stability**

  * Fixed Train LoRA crash with training\_dtype "none" and bfloat16 LoRA weights
  * Resolved text generation regression with LTXAV model
  * Fixed FP8 scaled checkpoints compatibility issues
  * Improved browser security handling for insecure browsers
  * Fixed SVG file MIME type registration for proper file handling

  **Infrastructure Updates**

  * Bumped manager version to 4.1 with improved functionality
  * Updated frontend to version 1.42.10 with enhanced stability
  * Added Intel XPU portable release support
  * Updated workflow templates to version 0.9.47
  * Enhanced asset registration system for output files
</Update>

<Update label="v0.18.5" description="March 25, 2026">
  **Stability**

  * Additional testing after fp8 checkpoint fix revert
</Update>

<Update label="v0.18.4" description="March 25, 2026">
  **Bug Fixes**

  * Fixed pinned memory accounting for Windows, reducing risk of OOM errors
  * Fixed fp8 scaled checkpoints not loading correctly
  * Reverted fp8 checkpoint fix causing regressions

  **Partner Node Updates**

  * Added new Wan2.7 partner nodes
</Update>

<Update label="v0.18.3" description="March 25, 2026">
  **Partner Node Updates**

  * Added new Topaz model in API nodes
</Update>

<Update label="v0.18.2" description="March 25, 2026">
  **Partner Node(API)**

  * Grok Reference to Video
  * Grok Video Extend
  * [Blog](https://blog.comfy.org/p/grok-imagine-model-feature-updates)
</Update>

<Update label="v0.18.1" description="March 23, 2026">
  **FP16 Support Fixes**

  * Fixed Canny node compatibility with FP16 precision, resolving workflow issues when using 16-bit floating point operations
  * Resolved sampling problems with FP16 intermediates that were causing inconsistent generation results
  * Fixed FP16 intermediates producing different results than expected, ensuring consistent output across runs

  **VAE Improvements**

  * Fixed light and color issues in WAN VAE processing, improving output quality and color accuracy
</Update>

<Update label="v0.18.0" description="March 21, 2026">
  **Memory & Performance Optimizations**

  * Added `--fp16-intermediates` flag to use FP16 for intermediate values between operations, reducing VRAM usage
  * Major VRAM reductions for LTX and WAN VAE models with inplace output processing and chunked encoder implementation
  * Improved tiled decode peak memory usage and fixed VRAM leaks in video VAE tiler fallback
  * Enhanced RAM pressure release strategies for Windows with comfy-aimdo updates (0.2.11-0.2.12)
  * Added `--enable-dynamic-vram` option to force enable dynamic VRAM management

  **Model & Hardware Support**

  * Added support for mxfp8 precision format for enhanced model compatibility
  * Enabled PyTorch Attention for AMD gfx1150 (Strix Point) GPUs
  * Enhanced training capabilities with FP4, 8, 16 native dtype support and quantized linear autograd functions
  * Fixed text encoder compatibility issues and disabled SageAttention for Hunyuan3D v2.1 DiT models

  **Node & API Enhancements**

  * Fixed Tencent TextToModel and ImageToModel API nodes
  * Added Nano Banana 2 "thought\_image" support and Quiver SVG nodes
  * Marked seedream-3-0-t2i and seedance-1-0-lite models as deprecated
  * Added slice\_cond and per-model context window conditioning resizing capabilities
  * Enhanced EmptyLatentImage and EmptyImage nodes to follow intermediate dtype settings

  **Frontend & Infrastructure**

  * Updated frontend package to version 1.41.21 with improved caching headers to prevent stale chunks
  * Added CacheProvider API for external distributed caching support
  * Implemented atomic writes for userdata to prevent data loss on crashes
  * Enhanced essentials category support for nodes and blueprints
  * Updated workflow templates to version 0.9.26

  **Bug Fixes & Stability**

  * Fixed pixel space VAE compatibility issues and model finalizer execution at exit
  * Improved weight dtype handling in Load Diffusion Model node (marked as advanced input)
  * Enhanced deferred weight initialization for subclassed models
  * Fixed various memory leaks and corruption issues in rare edge cases
</Update>

<Update label="v0.17.2" description="March 15, 2026">
  This release focuses on stability and bug fixes. For complete technical details, see the [full changelog](https://github.com/Comfy-Org/ComfyUI/compare/v0.17.1...v0.17.2) on GitHub.
</Update>

<Update label="v0.17.1" description="March 13, 2026">
  This is a patch release that includes various bug fixes and stability improvements. For full details on changes included in this release, see the complete changelog comparison between v0.17.0 and v0.17.1.
</Update>

<Update label="v0.17.0" description="March 13, 2026">
  **Architecture & Performance Improvements**

  * Implemented modular asset architecture with asynchronous two-phase scanner and background seeder for improved loading performance
  * Added Python fault handler for better debugging and stability
  * Enhanced memory usage optimization for KV cache models
  * Improved dynamic VRAM handling with better error management for AcceleratorError compatibility

  **Model Support & Enhancements**

  * Added support for Flux 2 Klein KV cache model through the FluxKVCache node
  * Enhanced model patching system with cleanup functions and pre-attention patches for Flux models
  * Added pre-attention and post-input patches to Qwen image model
  * Fixed text encoder LoRA loading for wrapped models
  * Improved batch processing with fixes for batch\_size > 1 on various models

  **New Nodes & Features**

  * Added Painter node for enhanced image editing capabilities
  * Introduced Reve Image API nodes for expanded functionality
  * Updated workflow templates to version 0.9.21
  * Enhanced gradient stops formatting for better frontend compatibility

  **Bug Fixes & Stability**

  * Fixed audio extraction and truncation issues
  * Resolved model detection problems with deep clone pre-edited weights
  * Improved ComfyUI Manager installation guidance and updated to version 4.1b2
  * Enhanced package version reporting for better troubleshooting

  **Frontend Updates**

  * Updated frontend package to version 1.41.18 with various improvements and bug fixes
  * Updated comfy-kitchen to version 0.2.8 and comfy-aimdo to version 0.2.10
</Update>

<Update label="v0.16.4" description="March 7, 2026">
  **New Nodes & Features**

  * Added Math Expression node with simpleeval evaluation for mathematical operations in workflows
  * Introduced TencentSmartTopology API node for enhanced topology processing capabilities
  * Added Gemini 3.1 Flash-Lite model support to LLM node, expanding AI language model options

  **Bug Fixes & Performance**

  * Fixed fp16 audio encoder models compatibility issues
  * Resolved Text Encoder CPU execution when dynamic VRAM is enabled
  * Fixed requirements version conflicts
  * Enhanced memory management with compute stream synchronization before buffer freeing

  **Workflow Templates**

  * Updated workflow templates to version 0.9.11 with latest improvements
</Update>

<Update label="v0.16.3" description="March 5, 2026">
  **LTX Audio Model Improvements**

  * Fixed LTX2 vocoder conv\_transpose1d with manual casting for improved audio processing stability
  * Resolved LTX audio VAE novram compatibility issues for better memory management during audio generation
  * Added causal\_fix parameter to add\_keyframe\_index and append\_keyframe functions, enhancing keyframe handling precision in video workflows
</Update>

<Update label="v0.16.2" description="March 5, 2026">
  **Core Updates**

  * Updated comfy-aimdo to version 0.2.7 for improved AI model operations
  * Enhanced CPU weight handling in VBAR caster for better performance across different hardware configurations

  **Workflow Templates**

  * Updated workflow templates to version 0.9.10 with latest improvements and optimizations
  * Code refactoring improvements for enhanced stability
</Update>

<Update label="v0.16.1" description="March 5, 2026">
  **API Nodes Updates**

  * Updated xAI models and pricing for improved cost management and model selection
  * Enabled Kling 3.0 Motion Control for enhanced video generation capabilities

  **Workflow Templates**

  * Updated workflow templates to version 0.9.8 with latest improvements and optimizations
</Update>

<Update label="v0.16.0" description="March 5, 2026">
  **New Nodes & Features**

  * Added ResolutionSelector node with aspect ratio presets for easier image dimension setup
  * Introduced CURVE type support for advanced parameter control
  * Added text preview support to jobs API for better workflow monitoring
  * Native LongCat-Image implementation for enhanced image processing capabilities

  **Model & Format Support**

  * Added ACE-Step 1.5 lycoris key alias mapping for LoKR compatibility
  * Support for SDPose-OOD models
  * Added SCAIL WanVideo model support
  * Support for zeta chroma weights loading
  * Added LTXAV 2.3 model support
  * Z-image pixel space support implementation

  **Memory & Performance**

  * Dynamic VRAM mode is now the default, improving memory efficiency
  * Implemented LoRA requantization for non-QuantizedTensor fp8
  * Enhanced dynamic offload heuristics for better performance
  * Updated comfy-aimdo to version 0.2.6 with improved allocator handling
  * Fixed dynamic VRAM conflicts with weight hooks and WSL compatibility

  **API & UI Improvements**

  * Added "IMAGE+TEXT" support in NanoBanana2 API node
  * Renamed Mahiro CFG to Similarity-Adaptive Guidance for clarity
  * Fixed GLSL node input dimension requirements
  * Enhanced VAEDecodeAudioTiled to properly use tile\_size input

  **Bug Fixes**

  * Fixed WanVAE encoder/decoder confusion in feat\_map processing
  * Resolved ACE-1.5 memory estimation issues with missing lm\_metadata
  * Fixed context window step handling for substep sigmas
  * Prevented VideoFromComponents crashes when writing to BytesIO
  * Limited image tile overlap to prevent processing issues

  **Workflow Templates**

  * Updated workflow templates to version 0.9.7
</Update>

<Update label="v0.15.1" description="February 26, 2026">
  **Bug Fixes & Stability**

  * Fixed KeyError when prompt entries lack class\_type key, preventing workflow crashes
  * Resolved GLSL node compatibility issues with pyopengl accelerate numpy textures
  * Fixed LTXAV text encoder minimum length and memory estimation problems
  * Disabled dynamic VRAM when using torch compiler to prevent conflicts

  **Model & API Updates**

  * Updated comfy aimdo to version 0.2.2 with improved fallback handling
  * Added WanVideo-based segmentation model FlowRVS support for advanced video processing
  * Added NanoBanana2 API node for expanded functionality
  * Fixed Aimdo fallback to prevent zero-copy sft issues

  **UI & Frontend**

  * Patched frontend to version 1.39.19, fixing progress text serialization in API nodes
  * Moved essentials\_category to correct replacement nodes for better organization

  **New Features**

  * Added per-guide attention strength control in self-attention for fine-tuned workflow control
  * Updated workflow templates to version 0.9.4
</Update>

<Update label="v0.15.0" description="February 24, 2026">
  **New Nodes & Features**

  * Added BBox widget for precise bounding box selection in image workflows
  * Introduced 3-band equalizer node for audio processing workflows
  * Added basic text generation support with native models, initially supporting Gemma3 and Qwen 3
  * New GLSL shader node using PyOpenGL for advanced visual effects
  * Added ElevenLabs API nodes for text-to-speech functionality
  * New gradient-slider display mode for FLOAT inputs with improved UI
  * Added SplitImageToTileList and ImageMergeTileList nodes for tiled processing workflows

  **API Nodes**

  * Added price badge for Rodin Gen-2 node
  * Added KlingAvatar node for avatar generation
  * Added ByteDance Seedream-5 model support
  * Fixed Gemini image MIME type handling with glob matching
  * Forced Gemini to return uncompressed images for better quality

  **Performance & Bug Fixes**

  * Fixed FP8 dynamic VRAM workflow performance issues by limiting return of requants
  * Resolved non-contiguous audio waveform crashes in video save operations
  * Fixed LTXAV model loading issues including fp8 checkpoint support and embedding connector dtype problems
  * Improved PyOpenGL compatibility for versions \< 3.1.4

  **UI Improvements**

  * Marked 429 widgets as advanced for collapsible UI
  * Added essentials\_category for better node organization
  * Enhanced essential subgraph blueprints with improved categorization
  * Updated frontend to version 1.39.16

  **Model Support**

  * Enhanced text generation with tokenization improvements and minimum length enforcement
  * Updated LTXAV av embedding connectors integration
  * Temporary compatibility fixes for LTX 2.0 workflows during migration period
</Update>

<Update label="v0.14.2" description="February 18, 2026">
  **Bug Fixes**

  * Fixed issue with Gemini/Nano banana API nodes that sometimes returned blank images, improving reliability for AI-powered image generation workflows.
</Update>

<Update label="v0.14.1" description="February 17, 2026">
  **Bug Fixes**

  * Fixed anima LLM adapter forward when manual cast

  **New Model Support**

  * Added "viduq3-turbo" model support in API nodes
  * Added Recraft V4 nodes for enhanced creative workflows

  **Updates**

  * Updated workflow templates to v0.8.43
</Update>

<Update label="v0.14.0" description="February 17, 2026">
  **New Open-Source Model Support**

  * [**Qwen 2512 ControlNet / Fun ControlNet**](https://github.com/Comfy-Org/ComfyUI/pull/12359): Support for Qwen-based ControlNet models for enhanced image control
  * **NAG Implementation**: Nesterov accelerated gradient applied to all Flux-based models

  **New Nodes & APIs**

  * [**VideoSlice Node**](https://github.com/Comfy-Org/ComfyUI/pull/12107): Video slicing utility for precise temporal control
  * [**Node Replacement API**](https://github.com/Comfy-Org/ComfyUI/pull/12014): Significant architecture change allowing node replacement in workflows
  * **Create List Node** ([#12173](https://github.com/Comfy-Org/ComfyUI/pull/12173)): List creation utility node

  **Performance & Technical Improvements**

  * Left-padded text encoder attention mask support
  * Torch RMSNorm for Flux models + Hunyuan video refactor
  * Dynamic VRAM: training fixes, vanilla-fp8 LoRA quality fix
  * ModelPatcherDynamic: force load non-leaf weights
  * Fix LoRA extraction in offload + dynamic VRAM mode
  * Use torch RMSNorm for flux models and refactor hunyuan video

  **Partner Node Updates**

  * **Magnific Upscalers** API nodes enabled
  * **Tencent 3D nodes**: ModelTo3DUV, 3DTextureEdit, 3DParts
  * **Bria RMBG** API nodes
  * **Kling API nodes**: V3, O3 models

  **Trainer Improvements**

  * Training with proper offloading (KohakuBlueleaf)
  * Built-in LoRA training now works on Anima
</Update>

<Update label="v0.13.0" description="February 10, 2026">
  **New Model Support & Improvements**

  * [**EasyCache: LTX2 Support**](https://github.com/Comfy-Org/ComfyUI/pull/12231): EasyCache now works with LTX2 for faster video generation
  * **ACE Step 1.5** ([#12311](https://github.com/Comfy-Org/ComfyUI/pull/12311)): Now works without LLM, base model default workflow fix, text encoding improvements
  * **FP16 for Cosmos-Predict2 and Anima** ([#12249](https://github.com/Comfy-Org/ComfyUI/pull/12249)): Reduced memory usage for supported models
  * **Make tonemap latent work on any dim latents** ([#12363](https://github.com/Comfy-Org/ComfyUI/pull/12363)): More flexible tone mapping

  **Performance & Fixes**

  * Dynamic VRAM fixes for ACE 1.5 performance + VRAM leak fix
  * LazyCache fix ([#12344](https://github.com/Comfy-Org/ComfyUI/pull/12344))
  * Disable prompt weights for LTXV2
  * Frontend bumped to 1.38.13

  **Partner Node Updates**

  * **Kling API nodes**: New V3, O3 models
  * Moonvalley API nodes fixes
</Update>

<Update label="v0.12.3" description="February 5, 2026">
  **ACE Step 1.5 Improvements**

  * [**LLM sampling options**](https://github.com/Comfy-Org/ComfyUI/pull/12295): Added sampling options and reference audio support
  * **Text encoding improvements** ([#12283](https://github.com/Comfy-Org/ComfyUI/pull/12283)): Better text processing for ACE
  * **VAE tiled decode for audio** ([#12299](https://github.com/Comfy-Org/ComfyUI/pull/12299))
  * Sage attention disabled for ACE Step 1.5
  * Fix NaN issue on some hardware/pytorch configs

  **3D Improvements**

  * File3DAny output on Load3D node; SaveGLB accepts File3DAny input
</Update>

<Update label="v0.12.2" description="February 4, 2026">
  **ACE Step 1.5**

  * [**4B LM model support**](https://github.com/Comfy-Org/ComfyUI/pull/12257): Support for the 4B ACE step 1.5 language model
  * VRAM leak fix in dynamic VRAM mode
</Update>

<Update label="v0.12.1" description="February 3, 2026">
  **ACE Step 1.5 Fixes**

  * [**Progress bar**](https://github.com/Comfy-Org/ComfyUI/pull/12242): Added progress bar for ACE Step
  * **Base model LoRAs** support
  * **Tiled VAE fix** for ACE
  * Mac compatibility fixes

  **3D & API**

  * Basic 3D model file types in API
  * LLM logits cast as comfy-weight
</Update>

<Update label="v0.12.0" description="February 3, 2026">
  **New Model Support**

  * [**ACE Step 1.5**](https://github.com/Comfy-Org/ComfyUI/pull/12237): Basic support for the ACE Step 1.5 audio/speech generation model — a major new model family
  * [**KV Cache for LLM text generation**](https://github.com/Comfy-Org/ComfyUI/pull/12195): Performance boost for running llama models with cached key-value pairs
  * [**Adaptive Model Loading**](https://github.com/Comfy-Org/ComfyUI/pull/11845): Reduced RAM usage, fixed VRAM OOMs, and fixed Windows shared memory spilling

  **New Nodes**

  * **Color type + Color to RGB Int node** ([#12145](https://github.com/Comfy-Org/ComfyUI/pull/12145))

  **API Nodes**

  * **HitPaw API nodes** ([#12117](https://github.com/Comfy-Org/ComfyUI/pull/12117))
  * **Recraft** style node
  * **Vidu**: Q3 model, Extend and MultiFrame nodes

  **Developer**

  * Assets Part 2 - more endpoints
  * send is\_input\_list on v1/v3 schema to frontend
</Update>

<Update label="v0.11.1" description="January 29, 2026">
  **Partner Node Updates**

  * [**Grok Imagine API nodes**](https://github.com/Comfy-Org/ComfyUI/pull/12136): Image generation via Grok
  * Manager bumped to 4.1b1

  **Developer**

  * Dev-only nodes support
  * Python 3.14 compat notes
</Update>

<Update label="v0.11.0" description="January 27, 2026">
  **New Open-Source Model Support**

  * [**Anima Model**](https://github.com/Comfy-Org/ComfyUI/pull/12012): Support for the Anima model family with fp16 optimization
  * [**Multi/InfiniteTalk**](https://github.com/Comfy-Org/ComfyUI/pull/10179): Large-scale multi-speaker support for LTXV
  * [**Flux2 LyCORIS LoKr**](https://github.com/Comfy-Org/ComfyUI/pull/11997): LoKr (KronA-based) LoRA support for Flux2
  * **LTX2 Tiny VAE** (taeltx\_2) support
  * **Z-Image Omni** base model support
  * **ModelScope LoRA** format for Flux2 Klein

  **New Nodes & Features**

  * **Magnific API nodes** ([#11986](https://github.com/Comfy-Org/ComfyUI/pull/11986)): Upscaling via Magnific
  * **Tencent Hunyuan3D API nodes** ([#12026](https://github.com/Comfy-Org/ComfyUI/pull/12026))
  * **WaveSpeed API nodes** ([#11945](https://github.com/Comfy-Org/ComfyUI/pull/11945))
  * **Search aliases** field in node schema for better node discoverability
  * **kwargs inputs** for arbitrary inputs from frontend
  * **RoPE Position Adjustment** for small grid IC-LoRA

  **Performance**

  * QWEN VAE and WAN speed/VRAM optimizations
  * LTX2 VAE VRAM reduction
  * LTX2 refactored forward for better VRAM efficiency

  **Model Enhancements**

  * Flux2 Klein checkpoints saved with SaveCheckpoint now load properly
  * Config for Qwen 3 0.6B model
  * Dynamically detect chroma radiance patch size
</Update>

<Update label="v0.10.0" description="January 21, 2026">
  **New Features**

  * [**API Node Auto-Discovery**](https://github.com/Comfy-Org/ComfyUI/pull/11943): All `nodes_*.py` files are now auto-discovered, simplifying node development
  * **Advanced Parameter support** ([#11939](https://github.com/Comfy-Org/ComfyUI/pull/11939)): Advanced widget support for input classes
  * **Image sizes added to CLIP vision outputs** ([#11923](https://github.com/Comfy-Org/ComfyUI/pull/11923))

  **Partner Node Updates**

  * **ByteDance Seedance 1.5 Pro** API node
  * **Bria Edit** node ([#11978](https://github.com/Comfy-Org/ComfyUI/pull/11978))
  * Autogrow validation improvements

  **Bug Fixes**

  * Mono audio to fake stereo for LTXV VAE encoding ([#11965](https://github.com/Comfy-Org/ComfyUI/pull/11965))
  * Flux2 Klein memory estimation adjustments
  * AMD GPU tensor type fix
</Update>

<Update label="v0.9.2" description="January 15, 2026">
  **New Model Support**

  * [**Flux2 Klein**](https://github.com/Comfy-Org/ComfyUI/pull/11890): Major new model family support — Flux2 Klein with expanded model capabilities
  * [**Z-Image ControlNet Lite**](https://github.com/Comfy-Org/ComfyUI/pull/11849): Lightweight version of Alibaba-Pai Z-Image ControlNet

  **New Nodes**

  * **Meshy 3D API nodes** ([#11843](https://github.com/Comfy-Org/ComfyUI/pull/11843))
  * **ResizeImageMaskNode**: Added crop-to-multiple mode
  * **Blueprints directory** for built-in templates

  **Performance & Technical**

  * NVFP4 LoRA optimization (multiple rounds)
  * Throttled ProgressBar WebSocket updates
  * Lanczos grayscale upscaling fix
  * VAELoader metadata loading
  * Repository URL updated to Comfy-Org/ComfyUI
</Update>

<Update label="v0.9.1" description="January 13, 2026">
  **Bug Fix**

  * Bumped LTXAV memory estimation
</Update>

<Update label="v0.9.0" description="January 13, 2026">
  **New Features**

  * [**Basic Asset Support**](https://github.com/Comfy-Org/ComfyUI/pull/11315): Foundation for model asset management — endpoints for model CRUD operations
  * **NVFP4 Model LoRA** ([#11837](https://github.com/Comfy-Org/ComfyUI/pull/11837)): LoRA support now works on NVFP4 quantized models
  * [**SigLIP 2 NAFlex**](https://github.com/Comfy-Org/ComfyUI/pull/11831): Support for SigLIP 2 NAFlex CLIP vision model
  * [**ImageCompare Node**](https://github.com/Comfy-Org/ComfyUI/pull/11343): Compare two images visually
  * [**JoinAudioChannels**](https://github.com/Comfy-Org/ComfyUI/pull/11728): Audio channel joining utility

  **Model Support**

  * ModelScope LoRA for Z-Image models ([#11805](https://github.com/Comfy-Org/ComfyUI/pull/11805))
  * FP4/FP8 fixes for Chroma and text encoders
  * VAEEncodeForInpaint now supports WAN VAE tuple downscale\_ratio
  * LTX2 VRAM reduction via efficient timestep embed handling

  **API Nodes**

  * **Vidu2** nodes ([#11760](https://github.com/Comfy-Org/ComfyUI/pull/11760))
  * **Topaz Enhance** fixes
  * **Gemini** safety block handling

  **Technical**

  * AMD gfx1200: PyTorch attention enabled by default
  * CI container version bump automation
  * Refactored model loading to lower memory usage
  * Frontend patched to 1.36.14
</Update>

<Update label="v0.8.1" description="January 8, 2026">
  **Model Support**

  * Added Gemma 12B support with quantized weights
  * Enhanced LTXAV text encoder with device selection support and reduced VRAM usage
  * Improved memory estimation for LTXAV text encoder

  **Performance Improvements**

  * Fixed FP8MM offloading performance issues
  * Added warning for outdated PyTorch versions with recommendation to upgrade to cu130 for performance boost
  * Updated comfy kitchen version requirements

  **Bug Fixes**

  * Fixed stable release workflow to properly pull latest comfy kitchen updates
  * Removed confusing load statistics from model patcher
  * Updated workflow templates to v0.7.69
</Update>

<Update label="v0.8.0" description="January 7, 2026">
  **New Models Support**

  * Added LTXV 2 model support
  * Added NVFP4 checkpoint support (fp4 matrix multiplication)
  * Added Sage Attention 3 support via CLI argument

  **API Improvements**

  * V3 API: Exposed DynamicCombo and Autogrow functionality
  * API nodes: Kling Omni 720p resolution support, WAN2.6 ReferenceToVideo
  * Tripo3D: Optimized face\_limit parameter handling
  * Fixed URL encoding preservation for Vidu API signed URLs

  **Fixes**

  * Fixed upscale model CPU offloading
  * Fixed LTXV2 text encoder lowvram compatibility
  * Fixed fp8 processing issues
  * Fixed MPO format images to use first frame only
  * Conditional comfy-kitchen CUDA support based on PyTorch version

  **Other**

  * Added OOM memory summary for debugging
  * Mahiro CFG display name update
  * Workflow templates updated to v0.7.67
  * Code refactoring and cleanup (CLIP preprocessing, comfy-kitchen integration)
</Update>

<Update label="v0.7.0" description="December 31, 2025">
  **System Requirements**

  * PyTorch 2.4+ minimum version requirement

  **Fixes & Improvements**

  * Enabled async memory offload by default for AMD GPUs
  * Fixed ancestral sampler noise on CPU inference
  * Improved memory management error handling (pin/unpin operations)
  * Added VACE context handling in context windows

  **Updates**

  * ComfyUI Frontend updated to v1.35.9
  * ComfyUI Manager updated to v4.0.4
  * Workflow templates updated to v0.7.64

  **New Nodes**

  * Added ManualSigmas node for sampling control
  * Added Kling Motion Control node
  * ResizeByLongerSide now supports video processing

  **API Nodes**

  * Gemini API: Force enable prompt enhancement
  * Billing changed from dollars to credits
  * Deprecated "seededit", updated Seedream node display names

  **Technical**

  * Converted image processing nodes to V3 schema
  * Optimized Lumina/Z image model (removed unused components)
</Update>

<Update label="v0.6.0" description="December 24, 2025">
  **New Model Support**

  * Qwen Image Layered
  * NewBie Image Exp0.1

  **New Features**

  * Unified jobs API with /api/jobs endpoints for workflow monitoring

  **Improvements**

  * Disabled watermark generation by default in API nodes
  * Refactored trainer with resolution bucketing for better training efficiency
  * Enhanced AMD GPU support
  * Extended Kling O1 StartEndFrame node duration range
  * Updated Topaz 4k video upscaling functionality

  **Bug Fixes**

  * Fixed mask concatenation issues in ZImageFunControlNet in --gpu-only mode
</Update>

<Update label="v0.5.1" description="December 18, 2025">
  * Added GPT-Image-1.5 API nodes
  * Fixed V3 nodes processing regression
  * Improved SA-Solver accuracy
</Update>

<Update label="v0.5.0" description="December 17, 2025">
  **New Models & Features**

  * WanMove model for advanced motion processing
  * Qwen Edit 2511 with automatic detection
  * Z-Image Fun Control Union 2.0 with inpainting

  **API Nodes**

  * Kling Omni Image, TextToVideoWithAudio, ImageToVideoWithAudio
  * Wan2.6 model integration
  * Tripo3.0 for 3D model generation

  **Performance**

  * Improved memory estimation for Z-Image and SD3 models
  * Better GPU memory management for Qwen-Image VAE
  * Frontend updated to v1.34.9
</Update>

<Update label="v0.4.0" description="December 10, 2025">
  **Model Support**

  * Ovis Image
  * Kandinsky 5.0 (T2V/I2V/T2I variants)
  * Z-Image Alibaba PAI-Fun ControlNet support
  * Improved Z-Image FP16 compatibility
  * Added PATCH method to CORS headers and chroma-radiance-x0 mode

  **Workflow &  Enhancements**

  * Context windows fixes and enhanced temporal processing
  * Kling API @image reference format
  * ComfyUI-Manager pip installation support

  **Frontend Improvements**

  * Improve frontend load/startup time significantly
  * Restored settings button in sidebar
  * GPU accelerated maskeditor rendering
  * Improve asset cards and queue progress panel designs
  * Add missing nodes warning UI to queue button and breadcrumb
  * Mobile fixes
  * various bug fixes

  **Major VRAM Optimizations**

  * Temporal rolling VAE delivering massive VRAM reductions for video models (Hunyuan/Kandinsky)
  * Reduced LoRA memory reservations, especially beneficial for Flux2 workflows
  * Fixed Flux2 OOM errors with improved dequantization offload accounting
  * Enhanced LoRA computation speed with FP16 processing
  * Optimized text encoder GPU usage to prevent unnecessary CPU fallbacks

  **V3 Schema Migration**

  * Converted 3D, audio, freelunch, and mask nodes to V3 schema
  * Added MatchType, DynamicCombo, and Autogrow support for improved workflow flexibility

  **Bug Fixes & Compatibility**

  * Fixed text encoder regression when loaded directly on GPU
  * Resolved transformer\_options clearing issue in Lumina models
  * Fixed Qwen Image LoRA training, HunyuanVideo 1.5 meanflow distil issues
  * Corrected EmptyAudio node input types for proper audio workflow integration
  * Enhanced VRAM calculation accuracy to prevent unwanted full offloading
  * Support for "transformer." LoRA prefix in Z-Image workflows
  * Improved scaled FP8 format compatibility with mixed quantization operations

  **Note: for Desktop users**

  * If you have not turned off the auto-update, please wait for the latest Desktop release, it will auto-update to the latest version.
  * If you are using the Desktop and **if you also turn off the auto-update**, the Desktop might not be able to auto-update for the latest version this time.
  * Please download the latest Desktop version from [here](https://www.comfy.org/download) to get the latest features.
</Update>

<Update label="v0.3.76" description="December 2, 2025">
  **Frontend UI/UX**

  * New UI: **Nodes 2.0** public beta
  * Linear mode beta version (You can enable it by setting a hot-key in keybinding.)
  * Subgraphs improvement and bug fixes
  * Improve missing node UX
  * New workflow progress panel
  * New Assets sidebar

  **3D feature**

  * Support panoramic image in the 3D node
  * Merge 3D animation node into 3D node

  **Lora Trainer**

  * Support multi-resolution for ComfyUI native LoRA trainer
  * Support Z-Image LoRA training

  **Performance & model support**

  * Support video tiny VAEs
  * Support z-image LoRA formats
  * Enable async offloading by default on Nvidia

  **Partner Nodes**

  * Veo3 First-Last-Frame Node
  * Add Kling v2.5 turbo to Kling FirstLastFrame node
  * Kling O1 model support
</Update>

<Update label="v0.3.75" description="November 26, 2025">
  **New Model Support**

  * Added Z Image model with optimized performance for image processing workflows

  **Bug Fixes**

  * Fixed LoRA functionality with mixed FP8 precision models
  * Enhanced Flux2 reference image memory estimation to reduce VRAM errors
</Update>

<Update label="v0.3.73" description="November 26, 2025">
  **Bug Fixes**

  * Fixed critical system crashes that could interrupt workflow execution
  * Optimized Flux 2 text encoder VRAM usage for better performance
</Update>

<Update label="v0.3.72" description="November 25, 2025">
  **New Model Support**

  * Added comprehensive Flux 2 model support including Flux 2 Pro API nodes
  * Enhanced HunyuanVideo workflows with new variants and improved display names

  **API & Security Improvements**

  * Improved API security with Content Security Policy headers
  * Fixed public API access issues and Gemini model support

  **Video Processing**

  * Added `get_frame_count` and `get_frame_rate` methods for better video workflow control

  **Performance Optimizations**

  * Optimized text encoder quantization with hardware-aware detection
  * Enhanced quantization support with better memory management

  **Developer Tools**

  * Added BlockInfo support for Chroma, Qwen-Image, and HunyuanVideo models

  **Frontend & Dependencies**

  * Updated frontend to v1.30.6
  * Bumped Transformers version
</Update>

<Update label="v0.3.71" description="November 21, 2025">
  **Model Compatibility & Enhancements**

  * **HunyuanVideo 1.5 Support**: Added compatibility for the latest version of HunyuanVideo models, expanding video generation capabilities
  * **LLAMA Text Encoder Improvements**: Added ability to disable final normalization in LLAMA-based text encoder models for better workflow customization
  * **HunyuanV3D Schema Migration**: Updated Hunyuan3D nodes to V3 schema for improved performance and compatibility

  **API Node Expansions**

  * **New Topaz API Nodes**: Added support for Topaz video enhancement workflows directly within ComfyUI
  * **Nano Banana Pro Integration**: Expanded API node collection with Nano Banana Pro for enhanced processing capabilities
  * **Kling Lip Sync Improvements**: Fixed audio format conversion issues in KlingLipSyncAudioToVideoNode, ensuring proper MP3 format handling

  **Image Processing & Workflow Improvements**

  * **Enhanced Image Batching**: Fixed ImageBatch node to handle images with different channel counts and automatically add alpha channels when needed
  * **Preview Node Refinement**: Renamed PreviewAny node to "Preview as Text" for clearer workflow organization
  * **Workflow Template Updates**: Enhanced server template handler to support multi-package distribution for better workflow management

  **Performance & System Optimizations**

  * **CUDA Optimization**: Disabled unnecessary workarounds on newer CUDNN versions for improved GPU performance
  * Fixed workflow naming issues and improved overall stability for complex processing pipelines
</Update>

<Update label="v0.3.70" description="November 19, 2025">
  **CUDA 12.6 Support & Distribution**

  * Added official CUDA 12.6 release workflow and portable download support for enhanced GPU compatibility
  * Updated README with corrected portable download links for streamlined installation

  **Model Compatibility & Fixes**

  * **HunYuan 3D 2.0 Support**: Fixed compatibility issues for improved 3D model generation workflows
  * **EasyCache Improvements**: Resolved input/output channel mismatches that affected certain model configurations
  * Enhanced block swap functionality by removing potentially harmful native custom node implementations

  **API Node Enhancements**

  * **New Gemini Models Added**: Expanded AI model options for text and multimodal generation workflows
  * Improved API node development infrastructure with updated PR templates and Python 3.10 minimum version requirements

  **Development & Infrastructure**

  * Enhanced pylint configuration for better code quality in custom node development
  * Improved release automation and distribution processes for more reliable updates
</Update>

<Update label="v0.3.69" description="November 18, 2025">
  **Memory & Performance Optimizations**

  * **Pinned Memory Enabled by Default** for NVIDIA and AMD GPUs
  * **Reduced VRAM Usage** for Flux, Qwen, and LTX-Video models
  * Smart model unloading that automatically frees memory when VRAM usage increases
  * Improved weight casting performance on offload streams

  **New Features**

  * **ScaleROPE Node Now Works with Flux Models**
  * Added left padding support to tokenizers
  * Added `create_time` field to `/history` and `/queue` endpoints

  **Bug Fixes**

  * Fixed custom node import errors for SingleStreamBlock/DoubleStreamBlock (temporary fix)
  * Fixed Qwen ControlNet regression
  * Enhanced quantized operations with offload support and stability improvements
  * Unified RoPE function implementation across models
</Update>

<Update label="v0.3.68" description="November 5, 2025">
  **Performance & Memory Optimizations**

  * Introduced **Mixed Precision Quantization System** for optimized model loading
  * Added **RAM Pressure Cache Mode** for intelligent memory management under resource constraints
  * Accelerated model offloading using pinned memory with automatic low-RAM hardware detection
  * Enhanced FP8 operations: reduced memory usage and fixed torch.compile performance regressions
  * Improved async offload speeds and resolved race conditions

  **New Nodes & Execution Features**

  * **ScaleROPE Node**: Rope scaling support for WAN and Lumina models
  * Enhanced subgraph execution allowing multiple runs within single workflows
  * Improved caching system with proper handling of bytes data and None outputs

  **API Node Enhancements**

  * Migrated API nodes to V3 client architecture: Luma, Minimax, Pixverse, Ideogram, StabilityAI, Pika, Recraft, Hypernetwork, OpenAI
  * Extended LTXV API nodes with 12s-20s duration options
  * Fixed img2img operations in DALL-E 2 node
  * Enhanced Rodin3D nodes to return proper relative paths

  **Updates**

  * Embedded documentation updated to v0.3.1
  * Workflow templates updated to v0.2.11
  * Fixed Windows pinned memory allocation issues
</Update>

<Update label="v0.3.67" description="October 28, 2025">
  **API Nodes**

  * **LTXV API Integration**: Added new LTXV API nodes for Lightricks LTX video generation
  * Network Client V2 upgrade with async operations and cancellation support
  * Converted Tripo and Gemini API nodes to V3 schema

  **Performance & Compatibility**

  * Improved AMD GPU support by only disabling cudnn on newer AMD GPUs
  * Fixed Windows-specific network issues in API nodes for better retry handling

  **Core Improvements**

  * Enhanced dependency-aware caching system that fixes --cache-none behavior with loops
  * Added support for multi-dimensional latents
  * Added custom node published subgraphs endpoint

  **Updates**

  * Frontend bumped to version 1.28.8
  * Template updates to version 0.2.4
</Update>

<Update label="v0.3.66" description="October 21, 2025">
  **Frontend Updates**

  * **Subgraph Widget Editing**: Edit subgraph parameters directly from new Parameters panel without entering the subgraph
  * **Template Modal Redesign**: New template browser with advanced filtering by model tags and categories

  **Performance Optimizations**

  * Iimproved workflow cancellation speed
  * Fixed VAE memory issue consuming 3x more on PyTorch 2.9 with NVIDIA GPUs
  * Enhanced chroma radiance processing speed and fixed batch size issues above 1

  **API Nodes**

  * Added Veo 3.1 model support
  * Added TemporalScoreRescaling node for advanced temporal control in video workflows

  **Hardware & Compatibility**

  * Disabled FP8 operations for AMD gfx942 GPUs
  * Improved CUDA memory management in --fast autotune mode

  **Execution & Schema**

  * Converted ControlNet nodes to V3 schema
  * Enhanced EasyCache with proper batch\_slice handling
  * Improved merge\_nested\_dicts functionality with proper input ordering
  * Added deprecation warnings for unused files
</Update>

<Update label="v0.3.65" description="October 14, 2025">
  **Node Schema Migration (V3)**

  * Migrated core node categories to V3 schema including model downscale, LoRA extraction, compositing, latent ops, SD3/SLG, Flux, upscale models, and HunyuanVideo nodes

  **Audio & Model Improvements**

  * Added MMaudio 16K VAE support for high-fidelity audio workflows
  * Fixed mono audio incorrectly saving as stereo
  * Refactored model sampling sigmas code and fixed FP8 scaled LoRA issues
  * Fixed loading of older Stable Diffusion checkpoints on newer NumPy versions

  **AMD GPU Optimizations**

  * Better memory estimation for SD/Flux VAE operations
  * Enabled RDNA4 PyTorch attention on ROCm 7.0+

  **API Node Updates**

  * Added price extractor and improvements to Kling/Pika API nodes
  * Enhanced Gemini Image API with aspect\_ratio support

  **Updates**

  * Template v0.1.95, node docs v0.3.0
  * Fixed WAN2.2 cache VRAM leak
</Update>

<Update label="v0.3.64" description="October 8, 2025">
  **API Nodes**

  * Added Sora2 API node for OpenAI's video generation API
</Update>

<Update label="v0.3.63" description="October 6, 2025">
  **Model Compatibility Enhancements**

  * **HunyuanVAE Support**: Added support for the new HunyuanVAE, expanding model compatibility for advanced image generation workflows
  * **Epsilon Scaling Node**: Introduced new Epsilon Scaling node that reduces exposure bias in diffusion models by scaling predicted noise, improving generation quality (based on the paper [Elucidating the Exposure Bias in Diffusion Models](https://arxiv.org/abs/2308.15321))

  **Memory and Performance Optimizations**

  * **VAE Memory Leak Fix**: Fixed VRAM leak caused by Python call stack holding tensor references during VAE OOM exception handling, significantly improving tiled fallback reliability on low VRAM devices
  * **AMD Support**: Enabled TORCH\_ROCM\_AOTRITON\_ENABLE\_EXPERIMENTAL by default

  **API Node Updates**

  * **Kling 2.5 Turbo**: Added support for kling-2-5-turbo in both txt2video and img2video nodes, with proper mode configuration fixes
  * **API Node Fixes**: Improved Gemini node base64 handling and fixed indentation issues in Recraft API node functions

  **Node Schema Migration (V3)**

  * **Extensive V3 Conversion**: Migrated numerous node categories to V3 schema including audio encoder, GITS, differential diffusion, optimal steps, PAG, LT, IP2P, morphology, torch compile, EPS, Pixverse, TomeSD, edit model, Rodin, and Stable3D nodes for improved workflow compatibility

  **Developer Experience Improvements**

  * **Code Quality**: Added pylint support for comfy\_api\_nodes folder and updated example\_node.py to use V3 schema, making custom node development more consistent
  * **Documentation Updates**: Enhanced AMD installation instructions with nightly PyTorch commands for Windows users

  **Frontend Updates**

  * **Subgraph Publish**: Allows publishing subgraphs to the node library
  * **Node Selection Toolbox Redesign**: Redesigned the node selection toolbox
</Update>

<Update label="v0.3.62" description="September 30, 2025">
  **API Node**

  * **Rodin3D-Gen2 Parameter Fix**
  * **Seedance Pro Model Support**
</Update>

<Update label="v0.3.61" description="September 30, 2025">
  **API Node**

  * **Rodin3D Gen-2**: Rodin's most powerful image-to-3D tool, is now live in ComfyUI!
  * **WAN Image-to-Image**: Wan2.5 Image-to-Image API node, support image editing.

  **Enhanced Audio Capabilities**

  * **New Audio Nodes**: Added new audio nodes for enhanced audio-driven workflows and multimodal content creation

  **Model Compatibility Fixes**

  * **Qwen2.5VL Template Handling**: Improved template management for Qwen2.5VL models when templates are already present in prompts
  * **HuMo View Operation**: Fixed .view() operation issues in HuMo models for more stable video generation

  **Memory and Performance Optimizations**

  * **Memory Leak Fix**: Resolved memory leaks by explicitly detaching model finalizers, improving long-running workflow stability
  * **Sampler CFG Enhancement**: Added 'input\_cond' and 'input\_uncond' parameters to sampler CFG function arguments for more flexible conditioning control
</Update>

<Update label="v0.3.60" description="September 23, 2025">
  **New Model Support**

  * **Wan2.2 Animate**: Support for Wan2.2 Animate video generation model with character replacement and motion transfer capabilities
  * **Qwen Image Edit 2509 Support**: Support for the updated Qwen Image Edit 2509 with multi-image editing, higher consistency, and native ControlNet support
  * **HuMo Models**: Added support for both 1.7B and 17B HuMo models that use audio to drive video generation while maintaining lip sync
  * **Chroma Radiance**: A model that performs image generation in pixel space, reducing losses during the image generation process
  * **Omnigen2 UMO LoRA**: Added support for Omnigen2 UMO LoRA models

  **API Node Additions**

  * **Kling v2.1 Support**: Added kling-v2-1 model to KlingStartEndFrame node
  * **Seedream4 Fixes**: Fixed the flag that ignores errors on partial success, making workflows more robust

  **Node Schema Migration (V3)**

  * **Core Node Updates**: Migrated multiple node categories to V3 schema including Minimax API, Cosmos, conditioning, CFG, and Canny nodes

  **Performance & Technical Improvements**

  * **FP8 Operations**: Enabled FP8 operations by default on gfx1200 hardware for faster processing
  * **LoRA Trainer Fixes**: Resolved bugs with FP8 model compatibility in LoRA training workflows

  **Frontend Updates**

  * **Frontend Version Update**: Updated to version 1.26.13
</Update>

<Update label="v0.3.59" description="September 10, 2025">
  **ByteDance Seedream 4.0 Integration**

  * **New Seedream Node**: Added ByteDanceSeedream (4.0) node.
</Update>

<Update label="v0.3.58" description="September 6, 2025">
  **New Model Support**

  * Hunyuan Image 2.1 regular model
  * Hunyuan 3D 2.1

  **New API Nodes**

  * Stable Audio 2.5 API
  * Seedance Video API
</Update>

<Update label="v0.3.57" description="September 4, 2025">
  **ByteDance USO Model Support**

  * **UXO Subject Identity LoRA Support**: It's a subject identity LoRA model based on FLUX architecture
  * **Related Workflow**: Please find the workflow in the template `Flux` -> `Flux.1 Dev USO Reference Image Generation`

  **Workflow Utilities**

  * **ImageScaleToMaxDimension Node**: New utility for intelligent image scaling
  * **SEEDS Noise System**: Updated noise decomposition with improved algorithms
  * **Enhanced Prompt Control**: Interrupt handler now accepts prompt\_id parameters

  **Performance & Architecture**

  * **V3 Schema Migration**: Converted some core nodes to V3 schema
  * **Convolution AutoTuning**: Enabled automatic convolution optimization

  **New API Integration**

  * **ByteDance Image Nodes**: Added support for ByteDance image generation services
  * **Ideogram Character Reference**: Ideogram v3 API now supports character reference
</Update>

<Update label="v0.3.56" description="August 30, 2025">
  **Performance Enhancement**

  * **Reduced RAM Usage on Windows**
</Update>

<Update label="v0.3.55" description="August 29, 2025">
  **Wan2.2 S2V Workflow Enhancements & Model Support Expansion**

  This release focuses on Wan2.2 S2V related video workflow capabilities and model support expansion:

  **Wan2.2 S2V Workflow Control**

  * **WanSoundImageToVideoExtend Node**: New manual video extension node for audio-driven video workflows, giving creators precise control over generated video length and timing. This enables fine-tuned control over how audio content translates to video sequences.
  * **Audio-Video Synchronization**: Fixed critical issue where extending video past audio length caused workflow failures, ensuring reliable sound-to-video generation regardless of audio duration.
  * **Automatic Audio Trimming**: Video saves now automatically trim audio to match video length, eliminating audio-video sync issues in final output files.

  **Advanced Latent Processing**

  * **LatentCut Node**: New node for cutting latents at precise points, enabling more granular control over latent space manipulation in complex generation workflows. This is particularly useful for batch processing and temporal video workflows, such as removing specific frames from videos.

  **Wan2.2 5B Model Integration**

  * **Fun Control Model Support**: Added support for Wan2.2 5B fun control model.
  * **Fun Inpaint Model Support**: Integrated Wan2.2 5B fun inpaint model.
</Update>

<Update label="v0.3.54" description="August 28, 2025">
  **Node Model Patch Improvements**

  This focused update improves the core node model patching system that underpins ComfyUI's flexible architecture:

  **Core Infrastructure Enhancement**

  * **Node Model Patch Updates**: Enhanced nodes\_model\_patch.py with improvements to the underlying model patching mechanism, making ComfyUI extensions for Qwen-Image ControlNet easier

  **Workflow Benefits**

  * **Enhanced Stability**: Core model patching improvements contribute to more reliable node execution and model handling across different workflow configurations
</Update>

<Update label="v0.3.53" description="August 28, 2025">
  **Audio Workflow Integration & Enhanced Performance Optimizations**

  This release adds ComfyUI audio processing capabilities and includes performance improvements and model compatibility updates:

  **Audio Processing Updates**

  * **Wav2vec2 Audio Encoder**: Added native wav2vec2 implementation as an audio encoder model, enabling audio-to-embedding workflows for multimodal applications
  * **Audio Encoders Directory**: Added models/audio\_encoders directory, which is the audio encoder directory for Wan2.2 S2V
  * **AudioEncoderOutput V3 Support**: Made AudioEncoderOutput compatible with V3 node schema, ensuring seamless integration with modern workflow architectures

  **Google Gemini API Integration**

  * **Gemini Image API Node**: Added new Google Gemini Image API node, the "nano-Nano-banana" image editing model API with high consistency

  **Video Generation Performance & Memory Optimizations**

  * **WAN 2.2 S2V Model Support**: Work-in-progress implementation of WAN 2.2 Sound-to-Video model with optimized memory usage and performance
  * **Enhanced S2V Performance**: Performance improvements for video generation longer than 120 frames, improving extended video workflows
  * **Better Memory Estimation**: Improved memory usage estimation for S2V workflows prevents out-of-memory errors during long video generation
  * **Negative Audio Handling**: Fixed negative audio input handling in S2V workflows to use proper zero values

  **Sampling & Node Enhancements**

  * **DPM++ 2M SDE Heun (RES) Sampler**: New advanced sampler by @Balladie provides additional sampling options for fine-tuned generation control
  * **LatentConcat Node**: New node for concatenating latent tensors, enabling advanced latent space manipulation workflows
  * **EasyCache/LazyCache Stability**: Fixed critical crashes when tensor properties (shape/dtype/device) change during sampling, ensuring workflow reliability

  **Model Compatibility Improvements**

  * **ControlNet Type Models**: Enhanced compatibility fixes for ControlNet-type models working with Qwen Edit and Kontext workflows
  * **Flux Memory Optimization**: Adjusted Flux model memory usage factors for better resource utilization

  **Infrastructure & Reliability**

  * **Template Updates**: Updated to versions 0.1.66 and 0.1.68
  * **Documentation Cleanup**: Removed incompletely implemented models from readme to avoid user confusion
</Update>

<Update label="v0.3.52" description="August 23, 2025">
  **Enhanced Model Support & Qwen Image ControlNet Integration**

  This release significantly expands ControlNet capabilities and improves model compatibility, making ComfyUI workflows more versatile and reliable:

  **Qwen ControlNet Ecosystem**

  * **Diffsynth ControlNet Support**: Added support for Qwen Diffsynth ControlNets with Canny and depth conditioning, enabling precise edge and depth-based image control
  * **InstantX Qwen ControlNet**: Integrated InstantX Qwen ControlNet for expanded creative control options
  * **Inpaint ControlNet/Model Patches**: Enhanced inpainting capabilities with dedicated Diffsynth inpaint ControlNet support

  **Node Architecture & API Evolution**

  * **V3 Architecture Migration**: String nodes, Google Veo API, and Ideogram API nodes upgraded to V3 architecture for better performance and consistency
  * **Enhanced API Nodes**: OpenAI Chat node renamed to "OpenAI ChatGPT" for clarity, Gemini Chat node now includes copy button functionality
  * **Improved Usability**: API nodes now provide better user experience with clearer labeling and enhanced interaction features

  **Workflow Reliability & Performance**

  * **LTXV Noise Mask Fix**: Resolved key frame noise mask dimension issues when real noise masks exist, ensuring stable video workflow execution
  * **3D Latent Conditioning Control**: Fixed conditioning masks on 3D latents, enabling proper depth-aware conditioning control in advanced workflows
  * **Invalid Filename Handling**: Improved workflow save functionality with proper handling of invalid filenames, preventing save failures
  * **EasyCache & LazyCache**: Implemented advanced caching systems for improved workflow execution performance

  **Platform & Development Improvements**

  * **Python 3.13 Support**: Full compatibility with Python 3.13, keeping ComfyUI current with latest Python developments
  * **Frontend Update**: Updated to v1.25.10 with improved navigation and user interface enhancements
  * **Elementwise Fusions**: Added performance optimizations through elementwise operations fusion
  * **Navigation Mode Rollback**: Rolled back navigation default to traditional legacy mode, avoiding user experience issues caused by default enabled standard navigation mode. Users can still enable standard navigation mode in settings
</Update>

<Update label="v0.3.51" description="August 20, 2025">
  **Model Support**

  * **Qwen-Image-Edit Model**: Native support for Qwen-Image-Edit
  * **FluxKontextMultiReferenceLatentMethod Node**: Multi-reference input node for Flux workflows
  * **WAN 2.2 Fun Camera Model Support**: Support for video generation through camera control
  * **Template Updates**: Upgraded to version 0.1.62, added Wan2.2 Fun Camera and Qwen Image Edit templates

  **Core Function Improvements**

  * **Context Windows Support**: Enhanced sampling code to support longer sequence generation tasks
  * **SDPA Backend Optimization**: Improved Scaled Dot Product Attention backend settings for better performance

  **Multimedia Node Support**

  * **Audio Recording Node**: New native audio recording node, now you can record audio directly in ComfyUI
  * **Audio Video Integration**: Complete audio-video dependency integration

  **API Node Support Updates**

  * **GPT-5 Series Models**: Support for the latest GPT-5 models
  * **Kling V2-1 and V2-1-Master**: Updated video generation model functionality
  * **Minimax Hailuo Video Node**: New video generation node
  * **Vidu Video Node**: Vidu API node support
  * **Google Model Updates**: Added new Google Gemini models
  * **OpenAI API Fix**: Fixed MIME type errors in OpenAI API node input images

  **Performance Optimization**

  * **Intel GPU Compatibility**: Fixed Intel integrated GPU compatibility issues
  * **PyTorch Compatibility**: Enhanced compatibility with older PyTorch versions
  * **Torch Compile Optimization**: Improved torch compile behavior
  * **Memory Management**: Optimized installation size and memory efficiency

  **Frontend Changes**

  * **Subgraph Support**: Subgraph functionality support
  * **Shortcut Panel**: Added bottom shortcut panel
  * **UI Layout Modifications**: Modified terminal entry layout, added template, log panel and other entries
  * **Standard Canvas Mode**: Added standard canvas mode, can be switched in `Lite Graph` > `Canvas` > `Canvas Navigation Mode`
  * **Mini Map**: Added workflow mini map
  * **Tab Preview**: Added workflow tab preview
  * **Top Tab Menu Layout Adjustments**
</Update>

<Update label="v0.3.50" description="August 13, 2025">
  **Model Integration & Performance Enhancements**

  This release expands ComfyUI's model ecosystem with enhanced Qwen support, async API capabilities, and stability improvements for complex workflows:

  **Qwen Model Ecosystem**

  * **Qwen Image Model Support**: Improved integration including proper LoRA loading and model merging capabilities for sophisticated vision workflows
  * **Qwen Model Merging Node**: New dedicated node for merging Qwen image models, allowing creators to combine different model strengths
  * **SimpleTuner Lycoris LoRA Support**: Extended compatibility with SimpleTuner-trained Lycoris LoRAs for Qwen-Image models

  **API & Performance Infrastructure**

  * **Async API Nodes**: Introduction of asynchronous API nodes, enabling non-blocking workflow execution for better performance
  * **Memory Handling**: Enhanced RepeatLatentBatch node now properly handles multi-dimensional latents, fixing workflow interruptions
  * **WAN 2.2 Fun Control Support**: Added support for WAN 2.2 fun control features, expanding creative control for video workflows

  **Hardware Optimization & Compatibility**

  * **AMD GPU Improvements**: Enhanced AMD Radeon support with improved FP16 accuracy handling and performance optimization
  * **RDNA3 Architecture Fixes**: Resolved issues with gfx1201 GPUs when using Flux models with PyTorch attention
  * **Updated PyTorch Support**: Bumped CUDA and ROCM PyTorch versions with testing on Python 3.13 and CUDA 12.9

  **Developer Experience Enhancements**

  * **Cleaner Logging**: Feature flags now only display in verbose mode, reducing console noise
  * **Audio Processing Safety**: Enhanced torchaudio import safety checks prevent crashes when audio dependencies are unavailable
  * **Kling API Improvements**: Fixed image type parameter handling in Kling Image API nodes

  **Workflow Benefits**

  * **Async Workflow Execution**: New async API capabilities enable more responsive workflows when integrating external services
  * **Model Flexibility**: Expanded Qwen support allows for more diverse vision-language workflows with improved LoRA compatibility
  * **Hardware Utilization**: AMD GPU optimizations and updated PyTorch support improve performance across hardware configurations
  * **Batch Processing**: Fixed RepeatLatentBatch ensures reliable operation with complex multi-dimensional data structures
  * **Video Control**: WAN 2.2 fun control features provide advanced creative control for video generation workflows
</Update>

<Update label="v0.3.49" description="August 5, 2025">
  **UI Experience & Model Support**

  This release brings user experience improvements and model support that enhance workflow creation and performance:

  **User Interface Enhancements**

  * **Recently Used Items API**: New API for tracking recently used items in the interface, streamlining workflow creation
  * **Workflow Navigation**: Enhanced user experience with better organization of commonly accessed elements

  **Model Integration**

  * **Qwen Vision Model Support**: Initial support for Qwen image models with configuration options
  * **Image Processing**: Enhanced Qwen model integration allows for more versatile image analysis and generation workflows

  **Video Generation**

  * **Veo3 Video Generation**: Added Veo3 video generation node with integrated audio support
  * **Audio-Visual Synthesis**: Capability combining video and audio generation in a single node

  **Performance & Stability Improvements**

  * **Memory Management**: Optimized conditional VRAM usage through improved casting and device transfer operations
  * **Device Consistency**: Fixes ensuring all conditioning data and context remain on correct devices
  * **ControlNet Stability**: Resolved ControlNet compatibility issues, restoring functionality for image control workflows

  **Developer & System Enhancements**

  * **Error Handling**: Added warnings and crash prevention when conditioning devices don't match
  * **Template Updates**: Multiple template version updates (0.1.47, 0.1.48, 0.1.51) maintaining compatibility

  **Workflow Benefits**

  * **Faster Iteration**: Recently used items API enables quicker workflow assembly and modification
  * **Enhanced Creativity**: Qwen vision models open new possibilities for image understanding and manipulation workflows
  * **Video Production**: Veo3 integration transforms ComfyUI into a comprehensive multimedia creation platform
  * **Reliability**: Memory optimizations and device management fixes ensure stable operation with complex workflows
  * **Performance**: Optimized VRAM usage allows for more ambitious projects on systems with limited resources
</Update>

<Update label="v0.3.48" description="August 2, 2025">
  **API Enhancement & Performance Optimizations**

  This release introduces backend improvements and performance optimizations that enhance workflow execution and node development:

  **ComfyAPI Core Framework**

  * **ComfyAPI Core v0.0.2**: Update to the core API framework, providing improved stability and extensibility
  * **Partial Execution Support**: New backend support for partial workflow execution, enabling efficient processing of multi-stage workflows

  **Video Processing Improvements**

  * **WAN Camera Memory Optimization**: Enhanced memory management for WAN-based camera workflows, reducing VRAM usage
  * **WanFirstLastFrameToVideo Fix**: Resolved issue preventing proper video generation when clip vision components are not available

  **Performance & Model Optimizations**

  * **VAE Nonlinearity Enhancement**: Replaced manual activation functions with optimized torch.silu in VAE operations
  * **WAN VAE Optimizations**: Fine-tuning optimizations for WAN VAE operations, improving processing speed and memory efficiency

  **Node Schema Evolution**

  * **V3 Node Schema Definition**: Implementation of next-generation node schema system
  * **Template Updates**: Multiple template version updates (0.1.44, 0.1.45) ensuring compatibility

  **Workflow Development Benefits**

  * **Video Workflows**: Improved stability and performance for video generation pipelines
  * **Memory Management**: Optimized memory usage patterns enable more complex workflows on systems with limited VRAM
  * **API Reliability**: Core API enhancements provide more stable foundation for custom node development
  * **Execution Flexibility**: New partial execution capabilities allow for more efficient debugging and development
</Update>

<Update label="v0.3.47" description="July 30, 2025">
  **Memory Optimization & Large Model Performance**

  This release focuses on memory optimizations for large model workflows, improving performance with WAN 2.2 models and VRAM management:

  **WAN 2.2 Model Optimizations**

  * **Reduced Memory Footprint**: Eliminated unnecessary memory clones in WAN 2.2 VAE operations, reducing memory usage
  * **5B I2V Model Support**: Memory optimization for WAN 2.2 5B image-to-video models, making these models more accessible

  **Enhanced VRAM Management**

  * **Windows Large Card Support**: Added reserved VRAM allocation for high-end graphics cards on Windows
  * **Memory Allocation**: Improved memory management for users working with multiple large models simultaneously

  **Workflow Performance Benefits**

  * **VAE Processing**: WAN 2.2 VAE operations now run more efficiently with reduced memory overhead
  * **Large Model Inference**: Enhanced stability when working with billion-parameter models
  * **Batch Processing**: Memory optimizations enable better handling of batch operations with large models
</Update>

<Update label="v0.3.46" description="July 28, 2025">
  **Hardware Acceleration & Audio Processing**

  This release expands hardware support and enhances audio processing capabilities:

  **Audio Processing Enhancements**

  * **PyAV Audio Backend**: Replaced torchaudio.load with PyAV for more reliable audio processing in video workflows
  * **Audio Integration**: Enhanced audio handling for multimedia generation workflows

  **Hardware Support**

  * **Iluvatar CoreX Support**: Added native support for Iluvatar CoreX accelerators
  * **Intel XPU Optimization**: XPU support improvements including async offload capabilities
  * **AMD ROCm Enhancements**: Enabled PyTorch attention by default for gfx1201 on Torch 2.8
  * **CUDA Memory Management**: Fixed CUDA malloc to only activate on CUDA-enabled PyTorch installations

  **Sampling Algorithm Improvements**

  * **Euler CFG++ Enhancement**: Separated denoised and noise estimation processes in Euler CFG++ sampler
  * **WAN Model Support**: Added support for WAN (Wavelet-based Attention Network) models

  **Training Features**

  * **Training Nodes**: Added algorithm support, gradient accumulation, and optional gradient checkpointing
  * **Training Flexibility**: Better memory management and performance optimization for custom model training

  **Node & Workflow Enhancements**

  * **Moonvalley V2V Node**: Added Moonvalley Marey V2V node with enhanced input validation
  * **Negative Prompt Updates**: Improved negative prompt handling for Moonvalley nodes
  * **History API Enhancement**: Added map\_function parameter to get\_history API

  **API & System Improvements**

  * **Frontend Version Tracking**: Added required\_frontend\_version parameter in /system\_stats API response
  * **Device Information**: Enhanced XPU device name printing for better hardware identification
  * **Template Updates**: Multiple template updates (0.1.40, 0.1.41) ensuring compatibility

  **Developer Experience**

  * **Documentation Updates**: Enhanced README with examples and updated model integration guides
  * **Line Ending Fixes**: Improved cross-platform compatibility by standardizing line endings
  * **Code Cleanup**: Removed deprecated code and optimized components
</Update>

<Update label="v0.3.45" description="July 21, 2025">
  **Sampling & Training Improvements**

  This release introduces enhancements to sampling algorithms, training capabilities, and node functionality:

  **Sampling & Generation Features**

  * **SA-Solver Sampler**: New reconstructed SA-Solver sampling algorithm providing enhanced numerical stability
  * **Experimental CFGNorm Node**: Classifier-free guidance normalization for improved control over generation quality
  * **Nested Dual CFG Support**: Added nested style configuration to DualCFGGuider node
  * **SamplingPercentToSigma Node**: New utility node for precise sigma calculation from sampling percentages

  **Training Capabilities**

  * **Multi Image-Caption Dataset Support**: LoRA training node now handles multiple image-caption datasets simultaneously
  * **Training Loop Implementation**: Optimized training algorithms for improved convergence and stability
  * **Error Detection**: Added model detection error hints for LoRA operations

  **Platform & Performance Improvements**

  * **Async Node Support**: Full support for asynchronous node functions with earlier execution optimization
  * **Chroma Flexibility**: Un-hardcoded patch\_size parameter in Chroma
  * **LTXV VAE Decoder**: Switched to improved default padding mode for better image quality
  * **Safetensors Memory Management**: Added workaround for mmap issues

  **API & Integration Enhancements**

  * **Custom Prompt IDs**: API now allows specifying prompt IDs for better workflow tracking
  * **Kling API Optimization**: Increased polling timeout to prevent user timeouts
  * **History Token Cleanup**: Removed sensitive tokens from history items
  * **Python 3.9 Compatibility**: Fixed compatibility issues ensuring broader platform support

  **Bug Fixes & Stability**

  * **MaskComposite Fixes**: Resolved errors when destination masks have 2 dimensions
  * **Fresca Input/Output**: Corrected input and output handling for Fresca model workflows
  * **Reference Bug Fixes**: Resolved incorrect reference bugs in Gemini node implementations
  * **Line Ending Standardization**: Automated detection and removal of Windows line endings

  **Developer Experience**

  * **Warning Systems**: Added torch import mistake warnings to catch common configuration issues
  * **Template Updates**: Multiple template version updates (0.1.36, 0.1.37, 0.1.39) for improved custom node development
  * **Documentation**: Enhanced fast\_fp16\_accumulation documentation
</Update>

<Update label="v0.3.44" description="July 8, 2025">
  **Sampling & Model Control Enhancements**

  This release delivers improvements to sampling algorithms and model control systems:

  **Sampling Capabilities**

  * **TCFG Node**: Enhanced classifier-free guidance control for more nuanced generation control
  * **ER-SDE Sampler**: Migrated from VE to VP algorithm with new sampler node
  * **Skip Layer Guidance (SLG)**: Implementation for precise layer-level control during inference

  **Development Tools**

  * **Custom Node Management**: New `--whitelist-custom-nodes` argument pairs with `--disable-all-custom-nodes`
  * **Performance Optimizations**: Dual CFG node now optimizes automatically when CFG is 1.0
  * **GitHub Actions Integration**: Automated release webhook notifications

  **Image Processing Improvements**

  * **Transform Nodes**: Added ImageRotate and ImageFlip nodes for enhanced image manipulation
  * **ImageColorToMask Fix**: Corrected mask value returns for more accurate color-based masking
  * **3D Model Support**: Upload 3D models to custom subfolders for better organization

  **Guidance & Conditioning Enhancements**

  * **PerpNeg Guider**: Updated with improved pre and post-CFG handling
  * **Latent Conditioning Fix**: Resolved issues with conditioning at index > 0 for multi-step workflows
  * **Denoising Steps**: Added denoising step support to several samplers

  **Platform Stability**

  * **PyTorch Compatibility**: Fixed contiguous memory issues with PyTorch nightly builds
  * **FP8 Fallback**: Automatic fallback to regular operations when FP8 operations encounter exceptions
  * **Audio Processing**: Removed deprecated torchaudio.save function dependencies

  **Model Integration**

  * **Moonvalley Nodes**: Added native support for Moonvalley model workflows
  * **Scheduler Reordering**: Simple scheduler now defaults first
  * **Template Updates**: Multiple template version updates (0.1.31-0.1.35)

  **Security & Safety**

  * **Safe Loading**: Added warnings when loading files unsafely
  * **File Validation**: Enhanced checkpoint loading safety measures
</Update>

<Update label="v0.3.43" description="June 30, 2025">
  **Model Support & Workflow Reliability**

  This release brings improvements to model compatibility and workflow stability:

  **Expanded Model Documentation**: Added support documentation for Flux Kontext and Omnigen 2 models
  **VAE Encoding Improvements**: Removed unnecessary random noise injection during VAE encoding
  **Memory Management Fix**: Resolved a memory estimation bug affecting Kontext model usage
</Update>

<Update label="v0.3.41" description="June 17, 2025">
  **Model Support Additions**

  * **Cosmos Predict2 Support**: Implementation for text-to-image (2B and 14B models) and image-to-video generation workflows
  * **Flux Compatibility**: Chroma Text Encoder now works with regular Flux models
  * **LoRA Training Integration**: New native LoRA training node using weight adapter scheme

  **Performance & Hardware Optimizations**

  * **AMD GPU Enhancements**: Enabled FP8 operations and PyTorch attention on AMD GPUs
  * **Apple Silicon Fixes**: Addressed FP16 attention issues on Apple devices
  * **Flux Model Stability**: Resolved black image generation issues with certain Flux models

  **Sampling Improvements**

  * **Rectified Flow Samplers**: Added SEEDS and multistep DPM++ SDE samplers with RF support
  * **ModelSamplingContinuousEDM**: New cosmos\_rflow option for enhanced sampling control
  * **Memory Optimization**: Improved memory estimation for Cosmos models

  **Developer & Integration Features**

  * **SQLite Database Support**: Enhanced data management capabilities for custom nodes
  * **PyProject.toml Integration**: Automatic web folder registration from pyproject files
  * **Frontend Flexibility**: Support for semver suffixes and prerelease frontend versions
  * **Tokenizer Enhancements**: Configurable min\_length settings with tokenizer\_data

  **Quality of Life Improvements**

  * **Kontext Aspect Ratio Fix**: Resolved widget-only limitation
  * **SaveLora Consistency**: Standardized filename format across all save nodes
  * **Python Version Warnings**: Added alerts for outdated Python installations
  * **WebcamCapture Fixes**: Corrected IS\_CHANGED signature
</Update>

<Update label="v0.3.40" description="June 5, 2025">
  **Workflow Tools & Performance Optimizations**

  This release brings new workflow utilities and performance optimizations:

  **Workflow Tools**

  * **ImageStitch Node**: Concatenate multiple images seamlessly in your workflows
  * **GetImageSize Node**: Extract image dimensions with batch processing support
  * **Regex Replace Node**: Advanced text manipulation capabilities for workflows

  **Model Compatibility**

  * **Tensor Handling**: Streamlined list processing makes multi-model workflows more reliable
  * **BFL API Optimization**: Refined support for Kontext models with cleaner node interfaces
  * **Performance Boost**: Fused multiply-add operations in chroma processing for faster generation

  **Developer Experience**

  * **Custom Node Support**: Added pyproject.toml support for better dependency management
  * **Help Menu Integration**: New help system in the Node Library sidebar
  * **API Documentation**: Enhanced API nodes documentation

  **Frontend & UI Enhancements**

  * **Frontend Updated to v1.21.7**: Stability fixes and performance improvements
  * **Custom API Base Support**: Better subpath handling for custom deployment configurations
  * **Security Hardening**: XSS vulnerability fixes

  **Bug Fixes & Stability**

  * **Pillow Compatibility**: Updated deprecated API calls
  * **ROCm Support**: Improved version detection for AMD GPU users
  * **Template Updates**: Enhanced project templates for custom node development
</Update>


# 3D Models
Source: https://docs.comfy.org/tutorials/partner-nodes/3d/overview

Generate textured 3D assets from text prompts or images with state-of-the-art 3D models through Partner Nodes in ComfyUI

## Overview

ComfyUI Partner Nodes give you access to 3D generation models that create textured meshes from text prompts or reference images.

### Browse 3D models

<CardGroup>
  <Card title="Hunyuan 3D 3.0" icon="cube" href="/tutorials/partner-nodes/hunyuan3d/hunyuan3d-3-0">
    Tencent's 3D generation model
  </Card>

  <Card title="Meshy 7" icon="cube" href="/tutorials/partner-nodes/meshy/meshy-7">
    Text-to-3D and image-to-3D with stylized and PBR-textured output
  </Card>

  <Card title="Meshy 6" icon="cube" href="/tutorials/partner-nodes/meshy/meshy-6">
    Text-to-3D and image-to-3D generation
  </Card>

  <Card title="Rodin" icon="cube" href="/tutorials/partner-nodes/rodin/model-generation">
    Reconstruct detailed 3D models from images, including characters
  </Card>

  <Card title="Tripo P2" icon="cube" href="/tutorials/partner-nodes/tripo/tripo-p2">
    Native quad-topology 3D generation with tiered texturing
  </Card>

  <Card title="Tripo P1" icon="cube" href="/tutorials/partner-nodes/tripo/tripo-p1">
    Fast text-to-3D and image-to-3D with clean topology
  </Card>

  <Card title="Tripo 3.1" icon="cube" href="/tutorials/partner-nodes/tripo/tripo-3-1">
    Text-to-3D and image-to-3D from Tripo
  </Card>

  <Card title="Tripo Model Generation" icon="cube" href="/tutorials/partner-nodes/tripo/model-generation">
    Tripo's model generation node
  </Card>
</CardGroup>

## What you can do with 3D models

* **Text-to-3D**: Generate a 3D asset from a text description
* **Image-to-3D**: Reconstruct a textured 3D model from one or more reference images
* **Export**: Download meshes for game engines, DCC tools, and 3D printing pipelines

## Choosing a model by task

### General-purpose 3D generation

* **Tripo P1 / Tripo 3.1** (Tripo) — fast text-to-3D and image-to-3D generation with clean topology
* **Meshy 7 / Meshy 6** (Meshy) — text-to-3D and image-to-3D with stylized and PBR-textured output
* **Hunyuan 3D 3.0** (Hunyuan 3D) — Tencent's 3D generation model

### Image-to-3D reconstruction

* **Rodin Model Generation** (Rodin) — reconstruct detailed 3D models from images, including human and character assets
* **Meshy 7** (Meshy) — image-to-3D with high texture fidelity

## All 3D partners

| Partner | Models |
| - | - |
| Hunyuan 3D | [Hunyuan 3D 3.0](/tutorials/partner-nodes/hunyuan3d/hunyuan3d-3-0) |
| Meshy | [Meshy 7](/tutorials/partner-nodes/meshy/meshy-7), [Meshy 6](/tutorials/partner-nodes/meshy/meshy-6) |
| Rodin | [Rodin](/tutorials/partner-nodes/rodin/model-generation) |
| Tripo | [Tripo P2](/tutorials/partner-nodes/tripo/tripo-p2), [Tripo P1](/tutorials/partner-nodes/tripo/tripo-p1), [Tripo 3.1](/tutorials/partner-nodes/tripo/tripo-3-1), [Tripo Model Generation](/tutorials/partner-nodes/tripo/model-generation) |

See [Pricing](/tutorials/partner-nodes/pricing) for per-model rates, and [Concurrency Limits](/tutorials/partner-nodes/concurrency-limits) for usage caps.


# Anthropic Claude Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/anthropic/claude

This article will introduce how to use Anthropic Claude Partner nodes in ComfyUI to complete conversational functions

Anthropic Claude is a family of powerful AI models known for strong reasoning, safety, and long-context capabilities. ComfyUI has integrated the Anthropic Claude API through Partner Nodes, allowing you to use Claude directly in your workflows for conversational and image analysis tasks.

## What Anthropic Claude is good at

* **Strong reasoning**: A model family known for strong reasoning, safety, and long-context capabilities
* **Conversational and image analysis tasks**: Use Claude directly inside your ComfyUI workflows through Partner Nodes
* **Multimodal input**: Every supported model accepts text-only and text + image inputs, with up to 20 images per request
* **A model for every workload**: From the flagship Opus line to fast, cost-effective Haiku for high-throughput use cases

## Supported Models

| Model | Strengths |
| - | - |
| **Opus 5.5** | Anthropic's newest flagship and the successor to Opus 5. Built for demanding reasoning, coding, and long-horizon agentic work, and priced below Opus 5. Thinking is always enabled, and `temperature` is unavailable. |
| **Opus 5** | Anthropic's previous flagship, released July 24, 2026. Priced at half the rate of Claude Fable 5.1 while offering comparable performance on coding and knowledge work tasks. |
| **Fable 5.1** | Anthropic's advanced reasoning model, released September 1, 2026. An update to Fable 5 with lower agentic workload costs and fewer false positives. Thinking is always enabled, and `temperature` is unavailable. |
| **Sonnet 5** | Anthropic's mid-tier model, released June 30, 2026. Designed for autonomous, agentic tasks at a lower price point than the Opus line. `temperature` is unavailable. |
| **Opus 4.8** | Previous generation flagship with strong all-around performance. |
| **Opus 4.7** | Anthropic's most capable model. Step-change improvement in agentic coding, complex reasoning, and nuanced analysis. 1M context window. Knowledge cutoff: Jan 2026. |
| **Opus 4.6** | Previous generation flagship with strong all-around performance. 1M context window. |
| **Sonnet 4.6** | Best balance of speed and intelligence for most workloads. 1M context window. Fast latency. |
| **Sonnet 4.5** | Fast and capable, good for everyday tasks. 200k context window. |
| **Haiku 4.5** | Fastest and most cost-effective option for simple queries and high-throughput use cases. 200k context window. |

All models support both text-only and multimodal (text + image) inputs with up to 20 images per request.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Anthropic Claude Chat Workflow

<img alt="Anthropic Claude Chat workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_anthropic_claude&utm_source=docs&utm_medium=referral&utm_campaign=claude">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_anthropic_claude.json">
    Download JSON or search "Anthropic Claude" in Template Library
  </Card>
</CardGroup>

<Note>
  In the corresponding template, we have built a prompt for analyzing and generating role prompts, used to interpret your images into corresponding drawing prompts.
</Note>

Refer to the numbered steps in the workflow image to complete the basic workflow execution:

1. In the `Load Image` node, load the image you need AI to interpret (optional: skip for text-only queries)
2. In the `Anthropic Claude` node, modify `prompt` to set your conversation prompt, or change `model` to select a different Claude model
3. (Optional) Set the `system_prompt` to define the model's behavioral instructions
4. Click `Run` or press `Ctrl(cmd) + Enter` to execute the conversation
5. After the API returns results, view the AI response in the `Preview Any` node

### Additional Notes

* Adjust `max_tokens` (up to 32768) and `temperature` (0.0 to 1.0) in the node's advanced options. `temperature` is unavailable when thinking is enabled, or on `Opus 4.7`
* The `seed` parameter controls whether the node re-runs: results are non-deterministic regardless of seed value

## Claude Fable 5.1 Workflow

Run Claude Fable 5.1, Anthropic's advanced reasoning model, directly in your workflow for long-running, multi-step problems. Fable 5.1 always runs with thinking enabled and does not expose a `temperature` control.

![Claude Fable 5.1 workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_anthropic_claude_fable5_1-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_anthropic_claude_fable5_1&utm_source=docs&utm_medium=referral&utm_campaign=claude">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_anthropic_claude_fable5_1.json">
    Download JSON or search "Claude: Fable 5.1" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Input Image: blue_poppies_field.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/blue_poppies_field.png">
    Image for the workflow, or use your own image.
  </Card>
</CardGroup>

Refer to the numbered steps in the workflow image:

1. In the `Load Image` node, load the image you need AI to interpret (optional: skip for text-only queries)
2. In the `Anthropic Claude` node, modify `prompt` to set your conversation prompt. The model is preset to `Fable 5.1` with a 32768 `max_tokens` limit
3. Click `Run` or press `Ctrl(cmd) + Enter` to execute the conversation
4. After the API returns results, view the AI response in the `Preview Any` node


# Audio Models
Source: https://docs.comfy.org/tutorials/partner-nodes/audio/overview

Generate speech, music, and sound effects with state-of-the-art audio models through Partner Nodes in ComfyUI

## Overview

ComfyUI Partner Nodes give you access to audio generation models for music, speech, and sound effects.

### Browse audio models

<CardGroup>
  <Card title="Seed Audio 1.0" icon="music" href="/tutorials/partner-nodes/bytedance/seed-audio-1-0">
    Text-to-audio and text-to-music, including instrumental and vocal tracks
  </Card>

  <Card title="Sonilo" icon="music" href="/tutorials/partner-nodes/sonilo/video-to-music">
    Generate a full soundtrack that matches a video's rhythm and content
  </Card>
</CardGroup>

## What you can do with audio models

* **Text-to-audio**: Generate music or sound effects from a text description
* **Video-to-music**: Create a soundtrack that matches a video's content and pacing
* **Voice & speech**: Generate speech or singing from text and reference audio

## Choosing a model by task

### Music & soundtracks

* **Seed Audio 1.0** (ByteDance) — text-to-audio and text-to-music generation, including instrumental and vocal tracks
* **Sonilo** (Sonilo) — generate a full soundtrack from a video: it analyzes the video's rhythm and content to produce a matching score

### Sound effects & utility

* **Seed Audio 1.0** (ByteDance) — also supports sound effects and audio-style transfer

## All audio partners

| Partner | Models |
| - | - |
| ByteDance | [Seed Audio 1.0](/tutorials/partner-nodes/bytedance/seed-audio-1-0) |
| Sonilo | [Sonilo](/tutorials/partner-nodes/sonilo/video-to-music) |

See [Pricing](/tutorials/partner-nodes/pricing) for per-model rates, and [Concurrency Limits](/tutorials/partner-nodes/concurrency-limits) for usage caps.


# FLUX 3 Video - AI video generation with native audio
Source: https://docs.comfy.org/tutorials/partner-nodes/black-forest-labs/flux-3-video

Generate videos with synchronized audio using FLUX 3 in ComfyUI, from text or images, with up to 20 seconds of footage in a single pass

FLUX 3 is Black Forest Labs' multimodal foundation model, announced July 23, 2026 and currently in Early Access. It jointly learns from images, videos, and audio within a unified architecture built on Self-Flow, their approach for aligning multimodal generation and understanding in the same model. Instead of treating each modality in isolation, FLUX 3 learns a shared representation of the world: how objects hold together, how things move, and how events sound. Capabilities and limits may change during the Early Access rollout.

For video, FLUX 3 creates highly diverse clips with native audio up to 20 seconds long in a single generation. All outputs come with synchronized audio generation, including ambient sound, speech, and effects. It supports text-to-video and image-to-video generation, with multi-shot output that chains individual clips into longer sequences and flexible aspect ratios.

## What FLUX 3 Video is good at

* **Native audio**: Every video comes with synchronized audio, including ambient sound, speech, and effects
* **Up to 20 seconds**: Generates long clips in a single pass
* **Text and image input**: Generates video from a text prompt, or continues from a starting frame image
* **Flexible formats**: 720p or 1080p resolution, 24fps, aspect ratios from 9:16 to 21:9
* **Multi-shot output**: Chains individual clips into longer sequences for extended storytelling

## Example outputs

Text-to-video generation from a single prompt, with synchronized audio, motion, and physics:

<video />

Image-to-video generation from a starting frame and a text prompt:

<video />

## Use it

<Card title="Call it from code" icon="code" href="/development/comfy-router/models/black-forest-labs/flux-3-video/code">
  Call it over HTTP through Comfy Router, with copy-paste Python, TypeScript, Swift and cURL snippets
</Card>

This runs on the same Comfy account and is billed in the same credits as running it in ComfyUI below. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for per-model rates and [Concurrency limits](/tutorials/partner-nodes/concurrency-limits) for how many requests you can have in flight.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## FLUX 3 text-to-video workflow

Generate a full video from a single text prompt. FLUX 3 expands natural language into a complete scene with synchronized audio, motion, and physics, without needing reference images or complex settings.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bfl_flux3_t2v&utm_source=docs&utm_medium=referral&utm_campaign=flux-3-video">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bfl_flux3_t2v.json">
    Download JSON or search "FLUX 3 Video" in Template Library
  </Card>
</CardGroup>

## FLUX 3 image-to-video workflow

Generate a full video from a text prompt and a starting frame image. FLUX 3 automatically expands your description into a cohesive scene with synchronized audio, motion, and physics.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bfl_flux3_i2v&utm_source=docs&utm_medium=referral&utm_campaign=flux-3-video">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bfl_flux3_i2v.json">
    Download JSON or search "FLUX 3 Video" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/space_caravan.png">
      Download sample input image
    </Card>
  </CardGroup>
</details>

![FLUX 3 image to video input](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/space_caravan.png)

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `FLUX 3 Video`


# FLUX Video Edit: Text-Prompt Video Editing in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/black-forest-labs/flux-video-edit

Edit an existing clip in ComfyUI with the FLUX Video Edit partner node: swap objects, restyle footage, or change on-screen text and dialogue.

FLUX Video Edit is Black Forest Labs' text-driven video editing endpoint, available in ComfyUI as a partner node. You give it a source clip and a plain-language instruction, and it rewrites the footage to match that instruction.

The edit changes what happens in the shot, not how it is shot. Length, framing, camera motion, and the audio track all come from the source clip, so the result cuts back into your edit without resynchronizing anything. That makes it useful for removing, adding, or replacing objects, restyling footage, changing the setting, rewriting on-screen text, and replacing spoken dialogue.

The node runs entirely on Black Forest Labs' servers through the Comfy API. No model downloads or local GPU are required; you need a Comfy API account with credits.

## What FLUX Video Edit is good at

* **Instruction only**: Describes the change in words, with no masks, no reference images, and no control inputs
* **Structure preserved**: Length, framing, camera motion, and audio come from the source clip
* **Object-level edits**: Removes, adds, or replaces objects, characters, and background elements
* **Restyling**: Changes the look, lighting, or setting of footage you already have
* **Text and dialogue**: Rewrites on-screen text and replaces spoken lines
* **Up to 15 seconds**: Accepts source clips from 0.7 to 15 seconds

## Example output

Replacing the performer in an existing clip while keeping the pose, lighting, and camera:

<video />

## Use it

<Card title="Call it from code" icon="code" href="/development/comfy-router/models/black-forest-labs/video-edit-v1/code">
  Call it over HTTP through Comfy Router, with copy-paste Python, TypeScript and cURL snippets
</Card>

This runs on the same Comfy account and is billed in the same credits as running it in ComfyUI below. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for per-model rates and [Concurrency limits](/tutorials/partner-nodes/concurrency-limits) for how many requests you can have in flight.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## FLUX Video Edit workflow

Edit a clip you already have: load the video, describe the change in the prompt, then run. The workflow sends the clip to Black Forest Labs through the FLUX Video Edit partner node and writes the edited clip back through `SaveVideo`.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_flux_video_edit&utm_source=docs&utm_medium=referral&utm_campaign=flux-video-edit">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_flux_video_edit.json">
    Download JSON or search "Flux Video Edit" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/subway_musician.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>

## Writing the edit instruction

The prompt is the only creative control, so it is worth writing carefully:

* Describe only what changes on screen. Anything you do not mention is meant to stay as it was.
* Name the subject and the outcome in the same sentence, for example "replace the guitarist with a gorilla in the same pose".
* Write the instruction in plain language, up to 4096 characters. Detail about shape, material, or action roughly maps to how much the model changes.
* Keep replacement dialogue close to the length of the original speech, since the new line has to fit the time the original speech takes. A silent clip stays silent.
* The seed does not make a run reproducible. FLUX picks its own seed, so the same instruction on the same clip can come back different.

## Node options reference

| Option | Values | Default | Notes |
| - | - | - | - |
| `video` | source clip | required | 0.7 to 15 seconds, at least 160x160 pixels |
| `prompt` | text | empty | What to change, in plain language, up to 4096 characters |
| `auto_downscale` | on / off | on | Downscales sources larger than 1280x704 in area before upload, preserving aspect ratio |
| `safety_tolerance` | 0 to 4 | 4 | Advanced. Moderation tolerance, `0` is the strictest |
| `seed` | 0 to 4294967295 | 42 | FLUX picks its own seed, so results are nondeterministic regardless of this value |

## Limits

* Source clips run from 0.7 to 15 seconds and must be at least 160x160 pixels.
* The output is rendered at 24 fps and capped at about 0.9 megapixels per frame (1280x704), so a larger source comes back smaller.
* Billing is per second of clip. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing).

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `Flux Video Edit`


# FLUX Video Upscale: AI video upscaling to 4K in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/black-forest-labs/flux-video-upscale

Upscale video to 1080p, 2K, or 4K with the FLUX Video Upscale partner node in ComfyUI. Precise mode preserves the source; creative mode adds fine detail.

FLUX Video Upscale is Black Forest Labs' FLUX 3 powered super-resolution tool for video, available in ComfyUI as a partner node. It upscales clips to 1080p, 2K, or 4K while keeping the source aspect ratio and its audio track.

## What FLUX Video Upscale is good at

* **Upscale to 4K**: Raises video resolution to 1080p, 2K, or 4K in a single API call
* **Two modes**: Precise mode preserves the source exactly; creative mode restores and invents fine detail
* **Audio preserved**: The output keeps the source clip's audio track
* **Up to 20 seconds**: Accepts clips up to 20 seconds at up to 2560x1440 source resolution

## Example outputs

Upscaling an existing clip while keeping its aspect ratio and audio track:

<video />

## Use it

<Card title="Call it from code" icon="code" href="/development/comfy-router/models/black-forest-labs/flux-video-upscale/code">
  Call it over HTTP through Comfy Router, with copy-paste Python, TypeScript, Swift and cURL snippets
</Card>

This runs on the same Comfy account and is billed in the same credits as running it in ComfyUI below. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for per-model rates and [Concurrency limits](/tutorials/partner-nodes/concurrency-limits) for how many requests you can have in flight.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## FLUX Video Upscale workflow

Upscale an existing video clip: load the video, choose a mode and upscale factor, then run. The workflow uses the FLUX Video Upscale partner node to process the clip through the Black Forest Labs API.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bfl_flux_video_upscale&utm_source=docs&utm_medium=referral&utm_campaign=flux-video-upscale">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bfl_flux_video_upscale.json">
    Download JSON or search "FLUX Video Upscale" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/color_spin_flower.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>

## Precise or creative mode

The node's **mode** option selects how the upscaler treats your footage:

* **Precise**: Sharpens the source without changing it. Use when identity matters: faces, products, brand assets, and footage of real people.
* **Creative (default)**: Restores and invents fine detail. Best for generated footage, textures, crowds, and scenery. Identity is not preserved as strictly, so faces and products can drift.

## Prompt tips

* Start from the least compressed source you have. Compression artifacts limit how much real detail the upscaler can recover.
* Use creative mode for generated footage, landscapes, textures, and crowds; use precise mode when faces, products, or brand assets must stay exactly as they are.
* A short prompt describing the clip's content can steer creative mode toward the right kind of detail, for example "detailed armor plating and reptilian skin texture". Leave it empty for a neutral upscale.
* The prompt does not change the clip's content. It only steers the enhanced detail, so no action chains, camera moves, or audio cues are needed.
* Run upscaling as your final step, after editing and trimming, so you only pay for footage you keep.

## Limits

* Input clips are limited to 1 to 20 seconds, at least 64px, with an aspect ratio between 1:4 and 4:1. Sources larger than 3840x2160 in area need **auto\_downscale** enabled.
* The upscale factor ranges from 1.5x to 3x, and the output keeps the source aspect ratio. Very large sources are upscaled by less than requested.
* Output is 24 fps, capped at about 14.4 megapixels per frame, and keeps the source audio track.

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `FLUX Video Upscale`


# ByteDance Seed Audio 1.0 - Universal Audio Generation
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/seed-audio-1-0

Generate speech, music, sound effects, and multi-speaker dialogue from one prompt with voice cloning and preset voices using Seed Audio 1.0 in ComfyUI

Seed Audio 1.0 is ByteDance's universal audio generation model, now available as a built-in node in ComfyUI. Unlike traditional text-to-speech systems that only read words aloud, Seed Audio understands the full spectrum of sound. It can generate speech, music, sound effects, ambient atmospheres, and multi-speaker dialogue from a single text prompt.

## What Seed Audio 1.0 is good at

* **Multi-modal audio generation**: Speech, music, sound effects, and ambient audio from one prompt. Describe what you hear, and Seed Audio produces it
* **Voice cloning**: Clone voices from up to 3 reference clips (tagged `@Audio1`, `@Audio2`, `@Audio3` in the prompt) for multi-character dialogue or consistent narration
* **Preset voices**: Pick from built-in TTS 2.0 voices when you need reliable, high-quality narration without a reference clip
* **Image-driven voice**: Derive a voice from a character image, matching the tone and style to the visual subject
* **Fine-grained control**: Adjust speech rate, pitch, loudness, and sample rate independently for each generation
* **Multi-speaker dialogue**: Name characters inline in the prompt and Seed Audio handles voice assignment, turn-taking, and emotional delivery
* **Up to 2 minutes per run**: Generate extended audio clips suitable for narration, podcast clips, video dubbing, and sound design

With these capabilities, Seed Audio 1.0 fits a wide range of use cases including video voiceovers, multi-character audio dramas, product demos, e-learning narration, game audio prototyping, and accessibility content.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Available workflows

### Seed Audio 1.0: Text to Audio

Input a text prompt to generate speech, dialogue, background music, and sound effects in one audio file.

<img alt="Seed Audio 1.0: Text to Audio workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_seed_audio1_0_t2a&utm_source=docs&utm_medium=referral&utm_campaign=seed-audio-1-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_seed_audio1_0_t2a.json">
    Download JSON or search "Seed Audio 1.0: Text to Audio" in Template Library
  </Card>
</CardGroup>

### Seed Audio 1.0: Text + Audio to Audio

Upload a reference audio clip and write a text prompt to clone the voice into a new scene.

<img alt="Seed Audio 1.0: Text + Audio to Audio workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_seed_audio1_0_ta2a&utm_source=docs&utm_medium=referral&utm_campaign=seed-audio-1-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_seed_audio1_0_ta2a.json">
    Download JSON or search "Seed Audio 1.0: Text + Audio to Audio" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadAudio` node:

<CardGroup>
  <Card title="seed_audio_ref_audio1.mp3" icon="music" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/seed_audio_ref_audio1.mp3">
    `LoadAudio` node 8 · `seed_audio_ref_audio1.mp3`
  </Card>
</CardGroup>

### Seed Audio 1.0: Text + Image to Audio

Upload a character image and write a text prompt to generate audio with a voice style matching the visual subject.

<img alt="Seed Audio 1.0: Text + Image to Audio workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_seed_audio1_0_ti2a&utm_source=docs&utm_medium=referral&utm_campaign=seed-audio-1-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_seed_audio1_0_ti2a.json">
    Download JSON or search "Seed Audio 1.0: Text + Image to Audio" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="girl_and_fish.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/girl_and_fish.png">
    `LoadImage` node 6 · `girl_and_fish.png`
  </Card>
</CardGroup>

<div>
  <img alt="girl_and_fish.png" />
</div>

## How to use Seed Audio 1.0 in ComfyUI

Seed Audio 1.0 ships as the **ByteDanceSeedAudio** built-in node. You can find it in the node menu under ByteDance.

### Choosing a reference mode

The node offers four reference modes that determine how the generated voice is conditioned:

| Mode | Description | When to use |
| - | - | - |
| **Text only** | Describe everything (voice style, emotion, ambience, and dialogue) in the prompt | Quick generation with no reference material |
| **Audio reference** | Connect up to 3 reference audio clips (30s max each) and tag them as `@Audio1`, `@Audio2`, `@Audio3` in the prompt | Cloning specific voices or creating multi-character dialogue |
| **Image reference** | Connect one character image; the model derives a voice from it | Deriving a voice from a visual character design |
| **Preset voice** | Select a built-in TTS 2.0 voice from the dropdown | Reliable narration without cloning |

### Prompt structure

For best results, structure your prompt to describe the audio scene:

* **Voice and emotion**: Describe the tone, age, gender, accent, or emotional delivery
* **Ambience and background**: Describe the acoustic environment (quiet studio, busy street, concert hall)
* **Sound effects**: Describe specific sounds at the right moment in the timeline
* **Dialogue lines**: Write the lines to speak, naming characters for multi-speaker scenes

**Example: narration with ambience**

> A calm, warm male voice speaks confidently. Soft rain falls in the background, with occasional distant thunder. "Seed Audio 1.0 generates natural speech with full control over pacing, pitch, and presence."

**Example: multi-speaker dialogue with audio references**

> @Audio1 says nervously in a low, fast whisper: "Did you see that?" @Audio2 replies in a calm, slow drawl: "See what? It's just the wind." Light wind ambience throughout.

### Parameter tuning

After connecting your inputs, tune these parameters for the desired output:

* **Speech rate**: Default 0 (normal). Range -50 (0.5x) to 100 (2.0x). Use negative values for relaxed narration, positive for energetic voiceovers
* **Pitch**: Shift in semitones (-12 to +12). Useful for character voices or matching a specific vocal range
* **Loudness**: Default 0 (normal). Range -50 (0.5x) to 100 (2.0x). Adjust for consistent volume across different source materials
* **Sample rate**: Choose from 8kHz to 48kHz. 24kHz is a good default for speech; 44.1kHz or 48kHz for music
* **Seed**: Controls whether the node reruns; results are non-deterministic regardless of seed value

### Edge cases and limitations

* **Reference clip duration**: Audio reference clips are limited to 30 seconds each. For longer reference material, trim or edit the clip before connecting
* **Audio reference ordering**: Reference inputs must be connected sequentially (1, 2, 3) without gaps
* **Tag limit**: A maximum of 3 `@AudioN` tags are supported in a single prompt
* **Character limit**: Prompts are limited to 3000 characters
* **Duration limit**: Maximum 2 minutes of audio per run

## Get started

1. Update ComfyUI to the latest version
2. Add the **ByteDanceSeedAudio** node from the node menu, or open one of the workflow templates above
3. Choose your reference mode and connect inputs
4. Write your prompt describing the audio scene and dialogue
5. Run the workflow


# Seedance 2.0 - AI video generation
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/seedance-2-0

Generate video from text, images, video, and audio with Seedance 2.0 in ComfyUI: synced audio, consistent characters, and cinematic camera control.

Seedance 2.0 is ByteDance's next-generation multimodal video generation model, now available inside ComfyUI. It accepts text, images, video, and audio as unified inputs and produces high-quality video with synced audio, consistent characters, and cinematic camera motion in a single pass.

## What Seedance 2.0 is good at

* **Multimodal in**: Prompt with text plus images, video, and audio
* **Audio-video sync**: Generate video and audio together
* **Directing control**: Camera moves and shot pacing stay controllable
* **Consistency**: Keep characters and scenes stable across a clip
* **Editing + extend**: Edit footage or extend clips without starting over

With these capabilities, Seedance 2.0 fits a wide range of use cases including advertising, short-form drama, film previsualization, product showcases, virtual character content, and assets for games and animation.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Available workflows

### Text to video (T2V)

Generate a video from a text prompt, with Seedance 2.0 handling scene, motion, and pacing.

<img alt="Seedance 2.0 Text-to-Video workflow preview" />

<CardGroup>
  <Card title="Run Text-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_t2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-0">
    Try the Text-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Text-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_t2v.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

### Reference to video (R2V)

Use reference images, video, or audio to guide look, motion, and rhythm while keeping results coherent.

<img alt="Seedance 2.0 Reference-to-Video workflow preview" />

<CardGroup>
  <Card title="Run Reference-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_r2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-0">
    Try the Reference-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Reference-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_r2v.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="Outfit reference 1" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/sd_outfit_1.png">
      Download sample outfit image 1
    </Card>

    <Card title="Outfit reference 2" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/sd_outfit_2.png">
      Download sample outfit image 2
    </Card>

    <Card title="Outfit reference 3" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/sd_outfit_3.png">
      Download sample outfit image 3
    </Card>

    <Card title="Subject reference" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/selfie_cartoon_style.png">
      Download sample subject reference
    </Card>
  </CardGroup>
</details>

### First-last-frame to video (FLF2V)

Provide a starting frame and ending frame, and Seedance 2.0 generates the motion and transitions between them.

<img alt="Seedance 2.0 FLF2V workflow preview" />

<CardGroup>
  <Card title="Run FLF2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_flf2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-0">
    Try the First-Last-Frame-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download FLF2V workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_flf2v.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="First frame" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/sd_first_frame.png">
      Download sample first frame
    </Card>

    <Card title="Last frame" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/sd_last_frame.png">
      Download sample last frame
    </Card>
  </CardGroup>
</details>

### Reference to video 4K (R2V 4K)

Generate 4K video from reference images with Seedance 2.0. The 4K workflow follows the same reference flow as standard R2V: provide subject, outfit, or scene references, and the model renders the final clip at 4K resolution for large screens and post-production crops.

<img alt="Seedance 2.0 Reference-to-Video 4K workflow preview" />

<CardGroup>
  <Card title="Run Reference-to-Video 4K on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_r2v_4k&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-0">
    Try the Reference-to-Video 4K workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Reference-to-Video 4K workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_r2v_4k.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Subject reference" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/green_rider.png">
      Download sample subject reference
    </Card>
  </CardGroup>
</details>

### Storyboard to video

Turn a storyboard into video in two passes. First, generate the storyboard: Nano Banana 2 and GPT Image draw each panel, a Gemini node writes the shot descriptions, and ImageStitch assembles the panel sheet. Then, feed the finished storyboard into Seedance 2.0 to animate it into a video with synced audio.

Both steps live in one workflow. Use [Partial Execution](/interface/features/partial-execution) to run the storyboard group first, swap the bypass to the Seedance group, then run the animation pass.

<img alt="Seedance 2.0 Storyboard to Video workflow preview" />

<CardGroup>
  <Card title="Run Storyboard to Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=template_seedance2_storyboard_to_video&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-0">
    Try the Storyboard to Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Storyboard to Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/template_seedance2_storyboard_to_video.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="Storyboard input" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/storyboard_input.png">
      Download sample storyboard input
    </Card>

    <Card title="Subject reference" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/ninja.png">
      Download sample subject reference
    </Card>
  </CardGroup>
</details>

## Seedance 2.0 Mini

Seedance 2.0 Mini is a lighter, faster variant of Seedance 2.0 for everyday video generation. It keeps the same audio-video sync, character consistency, and camera control as the full model, at a lower per-run cost.

Mini ships as two workflows today: Text-to-Video and Reference-to-Video. Both are tuned for quick iteration on multi-shot storytelling, branded content, and short film creation.

<Note>
  Seedance 2.0 Mini is on the same `Seedance 2.0` pricing line as the full model. See the [Seedance 2.0 pricing entries](/tutorials/partner-nodes/pricing#bytedance) for current rates.
</Note>

### Seedance 2.0 Mini text-to-video

Generate a cinematic video from a text prompt with AI camera controls and consistent character generation across scenes.

<img alt="Seedance 2.0 Mini Text-to-Video workflow preview" />

<CardGroup>
  <Card title="Run Seedance 2.0 Mini T2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_mini_t2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-0">
    Try the Mini Text-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Seedance 2.0 Mini T2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_mini_t2v.json">
    Download the workflow JSON or search "Seedance 2.0 Mini" in Template Library.
  </Card>
</CardGroup>

### Seedance 2.0 Mini reference-to-video

Generate a cinematic video from two reference images (subject + scene) with AI-driven camera motion and consistent character generation.

<img alt="Seedance 2.0 Mini Reference-to-Video workflow preview" />

<CardGroup>
  <Card title="Run Seedance 2.0 Mini R2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_mini_r2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-0">
    Try the Mini Reference-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Seedance 2.0 Mini R2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_mini_r2v.json">
    Download the workflow JSON or search "Seedance 2.0 Mini" in Template Library.
  </Card>

  <Card title="Download Subject Reference" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/asian_model_white_top.png">
    Get the example subject reference image.
  </Card>

  <Card title="Download Scene Reference" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/perfume_orange_shot.png">
    Get the example scene reference image.
  </Card>
</CardGroup>

## Using real-person and AI-generated portraits in ComfyUI for Seedance 2.0

Seedance 2.0 **supports both** **real-person portraits** (imagery of actual people you use as likeness or on-camera reference) and **AI-generated portraits** (fictional on-screen subjects produced by AI, not depicting a specific real individual). Which path you use determines whether you need ByteDance **liveness** and identity checks.

| | **AI-generated portrait** | **Real-person portrait** |
| - | - | - |
| **What it refers to** | The subject looks like an AI-synthesized character; it must not correspond to an identifiable natural person | You use portrait or appearance footage of a real person |
| **Identity verification** | No extra check | One-time ByteDance liveness (through **ByteDance Create Image/Video Asset**) |
| **Workflow** | Any standard Seedance 2.0 workflow (T2V, R2V, FLF2V) | Seedance 2.0 Real Human workflow with the **ByteDance Create Image/Video Asset** node |

### AI-generated portrait

<img alt="AI-generated portrait reference in a Seedance 2.0 workflow" />

Use the Seedance 2.0 node like any other generator: upload your **AI-generated character image** (or an equivalent reference), wire it up, and run.

After submission the service classifies the asset. **If it is flagged as protected real-person-related content**, the node returns an error: switch to the **real-person portrait** workflow below instead. Once the backend treats it as an AI portrait and the check clears, use it directly as reference with no extra verification steps.

### Real-person portrait

Use the **Real Human** workflow (requires **ByteDance Create Image/Video Asset**): real likeness needs **one** liveness verification to deter impersonation and unauthorized use of someone's likeness, and to comply with evolving AI transparency requirements.

**First use (verification required)**

1. Upload portrait imagery via **ByteDance Create Image/Video Asset**.
2. Run the workflow: a verification link is generated.
3. Open the link on your phone or browser and finish liveness (typically under \~30 seconds).
4. After verification succeeds you receive two IDs:
   * **Group ID**: the verified individual; retain it when uploading the same person again.
   * **Asset ID**: bound to this portrait; connect it for video generation and reuse across runs.

**New photo or video of the same person (no repeat liveness)**

1. Upload a new photo or video of that person.
2. Enter the saved **Group ID** on **ByteDance Create Image/Video Asset**.
3. The system compares the new face data with the original verification record; when it matches, the new asset activates automatically.

<CardGroup>
  <Card title="Seedance 2.0 Real Human" icon="book" href="/tutorials/partner-nodes/bytedance/seedance-2-0-real-human">
    Full walkthrough, verification flow, and Real Human workflow templates.
  </Card>
</CardGroup>


# Seedance 2.0 Real Human - Verified real person video generation
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/seedance-2-0-real-human

Generate videos of real people in Seedance 2.0 with consistent identity and native audio sync, after a one-time liveness check in ComfyUI.

<img alt="Seedance 2.0 Real Human Cover" />

**Seedance 2.0 Real Human** is available directly inside ComfyUI. You can upload a portrait through a ComfyUI workflow, complete a one-time verification, and then generate videos featuring that real person with a consistent identity and authentic facial expressions: without leaving ComfyUI.

With Real Human support in ComfyUI, you are no longer limited to virtual characters. Seedance 2.0's controllability and native audio-video sync now extend to real people, with identity and performance held together across a full clip, using the same node-based workflows you already use for other Seedance 2.0 generations.

## What Seedance 2.0 Real Human is good at

* **Real people, cinematic control**: Direct camera moves, lighting, and scene changes while keeping the subject believable
* **Identity consistency**: Facial features and overall appearance remain stable across motion, camera moves, and transitions
* **Native audio-video sync**: Video and audio (dialogue, ambient, music) are generated together with more reliable lip-sync and expressions
* **Multi-reference directing**: Mix text with up to **9 images**, **3 videos**, and **3 audio clips** to lock in look, motion, and rhythm

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Video guide

Watch the full walkthrough covering verification and both Seedance 2.0 Real Human workflows end to end in ComfyUI.

<video />

## How verification works in ComfyUI

Verification is required before any real person can appear in a Seedance 2.0 generation. It prevents impersonation and unauthorized use of someone's likeness and is handled by ByteDance, which complies with emerging AI transparency regulations. The entire flow is driven from ComfyUI through the **ByteDance Create Image/Video Asset** node: you only need to leave ComfyUI briefly to complete the liveness check on your phone or browser.

<img alt="ByteDance Create Image/Video Asset nodes used to generate Group ID and Asset ID" />

### First run (verification required)

1. In ComfyUI, add the **ByteDance Create Image/Video Asset** node to your workflow and upload a portrait image
2. Run the workflow: ComfyUI returns a verification link from ByteDance
3. Open the link on your phone or browser and complete the liveness check (less than 1 minute)
4. Once verification passes, return to ComfyUI: the node output now contains the verified asset

#### Verification flow screenshots

**Step 1: Upload and run to start verification**

<img alt="Upload your portrait and run to start liveness verification" />

**Step 2: Get the verification link**

<img alt="Workflow run returns a verification link to open in browser" />

**Step 3: Complete liveness check in the H5 page**

<img alt="Complete identity authentication in the H5 verification page" />

**Step 4: Return to ComfyUI and save IDs (no extra credits)**

<img alt="After verification, ComfyUI outputs Asset ID and Group ID to save for reuse" />

After real human verification passes, the node exposes two IDs you can use in downstream Seedance 2.0 video nodes:

* **Group ID**: represents the verified person. Save this so you can reuse the same identity later without re-verifying
* **Asset ID**: represents this specific image. Wire it into a Seedance 2.0 video generation node to produce a video of the verified person; it can be reused across multiple workflows

### Future uploads (no verification)

1. In ComfyUI, upload a new photo or video of the same person with the **ByteDance Create Image/Video Asset** node
2. Enter the saved **Group ID** in the node
3. On run, ByteDance compares facial features against the original verification
4. If it matches, the new asset is activated automatically and returned to ComfyUI, ready to feed into Seedance 2.0 video generation

#### Skipping verification with an existing Group ID

If you've already completed verification once, you can often skip the liveness step for new uploads of the same person by providing the existing **Group ID**. If ByteDance recognizes the new image as the same person, verification is bypassed.

<img alt="Reuse an existing Group ID to skip liveness verification when the person matches" />

## Available workflows

Two prebuilt Seedance 2.0 Real Human templates are available in ComfyUI. Both wire the **ByteDance Create Image/Video Asset** node into a Seedance 2.0 video generation node so verification and generation happen in a single run.

### Seedance 2.0 Real Human reference-to-video

Use a verified portrait (plus optional additional reference images, videos, or audio) to drive a Seedance 2.0 video with a consistent real-person identity.

<img alt="Seedance 2.0 Real Human R2V workflow preview" />

<CardGroup>
  <Card title="Run Seedance 2.0 Real Human R2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_r2v_real_human&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-0-real-human">
    Try the Seedance 2.0 Real Human Reference-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Seedance 2.0 Real Human R2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_r2v_real_human.json">
    Get the Seedance 2.0 Real Human Reference-to-Video workflow file.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Portrait reference" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/real_human_demo.png">
      Download sample portrait for verification
    </Card>
  </CardGroup>
</details>

### Seedance 2.0 Real Human first-last-frame to video

Provide a verified starting frame and ending frame to generate the video between them while preserving the real person's identity.

<img alt="Seedance 2.0 Real Human FLF2V workflow preview" />

<CardGroup>
  <Card title="Run Seedance 2.0 Real Human FLF2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_flf2v_real_human&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-0-real-human">
    Try the Seedance 2.0 Real Human First-Last-Frame-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Seedance 2.0 Real Human FLF2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_flf2v_real_human.json">
    Get the Seedance 2.0 Real Human First-Last-Frame-to-Video workflow file.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="First frame" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/flf2v_demo_first_frame.png">
      Download sample first frame
    </Card>

    <Card title="Last frame" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/flf2v_demo_last_frame.png">
      Download sample last frame
    </Card>
  </CardGroup>
</details>


# Seedance 2.5 - AI video generation with audio
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/seedance-2-5

Generate 30-second videos with synchronized audio, multimodal reference control, and precise editing using Seedance 2.5 in ComfyUI

Seedance 2.5 is ByteDance's new-generation video creation model, launched on July 31, 2026. Building on the unified multimodal audio-video joint-generation architecture of Seedance 2.0, it shifts the focus from generating a single clip to completing a full creative work, with major breakthroughs in long-form storytelling, multimodal reference, and editing.

The model generates up to 30 seconds of high-quality audio-video in a single pass, with improved shot transitions and scene changes for stronger continuity in longer videos. It supports multiple rounds of extension, so creators can build multi-minute content with a consistent audiovisual language, bringing a complete story to life in one take. Image, audio, and motion quality are all improved over the previous generation, resulting in more natural, polished visuals.

## What Seedance 2.5 is good at

* **30-second generation**: Produces high-quality, 30-second audio-video clips in a single pass with multi-round extension
* **Audio-video sync**: Generates video and audio together, including dialogue and lip-synced speech
* **Fully upgraded multimodal referencing**: Accepts up to 30 reference images, 10 video clips, and 10 audio clips for character consistency, visual style, and motion rhythm control
* **Precise editing**: Offers timestamp-level control for targeted edits of video and audio, plus green screen and reference-based editing
* **Multi-round extension**: Extends clips to build multi-minute content with consistent audiovisual language
* **Versatile use cases**: Suited for brand films, episodic series, e-commerce content, product showcases, and character-driven short series

## Example outputs

Text-to-video generation, producing a 30-second cinematic clip with synchronized sound and music:

<video />

Image-to-video generation, animating a single image into a 1080p clip with sound, music, and dialogue:

<video />

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Available workflows

### Text to video (T2V)

Generate a 30-second cinematic video from a text prompt, with synchronized sound and music. The node supports 480p, 720p, and 1080p output resolution.

<video />

<CardGroup>
  <Card title="Run Text-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_5_t2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-5">
    Try the Text-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Text-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_5_t2v.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

A dedicated 1080p variant of this workflow is also available:

<CardGroup>
  <Card title="Run 1080p Text-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_5_t2v_1080p&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-5">
    Try the 1080p Text-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download 1080p Text-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_5_t2v_1080p.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

### Image to video (I2V)

Animate a single image into a 1080p video clip with synchronized sound, music, and dialogue. The workflow supports clips up to 30 seconds across any aspect ratio, and takes a single image as its input.

<video />

<CardGroup>
  <Card title="Run Image-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_5_i2v_1080p&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-5">
    Try the Image-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Image-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_5_i2v_1080p.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/cosmoscape.png">
      Download sample input image
    </Card>
  </CardGroup>
</details>

### First-last-frame to video (FLF2V)

Provide a starting frame and an ending frame, and Seedance 2.5 generates the motion and transitions between them, locking both endpoints.

<img alt="Seedance 2.5 FLF2V workflow preview" />

<CardGroup>
  <Card title="Run FLF2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_5_flf2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-5">
    Try the First-Last-Frame-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download FLF2V workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_5_flf2v.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="First frame" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/pool_start_frame.png">
      Download sample first frame
    </Card>

    <Card title="Last frame" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/pool_end_frame.png">
      Download sample last frame
    </Card>
  </CardGroup>
</details>

### Reference to video (R2V)

Use reference images, video clips, or audio to control character consistency, visual style, and motion rhythm in a single output with synchronized sound and lip-synced dialogue.

<img alt="Seedance 2.5 Reference-to-Video workflow preview" />

<CardGroup>
  <Card title="Run Reference-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_5_r2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-5">
    Try the Reference-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Reference-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_5_r2v.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Reference image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/medusa_poster.png">
      Download sample reference image
    </Card>
  </CardGroup>
</details>

### Video editing

Edit existing video clips by describing changes in natural language. Replace objects, swap backgrounds, change scenes, or transfer styles while preserving the original composition and motion.

You can also extend an existing clip forward or backward. Connect the clip as the reference video, set the **task\_type** option to **extend**, and describe the continuation in the prompt, for example "extend forward", "extend backward", or "continue". The output contains only the newly generated segment at the duration you set, and its aspect ratio follows the source clip.

<img alt="Seedance 2.5 Video Editing workflow preview" />

<CardGroup>
  <Card title="Run Video Editing on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_5_video_editing&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-5">
    Try the Video Editing workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Video Editing workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_5_video_editing.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/kitten_cop.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>

### Draft mode (480p preview, then 1080p final)

Draft mode renders a low-cost 480p preview first, then the 1080p final from that draft. It applies to the Text to Video, First-Last-Frame to Video, and Reference to Video workflows. See [Seedance 2.5 Draft mode](/tutorials/partner-nodes/bytedance/seedance-2-5-draft) for the templates, sample inputs, and workflow tips.

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `Seedance 2.5`


# Seedance 2.5 Draft mode: preview at 480p, then render at 1080p
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/seedance-2-5-draft

Iterate cheaply with Seedance 2.5 Draft mode in ComfyUI: render a 480p preview with a draft_task_id, then render the 1080p final from that ID.

Seedance 2.5 Draft mode renders a fast, low-cost 480p preview before you commit to a full 1080p render, so you can iterate on a prompt, a first frame, or a set of reference images without paying for full-resolution generations.

Draft mode is available on three Seedance 2.5 workflows. Select **Seedance 2.5 Draft** as the model on the Text to Video, First-Last-Frame to Video, or Reference to Video node:

* **Text to video (T2V)**: iterate on the prompt and the duration
* **Image to video (I2V)**: iterate on the first frame
* **Reference to video (R2V)**: iterate on the reference images and the storyboard

Resolution is locked to 480p in draft mode, and each run returns both the preview and a `draft_task_id` that the final render uses.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<video />

## How the two stages work

Every draft workflow runs in two stages:

1. **Create the draft**: run the Seedance 2.5 node with the **Seedance 2.5 Draft** model to get the 480p preview and its `draft_task_id`, which the **Save Text** node writes to a `.txt` file in the output folder. Rerun with a different prompt or input until the draft looks right.
2. **Render the final**: copy the `draft_task_id` from that `.txt` file into the `draft_task_id` field on the **ByteDance Seedance 2.5 Draft to Final Video** node and run it. The node renders the 1080p final and reuses what the draft was created with, including the prompt, the input, the duration, the aspect ratio, and the audio setting, so there is nothing to re-enter.

Each template puts the two stages in separate node groups, named **Stage 1: Create and preview the draft video** and **Stage 2: Render the final video from the draft task ID**. Leave Stage 1 bypassed once you are happy with the draft, because a second run of the draft node creates a new draft instead of reusing the one you reviewed.

## Workflow templates

<CardGroup>
  <Card title="Run Draft Text-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_5_draft_t2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-5">
    Try the Draft Text-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Draft Text-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_5_draft_t2v.json">
    Download the workflow JSON.
  </Card>

  <Card title="Run Draft Image-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_5_draft_i2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-5">
    Try the Draft Image-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Draft Image-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_5_draft_i2v.json">
    Download the workflow JSON.
  </Card>

  <Card title="Run Draft Reference-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_5_draft_r2v&utm_source=docs&utm_medium=referral&utm_campaign=seedance-2-5">
    Try the Draft Reference-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Draft Reference-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_5_draft_r2v.json">
    Download the workflow JSON.
  </Card>
</CardGroup>

## Input materials

The draft image-to-video and reference-to-video templates use these sample inputs:

<CardGroup>
  <Card title="First frame" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/friends_enjoying_boba.png">
    Download sample first frame
  </Card>

  <Card title="Reference image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/yellow_mech_character_sheet.png">
    Download sample reference image
  </Card>

  <Card title="Storyboard" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/mech_comic_storyboard.png">
    Download sample storyboard
  </Card>
</CardGroup>

## Tips

* **Run only the stage you need**: select the Stage 1 nodes and press `Ctrl+B` (`Cmd+B` on macOS) to bypass them, then select the Stage 2 nodes and press `Ctrl+B` again to enable them, so only the final render runs
* **Keep the draft task ID**: the **Save Text** node writes it to a `.txt` file in the output folder, and Stage 2 reads it from there
* **Drafts stay renderable for 7 days** after they are created, so render the final within that window

See [Seedance 2.5](/tutorials/partner-nodes/bytedance/seedance-2-5) for the model overview, the standard workflows, and video editing.


# ByteDance vCube Video Enhance in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/vcube

Upscale and restore video with ByteDance vCube in ComfyUI: super-resolution up to 8K, artifact removal, color enhancement, and frame interpolation.

ByteDance vCube is ByteDance's AI video enhancement technology. It upscales low-resolution video with super-resolution up to 8K while removing compression artifacts and noise, enhancing color and sharpness, and optionally interpolating frames for a higher frame rate.

In ComfyUI, the ByteDance vCube Video Enhance node takes a video, upscales it to a target resolution preset, and restores its quality. The source video must be at most 2560x1440, and the output size is set by the resolution input.

## What vCube Video Enhance is good at

* **Super-resolution up to 8K**: Upscales low-resolution video to output presets from 720P to 8K, or a custom short side from 128 to 4320 pixels
* **Artifact and noise removal**: Cleans up compression artifacts and noise while restoring video quality
* **Color and sharpness enhancement**: Improves color and sharpness, with a natural high-definition look or a softer result
* **AI frame interpolation**: Raises the frame rate above the source, up to 120 fps
* **Scene-aware presets**: Tuned modes for AI-generated footage, general video, compressed phone clips, drama with faces, and scratched or flickering archive footage

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## ByteDance vCube video enhance workflow

Upload a video, choose the target resolution and frame rate, and run the workflow to get an upscaled, restored video.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_vcube_video_enhance&utm_source=docs&utm_medium=referral&utm_campaign=vcube">
    Run the video enhance workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_vcube_video_enhance.json">
    Download the workflow JSON file for local use.
  </Card>
</CardGroup>

![ByteDance vCube Video Enhance workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_bytedance_vcube_video_enhance-1.webp)

<Card title="Download Sample Input Video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/chill_capybara_dance_pose.mp4">
  Get the example input video for this workflow.
</Card>

### Node options

* **Scene preset**: Tuned to the content, with `aigc` for AI-generated footage, `common` for general video, `ugc` for compressed phone clips, `short_series` for drama with faces, and `old_film` for scratched or flickering archive footage
* **Enhancement style**: `hd` for a natural high-definition look, or `natural` for a softer result
* **Resolution**: Output presets from 720P to 8K, `source` to keep the source size, or a custom short side from 128 to 4320 pixels
* **Frame rate**: `source`, or 24, 25, 30, 48, 50, 60, and 120 fps. Rates above the source enable AI frame interpolation; rates above 30 fps cost 2x, above 60 fps 4x
* **Smoothness**: `low`, `medium`, or `high` bitrate level for the delivered file


# Fish Audio: Text to Speech, Voice Cloning, and Speech to Text in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/fishaudio/fish-audio

Run Fish Audio TTS, voice cloning, and speech to text workflows in ComfyUI: template walkthroughs, node setup, and Cloud links

Fish Audio is a speech AI service covering text to speech, voice cloning, and speech to text. In ComfyUI it ships as four partner nodes: Text to Speech, Speech to Text, Voice Selector, and Instant Voice Clone. This page walks through the ready-made workflow templates and how to connect the nodes. For the full inline tag reference (emotions, tone, pauses, phonemes), see the [Fish Audio prompt guide](/tutorials/partner-nodes/fishaudio/prompt-guide).

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Use Fish Audio in ComfyUI

The Fish Audio partner nodes are available in the node menu under `partner/audio/Fish Audio`. Four nodes cover the workflow:

* **Fish Audio Text to Speech**: converts text to speech, outputs `AUDIO`
* **Fish Audio Speech to Text**: transcribes audio to text, outputs `text`, `language_code`, and `segments_json`
* **Fish Audio Voice Selector**: selects one of the preset voices, or connects any fish.audio voice model through `custom` (the ID in `https://fish.audio/m/<id>/`), outputs `voice`
* **Fish Audio Instant Voice Clone**: creates a private cloned voice from recordings, outputs `voice`

### Choosing a model

The `model` parameter on the Text to Speech node offers two options:

* `s2.1-pro` (recommended): supports multiple speakers through an autogrow list of 0 to 5 voice inputs
* `s1` (legacy): accepts a single optional voice input and uses the parenthesis emotion tag syntax described in the prompt guide

### Connecting voices

The `voice` output of the Voice Selector or the Instant Voice Clone connects to the Text to Speech node. The input name depends on the model: `s2.1-pro` (recommended) exposes the growable `voices` input (up to 5 voice slots), while `s1` has a single optional `voice` input. With one connected voice, the node passes it internally as `reference_id`. With two or more, the text must mark speakers with `@Voice1`, `@Voice2`, and so on, and every connected voice must appear in the text at least once or the node raises an error. See [Multi-speaker dialogue](/tutorials/partner-nodes/fishaudio/prompt-guide#multi-speaker-dialogue) in the prompt guide.

### Voice cloning limits

The Instant Voice Clone node accepts 1 to 20 recordings, recommends 10 to 30 seconds per clip, and validates that the total duration stays under 270 seconds. The `enhance_audio_quality` option is enabled by default. For recording tips, see [Voice cloning quality](/tutorials/partner-nodes/fishaudio/prompt-guide#voice-cloning-quality) in the prompt guide.

### Account and pricing

The nodes require signing in to a ComfyUI account and are billed per use. Reference prices from the nodes: text to speech is about $21.45 per 1M bytes of text, speech to text is $0.00858 per minute, and voice cloning is free.

## Available workflows

Three ready-made templates cover the main Fish Audio flows: text to speech, voice clone to speech, and speech to text. Open them from the Template Library in ComfyUI, or run them directly on Comfy Cloud. The voice clone and speech to text templates require ComfyUI 0.34.0 or newer.

### Fish Audio: Text to Speech

Generate speech from your script with a preset voice. Write your text with the inline tags from the [prompt guide](/tutorials/partner-nodes/fishaudio/prompt-guide), then pick another preset in the Voice Selector or connect a cloned voice.

<img alt="Fish Audio: Text to Speech workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_fishaudio_text_to_speech&utm_source=docs&utm_medium=referral&utm_campaign=fishaudio">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_fishaudio_text_to_speech.json">
    Download JSON or search "Fish Audio: Text to Speech" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadAudio` node:

<CardGroup>
  <Card title="fish_audio_example.mp3" icon="music" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/fish_audio_example.mp3">
    `LoadAudio` node 11 · `fish_audio_example.mp3`
  </Card>
</CardGroup>

### Fish Audio: Voice Clone to Speech

Clone a voice from a short recording, then use it to speak any script. Record 2 to 3 clips of 15 to 20 seconds, upload them through the `LoadAudio` node (or record directly in the `RecordAudio` node), and connect the Instant Voice Clone output to the Text to Speech node. For recording tips, see [Voice cloning quality](/tutorials/partner-nodes/fishaudio/prompt-guide#voice-cloning-quality) in the prompt guide.

<img alt="Fish Audio: Voice Clone to Speech workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_fishaudio_voice_clone_tts&utm_source=docs&utm_medium=referral&utm_campaign=fishaudio">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_fishaudio_voice_clone_tts.json">
    Download JSON or search "Fish Audio: Voice Clone to Speech" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadAudio` node:

<CardGroup>
  <Card title="api_fishaudio_voice_clone_tts_fish_audio_example.mp3" icon="music" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_fishaudio_voice_clone_tts_fish_audio_example.mp3">
    `LoadAudio` node 11 · `api_fishaudio_voice_clone_tts_fish_audio_example.mp3`
  </Card>
</CardGroup>

### Fish Audio: Speech to Text

Transcribe an audio clip to text. Language is detected automatically across 80+ languages, and enabling `precise_timestamps` returns per-segment start and end times as JSON, which is handy for subtitles.

<img alt="Fish Audio: Speech to Text workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_fishaudio_speech_to_text&utm_source=docs&utm_medium=referral&utm_campaign=fishaudio">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_fishaudio_speech_to_text.json">
    Download JSON or search "Fish Audio: Speech to Text" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadAudio` node:

<CardGroup>
  <Card title="fish_audio_example.mp3" icon="music" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/fish_audio_example.mp3">
    `LoadAudio` node 11 · `fish_audio_example.mp3`
  </Card>
</CardGroup>

## Get started

1. Update ComfyUI to the latest version
2. Open a workflow template above, or add the Fish Audio nodes from the node menu under `partner/audio/Fish Audio`
3. Sign in to your ComfyUI account when prompted
4. Write your script with the inline tags from the [prompt guide](/tutorials/partner-nodes/fishaudio/prompt-guide)
5. Run the workflow and preview or save the audio


# Fish Audio Prompt Guide: writing prompts for Fish Audio TTS in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/fishaudio/prompt-guide

Write prompts for the Fish Audio partner nodes in ComfyUI: emotion tags, tone markers, audio effects, pauses, phoneme control, and multi-speaker dialogue.

Fish Audio TTS gives you direct control over how speech sounds through inline tags written in the text itself. This guide covers every tag category the model understands, where to place them, and how to combine them.

The examples below work in the Fish Audio Text to Speech node. Type them straight into the `text` field, replacing the sample script with your own. For node setup, workflow templates, and pricing, see [Fish Audio: Text to Speech, Voice Cloning, and Speech to Text](/tutorials/partner-nodes/fishaudio/fish-audio).

## How tags work

Fish Audio S2 models interpret natural-language cues written in square brackets inside your text:

```text theme={null}
[happy] What a beautiful day!
[sad] I'm sorry to hear that.
[excited] This is amazing news!
```

Three properties make this system flexible:

* **Position is meaning.** A tag applies from where it appears until the next tag or the end of the sentence. `[whispering] I didn't want to go inside` whispers the whole line. `I didn't want to go [whispering] inside` starts whispering at "inside".
* **Free-form descriptions work.** You are not limited to a fixed tag set. If you can describe it to a voice actor, write it in brackets: `[tired, end of a long shift]`, `[voice rough from crying, trying to sound normal]`, `[professional broadcast tone]`.
* **Tags work in your language.** Write cues in the same language as your script: `[低声说] 不要让他们听见`, `[ため息をついて] もう一度やり直そう`.

The legacy `s1` model uses the same emotion names but wraps them in parentheses with a fixed tag set: `(happy) What a beautiful day!` The current `s2.1-pro` model accepts bracket cues and free-form descriptions.

## Emotion tags

### Basic emotions

| Tag | Delivery | Common context |
| - | - | - |
| `[happy]` | Cheerful, upbeat | Good news, greetings |
| `[sad]` | Melancholic, downcast | Sympathy, bad news |
| `[angry]` | Frustrated, aggressive | Complaints, warnings |
| `[excited]` | Energetic, enthusiastic | Announcements, celebrations |
| `[calm]` | Peaceful, relaxed | Instructions, meditation |
| `[nervous]` | Anxious, uncertain | Disclaimers, apologies |
| `[confident]` | Assertive, self-assured | Presentations, sales |
| `[surprised]` | Shocked, amazed | Reactions, discoveries |
| `[satisfied]` | Content, pleased | Confirmations, reviews |
| `[delighted]` | Very pleased, joyful | Celebrations, compliments |
| `[scared]` | Frightened, fearful | Warnings, horror stories |
| `[worried]` | Concerned, troubled | Concerns, questions |
| `[upset]` | Disturbed, distressed | Complaints, problems |
| `[frustrated]` | Annoyed, exasperated | Technical issues, delays |
| `[depressed]` | Very sad, hopeless | Serious topics |
| `[empathetic]` | Understanding, caring | Support, counseling |
| `[embarrassed]` | Ashamed, awkward | Apologies, mistakes |
| `[disgusted]` | Repelled, revolted | Negative reviews |
| `[moved]` | Emotionally touched | Heartfelt moments |
| `[proud]` | Accomplished, satisfied | Achievements, praise |
| `[relaxed]` | At ease, casual | Casual conversation |
| `[grateful]` | Thankful, appreciative | Thanks, appreciation |
| `[curious]` | Inquisitive, interested | Questions, exploration |
| `[sarcastic]` | Ironic, mocking | Humor, criticism |

### Advanced emotions

| Tag | Delivery | Common context |
| - | - | - |
| `[disdainful]` | Contemptuous, scornful | Criticism, rejection |
| `[unhappy]` | Discontent, dissatisfied | Complaints, feedback |
| `[anxious]` | Very worried, uneasy | Urgent matters |
| `[hysterical]` | Uncontrollably emotional | Extreme reactions |
| `[indifferent]` | Uncaring, neutral | Neutral responses |
| `[uncertain]` | Doubtful, unsure | Speculation, questions |
| `[doubtful]` | Skeptical, questioning | Disbelief, questioning |
| `[confused]` | Puzzled, perplexed | Clarification requests |
| `[disappointed]` | Let down, dissatisfied | Unmet expectations |
| `[regretful]` | Sorry, remorseful | Apologies, mistakes |
| `[guilty]` | Culpable, responsible | Confessions, apologies |
| `[ashamed]` | Deeply embarrassed | Serious mistakes |
| `[jealous]` | Envious, resentful | Comparisons |
| `[envious]` | Wanting what others have | Admiration with desire |
| `[hopeful]` | Optimistic about future | Future plans |
| `[optimistic]` | Positive outlook | Encouragement |
| `[pessimistic]` | Negative outlook | Warnings, doubts |
| `[nostalgic]` | Longing for the past | Memories, stories |
| `[lonely]` | Isolated, alone | Emotional content |
| `[bored]` | Uninterested, weary | Disinterest |
| `[contemptuous]` | Showing contempt | Strong criticism |
| `[sympathetic]` | Showing sympathy | Condolences |
| `[compassionate]` | Showing deep care | Support, help |
| `[determined]` | Resolved, decided | Goals, commitments |
| `[resigned]` | Accepting defeat | Giving up, acceptance |

## Tone markers

Tone markers control volume, intensity, and emphasis. Place `[emphasis]` right before the word or phrase you want to stress:

```text theme={null}
This is [emphasis] really important.
```

| Tag | Delivery | When to use |
| - | - | - |
| `[in a hurry tone]` | Rushed, urgent | Time-sensitive information |
| `[shouting]` | Loud, calling out | Getting attention |
| `[screaming]` | Very loud, panicked | Emergencies, fear |
| `[whispering]` | Very soft, secretive | Secrets, quiet scenes |
| `[soft tone]` | Gentle, quiet | Comfort, lullabies |
| `[emphasis]` | Stress a word or phrase | Highlighting key words |

## Audio effects

Audio effect tags add natural human sounds. Follow the tag with matching text where suggested:

| Tag | Description | Suggested text after the tag |
| - | - | - |
| `[laughing]` | Full laughter | Ha, ha, ha |
| `[chuckling]` | Light laugh | Heh, heh |
| `[sobbing]` | Crying heavily | Optional text |
| `[crying loudly]` | Intense crying | Optional text |
| `[sighing]` | Exhale of relief or frustration | sigh |
| `[groaning]` | Sound of frustration | ugh |
| `[panting]` | Out of breath | huff, puff |
| `[gasping]` | Sharp intake of breath | gasp |
| `[yawning]` | Tired sound | yawn |
| `[snoring]` | Sleep sound | zzz |
| `[clear throat]` | Throat-clearing sound | ahem |

## Pauses and special effects

| Tag | Description |
| - | - |
| `[break]` | Brief pause in speech |
| `[long-break]` | Extended pause in speech |
| `[short pause]` | Short beat between lines |
| `[long pause]` | Extended silence |
| `[audience laughing]` | Crowd laughing sound |
| `[background laughter]` | Ambient laughter |
| `[crowd laughing]` | Large group laughing |

Plain pause words also shape rhythm without any tags: "um", "uh", "嗯", "啊".

## Combining tags

**Pair a physical tag with an emotion tag.** Physical tags like `[panting]` or `[whispering]` register on their own, but pairing them with an emotion produces more consistent, natural results:

```text theme={null}
[panting] [tired] I've been running for twenty minutes.
[whispering] [scared] Don't move. Don't make a sound.
[shouting] [angry] I told you this would happen!
```

**Layer emotions for complex expressions.** Keep combinations to three tags or fewer per sentence:

```text theme={null}
[sad][whispering] I miss you so much.
[angry][shouting] Get out of here now!
[excited][laughing] We won! Ha ha!
```

**Write emotion transitions** as a natural progression across sentences:

```text theme={null}
[happy] I got the promotion!
[uncertain] But... it means relocating.
[sad] I'll miss everyone here.
[hopeful] Though it's a great opportunity.
[determined] I'm going to make it work!
```

**Add background effects** for atmosphere:

```text theme={null}
The comedy show was amazing [audience laughing]
```

**Modulate intensity** with descriptive modifiers:

```text theme={null}
[slightly sad] I'm a bit disappointed.
[very excited] This is absolutely amazing!
[extremely angry] This is unacceptable!
```

## Best practices

**Do:**

* Use one primary emotion per sentence
* Match emotions to context logically
* Add text after sound effects, for example "Ha ha" after `[laughing]`
* Space out emotional changes for realism
* Test different combinations on the same voice

**Don't:**

* Overuse tags in short text
* Mix conflicting emotions in one sentence
* Write bracket descriptions so long they interrupt the flow
* Leave a descriptive tag without text after it
* Place sentence-level emotion cues far from the sentence they control

If the output sounds unnatural, space out emotional changes, lower the intensity, or try a different voice: the same tag lands differently on different voices.

## Multi-speaker dialogue

Connect two or more voices to the Fish Audio Text to Speech node, then mark speaker changes in the text with `@Voice1`, `@Voice2`, and so on. Every connected voice must appear in the text at least once, or the node raises an error. Voice connections are covered in [Fish Audio: Text to Speech, Voice Cloning, and Speech to Text](/tutorials/partner-nodes/fishaudio/fish-audio#connecting-voices).

```text theme={null}
@Voice1 [nervous] You're sure no one followed you?
@Voice2 [calm] Relax. I took the long way, exactly like you asked.
@Voice1 [sighing][relieved] Good. Then let's see what's inside.
@Voice2 [curious] You don't even know what it is?
```

## Phoneme control

Phoneme tags specify exact pronunciations for names, homographs, acronyms, and technical terms. Wrap the replacement pronunciation in `<|phoneme_start|>` and `<|phoneme_end|>` tags. Phoneme tags are preserved by text normalization, so keep `normalize` enabled.

**English** (CMU Arpabet, replaces one word):

```text theme={null}
I am an <|phoneme_start|>EH1 N JH AH0 N IH1 R<|phoneme_end|>.
```

**Chinese** (tone-number pinyin, replaces one character or syllable, useful for polyphonic characters and names):

```text theme={null}
我是一个<|phoneme_start|>gong1<|phoneme_end|><|phoneme_start|>cheng2<|phoneme_end|><|phoneme_start|>shi1<|phoneme_end|>。
```

**Japanese** (OpenJTalk-style romaji with pitch accent digits):

```text theme={null}
<|phoneme_start|>ha0shi1ga0<|phoneme_end|>見えます。
```

Phoneme control combines with other tags in the same text:

```text theme={null}
I am, um, an [break] <|phoneme_start|>EH1 N JH AH0 N IH1 R<|phoneme_end|>.
```

## Parameter tuning

The defaults are well tuned. Adjust only when you need to:

| Parameter | Default | Effect |
| - | - | - |
| `temperature` | 0.7 | Expressiveness. Higher is more varied, lower is more consistent |
| `top_p` | 0.7 | Diversity via nucleus sampling |
| `speed` | 1.0 | Speaking rate, 0.5 to 2.0 |
| `volume` | 0.0 | Volume adjustment in decibels, -10 to 10 |
| `normalize` | true | Expands numbers and dates for natural reading. Keep on unless normalization rewrites text you want read literally |

The `seed` controls whether the node reruns; results are non-deterministic regardless of seed value.

## Voice cloning quality

For the Fish Audio Instant Voice Clone node, reference recording quality decides the result. Recording limits are covered in [Fish Audio: Text to Speech, Voice Cloning, and Speech to Text](/tutorials/partner-nodes/fishaudio/fish-audio#voice-cloning-limits):

* Record 2 to 3 clips of 15 to 20 seconds each, under 270 seconds in total
* One speaker only, steady volume, consistent tone and emotion
* Small pauses between sentences, about half a second
* Quiet room, microphone about a hand's width from the mouth
* A phone recorder or headset mic works; avoid background music, TV, and echo

If the cloned voice sounds robotic, record more material, 30 to 60 seconds total, and speak naturally with pauses.

Only clone voices you have permission to use: your own voice, or someone who gave you explicit permission.

## References

* [Fish Audio emotion control documentation](https://docs.fish.audio/developer-guide/core-features/emotions)
* [Fish Audio fine-grained control documentation](https://docs.fish.audio/developer-guide/core-features/fine-grained-control)
* [Fish Audio voice cloning best practices](https://docs.fish.audio/developer-guide/best-practices/voice-cloning)


# Google Gemini Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/google/gemini

This article will introduce how to use Google Gemini Partner nodes in ComfyUI to complete conversational functions

Google Gemini is a powerful AI model developed by Google, supporting conversational and text generation functions. Currently, ComfyUI has integrated the Google Gemini API, allowing you to directly use the related nodes in ComfyUI to complete conversational functions.

## What Google Gemini is good at

* **Conversational and text generation**: Chat with Google's multimodal AI directly inside a ComfyUI workflow
* **Multimodal reasoning**: Interpret images with Gemini's reasoning capabilities
* **Image-to-prompt interpretation**: The official template ships with a prompt that turns your images into corresponding drawing prompts
* **Multi-image input**: Use `Batch Images` to send several images for AI interpretation in a single run

## Use it

<Card title="Call it from code" icon="code" href="/development/comfy-router/models/google/gemini/code">
  Call it over HTTP through Comfy Router, with copy-paste Python, TypeScript, Swift and cURL snippets
</Card>

This runs on the same Comfy account and is billed in the same credits as running it in ComfyUI below. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for per-model rates and [Concurrency limits](/tutorials/partner-nodes/concurrency-limits) for how many requests you can have in flight.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Google Gemini

Experience Google's multimodal AI with Gemini's reasoning capabilities.

<img alt="Google Gemini workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_google_gemini&utm_source=docs&utm_medium=referral&utm_campaign=gemini">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_google_gemini.json">
    Download JSON or search "Google Gemini" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="example.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/example.png">
    `LoadImage` node 2 · `example.png`
  </Card>
</CardGroup>

<div>
  <img alt="example.png" />
</div>

## Complete the workflow execution step by step

<img alt="OpenAI Chat Step Guide" />

<Note>
  In the corresponding template, we have built a prompt for analyzing and generating role prompts, used to interpret your images into corresponding drawing prompts
</Note>

You can refer to the numbers in the image to complete the basic text-to-image workflow execution:

1. In the `Load Image` node, load the image you need AI to interpret
2. (Optional) If needed, you can modify the prompt in `Google Gemini` to have AI execute specific tasks
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the conversation.
4. After waiting for the API to return results, you can view the corresponding AI returned content in the `Preview Any` node.

## Additional Notes

* Currently, the file input node `Gemini Input Files` requires files to be uploaded to the `ComfyUI/input/` directory first. This node is being improved, and we will modify the template after updates
* The workflow provides an example using `Batch Images` for input. If you have multiple images that need AI interpretation, you can refer to the step diagram and use right-click to set the corresponding node mode to `Always` to enable it


# Gemini Omni Flash: Conversational Video Generation
Source: https://docs.comfy.org/tutorials/partner-nodes/google/gemini-omni-flash

Generate and edit videos through natural language using Gemini Omni Flash 1.1, Google's multimodal video model, available in ComfyUI through Partner Nodes

Gemini Omni Flash is Google DeepMind's conversational video generation and editing model, part of the Gemini Omni family first introduced at Google I/O 2026. It combines Gemini's multimodal reasoning with native video creation: you describe what you want in plain language, attach reference images or videos, and the model generates a clip with synchronized audio. The current version, Gemini Omni Flash 1.1, reached general availability on August 27, 2026 and adds keyframe interpolation, 360p/4K output options, and scene extension.

## What Gemini Omni Flash 1.1 is good at

* **Conversational video editing**: Refine and edit videos using natural language: swap characters, relight scenes, alter angles, add or remove objects while maintaining the original audio and video tracks
* **Multimodal input**: Combine text, images (up to 14), and videos (up to 3, 10 seconds each) to guide generation. Every output carries a native audio track
* **Keyframe interpolation**: With the `image_to_video` task, attach a starting frame and an optional ending frame, and the model generates the footage in between
* **Reference to video**: Bind reference images to roles with tags like `<IMAGE_REF_0>` so characters, products, and objects from your images appear in a new scene without the image itself being used as a frame
* **Scene extension**: The `extend` task appends up to 10 seconds of new footage to a clip, reading the last 10 seconds of context for character and motion consistency, up to about 40 seconds cumulatively
* **Resolution control**: Draft at 360p (about one third of the 720p cost), then re-render at 720p, 1080p, or 4K. 16:9 and 9:16 aspect ratios are supported
* **World knowledge and simulation**: Combines physics understanding with Gemini's knowledge of history, science, and cultural context, enabling meaningful storytelling beyond photorealism
* **Text and action synchronization**: Render legible text and graphics directly into video, syncing kinetic typography with on-screen movements

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<Note>
  The Gemini Omni Flash 1.1 workflows require ComfyUI 0.34.2 or later. In the node, select **Omni Flash 1.1** from the model dropdown to use the GA model; the **Omni Flash** option runs the preview model, which is scheduled to retire on September 30, 2026.
</Note>

## Available workflows

### Text to Video (Omni Flash)

Generate video from a single text prompt with the preview-tier Gemini Omni Flash model. Describe the scene, the length, and the aspect ratio in one prompt, and the model renders the clip with a native audio track.

<img alt="Gemini Omni Flash Text to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_google_gemini_omni_flash_t2v&utm_source=docs&utm_medium=referral&utm_campaign=gemini-omni-flash">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_google_gemini_omni_flash_t2v.json">
    Download JSON or search "Gemini Omni" in Template Library
  </Card>
</CardGroup>

<Note>
  The preview Omni Flash model is scheduled to retire on September 30, 2026. Use the Omni Flash 1.1 workflows below for the GA model.
</Note>

### Text to Video (Omni Flash 1.1)

Generate cinematic video from natural language prompts with Gemini Omni Flash 1.1. Describe the desired length (3 to 10 seconds) directly in the prompt, and pick the aspect ratio and output resolution in the node: 16:9 or 9:16, 360p for cheap drafts, up to 4K for final renders. Every clip includes a generated audio track.

<img alt="Gemini Omni Flash 1.1 Text to Video workflow preview" />

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_google_gemini_omni_flash_1_1_t2v&utm_source=docs&utm_medium=referral&utm_campaign=gemini-omni-flash">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_google_gemini_omni_flash_1_1_t2v.json">
    Download JSON or search "Gemini Omni 1.1" in Template Library
  </Card>
</CardGroup>

### Image to Video (Omni Flash 1.1)

Animate an image with Gemini Omni Flash 1.1. With the `image_to_video` task, the first attached image becomes the starting frame and an optional second image becomes the ending frame: the model generates the footage in between, which makes camera orbits, zoom transitions, and looping clips predictable.

<img alt="Gemini Omni Flash 1.1 Image to Video workflow preview" />

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_google_gemini_omni_flash_1_1_i2v&utm_source=docs&utm_medium=referral&utm_campaign=gemini-omni-flash">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_google_gemini_omni_flash_1_1_i2v.json">
    Download JSON or search "Gemini Omni 1.1" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/blue_studio_car.png">
      Download sample input image
    </Card>
  </CardGroup>
</details>

### Reference to Video (Omni Flash 1.1)

Generate video that incorporates specific subjects from up to 14 reference images. In reference mode, bind each image to a role with tags like `<IMAGE_REF_0>` and refer to the tags in your prompt: characters, products, and objects from your images appear in the scene while the image itself is never used as a frame. Combine character references with style references for brand-consistent content.

<img alt="Gemini Omni Flash 1.1 Reference to Video workflow preview" />

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_google_gemini_omni_flash_1_1_r2v&utm_source=docs&utm_medium=referral&utm_campaign=gemini-omni-flash">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_google_gemini_omni_flash_1_1_r2v.json">
    Download JSON or search "Gemini Omni 1.1" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="Reference image 1" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/terracotta_eyeshadow_palette.png">
      Download the first sample reference image
    </Card>

    <Card title="Reference image 2" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/asian_female_model_beige_suit.png">
      Download the second sample reference image
    </Card>
  </CardGroup>
</details>

### Video Edit (Omni Flash 1.1)

Edit videos with natural language using Gemini Omni Flash 1.1. With the `edit` task, the node takes exactly one input video (10 seconds or less) and rewrites it based on your instructions: swap backgrounds, restyle scenes, add or remove elements. The `edit` and `extend` tasks keep the aspect ratio of the input video. Simple prompts work best; adding "keep everything else the same" maximizes consistency.

<img alt="Gemini Omni Flash 1.1 Video Edit workflow preview" />

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_google_gemini_omni_flash_1_1_edit&utm_source=docs&utm_medium=referral&utm_campaign=gemini-omni-flash">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_google_gemini_omni_flash_1_1_edit.json">
    Download JSON or search "Gemini Omni 1.1" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/hooded_wanderer_planet_bridge.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>

### Video Extend (Omni Flash 1.1)

Extend an existing video by up to 10 seconds per step with the `extend` task, building stories up to about 40 seconds total. The model analyzes the last 10 seconds of context, keeping characters, motion, and audio coherent as the scene continues from where it left off. Optionally attach reference images to introduce new characters mid-story. Extension appends new content only at the end of the clip, but the model may revise the final source frames to make the transition seamless.

<img alt="Gemini Omni Flash 1.1 Video Extend workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_google_gemini_omni_flash_1_1_extend&utm_source=docs&utm_medium=referral&utm_campaign=gemini-omni-flash">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_google_gemini_omni_flash_1_1_extend.json">
    Download JSON or search "Gemini Omni 1.1" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/rooster_duel_western.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>

## Get started

1. Update ComfyUI to the latest version (0.34.2 or later for the Omni Flash 1.1 workflows)
2. Double-click the canvas and search for "Gemini Omni Flash" nodes
3. Or go to the Template Library to use the ready-to-go workflows
4. Choose the workflow that matches your input type (text, image, or video)
5. Enter your prompt and generate

<Note>
  For the best results, combine Gemini Omni Flash with Nano Banana 2 Lite: generate images at high speed, then use Gemini Omni Flash to animate them into video.
</Note>


# Grok Imagine Video 1.5 Image to Video ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/grok/grok-imagine-video-1-5

This guide explains how to use the Grok Imagine Video 1.5 Partner Node in ComfyUI to generate high-quality videos with native audio from images

The [Grok Imagine Video 1.5](/built-in-nodes/GrokVideoNode) Partner Node enables high-quality video generation with native audio from a single image input. Powered by xAI's latest Grok model, it produces realistic motion with synchronized audio and supports up to **1080p** resolution.

The node supports two model variants selected via its `model` parameter:

* **`grok-imagine-video`**: the previous generation model, supports optional image input
* **`grok-imagine-video-1.5`**: the latest model, **always requires** an input image and supports 1080p output

Both variants generate **native audio**: sound effects, ambience, and dialogue are synthesized in the same pass, with no separate audio pipeline needed. Video duration ranges from **1 to 15 seconds**.

## What Grok Imagine Video 1.5 is good at

* **Image-to-video generation**: produces high-quality video from a single input image
* **Native audio**: sound effects, ambience, and dialogue are synthesized in the same pass, with no separate audio pipeline needed
* **Realistic motion**: motion stays synchronized with the generated audio
* **Up to 1080p output**: the 1.5 model supports 1080p resolution
* **Flexible duration**: video length from 1 to 15 seconds

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Grok Imagine Video 1.5: Image to Video

<img alt="Grok Imagine Video 1.5 Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_grok_imagine_video_1_5&utm_source=docs&utm_medium=referral&utm_campaign=grok-imagine-video-1-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_grok_imagine_video_1_5.json">
    Download JSON or search "Grok Imagine Video 1.5" in Template Library
  </Card>
</CardGroup>

<Card title="Download Sample Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/robot_nun_pray.png">
  Get the example input image for this workflow.
</Card>

### Workflow Overview

This workflow uses three nodes:

* **LoadImage**: provides the starting image frame
* **GrokVideoNode**: the core node configured with the `grok-imagine-video-1.5` model
* **SaveVideo**: saves the generated video with native audio

### Steps to Run

1. **Upload a starting image**: use the **LoadImage** node to load your reference image
2. **Enter your prompt**: describe the motion, atmosphere, and scene dynamics in the **GrokVideoNode** node
3. **Select model**: ensure `grok-imagine-video-1.5` is selected
4. **Set resolution**: choose output resolution (`720p` recommended)
5. **Set duration**: choose the video length in seconds
6. **Set seed**: control whether the node re-runs; outputs are not reproducible regardless of seed
7. **Click Queue**: press `Ctrl+Enter` to generate

### Output

The generated video includes **native audio** synchronized with the motion, saved automatically via the **SaveVideo** node.

### Tips

* Use high-quality input images for best results
* The prompt works best when it describes both the **visual scene** and the **motion dynamics**
* For different results, try varying the seed value


# Grok Imagine Video in ComfyUI: AI Video Generation, Editing, and Extension
Source: https://docs.comfy.org/tutorials/partner-nodes/grok/grok-video

Generate, edit, and extend videos with Grok Imagine in ComfyUI: text/image to video, video editing, video extension, and reference-to-video workflows

Grok Imagine Video is xAI's video generation family, available in ComfyUI through the Grok partner nodes. It covers video generation from text or an image, video editing, seamless video extension, and reference-to-video generation guided by character or style images.

For the latest model, see [Grok Imagine Video 1.5](/tutorials/partner-nodes/grok/grok-imagine-video-1-5).

## What Grok Imagine Video is good at

* **Video generation with audio**: produces up to 15-second clips with synchronized audio from a text prompt, with an optional starting image
* **Natural-language video editing**: restyles footage, changes the setting, or applies a new aesthetic while keeping the original motion and content
* **Seamless video extension**: continues a short video with a new clip that follows on from the original footage, based on a natural-language description of the next scene
* **Reference-to-video**: generates video guided by up to 7 reference images, keeping characters, products, or styles consistent
* **Resolution options**: outputs at 480p or 720p

## Example outputs

Video generation from a text prompt with synchronized audio:

<video />

Video editing with natural-language instructions, keeping the original motion:

<video />

Video extension, continuing a short clip with a new scene:

<video />

Reference-to-video, keeping the subject consistent from reference images:

<video />

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Grok: Video Generation

Generate a short video from a text prompt, with an optional starting image. This workflow uses the `grok-imagine-video` model to produce up to 15-second clips with synchronized audio.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_grok_video&utm_source=docs&utm_medium=referral&utm_campaign=grok-video">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_grok_video.json">
    Download JSON or search "Grok Imagine" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image: sci-fi_mech.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/sci-fi_mech.png">
      A sci-fi mech suit used as the optional starting frame
    </Card>
  </CardGroup>
</details>

### Workflow overview

This workflow uses three nodes:

* **LoadImage**: provides the optional starting image frame
* **GrokVideoNode**: the core node, configured with the `grok-imagine-video` model
* **SaveVideo**: saves the generated video with audio

### Steps to run

1. **Enter your prompt**: describe the motion, atmosphere, and scene dynamics in the **GrokVideoNode**
2. **Optionally load a starting image**: connect an image to the **LoadImage** node
3. **Set resolution**: `480p` or `720p`
4. **Set duration**: choose a length from 1 to 15 seconds
5. **Set seed**: control whether the node re-runs; outputs are not reproducible regardless of seed
6. **Click Queue**: press `Ctrl+Enter` to generate

## Grok: Video Edit

Edit an uploaded video with natural-language instructions. Restyle the footage, change the setting, or apply a new aesthetic while keeping the original motion and content.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_grok_video_edit&utm_source=docs&utm_medium=referral&utm_campaign=grok-video">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_grok_video_edit.json">
    Download JSON or search "Grok Imagine" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video: futuristic_motorcycle.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/futuristic_motorcycle.mp4">
      A futuristic motorcycle clip used as the base video
    </Card>
  </CardGroup>
</details>

### Workflow overview

This workflow uses three nodes:

* **LoadVideo**: provides the source video to edit
* **GrokVideoEditNode**: the core node, configured with the `grok-imagine-video` model
* **SaveVideo**: saves the edited video

### Steps to run

1. **Load a video**: connect your video to the **LoadVideo** node (1 to 8.7 seconds, up to 50MB)
2. **Describe the edit**: tell the model how to transform the footage in the **GrokVideoEditNode** prompt
3. **Click Queue**: press `Ctrl+Enter` to generate

## Grok: Video Extend

Extend a short video with a seamless continuation. Describe the next scene in natural language, and the model generates a new clip that follows on from the original footage.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_grok_video_extend&utm_source=docs&utm_medium=referral&utm_campaign=grok-video">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_grok_video_extend.json">
    Download JSON or search "Grok Imagine" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video: deep_space_nexus.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/deep_space_nexus.mp4">
      A short deep-space clip used as the base video
    </Card>
  </CardGroup>
</details>

### Workflow overview

This workflow uses three nodes:

* **LoadVideo**: provides the source video to extend
* **GrokVideoExtendNode**: the core node, configured with the `grok-imagine-video` model
* **SaveVideo**: saves the extended video

### Steps to run

1. **Load a video**: connect your video to the **LoadVideo** node (MP4, 2 to 15 seconds, up to 50MB)
2. **Describe the next scene**: tell the model what should happen next in the **GrokVideoExtendNode** prompt
3. **Set duration**: choose the extension length (2 to 10 seconds)
4. **Click Queue**: press `Ctrl+Enter` to generate

## Grok: Reference to Video

Generate a video guided by up to 7 reference images. Use character, product, or style references to keep the subject consistent while the prompt describes the motion and scene.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_grok_reference_to_video&utm_source=docs&utm_medium=referral&utm_campaign=grok-video">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_grok_reference_to_video.json">
    Download JSON or search "Grok Imagine" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="Character reference: quiet_girl.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/quiet_girl.png">
      A calm female character used as the subject reference
    </Card>

    <Card title="Object reference: phone.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/phone.png">
      A smartphone used as the object reference
    </Card>
  </CardGroup>
</details>

### Workflow overview

This workflow uses four nodes:

* **LoadImage** x2: provide the character and object reference images
* **GrokVideoReferenceNode**: the core node, configured with the `grok-imagine-video` model and reference images
* **SaveVideo**: saves the generated video

### Steps to run

1. **Load your references**: connect up to 7 reference images to the **LoadImage** nodes
2. **Enter your prompt**: describe the scene, motion, and how the references appear in the **GrokVideoReferenceNode**
3. **Set resolution**: `480p` or `720p`
4. **Set aspect ratio**: pick from `16:9` down to `9:16`
5. **Set duration**: choose a length from 2 to 10 seconds
6. **Click Queue**: press `Ctrl+Enter` to generate


# HappyHorse 1.0 Video Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/happyhorse/happyhorse1-0

Learn how to use HappyHorse 1.0 via Partner Nodes in ComfyUI for image-to-video, text-to-video, reference-to-video, and video editing with cinematic aesthetics and multi-shot consistency

HappyHorse 1.0 is a cinematic video generation model from Alibaba, now available in ComfyUI via Partner Nodes. It is designed for high-quality storytelling video and production-ready creative workflows.

HappyHorse 1.0 focuses on strong aesthetics, multi-shot sequencing, and powerful edit-style workflows (generation + editing). It's a great fit for creators building ads, e-commerce visuals, short-form content, and social marketing videos.

## What HappyHorse 1.0 is good at

* **Multi-modal creation paths**: Text-to-Video (T2V), Image-to-Video (I2V), and Subject-to-Video (S2V)
* **Cinematic aesthetics**: Wide-aperture framing, shallow depth of field, refined texture, and atmospheric mood
* **Multi-shot output**: Up to **15s** at **1080p**, with an emphasis on multi-shot consistency across cut transitions
* **Editing workflows**: V2V and SV2V for transforming footage or replacing/inserting subjects while preserving motion and composition

## Example outputs

Image-to-video generation with cinematic aesthetics and multi-shot consistency:

<Columns>
  <video />

  <video />
</Columns>

Text-to-video generation with multi-shot sequencing and refined visual atmosphere:

<video />

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## HappyHorse 1.0 image-to-video

Generate cinematic video from a single image with strong aesthetic control and multi-shot consistency.

<Columns>
  <video />

  <video />
</Columns>

<CardGroup>
  <Card title="Run HappyHorse 1.0 I2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_0_i2v&utm_source=docs&utm_medium=referral&utm_campaign=happyhorse1-0">
    Try the Image-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="HappyHorse 1.0 I2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_0_i2v.json">
    Get the HappyHorse 1.0 Image-to-Video workflow file.
  </Card>
</CardGroup>

![HappyHorse 1.0 Image-to-Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_happyhorse1_0_i2v-1.webp)

<Card title="Download Sample Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/pink_city_horse.png">
  Get the example input image for this workflow.
</Card>

## HappyHorse 1.0 text-to-video

Generate cinematic video from pure text prompts, with multi-shot sequencing and refined visual atmosphere.

<video />

<CardGroup>
  <Card title="Run HappyHorse 1.0 T2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_0_t2v&utm_source=docs&utm_medium=referral&utm_campaign=happyhorse1-0">
    Try the Text-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="HappyHorse 1.0 T2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_0_t2v.json">
    Get the HappyHorse 1.0 Text-to-Video workflow file.
  </Card>
</CardGroup>

![HappyHorse 1.0 Text-to-Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_happyhorse1_0_t2v-1.webp)

## HappyHorse 1.0 reference-to-video

Use a reference subject to drive video generation, preserving identity across cinematic multi-shot sequences.

<CardGroup>
  <Card title="Run HappyHorse 1.0 R2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_0_r2v&utm_source=docs&utm_medium=referral&utm_campaign=happyhorse1-0">
    Try the Reference-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="HappyHorse 1.0 R2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_0_r2v.json">
    Get the HappyHorse 1.0 Reference-to-Video workflow file.
  </Card>
</CardGroup>

![HappyHorse 1.0 Reference-to-Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_happyhorse1_0_r2v-1.webp)

<CardGroup>
  <Card title="Download Car Reference Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/car_ref.png">
    Get the example car reference image.
  </Card>

  <Card title="Download Person Reference Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/man_ref.png">
    Get the example person reference image.
  </Card>
</CardGroup>

## HappyHorse 1.0 video edit

Transform existing footage or replace/insert subjects while preserving motion and composition with V2V and SV2V editing workflows.

<CardGroup>
  <Card title="Run HappyHorse 1.0 Video Edit on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_0_video_edit&utm_source=docs&utm_medium=referral&utm_campaign=happyhorse1-0">
    Try the Video Edit workflow instantly on Comfy Cloud.
  </Card>

  <Card title="HappyHorse 1.0 Video Edit Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_0_video_edit.json">
    Get the HappyHorse 1.0 Video Edit workflow file.
  </Card>
</CardGroup>

![HappyHorse 1.0 Video Edit workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_happyhorse1_0_video_edit-1.webp)

<CardGroup>
  <Card title="Download Sample Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/urban_man.png">
    Get the example input image for the video edit workflow.
  </Card>

  <Card title="Download Sample Input Video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/woman_by_tram.mp4">
    Get the example input video for the video edit workflow.
  </Card>
</CardGroup>


# HappyHorse 1.1 Video Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/happyhorse/happyhorse1-1

Use HappyHorse 1.1 via ComfyUI Partner Nodes for image-to-video, text-to-video, and reference-to-video with native synchronized audio and multi-shot scenes.

HappyHorse 1.1 is the latest release of Alibaba's production-grade video generation model, now available in ComfyUI as a Partner Node. It is engineered for real-world creative production: short episodic series, e-commerce commercials, brand marketing content, and game cutscenes.

A standout feature is **native synchronized audio generation**: HappyHorse 1.1 produces dialogue, sound effects, and background music in a single render pass, with audio tightly bound to the visual timeline. There are no extra audio steps.

Version 1.1 targets five core production-critical capabilities: dynamic expressive motion, consistent character rendering, reliable prompt adherence, stable text rendering, and authentic cinematic framing.

## What HappyHorse 1.1 is good at

* **Native audio-video sync**: Dialogue, SFX, and background music in one pass (no extra steps)
* **Three creation paths**: Text-to-Video (T2V), Image-to-Video (I2V), Reference-to-Video (R2V)
* **Multi-image R2V**: Up to **9 reference images** per generation with preserved identity
* **Multi-character consistency**: Multiple character references stay distinct with no visual cross-contamination
* **Character × scene separation**: Feed characters and scenes as independent references; characters stay consistent as the background changes
* **Long-context prompts**: Handles prompts beyond 2,500 characters; a single prompt can describe 6–8 consecutive scenes with the model autonomously allocating time and switching camera angles
* **Cinematic language**: Full support for shot-reverse-shot, tracking shot, and cohesive transitions/pacing between shots
* **Flexible output**: 720p and 1080p, 3–15 seconds, aspect ratios 16:9 / 9:16 / 1:1 / 4:3 / 3:4 / 21:9 and more
* **Production-ready visuals**: Fixes shiny skin and over-sharpening issues from v1.0 for natural-looking close-ups and series content

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## HappyHorse 1.1 text-to-video

Build a complete scene from scratch. You control style, shot size, lighting, action, and audio entirely through the prompt. HappyHorse 1.1 returns a single video with dialogue, sound effects, and music baked in.

<CardGroup>
  <Card title="Run HappyHorse 1.1 T2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_1_t2v&utm_source=docs&utm_medium=referral&utm_campaign=happyhorse1-1">
    Try the Text-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download HappyHorse 1.1 T2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_1_t2v.json">
    Download the workflow JSON or search "HappyHorse 1.1" in Template Library.
  </Card>
</CardGroup>

![HappyHorse 1.1 Text-to-Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_happyhorse1_1_t2v-1.webp)

## HappyHorse 1.1 image-to-video

Animate a static first frame. The image already carries the look, so you describe the motion and the camera move. HappyHorse 1.1 returns a video with audio baked in.

<CardGroup>
  <Card title="Run HappyHorse 1.1 I2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_1_i2v&utm_source=docs&utm_medium=referral&utm_campaign=happyhorse1-1">
    Try the Image-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download HappyHorse 1.1 I2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_1_i2v.json">
    Download the workflow JSON or search "HappyHorse 1.1" in Template Library.
  </Card>

  <Card title="Download Sample Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/girl_lean_on_horse.png">
    Get the example input image for this workflow.
  </Card>
</CardGroup>

![HappyHorse 1.1 Image-to-Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_happyhorse1_1_i2v-1.webp)

## HappyHorse 1.1 reference-to-video

Orchestrate a multi-character stage play. Map characters and scenes to reference images, then direct them through a timestamped storyboard with per-character dialogue. Up to 9 reference images per generation, with character and scene references separated so characters stay consistent across background changes.

<CardGroup>
  <Card title="Run HappyHorse 1.1 R2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_1_r2v&utm_source=docs&utm_medium=referral&utm_campaign=happyhorse1-1">
    Try the Reference-to-Video workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download HappyHorse 1.1 R2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_1_r2v.json">
    Download the workflow JSON or search "HappyHorse 1.1" in Template Library.
  </Card>

  <Card title="Download Character Reference" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wooden_doll_2_views.png">
    Get the example character reference image.
  </Card>

  <Card title="Download Scene Reference" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/cave_ocean_living_room.png">
    Get the example scene reference image.
  </Card>
</CardGroup>

![HappyHorse 1.1 Reference-to-Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_happyhorse1_1_r2v-1.webp)

## Getting started

1. Update ComfyUI to the latest version
2. Find the HappyHorse nodes via the Node Library (search "HappyHorse") or load a ready-made template from the Templates Library
3. Pick your mode: Text-to-Video, Image-to-Video, or Reference-to-Video
4. Wire in your prompt and any reference images, then run
5. Output arrives with audio baked in at 720p or 1080p


# HeyGen Video 1.0 in ComfyUI: Text, Image, and Reference to Video
Source: https://docs.comfy.org/tutorials/partner-nodes/heygen/heygen-video-1

Generate 5 to 15 second clips with synced dialogue from a prompt, a first frame, or up to 12 reference images, videos, and audio clips in ComfyUI

**HeyGen Video 1.0** is a general-purpose video model from HeyGen that generates the picture, the spoken line, and the ambience in one pass. You describe the shot and the dialogue in the prompt, and the clip comes back with synchronized speech, so a talking-head or product video needs no shoot, no presenter, and no separate voice-over step.

In ComfyUI the model runs through two partner nodes. **HeyGen Video 1.0 Reference to Video** handles text to video on its own and reference to video once images, videos, or audio are connected; **HeyGen Video 1.0 Image to Video** starts from a first frame. Both are cloud API nodes: they need a Comfy account with credits and download no local model. See [Partner Nodes pricing](/tutorials/partner-nodes/pricing) for the per-second rates.

Every run returns a 5 to 15 second clip at 480p or 768p, with the dialogue, room tone, and any music already in the video.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Available workflows

### Text to Video

Generate a clip from a prompt alone. The prompt carries the action, the spoken line, and the sound, so one node run returns a finished talking clip.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_heygen_video_1_t2v&utm_source=docs&utm_medium=referral&utm_campaign=heygen-video-1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_heygen_video_1_t2v.json">
    Download JSON or search "HeyGen Video 1.0: Text to Video" in Template Library
  </Card>
</CardGroup>

The text-to-video template runs the Reference to Video node with nothing connected, which is the text-to-video mode of that node.

### Image to Video

Animate one image. The image is the first frame of the clip, and the output keeps its aspect ratio, so crop the image when you need a different shape. The prompt drives what happens and what is said.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_heygen_video_1_i2v&utm_source=docs&utm_medium=referral&utm_campaign=heygen-video-1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_heygen_video_1_i2v.json">
    Download JSON or search "HeyGen Video 1.0: Image to Video" in Template Library
  </Card>
</CardGroup>

**Input material**

<Card title="model_red_curls_ring.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/model_red_curls_ring.png">
  Load into the `LoadImage` node that feeds the HeyGen Video 1.0 Image to Video node
</Card>

### Reference to Video

Keep people, products, and places consistent across the shot by connecting them as references: up to 9 images, 3 videos, and 3 audio clips, 12 in total. The prompt then addresses them as `@Image1`, `@Video1`, and `@Audio1`, numbered per type in input order.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_heygen_video_1_r2v&utm_source=docs&utm_medium=referral&utm_campaign=heygen-video-1">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_heygen_video_1_r2v.json">
    Download JSON or search "HeyGen Video 1.0: Reference to Video" in Template Library
  </Card>
</CardGroup>

**Input materials**

<CardGroup>
  <Card title="model_black_blazer_red_earrings.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/model_black_blazer_red_earrings.png">
    Load into the first reference image slot · `@Image1`
  </Card>

  <Card title="cognac_leather_handbag.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/cognac_leather_handbag.png">
    Load into the second reference image slot · `@Image2`
  </Card>
</CardGroup>

## Node controls

| Control | Values | Applies to | Effect |
| - | - | - | - |
| `prompt` | text, up to 32000 characters | both nodes | The shot, the spoken line, and the sound. Reference media is addressed as `@Image1`, `@Video1`, `@Audio1` |
| `duration` | 5 to 15 seconds | both nodes | Slider, default 5 |
| `resolution` | `480p`, `768p` | both nodes | Output resolution |
| `aspect_ratio` | `auto`, `16:9`, `9:16`, `1:1`, `4:3`, `3:4`, `21:9` | Reference to Video | `auto` is 16:9 with nothing connected. With references it follows the first reference image, or the first reference video when no images are connected |
| `seed` | integer | both nodes | Results can still vary between runs with the same seed |
| `reference_images` | up to 9 | Reference to Video | One image per slot. A batched input on a single slot is rejected |
| `reference_videos` | up to 3 | Reference to Video | One video per slot |
| `reference_audios` | up to 3 | Reference to Video | Needs at least one reference image or video connected. A voice reference wants a few seconds of clean speech |

The Image to Video node takes the image, the prompt, the duration, the resolution, and the seed. It has no aspect ratio control, because the first frame sets the shape of the clip.

## Prompting tips

* **Write the spoken line into the prompt**. Put the dialogue in quotes as part of the description of the shot, so the model speaks it and matches the lip movement. Both templates ship long example prompts that show the shape: the shot and the subject first, the line in quotes, then the sound and the camera language.
* **Describe the sound with the picture**. Room tone, a piece of music, or the noise an action makes is written into the prompt rather than set with a control. The sample prompts end with the ambience, for example quiet room tone with a faint kettle whistle, or a soft glass clink as an object is set down.
* **Keep a product or presenter consistent**. Connect the product or the person as a reference image and name it in the prompt, then describe how it must stay the same, such as keeping the exact color, proportions, and hardware of a bag from `@Image2`.
* **Shape the shot with references**. With `aspect_ratio` set to `auto`, the framing follows the first reference image, so the reference you connect first decides the shape of the video.
* **Expect variation between runs**. The seed does not lock the result; the same settings can still produce a different take.

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `HeyGen Video 1.0`


# Hunyuan 3D Partner Nodes Model Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/hunyuan3d/hunyuan3d-3-0

This article will introduce how to use Hunyuan 3D node's API in ComfyUI for 3D model generation

Hunyuan 3D 3.0 is Tencent's state-of-the-art 3D generation model that enables minutes-level 3D content creation. It can generate production-ready 3D assets from text prompts, images, or sketches with far lower barriers to entry than traditional 3D modeling pipelines.

ComfyUI has now natively integrated the corresponding Hunyuan 3D API, allowing you to conveniently use the related nodes in ComfyUI for model generation.

Currently, ComfyUI's Partner nodes support the following Hunyuan 3D model generation capabilities:

* Text-to-3D generation
* Image-to-3D generation
* Multi-view-to-3D generation

## What Hunyuan 3D 3.0 is good at

* **Game development ideation**: Fast generation of characters, props, and environments with optimized topology for rigging and real-time rendering
* **Product & e-commerce**: Turn product photos into interactive 3D models for online display
* **Industrial design**: Sketch-to-3D prototyping and 3D-print-ready part decomposition
* **VFX & animation**: High-resolution assets with professional UVs and PBR materials

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Getting started

### 1. Access workflow templates

1. Open the Template Library in the sidebar
2. Navigate to **3D** → **Hunyuan 3D**
3. Select a workflow template for Hunyuan 3D

### 2. Run the workflow

1. Input your text prompt, images, or sketches depending on the workflow type
2. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation
3. After the workflow completes, preview and export your 3D model

### HunYuan3D: Text to Model

Input a text prompt or upload a reference image to generate a detailed 3D model asset.

**Example prompt**: "Mechanical dolphin with gears, steampunk"

<img alt="HunYuan3D: Text to Model workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_text_to_model&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan3d-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_hunyuan3d_text_to_model.json">
    Download JSON or search "HunYuan3D: Text to Model" in Template Library
  </Card>
</CardGroup>

### HY 3D: Image to Model

Upload an image to generate a 3D model with geometry and PBR textures. Upload 2–4 multi-view images from different angles for improved geometry and material fidelity.

<img alt="HY 3D: Image to Model workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan3d-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_hunyuan3d_image_to_model.json">
    Download JSON or search "HY 3D: Image to Model" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="pink_robot_front.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/pink_robot_front.png">
    `LoadImage` node 1 · `pink_robot_front.png`
  </Card>

  <Card title="pink_robot_back.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/pink_robot_back.png">
    `LoadImage` node 10 · `pink_robot_back.png`
  </Card>
</CardGroup>

<div>
  <img alt="pink_robot_front.png" />

  <img alt="pink_robot_back.png" />
</div>

## Advanced features

Following the [initial HY 3D 3.0 integration](https://blog.comfy.org/p/hunyuan-3d-30-in-comfyui-state-of), Hunyuan 3D's advanced processing features are now available via Partner Nodes. These workflows help close the gap between generation and production by bringing key post-processing steps into ComfyUI.

### HY 3D: 3D Parts Decomposition

Upload a 3D model to automatically segment it into its constituent parts, generating a fully decomposed 3D asset for reuse and editing.

<img alt="HY 3D: 3D Parts Decomposition workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_part&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan3d-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_hunyuan3d_part.json">
    Download JSON or search "HY 3D: 3D Parts Decomposition" in Template Library
  </Card>
</CardGroup>

### HY 3D: UV Unwrapping

Upload a 3D model to perform UV unwrapping. Generate a processed model with optimized UV layout for texturing.

<img alt="HY 3D: UV Unwrapping workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_model2uv&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan3d-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_hunyuan3d_model2uv.json">
    Download JSON or search "HY 3D: UV Unwrapping" in Template Library
  </Card>
</CardGroup>

### HY 3D: Smart Topology

Upload a high-poly 3D model file. Generate a lower-polygon, topologically optimized 3D model with a specified reduction level.

<img alt="HY 3D: Smart Topology workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_smart_topology&utm_source=docs&utm_medium=referral&utm_campaign=hunyuan3d-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_hunyuan3d_smart_topology.json">
    Download JSON or search "HY 3D: Smart Topology" in Template Library
  </Card>
</CardGroup>


# Kling 3.0 Video and Image Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/kling/kling-3-0

Learn how to use Kling 3.0 models in ComfyUI for multi-shot video generation, subject consistency, multilingual audio, and native text rendering

Kling 3.0 is one of the most advanced multi-modal generation systems, now available in ComfyUI via Partner Nodes. This release includes **Kling Video 3.0**, **Kling Video 3.0 Omni**, **Kling Image 3.0**, and **Kling Image 3.0 Omni**, bringing video, image, audio-visual, and narrative generation capabilities directly into your node-based workflows.

## What Kling 3.0 is good at

* **Multi-shot generation**: Generate multiple shots with duration control in a single generation
* **Locked subject consistency**: Maintain character and object identity across camera motion and scene evolution
* **Native audio with character awareness**: Multilingual dialogue with precise lip sync and facial expression alignment
* **Native text rendering**: Clear, structured on-screen text for ads, UI scenes, and branded content

## Example outputs

Text-to-image generation with the Kling 3.0 model:

![Kling 3.0: Text to Image example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_kling_v3_t2i.png)

## Available models

| Model | Type | Description |
| - | - | - |
| **Kling Video 3.0** | Video | Standard video generation with multi-shot support |
| **Kling Video 3.0 Omni** | Video | Advanced video generation with audio-visual capabilities |
| **Kling Image 3.0** | Image | High-quality image generation |
| **Kling Image 3.0 Omni** | Image | Multi-modal image generation with enhanced features |

## Learn more

For detailed examples, prompts, and video demonstrations of Kling 3.0's capabilities, check out our blog post:

<Card title="Kling 3.0 Models Are Now Available" icon="newspaper" href="https://blog.comfy.org/p/kling-30-models-are-now-available">
  Read the full announcement with video examples, prompt tips, and feature deep-dives.
</Card>

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Kling 3.0: Text to Image

Generate an image from a text prompt using the Kling 3.0 model.

<img alt="Kling 3.0: Text to Image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_kling_v3_t2i&utm_source=docs&utm_medium=referral&utm_campaign=kling-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_kling_v3_t2i.json">
    Download JSON or search "Kling 3.0: Text to Image" in Template Library
  </Card>
</CardGroup>

**Example output**

![Kling 3.0: Text to Image example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_kling_v3_t2i.png)

## Kling 3.0: Video Generation

Input text or image prompts to generate 15-second video sequences with multi-shot compositions, complex camera movements, and consistent subjects.

<img alt="Kling 3.0: Video Generation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_kling_v3_video&utm_source=docs&utm_medium=referral&utm_campaign=kling-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_kling_v3_video.json">
    Download JSON or search "Kling 3.0: Video Generation" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="boxing.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/boxing.png">
    `LoadImage` node 1 · `boxing.png`
  </Card>
</CardGroup>

<div>
  <img alt="boxing.png" />
</div>

## Kling 3.0: First Last Frame to Video

Input a first and last frame image to generate a continuous video sequence with multi-shot generation and precise element control.

<img alt="Kling 3.0: First Last Frame to Video workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_kling_v3_flf2v&utm_source=docs&utm_medium=referral&utm_campaign=kling-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_kling_v3_flf2v.json">
    Download JSON or search "Kling 3.0: First Last Frame to Video" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="goldenfish_in_bag.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/goldenfish_in_bag.png">
    `LoadImage` node 1 · `goldenfish_in_bag.png`
  </Card>

  <Card title="man_in_daydream.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/man_in_daydream.png">
    `LoadImage` node 13 · `man_in_daydream.png`
  </Card>
</CardGroup>

<div>
  <img alt="goldenfish_in_bag.png" />

  <img alt="man_in_daydream.png" />
</div>

## Legacy Kling models (EOL)

<Warning>
  **End of life (EOL)**: The following legacy Kling models and workflow templates are scheduled for retirement on **September 15, 2026**: Kling V1.5, V1.6, V2.1, V2.1 Master, and the Kolors Virtual Try-On API. Related Partner Nodes remain in ComfyUI but these model options will stop working after the retirement date.
</Warning>

### Retired workflow templates and replacements

| Removed template | Suggested replacement |
| :- | :- |
| `api_kling_i2v` (V2.1 Master) | [`api_kling_o3_i2v`](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_kling_o3_i2v.json) or [`api_kling2_6_i2v`](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_kling2_6_i2v.json) |
| `api_kling_effects` (V1.6) | Kling 3.0 effect workflows (`api_kling_v3_*`) |
| `api_kling_flf` (V1.6) | [`api_kling_v3_flf2v`](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_kling_v3_flf2v.json) or [`api_kling_o3_flf2v`](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_kling_o3_flf2v.json) |
| `api_kling_dual_characters_effects` (V1.6) | Kling 3.0 effect workflows (`api_kling_v3_*`) |

For virtual try-on, use [Flux Virtual Try-On](/built-in-nodes/FluxVTONode) (`api_flux_vto`) or other supported alternatives. Flux VTO and Gemini-based fashion templates are not affected by this retirement.


# Kling 2.6 Motion Control Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/kling/kling-motion-control

Learn how to use the Kling 2.6 Motion Control Partner node in ComfyUI for precise motion transfer from reference videos to character images

Kling 2.6 Motion Control is a specialized multimodal model developed by Kuaishou that enables precise motion transfer from reference videos to character images. By combining a **Reference Image** (your character) and a **Motion Reference Video** (the action), the AI applies the movement, expression, and pacing of the video to your static character while maintaining their identity.

Unlike standard image-to-video generation that guesses motion from text prompts, Motion Control uses a reference video as the movement blueprint. The model acts as a digital puppeteer, extracting choreography from your reference video and applying it to your character with cinema-grade fidelity.

## What Kling 2.6 Motion Control is good at

* **Complex motion handling**: Execute complicated sequences like dance routines, martial arts, or athletic movements without losing character coherence. The model understands weight transfer and momentum for realistic physical impact.
* **Precision hand and finger performance**: Hands have traditionally been a weak point for AI video. This feature specifically improves finger articulation and hand movements by mimicking real footage, making it ideal for presentations and demonstrations.
* **Scene and environment flexibility**: Use text prompts to change the environment while the character continues their referenced motion. You're not limited to the reference video's background.
* **Advanced camera and perspective modes**: Granular control over how the camera interprets your reference with distinct orientation modes.
* **30-second one-shot support**: Generate continuous actions up to 30 seconds in a single generation, enabling uninterrupted character motion for narrative scenes.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Character orientation modes

The `character_orientation` parameter determines how the model interprets spatial information and constrains output duration:

| Mode | Description | Max Duration |
| - | - | - |
| `video` | Output character orientation matches the reference video. Best for complex full-body performances like dance sequences and elaborate choreography. | 30 seconds |
| `image` | Output character orientation matches the reference image. Best for portrait animations with camera movement like pans, tilts, and tracking shots. | 10 seconds |

## Model tiers

| Tier | Resolution | Best For |
| - | - | - |
| **Standard** | 720p | Simple animations, social media content, memes, and quick tests. Faster and more credit-efficient. |
| **Pro** | 1080p | Complex choreography, intricate hand movements, professional marketing assets, and broadcast-quality content. |

## Kling2.6: Motion Control

Apply precise character actions and expressions from a reference video to your character image with synchronized motion control.

<img alt="Kling2.6: Motion Control workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_kling_motion_control&utm_source=docs&utm_medium=referral&utm_campaign=kling-motion-control">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_kling_motion_control.json">
    Download JSON or search "Kling2.6: Motion Control" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` and `LoadVideo` nodes:

<CardGroup>
  <Card title="streetwear_fox.jpg" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/streetwear_fox.jpg">
    `LoadImage` node 11 · `streetwear_fox.jpg`
  </Card>

  <Card title="street_dancer.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/street_dancer.mp4">
    `LoadVideo` node 2 · `street_dancer.mp4`
  </Card>
</CardGroup>

<div>
  <img alt="streetwear_fox.jpg" />
</div>

## Input requirements

* **Image formats**: JPG, PNG, WEBP, GIF, AVIF (max 10MB)
* **Video formats**: MP4, MOV, WEBM, M4V, GIF (max 100MB)
* **Video duration**: 3-30 seconds depending on orientation mode
* **Minimum resolution**: 720px width and height
* **Subject visibility**: Character must clearly show head, shoulders, and torso

## Tips for better results

* **Match aspect ratios**: Ensure your character image and reference video have similar aspect ratios (e.g., both 16:9 or both 9:16) to prevent awkward stretching or cropping.
* **Clean backgrounds**: Use reference videos with simple or static backgrounds for best motion extraction. High-contrast videos where the actor's silhouette is distinct work best.
* **Clear character angles**: If your reference video shows rotation, use 3D-style characters or realistic photos that handle rotation better. Flat 2D cartoons may struggle with back views.
* **Visible limbs**: Ensure the character's limbs are visible in the source image. If a character has hands in pockets but the motion requires waving, the AI will hallucinate hands, often leading to artifacts.
* **Leave breathing room**: Leave negative space around the subject. If the character will dance or move arms wide, they need space within the frame to avoid clipping.
* **Framing alignment**: Match the framing between your image and reference video. Use a close-up reference for face animations, or a full-body reference for walking/dancing sequences.


# LLMs
Source: https://docs.comfy.org/tutorials/partner-nodes/language/overview

Use large language models (LLMs) for chat, prompt writing, and vision inside ComfyUI workflows through Partner Nodes

## Overview

ComfyUI Partner Nodes give you access to large language models (LLMs) from leading providers. These nodes take text and images as input and return text, which makes them useful for prompt writing, image captioning, and conversation alongside your generation nodes.

### Browse LLM partners

<CardGroup>
  <Card title="Claude" icon="message-circle" href="/tutorials/partner-nodes/anthropic/claude">
    Strong reasoning and instruction following from Anthropic
  </Card>

  <Card title="Gemini" icon="message-circle" href="/tutorials/partner-nodes/google/gemini">
    Multimodal reasoning that interprets images and returns rich text prompts
  </Card>

  <Card title="OpenAI Chat" icon="message-circle" href="/tutorials/partner-nodes/openai/chat">
    Chat models with strong general-purpose reasoning and image understanding
  </Card>

  <Card title="OpenRouter LLM" icon="message-circle" href="/tutorials/partner-nodes/openrouter/llm">
    Access many different LLM providers through a single integration
  </Card>
</CardGroup>

## What you can do with LLMs

* **Prompt writing**: Generate or refine prompts for your image, video, and 3D workflows
* **Image captioning & understanding**: Describe images or answer questions about their content
* **Conversation**: Chat with a multimodal model inside your workflow
* **Agentic tasks**: Break down, plan, and orchestrate generation steps across nodes

## Choosing a model by provider

* **Claude** (Anthropic) — strong reasoning and instruction following; excellent at structured prompt engineering
* **Google Gemini** (Google) — multimodal reasoning that interprets images and returns rich text prompts
* **OpenAI Chat** (OpenAI) — chat models with strong general-purpose reasoning and image understanding
* **OpenRouter LLM** (OpenRouter) — access many different LLM providers through a single integration

## All LLM partners

| Partner | Models |
| - | - |
| Anthropic | [Claude](/tutorials/partner-nodes/anthropic/claude) |
| Google | [Gemini](/tutorials/partner-nodes/google/gemini) |
| OpenAI | [OpenAI Chat](/tutorials/partner-nodes/openai/chat) |
| OpenRouter | [OpenRouter LLM](/tutorials/partner-nodes/openrouter/llm) |

See [Pricing](/tutorials/partner-nodes/pricing) for per-model rates, and [Concurrency Limits](/tutorials/partner-nodes/concurrency-limits) for usage caps.


# LTX-2.5 API Video Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/lightricks/ltx-2-5

Use the LTX-2.5 API nodes in ComfyUI for text-to-video, image-to-video, and first-last-frame cloud workflows, with Fast and Pro model tiers.

[LTX-2.5](https://ltx.io/model/ltx-2-5) is Lightricks' open-weights video and world model, available in ComfyUI through the LTX-2.5 API nodes. The API workflows run generation on Lightricks' servers, so no model downloads or local GPU is required, and each second of generated video is billed to your Comfy API account.

The LTX-2.5 API offers two model tiers: **LTX-2.5 (Pro)** for maximum quality, and **LTX-2.5 (Fast)** for faster generation with the distilled model. Both tiers support synchronized audio and video generation with native multishot scenes, and output up to 4K resolution on the Fast tier.

## What LTX-2.5 is good at

* **Synchronized audio and video**: Both tiers generate audio and video together, with native multishot scenes
* **Two model tiers**: LTX-2.5 (Pro) for maximum quality, LTX-2.5 (Fast) for faster generation with the distilled model
* **Up to 4K output**: The Fast tier outputs up to 4K resolution
* **No local GPU required**: Generation runs on Lightricks' servers, with no model downloads
* **Multiple generation modes**: Text-to-video, image-to-video, and first-last-frame-to-video

## Example outputs

Text-to-video generation with synchronized audio:

<video />

Image-to-video generation from a single start image:

<video />

First-last-frame-to-video generation, blending two frames into one animated sequence:

<video />

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## LTX-2.5 API workflows

The template library ships with three API example workflows:

* **Text to Video**: Generate videos from text prompts
* **Image to Video**: Generate videos from a single start image
* **FLF2V**: Generate a video between a first and last frame image

### LTX-2.5 Text to Video

Generate videos from text prompts through the LTX-2.5 API, with synchronized audio.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_ltx2_5_t2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-5-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_ltx2_5_t2v.json">
    Download JSON or search "LTX-2.5 T2V" in Template Library
  </Card>
</CardGroup>

#### Prompting tips

1. **Model**: Choose `LTX-2.5 (Pro)` for the highest quality, or `LTX-2.5 (Fast)` for faster generation
2. **Duration**: Pro supports 2-10 seconds; Fast supports 2-20 seconds. Durations over 10 seconds require a 720p or 1080p resolution and 24/25 FPS
3. **Resolution and ratio**: Choose a resolution preset such as `1280x720` (landscape) or `720x1280` (portrait); Fast adds `2560x1440` and `3840x2160` options
4. **FPS**: Choose between 24, 25, 48, or 50 FPS on Fast, and 24, 25, or 50 FPS on Pro
5. **Audio**: Audio generation is on by default; disable it in the node's advanced settings if you only need a silent video
6. **Prompt**: Describe the whole scene in one flowing paragraph, including the shot, action, characters, camera movement, and the audio you want

### LTX-2.5 Image to Video

Generate a video from a single start image through the LTX-2.5 API, with synchronized audio.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_ltx2_5_i2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-5-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_ltx2_5_i2v.json">
    Download JSON or search "LTX-2.5 I2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Input Image: space_battle.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/space_battle.png">
    Start frame for the workflow, or use your own image.
  </Card>
</CardGroup>

#### Prompting tips

1. **Model**: This workflow ships with `LTX-2.5 (Fast)` selected for faster iteration; switch to `LTX-2.5 (Pro)` for maximum quality
2. **Single image only**: The image input accepts exactly one start image
3. **Prompt**: Describe what happens next: the motion, camera movement, and sounds that follow from the start image. Phrasing like "Use the provided start image as the first frame" helps anchor the generation
4. **Duration and resolution**: The Fast tier supports up to 20 seconds and resolutions up to 4K; durations over 10 seconds require 720p/1080p at 24/25 FPS

### LTX-2.5 FLF2V

Generate a video between a first and last frame image through the LTX-2.5 API, blending both frames into a single animated sequence.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_ltx2_5_flf2v&utm_source=docs&utm_medium=referral&utm_campaign=ltx-2-5-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_ltx2_5_flf2v.json">
    Download JSON or search "LTX-2.5 FLF2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="First Frame: porsche_car_01.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/porsche_car_01.png">
    First frame of the video.
  </Card>

  <Card title="Last Frame: porsche_car_02.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/porsche_car_02.png">
    Last frame of the video, connected to the `last_frame` input of the node.
  </Card>
</CardGroup>

#### Prompting tips

1. **Frames**: The workflow connects the first image to the `image` input and the second image to the `last_frame` input; the model generates the motion between them
2. **Keep frames aligned**: Use images with the same aspect ratio for a smooth interpolation
3. **Model**: This workflow ships with `LTX-2.5 (Pro)` selected; switch to `LTX-2.5 (Fast)` for faster generation
4. **Prompt**: Describe the transition between the frames, and the audio (dialogue, SFX, music) you want


# Luma Image to Video Partner Node
Source: https://docs.comfy.org/tutorials/partner-nodes/luma/luma-image-to-video

Luma Image to Video Partner node workflow: convert a static image into video in ComfyUI, including required credits and node parameters.

The Luma Image to Video node allows you to convert static images into smooth, dynamic videos using Luma AI's advanced technology, bringing life and motion to your images.

## What Luma Image to Video is good at

* **Image animation**: Converts static images into smooth, dynamic videos, bringing life and motion to your images
* **Prompt-guided motion**: Text prompts determine the video's motion effects
* **Camera control**: The Luma Concepts feature controls camera movement for professional cinematography
* **Flexible image inputs**: Works from a `first_image`, a `last_image`, or both
* **Adjustable output**: Video resolution and duration are adjustable, and different video generation models can be selected via the model parameter

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Image to Video Workflow with Luma Partner Nodes

The Luma Image to Video node requires at least one image input (`first_image` or `last_image`) along with text prompts to determine the video's motion effects. In this guide, we've created an example using `first_image` and `luma_concepts` to showcase Luma AI's video generation capabilities.

### 1. Download the Workflow

The workflow information is included in the metadata of the video below. Download and drag it into ComfyUI to load the workflow.

![Luma Image to Video Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/i2v/luma_i2v.mp4)

Download the following image to use as input:

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/i2v/input.png)

### 2. Follow the Workflow Steps

<img alt="Luma Image to Video Workflow Steps" />

Follow these basic steps to run the workflow:

1. Upload your input image in the `first_image` node
2. (Optional) Write prompts in the Luma Image to Video node to describe how you want the image animated
3. (Optional) Modify the `Luma Concepts` node to control camera movement for professional cinematography
4. Click `Run` or use `Ctrl(cmd) + Enter` to generate the video
5. Once the API returns results, view the generated video in the `Save Video` node. The video will also be saved to the `ComfyUI/output/` directory

### 3. Additional Notes

* **Image Input Requirements**: At least one of `first_image` or `last_image` is required, with a maximum of 1 image per input
* **Luma Concepts**: Controls camera movement for professional video effects
* **Seed Parameter**: Only determines if the node should rerun, doesn't affect generation results
* **Enable Input Nodes**: Right-click on purple "Bypass" mode nodes and set "mode" to "always" to enable inputs
* **Model Selection**: Different video generation models have unique characteristics, adjustable via the model parameter
* **Resolution and Duration**: Adjust output video resolution and length using resolution and duration parameters


# Luma Text to Video Partner Nodes ComfyUI Official Guide
Source: https://docs.comfy.org/tutorials/partner-nodes/luma/luma-text-to-video

Learn how to use the Luma Text to Video Partner node in ComfyUI

The Luma Text to Video node allows you to create high-quality, smooth videos from text descriptions using Luma AI's innovative video generation technology.

## What Luma Text to Video is good at

* **Text-to-video generation**: Creates high-quality, smooth videos from text descriptions of scenes, subjects, actions, and mood
* **Camera control**: The Luma Concepts feature adds camera movements for professional video shots and cinematography
* **Model selection**: Different video models with different features are selectable via the model parameter
* **Adjustable output**: Video resolution and duration are adjustable (except with the Ray 1.6 model, where these parameters don't apply)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Text to Video Workflow with Luma Partner Nodes

The Luma Text to Video node requires text prompts to describe the video content. In this guide, we've created examples using `prompt` and `luma_concepts` to showcase Luma AI's excellent video generation capabilities.

### 1. Download the Workflow

The workflow information is included in the metadata of the video below. Download and drag it into ComfyUI to load the workflow.

![Luma Text to Video Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/t2v/luma_t2v.mp4)

### 2. Follow the Steps

<img alt="Luma Text to Video Workflow Steps" />

Follow these basic steps to run the workflow:

1. Write your prompt in the `Luma Text to Video` node to describe the video content you want
2. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to generate the video
3. After the API returns results, you can view the generated video in the `Save Video` node. The video will also be saved to the `ComfyUI/output/` directory

> (Optional) Modify the `Luma Concepts` node to control camera movements and add professional cinematography

### 3. Additional Notes

* **Writing Prompts**: Describe scenes, subjects, actions, and mood in detail for best results
* **Luma Concepts**: Mainly used for camera control to create professional video shots
* **Seed Parameter**: Only determines if the node should rerun, doesn't affect generation results
* **Model Selection**: Different video models have different features, adjustable via the model parameter
* **Resolution and Duration**: Adjust output video resolution and length using these parameters
* **Ray 1.6 Model Note**: Duration and resolution parameters don't work when using the Ray 1.6 model


# Meshy 6 Partner Nodes Model Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/meshy/meshy-6

This article will introduce how to use Meshy 6 node's API in ComfyUI for 3D model generation

Meshy is a leading AI-powered 3D generation platform that enables users to create high-quality 3D models from text prompts, images, or multi-view inputs. ComfyUI has now natively integrated the Meshy API, allowing you to conveniently use the related nodes for 3D model generation.

## About Meshy 6

Meshy 6 is the latest generation of Meshy's 3D model generation technology, featuring significant improvements in geometry quality, texture fidelity, and workflow efficiency.

## What Meshy 6 is good at

* **Smarter geometry**: Improved mesh topology with cleaner edges and more coherent structures
* **Higher texture fidelity**: Enhanced texture generation with better detail preservation and color accuracy
* **Faster workflows**: Optimized generation pipeline for quicker turnaround times
* **Multiple input modes**: Supports text-to-3D, image-to-3D, and multi-view to 3D generation
* **PBR support**: Generate physically-based rendering maps including metallic, roughness, and normal maps

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Text-to-Model Workflow

Generate 3D models directly from text descriptions using Meshy 6.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_meshy_text_to_model&utm_source=docs&utm_medium=referral&utm_campaign=meshy-6">
    Run the text-to-model workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_meshy_text_to_model.json">
    Download the workflow JSON file for local use.
  </Card>
</CardGroup>

![Meshy 6 Text-to-Model workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_meshy_text_to_model-1.webp)

## Image-to-Model Workflow

Convert 2D images into detailed 3D models with Meshy 6's image-to-3D capabilities.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_meshy_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=meshy-6">
    Run the image-to-model workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_meshy_image_to_model.json">
    Download the workflow JSON file for local use.
  </Card>
</CardGroup>

![Meshy 6 Image-to-Model workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_meshy_image_to_model-1.webp)

<Card title="Download Sample Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/robot-warrior.png">
  Get the example input image for this workflow.
</Card>

## Multi-view to Model Workflow

Generate 3D models from multiple view images for more accurate geometry and texture reconstruction.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_meshy_multi_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=meshy-6">
    Run the multi-view workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_meshy_multi_image_to_model.json">
    Download the workflow JSON file for local use.
  </Card>
</CardGroup>

![Meshy 6 Multi-view to Model workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_meshy_multi_image_to_model-1.webp)

<CardGroup>
  <Card title="Download Front View" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/joker_front.jpg">
    Get the example front view image.
  </Card>

  <Card title="Download Back View" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/joker_back.jpg">
    Get the example back view image.
  </Card>

  <Card title="Download Side View" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/joker_side.jpg">
    Get the example side view image.
  </Card>
</CardGroup>


# Meshy 7 in ComfyUI: Text to 3D and Image to 3D Workflows
Source: https://docs.comfy.org/tutorials/partner-nodes/meshy/meshy-7

Generate production-ready 3D models with Meshy 7 in ComfyUI: text-to-3D and image-to-3D workflows with ultra mode, PBR textures, rigging, and animation

Meshy 7 is Meshy's newest 3D generation foundation model, built around image-to-3D alignment. It reads input images at multiple scales and accepts higher-resolution input, so fine shape information survives into generation instead of being averaged out. The result is 3D geometry, color, material, and pattern that stay aligned with the source image.

In ComfyUI, Meshy 7 is available through the Meshy Partner Nodes. You can generate a draft model from a text prompt or a single image, then refine it into a fully textured asset with PBR maps, rig it, and animate it, all inside one workflow.

## What Meshy 7 is good at

* **Text-to-3D and image-to-3D**: Generate a model from a text prompt or a single input image
* **Ultra Mode**: Higher-quality generation for single-view input, available on Meshy 7 and `latest` models
* **PBR texturing**: Generate metallic, roughness, and normal maps with 2K to 8K base color textures
* **Full asset pipeline**: Refine, rig, and animate the generated model in the same workflow

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Meshy 7 text-to-model workflow

Generate a 3D model directly from a text description. The workflow creates the draft mesh with the Meshy 7 Text to Model node, then textures, rigs, and animates it automatically.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_meshy7_text_to_model&utm_source=docs&utm_medium=referral&utm_campaign=meshy-7">
    Run the text-to-model workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_meshy7_text_to_model.json">
    Download the workflow JSON file for local use.
  </Card>
</CardGroup>

![Meshy 7 Text-to-Model workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_meshy7_text_to_model-1.webp)

## Meshy 7 image-to-model workflow

Convert a single 2D image into a detailed 3D model. Meshy 7's multi-scale image encoder preserves fine shape information from the source image, and the workflow textures, rigs, and animates the result in one pass.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_meshy7_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=meshy-7">
    Run the image-to-model workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_meshy7_image_to_model.json">
    Download the workflow JSON file for local use.
  </Card>
</CardGroup>

![Meshy 7 Image-to-Model workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_meshy7_image_to_model-1.webp)

<Card title="Download Sample Input Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/marble_robot_bust.png">
  Get the example input image for this workflow.
</Card>


# MiniMax H3 API Video Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/minimax/minimax-h3

Use the MiniMax H3 API nodes in ComfyUI for text-to-video, first/last-frame, and reference-to-video cloud workflows with native stereo audio.

[MiniMax H3](https://www.minimax.io/blog/minimax-h3) is MiniMax's general-purpose, omni-modal generation model, available in ComfyUI through the MiniMax H3 API nodes. The API workflows run generation on MiniMax's servers, so no model downloads or local GPU is required, and each second of generated video is billed to your Comfy API account.

MiniMax H3 generates video with **native stereo audio**: voice, sound effects, and music are modeled together in a single forward pass instead of being layered on afterward. Output is up to 2K resolution at 5-15 seconds per clip.

**MiniMax H3 Max** is a variant of MiniMax H3 post-trained by fal for high-speed generation, added to the same API nodes in ComfyUI 0.34.2. It generates faster than real time, accepts a prompt of up to 50,000 characters, and offers 480P and 768P resolutions with an optional two-stage graph built from nodes ComfyUI already supports: prompt enhancement through the MiniMax H3 Context IR node, then regeneration to 2K with the MiniMax H3 Regenerate to 2K node.

**MiniMax H3 Max Turbo** is a faster, cheaper H3 Max option added to the Text to Video and First-Last-Frame nodes in ComfyUI 0.34.4. It renders at 480P or 768P and drops resolution ratio controls on the First-Last-Frame node, where the output ratio follows the input frames.

<Note>
  These API workflows run on MiniMax's servers through your Comfy account. To run H3 locally on your own hardware for commercial work, you need a [MiniMax commercial license](https://comfy.org/minimax/license), available through Comfy, the only official reseller.
</Note>

## What MiniMax H3 is good at

* **Native stereo audio**: Voice, sound effects, and music are modeled together with the video in a single forward pass instead of being layered on afterward
* **High-resolution output**: Up to 2K resolution at 5-15 seconds per clip
* **Text-to-video**: Generates videos, with audio, from text prompts
* **First-last-frame video**: Generates the motion between a first frame and an optional last frame image
* **Reference-conditioned generation**: Generates videos conditioned on up to 9 reference images, 3 reference videos, and 3 reference audio clips
* **MiniMax H3 Max**: A faster variant with 480P/768P output, long prompts, and an optional 2K upscale stage. The Reference node accepts up to 12 reference files on H3 Max
* **MiniMax H3 Max Turbo**: The fastest H3 Max option for the Text to Video and First-Last-Frame nodes, at roughly half the Max per-second rate

## Example outputs

Text-to-video generation from a single prompt, with native stereo audio:

<video />

First-last-frame generation, with the model creating the motion between two frames:

<video />

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## MiniMax H3 API workflows

The template library ships with three API example workflows for the base H3 model, four for H3 Max, and two for H3 Max Turbo:

* **Text to Video**: Generate videos from text prompts
* **First-Last-Frame to Video**: Generate a video between a first and last frame image
* **Reference to Video**: Generate videos conditioned on reference images, videos, and audio
* **H3 Max T2V / I2V / FLF2V / R2V**: The same modes through the faster MiniMax H3 Max model, with optional prompt enhancement and 2K upscaling stages built into each workflow
* **H3 Max Turbo T2V / I2V**: Text-to-video and first/last-frame video through the fastest MiniMax H3 Max Turbo model, with the same optional prompt enhancement and 2K upscaling stages

### MiniMax H3 Max

The four `api_minimax_h3_max_*` templates run on the MiniMax H3 Max model through the same API nodes: the Text to Video and First-Last-Frame nodes gained an H3 Max option in ComfyUI 0.34.2, and the Reference to Video node in 0.34.3. Update ComfyUI to at least 0.34.3 to run all of them.

H3 Max generates faster than real time and bills at lower rates than the base model: 15.09 credits/sec at 480P and 24.14 credits/sec at 768P (see the [Minimax pricing table](/tutorials/partner-nodes/pricing)). Each Max template adds two optional stages behind a Switch node, both off by default:

1. **Prompt enhance**: Rewrites the prompt with the MiniMax H3 Context IR node before generation. Turn on the `Prompt Enhance` boolean to enable it
2. **Upscale to 2K**: Runs the MiniMax H3 Regenerate to 2K node on the first-pass video. Turn on the `Upscale to 2K` boolean to enable it

Keep the following in mind when wiring a Max template:

* **Generate at 768P if you plan to upscale**: The Regenerate to 2K node only accepts 768P source video
* **Match durations across nodes**: Generation and prompt enhance must use the same duration, or the stages drift out of sync. The Regenerate to 2K node has no duration input; it re-renders the submitted 768P video at its original duration
* **Duplicate extra inputs**: The three nodes do not share extra context automatically. If you add a reference video, audio, or another image, plug the same wires into both the Context IR and Regenerate nodes

### MiniMax H3 Text to Video

Generate videos from text prompts through the MiniMax H3 API, with native stereo audio.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_minimax_h3_t2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_minimax_h3_t2v.json">
    Download JSON or search "MiniMax H3 T2V" in Template Library
  </Card>
</CardGroup>

#### Prompting tips

1. **Prompt**: Describe the whole scene and the accompanying audio (dialogue, SFX, music) in one block
2. **Duration**: The duration input supports 5-15 seconds; the workflow ships with a fast 5-second preview
3. **Resolution and ratio**: The API renders at 2K; choose an aspect ratio preset such as `16:9`, `9:16`, or `1:1`
4. **Watermark**: The AIGC watermark is off by default; enable it in the node's advanced settings if required

#### Prompt writing guide

MiniMax publishes an official [video prompt writing guide](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_base_en.md) for the base generation modes: T2VA, I2VA, FL2VA, and L2VA. The guide explains how to structure a prompt into timed shots with camera movement and audio (dialogue, SFX, music), and includes examples for each mode.

#### MiniMax H3 Max: Text to Video

Generate videos from text prompts on the faster H3 Max model. The template renders at 768P by default, with optional prompt enhancement and 2K upscaling stages.

![MiniMax H3 Max Text to Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_minimax_h3_max_t2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_minimax_h3_max_t2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_minimax_h3_max_t2v.json">
    Download JSON or search "MiniMax H3 Max: Text to Video" in Template Library
  </Card>
</CardGroup>

#### MiniMax H3 Max Turbo: Text to Video

Generate videos from text prompts on the fastest H3 Max Turbo model. The template renders at 768P and 1:1 by default, with the same optional prompt enhancement and 2K upscaling stages as the Max templates. Requires ComfyUI 0.34.4 or later.

![MiniMax H3 Max Turbo Text to Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_minimax_h3_max_turbo_t2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_minimax_h3_max_turbo_t2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_minimax_h3_max_turbo_t2v.json">
    Download JSON or search "MiniMax H3 Turbo: Text to Video" in Template Library
  </Card>
</CardGroup>

### MiniMax H3 First-Last-Frame to Video

Generate a video between a first frame and an optional last frame image through the MiniMax H3 API. The aspect ratio of the output follows the input images.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_minimax_h3_flf2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_minimax_h3_flf2v.json">
    Download JSON or search "MiniMax H3 FLF2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="First Frame: angel-warrior-demon-battle-start.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/angel-warrior-demon-battle-start.png">
    First frame for the workflow, or use your own image.
  </Card>

  <Card title="Last Frame: angel-warrior-demon-battle-end.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/angel-warrior-demon-battle-end.png">
    Last frame for the workflow, or use your own image.
  </Card>
</CardGroup>

#### Prompting tips

1. **Frames**: The `first_frame` input is required; `last_frame` is optional. The model generates the motion between them
2. **Aspect ratio**: The output follows the input images, so keep both frames at the same aspect ratio
3. **Image constraints**: Each frame's width and height must be between 256 and 5760 pixels, with an aspect ratio between 2:5 and 5:2
4. **Prompt**: Describe the transition between the frames, and the audio (dialogue, SFX, music) you want

#### Prompt writing guide

MiniMax publishes an official [video prompt writing guide](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_base_en.md) for the base generation modes: T2VA, I2VA, FL2VA, and L2VA. The guide explains how to structure a prompt into timed shots with camera movement and audio (dialogue, SFX, music), and includes examples for each mode.

#### MiniMax H3 Max: Image to Video

Animate a still image on the faster H3 Max model. The template feeds a first frame into the First-Last-Frame node (the last frame stays optional) and ships with optional prompt enhancement and 2K upscaling stages.

![MiniMax H3 Max Image to Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_minimax_h3_max_i2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_minimax_h3_max_i2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_minimax_h3_max_i2v.json">
    Download JSON or search "MiniMax H3 Max: Image to Video" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Input Image: sneaker_black.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/sneaker_black.png">
    Input image for the workflow, or use your own.
  </Card>
</CardGroup>

#### MiniMax H3 Max Turbo: Image to Video

Animate a still image on the fastest H3 Max Turbo model. The template feeds a first frame into the First-Last-Frame node and ships with optional prompt enhancement and 2K upscaling stages. Requires ComfyUI 0.34.4 or later.

![MiniMax H3 Max Turbo Image to Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_minimax_h3_max_turbo_i2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_minimax_h3_max_turbo_i2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_minimax_h3_max_turbo_i2v.json">
    Download JSON or search "MiniMax H3 Max Turbo: Image to Video" in Template Library
  </Card>
</CardGroup>

### MiniMax H3 Reference to Video

Generate videos conditioned on reference images, videos, and audio through the MiniMax H3 API.

![MiniMax H3 Reference to Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_minimax_h3_r2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_minimax_h3_r2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_minimax_h3_r2v.json">
    Download JSON or search "MiniMax H3 R2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Reference Image: 9panel_storyboard_golden_hour_clay_court.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/9panel_storyboard_golden_hour_clay_court.png">
    Storyboard reference for the workflow, or use your own images.
  </Card>
</CardGroup>

#### Prompting tips

1. **Reference by tag**: Refer to each input by its order in the prompt, for example `Image 1`, `Video 1`, or `Audio 1`
2. **Limits**: Up to 9 reference images, 3 reference videos, and 3 reference audio clips. Each video or audio clip must be 2-15 seconds; total reference video and audio is capped at 15 seconds each
3. **Audio needs a visual anchor**: Reference audio cannot be used without at least one reference image or video
4. **Video requirements**: Reference videos must be 23.976-60 FPS
5. **Prompt**: Assign each reference a job (identity, style, motion, voice) and describe the target shot; explicit assignments tend to work much better

#### Prompt writing guide

MiniMax publishes an official [full-reference mode prompt guide](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_ref_en.md) for reference-driven generation (R2V). The guide covers the rewrite output structure, including subject definitions, reference labels, and retention analysis, and how to assign each reference a role in the target shot.

#### MiniMax H3 Max: First-Last-Frame to Video

Generate a video between a first and last frame image on the faster H3 Max model, with optional prompt enhancement and 2K upscaling stages.

![MiniMax H3 Max First-Last-Frame to Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_minimax_h3_max_flf2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_minimax_h3_max_flf2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_minimax_h3_max_flf2v.json">
    Download JSON or search "MiniMax H3 Max: FLF2V" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="First Frame: dream_face_first.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/dream_face_first.png">
    First frame for the workflow, or use your own image.
  </Card>

  <Card title="Last Frame: dream_face_last.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/dream_face_last.png">
    Last frame for the workflow, or use your own image.
  </Card>
</CardGroup>

#### MiniMax H3 Max: Reference to Video

Generate videos conditioned on reference media on the faster H3 Max model. The Reference node accepts up to 12 reference files in total on H3 Max, with a `reference_detail` option that trades reference image resolution for cost.

![MiniMax H3 Max Reference to Video workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_minimax_h3_max_r2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_minimax_h3_max_r2v&utm_source=docs&utm_medium=referral&utm_campaign=minimax-h3-api">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_minimax_h3_max_r2v.json">
    Download JSON or search "MiniMax H3 Max: Reference to Video" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Reference Image: burdened_warrior_in_dreamscape.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/burdened_warrior_in_dreamscape.png">
    Reference image for the workflow, or use your own images.
  </Card>
</CardGroup>


# Moonvalley Partner Nodes Official ComfyUI Example
Source: https://docs.comfy.org/tutorials/partner-nodes/moonvalley/moonvalley-video-generation

This article introduces how to use Moonvalley Partner nodes for text-to-video, image-to-video, and video-to-video capabilities in ComfyUI.

<Warning>
  **Service unavailable**: The Moonvalley API service is no longer available. These nodes have been deprecated and may not function as expected.
</Warning>

<iframe title="ComfyUI Selection Toolbox New Features" />

Moonvalley Marey Realism v1.5 is an AI video generation model designed for cinematic-level creation. The model is **trained entirely with commercially licensed content**, ensuring **copyright compliance and commercial safety**.

## What Moonvalley is good at

* Exceptional prompt comprehension: Accurately interprets complex prompt instructions.
* Native 1080p HD quality: The training dataset is based on **1080P** videos, resulting in fine and detailed output.
* Realistic physics and dynamic performance: Precisely simulates physical motion models and natural dynamics, delivering professional-grade realism.
* Complex scene layering and advanced lighting effects: Supports foreground, midground, and background layering in complex scenes, with intelligent spatial relationship understanding.
* Production-level control features such as motion and pose transfer: Automatically generates realistic lighting for composite scenes.

Currently, Moonvalley-related Partner nodes are natively supported in ComfyUI. You can use the corresponding text-to-video, image-to-video, and video-to-video capabilities directly in ComfyUI.

<Warning>
  **Service unavailable**: The Moonvalley API service is no longer available. These nodes have been deprecated and may not function as expected.
</Warning>

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Moonvalley Text-to-Video Workflow

### 1. Download the Workflow File

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/moonvalley/api_moonvalley_text_to_video.json">
  <p>Download the workflow file in JSON format</p>
</a>

### 2. Follow the Steps to Run the Workflow

<img alt="Text-to-Video Workflow" />

1. Enter the positive prompt (content you want to appear in the video)
2. Enter the negative prompt (content you do not want to appear in the video)
3. Modify the video output resolution
4. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to start video generation
5. After the API returns the result, you can view the generated video in the `Save Video` node. The video will also be saved in the `ComfyUI/output/` directory

## Moonvalley Image-to-Video Workflow

### 1. Download the Workflow File

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/moonvalley/api_moonvalley_image_to_video.json">
  <p>Download the workflow file in JSON format</p>
</a>

Download the image below as the input image

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/moonvalley/api_moonvalley_image_to_video_input.webp)

### 2. Follow the Steps to Run the Workflow

<img alt="Image-to-Video Workflow" />

1. Load the input image in the `Load Image` node
2. Enter the positive prompt (content you want to appear in the video)
3. Enter the negative prompt (content you do not want to appear in the video)
4. Modify the video output resolution
5. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to start video generation
6. After the API returns the result, you can view the generated video in the `Save Video` node. The video will also be saved in the `ComfyUI/output/` directory

## Moonvalley Video-to-Video Workflow

The `Moonvalley Marey Video to Video` node allows you to input a reference video for video re-drawing. You can use the reference video's motion or character poses for video generation.

### 1. Download the Workflow File

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/moonvalley/api_moonvalley_video_to_video.json">
  <p>Download the workflow file in JSON format</p>
</a>

Download the video below as the input video:

<video />

### 2. Follow the Steps to Run the Workflow

<img alt="Video-to-Video Workflow" />

1. Load the reference video (or your own material) in the `Load Video` node
   * If the final video duration is 5s, the input video must be longer than 5s
   * If the final video duration is 10s, the input video must be longer than 10s
2. Enter the positive prompt (content you want to appear in the video)
3. Enter the negative prompt (content you do not want to appear in the video)
4. Set the `control_type` parameter to choose the reference type for video re-drawing
   * `Motion Transfer`: Generate based on the motion in the reference video
   * `Pose Transfer`: Generate based on the character poses in the reference video
5. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to start video generation
6. After the API returns the result, you can view the generated video in the `Save Video` node. The video will also be saved in the `ComfyUI/output/` directory


# OpenAI Chat Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/openai/chat

This article will introduce how to use OpenAI Chat Partner nodes in ComfyUI to complete conversational functions

OpenAI is a company focused on generative AI, providing powerful conversational capabilities. Currently, ComfyUI has integrated the OpenAI API, allowing you to directly use the related nodes in ComfyUI to complete conversational functions.

## What OpenAI Chat is good at

* **Intelligent conversations**: engage with OpenAI's advanced language models directly inside ComfyUI
* **Image understanding**: load an image for the AI to interpret and respond to
* **Task control**: adjust `OpenAI Chat Advanced Options` to have the AI execute specific tasks, such as analyzing an image and generating a prompt
* **Model choice**: select different OpenAI models from the `OpenAI Chat` node
* **Multiple image input**: batch several images together when more than one image needs AI interpretation

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## OpenAI: ChatGPT

Engage with OpenAI's advanced language models for intelligent conversations.

<img alt="OpenAI: ChatGPT workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openai_chat&utm_source=docs&utm_medium=referral&utm_campaign=chat">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openai_chat.json">
    Download JSON or search "OpenAI: ChatGPT" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="example.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/example.png">
    `LoadImage` node 5 · `example.png`
  </Card>
</CardGroup>

<div>
  <img alt="example.png" />
</div>

## Complete the workflow execution step by step

<img alt="OpenAI Chat Step Guide" />

<Note>
  In the corresponding template, we have built a role setting for analyzing prompt generation.
</Note>

You can refer to the numbers in the image to complete the basic text-to-image workflow execution:

1. In the `Load Image` node, load the image you need AI to interpret
2. (Optional) If needed, you can modify the settings in `OpenAI Chat Advanced Options` to have AI execute specific tasks
3. In the `OpenAI Chat` node, you can modify `Prompt` to set the conversation prompt, or modify `model` to select different models
4. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the conversation.
5. After waiting for the API to return results, you can view the corresponding AI returned content in the `Preview Any` node.

## Additional Notes

* Currently, the file input node `OpenAI Chat Input Files` requires files to be uploaded to the `ComfyUI/input/` directory first. This node is being improved, and we will modify the template after updates
* The workflow provides an example using `Batch Images` for input. If you have multiple images that need AI interpretation, you can refer to the step diagram and use right-click to set the corresponding node mode to `Always` to enable it


# GPT-6 Astra in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/openai/gpt-6-astra

Use OpenAI GPT-6 Astra through the OpenAI Chat node for complex reasoning, image analysis, prompt generation, and LLM-driven workflows in ComfyUI

**GPT-6 Astra** is OpenAI's most capable model, built for the hardest end-to-end work: complex reasoning, coding, computer use, research, and document creation. Released on September 3, 2026, it supports a 1,050,000-token context window, text and image input, and reasoning effort levels from `low` through `max`.

In ComfyUI, GPT-6 Astra runs through the `OpenAI Chat` node: select `gpt-6-astra` in the node's `model` dropdown. This page focuses on how to use the model inside ComfyUI workflows. For node basics shared by all models, see the [OpenAI Chat tutorial](/tutorials/partner-nodes/openai/chat).

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## When to pick GPT-6 Astra

The `OpenAI Chat` node offers many models, from `gpt-5-nano` to `gpt-6-astra`. GPT-6 Astra is the strongest but also the most expensive option, so it fits tasks where cheaper models struggle:

* **Long-context image analysis**: feeding many images (via `Batch Images`) or large prompt files and asking for a structured analysis in one pass
* **Prompt engineering**: turning a reference image or a rough idea into a detailed, comma-separated positive prompt for image or video models
* **Agentic workflows**: multi-step tasks like analyzing a dataset description, then writing a generation plan, then drafting the prompts themselves
* **Complex instruction following**: precise output formats (JSON, YAML, fixed section order) that smaller models tend to break

For simple captioning or short answers, `gpt-5` or `gpt-5-mini` produce good results at a fraction of the cost. See the [pricing table](/tutorials/partner-nodes/pricing) for the per-model rates.

## Using the model in the OpenAI Chat node

The `OpenAI Chat` node takes:

* `prompt`: the instruction. For prompt-generation tasks, describe exactly what to extract from the image and the output format you want
* `images`: optional image context. Connect a `LoadImage`, or `Batch Images` for multiple images; every connected image is sent to the model
* `files`: optional documents from the `OpenAI Chat Input Files` node
* `advanced_options`: optional configuration from the `OpenAI Chat Advanced Options` node

The output is a `String`. Typical ways to use it downstream:

* Into a `Preview Any` node to read the response
* Into `Save Text` to write the generated prompt to a `.txt` file
* Into the positive prompt input of a `CLIP Text Encode` node, creating fully automatic image or video generation pipelines where the LLM writes the prompt
* Into text inputs of partner nodes, for example to draft a scene description before video generation

## Reasoning effort

GPT-6 Astra is a reasoning model. Connect an `OpenAI Chat Advanced Options` node and set `reasoning_effort` to control the trade-off between response quality and cost:

| Level | Behavior |
| - | - |
| `default` | The model chooses automatically |
| `low` | Fastest and cheapest, good for straightforward analysis |
| `medium` | Balanced default for prompt generation |
| `high` | Thorough analysis of complex images or instructions |
| `xhigh` | Deep multi-step reasoning |
| `max` | Maximum reasoning for the hardest tasks |

The same node also exposes `max_output_tokens` (16 to 16384, including reasoning tokens) and an `instructions` field that acts as a persistent system prompt, useful for fixing an output format across many runs.

## GPT-6 Astra template

A separate template shows GPT-6 Astra analyzing an image and generating a structured AI art prompt from it. The workflow loads an image, sends an analysis prompt to the `OpenAI Chat` node with `model` set to `gpt-6-astra`, and writes the result to a text file through `Save Text`.

![GPT-6 Astra workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_openai_gpt6_astra-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openai_gpt6_astra&utm_source=docs&utm_medium=referral&utm_campaign=gpt6-astra">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openai_gpt6_astra.json">
    Download JSON or search "GPT-6 Astra" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="blue_poppies_field.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/blue_poppies_field.png">
    `LoadImage` node · `blue_poppies_field.png`
  </Card>
</CardGroup>

Steps:

1. Load your image in the `LoadImage` node
2. In the `OpenAI Chat` node, adjust the analysis prompt or switch `model` as needed. The template's prompt asks the model to extract subject, composition, camera, lighting, color palette, texture, and style, then output a comma-separated positive prompt only
3. Click `Run`. The generated prompt appears in the preview and is saved to a `.txt` file by the `Save Text` node

To go further, copy the saved prompt into a `CLIP Text Encode` node or an image / video model node and generate directly from the model's output.

GPT-6 Astra bills from API token usage, at a higher rate than other OpenAI Chat models. See the [pricing table](/tutorials/partner-nodes/pricing) for details.


# OpenRouter LLM Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/openrouter/llm

Use the OpenRouter LLM partner node in ComfyUI for chat, reasoning, vision, and web-grounded answers across multiple frontier models.

[OpenRouter](https://openrouter.ai) is a unified routing platform for large language models. It exposes many providers through one API so you can switch models without changing your integration. ComfyUI connects through the **OpenRouter LLM** partner node, which offers a curated list of text and multimodal models (Claude, GPT, Gemini, Grok, DeepSeek, Qwen, Mistral, GLM, Kimi, and Perplexity Sonar) in a single node.

## What OpenRouter LLM is good at

* **Text chat**: prompts and optional `system_prompt` for role or task instructions
* **Vision**: attach reference images on supported models (slot count depends on the model)
* **Video input**: Gemini 3.5 Flash and Qwen 3.6 Plus/Flash support optional reference videos
* **Reasoning**: `reasoning_effort` on reasoning / frontier-reasoning models (`off`, `low`, `medium`, `high`)
* **Web search**: Perplexity Sonar models expose `search_context_size` for grounded answers

Token pricing is listed under [Partner Node Pricing](/tutorials/partner-nodes/pricing#openrouter).

## Supported models

| Model | Vision (max images) | Video | Extra options |
| :- | :- | :- | :- |
| `anthropic/claude-opus-4.8` | 20 | None | Reasoning effort |
| `anthropic/claude-opus-4.7` | 20 | None | Reasoning effort |
| `anthropic/claude-fable-5` | 20 | None | Reasoning effort |
| `anthropic/claude-sonnet-5` | 20 | None | Reasoning effort |
| `anthropic/claude-haiku-4.5` | 20 | None | Reasoning effort |
| `openai/gpt-5.6-sol-pro` | 20 | None | Reasoning effort |
| `openai/gpt-5.6-sol` | 20 | None | Reasoning effort |
| `openai/gpt-5.6-terra-pro` | 20 | None | Reasoning effort |
| `openai/gpt-5.6-terra` | 20 | None | Reasoning effort |
| `openai/gpt-5.6-luna-pro` | 20 | None | Reasoning effort |
| `openai/gpt-5.6-luna` | 20 | None | Reasoning effort |
| `openai/gpt-5.5-pro` | 20 | None | Reasoning effort |
| `openai/gpt-5.5` | 20 | None | Reasoning effort |
| `google/gemini-3.5-flash` | 20 | Up to 4 | Reasoning effort |
| `x-ai/grok-4.5` | 20 | None | Reasoning effort |
| `x-ai/grok-4.20` | 20 | None | Reasoning effort |
| `x-ai/grok-4.3` | 20 | None | Reasoning effort |
| `deepseek/deepseek-v4-pro` | None | None | Reasoning effort |
| `deepseek/deepseek-v4-flash` | None | None | Reasoning effort |
| `deepseek/deepseek-v3.2` | None | None | Reasoning effort |
| `qwen/qwen3.6-max-preview` | None | None | Reasoning effort |
| `qwen/qwen3.6-plus` | 10 | Up to 4 | Reasoning effort |
| `qwen/qwen3.6-flash` | 10 | Up to 4 | Reasoning effort |
| `mistralai/mistral-large-2512` | 8 | None | None |
| `mistralai/mistral-medium-3-5` | 8 | None | Reasoning effort |
| `z-ai/glm-4.6` | None | None | Reasoning effort |
| `z-ai/glm-5` | None | None | Reasoning effort |
| `moonshotai/kimi-k3` | 10 | None | Reasoning effort |
| `moonshotai/kimi-k2.6` | 10 | None | Reasoning effort |
| `moonshotai/kimi-k2-thinking` | None | None | Reasoning effort |
| `perplexity/sonar-pro` | None | None | Search context size |
| `perplexity/sonar-reasoning-pro` | None | None | Search context size, reasoning effort |
| `perplexity/sonar-deep-research` | None | None | Search context size, reasoning effort |

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model-specific inputs

The **model** dropdown is a dynamic combo. When you change the model, the node updates which inputs appear:

* **Image slots**: shown only for vision-capable models; the number of slots matches the model limit
* **Video slots**: shown only on Gemini 3.5 Flash and Qwen 3.6 Plus/Flash
* **Reasoning effort**: shown on reasoning and frontier-reasoning models
* **Search context size**: shown on Perplexity Sonar models

Text-only models hide image and video inputs.

### OpenRouter LLM

Select a model from OpenRouter's curated list (Claude, GPT, Gemini, etc.). Generate a text response with optional media uploads for vision-capable models.

<img alt="OpenRouter LLM workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openrouter_llm&utm_source=docs&utm_medium=referral&utm_campaign=llm">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openrouter_llm.json">
    Download JSON or search "OpenRouter LLM" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="contact_sheet_app_input_1.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/contact_sheet_app_input_1.png">
    `LoadImage` node 2 · `contact_sheet_app_input_1.png`
  </Card>
</CardGroup>

<div>
  <img alt="contact_sheet_app_input_1.png" />
</div>

<Note>
  In this sample, the workflow analyzes a reference image and returns a text-to-image prompt for downstream image nodes. You can omit **Load Image**, change the prompts, or rebuild the graph entirely for your own use case.
</Note>

If you use the template as a reference, a typical run looks like this:

1. In **Load Image**, load the reference image (skip for text-only chat)
2. In **OpenRouter LLM**, connect the image to `image_1` (more slots appear when the model supports them)
3. Set **prompt**, e.g. ask the model to analyze the image and output a generation prompt
4. (Optional) Set **system\_prompt** in advanced options for tone, format, or constraints
5. Pick a **model**; adjust **reasoning\_effort** or **search\_context\_size** when shown
6. Click **Run** or press `Ctrl(cmd) + Enter`
7. View the reply in **Preview Any**

### Additional notes

* **seed**: set to `0` to omit; most models treat it as a hint only
* Reference images and videos are uploaded automatically when the workflow runs; you only wire ComfyUI image/video outputs into the node
* For pricing per model, see [OpenRouter on the pricing page](/tutorials/partner-nodes/pricing#openrouter)


# Pruna P-Video-2: Text and Image to Video in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/pruna/p-video-2

Generate video with the Pruna P-Video-2 partner nodes in ComfyUI: 720p and 1080p output, 1 to 20 second clips, native audio, draft mode, and audio-driven motion.

Pruna P-Video-2 is Pruna's quality-focused video generation model, available in ComfyUI through two partner nodes: **Pruna P-Video-2 Text to Video** and **Pruna P-Video-2 Image to Video**. It produces clips from 1 to 20 seconds at 720p or 1080p, at 24 or 48 fps, in seven aspect ratios (16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 1:1), with native audio: ambience, sound effects, and lip-synced dialogue generated from the prompt.

The image-to-video node animates a first frame with an optional last frame, and both nodes accept an optional audio input that drives the motion and becomes the soundtrack. A draft mode renders faster, less detailed previews billed at 60% of the standard rate, so you can iterate on composition before committing to a full-quality render.

The nodes run entirely on Pruna's servers through the Comfy API. No model downloads or local GPU are required; you need a Comfy API account with credits.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## What P-Video-2 is good at

* **Native audio**: generates a soundtrack with ambience, sound effects, and lip-synced dialogue, or follows a connected audio track
* **Flexible output**: 720p or 1080p at 24 or 48 fps, 1 to 20 seconds (or `auto` duration chosen from the prompt), seven aspect ratios
* **Draft mode**: faster, less detailed previews at 60% of the standard rate
* **First and last frame**: image-to-video animates between two images with closely matched aspect ratios

Pricing depends on resolution and draft mode, billed per second. See [Pricing](/tutorials/partner-nodes/pricing) for details.

## P-Video-2: Text to Video

Generate a video from a text prompt.

<img alt="Pruna P-Video-2 Text to Video Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_pruna_p_video_t2v&utm_source=docs&utm_medium=referral&utm_campaign=pruna_p_video_t2v">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_pruna_p_video_t2v.json">
    Download JSON or search "Prune P-Video 2: Text to Video" in Template Library
  </Card>
</CardGroup>

### Steps to Run

1. **Enter your prompt**: describe the scene, its motion, and its sound in the **Pruna P-Video-2 Text to Video** node (up to 5000 characters)
2. **Set duration and resolution**: pick 1 to 20 seconds or `auto`, then 720p (about 0.9 megapixels) or 1080p (about 2 megapixels)
3. **Choose the frame rate**: 24 or 48 fps. 48 fps is not available with draft at 1080p
4. **Optional: connect audio**: an audio input drives the motion and sets the video length instead of `duration` (1 to 20 seconds; longer audio is truncated)
5. **Click Queue**: press `Ctrl+Enter` to generate

### Tips

* `enhance_prompt` (on by default) rewrites short prompts with more detail. Turn it off to reproduce a result exactly with the same seed
* `generate_audio` can be turned off for a silent clip

## P-Video-2: Image to Video

Animate an image into a video, with an optional last frame.

<img alt="Pruna P-Video-2 Image to Video Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_pruna_p_video_i2v&utm_source=docs&utm_medium=referral&utm_campaign=pruna_p_video_i2v">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_pruna_p_video_i2v.json">
    Download JSON or search "Prune P-Video 2: Image to Video" in Template Library
  </Card>
</CardGroup>

### Steps to Run

1. **Upload a first frame**: connect a **LoadImage** node. The output keeps the aspect ratio of this image
2. **Optional: upload a last frame**: the video ends on this image. Its aspect ratio must be close to the first frame's
3. **Describe the motion and sound**: write how the scene moves and sounds in the prompt (up to 5000 characters)
4. **Set duration, resolution, and frame rate**: same options as text to video
5. **Click Queue**: press `Ctrl+Enter` to generate

### Input asset

The example workflow uses this sample image:

* [alien\_mothership\_foggy\_megacity.png](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/alien_mothership_foggy_megacity.png)

## Node options reference

| Option | Values | Default | Notes |
| - | - | - | - |
| `duration` | 1 to 20, or auto | 5 | Ignored when audio is connected; the video then follows the audio length |
| `resolution` | 720p / 1080p | 720p | 720p is about 0.9 MP, 1080p about 2 MP at 16:9 |
| `fps` | 24 / 48 | 24 | 48 fps unavailable with draft at 1080p |
| `draft` | on / off | off | Faster, less detailed render at 60% of the standard rate |
| `generate_audio` | on / off | on | Ignored when audio is connected |
| `enhance_prompt` | on / off | on | Advanced. Turn off for exact seed reproducibility |
| `seed` | 0 to 2147483647 | 42 | Exact reproducibility requires enhance\_prompt off |


# Qwen Image 3.0 Pro - Advanced AI Image Generation
Source: https://docs.comfy.org/tutorials/partner-nodes/qwen/qwen-image-3-0-pro

Generate information-dense images with ultra-long prompts, precise small-text rendering, and multi-image editing using Qwen Image 3.0 Pro in ComfyUI

Qwen Image 3.0 Pro is Alibaba's third-generation image generation model, built around useful output: infographics, documents, and instruction-based editing rather than pure aesthetics. It is positioned as a tool for creating dense, information-rich visuals in a single pass, with the tagline "Rich Content, Authentic Details, Deep Knowledge."

The model accepts prompts of up to 4,500 tokens, roughly 4.5 times the input length of the previous generation. It uses that budget to compose newspaper pages, multi-panel infographics, academic papers with legible math notation, and other high-density layouts without compressing the brief into a few sentences. It also renders legible small text down to about 10 pixels across 12 languages and 20+ fonts, and integrates world knowledge for tasks like weather maps and live-stream interface replication.

## What Qwen Image 3.0 Pro is good at

* **Ultra-long prompts**: Accepts up to 4,500 tokens of instructions for detailed, information-dense compositions
* **Dense, practical layouts**: Generates full newspaper pages, multi-panel infographics, and academic documents with formulas in one pass
* **Small text rendering**: Produces legible text down to roughly 10px across 12 languages and 20+ fonts
* **World-knowledge integration**: Generates content grounded in real-world information, such as weather maps for named cities
* **Instruction-based editing**: Edits up to 3 reference images with targeted changes to objects, styles, or regions
* **Batch generation**: Generates 1 to 6 images per run

## Example outputs

Text-to-image generation, with the model handling layout, typography, and composition:

![Qwen Image 3.0 Pro text to image example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_qwen3_t2i.png)

Instruction-based image editing, preserving the original structure:

![Qwen Image 3.0 Pro image edit example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_qwen3_image_edit.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Qwen Image 3.0 Pro text-to-image workflow

Generate a detailed image from a text prompt, with Qwen Image 3.0 Pro handling layout, typography, and composition.

<img alt="Qwen Image 3.0 Pro Text-to-Image workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_qwen3_t2i&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image-3-0-pro">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_qwen3_t2i.json">
    Download JSON or search "Qwen Image 3.0 Pro" in Template Library
  </Card>
</CardGroup>

![Qwen Image 3.0 Pro text to image preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_qwen3_t2i.png)

## Qwen Image 3.0 Pro image edit workflow

Edit existing images with text instructions. Combine up to 3 reference images, change objects, swap styles, or recompose scenes while preserving the original structure.

<img alt="Qwen Image 3.0 Pro Image Edit workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_qwen3_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=qwen-image-3-0-pro">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_qwen3_image_edit.json">
    Download JSON or search "Qwen Image 3.0 Pro" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wasteland_merchant.png">
      Download sample input image
    </Card>
  </CardGroup>
</details>

![Qwen Image 3.0 Pro image edit input](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wasteland_merchant.png)

![Qwen Image 3.0 Pro image edit output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_qwen3_image_edit.png)

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `Qwen Image 3.0 Pro`


# Recraft Text to Image Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/recraft/recraft-text-to-image

Learn how to use the Recraft Text to Image Partner node in ComfyUI

The Recraft Text to Image node allows you to create high-quality images in various styles using Recraft AI's image generation technology based on text descriptions.

## What Recraft Text to Image is good at

* **High-quality generation**: Creates images from text descriptions using Recraft AI's image generation technology
* **Style control**: Preset styles such as digital art, realistic photos, and logo designs via the `Recraft Style` node
* **Color control**: Set a desired color with the `Recraft Color RGB` node
* **Adjustable output size**: Change the `size` parameter to control output dimensions
* **SVG conversion**: An optional `Recraft Vectorize Image` node converts the generated image to SVG format

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Recraft Text to Image Partner Nodes Workflow

### 1. Download the Workflow File

The workflow information is included in the metadata of the image below. Download and drag it into ComfyUI to load the workflow.

![Recraft Text to Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/recraft/t2i/recraft_t2i.png)

### 2. Follow the Steps to Run the Workflow

<img alt="Recraft Text to Image Workflow Steps" />

Follow these numbered steps to run the basic workflow:

1. (Optional) Change the `Recraft Color RGB` in the `Color` node to your desired color
2. (Optional) Modify the `Recraft Style` node to control the visual style, such as digital art, realistic photo, or logo design. This group includes other style nodes you can enable as needed
3. (Optional) Edit the `prompt` parameter in the `Recraft Text to Image` node. You can also change the `size` parameter
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to generate the image
5. After the API returns the result, you can view the generated image in the `Save Image` node. The image will also be saved to the `ComfyUI/output/` directory

> (Optional) We've included a **Convert to SVG** group in the workflow. Since the `Recraft Vectorize Image` node in this group consumes additional credits, enable it only when you need to convert the generated image to SVG format

### 3. Additional Notes

* **Recraft Style**: Offers various preset styles like realistic photos, digital art, and logo designs
* **Seed Parameter**: Only used to determine if the node should run again, the actual generation result is not affected by the seed value


# Recraft V4 & V4.1 Image & Vector Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/recraft/recraft-v4

Generate professional images and production-ready vectors with Recraft V4 and V4.1 in ComfyUI

Recraft V4 is an image generation model built for professional design work. It was developed in collaboration with designers and optimized for composition, lighting, color relationships, and material realism. Recraft V4.1 is the latest update to the model family, designed to interpret short prompts and produce natural photorealism across a range of output styles. Recraft V4.1 Flash is the fastest and lowest-cost model in the V4 family: it generates one image per run from a short prompt and does not support styles.

## What Recraft V4 is good at

* **Raster + vector in one model**: photorealistic images, stylized illustrations, and production-ready SVGs from the same model
* **Better detail**: cleaner textures, more accurate lighting, tighter geometry. Holds up in complex scenes
* **Faces and anatomy that work**: reliable proportions and expressions, even with multiple subjects or action poses
* **Text rendering**: legible text for signage, packaging, infographics. Handles short and mid-length phrases well
* **SVG output**: editable vectors with clean lines and proper color segmentation. Production-quality vector output
* **Prompt accuracy**: follows detailed creative direction closely, including spatial relationships, materials, and reflections
* **V4 Pro**: same model, higher resolution. Outputs at 2048×2048 for print and large-format work

## Example outputs

Editorial photography from a detailed text prompt:

![Street photography example](https://substack-post-media.s3.amazonaws.com/public/images/9fe39ca3-b0ba-4f26-aa26-b3eaa11185de_1792x1024.png)

Vector illustration output, ready for editing as SVG:

![Rooftop illustration](https://substack-post-media.s3.amazonaws.com/public/images/571c5214-5c7f-43f9-81c4-80cad1e5578b_1792x1024.png)

Recraft V4.1 text-to-image, producing natural photorealism from a short prompt:

![Recraft V4.1 Text to Image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_recraft_v4_1_t2i.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Recraft V4 text to image workflow

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_recraft_v4_t2i&utm_source=docs&utm_medium=referral&utm_campaign=recraft-v4">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_recraft_v4_t2i.json">
    Download JSON or search "Recraft V4 Text to Image" in Template Library
  </Card>
</CardGroup>

![Recraft V4 Text to Image workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_recraft_v4_t2i-1.webp)

### Steps to run the workflow

1. (Optional) Modify the `Recraft Style` node to control the visual style
2. (Optional) Edit the `prompt` parameter in the `Recraft Text to Image` node
3. (Optional) Change the `size` parameter for different output dimensions
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to generate the image
5. After the API returns the result, view the generated image in the `Save Image` node

### Image showcase

![Street photography example](https://substack-post-media.s3.amazonaws.com/public/images/9fe39ca3-b0ba-4f26-aa26-b3eaa11185de_1792x1024.png)
*Full-body editorial street photo of a young person wearing an oversized vintage Fear of God flannel layered over a faded Pyrex Vision hoodie, distressed wide-leg denim, original Just Don python-brim snapback, and beat-up Nike Dunk Lows. Shot on a gritty Brooklyn sidewalk, golden hour, 35mm film grain.*

![Hypebeast editorial](https://substack-post-media.s3.amazonaws.com/public/images/9fd968f1-f5f9-42a9-973d-74bd163babde_2560x1664.png)
*Full outfit shot: electric blue and coral camo hoodie, matching camo joggers, white G-Shock watch, matte black techwear crossbody harness bag, and New Balance 550s in a cream colorway. Concrete parking garage backdrop, harsh fluorescent overhead lighting casting sharp shadows.*

![Action shot](https://substack-post-media.s3.amazonaws.com/public/images/a8643f80-8cc4-4246-a95a-bed1f9ee10f1_2560x1664.png)
*Fish-eye lens, shot from inside an empty concrete pool: a guy in a shearling bomber and transparent PVC shell is mid-kickflip at the lip of the pool directly above the camera, board separating from his feet, his layered outfit catching air and fanning open revealing the hockey jersey underneath.*

## Recraft V4 text to vector workflow

Recraft V4 can generate production-ready SVG vector outputs directly. This is useful for logos, icons, brand assets, or anything that needs to scale. SVG outputs are compatible with Illustrator, Figma, and Sketch.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_recraft_v4_text_to_vector&utm_source=docs&utm_medium=referral&utm_campaign=recraft-v4">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_recraft_v4_text_to_vector.json">
    Download JSON or search "Recraft V4 Text to Vector" in Template Library
  </Card>
</CardGroup>

![Recraft V4 Text to Vector workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_recraft_v4_text_to_vector-1.webp)

### Vector showcase

![Rooftop illustration](https://substack-post-media.s3.amazonaws.com/public/images/571c5214-5c7f-43f9-81c4-80cad1e5578b_1792x1024.png)
*A group of friends lounging on a rooftop at sunset, string lights overhead, one person tending a small grill, another strumming a ukulele, a dog napping on a blanket beside a cooler: warm, relaxed, retro lifestyle illustration*

![Boombox illustration](https://substack-post-media.s3.amazonaws.com/public/images/748f04c7-50b9-433d-93cb-c619984c8e89_1792x1024.png)
*A giant neon boombox blasting music, with lightning bolts and sound waves exploding out of the speakers, melting cassette tapes swirling around it, and a pair of oversized headphones draped on top: bold, chaotic, and electrifying*

![Kitten sticker](https://substack-post-media.s3.amazonaws.com/public/images/3ddce7b4-8f37-4256-bd93-2e5796dfacca_1024x1024.png)
*Adorable kitten sticker, the kitten is using ComfyUI on a little tiny laptop*

## Recraft V4.1 text to image workflow

Generate photorealistic and illustrative images from text prompts using Recraft V4.1, producing one high-quality image per generation. The model interprets short prompts and outputs natural photorealistic results.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_recraft_v4_1_t2i&utm_source=docs&utm_medium=referral&utm_campaign=recraft-v4">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_recraft_v4_1_t2i.json">
    Download JSON or search "Recraft V4.1" in Template Library
  </Card>
</CardGroup>

![Recraft V4.1 Text to Image workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_recraft_v4_1_t2i-1.webp)

![Recraft V4.1 Text to Image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_recraft_v4_1_t2i.png)

### Steps to run the workflow

1. (Optional) Modify the `Recraft Style` node to control the visual style
2. (Optional) Edit the `prompt` parameter in the `Recraft Text to Image` node
3. (Optional) Change the `size` parameter for different output dimensions
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to generate the image
5. After the API returns the result, view the generated image in the `Save Image` node

## Recraft V4.1 Flash text to image workflow

Generate one image per run with Recraft V4.1 Flash, the fastest and lowest-cost model in the V4 family. It supports the standard V4 size presets and no style controls, so it fits high-volume generation, rapid iteration, and quick concept exploration.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_recraft_v4_1_flash_t2i&utm_source=docs&utm_medium=referral&utm_campaign=recraft-v4">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_recraft_v4_1_flash_t2i.json">
    Download JSON or search "Recraft 4.1 flash" in Template Library
  </Card>
</CardGroup>

![Recraft V4.1 Flash text to image output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_recraft_v4_1_flash_t2i.png)

### Steps to run the workflow

1. (Optional) Edit the `prompt` parameter in the `Recraft V4 Text to Image` node
2. (Optional) Set `model` to `recraftv4_1_flash`
3. (Optional) Change the `size` parameter for different output dimensions
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to generate the image
5. After the API returns the result, view the generated image in the `Save Image` node

## Recraft V4.1 text to vector workflow

Generate a clean, flat vector logo from a text prompt using Recraft V4.1, producing one scalable SVG output with no file input required. Ideal for branding and logo design, vector illustration projects, and consistent flat-color graphics.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_recraft_v4_1_text_to_vector&utm_source=docs&utm_medium=referral&utm_campaign=recraft-v4">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_recraft_v4_1_text_to_vector.json">
    Download JSON or search "Recraft V4.1" in Template Library
  </Card>
</CardGroup>

![Recraft V4.1 Text to Vector workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_recraft_v4_1_text_to_vector-1.webp)

## Recraft V4 styles

Recraft V4 and V4.1 generation nodes can apply a reusable style. Pass a `style_id` or connect style reference images to keep every output consistent with the same look.

* **Recraft V4 Create Style**: Creates a reusable style from 1 to 10 reference images and returns a `style_id`. The style works with every Recraft V4 and V4.1 model of the same output type (raster or vector), and total reference image size is limited to 10 MB
* **Style-required models**: The `recraftv4_styles` and `recraftv4_styles_pro` models, plus their vector variants, always require a `style_id` or style reference images. Other V4 models accept styles as an optional input
* **Style inputs**: `style_id` and `style_references` cannot be combined in one run. Style reference images are billed on top of the generation, and the node returns the created `style_id` for reuse
* **Style match**: `precise` reproduces the style in detail, `flexible` matches the general look

### Recraft V4 style reference workflow

Generate images in the style of one or more reference images with Recraft V4 Styles. The template creates a reusable `style_id` from four reference images with the Recraft V4 Create Style node, then feeds it into a Recraft V4 Text to Image generation. No training or fine-tuning is required: the style captures texture, composition, and rendering from the references alone.

![Recraft V4 Style Reference workflow preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_recraft_v4_style_reference-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_recraft_v4_style_reference&utm_source=docs&utm_medium=referral&utm_campaign=recraft-v4">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_recraft_v4_style_reference.json">
    Download JSON or search "Recraft V4: Style-Reference Image Generation" in Template Library
  </Card>
</CardGroup>

<CardGroup>
  <Card title="Style Reference 1: recraft_v4_style_ref_1.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/recraft_v4_style_ref_1.png">
    Style reference for the workflow, or use your own images.
  </Card>

  <Card title="Style Reference 2: recraft_v4_style_ref_2.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/recraft_v4_style_ref_2.png">
    Style reference for the workflow, or use your own images.
  </Card>

  <Card title="Style Reference 3: recraft_v4_style_ref_3.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/recraft_v4_style_ref_3.png">
    Style reference for the workflow, or use your own images.
  </Card>

  <Card title="Style Reference 4: recraft_v4_style_ref_4.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/recraft_v4_style_ref_4.png">
    Style reference for the workflow, or use your own images.
  </Card>
</CardGroup>

The created style ID is saved to `ComfyUI/output/Recraft_Style_v4/`, and you can customize the output location with the save node's `filename_prefix`. Reuse the same style ID in future generations to keep the look consistent across runs.

## Additional notes

* **Recraft Style**: Offers various preset styles like realistic photos, digital art, and logo designs
* **Seed Parameter**: Only used to determine if the node should run again; the actual generation result is not affected by the seed value


# Reve Image Create, Edit, and Remix in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/reve/reve-image

Learn how to use Reve Partner nodes in ComfyUI for high-quality image generation, editing, and remixing at up to 4K resolution

<Warning>
  Reve is no longer available: the provider has discontinued the Reve service.
  The Reve partner nodes have been retired and the workflows are archived for
  reference only. They can no longer be run on Comfy Cloud.
</Warning>

Reve is an image generation model available in ComfyUI through Partner Nodes. It supports text-to-image generation at up to **4K resolution**, image editing, and image remixing through three dedicated nodes.

## What Reve Image is good at

* **Up to 4K resolution**: Generates sharp, detailed images at high resolutions
* **Built-in aesthetic training**: Produces results suited for fashion editorial, cinematic, and natural lighting styles
* **Image editing**: Modifies lighting conditions, color grading, and adds motion effects to existing images
* **Image remixing**: Combines elements from reference images into a target image while preserving consistency

## Example outputs

Text-to-image generation with detailed aesthetics:

![Reve: Text to Image example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_reve_image_create.png)

Cinematic text-to-image work, here a fashion editorial portrait with dual-tone lighting:

![Fashion editorial portrait with dual-tone lighting](https://substack-post-media.s3.amazonaws.com/public/images/279c7067-7c65-4bb3-95ef-6d1ec934050b_2720x1536.png)

4K resolution output with fine detail preservation:

![Jaguar F-Type on a coastal trail at twilight](https://substack-post-media.s3.amazonaws.com/public/images/bf51794c-7044-4b1e-a5f1-1857ff78fb22_5440x3072.png)

Image editing with text instructions:

![Reve: Image Edit example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_reve_image_edit.png)

Image remixing, combining multiple reference images into a single output:

![Reve: Image Remix And Edit example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_reve_image_remix.png)

<Warning>
  Reve is no longer available: the provider has discontinued the Reve service.
  The Reve partner nodes have been retired and the workflows below are archived
  for reference only.
</Warning>

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Reve: Text to Image

Input text prompts to generate high-quality images with detailed aesthetics and accurate text rendering.

<img alt="Reve: Text to Image workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/archived/api_reve_image_create.json">
    Download JSON or search "Reve: Text to Image" in Template Library
  </Card>
</CardGroup>

**Example output**

![Reve: Text to Image example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_reve_image_create.png)

### Example outputs

![Fashion editorial portrait with dual-tone lighting](https://substack-post-media.s3.amazonaws.com/public/images/279c7067-7c65-4bb3-95ef-6d1ec934050b_2720x1536.png)

```
A high-fashion editorial portrait of a young East Asian model with long, straight black hair and thick bangs, crouched in a studio setting. She wears a minimalist, muted beige dress. The image features a cinematic dual-tone lighting setup, where the left side is washed in a soft greenish-yellow glow and the right side is cast in cool, muted blue-grey, creating a subtle color bleed effect. There is a slight motion blur, with the subject looking directly at the camera with a calm, neutral expression. High-end fashion magazine aesthetic, soft focus background, structured silhouette.
```

![Red sports car speeding through the night](https://substack-post-media.s3.amazonaws.com/public/images/5563d900-336c-42d0-b48c-6978883ae4ff_1360x768.png)

```
A high-speed, cinematic capture of a vibrant red sports car speeding through the night. The camera angle is positioned near the rear-three-quarter view, emphasizing the sleek, metallic curves and the car's aerodynamic design. The entire background is transformed into a dramatic radial blur of brilliant yellow, orange, and white light streaks, suggesting extreme velocity. The car's surface reflects the warm ambient lights of the city, contrasting sharply with the deep, dark blue of the night sky.
```

![Woman with glowing orb and amber tones](https://substack-post-media.s3.amazonaws.com/public/images/fea68697-1783-4f84-99a7-3065b4df577c_2720x1536.png)

```
A cinematic photograph of a woman with a bob haircut looking at her reflection in a mirror, her hands gently cradling a brilliant, glowing spherical white orb. The image is saturated in deep orange and amber tones, with heavy light leaks and lens flares washing out the center of the frame as the sphere radiates subtle, ethereal light. The composition features a soft, dreamy focus with significant analog film grain, creating a nostalgic atmosphere where the reflected face in the mirror appears slightly blurred and obscured by the warmth of the light leakage.
```

![Rally car drifting near a volcano](https://substack-post-media.s3.amazonaws.com/public/images/b73ad263-3045-4579-9e46-b6faaace9e5f_1360x768.png)

```
A high-action, wide-angle nighttime shot of a legendary Audi Quattro rally car drifting through a barren rocky field at the base of a volcano. The car is coated in white and black. Powerful auxiliary spotlights on the front of the car cast a bright, warm glow, catching the thick dust kicked up by the aggressive tread of the tires. In the background, out-of-focus volcano spraying lava. The scene is cold and dark, with the intense light from the lava creating dramatic contrast.
```

The following examples demonstrate 4K resolution output with fine detail preservation:

![Jaguar F-Type on a coastal trail at twilight](https://substack-post-media.s3.amazonaws.com/public/images/bf51794c-7044-4b1e-a5f1-1857ff78fb22_5440x3072.png)

```
A wide-angle landscape photograph of a solitary Jaguar F-Type car in British green, on a dirt trail facing a distant beach at twilight. The sky features dramatic long-exposure cloud streaks radiating from a low sun on the horizon. The foreground is dominated by jagged limestone rocks and blades of grass, leading the viewer's eye along a path that cuts through grassy hills toward the water. The lighting is cool and moody, casting deep shadows against the golden glow of the setting sun.
```

![White owl in a desert at golden hour](https://substack-post-media.s3.amazonaws.com/public/images/1af7e42a-aded-420b-b6b5-d2f96e5c5788_2720x1536.png)

```
A minimalist wide shot of a vast white sand dune desert during golden hour. A white owl with its wings spread is in the foreground. Soft warm sunlight grazing the tops of the dunes, casting long shadows. Sparse, golden-brown desert shrubs are scattered across the ripples, with a prominent patch of dry, cracked, hexagonal mud in the bottom right foreground. In the far distance, a hazy, ethereal range of mountains rests against a pale, washed-out sky.
```

### Reve: Image Edit

Upload an image and provide text instructions to edit it. Generate a modified output image using Reve's advanced editing model.

<img alt="Reve: Image Edit workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/archived/api_reve_image_edit.json">
    Download JSON or search "Reve: Image Edit" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadImage` node:

<CardGroup>
  <Card title="woman_running_in_field.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/woman_running_in_field.png">
    `LoadImage` node 4 · `woman_running_in_field.png`
  </Card>
</CardGroup>

<div>
  <img alt="Input image" />

  <img alt="Reve: Image Edit example output" />
</div>

### Example outputs

![Motion blur edit example](https://substack-post-media.s3.amazonaws.com/public/images/1842aadb-ae80-45e7-be65-c6cc8e7aaea5_1024x1024.png)

```
Add a cinematic horizontal streaks motion blur to the subject's body. The hand stays in clear focus.
```

![Lighting edit example](https://substack-post-media.s3.amazonaws.com/public/images/7cfec95f-40b0-4a09-9991-c37b6919155b_1920x1080.png)

```
The lighting is cold, soft glow emits from the window.
```

![Side profile edit example](https://substack-post-media.s3.amazonaws.com/public/images/52617409-4c10-4944-985d-ee86b01bde05_1024x1024.png)

```
Side profile shot of the subject, his hand is grabbing the sunglasses.
```

### Reve: Image Remix And Edit

Remix and edit images using Reve's advanced model. Combine multiple reference images into a single output.

<img alt="Reve: Image Remix And Edit workflow preview" />

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/archived/api_reve_image_remix.json">
    Download JSON or search "Reve: Image Remix And Edit" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="iced_drink_cup.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/iced_drink_cup.png">
    `LoadImage` node 2 · `iced_drink_cup.png`
  </Card>

  <Card title="casual_male_portrait.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/casual_male_portrait.png">
    `LoadImage` node 4 · `casual_male_portrait.png`
  </Card>

  <Card title="japanese_street_alley.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/japanese_street_alley.png">
    `LoadImage` node 5 · `japanese_street_alley.png`
  </Card>
</CardGroup>

**Example output**

![Reve: Image Remix And Edit example](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_reve_image_remix.png)

### Example outputs

![Shadow transfer remix example](https://substack-post-media.s3.amazonaws.com/public/images/bc91f624-5d2f-47d9-8299-31e06e72fc59_1920x1080.png)

```
Edit the shadows on the subject in image 1 to match the shadows from image 2.
```

![Color grading transfer remix example](https://substack-post-media.s3.amazonaws.com/public/images/87fc38a6-2cce-4de6-aa48-520fbdecff2a_1920x1080.png)

```
Transfer the color grading and aesthetic from image 2 onto image 1.
```

## Get started

1. **Update** ComfyUI to the latest version or visit [Comfy Cloud](https://cloud.comfy.org/?utm_source=docs).
2. **Find** the Reve Image Create, Reve Image Remix, and Reve Image Edit nodes in the Node Library or Templates in the left sidebar.
3. **Drop a node** on your canvas to begin.

## Available nodes

| Node | Type | Description |
| - | - | - |
| **Reve Image Create** | Text-to-Image | Generates images at up to 4K resolution from text prompts |
| **Reve Image Edit** | Image Edit | Modifies lighting, color grading, and motion in existing images |
| **Reve Image Remix** | Image Remix | Transfers visual properties from reference images to a target image |


# Rodin Partner Nodes Model Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/rodin/model-generation

This article will introduce how to use Rodin node's API in ComfyUI for model generation

Hyper3D Rodin (hyper3d.ai) is a platform focused on rapidly generating high-quality, production-ready 3D models and materials through artificial intelligence.
ComfyUI has now natively integrated the corresponding Rodin model generation API, allowing you to conveniently use the related nodes in ComfyUI for model generation.

## What Rodin Model Generation is good at

* **Single-view model generation**: Generates a 3D model from a single image input
* **Multi-view model generation**: Generates a 3D model from up to 5 image inputs, such as front, back, and left views
* **Different levels of detail**: Supports model generation with adjustable detail, including different polygon counts for smoother, more detailed models
* **Direct export**: Generated models are saved to the `ComfyUI/output/Rodin` directory and can be exported from the `Preview 3D` node

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Single-view Model Generation Workflow

Generate a 3D model from a single image input with Rodin.

<img alt="Rodin Single-view Model Generation workflow preview" />

<CardGroup>
  <Card title="Download Workflow File" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/rodin_image_to_model.json">
    Single-view Model Generation (Json Format)
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_rodin_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=model-generation">
    Open in Comfy Cloud
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_rodin_image_to_model_input_image.png">
      Download sample input image
    </Card>
  </CardGroup>
</details>

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/doll.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Rodin Image to Model Step Guide" />

You can refer to the numbers in the image to complete the basic text-to-image workflow execution:

1. In the `Load Image` node, load the provided input image
2. (Optional) In `Rodin 3D Generate - Regular Generate` adjust the corresponding parameters
   * polygon\_count: You can set different polygon counts, the higher the value, the smoother and more detailed the model
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation. After the workflow completes, the corresponding model will be automatically saved to the `ComfyUI/output/Rodin` directory
4. In the `Preview 3D` node, click to expand the menu
5. Select `Export` to directly export the corresponding model

## Multi-view Model Generation Workflow

The corresponding `Rodin 3D Generate - Regular Generate` allows up to 5 image inputs

### 1. Workflow File Download

You can modify the single-view workflow to a multi-view workflow, or directly download the workflow file below

<img alt="Rodin Multi-view Model Generation workflow preview" />

<CardGroup>
  <Card title="Download Workflow File" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/multiview_to_model/api_rodin_multiview_to_model.json">
    Multi-view Model Generation (Json Format)
  </Card>

  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_rodin_multiview_to_model&utm_source=docs&utm_medium=referral&utm_campaign=model-generation">
    Open in Comfy Cloud
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="Front view" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_rodin_multiview_to_model_front.jpg">
      Download front view
    </Card>

    <Card title="Back view" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_rodin_multiview_to_model_back.jpg">
      Download back view
    </Card>

    <Card title="Left view" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_rodin_multiview_to_model_left.jpg">
      Download left view
    </Card>
  </CardGroup>
</details>

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/multiview_to_model/front.jpg)
![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/multiview_to_model/back.jpg)
![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/multiview_to_model/left.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Rodin Image to Model Step Guide" />

You can refer to the numbers in the image to complete the basic text-to-image workflow execution:

1. In the `Load Image` node, load the provided input images
2. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation. After the workflow completes, the corresponding model will be automatically saved to the `ComfyUI/output/Rodin` directory
3. In the `Preview 3D` node, click to expand the menu
4. Select `Export` to directly export the corresponding model

## Other Related Nodes

Currently, Rodin provides different types of model generation nodes in ComfyUI, since the corresponding input conditions are the same as the workflow introduced in this article, you can enable them as needed. In addition, we have provided corresponding nodes in the corresponding templates, you can also modify the corresponding node mode as needed to enable them

<img alt="Rodin Other Related Nodes" />


# Runway Partner Nodes Image Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/runway/image-generation

This article will introduce how to use Runway nodes in ComfyUI for text-to-image and reference-to-image generation

Runway is a company focused on generative AI, providing powerful image generation capabilities. Its models support features such as style transfer, image extension, and detail control. Currently, ComfyUI has integrated the Runway API, allowing you to directly use the related nodes in ComfyUI for image generation.

## What Runway Image Generation is good at

* **Text-to-image generation**: Generates images from a text prompt with the `Runway Text to Image` node, with adjustable output aspect ratios
* **Reference-to-image generation**: Generates images guided by an input reference image plus a text prompt
* **Style transfer, image extension, and detail control**: Runway's models support these features for image generation

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Runway Image Text-to-Image Workflow

### 1. Workflow File Download

The image below contains workflow information in its `metadata`. Please download and drag it into ComfyUI to load the corresponding workflow.

![ComfyUI Runway Image Text to Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/image/text_to_image.png)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Runway Image Text to Image Step Guide" />

You can refer to the numbers in the image to complete the basic text-to-image workflow execution:

1. In the `Runway Text to Image` node, input your prompt in the `prompt` field
2. (Optional) Adjust the `ratio` setting to set different output aspect ratios
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute image generation.
4. After waiting for the API to return results, you can view the generated image in the `Save Image` node (right-click to save). The corresponding image will also be saved to the `ComfyUI/output/` directory.

## Runway Image Reference-to-Image Workflow

### 1. Workflow and Input Image Download

The image below contains workflow information in its `metadata`. Please download and drag it into ComfyUI to load the corresponding workflow.

![ComfyUI Runway Image Reference to Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/image/reference_to_image/runway_reference_to_image.png)

Download the image below for input

![ComfyUI Runway Image Reference to Image Input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/image/reference_to_image/input.png)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Runway Image Reference to Image Step Guide" />

You can refer to the numbers in the image to complete the basic reference-to-image workflow execution:

1. In the `Load Image` node, load the provided input image
2. In the `Runway Text to Image` node, input your prompt in the `prompt` field and adjust dimensions
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute image generation.
4. After waiting for the API to return results, you can view the generated image in the `Save Image` node (right-click to save). The corresponding image will also be saved to the `ComfyUI/output/` directory.


# Runway Partner Nodes Video Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/runway/video-generation

This article will introduce how to use Runway nodes in ComfyUI for video generation workflows

Runway is a company focused on generative AI, providing powerful video generation capabilities. Currently, ComfyUI has integrated the Runway API, allowing you to directly use the related nodes in ComfyUI for video generation.

Currently, ComfyUI natively integrates the following Runway video generation model:

* Runway Gen4 turbo

<Warning>
  **End of life (EOL)**: **Runway Gen3a Turbo** and **Runway First-Last-Frame to Video** reached end of life on **July 30, 2026**. Runway retired Gen-3 Alpha Turbo on that date. The related Partner Nodes (`RunwayImageToVideoNodeGen3a`, `RunwayFirstLastFrameNode`) and workflow templates are deprecated and no longer supported.
</Warning>

## What Runway Video Generation is good at

* **Image-to-video generation**: The `Runway Gen4 turbo` node generates a video from an input image and a text prompt describing the video content
* **Adjustable video length**: Modify the `duration` parameter to set the video length
* **Adjustable aspect ratio**: Modify the `ratio` parameter to set the video aspect ratio

<Warning>
  **End of life (EOL)**: **Runway Gen3a Turbo** and **Runway First-Last-Frame to Video** reached end of life on **July 30, 2026**. Runway retired Gen-3 Alpha Turbo on that date. The related Partner Nodes (`RunwayImageToVideoNodeGen3a`, `RunwayFirstLastFrameNode`) and workflow templates are deprecated and no longer supported.
</Warning>

### Retired workflows and replacements

| Removed template | Suggested replacement |
| :- | :- |
| `api_runway_gen3a_turbo_image_to_video` | [`api_runway_gen4_turbo_image_to_video`](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_runway_gen4_turbo_image_to_video.json) (Gen4 Turbo) |
| `api_runway_first_last_frame` | [Kling 3.0 FLF2V](/tutorials/partner-nodes/kling/kling-3-0) (`api_kling_v3_flf2v`) or other first-last-frame templates |

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Gen4 turbo Image-to-Video Workflow

### 1. Workflow File Download

The video below contains workflow information in its `metadata`. Please download and drag it into ComfyUI to load the corresponding workflow.

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/gen4_turbo_image_to_video/runway_gen4_turo_image_to_video.json">
  <p>Download Json Format Workflow File</p>
</a>

Download the image below as input image

![ComfyUI Runway gen4 turbo image to video Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/gen4_turbo_image_to_video/godfather.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Runway gen4 turbo image to video Step Guide" />

You can refer to the numbers in the image to complete the basic image-to-video workflow execution:

1. In the `Load Image` node, load the provided input image
2. In the `Runway Gen4 turbo` node, set the `prompt` to describe video content, modify the `duration` parameter to set video length, modify the `ratio` parameter to set video aspect ratio
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.
4. After waiting for the API to return results, you can view the generated video in the `Save Video` node (right-click to save). The corresponding video will also be saved to the `ComfyUI/output/` directory.


# Sonilo Partner Nodes Official ComfyUI Example
Source: https://docs.comfy.org/tutorials/partner-nodes/sonilo/video-to-music

This article introduces how to use Sonilo Partner nodes for video-to-music and text-to-audio generation in ComfyUI.

Sonilo is an AI-powered video-to-music service that generates soundtracks synchronized to your footage. It analyzes visuals, pacing, and emotional cues to produce music locked to your timeline, frame by frame.

You can drive music generation directly from your ComfyUI node graphs, alongside your existing workflows.

## What Sonilo Video to Music is good at

* **Length, pace and emotion alignment** - Music is generated to match the exact duration, pacing, and emotional arc of your video, delivering soundtracks that feel intentionally composed for the content.
* **Instant generation** - Generate full-length, high-quality music in seconds, enabling faster iteration and a seamless creative workflow.
* **Commercial-ready usage** - All generated music includes commercial use rights, making it ready for use across professional, brand, and production environments without additional licensing complexity.

## Use cases

* **Advertising and creative studios** - Generate music that matches the pacing of product videos, brand spots, and social ads.
* **Video production and post houses** - Automate soundtrack generation across large volumes of footage.
* **VFX and motion graphics artists** - Generate music that evolves with your visuals, frame by frame.
* **Content creators and agencies** - Produce platform-ready videos with synchronized music across multiple formats.
* **Developers and pipeline engineers** - Integrate music generation directly into automated workflows via ComfyUI.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Get started

<Steps>
  <Step title="Update ComfyUI">
    Update ComfyUI to the latest version, or use [Comfy Cloud](https://www.comfy.org/cloud).
  </Step>

  <Step title="Find a Sonilo workflow">
    Open the **Workflow Library**, browse **Templates**, and search for "Sonilo" to find a ready-to-use workflow.
  </Step>

  <Step title="Run the workflow">
    Connect your video source, update the prompt, and click the **Run** button or use `Ctrl(Cmd) + Enter` to generate.
  </Step>
</Steps>

### Sonilo: Video Soundtrack Generation

Generate synchronized soundtracks from video footage. Input a video to produce music that matches its pacing and emotional cues.

<img alt="Sonilo: Video Soundtrack Generation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_sonilo_v2m&utm_source=docs&utm_medium=referral&utm_campaign=video-to-music">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_sonilo_v2m.json">
    Download JSON or search "Sonilo: Video Soundtrack Generation" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload this file to the matching `LoadVideo` node:

<CardGroup>
  <Card title="leopard_rider.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/leopard_rider.mp4">
    `LoadVideo` node 705 · `leopard_rider.mp4`
  </Card>
</CardGroup>

1. Load your video in the input node.
2. (Optional) Add a text prompt to guide the style or mood of the generated music.
3. Click the **Run** button or use the shortcut `Ctrl(Cmd) + Enter` to start music generation.
4. The generated audio will be saved to the `ComfyUI/output/audio` directory.

### Sonilo: Text to Music Generation

Generate high-quality, production-ready music from text prompts.

<img alt="Sonilo: Text to Music Generation workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_sonilo_t2m&utm_source=docs&utm_medium=referral&utm_campaign=video-to-music">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_sonilo_t2m.json">
    Download JSON or search "Sonilo: Text to Music Generation" in Template Library
  </Card>
</CardGroup>

**Example prompts:**

* `Dreamy ambient electronic music, gentle rhythm, suitable for short videos`
* `Futuristic electronic instrumental, sci-fi sense, ethereal and deep`
* `Lazy jazz instrumental, saxophone, relaxing cafe atmosphere`

1. Enter your text prompt describing the music you want to generate.
2. Click the **Run** button or use the shortcut `Ctrl(Cmd) + Enter` to start audio generation.
3. The generated audio will be saved to the `ComfyUI/output/audio` directory.


# Tencent Hunyuan Image 3.5 Preview in ComfyUI: Text to Image and Edit Workflows
Source: https://docs.comfy.org/tutorials/partner-nodes/tencent/hy-image-3-5

Generate and edit images with Tencent Hunyuan Image 3.5 Preview in ComfyUI: multilingual text rendering, up to 5 reference images, and 4K output upscaled from 2K.

Tencent Hunyuan Image 3.5 Preview is Tencent's preview image model, available in ComfyUI through Partner Nodes. It generates images from text and edits existing images from an instruction, with a focus on multilingual text rendering, photorealism, and consistency between a reference image and the edited result.

Compared with earlier Hunyuan image models, HY Image 3.5 Preview strengthens three areas: multilingual text rendering and typesetting for advertising, infographics, and UI design; photorealism and stylistic range across cinematic, comic, commercial photography, and illustration; and editing consistency that preserves the key traits of people and products across background, outfit, and style changes.

Two workflows are available. `Tencent HY Image: Text to Image` generates an image from a prompt, and `Tencent HY Image: Edit` edits or combines up to five reference images. Both run on Tencent's servers through Comfy API, so no model downloads or local GPU are required.

## What HY Image 3.5 Preview is good at

* **Multilingual text and typesetting**: renders legible text for posters, infographics, and UI mockups instead of plain scene images
* **Photorealistic range**: covers cinematic stills, comic art, commercial photography, and illustration from short prompts
* **Editing consistency**: keeps the defining traits of people and products stable when you change the background, outfit, or style
* **Up to 5 reference images**: combine several images in one edit and reference each one in the prompt
* **Output up to 4K**: renders up to 2K natively and upscales 4K output from a 2K render

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Tencent HY Image 3.5 Preview text to image workflow

Generate one image from a text prompt. The model rewrites and expands the prompt before rendering, so short prompts work.

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tencent_hy_image_3_5_preview_t2i&utm_source=docs&utm_medium=referral&utm_campaign=hy-image-3-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tencent_hy_image_3_5_preview_t2i.json">
    Download JSON or search "HY Image 3.5" in Template Library
  </Card>
</CardGroup>

![Poster reading HY Image 3.5 Preview in white capitals over a glossy liquid-metal shape with iridescent highlights on a dark background](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_tencent_hy_image_3_5_preview_t2i.png)

### Steps to run the workflow

1. Edit the `prompt` in the `Tencent HY Image: Text to Image` node
2. (Optional) Set `aspect_ratio` to control the output shape. With `auto` the model picks the aspect ratio from the prompt, and `auto` is not available at 4K
3. (Optional) Change `resolution` from the default `2K`. `1K` is about 1024x1024 and `2K` is about 2048x2048 pixels. `4K` output is rendered at 2K and then upscaled by the model
4. (Optional) Switch `resolution` to `custom` to set an exact `width` and `height` instead. Both must be multiples of 16 and the total area can be up to 4096x4096. Above roughly a 6:1 ratio the model starts repeating the subject
5. Click `Run` or press `Ctrl(cmd) + Enter` to generate the image
6. View the result in the `Save Image` node

## Tencent HY Image 3.5 Preview image edit workflow

Edit or combine up to five reference images from a text instruction. Use it to change a background, swap an outfit, restyle a product shot, or merge several references into one image while keeping the subject's defining traits.

<img alt="Tencent HY Image 3.5 Preview image edit example output" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tencent_hy_image_3_5_preview_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=hy-image-3-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tencent_hy_image_3_5_preview_image_edit.json">
    Download JSON or search "HY Image 3.5" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/futuristic_brutalist_motorcycle.png">
      Download sample input image
    </Card>
  </CardGroup>
</details>

![Angular matte black concept motorcycle on an orange paddock stand against a deep red background](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/futuristic_brutalist_motorcycle.png)

### Steps to run the workflow

1. Upload the sample image into the `Load Image` node that is already connected to the `Tencent HY Image: Edit` node. The downloaded workflow refers to the file by name (`futuristic_brutalist_motorcycle.png`), so that node stays empty until you upload it. To edit your own images instead, connect 1 to 5 images to the `images` input of the `Tencent HY Image: Edit` node
2. Write the editing instruction in `prompt`. Reference the inputs in order as `@Image1`, `@Image2`, and so on. A batched input counts once per image
3. (Optional) Set `aspect_ratio` and `resolution`. With `auto`, the output follows the aspect ratio of the first reference image. `4K` output is rendered at 2K and then upscaled by the model
4. (Optional) Set `reference_detail` to `high` to let the model see references at up to 2048x2048 pixels instead of 1024x1024. This preserves small text and fine detail better but takes longer
5. Click `Run` or press `Ctrl(cmd) + Enter` to generate the image
6. View the result in the `Save Image` node

### Prompting tips

* Describe the edit and the parts that must stay unchanged separately, for example `@Image1 change the background to a night market, keep the subject and jacket unchanged`
* Number references in the order they are connected. The numbering in the prompt has to match the input order
* `watermark` sits in the node's advanced options and is off by default. Turn it on to add an AI-generated watermark to the output

## Get started

1. Update ComfyUI to the latest version, or use [Comfy Cloud](https://cloud.comfy.org/?utm_source=docs\&utm_medium=referral\&utm_campaign=hy-image-3-5)
2. Go to Template Library and search for `HY Image 3.5`
3. Open the text to image or image edit workflow and run it


# Astra 2 - Creative diffusion video upscaling
Source: https://docs.comfy.org/tutorials/partner-nodes/topaz/astra-2

What Astra 2 does for your videos in ComfyUI, plus creative upscaling with control over detail and style.

Enhanced creative upscaling for GenAI video, with advanced control over detail and style.

## What is Astra 2?

**If you're new here:** Astra 2 targets **AI-generated and stylized video**. Plain upscaling mostly enlarges and sharpens existing pixels; Astra 2 can **add plausible new detail and texture** where the source is soft, so the clip feels richer, not only bigger.

## Model overview

It builds on Astra 1 with clearer control over how detail and stylization are produced (creativity, sharpness, optional **descriptive** prompts, not step lists). Strong fits: stylized/GenAI footage, wides and sparse-detail scenes, and footage that looks overly smooth until texture is restored.

## What Astra 2 is good at

* **Adds texture and detail**: Not only sharpening.
* **Steerable look**: Creativity, sharpness, optional prompt guidance.
* **Stylized & wides**: Where inferred detail matters.

## Related

* [Video upscaling in ComfyUI](/tutorials/utility/video-upscale): guidance on choosing an upscaling approach.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## In ComfyUI

Use **Topaz Video Enhance**. **Topaz Video Enhance (Legacy)** does not offer **Astra 2**. Set upscaler to **Astra 2**, resolution to **FullHD** or **4K**; input must be **MP4**.

Optional **Prompt**: max **450** frames (\~15 s @ 30 fps). Empty prompt: up to **9000** frames. Expand advanced controls for **Sharp** and **Realism** when needed.

## Example workflow

**Load Video** → **Topaz Video Enhance** → **Save Video**. After opening the template, pick **Astra 2** on the upscaler if another preset is selected.

<img alt="Astra 2 workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_topaz_astra2&utm_source=docs&utm_medium=referral&utm_campaign=astra-2">
    Open the workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_topaz_astra2.json">
    Download the workflow JSON for local ComfyUI.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/cyber_fight.mp4">
      Download sample input video
    </Card>
  </CardGroup>
</details>


# Topaz Image Enhance Bloom 2 - AI creative image upscaling
Source: https://docs.comfy.org/tutorials/partner-nodes/topaz/image-enhance-bloom-2

Upscale and enhance images with Topaz Image Enhance Bloom 2 in ComfyUI: creative upscaling that adds new detail, texture, and visual elements

Topaz Image Enhance Bloom 2 is a creative upscaling model available in ComfyUI through the Topaz partner nodes. It adds new detail, texture, and visual elements to your images, with a creativity control from 1 to 9 for subtle refinement or bold reinterpretation. It preserves the input aspect ratio and supports upscale factors from 1x to 6x.

## What Topaz Image Enhance Bloom 2 is good at

* **Creative upscaling**: Adds new detail, texture, and visual elements to your images
* **Adjustable creativity**: A control from 1 for restrained enhancement to 9 for pronounced reinterpretation
* **Automatic prompting**: If the prompt is empty, the model creates one automatically
* **Flexible output**: Preserves the input aspect ratio and supports upscale factors from 1x to 6x

## Example outputs

Creative upscaling of an AI-generated image, with new detail and texture added:

![Topaz Image Enhance Bloom 2 output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/Upscaled_topaz_bloom2.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Topaz Image Enhance Bloom 2

Enhance AI-generated images with Bloom 2's creative upscaling model, which adds new detail, texture, and visual elements. The Creativity control ranges from 1 for restrained enhancement to 9 for pronounced reinterpretation. If the prompt is empty, the model creates one automatically.

<img alt="Topaz Image Enhance Bloom 2 workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_topaz_image_enhance_bloom2&utm_source=docs&utm_medium=referral&utm_campaign=topaz-image-enhance-bloom-2">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_topaz_image_enhance_bloom2.json">
    Download JSON or search "Topaz Image Enhance Bloom 2" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/digital_bloom.png">
      Download sample input image
    </Card>
  </CardGroup>
</details>

![Topaz Image Enhance Bloom 2 output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/Upscaled_topaz_bloom2.png)

### Workflow overview

This workflow uses four nodes:

* **LoadImage**: provides the source image
* **TopazImageEnhanceV2**: the core node, configured with the `Bloom 2` enhancement model
* **SaveImageAdvanced**: saves the enhanced output as PNG
* **ImageCompare**: shows the enhanced result next to the original for comparison

### Steps to run

1. **Load an image**: upload or select your input image in the **LoadImage** node
2. **Select the model**: keep `Bloom 2` on the **TopazImageEnhanceV2** node
3. **Set creativity**: from 1 for restrained enhancement to 9 for pronounced reinterpretation
4. **Optional prompt**: leave empty to let the model create one automatically
5. **Click Queue**: press `Ctrl+Enter` to generate

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `Topaz Image Enhance Bloom 2`


# Topaz Image Enhance Wonder 3.5 - AI image enhancement
Source: https://docs.comfy.org/tutorials/partner-nodes/topaz/image-enhance-wonder-3-5

Upscale and enhance images with Topaz Image Enhance Wonder 3.5 in ComfyUI: generative detail restoration, noise reduction, and text sharpening

Topaz Image Enhance Wonder 3.5 is a generative enhancement model available in ComfyUI through the Topaz partner nodes. It adds fine detail, reduces noise, and sharpens text and structured graphics, with low, medium, and high enhancement strengths. It preserves the input aspect ratio and supports upscale factors from 1x to 6x.

## What Topaz Image Enhance Wonder 3.5 is good at

* **Generative detail restoration**: Adds fine detail to the source image
* **Noise reduction**: Cleans up noise while enhancing
* **Text and graphics sharpening**: Sharpens text and structured graphics
* **Adjustable strength**: Choose low, medium, or high enhancement strength
* **Flexible output**: Preserves the input aspect ratio and supports upscale factors from 1x to 6x

## Example outputs

Image enhancement with fine detail added and noise reduced:

![Topaz Image Enhance Wonder 3.5 output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_topaz_image_enhance_wonder3_5.png)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Topaz Image Enhance Wonder 3.5

Upscale and enhance a single image with Wonder 3.5's generative model, which adds fine detail, reduces noise, and sharpens text and structured graphics. The workflow takes 1 input image and produces 1 enhanced output alongside a side-by-side comparison.

<img alt="Topaz Image Enhance Wonder 3.5 workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_topaz_image_enhance_wonder3_5&utm_source=docs&utm_medium=referral&utm_campaign=topaz-image-enhance-wonder-3-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_topaz_image_enhance_wonder3_5.json">
    Download JSON or search "Topaz Image Enhance Wonder 3.5" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/wild_run.png">
      Download sample input image
    </Card>
  </CardGroup>
</details>

![Topaz Image Enhance Wonder 3.5 output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_topaz_image_enhance_wonder3_5.png)

### Workflow overview

This workflow uses four nodes:

* **LoadImage**: provides the source image
* **TopazImageEnhanceV2**: the core node, configured with the `Wonder 3.5` enhancement model
* **SaveImageAdvanced**: saves the enhanced output as PNG
* **ImageCompare**: shows the enhanced result next to the original for comparison

### Steps to run

1. **Load an image**: upload or select your input image in the **LoadImage** node
2. **Select the model**: keep `Wonder 3.5` on the **TopazImageEnhanceV2** node
3. **Choose enhancement strength**: `low`, `medium`, or `high`
4. **Set upscale factor**: from 1x to 6x
5. **Click Queue**: press `Ctrl+Enter` to generate

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `Topaz Image Enhance Wonder 3.5`


# Topaz Astra Video Creative Upscale - AI video upscaling
Source: https://docs.comfy.org/tutorials/partner-nodes/topaz/video-enhance-astra

Upscale and enhance videos with Topaz Astra in ComfyUI: Starlight (Astra) Fast upscaling with optional apo-8 frame interpolation

Topaz Astra Video Creative Upscale is available in ComfyUI through the Topaz partner nodes. It upscales and enhances video with the Starlight (Astra) Fast model, optionally combined with apo-8 frame interpolation to raise the frame rate. The workflow accepts MP4 input and produces enhanced MP4 output.

## What Topaz Astra Video Creative Upscale is good at

* **Creative video upscaling**: Upscales and enhances video with the Starlight (Astra) Fast model
* **Optional frame interpolation**: Switch to the apo-8 interpolation model to raise the frame rate and smooth motion
* **Resolution targets**: Output at FullHD (1080p) or 4K (2160p)
* **Simple I/O**: Accepts MP4 input and produces enhanced MP4 output

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Topaz Astra: Video Creative Upscale

Upscale and enhance a video with the Starlight (Astra) Fast model, with optional apo-8 frame interpolation to smooth motion.

<img alt="Topaz Astra Video Creative Upscale workflow preview" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_topaz_video_enhance&utm_source=docs&utm_medium=referral&utm_campaign=topaz-astra-video-upscale">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_topaz_video_enhance.json">
    Download JSON or search "Topaz Astra" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video: api_topaz_video_enhance_input_video.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_topaz_video_enhance_input_video.mp4">
      A sample clip used as the base video
    </Card>
  </CardGroup>
</details>

### Workflow overview

This workflow uses three nodes:

* **LoadVideo**: provides the source video
* **TopazVideoEnhanceV2**: the core node, configured with the `Starlight (Astra) Fast` upscaler model
* **SaveVideo**: saves the enhanced video

### Steps to run

1. **Load a video**: connect your MP4 video to the **LoadVideo** node
2. **Select the upscaler**: keep `Starlight (Astra) Fast` on the **TopazVideoEnhanceV2** node
3. **Set resolution**: `FullHD (1080p)` or `4K (2160p)`
4. **Optional frame interpolation**: switch the interpolation model to `apo-8` to raise the frame rate
5. **Click Queue**: press `Ctrl+Enter` to generate

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `Topaz Astra`


# Topaz Starlight Precise 2.5 - AI video upscaling
Source: https://docs.comfy.org/tutorials/partner-nodes/topaz/video-enhance-starlight-precise-2-5

Upscale videos with Topaz Starlight Precise 2.5 in ComfyUI: sharper 4K output with reduced artifacts for live-action footage

Topaz Starlight Precise 2.5 is a video upscaling model available in ComfyUI through the Topaz partner nodes. It upscales MP4 videos up to 4K resolution with sharper output and fewer artifacts.

## What Topaz Starlight Precise 2.5 is good at

* **4K upscaling**: Upscales MP4 videos up to 4K resolution
* **Sharper results**: Sharper output with fewer artifacts
* **Live-action footage**: Reduced artifacts make it a good fit for live-action video
* **Resolution options**: Output at FullHD (1080p) or 4K (2160p)

## Example outputs

Video upscaling with the Starlight Precise 2.5 model, showing the sharper enhanced result:

<video />

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Topaz Starlight Precise 2.5

Upscale a video to sharper, higher-resolution output with the Starlight Precise 2.5 model. This workflow upscales MP4 videos up to 4K with sharper output and fewer artifacts.

<video />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_topaz_starlight_precise25&utm_source=docs&utm_medium=referral&utm_campaign=topaz-starlight-precise-2-5">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_topaz_starlight_precise25.json">
    Download JSON or search "Topaz Starlight Precise 2.5" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input video to try the workflow:

  <CardGroup>
    <Card title="Input video: running_horse.mp4" icon="video" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/running_horse.mp4">
      A horse running clip used as the base video
    </Card>
  </CardGroup>
</details>

### Workflow overview

This workflow uses three nodes:

* **LoadVideo**: provides the source video
* **TopazVideoEnhanceV2**: the core node, configured with the `Starlight Precise 2.5` upscaler model
* **SaveVideo**: saves the enhanced video

### Steps to run

1. **Load a video**: connect your MP4 video to the **LoadVideo** node
2. **Select the upscaler**: keep `Starlight Precise 2.5` on the **TopazVideoEnhanceV2** node
3. **Set resolution**: `FullHD (1080p)` or `4K (2160p)`
4. **Click Queue**: press `Ctrl+Enter` to generate

## Get started

1. Update ComfyUI to the latest version
2. Go to Template Library, search for `Topaz Starlight Precise 2.5`


# Tripo Partner Nodes Model Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/tripo/model-generation

This article will introduce how to use Tripo node's API in ComfyUI for model generation

Tripo AI is a company focused on generative AI 3D modeling. It provides user-friendly platforms and API services that can quickly convert text prompts or 2D images (single or multiple) into high-quality 3D models.
ComfyUI has now natively integrated the corresponding Tripo API, allowing you to conveniently use the related nodes in ComfyUI for model generation.

## What Tripo Model Generation is good at

Currently, ComfyUI's Partner nodes support the following Tripo model generation capabilities:

* Text-to-model
* Image-to-model
* Multi-view model generation
* Rig model
* Retarget rigged model

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Text-to-Model Workflow

Generate a 3D model from a text prompt with Tripo's text-to-model capabilities.

<img alt="Tripo Text-to-Model workflow preview" />

<CardGroup>
  <Card title="Run Text-to-Model on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo_text_to_model&utm_source=docs&utm_medium=referral&utm_campaign=model-generation">
    Try the Text-to-Model workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Text-to-Model Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/api_tripo_text_to_model.json">
    Download JSON to run locally in ComfyUI.
  </Card>
</CardGroup>

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Tripo Text to Model Step Guide" />

You can refer to the numbers in the image to complete the basic text-to-model workflow execution:

1. In the `Tripo: Text to Model` node, input your prompt in the `prompt` field
   * model: You can select different models
   * style: You can set different styles
   * texture\_quality: You can set different texture qualities
2. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation. After the workflow completes, the corresponding model will be automatically saved to the `ComfyUI/output/` directory
3. In the `Preview 3D` node, click to expand the menu
4. Select `Export` to directly export the corresponding model

## Image-to-Model Workflow

Generate a 3D model from a single image input.

<img alt="Tripo Image-to-Model workflow preview" />

<CardGroup>
  <Card title="Run Image-to-Model on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=model-generation">
    Try the Image-to-Model workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Image-to-Model Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/image_to_model/api_tripo_image_to_model.json">
    Download JSON to run locally in ComfyUI.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="Input image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_tripo_image_to_model_input_image.jpg">
      Download sample input image
    </Card>
  </CardGroup>
</details>

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/image_to_model/panda.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Tripo Text to Model Step Guide" />

You can refer to the numbers in the image to complete the basic image-to-model workflow execution:

1. In the `Load Image` node, load the provided input image
2. In the `Tripo: Image to Model` node, modify the corresponding parameter settings
   * model: You can select different models
   * style: You can set different styles
   * texture\_quality: You can set different texture qualities
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation. After the workflow completes, the corresponding model will be automatically saved to the `ComfyUI/output/` directory
4. For model download, please refer to the instructions in the text-to-model section

## Multi-view Model Generation Workflow

Generate a 3D model from multiple view images for enhanced accuracy.

<img alt="Tripo Multi-view Model Generation workflow preview" />

<CardGroup>
  <Card title="Run Multiview-to-Model on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo_multiview_to_model&utm_source=docs&utm_medium=referral&utm_campaign=model-generation">
    Try the Multiview-to-Model workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Multiview-to-Model Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/multiview_to_image/api_tripo_multiview_to_model.json">
    Download JSON to run locally in ComfyUI.
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="Front view" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_tripo_multiview_to_model_front_image.jpg">
      Download front view input
    </Card>

    <Card title="Back view" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/api_tripo_multiview_to_model_back_image.jpg">
      Download back view input
    </Card>
  </CardGroup>
</details>

![Front View](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/multiview_to_image/front.jpg)
![Back View](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/multiview_to_image/back.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Tripo Text to Model Step Guide" />

You can refer to the numbers in the image to complete the basic multi-view to model workflow execution:

1. In the `Load Image` nodes, load the provided input images respectively
2. In the `Tripo: Image to Model` node, modify the corresponding parameter settings
   * model: You can select different models
   * style: You can set different styles
   * texture\_quality: You can set different texture qualities
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation. After the workflow completes, the corresponding model will be automatically saved to the `ComfyUI/output/` directory
4. For other view inputs, you can refer to the step diagram and set the corresponding node mode to `Always` to enable it
5. For model download, please refer to the instructions in the text-to-model section

## Subsequent Task Processing for the Same Task

Tripo's corresponding nodes provide subsequent processing for the same task, you only need to input the corresponding `model_task_id` in the relevant nodes, and we have also provided the corresponding nodes in the relevant templates, you can also modify the corresponding node mode as needed to enable it

<img alt="Tripo Task Processing" />


# Tripo 3.1: High-Detail 3D Asset Generation ComfyUI Official Guide
Source: https://docs.comfy.org/tutorials/partner-nodes/tripo/tripo-3-1

Generate high-detail 3D assets with Tripo 3.1 in ComfyUI Partner Nodes: denser geometry, improved surface quality, and PBR-ready materials.

Tripo 3.1 is the latest model version available through Tripo Partner Nodes in ComfyUI. It offers higher geometry density and improved surface quality compared to previous versions, making it suitable for close-up production use.

## What Tripo 3.1 is good at

Compared to previous Tripo model versions, 3.1 provides the following improvements:

* **High-density geometry**: Sharper edges, cleaner silhouettes, and more precise forms for production-level 3D assets.
* **PBR-ready materials**: More reliable lighting response across different render environments.
* **Hero asset quality**: Stable detail retention in close-up shots.
* **Cross-scenario reuse**: A single model can work across game, marketing, and render pipelines without regeneration.

## Use Cases

* **Game hero assets**: For close-up camera shots and promotional key art.
* **Marketing visuals**: Where geometric fidelity and material quality are critical.
* **Product visualization**: Cleaner shape definition in studio-style renders.
* **3D printing preparation**: Better structural clarity.

## Version Comparison

| Aspect | Tripo 3.1 | Previous Versions |
| - | - | - |
| Geometry Density | High-density, production-ready | Standard density |
| Surface Quality | Cleaner edges and silhouettes | Good, but may require polish for close-ups |
| Material Output | PBR-ready | Standard material maps |

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Text-to-Model

Generate a high-detail 3D model from a text prompt using Tripo 3.1.

<img alt="Tripo 3.1 Text-to-Model workflow preview" />

<CardGroup>
  <Card title="Run Text-to-Model on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo3_1_text_to_model&utm_source=docs&utm_medium=referral&utm_campaign=tripo-3-1">
    Try the Text-to-Model workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Text-to-Model Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo3_1_text_to_model.json">
    Download JSON or search "Tripo 3.1 Text-to-Model" in Template Library.
  </Card>
</CardGroup>

## Image-to-Model

Generate a high-detail 3D model from an image input using Tripo 3.1.

<img alt="Tripo 3.1 Image-to-Model workflow preview" />

<CardGroup>
  <Card title="Run Image-to-Model on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo3_1_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=tripo-3-1">
    Try the Image-to-Model workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Image-to-Model Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo3_1_image_to_model.json">
    Download JSON or search "Tripo 3.1 Image-to-Model" in Template Library.
  </Card>
</CardGroup>

## Multiview-to-Model

Generate a high-detail 3D model from multiple view images using Tripo 3.1.

<img alt="Tripo 3.1 Multiview-to-Model workflow preview" />

<CardGroup>
  <Card title="Run Multiview-to-Model on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo3_1_multiview_to_model&utm_source=docs&utm_medium=referral&utm_campaign=tripo-3-1">
    Try the Multiview-to-Model workflow instantly on Comfy Cloud.
  </Card>

  <Card title="Download Multiview-to-Model Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo3_1_multiview_to_model.json">
    Download JSON or search "Tripo 3.1 Multiview-to-Model" in Template Library.
  </Card>
</CardGroup>


# Tripo P1 3D Model Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/tripo/tripo-p1

This guide explains how to use Tripo P1 Partner Nodes in ComfyUI to generate game-ready 3D models from text, images, or multiview references

The [Tripo P1](/built-in-nodes/TripoP1ImageToModelNode) Partner Nodes enable fast, high-quality 3D model generation from text prompts, single images, or multi-view references. The generated models come with clean topology, optimized polygon budgets, and support for texturing, rigging, and retargeting — ready for use in game engines and 3D applications.

## What Tripo P1 is good at

* **Flexible inputs**: Generate 3D models from text prompts, single images, or multi-view references
* **Clean topology**: Models come with clean topology and optimized polygon budgets
* **Texturing, rigging, and retargeting**: Generated models support texturing, rigging, and retargeting
* **Game-ready output**: Assets are ready for use in game engines and 3D applications

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Tripo P1: Text to Model

Generate a 3D model from a text description.

<img alt="Tripo P1 Text to Model Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo_p1_text_to_model&utm_source=docs&utm_medium=referral&utm_campaign=tripo_p1_t2m">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo_p1_text_to_model.json">
    Download JSON or search "Tripo P1: Text to Model" in Template Library
  </Card>
</CardGroup>

### Steps to Run

1. **Enter your prompt** — describe the 3D model in the **TripoP1TextToModelNode**
2. **Select texture mode** — choose between Textured, None, or PBR
3. **Enable refinement** — toggle quad remeshing for cleaner topology
4. **Set seed** — control reproducibility
5. **Click Queue** — press `Ctrl+Enter` to generate
6. **Preview and export** — use the **Preview3D** node to inspect, and **SaveGLB** to export

### Key Processing Nodes

After the initial generation, the workflow automatically processes the model through:

* **TripoTextureNode** — applies materials and textures
* **TripoConversionNode** — converts to GLTF format (or other export formats)
* **TripoRigNode** — adds a skeleton for animation
* **TripoRetargetNode** — applies a preset animation (default: idle)

## Tripo P1: Image to Model

Generate a 3D model from a single reference image.

<img alt="Tripo P1 Image to Model Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo_p1_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=tripo_p1_i2m">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo_p1_image_to_model.json">
    Download JSON or search "Tripo P1: Image to Model" in Template Library
  </Card>
</CardGroup>

### Steps to Run

1. **Upload a reference image** — use the **LoadImage** node to load a front-view image of your subject
2. **Select texture mode** — choose Textured, None, or PBR
3. **Enable refinement** — toggle quad remeshing
4. **Choose texture type** — options include `original_image` or `standard`
5. **Click Queue** — press `Ctrl+Enter` to generate

## Tripo P1: Multiview to Model

Generate a 3D model from multiple viewpoint images for better accuracy.

<img alt="Tripo P1 Multiview to Model Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo_p1_mv_to_model&utm_source=docs&utm_medium=referral&utm_campaign=tripo_p1_mv">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo_p1_mv_to_model.json">
    Download JSON or search "Tripo P1: Multiview to Model" in Template Library
  </Card>
</CardGroup>

### Steps to Run

1. **Upload multi-view images** — use multiple **LoadImage** nodes for front, left, back, and other angles
2. **Select texture mode** — choose Textured, None, or PBR
3. **Choose detail level** — options include `standard` and `detailed`
4. **Set texture references** — choose which image drives the texture
5. **Click Queue** — press `Ctrl+Enter` to generate

### Input Tips

* Provide at least **front-facing and profile views** for best results
* Ensure consistent lighting and pose across all reference images
* Higher-quality input images produce better textured output


# Tripo P2: Quad Topology 3D Model Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/tripo/tripo-p2

Generate production-ready 3D models with Tripo P2 partner nodes in ComfyUI: native quad topology, face budgets up to 50,000, and texture levels from 2K to 8K.

Tripo P2 is Tripo's P-series 3D generation model that outputs native quad-topology meshes. Where traditional text-to-3D and image-to-3D models return triangle meshes, Tripo P2 builds geometry from four-sided faces with clean edge loops around joints and even density on flat surfaces. Quads deform predictably under a rig, subdivide cleanly, and are the standard input for retopology-heavy pipelines in games, film, and product visualization.

Tripo P2 supports three input modes: text to model, single image to model, and multiview to model (front, left, back, and right references). Mesh budgets reach 50,000 triangles, or 25,000 quads in quad mode. Texture output is tiered: standard at 2K, detailed at 4K, extreme at 8K, with PBR maps (metallic, roughness, normal) available alongside the base color.

In ComfyUI, the P2 nodes work like the rest of the Tripo partner nodes: add the node, provide your input, and the workflow handles texturing, rigging, conversion, and export automatically. No local GPU or model download is required.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## What Tripo P2 is good at

* **Native quad topology**: quad meshes with clean edge flow, ready for rigging and animation without manual retopology
* **Large mesh budgets**: 48 to 50,000 triangles, or 48 to 25,000 quads in quad mode
* **Tiered texturing**: standard (2K), detailed (4K), or extreme (8K) base color textures, with optional PBR maps
* **Three input modes**: text prompts, a single reference image, or up to four multiview images (front, left, back, right)

Pricing depends on the selected texture level. See [Pricing](/tutorials/partner-nodes/pricing) for details.

## Tripo P2: Text to Model

Generate a 3D model from a text description. Tripo P2 first draws a concept image from the prompt (controlled by `image_seed`), then models the geometry from it.

<img alt="Tripo P2 Text to Model Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo_p2_text_to_model&utm_source=docs&utm_medium=referral&utm_campaign=tripo_p2_t2m">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo_p2_text_to_model.json">
    Download JSON or search "Tripo P2: Text to Model" in Template Library
  </Card>
</CardGroup>

### Steps to Run

1. **Enter your prompt**: describe the 3D model in the **Tripo P2: Text to Model** node (up to 1024 characters). A negative prompt is available in advanced options
2. **Choose the texture level**: `standard` (2K), `detailed` (4K), `extreme` (8K), or `none` for an untextured mesh
3. **Toggle quad output**: with `quad` enabled the mesh returns as FBX; disabled it returns as GLB
4. **Set the face limit**: target face count between 48 and 50,000 (48 to 25,000 with quad), or leave at -1 to let Tripo choose
5. **Click Queue**: press `Ctrl+Enter` to generate

After generation, the node requests the texture level you selected, so the mesh is textured as part of generation, and the workflow saves that result directly (the GLB output, or FBX when `quad` is on). The template also contains **TripoTextureNodeV2**, **TripoRigNode**, **TripoRetargetNode**, and **TripoConversionNode** nodes, but they are bypassed and disconnected by default: connect and enable them (`Ctrl+B` toggles bypass) when you want that extra post-processing.

### Quad output note

When `quad` is enabled, connect **Save 3D** to the FBX output slot. When `quad` is disabled, use the GLB output slot.

## Tripo P2: Image to Model

Generate a 3D model from a single reference image.

<img alt="Tripo P2 Image to Model Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo_p2_image_to_model&utm_source=docs&utm_medium=referral&utm_campaign=tripo_p2_i2m">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo_p2_image_to_model.json">
    Download JSON or search "Tripo P2: Image to Model" in Template Library
  </Card>
</CardGroup>

### Steps to Run

1. **Upload a reference image**: load a front-view image of your subject with the **LoadImage** node
2. **Choose the texture level**: `standard`, `detailed`, `extreme`, or `none`
3. **Toggle quad output**: FBX when enabled, GLB when disabled
4. **Set texture alignment**: `original_image` matches the input image's colors, `geometry` fits the textures to the generated shape (advanced options)
5. **Click Queue**: press `Ctrl+Enter` to generate

### Input tips

* Low-resolution or low-quality images can be enhanced before modeling with the `enable_image_autofix` advanced option
* `align_image` orientation rotates the model to the viewpoint of the input image (advanced options)

## Tripo P2: Multiview to Model

Generate a 3D model from reference views. The multiview node takes a required front view plus up to three of the left, back, and right views, and at least one of those extra views must be connected: with the front view alone the node returns an error. It reconstructs the geometry with the same native quad topology as the other P2 nodes.

<img alt="Tripo P2 Multiview to Model Workflow" />

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo_p2_multiview_to_model&utm_source=docs&utm_medium=referral&utm_campaign=tripo_p2_mv2m">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo_p2_multiview_to_model.json">
    Download JSON or search "Tripo P2: Multiview to Model" in Template Library
  </Card>
</CardGroup>

**Input materials**

Upload these files to the matching `LoadImage` nodes:

<CardGroup>
  <Card title="worker_doll_front.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/worker_doll_front.png">
    `LoadImage` node 16 · front view
  </Card>

  <Card title="worker_doll_back.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/worker_doll_back.png">
    `LoadImage` node 19 · back view
  </Card>
</CardGroup>

### Steps to Run

1. **Load the reference views**: the template ships with a front view (`LoadImage` node 16) and a back view (`LoadImage` node 19). The node also exposes `image_left` and `image_right` inputs for a four-view reconstruction
2. **Choose the texture level**: `standard` (2K), `detailed` (4K), `extreme` (8K), or `none` for an untextured mesh
3. **Toggle quad output**: with `quad` enabled the mesh returns as FBX; disabled it returns as GLB
4. **Set the face limit**: target face count between 48 and 50,000 (48 to 25,000 with quad), or leave at -1 to let Tripo choose
5. **Click Queue**: press `Ctrl+Enter` to generate

The workflow saves the generated mesh directly. The texture, rig, retarget, and conversion nodes the template also contains are bypassed and disconnected by default.

## Node options reference

Options shared by all three P2 nodes:

| Option | Values | Default | Notes |
| - | - | - | - |
| `quad` | on / off | off | Quad mesh as FBX when on, triangle mesh as GLB when off |
| `face_limit` | 48 to 50,000 (25,000 with quad) | -1 | Target face count; the result can exceed it |
| `texture` | standard / detailed / extreme / none | standard | 2K / 4K / 8K base color; none returns an untextured mesh |
| `pbr` | on / off | on | Metallic, roughness, and normal maps; ignored when texture is none |
| `model_seed` | 0 to 2147483647 | 42 | Seed for the geometry |

Advanced options include `texture_seed`, `auto_size` (real-world scale in meters), `export_uv`, and `compress_geometry` (Meshopt compression; compressed meshes are much smaller but cannot be previewed in ComfyUI's 3D viewport).


# Video Models
Source: https://docs.comfy.org/tutorials/partner-nodes/video/overview

Choose the right video model for your use case: text-to-video, image-to-video, video enhancement, and more

ComfyUI Partner Nodes give you access to hosted video models from providers such as Black Forest Labs, ByteDance, Google, Kling, Luma, Runway, and Topaz, so you can generate video without a local GPU. This page helps you pick the right model for text-to-video, image-to-video, video enhancement, or motion control.

## Browse video models

<CardGroup>
  <Card title="FLUX 3 Video" icon="video" href="/tutorials/partner-nodes/black-forest-labs/flux-3-video">
    Black Forest Labs' video model, built on the Flux family
  </Card>

  <Card title="FLUX Video Upscale" icon="video" href="/tutorials/partner-nodes/black-forest-labs/flux-video-upscale">
    Upscale and enhance generated video
  </Card>

  <Card title="Seedance 2.5" icon="video" href="/tutorials/partner-nodes/bytedance/seedance-2-5">
    Strong all-round text-to-video generation
  </Card>

  <Card title="Seedance 2.0" icon="video" href="/tutorials/partner-nodes/bytedance/seedance-2-0">
    Text-to-video generation from ByteDance
  </Card>

  <Card title="Seedance 2.0 Real Human" icon="video" href="/tutorials/partner-nodes/bytedance/seedance-2-0-real-human">
    Human motion and character animation
  </Card>

  <Card title="VCube" icon="video" href="/tutorials/partner-nodes/bytedance/vcube">
    Video generation from ByteDance
  </Card>

  <Card title="Gemini Omni Flash" icon="video" href="/tutorials/partner-nodes/google/gemini-omni-flash">
    Multimodal video generation from Google
  </Card>

  <Card title="Grok Video" icon="video" href="/tutorials/partner-nodes/grok/grok-video">
    Video generation and extension from xAI
  </Card>

  <Card title="Grok Imagine Video 1.5" icon="video" href="/tutorials/partner-nodes/grok/grok-imagine-video-1-5">
    Fast text-to-video from xAI
  </Card>

  <Card title="HappyHorse 1.1" icon="video" href="/tutorials/partner-nodes/happyhorse/happyhorse1-1">
    Image-driven animation
  </Card>

  <Card title="HappyHorse 1.0" icon="video" href="/tutorials/partner-nodes/happyhorse/happyhorse1-0">
    Image-driven animation
  </Card>

  <Card title="Kling 3.0" icon="video" href="/tutorials/partner-nodes/kling/kling-3-0">
    Image-to-video and text-to-video with strong motion
  </Card>

  <Card title="Kling Motion Control" icon="video" href="/tutorials/partner-nodes/kling/kling-motion-control">
    Control camera and subject motion
  </Card>

  <Card title="LTX-2.5" icon="video" href="/tutorials/partner-nodes/lightricks/ltx-2-5">
    Video generation from Lightricks
  </Card>

  <Card title="Luma Text-to-Video" icon="video" href="/tutorials/partner-nodes/luma/luma-text-to-video">
    Turn a text prompt into a short animated clip
  </Card>

  <Card title="Luma Image-to-Video" icon="video" href="/tutorials/partner-nodes/luma/luma-image-to-video">
    Turn a single image into a short animated clip
  </Card>

  <Card title="MiniMax H3" icon="video" href="/tutorials/partner-nodes/minimax/minimax-h3">
    Video generation from MiniMax
  </Card>

  <Card title="Moonvalley" icon="video" href="/tutorials/partner-nodes/moonvalley/moonvalley-video-generation">
    Video generation from Moonvalley
  </Card>

  <Card title="Pruna P-Video-2" icon="video" href="/tutorials/partner-nodes/pruna/p-video-2">
    Quality-focused video generation with native audio
  </Card>

  <Card title="Runway Video Generation" icon="video" href="/tutorials/partner-nodes/runway/video-generation">
    Image-to-video and text-to-video with cinematic quality
  </Card>

  <Card title="Topaz Astra 2" icon="video" href="/tutorials/partner-nodes/topaz/astra-2">
    Creative diffusion video upscaling
  </Card>

  <Card title="Topaz Video Enhance Astra" icon="video" href="/tutorials/partner-nodes/topaz/video-enhance-astra">
    Quality restoration tools from Topaz
  </Card>

  <Card title="Topaz Video Enhance Starlight Precise 2.5" icon="video" href="/tutorials/partner-nodes/topaz/video-enhance-starlight-precise-2-5">
    Upscaling and enhancement from Topaz
  </Card>

  <Card title="Wan 3.0" icon="video" href="/tutorials/partner-nodes/wan/wan3-0">
    Open-model video generation with good motion quality
  </Card>

  <Card title="Wan 2.7" icon="video" href="/tutorials/partner-nodes/wan/wan2-7">
    Open-model video generation from Wan
  </Card>
</CardGroup>

## What you can do with video models

* **Text-to-video**: Generate a video from a text prompt
* **Image-to-video**: Animate a still image to bring a photo or artwork to life
* **Video enhancement**: Upscale, interpolate frames, or improve video quality
* **Motion control**: Control camera movement, subject motion, or character motion in generated videos

## Choosing a model by task

### General-purpose text-to-video

* **Seedance 2.5 / 2.0** (ByteDance): strong all-round text-to-video generation
* **FLUX 3 Video** (Black Forest Labs): Black Forest Labs' video model, built on the Flux family
* **Wan 3.0 / Wan 2.7** (Wan): open-model video generation with good motion quality
* **Grok Imagine Video 1.5** (Grok): fast text-to-video from xAI

### Image-to-video

* **Luma Image-to-Video** (Luma): turn a single image into a short animated clip
* **Kling 3.0** (Kling): image-to-video and text-to-video with strong motion
* **Runway Video Generation** (Runway): image-to-video and text-to-video with cinematic quality
* **HappyHorse 1.1 / 1.0** (HappyHorse): image-driven animation

### Video enhancement & upscaling

* **FLUX Video Upscale** (Black Forest Labs): upscale and enhance generated video
* **Topaz Video Enhance Starlight Precise 2.5** (Topaz): upscaling and enhancement
* **Topaz Astra / Video Enhance Astra** (Topaz): quality restoration tools

### Motion control & character animation

* **Kling Motion Control** (Kling): control camera and subject motion
* **Seedance 2.0 Real Human** (ByteDance): human motion and character animation

## All video partners

| Partner | Models |
| - | - |
| Black Forest Labs | [FLUX 3 Video](/tutorials/partner-nodes/black-forest-labs/flux-3-video), [FLUX Video Upscale](/tutorials/partner-nodes/black-forest-labs/flux-video-upscale) |
| ByteDance | [Seedance 2.5](/tutorials/partner-nodes/bytedance/seedance-2-5), [Seedance 2.0](/tutorials/partner-nodes/bytedance/seedance-2-0), [Seedance 2.0 Real Human](/tutorials/partner-nodes/bytedance/seedance-2-0-real-human), [VCube](/tutorials/partner-nodes/bytedance/vcube) |
| Google | [Gemini Omni Flash](/tutorials/partner-nodes/google/gemini-omni-flash) |
| Grok | [Grok Video](/tutorials/partner-nodes/grok/grok-video), [Grok Imagine Video 1.5](/tutorials/partner-nodes/grok/grok-imagine-video-1-5) |
| HappyHorse | [HappyHorse 1.1](/tutorials/partner-nodes/happyhorse/happyhorse1-1), [HappyHorse 1.0](/tutorials/partner-nodes/happyhorse/happyhorse1-0) |
| Kling | [Kling 3.0](/tutorials/partner-nodes/kling/kling-3-0), [Kling Motion Control](/tutorials/partner-nodes/kling/kling-motion-control) |
| Lightricks | [LTX-2.5](/tutorials/partner-nodes/lightricks/ltx-2-5) |
| Luma | [Luma Text-to-Video](/tutorials/partner-nodes/luma/luma-text-to-video), [Luma Image-to-Video](/tutorials/partner-nodes/luma/luma-image-to-video) |
| MiniMax | [MiniMax H3](/tutorials/partner-nodes/minimax/minimax-h3) |
| Moonvalley | [Moonvalley](/tutorials/partner-nodes/moonvalley/moonvalley-video-generation) |
| Pruna | [P-Video-2](/tutorials/partner-nodes/pruna/p-video-2) |
| Runway | [Video Generation](/tutorials/partner-nodes/runway/video-generation) |
| Topaz | [Video Enhance Starlight Precise 2.5](/tutorials/partner-nodes/topaz/video-enhance-starlight-precise-2-5), [Video Enhance Astra](/tutorials/partner-nodes/topaz/video-enhance-astra), [Astra 2](/tutorials/partner-nodes/topaz/astra-2) |
| Wan | [Wan 3.0](/tutorials/partner-nodes/wan/wan3-0), [Wan 2.7](/tutorials/partner-nodes/wan/wan2-7) |

See [Pricing](/tutorials/partner-nodes/pricing) for per-model rates, and [Concurrency Limits](/tutorials/partner-nodes/concurrency-limits) for usage caps.


# Wan2.7 Video Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/wan/wan2-7

Learn how to use Wan2.7 via Partner Nodes in ComfyUI for image-to-video, text-to-video, reference-to-video, video continuation, and video editing

Wan2.7 is Alibaba's latest video generation model, now available in ComfyUI via Partner Nodes. It is a comprehensive upgrade over version 2.6 with significant improvements across image quality, audio, motion dynamics, stylization, and consistency.

This release brings a fully upgraded multimodal video pipeline directly into your node graph, supporting text, image, audio, and video inputs across five task types.

## What Wan2.7 is good at

* **Image-to-video**: First-frame, first+last-frame, and audio-driven generation
* **Text-to-video**: Pure text prompts with optional audio input and multi-shot narration
* **Video continuation**: Extend an existing clip with new content guided by a text prompt
* **Reference-to-video**: Reference both a subject's visual appearance and vocal timbre; supports up to 5 real-person inputs and multi-character interactions
* **Video edit**: Edit or replicate videos via text prompts, reference image, or style transfer

## Highlights

* Supports up to **5 real-person image inputs** for multi-character scenes
* Vocal timbre reference for consistent audio-visual identity
* 3x3 grid-based image generation
* Significant improvements in motion dynamics, stylization, and consistency over Wan2.6

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Wan2.7 image-to-video

Generate video from image inputs. Supports first-frame, first+last-frame, and audio-driven generation modes.

<img alt="Wan2.7 I2V workflow preview" />

<CardGroup>
  <Card title="Wan2.7 I2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan2_7_i2v.json">
    Get the Wan2.7 Image-to-Video workflow file.
  </Card>

  <Card title="Run Wan2.7 I2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan2_7_i2v&utm_source=docs&utm_medium=referral&utm_campaign=wan2-7">
    Try the Image-to-Video workflow instantly on Comfy Cloud.
  </Card>
</CardGroup>

## Wan2.7 text-to-video

Generate video from pure text prompts. Optionally include audio input and multi-shot narration for richer storytelling.

<img alt="Wan2.7 T2V workflow preview" />

<CardGroup>
  <Card title="Wan2.7 T2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan2_7_t2v.json">
    Get the Wan2.7 Text-to-Video workflow file.
  </Card>

  <Card title="Run Wan2.7 T2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan2_7_t2v&utm_source=docs&utm_medium=referral&utm_campaign=wan2-7">
    Try the Text-to-Video workflow instantly on Comfy Cloud.
  </Card>
</CardGroup>

## Wan2.7 reference-to-video

Use reference images of a subject's visual appearance along with an optional vocal timbre reference. Supports up to 5 real-person inputs for multi-character interaction scenes.

<img alt="Wan2.7 R2V workflow preview" />

<CardGroup>
  <Card title="Wan2.7 R2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan2_7_r2v.json">
    Get the Wan2.7 Reference-to-Video workflow file.
  </Card>

  <Card title="Run Wan2.7 R2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan2_7_r2v&utm_source=docs&utm_medium=referral&utm_campaign=wan2-7">
    Try the Reference-to-Video workflow instantly on Comfy Cloud.
  </Card>
</CardGroup>

## Wan2.7 video edit

Edit or replicate existing videos using text prompts, a reference image, or style transfer.

<img alt="Wan2.7 Video Edit workflow preview" />

<CardGroup>
  <Card title="Wan2.7 Video Edit Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan2_7_video_edit.json">
    Get the Wan2.7 Video Edit workflow file.
  </Card>

  <Card title="Run Wan2.7 Video Edit on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan2_7_video_edit&utm_source=docs&utm_medium=referral&utm_campaign=wan2-7">
    Try the Video Edit workflow instantly on Comfy Cloud.
  </Card>
</CardGroup>


# Wan 3.0 Video Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/wan/wan3-0

Learn how to use Wan 3.0 via Partner Nodes in ComfyUI for text-to-video, image-to-video, and reference-to-video generation with synchronized audio

Wan 3.0 is Alibaba's latest video generation model, now available in ComfyUI via Partner Nodes. It generates up to 30 seconds of video in a single pass with a synchronized audio track, and combines text prompts with reference images, videos, and audio for consistent characters and scenes.

## What Wan 3.0 is good at

* **Up to 30 seconds**: Generates long clips with coherent motion and audio in a single pass
* **Native audio**: Every output includes a synchronized audio track by default
* **Text, image, and reference input**: Pure text prompts, first-frame animation, or up to 10 reference images, 5 reference videos, and 5 reference audio clips
* **Reference tags**: Mention connected media directly in the prompt as `@Image1`, `@Video1`, or `@Audio1`
* **Flexible output**: 480p, 720p, or 1080p resolution with adaptive, 16:9, 9:16, 1:1, 4:3, or 3:4 aspect ratios
* **WAN3-Prime model**: The `model` option also offers `wan3.0-video-prime` for higher-fidelity output at a higher per-second rate
* **Bilingual prompts**: Prompt in English or Chinese

## Example outputs

Text-to-video generation from a prompt alone, with synchronized audio included by default:

![Wan 3.0 text-to-video example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_wan3_0_t2v-1.webp)

Image-to-video generation, animating a single image into a full clip:

![Wan 3.0 image-to-video example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_wan3_0_i2v-1.webp)

Reference-to-video generation, keeping a product and character consistent from reference images:

![Wan 3.0 reference-to-video example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_wan3_0_r2v-1.webp)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Local users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated.

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Cloud users">
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Wan 3.0 text-to-video workflow

Generate a video from a text prompt alone, with synchronized audio included by default.

![Wan 3.0 text-to-video example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_wan3_0_t2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan3_0_t2v&utm_source=docs&utm_medium=referral&utm_campaign=wan-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan3_0_t2v.json">
    Download JSON or search "Wan 3.0" in Template Library
  </Card>
</CardGroup>

#### Prompting tips

1. **Duration**: Set 2 to 30 seconds, or `auto` to let the model choose a duration that fits the prompt
2. **Resolution and ratio**: The workflow ships at 720p with `adaptive` ratio; switch to 1080p or a fixed ratio like `16:9` for specific formats
3. **Audio**: Audio is generated by default. Disable the `audio` option to get silent video
4. **Prompt extend**: Prompt enhancement is on by default and rewrites your prompt for better results. Turn it off in advanced settings if you need exact wording

## Wan 3.0 image-to-video workflow

Animate a single image into a video, with an optional last frame that the output transitions toward.

![Wan 3.0 image-to-video example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_wan3_0_i2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan3_0_i2v&utm_source=docs&utm_medium=referral&utm_campaign=wan-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan3_0_i2v.json">
    Download JSON or search "Wan 3.0" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download this sample input image to try the workflow:

  <CardGroup>
    <Card title="First frame: beetle_rider.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/beetle_rider.png">
      First frame for the workflow, or use your own image.
    </Card>
  </CardGroup>
</details>

#### Prompting tips

1. **First frame**: The `first_frame` input is required. The `last_frame` input is optional, and the model generates the motion between the two
2. **Adaptive ratio**: With `adaptive`, the output dimensions follow the input image
3. **Prompt**: Describe what moves and how, plus the audio you want. Keep the subjects and composition unchanged unless you want the model to alter them

## Wan 3.0 reference-to-video workflow

Generate a video conditioned on reference images, videos, and audio, with each reference assigned a job through tags in the prompt.

![Wan 3.0 reference-to-video example output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/api_wan3_0_r2v-1.webp)

<CardGroup>
  <Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan3_0_r2v&utm_source=docs&utm_medium=referral&utm_campaign=wan-3-0">
    Open in Comfy Cloud
  </Card>

  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan3_0_r2v.json">
    Download JSON or search "Wan 3.0" in Template Library
  </Card>
</CardGroup>

<details>
  <summary>Input materials</summary>

  Download these sample input images to try the workflow:

  <CardGroup>
    <Card title="Product reference: vortex_shoe.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/vortex_shoe.png">
      Reference image for the product in the video.
    </Card>

    <Card title="Character reference: psss_character.png" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/psss_character.png">
      Reference image for the character in the video.
    </Card>
  </CardGroup>
</details>

#### Prompting tips

1. **Reference by tag**: Refer to each input in the prompt as `@Image1`, `@Video1`, or `@Audio1`, numbered per type in input order. The sample prompt assigns the shoe design to `@Image1` and the character to `@Image2`
2. **Limits**: Up to 10 reference images, 5 reference videos, and 5 reference audio clips. Each reference video or audio clip must be 15 seconds or shorter, and the combined duration of all reference videos must stay within 15 seconds (same for audio). Total reference video plus output duration must not exceed 30 seconds
3. **Assign a job**: State what each reference controls (product design, character identity, style, motion, voice) and what must stay unchanged. Explicit assignments produce more consistent results
4. **Prompt or reference required**: Provide a prompt or at least one reference input, or the node returns an error

## Get started

1. Update ComfyUI to the latest version, or use the latest [Comfy Desktop](https://www.comfy.org/download)
2. Go to Template Library, search for `Wan 3.0`
3. Load one of the three workflows (text-to-video, image-to-video, or reference-to-video)
4. Log in with your Comfy account and ensure you have enough [credits](/interface/credits)
5. Connect the input materials (first frame or reference images) and run

## FAQs

<AccordionGroup>
  <Accordion title="What is Wan 3.0?">
    Wan 3.0 is Alibaba's latest video generation model, available in ComfyUI through Partner Nodes. It generates up to 30 seconds of video with synchronized audio in a single pass, and accepts text prompts, reference images, reference videos, and reference audio.
  </Accordion>

  <Accordion title="How long can Wan 3.0 videos be?">
    Up to 30 seconds per clip. The duration input accepts 2 to 30 seconds, or `auto` to let the model choose a duration that fits the prompt.
  </Accordion>

  <Accordion title="Does Wan 3.0 generate audio?">
    Yes. Every output includes a synchronized audio track by default, with dialogue, sound effects, and music generated together with the video. Disable the `audio` option for silent video.
  </Accordion>

  <Accordion title="Can Wan 3.0 use reference images, videos, or audio?">
    Yes, in the reference-to-video workflow. Connect up to 10 reference images, 5 reference videos, and 5 reference audio clips, then refer to them in the prompt as `@Image1`, `@Video1`, or `@Audio1`.
  </Accordion>

  <Accordion title="What is the difference between Wan 3.0 and Wan 2.7?">
    Wan 3.0 is the newest generation of Alibaba's video model. It extends the multimodal pipeline with reference tags for images, videos, and audio, native synchronized audio by default, and up to 30 seconds of output per clip. See the [Wan 2.7 page](/tutorials/partner-nodes/wan/wan2-7) for the previous generation.
  </Accordion>

  <Accordion title="Does Wan 3.0 support Chinese prompts?">
    Yes. The prompt input supports both English and Chinese.
  </Accordion>
</AccordionGroup>


# ByteDanceImageEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceImageEditNode

The ByteDance Image Edit node allows you to modify images using ByteDance's AI models through an API.

The ByteDance Image Edit node allows you to modify images using ByteDance's AI models through an API. You provide an input image and a text prompt describing the desired changes, and the node processes the image according to your instructions. The node handles the API communication automatically and returns the edited image.

## Inputs

| Parameter | Description | Data Type | Input Type | Default | Range |
| - | - | - | - | - | - |
| `model` | Model name | MODEL | COMBO | seededit\_3 | Image2ImageModelName options |
| `image` | The base image to edit | IMAGE | IMAGE | - | - |
| `prompt` | Instruction to edit image | STRING | STRING | "" | - |
| `seed` | Seed to use for generation | INT | INT | 0 | 0-2147483647 |
| `guidance_scale` | Higher value makes the image follow the prompt more closely | FLOAT | FLOAT | 5.5 | 1.0-10.0 |
| `watermark` | Whether to add an "AI generated" watermark to the image | BOOLEAN | BOOLEAN | True | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The edited image returned from the ByteDance API | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceImageEditNode/en.md)

***

**Source fingerprint (SHA-256):** `9dc13d89f84756b545120efb5535e08ada163d4534975809f5056bdf7d8bfb73`


# ByteDanceImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceImageNode

The ByteDance Image node generates images using ByteDance models through an API based on text prompts.

The ByteDance Image node generates images using ByteDance models through an API based on text prompts. It allows you to select a model, specify image dimensions, and control various generation parameters like seed and guidance scale. The node connects to ByteDance's image generation service and returns the created image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The ByteDance model to use for image generation. Currently only one model option is available. | STRING | Yes | `"seedream-3-0-t2i-250415"` |
| `prompt` | The text prompt used to generate the image. Must be at least 1 character long after stripping whitespace. | STRING | Yes | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. Available presets are defined by the `RECOMMENDED_PRESETS` list. | STRING | Yes | See description |
| `width` | Custom width for the image. This value is only used when `size_preset` is set to `Custom`. Default: 1024. | INT | Yes | 512 to 2048 (step 64) |
| `height` | Custom height for the image. This value is only used when `size_preset` is set to `Custom`. Default: 1024. | INT | Yes | 512 to 2048 (step 64) |
| `seed` | Seed to use for generation. Default: 0. | INT | No | 0 to 2147483647 (step 1) |
| `guidance_scale` | Higher value makes the image follow the prompt more closely. Default: 2.5. | FLOAT | No | 1.0 to 10.0 (step 0.01) |
| `watermark` | Whether to add an "AI generated" watermark to the image. Default: False. This is an advanced parameter. | BOOLEAN | No | True / False |

**Note on size parameters:** The `width` and `height` parameters are only used when `size_preset` is set to `Custom`. If a preset size is selected, the preset's dimensions override the custom width and height values. Both width and height must be between 512 and 2048 pixels when using custom dimensions.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated image returned from the ByteDance API as a tensor. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceImageNode/en.md)

***

**Source fingerprint (SHA-256):** `0b40c75ca43ef3cccbc644e64822f701a0d772decacd813c58d7d5ac60c230a1`


# ByteDanceImageReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceImageReferenceNode

The ByteDance Image Reference Node generates videos using a text prompt and one to four reference images.

The ByteDance Image Reference Node generates videos using a text prompt and one to four reference images. It sends the images and prompt to an external API service that creates a video matching your description while incorporating the visual style and content from your reference images. The node provides various controls for video resolution, aspect ratio, duration, and other generation parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for video generation (default: `"seedance-1-0-lite-i2v-250428"`). | STRING | Yes | `"seedance-1-0-pro-250528"`<br />`"seedance-1-0-lite-i2v-250428"` |
| `prompt` | The text prompt used to generate the video. | STRING | Yes | - |
| `images` | One to four images. Each image must be between 300x300 and 6000x6000 pixels, with an aspect ratio between 0.4 and 2.5. | IMAGE | Yes | - |
| `resolution` | The resolution of the output video. | STRING | Yes | `"480p"`<br />`"720p"` |
| `aspect_ratio` | The aspect ratio of the output video (default: `"adaptive"`). | STRING | Yes | `"adaptive"`<br />`"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"` |
| `duration` | The duration of the output video in seconds (default: 5). | INT | Yes | 3 - 12 |
| `seed` | Seed to use for generation (default: 0). | INT | No | 0 - 2147483647 |
| `watermark` | Whether to add an "AI generated" watermark to the video (default: False). | BOOLEAN | No | - |

**Note:** The prompt text must not contain the following parameter strings: `--resolution`, `--ratio`, `--duration`, `--seed`, or `--watermark`. These values are controlled exclusively through their dedicated input widgets.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file based on the input prompt and reference images. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceImageReferenceNode/en.md)

***

**Source fingerprint (SHA-256):** `77a0f9aee920d07a1374eaec8489eed494a4505369246c16007765d67e52ef99`


# CFGNorm - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CFGNorm

CFGNorm adjusts how classifier-free guidance (CFG) is applied in diffusion models by comparing the size (norm) of the conditional prediction with the guided prediction and rescalin

CFGNorm adjusts how classifier-free guidance (CFG) is applied in diffusion models by comparing the size (norm) of the conditional prediction with the guided prediction and rescaling the result. A `strength` value controls how much of the adjustment is applied. By default the scaling only attenuates the guidance output, while enabling `pre_cfg` rescales the combined noise before the sampler's CFG combine without clamping, which can amplify the result.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to apply CFG normalization to | MODEL | Yes | - |
| `strength` | Controls the intensity of the normalization effect applied to the CFG scaling (default: 1.0) | FLOAT | Yes | 0.0 to 100.0 (step 0.01) |
| `pre_cfg` | If true, rescale the combined noise BEFORE the sampler's CFG combine, without clamping (can amplify). Matches the norm-scaled CFG used by models like Lens. Default false keeps the original post-CFG x0-space attenuate-only behavior. (default: False) | BOOLEAN | No | true / false |

Note: This node is marked as experimental.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `patched_model` | Returns the modified model with CFG normalization applied to its sampling process | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CFGNorm/en.md)

***

**Source fingerprint (SHA-256):** `427dda498ebda2642489aa2591f063355a77b1e064e0dc7fa8570ed8200c2734`


# CFGZeroStar - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CFGZeroStar

The CFGZeroStar node applies a specialized guidance scaling technique to diffusion models.

The CFGZeroStar node applies a specialized guidance scaling technique to diffusion models. It modifies the classifier-free guidance process by calculating an optimized scale factor based on the difference between conditional and unconditional predictions. This approach adjusts the final output to provide enhanced control over the generation process while maintaining model stability.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to be modified with the CFGZeroStar guidance scaling technique | MODEL | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `patched_model` | The modified model with CFGZeroStar guidance scaling applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CFGZeroStar/en.md)

***

**Source fingerprint (SHA-256):** `4ec70f67eed8aaca964ce3dfb5b650af2f44d34bcde3b74c3886c91e1e8e8cc0`


# CombineHooks - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CombineHooks

The Combine Hooks [2] node merges two hook groups into a single combined hook group.

The Combine Hooks \[2] node merges two hook groups into a single combined hook group. It takes two optional hook inputs and combines them using ComfyUI's hook combination functionality. This allows you to consolidate multiple hook configurations for streamlined processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `hooks_A` | First hook group to combine | HOOKS | No | - |
| `hooks_B` | Second hook group to combine | HOOKS | No | - |

**Note:** Both inputs are optional, but at least one hook group must be provided for the node to function. If only one hook group is provided, it will be returned unchanged.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `hooks` | Combined hook group containing all hooks from both input groups | HOOKS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CombineHooks/en.md)

***

**Source fingerprint (SHA-256):** `558ceef1cebedd0b7e045b7d1eb1afa4316ea6a3c35f982968af132dca164126`


# CombineHooksEight - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CombineHooksEight

The Combine Hooks [8] node merges up to eight different hook groups into a single combined hook group.

The Combine Hooks \[8] node merges up to eight different hook groups into a single combined hook group. It takes multiple hook inputs and combines them using ComfyUI's hook combination functionality. This allows you to consolidate multiple hook configurations for streamlined processing in advanced workflows.

## Inputs

| Parameter | Description | Data Type | Input Type | Default | Range |
| - | - | - | - | - | - |
| `hooks_A` | First hook group to combine | HOOKS | optional | None | - |
| `hooks_B` | Second hook group to combine | HOOKS | optional | None | - |
| `hooks_C` | Third hook group to combine | HOOKS | optional | None | - |
| `hooks_D` | Fourth hook group to combine | HOOKS | optional | None | - |
| `hooks_E` | Fifth hook group to combine | HOOKS | optional | None | - |
| `hooks_F` | Sixth hook group to combine | HOOKS | optional | None | - |
| `hooks_G` | Seventh hook group to combine | HOOKS | optional | None | - |
| `hooks_H` | Eighth hook group to combine | HOOKS | optional | None | - |

**Note:** All input parameters are optional. The node will combine only the hook groups that are provided, ignoring any that are left empty. You can provide anywhere from one to eight hook groups for combination.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `HOOKS` | A single combined hook group containing all the provided hook configurations | HOOKS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CombineHooksEight/en.md)

***

**Source fingerprint (SHA-256):** `8cd13ec6710a9b2905c14301cfd15be616c00f1b4140451cdf0915f091c77197`


# CombineHooksFour - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CombineHooksFour

The Combine Hooks [4] node merges up to four separate hook groups into a single combined hook group.

The Combine Hooks \[4] node merges up to four separate hook groups into a single combined hook group. It takes any combination of the four available hook inputs and combines them using ComfyUI's hook combination system. This allows you to consolidate multiple hook configurations for streamlined processing in advanced workflows.

## Inputs

| Parameter | Description | Data Type | Input Type | Default | Range |
| - | - | - | - | - | - |
| `hooks_A` | First hook group to combine | HOOKS | optional | None | - |
| `hooks_B` | Second hook group to combine | HOOKS | optional | None | - |
| `hooks_C` | Third hook group to combine | HOOKS | optional | None | - |
| `hooks_D` | Fourth hook group to combine | HOOKS | optional | None | - |

**Note:** All four hook inputs are optional. The node will combine only the hook groups that are provided, and will return an empty hook group if no inputs are connected.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `HOOKS` | Combined hook group containing all provided hook configurations | HOOKS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CombineHooksFour/en.md)

***

**Source fingerprint (SHA-256):** `92a8038e7b5a7491afcbd48830a1e278fe4d697321fb874821ebf7edd09d5815`


# ComfyCloudFlux2TextToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyCloudFlux2TextToImageNode

Runs the Flux 2 dev text-to-image model on a Comfy Cloud GPU and returns the generated image.

Runs the Flux 2 dev text-to-image model on a Comfy Cloud GPU and returns the generated image. The `turbo` option applies the Turbo LoRA with a short schedule for a much quicker run at the cost of a little fidelity; turning it off performs the full-length dev pass without the LoRA. This is a beta node set, billed by how long it runs in credits.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | The text prompt describing the image to generate. Leading and trailing whitespace is removed before submission. | STRING | Yes | 1 to 4096 characters |
| `seed` | Random seed that controls the generated result for reproducibility (default: 42). | INT | Yes | 0 to 18446744073709551615 |
| `aspect_ratio` | Aspect ratio of the output image (default: "1:1"). | COMBO | Yes | "1:1"<br />"3:4"<br />"2:3"<br />"3:2"<br />"4:3"<br />"16:9"<br />"9:16"<br />"21:9" |
| `megapixels` | Total pixel budget. 1.0 is about 1024x1024 at a square ratio (default: 1.0). | FLOAT | Yes | 0.1 to 16.0 (step 0.1) |
| `turbo` | Run the Turbo LoRA on a short schedule, trading a little fidelity for a much quicker run. Off runs the full dev pass with no LoRA (default: True). | BOOLEAN | Yes | True / False |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The image generated from the text prompt, returned as a ComfyUI image tensor that can be passed to other nodes. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyCloudFlux2TextToImageNode/en.md)

***

**Source fingerprint (SHA-256):** `1b51a8ab89ae7c355dec4256a1a25a09a15e192c72fc8d1862c652dbdf337fcb`


# ComfyCloudMageFlowTextToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyCloudMageFlowTextToImageNode

This node generates an image from a text prompt by sending the request to the Mage-Flow text-to-image workflow in the Comfy Cloud.

This node generates an image from a text prompt by sending the request to the Mage-Flow text-to-image workflow in the Comfy Cloud. It runs the full 30-step generation pass rather than the faster distilled turbo pass, and it accepts a negative prompt so you can describe content you do not want in the final image. The negative prompt is supported in this 30-step mode; per the node summary, the distilled turbo variant cannot make good use of it.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | The text description of the image to generate. | STRING | Yes | Free-form text |
| `negative_prompt` | Text describing content that should not appear in the generated image. This input is used during the standard 30-step generation pass, but the distilled turbo variant does not use negative prompts well. | STRING | No | Free-form text |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The image generated from the provided text prompt and negative prompt. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyCloudMageFlowTextToImageNode/en.md)

***

**Source fingerprint (SHA-256):** `80f4ecf1df3f2c46d94138f8ada817e12cc49e69e69a001630776ed644868367`


# ComfyCloudMageFlowTurboTextToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyCloudMageFlowTurboTextToImageNode

This Comfy Cloud node generates an image from a text prompt using the Mage-Flow Turbo workflow (mage-flow-turbo/text-to-image).

This Comfy Cloud node generates an image from a text prompt using the Mage-Flow Turbo workflow (`mage-flow-turbo/text-to-image`). It runs a distilled version of the Mage-Flow model that produces the image in 4 steps at a cfg value of 1, taking roughly one seventh of the GPU time of a full Mage-Flow pass, which makes it the variant intended for fast iteration.

## Inputs

The node class itself does not declare input widgets in the available source; its input schema is inherited from the shared base class `_ComfyCloudMageFlowNode`, whose definition is not included in the source snapshot. Based on the node summary and the text-to-image workflow name, the node takes a text prompt describing the image to generate.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | The text prompt describing the image to generate. The exact parameter name is set by the inherited `_ComfyCloudMageFlowNode` base schema and may differ from this label. | STRING | Yes | Free text |

Note: Additional input parameters may exist in the inherited base node definition, which is not available in the provided source.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The image generated from the text prompt. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyCloudMageFlowTurboTextToImageNode/en.md)

***

**Source fingerprint (SHA-256):** `8d867a0c906028597ef52c75f5c9a994fdc00211c7aae410ffca8204943f0c34`


# ComfyCloudZImageTurboNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyCloudZImageTurboNode

This node generates an image from a text prompt using the Z-Image Turbo model, which completes in just 8 steps.

This node generates an image from a text prompt using the Z-Image Turbo model, which completes in just 8 steps. The generation runs remotely on Comfy Cloud GPUs and is billed by how long it runs, making this one of the quickest and cheapest options here for iterating on image ideas. Once the generation finishes, the node downloads the finished image for use in your workflow. This node is part of the Comfy Cloud node set, which is marked BETA: options may be added or removed, and a workflow may be retired.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt describing the image to generate. Accepts multi-line input and is trimmed before submission. Must not be empty after trimming. Default: "" (empty). | STRING | Yes | 1 - 4096 characters |
| `seed` | Random seed used to control generation reproducibility. Changing it produces a different variation. Includes a control-after-generate option. Default: 42. | INT | No | 0 - 18446744073709551615 |
| `aspect_ratio` | Aspect ratio of the generated image. Default: "1:1". | COMBO | No | "1:1"<br />"3:4"<br />"2:3"<br />"3:2"<br />"4:3"<br />"16:9"<br />"9:16"<br />"21:9" |
| `megapixels` | Total pixel budget. 1.0 is about 1024x1024 at a square ratio. Default: 1.0. | FLOAT | No | 0.1 - 16.0<br />(step of 0.1) |

Note: Input values are validated before the generation is submitted. The `prompt` must contain between 1 and 4,096 characters after whitespace is trimmed, `aspect_ratio` must be one of the listed options, and `megapixels` must be entered in increments of 0.1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated image returned as an image tensor, ready for further image processing or saving nodes. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyCloudZImageTurboNode/en.md)

***

**Source fingerprint (SHA-256):** `9c78bf9aca5800212d1c5a8f9581dc6c154a82220cd60a8b55ebe74111d2f542`


# ConditioningSetDefaultAndCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetDefaultAndCombine

This node combines a primary conditioning input with a default conditioning input using a hook-based system.

This node combines a primary conditioning input with a default conditioning input using a hook-based system. It merges the two conditioning sources into a single output, allowing the default conditioning to serve as a fallback or base when the primary conditioning is incomplete.

## Inputs

| Parameter | Description | Data Type | Input Type | Default | Range |
| - | - | - | - | - | - |
| `cond` | The primary conditioning input to be processed and combined | CONDITIONING | Required | - | - |
| `cond_DEFAULT` | The default conditioning data to be combined with the primary conditioning | CONDITIONING | Required | - | - |
| `hooks` | Optional hook configuration that controls how the conditioning data is processed and combined | HOOKS | Optional | - | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The combined conditioning data resulting from merging the primary and default conditioning inputs | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetDefaultAndCombine/en.md)

***

**Source fingerprint (SHA-256):** `5e6c95f454c7e262878cc362c6b199e01abff10f803c81afe6e76a317c30d039`


# ConditioningSetProperties - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetProperties

The ConditioningSetProperties node modifies the properties of conditioning data by adjusting strength, area settings, and applying optional masks, hooks, or timestep ranges.

The ConditioningSetProperties node modifies the properties of conditioning data by adjusting strength, area settings, and applying optional masks, hooks, or timestep ranges. It allows you to control how conditioning influences the generation process by setting specific parameters that affect the application of conditioning data during image generation.

## Inputs

| Parameter | Description | Data Type | Input Type | Default | Range |
| - | - | - | - | - | - |
| `cond_NEW` | The conditioning data to modify | CONDITIONING | Required | - | - |
| `strength` | Controls the intensity of the conditioning effect | FLOAT | Required | 1.0 | 0.0 - 10.0 (step: 0.01) |
| `set_cond_area` | Determines how the conditioning area is applied. Choose "default" for standard behavior or "mask bounds" to restrict to the mask region | STRING | Required | default | \["default", "mask bounds"] |
| `mask` | Optional mask to restrict where conditioning is applied | MASK | Optional | - | - |
| `hooks` | Optional hook functions for custom processing | HOOKS | Optional | - | - |
| `timesteps` | Optional timestep range to limit when conditioning is active | TIMESTEPS\_RANGE | Optional | - | - |

**Note:** When a `mask` is provided, the `set_cond_area` parameter can be set to "mask bounds" to restrict conditioning application to the masked region only. The `hooks` parameter allows for custom processing via hook functions, and `timesteps` limits the conditioning effect to a specific range of timesteps during generation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The modified conditioning data with updated properties | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetProperties/en.md)

***

**Source fingerprint (SHA-256):** `5e3f5348f6df8f2fa1c1d42b883efcab3ee07d933e219f11fa48730aacc168d7`


# ConditioningSetPropertiesAndCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetPropertiesAndCombine

The ConditioningSetPropertiesAndCombine node modifies conditioning data by applying properties from a new conditioning input to an existing conditioning input.

The ConditioningSetPropertiesAndCombine node modifies conditioning data by applying properties from a new conditioning input to an existing conditioning input. It combines the two conditioning sets while controlling the strength of the new conditioning and specifying how the conditioning area should be applied.

## Inputs

| Parameter | Description | Data Type | Input Type | Default | Range |
| - | - | - | - | - | - |
| `cond` | The original conditioning data to be modified | CONDITIONING | Required | - | - |
| `cond_NEW` | The new conditioning data providing properties to apply | CONDITIONING | Required | - | - |
| `strength` | Controls the intensity of the new conditioning properties | FLOAT | Required | 1.0 | 0.0 - 10.0 |
| `set_cond_area` | Determines how the conditioning area is applied | STRING | Required | default | \["default", "mask bounds"] |
| `mask` | Optional mask to define specific areas for conditioning | MASK | Optional | - | - |
| `hooks` | Optional hook functions for custom processing | HOOKS | Optional | - | - |
| `timesteps` | Optional timestep range for controlling when conditioning is applied | TIMESTEPS\_RANGE | Optional | - | - |

**Note:** When `mask` is provided, the `set_cond_area` parameter can use "mask bounds" to constrain the conditioning application to the masked regions.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The combined conditioning data with modified properties | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetPropertiesAndCombine/en.md)

***

**Source fingerprint (SHA-256):** `da57eeae428a103cbad77af063419ed0e85aeaa0b8805c8c197df27613477fa8`


# ConditioningTimestepsRange - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningTimestepsRange

The ConditioningTimestepsRange node creates three distinct timestep ranges for controlling when conditioning effects are applied during the generation process.

The ConditioningTimestepsRange node creates three distinct timestep ranges for controlling when conditioning effects are applied during the generation process. It takes start and end percentage values and divides the entire timestep range (0.0 to 1.0) into three segments: the main range between the specified percentages, the range before the start percentage, and the range after the end percentage.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `start_percent` | The starting percentage of the timestep range (default: 0.0) | FLOAT | Yes | 0.0 - 1.0 |
| `end_percent` | The ending percentage of the timestep range (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `TIMESTEPS_RANGE` | The main timestep range defined by start\_percent and end\_percent | TIMESTEPS\_RANGE |
| `BEFORE_RANGE` | The timestep range from 0.0 to start\_percent | TIMESTEPS\_RANGE |
| `AFTER_RANGE` | The timestep range from end\_percent to 1.0 | TIMESTEPS\_RANGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningTimestepsRange/en.md)

***

**Source fingerprint (SHA-256):** `dee21b5ac80fabdeacf3f4a985550fff795702e02911400ae49a97baae834e5e`


# CreateHookKeyframe - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookKeyframe

The Create Hook Keyframe node allows you to define specific points in a generation process where hook behavior changes.

The Create Hook Keyframe node allows you to define specific points in a generation process where hook behavior changes. It creates keyframes that modify the strength of hooks at particular percentages of the generation progress, and these keyframes can be chained together to create complex scheduling patterns.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `strength_mult` | Multiplier for hook strength at this keyframe (default: 1.0) | FLOAT | Yes | -20.0 to 20.0 |
| `start_percent` | The percentage point in the generation process where this keyframe takes effect (default: 0.0) | FLOAT | Yes | 0.0 to 1.0 |
| `prev_hook_kf` | Optional previous hook keyframe group to add this keyframe to | HOOK\_KEYFRAMES | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `HOOK_KF` | A group of hook keyframes including the newly created keyframe | HOOK\_KEYFRAMES |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookKeyframe/en.md)

***

**Source fingerprint (SHA-256):** `51893311a0623cafcf8c2d8af00e4005ca2fea2df9474e87d7d4b332b38435c3`


# CreateHookKeyframesFromFloats - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookKeyframesFromFloats

This node creates hook keyframes from a list of floating-point strength values, distributing them evenly between specified start and end percentages.

This node creates hook keyframes from a list of floating-point strength values, distributing them evenly between specified start and end percentages. It generates a sequence of keyframes where each strength value is assigned to a specific percentage position in the animation timeline. The node can either create a new keyframe group or add to an existing one, with an option to print the generated keyframes for debugging purposes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `floats_strength` | A single float value or list of float values representing strength values for the keyframes (default: -1) | FLOATS | Yes | -1 to ∞ |
| `start_percent` | The starting percentage position for the first keyframe in the timeline (default: 0.0) | FLOAT | Yes | 0.0 to 1.0 |
| `end_percent` | The ending percentage position for the last keyframe in the timeline (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `print_keyframes` | When enabled, prints the generated keyframe information to the console (default: False) | BOOLEAN | Yes | True/False |
| `prev_hook_kf` | An existing hook keyframe group to add the new keyframes to, or creates a new group if not provided | HOOK\_KEYFRAMES | No | - |

**Note:** The `floats_strength` parameter accepts either a single float value or an iterable list of floats. The keyframes are distributed linearly between `start_percent` and `end_percent` based on the number of strength values provided. The first keyframe is guaranteed to have at least one step to ensure it is applied.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `HOOK_KF` | A hook keyframe group containing the newly created keyframes, either as a new group or appended to the input keyframe group | HOOK\_KEYFRAMES |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookKeyframesFromFloats/en.md)

***

**Source fingerprint (SHA-256):** `566864ec72062d913d95b38b3c53c655d4fdd971a01c4bec54669850b2feddc8`


# CreateHookKeyframesInterpolated - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookKeyframesInterpolated

Creates a sequence of hook keyframes with interpolated strength values between a start and end point.

Creates a sequence of hook keyframes with interpolated strength values between a start and end point. The node generates multiple keyframes that smoothly transition the strength parameter across a specified percentage range of the generation process, using various interpolation methods to control the transition curve.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `strength_start` | The starting strength value for the interpolation sequence (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 |
| `strength_end` | The ending strength value for the interpolation sequence (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 |
| `interpolation` | The interpolation method used to transition between strength values (default: LINEAR) | COMBO | Yes | `LINEAR`<br />`EASE_IN`<br />`EASE_OUT`<br />`EASE_IN_OUT`<br />`EASE_OUT_IN`<br />`SINE`<br />`CUBIC`<br />`QUARTIC`<br />`QUINTIC`<br />`EXPO`<br />`CIRC`<br />`BACK`<br />`BOUNCE`<br />`ELASTIC` |
| `start_percent` | The starting percentage position in the generation process (default: 0.0) | FLOAT | Yes | 0.0 - 1.0 |
| `end_percent` | The ending percentage position in the generation process (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `keyframes_count` | The number of keyframes to generate in the interpolation sequence (default: 5) | INT | Yes | 2 - 100 |
| `print_keyframes` | Whether to print generated keyframe information to the log (default: False) | BOOLEAN | Yes | True/False |
| `prev_hook_kf` | Optional previous hook keyframes group to append to | HOOK\_KEYFRAMES | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `HOOK_KF` | The generated hook keyframes group containing the interpolated sequence | HOOK\_KEYFRAMES |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookKeyframesInterpolated/en.md)

***

**Source fingerprint (SHA-256):** `f90c96745ca1f02bbb02e08d2d82be1bbb1f3c80ac5d53a4c6bc07a0e2b8d76f`


# CreateHookLora - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookLora

The Create Hook LoRA node generates hook objects for applying LoRA (Low-Rank Adaptation) modifications to models.

The Create Hook LoRA node generates hook objects for applying LoRA (Low-Rank Adaptation) modifications to models. It loads a specified LoRA file and creates hooks that can adjust model and CLIP strengths, then combines these hooks with any existing hooks passed to it. The node efficiently manages LoRA loading by caching previously loaded LoRA files to avoid redundant operations.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `lora_name` | The name of the LoRA file to load from the loras directory | STRING | Yes | Multiple options available |
| `strength_model` | The strength multiplier for model adjustments (default: 1.0) | FLOAT | Yes | -20.0 to 20.0 |
| `strength_clip` | The strength multiplier for CLIP adjustments (default: 1.0) | FLOAT | Yes | -20.0 to 20.0 |
| `prev_hooks` | Optional existing hook group to combine with the new LoRA hooks | HOOKS | No | N/A |

**Parameter Constraints:**

* If both `strength_model` and `strength_clip` are set to 0, the node will skip creating new LoRA hooks and return the existing hooks unchanged
* The node caches the last loaded LoRA file to optimize performance when the same LoRA is used repeatedly

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `HOOKS` | A hook group containing the combined LoRA hooks and any previous hooks | HOOKS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookLora/en.md)

***

**Source fingerprint (SHA-256):** `42d5d776bfc9b239191952e2bce23513d183f904fc3c15039469381a547486f8`


# CreateHookLoraModelOnly - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookLoraModelOnly

This node creates a LoRA (Low-Rank Adaptation) hook that applies only to the model component, leaving the CLIP component completely unchanged.

This node creates a LoRA (Low-Rank Adaptation) hook that applies only to the model component, leaving the CLIP component completely unchanged. It loads a LoRA file and applies it with a specified strength to the model while setting the CLIP strength to zero. The node can be chained with previous hooks to build complex modification pipelines.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `lora_name` | The name of the LoRA file to load from the loras folder | STRING | Yes | Multiple options available |
| `strength_model` | The strength multiplier for applying the LoRA to the model component (default: 1.0) | FLOAT | Yes | -20.0 to 20.0 |
| `prev_hooks` | Optional previous hooks to chain with this hook | HOOKS | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `hooks` | The created LoRA hook that can be applied to model processing | HOOKS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookLoraModelOnly/en.md)

***

**Source fingerprint (SHA-256):** `10adbdfc2e37fcf317e93130f87d9a7038d00b091cb6d1b45f4658c81632ef80`


# CreateHookModelAsLora - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookModelAsLora

This node creates a hook model as a LoRA (Low-Rank Adaptation) by loading checkpoint weights and applying strength adjustments to both the model and CLIP components.

This node creates a hook model as a LoRA (Low-Rank Adaptation) by loading checkpoint weights and applying strength adjustments to both the model and CLIP components. It allows you to apply LoRA-style modifications to existing models through a hook-based approach, enabling fine-tuning and adaptation without permanent model changes. The node can combine with previous hooks and caches loaded weights for efficiency.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `ckpt_name` | The checkpoint file to load weights from (select from available checkpoints) | STRING | Yes | Multiple options available |
| `strength_model` | The strength multiplier applied to the model weights (default: 1.0) | FLOAT | Yes | -20.0 to 20.0 |
| `strength_clip` | The strength multiplier applied to the CLIP weights (default: 1.0) | FLOAT | Yes | -20.0 to 20.0 |
| `prev_hooks` | Optional previous hooks to combine with the newly created LoRA hooks | HOOKS | No | - |

**Parameter Constraints:**

* The `ckpt_name` parameter loads checkpoints from the available checkpoints folder
* Both strength parameters accept values from -20.0 to 20.0 with 0.01 step increments
* When `prev_hooks` is not provided, the node creates a new hook group
* The node caches loaded weights to avoid reloading the same checkpoint multiple times

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `HOOKS` | The created LoRA hooks, combined with any previous hooks if provided | HOOKS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookModelAsLora/en.md)

***

**Source fingerprint (SHA-256):** `8c0dd6b2e8e99e1d7dbc864aa802c0713842fb0d4ee018ea5cbedfb7896a770d`


# CreateHookModelAsLoraModelOnly - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookModelAsLoraModelOnly

This node creates a hook that applies a LoRA (Low-Rank Adaptation) model to modify only the model component of a neural network.

This node creates a hook that applies a LoRA (Low-Rank Adaptation) model to modify only the model component of a neural network. It loads a checkpoint file and applies it with a specified strength to the model while leaving the CLIP component unchanged. This is an experimental node that extends the functionality of the base CreateHookModelAsLora class.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `ckpt_name` | The checkpoint file to load as a LoRA model. Available options depend on the checkpoints folder contents. | STRING | Yes | Multiple options available |
| `strength_model` | The strength multiplier for applying the LoRA to the model component (default: 1.0) | FLOAT | Yes | -20.0 to 20.0 |
| `prev_hooks` | Optional previous hooks to chain with this hook | HOOKS | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `hooks` | The created hook group containing the LoRA model modification | HOOKS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookModelAsLoraModelOnly/en.md)

***

**Source fingerprint (SHA-256):** `adbeaede65aa89d48c59225ca1c8edc4c9394a364f93a00dae4a83a2270f093b`


# DeprecatedCheckpointLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DeprecatedCheckpointLoader

The CheckpointLoader node is designed for advanced loading operations, specifically to load model checkpoints along with their configurations.

The CheckpointLoader node is designed for advanced loading operations, specifically to load model checkpoints along with their configurations. It facilitates the retrieval of model components necessary for initializing and running generative models, including configurations and checkpoints from specified directories.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `config_name` | Specifies the name of the configuration file to be used. This is crucial for determining the model's parameters and settings, affecting the model's behavior and performance. | COMBO\[STRING] |
| `ckpt_name` | Indicates the name of the checkpoint file to be loaded. This directly influences the state of the model being initialized, impacting its initial weights and biases. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | Represents the primary model loaded from the checkpoint, ready for further operations or inference. | MODEL |
| `clip` | Provides the CLIP model component, if available and requested, loaded from the checkpoint. | CLIP |
| `vae` | Delivers the VAE model component, if available and requested, loaded from the checkpoint. | VAE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DeprecatedCheckpointLoader/en.md)


# DeprecatedDiffusersLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DeprecatedDiffusersLoader

The DiffusersLoader node is designed for loading models from the diffusers library, specifically handling the loading of UNet, CLIP, and VAE models based on provided model paths.

The DiffusersLoader node is designed for loading models from the diffusers library, specifically handling the loading of UNet, CLIP, and VAE models based on provided model paths. It facilitates the integration of these models into the ComfyUI framework, enabling advanced functionalities such as text-to-image generation, image manipulation, and more.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model_path` | Specifies the path to the model to be loaded. This path is crucial as it determines which model will be utilized for subsequent operations, affecting the output and capabilities of the node. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The loaded UNet model, which is part of the output tuple. This model is essential for image synthesis and manipulation tasks within the ComfyUI framework. | MODEL |
| `clip` | The loaded CLIP model, included in the output tuple if requested. This model enables advanced text and image understanding and manipulation capabilities. | CLIP |
| `vae` | The loaded VAE model, included in the output tuple if requested. This model is crucial for tasks involving latent space manipulation and image generation. | VAE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DeprecatedDiffusersLoader/en.md)


# EasyCache - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EasyCache

The EasyCache node adds a native caching system to a diffusion model that speeds up sampling by reusing results from previously computed steps instead of recomputing every step.

The EasyCache node adds a native caching system to a diffusion model that speeds up sampling by reusing results from previously computed steps instead of recomputing every step. It activates only between a configurable start and end point of the sampling process and skips steps when the estimated output change stays below a user-defined threshold. This is an experimental node intended for advanced debugging use.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to add EasyCache to. | MODEL | Yes | - |
| `reuse_threshold` | The threshold for reusing cached steps (default: 0.2). | FLOAT | Yes | 0.0 - 3.0 |
| `start_percent` | The relative sampling step to begin use of EasyCache (default: 0.15). | FLOAT | Yes | 0.0 - 1.0 |
| `end_percent` | The relative sampling step to end use of EasyCache (default: 0.95). | FLOAT | Yes | 0.0 - 1.0 |
| `verbose` | Whether to log verbose information (default: False). | BOOLEAN | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The model with EasyCache functionality added. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EasyCache/en.md)

***

**Source fingerprint (SHA-256):** `3e10ac65f8df58ce8649fdf599e62bfb86f2d4166840bed5622c0aa2c419cd38`


# FluxProCannyNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProCannyNode

Generate image using a control image (canny).

Generate image using a control image (canny). This node takes a control image and generates a new image based on the provided prompt while following the edge structure detected in the control image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `control_image` | The input image used for canny edge detection control | IMAGE | Yes | - |
| `prompt` | Prompt for the image generation (default: empty string) | STRING | No | - |
| `prompt_upsampling` | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: False) | BOOLEAN | No | - |
| `canny_low_threshold` | Low threshold for Canny edge detection; ignored if `skip_preprocessing` is True (default: 0.1) | FLOAT | No | 0.01 - 0.99 |
| `canny_high_threshold` | High threshold for Canny edge detection; ignored if `skip_preprocessing` is True (default: 0.4) | FLOAT | No | 0.01 - 0.99 |
| `skip_preprocessing` | Whether to skip preprocessing; set to True if `control_image` already is canny-fied, False if it is a raw image. (default: False) | BOOLEAN | No | - |
| `guidance` | Guidance strength for the image generation process (default: 30) | FLOAT | No | 1 - 100 |
| `steps` | Number of steps for the image generation process (default: 50) | INT | No | 15 - 50 |
| `seed` | The random seed used for creating the noise. (default: 0) | INT | No | 0 - 18446744073709551615 |

**Note:** When `skip_preprocessing` is set to True, the `canny_low_threshold` and `canny_high_threshold` parameters are ignored since the control image is assumed to already be processed as a canny edge image. The `control_image` is then used directly as the preprocessed image.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output_image` | The generated image based on the control image and prompt | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProCannyNode/en.md)

***

**Source fingerprint (SHA-256):** `dedf55a2b2c183519d7f5be0d9a96abbe40716a247f574fc0d50f10f715949a7`


# FluxProDepthNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProDepthNode

This node generates images using a depth control image as guidance.

This node generates images using a depth control image as guidance. It takes a control image and a text prompt, then creates a new image that follows both the depth information from the control image and the description in the prompt. The node connects to an external API to perform the image generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `control_image` | The depth control image used to guide the image generation | IMAGE | Yes | - |
| `prompt` | Prompt for the image generation (default: empty string) | STRING | No | - |
| `prompt_upsampling` | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: False) | BOOLEAN | No | - |
| `skip_preprocessing` | Whether to skip preprocessing; set to True if `control_image` already is depth-ified, False if it is a raw image. (default: False) | BOOLEAN | No | - |
| `guidance` | Guidance strength for the image generation process (default: 15) | FLOAT | No | 1-100 |
| `steps` | Number of steps for the image generation process (default: 50) | INT | No | 15-50 |
| `seed` | The random seed used for creating the noise. (default: 0) | INT | No | 0-18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output_image` | The generated image based on the depth control image and prompt | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProDepthNode/en.md)

***

**Source fingerprint (SHA-256):** `34b80d7d63158b7dc4ad02da6b3a573b713d77efd0955d3477409f776f964462`


# FluxProImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProImageNode

Generates images synchronously based on prompt and resolution.

Generates images synchronously based on prompt and resolution. This node creates images using the Flux 1.1 Pro model by sending requests to an API endpoint and waiting for the complete response before returning the generated image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the image generation (default: empty string) | STRING | Yes | - |
| `prompt_upsampling` | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: False) | BOOLEAN | Yes | - |
| `width` | Image width in pixels (default: 1024, step: 32) | INT | Yes | 256-1440 |
| `height` | Image height in pixels (default: 768, step: 32) | INT | Yes | 256-1440 |
| `seed` | The random seed used for creating the noise. (default: 0) | INT | Yes | 0-18446744073709551615 |
| `image_prompt` | Optional reference image to guide the generation | IMAGE | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated image returned from the API | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProImageNode/en.md)

***

**Source fingerprint (SHA-256):** `89316d84f364854541157b5b60bae3d4e25024bd4af61a47a1748c6671b463c1`


# IdeogramV1 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/IdeogramV1

The IdeogramV1 node generates images using the Ideogram V1 model through an API.

The IdeogramV1 node generates images using the Ideogram V1 model through an API. It takes text prompts and various generation settings to create one or more images based on your input. The node supports different aspect ratios and generation modes to customize the output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the image generation (default: empty) | STRING | Yes | - |
| `turbo` | Whether to use turbo mode (faster generation, potentially lower quality) (default: False) | BOOLEAN | Yes | - |
| `aspect_ratio` | The aspect ratio for image generation (default: "1:1") | COMBO | No | "1:1"<br />"4:3"<br />"3:4"<br />"16:9"<br />"9:16"<br />"2:1"<br />"1:2"<br />"3:2"<br />"2:3"<br />"4:5"<br />"5:4" |
| `magic_prompt_option` | Determine if MagicPrompt should be used in generation (default: "AUTO") | COMBO | No | "AUTO"<br />"ON"<br />"OFF" |
| `seed` | Random seed value for generation (default: 0) | INT | No | 0-2147483647 |
| `negative_prompt` | Description of what to exclude from the image (default: empty) | STRING | No | - |
| `num_images` | Number of images to generate (default: 1) | INT | No | 1-8 |

**Note:** The `num_images` parameter has a maximum limit of 8 images per generation request.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated image(s) from the Ideogram V1 model | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/IdeogramV1/en.md)

***

**Source fingerprint (SHA-256):** `c9b336054cf5d66228aeccab615985d2e9c9bdf7dce5d607212fed8a35c2c793`


# IdeogramV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/IdeogramV2

The Ideogram V2 node generates images using the Ideogram V2 AI model.

The Ideogram V2 node generates images using the Ideogram V2 AI model. It takes text prompts and various generation settings to create images through an API service. The node supports different aspect ratios, resolutions, and style options to customize the output images.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the image generation (default: empty string) | STRING | Yes | - |
| `turbo` | Whether to use turbo mode (faster generation, potentially lower quality) (default: False) | BOOLEAN | No | - |
| `aspect_ratio` | The aspect ratio for image generation. Ignored if resolution is not set to AUTO. (default: "1:1") | COMBO | No | "1:1"<br />"4:3"<br />"3:4"<br />"16:9"<br />"9:16"<br />"2:1"<br />"1:2"<br />"3:2"<br />"2:3"<br />"4:5"<br />"5:4" |
| `resolution` | The resolution for image generation. If not set to AUTO, this overrides the aspect\_ratio setting. (default: "Auto") | COMBO | No | "Auto"<br />"512 x 1536"<br />"576 x 1408"<br />"576 x 1472"<br />"576 x 1536"<br />"640 x 1024"<br />"640 x 1344"<br />"640 x 1408"<br />"640 x 1472"<br />"640 x 1536"<br />"704 x 1152"<br />"704 x 1216"<br />"704 x 1280"<br />"704 x 1344"<br />"704 x 1408"<br />"704 x 1472"<br />"720 x 1280"<br />"736 x 1312"<br />"768 x 1024"<br />"768 x 1088"<br />"768 x 1152"<br />"768 x 1216"<br />"768 x 1232"<br />"768 x 1280"<br />"768 x 1344"<br />"832 x 960"<br />"832 x 1024"<br />"832 x 1088"<br />"832 x 1152"<br />"832 x 1216"<br />"832 x 1248"<br />"864 x 1152"<br />"896 x 960"<br />"896 x 1024"<br />"896 x 1088"<br />"896 x 1120"<br />"896 x 1152"<br />"960 x 832"<br />"960 x 896"<br />"960 x 1024"<br />"960 x 1088"<br />"1024 x 640"<br />"1024 x 768"<br />"1024 x 832"<br />"1024 x 896"<br />"1024 x 960"<br />"1024 x 1024"<br />"1088 x 768"<br />"1088 x 832"<br />"1088 x 896"<br />"1088 x 960"<br />"1120 x 896"<br />"1152 x 704"<br />"1152 x 768"<br />"1152 x 832"<br />"1152 x 864"<br />"1152 x 896"<br />"1216 x 704"<br />"1216 x 768"<br />"1216 x 832"<br />"1232 x 768"<br />"1248 x 832"<br />"1280 x 704"<br />"1280 x 720"<br />"1280 x 768"<br />"1280 x 800"<br />"1312 x 736"<br />"1344 x 640"<br />"1344 x 704"<br />"1344 x 768"<br />"1408 x 576"<br />"1408 x 640"<br />"1408 x 704"<br />"1472 x 576"<br />"1472 x 640"<br />"1472 x 704"<br />"1536 x 512"<br />"1536 x 576"<br />"1536 x 640" |
| `magic_prompt_option` | Determine if MagicPrompt should be used in generation (default: "AUTO") | COMBO | No | "AUTO"<br />"ON"<br />"OFF" |
| `seed` | Random seed for generation (default: 0) | INT | No | 0-2147483647 |
| `style_type` | Style type for generation (V2 only) (default: "NONE") | COMBO | No | "AUTO"<br />"GENERAL"<br />"REALISTIC"<br />"DESIGN"<br />"RENDER\_3D"<br />"ANIME" |
| `negative_prompt` | Description of what to exclude from the image (default: empty string) | STRING | No | - |
| `num_images` | Number of images to generate (default: 1) | INT | No | 1-8 |

**Note:** When `resolution` is not set to "Auto", it overrides the `aspect_ratio` setting. The `num_images` parameter has a maximum limit of 8 images per generation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated image(s) from the Ideogram V2 model | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/IdeogramV2/en.md)

***

**Source fingerprint (SHA-256):** `a034a57996ac0b3902cab36096ac6b8401bb544faa00b8ed213bf752fdd423e2`


# KlingCameraControlI2VNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingCameraControlI2VNode

The Kling Image to Video Camera Control Node transforms still images into cinematic videos with professional camera movements.

The Kling Image to Video Camera Control Node transforms still images into cinematic videos with professional camera movements. This specialized image-to-video node allows you to control virtual camera actions including zoom, rotation, pan, tilt, and first-person view while maintaining focus on your original image. Camera control is currently only supported in pro mode with the kling-v1-5 model at 5-second duration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `start_frame` | Reference Image - URL or Base64 encoded string, cannot exceed 10MB, resolution not less than 300x300px, aspect ratio between 1:2.5 and 2.5:1. Base64 should not include data:image prefix. | IMAGE | Yes | - |
| `prompt` | Positive text prompt describing the desired video content. Maximum length is 500 characters. | STRING | Yes | - |
| `negative_prompt` | Negative text prompt describing what to avoid in the generated video. Maximum length is 500 characters. | STRING | Yes | - |
| `cfg_scale` | Controls the strength of text guidance. Higher values make the output more closely follow the prompt (default: 0.75) | FLOAT | No | 0.0 to 1.0 |
| `aspect_ratio` | The aspect ratio of the generated video (default: "16:9") | COMBO | No | `"16:9"`<br />`"9:16"`<br />`"1:1"` |
| `camera_control` | Can be created using the Kling Camera Controls node. Controls the camera movement and motion during the video generation. | CAMERA\_CONTROL | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video output | VIDEO |
| `video_id` | Unique identifier for the generated video | STRING |
| `duration` | Duration of the generated video | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingCameraControlI2VNode/en.md)

***

**Source fingerprint (SHA-256):** `65b1e4a46c2de1558c8f27ebe031f1736e84d532908170c91fb70121c350347e`


# KlingCameraControlT2VNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingCameraControlT2VNode

Kling Text to Video Camera Control Node transforms text into cinematic videos with professional camera movements that simulate real-world cinematography.

Kling Text to Video Camera Control Node transforms text into cinematic videos with professional camera movements that simulate real-world cinematography. This node supports controlling virtual camera actions including zoom, rotation, pan, tilt, and first-person view while maintaining focus on your original text. The duration, mode, and model name are hard-coded because camera control is only supported in pro mode with the kling-v1-5 model at 5-second duration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Positive text prompt | STRING | Yes | - |
| `negative_prompt` | Negative text prompt | STRING | Yes | - |
| `cfg_scale` | Controls how closely the output follows the prompt (default: 0.75) | FLOAT | No | 0.0-1.0 |
| `aspect_ratio` | The aspect ratio for the generated video (default: "16:9") | COMBO | No | "16:9"<br />"9:16"<br />"1:1"<br />"21:9"<br />"3:4"<br />"4:3" |
| `camera_control` | Can be created using the Kling Camera Controls node. Controls the camera movement and motion during the video generation. | CAMERA\_CONTROL | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video with camera control effects | VIDEO |
| `video_id` | The unique identifier for the generated video | STRING |
| `duration` | The duration of the generated video | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingCameraControlT2VNode/en.md)

***

**Source fingerprint (SHA-256):** `7975d97c4f9242a9ae3c17be03696d174a2495bd53fb9fc4405f86c44167fa21`


# KlingCameraControls - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingCameraControls

The Kling Camera Controls node allows you to configure various camera movement and rotation parameters for creating motion control effects in video generation.

The Kling Camera Controls node allows you to configure various camera movement and rotation parameters for creating motion control effects in video generation. It provides controls for camera positioning, rotation, and zoom to simulate different camera movements.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `camera_control_type` | Specifies the type of camera control configuration to use | COMBO | Yes | `"simple"`<br />`"advanced"` |
| `horizontal_movement` | Controls camera's movement along horizontal axis (x-axis). Negative indicates left, positive indicates right (default: 0.0) | FLOAT | No | -10.0 to 10.0 |
| `vertical_movement` | Controls camera's movement along vertical axis (y-axis). Negative indicates downward, positive indicates upward (default: 0.0) | FLOAT | No | -10.0 to 10.0 |
| `pan` | Controls camera's rotation in vertical plane (x-axis). Negative indicates downward rotation, positive indicates upward rotation (default: 0.5) | FLOAT | No | -10.0 to 10.0 |
| `tilt` | Controls camera's rotation in horizontal plane (y-axis). Negative indicates left rotation, positive indicates right rotation (default: 0.0) | FLOAT | No | -10.0 to 10.0 |
| `roll` | Controls camera's rolling amount (z-axis). Negative indicates counterclockwise, positive indicates clockwise (default: 0.0) | FLOAT | No | -10.0 to 10.0 |
| `zoom` | Controls change in camera's focal length. Negative indicates narrower field of view, positive indicates wider field of view (default: 0.0) | FLOAT | No | -10.0 to 10.0 |

**Note:** At least one of the camera control parameters (`horizontal_movement`, `vertical_movement`, `pan`, `tilt`, `roll`, or `zoom`) must have a non-zero value for the configuration to be valid.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `camera_control` | Returns the configured camera control settings for use in video generation | CAMERA\_CONTROL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingCameraControls/en.md)

***

**Source fingerprint (SHA-256):** `dbba1083b662bb2563c77dec857e4f3123e4e53d58a1d51f2646288af28ebba0`


# KlingDualCharacterVideoEffectNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingDualCharacterVideoEffectNode

The Kling Dual Character Video Effect Node creates videos with special effects based on the selected scene.

The Kling Dual Character Video Effect Node creates videos with special effects based on the selected scene. It takes two images and positions the first image on the left side and the second image on the right side of the composite video. Different visual effects are applied depending on the chosen effect scene.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image_left` | Left side image | IMAGE | Yes | - |
| `image_right` | Right side image | IMAGE | Yes | - |
| `effect_scene` | The type of special effect scene to apply to the video generation | COMBO | Yes | `"chat"`<br />`"dance"`<br />`"hug"`<br />`"kill"`<br />`"kiss"`<br />`"pat"`<br />`"punch"`<br />`"shrug"`<br />`"slap"`<br />`"tickle"` |
| `model_name` | The model to use for character effects (default: "kling-v1") | COMBO | No | `"kling-v1"`<br />`"kling-v1-5"`<br />`"kling-v1-6"` |
| `mode` | The video generation mode (default: "std") | COMBO | No | `"std"`<br />`"pro"` |
| `duration` | The duration of the generated video in seconds | COMBO | Yes | `"5"`<br />`"10"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video with dual character effects | VIDEO |
| `duration` | The duration information of the generated video | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingDualCharacterVideoEffectNode/en.md)

***

**Source fingerprint (SHA-256):** `314fc23940225eb4559ecc74f333bb23e9a4939bbb884c93341f4d6f6e7b64df`


# KlingSingleImageVideoEffectNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingSingleImageVideoEffectNode

The Kling Single Image Video Effect Node creates videos with different special effects based on a single reference image.

The Kling Single Image Video Effect Node creates videos with different special effects based on a single reference image. It applies various visual effects and scenes to transform static images into dynamic video content. The node supports different effect scenes, model options, and video durations to achieve the desired visual outcome.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Reference Image. URL or Base64 encoded string (without data:image prefix). File size cannot exceed 10MB, resolution not less than 300x300px, aspect ratio between 1:2.5 to 2.5:1 | IMAGE | Yes | - |
| `effect_scene` | The type of special effect scene to apply to the video generation. Some effects may have different pricing. | COMBO | Yes | `"dizzydizzy"`<br />`"bloombloom"`<br />`"neon"`<br />`"cartoon"`<br />`"sketch"`<br />`"oil"`<br />`"watercolor"`<br />`"3d"` |
| `model_name` | The specific model version to use for generating the video effect. | COMBO | Yes | `"kling-v1-5"`<br />`"kling-v1-6"` |
| `duration` | The length of the generated video in seconds. | COMBO | Yes | `"5"`<br />`"10"` |

**Note:** The `effect_scene` parameter affects the pricing of the node. Effects `dizzydizzy` and `bloombloom` cost $0.49 USD per generation, while all other effects cost $0.28 USD per generation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video with applied effects | VIDEO |
| `video_id` | The unique identifier for the generated video | STRING |
| `duration` | The duration of the generated video | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingSingleImageVideoEffectNode/en.md)

***

**Source fingerprint (SHA-256):** `fb4a8b044daa99154a58d6926ff746bd2397b71ea32f1fafc851589f163ab51a`


# KlingVideoExtendNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingVideoExtendNode

The Kling Video Extend Node allows you to extend videos created by other Kling nodes.

The Kling Video Extend Node allows you to extend videos created by other Kling nodes. It takes an existing video identified by its video ID and generates additional content based on your text prompts. The node works by sending your extension request to the Kling API and returning the extended video along with its new ID and duration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Positive text prompt for guiding the video extension | STRING | No | - |
| `negative_prompt` | Negative text prompt for elements to avoid in the extended video | STRING | No | - |
| `cfg_scale` | Controls the strength of prompt guidance (default: 0.5) | FLOAT | No | 0.0 - 1.0 |
| `video_id` | The ID of the video to be extended. Supports videos generated by text-to-video, image-to-video, and previous video extension operations. Cannot exceed 3 minutes total duration after extension. | STRING | Yes | - |

**Note:** The `video_id` must reference a video created by other Kling nodes, and the total duration after extension cannot exceed 3 minutes. The positive prompt must not be empty and both prompts must be under 2500 characters.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The extended video generated by the Kling API | VIDEO |
| `video_id` | The unique identifier for the extended video | STRING |
| `duration` | The duration of the extended video | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingVideoExtendNode/en.md)

***

**Source fingerprint (SHA-256):** `56674dee721a1784138852f5fd1cce137acf0b5e09bd9ee17353dde6fb251b5e`


# KlingVirtualTryOnNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingVirtualTryOnNode

Kling Virtual Try On Node.

Kling Virtual Try On Node. Input a human image and a cloth image to try on the cloth on the human. You can merge multiple clothing item pictures into one image with a white background.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `human_image` | The human image to try clothes on | IMAGE | Yes | - |
| `cloth_image` | The clothing image to try on the human | IMAGE | Yes | - |
| `model_name` | The virtual try-on model to use (default: "kolors-virtual-try-on-v1") | STRING | Yes | `"kolors-virtual-try-on-v1"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The resulting image showing the human with the clothing item tried on | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingVirtualTryOnNode/en.md)

***

**Source fingerprint (SHA-256):** `bf256d8732f4c6acf65838812fc322e48ef886257bbb48c02b0cc6ab5d78dce5`


# LTXVModalityGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVModalityGuidance

This node applies cross-modal (audio-video) guidance to an LTXV-AV model.

This node applies cross-modal (audio-video) guidance to an LTXV-AV model. During sampling, it runs one extra forward pass per step with the audio-to-video and video-to-audio cross-attention connections disabled, then pushes the result toward the coupled prediction to strengthen audio-visual synchronization, such as lip-sync. The reference default for `modality_scale` is 3.0; setting it to 1.0 disables the extra pass, and it stacks with the dual-CFG guider and STG.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The base model to which modality guidance will be applied. It is cloned internally, leaving the original model unchanged. | MODEL | Yes | - |
| `modality_scale` | Strength of the audio-video coupling guidance. Default is 3.0. Set to 1.0 to disable the extra forward pass. | FLOAT | Yes | 1.0 to 100.0 (default: 3.0) |
| `start_percent` | The point in the sampling process, as a percentage from 0.0 to 1.0, at which modality guidance begins. This is an advanced parameter. Default is 0.0. | FLOAT | Yes | 0.0 to 1.0 (default: 0.0) |
| `end_percent` | The point in the sampling process, as a percentage from 0.0 to 1.0, at which modality guidance ends. This is an advanced parameter. Default is 1.0. | FLOAT | Yes | 0.0 to 1.0 (default: 1.0) |

Guidance is applied only for sampling steps whose sigma values fall within the range defined by `start_percent` and `end_percent`. Outside this range, the node returns the denoised result unchanged. A `modality_scale` of 1.0 also disables the extra forward pass entirely.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The cloned model with a post-CFG guidance function attached. This modified model applies modality guidance during sampling. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVModalityGuidance/en.md)

***

**Source fingerprint (SHA-256):** `038be607c42e626a8a8f5fe336ee466d0847d43835edb71e20ff38f668069cfb`


# LTXVSpatioTemporalGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVSpatioTemporalGuidance

This node improves the spatial detail and motion coherence of LTXV video generation by running one extra pass at each sampling step.

This node improves the spatial detail and motion coherence of LTXV video generation by running one extra pass at each sampling step. During this pass, the self-attention of the selected transformer blocks is degraded to a value-passthrough, and the generation is guided away from that degraded result.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The base model to apply spatio-temporal guidance to. The model is cloned and a post-CFG guidance function is attached to the clone. | MODEL | Yes | — |
| `scale` | The strength of the guidance applied to the denoised result. When set to 0, the guidance has no effect. (default: 1.0) | FLOAT | Yes | 0.0 to 100.0 (step 0.01) |
| `blocks` | Comma-separated transformer block indices to perturb. Only numeric values are used; any other characters are ignored. (default: "29") | STRING | Yes | — |
| `start_percent` | The fraction of the sampling process at which guidance begins. This is an advanced parameter. (default: 0.0) | FLOAT | Yes | 0.0 to 1.0 (step 0.001) |
| `end_percent` | The fraction of the sampling process at which guidance ends. This is an advanced parameter. (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step 0.001) |

Note: Guidance is only applied during the sampling interval between `start_percent` and `end_percent`. Outside that interval, the original denoised result is returned unchanged. If `scale` is 0 or `blocks` contains no numeric values, the guided pass has no effect on the sampling process.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The cloned model with the spatio-temporal guidance function attached. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVSpatioTemporalGuidance/en.md)

***

**Source fingerprint (SHA-256):** `0e14137b3bf416d36005b6b4b6db46495b1523f88b2bf574e2dc582175422a48`


# LazyCache - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LazyCache

LazyCache is an experimental, homebrew version of EasyCache that adds caching during sampling to reduce computation.

LazyCache is an experimental, homebrew version of EasyCache that adds caching during sampling to reduce computation. It is designed for universal compatibility with models in ComfyUI, though it generally performs worse than EasyCache and may work better only in rare cases.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to add LazyCache to. | MODEL | Yes | - |
| `reuse_threshold` | The threshold for reusing cached steps. Default: 0.2. | FLOAT | Yes | 0.0 - 3.0 (step 0.01) |
| `start_percent` | The relative sampling step to begin use of LazyCache. Default: 0.15. | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |
| `end_percent` | The relative sampling step to end use of LazyCache. Default: 0.95. | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |
| `verbose` | Whether to log verbose information. Default: False. | BOOLEAN | Yes | - |

Note: `reuse_threshold`, `start_percent`, `end_percent`, and `verbose` are marked as advanced inputs.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The model with LazyCache functionality added. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LazyCache/en.md)

***

**Source fingerprint (SHA-256):** `78f9c13473567e068fc2be35b2f8f5aa459d43d3f13300a6ea858af98d3e2a44`


# LoopIteration - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoopIteration

This node provides iteration metadata for loop-style workflows.

This node provides iteration metadata for loop-style workflows. It receives list-based inputs and passes through the first element of each list, so a loop can track the current index, whether it is the first or last step, the current list item, and any running iteration value. Cache behavior is controlled by the `reuse_cache` flag. This node is marked as developer-only.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `iteration_index` | The index of the current iteration, supplied as a list. The first element is passed through to the output. | INT | Yes | - |
| `is_first` | Indicates whether the current iteration is the first one, supplied as a list. The first element is passed through to the output. | BOOLEAN | Yes | - |
| `is_last` | Indicates whether the current iteration is the last one, supplied as a list. The first element is passed through to the output. | BOOLEAN | Yes | - |
| `list_item` | The item taken from the list for this iteration. Optional; the first element is passed through to the output when provided, otherwise None is returned. | ANY | No | - |
| `current_iteration_value` | The value carried by the current iteration. Optional; when provided, the full value is passed through to the output, otherwise None is returned. | ANY | No | - |
| `reuse_cache` | Controls whether the result may be reused from cache. When enabled, the node keeps a stable fingerprint so cached results can be reused. When disabled, a non-matching fingerprint is produced so the node runs again on each iteration. | BOOLEAN | Yes | - |

Note: This node is list-input enabled, meaning each input is expected to arrive as a list and the node outputs only the first element of each list (except `current_iteration_value`, which is passed through as a list). It also accepts additional inputs beyond those listed here.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `iteration_index` | The index of the current iteration. | INT |
| `is_first` | Whether the current iteration is the first one. | BOOLEAN |
| `is_last` | Whether the current iteration is the last one. | BOOLEAN |
| `list_item` | The item taken from the list for this iteration, or None when no item was provided. | ANY |
| `current_iteration_value` | The value carried by the current iteration, or None when no value was provided. This output is returned as a list. | ANY |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoopIteration/en.md)

***

**Source fingerprint (SHA-256):** `c7072f22bd382f567792d2ea7a30312c64d33c213551f8983c25cd7b95adc4fb`


# LoopProgress - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoopProgress

LoopProgress is a development-only helper node that reports the progress of a loop to the ComfyUI server interface.

LoopProgress is a development-only helper node that reports the progress of a loop to the ComfyUI server interface. On each execution it sends the text "Iteration X / Y" to the client and returns the current iteration position unchanged, which allows it to sit inline inside a loop without altering the data flow.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `start_id` | Identifier of the prompt/loop instance the progress message belongs to. The first item of the supplied list is used to route the progress text to the correct running execution. | STRING | Yes | - |
| `position` | The current iteration position (index). The first item of the supplied list is used in the progress message and is also returned as the output. | INT | Yes | - |
| `total` | The total number of iterations. Used together with `position` to build the "Iteration X / Y" progress message. | INT | Yes | - |

Note: this node is declared with list inputs (`is_input_list=True`) and accepts all inputs, so each connected value is treated as a list and only its first element is read. The node always runs (its input fingerprint is fixed), so it re-executes on every loop pass.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `position` | The current iteration position, passed through unchanged from the `position` input. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoopProgress/en.md)

***

**Source fingerprint (SHA-256):** `505ba814b93533679516b4f4239f5eee0dbac125d7ea16746c6cdbb7a68f803d`


# LoopResult - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoopResult

LoopResult is a developer-only output node that marks the closing point of a loop block.

LoopResult is a developer-only output node that marks the closing point of a loop block. It collects the values that are passed into it in order (named `output0`, `output1`, and so on) and releases the external execution block identified by a close ID. Because input fingerprinting always returns NaN, the node is treated as always changed and is re-executed every run.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `close_id` | Identifier of the loop block to close; only the first value of the list is used | STRING | Yes | - |
| `output0`, `output1`, ... | Values collected from the loop block. The node accepts any additional inputs and gathers them in sequential order starting at `output0`, stopping at the first missing index | Any type | No | - |

Note: This node accepts all inputs (`accept_all_inputs`). Any input beyond `close_id` is treated as a collected loop value and must be named `output0`, `output1`, `output2`, etc., without gaps, for it to be included in the result.

## Outputs

This node does not return any outputs. It only releases the external execution block associated with `close_id`.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoopResult/en.md)

***

**Source fingerprint (SHA-256):** `637f8a39b0e99e8d4453cfc482463bd14d909b710264021ac2c27fdcd68b6063`


# LtxvApiImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LtxvApiImageToVideo

The LTXV Image To Video node generates a professional-quality video from a single starting image.

The LTXV Image To Video node generates a professional-quality video from a single starting image. It uses an external API to create a video sequence based on your text prompt, allowing you to customize the duration, resolution, and frame rate.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | First frame to be used for the video. | IMAGE | Yes | - |
| `model` | The AI model to use for video generation. The "Pro" model is optimized for quality, while the "Fast" model is optimized for speed. | COMBO | Yes | `"LTX-2 (Pro)"`<br />`"LTX-2 (Fast)"` |
| `prompt` | A text description that guides the content and motion of the generated video (default: empty). | STRING | Yes | - |
| `duration` | The length of the video in seconds (default: 8). | COMBO | Yes | `6`<br />`8`<br />`10`<br />`12`<br />`14`<br />`16`<br />`18`<br />`20` |
| `resolution` | The output resolution of the generated video. | COMBO | Yes | `"1920x1080"`<br />`"2560x1440"`<br />`"3840x2160"` |
| `fps` | The frames per second for the video (default: 25). | COMBO | Yes | `25`<br />`50` |
| `generate_audio` | When true, the generated video will include AI-generated audio matching the scene (default: False). | BOOLEAN | No | - |

**Important Constraints:**

* The `image` input must contain exactly one image.
* The `prompt` must be between 1 and 10,000 characters long.
* If you select a `duration` longer than 10 seconds, you must use the **"LTX-2 (Fast)"** model, a **"1920x1080"** resolution, and **25** FPS. This combination is required for longer videos.

**Note:** This node is marked as deprecated. The estimated cost displayed on the node depends on the selected `model`, `duration`, and `resolution`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LtxvApiImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `fa3928262e59105718b6ed97ddc8d2801e540b6b0c142541d92525dd75540cc7`


# LtxvApiTextToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LtxvApiTextToVideo

The LTXV Text To Video node generates professional-quality videos from a text description.

The LTXV Text To Video node generates professional-quality videos from a text description. It connects to an external API to create videos with customizable duration, resolution, and frame rate. You can also choose to have AI-generated audio added to the video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for video generation. "LTX-2 (Pro)" offers higher quality, while "LTX-2 (Fast)" is optimized for speed. | COMBO | Yes | `"LTX-2 (Pro)"`<br />`"LTX-2 (Fast)"` |
| `prompt` | The text description that the AI will use to generate the video. This field supports multiple lines of text and must contain 1 to 10,000 characters. Default: "" (empty). | STRING | Yes | - |
| `duration` | The length of the generated video in seconds (default: 8). | COMBO | Yes | `6`<br />`8`<br />`10`<br />`12`<br />`14`<br />`16`<br />`18`<br />`20` |
| `resolution` | The pixel dimensions (width x height) of the output video. | COMBO | Yes | `"1920x1080"`<br />`"2560x1440"`<br />`"3840x2160"` |
| `fps` | The frames per second for the video (default: 25). | COMBO | Yes | `25`<br />`50` |
| `generate_audio` | When true, the generated video will include AI-generated audio matching the scene (default: False). This is an advanced optional setting. | BOOLEAN | No | - |

**Important Constraints:**

* The `prompt` must be between 1 and 10,000 characters long.
* If you select a `duration` greater than 10 seconds, you must also use the `"LTX-2 (Fast)"` model, a resolution of `"1920x1080"`, and an `fps` of `25`. This combination is required for longer videos.
* Pricing depends on the selected `model`, `duration`, and `resolution`.

**Note:** This node is deprecated.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LtxvApiTextToVideo/en.md)

***

**Source fingerprint (SHA-256):** `8cf7409e46bb92abdff8a12e0d4ab49d67bb70e66c0c9074c9af99d1cf250df8`


# ModelComputeDtype - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelComputeDtype

The ModelComputeDtype node changes the computational data type (precision) used by a model during processing.

The ModelComputeDtype node changes the computational data type (precision) used by a model during processing. It creates a copy of the input model and applies the selected precision setting, which can help optimize memory usage and performance depending on your hardware. This is useful for debugging and testing different precision configurations.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The input model to modify with a new compute data type | MODEL | Yes | - |
| `dtype` | The computational data type to apply to the model (default: "default"). This parameter is marked as an advanced option. | COMBO | Yes | "default"<br />"fp32"<br />"fp16"<br />"bf16" |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with the new compute data type applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelComputeDtype/en.md)

***

**Source fingerprint (SHA-256):** `ad9c39e1217fd2e343ad4f49df9d1acabbc4708966dadec5340bb975adb59854`


# MoonvalleyImg2VideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoonvalleyImg2VideoNode

The Moonvalley Marey Image to Video node transforms a reference image into a video using the Moonvalley API.

The Moonvalley Marey Image to Video node transforms a reference image into a video using the Moonvalley API. It takes an input image and a text prompt to generate a video with specified resolution, quality settings, and creative controls. The node handles the entire process from image upload to video generation and download.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The reference image used to generate the video | IMAGE | Yes | - |
| `prompt` | Text description for video generation (multiline input) | STRING | Yes | - |
| `negative_prompt` | Negative prompt text to exclude unwanted elements (default: extensive negative prompt list) | STRING | No | - |
| `resolution` | Resolution of the output video (default: "16:9 (1920 x 1080)") | COMBO | No | "16:9 (1920 x 1080)"<br />"9:16 (1080 x 1920)"<br />"1:1 (1152 x 1152)"<br />"4:3 (1536 x 1152)"<br />"3:4 (1152 x 1536)" |
| `prompt_adherence` | Guidance scale for generation control (default: 4.5, step: 1.0) | FLOAT | No | 1.0 - 20.0 |
| `seed` | Random seed value (default: 9, control after generate enabled) | INT | No | 0 - 4294967295 |
| `steps` | Number of denoising steps (default: 33, step: 1) | INT | No | 1 - 100 |

**Constraints:**

* The input image must have dimensions between 300x300 pixels and the maximum allowed height/width
* Prompt and negative prompt text length is limited to the Moonvalley Marey maximum prompt length

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video output | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoonvalleyImg2VideoNode/en.md)

***

**Source fingerprint (SHA-256):** `674e69a7f106f6f961f10c179008b7bb1147bf0e569c72d207a105f3fab2aaf5`


# MoonvalleyTxt2VideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoonvalleyTxt2VideoNode

The Moonvalley Marey Text to Video node generates video content from text descriptions using the Moonvalley API.

The Moonvalley Marey Text to Video node generates video content from text descriptions using the Moonvalley API. It takes a text prompt and converts it into a video with customizable settings for resolution, quality, and style. The node handles the entire process from sending the generation request to downloading the final video output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text description of the video content to generate | STRING | Yes | - |
| `negative_prompt` | Negative prompt text (default: extensive list of excluded elements like synthetic, scene cut, artifacts, noise, etc.) | STRING | No | - |
| `resolution` | Resolution of the output video (default: "16:9 (1920 x 1080)") | STRING | No | "16:9 (1920 x 1080)"<br />"9:16 (1080 x 1920)"<br />"1:1 (1152 x 1152)"<br />"4:3 (1536 x 1152)"<br />"3:4 (1152 x 1536)"<br />"21:9 (2560 x 1080)" |
| `prompt_adherence` | Guidance scale for generation control (default: 4.0) | FLOAT | No | 1.0-20.0 |
| `seed` | Random seed value (default: 9) | INT | No | 0-4294967295 |
| `steps` | Inference steps (default: 33) | INT | No | 1-100 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video output based on the text prompt | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoonvalleyTxt2VideoNode/en.md)

***

**Source fingerprint (SHA-256):** `3654043567d7aca3af741d706ee07a8d2e28dbeb4b5b8755514b790aa7c1bd41`


# MoonvalleyVideo2VideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoonvalleyVideo2VideoNode

The Moonvalley Marey Video to Video node transforms an input video into a new video based on a text description.

The Moonvalley Marey Video to Video node transforms an input video into a new video based on a text description. It uses the Moonvalley API to generate videos that match your prompt while preserving motion or pose characteristics from the original video. You can control the style and content of the output video through text prompts and various generation parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Describes the video to generate (multiline input) | STRING | Yes | - |
| `negative_prompt` | Negative prompt text (default: extensive list of negative descriptors) | STRING | No | - |
| `seed` | Random seed value (default: 9) | INT | Yes | 0 to 4294967295 |
| `video` | The reference video used to generate the output video. Must be at least 5 seconds long. Videos longer than 5s will be automatically trimmed. Only MP4 format supported. | VIDEO | Yes | - |
| `control_type` | Control type selection (default: "Motion Transfer") | COMBO | No | "Motion Transfer"<br />"Pose Transfer" |
| `motion_intensity` | Only used if control\_type is "Motion Transfer" (default: 100) | INT | No | 0 to 100 |
| `steps` | Number of inference steps (default: 33) | INT | Yes | 1 to 100 |

**Note:** The `motion_intensity` parameter is only applied when `control_type` is set to "Motion Transfer". When using "Pose Transfer", this parameter is ignored.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video output | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoonvalleyVideo2VideoNode/en.md)

***

**Source fingerprint (SHA-256):** `8202a4be469afa16d77b9e0287c290b9c3f390347fc60f23878f50fd95a758e0`


# MultiGPU_Options - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MultiGPU_Options

Documentation for MultiGPUOptions node.

## Overview

This node allows you to specify the relative performance of each GPU when using multiple graphics cards with different speeds. It creates a group of GPU options that can be used to distribute work across devices, though the actual speed-based workload distribution is not yet implemented in the current version.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `device_index` | The index number of the GPU device to configure (default: 0) | INT | Yes | 0 to 64 |
| `relative_speed` | The relative speed of this GPU compared to others, used for workload distribution (default: 1.0, step: 0.01) | FLOAT | Yes | 0.0 to unlimited |
| `gpu_options` | An existing GPU options group to add this device's options to. If not provided, a new group is created | GPU\_OPTIONS | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `GPU_OPTIONS` | A group of GPU options containing the configured device settings, which can be passed to other nodes for multi-GPU operations | GPU\_OPTIONS |

**Note:** The `relative_speed` parameter is defined but not yet used by the internal scheduler for distributing work across GPUs. In the current implementation, work is distributed evenly across all devices regardless of their relative speeds.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MultiGPU_Options/en.md)

***

**Source fingerprint (SHA-256):** `8010460560a69c57d4ee0d8c3728a7a5d999e56ef5316b557fba0c660c9f38b0`


# MultiGPU_WorkUnits - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MultiGPU_WorkUnits

Documentation for MultiGPUWorkUnits node.

## Overview:

The MultiGPU CFG Split Node allows diffusion processing to occur using multiple GPUs installed in the same system. Performance results are workflow dependent, but speedups of up to 1.95x have been measured in common workflows.

## Key Details:

Mixing different GPU types is not supported, the installed GPUs must be the same (ie 2x 5090, or 2x 5080, etc.)

ComfyUI will automatically detect multiple installed GPUs at startup.

## Supported GPUs:

Any homogeneous dual GPU setups with Ampere+ architecture (e.g 2 x 3090 or 2 x RTX6000 Pro)

## Supported Models:

* LTX-2.3
* WAN 2.2
* FLUX.2 Klein - Base Versions
* Z-Image
* Stable Diffusion 3.5 Large
* Hunyuan Video
* Qwen-Image-Edit-2511
* Hunyuan-3D-v2.1
* SDXL

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to prepare for MultiGPU CFG splitting before sampling. | MODEL | Yes | N/A |
| `max_gpus` | The maximum number of identical GPUs to use for splitting the workload. Set this to the number of matching GPUs installed in your system. | INT | Yes | Minimum: 1<br />Step: 1<br />Default: 2 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The model prepared for MultiGPU CFG splitting, ready for accelerated sampling. | MODEL |

## Node:

<img alt="image1.png" />\
The max\_gpus field should be set to the maximum number of identical GPUs installed in the system.

**Node placement:**  The MultiGPU CFG Split needs to be placed between the Model Load node and Sampling node. If other nodes are connected to the model output of the model loader node, the MultiGPU CFG should be the last node in the chain before the Sampling node.

<img alt="image2.png" />

**Workflow Requirements:** The node works by splitting the diffusion workflow at the CFG level, due to this, the CFG in the workflow must be greater than CFG=1. Distilled workflows which require a CFG =1 will not show a performance benefit when using the MultiGPU CFG Split node to run on multiple GPUs.

## Verifying Multi-GPU Utilization

When running a workflow with MultiGPU CFG Split enabled, you can look at the Windows Task Manager and select the performance category\
<img alt="image3.png" />\
<img alt="image4.png" />\
You should see activity on both installed GPUs while the sampler is running in the workflow.

## Sample Multi-GPU Workflow: (Wan 2.2 FP8)

[Sample workflow (Wan 2.2 FP8)](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/MultiGPU_WorkUnits/asset/video_wan2_2_14B_t2v_mGPU.json)

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MultiGPU_WorkUnits/en.md)

***

**Source fingerprint (SHA-256):** `7293ee785e29aea9a1a70a10444b99e89fb23c866505628ec57c209a2b8aaee0`


# NAGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/NAGuidance

The NAGuidance node applies Normalized Attention Guidance to a model.

The NAGuidance node applies Normalized Attention Guidance to a model. This technique enables the use of negative prompts with distilled or schnell models by modifying the model's attention mechanism during the sampling process to steer the generation away from undesired concepts.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply Normalized Attention Guidance to. | MODEL | Yes | - |
| `nag_scale` | The guidance scale factor. Higher values push the generation further from the negative prompt. (default: 5.0) | FLOAT | Yes | 0.0 - 50.0 |
| `nag_alpha` | The blending factor for the normalized attention. A value of 1.0 fully replaces the original attention, while 0.0 has no effect. (default: 0.5) | FLOAT | Yes | 0.0 - 1.0 |
| `nag_tau` | A scaling factor used to limit the normalization ratio. (default: 1.5) | FLOAT | Yes | 1.0 - 10.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The patched model with Normalized Attention Guidance enabled. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/NAGuidance/en.md)

***

**Source fingerprint (SHA-256):** `42b4d601312dcbb1c934c6a79bbb5e9fd6598fa5f32b18f5c0affcb596672cba`


# OpenAIDalle2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIDalle2

Generates images synchronously via OpenAI's DALL·E 2 endpoint.

Generates images synchronously via OpenAI's DALL·E 2 endpoint. The node sends a text prompt to OpenAI's DALL·E 2 API and returns the resulting image(s) to ComfyUI. It can also edit an existing image when both an `image` and a `mask` are provided together.

## How It Works

This node connects to OpenAI's DALL·E 2 API to create images based on text descriptions. When you provide a text prompt, the node sends it to OpenAI's servers which generate corresponding images and return them to ComfyUI. The node can operate in two modes: standard image generation using just a text prompt, or image editing mode when both an image and mask are provided. In editing mode, it uses the mask to determine which parts of the original image should be modified while keeping other areas unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for DALL·E (default: empty) | STRING | Yes | - |
| `seed` | not implemented yet in backend (default: 0) | INT | No | 0 to 2147483647 |
| `size` | Image size (default: "1024x1024") | COMBO | No | "256x256"<br />"512x512"<br />"1024x1024" |
| `n` | How many images to generate (default: 1) | INT | No | 1 to 8 |
| `image` | Optional reference image for image editing. | IMAGE | No | - |
| `mask` | Optional mask for inpainting (white areas will be replaced) | MASK | No | - |

**Note:** Image editing mode is activated only when both `image` and `mask` are provided together. If only one of them is supplied, an error is raised. The `mask` must be the same size as the `image`; otherwise an error is raised. In editing mode, the white areas of the mask indicate the regions that will be replaced.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated or edited image(s) from DALL·E 2 | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIDalle2/en.md)

***

**Source fingerprint (SHA-256):** `c6bba5dd44ebed1d795e6ec93bdd2e19685e8ae9f24be9145ad9d74d3a9b7a0c`


# OpenAIDalle3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIDalle3

Generates images synchronously via OpenAI's DALL·E 3 endpoint.

Generates images synchronously via OpenAI's DALL·E 3 endpoint. This node takes a text prompt and creates corresponding images using OpenAI's DALL·E 3 model, allowing you to specify image quality, style, and dimensions.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for DALL·E (default: "") | STRING | Yes | - |
| `seed` | Not implemented yet in backend (default: 0) | INT | No | 0 to 2147483647 |
| `quality` | Image quality (default: "standard") | COMBO | No | "standard"<br />"hd" |
| `style` | Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images. (default: "natural") | COMBO | No | "natural"<br />"vivid" |
| `size` | Image size (default: "1024x1024") | COMBO | No | "1024x1024"<br />"1024x1792"<br />"1792x1024" |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated image from DALL·E 3 | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIDalle3/en.md)

***

**Source fingerprint (SHA-256):** `9077628610503d8c0afdd04e30dadac46106bd577d10f2d7aa10864db4430605`


# PairConditioningCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PairConditioningCombine

The PairConditioningCombine node merges two separate conditioning pairs (each consisting of a positive and negative conditioning) into a single combined pair.

The PairConditioningCombine node merges two separate conditioning pairs (each consisting of a positive and negative conditioning) into a single combined pair. It takes the positive and negative conditioning from two different sources and combines them using ComfyUI's internal logic, outputting one final positive and one final negative conditioning. This node is experimental and designed for advanced conditioning manipulation workflows.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive_A` | First positive conditioning input | CONDITIONING | Yes | - |
| `negative_A` | First negative conditioning input | CONDITIONING | Yes | - |
| `positive_B` | Second positive conditioning input | CONDITIONING | Yes | - |
| `negative_B` | Second negative conditioning input | CONDITIONING | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Combined positive conditioning output | CONDITIONING |
| `negative` | Combined negative conditioning output | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PairConditioningCombine/en.md)

***

**Source fingerprint (SHA-256):** `34c14207930ba31fea054b2e641e9666e738ed786aa117449c4a27667bde41b1`


# PairConditioningSetDefaultAndCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PairConditioningSetDefaultAndCombine

The PairConditioningSetDefaultAndCombine node sets default conditioning values and combines them with input conditioning data.

The **PairConditioningSetDefaultAndCombine** node sets default conditioning values and combines them with input conditioning data. It takes positive and negative conditioning inputs along with their default counterparts, then processes them through ComfyUI's hook system to produce final conditioning outputs that incorporate the default values.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The primary positive conditioning input to be processed | CONDITIONING | Yes | - |
| `negative` | The primary negative conditioning input to be processed | CONDITIONING | Yes | - |
| `positive_DEFAULT` | The default positive conditioning values to be used as fallback | CONDITIONING | Yes | - |
| `negative_DEFAULT` | The default negative conditioning values to be used as fallback | CONDITIONING | Yes | - |
| `hooks` | Optional hook group for custom processing logic | HOOKS | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The processed positive conditioning with default values incorporated | CONDITIONING |
| `negative` | The processed negative conditioning with default values incorporated | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PairConditioningSetDefaultAndCombine/en.md)

***

**Source fingerprint (SHA-256):** `dfa47d0fe02e81db8b68d20ae9b765c2518773f4f7fc8caf774cb870267dbb21`


# PairConditioningSetProperties - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PairConditioningSetProperties

The PairConditioningSetProperties node allows you to modify properties of both positive and negative conditioning pairs at the same time.

The **PairConditioningSetProperties** node allows you to modify properties of both positive and negative conditioning pairs at the same time. It applies strength adjustments, conditioning area settings, and optional masking or timing controls to both conditioning inputs, returning the modified positive and negative conditioning data.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive_NEW` | The positive conditioning input to modify | CONDITIONING | Yes | - |
| `negative_NEW` | The negative conditioning input to modify | CONDITIONING | Yes | - |
| `strength` | The strength multiplier applied to the conditioning (default: 1.0) | FLOAT | Yes | 0.0 to 10.0 |
| `set_cond_area` | Determines how the conditioning area is calculated (default: "default") | STRING | Yes | "default"<br />"mask bounds" |
| `mask` | Optional mask to constrain the conditioning area | MASK | No | - |
| `hooks` | Optional hook group for advanced conditioning modifications | HOOKS | No | - |
| `timesteps` | Optional timestep range to limit when conditioning is applied | TIMESTEPS\_RANGE | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning with applied properties | CONDITIONING |
| `negative` | The modified negative conditioning with applied properties | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PairConditioningSetProperties/en.md)

***

**Source fingerprint (SHA-256):** `3f750c270665b4f3567790ab1ae0bdbfa176527d4f8d96cf10570a5c5deb9636`


# PairConditioningSetPropertiesAndCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PairConditioningSetPropertiesAndCombine

The PairConditioningSetPropertiesAndCombine node modifies and combines conditioning pairs by applying new conditioning data to existing positive and negative conditioning inputs.

The PairConditioningSetPropertiesAndCombine node modifies and combines conditioning pairs by applying new conditioning data to existing positive and negative conditioning inputs. It allows you to adjust the strength of the applied conditioning and control how the conditioning area is set. This node is particularly useful for advanced conditioning manipulation workflows where you need to blend multiple conditioning sources together.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The original positive conditioning input | CONDITIONING | Yes | - |
| `negative` | The original negative conditioning input | CONDITIONING | Yes | - |
| `positive_NEW` | The new positive conditioning to apply | CONDITIONING | Yes | - |
| `negative_NEW` | The new negative conditioning to apply | CONDITIONING | Yes | - |
| `strength` | The strength factor for applying the new conditioning (default: 1.0) | FLOAT | Yes | 0.0 to 10.0 |
| `set_cond_area` | Controls how the conditioning area is applied (default: "default") | STRING | Yes | "default"<br />"mask bounds" |
| `mask` | Optional mask to constrain the conditioning application area | MASK | No | - |
| `hooks` | Optional hook group for advanced control | HOOKS | No | - |
| `timesteps` | Optional timestep range specification | TIMESTEPS\_RANGE | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The combined positive conditioning output | CONDITIONING |
| `negative` | The combined negative conditioning output | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PairConditioningSetPropertiesAndCombine/en.md)

***

**Source fingerprint (SHA-256):** `d434fdc1ccbe3ddee6293a6300cc55d30cb5bf357025b26777791746f51e755e`


# SaveLoRANode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveLoRANode

The SaveLoRA node saves LoRA (Low-Rank Adaptation) models to your output directory.

The SaveLoRA node saves LoRA (Low-Rank Adaptation) models to your output directory. It takes a LoRA model as input and creates a safetensors file with an automatically generated filename. You can customize the filename prefix and optionally include the training step count in the filename for better organization.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `lora` | The LoRA model to save. Do not use the model with LoRA layers. | LORA\_MODEL | Yes | - |
| `prefix` | The prefix to use for the saved LoRA file (default: "loras/ComfyUI\_trained\_lora"). | STRING | Yes | - |
| `steps` | Optional: The number of steps the LoRA has been trained for, used to name the saved file. | INT | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| *None* | This node does not return any outputs but saves the LoRA model to the output directory. | - |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveLoRANode/en.md)

***

**Source fingerprint (SHA-256):** `06a1067433aa4b720b51050b09fbad4870caf12c5e92f788d44ea022a39efef4`


# SeedVR2ProgressiveSampler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SeedVR2ProgressiveSampler

Sequential temporal chunking sampler for SeedVR2 native workflows.

Sequential temporal chunking sampler for SeedVR2 native workflows. This node processes long video latents by splitting them into smaller temporal chunks, sampling each chunk sequentially, and blending the results together. It serves as a drop-in replacement for the standard KSampler when working with SeedVR2 models on sequences that would otherwise cause out-of-memory errors.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model used for denoising the input latent | MODEL | Yes | |
| `seed` | The random seed used for creating the noise (default: 0) | INT | Yes | 0 to 0xffffffffffffffff |
| `steps` | The number of steps used in the denoising process (default: 20) | INT | Yes | 1 to 10000 |
| `cfg` | The Classifier-Free Guidance scale balances creativity and adherence to the prompt. Higher values result in images more closely matching the prompt however too high values will negatively impact quality (default: 1.0) | FLOAT | Yes | 0.0 to 100.0 |
| `sampler_name` | The algorithm used when sampling, this can affect the quality, speed, and style of the generated output | COMBO | Yes | Multiple options available |
| `scheduler` | The scheduler controls how noise is gradually removed to form the image | COMBO | Yes | Multiple options available |
| `positive` | The conditioning describing the attributes you want to include in the image | CONDITIONING | Yes | |
| `negative` | The conditioning describing the attributes you want to exclude from the image | CONDITIONING | Yes | |
| `latent` | The latent image to denoise | LATENT | Yes | |
| `denoise` | The amount of denoising applied, lower values will maintain the structure of the initial image allowing for image to image sampling (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `frames_per_chunk` | Pixel frames per temporal chunk. Must be a 4n+1 value (1, 5, 9, 13, 17, 21, ...) to match SeedVR2 constraints (default: 21) | INT | Yes | 1 to 16384 (step of 4) |
| `temporal_overlap` | Latent frames blended between adjacent chunks to hide the seam; 0 means no blend (default: 0) | INT | Yes | 0 to 16384 |
| `chunking_mode` | manual = use frames\_per\_chunk exactly; auto = shrink the chunk until it fits in VRAM (default: "manual") | COMBO | Yes | "manual"<br />"auto" |

**Note on `frames_per_chunk`:** This parameter must be a 4n+1 pixel-frame count (1, 5, 9, 13, 17, 21, ...). The node will raise an error if an invalid value is provided.

**Note on `temporal_overlap`:** The overlap value is automatically capped to be at most one less than the latent chunk size to ensure valid chunk processing.

**Note on `chunking_mode`:** When set to "auto", the node will automatically try smaller chunk sizes if the current chunk causes an out-of-memory error. If all attempts fail, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latent` | The denoised latent output, concatenated from all temporal chunks back into a single collapsed SeedVR2 latent tensor | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SeedVR2ProgressiveSampler/en.md)

***

**Source fingerprint (SHA-256):** `a4574c3e619954b5569551b5b2ba112ecbff918dcebb5ba718a14e77701144a9`


# SelectCLIPDevice - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SelectCLIPDevice

Documentation for SelectCLIPDevice node.

## Overview

The Select CLIP Device node lets you choose which device (CPU or a specific GPU) the CLIP text encoder runs on. By default, the device is assigned by the model loader, but you can override it to use the CPU or a particular GPU. If the requested device doesn't exist on your machine, the node simply passes the CLIP through unchanged and logs a message instead of causing an error.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP text encoder to assign to a specific device. | CLIP | Yes | |
| `device` | The device to place the CLIP text encoder on. `"default"` restores the device assigned by the loader. `"cpu"` pins both the load and offload device to CPU. `"gpu:N"` pins the load device to the Nth available GPU (default: `"default"`). | COMBO | Yes | `"default"`<br />`"cpu"`<br />`"gpu:0"`<br />`"gpu:1"`<br />`"gpu:2"`<br />`"gpu:3"`<br />`"gpu:4"`<br />`"gpu:5"`<br />`"gpu:6"`<br />`"gpu:7"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `clip` | The CLIP text encoder assigned to the selected device, or the original CLIP passed through unchanged if the requested device is not available. | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SelectCLIPDevice/en.md)

***

**Source fingerprint (SHA-256):** `92af94d9f5eea27095cc008debdf7339d26888a0e2cc8bd71ae9c9ba8718eb01`


# SelectModelDevice - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SelectModelDevice

The Select Model Device node allows you to manually choose which device (CPU or a specific GPU) a diffusion model runs on.

The Select Model Device node allows you to manually choose which device (CPU or a specific GPU) a diffusion model runs on. It can move a model to a different device, and it handles conflicts with other multi-GPU nodes automatically. Selecting `"default"` restores the original device chosen by the model loader.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to place on a specific device. | MODEL | Yes | |
| `device` | The target device for the model. Options are dynamically generated based on the available devices on the current machine. (default: `"default"`) | COMBO | Yes | `"default"`<br />`"cpu"`<br />`"gpu:0"`<br />`"gpu:1"`<br />... (one `"gpu:N"` entry per detected GPU) |

**Parameter Details:**

* `"default"`: Restores the load and offload devices assigned by the model loader, even after a previous Select Model Device call.
* `"cpu"`: Pins both the load and offload device to CPU.
* `"gpu:N"`: Pins the load device to the Nth available GPU (for example, `"gpu:0"` for the first GPU). The offload device is restored to the loader's original choice.

**Important Notes:**

* If the requested device does not exist on the current machine (for example, a workflow created on a 2-GPU machine is opened on a 1-GPU machine), the node passes the model through unchanged and logs a message instead of failing. Unknown `gpu:N` values are allowed during input validation so portable workflows do not error early.
* If the model is already on the requested device, the node uses a fast path and does not reload the model.
* When the requested device differs from the device the input model is already on, a fresh model is spawned using the loader's reload factory so the new patcher owns independent weights on the new device.
* If the model loader does not support multi-GPU (no reload factory), the node passes the model through unchanged and logs a warning.
* When a MultiGPU CFG Split clone already occupies the selected device, that clone is pruned so two models are not bound to the same device.
* When a non-default device is selected (CPU or GPU), the node also adjusts the model's compute dtype to one supported by that device.
* Placing this node after a node that has already consumed the model (for example, a KSampler) is not recommended, because any state changed by the prior node will be observed if the device matches the original.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The diffusion model, now placed on the selected device. If the device was invalid or unavailable, the model is passed through unchanged. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SelectModelDevice/en.md)

***

**Source fingerprint (SHA-256):** `d02a8bd9612861cf696f03969fe693088351de5a72ccbd4c1aed405b104eb71e`


# SelectVAEDevice - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SelectVAEDevice

Documentation for SelectVAEDevice node.

## Overview

This node allows you to manually select which GPU device the VAE model should be placed on. By default, the VAE is placed on the device assigned by the model loader, but you can pin it to a specific GPU (e.g., `gpu:0`, `gpu:1`). If the selected device is not available on your machine, the node will pass the VAE through unchanged and log a message instead of failing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `vae` | The VAE model to assign to a specific device. | VAE | Yes | |
| `device` | The target device for the VAE. `"default"` restores the device assigned by the loader. `"gpu:N"` pins the VAE to the Nth available GPU. CPU is not a supported choice and will be ignored if provided. (default: `"default"`) | COMBO | Yes | `"default"`<br />`"gpu:0"`<br />`"gpu:1"`<br />`"gpu:2"`<br />`"gpu:3"`<br />`"gpu:4"`<br />`"gpu:5"`<br />`"gpu:6"`<br />`"gpu:7"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `vae` | The VAE model, now assigned to the selected device. If the requested device is unavailable or invalid, the VAE is passed through unchanged. | VAE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SelectVAEDevice/en.md)

***

**Source fingerprint (SHA-256):** `011154043fc02f930b0074de656bb24baf4dfe74bcfd2e89ea76284f0a5b7d8e`


# SetClipHooks - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetClipHooks

The SetClipHooks node allows you to apply custom hooks to a CLIP model, enabling advanced modifications to its behavior.

The SetClipHooks node allows you to apply custom hooks to a CLIP model, enabling advanced modifications to its behavior. It can apply hooks to conditioning outputs and optionally enable clip scheduling functionality. This node creates a cloned copy of the input CLIP model with the specified hook configurations applied.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model to apply hooks to | CLIP | Yes | - |
| `apply_to_conds` | Whether to apply hooks to conditioning outputs (default: True) | BOOLEAN | Yes | - |
| `schedule_clip` | Whether to enable clip scheduling (default: False) | BOOLEAN | Yes | - |
| `hooks` | Optional hook group to apply to the CLIP model | HOOKS | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `clip` | A cloned CLIP model with the specified hooks applied | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetClipHooks/en.md)

***

**Source fingerprint (SHA-256):** `904a878638c015bdce1983ae0c11a2b580b271090fca39edb304f6ed90c8c66d`


# SetHookKeyframes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetHookKeyframes

The Set Hook Keyframes node allows you to apply keyframe scheduling to existing hook groups.

The Set Hook Keyframes node allows you to apply keyframe scheduling to existing hook groups. It takes a hook group and optionally applies keyframe timing information to control when different hooks are executed during the generation process. When keyframes are provided, the node clones the hook group and sets the keyframe timing on all hooks within the group.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `hooks` | The hook group to which keyframe scheduling will be applied | HOOKS | Yes | - |
| `hook_kf` | Optional keyframe group containing timing information for hook execution | HOOK\_KEYFRAMES | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `hooks` | The modified hook group with keyframe scheduling applied (cloned if keyframes were provided) | HOOKS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetHookKeyframes/en.md)

***

**Source fingerprint (SHA-256):** `48908e5247b18e5b7b1d894c2f1adcf6403e499125b0c3eb05978584b3d5759b`


# SetModelHooksOnCond - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetModelHooksOnCond

This node attaches custom hooks to conditioning data, allowing you to intercept and modify the conditioning process during model execution.

This node attaches custom hooks to conditioning data, allowing you to intercept and modify the conditioning process during model execution. It takes a set of hooks and applies them to the provided conditioning data, enabling advanced customization of the text-to-image generation workflow. The modified conditioning with attached hooks is then returned for use in subsequent processing steps.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `conditioning` | The conditioning data to which hooks will be attached | CONDITIONING | Yes | - |
| `hooks` | The hook definitions that will be applied to the conditioning data | HOOKS | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `conditioning` | The modified conditioning data with hooks attached | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetModelHooksOnCond/en.md)

***

**Source fingerprint (SHA-256):** `a6e63a3a4d94d1b66a82d449af5ae001e1fc4a04f0f81d9fb5c4f8c13e5bdf8b`


# SkipLayerGuidanceDiT - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SkipLayerGuidanceDiT

Enhances guidance towards detailed structure by using another set of CFG negative with skipped layers.

Enhances guidance towards detailed structure by using another set of CFG negative with skipped layers. This generic version of SkipLayerGuidance can be used on every DiT model and is inspired by Perturbed Attention Guidance. The original experimental implementation was created for SD3.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply skip layer guidance to | MODEL | Yes | - |
| `double_layers` | Comma-separated layer numbers for double blocks to skip (default: "7, 8, 9") | STRING | Yes | - |
| `single_layers` | Comma-separated layer numbers for single blocks to skip (default: "7, 8, 9") | STRING | Yes | - |
| `scale` | Guidance scale factor (default: 3.0) | FLOAT | Yes | 0.0 - 10.0 |
| `start_percent` | Starting percentage for guidance application (default: 0.01) | FLOAT | Yes | 0.0 - 1.0 |
| `end_percent` | Ending percentage for guidance application (default: 0.15) | FLOAT | Yes | 0.0 - 1.0 |
| `rescaling_scale` | Rescaling scale factor to adjust the output magnitude (default: 0.0, meaning no rescaling) | FLOAT | Yes | 0.0 - 10.0 |

**Note:** If both `double_layers` and `single_layers` are empty (contain no layer numbers), the node returns the original model without applying any guidance.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with skip layer guidance applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SkipLayerGuidanceDiT/en.md)

***

**Source fingerprint (SHA-256):** `35ca97f87913d0efcbb502ca040a8f357da112b202184d8786f63acd76809808`


# SkipLayerGuidanceDiTSimple - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SkipLayerGuidanceDiTSimple

Simple version of the SkipLayerGuidanceDiT node that only modifies the unconditional pass during the denoising process.

Simple version of the SkipLayerGuidanceDiT node that only modifies the unconditional pass during the denoising process. This node applies skip layer guidance to specific transformer layers in DiT (Diffusion Transformer) models by selectively skipping certain layers during the unconditional pass based on specified timing and layer parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply skip layer guidance to | MODEL | Yes | - |
| `double_layers` | Comma-separated list of double block layer indices to skip (default: "7, 8, 9") | STRING | No | - |
| `single_layers` | Comma-separated list of single block layer indices to skip (default: "7, 8, 9") | STRING | No | - |
| `start_percent` | The starting percentage of the denoising process when skip layer guidance begins (default: 0.0) | FLOAT | No | 0.0 - 1.0 |
| `end_percent` | The ending percentage of the denoising process when skip layer guidance stops (default: 1.0) | FLOAT | No | 0.0 - 1.0 |

**Note:** Skip layer guidance is only applied when both `double_layers` and `single_layers` contain valid layer indices. If both are empty, the node returns the original model unchanged. The skip layer guidance is active only when the current denoising step's sigma value falls between `start_percent` and `end_percent` (converted to sigma values internally).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with skip layer guidance applied to the specified layers | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SkipLayerGuidanceDiTSimple/en.md)

***

**Source fingerprint (SHA-256):** `f153348d75cf3b52d7d7d541f7467e51c797e1fe5844516591db7a191415cdb2`


# SkipLayerGuidanceSD3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SkipLayerGuidanceSD3

The SkipLayerGuidanceSD3 node enhances guidance towards detailed structure by applying an additional set of classifier-free guidance with skipped layers.

The SkipLayerGuidanceSD3 node enhances guidance towards detailed structure by applying an additional set of classifier-free guidance with skipped layers. This experimental implementation is inspired by Perturbed Attention Guidance and works by selectively bypassing certain layers during the negative conditioning process to improve structural details in the generated output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply skip layer guidance to | MODEL | Yes | - |
| `layers` | Comma-separated list of layer indices to skip (default: "7, 8, 9") | STRING | Yes | - |
| `scale` | The strength of the skip layer guidance effect (default: 3.0) | FLOAT | Yes | 0.0 - 10.0 |
| `start_percent` | The starting point of guidance application as a percentage of total steps (default: 0.01) | FLOAT | Yes | 0.0 - 1.0 |
| `end_percent` | The ending point of guidance application as a percentage of total steps (default: 0.15) | FLOAT | Yes | 0.0 - 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with skip layer guidance applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SkipLayerGuidanceSD3/en.md)

***

**Source fingerprint (SHA-256):** `8fba6e3037387e6beab64175099de1c96babdd492609099ba8ad3a49a6c34efe`


# StabilityAudioInpaint - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityAudioInpaint

Transforms part of an existing audio sample using text instructions.

Transforms part of an existing audio sample using text instructions. This node allows you to modify specific sections of audio by providing descriptive prompts, effectively "inpainting" or regenerating selected portions while preserving the rest of the audio.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for audio inpainting. | STRING | Yes | `"stable-audio-2.5"` |
| `prompt` | Text description guiding how the audio should be transformed (default: empty). Maximum length is 10,000 characters. | STRING | Yes | |
| `audio` | Input audio file to transform. Audio must be between 6 and 190 seconds long. | AUDIO | Yes | |
| `duration` | Controls the duration in seconds of the generated audio (default: 190). | INT | No | 1 to 190 |
| `seed` | The random seed used for generation (default: 0). | INT | No | 0 to 4294967294 |
| `steps` | Controls the number of sampling steps (default: 8). | INT | No | 4 to 8 |
| `mask_start` | Starting position in seconds for the audio section to transform (default: 30). | INT | No | 0 to 190 |
| `mask_end` | Ending position in seconds for the audio section to transform (default: 190). | INT | No | 0 to 190 |

**Note:** The `mask_end` value must be greater than the `mask_start` value. The input audio must be between 6 and 190 seconds in duration.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The transformed audio output with the specified section modified according to the prompt. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityAudioInpaint/en.md)

***

**Source fingerprint (SHA-256):** `3c180043c538311b1808cddd84b0c0ab22a6fa1d943b7f9ddc9edab0fb3413ad`


# StabilityAudioToAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityAudioToAudio

Transforms existing audio samples into new high-quality compositions using text instructions.

Transforms existing audio samples into new high-quality compositions using text instructions. This node takes an input audio file and modifies it based on your text prompt to create new audio content.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for audio transformation | COMBO | Yes | "stable-audio-2.5" |
| `prompt` | Text instructions describing how to transform the audio (default: empty, max length: 10000 characters) | STRING | Yes | |
| `audio` | Audio must be between 6 and 190 seconds long | AUDIO | Yes | |
| `duration` | Controls the duration in seconds of the generated audio (default: 190) | INT | No | 1-190 |
| `seed` | The random seed used for generation (default: 0) | INT | No | 0-4294967294 |
| `steps` | Controls the number of sampling steps (default: 8) | INT | No | 4-8 |
| `strength` | Parameter controls how much influence the audio parameter has on the generated audio (default: 1.0) | FLOAT | No | 0.01-1.0 |

**Note:** The input audio must be between 6 and 190 seconds in duration. The prompt text has a maximum length of 10,000 characters.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The transformed audio generated based on the input audio and text prompt | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityAudioToAudio/en.md)

***

**Source fingerprint (SHA-256):** `3df67797bf2eccf9d7464a1dd00ea5b6c5a9527f7290911c60a9ebff69302241`


# StabilityStableImageSD_3_5Node - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityStableImageSD_3_5Node

This node generates images synchronously using Stability AI's Stable Diffusion 3.5 model.

This node generates images synchronously using Stability AI's Stable Diffusion 3.5 model. It creates images based on text prompts and can also modify existing images when provided as input. The node supports various aspect ratios and style presets to customize the output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results. (default: empty string) | STRING | Yes | - |
| `model` | The Stable Diffusion 3.5 model to use for generation. | COMBO | Yes | `sd3.5-large`<br />`sd3.5-large-turbo`<br />`sd3.5-medium` |
| `aspect_ratio` | Aspect ratio of generated image. (default: 1:1) | COMBO | Yes | `16:9`<br />`1:1`<br />`21:9`<br />`2:3`<br />`3:2`<br />`4:5`<br />`5:4`<br />`9:16`<br />`9:21` |
| `style_preset` | Optional desired style of generated image. Select "None" for no style preset. | COMBO | No | `3d-model`<br />`analog-film`<br />`anime`<br />`cinematic`<br />`comic-book`<br />`digital-art`<br />`enhance`<br />`fantasy-art`<br />`isometric`<br />`line-art`<br />`low-poly`<br />`modeling-compound`<br />`neon-punk`<br />`origami`<br />`photographic`<br />`pixel-art`<br />`tile-texture`<br />`None` |
| `cfg_scale` | How strictly the diffusion process adheres to the prompt text (higher values keep your image closer to your prompt). (default: 4.0) | FLOAT | Yes | 1.0 to 10.0 |
| `seed` | The random seed used for creating the noise. (default: 0) | INT | Yes | 0 to 4294967294 |
| `image` | Optional input image for image-to-image generation. When provided, the node switches to image-to-image mode and the `aspect_ratio` parameter is ignored. | IMAGE | No | - |
| `negative_prompt` | Keywords of what you do not wish to see in the output image. This is an advanced feature. (default: empty string) | STRING | No | - |
| `image_denoise` | Denoise of input image; 0.0 yields image identical to input, 1.0 is as if no image was provided at all. (default: 0.5) This parameter is only used when an `image` is provided. | FLOAT | No | 0.0 to 1.0 |

**Note:** When an `image` is provided, the node switches to image-to-image generation mode and the `aspect_ratio` parameter is automatically determined from the input image. When no `image` is provided, the `image_denoise` parameter is ignored.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated or modified image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityStableImageSD_3_5Node/en.md)

***

**Source fingerprint (SHA-256):** `0ef029d4651fb4a9132899a6df1a2c2de6152dd9091129573f366a2aac39bbae`


# StabilityStableImageUltraNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityStableImageUltraNode

Generates images synchronously based on prompt and resolution.

Generates images synchronously based on prompt and resolution. This node creates images using Stability AI's Stable Image Ultra model, processing your text prompt and generating a corresponding image with the specified aspect ratio and style.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results. To control the weight of a given word use the format `(word:weight)`, where `word` is the word you'd like to control the weight of and `weight` is a value between 0 and 1. For example: `The sky was a crisp (blue:0.3) and (green:0.8)` would convey a sky that was blue and green, but more green than blue. | STRING | Yes | - |
| `aspect_ratio` | Aspect ratio of generated image (default: "1:1"). | COMBO | Yes | `"1:1"`<br />`"16:9"`<br />`"21:9"`<br />`"2:3"`<br />`"3:2"`<br />`"4:5"`<br />`"5:4"`<br />`"9:16"`<br />`"9:21"` |
| `style_preset` | Optional desired style of generated image. Select "None" to not apply any style preset. | COMBO | No | `"3d-model"`<br />`"analog-film"`<br />`"anime"`<br />`"cinematic"`<br />`"comic-book"`<br />`"digital-art"`<br />`"enhance"`<br />`"fantasy-art"`<br />`"isometric"`<br />`"line-art"`<br />`"low-poly"`<br />`"modeling-compound"`<br />`"neon-punk"`<br />`"origami"`<br />`"photographic"`<br />`"pixel-art"`<br />`"tile-texture"` |
| `seed` | The random seed used for creating the noise. | INT | Yes | 0 - 4294967294 |
| `image` | Optional input image for image-to-image generation. | IMAGE | No | - |
| `negative_prompt` | A blurb of text describing what you do not wish to see in the output image. This is an advanced feature. | STRING | No | - |
| `image_denoise` | Denoise of input image; 0.0 yields image identical to input, 1.0 is as if no image was provided at all (default: 0.5). | FLOAT | No | 0.0 - 1.0 |

**Note:** When an input image is not provided, the `image_denoise` parameter is automatically disabled and ignored.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated image based on the input parameters. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityStableImageUltraNode/en.md)

***

**Source fingerprint (SHA-256):** `86a9ace60a1f9f2b872865381c695bd0e3e3578e0dd3453f1ab3be58bae2e2f0`


# StabilityTextToAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityTextToAudio

Generates high-quality music and sound effects from text descriptions.

Generates high-quality music and sound effects from text descriptions. This node uses Stability AI's audio generation technology to create audio content based on your text prompts.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The audio generation model to use (default: "stable-audio-2.5") | COMBO | Yes | `"stable-audio-2.5"` |
| `prompt` | The text description used to generate audio content (default: empty string) | STRING | Yes | - |
| `duration` | Controls the duration in seconds of the generated audio (default: 190) | INT | No | 1-190 |
| `seed` | The random seed used for generation (default: 0) | INT | No | 0-4294967294 |
| `steps` | Controls the number of sampling steps (default: 8) | INT | No | 4-8 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The generated audio file based on the text prompt | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityTextToAudio/en.md)

***

**Source fingerprint (SHA-256):** `8dfe0eafb6157bc458c2ba3053a98e2bb5dfe896921cf90a70a88c695f8c5edc`


# StabilityUpscaleConservativeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityUpscaleConservativeNode

Upscale image with minimal alterations to 4K resolution.

Upscale image with minimal alterations to 4K resolution. This node uses Stability AI's conservative upscaling to increase image resolution while preserving the original content and making only subtle changes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be upscaled | IMAGE | Yes | - |
| `prompt` | What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results. (default: empty string) | STRING | Yes | - |
| `creativity` | Controls the likelihood of creating additional details not heavily conditioned by the init image. (default: 0.35) | FLOAT | Yes | 0.2 - 0.5 |
| `seed` | The random seed used for creating the noise. (default: 0) | INT | Yes | 0 - 4294967294 |
| `negative_prompt` | Keywords of what you do not wish to see in the output image. This is an advanced feature. (default: empty string) | STRING | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The upscaled image at 4K resolution | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityUpscaleConservativeNode/en.md)

***

**Source fingerprint (SHA-256):** `e4faa795d5a197cdc85c6985b99e8a7229b2b64f929eea3fefff3aff32558c18`


# StabilityUpscaleCreativeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityUpscaleCreativeNode

Upscale image with minimal alterations to 4K resolution.

Upscale image with minimal alterations to 4K resolution. This node uses Stability AI's creative upscaling technology to enhance image resolution while preserving the original content and adding subtle creative details.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be upscaled | IMAGE | Yes | - |
| `prompt` | What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results. (default: empty string) | STRING | Yes | - |
| `creativity` | Controls the likelihood of creating additional details not heavily conditioned by the init image. (default: 0.3) | FLOAT | Yes | 0.1-0.5 |
| `style_preset` | Optional desired style of generated image. (default: "None") | STRING | Yes | `"3d-model"`<br />`"analog-film"`<br />`"anime"`<br />`"cinematic"`<br />`"comic-book"`<br />`"digital-art"`<br />`"enhance"`<br />`"fantasy-art"`<br />`"isometric"`<br />`"line-art"`<br />`"low-poly"`<br />`"modeling-compound"`<br />`"neon-punk"`<br />`"origami"`<br />`"photographic"`<br />`"pixel-art"`<br />`"tile-texture"` |
| `seed` | The random seed used for creating the noise. (default: 0) | INT | Yes | 0-4294967294 |
| `negative_prompt` | Keywords of what you do not wish to see in the output image. This is an advanced feature. (default: empty string) | STRING | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The upscaled image at 4K resolution | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityUpscaleCreativeNode/en.md)

***

**Source fingerprint (SHA-256):** `dc9bfacee3bfa663cff22cd0bcef6759f7808e2ae8e19526de28d55a3bef26e6`


# StabilityUpscaleFastNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityUpscaleFastNode

Quickly upscales an image via Stability API call to 4x its original size.

Quickly upscales an image via Stability API call to 4x its original size. This node is specifically intended for upscaling low-quality or compressed images by sending them to Stability AI's fast upscaling service.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be upscaled | IMAGE | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The upscaled image returned from the Stability AI API | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityUpscaleFastNode/en.md)

***

**Source fingerprint (SHA-256):** `2d24f44fdd96a528a48869ca9c1343ca03311e982dfdbc4a8841bc147c9a621e`


# TCFG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TCFG

TCFG (Tangential Damping CFG) refines the unconditional (negative) predictions to better align with the conditional (positive) predictions during the sampling process.

TCFG (Tangential Damping CFG) refines the unconditional (negative) predictions to better align with the conditional (positive) predictions during the sampling process. This technique improves output quality by applying tangential damping to the unconditional guidance, based on the research paper 2503.18137. The node modifies the model's sampling behavior by adjusting how unconditional predictions are processed during classifier-free guidance.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply tangential damping CFG to | MODEL | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `patched_model` | The modified model with tangential damping CFG applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TCFG/en.md)

***

**Source fingerprint (SHA-256):** `6e0e1df09bdc29f14a4828ec54fd29f89926b9d8121bc8ba9f95ce066b899e95`


# TripoRefineNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoRefineNode

The TripoRefineNode refines draft 3D models created specifically by Tripo v1.4 models.

The TripoRefineNode refines draft 3D models created specifically by Tripo v1.4 models. It takes a model task ID and processes it through the Tripo API to generate an improved version of the model. This node is designed to work exclusively with draft models produced by Tripo v1.4 models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_task_id` | Must be a v1.4 Tripo model | MODEL\_TASK\_ID | Yes | - |

**Note:** This node only accepts draft models created by Tripo v1.4 models. Using models from other versions may result in errors.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The file path or reference to the refined model (for backward compatibility only) | STRING |
| `model task_id` | The task identifier for the refined model operation | MODEL\_TASK\_ID |
| `GLB` | The refined 3D model in GLB format | FILE3DGLB |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoRefineNode/en.md)

***

**Source fingerprint (SHA-256):** `502064a5f153ed05b985f859f27b26eb5219427a17b876cfebedfdcf3194fe12`


# VeoVideoGenerationNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VeoVideoGenerationNode

Generates videos from text prompts using Google's Veo API.

Generates videos from text prompts using Google's Veo API. This node can create videos from text descriptions and optional image inputs, with control over parameters like aspect ratio, duration, and more.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text description of the video (default: empty) | STRING | Yes | - |
| `aspect_ratio` | Aspect ratio of the output video (default: "16:9") | COMBO | Yes | "16:9"<br />"9:16" |
| `negative_prompt` | Negative text prompt to guide what to avoid in the video (default: empty) | STRING | No | - |
| `duration_seconds` | Duration of the output video in seconds (default: 5) | INT | No | 5-8 |
| `enhance_prompt` | Whether to enhance the prompt with AI assistance (default: True). This is an advanced parameter. | BOOLEAN | No | - |
| `person_generation` | Whether to allow generating people in the video (default: "ALLOW"). This is an advanced parameter. | COMBO | No | "ALLOW"<br />"BLOCK" |
| `seed` | Seed for video generation (0 for random) (default: 0). This is an advanced parameter. | INT | No | 0-4294967295 |
| `image` | Optional reference image to guide video generation | IMAGE | No | - |
| `model` | Veo model to use for video generation (default: "veo-2.0-generate-001") | COMBO | No | "veo-2.0-generate-001"<br />"veo-3.1-generate"<br />"veo-3.1-fast-generate"<br />"veo-3.1-lite"<br />"veo-3.0-generate-001"<br />"veo-3.0-fast-generate-001" |

**Note:** The `generate_audio` parameter is only available for Veo 3.0 and Veo 3.1 models and is automatically handled by the node based on the selected model. When using Veo 3.0 or Veo 3.1 models, the `enhance_prompt` parameter is forced to True.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VeoVideoGenerationNode/en.md)

***

**Source fingerprint (SHA-256):** `055569f26c7e8f074371239f12f307ca86ce2aa5fd17ca55dd951b34f71fa559`


# VoxelToMeshBasic - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VoxelToMeshBasic

The VoxelToMeshBasic node converts 3D voxel data into mesh geometry.

The VoxelToMeshBasic node converts 3D voxel data into mesh geometry. It processes voxel volumes by applying a threshold value to determine which parts of the volume become solid surfaces in the resulting mesh. The node outputs a complete mesh structure with vertices and faces that can be used for 3D rendering and modeling.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `voxel` | The 3D voxel data to convert into a mesh | VOXEL | Yes | - |
| `threshold` | The threshold value used to determine which voxels become part of the mesh surface (default: 0.6) | FLOAT | Yes | -1.0 to 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MESH` | The generated 3D mesh containing vertices and faces | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VoxelToMeshBasic/en.md)

***

**Source fingerprint (SHA-256):** `95d729463e9d32fb0b8a82a397c6ed7fccaf190ec8a183d71a99fef170747fd1`


# Flux 1.1 [pro] Ultra Image - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/bfl/flux-1-1-pro-ultra-image

Create images using Black Forest Labs' high-resolution image generation API

<img alt="ComfyUI Native Flux 1.1 [pro] Ultra Image node" />

The Flux 1.1 \[pro] Ultra Image node allows you to generate ultra-high-resolution images through text prompts, directly connecting to Black Forest Labs' latest image generation API.

This node supports two main usage modes:

1. **Text-to-Image**: Generate high-quality images from text prompts (when no image input is used)
2. **Image-to-Image**: Combine existing images with prompts to create new images that blend features from both (Remix mode)

This node supports Ultra mode through API calls, capable of generating images at 4 times the resolution of standard Flux 1.1 \[pro] (up to 4MP), without sacrificing prompt adherence, and maintaining super-fast generation times of just 10 seconds. Compared to other high-resolution models, it's more than 2.5 times faster.

## Parameter Description

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | String | "" | Text description for generating the image |
| prompt\_upsampling | Boolean | False | Whether to use prompt upsampling technique to enhance details. When enabled, automatically modifies prompts for more creative generation, but results become non-deterministic (same seed won't produce exactly the same result) |
| seed | Integer | 0 | Random seed value, controls generation randomness |
| aspect\_ratio | String | "16:9" | Width-to-height ratio of the image, must be between 1:4 and 4:1 |
| raw | Boolean | False | When set to True, generates less processed, more natural-looking images |

### Optional Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image\_prompt | Image | None | Optional input, used for Image-to-Image (Remix) mode |
| image\_prompt\_strength | Float | 0.1 | Active when `image_prompt` is input, adjusts the blend between prompt and image prompt. Higher values make output closer to input image, range is 0.0-1.0 |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | Image | Generated high-resolution image result |

## Usage Examples

Please visit the tutorial below to see corresponding usage examples

* [Flux 1.1 Pro Ultra Image Partner Nodes ComfyUI Official Example Workflow](/tutorials/partner-nodes/black-forest-labs/flux-1-1-pro-ultra-image)

## How It Works

Flux 1.1 \[pro] Ultra mode uses optimized deep learning architecture and efficient GPU acceleration technology to achieve high-resolution image generation without sacrificing speed. When a request is sent to the API, the system parses the prompt, applies appropriate parameters, then computes the image in parallel, finally generating and returning the high-resolution result.

Compared to regular models, Ultra mode particularly focuses on detail preservation and consistency at large scales, ensuring impressive quality even at 4MP high resolution.

## Source Code

\[Node Source Code (Updated on 2025-05-03)]

```python theme={null}
class FluxProUltraImageNode(ComfyNodeABC):
    """
    Generates images synchronously based on prompt and resolution.
    """

    MINIMUM_RATIO = 1 / 4
    MAXIMUM_RATIO = 4 / 1
    MINIMUM_RATIO_STR = "1:4"
    MAXIMUM_RATIO_STR = "4:1"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation",
                    },
                ),
                "prompt_upsampling": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                        "tooltip": "Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result).",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "The random seed used for creating the noise.",
                    },
                ),
                "aspect_ratio": (
                    IO.STRING,
                    {
                        "default": "16:9",
                        "tooltip": "Aspect ratio of image; must be between 1:4 and 4:1.",
                    },
                ),
                "raw": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                        "tooltip": "When True, generate less processed, more natural-looking images.",
                    },
                ),
            },
            "optional": {
                "image_prompt": (IO.IMAGE,),
                "image_prompt_strength": (
                    IO.FLOAT,
                    {
                        "default": 0.1,
                        "min": 0.0,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Blend between the prompt and the image prompt.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    @classmethod
    def VALIDATE_INPUTS(cls, aspect_ratio: str):
        try:
            validate_aspect_ratio(
                aspect_ratio,
                minimum_ratio=cls.MINIMUM_RATIO,
                maximum_ratio=cls.MAXIMUM_RATIO,
                minimum_ratio_str=cls.MINIMUM_RATIO_STR,
                maximum_ratio_str=cls.MAXIMUM_RATIO_STR,
            )
        except Exception as e:
            return str(e)
        return True

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/bfl"

    def api_call(
        self,
        prompt: str,
        aspect_ratio: str,
        prompt_upsampling=False,
        raw=False,
        seed=0,
        image_prompt=None,
        image_prompt_strength=0.1,
        auth_token=None,
        **kwargs,
    ):
        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/bfl/flux-pro-1.1-ultra/generate",
                method=HttpMethod.POST,
                request_model=BFLFluxProUltraGenerateRequest,
                response_model=BFLFluxProGenerateResponse,
            ),
            request=BFLFluxProUltraGenerateRequest(
                prompt=prompt,
                prompt_upsampling=prompt_upsampling,
                seed=seed,
                aspect_ratio=validate_aspect_ratio(
                    aspect_ratio,
                    minimum_ratio=self.MINIMUM_RATIO,
                    maximum_ratio=self.MAXIMUM_RATIO,
                    minimum_ratio_str=self.MINIMUM_RATIO_STR,
                    maximum_ratio_str=self.MAXIMUM_RATIO_STR,
                ),
                raw=raw,
                image_prompt=(
                    image_prompt
                    if image_prompt is None
                    else convert_image_to_base64(image_prompt)
                ),
                image_prompt_strength=(
                    None if image_prompt is None else round(image_prompt_strength, 2)
                ),
            ),
            auth_token=auth_token,
        )
        output_image = handle_bfl_synchronous_operation(operation)
        return (output_image,)
```


# Ideogram V1 - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/ideogram/ideogram-v1

Node for creating precise text rendering images using Ideogram API

<img alt="ComfyUI Native Ideogram V1 Node" />

The Ideogram V1 node allows you to generate images with high-quality text rendering capabilities using Ideogram's text-to-image API.

## Parameter Description

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text prompt describing the content to generate |
| turbo | boolean | False | Whether to use turbo mode (faster but possibly lower quality) |
| aspect\_ratio | select | "1:1" | Image aspect ratio |
| magic\_prompt\_option | select | "AUTO" | Determines whether to use MagicPrompt in generation, options: AUTO, ON, OFF |
| seed | integer | 0 | Random seed value (0-2147483647) |
| negative\_prompt | string | "" | Specifies elements you don't want in the image |
| num\_images | integer | 1 | Number of images to generate (1-8) |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | Generated image result |

## Source Code

\[Node Source Code (Updated on 2025-05-03)]

```python theme={null}
class IdeogramV1(ComfyNodeABC):
    """
    Generates images synchronously using the Ideogram V1 model.

    Images links are available for a limited period of time; if you would like to keep the image, you must download it.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation",
                    },
                ),
                "turbo": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                        "tooltip": "Whether to use turbo mode (faster generation, potentially lower quality)",
                    }
                ),
            },
            "optional": {
                "aspect_ratio": (
                    IO.COMBO,
                    {
                        "options": list(V1_V2_RATIO_MAP.keys()),
                        "default": "1:1",
                        "tooltip": "The aspect ratio for image generation.",
                    },
                ),
                "magic_prompt_option": (
                    IO.COMBO,
                    {
                        "options": ["AUTO", "ON", "OFF"],
                        "default": "AUTO",
                        "tooltip": "Determine if MagicPrompt should be used in generation",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2147483647,
                        "step": 1,
                        "control_after_generate": True,
                        "display": "number",
                    },
                ),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Description of what to exclude from the image",
                    },
                ),
                "num_images": (
                    IO.INT,
                    {"default": 1, "min": 1, "max": 8, "step": 1, "display": "number"},
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/ideogram/v1"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        turbo=False,
        aspect_ratio="1:1",
        magic_prompt_option="AUTO",
        seed=0,
        negative_prompt="",
        num_images=1,
        auth_token=None,
    ):
        # Determine the model based on turbo setting
        aspect_ratio = V1_V2_RATIO_MAP.get(aspect_ratio, None)
        model = "V_1_TURBO" if turbo else "V_1"

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/ideogram/generate",
                method=HttpMethod.POST,
                request_model=IdeogramGenerateRequest,
                response_model=IdeogramGenerateResponse,
            ),
            request=IdeogramGenerateRequest(
                image_request=ImageRequest(
                    prompt=prompt,
                    model=model,
                    num_images=num_images,
                    seed=seed,
                    aspect_ratio=aspect_ratio if aspect_ratio != "ASPECT_1_1" else None,
                    magic_prompt_option=(
                        magic_prompt_option if magic_prompt_option != "AUTO" else None
                    ),
                    negative_prompt=negative_prompt if negative_prompt else None,
                )
            ),
            auth_token=auth_token,
        )

        response = operation.execute()

        if not response.data or len(response.data) == 0:
            raise Exception("No images were generated in the response")

        image_urls = [image_data.url for image_data in response.data if image_data.url]

        if not image_urls:
            raise Exception("No image URLs were generated in the response")

        return (download_and_process_images(image_urls),)
```


# Ideogram V2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/ideogram/ideogram-v2

Node for creating high-quality images and text rendering using Ideogram V2 API

<img alt="ComfyUI Built-in Ideogram V2 Node" />

The Ideogram V2 node allows you to generate more refined images using Ideogram's second-generation AI model, with significant improvements in text rendering, image quality, and overall aesthetics.

## Parameters

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text prompt describing the content to generate |
| turbo | boolean | False | Whether to use turbo mode (faster generation, possibly lower quality) |

### Optional Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| aspect\_ratio | dropdown | "1:1" | Image aspect ratio, effective when resolution is set to "Auto" |
| resolution | dropdown | "Auto" | Output image resolution, if not set to "Auto", it will override the aspect\_ratio setting |
| magic\_prompt\_option | dropdown | "AUTO" | Determines whether to use MagicPrompt feature during generation, options are \["AUTO", "ON", "OFF"] |
| seed | integer | 0 | Random seed value, range 0-2147483647 |
| style\_type | dropdown | "NONE" | Generation style type (V2 only), options are \["AUTO", "GENERAL", "REALISTIC", "DESIGN", "RENDER\_3D", "ANIME"] |
| negative\_prompt | string | "" | Specifies elements you don't want to appear in the image |
| num\_images | integer | 1 | Number of images to generate, range 1-8 |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | Generated image(s) |

## Source Code

\[Node Source Code (Updated on 2025-05-03)]

```python theme={null}

class IdeogramV2(ComfyNodeABC):
    """
    Generates images synchronously using the Ideogram V2 model.

    Images links are available for a limited period of time; if you would like to keep the image, you must download it.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation",
                    },
                ),
                "turbo": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                        "tooltip": "Whether to use turbo mode (faster generation, potentially lower quality)",
                    }
                ),
            },
            "optional": {
                "aspect_ratio": (
                    IO.COMBO,
                    {
                        "options": list(V1_V2_RATIO_MAP.keys()),
                        "default": "1:1",
                        "tooltip": "The aspect ratio for image generation. Ignored if resolution is not set to AUTO.",
                    },
                ),
                "resolution": (
                    IO.COMBO,
                    {
                        "options": list(V1_V1_RES_MAP.keys()),
                        "default": "Auto",
                        "tooltip": "The resolution for image generation. If not set to AUTO, this overrides the aspect_ratio setting.",
                    },
                ),
                "magic_prompt_option": (
                    IO.COMBO,
                    {
                        "options": ["AUTO", "ON", "OFF"],
                        "default": "AUTO",
                        "tooltip": "Determine if MagicPrompt should be used in generation",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2147483647,
                        "step": 1,
                        "control_after_generate": True,
                        "display": "number",
                    },
                ),
                "style_type": (
                    IO.COMBO,
                    {
                        "options": ["AUTO", "GENERAL", "REALISTIC", "DESIGN", "RENDER_3D", "ANIME"],
                        "default": "NONE",
                        "tooltip": "Style type for generation (V2 only)",
                    },
                ),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Description of what to exclude from the image",
                    },
                ),
                "num_images": (
                    IO.INT,
                    {"default": 1, "min": 1, "max": 8, "step": 1, "display": "number"},
                ),
                #"color_palette": (
                #    IO.STRING,
                #    {
                #        "multiline": False,
                #        "default": "",
                #        "tooltip": "Color palette preset name or hex colors with weights",
                #    },
                #),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/ideogram/v2"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        turbo=False,
        aspect_ratio="1:1",
        resolution="Auto",
        magic_prompt_option="AUTO",
        seed=0,
        style_type="NONE",
        negative_prompt="",
        num_images=1,
        color_palette="",
        auth_token=None,
    ):
        aspect_ratio = V1_V2_RATIO_MAP.get(aspect_ratio, None)
        resolution = V1_V1_RES_MAP.get(resolution, None)
        # Determine the model based on turbo setting
        model = "V_2_TURBO" if turbo else "V_2"

        # Handle resolution vs aspect_ratio logic
        # If resolution is not AUTO, it overrides aspect_ratio
        final_resolution = None
        final_aspect_ratio = None

        if resolution != "AUTO":
            final_resolution = resolution
        else:
            final_aspect_ratio = aspect_ratio if aspect_ratio != "ASPECT_1_1" else None

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/ideogram/generate",
                method=HttpMethod.POST,
                request_model=IdeogramGenerateRequest,
                response_model=IdeogramGenerateResponse,
            ),
            request=IdeogramGenerateRequest(
                image_request=ImageRequest(
                    prompt=prompt,
                    model=model,
                    num_images=num_images,
                    seed=seed,
                    aspect_ratio=final_aspect_ratio,
                    resolution=final_resolution,
                    magic_prompt_option=(
                        magic_prompt_option if magic_prompt_option != "AUTO" else None
                    ),
                    style_type=style_type if style_type != "NONE" else None,
                    negative_prompt=negative_prompt if negative_prompt else None,
                    color_palette=color_palette if color_palette else None,
                )
            ),
            auth_token=auth_token,
        )

        response = operation.execute()

        if not response.data or len(response.data) == 0:
            raise Exception("No images were generated in the response")

        image_urls = [image_data.url for image_data in response.data if image_data.url]

        if not image_urls:
            raise Exception("No image URLs were generated in the response")

        return (download_and_process_images(image_urls),)

```


# Luma Image to Image - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/luma/luma-image-to-image

Node for modifying images using Luma AI

<img alt="ComfyUI Built-in Luma Image to Image Node" />

The Luma Image to Image node allows you to modify existing images using Luma AI technology based on text prompts, while preserving certain features and structure of the original image.

## Node Function

This node connects to Luma AI's text-to-image API, enabling users to generate images through detailed text prompts. Luma AI is known for its excellent realism and detail, particularly excelling at generating photorealistic content and artistic style images.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text prompt describing the content to generate |
| model | select | - | Select which generation model to use |
| aspect\_ratio | select | 16:9 | Set the aspect ratio of the output image |
| seed | integer | 0 | Seed value to determine if node should rerun, but actual results don't depend on seed |
| style\_image\_weight | float | 1.0 | Weight of the style image, range 0.02-1.0, only effective when style\_image is provided |

### Optional Parameters

Without the following parameter inputs, the node functions in text-to-image mode

| Parameter | Type | Description |
| - | - | - |
| image\_luma\_ref | LUMA\_REF | Luma reference node connection, influences generation results through input images, can consider up to 4 images |
| style\_image | image | Style reference image, uses only 1 image, influences the style of generated images, adjusted through `style_image_weight` |
| character\_image | image | Adds character features to the generated results, can be a batch of multiple images, up to 4 images |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | The generated image |

## Usage Examples

## How It Works

The Luma Image to Image node analyzes the input image and combines it with text prompts to guide the modification process. It uses Luma AI's generation models to make creative changes to images based on prompts.

Node process:

1. First uploads the input image to ComfyAPI
2. Then sends the image URL with the prompt to Luma API
3. Waits for Luma AI to complete processing
4. Downloads and returns the generated image

The image\_weight parameter controls the degree of influence from the original image - values closer to 0 will preserve more of the original image features, while values closer to 1 allow for more substantial modifications.

## Source Code

\[Node Source Code (Updated on 2025-05-05)]

```python theme={null}

class LumaImageModifyNode(ComfyNodeABC):
    """
    Modifies images synchronously based on prompt and aspect ratio.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE,),
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation",
                    },
                ),
                "image_weight": (
                    IO.FLOAT,
                    {
                        "default": 1.0,
                        "min": 0.02,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Weight of the image; the closer to 0.0, the less the image will be modified.",
                    },
                ),
                "model": ([model.value for model in LumaImageModel],),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {},
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        model: str,
        image: torch.Tensor,
        image_weight: float,
        seed,
        auth_token=None,
        **kwargs,
    ):
        # first, upload image
        download_urls = upload_images_to_comfyapi(
            image, max_images=1, auth_token=auth_token
        )
        image_url = download_urls[0]
        # next, make Luma call with download url provided
        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/luma/generations/image",
                method=HttpMethod.POST,
                request_model=LumaImageGenerationRequest,
                response_model=LumaGeneration,
            ),
            request=LumaImageGenerationRequest(
                prompt=prompt,
                model=model,
                modify_image_ref=LumaModifyImageRef(
                    url=image_url, weight=round(image_weight, 2)
                ),
            ),
            auth_token=auth_token,
        )
        response_api: LumaGeneration = operation.execute()

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/luma/generations/{response_api.id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=LumaGeneration,
            ),
            completed_statuses=[LumaState.completed],
            failed_statuses=[LumaState.failed],
            status_extractor=lambda x: x.state,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        img_response = requests.get(response_poll.assets.image)
        img = process_image_response(img_response)
        return (img,)

```


# Luma Reference - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/luma/luma-reference

Helper node providing reference images for Luma image generation

<img alt="ComfyUI Built-in Luma Reference Node" />

The Luma Reference node allows you to set reference images and weights to guide the creation process of Luma image generation nodes, making the generated images closer to specific features of the reference images.

## Node Function

This node works as a helper tool for Luma generation nodes, allowing users to provide reference images to influence generation results. It enables users to set the weight of reference images to control how much they affect the final result.
Multiple Luma Reference nodes can be chained together, with a maximum of 4 working simultaneously according to API requirements.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | Image | - | Input image used as reference |
| weight | Float | 1.0 | Controls the strength of the reference image's influence (0-1) |

### Output

| Output | Type | Description |
| - | - | - |
| luma\_ref | LUMA\_REF | Reference object containing image and weight |

## Usage Example

<Card title="Luma Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/luma/luma-text-to-image">
  Luma Text to Image Workflow Example
</Card>

## How It Works

The Luma Reference node receives image input and allows setting a weight value. The node doesn't directly generate or modify images but creates a reference object containing image data and weight information, which is then passed to Luma generation nodes.

During the generation process, Luma AI analyzes the features of the reference image and incorporates these features into the generation results based on the set weight. Higher weight values mean the generated image will be closer to the reference image's features, while lower weight values indicate the reference image will only slightly influence the final result.

## Source Code

\[Node Source Code (Updated on 2025-05-03)]

```python theme={null}

class LumaReferenceNode(ComfyNodeABC):
    """
    Holds an image and weight for use with Luma Generate Image node.
    """

    RETURN_TYPES = (LumaIO.LUMA_REF,)
    RETURN_NAMES = ("luma_ref",)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "create_luma_reference"
    CATEGORY = "api node/image/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (
                    IO.IMAGE,
                    {
                        "tooltip": "Image to use as reference.",
                    },
                ),
                "weight": (
                    IO.FLOAT,
                    {
                        "default": 1.0,
                        "min": 0.0,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Weight of image reference.",
                    },
                ),
            },
            "optional": {"luma_ref": (LumaIO.LUMA_REF,)},
        }

    def create_luma_reference(
        self, image: torch.Tensor, weight: float, luma_ref: LumaReferenceChain = None
    ):
        if luma_ref is not None:
            luma_ref = luma_ref.clone()
        else:
            luma_ref = LumaReferenceChain()
        luma_ref.add(LumaReference(image=image, weight=round(weight, 2)))
        return (luma_ref,)

```


# Luma Text to Image - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/luma/luma-text-to-image

A node that converts text descriptions into high-quality images using Luma AI

<img alt="ComfyUI Native Luma Text to Image Node" />

The Luma Text to Image node allows you to create highly realistic and artistic images from text descriptions using Luma AI's advanced image generation capabilities.

## Node Function

This node connects to Luma AI's text-to-image API, enabling users to generate images through detailed text prompts. Luma AI is known for its excellent realism and detail representation, particularly excelling at producing photorealistic content and artistic style images.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | String | "" | Text prompt describing the content to generate |
| model | Select | - | Choose which generation model to use |
| aspect\_ratio | Select | 16:9 | Set the output image's aspect ratio |
| seed | Integer | 0 | Seed value to determine if the node should re-run, but actual results are independent of the seed |
| style\_image\_weight | Float | 1.0 | Style image weight, range 0.0-1.0, only applies when style\_image is provided, higher means stronger style reference |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| image\_luma\_ref | LUMA\_REF | Luma reference node connection to influence generation with input images; up to 4 images |
| style\_image | Image | Style reference image; only 1 image will be used |
| character\_image | Image | Character reference images; can be a batch of multiple, up to 4 images |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | Image | Generated image result |

## Usage Example

<Card title="Luma Text to Image Usage Example" icon="book" href="/tutorials/partner-nodes/luma/luma-text-to-image">
  Detailed guide for Luma Text to Image workflow
</Card>

## How It Works

The Luma Text to Image node analyzes the text prompt provided by the user and creates corresponding images through Luma AI's generation models. This process uses deep learning technology to understand text descriptions and convert them into visual representations. Users can fine-tune the generation process by adjusting various parameters, including resolution, guidance scale, and negative prompts.

Additionally, the node supports using reference images and concept guidance to further influence the generation results, allowing creators to more precisely achieve their creative vision.

## Source Code

\[Node Source Code (Updated on 2025-05-03)]

```python theme={null}

class LumaImageGenerationNode(ComfyNodeABC):
    """
    Generates images synchronously based on prompt and aspect ratio.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation",
                    },
                ),
                "model": ([model.value for model in LumaImageModel],),
                "aspect_ratio": (
                    [ratio.value for ratio in LumaAspectRatio],
                    {
                        "default": LumaAspectRatio.ratio_16_9,
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
                "style_image_weight": (
                    IO.FLOAT,
                    {
                        "default": 1.0,
                        "min": 0.0,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Weight of style image. Ignored if no style_image provided.",
                    },
                ),
            },
            "optional": {
                "image_luma_ref": (
                    LumaIO.LUMA_REF,
                    {
                        "tooltip": "Luma Reference node connection to influence generation with input images; up to 4 images can be considered."
                    },
                ),
                "style_image": (
                    IO.IMAGE,
                    {"tooltip": "Style reference image; only 1 image will be used."},
                ),
                "character_image": (
                    IO.IMAGE,
                    {
                        "tooltip": "Character reference images; can be a batch of multiple, up to 4 images can be considered."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        model: str,
        aspect_ratio: str,
        seed,
        style_image_weight: float,
        image_luma_ref: LumaReferenceChain = None,
        style_image: torch.Tensor = None,
        character_image: torch.Tensor = None,
        auth_token=None,
        **kwargs,
    ):
        # handle image_luma_ref
        api_image_ref = None
        if image_luma_ref is not None:
            api_image_ref = self._convert_luma_refs(
                image_luma_ref, max_refs=4, auth_token=auth_token
            )
        # handle style_luma_ref
        api_style_ref = None
        if style_image is not None:
            api_style_ref = self._convert_style_image(
                style_image, weight=style_image_weight, auth_token=auth_token
            )
        # handle character_ref images
        character_ref = None
        if character_image is not None:
            download_urls = upload_images_to_comfyapi(
                character_image, max_images=4, auth_token=auth_token
            )
            character_ref = LumaCharacterRef(
                identity0=LumaImageIdentity(images=download_urls)
            )

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/luma/generations/image",
                method=HttpMethod.POST,
                request_model=LumaImageGenerationRequest,
                response_model=LumaGeneration,
            ),
            request=LumaImageGenerationRequest(
                prompt=prompt,
                model=model,
                aspect_ratio=aspect_ratio,
                image_ref=api_image_ref,
                style_ref=api_style_ref,
                character_ref=character_ref,
            ),
            auth_token=auth_token,
        )
        response_api: LumaGeneration = operation.execute()

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/luma/generations/{response_api.id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=LumaGeneration,
            ),
            completed_statuses=[LumaState.completed],
            failed_statuses=[LumaState.failed],
            status_extractor=lambda x: x.state,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        img_response = requests.get(response_poll.assets.image)
        img = process_image_response(img_response)
        return (img,)

    def _convert_luma_refs(
        self, luma_ref: LumaReferenceChain, max_refs: int, auth_token=None
    ):
        luma_urls = []
        ref_count = 0
        for ref in luma_ref.refs:
            download_urls = upload_images_to_comfyapi(
                ref.image, max_images=1, auth_token=auth_token
            )
            luma_urls.append(download_urls[0])
            ref_count += 1
            if ref_count >= max_refs:
                break
        return luma_ref.create_api_model(download_urls=luma_urls, max_refs=max_refs)

    def _convert_style_image(
        self, style_image: torch.Tensor, weight: float, auth_token=None
    ):
        chain = LumaReferenceChain(
            first_ref=LumaReference(image=style_image, weight=weight)
        )
        return self._convert_luma_refs(chain, max_refs=1, auth_token=auth_token)

```


# OpenAI DALL·E 2 - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/openai/openai-dalle2

Node for generating images using OpenAI's DALL·E 2 model

<img alt="ComfyUI Native Stability AI Stable Image Ultra Node" />

The OpenAI DALL·E 2 node allows you to use OpenAI's DALL·E 2 API to generate creative images from text descriptions.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text prompt for DALL·E to generate images, supports multi-line input |
| seed | integer | 0 | The result is not actually related to the seed, this parameter only determines whether to re-execute |
| size | select | "1024x1024" | Output image size, options: 256x256, 512x512, 1024x1024 |
| n | integer | 1 | Number of images to generate, range 1-8 |

### Optional Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | image | None | Optional reference image for image editing |
| mask | mask | None | Optional mask for inpainting (white areas will be replaced) |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | Generated image(s) |

## Features

* Basic function: Generate images from text prompts
* Image editing: When both image and mask parameters are provided, performs image editing (white masked areas will be replaced)

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class OpenAIDalle2(ComfyNodeABC):
    """
    Generates images synchronously via OpenAI's DALL·E 2 endpoint.

    Uses the proxy at /proxy/openai/images/generations. Returned URLs are short‑lived,
    so download or cache results if you need to keep them.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text prompt for DALL·E",
                    },
                ),
            },
            "optional": {
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2**31 - 1,
                        "step": 1,
                        "display": "number",
                        "control_after_generate": True,
                        "tooltip": "not implemented yet in backend",
                    },
                ),
                "size": (
                    IO.COMBO,
                    {
                        "options": ["256x256", "512x512", "1024x1024"],
                        "default": "1024x1024",
                        "tooltip": "Image size",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 8,
                        "step": 1,
                        "display": "number",
                        "tooltip": "How many images to generate",
                    },
                ),
                "image": (
                    IO.IMAGE,
                    {
                        "default": None,
                        "tooltip": "Optional reference image for image editing.",
                    },
                ),
                "mask": (
                    IO.MASK,
                    {
                        "default": None,
                        "tooltip": "Optional mask for inpainting (white areas will be replaced)",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/openai"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        seed=0,
        image=None,
        mask=None,
        n=1,
        size="1024x1024",
        auth_token=None,
    ):
        model = "dall-e-2"
        path = "/proxy/openai/images/generations"
        content_type = "application/json"
        request_class = OpenAIImageGenerationRequest
        img_binary = None

        if image is not None and mask is not None:
            path = "/proxy/openai/images/edits"
            content_type = "multipart/form-data"
            request_class = OpenAIImageEditRequest

            input_tensor = image.squeeze().cpu()
            height, width, channels = input_tensor.shape
            rgba_tensor = torch.ones(height, width, 4, device="cpu")
            rgba_tensor[:, :, :channels] = input_tensor

            if mask.shape[1:] != image.shape[1:-1]:
                raise Exception("Mask and Image must be the same size")
            rgba_tensor[:, :, 3] = 1 - mask.squeeze().cpu()

            rgba_tensor = downscale_image_tensor(rgba_tensor.unsqueeze(0)).squeeze()

            image_np = (rgba_tensor.numpy() * 255).astype(np.uint8)
            img = Image.fromarray(image_np)
            img_byte_arr = io.BytesIO()
            img.save(img_byte_arr, format="PNG")
            img_byte_arr.seek(0)
            img_binary = img_byte_arr  # .getvalue()
            img_binary.name = "image.png"
        elif image is not None or mask is not None:
            raise Exception("Dall-E 2 image editing requires an image AND a mask")

        # Build the operation
        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=path,
                method=HttpMethod.POST,
                request_model=request_class,
                response_model=OpenAIImageGenerationResponse,
            ),
            request=request_class(
                model=model,
                prompt=prompt,
                n=n,
                size=size,
                seed=seed,
            ),
            files=(
                {
                    "image": img_binary,
                }
                if img_binary
                else None
            ),
            content_type=content_type,
            auth_token=auth_token,
        )

        response = operation.execute()

        img_tensor = validate_and_cast_response(response)
        return (img_tensor,)
```


# OpenAI DALL·E 3 - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/openai/openai-dalle3

Node for generating high-quality images using OpenAI's DALL·E 3 model

<img alt="ComfyUI Native OpenAI DALL·E 3 Node" />

This node connects to OpenAI's DALL·E 3 API, allowing users to generate high-quality images through detailed text prompts. DALL·E 3 is OpenAI's image generation model that offers significantly improved image quality, more accurate prompt understanding, and better detail rendering compared to previous versions.

## Parameters

### Input Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Detailed text prompt describing what to generate |
| seed | integer | 0 | Final result is not related to seed, this parameter only determines whether to re-execute |
| quality | selection | "standard" | Image quality, options: "standard" or "hd" |
| style | selection | "natural" | Visual style, options: "natural" or "vivid". "Vivid" makes the model tend to create more surreal and dramatic images, while "natural" generates more realistic, less surreal images |
| size | selection | "1024x1024" | Output image size, options: "1024x1024", "1024x1792", or "1792x1024" |

### Output Parameters

| Output | Type | Description |
| - | - | - |
| IMAGE | image | The generated image result |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class OpenAIDalle3(ComfyNodeABC):
    """
    Generates images synchronously via OpenAI's DALL·E 3 endpoint.

    Uses the proxy at /proxy/openai/images/generations. Returned URLs are short‑lived,
    so download or cache results if you need to keep them.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text prompt for DALL·E",
                    },
                ),
            },
            "optional": {
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2**31 - 1,
                        "step": 1,
                        "display": "number",
                        "control_after_generate": True,
                        "tooltip": "not implemented yet in backend",
                    },
                ),
                "quality": (
                    IO.COMBO,
                    {
                        "options": ["standard", "hd"],
                        "default": "standard",
                        "tooltip": "Image quality",
                    },
                ),
                "style": (
                    IO.COMBO,
                    {
                        "options": ["natural", "vivid"],
                        "default": "natural",
                        "tooltip": "Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images.",
                    },
                ),
                "size": (
                    IO.COMBO,
                    {
                        "options": ["1024x1024", "1024x1792", "1792x1024"],
                        "default": "1024x1024",
                        "tooltip": "Image size",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/openai"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        seed=0,
        style="natural",
        quality="standard",
        size="1024x1024",
        auth_token=None,
    ):
        model = "dall-e-3"

        # build the operation
        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/openai/images/generations",
                method=HttpMethod.POST,
                request_model=OpenAIImageGenerationRequest,
                response_model=OpenAIImageGenerationResponse,
            ),
            request=OpenAIImageGenerationRequest(
                model=model,
                prompt=prompt,
                quality=quality,
                size=size,
                style=style,
                seed=seed,
            ),
            auth_token=auth_token,
        )

        response = operation.execute()

        img_tensor = validate_and_cast_response(response)
        return (img_tensor,)
```


# OpenAI GPT Image 1 - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/openai/openai-gpt-image1

Node for generating images using OpenAI's GPT-4 Vision model

<img alt="ComfyUI Native OpenAI GPT Image 1 Node" />

This node connects to OpenAI's GPT Image 1 API, allowing users to generate images through detailed text prompts. Unlike traditional DALL·E models, GPT Image 1 leverages GPT-4's language understanding capabilities to handle more complex prompts and generate images that better match user intent.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text prompt describing what to generate |
| quality | selection | "low" | Image quality level, options: "low", "medium", "high" |
| size | selection | "auto" | Output image size, options: "auto", "1024x1024", "1024x1536", "1536x1024" |

### Image Editing Parameters

| Parameter | Type | Description |
| - | - | - |
| image | image | Input image for editing, supports multiple images |
| mask | mask | Optional mask to specify areas to modify (single image only) |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| background | selection | Background options: "opaque" or "transparent" |
| seed | integer | Random seed (not yet implemented in backend) |
| n | integer | Number of images to generate, range 1-8 |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | Generated image result |

## How It Works

The OpenAI GPT Image 1 node combines GPT-4's language understanding with image generation. It analyzes the text prompt to understand its meaning and intent, then generates matching images.

In image editing mode, the node can modify existing images. Using a mask allows precise control over which areas to change. Note that mask input only works with single image input.

Users can control the output by adjusting parameters like quality level, size, background handling, and number of generations.

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class OpenAIGPTImage1(ComfyNodeABC):
    """
    Generates images synchronously via OpenAI's GPT Image 1 endpoint.

    Uses the proxy at /proxy/openai/images/generations. Returned URLs are short‑lived,
    so download or cache results if you need to keep them.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text prompt for GPT Image 1",
                    },
                ),
            },
            "optional": {
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2**31 - 1,
                        "step": 1,
                        "display": "number",
                        "control_after_generate": True,
                        "tooltip": "not implemented yet in backend",
                    },
                ),
                "quality": (
                    IO.COMBO,
                    {
                        "options": ["low", "medium", "high"],
                        "default": "low",
                        "tooltip": "Image quality, affects cost and generation time.",
                    },
                ),
                "background": (
                    IO.COMBO,
                    {
                        "options": ["opaque", "transparent"],
                        "default": "opaque",
                        "tooltip": "Return image with or without background",
                    },
                ),
                "size": (
                    IO.COMBO,
                    {
                        "options": ["auto", "1024x1024", "1024x1536", "1536x1024"],
                        "default": "auto",
                        "tooltip": "Image size",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 8,
                        "step": 1,
                        "display": "number",
                        "tooltip": "How many images to generate",
                    },
                ),
                "image": (
                    IO.IMAGE,
                    {
                        "default": None,
                        "tooltip": "Optional reference image for image editing.",
                    },
                ),
                "mask": (
                    IO.MASK,
                    {
                        "default": None,
                        "tooltip": "Optional mask for inpainting (white areas will be replaced)",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/openai"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        seed=0,
        quality="low",
        background="opaque",
        image=None,
        mask=None,
        n=1,
        size="1024x1024",
        auth_token=None,
    ):
        model = "gpt-image-1"
        path = "/proxy/openai/images/generations"
        content_type="application/json"
        request_class = OpenAIImageGenerationRequest
        img_binaries = []
        mask_binary = None
        files = []

        if image is not None:
            path = "/proxy/openai/images/edits"
            request_class = OpenAIImageEditRequest
            content_type ="multipart/form-data"

            batch_size = image.shape[0]

            for i in range(batch_size):
                single_image = image[i : i + 1]
                scaled_image = downscale_image_tensor(single_image).squeeze()

                image_np = (scaled_image.numpy() * 255).astype(np.uint8)
                img = Image.fromarray(image_np)
                img_byte_arr = io.BytesIO()
                img.save(img_byte_arr, format="PNG")
                img_byte_arr.seek(0)
                img_binary = img_byte_arr
                img_binary.name = f"image_{i}.png"

                img_binaries.append(img_binary)
                if batch_size == 1:
                    files.append(("image", img_binary))
                else:
                    files.append(("image[]", img_binary))

        if mask is not None:
            if image.shape[0] != 1:
                raise Exception("Cannot use a mask with multiple image")
            if image is None:
                raise Exception("Cannot use a mask without an input image")
            if mask.shape[1:] != image.shape[1:-1]:
                raise Exception("Mask and Image must be the same size")
            batch, height, width = mask.shape
            rgba_mask = torch.zeros(height, width, 4, device="cpu")
            rgba_mask[:, :, 3] = 1 - mask.squeeze().cpu()

            scaled_mask = downscale_image_tensor(rgba_mask.unsqueeze(0)).squeeze()

            mask_np = (scaled_mask.numpy() * 255).astype(np.uint8)
            mask_img = Image.fromarray(mask_np)
            mask_img_byte_arr = io.BytesIO()
            mask_img.save(mask_img_byte_arr, format="PNG")
            mask_img_byte_arr.seek(0)
            mask_binary = mask_img_byte_arr
            mask_binary.name = "mask.png"
            files.append(("mask", mask_binary))

        # Build the operation
        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=path,
                method=HttpMethod.POST,
                request_model=request_class,
                response_model=OpenAIImageGenerationResponse,
            ),
            request=request_class(
                model=model,
                prompt=prompt,
                quality=quality,
                background=background,
                n=n,
                seed=seed,
                size=size,
            ),
            files=files if files else None,
            content_type=content_type,
            auth_token=auth_token,
        )

        response = operation.execute()

        img_tensor = validate_and_cast_response(response)
        return (img_tensor,)
```


# Recraft Color RGB - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-color-rgb

Helper node for defining color controls in Recraft image generation

<img alt="ComfyUI Native Recraft Color RGB Node" />

The Recraft Color RGB node lets you define precise RGB color values to control colors in Recraft image generation.

## Node Function

This node creates a color configuration object that connects to the Recraft Controls node to specify colors used in generated images.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| r | integer | 0 | Red channel (0-255) |
| g | integer | 0 | Green channel (0-255) |
| b | integer | 0 | Blue channel (0-255) |

### Output

| Output | Type | Description |
| - | - | - |
| recraft\_color | Recraft Color | Color config object to connect to Recraft Controls |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftColorRGBNode:
    """
    Create Recraft Color by choosing specific RGB values.
    """

    RETURN_TYPES = (RecraftIO.COLOR,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    RETURN_NAMES = ("recraft_color",)
    FUNCTION = "create_color"
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "r": (IO.INT, {
                    "default": 0,
                    "min": 0,
                    "max": 255,
                    "tooltip": "Red value of color."
                }),
                "g": (IO.INT, {
                    "default": 0,
                    "min": 0,
                    "max": 255,
                    "tooltip": "Green value of color."
                }),
                "b": (IO.INT, {
                    "default": 0,
                    "min": 0,
                    "max": 255,
                    "tooltip": "Blue value of color."
                }),
            },
            "optional": {
                "recraft_color": (RecraftIO.COLOR,),
            }
        }

    def create_color(self, r: int, g: int, b: int, recraft_color: RecraftColorChain=None):
        recraft_color = recraft_color.clone() if recraft_color else RecraftColorChain()
        recraft_color.add(RecraftColor(r, g, b))
        return (recraft_color, )

```


# Recraft Controls - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-controls

Node providing advanced control parameters for Recraft image generation

<img alt="ComfyUI Native Recraft Controls Node" />

The Recraft Controls node lets you define control parameters (like colors and background colors) to guide Recraft's image generation process. This node combines multiple control inputs into a unified control object.

## Parameters

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| colors | Recraft Color | Color controls for image generation |
| background\_color | Recraft Color | Background color control |

### Output

| Output | Type | Description |
| - | - | - |
| recraft\_controls | Recraft Controls | Control config object for Recraft generation nodes |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## How It Works

Node process:

1. Collects input control parameters (colors and background\_color)
2. Combines these parameters into a structured control object
3. Outputs this control object for connecting to Recraft generation nodes

When connected to Recraft generation nodes, these control parameters influence the AI generation process. The AI considers multiple factors beyond just the text prompt's semantic content. If color inputs are configured, the AI will try to use these colors appropriately in the generated image.

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftControlsNode:
    """
    Create Recraft Controls for customizing Recraft generation.
    """

    RETURN_TYPES = (RecraftIO.CONTROLS,)
    RETURN_NAMES = ("recraft_controls",)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "create_controls"
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
            },
            "optional": {
                "colors": (RecraftIO.COLOR,),
                "background_color": (RecraftIO.COLOR,),
            }
        }

    def create_controls(self, colors: RecraftColorChain=None, background_color: RecraftColorChain=None):
        return (RecraftControls(colors=colors, background_color=background_color), )

```


# Recraft Creative Upscale - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-creative-upscale

A Recraft Partner node that uses AI to creatively enhance image details and resolution

<img alt="ComfyUI Native Recraft Creative Upscale Node" />

The Recraft Creative Upscale node uses Recraft's API to increase image resolution while creatively enhancing and enriching image details.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | image | - | Input image to be creatively upscaled |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | High-resolution image after creative upscaling |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftCreativeUpscaleNode(RecraftCrispUpscaleNode):
    """
    Upscale image synchronously.
    Enhances a given raster image using ‘creative upscale’ tool, boosting resolution with a focus on refining small details and faces.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    RECRAFT_PATH = "/proxy/recraft/images/creativeUpscale"
```


# Recraft Crisp Upscale - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-crisp-upscale

A Recraft Partner node that enhances image clarity and resolution using AI

<img alt="ComfyUI Native Recraft Crisp Upscale Node" />

The Recraft Crisp Upscale node uses Recraft's API to improve image resolution and clarity.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | image | - | Input image to be upscaled |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | Upscaled and enhanced output image |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftCrispUpscaleNode:
    """
    Upscale image synchronously.
    Enhances a given raster image using ‘crisp upscale’ tool, increasing image resolution, making the image sharper and cleaner.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    RECRAFT_PATH = "/proxy/recraft/images/crispUpscale"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
            },
            "optional": {
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        auth_token=None,
        **kwargs,
    ):
        images = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                path=self.RECRAFT_PATH,
                auth_token=auth_token,
            )
            images.append(torch.cat([bytesio_to_image_tensor(x) for x in sub_bytes], dim=0))
            pbar.update(1)

        images_tensor = torch.cat(images, dim=0)
        return (images_tensor,)
```


# Recraft Image Inpainting - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-image-inpainting

Selectively modify image regions using Recraft API

<img alt="ComfyUI Native Recraft Image Inpainting Node" />

The Recraft Image Inpainting node lets you modify specific areas of an image while keeping the rest unchanged. By providing an image, mask and text prompt, you can generate new content to fill the selected areas.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | image | - | Input image to modify |
| mask | mask | - | Black and white mask defining areas to change |
| prompt | string | "" | Text describing what to generate in masked area |
| n | integer | 1 | Number of results to generate (1-6) |
| seed | integer | 0 | Random seed value |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| recraft\_style | Recraft Style | Style settings for generated content |
| negative\_prompt | string | Elements to avoid in generated content |
| recraft\_controls | Recraft Controls | Additional controls like colors |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | Modified image result |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftImageInpaintingNode:
    """
    Modify image based on prompt and mask.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
                "mask": (IO.MASK, ),
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation.",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 6,
                        "tooltip": "The number of images to generate.",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "recraft_style": (RecraftIO.STYLEV3,),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        mask: torch.Tensor,
        prompt: str,
        n: int,
        seed,
        auth_token=None,
        recraft_style: RecraftStyle = None,
        negative_prompt: str = None,
        **kwargs,
    ):
        default_style = RecraftStyle(RecraftStyleV3.realistic_image)
        if recraft_style is None:
            recraft_style = default_style

        if not negative_prompt:
            negative_prompt = None

        request = RecraftImageGenerationRequest(
            prompt=prompt,
            negative_prompt=negative_prompt,
            model=RecraftModel.recraftv3,
            n=n,
            style=recraft_style.style,
            substyle=recraft_style.substyle,
            style_id=recraft_style.style_id,
            random_seed=seed,
        )

        # prepare mask tensor
        _, H, W, _ = image.shape
        mask = mask.unsqueeze(-1)
        mask = mask.movedim(-1,1)
        mask = common_upscale(mask, width=W, height=H, upscale_method="nearest-exact", crop="disabled")
        mask = mask.movedim(1,-1)
        mask = (mask > 0.5).float()

        images = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                mask=mask[i:i+1],
                path="/proxy/recraft/images/inpaint",
                request=request,
                auth_token=auth_token,
            )
            images.append(torch.cat([bytesio_to_image_tensor(x) for x in sub_bytes], dim=0))
            pbar.update(1)

        images_tensor = torch.cat(images, dim=0)
        return (images_tensor, )
```


# Recraft Image to Image - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-image-to-image

A Recraft Partner node that generates new images based on text prompts and reference images

<img alt="ComfyUI Native Recraft Image to Image Node" />

The Recraft Image to Image node uses Recraft's API to generate new images based on a reference image and text prompts.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | image | - | Reference image input |
| prompt | string | "" | Text description for the generated image |
| n | integer | 1 | Number of images to generate (1-6) |
| seed | integer | 0 | Random seed value |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| recraft\_style | Recraft Style | Style settings for generated images |
| negative\_prompt | string | Elements to avoid in generated images |
| recraft\_controls | Recraft Controls | Additional controls like colors |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | Generated image result |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class RecraftImageToImageNode:
    """
    Modify image based on prompt and strength.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation.",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 6,
                        "tooltip": "The number of images to generate.",
                    },
                ),
                "strength": (
                    IO.FLOAT,
                    {
                        "default": 0.5,
                        "min": 0.0,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Defines the difference with the original image, should lie in [0, 1], where 0 means almost identical, and 1 means miserable similarity."
                    }
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "recraft_style": (RecraftIO.STYLEV3,),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
                "recraft_controls": (
                    RecraftIO.CONTROLS,
                    {
                        "tooltip": "Optional additional controls over the generation via the Recraft Controls node."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        prompt: str,
        n: int,
        strength: float,
        seed,
        auth_token=None,
        recraft_style: RecraftStyle = None,
        negative_prompt: str = None,
        recraft_controls: RecraftControls = None,
        **kwargs,
    ):
        default_style = RecraftStyle(RecraftStyleV3.realistic_image)
        if recraft_style is None:
            recraft_style = default_style

        controls_api = None
        if recraft_controls:
            controls_api = recraft_controls.create_api_model()

        if not negative_prompt:
            negative_prompt = None

        request = RecraftImageGenerationRequest(
            prompt=prompt,
            negative_prompt=negative_prompt,
            model=RecraftModel.recraftv3,
            n=n,
            strength=round(strength, 2),
            style=recraft_style.style,
            substyle=recraft_style.substyle,
            style_id=recraft_style.style_id,
            controls=controls_api,
            random_seed=seed,
        )

        images = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                path="/proxy/recraft/images/imageToImage",
                request=request,
                auth_token=auth_token,
            )
            images.append(torch.cat([bytesio_to_image_tensor(x) for x in sub_bytes], dim=0))
            pbar.update(1)

        images_tensor = torch.cat(images, dim=0)
        return (images_tensor, )
```


# Recraft Remove Background - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-remove-background

A Recraft Partner node that automatically removes image backgrounds and creates transparent alpha channels

<img alt="ComfyUI Native Recraft Remove Background Node" />

The Recraft Remove Background node uses Recraft's API to intelligently detect and remove image backgrounds, creating images with transparent backgrounds and corresponding alpha masks.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | image | - | Input image to remove background from |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | Image with background removed (with alpha channel) |
| MASK | mask | Mask of the main subject (white areas are preserved) |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftRemoveBackgroundNode:
    """
    Remove background from image, and return processed image and mask.
    """

    RETURN_TYPES = (IO.IMAGE, IO.MASK)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
            },
            "optional": {
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        auth_token=None,
        **kwargs,
    ):
        images = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                path="/proxy/recraft/images/removeBackground",
                auth_token=auth_token,
            )
            images.append(torch.cat([bytesio_to_image_tensor(x) for x in sub_bytes], dim=0))
            pbar.update(1)

        images_tensor = torch.cat(images, dim=0)
        # use alpha channel as masks, in B,H,W format
        masks_tensor = images_tensor[:,:,:,-1:].squeeze(-1)
        return (images_tensor, masks_tensor)

```


# Recraft Replace Background - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-replace-background

A Recraft Partner node that automatically detects foreground subjects and replaces backgrounds

<img alt="ComfyUI Native Recraft Replace Background Node" />

The Recraft Replace Background node uses Recraft's API to intelligently detect subjects in images and generate new backgrounds based on text prompts.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | image | - | Input image with subject to preserve |
| prompt | string | "" | Text prompt for background generation |
| n | integer | 1 | Number of images to generate (1-6) |
| seed | integer | 0 | Random seed value for node re-runs |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| recraft\_style | Recraft Style | Style settings for background generation |
| negative\_prompt | string | Text describing elements to avoid |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | Final image with replaced background |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class RecraftReplaceBackgroundNode:
    """
    Replace background on image, based on provided prompt.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation.",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 6,
                        "tooltip": "The number of images to generate.",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "recraft_style": (RecraftIO.STYLEV3,),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        prompt: str,
        n: int,
        seed,
        auth_token=None,
        recraft_style: RecraftStyle = None,
        negative_prompt: str = None,
        **kwargs,
    ):
        default_style = RecraftStyle(RecraftStyleV3.realistic_image)
        if recraft_style is None:
            recraft_style = default_style

        if not negative_prompt:
            negative_prompt = None

        request = RecraftImageGenerationRequest(
            prompt=prompt,
            negative_prompt=negative_prompt,
            model=RecraftModel.recraftv3,
            n=n,
            style=recraft_style.style,
            substyle=recraft_style.substyle,
            style_id=recraft_style.style_id,
        )

        images = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                path="/proxy/recraft/images/replaceBackground",
                request=request,
                auth_token=auth_token,
            )
            images.append(torch.cat([bytesio_to_image_tensor(x) for x in sub_bytes], dim=0))
            pbar.update(1)

        images_tensor = torch.cat(images, dim=0)
        return (images_tensor, )

```


# Recraft Style - Digital Illustration - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-style-digital-illustration

A helper node for setting digital illustration style in Recraft image generation

<img alt="ComfyUI Native Recraft Style Digital Illustration Node" />

This node creates a style configuration object that guides Recraft's image generation process towards a digital illustration look.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| substyle | select | None | Specific substyle of digital illustration |

### Output

| Output | Type | Description |
| - | - | - |
| recraft\_style | Recraft Style | Style config object to connect to Recraft generation nodes |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftStyleV3DigitalIllustrationNode(RecraftStyleV3RealisticImageNode):
    """
    Select digital_illustration style and optional substyle.
    """

    RECRAFT_STYLE = RecraftStyleV3.digital_illustration

```


# AdjustBrightness - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AdjustBrightness

The Adjust Brightness node changes how bright an image looks.

The Adjust Brightness node changes how bright an image looks. It multiplies the image's color values by a `factor` and keeps the results within the valid 0.0 to 1.0 range. A factor of 1.0 leaves the image unchanged, values below 1.0 make it darker, and values above 1.0 make it brighter.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to adjust. Accepts a single image or a batch of images. | IMAGE | Yes | - |
| `factor` | Brightness factor. 1.0 = no change, \<1.0 = darker, >1.0 = brighter. (default: 1.0) | FLOAT | No | 0.0 - 2.0 |

Note: If the input image has an alpha channel (RGBA), only the color channels are adjusted. The alpha channel is copied from the input unchanged because it stores transparency, not color.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The output image with adjusted brightness. If the input has an alpha channel, the alpha values remain unchanged. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AdjustBrightness/en.md)

***

**Source fingerprint (SHA-256):** `64c1499d16deb5922fa63538182cd227e8f2ba9ded5962064ce9f228a0f4a163`


# AdjustContrast - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AdjustContrast

The Adjust Contrast node adjusts the contrast of an input image by scaling the difference between light and dark areas around the midpoint of the color range.

The Adjust Contrast node adjusts the contrast of an input image by scaling the difference between light and dark areas around the midpoint of the color range. A factor of 1.0 leaves the image unchanged, values below 1.0 reduce contrast, and values above 1.0 increase contrast.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to have its contrast adjusted. | IMAGE | Yes | - |
| `factor` | Contrast factor. 1.0 = no change, \<1.0 = less contrast, >1.0 = more contrast. (default: 1.0) | FLOAT | No | 0.0 - 2.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resulting image with adjusted contrast. Pixel values are clamped to the 0.0–1.0 range. If the input image has an alpha channel, that channel is preserved unchanged. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AdjustContrast/en.md)

***

**Source fingerprint (SHA-256):** `489f840cc3d98339a5cf7b55e9179c60878c58b2f992740796c7d49642e05932`


# AudioAdjustVolume - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioAdjustVolume

The AudioAdjustVolume node modifies the loudness of audio by applying volume adjustments in decibels (dB).

The AudioAdjustVolume node modifies the loudness of audio by applying volume adjustments in decibels (dB). It takes an audio input and applies a gain factor based on the specified volume level, where positive values increase volume and negative values decrease it. The node returns the modified audio with the same sample rate as the original.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio input to be processed | AUDIO | Yes | - |
| `volume` | Volume adjustment in decibels (dB). 0 = no change, +6 = double, -6 = half, etc (default: 1) | INT | Yes | -100 to 100 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The processed audio with adjusted volume level | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioAdjustVolume/en.md)

***

**Source fingerprint (SHA-256):** `8c19625104901a0c57021b1a775fdf287c8bd0fb1fd535809e1983b1949ca752`


# AudioConcat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioConcat

The AudioConcat node combines two audio inputs by joining them together.

The AudioConcat node combines two audio inputs by joining them together. It takes two audio inputs and connects them in the order you specify, either placing the second audio before or after the first audio. The node automatically handles different audio formats by converting mono audio to stereo and matching sample rates between the two inputs.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio1` | The first audio input to be concatenated | AUDIO | Yes | - |
| `audio2` | The second audio input to be concatenated | AUDIO | Yes | - |
| `direction` | Whether to append audio2 after or before audio1 (default: "after") | COMBO | Yes | `"after"`<br />`"before"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `AUDIO` | The combined audio containing both input audio files joined together | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioConcat/en.md)

***

**Source fingerprint (SHA-256):** `faccc3d42e9c6927deadb7d5f7fe9e5bbbf08e4e9a3d636f42a2b9f995eec8c1`


# AudioEqualizer3Band - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioEqualizer3Band

The Audio Equalizer (3-Band) node allows you to adjust the bass, mid, and treble frequencies of an audio waveform.

The Audio Equalizer (3-Band) node allows you to adjust the bass, mid, and treble frequencies of an audio waveform. It applies three separate filters: a low shelf for bass, a peaking filter for mids, and a high shelf for treble. Each band can be independently controlled with gain, frequency, and bandwidth settings.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The input audio data containing the waveform and sample rate. | AUDIO | Yes | - |
| `low_gain_dB` | Gain for Low frequencies (Bass). Positive values boost, negative values cut. (default: 0.0) | FLOAT | No | -24.0 to 24.0 |
| `low_freq` | Cutoff frequency for Low shelf filter in Hertz (Hz). (default: 100) | INT | No | 20 to 500 |
| `mid_gain_dB` | Gain for Mid frequencies. Positive values boost, negative values cut. (default: 0.0) | FLOAT | No | -24.0 to 24.0 |
| `mid_freq` | Center frequency for the Mid peaking filter in Hertz (Hz). (default: 1000) | INT | No | 200 to 4000 |
| `mid_q` | Q factor (bandwidth) for the Mid peaking filter. Lower values create a wider band, higher values create a narrower band. (default: 0.707) | FLOAT | No | 0.1 to 10.0 |
| `high_gain_dB` | Gain for High frequencies (Treble). Positive values boost, negative values cut. (default: 0.0) | FLOAT | No | -24.0 to 24.0 |
| `high_freq` | Cutoff frequency for High shelf filter in Hertz (Hz). (default: 5000) | INT | No | 1000 to 15000 |

**Note:** The `low_gain_dB`, `mid_gain_dB`, and `high_gain_dB` parameters are only applied when their value is not zero. If a gain is set to 0.0, the corresponding filter stage is skipped.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The processed audio data with the equalization applied, containing the modified waveform and the original sample rate. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioEqualizer3Band/en.md)

***

**Source fingerprint (SHA-256):** `be3a0981d8285885cb465e82717c3f56c9d301d55708962f9a9dd5b2c400ec81`


# AudioMerge - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioMerge

The AudioMerge node combines two audio tracks by overlaying their waveforms.

The AudioMerge node combines two audio tracks by overlaying their waveforms. It automatically matches the sample rates of both audio inputs and adjusts their lengths to be equal before merging. The node provides several mathematical methods for combining the audio signals and ensures the output remains within acceptable volume levels.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio1` | First audio input to merge | AUDIO | Yes | - |
| `audio2` | Second audio input to merge | AUDIO | Yes | - |
| `merge_method` | The method used to combine the audio waveforms. | COMBO | Yes | `"add"`<br />`"mean"`<br />`"subtract"`<br />`"multiply"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `AUDIO` | The merged audio output containing the combined waveform and sample rate | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioMerge/en.md)

***

**Source fingerprint (SHA-256):** `3bb8c223e9a5155b5e60f901e8653c6654336a10a56d25ba7a3c5e8f5382ad27`


# CLIPAttentionMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPAttentionMultiply

The CLIPAttentionMultiply node allows you to adjust the attention mechanism in CLIP models by applying multiplication factors to different components of the self-attention layers.

The CLIPAttentionMultiply node allows you to adjust the attention mechanism in CLIP models by applying multiplication factors to different components of the self-attention layers. It works by modifying the query, key, value, and output projection weights and biases in the CLIP model's attention mechanism. This experimental node creates a modified copy of the input CLIP model with the specified scaling factors applied.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model to modify | CLIP | Yes | - |
| `q` | Multiplication factor for query projection weights and biases (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 |
| `k` | Multiplication factor for key projection weights and biases (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 |
| `v` | Multiplication factor for value projection weights and biases (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 |
| `out` | Multiplication factor for output projection weights and biases (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CLIP` | Returns a modified CLIP model with the specified attention scaling factors applied | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPAttentionMultiply/en.md)

***

**Source fingerprint (SHA-256):** `1f5c437cb4a372dfd69ad3c10e2b8cfc68821e0fe82dcf37df5e6fd64aa0b436`


# ConditioningAverage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningAverage

The ConditioningAverage node is used to blend two different sets of conditioning (such as text prompts) according to a specified weight, generating a new conditioning vector that l

The `ConditioningAverage` node is used to blend two different sets of conditioning (such as text prompts) according to a specified weight, generating a new conditioning vector that lies between the two. By adjusting the weight parameter, you can flexibly control the influence of each conditioning on the final result. This is especially suitable for prompt interpolation, style fusion, and other advanced use cases.

As shown below, by adjusting the strength of `conditioning_to`, you can output a result between the two conditionings.

<img alt="example" />

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `conditioning_to` | The target conditioning vector, serving as the main base for the weighted average. | `CONDITIONING` |
| `conditioning_from` | The source conditioning vector, which will be blended into the target according to a certain weight. | `CONDITIONING` |
| `conditioning_to_strength` | The strength of the target conditioning, range 0.0-1.0, default 1.0, step 0.01. | `FLOAT` |

## Outputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `conditioning` | The resulting conditioning vector after blending, reflecting the weighted average. | `CONDITIONING` |

## Typical Use Cases

* **Prompt Interpolation:** Smoothly transition between two different text prompts, generating content with intermediate style or semantics.
* **Style Fusion:** Combine different artistic styles or semantic conditions to create novel effects.
* **Strength Adjustment:** Precisely control the influence of a particular conditioning on the result by adjusting the weight.
* **Creative Exploration:** Explore diverse generative effects by mixing different prompts.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningAverage/en.md)


# DifferentialDiffusion - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DifferentialDiffusion

The Differential Diffusion node modifies the denoising process by applying a binary mask based on timestep thresholds.

The Differential Diffusion node modifies the denoising process by applying a binary mask based on timestep thresholds. It creates a mask that blends between the original denoise mask and a threshold-based binary mask, allowing controlled adjustment of the diffusion process strength.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to modify | MODEL | Yes | - |
| `strength` | Controls the blending strength between the original denoise mask and the binary threshold mask (default: 1.0) | FLOAT | No | 0.0 - 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified diffusion model with updated denoise mask function | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DifferentialDiffusion/en.md)

***

**Source fingerprint (SHA-256):** `26387c3e6c7ead5415b36cfc9b9eef73448527e70646ab253984ff9627f69a25`


# DrawBBoxes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DrawBBoxes

The DrawBBoxes node visualizes object detection results by drawing bounding boxes, labels, and confidence scores onto an image.

The DrawBBoxes node visualizes object detection results by drawing bounding boxes, labels, and confidence scores onto an image. If no input image is provided, it creates a blank canvas large enough to contain all the drawn boxes. It supports batch processing, allowing you to draw different sets of detections for multiple images or repeat the same detections across a batch.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image(s) to draw the bounding boxes onto. If not provided, a blank canvas will be generated. | IMAGE | No | - |
| `bboxes` | A list of bounding box dictionaries. Each dictionary should contain keys for `x`, `y`, `width`, `height`, and optionally `label` and `score`. | BOUNDINGBOX | Yes | - |

**Input Constraints:**

* The `bboxes` input is required and must be provided.
* The node automatically handles different input formats for `bboxes`. A single dictionary will be applied to all images in the batch. A flat list of dictionaries will be treated as the same set of detections for every image. A list of lists allows you to specify different detections for each image in the batch.
* If an `image` is not provided, the node will create a blank image with dimensions large enough to fit all provided bounding boxes, with a default minimum size of 640x640.
* The `label` field in each bounding box dictionary is matched against the COCO dataset classes. If the label is not a recognized COCO class, it will be ignored and no text label will be drawn for that box.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `out_image` | The output image(s) with the drawn bounding boxes, labels, and confidence scores overlaid. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DrawBBoxes/en.md)

***

**Source fingerprint (SHA-256):** `ce5da10ec83e579515d70b7184fc78dfa04df4c514faccdcb75130212f56c84f`


# EmptyAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyAudio

The EmptyAudio node generates a silent audio clip with specified duration, sample rate, and channel configuration.

The EmptyAudio node generates a silent audio clip with specified duration, sample rate, and channel configuration. It creates a waveform containing all zeros, producing complete silence for the given duration. This node is useful for creating placeholder audio or generating silent segments in audio workflows.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `duration` | Duration of the empty audio clip in seconds (default: 60.0) | FLOAT | Yes | 0.0 to 1.8446744073709552e+19 |
| `sample_rate` | Sample rate of the empty audio clip (default: 44100) | INT | Yes | 1 to 192000 |
| `channels` | Number of audio channels (1 for mono, 2 for stereo) (default: 2) | INT | Yes | 1 to 2 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `AUDIO` | The generated silent audio clip containing waveform data and sample rate information | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyAudio/en.md)

***

**Source fingerprint (SHA-256):** `687bfe02cb0192add9128ae9040fa5773be0d7a0a5df17618cf56050901c6dc5`


# FluxKVCache - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxKVCache

The Flux KV Cache node enables a Key-Value (KV) Cache optimization for Flux family models.

The Flux KV Cache node enables a Key-Value (KV) Cache optimization for Flux family models. This optimization improves performance when using reference images by caching certain computations, which can speed up the generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply KV Cache optimization on. | MODEL | Yes | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The patched model with KV Cache optimization enabled. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxKVCache/en.md)

***

**Source fingerprint (SHA-256):** `bf2b19dd11336bec694a6eb586141fa850e3d0a5102c5d320455f7346738660c`


# FreSca - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FreSca

The FreSca node applies frequency-dependent scaling to the guidance during the sampling process.

The FreSca node applies frequency-dependent scaling to the guidance during the sampling process. It separates the guidance signal into low-frequency and high-frequency components using Fourier filtering, then applies different scaling factors to each frequency range before recombining them. This allows for more nuanced control over how guidance affects different aspects of the generated output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply frequency scaling to | MODEL | Yes | - |
| `scale_low` | Scaling factor for low-frequency components (default: 1.0) | FLOAT | No | 0 - 10 |
| `scale_high` | Scaling factor for high-frequency components (default: 1.25) | FLOAT | No | 0 - 10 |
| `freq_cutoff` | Number of frequency indices around center to consider as low-frequency (default: 20) | INT | No | 1 - 10000 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with frequency-dependent scaling applied to its guidance function | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FreSca/en.md)

***

**Source fingerprint (SHA-256):** `2ff3517619d856db68a9091ae7c87af8c56a23420fa2176b089bf9700475a7a9`


# ImageColorSpace - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageColorSpace

The ImageColorSpace node converts images between sRGB (Rec.709), linear Rec.709, HDR (Rec.2020 HLG), HDR PQ (Rec.2020 PQ), HDR LogC3, and HDR ACEScct color spaces.

The ImageColorSpace node converts images between sRGB (Rec.709), linear Rec.709, HDR (Rec.2020 HLG), HDR PQ (Rec.2020 PQ), HDR LogC3, and HDR ACEScct color spaces. LogC3 uses the EI 800 curve with Rec.709 primaries and codes clamped to \[0, 1]; ACEScct uses AP1 primaries and D60 white, with Bradford adaptation to D65. When converting to SDR output, or from HDR PQ to HDR, it tone-maps excess luminance across the batch and compresses out-of-gamut colors; linear and ACEScct outputs, and linear-to-HDR conversions, preserve extended values. HLG and PQ outputs clip negative channels. Conversions are computed in float32, and any alpha channel is passed through unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be converted. | IMAGE | Yes | Any valid image. |
| `source` | Color space of the input pixels. Default: "sRGB". | COMBO | Yes | `"sRGB"`<br />`"HDR"`<br />`"HDR PQ"`<br />`"linear"`<br />`"HDR LogC3"`<br />`"HDR ACEScct"` |
| `destination` | Color space of the output pixels. Set the save node to this same color space. Convert LogC3 or ACEScct to linear before saving EXR, or to sRGB/HDR/HDR PQ before saving video. Default: "sRGB". | COMBO | Yes | `"sRGB"`<br />`"HDR"`<br />`"HDR PQ"`<br />`"linear"`<br />`"HDR LogC3"`<br />`"HDR ACEScct"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The converted image in the specified destination color space. | IMAGE |

## Notes

* Linear 1.0 uses the same 203-nit reference white as sRGB; HLG uses a 1000-nit reference display.
* Linear and ACEScct outputs preserve extended values; linear-to-HDR conversions preserve highlights without tone mapping.
* SDR output and PQ-to-HLG conversion tone-map excess luminance across the batch (sharing one white point so exposure does not change frame by frame) and compress out-of-gamut colors. HLG and PQ outputs clip negative channels.
* Conversions are computed in float32 and return the intermediate device and dtype.
* LogC3 and ACEScct are camera log encodings: convert them to linear for EXR saving, or to sRGB/HDR/HDR PQ before saving video.
* Straight alpha is not color-transformed; only the RGB channels are converted.
* If `source` and `destination` are the same, no color transformation is applied — the image is only moved to the intermediate device and dtype.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageColorSpace/en.md)

***

**Source fingerprint (SHA-256):** `fdf8b4f16a1e0c7ff9a86b8cc40f6f796175205e4b1f491b595a74a8456b9b94`


# ImageCompositeMasked - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageCompositeMasked

The ImageCompositeMasked node is designed for compositing images, allowing for the overlay of a source image onto a destination image at specified coordinates, with optional resi

The `ImageCompositeMasked` node is designed for compositing images, allowing for the overlay of a source image onto a destination image at specified coordinates, with optional resizing and masking.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `destination` | The destination image onto which the source image will be composited. It serves as the background for the composite operation. | `IMAGE` |
| `source` | The source image to be composited onto the destination image. This image can optionally be resized to fit the destination image's dimensions. | `IMAGE` |
| `x` | The x-coordinate in the destination image where the top-left corner of the source image will be placed. | `INT` |
| `y` | The y-coordinate in the destination image where the top-left corner of the source image will be placed. | `INT` |
| `resize_source` | A boolean flag indicating whether the source image should be resized to match the destination image's dimensions. | `BOOLEAN` |
| `mask` | An optional mask that specifies which parts of the source image should be composited onto the destination image. This allows for more complex compositing operations, such as blending or partial overlays. | `MASK` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The resulting image after the compositing operation, which combines elements of both t | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageCompositeMasked/en.md)


# ImageDeduplication - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageDeduplication

This node removes duplicate or very similar images from a batch.

This node removes duplicate or very similar images from a batch. It works by creating a perceptual hash for each image—a simple numerical fingerprint based on its visual content—and then comparing them. Images whose hashes are more similar than a set threshold are considered duplicates and filtered out.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The batch of images to process for deduplication. | IMAGE | Yes | - |
| `similarity_threshold` | Similarity threshold (0-1). Higher means more similar. Images above this threshold are considered duplicates. (default: 0.95) | FLOAT | No | 0.0 - 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The filtered list of images with duplicates removed. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageDeduplication/en.md)

***

**Source fingerprint (SHA-256):** `d0c40694853c3dd0952d58b920bf735a4626cb2921928bb982ba479dc58fbe53`


# ImageFromBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageFromBatch

The ImageFromBatch node is designed for extracting a specific segment of images from a batch based on the provided index and length.

The `ImageFromBatch` node is designed for extracting a specific segment of images from a batch based on the provided index and length. It allows for more granular control over the batched images, enabling operations on individual or subsets of images within a larger batch.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The batch of images from which a segment will be extracted. This parameter is crucial for specifying the source batch. | `IMAGE` |
| `batch_index` | The starting index within the batch from which the extraction begins. It determines the initial position of the segment to be extracted from the batch. | `INT` |
| `length` | The number of images to extract from the batch starting from the batch\_index. This parameter defines the size of the segment to be extracted. | `INT` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The extracted segment of images from the specified batch. This output represents a subset of the original batch, determined by the batch\_index and length parameters. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageFromBatch/en.md)


# ImageGrid - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageGrid

The Image Grid node combines multiple images into a single, organized grid or collage.

The Image Grid node combines multiple images into a single, organized grid or collage. It takes a list of images and arranges them into a specified number of columns, resizing each image to fit a defined cell size and adding optional padding between them. The result is a single, new image containing all the input images in a grid layout.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | A list of images to be arranged into the grid. The node requires at least one image to function. | IMAGE | Yes | - |
| `columns` | The number of columns in the grid (default: 4). | INT | No | 1 - 20 |
| `cell_width` | The width, in pixels, of each cell in the grid (default: 256). | INT | No | 32 - 2048 |
| `cell_height` | The height, in pixels, of each cell in the grid (default: 256). | INT | No | 32 - 2048 |
| `padding` | The amount of padding, in pixels, to place between images in the grid (default: 4). | INT | No | 0 - 50 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The single output image containing all the input images arranged in a grid. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageGrid/en.md)

***

**Source fingerprint (SHA-256):** `87bc0af8af33a0fd703f13fec782075502c9562847fa3887a2273afa5b28c47e`


# ImageMergeTileList - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageMergeTileList

This node takes a list of image tiles and merges them back into a single, larger image.

This node takes a list of image tiles and merges them back into a single, larger image. It is designed to reconstruct an image that was previously split into a grid of overlapping tiles, using a weighted blending technique to create a seamless final result.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image_list` | A list of image tiles to be merged. The first tile in the list is used to determine the tile dimensions and data type for the entire process. | IMAGE | Yes | N/A |
| `final_width` | The width of the final merged image in pixels (default: 1024). | INT | Yes | 64 - 32768 |
| `final_height` | The height of the final merged image in pixels (default: 1024). | INT | Yes | 64 - 32768 |
| `overlap` | The amount of overlap between adjacent tiles in pixels. A value greater than 0 enables a smooth blending effect at the tile seams (default: 128). | INT | Yes | 0 - 4096 |

**Note:** The `image_list` is a dynamic input list. The node will process tiles in the order they are provided, up to the number required to fill the grid defined by the `final_width`, `final_height`, and the dimensions of the first tile. If the list contains more tiles than needed, the extra tiles are ignored.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The final merged image, reconstructed from the input tiles. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageMergeTileList/en.md)

***

**Source fingerprint (SHA-256):** `41b570bf758093f3693c015e7976b946b9d93ca56db2bf66617149f259ae8c06`


# ImageRGBToYUV - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageRGBToYUV

The ImageRGBToYUV node converts an RGB image into YUV-style color components using an RGB-to-YCbCr color conversion.

The ImageRGBToYUV node converts an RGB image into YUV-style color components using an RGB-to-YCbCr color conversion. It splits the result into three separate images — Y (luminance, or brightness), U (blue-difference chroma), and V (red-difference chroma) — and returns each component at the same width and height as the input.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input RGB image to convert into Y, U, and V components. If the image contains an alpha channel, only the first three (RGB) channels are used. | IMAGE | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `Y` | The luminance (brightness) component of the YUV color space, returned as a three-channel image | IMAGE |
| `U` | The blue-difference chroma component of the YUV color space, returned as a three-channel image | IMAGE |
| `V` | The red-difference chroma component of the YUV color space, returned as a three-channel image | IMAGE |

Each output has the same width and height as the input image. The corresponding Y, U, or V component is repeated across all three channels so that every output is returned as a standard three-channel image.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageRGBToYUV/en.md)

***

**Source fingerprint (SHA-256):** `1a75ce64dfaec316a8f4b3a210cede388c9ba12d3ab3ec5ec14b0027be383744`


# ImageYUVToRGB - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageYUVToRGB

The ImageYUVToRGB node converts YUV color space images to RGB color space.

The ImageYUVToRGB node converts YUV color space images to RGB color space. It takes three separate input images representing the Y (luma), U (blue projection), and V (red projection) components and combines them into a single RGB image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `Y` | The Y (luminance) component input image. If the image has more than three channels, only the first three are used and averaged into a single channel. | IMAGE | Yes | - |
| `U` | The U (blue projection) component input image. If the image has more than three channels, only the first three are used and averaged into a single channel. | IMAGE | Yes | - |
| `V` | The V (red projection) component input image. If the image has more than three channels, only the first three are used and averaged into a single channel. | IMAGE | Yes | - |

**Note:** All three input images (Y, U, and V) must be provided together and must have compatible dimensions (matching height, width, and batch size) for the conversion to succeed.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The converted RGB image | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageYUVToRGB/en.md)

***

**Source fingerprint (SHA-256):** `47e90b1a9aeb5ddfccea4493021b83e06faad3f84d40c8b0f2b3cec59b192c2e`


# JoinAudioChannels - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/JoinAudioChannels

The Join Audio Channels node combines two separate mono audio inputs into a single stereo audio output.

The Join Audio Channels node combines two separate mono audio inputs into a single stereo audio output. It takes a left channel and a right channel, ensures they have compatible sample rates and lengths, and merges them into a two-channel audio waveform.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio_left` | The mono audio data to be used as the left channel in the resulting stereo audio. | AUDIO | Yes | |
| `audio_right` | The mono audio data to be used as the right channel in the resulting stereo audio. | AUDIO | Yes | |

**Note:** Both input audio streams must be mono (single-channel). If they have different sample rates, the channel with the lower rate will be automatically resampled to match the higher rate. If the audio streams have different lengths, they will be trimmed to the length of the shorter one.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The resulting stereo audio, containing the joined left and right channels. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/JoinAudioChannels/en.md)

***

**Source fingerprint (SHA-256):** `8a68e59e0d037882e9dd87d93b38673a0de3072bab2c574c7a9750de93b50a68`


# JoinImageWithAlpha - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/JoinImageWithAlpha

This node is designed for compositing operations, specifically to join an image with its corresponding alpha mask to produce a single output image.

This node is designed for compositing operations, specifically to join an image with its corresponding alpha mask to produce a single output image. It effectively combines visual content with transparency information, enabling the creation of images where certain areas are transparent or semi-transparent.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The main visual content to be combined with an alpha mask. It represents the image without transparency information. | `IMAGE` |
| `alpha` | The alpha mask that defines the transparency of the corresponding image. It is used to determine which parts of the image should be transparent or semi-transparent. | `MASK` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The output is a single image that combines the input image with the alpha mask, incorporating transparency information into the visual content. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/JoinImageWithAlpha/en.md)


# LatentBlend - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentBlend

The LatentBlend node combines two latent samples by blending them together using a specified blend factor.

The LatentBlend node combines two latent samples by blending them together using a specified blend factor. It takes two latent inputs and creates a new output where the first sample is weighted by the blend factor and the second sample is weighted by the inverse. If the input samples have different shapes, the second sample is automatically resized to match the first sample's dimensions.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples1` | The first latent sample to blend | LATENT | Yes | - |
| `samples2` | The second latent sample to blend | LATENT | Yes | - |
| `blend_factor` | Controls the blending ratio between the two samples (default: 0.5) | FLOAT | Yes | 0 to 1 |

**Note:** If `samples1` and `samples2` have different shapes, `samples2` will be automatically resized to match the dimensions of `samples1` using bicubic interpolation with center cropping.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latent` | The blended latent sample combining both input samples | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentBlend/en.md)

***

**Source fingerprint (SHA-256):** `a19808c5b606a8c05f2685fcd78d9f08c1ba51613a4029b36cf0ce5305618c2f`


# LoadAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadAudio

The LoadAudio node loads audio files from the input directory and converts them into a format that can be processed by other audio nodes in ComfyUI.

The LoadAudio node loads audio files from the input directory and converts them into a format that can be processed by other audio nodes in ComfyUI. It reads audio files and extracts both the waveform data and sample rate, making them available for downstream audio processing tasks.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio file to load from the input directory | AUDIO | Yes | All supported audio and video files in the input directory |

**Note:** The node only accepts audio and video files that are present in ComfyUI's input directory. The file must exist and be accessible for successful loading.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `AUDIO` | Audio data containing waveform and sample rate information | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadAudio/en.md)

***

**Source fingerprint (SHA-256):** `5631a5c50471e4612344c4bd0457e9824e9a7a8f8b75b22d06f13d5136c75258`


# LoraSave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraSave

The LoraSave node extracts and saves LoRA (Low-Rank Adaptation) files from model differences.

The LoraSave node extracts and saves LoRA (Low-Rank Adaptation) files from model differences. It can process diffusion model differences, text encoder differences, or both, converting them into LoRA format with specified rank and type. The resulting LoRA file is saved to the output directory for later use.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `filename_prefix` | The prefix for the output filename (default: "loras/ComfyUI\_extracted\_lora") | STRING | Yes | - |
| `rank` | The rank value for the LoRA, controlling the size and complexity (default: 8) | INT | Yes | 1-4096 |
| `lora_type` | The type of LoRA to create. "standard" extracts low-rank matrices via SVD; "full\_diff" saves the full weight difference (default: "standard") | COMBO | Yes | `"standard"`<br />`"full_diff"` |
| `bias_diff` | Whether to include bias differences in the LoRA calculation (default: True) | BOOLEAN | Yes | - |
| `model_diff` | The ModelSubtract output to be converted to a lora | MODEL | No | - |
| `text_encoder_diff` | The CLIPSubtract output to be converted to a lora | CLIP | No | - |

**Note:** At least one of `model_diff` or `text_encoder_diff` must be provided for the node to function. If both are omitted, the node will produce no output.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| - | This node saves a LoRA file to the output directory but does not return any data through the workflow | - |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoraSave/en.md)

***

**Source fingerprint (SHA-256):** `642510bfe083130cb2724d7ae38d30d4694c85a43c7ce27230690ddd9fe76b79`


# Mahiro - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Mahiro

The Mahiro node modifies the guidance function to focus more on the direction of the positive prompt rather than the difference between positive and negative prompts.

The Mahiro node modifies the guidance function to focus more on the direction of the positive prompt rather than the difference between positive and negative prompts. It creates a patched model that applies a custom guidance scaling approach using cosine similarity between normalized conditional and unconditional denoised outputs. This experimental node helps steer the generation more strongly toward the positive prompt's intended direction.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to be patched with the modified guidance function | MODEL | Yes | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `patched_model` | The modified model with the Mahiro guidance function applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Mahiro/en.md)

***

**Source fingerprint (SHA-256):** `56f13cd14ffde21ab980850b62e07bdd4db6733a545f9329bf908c6030147981`


# MediaPipeFaceLandmarker - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MediaPipeFaceLandmarker

Documentation for MediaPipeFaceLandmarker node.

## Overview

Detects faces in an image and identifies 468 facial landmarks (key points) on each face using MediaPipe's BlazeFace and FaceMesh models. It also calculates ARKit-52 blendshape coefficients for facial expression analysis. The node can process multiple images in a batch and outputs both the landmark data and bounding boxes for each detected face.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `face_detection_model` | The MediaPipe face detection model to use for landmark detection. | FACE\_DETECTION\_MODEL | Yes | |
| `image` | The input image or batch of images to detect faces in. | IMAGE | Yes | |
| `detector_variant` | Face detector range. `"short"` is tuned for close-up faces (within \~2 m of the camera); `"full"` covers farther/smaller faces (up to \~5 m) but is slower. `"both"` runs both detectors and keeps whichever found more faces per frame (\~2x detection cost). Default: `"short"`. | COMBO | Yes | `"short"`<br />`"full"`<br />`"both"` |
| `num_faces` | Maximum number of faces to return per frame. 0 means no cap (return all detected). Default: 1. | INT | Yes | 0 to 16 |
| `min_confidence` | BlazeFace score threshold. Lower values help catch small or occluded faces. Default: 0.5. | FLOAT | No | 0.00 to 1.00 |
| `missing_frame_fallback` | Per-frame behavior when detection fails in a batch. `"empty"` leaves the frame faceless. `"previous"` copies the most recent successful detection. `"interpolate"` lerps landmarks/bbox/blendshapes between bracketing successful frames. Multi-face: pairs faces across frames by greedy bbox-centre NN. Default: `"empty"`. | COMBO | No | `"empty"`<br />`"previous"`<br />`"interpolate"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `face_landmarks` | A structured output containing per-frame face detection results, including 468 facial landmarks, ARKit-52 blendshape coefficients, transformation matrices, and connection sets for mesh visualization. | FACE\_LANDMARKS |
| `bboxes` | A list of bounding boxes for each detected face, with coordinates (x, y, width, height), label "face", and confidence score. One list per input frame. | BOUNDING\_BOX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MediaPipeFaceLandmarker/en.md)

***

**Source fingerprint (SHA-256):** `f60ed6201288a59d65d62cc98c12f227a353870c36decea8da81a063cfdf2bba`


# MediaPipeFaceMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MediaPipeFaceMask

Documentation for MediaPipeFaceMask node.

## Overview

This node creates a binary mask (a black and white image) based on face landmarks detected by MediaPipe. It draws filled polygon shapes for each detected face region, producing one mask per frame in a batch. When multiple faces are detected in the same frame, their masks are combined into a single mask.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `face_landmarks` | The face landmarks data from a MediaPipe face detection node. | FACE\_LANDMARKS | Yes | - |
| `regions` | Selects which facial regions to include in the mask. `"all"` creates a mask from the union of all face regions (face oval, lips, eyes, irises). `"custom"` allows you to toggle each region individually. Default: `"all"` | COMBO | Yes | `"all"`<br />`"custom"` |

When `regions` is set to `"custom"`, the following additional boolean parameters become available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `face_oval` | Include the face oval region in the mask. Default: True | BOOLEAN | No | True/False |
| `lips` | Include the lips region in the mask. Default: True | BOOLEAN | No | True/False |
| `eyes` | Include the eyes region in the mask. Default: True | BOOLEAN | No | True/False |
| `irises` | Include the irises region in the mask. Default: True | BOOLEAN | No | True/False |

**Note:** When using `"all"` mode, the mask includes all regions combined. Since the face oval encloses the other regions, selecting `"all"` effectively produces the same result as selecting only the face oval.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MASK` | A binary mask tensor where face regions are white (value 1.0) and background is black (value 0.0). The mask has the same dimensions as the input image and contains one mask per frame in the batch. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MediaPipeFaceMask/en.md)

***

**Source fingerprint (SHA-256):** `92270002a42ed59bc75e676a6881e1899186d3c8a1bb4dd4c0d39b3762b5bb66`


# MediaPipeFaceMeshVisualize - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MediaPipeFaceMeshVisualize

Documentation for MediaPipeFaceMeshVisualize node.

## Overview

Draws face landmark points and connection lines (a face mesh) on top of an input image. This node uses the landmark data produced by a face detection node to visualize the detected facial features, such as the eyes, nose, mouth, and face outline.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `face_landmarks` | The face landmark data from a detection node. | FACE\_LANDMARKS | Yes | |
| `image` | The image to draw the mesh on. If not connected, a black canvas of the same size as the detection result will be used. | IMAGE | No | |
| `connections` | Determines which parts of the face mesh to draw. `"all"` draws the full mesh (oval, eyes, brows, lips, irises, nose). `"fill"` draws a solid polygon of the face oval (silhouette mask). `"custom"` lets you toggle each feature individually. (default: `"all"`) | COMBO | Yes | `"all"`<br />`"fill"`<br />`"custom"` |
| `color` | The color of the mesh lines and points. (default: `#00ff00`) | COLOR | Yes | |
| `thickness` | The thickness of the mesh lines in pixels. Setting this to 0 disables line drawing. (default: 1) | INT | Yes | 0 to 8 |
| `point_size` | The radius of the landmark dots in pixels. Setting this to 0 disables dot drawing. (default: 2) | INT | Yes | 0 to 16 |

**Note on `connections` parameter:** When `"custom"` is selected, additional boolean inputs appear for each facial feature (e.g., `face_oval`, `lips`, `left_eye`, `right_eye`, `left_eyebrow`, `right_eyebrow`, `left_iris`, `right_iris`, `nose`, `tesselation`). Only the features you enable will be drawn.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The input image with the face landmarks mesh drawn on it. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MediaPipeFaceMeshVisualize/en.md)

***

**Source fingerprint (SHA-256):** `fb5437d73378b0c8daa68669c2e19058ccb7133ed68fc51c8d4c5bab8662f243`


# MergeImageLists - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MergeImageLists

The Merge Image Lists node combines multiple separate lists of images into a single, continuous list.

The Merge Image Lists node combines multiple separate lists of images into a single, continuous list. It works by taking all the images from each connected input and appending them together in the order they are received. This is useful for organizing or batching images from different sources for further processing.

**Note:** This node is deprecated and superseded by the Create List node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | A list of images to be merged. This input can accept multiple connections, and each connected list will be concatenated into the final output. | IMAGE | Yes | - |

**Note:** This node is designed to receive multiple inputs. You can connect several image lists to the single `images` input socket. The node will automatically concatenate all images from all connected lists into one output list.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The single, merged list containing all images from every connected input list. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MergeImageLists/en.md)

***

**Source fingerprint (SHA-256):** `0c9e302b02694a6a23fc7776c872856b1a629df3efe914a3e591a89d5a28914a`


# NormalizeImages - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/NormalizeImages

This node normalizes the colors of an input image by adjusting its pixel values based on a specified mean and standard deviation.

This node normalizes the colors of an input image by adjusting its pixel values based on a specified mean and standard deviation. Each pixel has the mean subtracted from it and is then divided by the standard deviation, which is a common step to standardize image data before other processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be normalized. | IMAGE | Yes | - |
| `mean` | Mean value for normalization (default: 0.5). | FLOAT | No | 0.0 - 1.0 |
| `std` | Standard deviation for normalization (default: 0.5). | FLOAT | No | 0.001 - 1.0 |

The `mean` and `std` parameters control the normalization applied to the input image. The default value for both parameters is 0.5.

Note: If the input image has an alpha (transparency) channel, that channel is not normalized. It is copied unchanged to the output because alpha stores transparency rather than color.

Note: The node works with any batch size, so multiple images can be processed at once.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resulting image after the normalization process has been applied. Pixel values are adjusted using the specified mean and standard deviation, and the alpha channel (if present) is preserved. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/NormalizeImages/en.md)

***

**Source fingerprint (SHA-256):** `30c0587265754842ff7d1e5f339fc934b58d59bb3ba18716c2a1f9679f2d561d`


# PerpNeg - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PerpNeg

The PerpNeg node applies perpendicular negative guidance to a model's sampling process.

The PerpNeg node applies perpendicular negative guidance to a model's sampling process. This node modifies the model's configuration function to adjust noise predictions using negative conditioning and scaling factors. It has been deprecated and replaced by the PerpNegGuider node for improved functionality.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply perpendicular negative guidance to | MODEL | Yes | - |
| `empty_conditioning` | Empty conditioning used for negative guidance calculations | CONDITIONING | Yes | - |
| `neg_scale` | Scaling factor for negative guidance (default: 1.0) | FLOAT | No | 0.0 - 100.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with perpendicular negative guidance applied | MODEL |

**Note**: This node is deprecated and has been replaced by PerpNegGuider. It is marked as experimental and should not be used in production workflows.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PerpNeg/en.md)

***

**Source fingerprint (SHA-256):** `016bd9a9a9ee42855c15b3e582ada03557297df9a786d977439edd9d3363a5ba`


# PerpNegGuider - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PerpNegGuider

The PerpNegGuider node creates a guidance system for controlling image generation using perpendicular negative conditioning.

The PerpNegGuider node creates a guidance system for controlling image generation using perpendicular negative conditioning. It takes positive, negative, and empty conditioning inputs and applies a specialized guidance algorithm that computes all three noise predictions in a single batch for efficiency. This node is designed for experimental testing and provides fine control over the guidance strength and negative scaling.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to use for guidance generation | MODEL | Yes | - |
| `positive` | The positive conditioning that guides the generation toward desired content | CONDITIONING | Yes | - |
| `negative` | The negative conditioning that guides the generation away from unwanted content | CONDITIONING | Yes | - |
| `empty_conditioning` | The empty or neutral conditioning used as a baseline reference for perpendicular negative guidance | CONDITIONING | Yes | - |
| `cfg` | The classifier-free guidance scale that controls how strongly the conditioning influences the generation (default: 8.0) | FLOAT | Yes | 0.0 - 100.0 |
| `neg_scale` | The negative scaling factor that adjusts the strength of the perpendicular negative effect (default: 1.0) | FLOAT | Yes | 0.0 - 100.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `guider` | A configured guidance system ready for use in the generation pipeline | GUIDER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PerpNegGuider/en.md)

***

**Source fingerprint (SHA-256):** `02e4b4e0ea413da31c280cb1e510bdf5caa7b5187eb6de94632e45a91e881820`


# PikaImageToVideoNode2_2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PikaImageToVideoNode2_2

The Pika Image to Video node sends an image and text prompt to the Pika API version 2.2 to generate a video.

The Pika Image to Video node sends an image and text prompt to the Pika API version 2.2 to generate a video. It converts your input image into video format based on the provided description and settings. The node handles the API communication and returns the generated video as output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image to convert to video | IMAGE | Yes | - |
| `prompt_text` | The text description guiding video generation | STRING | Yes | - |
| `negative_prompt` | Text describing what to avoid in the video | STRING | Yes | - |
| `seed` | Random seed value for reproducible results | INT | Yes | - |
| `resolution` | Output video resolution setting | STRING | Yes | - |
| `duration` | Length of the generated video in seconds | INT | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PikaImageToVideoNode2_2/en.md)

***

**Source fingerprint (SHA-256):** `aaa8dc49b94f0fae2010a3b61a3fb41e212fa9d2946a934a1a7c651fdced81b3`


# PikaScenesV2_2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PikaScenesV2_2

The PikaScenes v2.2 node combines multiple images to create a video that incorporates objects from all the input images.

The PikaScenes v2.2 node combines multiple images to create a video that incorporates objects from all the input images. You can upload up to five different images as ingredients and generate a high-quality video that blends them together seamlessly.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt_text` | Text description of what to generate | STRING | Yes | - |
| `negative_prompt` | Text description of what to avoid in the generation | STRING | Yes | - |
| `seed` | Random seed value for generation | INT | Yes | - |
| `resolution` | Output resolution for the video | STRING | Yes | - |
| `duration` | Duration of the generated video | INT | Yes | - |
| `ingredients_mode` | Mode for combining ingredients (default: "creative") | STRING | No | "creative"<br />"precise" |
| `aspect_ratio` | Aspect ratio (width / height) (default: 1.778) | FLOAT | No | 0.4 - 2.5 |
| `image_ingredient_1` | Image that will be used as ingredient to create a video | IMAGE | No | - |
| `image_ingredient_2` | Image that will be used as ingredient to create a video | IMAGE | No | - |
| `image_ingredient_3` | Image that will be used as ingredient to create a video | IMAGE | No | - |
| `image_ingredient_4` | Image that will be used as ingredient to create a video | IMAGE | No | - |
| `image_ingredient_5` | Image that will be used as ingredient to create a video | IMAGE | No | - |

**Note:** You can provide up to 5 image ingredients, but at least one image is required to generate a video. The node will use all provided images to create the final video composition.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video combining all input images | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PikaScenesV2_2/en.md)

***

**Source fingerprint (SHA-256):** `dda8f10a58527c2b9037744f59f30821cdde37ad23427b856ba5e699a05acafd`


# PikaStartEndFrameNode2_2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PikaStartEndFrameNode2_2

The PikaFrames v2.2 Node generates a video by combining your first and last frame.

The PikaFrames v2.2 Node generates a video by combining your first and last frame. You upload two images to define the start and end points, and the AI creates a smooth transition between them to produce a complete video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image_start` | The first image to combine. | IMAGE | Yes | - |
| `image_end` | The last image to combine. | IMAGE | Yes | - |
| `prompt_text` | Text prompt describing the desired video content. | STRING | Yes | - |
| `negative_prompt` | Text describing what to avoid in the video. | STRING | Yes | - |
| `seed` | Random seed value for generation consistency. | INT | Yes | - |
| `resolution` | Output video resolution. | STRING | Yes | - |
| `duration` | Duration of the generated video. | INT | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video combining the start and end frames with AI transitions. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PikaStartEndFrameNode2_2/en.md)

***

**Source fingerprint (SHA-256):** `0a26f6db754c61d1f35e3fd9faceb631a8103ce9ff38190a5dd637991914e238`


# PikaTextToVideoNode2_2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PikaTextToVideoNode2_2

The Pika Text2Video v2.2 Node sends a text prompt to the Pika API version 2.2 to generate a video.

The Pika Text2Video v2.2 Node sends a text prompt to the Pika API version 2.2 to generate a video. It converts your text description into a video using Pika's AI video generation service. The node allows you to customize various aspects of the video generation process including aspect ratio, duration, and resolution.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt_text` | The main text description that describes what you want to generate in the video | STRING | Yes | - |
| `negative_prompt` | Text describing what you don't want to appear in the generated video | STRING | Yes | - |
| `seed` | A number that controls the randomness of the generation for reproducible results | INT | Yes | - |
| `resolution` | The resolution setting for the output video | STRING | Yes | - |
| `duration` | The length of the video in seconds | INT | Yes | - |
| `aspect_ratio` | Aspect ratio (width / height) (default: 1.7777777777777777) | FLOAT | No | 0.4 - 2.5 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file returned from the Pika API | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PikaTextToVideoNode2_2/en.md)

***

**Source fingerprint (SHA-256):** `b4287519f5d4cc4a1077a58fb13aa99697e3be038a0b382c4b4c9b0e53a0d8a8`


# Pikadditions - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Pikadditions

The Pikadditions node allows you to add any object or image into your video.

The Pikadditions node allows you to add any object or image into your video. You upload a video and specify what you'd like to add to create a seamlessly integrated result. This node uses the Pika API to insert images into videos with natural-looking integration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The video to add an image to. | VIDEO | Yes | - |
| `image` | The image to add to the video. | IMAGE | Yes | - |
| `prompt_text` | Text description of what to add to the video. | STRING | Yes | - |
| `negative_prompt` | Text description of what to avoid in the video. | STRING | Yes | - |
| `seed` | Random seed value for reproducible results. | INT | Yes | 0 to 4294967295 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The processed video with the image inserted. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Pikadditions/en.md)

***

**Source fingerprint (SHA-256):** `cf7bb4ee0a672e20c0ffc128fa95df43e05356aea03b2070f928a0263aff6234`


# Pikaffects - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Pikaffects

The Pikaffects node generates videos with various visual effects applied to an input image.

The Pikaffects node generates videos with various visual effects applied to an input image. It uses Pika's video generation API to transform static images into animated videos with specific effects like melting, exploding, or levitating. The node requires an API key and authentication token to access the Pika service.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The reference image to apply the Pikaffect to. | IMAGE | Yes | - |
| `pikaffect` | The specific visual effect to apply to the image (default: "Cake-ify"). | COMBO | Yes | "Cake-ify"<br />"Crumble"<br />"Crush"<br />"Decapitate"<br />"Deflate"<br />"Dissolve"<br />"Explode"<br />"Eye-pop"<br />"Inflate"<br />"Levitate"<br />"Melt"<br />"Peel"<br />"Poke"<br />"Squish"<br />"Ta-da"<br />"Tear" |
| `prompt_text` | Text description guiding the video generation. | STRING | Yes | - |
| `negative_prompt` | Text description of what to avoid in the generated video. | STRING | Yes | - |
| `seed` | Random seed value for reproducible results. | INT | Yes | 0 to 4294967295 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video with the applied Pikaffect. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Pikaffects/en.md)

***

**Source fingerprint (SHA-256):** `68ebbee465763d463bf73678254eed38d37ebacb1c62d386bbe66961deffd5a8`


# Pikaswaps - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Pikaswaps

The Pika Swaps node replaces objects or regions in your video with a new image.

The Pika Swaps node replaces objects or regions in your video with a new image. You define the areas to replace using a mask, and the node seamlessly swaps the specified content throughout the video sequence.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The video to swap an object in. | VIDEO | Yes | - |
| `image` | The image used to replace the masked object in the video. | IMAGE | Yes | - |
| `mask` | Use the mask to define areas in the video to replace. | MASK | Yes | - |
| `prompt_text` | Text prompt describing the desired replacement. | STRING | Yes | - |
| `negative_prompt` | Text prompt describing what to avoid in the replacement. | STRING | Yes | - |
| `seed` | Random seed value for consistent results. | INT | Yes | 0 to 4294967295 |

**Note:** This node requires all input parameters to be provided. The `video`, `image`, and `mask` work together to define the replacement operation, where the mask specifies which areas of the video will be replaced with the provided image.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The processed video with the specified object or region replaced. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Pikaswaps/en.md)

***

**Source fingerprint (SHA-256):** `007b7bc429fdada2fb8910392b056ae3a98d482cce9e280bdcd162ede497eb03`


# PorterDuffImageComposite - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PorterDuffImageComposite

The PorterDuffImageComposite node is designed to perform image compositing using the Porter-Duff compositing operators.

The PorterDuffImageComposite node is designed to perform image compositing using the Porter-Duff compositing operators. It allows for the combination of source and destination images according to various blending modes, enabling the creation of complex visual effects by manipulating image transparency and overlaying images in creative ways.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `source` | The source image tensor to be composited over the destination image. It plays a crucial role in determining the final visual outcome based on the selected compositing mode. | `IMAGE` |
| `source_alpha` | The alpha channel of the source image, which specifies the transparency of each pixel in the source image. It affects how the source image blends with the destination image. | `MASK` |
| `destination` | The destination image tensor that serves as the backdrop over which the source image is composited. It contributes to the final composited image based on the blending mode. | `IMAGE` |
| `destination_alpha` | The alpha channel of the destination image, defining the transparency of the destination image's pixels. It influences the blending of the source and destination images. | `MASK` |
| `mode` | The Porter-Duff compositing mode to apply, which determines how the source and destination images are blended together. Each mode creates different visual effects. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The composited image resulting from the application of the specified Porter-Duff mode. | `IMAGE` |
| `mask` | The alpha channel of the composited image, indicating the transparency of each pixel. | `MASK` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PorterDuffImageComposite/en.md)


# PreviewAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PreviewAudio

The Preview Audio node lets you listen to audio directly inside ComfyUI without saving it to the output directory.

The Preview Audio node lets you listen to audio directly inside ComfyUI without saving it to the output directory. It receives an audio input, checks that audio data is actually present, and then plays it through a preview player in the interface while passing the same audio on as its output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio data to preview. If this input is None, the node raises a ValueError, which can happen when the source video has no audio track. | AUDIO | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The audio data passed through unchanged from the input, so the node can be placed in the middle of a workflow. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PreviewAudio/en.md)

***

**Source fingerprint (SHA-256):** `02dbc5cb7d6924aae63c59e926a8ea265eb0889dbc2e6b47ff60f666a55d1adf`


# RTDETR_detect - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RTDETR_detect

The RT-DETR Detect node performs object detection on input images using an RT-DETR model.

The RT-DETR Detect node performs object detection on input images using an RT-DETR model. It identifies objects, returns bounding boxes around them, and labels them according to the COCO dataset classes. You can filter the results by confidence score, object class, and limit the total number of detections.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The RT-DETR model used for object detection. | MODEL | Yes | N/A |
| `image` | The input image(s) to detect objects in. The node processes images in batches of up to 32. | IMAGE | Yes | N/A |
| `threshold` | The minimum confidence score a detection must have to be included in the results (default: 0.5). | FLOAT | Yes | N/A |
| `class_name` | Filter detections by class. Set to 'all' to disable filtering (default: "all"). | COMBO | Yes | `"all"`<br />`"person"`<br />`"bicycle"`<br />`"car"`<br />`"motorcycle"`<br />`"airplane"`<br />`"bus"`<br />`"train"`<br />`"truck"`<br />`"boat"`<br />`"traffic light"`<br />`"fire hydrant"`<br />`"stop sign"`<br />`"parking meter"`<br />`"bench"`<br />`"bird"`<br />`"cat"`<br />`"dog"`<br />`"horse"`<br />`"sheep"`<br />`"cow"`<br />`"elephant"`<br />`"bear"`<br />`"zebra"`<br />`"giraffe"`<br />`"backpack"`<br />`"umbrella"`<br />`"handbag"`<br />`"tie"`<br />`"suitcase"`<br />`"frisbee"`<br />`"skis"`<br />`"snowboard"`<br />`"sports ball"`<br />`"kite"`<br />`"baseball bat"`<br />`"baseball glove"`<br />`"skateboard"`<br />`"surfboard"`<br />`"tennis racket"`<br />`"bottle"`<br />`"wine glass"`<br />`"cup"`<br />`"fork"`<br />`"knife"`<br />`"spoon"`<br />`"bowl"`<br />`"banana"`<br />`"apple"`<br />`"sandwich"`<br />`"orange"`<br />`"broccoli"`<br />`"carrot"`<br />`"hot dog"`<br />`"pizza"`<br />`"donut"`<br />`"cake"`<br />`"chair"`<br />`"couch"`<br />`"potted plant"`<br />`"bed"`<br />`"dining table"`<br />`"toilet"`<br />`"tv"`<br />`"laptop"`<br />`"mouse"`<br />`"remote"`<br />`"keyboard"`<br />`"cell phone"`<br />`"microwave"`<br />`"oven"`<br />`"toaster"`<br />`"sink"`<br />`"refrigerator"`<br />`"book"`<br />`"clock"`<br />`"vase"`<br />`"scissors"`<br />`"teddy bear"`<br />`"hair drier"`<br />`"toothbrush"` |
| `max_detections` | Maximum number of detections to return per image. In order of descending confidence score (default: 100). | INT | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `bboxes` | A list of bounding boxes for each input image. Each box contains coordinates (x, y, width, height), a class label, and a confidence score. | BOUNDINGBOX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RTDETR_detect/en.md)

***

**Source fingerprint (SHA-256):** `658a47cae788da207a52edc6bf8a428c9f3d8cf415e5f20f71d6125ad6d49734`


# RebatchImages - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RebatchImages

The RebatchImages node is designed to reorganize a batch of images into a new batch configuration, adjusting the batch size as specified.

The RebatchImages node is designed to reorganize a batch of images into a new batch configuration, adjusting the batch size as specified. This process is essential for managing and optimizing the processing of image data in batch operations, ensuring that images are grouped according to the desired batch size for efficient handling.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `images` | A list of images to be rebatched. This parameter is crucial for determining the input data that will undergo the rebatching process. | `IMAGE` |
| `batch_size` | Specifies the desired size of the output batches. This parameter directly influences how the input images are grouped and processed, impacting the structure of the output. | `INT` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The output consists of a list of image batches, reorganized according to the specified batch size. This allows for flexible and efficient processing of image data in batch operations. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RebatchImages/en.md)


# RecordAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecordAudio

The RecordAudio node loads audio files that have been recorded or selected through the audio recording interface.

The RecordAudio node loads audio files that have been recorded or selected through the audio recording interface. It processes the audio file and converts it into a waveform format that can be used by other audio processing nodes in the workflow. The node automatically detects the sample rate and prepares the audio data for further manipulation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio recording input from the audio recording interface | AUDIO\_RECORD | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `AUDIO` | The processed audio data containing waveform and sample rate information | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecordAudio/en.md)

***

**Source fingerprint (SHA-256):** `ca4dde492ecc4f57fcf87b022162692e3123ee90cce51186433ff8f14f606b70`


# RemoveBackground - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RemoveBackground

Documentation for RemoveBackground node.

## Overview

The Remove Background node generates a foreground mask that separates the main subject from the background of an input image. It uses a background removal model to analyze the image and produce a mask highlighting the foreground elements.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `bg_removal_model` | Background removal model used to generate the mask | BACKGROUND\_REMOVAL\_MODEL | Yes | N/A |
| `image` | Input image to remove the background from | IMAGE | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mask` | Generated foreground mask | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RemoveBackground/en.md)

***

**Source fingerprint (SHA-256):** `75b415acedaeaa1a694aeba2e4b0367524c6878e3e4a1f48b2a62898c68109f9`


# RepeatImageBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RepeatImageBatch

The RepeatImageBatch node is designed to replicate a given image a specified number of times, creating a batch of identical images.

The RepeatImageBatch node is designed to replicate a given image a specified number of times, creating a batch of identical images. This functionality is useful for operations that require multiple instances of the same image, such as batch processing or data augmentation.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The 'image' parameter represents the image to be replicated. It is crucial for defining the content that will be duplicated across the batch. | `IMAGE` |
| `amount` | The 'amount' parameter specifies the number of times the input image should be replicated. It directly influences the size of the output batch, allowing for flexible batch creation. | `INT` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The output is a batch of images, each identical to the input image, replicated according to the specified 'amount'. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RepeatImageBatch/en.md)


# SAM3_Detect - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3_Detect

Documentation for SAM3Detect node.

## Overview

The SAM3 Detect node performs open-vocabulary detection and segmentation using text descriptions, bounding boxes, or point prompts. It can identify and segment objects in an image based on what you describe in text, where you draw boxes, or where you click points.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The SAM3 model to use for detection and segmentation | MODEL | Yes | - |
| `image` | The input image to process | IMAGE | Yes | - |
| `conditioning` | Text conditioning from CLIPTextEncode. Required when using text prompts for detection | CONDITIONING | No | - |
| `bboxes` | Bounding boxes to segment within. Can be a single box (applied to all frames), a list of boxes (applied to all frames), or a list of lists (per-frame boxes). When provided without text conditioning, the node segments inside each box | BOUNDING\_BOX | No | - |
| `positive_coords` | Positive point prompts as JSON format `[{"x": int, "y": int}, ...]` using pixel coordinates. These are points you want to include in the segmentation | STRING | No | - |
| `negative_coords` | Negative point prompts as JSON format `[{"x": int, "y": int}, ...]` using pixel coordinates. These are points you want to exclude from the segmentation | STRING | No | - |
| `threshold` | Confidence threshold for text-based detections. Only detections with scores above this value are kept (default: 0.5) | FLOAT | No | 0.0 to 1.0 |
| `refine_iterations` | Number of SAM decoder refinement passes. Higher values can improve mask quality. Set to 0 to use raw detector masks without refinement (default: 2) | INT | No | 0 to 5 |
| `individual_masks` | When enabled, outputs separate masks for each detected object instead of combining them into a single mask (default: False) | BOOLEAN | No | True/False |

### Parameter Constraints and Notes

* **Text prompts**: To use text-based detection, you must provide `conditioning` input. When text conditioning is provided, the node runs text-guided detection on the image.
* **Box prompts**: When `bboxes` are provided without text conditioning, the node segments the area inside each bounding box.
* **Point prompts**: When `positive_coords` or `negative_coords` are provided, the node uses point-based segmentation. Points are scaled to the model's internal resolution automatically.
* **Multiple prompt types**: You can combine different prompt types. For example, you can provide both text conditioning and bounding boxes to restrict text detection to specific areas.
* **Batch processing**: The node supports batched images. When processing multiple frames, bounding boxes can be provided per-frame using a list of lists format.
* **JSON format for points**: Point coordinates must be provided as valid JSON strings in the format `[{"x": 100, "y": 200}, {"x": 150, "y": 250}]`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `masks` | Segmentation masks. When `individual_masks` is False (default), returns a single combined mask per frame. When True, returns individual masks for each detected object | MASK |
| `bboxes` | Detected bounding boxes with coordinates and confidence scores. Each box includes `x`, `y`, `width`, `height`, and `score` values | BOUNDING\_BOX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3_Detect/en.md)

***

**Source fingerprint (SHA-256):** `3f61343c284c249476f2010831863c6094260b11d0a348003b270a126c67d399`


# SAM3_TrackPreview - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3_TrackPreview

Documentation for SAM3TrackPreview node.

## Overview

This node creates a video preview of tracked objects, drawing each tracked object with a distinct color overlay and a number label. It does not output any image or video tensors — instead, it saves the resulting preview video directly to a temporary file.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `track_data` | The tracking data containing packed masks and object information from a SAM3 tracking node. | TRACK\_DATA | Yes | - |
| `images` | Optional input images to use as the background for the preview. If not provided, a black background is used. | IMAGE | No | - |
| `opacity` | The opacity of the color overlay applied to tracked objects (default: 0.5). | FLOAT | No | 0.0 to 1.0 (step: 0.05) |
| `fps` | The frame rate of the output video (default: 24.0). | FLOAT | No | 1.0 to 120.0 (step: 1.0) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `ui` | A UI element that displays the generated preview video. No tensor data is returned. | PREVIEW\_VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3_TrackPreview/en.md)

***

**Source fingerprint (SHA-256):** `76389f354c8acdf249137d966765069d530034a0f8eeb39d769bde3c0f7a1bd0`


# SAM3_TrackToMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3_TrackToMask

Documentation for SAM3TrackToMask node.

## Overview

Selects specific tracked objects from a SAM3 tracking session by their index numbers and combines them into a single output mask. This allows you to choose which objects to keep and which to ignore from the tracking results.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `track_data` | The tracking data output from a SAM3 tracker node, containing the packed masks and original image size. | SAM3TRACKDATA | Yes | N/A |
| `object_indices` | Comma-separated object indices to include in the output mask (e.g., '0,2,3'). If left empty, all tracked objects are included. | STRING | No | Any comma-separated list of integers |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `masks` | A single binary mask for each frame, where selected objects are combined into one mask. If no objects are selected or no tracking data exists, returns a zero mask. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3_TrackToMask/en.md)

***

**Source fingerprint (SHA-256):** `77c9f5142f2078fabb81e58979df01ad9ec41d3de953939570bebb4f2687f8ad`


# SAM3_VideoTrack - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3_VideoTrack

Track objects across video frames using SAM3's memory-based tracker.

Track objects across video frames using SAM3's memory-based tracker. The node processes a sequence of video frames and maintains object identities across frames, using either initial masks or text prompts to define what to track, and can detect new objects along the way using text conditioning.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Video frames as batched images | IMAGE | Yes | Batched video frames |
| `model` | The SAM3 model to use for tracking | MODEL | Yes | SAM3 model |
| `initial_mask` | Mask(s) for the first frame to track (one per object) | MASK | No | One mask per object |
| `conditioning` | Text conditioning for detecting new objects during tracking | CONDITIONING | No | Text conditioning |
| `detection_threshold` | Score threshold for text-prompted detection (default: 0.5) | FLOAT | No | 0.0 to 1.0 (step 0.01) |
| `max_objects` | Max tracked objects. Initial masks count toward this limit. 0 uses the internal cap of 64. (default: 4) | INT | No | 0 to 64 |
| `detect_interval` | Run detection every N frames (1=every frame). Higher values save compute. (default: 1) | INT | No | 1 or higher |

**Note:** Either `initial_mask` or `conditioning` must be provided. If both are omitted, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `track_data` | Tracking data containing object masks and metadata across all video frames | SAM3\_TRACK\_DATA |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3_VideoTrack/en.md)

***

**Source fingerprint (SHA-256):** `ef584628b334997a001a857a7deffb7eda34db8fa50e3d734a07b5e92566d48d`


# SVD_img2vid_Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SVD_img2vid_Conditioning

The SVDimg2vidConditioning node prepares conditioning data for video generation using Stable Video Diffusion.

The SVD\_img2vid\_Conditioning node prepares conditioning data for video generation using Stable Video Diffusion. It takes an initial image and processes it through CLIP vision and VAE encoders to create positive and negative conditioning pairs, along with an empty latent space for video generation. This node sets up the necessary parameters for controlling motion, frame rate, and augmentation levels in the generated video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_vision` | CLIP vision model for encoding the input image | CLIP\_VISION | Yes | - |
| `init_image` | Initial image to use as the starting point for video generation | IMAGE | Yes | - |
| `vae` | VAE model for encoding the image into latent space | VAE | Yes | - |
| `width` | Output video width (default: 1024, step: 8) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Output video height (default: 576, step: 8) | INT | Yes | 16 to MAX\_RESOLUTION |
| `video_frames` | Number of frames to generate in the video (default: 14) | INT | Yes | 1 to 4096 |
| `motion_bucket_id` | Controls the amount of motion in the generated video (default: 127) | INT | Yes | 1 to 1023 |
| `fps` | Frames per second for the generated video (default: 6) | INT | Yes | 1 to 1024 |
| `augmentation_level` | Level of noise augmentation to apply to the input image (default: 0.0, step: 0.01) | FLOAT | Yes | 0.0 to 10.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning data containing image embeddings and video parameters | CONDITIONING |
| `negative` | Negative conditioning data with zeroed embeddings and video parameters | CONDITIONING |
| `latent` | Empty latent space tensor ready for video generation | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SVD_img2vid_Conditioning/en.md)

***

**Source fingerprint (SHA-256):** `33b295b6f2e459852aaa95d9dca26c724aa2e9ad0f884a1c7760766530a00a09`


# SamplerEulerCFGpp - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerEulerCFGpp

The SamplerEulerCFGpp node provides an Euler CFG++ sampling method for generating outputs.

The SamplerEulerCFGpp node provides an Euler CFG++ sampling method for generating outputs. This node offers two different implementation versions of the Euler CFG++ sampler that can be selected based on user preference.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `version` | The implementation version of the Euler CFG++ sampler to use (default: "regular") | STRING | Yes | `"regular"`<br />`"alternative"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | Returns a configured Euler CFG++ sampler instance | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerEulerCFGpp/en.md)

***

**Source fingerprint (SHA-256):** `ff80ae845259b6fd415f11f20bb224617c7a6134b8e02799fef4549d42d44b83`


# SaveAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAudio

This node saves audio data to a file in FLAC format.

This node saves audio data to a file in FLAC format. It takes an audio input and writes it to the output directory using the specified filename prefix, and also passes the audio through to its output. This node is deprecated and should be replaced with the current Save Audio node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio data to be saved | AUDIO | Yes | - |
| `filename_prefix` | The prefix for the output filename (default: "audio/ComfyUI") | STRING | No | - |

*Note: The `prompt` and `extra_pnginfo` parameters are hidden and automatically handled by the system.*

If the `audio` input receives no data (for example, when the source video has no audio track), the node raises an error and no file is saved.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The audio data that was provided to the input, passed through after the file is saved | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveAudio/en.md)

***

**Source fingerprint (SHA-256):** `6ac62d315f14213091cd179a05f0bbd51f1b1a5056bb5c06ca137d2b574d6017`


# SaveAudioAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAudioAdvanced

Saves the input audio to your ComfyUI output directory.

Saves the input audio to your ComfyUI output directory. This node allows you to export audio in various formats including FLAC, MP3, and Opus with configurable quality settings.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio to save. | AUDIO | Yes | - |
| `filename_prefix` | The prefix for the file to save. May include formatting tokens such as %date:yyyy-MM-dd%. (default: "audio/ComfyUI") | STRING | Yes | - |
| `format` | The file format in which to save the audio. | DYNAMIC\_COMBO | Yes | "flac"<br />"mp3"<br />"opus" |

### MP3 Inputs

When "mp3" is selected as the format, the following setting becomes available.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `quality` | The encoding quality of the output MP3 file. (default: "V0") | COMBO | No | "V0"<br />"128k"<br />"320k" |

### Opus Inputs

When "opus" is selected as the format, the following setting becomes available.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `quality` | The encoding quality of the output Opus file. (default: "128k") | COMBO | No | "64k"<br />"96k"<br />"128k"<br />"192k"<br />"320k" |

Note: The `quality` setting is only available when the matching format is selected. When "flac" is selected, no additional quality setting is available.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The input audio, passed through unchanged after being saved. | AUDIO |

The node also returns UI information containing the saved audio file information.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveAudioAdvanced/en.md)

***

**Source fingerprint (SHA-256):** `5f3af49670b485bbd31f0ed0c5667c12e9b9b23014cadcf64442a486255d0e6d`


# SaveAudioMP3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAudioMP3

The SaveAudioMP3 node saves audio data as an MP3 file.

The SaveAudioMP3 node saves audio data as an MP3 file. It takes an audio input and exports it to the output directory with a customizable filename and quality setting, handling file naming and MP3 format conversion automatically. **This node is deprecated and may be removed in future versions.**

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio data to be saved as an MP3 file | AUDIO | Yes | - |
| `filename_prefix` | The prefix for the output filename (default: "audio/ComfyUI") | STRING | No | - |
| `quality` | The audio quality setting for the MP3 file (default: "V0") | COMBO | No | `"V0"`<br />`"128k"`<br />`"320k"` |
| `prompt` | Internal prompt data, automatically provided by the system | PROMPT | No | - |
| `extra_pnginfo` | Additional PNG information, automatically provided by the system | EXTRA\_PNGINFO | No | - |

**Note:** If the input `audio` is None (for example, when the source video has no audio track), the node raises a ValueError.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The audio data that was saved to an MP3 file | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveAudioMP3/en.md)

***

**Source fingerprint (SHA-256):** `7d3b439dfd7cb211dd6568f6b5124bb225909dcf0ae150addc4ca226d947a4f0`


# SaveAudioOpus - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAudioOpus

The SaveAudioOpus node saves audio data to a file in the Opus format, letting you choose the encoding quality (bitrate) and the filename prefix for the exported file.

The SaveAudioOpus node saves audio data to a file in the Opus format, letting you choose the encoding quality (bitrate) and the filename prefix for the exported file. This node is deprecated and may be removed in future versions.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio data to be saved as an Opus file. A ValueError is raised if this is None (for example, when the source video has no audio track). | AUDIO | Yes | - |
| `filename_prefix` | The prefix used for the output filename (default: "audio/ComfyUI"). | STRING | No | - |
| `quality` | The bitrate used to encode the Opus file; higher values produce better quality but larger files (default: "128k"). | COMBO | No | `"64k"`<br />`"96k"`<br />`"128k"`<br />`"192k"`<br />`"320k"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The audio data that was saved to the Opus file. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveAudioOpus/en.md)

***

**Source fingerprint (SHA-256):** `a2f585f45299759738fa85f6b73f51680d4e86da57d3fc9c2236e66114fa3d6c`


# Sd4xupscaleConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Sd4xupscaleConditioning

This node specializes in enhancing the resolution of images through a 4x upscale process, incorporating conditioning elements to refine the output.

This node specializes in enhancing the resolution of images through a 4x upscale process, incorporating conditioning elements to refine the output. It leverages diffusion techniques to upscale images while allowing for the adjustment of scale ratio and noise augmentation to fine-tune the enhancement process.

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `images` | The input images to be upscaled. This parameter is crucial as it directly influences the quality and resolution of the output images. | `IMAGE` |
| `positive` | Positive conditioning elements that guide the upscale process towards desired attributes or features in the output images. | `CONDITIONING` |
| `negative` | Negative conditioning elements that the upscale process should avoid, helping to steer the output away from undesired attributes or features. | `CONDITIONING` |
| `scale_ratio` | Determines the factor by which the image resolution is increased. A higher scale ratio results in a larger output image, allowing for greater detail and clarity. | `FLOAT` |
| `noise_augmentation` | Controls the level of noise augmentation applied during the upscale process. This can be used to introduce variability and improve the robustness of the output images. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `positive` | The refined positive conditioning elements resulting from the upscale process. | `CONDITIONING` |
| `negative` | The refined negative conditioning elements resulting from the upscale process. | `CONDITIONING` |
| `latent` | A latent representation generated during the upscale process, which can be utilized in further processing or model training. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Sd4xupscaleConditioning/en.md)


# SelfAttentionGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SelfAttentionGuidance

The Self-Attention Guidance node applies guidance to diffusion models by modifying the attention mechanism during the sampling process.

The Self-Attention Guidance node applies guidance to diffusion models by modifying the attention mechanism during the sampling process. It captures attention scores from unconditional denoising steps and uses them to create blurred guidance maps that influence the final output. This technique helps guide the generation process by leveraging the model's own attention patterns.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to apply self-attention guidance to | MODEL | Yes | - |
| `scale` | The strength of the self-attention guidance effect (default: 0.5) | FLOAT | No | -2.0 to 5.0 |
| `blur_sigma` | The amount of blur applied to create the guidance map (default: 2.0) | FLOAT | No | 0.0 to 10.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with self-attention guidance applied | MODEL |

**Note:** This node is currently experimental and has limitations with chunked batches. It can only save attention scores from one UNet call and may not work properly with larger batch sizes.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SelfAttentionGuidance/en.md)

***

**Source fingerprint (SHA-256):** `ab8f7a0cf19c85f8e77b2d6b380c0224a407a900a42341de7503f5394a3216fb`


# ShuffleDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ShuffleDataset

The Shuffle Dataset node takes a list of images and randomly changes their order.

The Shuffle Dataset node takes a list of images and randomly changes their order. It uses a seed value to control the randomness, ensuring the same shuffle order can be reproduced. This is useful for randomizing the sequence of images in a dataset before processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The list of images to be shuffled. | IMAGE | Yes | - |
| `seed` | Random seed. (default: 0) | INT | No | 0 to 18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The same list of images, but in a new, randomly shuffled order. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ShuffleDataset/en.md)

***

**Source fingerprint (SHA-256):** `6cde5dcf15817ab98f35f7b2e40fe79a5451c86dba93c0e3cd2622d1cec76c36`


# ShuffleImageTextDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ShuffleImageTextDataset

This node shuffles a list of images and a list of texts together, keeping their pairings intact.

This node shuffles a list of images and a list of texts together, keeping their pairings intact. It uses a random seed to determine the shuffle order, ensuring the same input lists will be shuffled in the same way each time the seed is reused.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | List of images to shuffle. | IMAGE | Yes | - |
| `texts` | List of texts to shuffle. | STRING | Yes | - |
| `seed` | Random seed. The shuffle order is determined by this value (default: 0). | INT | No | 0 to 18446744073709551615 |

**Note:** The `images` and `texts` inputs must be lists of the same length. The node will pair the first image with the first text, the second image with the second text, and so on, before shuffling these pairs together.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The shuffled list of images. | IMAGE |
| `texts` | The shuffled list of texts, maintaining their original pairings with the images. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ShuffleImageTextDataset/en.md)

***

**Source fingerprint (SHA-256):** `77050e9f7255e64b07bd394908b679acef399d78ec9be7c1346d6f297c109968`


# SplitAudioChannels - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplitAudioChannels

The SplitAudioChannels node separates stereo audio into individual left and right channels.

The SplitAudioChannels node separates stereo audio into individual left and right channels. It takes a stereo audio input with two channels and outputs two separate audio streams, one for the left channel and one for the right channel.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The stereo audio input to be separated into channels | AUDIO | Yes | - |

**Note:** The input audio must have exactly two channels (stereo). The node will raise an error if the input audio has only one channel.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `left` | The separated left channel audio | AUDIO |
| `right` | The separated right channel audio | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SplitAudioChannels/en.md)

***

**Source fingerprint (SHA-256):** `c6e6ecb219e0cb47b003ec9c28fdc060ef83bf1c8bd77d9fb29a088d55a9ab3f`


# SplitImageToTileList - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplitImageToTileList

The Split Image into List of Tiles node divides a single input image into a series of smaller, overlapping rectangular sections called tiles.

The Split Image into List of Tiles node divides a single input image into a series of smaller, overlapping rectangular sections called tiles. It creates a batched list of these tiles, which can be processed individually by other nodes. The size of each tile and the amount of overlap between them can be specified.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be split into tiles. | IMAGE | Yes | - |
| `tile_width` | The width of each output tile in pixels (default: 1024). | INT | Yes | 64 to 1048576 |
| `tile_height` | The height of each output tile in pixels (default: 1024). | INT | Yes | 64 to 1048576 |
| `overlap` | The number of pixels that adjacent tiles will overlap (default: 128). | INT | Yes | 0 to 4096 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | A batched list containing all the individual image tiles. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SplitImageToTileList/en.md)

***

**Source fingerprint (SHA-256):** `4a04e7042446c2368091ffd051c781f9f0ec8496ab681ee9e0741bb269bb54af`


# SplitImageWithAlpha - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplitImageWithAlpha

The SplitImageWithAlpha node is designed to separate the color and alpha components of an image.

The SplitImageWithAlpha node is designed to separate the color and alpha components of an image. It processes an input image tensor, extracting the RGB channels as the color component and the alpha channel as the transparency component, facilitating operations that require manipulation of these distinct image aspects.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The 'image' parameter represents the input image tensor from which the RGB and alpha channels are to be separated. It is crucial for the operation as it provides the source data for the split. | `IMAGE` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The 'image' output represents the separated RGB channels of the input image, providing the color component without the transparency information. | `IMAGE` |
| `mask` | The 'mask' output represents the separated alpha channel of the input image, providing the transparency information. | `MASK` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SplitImageWithAlpha/en.md)


# StableCascade_SuperResolutionControlnet - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableCascade_SuperResolutionControlnet

This node is part of the experimental Stable Cascade group.

This node is part of the experimental Stable Cascade group. It prepares inputs for Stable Cascade super-resolution processing by encoding an input image with a VAE to create a controlnet input, and by generating empty (zero-filled) latent placeholders for stage C and stage B of the Stable Cascade pipeline.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be processed for super-resolution. Only the first 3 color channels (RGB) of the image are used for encoding. | IMAGE | Yes | - |
| `vae` | The VAE model used to encode the input image | VAE | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `controlnet_input` | The VAE-encoded image representation suitable for controlnet input | IMAGE |
| `stage_c` | Placeholder (zero-filled) latent representation for stage C of Stable Cascade processing, with 16 channels and dimensions based on the input image size divided by 16 | LATENT |
| `stage_b` | Placeholder (zero-filled) latent representation for stage B of Stable Cascade processing, with 4 channels and dimensions based on the input image size divided by 2 | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableCascade_SuperResolutionControlnet/en.md)

***

**Source fingerprint (SHA-256):** `d9eff373ac7736f2e2f9788d1b43c04bb3212422aa1703d1d58ac512ce476925`


# Stablezero123Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Stablezero123Conditioning

This node is designed to process and condition data for use in StableZero123 models, focusing on preparing the input in a specific format that is compatible and optimized for these

This node is designed to process and condition data for use in StableZero123 models, focusing on preparing the input in a specific format that is compatible and optimized for these models.

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `clip_vision` | Processes visual data to align with the model's requirements, enhancing the model's understanding of visual context. | `CLIP_VISION` |
| `init_image` | Serves as the initial image input for the model, setting the baseline for further image-based operations. | `IMAGE` |
| `vae` | Integrates variational autoencoder outputs, facilitating the model's ability to generate or modify images. | `VAE` |
| `width` | Specifies the width of the output image, allowing for dynamic resizing according to model needs. | `INT` |
| `height` | Determines the height of the output image, enabling customization of the output dimensions. | `INT` |
| `batch_size` | Controls the number of images processed in a single batch, optimizing computational efficiency. | `INT` |
| `elevation` | Adjusts the elevation angle for 3D model rendering, enhancing the model's spatial understanding. | `FLOAT` |
| `azimuth` | Modifies the azimuth angle for 3D model visualization, improving the model's perception of orientation. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `positive` | Generates positive conditioning vectors, aiding in the model's positive feature reinforcement. | `CONDITIONING` |
| `negative` | Produces negative conditioning vectors, assisting in the model's avoidance of certain features. | `CONDITIONING` |
| `latent` | Creates latent representations, facilitating deeper model insights into the data. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Stablezero123Conditioning/en.md)


# Stablezero123ConditioningBatched - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Stablezero123ConditioningBatched

This node is designed to process conditioning information in a batched manner specifically tailored for the StableZero123 model.

This node is designed to process conditioning information in a batched manner specifically tailored for the StableZero123 model. It focuses on efficiently handling multiple sets of conditioning data simultaneously, optimizing the workflow for scenarios where batch processing is crucial.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `clip_vision` | The CLIP vision embeddings that provide visual context for the conditioning process. | `CLIP_VISION` |
| `init_image` | The initial image to be conditioned upon, serving as a starting point for the generation process. | `IMAGE` |
| `vae` | The variational autoencoder used for encoding and decoding images in the conditioning process. | `VAE` |
| `width` | The width of the output image. | `INT` |
| `height` | The height of the output image. | `INT` |
| `batch_size` | The number of conditioning sets to be processed in a single batch. | `INT` |
| `elevation` | The elevation angle for 3D model conditioning, affecting the perspective of the generated image. | `FLOAT` |
| `azimuth` | The azimuth angle for 3D model conditioning, affecting the orientation of the generated image. | `FLOAT` |
| `elevation_batch_increment` | The incremental change in elevation angle across the batch, allowing for varied perspectives. | `FLOAT` |
| `azimuth_batch_increment` | The incremental change in azimuth angle across the batch, allowing for varied orientations. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning output, tailored for promoting certain features or aspects in the generated content. | `CONDITIONING` |
| `negative` | The negative conditioning output, tailored for demoting certain features or aspects in the generated content. | `CONDITIONING` |
| `latent` | The latent representation derived from the conditioning process, ready for further processing or generation steps. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Stablezero123ConditioningBatched/en.md)


# SvdImg2vidConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SvdImg2vidConditioning

This node is designed for generating conditioning data for video generation tasks, specifically tailored for use with SVDimg2vid models.

This node is designed for generating conditioning data for video generation tasks, specifically tailored for use with SVD\_img2vid models. It takes various inputs including initial images, video parameters, and a VAE model to produce conditioning data that can be used to guide the generation of video frames.

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `clip_vision` | Represents the CLIP vision model used for encoding visual features from the initial image, playing a crucial role in understanding the content and context of the image for video generation. | `CLIP_VISION` |
| `init_image` | The initial image from which the video will be generated, serving as the starting point for the video generation process. | `IMAGE` |
| `vae` | A Variational Autoencoder (VAE) model used for encoding the initial image into a latent space, facilitating the generation of coherent and continuous video frames. | `VAE` |
| `width` | The desired width of the video frames to be generated, allowing for customization of the video's resolution. | `INT` |
| `height` | The desired height of the video frames, enabling control over the video's aspect ratio and resolution. | `INT` |
| `video_frames` | Specifies the number of frames to be generated for the video, determining the video's length. | `INT` |
| `motion_bucket_id` | An identifier for categorizing the type of motion to be applied in the video generation, aiding in the creation of dynamic and engaging videos. | `INT` |
| `fps` | The frames per second (fps) rate for the video, influencing the smoothness and realism of the generated video. | `INT` |
| `augmentation_level` | A parameter controlling the level of augmentation applied to the initial image, affecting the diversity and variability of the generated video frames. | `FLOAT` |

## Outputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `positive` | The positive conditioning data, consisting of encoded features and parameters for guiding the video generation process in a desired direction. | `CONDITIONING` |
| `negative` | The negative conditioning data, providing a contrast to the positive conditioning, which can be used to avoid certain patterns or features in the generated video. | `CONDITIONING` |
| `latent` | Latent representations generated for each frame of the video, serving as a foundational component for the video generation process. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SvdImg2vidConditioning/en.md)


# TorchCompileModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TorchCompileModel

The TorchCompileModel node applies PyTorch compilation to a model to optimize its performance.

The TorchCompileModel node applies PyTorch compilation to a model to optimize its performance. It creates a copy of the input model and wraps it with PyTorch's compilation functionality using the specified backend. This can improve the model's execution speed during inference.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to be compiled and optimized | MODEL | Yes | - |
| `backend` | The PyTorch compilation backend to use for optimization (default: "inductor") | STRING | Yes | "inductor"<br />"cudagraphs" |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The compiled model with PyTorch compilation applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TorchCompileModel/en.md)

***

**Source fingerprint (SHA-256):** `240c6eb84ce2b93fe4d7c04fcf69df571e662f17893a4fd8e721241ea082edc8`


# TrimAudioDuration - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TrimAudioDuration

The TrimAudioDuration node allows you to cut a specific time segment from an audio file.

The TrimAudioDuration node allows you to cut a specific time segment from an audio file. You can specify when to start the trim and how long the resulting audio clip should be. The node works by converting time values to audio frame positions and extracting the corresponding portion of the audio waveform.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio input to be trimmed | AUDIO | Yes | - |
| `start_index` | Start time in seconds, can be negative to count from the end (supports sub-seconds). Default: 0.0 | FLOAT | Yes | -0xffffffffffffffff to 0xffffffffffffffff |
| `duration` | Duration in seconds. Default: 60.0 | FLOAT | Yes | 0.0 to 0xffffffffffffffff |

**Note:** The start time must be less than the end time and within the audio length. Negative start values count backwards from the end of the audio. If the start time is negative, it is converted to a frame position counting from the end of the audio. The start and end frames are clamped to the audio boundaries. If the start time equals or exceeds the end time, the node will raise an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The trimmed audio segment with the specified start time and duration | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TrimAudioDuration/en.md)

***

**Source fingerprint (SHA-256):** `4f8c9f966fec8c1d1a1a2bb531014fe7460d61abbafdc367adb667a5044752ef`


# UNetCrossAttentionMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UNetCrossAttentionMultiply

The UNetCrossAttentionMultiply node applies multiplication factors to the cross-attention mechanism in a UNet model.

The UNetCrossAttentionMultiply node applies multiplication factors to the cross-attention mechanism in a UNet model. It allows you to scale the query, key, value, and output components of the cross-attention layers to experiment with different attention behaviors and effects.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The UNet model to modify with attention scaling factors | MODEL | Yes | - |
| `q` | Scaling factor for query components in cross-attention (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `k` | Scaling factor for key components in cross-attention (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `v` | Scaling factor for value components in cross-attention (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `out` | Scaling factor for output components in cross-attention (default: 1.0) | FLOAT | No | 0.0 - 10.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified UNet model with scaled cross-attention components | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/UNetCrossAttentionMultiply/en.md)

***

**Source fingerprint (SHA-256):** `f55a6809be88bfb32fa2c70fabd0e5bb7360be78670c9473d4a79517b811454e`


# UNetSelfAttentionMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UNetSelfAttentionMultiply

The UNetSelfAttentionMultiply node applies multiplication factors to the query, key, value, and output components of the self-attention mechanism in a UNet model.

The UNetSelfAttentionMultiply node applies multiplication factors to the query, key, value, and output components of the self-attention mechanism in a UNet model. It allows you to scale different parts of the attention computation to experiment with how attention weights affect the model's behavior.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The UNet model to modify with attention scaling factors | MODEL | Yes | - |
| `q` | Multiplication factor for query component (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `k` | Multiplication factor for key component (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `v` | Multiplication factor for value component (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `out` | Multiplication factor for output component (default: 1.0) | FLOAT | No | 0.0 - 10.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The modified UNet model with scaled attention components | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/UNetSelfAttentionMultiply/en.md)

***

**Source fingerprint (SHA-256):** `7a6039eb2faae56437a5eb6fe01be6d38e53c0632175a3405a1e24a476d4da82`


# UNetTemporalAttentionMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UNetTemporalAttentionMultiply

The UNetTemporalAttentionMultiply node applies multiplication factors to different types of attention mechanisms in a temporal UNet model.

The UNetTemporalAttentionMultiply node applies multiplication factors to different types of attention mechanisms in a temporal UNet model. It modifies the model by adjusting the weights of self-attention and cross-attention layers, distinguishing between structural and temporal components. This allows fine-tuning of how much influence each attention type has on the model's output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The input model to modify with attention multipliers | MODEL | Yes | - |
| `self_structural` | Multiplier for self-attention structural components (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `self_temporal` | Multiplier for self-attention temporal components (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `cross_structural` | Multiplier for cross-attention structural components (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `cross_temporal` | Multiplier for cross-attention temporal components (default: 1.0) | FLOAT | No | 0.0 - 10.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with adjusted attention weights | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/UNetTemporalAttentionMultiply/en.md)

***

**Source fingerprint (SHA-256):** `b43c7c51cbc71349dd267c4abe1704899a394e205a60a13b45869f690d83a0f0`


# Wan Vace To Video - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/conditioning/video-models/wan-vace-to-video

Create videos using Alibaba Tongyi Wanxiang's high-resolution video generation API

<img alt="Wan Vace To Video" />

The Wan Vace To Video node allows you to generate videos through text prompts and supports multiple input methods, including text, images, videos, masks, and control signals.

This node combines input conditions (prompts), control videos, and masks to generate high-quality videos. It first preprocesses and encodes the inputs, then applies the conditional information to generate the final video latent representation.
When a reference image is provided, it serves as the initial reference for the video. Control videos and masks can be used to guide the generation process, making the generated video more aligned with expectations.

## Parameter Description

### Required Parameters

| Parameter | Type | Default | Range | Description |
| - | - | - | - | - |
| positive | CONDITIONING | - | - | Positive prompt condition |
| negative | CONDITIONING | - | - | Negative prompt condition |
| vae | VAE | - | - | VAE model for encoding/decoding |
| width | INT | 832 | 16-MAX\_RESOLUTION | Video width, step size 16 |
| height | INT | 480 | 16-MAX\_RESOLUTION | Video height, step size 16 |
| length | INT | 81 | 1-MAX\_RESOLUTION | Number of video frames, step size 4 |
| batch\_size | INT | 1 | 1-4096 | Batch size |
| strength | FLOAT | 1.0 | 0.0-1000.0 | Condition strength for VACE control, step size 0.01. This is not a LoRA strength. LoRA weights are applied through separate LoRA nodes. |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| control\_video | IMAGE | Control video for guiding the generation process |
| control\_masks | MASK | Control masks defining which areas should be controlled |
| reference\_image | IMAGE | Reference image as starting point or reference (single image) |

### Output Parameters

| Parameter | Type | Description |
| - | - | - |
| positive | CONDITIONING | Processed positive prompt condition |
| negative | CONDITIONING | Processed negative prompt condition |
| latent | LATENT | Generated video latent representation |
| trim\_latent | INT | Parameter for trimming latent representation, default value is 0. When a reference image is provided, this value is set to the shape size of the reference image in latent space. It indicates how much content from the reference image downstream nodes should trim from the generated latent representation to ensure proper control of the reference image's influence in the final video output. |

## Source Code

\[Source code update time: 2025-05-15]

```Python theme={null}
class WanVaceToVideo:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {"positive": ("CONDITIONING", ),
                             "negative": ("CONDITIONING", ),
                             "vae": ("VAE", ),
                             "width": ("INT", {"default": 832, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
                             "height": ("INT", {"default": 480, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
                             "length": ("INT", {"default": 81, "min": 1, "max": nodes.MAX_RESOLUTION, "step": 4}),
                             "batch_size": ("INT", {"default": 1, "min": 1, "max": 4096}),
                             "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1000.0, "step": 0.01}),
                },
                "optional": {"control_video": ("IMAGE", ),
                             "control_masks": ("MASK", ),
                             "reference_image": ("IMAGE", ),
                }}

    RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "LATENT", "INT")
    RETURN_NAMES = ("positive", "negative", "latent", "trim_latent")
    FUNCTION = "encode"

    CATEGORY = "conditioning/video_models"

    EXPERIMENTAL = True

    def encode(self, positive, negative, vae, width, height, length, batch_size, strength, control_video=None, control_masks=None, reference_image=None):
        latent_length = ((length - 1) // 4) + 1
        if control_video is not None:
            control_video = comfy.utils.common_upscale(control_video[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
            if control_video.shape[0] < length:
                control_video = torch.nn.functional.pad(control_video, (0, 0, 0, 0, 0, 0, 0, length - control_video.shape[0]), value=0.5)
        else:
            control_video = torch.ones((length, height, width, 3)) * 0.5

        if reference_image is not None:
            reference_image = comfy.utils.common_upscale(reference_image[:1].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
            reference_image = vae.encode(reference_image[:, :, :, :3])
            reference_image = torch.cat([reference_image, comfy.latent_formats.Wan21().process_out(torch.zeros_like(reference_image))], dim=1)

        if control_masks is None:
            mask = torch.ones((length, height, width, 1))
        else:
            mask = control_masks
            if mask.ndim == 3:
                mask = mask.unsqueeze(1)
            mask = comfy.utils.common_upscale(mask[:length], width, height, "bilinear", "center").movedim(1, -1)
            if mask.shape[0] < length:
                mask = torch.nn.functional.pad(mask, (0, 0, 0, 0, 0, 0, 0, length - mask.shape[0]), value=1.0)

        control_video = control_video - 0.5
        inactive = (control_video * (1 - mask)) + 0.5
        reactive = (control_video * mask) + 0.5

        inactive = vae.encode(inactive[:, :, :, :3])
        reactive = vae.encode(reactive[:, :, :, :3])
        control_video_latent = torch.cat((inactive, reactive), dim=1)
        if reference_image is not None:
            control_video_latent = torch.cat((reference_image, control_video_latent), dim=2)

        vae_stride = 8
        height_mask = height // vae_stride
        width_mask = width // vae_stride
        mask = mask.view(length, height_mask, vae_stride, width_mask, vae_stride)
        mask = mask.permute(2, 4, 0, 1, 3)
        mask = mask.reshape(vae_stride * vae_stride, length, height_mask, width_mask)
        mask = torch.nn.functional.interpolate(mask.unsqueeze(0), size=(latent_length, height_mask, width_mask), mode='nearest-exact').squeeze(0)

        trim_latent = 0
        if reference_image is not None:
            mask_pad = torch.zeros_like(mask[:, :reference_image.shape[2], :, :])
            mask = torch.cat((mask_pad, mask), dim=1)
            latent_length += reference_image.shape[2]
            trim_latent = reference_image.shape[2]

        mask = mask.unsqueeze(0)
        positive = node_helpers.conditioning_set_values(positive, {"vace_frames": control_video_latent, "vace_mask": mask, "vace_strength": strength})
        negative = node_helpers.conditioning_set_values(negative, {"vace_frames": control_video_latent, "vace_mask": mask, "vace_strength": strength})

        latent = torch.zeros([batch_size, 16, latent_length, height // 8, width // 8], device=comfy.model_management.intermediate_device())
        out_latent = {}
        out_latent["samples"] = latent
        return (positive, negative, out_latent, trim_latent)

```


# Recraft Style - Logo Raster - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-style-logo-raster

Helper node for setting logo raster style in Recraft image generation

<img alt="ComfyUI Built-in Recraft Style - Logo Raster Node" />

This node creates a style configuration object that guides Recraft's image generation process toward professional logo design effects. By selecting different substyles, you can define the design style, complexity and use cases of the generated logo.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| substyle | Selection | - | Specific substyle for logo raster (Required) |

### Output

| Output | Type | Description |
| - | - | - |
| recraft\_style | Recraft Style | Style configuration object, connects to Recraft generation node |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}
class RecraftStyleV3LogoRasterNode(RecraftStyleV3RealisticImageNode):
    """
    Select vector_illustration style and optional substyle.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "substyle": (get_v3_substyles(s.RECRAFT_STYLE, include_none=False),),
            }
        }

    RECRAFT_STYLE = RecraftStyleV3.logo_raster
```


# Recraft Style - Realistic Image - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-style-realistic-image

A helper node for setting realistic photo style in Recraft image generation

<img alt="ComfyUI Native Recraft Style - Realistic Image Node" />

The Recraft Style - Realistic Image node helps set up realistic photo styles for Recraft image generation, with various substyle options to control the visual characteristics of generated images.

## Node Function

This node creates a style configuration object that guides Recraft's image generation process towards realistic photo effects.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| substyle | select | None | Specific substyle of realistic photo (Required) |

### Output

| Output | Type | Description |
| - | - | - |
| recraft\_style | Recraft Style | Style config object to connect to Recraft generation nodes |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class RecraftStyleV3RealisticImageNode:
    """
    Select realistic_image style and optional substyle.
    """

    RETURN_TYPES = (RecraftIO.STYLEV3,)
    RETURN_NAMES = ("recraft_style",)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "create_style"
    CATEGORY = "api node/image/Recraft"

    RECRAFT_STYLE = RecraftStyleV3.realistic_image

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "substyle": (get_v3_substyles(s.RECRAFT_STYLE),),
            }
        }

    def create_style(self, substyle: str):
        if substyle == "None":
            substyle = None
        return (RecraftStyle(self.RECRAFT_STYLE, substyle),)

```


# Recraft Text to Image - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-text-to-image

A Recraft Partner node that generates high-quality images from text descriptions

<img alt="ComfyUI Built-in Recraft Text to Image Node" />

The Recraft Text to Image node lets you generate high-quality images from text prompts by directly connecting to Recraft AI's image generation API to create images in various styles.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text description for the image |
| size | select | 1024x1024 | Output image size |
| n | int | 1 | Number of images (1-6) |
| seed | int | 0 | Random seed value |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| recraft\_style | Recraft Style | Image style setting, default is "realistic photo" |
| negative\_prompt | string | Elements to exclude from generation |
| recraft\_controls | Recraft Controls | Additional control parameters (colors, etc.) |

### Output

| Output | Type | Description |
| - | - | - |
| IMAGE | image | Generated image(s) |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftTextToImageNode:
    """
    Generates images synchronously based on prompt and resolution.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation.",
                    },
                ),
                "size": (
                    [res.value for res in RecraftImageSize],
                    {
                        "default": RecraftImageSize.res_1024x1024,
                        "tooltip": "The size of the generated image.",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 6,
                        "tooltip": "The number of images to generate.",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "recraft_style": (RecraftIO.STYLEV3,),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
                "recraft_controls": (
                    RecraftIO.CONTROLS,
                    {
                        "tooltip": "Optional additional controls over the generation via the Recraft Controls node."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        size: str,
        n: int,
        seed,
        recraft_style: RecraftStyle = None,
        negative_prompt: str = None,
        recraft_controls: RecraftControls = None,
        auth_token=None,
        **kwargs,
    ):
        default_style = RecraftStyle(RecraftStyleV3.realistic_image)
        if recraft_style is None:
            recraft_style = default_style

        controls_api = None
        if recraft_controls:
            controls_api = recraft_controls.create_api_model()

        if not negative_prompt:
            negative_prompt = None

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/recraft/image_generation",
                method=HttpMethod.POST,
                request_model=RecraftImageGenerationRequest,
                response_model=RecraftImageGenerationResponse,
            ),
            request=RecraftImageGenerationRequest(
                prompt=prompt,
                negative_prompt=negative_prompt,
                model=RecraftModel.recraftv3,
                size=size,
                n=n,
                style=recraft_style.style,
                substyle=recraft_style.substyle,
                style_id=recraft_style.style_id,
                controls=controls_api,
            ),
            auth_token=auth_token,
        )
        response: RecraftImageGenerationResponse = operation.execute()
        images = []
        for data in response.data:
            image = bytesio_to_image_tensor(
                download_url_to_bytesio(data.url, timeout=1024)
            )
            if len(image.shape) < 4:
                image = image.unsqueeze(0)
            images.append(image)
        output_image = torch.cat(images, dim=0)

        return (output_image,)
```


# Recraft Text to Vector - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-text-to-vector

A Recraft Partner node that generates scalable vector graphics from text descriptions

<img alt="ComfyUI Native Recraft Text to Vector Node" />

The Recraft Text to Vector node lets you create high-quality vector graphics (SVG format) from text descriptions using Recraft's API. It's perfect for making logos, icons, and infinitely scalable illustrations.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text description of the vector graphic to generate |
| substyle | select | - | Vector style subtype |
| size | select | 1024x1024 | Canvas size for the vector output |
| n | integer | 1 | Number of results to generate (1-6) |
| seed | integer | 0 | Random seed value |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| negative\_prompt | string | Elements to exclude from generation |
| recraft\_controls | Recraft Controls | Additional control parameters (colors, etc.) |

### Output

| Output | Type | Description |
| - | - | - |
| SVG | vector | Generated SVG vector graphic, connect to SaveSVG node to save |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class RecraftTextToVectorNode:
    """
    Generates SVG synchronously based on prompt and resolution.
    """

    RETURN_TYPES = (RecraftIO.SVG,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation.",
                    },
                ),
                "substyle": (get_v3_substyles(RecraftStyleV3.vector_illustration),),
                "size": (
                    [res.value for res in RecraftImageSize],
                    {
                        "default": RecraftImageSize.res_1024x1024,
                        "tooltip": "The size of the generated image.",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 6,
                        "tooltip": "The number of images to generate.",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
                "recraft_controls": (
                    RecraftIO.CONTROLS,
                    {
                        "tooltip": "Optional additional controls over the generation via the Recraft Controls node."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        substyle: str,
        size: str,
        n: int,
        seed,
        negative_prompt: str = None,
        recraft_controls: RecraftControls = None,
        auth_token=None,
        **kwargs,
    ):
        # create RecraftStyle so strings will be formatted properly (i.e. "None" will become None)
        recraft_style = RecraftStyle(RecraftStyleV3.vector_illustration, substyle=substyle)

        controls_api = None
        if recraft_controls:
            controls_api = recraft_controls.create_api_model()

        if not negative_prompt:
            negative_prompt = None

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/recraft/image_generation",
                method=HttpMethod.POST,
                request_model=RecraftImageGenerationRequest,
                response_model=RecraftImageGenerationResponse,
            ),
            request=RecraftImageGenerationRequest(
                prompt=prompt,
                negative_prompt=negative_prompt,
                model=RecraftModel.recraftv3,
                size=size,
                n=n,
                style=recraft_style.style,
                substyle=recraft_style.substyle,
                controls=controls_api,
            ),
            auth_token=auth_token,
        )
        response: RecraftImageGenerationResponse = operation.execute()
        svg_data = []
        for data in response.data:
            svg_data.append(download_url_to_bytesio(data.url, timeout=1024))

        return (SVG(svg_data),)
```


# Recraft Vectorize Image - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-vectorize-image

A Recraft Partner node that converts raster images to vector SVG format

<img alt="ComfyUI Built-in Recraft Vectorize Image Node" />

The Recraft Vectorize Image node uses Recraft's API to convert raster images (like photos, PNGs or JPEGs) into vector SVG format.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | Image | - | Input image to be converted to vector |

### Output

| Output | Type | Description |
| - | - | - |
| SVG | Vector | Converted SVG vector graphic, needs to be connected to SaveSVG node to save |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class RecraftVectorizeImageNode:
    """
    Generates SVG synchronously from an input image.
    """

    RETURN_TYPES = (RecraftIO.SVG,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
            },
            "optional": {
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        auth_token=None,
        **kwargs,
    ):
        svgs = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                path="/proxy/recraft/images/vectorize",
                auth_token=auth_token,
            )
            svgs.append(SVG(sub_bytes))
            pbar.update(1)

        return (SVG.combine_all(svgs), )

```


# Save SVG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/save-svg

A utility node for saving SVG vector graphics to files

<img alt="ComfyUI Built-in Save SVG Node" />

The Save SVG node allows you to save SVG data from Recraft vector generation nodes as usable files in the filesystem. This is an essential component for handling and exporting vector graphics.

## Node Function

This node receives SVG vector data and saves it as standard SVG files in the filesystem. It supports automatic file naming and save path specification, allowing vector graphics to be opened and edited in other software.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| svg | SVG | - | SVG vector data to save |
| filename\_prefix | string | "recraft" | Prefix for the filename |
| output\_dir | string | - | Output directory, defaults to ComfyUI output folder at `ComfyUI/output/svg/` |
| index | integer | -1 | Save index, -1 means save all generated SVGs |

### Output

| Output | Type | Description |
| - | - | - |
| SVG | SVG | Passes through the input SVG data |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}
class SaveSVGNode:
    """
    Save SVG files on disk.
    """

    def __init__(self):
        self.output_dir = folder_paths.get_output_directory()
        self.type = "output"
        self.prefix_append = ""

    RETURN_TYPES = ()
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "save_svg"
    CATEGORY = "api node/image/Recraft"
    OUTPUT_NODE = True

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "svg": (RecraftIO.SVG,),
                "filename_prefix": ("STRING", {"default": "svg/ComfyUI", "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes."})
            },
            "hidden": {
                "prompt": "PROMPT",
                "extra_pnginfo": "EXTRA_PNGINFO"
            }
        }

    def save_svg(self, svg: SVG, filename_prefix="svg/ComfyUI", prompt=None, extra_pnginfo=None):
        filename_prefix += self.prefix_append
        full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
        results = list()

        # Prepare metadata JSON
        metadata_dict = {}
        if prompt is not None:
            metadata_dict["prompt"] = prompt
        if extra_pnginfo is not None:
            metadata_dict.update(extra_pnginfo)

        # Convert metadata to JSON string
        metadata_json = json.dumps(metadata_dict, indent=2) if metadata_dict else None

        for batch_number, svg_bytes in enumerate(svg.data):
            filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
            file = f"{filename_with_batch_num}_{counter:05}_.svg"

            # Read SVG content
            svg_bytes.seek(0)
            svg_content = svg_bytes.read().decode('utf-8')

            # Inject metadata if available
            if metadata_json:
                # Create metadata element with CDATA section
                metadata_element = f"""  <metadata>
    <![CDATA[
{metadata_json}
    ]]>
  </metadata>
"""
                # Insert metadata after opening svg tag using regex
                import re
                svg_content = re.sub(r'(<svg[^>]*>)', r'\1\n' + metadata_element, svg_content)

            # Write the modified SVG to file
            with open(os.path.join(full_output_folder, file), 'wb') as svg_file:
                svg_file.write(svg_content.encode('utf-8'))

            results.append({
                "filename": file,
                "subfolder": subfolder,
                "type": self.type
            })
            counter += 1
        return { "ui": { "images": results } }

```


# Google Veo2 Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/google/google-veo2-video

A node that generates videos from text descriptions using Google's Veo2 technology

<img alt="ComfyUI Native Google Veo2 Video Node" />

The Google Veo2 Video node generates high-quality videos from text descriptions using Google's Veo2 API technology, converting text prompts into dynamic video content.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text description of the video content to generate |
| aspect\_ratio | select | "16:9" | Output video aspect ratio, "16:9" or "9:16" |
| negative\_prompt | string | "" | Text describing what to avoid in the video |
| duration\_seconds | integer | 5 | Video duration, 5-8 seconds |
| enhance\_prompt | boolean | True | Whether to use AI to enhance the prompt |
| person\_generation | select | "ALLOW" | Allow or block person generation, "ALLOW" or "BLOCK" |
| seed | integer | 0 | Random seed, 0 means randomly generated |

### Optional Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | image | None | Optional reference image to guide video creation |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class VeoVideoGenerationNode(ComfyNodeABC):
    """
    Generates videos from text prompts using Google's Veo API.

    This node can create videos from text descriptions and optional image inputs,
    with control over parameters like aspect ratio, duration, and more.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text description of the video",
                    },
                ),
                "aspect_ratio": (
                    IO.COMBO,
                    {
                        "options": ["16:9", "9:16"],
                        "default": "16:9",
                        "tooltip": "Aspect ratio of the output video",
                    },
                ),
            },
            "optional": {
                "negative_prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Negative text prompt to guide what to avoid in the video",
                    },
                ),
                "duration_seconds": (
                    IO.INT,
                    {
                        "default": 5,
                        "min": 5,
                        "max": 8,
                        "step": 1,
                        "display": "number",
                        "tooltip": "Duration of the output video in seconds",
                    },
                ),
                "enhance_prompt": (
                    IO.BOOLEAN,
                    {
                        "default": True,
                        "tooltip": "Whether to enhance the prompt with AI assistance",
                    }
                ),
                "person_generation": (
                    IO.COMBO,
                    {
                        "options": ["ALLOW", "BLOCK"],
                        "default": "ALLOW",
                        "tooltip": "Whether to allow generating people in the video",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFF,
                        "step": 1,
                        "display": "number",
                        "control_after_generate": True,
                        "tooltip": "Seed for video generation (0 for random)",
                    },
                ),
                "image": (IO.IMAGE, {
                    "default": None,
                    "tooltip": "Optional reference image to guide video generation",
                }),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    RETURN_TYPES = (IO.VIDEO,)
    FUNCTION = "generate_video"
    CATEGORY = "api node/video/Veo"
    DESCRIPTION = "Generates videos from text prompts using Google's Veo API"
    API_NODE = True

    def generate_video(
        self,
        prompt,
        aspect_ratio="16:9",
        negative_prompt="",
        duration_seconds=5,
        enhance_prompt=True,
        person_generation="ALLOW",
        seed=0,
        image=None,
        auth_token=None,
    ):
        # Prepare the instances for the request
        instances = []

        instance = {
            "prompt": prompt
        }

        # Add image if provided
        if image is not None:
            image_base64 = convert_image_to_base64(image)
            if image_base64:
                instance["image"] = {
                    "bytesBase64Encoded": image_base64,
                    "mimeType": "image/png"
                }

        instances.append(instance)

        # Create parameters dictionary
        parameters = {
            "aspectRatio": aspect_ratio,
            "personGeneration": person_generation,
            "durationSeconds": duration_seconds,
            "enhancePrompt": enhance_prompt,
        }

        # Add optional parameters if provided
        if negative_prompt:
            parameters["negativePrompt"] = negative_prompt
        if seed > 0:
            parameters["seed"] = seed

        # Initial request to start video generation
        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/veo/generate",
                method=HttpMethod.POST,
                request_model=Veo2GenVidRequest,
                response_model=Veo2GenVidResponse
            ),
            request=Veo2GenVidRequest(
                instances=instances,
                parameters=parameters
            ),
            auth_token=auth_token
        )

        initial_response = initial_operation.execute()
        operation_name = initial_response.name

        logging.info(f"Veo generation started with operation name: {operation_name}")

        # Define status extractor function
        def status_extractor(response):
            # Only return "completed" if the operation is done, regardless of success or failure
            # We'll check for errors after polling completes
            return "completed" if response.done else "pending"

        # Define progress extractor function
        def progress_extractor(response):
            # Could be enhanced if the API provides progress information
            return None

        # Define the polling operation
        poll_operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path="/proxy/veo/poll",
                method=HttpMethod.POST,
                request_model=Veo2GenVidPollRequest,
                response_model=Veo2GenVidPollResponse
            ),
            completed_statuses=["completed"],
            failed_statuses=[],  # No failed statuses, we'll handle errors after polling
            status_extractor=status_extractor,
            progress_extractor=progress_extractor,
            request=Veo2GenVidPollRequest(
                operationName=operation_name
            ),
            auth_token=auth_token,
            poll_interval=5.0
        )

        # Execute the polling operation
        poll_response = poll_operation.execute()

        # Now check for errors in the final response
        # Check for error in poll response
        if hasattr(poll_response, 'error') and poll_response.error:
            error_message = f"Veo API error: {poll_response.error.message} (code: {poll_response.error.code})"
            logging.error(error_message)
            raise Exception(error_message)

        # Check for RAI filtered content
        if (hasattr(poll_response.response, 'raiMediaFilteredCount') and
            poll_response.response.raiMediaFilteredCount > 0):

            # Extract reason message if available
            if (hasattr(poll_response.response, 'raiMediaFilteredReasons') and
                poll_response.response.raiMediaFilteredReasons):
                reason = poll_response.response.raiMediaFilteredReasons[0]
                error_message = f"Content filtered by Google's Responsible AI practices: {reason} ({poll_response.response.raiMediaFilteredCount} videos filtered.)"
            else:
                error_message = f"Content filtered by Google's Responsible AI practices ({poll_response.response.raiMediaFilteredCount} videos filtered.)"

            logging.error(error_message)
            raise Exception(error_message)

        # Extract video data
        video_data = None
        if poll_response.response and hasattr(poll_response.response, 'videos') and poll_response.response.videos and len(poll_response.response.videos) > 0:
            video = poll_response.response.videos[0]

            # Check if video is provided as base64 or URL
            if hasattr(video, 'bytesBase64Encoded') and video.bytesBase64Encoded:
                # Decode base64 string to bytes
                video_data = base64.b64decode(video.bytesBase64Encoded)
            elif hasattr(video, 'gcsUri') and video.gcsUri:
                # Download from URL
                video_url = video.gcsUri
                video_response = requests.get(video_url)
                video_data = video_response.content
            else:
                raise Exception("Video returned but no data or URL was provided")
        else:
            raise Exception("Video generation completed but no video was returned")

        if not video_data:
            raise Exception("No video data was returned")

        logging.info("Video generation completed successfully")

        # Convert video data to BytesIO object
        video_io = io.BytesIO(video_data)

        # Return VideoFromFile object
        return (VideoFromFile(video_io),)

```


# Kling Image to Video (Camera Control) - ComfyUI Built-in Node
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-camera-control-i2v

Image to video conversion node with camera control features

<img alt="ComfyUI Built-in Kling Image to Video (Camera Control) Node" />

The Kling Image to Video (Camera Control) node converts static images into videos with professional camera movements. It supports camera controls like zoom, rotation, pan, tilt and first-person view while maintaining focus on the original image content.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| start\_frame | Image | - | Input image to convert to video |
| prompt | String | "" | Text prompt describing video action and content |
| negative\_prompt | String | "" | Elements to avoid in the video |
| cfg\_scale | Float | 7.0 | Controls how closely to follow the prompt |
| aspect\_ratio | Select | 16:9 | Output video aspect ratio |

### Camera Control Parameters

| Parameter | Type | Description |
| - | - | - |
| camera\_control | CameraControl | Camera control config from Kling Camera Controls node |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | Video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class KlingCameraControlI2VNode(KlingImage2VideoNode):
    """
    Kling Image to Video Camera Control Node. This node is a image to video node, but it supports controlling the camera.
    Duration, mode, and model_name request fields are hard-coded because camera control is only supported in pro mode with the kling-v1-5 model at 5s duration as of 2025-05-02.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "start_frame": model_field_to_node_input(
                    IO.IMAGE, KlingImage2VideoRequest, "image"
                ),
                "prompt": model_field_to_node_input(
                    IO.STRING, KlingImage2VideoRequest, "prompt", multiline=True
                ),
                "negative_prompt": model_field_to_node_input(
                    IO.STRING,
                    KlingImage2VideoRequest,
                    "negative_prompt",
                    multiline=True,
                ),
                "cfg_scale": model_field_to_node_input(
                    IO.FLOAT, KlingImage2VideoRequest, "cfg_scale"
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "aspect_ratio",
                    enum_type=AspectRatio,
                ),
                "camera_control": (
                    "CAMERA_CONTROL",
                    {
                        "tooltip": "Can be created using the Kling Camera Controls node. Controls the camera movement and motion during the video generation.",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    DESCRIPTION = "Transform still images into cinematic videos with professional camera movements that simulate real-world cinematography. Control virtual camera actions including zoom, rotation, pan, tilt, and first-person view, while maintaining focus on your original image."

    def api_call(
        self,
        start_frame: torch.Tensor,
        prompt: str,
        negative_prompt: str,
        cfg_scale: float,
        aspect_ratio: str,
        camera_control: CameraControl,
        auth_token: Optional[str] = None,
    ):
        return super().api_call(
            model_name="kling-v1-5",
            start_frame=start_frame,
            cfg_scale=cfg_scale,
            mode="pro",
            aspect_ratio=aspect_ratio,
            duration="5",
            prompt=prompt,
            negative_prompt=negative_prompt,
            camera_control=camera_control,
            auth_token=auth_token,
        )



```


# Kling Text to Video (Camera Control) - ComfyUI Built-in Node
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-camera-control-t2v

A text to video generation node with camera control features

<img alt="ComfyUI Built-in Kling Text to Video (Camera Control) Node" />

The Kling Text to Video (Camera Control) node converts text into videos with professional camera movements. It extends the standard Kling Text to Video node by adding camera control capabilities.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | String | "" | Text prompt describing video content |
| negative\_prompt | String | "" | Elements to avoid in the video |
| cfg\_scale | Float | 7.0 | Controls how closely to follow the prompt |
| aspect\_ratio | Select | "16:9" | Output video aspect ratio |
| camera\_control | CAMERA\_CONTROL | - | Camera settings from Kling Camera Controls node |

### Fixed Parameters

Note: The following parameters are fixed and cannot be changed:

* Model: kling-v1-5
* Mode: pro
* Duration: 5 seconds

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | Video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class KlingCameraControlT2VNode(KlingTextToVideoNode):
    """
    Kling Text to Video Camera Control Node. This node is a text to video node, but it supports controlling the camera.
    Duration, mode, and model_name request fields are hard-coded because camera control is only supported in pro mode with the kling-v1-5 model at 5s duration as of 2025-05-02.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": model_field_to_node_input(
                    IO.STRING, KlingText2VideoRequest, "prompt", multiline=True
                ),
                "negative_prompt": model_field_to_node_input(
                    IO.STRING,
                    KlingText2VideoRequest,
                    "negative_prompt",
                    multiline=True,
                ),
                "cfg_scale": model_field_to_node_input(
                    IO.FLOAT, KlingText2VideoRequest, "cfg_scale"
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.COMBO,
                    KlingText2VideoRequest,
                    "aspect_ratio",
                    enum_type=AspectRatio,
                ),
                "camera_control": (
                    "CAMERA_CONTROL",
                    {
                        "tooltip": "Can be created using the Kling Camera Controls node. Controls the camera movement and motion during the video generation.",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    DESCRIPTION = "Transform text into cinematic videos with professional camera movements that simulate real-world cinematography. Control virtual camera actions including zoom, rotation, pan, tilt, and first-person view, while maintaining focus on your original text."

    def api_call(
        self,
        prompt: str,
        negative_prompt: str,
        cfg_scale: float,
        aspect_ratio: str,
        camera_control: Optional[CameraControl] = None,
        auth_token: Optional[str] = None,
    ):
        return super().api_call(
            model_name="kling-v1-5",
            cfg_scale=cfg_scale,
            mode="pro",
            aspect_ratio=aspect_ratio,
            duration="5",
            prompt=prompt,
            negative_prompt=negative_prompt,
            camera_control=camera_control,
            auth_token=auth_token,
        )



```


# Kling Camera Controls - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-camera-controls

A node that provides camera control parameters for Kling video generation

<img alt="ComfyUI Built-in Kling Camera Controls Node" />

The Kling Camera Controls node defines virtual camera behavior parameters to control camera movement and view changes during Kling video generation.

## Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| camera\_control\_type | Select | "simple" | Preset camera motion types. simple: Custom camera movement; down\_back: Camera moves down and back; forward\_up: Camera moves forward and up; right\_turn\_forward: Rotate right and move forward; left\_turn\_forward: Rotate left and move forward |
| horizontal\_movement | Float | 0 | Controls camera movement on horizontal axis (x-axis). Negative values move left, positive values move right |
| vertical\_movement | Float | 0 | Controls camera movement on vertical axis (y-axis). Negative values move down, positive values move up |
| pan | Float | 0.5 | Controls camera rotation in vertical plane (x-axis). Negative values rotate down, positive values rotate up |
| tilt | Float | 0 | Controls camera rotation in horizontal plane (y-axis). Negative values rotate left, positive values rotate right |
| roll | Float | 0 | Controls camera roll amount (z-axis). Negative values rotate counterclockwise, positive values rotate clockwise |
| zoom | Float | 0 | Controls camera focal length. Negative values narrow field of view, positive values widen it |

**Note**: At least one non-zero camera control parameter is required for the effect to work.

### Output

| Output | Type | Description |
| - | - | - |
| camera\_control | CAMERA\_CONTROL | Configuration object with camera settings |

**Note**: Not all model and mode combinations support camera control. Please check the Kling API documentation for details.

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class KlingCameraControls(KlingNodeBase):
    """Kling Camera Controls Node"""

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "camera_control_type": (
                    IO.COMBO,
                    {
                        "options": [
                            camera_control_type.value
                            for camera_control_type in CameraType
                        ],
                        "default": "simple",
                        "tooltip": "Predefined camera movements type. simple: Customizable camera movement. down_back: Camera descends and moves backward. forward_up: Camera moves forward and tilts up. right_turn_forward: Rotate right and move forward. left_turn_forward: Rotate left and move forward.",
                    },
                ),
                "horizontal_movement": get_camera_control_input_config(
                    "Controls camera's movement along horizontal axis (x-axis). Negative indicates left, positive indicates right"
                ),
                "vertical_movement": get_camera_control_input_config(
                    "Controls camera's movement along vertical axis (y-axis). Negative indicates downward, positive indicates upward."
                ),
                "pan": get_camera_control_input_config(
                    "Controls camera's rotation in vertical plane (x-axis). Negative indicates downward rotation, positive indicates upward rotation.",
                    default=0.5,
                ),
                "tilt": get_camera_control_input_config(
                    "Controls camera's rotation in horizontal plane (y-axis). Negative indicates left rotation, positive indicates right rotation.",
                ),
                "roll": get_camera_control_input_config(
                    "Controls camera's rolling amount (z-axis). Negative indicates counterclockwise, positive indicates clockwise.",
                ),
                "zoom": get_camera_control_input_config(
                    "Controls change in camera's focal length. Negative indicates narrower field of view, positive indicates wider field of view.",
                ),
            }
        }

    DESCRIPTION = "Kling Camera Controls Node. Not all model and mode combinations support camera control. Please refer to the Kling API documentation for more information."
    RETURN_TYPES = ("CAMERA_CONTROL",)
    RETURN_NAMES = ("camera_control",)
    FUNCTION = "main"

    @classmethod
    def VALIDATE_INPUTS(
        cls,
        horizontal_movement: float,
        vertical_movement: float,
        pan: float,
        tilt: float,
        roll: float,
        zoom: float,
    ) -> bool | str:
        if not is_valid_camera_control_configs(
            [
                horizontal_movement,
                vertical_movement,
                pan,
                tilt,
                roll,
                zoom,
            ]
        ):
            return "Invalid camera control configs: at least one of the values must be non-zero"
        return True

    def main(
        self,
        camera_control_type: str,
        horizontal_movement: float,
        vertical_movement: float,
        pan: float,
        tilt: float,
        roll: float,
        zoom: float,
    ) -> tuple[CameraControl]:
        return (
            CameraControl(
                type=CameraType(camera_control_type),
                config=CameraConfig(
                    horizontal=horizontal_movement,
                    vertical=vertical_movement,
                    pan=pan,
                    roll=roll,
                    tilt=tilt,
                    zoom=zoom,
                ),
            ),
        )
```


# Kling Image to Video - ComfyUI Built-in Node
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-image-to-video

A node that converts static images to dynamic videos using Kling's AI technology

<img alt="ComfyUI Built-in Kling Image to Video Node" />

The Kling Image to Video node converts static images into dynamic video content using Kling's image-to-video API.

## Parameters

### Basic Parameters

All parameters below are required:

| Parameter | Type | Default | Description |
| - | - | - | - |
| start\_frame | Image | - | Input source image |
| prompt | String | "" | Text prompt describing video action and content |
| negative\_prompt | String | "" | Elements to avoid in the video |
| cfg\_scale | Float | 7.0 | Controls how closely to follow the prompt |
| model\_name | Select | "kling-v1-5" | Model type to use |
| aspect\_ratio | Select | "16:9" | Output video aspect ratio |
| duration | Select | "5s" | Generated video duration |
| mode | Select | "pro" | Video generation mode |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | Video | Generated video |
| video\_id | String | Unique video identifier |
| duration | String | Actual video duration |

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class KlingImage2VideoNode(KlingNodeBase):
    """Kling Image to Video Node"""

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "start_frame": model_field_to_node_input(
                    IO.IMAGE, KlingImage2VideoRequest, "image"
                ),
                "prompt": model_field_to_node_input(
                    IO.STRING, KlingImage2VideoRequest, "prompt", multiline=True
                ),
                "negative_prompt": model_field_to_node_input(
                    IO.STRING,
                    KlingImage2VideoRequest,
                    "negative_prompt",
                    multiline=True,
                ),
                "model_name": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "model_name",
                    enum_type=KlingVideoGenModelName,
                ),
                "cfg_scale": model_field_to_node_input(
                    IO.FLOAT, KlingImage2VideoRequest, "cfg_scale"
                ),
                "mode": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "mode",
                    enum_type=KlingVideoGenMode,
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "aspect_ratio",
                    enum_type=KlingVideoGenAspectRatio,
                ),
                "duration": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "duration",
                    enum_type=KlingVideoGenDuration,
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = ("VIDEO", "STRING", "STRING")
    RETURN_NAMES = ("VIDEO", "video_id", "duration")
    DESCRIPTION = "Kling Image to Video Node"

    def get_response(self, task_id: str, auth_token: str) -> KlingImage2VideoResponse:
        return poll_until_finished(
            auth_token,
            ApiEndpoint(
                path=f"{PATH_IMAGE_TO_VIDEO}/{task_id}",
                method=HttpMethod.GET,
                request_model=KlingImage2VideoRequest,
                response_model=KlingImage2VideoResponse,
            ),
        )

    def api_call(
        self,
        start_frame: torch.Tensor,
        prompt: str,
        negative_prompt: str,
        model_name: str,
        cfg_scale: float,
        mode: str,
        aspect_ratio: str,
        duration: str,
        camera_control: Optional[KlingCameraControl] = None,
        end_frame: Optional[torch.Tensor] = None,
        auth_token: Optional[str] = None,
    ) -> tuple[VideoFromFile]:
        validate_prompts(prompt, negative_prompt, MAX_PROMPT_LENGTH_I2V)
        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=PATH_IMAGE_TO_VIDEO,
                method=HttpMethod.POST,
                request_model=KlingImage2VideoRequest,
                response_model=KlingImage2VideoResponse,
            ),
            request=KlingImage2VideoRequest(
                model_name=KlingVideoGenModelName(model_name),
                image=tensor_to_base64_string(start_frame),
                image_tail=(
                    tensor_to_base64_string(end_frame)
                    if end_frame is not None
                    else None
                ),
                prompt=prompt,
                negative_prompt=negative_prompt if negative_prompt else None,
                cfg_scale=cfg_scale,
                mode=KlingVideoGenMode(mode),
                aspect_ratio=KlingVideoGenAspectRatio(aspect_ratio),
                duration=KlingVideoGenDuration(duration),
                camera_control=camera_control,
            ),
            auth_token=auth_token,
        )

        task_creation_response = initial_operation.execute()
        validate_task_creation_response(task_creation_response)
        task_id = task_creation_response.data.task_id

        final_response = self.get_response(task_id, auth_token)
        validate_video_result_response(final_response)

        video = get_video_from_response(final_response)
        return video_result_to_node_output(video)

```


# Kling Start-End Frame to Video - ComfyUI Built-in Node
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-start-end-frame-to-video

A node that creates smooth video transitions between start and end frames using Kling's AI technology

<img alt="ComfyUI Built-in Kling Start-End Frame to Video Node" />

The Kling Start-End Frame to Video node lets you create smooth video transitions between two images. It automatically generates all the intermediate frames to produce a fluid transformation.

## Parameters

### Required Parameters

| Parameter | Type | Description |
| - | - | - |
| start\_frame | Image | Starting image for the video |
| end\_frame | Image | Ending image for the video |
| prompt | String | Text describing video content and transition |
| negative\_prompt | String | Elements to avoid in the video |
| cfg\_scale | Float | Controls how closely to follow the prompt |
| aspect\_ratio | Select | Output video aspect ratio |
| mode | Select | Video generation settings (mode/duration/model) |

### Mode Options

Available mode combinations:

* standard mode / 5s duration / kling-v1
* standard mode / 5s duration / kling-v1-5
* pro mode / 5s duration / kling-v1
* pro mode / 5s duration / kling-v1-5
* pro mode / 5s duration / kling-v1-6
* pro mode / 10s duration / kling-v1-5
* pro mode / 10s duration / kling-v1-6

Default: "pro mode / 5s duration / kling-v1"

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | Video | Generated video |

## How It Works

The node analyzes the start and end frames to create a smooth transition sequence between them. It sends the images and parameters to Kling's API server, which generates all necessary intermediate frames for a fluid transformation.

The transition style and content can be guided using prompts, while negative prompts help avoid unwanted elements.

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}


class KlingStartEndFrameNode(KlingImage2VideoNode):
    """
    Kling First Last Frame Node. This node allows creation of a video from a first and last frame. It calls the normal image to video endpoint, but only allows the subset of input options that support the `image_tail` request field.
    """

    @staticmethod
    def get_mode_string_mapping() -> dict[str, tuple[str, str, str]]:
        """
        Returns a mapping of mode strings to their corresponding (mode, duration, model_name) tuples.
        Only includes config combos that support the `image_tail` request field.
        """
        return {
            "standard mode / 5s duration / kling-v1": ("std", "5", "kling-v1"),
            "standard mode / 5s duration / kling-v1-5": ("std", "5", "kling-v1-5"),
            "pro mode / 5s duration / kling-v1": ("pro", "5", "kling-v1"),
            "pro mode / 5s duration / kling-v1-5": ("pro", "5", "kling-v1-5"),
            "pro mode / 5s duration / kling-v1-6": ("pro", "5", "kling-v1-6"),
            "pro mode / 10s duration / kling-v1-5": ("pro", "10", "kling-v1-5"),
            "pro mode / 10s duration / kling-v1-6": ("pro", "10", "kling-v1-6"),
        }

    @classmethod
    def INPUT_TYPES(s):
        modes = list(KlingStartEndFrameNode.get_mode_string_mapping().keys())
        return {
            "required": {
                "start_frame": model_field_to_node_input(
                    IO.IMAGE, KlingImage2VideoRequest, "image"
                ),
                "end_frame": model_field_to_node_input(
                    IO.IMAGE, KlingImage2VideoRequest, "image_tail"
                ),
                "prompt": model_field_to_node_input(
                    IO.STRING, KlingImage2VideoRequest, "prompt", multiline=True
                ),
                "negative_prompt": model_field_to_node_input(
                    IO.STRING,
                    KlingImage2VideoRequest,
                    "negative_prompt",
                    multiline=True,
                ),
                "cfg_scale": model_field_to_node_input(
                    IO.FLOAT, KlingImage2VideoRequest, "cfg_scale"
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "aspect_ratio",
                    enum_type=AspectRatio,
                ),
                "mode": (
                    modes,
                    {
                        "default": modes[2],
                        "tooltip": "The configuration to use for the video generation following the format: mode / duration / model_name.",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    DESCRIPTION = "Generate a video sequence that transitions between your provided start and end images. The node creates all frames in between, producing a smooth transformation from the first frame to the last."

    def parse_inputs_from_mode(self, mode: str) -> tuple[str, str, str]:
        """Parses the mode input into a tuple of (model_name, duration, mode)."""
        return KlingStartEndFrameNode.get_mode_string_mapping()[mode]

    def api_call(
        self,
        start_frame: torch.Tensor,
        end_frame: torch.Tensor,
        prompt: str,
        negative_prompt: str,
        cfg_scale: float,
        aspect_ratio: str,
        mode: str,
        auth_token: Optional[str] = None,
    ):
        mode, duration, model_name = self.parse_inputs_from_mode(mode)
        return super().api_call(
            prompt=prompt,
            negative_prompt=negative_prompt,
            model_name=model_name,
            start_frame=start_frame,
            cfg_scale=cfg_scale,
            mode=mode,
            aspect_ratio=aspect_ratio,
            duration=duration,
            end_frame=end_frame,
            auth_token=auth_token,
        )


```


# Kling Text to Video - ComfyUI Built-in Node
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-text-to-video

A node that converts text descriptions into videos using Kling's AI technology

<img alt="ComfyUI Built-in Kling Text to Video Node" />

The Kling Text to Video node connects to Kling's API service to generate videos from text descriptions. Users simply provide descriptive text to create corresponding video content.

## Parameters

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | String | "" | Text prompt describing desired video content |
| negative\_prompt | String | "" | Elements to avoid in the video |
| cfg\_scale | Float | 7.0 | Controls how closely to follow the prompt |
| model\_name | Select | "kling-v2-master" | Video generation model to use |
| aspect\_ratio | Select | AspectRatio enum | Output video aspect ratio |
| duration | Select | Duration enum | Length of generated video |
| mode | Select | Mode enum | Video generation mode |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | Video | Generated video |
| Kling ID | String | Task identifier |
| Duration (sec) | String | Video length in seconds |

## How It Works

The node sends text prompts to Kling's API server, which processes and returns the generated video. The process includes initial request and status polling. When complete, the node downloads and outputs the video.

Users can control the generation by adjusting parameters like negative prompts, configuration scale, and video properties. The system validates prompt length to ensure API compliance.

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class KlingTextToVideoNode(KlingNodeBase):
    """Kling Text to Video Node"""

    @staticmethod
    def poll_for_task_status(task_id: str, auth_token: str) -> KlingText2VideoResponse:
        """Polls the Kling API endpoint until the task reaches a terminal state."""
        polling_operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"{PATH_TEXT_TO_VIDEO}/{task_id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=KlingText2VideoResponse,
            ),
            completed_statuses=[
                TaskStatus.succeed.value,
            ],
            failed_statuses=[TaskStatus.failed.value],
            status_extractor=lambda response: (
                response.data.task_status.value
                if response.data and response.data.task_status
                else None
            ),
            auth_token=auth_token,
        )
        return polling_operation.execute()

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": model_field_to_node_input(
                    IO.STRING, KlingText2VideoRequest, "prompt", multiline=True
                ),
                "negative_prompt": model_field_to_node_input(
                    IO.STRING, KlingText2VideoRequest, "negative_prompt", multiline=True
                ),
                "model_name": model_field_to_node_input(
                    IO.COMBO,
                    KlingText2VideoRequest,
                    "model_name",
                    enum_type=ModelName,
                    default="kling-v2-master",
                ),
                "cfg_scale": model_field_to_node_input(
                    IO.FLOAT, KlingText2VideoRequest, "cfg_scale"
                ),
                "mode": model_field_to_node_input(
                    IO.COMBO, KlingText2VideoRequest, "mode", enum_type=Mode
                ),
                "duration": model_field_to_node_input(
                    IO.COMBO, KlingText2VideoRequest, "duration", enum_type=Duration
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.COMBO,
                    KlingText2VideoRequest,
                    "aspect_ratio",
                    enum_type=AspectRatio,
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = ("VIDEO", "STRING", "STRING")
    RETURN_NAMES = ("VIDEO", "Kling ID", "Duration (sec)")
    DESCRIPTION = "Kling Text to Video Node"

    def api_call(
        self,
        prompt: str,
        negative_prompt: str,
        model_name: str,
        cfg_scale: float,
        mode: str,
        duration: int,
        aspect_ratio: str,
        camera_control: Optional[CameraControl] = None,
        auth_token: Optional[str] = None,
    ) -> tuple[VideoFromFile, str, str]:
        validate_prompts(prompt, negative_prompt, MAX_PROMPT_LENGTH_T2V)
        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=PATH_TEXT_TO_VIDEO,
                method=HttpMethod.POST,
                request_model=KlingText2VideoRequest,
                response_model=KlingText2VideoResponse,
            ),
            request=KlingText2VideoRequest(
                prompt=prompt if prompt else None,
                negative_prompt=negative_prompt if negative_prompt else None,
                duration=Duration(duration),
                mode=Mode(mode),
                model_name=ModelName(model_name),
                cfg_scale=cfg_scale,
                aspect_ratio=AspectRatio(aspect_ratio),
                camera_control=camera_control,
            ),
            auth_token=auth_token,
        )

        initial_response = initial_operation.execute()
        if not is_valid_initial_response(initial_response):
            error_msg = f"Kling initial request failed. Code: {initial_response.code}, Message: {initial_response.message}, Data: {initial_response.data}"
            logging.error(error_msg)
            raise KlingApiError(error_msg)

        task_id = initial_response.data.task_id
        final_response = self.poll_for_task_status(task_id, auth_token)
        if not is_valid_video_response(final_response):
            error_msg = (
                f"Kling task {task_id} succeeded but no video data found in response."
            )
            logging.error(error_msg)
            raise KlingApiError(error_msg)

        video = final_response.data.task_result.videos[0]
        logging.debug("Kling task %s succeeded. Video URL: %s", task_id, video.url)
        return (
            download_url_to_video_output(video.url),
            str(video.id),
            str(video.duration),
        )

```


# Luma Concepts - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/luma/luma-concepts

A helper node that provides concept guidance for Luma image generation

<img alt="ComfyUI Native Luma Concepts Node" />

The Luma Concepts node allows you to apply predefined camera concepts to the Luma generation process, providing precise control over camera angles and perspectives without complex prompt descriptions.

## Node Function

This node serves as a helper tool for Luma generation nodes, enabling users to select and apply predefined camera concepts. These concepts include different shooting angles (like overhead or low angle), camera distances (like close-up or long shot), and movement styles (like push-in or follow). It simplifies the creative workflow by providing an intuitive way to control camera effects in the generated output.

## Parameters

### Basic Parameters

| Parameter | Type | Description |
| - | - | - |
| concept1 | select | First camera concept choice, includes various presets and "none" |
| concept2 | select | Second camera concept choice, includes various presets and "none" |
| concept3 | select | Third camera concept choice, includes various presets and "none" |
| concept4 | select | Fourth camera concept choice, includes various presets and "none" |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| luma\_concepts | LUMA\_CONCEPTS | Optional Camera Concepts to merge with selected concepts |

### Output

| Output | Type | Description |
| - | - | - |
| luma\_concepts | LUMA\_CONCEPT | Combined object containing all selected concepts |

## Usage Examples

<Card title="Luma Text to Video Workflow Example" icon="book" href="/tutorials/partner-nodes/luma/luma-text-to-video">
  Luma Text to Video Workflow Example
</Card>

<Card title="Luma Image to Video Workflow Example" icon="book" href="/tutorials/partner-nodes/luma/luma-image-to-video">
  Luma Image to Video Workflow Example
</Card>

## How It Works

The Luma Concepts node offers a variety of predefined camera concepts including:

* Camera distances (close-up, medium shot, long shot)
* View angles (eye level, overhead, low angle)
* Movement types (push-in, follow, orbit)
* Special effects (handheld, stabilized, floating)

Users can select up to 4 concepts to use together. The node creates an object containing the selected camera concepts, which is then passed to Luma generation nodes. During generation, Luma AI uses these camera concepts to influence the viewpoint and composition of the output, ensuring the results reflect the chosen photographic effects.

By combining multiple camera concepts, users can create complex camera guidance without writing detailed prompt descriptions. This is particularly useful when specific camera angles or compositions are needed.

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class LumaConceptsNode(ComfyNodeABC):
    """
    Holds one or more Camera Concepts for use with Luma Text to Video and Luma Image to Video nodes.
    """

    RETURN_TYPES = (LumaIO.LUMA_CONCEPTS,)
    RETURN_NAMES = ("luma_concepts",)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "create_concepts"
    CATEGORY = "api node/image/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "concept1": (get_luma_concepts(include_none=True),),
                "concept2": (get_luma_concepts(include_none=True),),
                "concept3": (get_luma_concepts(include_none=True),),
                "concept4": (get_luma_concepts(include_none=True),),
            },
            "optional": {
                "luma_concepts": (
                    LumaIO.LUMA_CONCEPTS,
                    {
                        "tooltip": "Optional Camera Concepts to add to the ones chosen here."
                    },
                ),
            },
        }

    def create_concepts(
        self,
        concept1: str,
        concept2: str,
        concept3: str,
        concept4: str,
        luma_concepts: LumaConceptChain = None,
    ):
        chain = LumaConceptChain(str_list=[concept1, concept2, concept3, concept4])
        if luma_concepts is not None:
            chain = luma_concepts.clone_and_merge(chain)
        return (chain,)


```


# Luma Image to Video - ComfyUI Native Partner Nodes Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/luma/luma-image-to-video

A node that converts static images to dynamic videos using Luma AI

<img alt="ComfyUI Native Luma Image to Video Node" />

The Luma Image to Video node uses Luma AI's technology to transform static images into smooth, dynamic videos, bringing your images to life.

## Node Function

This node connects to Luma AI's image-to-video API, allowing users to create dynamic videos from input images. It understands the image content and generates natural, coherent motion while maintaining the original visual style. Combined with text prompts, users can precisely control the video's dynamic effects.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text prompt describing video motion and content |
| model | select | - | Video generation model to use |
| resolution | select | "540p" | Output video resolution |
| duration | select | - | Video length options |
| loop | boolean | False | Whether to loop the video |
| seed | integer | 0 | Seed value for node rerun, results are nondeterministic |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| first\_image | image | First frame of video (required if no last\_image) |
| last\_image | image | Last frame of video (required if no first\_image) |
| luma\_concepts | LUMA\_CONCEPTS | Concepts for controlling camera motion and shot style |

### Requirements

* Either **first\_image** or **last\_image** must be provided
* Each image input (first\_image and last\_image) accepts only 1 image

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | video | Generated video |

## Usage Example

<Card title="Luma Image to Video Workflow Example" icon="book" href="/tutorials/partner-nodes/luma/luma-image-to-video">
  Luma Image to Video Workflow Tutorial
</Card>

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class LumaImageToVideoGenerationNode(ComfyNodeABC):
    """
    Generates videos synchronously based on prompt, input images, and output_size.
    """

    RETURN_TYPES = (IO.VIDEO,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/video/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the video generation",
                    },
                ),
                "model": ([model.value for model in LumaVideoModel],),
                # "aspect_ratio": ([ratio.value for ratio in LumaAspectRatio], {
                #     "default": LumaAspectRatio.ratio_16_9,
                # }),
                "resolution": (
                    [resolution.value for resolution in LumaVideoOutputResolution],
                    {
                        "default": LumaVideoOutputResolution.res_540p,
                    },
                ),
                "duration": ([dur.value for dur in LumaVideoModelOutputDuration],),
                "loop": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "first_image": (
                    IO.IMAGE,
                    {"tooltip": "First frame of generated video."},
                ),
                "last_image": (IO.IMAGE, {"tooltip": "Last frame of generated video."}),
                "luma_concepts": (
                    LumaIO.LUMA_CONCEPTS,
                    {
                        "tooltip": "Optional Camera Concepts to dictate camera motion via the Luma Concepts node."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        model: str,
        resolution: str,
        duration: str,
        loop: bool,
        seed,
        first_image: torch.Tensor = None,
        last_image: torch.Tensor = None,
        luma_concepts: LumaConceptChain = None,
        auth_token=None,
        **kwargs,
    ):
        if first_image is None and last_image is None:
            raise Exception(
                "At least one of first_image and last_image requires an input."
            )
        keyframes = self._convert_to_keyframes(first_image, last_image, auth_token)
        duration = duration if model != LumaVideoModel.ray_1_6 else None
        resolution = resolution if model != LumaVideoModel.ray_1_6 else None

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/luma/generations",
                method=HttpMethod.POST,
                request_model=LumaGenerationRequest,
                response_model=LumaGeneration,
            ),
            request=LumaGenerationRequest(
                prompt=prompt,
                model=model,
                aspect_ratio=LumaAspectRatio.ratio_16_9,  # ignored, but still needed by the API for some reason
                resolution=resolution,
                duration=duration,
                loop=loop,
                keyframes=keyframes,
                concepts=luma_concepts.create_api_model() if luma_concepts else None,
            ),
            auth_token=auth_token,
        )
        response_api: LumaGeneration = operation.execute()

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/luma/generations/{response_api.id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=LumaGeneration,
            ),
            completed_statuses=[LumaState.completed],
            failed_statuses=[LumaState.failed],
            status_extractor=lambda x: x.state,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        vid_response = requests.get(response_poll.assets.video)
        return (VideoFromFile(BytesIO(vid_response.content)),)

    def _convert_to_keyframes(
        self,
        first_image: torch.Tensor = None,
        last_image: torch.Tensor = None,
        auth_token=None,
    ):
        if first_image is None and last_image is None:
            return None
        frame0 = None
        frame1 = None
        if first_image is not None:
            download_urls = upload_images_to_comfyapi(
                first_image, max_images=1, auth_token=auth_token
            )
            frame0 = LumaImageReference(type="image", url=download_urls[0])
        if last_image is not None:
            download_urls = upload_images_to_comfyapi(
                last_image, max_images=1, auth_token=auth_token
            )
            frame1 = LumaImageReference(type="image", url=download_urls[0])
        return LumaKeyframes(frame0=frame0, frame1=frame1)

```


# Luma Text to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/luma/luma-text-to-video

A node that converts text descriptions to videos using Luma AI

<img alt="ComfyUI Native Luma Text to Video Node" />

The Luma Text to Video node lets you create high-quality, smooth videos from text descriptions using Luma AI's video generation technology.

## Node Function

This node connects to Luma AI's text-to-video API, allowing users to generate dynamic video content from detailed text prompts.

## Parameters

### Basic Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text prompt describing the video content to generate |
| model | select | - | Video generation model to use |
| aspect\_ratio | select | "ratio\_16\_9" | Video aspect ratio |
| resolution | select | "res\_540p" | Video resolution |
| duration | select | - | Video length options |
| loop | boolean | False | Whether to loop the video |
| seed | integer | 0 | Seed value for node rerun, results are nondeterministic |

<Note>
  When using Ray 1.6 model, duration and resolution parameters will not take effect.
</Note>

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| luma\_concepts | LUMA\_CONCEPTS | Camera concepts to control motion via Luma Concepts node |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | video | Generated video |

## Usage Example

<Card title="Luma Text to Video Workflow Example" icon="book" href="/tutorials/partner-nodes/luma/luma-text-to-video">
  Luma Text to Video Workflow Example
</Card>

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class LumaTextToVideoGenerationNode(ComfyNodeABC):
    """
    Generates videos synchronously based on prompt and output_size.
    """

    RETURN_TYPES = (IO.VIDEO,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/video/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the video generation",
                    },
                ),
                "model": ([model.value for model in LumaVideoModel],),
                "aspect_ratio": (
                    [ratio.value for ratio in LumaAspectRatio],
                    {
                        "default": LumaAspectRatio.ratio_16_9,
                    },
                ),
                "resolution": (
                    [resolution.value for resolution in LumaVideoOutputResolution],
                    {
                        "default": LumaVideoOutputResolution.res_540p,
                    },
                ),
                "duration": ([dur.value for dur in LumaVideoModelOutputDuration],),
                "loop": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "luma_concepts": (
                    LumaIO.LUMA_CONCEPTS,
                    {
                        "tooltip": "Optional Camera Concepts to dictate camera motion via the Luma Concepts node."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        model: str,
        aspect_ratio: str,
        resolution: str,
        duration: str,
        loop: bool,
        seed,
        luma_concepts: LumaConceptChain = None,
        auth_token=None,
        **kwargs,
    ):
        duration = duration if model != LumaVideoModel.ray_1_6 else None
        resolution = resolution if model != LumaVideoModel.ray_1_6 else None

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/luma/generations",
                method=HttpMethod.POST,
                request_model=LumaGenerationRequest,
                response_model=LumaGeneration,
            ),
            request=LumaGenerationRequest(
                prompt=prompt,
                model=model,
                resolution=resolution,
                aspect_ratio=aspect_ratio,
                duration=duration,
                loop=loop,
                concepts=luma_concepts.create_api_model() if luma_concepts else None,
            ),
            auth_token=auth_token,
        )
        response_api: LumaGeneration = operation.execute()

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/luma/generations/{response_api.id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=LumaGeneration,
            ),
            completed_statuses=[LumaState.completed],
            failed_statuses=[LumaState.failed],
            status_extractor=lambda x: x.state,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        vid_response = requests.get(response_poll.assets.video)
        return (VideoFromFile(BytesIO(vid_response.content)),)

```


# MiniMax Image to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/minimax/minimax-image-to-video

A node that converts static images to dynamic videos using MiniMax AI

<img alt="ComfyUI Native MiniMax Image to Video Node" />

The MiniMax Image to Video node uses MiniMax's API to generate videos from input images and text prompts.

## Parameters

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | image | - | Input image used as the first frame of video |
| prompt\_text | string | "" | Text prompt to guide video generation |
| model | select | "I2V-01" | Available models: "I2V-01-Director", "I2V-01", "I2V-01-live" |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| seed | integer | Random seed for noise generation |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | video | Generated video |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class MinimaxImageToVideoNode(MinimaxTextToVideoNode):
    """
    Generates videos synchronously based on an image and prompt, and optional parameters using Minimax's API.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (
                    IO.IMAGE,
                    {
                        "tooltip": "Image to use as first frame of video generation"
                    },
                ),
                "prompt_text": (
                    "STRING",
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text prompt to guide the video generation",
                    },
                ),
                "model": (
                    [
                        "I2V-01-Director",
                        "I2V-01",
                        "I2V-01-live",
                    ],
                    {
                        "default": "I2V-01",
                        "tooltip": "Model to use for video generation",
                    },
                ),
            },
            "optional": {
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "The random seed used for creating the noise.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    RETURN_TYPES = ("VIDEO",)
    DESCRIPTION = "Generates videos from an image and prompts using Minimax's API"
    FUNCTION = "generate_video"
    CATEGORY = "api node/video/Minimax"
    API_NODE = True
    OUTPUT_NODE = True
```


# MiniMax Text to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/minimax/minimax-text-to-video

A node that converts text descriptions into videos using MiniMax AI

<img alt="ComfyUI Native MiniMax Text to Video Node" />

The MiniMax Text to Video node connects to MiniMax's API to generate high-quality, smooth videos from text prompts. It supports different video generation models to create short video clips in various styles.

## Parameters

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt\_text | String | "" | Text prompt that guides the video generation |
| model | Select | "T2V-01" | Video model to use, options are "T2V-01" and "T2V-01-Director" |
| seed | Integer | 0 | Random seed for noise generation, defaults to 0 |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | Video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class MinimaxTextToVideoNode:
    """
    Generates videos synchronously based on a prompt, and optional parameters using Minimax's API.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt_text": (
                    "STRING",
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text prompt to guide the video generation",
                    },
                ),
                "model": (
                    [
                        "T2V-01",
                        "T2V-01-Director",
                    ],
                    {
                        "default": "T2V-01",
                        "tooltip": "Model to use for video generation",
                    },
                ),
            },
            "optional": {
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "The random seed used for creating the noise.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    RETURN_TYPES = ("VIDEO",)
    DESCRIPTION = "Generates videos from prompts using Minimax's API"
    FUNCTION = "generate_video"
    CATEGORY = "api node/video/Minimax"
    API_NODE = True
    OUTPUT_NODE = True

    def generate_video(
        self,
        prompt_text,
        seed=0,
        model="T2V-01",
        image: torch.Tensor=None, # used for ImageToVideo
        subject: torch.Tensor=None, # used for SubjectToVideo
        auth_token=None,
    ):
        '''
        Function used between Minimax nodes - supports T2V, I2V, and S2V, based on provided arguments.
        '''
        # upload image, if passed in
        image_url = None
        if image is not None:
            image_url = upload_images_to_comfyapi(image, max_images=1, auth_token=auth_token)[0]

        # TODO: figure out how to deal with subject properly, API returns invalid params when using S2V-01 model
        subject_reference = None
        if subject is not None:
            subject_url = upload_images_to_comfyapi(subject, max_images=1, auth_token=auth_token)[0]
            subject_reference = [SubjectReferenceItem(image=subject_url)]


        video_generate_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/minimax/video_generation",
                method=HttpMethod.POST,
                request_model=MinimaxVideoGenerationRequest,
                response_model=MinimaxVideoGenerationResponse,
            ),
            request=MinimaxVideoGenerationRequest(
                model=Model(model),
                prompt=prompt_text,
                callback_url=None,
                first_frame_image=image_url,
                subject_reference=subject_reference,
                prompt_optimizer=None,
            ),
            auth_token=auth_token,
        )
        response = video_generate_operation.execute()

        task_id = response.task_id
        if not task_id:
            raise Exception(f"Minimax generation failed: {response.base_resp}")

        video_generate_operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path="/proxy/minimax/query/video_generation",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=MinimaxTaskResultResponse,
                query_params={"task_id": task_id},
            ),
            completed_statuses=["Success"],
            failed_statuses=["Fail"],
            status_extractor=lambda x: x.status.value,
            auth_token=auth_token,
        )
        task_result = video_generate_operation.execute()

        file_id = task_result.file_id
        if file_id is None:
            raise Exception("Request was not successful. Missing file ID.")
        file_retrieve_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/minimax/files/retrieve",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=MinimaxFileRetrieveResponse,
                query_params={"file_id": int(file_id)},
            ),
            request=EmptyRequest(),
            auth_token=auth_token,
        )
        file_result = file_retrieve_operation.execute()

        file_url = file_result.file.download_url
        if file_url is None:
            raise Exception(
                f"No video was found in the response. Full response: {file_result.model_dump()}"
            )
        logging.info(f"Generated video URL: {file_url}")

        video_io = download_url_to_bytesio(file_url)
        if video_io is None:
            error_msg = f"Failed to download video from {file_url}"
            logging.error(error_msg)
            raise Exception(error_msg)
        return (VideoFromFile(video_io),)
```


# Pika 2.2 Image to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pika/pika-image-to-video

A node that converts static images to dynamic videos using Pika AI

<img alt="ComfyUI Native Pika 2.2 Image to Video Node" />

The Pika 2.2 Image to Video node connects to Pika's latest 2.2 API to transform static images into dynamic videos. It preserves the visual features of the original image while adding natural motion based on text prompts.

## Parameters

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | Image | - | Input image to convert to video |
| prompt\_text | String | "" | Text prompt describing video motion and content |
| negative\_prompt | String | "" | Elements to avoid in the video |
| seed | Integer | 0 | Random seed for generation |
| resolution | Select | "1080p" | Output video resolution |
| duration | Select | "5s" | Length of generated video |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | Video | Generated video |

## How It Works

The node sends the input image and parameters (prompts, resolution, duration, etc.) to Pika's API server as multipart form data. The API processes this and returns the generated video. Users can control the output by adjusting the prompts, negative prompts, random seed and other parameters.

## Source Code

\[Node Source Code (Updated 2025-05-05)]

```python theme={null}

class PikaImageToVideoV2_2(PikaNodeBase):
    """Pika 2.2 Image to Video Node."""

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "image": (
                    IO.IMAGE,
                    {"tooltip": "The image to convert to video"},
                ),
                **cls.get_base_inputs_types(PikaBodyGenerate22I2vGenerate22I2vPost),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    DESCRIPTION = "Sends an image and prompt to the Pika API v2.2 to generate a video."
    RETURN_TYPES = ("VIDEO",)

    def api_call(
        self,
        image: torch.Tensor,
        prompt_text: str,
        negative_prompt: str,
        seed: int,
        resolution: str,
        duration: int,
        auth_token: Optional[str] = None,
    ) -> tuple[VideoFromFile]:
        """API call for Pika 2.2 Image to Video."""
        # Convert image to BytesIO
        image_bytes_io = tensor_to_bytesio(image)
        image_bytes_io.seek(0)  # Reset stream position

        # Prepare file data for multipart upload
        pika_files = {"image": ("image.png", image_bytes_io, "image/png")}

        # Prepare non-file data using the Pydantic model
        pika_request_data = PikaBodyGenerate22I2vGenerate22I2vPost(
            promptText=prompt_text,
            negativePrompt=negative_prompt,
            seed=seed,
            resolution=resolution,
            duration=duration,
        )

        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=PATH_IMAGE_TO_VIDEO,
                method=HttpMethod.POST,
                request_model=PikaBodyGenerate22I2vGenerate22I2vPost,
                response_model=PikaGenerateResponse,
            ),
            request=pika_request_data,
            files=pika_files,
            content_type="multipart/form-data",
            auth_token=auth_token,
        )

        return self.execute_task(initial_operation, auth_token)

```


# Pika 2.2 Scenes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pika/pika-scenes

A node that creates coherent scene videos from multiple images using Pika AI

<img alt="ComfyUI Built-in Pika 2.2 Scenes Node" />

The Pika 2.2 Scenes node allows you to upload multiple images and generate a high-quality video incorporating these elements. It uses Pika's 2.2 API to create smooth scene transitions between the images.

## Parameters

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt\_text | string | "" | Text prompt describing video content and scenes |
| negative\_prompt | string | "" | Elements to exclude from the video |
| seed | integer | 0 | Random seed for generation |
| ingredients\_mode | select | "creative" | Image combination mode |
| resolution | select | API default | Output video resolution |
| duration | select | API default | Output video length |
| aspect\_ratio | float | 1.7777777777777777 (16:9) | Video aspect ratio, range 0.4-2.5 |

### Optional Parameters

| Parameter | Type | Description |
| - | - | - |
| image\_ingredient\_1 | image | First scene image |
| image\_ingredient\_2 | image | Second scene image |
| image\_ingredient\_3 | image | Third scene image |
| image\_ingredient\_4 | image | Fourth scene image |
| image\_ingredient\_5 | image | Fifth scene image |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | video | Generated video |

## How It Works

The Pika 2.2 Scenes node analyzes all input images and creates a video containing these image elements. The node sends the images and parameters to Pika's API server, which processes them and returns the generated video.

Users can guide the video style and content through prompts, and exclude unwanted elements using negative prompts. The node supports up to 5 input images as ingredients and generates the final video based on the specified combination mode, resolution, duration, and aspect ratio.

## Source Code

```python theme={null}

class PikaScenesV2_2(PikaNodeBase):
    """Pika 2.2 Scenes Node."""

    @classmethod
    def INPUT_TYPES(cls):
        image_ingredient_input = (
            IO.IMAGE,
            {"tooltip": "Image that will be used as ingredient to create a video."},
        )
        return {
            "required": {
                **cls.get_base_inputs_types(
                    PikaBodyGenerate22C2vGenerate22PikascenesPost,
                ),
                "ingredients_mode": model_field_to_node_input(
                    IO.COMBO,
                    PikaBodyGenerate22C2vGenerate22PikascenesPost,
                    "ingredientsMode",
                    enum_type=IngredientsMode,
                    default="creative",
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.FLOAT,
                    PikaBodyGenerate22C2vGenerate22PikascenesPost,
                    "aspectRatio",
                    step=0.001,
                    min=0.4,
                    max=2.5,
                    default=1.7777777777777777,
                ),
            },
            "optional": {
                "image_ingredient_1": image_ingredient_input,
                "image_ingredient_2": image_ingredient_input,
                "image_ingredient_3": image_ingredient_input,
                "image_ingredient_4": image_ingredient_input,
                "image_ingredient_5": image_ingredient_input,
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    DESCRIPTION = "Combine your images to create a video with the objects in them. Upload multiple images as ingredients and generate a high-quality video that incorporates all of them."
    RETURN_TYPES = ("VIDEO",)

    def api_call(
        self,
        prompt_text: str,
        negative_prompt: str,
        seed: int,
        resolution: str,
        duration: int,
        ingredients_mode: str,
        aspect_ratio: float,
        image_ingredient_1: Optional[torch.Tensor] = None,
        image_ingredient_2: Optional[torch.Tensor] = None,
        image_ingredient_3: Optional[torch.Tensor] = None,
        image_ingredient_4: Optional[torch.Tensor] = None,
        image_ingredient_5: Optional[torch.Tensor] = None,
        auth_token: Optional[str] = None,
    ) -> tuple[VideoFromFile]:
        """API call for Pika Scenes 2.2."""
        all_image_bytes_io = []
        for image in [
            image_ingredient_1,
            image_ingredient_2,
            image_ingredient_3,
            image_ingredient_4,
            image_ingredient_5,
        ]:
            if image is not None:
                image_bytes_io = tensor_to_bytesio(image)
                image_bytes_io.seek(0)
                all_image_bytes_io.append(image_bytes_io)

        # Prepare files data for multipart upload
        pika_files = [
            ("images", (f"image_{i}.png", image_bytes_io, "image/png"))
            for i, image_bytes_io in enumerate(all_image_bytes_io)
        ]

        # Prepare non-file data using the Pydantic model
        pika_request_data = PikaBodyGenerate22C2vGenerate22PikascenesPost(
            ingredientsMode=ingredients_mode,
            promptText=prompt_text,
            negativePrompt=negative_prompt,
            seed=seed,
            resolution=resolution,
            duration=duration,
            aspectRatio=aspect_ratio,
        )

        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=PATH_PIKASCENES,
                method=HttpMethod.POST,
                request_model=PikaBodyGenerate22C2vGenerate22PikascenesPost,
                response_model=PikaGenerateResponse,
            ),
            request=pika_request_data,
            files=pika_files,
            content_type="multipart/form-data",
            auth_token=auth_token,
        )

        return self.execute_task(initial_operation, auth_token)


```


# Pika 2.2 Text to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pika/pika-text-to-video

A node that converts text descriptions into videos using Pika AI

<img alt="ComfyUI Native Pika 2.2 Text to Video Node" />

The Pika 2.2 Text to Video node uses Pika's 2.2 API to create videos from text descriptions. It connects to Pika's text-to-video API, allowing users to generate videos using text prompts with various control parameters.

## Parameters

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt\_text | String | "" | Text prompt describing the video content |
| negative\_prompt | String | "" | Elements to exclude from the video |
| seed | Integer | 0 | Random seed for generation |
| resolution | Select | "1080p" | Output video resolution |
| duration | Select | "5s" | Length of generated video |
| aspect\_ratio | Float | 1.7777777777777777 | Video aspect ratio, range 0.4-2.5, step 0.001 |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | Video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-05)]

```python theme={null}

class PikaTextToVideoNodeV2_2(PikaNodeBase):
    """Pika 2.2 Text to Video Node."""

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                **cls.get_base_inputs_types(PikaBodyGenerate22T2vGenerate22T2vPost),
                "aspect_ratio": model_field_to_node_input(
                    IO.FLOAT,
                    PikaBodyGenerate22T2vGenerate22T2vPost,
                    "aspectRatio",
                    step=0.001,
                    min=0.4,
                    max=2.5,
                    default=1.7777777777777777,
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    RETURN_TYPES = ("VIDEO",)
    DESCRIPTION = "Sends a text prompt to the Pika API v2.2 to generate a video."

    def api_call(
        self,
        prompt_text: str,
        negative_prompt: str,
        seed: int,
        resolution: str,
        duration: int,
        aspect_ratio: float,
        auth_token: Optional[str] = None,
    ) -> tuple[VideoFromFile]:
        """API call for Pika 2.2 Text to Video."""
        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=PATH_TEXT_TO_VIDEO,
                method=HttpMethod.POST,
                request_model=PikaBodyGenerate22T2vGenerate22T2vPost,
                response_model=PikaGenerateResponse,
            ),
            request=PikaBodyGenerate22T2vGenerate22T2vPost(
                promptText=prompt_text,
                negativePrompt=negative_prompt,
                seed=seed,
                resolution=resolution,
                duration=duration,
                aspectRatio=aspect_ratio,
            ),
            auth_token=auth_token,
            content_type="application/x-www-form-urlencoded",
        )

        return self.execute_task(initial_operation, auth_token)


```


# PixVerse Image to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pixverse/pixverse-image-to-video

A node that converts static images to dynamic videos using PixVerse AI

<img alt="ComfyUI Native PixVerse Image to Video Node" />

The PixVerse Image to Video node uses PixVerse's API to transform static images into dynamic videos. It preserves the visual features of the original image while adding natural motion based on text prompts.

## Parameters

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| image | Image | - | Input image to convert to video |
| prompt | String | "" | Text prompt describing video motion/content |
| negative\_prompt | String | "" | Elements to avoid in the video |
| seed | Integer | -1 | Random seed (-1 for random) |
| quality | Select | "high" | Output video quality level |
| aspect\_ratio | Select | "r16\_9" | Output video aspect ratio |
| duration | Select | "seconds\_4" | Length of generated video |
| motion\_mode | Select | "standard" | Video motion style |

### Optional Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| pixverse\_template | PIXVERSE\_TEMPLATE | None | Optional PixVerse template |

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | Video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-05)]

```python theme={null}
class PixverseImageToVideoNode(ComfyNodeABC):
    """
    Pixverse Image to Video

    Generates videos from an image and prompts.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": ("IMAGE",),
                "prompt": ("STRING", {"multiline": True, "default": ""}),
                "negative_prompt": ("STRING", {"multiline": True, "default": ""}),
                "seed": ("INT", {"default": -1, "min": -1, "max": 0xffffffffffffffff}),
                "quality": (list(PixverseQuality.__members__.keys()), {"default": "high"}),
                "aspect_ratio": (list(PixverseAspectRatio.__members__.keys()), {"default": "r16_9"}),
                "duration": (list(PixverseDuration.__members__.keys()), {"default": "seconds_4"}),
                "motion_mode": (list(PixverseMotionMode.__members__.keys()), {"default": "standard"}),
            },
            "optional": {
                "pixverse_template": ("PIXVERSE_TEMPLATE",),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    RETURN_TYPES = ("VIDEO",)
    DESCRIPTION = "Generates videos from an image and prompts using Pixverse's API"
    FUNCTION = "generate_video"
    CATEGORY = "api node/video/Pixverse"
    API_NODE = True
    OUTPUT_NODE = True
```


# PixVerse Template - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pixverse/pixverse-template

A helper node that provides preset templates for PixVerse video generation

<img alt="ComfyUI Native PixVerse Template Node" />

The PixVerse Template node lets you choose from predefined video generation templates to control the style and effects of PixVerse video generation nodes.
This helper node connects to PixVerse video generation nodes, allowing users to quickly apply preset video styles without manually adjusting complex parameter combinations.

## Parameters

### Required Parameters

| Parameter | Type | Description |
| - | - | - |
| template | Select | Choose a template from available video presets |

### Output

| Output | Type | Description |
| - | - | - |
| pixverse\_template | PixverseIO.TEMPLATE | Configuration object containing the selected template ID |

## Source Code

\[Node Source Code (Updated 2025-05-05)]

```python theme={null}

class PixverseTemplateNode:
    """
    Select template for Pixverse Video generation.
    """

    RETURN_TYPES = (PixverseIO.TEMPLATE,)
    RETURN_NAMES = ("pixverse_template",)
    FUNCTION = "create_template"
    CATEGORY = "api node/video/Pixverse"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "template": (list(pixverse_templates.keys()), ),
            }
        }

    def create_template(self, template: str):
        template_id = pixverse_templates.get(template, None)
        if template_id is None:
            raise Exception(f"Template '{template}' is not recognized.")
        # just return the integer
        return (template_id,)

```


# PixVerse Text to Video - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pixverse/pixverse-text-to-video

A node that converts text descriptions into videos using PixVerse AI technology

<img alt="ComfyUI Built-in PixVerse Text to Video Node" />

The PixVerse Text to Video node connects to PixVerse's text-to-video API, allowing users to generate high-quality videos from text descriptions. Users can customize their creations by adjusting various parameters like video quality, duration, and motion mode.

## Parameters

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| prompt | string | "" | Text prompt describing the video content |
| aspect\_ratio | select | - | Output video aspect ratio |
| quality | select | PixverseQuality.res\_540p | Video quality level |
| duration\_seconds | select | - | Video duration |
| motion\_mode | select | - | Video motion mode |
| seed | integer | 0 | Random seed for consistent generation results |

### Optional Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| negative\_prompt | string | "" | Elements to exclude from the video |
| pixverse\_template | PIXVERSE\_TEMPLATE | None | Optional template for style settings |

### Limitations

* 1080p quality only supports normal motion mode with 5-second duration
* Non 5-second durations only support normal motion mode

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-05)]

```python theme={null}

class PixverseTextToVideoNode(ComfyNodeABC):
    """
    Generates videos synchronously based on prompt and output_size.
    """

    RETURN_TYPES = (IO.VIDEO,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/video/Pixverse"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the video generation",
                    },
                ),
                "aspect_ratio": (
                    [ratio.value for ratio in PixverseAspectRatio],
                ),
                "quality": (
                    [resolution.value for resolution in PixverseQuality],
                    {
                        "default": PixverseQuality.res_540p,
                    },
                ),
                "duration_seconds": ([dur.value for dur in PixverseDuration],),
                "motion_mode": ([mode.value for mode in PixverseMotionMode],),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2147483647,
                        "control_after_generate": True,
                        "tooltip": "Seed for video generation.",
                    },
                ),
            },
            "optional": {
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
                "pixverse_template": (
                    PixverseIO.TEMPLATE,
                    {
                        "tooltip": "An optional template to influence style of generation, created by the Pixverse Template node."
                    }
                )
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        aspect_ratio: str,
        quality: str,
        duration_seconds: int,
        motion_mode: str,
        seed,
        negative_prompt: str=None,
        pixverse_template: int=None,
        auth_token=None,
        **kwargs,
    ):
        # 1080p is limited to 5 seconds duration
        # only normal motion_mode supported for 1080p or for non-5 second duration
        if quality == PixverseQuality.res_1080p:
            motion_mode = PixverseMotionMode.normal
            duration_seconds = PixverseDuration.dur_5
        elif duration_seconds != PixverseDuration.dur_5:
            motion_mode = PixverseMotionMode.normal

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/pixverse/video/text/generate",
                method=HttpMethod.POST,
                request_model=PixverseTextVideoRequest,
                response_model=PixverseVideoResponse,
            ),
            request=PixverseTextVideoRequest(
                prompt=prompt,
                aspect_ratio=aspect_ratio,
                quality=quality,
                duration=duration_seconds,
                motion_mode=motion_mode,
                negative_prompt=negative_prompt if negative_prompt else None,
                template_id=pixverse_template,
                seed=seed,
            ),
            auth_token=auth_token,
        )
        response_api = operation.execute()

        if response_api.Resp is None:
            raise Exception(f"Pixverse request failed: '{response_api.ErrMsg}'")

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/pixverse/video/result/{response_api.Resp.video_id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=PixverseGenerationStatusResponse,
            ),
            completed_statuses=[PixverseStatus.successful],
            failed_statuses=[PixverseStatus.contents_moderation, PixverseStatus.failed, PixverseStatus.deleted],
            status_extractor=lambda x: x.Resp.status,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        vid_response = requests.get(response_poll.Resp.url)
        return (VideoFromFile(BytesIO(vid_response.content)),)

```


# PixVerse Transition Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pixverse/pixverse-transition-video

Create smooth transition videos between start and end frames using PixVerse AI

<img alt="ComfyUI Native PixVerse Transition Video Node" />

The Pixverse Transition Video node connects to PixVerse's API to generate smooth video transitions between two images. It automatically creates all intermediate frames to produce fluid transformations, perfect for morphing effects, scene transitions, and object evolution.

## Parameters

### Required Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| first\_frame | Image | - | Starting frame image |
| last\_frame | Image | - | Ending frame image |
| prompt | String | "" | Text prompt describing video and transition |
| quality | Select | "PixverseQuality.res\_540p" | Output video quality |
| duration\_seconds | Select | - | Length of generated video |
| motion\_mode | Select | - | Video motion style |
| seed | Integer | 0 | Random seed (range: 0-2147483647) |

### Optional Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| negative\_prompt | String | "" | Elements to avoid in video |
| pixverse\_template | PIXVERSE\_TEMPLATE | None | Optional style preset |

### Parameter Constraints

* When quality is set to 1080p, motion\_mode is forced to normal and duration\_seconds to 5 seconds
* When duration\_seconds is not 5 seconds, motion\_mode is forced to normal

### Output

| Output | Type | Description |
| - | - | - |
| VIDEO | Video | Generated video |

## Source Code

```python theme={null}

class PixverseTransitionVideoNode(ComfyNodeABC):
    """
    Generates videos synchronously based on prompt and output_size.
    """

    RETURN_TYPES = (IO.VIDEO,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/video/Pixverse"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "first_frame": (
                    IO.IMAGE,
                ),
                "last_frame": (
                    IO.IMAGE,
                ),
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the video generation",
                    },
                ),
                "quality": (
                    [resolution.value for resolution in PixverseQuality],
                    {
                        "default": PixverseQuality.res_540p,
                    },
                ),
                "duration_seconds": ([dur.value for dur in PixverseDuration],),
                "motion_mode": ([mode.value for mode in PixverseMotionMode],),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2147483647,
                        "control_after_generate": True,
                        "tooltip": "Seed for video generation.",
                    },
                ),
            },
            "optional": {
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
                "pixverse_template": (
                    PixverseIO.TEMPLATE,
                    {
                        "tooltip": "An optional template to influence style of generation, created by the Pixverse Template node."
                    }
                )
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        first_frame: torch.Tensor,
        last_frame: torch.Tensor,
        prompt: str,
        quality: str,
        duration_seconds: int,
        motion_mode: str,
        seed,
        negative_prompt: str=None,
        pixverse_template: int=None,
        auth_token=None,
        **kwargs,
    ):
        first_frame_id = upload_image_to_pixverse(first_frame, auth_token=auth_token)
        last_frame_id = upload_image_to_pixverse(last_frame, auth_token=auth_token)

        # 1080p is limited to 5 seconds duration
        # only normal motion_mode supported for 1080p or for non-5 second duration
        if quality == PixverseQuality.res_1080p:
            motion_mode = PixverseMotionMode.normal
            duration_seconds = PixverseDuration.dur_5
        elif duration_seconds != PixverseDuration.dur_5:
            motion_mode = PixverseMotionMode.normal

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/pixverse/video/transition/generate",
                method=HttpMethod.POST,
                request_model=PixverseTransitionVideoRequest,
                response_model=PixverseVideoResponse,
            ),
            request=PixverseTransitionVideoRequest(
                first_frame_img=first_frame_id,
                last_frame_img=last_frame_id,
                prompt=prompt,
                quality=quality,
                duration=duration_seconds,
                motion_mode=motion_mode,
                negative_prompt=negative_prompt if negative_prompt else None,
                template_id=pixverse_template,
                seed=seed,
            ),
            auth_token=auth_token,
        )
        response_api = operation.execute()

        if response_api.Resp is None:
            raise Exception(f"Pixverse request failed: '{response_api.ErrMsg}'")

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/pixverse/video/result/{response_api.Resp.video_id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=PixverseGenerationStatusResponse,
            ),
            completed_statuses=[PixverseStatus.successful],
            failed_statuses=[PixverseStatus.contents_moderation, PixverseStatus.failed, PixverseStatus.deleted],
            status_extractor=lambda x: x.Resp.status,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        vid_response = requests.get(response_poll.Resp.url)
        return (VideoFromFile(BytesIO(vid_response.content)),)
```


# ARVideoI2V - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ARVideoI2V

This node prepares an image-to-video generation setup for AR (Auto-Regressive) video models that use Causal Forcing or Self-Forcing.

This node prepares an image-to-video generation setup for AR (Auto-Regressive) video models that use Causal Forcing or Self-Forcing. It encodes a starting image into latent space with a VAE and stores it in the model's transformer options, so the video sampling process can seed the KV cache before denoising. It uses the same text-to-video model checkpoint, so no separate image-to-video architecture is needed.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AR video model to be used for generation. | MODEL | Yes | - |
| `vae` | The VAE model used to encode the starting image into latent space. | VAE | Yes | - |
| `start_image` | The initial image that will serve as the first frame of the generated video. Only the first image in the input batch is used, and only its RGB channels are encoded. | IMAGE | Yes | - |
| `width` | The width of the generated video frames (default: 832). | INT | Yes | 16 to 8192 (step: 16) |
| `height` | The height of the generated video frames (default: 480). | INT | Yes | 16 to 8192 (step: 16) |
| `length` | The total number of frames of the generated video (default: 81). | INT | Yes | 1 to 1024 (step: 4) |
| `batch_size` | The number of video sequences to generate in a single batch (default: 1). | INT | Yes | 1 to 64 |

Note: The start image is resized to the specified `width` and `height` before being encoded. The latent temporal dimension is calculated as `((length - 1) // 4) + 1`, and the latent spatial dimensions are `height / 8` and `width / 8`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The cloned model with the encoded start image stored in its transformer options (`ar_config.initial_latent`), which the sampler uses to seed the KV cache before denoising. | MODEL |
| `LATENT` | A zero-filled latent tensor with shape `[batch_size, 16, lat_t, height // 8, width // 8]`, where `lat_t = ((length - 1) // 4) + 1`. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ARVideoI2V/en.md)

***

**Source fingerprint (SHA-256):** `984834951b9d5a22aef51c85a5019fd8ba58cdb2d6fff235371ed29f316896d8`


# AddLayer - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AddLayer

The Add Layer node turns an input image into a layer and places it on a canvas, either starting a new layer stack or appending it to an existing one.

The Add Layer node turns an input image into a layer and places it on a canvas, either starting a new layer stack or appending it to an existing one. You can set the layer's name, position, size, rotation, opacity, blend mode, stacking order, and horizontal or vertical flipping. This node is marked as experimental.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `layers` | Layer stack to append to. Leave unconnected to start a new stack. | LAYERS | No | — |
| `image` | Layer content at its native size. A batch expands to consecutive layers. | IMAGE | Yes | — |
| `mask` | Transparency mask for this layer. Masked areas (value 1) become transparent, multiplying with any alpha channel the image already carries. | MASK | No | — |
| `name` | Layer name shown in the compositor editor. (default: "") | STRING | No | — |
| `x` | Initial horizontal placement on the canvas. (default: 0) | INT | No | -MAX\_RESOLUTION to MAX\_RESOLUTION |
| `y` | Initial vertical placement on the canvas. (default: 0) | INT | No | -MAX\_RESOLUTION to MAX\_RESOLUTION |
| `opacity` | Initial layer opacity. (default: 1.0) | FLOAT | No | 0.0 to 1.0 (step: 0.01) |
| `blend_mode` | Initial blend mode, applied against the layers below. On the bottom layer over the default transparent background, non-normal modes produce transparency. (default: "normal") | COMBO | No | Multiple options available |
| `rotation` | Initial rotation in degrees, clockwise. (default: 0.0) | FLOAT | No | -360.0 to 360.0 (step: 1.0) |
| `width` | Initial display width. 0 keeps the image's native width. (default: 0) | INT | No | 0 to MAX\_RESOLUTION |
| `height` | Initial display height. 0 keeps the image's native height. (default: 0) | INT | No | 0 to MAX\_RESOLUTION |
| `z_index` | Stacking override. Layers are stable-sorted by z\_index; equal values keep their list order. (default: 0) | INT | No | -1000 to 1000 |
| `flip_h` | Flip the layer horizontally. (default: False) | BOOLEAN | No | false / true |
| `flip_v` | Flip the layer vertically. (default: False) | BOOLEAN | No | false / true |

Notes:

* Only `image` is required; all other inputs are optional.
* When `layers` is left unconnected, a new layer stack is created. When a layer stack is connected, the new layer is appended to it.
* A batch of images in the `image` input creates multiple consecutive layers.
* `width` and `height` default to 0, which keeps the image's native dimensions. Values greater than 0 override the display size.
* `opacity`, `blend_mode`, `rotation`, `width`, and `height` are only applied when they differ from their default values.
* The canvas size of a connected layer stack is preserved in the output.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `layers` | The layer stack with this layer appended. | LAYERS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AddLayer/en.md)

***

**Source fingerprint (SHA-256):** `b7bf1a012d17cb5768b49d5c0617e13562ba015f695e6c9b1d1bbefba4150f9e`


# BatchImagesNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BatchImagesNode

The Batch Images node combines multiple individual images into a single batch.

The Batch Images node combines multiple individual images into a single batch. It takes a variable number of image inputs and outputs them as one batched image tensor, allowing them to be processed together in subsequent nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | A dynamic list of image inputs. You can add between 2 and 50 images to be combined into a batch. The node interface allows you to add more image input slots as needed. | IMAGE | Yes | 2 to 50 inputs |

**Note:** You must connect at least two images for the node to function. The first input slot is always required, and you can add more using the "+" button that appears in the node interface.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | A single batched image tensor containing all the input images stacked together. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BatchImagesNode/en.md)

***

**Source fingerprint (SHA-256):** `f756fb15760cd2518da9c3f88281d3ab3361b4c2b4820fe2be152e4db1cf102c`


# BatchMasksNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BatchMasksNode

The Batch Masks node combines multiple individual mask inputs into a single batch.

The Batch Masks node combines multiple individual mask inputs into a single batch. It takes a variable number of mask inputs and outputs them as a single batched mask tensor, allowing for batch processing of masks in subsequent nodes. If the input masks have different sizes, they are automatically resized to match the dimensions of the first mask.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mask` | The mask inputs to combine into a batch. At least one mask is required. You can add up to 50 masks total by clicking the "+" button on the node. If masks have different sizes, they are automatically resized to match the first mask's dimensions. | MASK | Yes | 1 to 50 masks |

**Note:** This node uses an autogrow input template. You must connect at least one mask. You can add up to 49 more mask inputs for a total of 50 masks. All connected masks will be combined into a single batch. If masks have different heights or widths, they are automatically resized to match the dimensions of the first mask using bilinear interpolation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | A single batched mask containing all the input masks stacked together. If no masks are provided, returns None. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BatchMasksNode/en.md)

***

**Source fingerprint (SHA-256):** `7e9bc4be72c7fa8fceab2cf167c72b7e1ff858c0281d977f2ad3ab433d9d58d6`


# BerniniConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BerniniConditioning

The BerniniConditioning node prepares video and image conditioning data for the Wan2.2-A14B model.

The BerniniConditioning node prepares video and image conditioning data for the Wan2.2-A14B model. It encodes source videos, reference videos, and reference images using the provided VAE, then attaches them to the conditioning data as in-context tokens. The task is automatically inferred from which inputs are connected.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning data | CONDITIONING | Yes | - |
| `negative` | Negative conditioning data | CONDITIONING | Yes | - |
| `vae` | VAE model used to encode video and image inputs | VAE | Yes | - |
| `width` | Width of the output latent (default: 832) | INT | Yes | 16 to 8192 (step: 16) |
| `height` | Height of the output latent (default: 480) | INT | Yes | 16 to 8192 (step: 16) |
| `length` | Number of frames in the output latent (default: 81) | INT | Yes | 1 to 8192 (step: 4) |
| `batch_size` | Number of videos to generate in a single batch (default: 1) | INT | Yes | 1 to 4096 |
| `source_video` | Source video to edit or restyle (v2v, rv2v). Resized to width/height and trimmed to length. | IMAGE | No | - |
| `reference_video` | Video to insert into the source video (ads2v). Trimmed to length and resized with preserved aspect ratio (long edge capped at ref\_max\_size). | IMAGE | No | - |
| `reference_images` | Reference images injected as in-context tokens (r2v, rv2v). Each image is encoded independently at its own native aspect ratio (long edge capped at ref\_max\_size). Up to 8 images can be provided. | IMAGE | No | 0 to 8 images |
| `ref_max_size` | Max size for the long edge of reference\_video and reference\_images. Resized with preserved aspect ratio and snapped to 16px (default: 848). | INT | No | 16 to 8192 (step: 16) |

**Note:** The task is inferred from which inputs are connected:

* No inputs connected → text-to-video (t2v)
* `source_video` only → video-to-video (v2v)
* `source_video` + `reference_images` → reference-guided video editing (rv2v)
* `reference_images` only → reference-to-video (r2v)
* `source_video` + `reference_video` → insert image/video into video (ads2v)

Context streams are attached in a fixed order: `source_video` (source ID 1), then `reference_video` (source ID 2), then each reference image (source IDs 3, 4, ...). A reference image input containing multiple images contributes one stream per image.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with context latents attached | CONDITIONING |
| `negative` | Negative conditioning with context latents attached | CONDITIONING |
| `latent` | Empty latent tensor with dimensions matching the specified width, height, length, and batch size | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BerniniConditioning/en.md)

***

**Source fingerprint (SHA-256):** `70b5026f9479249bc5d1fe4695583193216e34e1b092764ac30e0ec3b7eba670`


# Canny - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Canny

Extract all edge lines from photos, like using a pen to outline a photo, drawing out the contours and detail boundaries of objects.

Extract all edge lines from photos, like using a pen to outline a photo, drawing out the contours and detail boundaries of objects.

## Working Principle

Imagine you are an artist who needs to use a pen to outline a photo. The Canny node acts like an intelligent assistant, helping you decide where to draw lines (edges) and where not to.

This process is like a screening job:

* **High threshold** is the "must draw line standard": only very obvious and clear contour lines will be drawn, such as facial contours of people and building frames
* **Low threshold** is the "definitely don't draw line standard": edges that are too weak will be ignored to avoid drawing noise and meaningless lines
* **Middle area**: edges between the two standards will be drawn together if they connect to "must draw lines", but won't be drawn if they are isolated

The final output is a black and white image, where white parts are detected edge lines and black parts are areas without edges.

## Inputs

| Parameter Name | Function Description | Data Type | Input Type | Default | Range |
| - | - | - | - | - | - |
| `image` | Original photo that needs edge extraction | IMAGE | Input | - | - |
| `low_threshold` | Low threshold, determines how weak edges to ignore. Lower values preserve more details but may produce noise | FLOAT | Widget | 0.4 | 0.01-0.99 |
| `high_threshold` | High threshold, determines how strong edges to preserve. Higher values only keep the most obvious contour lines | FLOAT | Widget | 0.8 | 0.01-0.99 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | Black and white edge image, white lines are detected edges, black areas are parts without edges | IMAGE |

## Parameter Comparison

<img alt="Original Image" />

<img alt="Parameter Comparison" />

**Common Issues:**

* Broken edges: Try lowering high threshold
* Too much noise: Raise low threshold
* Missing important details: Lower low threshold
* Edges too rough: Check input image quality and resolution

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Canny/en.md)


# CenterCropImages - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CenterCropImages

The Center Crop Images node crops an image from its center to a specified width and height.

The Center Crop Images node crops an image from its center to a specified width and height. It calculates the central region of the input image and extracts a rectangular area of the defined dimensions. If the requested crop size is larger than the image, the crop will be constrained to the image's boundaries.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be cropped. | IMAGE | Yes | - |
| `width` | The width of the crop area (default: 512). | INT | Yes | 1 to 8192 |
| `height` | The height of the crop area (default: 512). | INT | Yes | 1 to 8192 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resulting image after the center crop operation. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CenterCropImages/en.md)

***

**Source fingerprint (SHA-256):** `1b22529602e3aca816b583158c4bb5aa51de3478ac8068c2a69a3392fb12746f`


# ColorTransfer - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ColorTransfer

The ColorTransfer node adjusts the color palette of a target image to match the colors of a reference image.

The ColorTransfer node adjusts the color palette of a target image to match the colors of a reference image. It uses different mathematical algorithms to analyze and transfer the color characteristics, such as brightness, contrast, and hue distribution, from the reference to the target. This is useful for creating visual consistency across multiple images or applying a specific color grade.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image_target` | Image(s) to apply the color transform to. | IMAGE | Yes | - |
| `image_ref` | Reference image(s) to match colors to. | IMAGE | Yes | - |
| `method` | The color transfer algorithm to use. | COMBO | Yes | `"reinhard_lab"`<br />`"mkl_lab"`<br />`"histogram"` |
| `source_stats` | Determines how color statistics are calculated from the source (target) image(s). | DYNAMICCOMBO | Yes | `"per_frame"`<br />`"uniform"`<br />`"target_frame"` |
| `strength` | The intensity of the color transfer effect. A value of 1.0 applies the full transform, while 0.0 returns the original image. Default: 1.0 | FLOAT | Yes | 0.0 to 10.0 |

**Parameter Details:**

* **`source_stats` Options:**
  * **`per_frame`**: Each frame in a batch is matched to the `image_ref` individually.
  * **`uniform`**: Color statistics are pooled across all source frames to create a single baseline, which is then matched to the `image_ref`.
  * **`target_frame`**: Uses one chosen frame from the target batch as the baseline for computing the transform to the `image_ref`. This transform is then applied uniformly to all frames, which preserves the relative color differences between them. When this option is selected, an additional `target_index` parameter becomes available.
* **`target_index`** (appears when `source_stats` is `"target_frame"`): The frame index (starting from 0) used as the source baseline for computing the transform. Default: 0. Must be between 0 and 10000.

**Constraints:**

* If `strength` is set to 0.0 or `image_ref` is `None`, the node returns the original `image_target` without processing.
* When `source_stats` is set to `"target_frame"`, the `target_index` must be a valid index within the batch of `image_target`. If it exceeds the number of frames, the last frame is used.
* For the `histogram` method with `source_stats` set to `"per_frame"`, if the batch size of `image_ref` is greater than 1, each target frame is matched to the corresponding reference frame by index. If the reference batch has only one frame, it is used for all target frames.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resulting image(s) after the color transfer has been applied. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ColorTransfer/en.md)

***

**Source fingerprint (SHA-256):** `f844af34ac6129c7751953c48e2d12aa0d2c556937e610f649f3eb2725955711`


# ConditioningCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningCombine

This node combines two conditioning inputs into a single output, effectively merging their information.

This node combines two conditioning inputs into a single output, effectively merging their information. The two conditions are combined using list concatenation.

## Inputs

| Parameter Name | Description | Data Type |
| - | - | - |
| `conditioning_1` | The first conditioning input to be combined. It has equal importance with `conditioning_2` in the combination process. | `CONDITIONING` |
| `conditioning_2` | The second conditioning input to be combined. It has equal importance with `conditioning_1` in the combination process. | `CONDITIONING` |

## Outputs

| Parameter Name | Description | Data Type |
| - | - | - |
| `conditioning` | The result of combining `conditioning_1` and `conditioning_2`, encapsulating the merged information. | `CONDITIONING` |

## Usage Scenarios

Compare the two groups below: the left side uses the ConditioningCombine node, while the right side shows normal output.

<img alt="Compare" />

In this example, the two conditions used in `Conditioning Combine` have equivalent importance. Therefore, you can use different text encodings for image style, subject features, etc., allowing the prompt features to be output more completely. The second prompt uses the combined complete prompt, but semantic understanding may encode completely different conditions.

Using this node, you can achieve:

* Basic text merging: Connect the outputs of two `CLIP Text Encode` nodes to the two input ports of `Conditioning Combine`
* Complex prompt combination: Combine positive and negative prompts, or separately encode main descriptions and style descriptions before merging
* Conditional chain combination: Multiple `Conditioning Combine` nodes can be used in series to achieve gradual combination of multiple conditions

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningCombine/en.md)


# ControlNetLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ControlNetLoader

This node will detect models located in the ComfyUI/models/controlnet folder, and it will also read models from additional paths configured in the extramodelpaths.yaml file.

This node will detect models located in the `ComfyUI/models/controlnet` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The ControlNetLoader node is designed to load a ControlNet model from a specified path. It plays a crucial role in initializing ControlNet models, which are essential for applying control mechanisms over generated content or modifying existing content based on control signals.

## Inputs

| Field | Description | Comfy dtype |
| - | - | - |
| `control_net_name` | Specifies the name of the ControlNet model to be loaded, used to locate the model file within a predefined directory structure. | `COMBO[STRING]` |

## Outputs

| Field | Description | Comfy dtype |
| - | - | - |
| `control_net` | Returns the loaded ControlNet model, ready for use in controlling or modifying content generation processes. | `CONTROL_NET` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ControlNetLoader/en.md)


# CropByBBoxes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CropByBBoxes

The CropByBBoxes node extracts and resizes specific rectangular regions from an input image batch.

The CropByBBoxes node extracts and resizes specific rectangular regions from an input image batch. It uses provided bounding box coordinates to define the area to crop from each image. The cropped regions are then resized to a specified output dimension, with options to either stretch the crop or pad it to preserve its original aspect ratio.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input batch of images to crop. | IMAGE | Yes | - |
| `bboxes` | The list of bounding boxes defining the regions to crop. This input is forced, meaning it must be connected. | BOUNDINGBOX | Yes | - |
| `output_width` | The width each crop is resized to (default: 512). | INT | No | 64 - 4096 |
| `output_height` | The height each crop is resized to (default: 512). | INT | No | 64 - 4096 |
| `padding` | Extra padding in pixels added on each side of the bounding box before cropping (default: 0). | INT | No | 0 - 1024 |
| `keep_aspect` | Whether to stretch the crop to fit the output size, or pad with black pixels to preserve its aspect ratio (default: "stretch"). | COMBO | No | `"stretch"`<br />`"pad"` |

**Note:** The node processes one image frame at a time. If multiple bounding boxes are provided for a single frame, it calculates a single crop region that is the union (the smallest rectangle containing all boxes) of all provided boxes. If a calculated crop region is invalid (e.g., zero width or height), the node will create a fallback crop from the center-top of the image.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | All cropped and resized regions, stacked into a single image batch. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CropByBBoxes/en.md)

***

**Source fingerprint (SHA-256):** `7524d629e61f5af2475f819bc9431d4f4173feb5ad59f9bcf81d822330fb3e22`


# CropMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CropMask

The CropMask node is designed for cropping a specified area from a given mask.

The CropMask node is designed for cropping a specified area from a given mask. It allows users to define the region of interest by specifying coordinates and dimensions, effectively extracting a portion of the mask for further processing or analysis.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The mask input represents the mask image to be cropped. It is essential for defining the area to be extracted based on the specified coordinates and dimensions. | MASK |
| `x` | The x coordinate specifies the starting point on the horizontal axis from which the cropping should begin. | INT |
| `y` | The y coordinate determines the starting point on the vertical axis for the cropping operation. | INT |
| `width` | Width defines the horizontal extent of the crop area from the starting point. | INT |
| `height` | Height specifies the vertical extent of the crop area from the starting point. | INT |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The output is a cropped mask, which is a portion of the original mask defined by the specified coordinates and dimensions. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CropMask/en.md)


# DA3GeometryToMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DA3GeometryToMesh

This node converts a DA3GEOMETRY packet into a 3D mesh by unprojecting the depth map and triangulating the resulting point cloud.

This node converts a DA3\_GEOMETRY packet into a 3D mesh by unprojecting the depth map and triangulating the resulting point cloud. It processes a single image from a batch and produces a textured or untextured mesh suitable for 3D rendering.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `da3_geometry` | The DA3\_GEOMETRY packet containing depth map, optional confidence map, optional sky map, and source image | DA3\_GEOMETRY | Yes | - |
| `batch_index` | Which image of a batch to convert. Per-image vertex counts differ so batches cannot be stacked (default: 0). Must be less than the batch size of the input geometry, otherwise an error is raised | INT | Yes | 0 to 4096 |
| `decimation` | Vertex stride. 1 = full resolution, 2 = half, etc. (default: 1) | INT | Yes | 1 to 8 |
| `discontinuity_threshold` | Drop triangles whose 3x3 depth span exceeds this fraction. 0 = off (default: 0.04) | FLOAT | Yes | 0.0 to 1.0 |
| `confidence_threshold` | Exclude pixels whose per-image normalised confidence is below this value. 0 = keep all, 1 = keep only the single most confident pixel. Used when the geometry has a confidence map (Small/Base models) (default: 0.1) | FLOAT | Yes | 0.0 to 1.0 |
| `use_sky_mask` | Exclude sky-probability pixels (sky >= 0.5) from the mesh. Used when the geometry has a sky map (Mono/Metric models) (default: True) | BOOLEAN | Yes | True or False |
| `texture` | Use the source image as a base color texture (default: True) | BOOLEAN | Yes | True or False |

Pixels with non-finite, zero, or negative depth values are always excluded from the mesh. An error is raised if the resulting mesh is empty; the error message suggests raising `discontinuity_threshold`, lowering `confidence_threshold`, or disabling `use_sky_mask`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MESH` | A triangulated 3D mesh with vertices, faces, UV coordinates, and optional texture | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DA3GeometryToMesh/en.md)

***

**Source fingerprint (SHA-256):** `1d311223a8d131030bcd4930d21852a21ac9dd5758e7f8b8d20b1cf68698893b`


# DA3GeometryToPointCloud - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DA3GeometryToPointCloud

Convert a depth map from a DA3GEOMETRY object into a 3D point cloud.

Convert a depth map from a DA3\_GEOMETRY object into a 3D point cloud. It applies filtering based on confidence and sky masks, and transforms the points into a common world coordinate system suitable for multi-view scenes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `da3_geometry` | The DA3\_GEOMETRY object containing depth data and optional image, confidence, and sky maps | DA3\_GEOMETRY | Yes | - |
| `batch_index` | Which image of a batch to convert (default: 0) | INT | Yes | 0 to 4096 |
| `confidence_threshold` | Exclude pixels whose per-image normalised confidence is below this value (0 = keep all). Used when the geometry has a confidence map (Small/Base models). (default: 0.1) | FLOAT | Yes | 0.0 to 1.0 |
| `use_sky_mask` | Exclude sky-probability pixels (sky >= 0.5). Used when the geometry has a sky map (Mono/Metric models). (default: True) | BOOLEAN | Yes | True or False |
| `downsample` | Take every Nth pixel (1 = full resolution). Higher values give fewer points and faster processing. (default: 1) | INT | Yes | 1 to 16 |

**Notes:**

* `batch_index` must be smaller than the batch size of the input geometry; otherwise the node raises an error.
* If filtering removes all pixels, the node raises an error. Lowering `confidence_threshold` or disabling `use_sky_mask` can prevent this.
* `confidence_threshold` is only applied when the geometry includes a confidence map (Small/Base models).
* `use_sky_mask` is only applied when the geometry includes a sky map (Mono/Metric models).
* When `downsample` is greater than 1, the camera intrinsics are scaled accordingly so the projected points remain correct.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `point_cloud` | A point cloud containing filtered 3D points, optional colors, and optional confidence values | DA3\_POINT\_CLOUD |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DA3GeometryToPointCloud/en.md)

***

**Source fingerprint (SHA-256):** `3cf5bdbb8afdfcfc02f9832a8cbc5a3df49da755dea6df01792aa6ef9e5d7287`


# DA3Inference - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DA3Inference

This node runs the Depth Anything 3 model on an image to estimate depth and geometry information.

This node runs the Depth Anything 3 model on an image to estimate depth and geometry information. In multi-view mode, multiple images are processed together as separate views of the same scene to produce geometrically consistent depth maps and camera poses.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `da3_model` | The Depth Anything 3 model to use for inference | DA3\_MODEL | Yes | - |
| `image` | Input image or images to process | IMAGE | Yes | - |
| `resolution` | Resolution the model runs at (longest side, multiple of 14). Lower values are faster and use less VRAM. Higher values produce more detail. The output is upsampled back to the original size (default: 504) | INT | Yes | 140 to 2520 (step: 14) |
| `resize_method` | upper\_bound\_resize: scale so the longest side equals the resolution (caps memory, default). lower\_bound\_resize: scale so the shortest side equals the resolution (preserves more detail on tall/wide images, uses more memory) | COMBO | Yes | `"upper_bound_resize"`<br />`"lower_bound_resize"` |
| `mode` | mono: single view image processing (works with any model variant). multiview: all images processed together for geometric consistency and camera pose estimation (for Small and Base models only) | COMBO | Yes | `"mono"`<br />`"multiview"` |
| `ref_view_strategy` | Which view acts as the geometric anchor in multi-view mode. saddle\_balanced: the view most average across all others (best general choice). saddle\_sim\_range: the view most visually distinct from the others. first / middle: fixed positional picks (default: saddle\_balanced) | COMBO | No (conditional) | `"saddle_balanced"`<br />`"saddle_sim_range"`<br />`"first"`<br />`"middle"` |
| `pose_method` | How the camera field-of-view is estimated (for Small and Base models only). cam\_dec: learned from image features. ray\_pose: derived geometrically from the model's 3D ray output. Affects perspective correctness of the 3D output (default: cam\_dec) | COMBO | No (conditional) | `"cam_dec"`<br />`"ray_pose"` |

**Notes on parameter constraints:**

* The `ref_view_strategy` and `pose_method` parameters are only available when `mode` is set to `"multiview"`.
* Multi-view mode requires a Small or Base model variant. Models with other head types (such as Metric or Mono) do not support cross-view attention or camera pose estimation.
* When `pose_method` is set to `"cam_dec"`, the model must have a camera decoder. If set to `"ray_pose"`, the model must have a DualDPT head.
* If the selected `pose_method` is not compatible with the loaded model, an error will be raised.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `da3_geometry` | Dictionary of non-normalized tensors. Always contains the keys: depth, image, mode. Optional keys include: sky (for Mono/Metric models), confidence (for Small/Base models), extrinsics and intrinsics (for multi-view mode) | DA3\_GEOMETRY |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DA3Inference/en.md)

***

**Source fingerprint (SHA-256):** `e91dd47e6a01719cdd6b6ce8a9bcc45933cac72c5e147ac42906d2f83ab7c250`


# DA3Render - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DA3Render

This node renders a visualization from Depth Anything 3 geometry data.

This node renders a visualization from Depth Anything 3 geometry data. It can output depth maps, confidence maps, or sky masks depending on the selected output mode.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `da3_geometry` | The Depth Anything 3 geometry data packet containing depth, and optionally sky and confidence tensors | DA3\_GEOMETRY | Yes | - |
| `output` | The type of visualization to render.<br />- depth: normalised greyscale depth image.<br />- depth\_colored: depth mapped through the Turbo colormap.<br />- sky\_mask: sky probability in \[0, 1] (for Mono/Metric models only).<br />- confidence: normalised depth confidence (for Small/Base models only). | COMBO | Yes | "depth"<br />"depth\_colored"<br />"sky\_mask"<br />"confidence" |

### Sub-parameters for `output` options

When `output` is set to `"depth"` or `"depth_colored"`:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `normalization` | Depth normalization method.<br />- v2\_style: mean/std normalisation for perceptually balanced results (default).<br />- min\_max: stretches the full depth range to \[0, 1] for maximum contrast.<br />- raw: no scaling, preserves metric units for Metric model. | COMBO | Yes | "v2\_style"<br />"min\_max"<br />"raw" |
| `apply_sky_clip` | Clip sky-region depth to the 99th percentile of foreground depth before normalisation. Requires a sky key in the da3\_geometry input (for Mono/Metric models only). Default: False | BOOLEAN | Yes | True<br />False |

When `output` is set to `"sky_mask"`:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `colored` | Apply the Turbo colormap to the sky mask. Default: False | BOOLEAN | Yes | True<br />False |

When `output` is set to `"confidence"`:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `colored` | Apply the Turbo colormap to the confidence map. Default: False | BOOLEAN | Yes | True<br />False |

### Parameter Constraints

* When `apply_sky_clip` is set to True, the `da3_geometry` input must contain a sky tensor. This is only available when using Mono or Metric models. If the sky tensor is missing, the node will raise an error.
* The `sky_mask` output option requires a sky tensor in the `da3_geometry` input. This is only available with Mono or Metric models.
* The `confidence` output option requires a confidence tensor in the `da3_geometry` input. This is only available with Small or Base models.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The rendered visualization as an image tensor. For depth outputs, returns a greyscale or colored depth map. For sky\_mask and confidence, returns either a greyscale or colored visualization depending on the colored parameter. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DA3Render/en.md)

***

**Source fingerprint (SHA-256):** `54d4cde95a916cac26c8a2e19c5623e794d46c0d7652f1c8204f9f2a0deabe0c`


# EmptyImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyImage

Documentation for EmptyImage node.

## Function Description

The EmptyImage node is used to create blank images with specified dimensions and colors. It can generate solid-color background images, commonly used as starting points or background images for image processing workflows.

## Working Principle

Just like a painter preparing a blank canvas before starting to create, the EmptyImage node provides you with a "digital canvas". You can specify the canvas size (width and height), choose the base color of the canvas, and even prepare multiple canvases of the same specifications at once. This node is like an intelligent art supply store that can create standardized canvases that perfectly meet your size and color requirements.

## Inputs

| Parameter Name | Description | Data Type |
| - | - | - |
| `width` | Sets the width of the generated image (in pixels), determining the horizontal dimensions of the canvas | INT |
| `height` | Sets the height of the generated image (in pixels), determining the vertical dimensions of the canvas | INT |
| `batch_size` | The number of images to generate at once, used for batch creation of images with the same specifications | INT |
| `color` | The background color of the image. You can input hexadecimal color settings, which will be automatically converted to decimal | INT |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated blank image tensor, formatted as \[batch\_size, height, width, 3], containing RGB three color channels | IMAGE |

## Common Color Reference Values

Since the current color input for this node is not user-friendly, with all color values being converted to decimal, here are some common color values that can be used directly for quick application.

| Color Name | Hexadecimal Value |
| - | - |
| Black | 0x000000 |
| White | 0xFFFFFF |
| Red | 0xFF0000 |
| Green | 0x00FF00 |
| Blue | 0x0000FF |
| Yellow | 0xFFFF00 |
| Cyan | 0x00FFFF |
| Magenta | 0xFF00FF |
| Orange | 0xFF8000 |
| Purple | 0x8000FF |
| Pink | 0xFF80C0 |
| Brown | 0x8B4513 |
| Dark Gray | 0x404040 |
| Light Gray | 0xC0C0C0 |
| Navy Blue | 0x000080 |
| Dark Green | 0x008000 |
| Dark Red | 0x800000 |
| Gold | 0xFFD700 |
| Silver | 0xC0C0C0 |
| Beige | 0xF5F5DC |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyImage/en.md)


# FeatherMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FeatherMask

The FeatherMask node applies a feathering effect to the edges of a given mask, smoothly transitioning the mask's edges by adjusting their opacity based on specified distances from 

The `FeatherMask` node applies a feathering effect to the edges of a given mask, smoothly transitioning the mask's edges by adjusting their opacity based on specified distances from each edge. This creates a softer, more blended edge effect.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The mask to which the feathering effect will be applied. It determines the area of the image that will be affected by the feathering. | MASK |
| `left` | Specifies the distance from the left edge within which the feathering effect will be applied. | INT |
| `top` | Specifies the distance from the top edge within which the feathering effect will be applied. | INT |
| `right` | Specifies the distance from the right edge within which the feathering effect will be applied. | INT |
| `bottom` | Specifies the distance from the bottom edge within which the feathering effect will be applied. | INT |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The output is a modified version of the input mask with a feathering effect applied to its edges. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FeatherMask/en.md)


# GLSLShader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GLSLShader

The GLSL Shader node lets you write custom fragment shaders in GLSL ES 3.00 (WebGL 2.0 compatible) to process images directly on the GPU.

The **GLSL Shader** node lets you write custom fragment shaders in **GLSL ES 3.00** (WebGL 2.0 compatible) to process images directly on the GPU. You can create image effects like blurs, color grading, film grain, glow, and much more - all running at GPU speed.

<Note>
  The GLSL Shader node is currently marked as **experimental**, so the node may be updated and extended in future releases.
</Note>

## Minimal Shader

The simplest possible shader - a passthrough that outputs the input image unchanged:

```glsl theme={null}
#version 300 es
precision highp float;

uniform sampler2D u_image0;

in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;

void main() {
    fragColor0 = texture(u_image0, v_texCoord);
}
```

<Note>
  **Why GLSL ES 3.00?** Shaders need to run in two environments: the **browser** (via WebGL 2.0, which only supports GLSL ES 3.00) for live preview in the ComfyUI frontend, and the **Python backend** (via desktop OpenGL) when the workflow executes. GLSL ES 3.00 is the common denominator that works in both places.
</Note>

## Available Uniforms

These uniforms are automatically set by ComfyUI. You don't need to declare all of them - only declare the ones you use.

### Images

| Uniform | Description | Type |
| - | - | - |
| `u_image0` – `u_image4` | Input images (up to 5). Sampled with `texture(u_image0, v_texCoord)`. Images are RGBA float textures with linear filtering and clamp-to-edge wrapping. | `sampler2D` |

### Floats

| Uniform | Description | Type |
| - | - | - |
| `u_float0` – `u_float19` | Up to 20 user-controlled float values. Mapped from the **floats** input group on the node. | `float` |

### Integers

| Uniform | Description | Type |
| - | - | - |
| `u_int0` – `u_int19` | Up to 20 user-controlled integer values. Mapped from the **ints** input group on the node. | `int` |

<Note>
  **Using int uniforms as dropdowns:** Int uniforms pair well with the **Custom Combo** node's index output - users pick an option from a dropdown and the shader receives the selected item's index.

  ```glsl theme={null}
  const int BLEND_SCREEN  = 0;
  const int BLEND_OVERLAY = 1;
  const int BLEND_MULTIPLY = 2;

  // ...

  if (u_int0 == BLEND_SCREEN) {
      // ...
  }
  ```
</Note>

### Booleans

| Uniform | Description | Type |
| - | - | - |
| `u_bool0` – `u_bool9` | Up to 10 user-controlled boolean values. Mapped from the **bools** input group on the node. | `bool` |

### Curves (1D LUTs)

| Uniform | Description | Type |
| - | - | - |
| `u_curve0` – `u_curve3` | Up to 4 user-editable curve LUTs from the **curves** input group. Each curve is a 1D lookup table stored as a single-row texture. | `sampler2D` |

<Note>
  **Using curve uniforms:** Curves let users draw arbitrary tone-mapping graphs in the UI (e.g. for contrast, gamma, per-channel grading, or any custom `input → output` remap). Sample the curve using your input value as the X coordinate - remember to clamp it to `[0, 1]` first:

  ```glsl theme={null}
  float applyCurve(sampler2D curve, float value) {
      return texture(curve, vec2(clamp(value, 0.0, 1.0), 0.5)).r;
  }

  // Usage: remap each RGB channel through a master curve
  color.r = applyCurve(u_curve0, color.r);
  color.g = applyCurve(u_curve0, color.g);
  color.b = applyCurve(u_curve0, color.b);
  ```

  Common uses: master RGB curves, per-channel R/G/B curves, luminance-driven remaps, custom gamma, and any effect where you want the user to shape a response curve visually.
</Note>

### Resolution

| Uniform | Description | Type |
| - | - | - |
| `u_resolution` | **Output** framebuffer dimensions in pixels (`width, height`). This is the size you're writing to, which may differ from any input image's size when `size_mode` is `"custom"`. | `vec2` |

<Note>
  **Computing texel size for sampling:** Don't use `1.0 / u_resolution` to step one pixel in an input texture. `u_resolution` is the *output* size, which may not match the input's size. Instead use `textureSize()` on the actual texture you're sampling:

  ```glsl theme={null}
  vec2 texel = 1.0 / vec2(textureSize(u_image0, 0));
  ```

  Use `u_resolution` only when you need the output framebuffer dimensions themselves (e.g. computing `gl_FragCoord.xy / u_resolution` to get screen-space UVs).
</Note>

### Multi-Pass

| Uniform | Description | Type |
| - | - | - |
| `u_pass` | Current pass index (0-based). Only meaningful when using `#pragma passes` - see [Multi-Pass Ping-Pong Rendering](#multi-pass-ping-pong-rendering) for details. | `int` |

### Vertex Shader Output

| Varying | Description | Type |
| - | - | - |
| `v_texCoord` | Texture coordinates ranging from (0,0) at bottom-left to (1,1) at top-right. | `vec2` |

## Multiple Outputs (MRT)

The node supports up to **4 simultaneous outputs** using Multiple Render Targets. Declare additional outputs with explicit locations:

```glsl theme={null}
#version 300 es
precision highp float;

uniform sampler2D u_image0;

in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;
layout(location = 1) out vec4 fragColor1;
layout(location = 2) out vec4 fragColor2;
layout(location = 3) out vec4 fragColor3;

void main() {
    vec4 color = texture(u_image0, v_texCoord);
    fragColor0 = vec4(vec3(color.r), 1.0);  // Red channel
    fragColor1 = vec4(vec3(color.g), 1.0);  // Green channel
    fragColor2 = vec4(vec3(color.b), 1.0);  // Blue channel
    fragColor3 = vec4(vec3(color.a), 1.0);  // Alpha channel
}
```

Each `fragColor` maps to the corresponding `IMAGE` output on the node. ComfyUI auto-detects which outputs you use - unused outputs will be black.

## Multi-Pass Ping-Pong Rendering

Some effects (like separable blur) need multiple passes over the image. Use the `#pragma passes N` directive to enable this:

```glsl theme={null}
#version 300 es
#pragma passes 2
precision highp float;

uniform sampler2D u_image0;
uniform float u_float0;  // Blur radius
uniform int u_pass;

in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;

void main() {
    vec2 texel = 1.0 / vec2(textureSize(u_image0, 0));
    int radius = int(ceil(u_float0));

    // Pass 0 = horizontal blur, Pass 1 = vertical blur
    vec2 dir = (u_pass == 0) ? vec2(1.0, 0.0) : vec2(0.0, 1.0);

    vec4 color = vec4(0.0);
    float total = 0.0;

    for (int i = -radius; i <= radius; i++) {
        vec2 offset = dir * float(i) * texel;
        float w = 1.0;  // box blur weight
        color += texture(u_image0, v_texCoord + offset) * w;
        total += w;
    }

    fragColor0 = color / total;
}
```

### How ping-pong works

1. **Pass 0**: Reads from the original `u_image0` input, writes to an internal ping-pong texture.
2. **Pass 1–N**: Reads from the *previous pass output* via `u_image0` (the binding is swapped automatically), writes to the other ping-pong texture.
3. **Final pass**: Writes to the actual output framebuffer (`fragColor0`).

<Note>
  When using multi-pass with MRT (multiple outputs), only the first output (`fragColor0`) participates in ping-pong. The final pass writes all outputs.
</Note>

## Examples

### Grayscale Conversion

```glsl theme={null}
#version 300 es
precision highp float;

uniform sampler2D u_image0;
in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;

void main() {
    vec4 color = texture(u_image0, v_texCoord);
    float gray = dot(color.rgb, vec3(0.2126, 0.7152, 0.0722));
    fragColor0 = vec4(vec3(gray), color.a);
}
```

### Image Blending

Blend two input images using a float parameter as the mix factor:

```glsl theme={null}
#version 300 es
precision highp float;

uniform sampler2D u_image0;
uniform sampler2D u_image1;
uniform float u_float0;  // mix factor [0.0 – 1.0]

in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;

void main() {
    vec4 a = texture(u_image0, v_texCoord);
    vec4 b = texture(u_image1, v_texCoord);
    fragColor0 = mix(a, b, clamp(u_float0, 0.0, 1.0));
}
```

## Using an LLM to Generate Shaders

You can use any LLM (Claude, ChatGPT, etc.) to write GLSL shaders for you. Copy the following prompt and fill in your desired effect:

````markdown theme={null}
Write a GLSL ES 3.00 fragment shader for ComfyUI's GLSLShader node.

**Effect I want:** [DESCRIBE YOUR DESIRED EFFECT HERE]

**Requirements:**
- Must start with `#version 300 es`
- Use `precision highp float;`
- The vertex shader provides `in vec2 v_texCoord` (0–1 UV coordinates, bottom-left origin)
- Output to `layout(location = 0) out vec4 fragColor0` (RGBA)
- Additional outputs available: `fragColor1`, `fragColor2`, `fragColor3` at locations 1–3

**Template to follow (minimal passthrough shader - use this exact structure):**

```glsl
#version 300 es
precision highp float;

uniform sampler2D u_image0;

in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;

void main() &#123;
    fragColor0 = texture(u_image0, v_texCoord);
&#125;
```

**Available uniforms (declare only what you use):**
- `uniform sampler2D u_image0;` through `u_image4` - up to 5 input images (RGBA float, linear filtering, clamp-to-edge)
- `uniform vec2 u_resolution;` - **output framebuffer** width and height in pixels. This is NOT the input texture size (they can differ when the user sets a custom output size). **To step one pixel in an input texture, use `vec2 texel = 1.0 / vec2(textureSize(u_image0, 0));` - do NOT use `1.0 / u_resolution` for this.**
- `uniform float u_float0;` through `u_float19;` - up to 20 user-controlled float parameters
- `uniform int u_int0;` through `u_int19;` - up to 20 user-controlled integer parameters. Tip: int uniforms can be wired from a **Custom Combo** node's index output, so users select from a dropdown and the shader receives the index. Use this for mode selection (e.g. blend mode, blur type). Define named constants for each option and branch on those - do NOT compare against raw integer literals. For example: `const int BLUR_GAUSSIAN = 0; const int BLUR_BOX = 1; ... if (u_int0 == BLUR_GAUSSIAN) { ... }`.
- `uniform bool u_bool0;` through `u_bool9;` - up to 10 user-controlled boolean parameters (use for feature toggles)
- `uniform sampler2D u_curve0;` through `u_curve3;` - up to 4 user-editable 1D LUT curves. Sample with `texture(u_curve0, vec2(clamp(x, 0.0, 1.0), 0.5)).r` where `x` is 0–1. Use for tone curves, remapping, etc.
- `uniform int u_pass;` - current pass index (when using multi-pass)

**Multi-pass rendering:**
- Add `#pragma passes N` on the second line to enable N passes
- On pass 0, `u_image0` is the original input; on subsequent passes it contains the previous pass output
- Use `u_pass` to vary behavior per pass (e.g., horizontal vs. vertical blur)

**Important constraints:**
- GLSL ES 3.00 only - no GLSL 1.x `varying`/`attribute`, no `gl_FragColor`
- No `#include`, no external textures, no custom vertex shader
- Document each uniform with a comment showing its purpose and expected range
````

### Example prompt fill-in

> **Effect I want:** A chromatic aberration effect that splits RGB channels outward from the center of the image. u\_float0 controls the strength of the offset (0 = no effect, 10 = extremely strong). The offset should scale with distance from the center.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GLSLShader/en.md)

***

**Source fingerprint (SHA-256):** `ded589d5b0cb5413ecc42c7177e3076427ceac1d3218a20cfec6f2e005fe7e27`


# GetImageSize - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GetImageSize

GetImageSize reads an input image and returns its width, height, and batch size.

GetImageSize reads an input image and returns its width, height, and batch size. The node also displays these measured values directly on the node interface.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image from which the width, height, and batch size are extracted | IMAGE | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `width` | The width of the input image in pixels | INT |
| `height` | The height of the input image in pixels | INT |
| `batch_size` | The number of images contained in the input batch | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GetImageSize/en.md)

***

**Source fingerprint (SHA-256):** `dc29add37a3362384e63cb1e57f03758a82f77811c78797fdffd486462cb19b8`


# GrowMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrowMask

The GrowMask node is designed to modify the size of a given mask, either expanding or contracting it, while optionally applying a tapered effect to the corners.

The `GrowMask` node is designed to modify the size of a given mask, either expanding or contracting it, while optionally applying a tapered effect to the corners. This functionality is crucial for dynamically adjusting mask boundaries in image processing tasks, allowing for more flexible and precise control over the area of interest.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The input mask to be modified. This parameter is central to the node's operation, serving as the base upon which the mask is either expanded or contracted. | MASK |
| `expand` | Determines the magnitude and direction of the mask modification. Positive values cause the mask to expand, while negative values lead to contraction. This parameter directly influences the final size of the mask. | INT |
| `tapered_corners` | A boolean flag that, when set to True, applies a tapered effect to the corners of the mask during modification. This option allows for smoother transitions and visually appealing results. | BOOLEAN |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The modified mask after applying the specified expansion/contraction and optional tapered corners effect. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrowMask/en.md)


# ImageAddNoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageAddNoise

The ImageAddNoise node adds random noise to an input image.

The ImageAddNoise node adds random noise to an input image. It uses a specified random seed to generate consistent noise patterns and allows controlling the intensity of the noise effect. The resulting image maintains the same dimensions as the input but with added visual texture.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to which noise will be added | IMAGE | Yes | - |
| `seed` | The random seed used for creating the noise (default: 0). This parameter supports "control after generate" functionality. | INT | Yes | 0 to 18446744073709551615 |
| `strength` | Controls the intensity of the noise effect (default: 0.5, step: 0.01) | FLOAT | Yes | 0.0 to 1.0 |

**Note:** Noise values are added to the image and the result is clipped to the 0.0–1.0 range. If the input image has an alpha channel (4 channels), the original alpha channel is preserved unchanged — noise is only applied to the color channels.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The output image with added noise applied | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageAddNoise/en.md)

***

**Source fingerprint (SHA-256):** `e6b9815e7c075c7ee97c924c22a92dfef6d9c65b97b6e65b0f9e1c96628f39f2`


# ImageBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageBatch

The ImageBatch node is designed for combining two images into a single batch.

The `ImageBatch` node is designed for combining two images into a single batch. If the dimensions of the images do not match, it automatically rescales the second image to match the first one's dimensions before combining them.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image1` | The first image to be combined into the batch. It serves as the reference for the dimensions to which the second image will be adjusted if necessary. | `IMAGE` |
| `image2` | The second image to be combined into the batch. It is automatically rescaled to match the dimensions of the first image if they differ. | `IMAGE` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The combined batch of images, with the second image rescaled to match the first one's dimensions if needed. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageBatch/en.md)


# ImageBlend - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageBlend

The ImageBlend node is designed to blend two images together based on a specified blending mode and blend factor.

The `ImageBlend` node is designed to blend two images together based on a specified blending mode and blend factor. It supports various blending modes such as normal, multiply, screen, overlay, soft light, and difference, allowing for versatile image manipulation and compositing techniques. This node is essential for creating composite images by adjusting the visual interaction between two image layers.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `image1` | The first image to be blended. It serves as the base layer for the blending operation. | `IMAGE` |
| `image2` | The second image to be blended. Depending on the blend mode, it modifies the appearance of the first image. | `IMAGE` |
| `blend_factor` | Determines the weight of the second image in the blend. A higher blend factor gives more prominence to the second image in the resulting blend. | `FLOAT` |
| `blend_mode` | Specifies the method of blending the two images. Supports modes like normal, multiply, screen, overlay, soft light, and difference, each producing a unique visual effect. | COMBO\[STRING] |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The resulting image after blending the two input images according to the specified blend mode and factor. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageBlend/en.md)


# ImageBlur - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageBlur

The ImageBlur node applies a Gaussian blur to an image, allowing for the softening of edges and reduction of detail and noise.

The `ImageBlur` node applies a Gaussian blur to an image, allowing for the softening of edges and reduction of detail and noise. It provides control over the intensity and spread of the blur through parameters.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The input image to be blurred. This is the primary target for the blur effect. | `IMAGE` |
| `blur_radius` | Determines the radius of the blur effect. A larger radius results in a more pronounced blur. | `INT` |
| `sigma` | Controls the spread of the blur. A higher sigma value means the blur will affect a wider area around each pixel. | `FLOAT` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The output is the blurred version of the input image, with the degree of blur determined by the input parameters. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageBlur/en.md)


# ImageColorToMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageColorToMask

The ImageColorToMask node is designed to convert a specified color in an image to a mask.

The `ImageColorToMask` node is designed to convert a specified color in an image to a mask. It processes an image and a target color, generating a mask where the specified color is highlighted, facilitating operations like color-based segmentation or object isolation.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The 'image' parameter represents the input image to be processed. It is crucial for determining the areas of the image that match the specified color to be converted into a mask. | `IMAGE` |
| `color` | The 'color' parameter specifies the target color in the image to be converted into a mask. It plays a key role in identifying the specific color areas to be highlighted in the resulting mask. | `INT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The output is a mask highlighting the areas of the input image that match the specified color. This mask can be used for further image processing tasks, such as segmentation or object isolation. | `MASK` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageColorToMask/en.md)


# ImageCompare - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageCompare

Documentation for ImageCompare node.

## Overview

The Image Compare node provides a visual interface to compare two images side-by-side using a draggable slider. It is designed as an output node, meaning it does not pass data to other nodes but instead displays the images directly in the user interface for inspection.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image_a` | The first image to compare. | IMAGE | No | - |
| `image_b` | The second image to compare. | IMAGE | No | - |
| `compare_view` | The control that enables the slider comparison view in the UI. | IMAGECOMPARE | Yes | - |

**Note:** This node is an output node. While `image_a` and `image_b` are optional, at least one image must be provided for the node to have a visible effect. The node will display an empty area for any image input that is not connected. Each provided image batch is saved to temporary storage under the prefixes `comfy.compare.a` and `comfy.compare.b` respectively, then shown in the slider view.

## Outputs

This node is an output node and does not produce any data outputs for use in other nodes. Its function is to display the provided images in the ComfyUI interface.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageCompare/en.md)

***

**Source fingerprint (SHA-256):** `bc065572c5631ed80c0590aabae775c51d0f607895a87cb2cca78037ab9a6638`


# ImageCompositor - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageCompositor

This node combines multiple image layers into a single composited image.

This node combines multiple image layers into a single composited image. It takes a layer stack built with the Add Layer node and optionally applies saved composition settings from the compositor editor, blending the layers according to their placement, size, rotation, opacity, and blend mode. A saved composition that matches the current inputs takes priority; otherwise the node composes from the layer properties and marks the saved state as stale.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `layers` | Layer stack to composite; build it with Add Layer. Items are stacked by z\_index, batch frames inside an item expand to consecutive layers, and item placement, opacity, and blend mode define the initial composition. Without an explicit document canvas the size is a best-effort maximum extent of the placed layers. A saved composition that matches the current inputs takes priority. | LAYERS | Yes | Maximum 50 layers |
| `compositor` | Layered composition saved by the compositor editor. | COMPOSITOR | No | None |

**Notes on constraints:**

* The layer stack supports a maximum of 50 expanded layers; providing more raises an error.
* Only raster layer items are currently supported; other item types raise an error.
* The `layers` document version must be 1; other versions raise an error.
* Saved `compositor` state is only replayed when its recorded input fingerprints match the current layer stack. If they do not match, the node falls back to composing from the layer properties and marks the saved state as stale.
* Layer opacity is clamped to the range 0.0 to 1.0.
* Layer horizontal and vertical placement (`x`, `y`) is clamped to the maximum resolution limit.
* Layer width and height fall back to the natural image size when set to zero or less, and are capped at the maximum resolution limit.
* The composited canvas size must not exceed the maximum resolution limit.
* When no layers are provided, a 64x64 placeholder image is returned.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | Composited image. Carries an alpha channel when the composite has transparent areas (e.g. hidden background), otherwise plain RGB. | IMAGE |
| `MASK` | Transparency of the composite (1 = fully transparent). All zeros when the composite is opaque. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageCompositor/en.md)

***

**Source fingerprint (SHA-256):** `76e5e57ade89f9ee172c5e1f0b82579d846d15bafb52b2052246f1f2ad7f0034`


# ImageCrop - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageCrop

The ImageCrop node is designed for cropping images to a specified width and height starting from a given x and y coordinate.

The `ImageCrop` node is designed for cropping images to a specified width and height starting from a given x and y coordinate. This functionality is essential for focusing on specific regions of an image or for adjusting the image size to meet certain requirements.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The input image to be cropped. This parameter is crucial as it defines the source image from which a region will be extracted based on the specified dimensions and coordinates. | `IMAGE` |
| `width` | Specifies the width of the cropped image. This parameter determines how wide the resulting cropped image will be. | `INT` |
| `height` | Specifies the height of the cropped image. This parameter determines the height of the resulting cropped image. | `INT` |
| `x` | The x-coordinate of the top-left corner of the cropping area. This parameter sets the starting point for the width dimension of the crop. | `INT` |
| `y` | The y-coordinate of the top-left corner of the cropping area. This parameter sets the starting point for the height dimension of the crop. | `INT` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The cropped image as a result of the cropping operation. This output is significant for further processing or analysis of the specified image region. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageCrop/en.md)


# ImageCropToMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageCropToMask

Crops an image to the bounding box of its mask, producing a centered subject over a solid background color.

Crops an image to the bounding box of its mask, producing a centered subject over a solid background color. The node composites the masked image over the chosen background and resizes the result to the specified output dimensions, making it suitable for 3D pipelines that expect a centered, background-free subject at a fixed resolution.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The input image or batch of images to crop. | IMAGE | Yes | — |
| `masks` | The mask or batch of masks that defines the subject area. A single mask is applied to all images; otherwise the mask batch size must match the image batch size. If the mask resolution differs from the image resolution, the mask is automatically resized to match. | MASK | Yes | — |
| `width` | Output width in pixels. (default: 1024) | INT | Yes | 64 to 4096 (step 8) |
| `height` | Output height in pixels. (default: 1024) | INT | Yes | 64 to 4096 (step 8) |
| `pad_factor` | Extra margin around the mask bounding box as a multiplier. (default: 1.0) | FLOAT | Yes | 1.0 to 2.0 (step 0.01) |
| `grow_mask` | Grow or shrink the mask by this many pixels before cropping. Positive values expand the mask, negative values shrink it. (default: 0) | INT | Yes | -32 to 32 (step 1) |
| `background` | Background color behind the masked subject. (default: #000000) | COLOR | Yes | — |

Note: The crop region is centered on the mask's bounding box and its aspect ratio matches `width` / `height`. The node automatically detects and corrects an inverted mask (foreground pixels along the border, background in the center). If the mask contains no foreground pixels, the node tries the inverted mask; if that is also empty, it logs a warning and crops the entire image. An error is raised when the mask batch size does not match the image batch size and is not a single mask.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The cropped composite images (masked subject over the chosen background color), resized to `width` x `height`. The batch size matches the input image batch. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageCropToMask/en.md)

***

**Source fingerprint (SHA-256):** `fcc14b5db7318699526dd544d404f78f9d1ab362b73769276f113f2b1062b214`


# ImageCropV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageCropV2

The Crop Image node extracts a rectangular section from an input image.

The Crop Image node extracts a rectangular section from an input image. You define the region to keep by specifying its top-left corner coordinates and its width and height. The node then returns the cropped portion of the original image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be cropped. | IMAGE | Yes | N/A |
| `crop_region` | Defines the rectangular area to extract from the image. It is specified by `x` (horizontal start), `y` (vertical start), `width`, and `height`. If the defined region extends beyond the image's borders, it will be automatically adjusted to fit within the image dimensions. | BOUNDINGBOX | Yes | N/A |

**Note on Region Constraints:** The crop region is automatically constrained to stay within the bounds of the input image. If the specified `x` or `y` coordinate is greater than the image's width or height, it will be set to the maximum valid position. The resulting crop width and height will be adjusted so the region does not exceed the image's edges.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The cropped section of the original input image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageCropV2/en.md)

***

**Source fingerprint (SHA-256):** `c09c68a46c4b0418903a627b98dd848264d53b58bd3ffe99e40ef125b15b3aae`


# ImageFlip - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageFlip

The ImageFlip node flips images along different axes.

The ImageFlip node flips images along different axes. It can flip images vertically along the x-axis or horizontally along the y-axis. The node uses torch.flip operations to perform the flipping based on the selected method.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be flipped | IMAGE | Yes | - |
| `flip_method` | The flipping direction to apply (default: "x-axis: vertically") | STRING | Yes | "x-axis: vertically"<br />"y-axis: horizontally" |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The flipped output image | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageFlip/en.md)

***

**Source fingerprint (SHA-256):** `481cd167d57746f242fcc4b5f2e3bb0bff0184b5870626d5f24a34422464ddd6`


# ImageInvert - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageInvert

The ImageInvert node is designed to invert the colors of an image, effectively transforming each pixel's color value to its complementary color on the color wheel.

The `ImageInvert` node is designed to invert the colors of an image, effectively transforming each pixel's color value to its complementary color on the color wheel. This operation is useful for creating negative images or for visual effects that require color inversion.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The 'image' parameter represents the input image to be inverted. It is crucial for specifying the target image whose colors are to be inverted, affecting the node's execution and the visual outcome of the inversion process. | `IMAGE` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The output is an inverted version of the input image, with each pixel's color value transformed to its complementary color. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageInvert/en.md)


# ImagePadForOutpaint - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImagePadForOutpaint

This node is designed for preparing images for the outpainting process by adding padding around them.

This node is designed for preparing images for the outpainting process by adding padding around them. It adjusts the image dimensions to ensure compatibility with outpainting algorithms, facilitating the generation of extended image areas beyond the original boundaries.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The 'image' input is the primary image to be prepared for outpainting, serving as the base for padding operations. | `IMAGE` |
| `left` | Specifies the amount of padding to add to the left side of the image, influencing the expanded area for outpainting. | `INT` |
| `top` | Determines the amount of padding to add to the top of the image, affecting the vertical expansion for outpainting. | `INT` |
| `right` | Defines the amount of padding to add to the right side of the image, impacting the horizontal expansion for outpainting. | `INT` |
| `bottom` | Indicates the amount of padding to add to the bottom of the image, contributing to the vertical expansion for outpainting. | `INT` |
| `feathering` | Controls the smoothness of the transition between the original image and the added padding, enhancing the visual integration for outpainting. | `INT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The output 'image' represents the padded image, ready for the outpainting process. | `IMAGE` |
| `mask` | The output 'mask' indicates the areas of the original image and the added padding, useful for guiding the outpainting algorithms. | `MASK` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImagePadForOutpaint/en.md)


# ImageQuantize - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageQuantize

The ImageQuantize node is designed to reduce the number of colors in an image to a specified number, optionally applying dithering techniques to maintain visual quality.

The ImageQuantize node is designed to reduce the number of colors in an image to a specified number, optionally applying dithering techniques to maintain visual quality. This process is useful for creating palette-based images or reducing the color complexity for certain applications.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The input image tensor to be quantized. It affects the node's execution by being the primary data upon which color reduction is performed. | `IMAGE` |
| `colors` | Specifies the number of colors to reduce the image to. It directly influences the quantization process by determining the color palette size. | `INT` |
| `dither` | Determines the dithering technique to be applied during quantization, affecting the visual quality and appearance of the output image. | COMBO\[STRING] |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The quantized version of the input image, with reduced color complexity and optionally dithered to maintain visual quality. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageQuantize/en.md)


# ImageRotate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageRotate

The ImageRotate node rotates an input image by specified angles.

The ImageRotate node rotates an input image by specified angles. It supports four rotation options: no rotation, 90 degrees clockwise, 180 degrees, and 270 degrees clockwise. The rotation is performed using efficient tensor operations that maintain the image data integrity.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be rotated | IMAGE | Yes | - |
| `rotation` | The rotation angle to apply to the image (default: "none") | STRING | Yes | "none"<br />"90 degrees"<br />"180 degrees"<br />"270 degrees" |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The rotated output image | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageRotate/en.md)

***

**Source fingerprint (SHA-256):** `1de36d9e42e64fe80cc13dd7da96bd946f02ba78d81317f073cf54c4e5bd12f7`


# ImageScale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageScale

The ImageScale node is designed for resizing images to specific dimensions, offering a selection of upscale methods and the ability to crop the resized image.

The ImageScale node is designed for resizing images to specific dimensions, offering a selection of upscale methods and the ability to crop the resized image. It abstracts the complexity of image upscaling and cropping, providing a straightforward interface for modifying image dimensions according to user-defined parameters.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The input image to be upscaled. This parameter is central to the node's operation, serving as the primary data upon which resizing transformations are applied. The quality and dimensions of the output image are directly influenced by the original image's properties. | `IMAGE` |
| `upscale_method` | Specifies the method used for upscaling the image. The choice of method can affect the quality and characteristics of the upscaled image, influencing the visual fidelity and potential artifacts in the resized output. | COMBO\[STRING] |
| `width` | The target width for the upscaled image. This parameter directly influences the dimensions of the output image, determining the horizontal scale of the resizing operation. | `INT` |
| `height` | The target height for the upscaled image. This parameter directly influences the dimensions of the output image, determining the vertical scale of the resizing operation. | `INT` |
| `crop` | Determines whether and how the upscaled image should be cropped, offering options for disabled cropping or center cropping. This affects the final composition of the image by potentially removing edges to fit the specified dimensions. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The upscaled (and optionally cropped) image, ready for further processing or visualization. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageScale/en.md)


# ImageScaleBy - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageScaleBy

The ImageScaleBy node is designed for upscaling images by a specified scale factor using various interpolation methods.

The ImageScaleBy node is designed for upscaling images by a specified scale factor using various interpolation methods. It allows for the adjustment of the image size in a flexible manner, catering to different upscaling needs.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The input image to be upscaled. This parameter is crucial as it provides the base image that will undergo the upscaling process. | `IMAGE` |
| `upscale_method` | Specifies the interpolation method to be used for upscaling. The choice of method can affect the quality and characteristics of the upscaled image. | COMBO\[STRING] |
| `scale_by` | The factor by which the image will be upscaled. This determines the increase in size of the output image relative to the input image. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The upscaled image, which is larger than the input image according to the specified scale factor and interpolation method. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageScaleBy/en.md)


# ImageScaleToMaxDimension - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageScaleToMaxDimension

The ImageScaleToMaxDimension node resizes images to fit within a specified maximum dimension while maintaining the original aspect ratio.

The ImageScaleToMaxDimension node resizes images to fit within a specified maximum dimension while maintaining the original aspect ratio. It calculates whether the image is portrait or landscape oriented, then scales the larger dimension to match the target size while proportionally adjusting the smaller dimension. The node supports multiple upscaling methods for different quality and performance requirements.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be scaled | IMAGE | Yes | - |
| `upscale_method` | The interpolation method used for scaling the image (default: "area") | STRING | Yes | "area"<br />"lanczos"<br />"bilinear"<br />"nearest-exact"<br />"bilinear"<br />"bicubic" |
| `largest_size` | The maximum dimension for the scaled image (default: 512) | INT | Yes | 0 to 16384 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The scaled image with the largest dimension matching the specified size | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageScaleToMaxDimension/en.md)

***

**Source fingerprint (SHA-256):** `83eba56d9f673fb570edc6504fd82f1274ead1d3e055a1a8bcc207c178388015`


# ImageScaleToTotalPixels - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageScaleToTotalPixels

The ImageScaleToTotalPixels node is designed for resizing images to a specified total number of pixels while maintaining the aspect ratio.

The ImageScaleToTotalPixels node is designed for resizing images to a specified total number of pixels while maintaining the aspect ratio. It provides various methods for upscaling the image to achieve the desired pixel count.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The input image to be upscaled to the specified total number of pixels. | `IMAGE` |
| `upscale_method` | The method used for upscaling the image. It affects the quality and characteristics of the upscaled image. | COMBO\[STRING] |
| `megapixels` | The target size of the image in megapixels. This determines the total number of pixels in the upscaled image. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The upscaled image with the specified total number of pixels, maintaining the original aspect ratio. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageScaleToTotalPixels/en.md)


# ImageSharpen - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageSharpen

The ImageSharpen node enhances the clarity of an image by accentuating its edges and details.

The ImageSharpen node enhances the clarity of an image by accentuating its edges and details. It applies a sharpening filter to the image, which can be adjusted in intensity and radius, thereby making the image appear more defined and crisp.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The input image to be sharpened. This parameter is crucial as it determines the base image on which the sharpening effect will be applied. | `IMAGE` |
| `sharpen_radius` | Defines the radius of the sharpening effect. A larger radius means that more pixels around the edge will be affected, leading to a more pronounced sharpening effect. | `INT` |
| `sigma` | Controls the spread of the sharpening effect. A higher sigma value results in a smoother transition at the edges, while a lower sigma makes the sharpening more localized. | `FLOAT` |
| `alpha` | Adjusts the intensity of the sharpening effect. Higher alpha values result in a stronger sharpening effect. | `FLOAT` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `image` | The sharpened image, with enhanced edges and details, ready for further processing or display. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageSharpen/en.md)


# ImageStitch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageStitch

This node allows you to stitch two images together in a specified direction (up, down, left, right), with support for size matching and spacing between images.

This node allows you to stitch two images together in a specified direction (up, down, left, right), with support for size matching and spacing between images.

## Inputs

| Parameter Name | Description | Data Type | Input Type | Default | Range |
| - | - | - | - | - | - |
| `image1` | The first image to be stitched | IMAGE | Required | - | - |
| `image2` | The second image to be stitched, if not provided returns only the first image | IMAGE | Optional | None | - |
| `direction` | The direction to stitch the second image: right, down, left, or up | STRING | Required | right | right/down/left/up |
| `match_image_size` | Whether to resize the second image to match the dimensions of the first image | BOOLEAN | Required | True | True/False |
| `spacing_width` | Width of spacing between images, must be an even number | INT | Required | 0 | 0-1024 |
| `spacing_color` | Color of the spacing between stitched images | STRING | Required | white | white/black/red/green/blue |

> For `spacing_color`, when using colors other than "white/black", if `match_image_size` is set to `false`, the padding area will be filled with black

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The stitched image | IMAGE |

## Workflow Example

In the workflow below, we use 3 input images of different sizes as examples:

* image1: 500x300
* image2: 400x250
* image3: 300x300

<img alt="workflow" />

**First Image Stitch Node**

* `match_image_size`: false, images will be stitched at their original sizes
* `direction`: up, `image2` will be placed above `image1`
* `spacing_width`: 20
* `spacing_color`: black

Output image 1:

<img alt="output1" />

**Second Image Stitch Node**

* `match_image_size`: true, the second image will be scaled to match the height or width of the first image
* `direction`: right, `image3` will appear on the right side
* `spacing_width`: 20
* `spacing_color`: white

Output image 2:

<img alt="output2" />

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageStitch/en.md)


# ImageToMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageToMask

The ImageToMask node is designed to convert an image into a mask based on a specified color channel.

The ImageToMask node is designed to convert an image into a mask based on a specified color channel. It allows for the extraction of mask layers corresponding to the red, green, blue, or alpha channels of an image, facilitating operations that require channel-specific masking or processing.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The 'image' parameter represents the input image from which a mask will be generated based on the specified color channel. It plays a crucial role in determining the content and characteristics of the resulting mask. | `IMAGE` |
| `channel` | The 'channel' parameter specifies which color channel (red, green, blue, or alpha) of the input image should be used to generate the mask. This choice directly influences the mask's appearance and which parts of the image are highlighted or masked out. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The output 'mask' is a binary or grayscale representation of the specified color channel from the input image, useful for further image processing or masking operations. | `MASK` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageToMask/en.md)


# ImageUpscaleWithModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageUpscaleWithModel

This node is designed for upscaling images using a specified upscale model.

This node is designed for upscaling images using a specified upscale model. It efficiently manages the upscaling process by adjusting the image to the appropriate device, optimizing memory usage, and applying the upscale model in a tiled manner to prevent potential out-of-memory errors.

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `upscale_model` | The upscale model to be used for upscaling the image. It is crucial for defining the upscaling algorithm and its parameters. | `UPSCALE_MODEL` |
| `image` | The image to be upscaled. This input is essential for determining the source content that will undergo the upscaling process. | `IMAGE` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The upscaled image, processed by the upscale model. This output is the result of the upscaling operation, showcasing the enhanced resolution or quality. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageUpscaleWithModel/en.md)


# InvertMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/InvertMask

The InvertMask node is designed to invert the values of a given mask, effectively flipping the masked and unmasked areas.

The InvertMask node is designed to invert the values of a given mask, effectively flipping the masked and unmasked areas. This operation is fundamental in image processing tasks where the focus of interest needs to be switched between the foreground and the background.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The 'mask' parameter represents the input mask to be inverted. It is crucial for determining the areas to be flipped in the inversion process. | MASK |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The output is an inverted version of the input mask, with previously masked areas becoming unmasked and vice versa. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/InvertMask/en.md)


# LayersFromBoundingBoxes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LayersFromBoundingBoxes

This node converts an image batch and its bounding boxes into a layer stack, creating one layer per frame and placing each layer according to its matching box.

This node converts an image batch and its bounding boxes into a layer stack, creating one layer per frame and placing each layer according to its matching box. Use it when a node outputs layers as a batch, because a batch carries only a single placement for every frame and the individual positions would otherwise be lost.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Image batch; each frame becomes one layer. | IMAGE | Yes | — |
| `bboxes` | Placement boxes, index-aligned with the image batch. Accepts bounding boxes (x, y, width, height), normalized elements (with a "bbox" — these need canvas\_width/canvas\_height to resolve to pixels), or a JSON string of either. Frames without a matching box are placed at the origin. A box's width/height scales the layer to fit it. metadata.name (or desc) and metadata.z\_index are used when present, and metadata.content\_rect (frame-relative) crops the frame to its real content. | BOUNDING\_BOX, ARRAY, or STRING | Yes | — |
| `mask` | Per-frame transparency, index-aligned with the image batch (1 = transparent, LoadImage convention). | MASK | No | — |
| `layers` | Layer stack to append to. Leave unconnected to start a new stack. | LAYERS | No | — |
| `crop_to_content` | Crop each frame to metadata.content\_rect where present and place the content at the box position plus the rect offset. Leave on for batches whose frames are padded — it keeps only the real content at its true spot. (default: true) | BOOLEAN | No | true<br />false |
| `canvas_width` | Document canvas width. 0 derives it from the placed layers. (default: 0) | INT | No | 0 to MAX\_RESOLUTION |
| `canvas_height` | Document canvas height. 0 derives it from the placed layers. (default: 0) | INT | No | 0 to MAX\_RESOLUTION |

Notes:

* `bboxes` and `mask` must be index-aligned with `image`: the nth box and the nth mask frame correspond to the nth image frame. Frames without a matching box are placed at the origin.
* When `bboxes` contains normalized elements (with a "bbox"), `canvas_width` and `canvas_height` must be provided so those normalized positions can be resolved to pixels.
* `canvas_width` and `canvas_height` must both be greater than 0 to set the document canvas explicitly. If either is 0, the canvas is derived from the placed layers or inherited from the connected `layers` stack.
* When `layers` is connected, new layers are appended to it and receive z-index values above the highest z-index already present in the stack.
* When `crop_to_content` is enabled and a frame has a metadata.content\_rect, the frame is cropped to that rect and the box's width/height scaling is not applied; instead, the rect's offset is added to the box position.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LAYERS` | The layer stack, ready for Create Layered Image. | LAYERS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LayersFromBoundingBoxes/en.md)

***

**Source fingerprint (SHA-256):** `a70956bf0d7ea8bdbd16767ed8b19600b274a6eeb745728f95219578adc73712`


# LoadImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImage

The LoadImage node is designed to load and preprocess images from a specified path.

The LoadImage node is designed to load and preprocess images from a specified path. It handles image formats with multiple frames, applies necessary transformations such as rotation based on EXIF data, normalizes pixel values, and optionally generates a mask for images with an alpha channel. This node is essential for preparing images for further processing or analysis within a pipeline.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The 'image' parameter specifies the identifier of the image to be loaded and processed. It is crucial for determining the path to the image file and subsequently loading the image for transformation and normalization. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The processed image, with pixel values normalized and transformations applied as necessary. It is ready for further processing or analysis. | `IMAGE` |
| `mask` | An optional output providing a mask for the image, useful in scenarios where the image includes an alpha channel for transparency. | `MASK` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImage/en.md)


# LoadImageDataSetFromFolder - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageDataSetFromFolder

This node loads multiple images from a selected subfolder within ComfyUI's main input directory and returns them as a list.

This node loads multiple images from a selected subfolder within ComfyUI's main input directory and returns them as a list. It scans the chosen folder for image files in PNG, JPG, JPEG, or WEBP format, which makes it useful for batch processing or preparing image datasets.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `folder` | The folder to load images from. The options are the subfolders present in ComfyUI's main input directory. | COMBO | Yes | Multiple options available |

Note: The selected folder must be a subfolder of ComfyUI's main input directory; any value that resolves outside of it (for example, using `..`, absolute paths, drive letters, or symlinks) is rejected. Only files with the extensions .png, .jpg, .jpeg, or .webp are loaded, and the extension check is case-insensitive. Loaded images are converted to RGB and scaled to the 0-1 range. If the selected folder contains no valid image files, the node raises an error. This node is marked as experimental.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | List of loaded images. The node loads all valid image files (PNG, JPG, JPEG, WEBP) found in the selected folder. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageDataSetFromFolder/en.md)

***

**Source fingerprint (SHA-256):** `cdee4e372890c126dd5f09654a7dd4103bba97a7901b6f5df8e02f29c4064ed2`


# LoadImageMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageMask

The LoadImageMask node is designed to load images and their associated masks from a specified path, processing them to ensure compatibility with further image manipulation or analy

The LoadImageMask node is designed to load images and their associated masks from a specified path, processing them to ensure compatibility with further image manipulation or analysis tasks. It focuses on handling various image formats and conditions, such as presence of an alpha channel for masks, and prepares the images and masks for downstream processing by converting them to a standardized format.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The 'image' parameter specifies the image file to be loaded and processed. It plays a crucial role in determining the output by providing the source image for mask extraction and format conversion. | COMBO\[STRING] |
| `channel` | The 'channel' parameter specifies the color channel of the image that will be used to generate the mask. This allows for flexibility in mask creation based on different color channels, enhancing the node's utility in various image processing scenarios. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | This node outputs the mask generated from the specified image and channel, prepared in a standardized format suitable for further processing in image manipulation tasks. | `MASK` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageMask/en.md)


# LoadImageOutput - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageOutput

The LoadImageOutput node loads images from the output folder.

The LoadImageOutput node loads images from the output folder. When you click the refresh button, it updates the list of available images and automatically selects the first one, making it easy to iterate through your generated images.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Load an image from the output folder. Includes an upload option and refresh button to update the image list. When the refresh button is clicked, the node will update the image list and automatically select the first image, allowing for easy iteration. | COMBO | Yes | Multiple options available |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The loaded image from the output folder | IMAGE |
| `mask` | The mask associated with the loaded image | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageOutput/en.md)

***

**Source fingerprint (SHA-256):** `d1de0140765c9d5dd393715faa84dc5c3f0e49117391b8823a51b176bcb568d8`


# LoadImageSetFromFolderNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageSetFromFolderNode

The LoadImageSetFromFolderNode loads multiple images from a specified folder directory for training purposes.

The LoadImageSetFromFolderNode loads multiple images from a specified folder directory for training purposes. It automatically detects common image formats and can optionally resize the images using different methods before returning them as a batch.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `folder` | The folder to load images from. | STRING | Yes | Multiple options available |
| `resize_method` | The method to use for resizing images (default: "None"). | STRING | No | "None"<br />"Stretch"<br />"Crop"<br />"Pad" |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The batch of loaded images as a single tensor. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageSetFromFolderNode/en.md)

***

**Source fingerprint (SHA-256):** `46fcfbf6a2ad95e707e32e54ed7b4c06bfd1cc290df122042187689f41bed828`


# LoadImageSetNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageSetNode

The LoadImageSetNode loads multiple images from the input directory for batch processing and training purposes.

The LoadImageSetNode loads multiple images from the input directory for batch processing and training purposes. It supports various image formats and can optionally resize the images using different methods. This node processes all selected images as a batch and returns them as a single tensor.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Select multiple images from the input directory. Supports PNG, JPG, JPEG, WEBP, BMP, GIF, JPE, APNG, TIF, and TIFF formats. Allows batch selection of images. | IMAGE | Yes | Multiple image files |
| `resize_method` | Optional method to resize loaded images (default: "None"). Choose "None" to keep original sizes, "Stretch" to force resize, "Crop" to maintain aspect ratio by cropping, or "Pad" to maintain aspect ratio by adding padding. | STRING | No | "None"<br />"Stretch"<br />"Crop"<br />"Pad" |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | A tensor containing all loaded images as a batch for further processing. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageSetNode/en.md)

***

**Source fingerprint (SHA-256):** `acf0255bcf170ef3ac3b86a3f3e060c3b81064ca8924918a026ec8e3b86f7ac0`


# LoadImageTextDataSetFromFolder - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageTextDataSetFromFolder

This node loads a dataset of image-text caption pairs from a selected folder and returns them as a list.

This node loads a dataset of image-text caption pairs from a selected folder and returns them as a list. It supports PNG, JPG, JPEG, and WEBP images, and for each image it looks for a caption in a `.txt` file with the same base name. The node also supports the kohya-ss/sd-scripts folder structure, where a subfolder name that starts with a number (such as `10_cats`) repeats the images inside that subfolder that many times in the output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `folder` | The folder to load images and text captions from. | COMBO | Yes | Subfolders inside ComfyUI's input directory (dynamically loaded) |

**Note:** The selected folder must be a subfolder of ComfyUI's input directory. The node expects one `.txt` caption file per image: for each image file (`.png`, `.jpg`, `.jpeg`, `.webp`) it looks for a `.txt` file with the same base name in the same location and uses its trimmed contents as the caption. If no caption file is found, an empty string is used. The node also supports the kohya-ss/sd-scripts folder structure: subfolders whose name starts with a number and an underscore (for example `5_cats`) repeat the images inside them that number of times in the final output list. If the selected folder contains no valid images, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | List of loaded images. Images are converted to RGB and normalized to the 0–1 float range. | IMAGE |
| `texts` | List of text captions, one for each loaded image. Captions are the trimmed contents of the matching `.txt` file, or an empty string when no caption file exists. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageTextDataSetFromFolder/en.md)

***

**Source fingerprint (SHA-256):** `d34494d59a65edb38d7e6a5f12c241fb0093371db0b0bf1e52789e84209ad3f5`


# LoadImageTextSetFromFolderNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageTextSetFromFolderNode

Loads a batch of images and their corresponding text captions from a specified directory for training purposes.

Loads a batch of images and their corresponding text captions from a specified directory for training purposes. The node automatically searches for image files and their associated caption text files, processes the images according to specified resize settings, and encodes the captions using the provided CLIP model.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `folder` | The folder to load images from. | STRING | Yes | - |
| `clip` | The CLIP model used for encoding the text. | CLIP | Yes | - |
| `resize_method` | The method used to resize images (default: "None"). | COMBO | No | "None"<br />"Stretch"<br />"Crop"<br />"Pad" |
| `width` | The width to resize the images to. -1 means use the original width (default: -1). | INT | No | -1 to 10000 |
| `height` | The height to resize the images to. -1 means use the original height (default: -1). | INT | No | -1 to 10000 |

**Note:** The CLIP input must be valid and cannot be None. If the CLIP model comes from a checkpoint loader node, ensure the checkpoint contains a valid CLIP or text encoder model.

**Note on folder structure:** The node supports the kohya-ss/sd-scripts folder structure. If a subfolder's name starts with a number followed by an underscore (e.g., `5_myclass`), that number is used as a repeat count, and the images inside that subfolder will be loaded that many times.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The batch of loaded and processed images. | IMAGE |
| `CONDITIONING` | The encoded conditioning data from the text captions. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageTextSetFromFolderNode/en.md)

***

**Source fingerprint (SHA-256):** `ffd6399783fc281a58bae811112d9ecacb51ab8ea3b512befa9b9fab2c6860de`


# LoraLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraLoader

This node automatically detects models located in the LoRA folder (including subfolders) with the corresponding model path being ComfyUI\models\loras.

This node automatically detects models located in the LoRA folder (including subfolders) with the corresponding model path being `ComfyUI\models\loras`. For more information, please refer to Installing LoRA Models

The LoRA Loader node is primarily used to load LoRA models. You can think of LoRA models as filters that can give your images specific styles, content, and details:

* Apply specific artistic styles (like ink painting)
* Add characteristics of certain characters (like game characters)
* Add specific details to the image
  All of these can be achieved through LoRA.

If you need to load multiple LoRA models, you can directly chain multiple nodes together, as shown below:

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | Typically used to connect to the base model | MODEL |
| `clip` | Typically used to connect to the CLIP model | CLIP |
| `lora_name` | Select the name of the LoRA model to use | COMBO\[STRING] |
| `strength_model` | Value range from -100.0 to 100.0, typically used between 0\~1 for daily image generation. Higher values result in more pronounced model adjustment effects | FLOAT |
| `strength_clip` | Value range from -100.0 to 100.0, typically used between 0\~1 for daily image generation. Higher values result in more pronounced model adjustment effects | FLOAT |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The model with LoRA adjustments applied | MODEL |
| `clip` | The CLIP instance with LoRA adjustments applied | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoraLoader/en.md)


# LoraLoaderModelOnly - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraLoaderModelOnly

This node will detect models located in the ComfyUI/models/loras folder, and it will also read models from additional paths configured in the extramodelpaths.yaml file.

This node will detect models located in the `ComfyUI/models/loras` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

This node specializes in loading a LoRA model without requiring a CLIP model, focusing on enhancing or modifying a given model based on LoRA parameters. It allows for the dynamic adjustment of the model's strength through LoRA parameters, facilitating fine-tuned control over the model's behavior.

## Inputs

| Field | Description | Comfy dtype |
| - | - | - |
| `model` | The base model for modifications, to which LoRA adjustments will be applied. | `MODEL` |
| `lora_name` | The name of the LoRA file to be loaded, specifying the adjustments to apply to the model. | `COMBO[STRING]` |
| `strength_model` | Determines the intensity of the LoRA adjustments, with higher values indicating stronger modifications. | `FLOAT` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `model` | The modified model with LoRA adjustments applied, reflecting changes in model behavior or capabilities. | `MODEL` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoraLoaderModelOnly/en.md)


# MarigoldV2PostProcess - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MarigoldV2PostProcess

This node converts a decoded Marigold V2 prediction into a viewable image.

This node converts a decoded Marigold V2 prediction into a viewable image. It takes the raw prediction tensor and formats it depending on which type of prediction it is: normalized depth (near objects appear bright), unit-length surface normals, or sRGB albedo.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The decoded Marigold V2 prediction to be converted into a displayable image. | IMAGE | Yes | - |
| `prediction` | The type of prediction contained in the input, which determines how the data is converted. `"depth"` normalizes the depth values so that near surfaces are bright and far surfaces are dark, then copies the result into all three color channels. `"normals"` rescales the values to the -1..1 range, normalizes them into unit surface normals, and maps them back to 0..1. `"albedo"` applies a linear-to-sRGB conversion to the values. | COMBO | Yes | `"depth"`<br />`"normals"`<br />`"albedo"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The processed image in the selected representation: normalized depth (grayscale repeated across three channels), unit surface normals, or sRGB albedo. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MarigoldV2PostProcess/en.md)

***

**Source fingerprint (SHA-256):** `848b29e2dfcd34c44cf9707b9b26cb13c18e82bb16618a15afbe477a1d620e1e`


# MaskComposite - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MaskComposite

This node specializes in combining two mask inputs through a variety of operations such as addition, subtraction, and logical operations, to produce a new, modified mask.

This node specializes in combining two mask inputs through a variety of operations such as addition, subtraction, and logical operations, to produce a new, modified mask. It abstractly handles the manipulation of mask data to achieve complex masking effects, serving as a crucial component in mask-based image editing and processing workflows.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `destination` | The primary mask that will be modified based on the operation with the source mask. It plays a central role in the composite operation, acting as the base for modifications. | MASK |
| `source` | The secondary mask that will be used in conjunction with the destination mask to perform the specified operation, influencing the final output mask. | MASK |
| `x` | The horizontal offset at which the source mask will be applied to the destination mask, affecting the positioning of the composite result. | INT |
| `y` | The vertical offset at which the source mask will be applied to the destination mask, affecting the positioning of the composite result. | INT |
| `operation` | Specifies the type of operation to apply between the destination and source masks, such as 'add', 'subtract', or logical operations, determining the nature of the composite effect. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The resulting mask after applying the specified operation between the destination and source masks, representing the composite outcome. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MaskComposite/en.md)


# MaskPreview - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MaskPreview

The MaskPreview node displays a visual preview of the mask data directly in the ComfyUI interface, without saving it to the output directory.

The MaskPreview node displays a visual preview of the mask data directly in the ComfyUI interface, without saving it to the output directory. This lets you inspect the mask at any point in your workflow, while the mask also passes through the node unchanged so it can continue to be used downstream.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mask` | The mask data to preview | MASK | Yes | - |
| `filename_prefix` | Filename prefix used for the preview (default: "ComfyUI") | STRING | No | - |
| `prompt` | Prompt information for metadata (automatically provided) | PROMPT | No | - |
| `extra_pnginfo` | Additional PNG information for metadata (automatically provided) | EXTRA\_PNGINFO | No | - |

Only `mask` is a visible input that needs to be connected. The `filename_prefix`, `prompt`, and `extra_pnginfo` parameters are supplied by the system: `filename_prefix` falls back to its default value, while `prompt` and `extra_pnginfo` are hidden and provided automatically by the ComfyUI runtime.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mask` | The same mask data that was previewed, returned unchanged so it can be used elsewhere in the workflow | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MaskPreview/en.md)

***

**Source fingerprint (SHA-256):** `fb7abe8cb6b5ac8a6a38e88ef90a146d16caf41d24c5de95309a94bc3c371d75`


# MaskToImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MaskToImage

The MaskToImage node is designed to convert a mask into an image format.

The `MaskToImage` node is designed to convert a mask into an image format. This transformation allows for the visualization and further processing of masks as images, facilitating a bridge between mask-based operations and image-based applications.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | The mask input is essential for the conversion process, serving as the source data that will be transformed into an image format. This input dictates the shape and content of the resulting image. | `MASK` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The output is an image representation of the input mask, enabling visual inspection and further image-based manipulations. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MaskToImage/en.md)


# MoGeGeometryToFOV - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoGeGeometryToFOV

This node derives the field of view and focal length from the camera intrinsics stored in a MoGe geometry object.

This node derives the field of view and focal length from the camera intrinsics stored in a MoGe geometry object. It can return the vertical, horizontal, or diagonal FOV, in degrees or radians. The vertical FOV output can be used, for example, to feed the SAM3DBody\_Predict node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `moge_geometry` | The MoGe geometry object. It must contain an intrinsics matrix and at least one of `image`, `points`, or `depth` data, which is used to read the pixel height for the focal-length conversion. | MOGE\_GEOMETRY | Yes | — |
| `axis` | The axis along which the FOV is computed: "vertical" (fov\_y), "horizontal" (fov\_x), or "diagonal" (default: "vertical"). | COMBO | Yes | "vertical"<br />"horizontal"<br />"diagonal" |
| `unit` | Output unit for the FOV (default: "degrees"). | COMBO | Yes | "degrees"<br />"radians" |

Note: The node raises an error if `moge_geometry` contains no intrinsics (panorama geometry has none) or if it contains neither `image`, `points`, nor `depth` data.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `fov` | The field of view along the selected axis, in the selected unit (degrees or radians). | FLOAT |
| `focal_pixels` | The lens focal length in pixels, derived from the vertical intrinsic and the pixel height. | FLOAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoGeGeometryToFOV/en.md)

***

**Source fingerprint (SHA-256):** `983dc984847f93a8e002c73982571ecb38b7bae9c3dc4c201d9be17f785dcaed`


# MoGeInference - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoGeInference

Run MoGe on images to estimate depth and geometry.

Run MoGe on images to estimate depth and geometry. This node processes an input image through the MoGe model to generate a 3D point cloud, depth map, camera intrinsics, a mask, and surface normals.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `moge_model` | The MoGe model to use for inference. | MOGE\_MODEL | Yes | N/A |
| `image` | The input image for depth and geometry estimation. Only the first three color channels (RGB) are used. | IMAGE | Yes | N/A |
| `resolution_level` | Controls the processing resolution. 0 = fastest, 9 = most detail. (default: 9) | INT | Yes | 0 to 9 |
| `fov_x_degrees` | (Advanced) Horizontal field of view of the source camera. Sets the focal length used to unproject the depth map into 3D. 0 = auto-recover from the predicted points. (default: 0.0) | FLOAT | Yes | 0.0 to 170.0 (step 0.1) |
| `batch_size` | Images per inference call. Lower if you OOM on a long video / image set. (default: 4) | INT | Yes | 1 to 64 |
| `force_projection` | (Advanced) Forces projection of the predicted points. (default: True) | BOOLEAN | Yes | True/False |
| `apply_mask` | (Advanced) Set masked-out (sky / invalid) pixels to inf in points and depth so meshing culls them. Disable to keep the raw predicted geometry everywhere; the mask is still returned separately. (default: True) | BOOLEAN | Yes | True/False |
| `refine_steps` | (Advanced) MoGe-3 only: sparse volumetric refinement passes over the predicted depth. More passes sharpen fine detail and edges at a roughly linear cost. 0 disables refinement. Ignored by MoGe-1 / MoGe-2. (default: 3) | INT | Yes | 0 to 8 |

Note: When the input `image` contains more frames than `batch_size`, the node processes them in multiple inference calls and combines the results into a single output geometry.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `moge_geometry` | A dictionary containing the estimated geometry. It includes the original `image`, and may contain `points` (3D point cloud), `depth` (depth map), `intrinsics` (camera intrinsics matrix), `mask` (mask identifying valid pixels), and `normal` (surface normals). | MOGE\_GEOMETRY |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoGeInference/en.md)

***

**Source fingerprint (SHA-256):** `10f3399d9b6bc4ff8a940c940f538a8ec8f38a15e7d65f162499c5ab264fad65`


# MoGePanoramaInference - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoGePanoramaInference

This node performs depth estimation on equirectangular panorama images.

This node performs depth estimation on equirectangular panorama images. It splits the panorama into 12 perspective views, runs the MoGe depth estimation model on each view, and merges the per-view results back into a single depth map covering the full panorama. Per-view predicted normals and metric scale are ignored, because per-view scales would not align across the overlap seams.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `moge_model` | The MoGe model to use for inference. | MOGE\_MODEL | Yes | |
| `image` | Equirectangular panorama (any aspect). The node accepts a single image only; passing a batch of images raises an error. Only the first 3 color channels (RGB) are used. | IMAGE | Yes | |
| `resolution_level` | Per-view detail (0 = fastest, 9 = most detailed) (default: 9). | INT | Yes | 0 to 9 |
| `split_resolution` | Resolution of each perspective split (default: 512). | INT | Yes | 256 to 1024 |
| `merge_resolution` | Long-side resolution of the merged equirect distance map (default: 1920). | INT | Yes | 256 to 8192 |
| `batch_size` | Views per inference batch (12 splits total) (default: 4). | INT | Yes | 1 to 12 |
| `refine_steps` | MoGe-3 only: sparse volumetric refinement passes over the predicted depth. More passes sharpen fine detail and edges at a roughly linear cost. 0 disables refinement. Ignored by MoGe-1 / MoGe-2 (default: 3). | INT | Yes | 0 to 8 |

**Notes:**

* The input must be a single image. If `image` contains more than one image in the batch, the node raises an error.
* `merge_resolution` is treated as a maximum long-side size. If the panorama is smaller than this value, the merged map is produced at the original panorama size instead of being upscaled. The merged result is resized back to the original panorama resolution before being returned.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `moge_geometry` | A dictionary containing the estimated geometry: `points` (3D point cloud), `depth` (depth map), `mask` (valid area mask), and `image` (the input image). | MOGE\_GEOMETRY |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoGePanoramaInference/en.md)

***

**Source fingerprint (SHA-256):** `7f21452d035b2fe9d30b0cd15ddad10916439492b1d682a8b28f1a79e375df58`


# MoGePointMapToMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoGePointMapToMesh

This node converts a MoGe point map into a 3D mesh.

This node converts a MoGe point map into a 3D mesh. It takes geometry data produced by a MoGe depth estimation node and triangulates it into a mesh with UV coordinates and an optional texture.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `moge_geometry` | The MoGe geometry data containing point maps, depth, and optionally the source image. | MOGE\_GEOMETRY | Yes | N/A |
| `batch_index` | Which image of a batched MoGe geometry to mesh. Per-image vertex counts differ, so batches can't be stacked into a single MESH (default: 0). | INT | Yes | 0 to 4096 |
| `decimation` | Vertex stride; 1 = full resolution (default: 1). | INT | Yes | 1 to 8 |
| `discontinuity_threshold` | Drop pixels whose 3x3 depth span exceeds this fraction. 0 = off (default: 0.04). | FLOAT | Yes | 0.0 to 1.0 |
| `texture` | Carry the source image through as the baseColor texture (default: True). | BOOLEAN | Yes | True/False |

Note: `batch_index` must be smaller than the batch size of the input `moge_geometry`; selecting an out-of-range index raises an error. The input must contain a points output, otherwise the node raises an error. If the triangulation produces an empty mesh, the node raises an error — setting `discontinuity_threshold` to 0 disables the depth-discontinuity filter. The output mesh is converted to glTF coordinates: perspective MoGe data (X right, Y down, Z forward) is flipped to match glTF (Y up, Z back), and panoramic data (geometry without intrinsic parameters) is rotated accordingly with corrected winding. When `texture` is enabled, the source image from `moge_geometry` is used as the baseColor texture.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MESH` | A 3D mesh with vertices, faces, UV coordinates, and an optional baseColor texture from the source image. | MESH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoGePointMapToMesh/en.md)

***

**Source fingerprint (SHA-256):** `626925866eed6805d2ce87529909fc76b9484cd2e8118fdd1669a237d44b9b0b`


# MoGeRender - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoGeRender

This node takes a MOGEGEOMETRY packet (produced by a MoGe depth/normal estimation node) and renders it into a standard image format.

This node takes a MOGE\_GEOMETRY packet (produced by a MoGe depth/normal estimation node) and renders it into a standard image format. You can choose to output a depth map, a colored depth map, a normal map, or a mask.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `moge_geometry` | The geometry data packet from a MoGe estimation node. | MOGE\_GEOMETRY | Yes | N/A |
| `output` | The type of image to render from the geometry data. `depth` outputs a grayscale depth map, `depth_colored` outputs a colored depth map, `normal_opengl` and `normal_directx` output normal maps, and `mask` outputs a mask. DirectX vs OpenGL controls the normal-map green-channel convention. DirectX: green = -Y down (Unreal). OpenGL: green = +Y up (Blender, Substance, Unity, glTF). (default: "depth") | COMBO | Yes | `"depth"`<br />`"depth_colored"`<br />`"normal_opengl"`<br />`"normal_directx"`<br />`"mask"` |

**Note:** The geometry packet must contain data matching the chosen `output` mode. The `depth` and `depth_colored` modes require depth data in the packet. The `normal_opengl` and `normal_directx` modes require normal data, or points data from which normals are derived. The `mask` mode requires mask data. If the required data is missing, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The rendered image as a batch of RGB tensors. The content depends on the `output` mode: a grayscale depth map, a colored depth map, a normal map, or a mask converted to RGB. The output batch size matches the input geometry batch size. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoGeRender/en.md)

***

**Source fingerprint (SHA-256):** `ca602f7a7d6eb1b1d00986459621d94ecf9331266ff1d3ce7bb759d24448a346`


# Morphology - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Morphology

The Morphology node applies various morphological operations to images, which are mathematical operations used to process and analyze shapes in images.

The Morphology node applies various morphological operations to images, which are mathematical operations used to process and analyze shapes in images. It can perform operations like erosion, dilation, opening, closing, and more using a customizable kernel size to control the effect strength.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to process | IMAGE | Yes | - |
| `operation` | The morphological operation to apply (default: "erode") | STRING | Yes | `"erode"`<br />`"dilate"`<br />`"open"`<br />`"close"`<br />`"gradient"`<br />`"bottom_hat"`<br />`"top_hat"` |
| `kernel_size` | The size of the structuring element kernel (default: 3). Must be an odd number. | INT | Yes | 3-999 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The processed image after applying the morphological operation | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Morphology/en.md)

***

**Source fingerprint (SHA-256):** `ea596f8d30975f153fccbc5651eec0fbbf308ef1c616313d996c200cddf748e3`


# Painter - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Painter

The Painter node provides an interactive canvas for creating or editing images and masks directly within ComfyUI.

The Painter node provides an interactive canvas for creating or editing images and masks directly within ComfyUI. It allows you to start with a blank canvas or an existing image, paint on it using a brush tool, and outputs both the resulting image and a corresponding alpha mask. The mask defines the painted areas, which are then composited over the base image or background color.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Optional base image to paint over. If not provided, a blank canvas is created using the specified background color, width, and height. | IMAGE | No | - |
| `mask` | The painting data, typically generated by the node's built-in interactive widget. This parameter is managed by the UI's painter tool and is not meant to be connected to a standard socket. | STRING | Yes | - |
| `width` | The width of the canvas in pixels, used when no base `image` is provided. The value must be a multiple of 64. Default is 512. | INT | Yes | 64 to 4096 |
| `height` | The height of the canvas in pixels, used when no base `image` is provided. The value must be a multiple of 64. Default is 512. | INT | Yes | 64 to 4096 |
| `bg_color` | The background color for the canvas, specified as a hex code (e.g., #000000). This is only used when no base `image` is provided. Default is black (#000000). | COLOR | Yes | - |

**Note:** The `mask` input is designed to work with the node's specialized UI widget. When you paint on the canvas, the widget automatically populates this value. The `width` and `height` inputs are hidden in the standard UI but define the canvas dimensions when creating a new image. If a base `image` is provided, its dimensions override the `width` and `height` settings.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The final composited image. This is the result of blending the painted areas (from the `mask`) over the provided base `image` or the colored background. | IMAGE |
| `MASK` | The alpha channel (transparency) mask extracted from the painting. White areas represent the painted regions, and black areas represent the untouched background. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Painter/en.md)

***

**Source fingerprint (SHA-256):** `217a6d8abbad02cb43cab18d0a592bdd5bfbfe321a742d0c14e8f4e1fa5e2630`


# PreviewImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PreviewImage

The PreviewImage node is designed for creating temporary preview images.

The PreviewImage node is designed for creating temporary preview images. It automatically generates a unique temporary file name for each image, compresses the image to a specified level, and saves it to a temporary directory. This functionality is particularly useful for generating previews of images during processing without affecting the original files.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `images` | The 'images' input specifies the images to be processed and saved as temporary preview images. This is the primary input for the node, determining which images will undergo the preview generation process. | `IMAGE` |

## Outputs

The node doesn't have output types.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PreviewImage/en.md)


# RandomCropImages - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RandomCropImages

The Random Crop Images node randomly selects a rectangular section from each input image and crops it to a specified width and height.

The Random Crop Images node randomly selects a rectangular section from each input image and crops it to a specified width and height. This is commonly used for data augmentation to create variations of training images. The random position for the crop is determined by a seed value, ensuring the same crop can be reproduced.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image to be cropped. | IMAGE | Yes | - |
| `width` | The width of the crop area (default: 512). | INT | No | 1 - 8192 |
| `height` | The height of the crop area (default: 512). | INT | No | 1 - 8192 |
| `seed` | A number used to control the random position of the crop (default: 0). | INT | No | 0 - 18446744073709551615 |

**Note:** The `width` and `height` parameters must be less than or equal to the dimensions of the input image. If a specified dimension is larger than the image, the crop will be limited to the image's boundary.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resulting image after the random crop has been applied. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RandomCropImages/en.md)

***

**Source fingerprint (SHA-256):** `8452a07a1cf66a520fb482f5239df3f33cfe3a77a28e289894ccd1d2544ecf40`


# ResizeAndPadImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResizeAndPadImage

The ResizeAndPadImage node resizes an image to fit within specified dimensions while maintaining its original aspect ratio.

The ResizeAndPadImage node resizes an image to fit within specified dimensions while maintaining its original aspect ratio. It scales the image down proportionally to fit within the target width and height, then adds padding around the edges to fill any remaining space. The padding color and interpolation method can be customized to control the appearance of the padded areas and the quality of the resizing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be resized and padded | IMAGE | Yes | - |
| `target_width` | The desired width of the output image (default: 512) | INT | Yes | 1 to MAX\_RESOLUTION |
| `target_height` | The desired height of the output image (default: 512) | INT | Yes | 1 to MAX\_RESOLUTION |
| `padding_color` | The color to use for padding areas around the resized image (default: "white") | COMBO | Yes | "white"<br />"black" |
| `interpolation` | The interpolation method used for resizing the image (default: "area") | COMBO | Yes | "area"<br />"bicubic"<br />"nearest-exact"<br />"bilinear"<br />"lanczos" |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resized and padded output image | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResizeAndPadImage/en.md)

***

**Source fingerprint (SHA-256):** `cc516caee9f466d557e1c8e3c7fcef25acc1e33d181bc4b100302dc93530cb95`


# ResizeImageMaskNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResizeImageMaskNode

The Resize Image/Mask node provides multiple methods to change the dimensions of an input image or mask.

The Resize Image/Mask node provides multiple methods to change the dimensions of an input image or mask. It can scale by a multiplier, set specific dimensions, match the size of another input, or adjust based on pixel count, using various interpolation methods for quality.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `input` | The image or mask to be resized. | IMAGE or MASK | Yes | N/A |
| `resize_type` | The method used to determine the new size. The required parameters change based on the selected type. | COMBO | Yes | `SCALE_BY`<br />`SCALE_DIMENSIONS`<br />`SCALE_LONGER_DIMENSION`<br />`SCALE_SHORTER_DIMENSION`<br />`SCALE_WIDTH`<br />`SCALE_HEIGHT`<br />`SCALE_TOTAL_PIXELS`<br />`MATCH_SIZE` |
| `multiplier` | The scaling factor. Required when `resize_type` is `SCALE_BY` (default: 1.00). | FLOAT | No | 0.01 to 8.0 |
| `width` | The target width in pixels. Required when `resize_type` is `SCALE_DIMENSIONS` or `SCALE_WIDTH` (default: 512). | INT | No | 0 to 8192 |
| `height` | The target height in pixels. Required when `resize_type` is `SCALE_DIMENSIONS` or `SCALE_HEIGHT` (default: 512). | INT | No | 0 to 8192 |
| `crop` | The cropping method to apply when dimensions don't match the aspect ratio. Only available when `resize_type` is `SCALE_DIMENSIONS` or `MATCH_SIZE` (default: "center"). | COMBO | No | `"disabled"`<br />`"center"` |
| `longer_size` | The target size for the longer side of the image. Required when `resize_type` is `SCALE_LONGER_DIMENSION` (default: 512). | INT | No | 0 to 8192 |
| `shorter_size` | The target size for the shorter side of the image. Required when `resize_type` is `SCALE_SHORTER_DIMENSION` (default: 512). | INT | No | 0 to 8192 |
| `megapixels` | The target total number of megapixels. Required when `resize_type` is `SCALE_TOTAL_PIXELS` (default: 1.0). | FLOAT | No | 0.01 to 16.0 |
| `match` | An image or mask whose dimensions the input will be resized to match. Required when `resize_type` is `MATCH_SIZE`. | IMAGE or MASK | No | N/A |
| `scale_method` | The interpolation algorithm used for scaling (default: "area"). | COMBO | Yes | `"nearest-exact"`<br />`"bilinear"`<br />`"area"`<br />`"bicubic"`<br />`"lanczos"` |

**Note:** The `crop` parameter is only available and relevant when the `resize_type` is set to `SCALE_DIMENSIONS` or `MATCH_SIZE`. When using `SCALE_WIDTH` or `SCALE_HEIGHT`, the other dimension is automatically scaled to maintain the original aspect ratio.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `resized` | The resized image or mask, matching the data type of the input. | IMAGE or MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResizeImageMaskNode/en.md)

***

**Source fingerprint (SHA-256):** `9ac0b153608ac971bb11d9d12ebd1f0f4d6e926604e8727a1bc3a311d95fbc03`


# ResizeImagesByLongerEdge - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResizeImagesByLongerEdge

The Resize Images by Longer Edge node resizes one or more images so that their longest side matches a specified target length.

The Resize Images by Longer Edge node resizes one or more images so that their longest side matches a specified target length. It automatically determines whether the width or height is longer and scales the other dimension proportionally to preserve the original aspect ratio. This node is deprecated and superseded by the Resize Image/Mask node with the resize type set to "scale longer dimension".

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image or batch of images to be resized. | IMAGE | Yes | - |
| `longer_edge` | Target dimension for the longer edge. The shorter edge will be scaled proportionally. (default: 1024) | INT | Yes | 1 - 8192 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resized image or batch of images. The output will have the same number of images as the input, with each one's longer edge matching the specified `longer_edge` length. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResizeImagesByLongerEdge/en.md)

***

**Source fingerprint (SHA-256):** `bf66808acbc654d5a9ea58b062b5b89d6c13dbec0929d6d92aaa3c8914dcece0`


# ResizeImagesByShorterEdge - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResizeImagesByShorterEdge

This node resizes images so that the shorter edge matches a specified length while preserving the original aspect ratio.

This node resizes images so that the shorter edge matches a specified length while preserving the original aspect ratio. It calculates new dimensions based on the target length for the shorter side and returns the resized image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be resized. | IMAGE | Yes | - |
| `shorter_edge` | Target dimension for the shorter edge. (default: 512) | INT | Yes | 1 to 8192 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resized image with the shorter edge matching the specified target length. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResizeImagesByShorterEdge/en.md)

***

**Source fingerprint (SHA-256):** `6bb3e1c974108ee7b75b47406ea02b3f47ca14305f9ee54d3d379eefbb7f26cd`


# SAM3DBody_FaceExpression - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3DBody_FaceExpression

This node adds facial expressions to a SAM3D body by detecting faces in an image with the MediaPipe Face Landmarker, matching each detected face to a tracked person, and mapping th

This node adds facial expressions to a SAM3D body by detecting faces in an image with the MediaPipe Face Landmarker, matching each detected face to a tracked person, and mapping the 52 ARKit blendshapes onto MHR's 72-axis expression parameters. It then re-runs the body model so the output mesh vertices and keypoints reflect the new expression.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `sam3d_body_model` | The SAM3D body model containing the face landmark detector used to detect faces and regenerate the body mesh. | SAM3D\_BODY\_MODEL | Yes | - |
| `mhr_pose_data` | Pose data containing per-frame tracked persons with bounding boxes, keypoints, and expression parameters. The node matches each detected face to a person and writes updated expression parameters into this data. | MHR\_POSE\_DATA | Yes | - |
| `image` | Image frames used to detect faces. If the image batch has fewer frames than the pose data, the last frame is reused for the remaining frames. | IMAGE | Yes | - |
| `strength` | Global multiplier on all blendshapes. >1 exaggerates. Default: 1.0. | FLOAT | No | 0.0 to 4.0 (step 0.05, default 1.0) |
| `mouth_strength` | Multiplier on mouth/jaw shapes. MediaPipe's jawOpen saturates near 1.0. Default: 1.0. | FLOAT | No | 0.0 to 4.0 (step 0.05, default 1.0) |
| `eye_strength` | Multiplier on eye shapes. MediaPipe rarely exceeds 0.5; 2-3x often needed. Default: 2.0. | FLOAT | No | 0.0 to 4.0 (step 0.05, default 2.0) |
| `brow_strength` | Multiplier on brow/cheek/sneer shapes. MediaPipe outputs \~0.1-0.3; 2-3x. Default: 2.0. | FLOAT | No | 0.0 to 4.0 (step 0.05, default 2.0) |
| `input_threshold` | Deadzone on MediaPipe's raw output (below = zero, above = linear remap). Default: 0.02. | FLOAT | No | 0.0 to 0.5 (step 0.01, default 0.02) |
| `blendshape_smooth_window` | Gaussian window on MediaPipe's per-frame signal before MHR mapping. MediaPipe's raw output swings 30-70% frame-to-frame on static faces. 1 = disabled. Use odd values. Default: 7. | INT | No | 1 to 31 (step 2, default 7) |

Note: A per-clip baseline subtraction is applied only when at least 30 frames in the clip contain detected persons. Detection gaps of up to 12 frames per person are filled by interpolation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mhr_pose_data` | The updated pose data. Each tracked person's expression parameters are replaced with the mapped face expression, and the mesh vertices and keypoints are regenerated to match. | MHR\_POSE\_DATA |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3DBody_FaceExpression/en.md)

***

**Source fingerprint (SHA-256):** `b2299e51be3556e639d5b04fcbee541ecf41e0d84c2c8a0fd4e211b2f6caba0b`


# SAM3DBody_Loader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3DBody_Loader

Loads a SAM3D Body model from a checkpoint file stored in the detection folder and prepares it for 3D body detection use.

Loads a SAM3D Body model from a checkpoint file stored in the detection folder and prepares it for 3D body detection use. The node loads the model weights, detects and applies quantization settings if present, and wraps the model for automatic memory management.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_file` | The SAM3D Body checkpoint file to load. The file must be placed in the detection folder. All model files available in the detection folder are listed as options. | COMBO | Yes | All model files available in the detection folder |

Note: The model file must be located in the detection folder. Loading fails with an error if the checkpoint's state dictionary keys do not match the SAM3D Body model structure.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sam3d_body_model` | The loaded SAM3D Body model, wrapped for automatic memory management between GPU and CPU. Hand-detection weights are removed, so the model is specialized for body detection only. | SAM3D\_BODY\_MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3DBody_Loader/en.md)

***

**Source fingerprint (SHA-256):** `c66a1639b5f19dafcfb1466d68908969a4d33ab0d01c30e8b31d1f1ce41fd782`


# SAM3DBody_Predict - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3DBody_Predict

SAM3D Body Prediction runs 3D body and hand pose estimation on input images, detecting one or more people per frame.

SAM3D Body Prediction runs 3D body and hand pose estimation on input images, detecting one or more people per frame. Tracking data or bounding boxes can be supplied to improve detection; when neither is provided, the node falls back to full-frame single-person detection.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `sam3d_body_model` | The SAM3D body model to use for prediction. | SAM3D\_BODY\_MODEL | Yes | — |
| `image` | Image or batch of images to run body prediction on. | IMAGE | Yes | — |
| `track_data` | Tracking data from SAM3 Video Track, required for multi-person detection. | SAM3\_TRACK\_DATA | No | — |
| `bboxes` | Per-frame bounding boxes used for better detection. Can be used as an alternative to tracking data. | BBOX | No | — |
| `run_hand_refinement` | Improves hand pose at the cost of extra inference time and memory use. Default: true. | BOOLEAN | No | true<br />false |
| `fov` | Vertical FoV in degrees. Affects predicted depth and absolute scale. 0 = fall back to \~53° (16:9). Default: 0.0. | FLOAT | No | 0.0 or greater |
| `batch_size` | Max person crops to process as a batch. Larger values use more VRAM for faster inference. Default: 64. | INT | No | 1 to 512 |

Note: When `track_data` is provided, it takes precedence over `bboxes`. If neither `track_data` nor `bboxes` is provided, the node falls back to single-person full-frame detection. Bounding boxes can be provided for a single frame (applied to every frame) or per frame.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mhr_pose_data` | Body pose data bundle containing per-frame pose detection results, face geometry, the input image size, canonical vertex colors, and a hand vertex mask. | MHR\_POSE\_DATA |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3DBody_Predict/en.md)

***

**Source fingerprint (SHA-256):** `f1039349cd2809423053bffde1c7d119c7c42f217327d23c608b1224d183770e`


# SAM3DBody_Render - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3DBody_Render

Renders 3D body pose data into an image using a selectable style.

Renders 3D body pose data into an image using a selectable style. The node accepts pose data from the SAM3D body tracker (MHR) or from an external Y-up rig such as Kimodo, and can composite the result over an optional background image (or a black canvas when none is provided). Available render styles include a shaded 3D mesh, a binary silhouette, 2D and 3D OpenPose-style skeletons, and SCAIL-style body capsules.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `render_style` | Render mode. 'mesh' = 3D MHR mesh rasterized through the camera. 'silhouette' = binary mask of the mesh. 'openpose\_2d' = flat 2D skeleton. 'openpose\_3d' = OpenPose skeleton as flat-shaded 3D model. 'scail' = SCAIL 3D capsules. (default: "mesh") | DYNAMIC\_COMBO | Yes | "mesh"<br />"silhouette"<br />"openpose\_2d"<br />"openpose\_3d"<br />"scail" |
| `pose_data` | MHR pose data, or external Y-up rig pose data (KimodoSample). All render styles work for external rigs that carry OpenPose joint maps in their `_skeleton_override` (KimodoSample does). | MHR\_POSE\_DATA or KIMODO\_POSE\_DATA | Yes | — |
| `background` | Per-frame background. Omitted = black canvas. | IMAGE | No | — |
| `width` | Output width in pixels. 0 = use pose data's native image\_size. If only one of width/height is set, the other is derived preserving the original aspect. (default: 0) | INT | No | 0 to 16384, step 8 |
| `height` | Output height in pixels. 0 = use pose data's native image\_size. If only one of width/height is set, the other is derived preserving the original aspect. (default: 0) | INT | No | 0 to 16384, step 8 |
| `camera_info` | Free 6DOF camera override. When wired, the pose is re-projected through this camera (position/target/zoom/rotation/FoV) instead of the predicted one. | LOAD\_3D\_CAMERA | No | — |

### Mesh Inputs

These parameters appear when `render_style` is "mesh".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `shader` | Preset shader. 'normals' = current surface normal in camera space (OpenGL Y+ normal-map convention: +X→R, +Y→G, +Z→B). 'rainbow' = RealisDance style body-Y jet; the 'rainbow\_face\_\*' variants override face verts with normal/per-region colors; 'depth' = linear gray. (default: "default") | DYNAMIC\_COMBO | No | "default"<br />"normals"<br />"rainbow"<br />"rainbow\_face\_normal"<br />"rainbow\_face\_semantic"<br />"depth" |
| `rainbow_tilt_z` | Rotate rainbow jet axis around Z (forward). Differentiates left/right. Only available when `shader` is "rainbow", "rainbow\_face\_normal", or "rainbow\_face\_semantic". (default: -35.0) | FLOAT | No | -90.0 to 90.0, step 0.5 |
| `rainbow_tilt_x` | Rotate rainbow jet axis around X (right). Differentiates front/back. Only available when `shader` is "rainbow", "rainbow\_face\_normal", or "rainbow\_face\_semantic". (default: 0.0) | FLOAT | No | -90.0 to 90.0, step 0.5 |
| `opacity` | Mesh alpha over the background image, or over black when none is connected. (default: 1.0) | FLOAT | No | 0.0 to 1.0, step 0.01 |
| `person_palette_falloff` | Per-person desaturation toward white: track k gets a (1 - falloff^k) pastel mix (SCAIL 'softer second person'). 1.0 = off. (default: 0.6) | FLOAT | No | 0.1 to 1.0, step 0.05 |
| `region` | 'hands\_only' filters faces via the precomputed `hand_vert_mask` (LBS weights against canonical hand KPs) — isolates the hand mesh for debugging. Falls back to full mesh if the mask is missing. (default: "full\_body") | COMBO | No | "full\_body"<br />"hands\_only" |

### Silhouette Inputs

When `render_style` is "silhouette", the node renders a binary mask of the 3D mesh. This mode has no additional parameters.

### OpenPose 2D Inputs

These parameters appear when `render_style` is "openpose\_2d".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `marker_radius_px` | Body keypoint dot radius (px). (default: 4) | INT | No | 1 to 32, step 1 |
| `stick_width_px` | Body limb ellipse half-width (px). DWPose default = 4. (default: 4) | INT | No | 1 to 32, step 1 |
| `limb_alpha` | Per-limb alpha. DWPose default = 0.6. (default: 0.6) | FLOAT | No | 0.0 to 1.0, step 0.05 |
| `face_style` | 'full' = all face landmarks (sapiens-238 if present, else rig-fallback \~30). 'eyes\_mouth' = rig-fallback subset (\~12 dots: eyes + outer lips only). 'disabled' = no face dots. (default: "disabled") | COMBO | No | "disabled"<br />"full"<br />"eyes\_mouth" |
| `hand_style` | Draw 21+21 hand keypoints + sticks. 'disabled' = no hands. 'dwpose' = solid-blue dots; 'openpose' = rainbow dots. (default: "disabled") | COMBO | No | "disabled"<br />"dwpose"<br />"openpose" |
| `person_palette_falloff` | Per-person desaturation: track k blends toward white by 1 - falloff^k. Track 0 stays vivid; 1.0 disables falloff. (default: 0.6) | FLOAT | No | 0.1 to 1.0, step 0.05 |

### OpenPose 3D Inputs

These parameters appear when `render_style` is "openpose\_3d".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `radius_m` | Limb capsule radius in meters (thin = stick-like). (default: 0.015) | FLOAT | No | 0.004 to 0.1, step 0.001 |
| `include_hands` | Draw 21+21 hand keypoints as 3D capsules. (default: True) | BOOLEAN | No | True or False |
| `person_palette_falloff` | Per-person desaturation: track k blends toward white by 1 - falloff^k. Track 0 stays vivid; 1.0 disables falloff. (default: 0.6) | FLOAT | No | 0.1 to 1.0, step 0.05 |

### SCAIL Inputs

These parameters appear when `render_style` is "scail".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `radius_m` | Capsule radius in meters (SCAIL reference: \~0.022 m). (default: 0.022) | FLOAT | No | 0.005 to 0.2, step 0.001 |
| `hand_style` | Composite 2D OpenPose hands on top of the 3D capsule body (matches SCAIL — no 3D hand capsules). 'disabled' = no hands. 'dwpose' = solid-blue hand dots; 'openpose' = rainbow dots. Sticks stay rainbow per-finger either way. (default: "dwpose") | COMBO | No | "disabled"<br />"dwpose"<br />"openpose" |
| `face_style` | 'full' = all face landmarks (sapiens-238 if present, else rig-fallback \~30). 'eyes\_mouth' = rig-fallback subset (\~12 dots: eyes + outer lips only). 'disabled' = no face dots. (default: "disabled") | COMBO | No | "disabled"<br />"full"<br />"eyes\_mouth" |
| `person_palette_falloff` | Per-person desaturation: track k blends toward white by 1 - falloff^k. Track 0 stays vivid; 1.0 disables falloff. (default: 0.6) | FLOAT | No | 0.1 to 1.0, step 0.05 |

### Notes

* If both `width` and `height` are 0, the output uses the pose data's native image size. If only one of them is set, the other is derived while preserving the original aspect ratio. A connected `background` is resized to match the render resolution.
* When `camera_info` is connected, the pose is re-projected through that camera instead of the predicted one.
* In mesh mode, `rainbow_tilt_z` and `rainbow_tilt_x` are only available when `shader` is set to "rainbow", "rainbow\_face\_normal", or "rainbow\_face\_semantic".
* In mesh mode, when `region` is "hands\_only", the hand region filter requires the pose data to contain a hand vertex mask; if the mask is missing, the full mesh is rendered instead.
* In scail mode, hands are drawn as 2D OpenPose overlays on top of the 3D capsule body rather than as 3D capsules; setting `hand_style` to "disabled" removes them entirely.
* When the output resolution differs from the pose data's native resolution, the openpose\_2d marker and stick sizes are scaled proportionally.
* If the background has fewer frames than the pose data, the last background frame is reused for the remaining frames.
* The output contains one frame per input pose frame. If the pose data contains no frames, a single black image is returned.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The rendered frames: the pose data drawn in the selected render style, composited over the background when one is connected, or over black otherwise. One frame per input pose frame, returned as a single batched image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3DBody_Render/en.md)

***

**Source fingerprint (SHA-256):** `96556283cf07727e6b4bb3549537bf925ed771bab8607f65c93ab54a5f0e9ba5`


# SAM3DBody_Smooth - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3DBody_Smooth

Smooth SAM3D Body Pose Data reduces frame-to-frame jitter in a sequence of 3D body poses by averaging motion over time.

Smooth SAM3D Body Pose Data reduces frame-to-frame jitter in a sequence of 3D body poses by averaging motion over time. Camera and appearance data are smoothed fully, while mesh geometry is smoothed less when the subject rotates quickly, so fast spins are not flattened.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mhr_pose_data` | The MHR pose data sequence to smooth, containing model parameters, shape parameters, expression parameters, MHR70 keypoint layout, and related mesh data. | MHR\_POSE\_DATA | Yes | — |
| `strength` | Smoothing strength. 0 = raw, 1 = smoothed. (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step 0.05) |
| `method` | gaussian: symmetric weighted average, best general-purpose smoother.<br />savgol: sliding polynomial fit, preserves sharp peaks. (default: "savgol") | COMBO | Yes | "gaussian"<br />"savgol" |
| `window` | Temporal window in frames (odd values). (default: 7) | INT | Yes | 1 to 51 (odd values, step 2) |
| `rotation_threshold_degrees` | Disables smoothing for this root rotation rate (degree/frame) to preserve fast spins. 30° suits most content, low values might disable smoothing on ordinary jitter and silently impacts quality. 0 = disable. (default: 30.0) | FLOAT | Yes | 0.0 to 90.0 (step 1.0) |

Note: When `strength` is 0.0 or lower, or `window` is 1 or lower, the node returns the input data unchanged. The input must contain at least 2 frames and keypoint data; otherwise the node returns the input data unchanged. When `rotation_threshold_degrees` is 0.0, the rotation-based smoothing backoff is disabled.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mhr_pose_data` | The smoothed MHR pose data sequence with reduced frame-to-frame jitter. | MHR\_POSE\_DATA |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3DBody_Smooth/en.md)

***

**Source fingerprint (SHA-256):** `a80a1c121f1d2bc49e9112576775588d5deab4690c4cd6ec9c1f98de78457b30`


# SDPoseDrawKeypoints - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SDPoseDrawKeypoints

The SDPoseDrawKeypoints node takes pose estimation data (keypoints) and draws them as a visual skeleton on a blank canvas.

The SDPoseDrawKeypoints node takes pose estimation data (keypoints) and draws them as a visual skeleton on a blank canvas. It allows you to selectively draw different parts of the pose, such as the body, head, hands, face, and feet, with customizable line widths and point sizes. The resulting image can be used for visualization or as input for other nodes that require a pose image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `keypoints` | The pose keypoint data to be drawn. This data typically comes from a pose detection node and can contain one or more frames. | POSE\_KEYPOINT | Yes | - |
| `draw_body` | Controls whether the main body skeleton is drawn (default: True). | BOOLEAN | No | - |
| `draw_hands` | Controls whether the hand keypoints are drawn (default: True). | BOOLEAN | No | - |
| `draw_face` | Controls whether the face keypoints are drawn (default: True). | BOOLEAN | No | - |
| `draw_feet` | Controls whether the foot keypoints are drawn (default: False). | BOOLEAN | No | - |
| `stick_width` | The width of the lines used to draw the body and head skeleton (default: 4). | INT | No | 1 to 10 |
| `face_point_size` | The size of the points used to draw the face keypoints (default: 3). | INT | No | 1 to 10 |
| `score_threshold` | The minimum confidence score a keypoint must have to be drawn. Keypoints with scores below this value are ignored (default: 0.3). | FLOAT | No | 0.0 to 1.0 |
| `draw_head` | Controls whether the head keypoints (nose, eyes, ears) are drawn (default: True). | BOOLEAN | No | - |

**Note:** If the `keypoints` input is empty or `None`, the node will output a blank 64x64 image.

**Note:** `draw_body` and `draw_head` work independently. When `draw_head` is disabled, the head keypoints are not drawn even if `draw_body` is enabled. When `draw_body` is disabled but `draw_head` is enabled, only the head keypoints and the neck point are drawn. If both are disabled, no body or head keypoints are drawn.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | An image with the drawn pose keypoints. The image dimensions match the `canvas_height` and `canvas_width` specified in the input keypoint data. When the input contains multiple frames, a batch of images is returned. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SDPoseDrawKeypoints/en.md)

***

**Source fingerprint (SHA-256):** `2b2b9530b55c56e278666bd5d139bb6a1bb503b75b948a89266b9982b5a295e4`


# SDPoseFaceBBoxes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SDPoseFaceBBoxes

The SDPoseFaceBBoxes node processes pose keypoint data to detect and generate bounding boxes around human faces.

The SDPoseFaceBBoxes node processes pose keypoint data to detect and generate bounding boxes around human faces. It analyzes the 2D face keypoints for each person in a frame, calculates a bounding box based on those points, and can adjust the box's size and shape. The resulting bounding boxes are formatted to be compatible with other nodes in the SDPose workflow, such as the SDPoseKeypointExtractor.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `keypoints` | The pose keypoint data containing information about detected people and their body/face landmarks per frame. | POSE\_KEYPOINT | Yes | - |
| `scale` | Multiplier for the bounding box area around each detected face. A larger value creates a larger box. (default: 1.5) | FLOAT | No | 1.0 - 10.0 |
| `force_square` | Expand the shorter bbox axis so the crop region is always square. (default: True) | BOOLEAN | No | - |

**Note:** The `keypoints` input must be in the specific format produced by nodes like SDPoseKeypointExtractor, containing `canvas_height`, `canvas_width`, and `people` data with `face_keypoints_2d` for each person.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `bboxes` | A list of face bounding boxes for each frame. Each bounding box is defined by its top-left coordinates (`x`, `y`), `width`, and `height`. This output is compatible with the `bboxes` input of the SDPoseKeypointExtractor node. | BOUNDINGBOX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SDPoseFaceBBoxes/en.md)

***

**Source fingerprint (SHA-256):** `dc68640f46afcba4c10a907fd9467671d508cd5bac7670b35a038d159f9d8f50`


# SDPoseKeypointExtractor - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SDPoseKeypointExtractor

The SDPoseKeypointExtractor node detects human pose keypoints from input images using the SDPose model.

The SDPoseKeypointExtractor node detects human pose keypoints from input images using the SDPose model. It can process full images or specific regions defined by bounding boxes and outputs the detected keypoints in the OpenPose format, which includes the coordinates for each person and a confidence score for each keypoint.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The SDPose model used for keypoint detection. Must be a model with a `heatmap_head` attribute, specifically from the SDPose repository. | MODEL | Yes | - |
| `vae` | The VAE model used to encode the input images into the latent space for processing. | VAE | Yes | - |
| `image` | The input image or batch of images from which to extract pose keypoints. | IMAGE | Yes | - |
| `batch_size` | The number of images to process at once when running in full-image mode (i.e., when `bboxes` is not provided). This can speed up processing. (default: 16) | INT | No | 1 to 10000 |
| `bboxes` | Optional bounding boxes for more accurate detections. Required for multi-person detection. If provided, the node will extract keypoints from each specified region. | BOUNDINGBOX | No | - |

**Parameter Constraints:**

* The `model` input must be a specific SDPose model. If the provided model does not have a `heatmap_head` attribute, the node will raise an error.
* The node operates in two distinct modes based on the `bboxes` input:
  1. **Bounding Box Mode:** When `bboxes` is provided, it processes each specified region individually. This is required for detecting multiple people in a single image.
  2. **Full-Image Mode:** When `bboxes` is not provided, it processes the entire image as a batch. The `batch_size` parameter only applies in this mode.
* When `bboxes` is provided, it must be a list of bounding boxes. If there are fewer bounding box lists than images, the last list is reused for remaining images.
* Bounding boxes with zero width or height (e.g., `x2 <= x1` or `y2 <= y1`) are skipped.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `keypoints` | Keypoints in OpenPose frame format (canvas\_width, canvas\_height, people). The output contains the detected persons, each with an array of keypoint coordinates (x, y) and their corresponding confidence scores. | POSE\_KEYPOINT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SDPoseKeypointExtractor/en.md)

***

**Source fingerprint (SHA-256):** `5e199e9d08a46d934c6d1f4b1a411f0ca95eb5e7f85ec39f59a058c9be598e9f`


# SaveAnimatedPNG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAnimatedPNG

The SaveAnimatedPNG node is designed for creating and saving animated PNG images from a sequence of frames.

The SaveAnimatedPNG node is designed for creating and saving animated PNG images from a sequence of frames. It handles the assembly of individual image frames into a cohesive animation, allowing for customization of frame duration, looping, and metadata inclusion.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `images` | A list of images to be processed and saved as an animated PNG. Each image in the list represents a frame in the animation. | `IMAGE` |
| `filename_prefix` | Specifies the base name for the output file, which will be used as a prefix for the generated animated PNG files. | `STRING` |
| `fps` | The frames per second rate for the animation, controlling how quickly the frames are displayed. | `FLOAT` |
| `compress_level` | The level of compression applied to the animated PNG files, affecting file size and image clarity. | `INT` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `ui` | Provides a UI component displaying the generated animated PNG images and indicating whether the animation is single-frame or multi-frame. | N/A |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveAnimatedPNG/en.md)


# SaveAnimatedWEBP - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAnimatedWEBP

This node is designed for saving a sequence of images as an animated WEBP file.

This node is designed for saving a sequence of images as an animated WEBP file. It handles the aggregation of individual frames into a cohesive animation, applying specified metadata, and optimizing the output based on quality and compression settings.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `images` | A list of images to be saved as frames in the animated WEBP. This parameter is essential for defining the visual content of the animation. | `IMAGE` |
| `filename_prefix` | Specifies the base name for the output file, which will be appended with a counter and the '.webp' extension. This parameter is crucial for identifying and organizing the saved files. | `STRING` |
| `fps` | The frames per second rate for the animation, influencing the playback speed. | `FLOAT` |
| `lossless` | A boolean indicating whether to use lossless compression, affecting the file size and quality of the animation. | `BOOLEAN` |
| `quality` | A value between 0 and 100 that sets the compression quality level, with higher values resulting in better image quality but larger file sizes. | `INT` |
| `method` | Specifies the compression method to use, which can impact the encoding speed and file size. | COMBO\[STRING] |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `ui` | Provides a UI component displaying the saved animated WEBP images along with their metadata, and indicates whether the animation is enabled. | N/A |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveAnimatedWEBP/en.md)


# SaveImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveImage

The SaveImage node saves the input images as PNG files to your ComfyUI output directory.

The SaveImage node saves the input images as PNG files to your ComfyUI output directory. It can embed workflow metadata, such as the prompt, into each saved file, and it returns the images unchanged so they can still be used by other nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The images to save. | IMAGE | Yes | - |
| `filename_prefix` | The prefix for the file to save. This may include formatting information such as `%date:yyyy-MM-dd%` or `%Empty Latent Image.width%` to include values from nodes (default: "ComfyUI"). | STRING | Yes | - |

The node also receives two hidden inputs, `prompt` and `extra_pnginfo`, which are automatically populated by ComfyUI with the workflow prompt and extra PNG information. When metadata is enabled, this information is embedded as text metadata in each saved PNG file.

The file name for each saved image is built from `filename_prefix`, an optional `%batch_num%` placeholder that is replaced with the image's position in the batch, and a five-digit counter, for example `ComfyUI_00001_.png`. Images are written with PNG compression level 4.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The original input images, returned unchanged after being saved to disk. | IMAGE |
| `ui` | A UI-only result containing the list of saved image files (filename, subfolder, and type) for display in the frontend. | UI\_RESULT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveImage/en.md)

***

**Source fingerprint (SHA-256):** `4a718495fd0801304d2bc3afee859e6b9839f9aba8e929bb9ba90ae6a229a750`


# SaveImageAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveImageAdvanced

The Save Image (Advanced) node saves the input images to your ComfyUI output directory with advanced control over file format, bit depth, and color space.

The **Save Image (Advanced)** node saves the input images to your ComfyUI output directory with advanced control over file format, bit depth, and color space. It supports saving as PNG, EXR, or AVIF files (including animated AVIF) and can embed workflow metadata into the saved files.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The images to save. | IMAGE | Yes | - |
| `filename_prefix` | The prefix for the file to save. May include formatting tokens such as `%date:yyyy-MM-dd%` or `%Empty Latent Image.width%`. (default: "ComfyUI") | STRING | Yes | - |
| `format` | The file format in which to save the image. Selecting a format reveals additional options for that format. | DYNAMIC\_COMBO | Yes | `"png"`<br />`"exr"`<br />`"avif"` |

### PNG Inputs

These options appear when `format` is set to `"png"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `bit_depth` | The bit depth for the saved PNG file. (default: "8-bit") | COMBO | Yes (conditional) | `"8-bit"`<br />`"16-bit"` |
| `input_color_space` | Colorspace of the input tensor. Only sRGB is available for PNG format. (default: "sRGB") | COMBO | Yes (conditional) | `"sRGB"` |

### EXR Inputs

These options appear when `format` is set to `"exr"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `bit_depth` | The bit depth for the saved EXR file. (default: "32-bit float") | COMBO | Yes (conditional) | `"32-bit float"` |
| `input_color_space` | Colorspace of the input tensor. The EXR is always written as scene-linear in the matching gamut.<br />`"sRGB"` — input is sRGB-encoded Rec.709; the inverse sRGB EOTF is applied.<br />`"HDR"` — input is HLG-encoded Rec.2020 (BT.2100); the inverse HLG OETF is applied to get scene-linear light.<br />`"linear"` — input is already scene-linear (Rec.709 primaries); written through unchanged. Use this for renderer/compositor output. (default: "sRGB") | COMBO | Yes (conditional) | `"sRGB"`<br />`"HDR"`<br />`"linear"` |

### AVIF Inputs

These options appear when `format` is set to `"avif"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `bit_depth` | The bit depth for the saved AVIF file. Auto uses 8-bit YUV420 for sRGB and 10-bit YUV420 for HDR. (default: "auto") | COMBO | Yes (conditional) | `"auto"`<br />`"8-bit YUV420"`<br />`"10-bit YUV420"` |
| `input_color_space` | Colorspace of the input images. HDR selects BT.2020/HLG and HDR PQ selects BT.2020/PQ. (default: "sRGB") | COMBO | Yes (conditional) | `"sRGB"`<br />`"HDR"`<br />`"HDR PQ"` |
| `crf` | Lower values produce higher quality and larger files. (default: 18) | INT | Yes (conditional) | 1 to 63 |
| `save_mode` | The save mode for the AVIF file. `"still images"` saves each image in the batch as a separate still file; `"animated"` saves the entire batch as a single animated AVIF file and reveals `fps` and `loop_count`. (default: "still images") | DYNAMIC\_COMBO | Yes (conditional) | `"still images"`<br />`"animated"` |

### AVIF Animated Options

These options appear when `save_mode` is set to `"animated"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `fps` | The frame rate of the animation. (default: 6.0) | FLOAT | Yes (conditional) | 0.01 to 1000.0 |
| `loop_count` | Number of times to loop the animation. 0 loops forever. (default: 0) | INT | Yes (conditional) | 0 to 1000 |

**Notes on Parameter Dependencies:**

* The format-specific parameters (`bit_depth`, `input_color_space`, and for AVIF also `crf` and `save_mode`) are only available when a specific `format` is selected.
* For PNG format, only "8-bit" and "16-bit" bit depths are available, and only "sRGB" color space.
* For EXR format, only "32-bit float" bit depth is available, with "sRGB", "HDR", or "linear" color spaces.
* For AVIF format, `fps` and `loop_count` are only available when `save_mode` is set to `"animated"`.
* PNG and EXR images must have 1 (grayscale), 3 (RGB), or 4 (RGBA) channels; other channel counts are not supported and raise an error.
* AVIF supports only 1-channel grayscale and 3-channel RGB images; RGBA (alpha) images are not supported and raise an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The input images, passed through unchanged. The node's UI output provides a list of saved image results, each containing the filename, subfolder, and type ("output"). For animated AVIF with more than one image, the UI output also includes an `animated` flag. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveImageAdvanced/en.md)

***

**Source fingerprint (SHA-256):** `d3df3caca99d58d973d0bc2ff7c22c4626185d390ec2acf870d4014331c4c335`


# SaveImageDataSetToFolder - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveImageDataSetToFolder

This node saves a list of images to a specified folder inside ComfyUI's output directory.

This node saves a list of images to a specified folder inside ComfyUI's output directory. It writes each image to disk as a PNG file using a configurable filename prefix. This node is deprecated and superseded by existing Save Image nodes, where the target folder can be specified in the filename prefix.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | List of images to save. | IMAGE | Yes | N/A |
| `folder_name` | Name of the folder to save images to (inside output directory). Default: "dataset". | STRING | No | N/A |
| `filename_prefix` | Prefix for saved image filenames. Default: "image". Advanced parameter. | STRING | No | N/A |
| `mode` | Whether to overwrite existing files or increment filenames to avoid overwriting. Default: "overwrite". | COMBO | No | "overwrite"<br />"increment" |

**Notes:**

* The `images` input is a list, so multiple images can be saved in a single run.
* The `folder_name`, `filename_prefix`, and `mode` parameters are scalar values; if a list is connected, only the first value from that list is used.
* The `folder_name` must resolve to a location inside ComfyUI's output directory. Values that escape the output directory (for example, paths containing `..` or absolute paths, drive letters, or symlink escapes) are rejected with an error.
* In "overwrite" mode, files are saved as `{prefix}_00000.png`, `{prefix}_00001.png`, and so on, replacing any existing files. In "increment" mode, a counter is inserted into the filename so existing files are not overwritten.
* Only PNG output is supported.

## Outputs

This node does not have any outputs. It is an output node that performs a save operation to the filesystem.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveImageDataSetToFolder/en.md)

***

**Source fingerprint (SHA-256):** `ee92340ca1581edcfe1cc1d5659ee705ad53425bed6658161a56e6d130680e50`


# SaveImageTextDataSetToFolder - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveImageTextDataSetToFolder

Save Image-Text (to Folder) saves a dataset of image and text caption pairs to a folder inside ComfyUI's output directory.

Save Image-Text (to Folder) saves a dataset of image and text caption pairs to a folder inside ComfyUI's output directory. Each image is written as a PNG file, and its matching caption is written as a TXT file with the same base filename, so every image ends up paired with its description.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | List of images to save. | IMAGE | Yes | - |
| `texts` | List of text captions to save. This input is optional. | STRING | No | - |
| `folder_name` | Name of the folder to save images to (inside output directory). (default: "dataset") | STRING | Yes | - |
| `filename_prefix` | Prefix for saved image filenames. (default: "image") | STRING | Yes | - |
| `mode` | Whether to overwrite existing files or increment filenames to avoid overwriting. (default: "overwrite") | COMBO | Yes | "overwrite"<br />"increment" |

**Note:** The `images` input is a list, and the node receives both `images` and `texts` as lists. The `texts` input is optional; if provided, it should be a list of text captions and should contain the same number of items as `images`. Each caption is saved as a `.txt` file corresponding to its paired image. In `overwrite` mode, files are named `{filename_prefix}_{index}.png` and replace any existing files with the same name. In `increment` mode, a unique counter is added to the filenames so existing files are not overwritten. The `folder_name` must resolve to a path inside the output directory; folder names that try to escape it (for example with `..`) are rejected.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| - | This node returns no data. It saves files directly to the filesystem. | - |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveImageTextDataSetToFolder/en.md)

***

**Source fingerprint (SHA-256):** `46c5a04ba1befedf62b75abbff2442dde934048f365fa7e2604ea37e70d8fdcb`


# SaveSVGNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveSVGNode

Save SVG files on disk.

Save SVG files on disk. This node takes SVG data as input and writes it to the ComfyUI output directory, automatically handling file naming with counter suffixes. When workflow prompt information is available, it is embedded directly into the SVG file as a metadata element.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `svg` | The SVG data to be saved to disk | SVG | Yes | - |
| `filename_prefix` | The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes. (default: "svg/ComfyUI") | STRING | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `svg` | The original SVG data, passed through after saving | SVG |
| `ui` | Saved file information including filename, subfolder, and type for display in the ComfyUI interface | DICT |

**Note:** This node automatically embeds workflow metadata (prompt and extra PNG information) into the SVG file when available. The metadata is inserted as a CDATA section within the SVG's metadata element. Files are saved using the pattern `filename_prefix_00001_.svg`; when processing a batch, `%batch_num%` in the prefix is replaced with the index of the current batch item. The node is an output node, so it produces a saved result in the output folder even though the file itself is not displayed as an image preview.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveSVGNode/en.md)

***

**Source fingerprint (SHA-256):** `365137d5dacab3142c25945fd97bce4b827d9d7d4dd839986c68f491a28fb805`


# SeedVR2PostProcessing - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SeedVR2PostProcessing

This node aligns the generated image with the original resized image and applies optional color correction.

This node aligns the generated image with the original resized image and applies optional color correction. It takes the output from a SeedVR2 upscaling process and adjusts it to match the colors and dimensions of the original reference image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The generated image to process. | IMAGE | Yes | - |
| `original_resized_images` | The original resized image before pre-processing, used as reference. | IMAGE | Yes | - |
| `color_correction_method` | Method to match the generated image colors to the original image. lab: transfer color in CIELAB space, preserving detail (most faithful). wavelet: transfer low-frequency color, keeping upscaled high-frequency detail. adain: match per-channel mean/std (fastest, global tint). none: skip color transfer (geometry alignment only). (default: "lab") | COMBO | Yes | `"lab"`<br />`"wavelet"`<br />`"adain"`<br />`"none"` |

**Note:** Both inputs may be 4-D (batch, height, width, channels) or 5-D (batch, frames, height, width, channels) tensors. The node crops both to the smallest batch, frame count, height, and width, so they do not need to match exactly. When a color correction method other than `none` is used, the reference image is resized to the output size first. Color correction is processed in memory-aware chunks, backing off to a smaller chunk size if memory runs out. Output height and width are rounded down to even numbers. If the reference image has an alpha channel (4 channels), that alpha channel is preserved and applied to the output.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The aligned, color-corrected image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SeedVR2PostProcessing/en.md)

***

**Source fingerprint (SHA-256):** `00a3a3ef06edc7e0eca8f67a96095920a3e0e885dac3fb676d081e4c4c30bec5`


# SeedVR2Preprocess - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SeedVR2Preprocess

This node prepares a resized image or video for the SeedVR2 model by padding it to the shape the model expects.

This node prepares a resized image or video for the SeedVR2 model by padding it to the shape the model expects. Pixel values are clamped to the 0-1 range, the height and width are padded to multiples of 16, and the frame count is padded by repeating the last frame until it follows a 4n+1 pattern (1, 5, 9, 13, ...). The alpha channel is dropped during processing; the companion Post-Process SeedVR2 Output node restores it later from the original resized image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `resized_images` | The resized image to process. | IMAGE | Yes | - |

Note: The input can be a single frame, a sequence of frames, or a batch of videos (4-D or 5-D IMAGE tensors). If it has more than 3 channels, the alpha channel is dropped and only RGB is kept. The shorter edge of the input must be at least 2 pixels. Spatial padding is filled with black (value 0), and valid frame counts follow a 4n+1 pattern (1, 5, 9, 13, ...).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The padded image for VAE encoding. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SeedVR2Preprocess/en.md)

***

**Source fingerprint (SHA-256):** `f4fa433d299feba40696f27ff365c59988e5102112f09536724b5db5b09416bb`


# SolidMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SolidMask

The SolidMask node generates a uniform mask with a specified value across its entire area.

The SolidMask node generates a uniform mask with a specified value across its entire area. It's designed to create masks of specific dimensions and intensity, useful in various image processing and masking tasks.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `value` | Specifies the intensity value of the mask, affecting its overall appearance and utility in subsequent operations. | FLOAT |
| `width` | Determines the width of the generated mask, directly influencing its size and aspect ratio. | INT |
| `height` | Sets the height of the generated mask, affecting its size and aspect ratio. | INT |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `mask` | Outputs a uniform mask with the specified dimensions and value. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SolidMask/en.md)


# TextEncodeAceStepAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeAceStepAudio

The TextEncodeAceStepAudio node processes text inputs for audio conditioning by combining tags and lyrics into tokens, then encoding them with adjustable lyrics strength.

The TextEncodeAceStepAudio node processes text inputs for audio conditioning by combining tags and lyrics into tokens, then encoding them with adjustable lyrics strength. It takes a CLIP model along with text descriptions and lyrics, tokenizes them together, and generates conditioning data suitable for audio generation tasks. The node allows fine-tuning the influence of lyrics through a strength parameter that controls their impact on the final output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for tokenization and encoding | CLIP | Yes | - |
| `tags` | Text tags or descriptions for audio conditioning (supports multiline input and dynamic prompts) | STRING | Yes | - |
| `lyrics` | Lyrics text for audio conditioning (supports multiline input and dynamic prompts) | STRING | Yes | - |
| `lyrics_strength` | Controls the strength of lyrics influence on the conditioning output (default: 1.0, step: 0.01) | FLOAT | Yes | 0.0 - 10.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `conditioning` | The encoded conditioning data containing processed text tokens with applied lyrics strength | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeAceStepAudio/en.md)

***

**Source fingerprint (SHA-256):** `2226c9f25dd26bf454bcce2e298d6d261dace5a9bbed164a2fcf0e1204d7c3f4`


# TextEncodeAceStepAudio1.5 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeAceStepAudio1.5

The TextEncodeAceStepAudio1.5 node prepares text and audio-related metadata for use with the AceStepAudio 1.5 model.

The TextEncodeAceStepAudio1.5 node prepares text and audio-related metadata for use with the AceStepAudio 1.5 model. It takes descriptive tags, lyrics, and musical parameters, then uses a CLIP model to convert them into a conditioning format suitable for audio generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used to tokenize and encode the input text. | CLIP | Yes | N/A |
| `tags` | Descriptive tags for the audio, such as genre, mood, or instruments. Supports multiline input and dynamic prompts. | STRING | Yes | N/A |
| `lyrics` | The lyrics for the audio track. Supports multiline input and dynamic prompts. | STRING | Yes | N/A |
| `seed` | A random seed value for reproducible generation. Has a control\_after\_generate widget. Default: 0. | INT | No | 0 to 18446744073709551615 |
| `bpm` | The beats per minute (BPM) for the generated audio. Default: 120. | INT | No | 10 to 300 |
| `duration` | The desired duration of the audio in seconds. Default: 120.0. | FLOAT | No | 0.0 to 2000.0 |
| `timesignature` | The musical time signature. | COMBO | No | `"2"`<br />`"3"`<br />`"4"`<br />`"6"` |
| `language` | The language of the input text. Default: "en". | COMBO | No | `"ar"`<br />`"az"`<br />`"bg"`<br />`"bn"`<br />`"ca"`<br />`"cs"`<br />`"da"`<br />`"de"`<br />`"el"`<br />`"en"`<br />`"es"`<br />`"fa"`<br />`"fi"`<br />`"fr"`<br />`"he"`<br />`"hi"`<br />`"hr"`<br />`"ht"`<br />`"hu"`<br />`"id"`<br />`"is"`<br />`"it"`<br />`"ja"`<br />`"ko"`<br />`"la"`<br />`"lt"`<br />`"ms"`<br />`"ne"`<br />`"nl"`<br />`"no"`<br />`"pa"`<br />`"pl"`<br />`"pt"`<br />`"ro"`<br />`"ru"`<br />`"sa"`<br />`"sk"`<br />`"sr"`<br />`"sv"`<br />`"sw"`<br />`"ta"`<br />`"te"`<br />`"th"`<br />`"tl"`<br />`"tr"`<br />`"uk"`<br />`"ur"`<br />`"vi"`<br />`"yue"`<br />`"zh"`<br />`"unknown"` |
| `keyscale` | The musical key and scale (major or minor). | COMBO | No | `"C major"`<br />`"C# major"`<br />`"Db major"`<br />`"D major"`<br />`"D# major"`<br />`"Eb major"`<br />`"E major"`<br />`"F major"`<br />`"F# major"`<br />`"Gb major"`<br />`"G major"`<br />`"G# major"`<br />`"Ab major"`<br />`"A major"`<br />`"A# major"`<br />`"Bb major"`<br />`"B major"`<br />`"C minor"`<br />`"C# minor"`<br />`"Db minor"`<br />`"D minor"`<br />`"D# minor"`<br />`"Eb minor"`<br />`"E minor"`<br />`"F minor"`<br />`"F# minor"`<br />`"Gb minor"`<br />`"G minor"`<br />`"G# minor"`<br />`"Ab minor"`<br />`"A minor"`<br />`"A# minor"`<br />`"Bb minor"`<br />`"B minor"` |
| `generate_audio_codes` | Enable the LLM that generates audio codes. This can be slow but will increase the quality of the generated audio. Turn this off if you are giving the model an audio reference. Default: True. | BOOLEAN | No | N/A |
| `cfg_scale` | The classifier-free guidance scale. Higher values make the output more closely follow the prompt. Default: 2.0. | FLOAT | No | 0.0 to 100.0 |
| `temperature` | A sampling temperature. Lower values make the output more deterministic. Default: 0.85. | FLOAT | No | 0.0 to 2.0 |
| `top_p` | The nucleus sampling probability (top-p). Default: 0.9. | FLOAT | No | 0.0 to 2000.0 |
| `top_k` | The number of highest probability tokens to consider (top-k). Default: 0. | INT | No | 0 to 100 |
| `min_p` | The minimum probability threshold for token sampling (min-p). Default: 0.000. | FLOAT | No | 0.0 to 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The conditioning data, which contains the encoded text and audio parameters for the AceStepAudio 1.5 model. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeAceStepAudio1.5/en.md)

***

**Source fingerprint (SHA-256):** `4bc97ec6220514b71fafde610339f2dca4ded26f68b541ed43ea492f127321f8`


# TextEncodeBooguEdit - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeBooguEdit

This node prepares conditioning for image editing with Boogu.

This node prepares conditioning for image editing with Boogu. It processes reference images to create both positive and negative conditioning outputs. The reference image is used twice: vision tokens from the image are added only to the positive conditioning to amplify the edit instruction, while a VAE reference latent is added to both positive and negative conditioning so it cancels out under CFG, preserving the original image identity; the tokenizer automatically selects the appropriate system prompt based on the presence of images and empty negative prompts.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for text encoding | CLIP | Yes | |
| `prompt` | The text prompt describing the desired edit. Supports multiline text and dynamic prompts. | STRING | Yes | |
| `negative_prompt` | The text prompt describing what to avoid in the edit. Can be left empty to drop negative conditioning. Advanced parameter. | STRING | Yes | |
| `vae` | The VAE model used to encode reference images into latent space. Needed to add reference latents to the conditioning outputs. | VAE | No | |
| `images` | Reference image(s) to edit. Boogu focuses on one reference per sample; more are allowed. | IMAGE | No | Up to 16 images |

Reference latents are added to both conditioning outputs only when `vae` is provided together with at least one reference `image`. If `vae` is omitted, the positive output still receives vision tokens from the reference images, but neither output includes reference latents.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Conditioning containing both the text prompt with vision tokens and the reference latents | CONDITIONING |
| `negative` | Conditioning containing the negative text prompt and the reference latents | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeBooguEdit/en.md)

***

**Source fingerprint (SHA-256):** `170979acf5b2e9f25f96231a4b23a4376cfddcd4bda2fdd6e03528417e6931b0`


# ThresholdMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ThresholdMask

The ThresholdMask node converts a mask to a binary mask by applying a threshold value.

The ThresholdMask node converts a mask to a binary mask by applying a threshold value. It compares each pixel in the input mask against the specified threshold value and creates a new mask where pixels above the threshold become 1 (white) and pixels below or equal to the threshold become 0 (black).

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mask` | The input mask to be processed | MASK | Yes | - |
| `value` | The threshold value for binarization (default: 0.5) | FLOAT | Yes | 0.0 - 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mask` | The resulting binary mask after thresholding | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ThresholdMask/en.md)

***

**Source fingerprint (SHA-256):** `eff4479b70c1ca87ba9ba17b771edf5d816cf13c12ac0767cd7ee79d18e326c3`


# VOIDQuadmaskPreprocess - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VOIDQuadmaskPreprocess

Documentation for VOIDQuadmaskPreprocess node.

## Overview

The VOIDQuadmaskPreprocess node prepares a mask for VOID inpainting by converting it into a special four-level "quadmask." It takes an input mask, optionally dilates the primary region, then quantizes the mask values into four distinct levels representing different semantic regions (primary object, overlap, affected area, and background). Finally, it inverts and normalizes the mask so the output values are in the range \[0, 1], where 1.0 indicates the area to remove and 0.0 indicates the area to keep.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mask` | The input mask to be preprocessed. | MASK | Yes | N/A |
| `dilate_width` | Dilation radius for the primary mask region. A value of 0 means no dilation is applied. (default: 0) | INT | No | 0 to 50 (step: 1) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `quadmask` | The preprocessed quadmask with values in \[0, 1], representing four discrete levels: 1.0 (primary object to remove), \~0.75 (overlap of primary and affected), \~0.50 (affected region), and 0.0 (background to keep). | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VOIDQuadmaskPreprocess/en.md)

***

**Source fingerprint (SHA-256):** `a972ff74686baaa3a3659a74517d3b6f7335e8f62d09be9329d0e71d1fad137a`


# WanDancerPadKeyframes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanDancerPadKeyframes

Documentation for WanDancerPadKeyframes node.

## Overview

This node prepares a sequence of keyframes for a specific segment of a longer video generation process. It takes a batch of input images and an audio track, calculates how many total frames the full video should have based on the audio duration, and then distributes the input images as keyframes across the chosen segment, padding the rest with blank frames. It also extracts the corresponding portion of the audio for that segment.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The input images to be distributed as keyframes. | IMAGE | Yes | Batch of images |
| `segment_length` | Length of this segment in frames (default: 149). | INT | Yes | 1 to 10000 |
| `segment_index` | Which segment this is (0 for first, 1 for second, etc., default: 0). | INT | Yes | 0 to 100 |
| `audio` | Audio to calculate total output frames from and extract segment audio. | AUDIO | Yes | Audio data |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `keyframes_sequence` | Padded keyframe sequence for the specified segment. | IMAGE |
| `keyframes_mask` | Mask indicating valid frames (1 for keyframe positions, 0 for padded positions). | MASK |
| `audio_segment` | Audio segment for this video segment. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanDancerPadKeyframes/en.md)

***

**Source fingerprint (SHA-256):** `93393e39cb1968b6e8720dfad213c16c534857bcfafcc577be64e0733ab3a760`


# WanDancerPadKeyframesList - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanDancerPadKeyframesList

Documentation for WanDancerPadKeyframesList node.

## Overview

This node takes a sequence of images and an optional audio track, and splits them into a specified number of padded segments. It is designed to prepare keyframe sequences for video generation, where each segment is padded to a consistent length and a corresponding mask is created to indicate which frames are valid.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The input image sequence to be split into segments. | IMAGE | Yes | N/A |
| `segment_length` | Length of each segment in frames (default: 149). | INT | Yes | 1 to 10000 |
| `num_segments` | How many padded segments to emit as lists (default: 1). | INT | Yes | 1 to 100 |
| `audio` | Audio to slice for each emitted segment. | AUDIO | No | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `keyframes_sequence` | A list of padded keyframe sequences, one for each segment. | IMAGE |
| `keyframes_mask` | A list of masks indicating valid frames for each segment. | MASK |
| `audio_segment` | A list of audio segments, one for each video segment. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanDancerPadKeyframesList/en.md)

***

**Source fingerprint (SHA-256):** `f9918166a75f688f1de6a09008780bc629bbdfb3b8d547de9ba8661ef07fc97e`


# WebcamCapture - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WebcamCapture

The WebcamCapture node captures images from a webcam device and converts them into a format that can be used within ComfyUI workflows.

The WebcamCapture node captures images from a webcam device and converts them into a format that can be used within ComfyUI workflows. It inherits from the LoadImage node and provides options to control the capture dimensions and timing. When enabled, the node can capture new images each time the workflow queue is processed.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The webcam input source to capture images from | WEBCAM | Yes | - |
| `width` | The desired width for the captured image (default: 0, uses webcam's native resolution) | INT | Yes | 0 to MAX\_RESOLUTION |
| `height` | The desired height for the captured image (default: 0, uses webcam's native resolution) | INT | Yes | 0 to MAX\_RESOLUTION |
| `capture_on_queue` | When enabled, captures a new image each time the workflow queue is processed (default: True) | BOOLEAN | Yes | - |

**Note:** When both `width` and `height` are set to 0, the node uses the webcam's native resolution. Setting either dimension to a non-zero value will resize the captured image accordingly.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The captured webcam image converted to ComfyUI's image format | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WebcamCapture/en.md)

***

**Source fingerprint (SHA-256):** `551368150fc293309f917eabaa066f223b1fa1a016ffd3643b57b80c83f812cc`


# TrimVideoLatent Node
Source: https://docs.comfy.org/built-in-nodes/latent/video/trim-video-latent

Trim video frames in latent space

<img alt="ComfyUI TrimVideoLatent Node" />

The TrimVideoLatent node is used to trim video frames in latent space (LATENT). It is commonly used when processing video latent sequences to remove unwanted frames from the beginning, achieving "forward trimming" of the video.

Basic usage: Input the video latent data to be trimmed into samples, and set trim\_amount to the number of frames to trim. The node will trim the specified number of frames from the beginning of the video and output the remaining latent sequence.
Typical scenarios: Used in video generation, video editing and other scenarios to remove unwanted leading frames, or to work with other nodes to achieve video segment splicing and processing.

## Parameters

### Input Parameters

| Parameter | Type | Required | Default | Description |
| - | - | - | - | - |
| samples | LATENT | Yes | None | Input latent video data |
| trim\_amount | INT | Yes | 0 | Number of frames to trim (from start) |

### Output Parameters

| Parameter | Type | Description |
| - | - | - |
| samples | LATENT | Trimmed video latent data |

## Usage Example

<Card title="Wan2.1 VACE Video Generation Workflow Example" icon="book" href="/tutorials/video/wan/vace">
  Wan2.1 VACE Video Generation Workflow Example
</Card>

### Source Code

```python theme={null}
class TrimVideoLatent:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": { "samples": ("LATENT",),
                              "trim_amount": ("INT", {"default": 0, "min": 0, "max": 99999}),
                             }}

    RETURN_TYPES = ("LATENT",)
    FUNCTION = "op"

    CATEGORY = "latent/video"

    EXPERIMENTAL = True

    def op(self, samples, trim_amount):
        samples_out = samples.copy()

        s1 = samples["samples"]
        samples_out["samples"] = s1[:, :, trim_amount:]
        return (samples_out,)

```


# CLIPTextEncodeHiDream - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodeHiDream

The CLIPTextEncodeHiDream node processes four separate text inputs using different language models (CLIP-L, CLIP-G, T5-XXL, and LLaMA) and combines them into a single conditioning 

The CLIPTextEncodeHiDream node processes four separate text inputs using different language models (CLIP-L, CLIP-G, T5-XXL, and LLaMA) and combines them into a single conditioning output. It tokenizes each text input with its corresponding model and encodes them together using a scheduled encoding approach, enabling more sophisticated text conditioning by leveraging multiple language models simultaneously.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for tokenization and encoding | CLIP | Yes | - |
| `clip_l` | Text input for CLIP-L model processing. Supports multiline text and dynamic prompts. | STRING | Yes | - |
| `clip_g` | Text input for CLIP-G model processing. Supports multiline text and dynamic prompts. | STRING | Yes | - |
| `t5xxl` | Text input for T5-XXL model processing. Supports multiline text and dynamic prompts. | STRING | Yes | - |
| `llama` | Text input for LLaMA model processing. Supports multiline text and dynamic prompts. | STRING | Yes | - |

**Note:** All four text inputs (`clip_l`, `clip_g`, `t5xxl`, and `llama`) are required for proper functioning, as each contributes to the final conditioning output through the scheduled encoding process.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The combined conditioning output from all processed text inputs, encoded using the scheduled encoding method | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeHiDream/en.md)

***

**Source fingerprint (SHA-256):** `c5e269c17bd2dd7d7171c02598a87983a988d953dd7df285978fc25a9c896e46`


# CLIPTextEncodeKandinsky5 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodeKandinsky5

The CLIP Text Encode (Kandinsky 5) node prepares text prompts for use with the Kandinsky 5 model.

The CLIP Text Encode (Kandinsky 5) node prepares text prompts for use with the Kandinsky 5 model. It takes two separate text inputs, tokenizes them with a provided CLIP model, and combines them into a single conditioning output that guides the image generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used to tokenize and encode the text prompts. | CLIP | Yes | |
| `clip_l` | The primary text prompt. This input supports multiline text and dynamic prompts. | STRING | Yes | |
| `qwen25_7b` | The secondary text prompt. This input supports multiline text and dynamic prompts. | STRING | Yes | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The combined conditioning data generated from both text prompts, ready to be fed into a Kandinsky 5 model for image generation. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeKandinsky5/en.md)

***

**Source fingerprint (SHA-256):** `d988c47ab9a5f01549a3ae01b365d39e9fa2464bb69ea018ec20151939dcfc56`


# CLIPTextEncodeLumina2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodeLumina2

This node encodes a system prompt and a user prompt using a CLIP model into an embedding that can be used to guide the diffusion model towards generating specific images.

This node encodes a system prompt and a user prompt using a CLIP model into an embedding that can be used to guide the diffusion model towards generating specific images. It combines a pre-defined Lumina 2 system prompt with your custom text prompt and processes them through the CLIP model to create conditioning data for image generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `system_prompt` | Lumina2 provide two types of system prompts: Superior: You are an assistant designed to generate superior images with the superior degree of image-text alignment based on textual prompts or user prompts. Alignment: You are an assistant designed to generate high-quality images with the highest degree of image-text alignment based on textual prompts. | COMBO | Yes | `"superior"`<br />`"alignment"` |
| `user_prompt` | The text to be encoded. Supports multiline input and dynamic prompts. | STRING | Yes | N/A |
| `clip` | The CLIP model used for encoding the text. | CLIP | Yes | N/A |

**Note:** The `clip` input is required and cannot be None. If the clip input is invalid, the node will raise an error indicating that the checkpoint may not contain a valid CLIP or text encoder model.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | A conditioning containing the embedded text used to guide the diffusion model. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeLumina2/en.md)

***

**Source fingerprint (SHA-256):** `0c7540e6232c93b0f76c4903f5646e00a639ccb0b7720f70b5ac727513358a02`


# CLIPTextEncodePixArtAlpha - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodePixArtAlpha

Encodes text and sets the resolution conditioning for PixArt Alpha.

Encodes text and sets the resolution conditioning for PixArt Alpha. This node processes text input and adds width and height information to create conditioning data specifically for PixArt Alpha models. It does not apply to PixArt Sigma models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width dimension for resolution conditioning (default: 1024) | INT | Yes | 0 to MAX\_RESOLUTION |
| `height` | The height dimension for resolution conditioning (default: 1024) | INT | Yes | 0 to MAX\_RESOLUTION |
| `text` | Text input to be encoded. Supports multiline input and dynamic prompts. | STRING | Yes | - |
| `clip` | CLIP model used for tokenization and encoding | CLIP | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Encoded conditioning data with text tokens and resolution information | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodePixArtAlpha/en.md)

***

**Source fingerprint (SHA-256):** `d25a4117d39e3528cd0f64bc34462cd7b4076c67cb4e454c77fcc66490f89be6`


# CLIPTextEncodeSD3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodeSD3

CLIPTextEncodeSD3 processes text inputs for Stable Diffusion 3 models by encoding multiple text prompts using different CLIP models.

CLIPTextEncodeSD3 processes text inputs for Stable Diffusion 3 models by encoding multiple text prompts using different CLIP models. It handles three separate text inputs (`clip_g`, `clip_l`, and `t5xxl`) and provides options for managing empty text padding. The node ensures proper token alignment between different text inputs and returns conditioning data suitable for SD3 generation pipelines.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for text encoding | CLIP | Yes | - |
| `clip_l` | Text input for the local CLIP model. Supports multiline text and dynamic prompts. | STRING | Yes | - |
| `clip_g` | Text input for the global CLIP model. Supports multiline text and dynamic prompts. | STRING | Yes | - |
| `t5xxl` | Text input for the T5-XXL model. Supports multiline text and dynamic prompts. | STRING | Yes | - |
| `empty_padding` | Controls how empty text inputs are handled. When set to "none", empty text inputs for `clip_g`, `clip_l`, or `t5xxl` result in empty token lists instead of padding. When set to "empty\_prompt", empty inputs are tokenized as empty prompts (standard padding behavior). This is an advanced parameter (default: "none"). | COMBO | Yes | `"none"`<br />`"empty_prompt"` |

**Parameter Constraints:**

* When `empty_padding` is set to "none", empty text inputs for `clip_g`, `clip_l`, or `t5xxl` result in empty token lists instead of padding
* The node automatically balances token lengths between `clip_l` and `clip_g` inputs by padding the shorter one with empty tokens when lengths differ
* All text inputs support dynamic prompts and multiline text entry

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The encoded text conditioning data ready for use in SD3 generation pipelines | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeSD3/en.md)

***

**Source fingerprint (SHA-256):** `874869bac024e6b5ac6b4bf4f79c31bb750e54f7096f6638647aac6b95bb202f`


# CLIPTextEncodeFlux - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipTextEncodeFlux

CLIPTextEncodeFlux is a text encoding node designed for the Flux architecture.

`CLIPTextEncodeFlux` is a text encoding node designed for the Flux architecture. It processes two separate text inputs through different encoders—CLIP-L and T5XXL—and combines them with a guidance scale to produce a unified conditioning output for image generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | A CLIP model that supports the Flux architecture, including both CLIP-L and T5XXL encoders. | CLIP | Yes | - |
| `clip_l` | Text input processed by the CLIP-L encoder. Suitable for concise keyword descriptions, such as style or theme. Supports multiline input and dynamic prompts. | STRING | Yes | - |
| `t5xxl` | Text input processed by the T5XXL encoder. Suitable for detailed natural language descriptions, expressing complex scenes and details. Supports multiline input and dynamic prompts. | STRING | Yes | - |
| `guidance` | Controls the influence of text conditions on the generation process. Higher values mean stricter adherence to the text. Default: 3.5. Adjustable in increments of 0.1. | FLOAT | Yes | 0.0 - 100.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Contains the fused embeddings from both encoders and the guidance parameter, used for conditional image generation. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeFlux/en.md)

***

**Source fingerprint (SHA-256):** `022928fa6917102f5dc599364df9541b2451b42eb36a11813931b5fd71990b74`


# CLIPTextEncodeHunyuanDiT - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipTextEncodeHunyuanDit

The CLIPTextEncodeHunyuanDiT node converts text descriptions into a format that the HunyuanDiT model can understand.

The `CLIPTextEncodeHunyuanDiT` node converts text descriptions into a format that the HunyuanDiT model can understand. It is an advanced conditioning node designed for the dual text encoder architecture of HunyuanDiT, processing two separate text inputs through different tokenizers and combining their results into a single conditioning output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | A CLIP model instance used for text tokenization and encoding, which is core to generating conditions. | CLIP | Yes | - |
| `bert` | Text input for encoding via the BERT tokenizer. Prefers phrases and keywords. Supports multiline and dynamic prompts. | STRING | Yes | - |
| `mt5xl` | Text input for encoding via the mT5-XL tokenizer. Supports multiline and dynamic prompts (multilingual). Can use complete sentences and complex descriptions. | STRING | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The encoded conditioning output, combining both BERT and mT5-XL tokenized text, used for further processing in generation tasks. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeHunyuanDiT/en.md)

***

**Source fingerprint (SHA-256):** `550e8c09b8b74974576a852a9b690a87a0156ef49fe7ec1050b10415c6af78aa`


# CLIPTextEncodeSDXL - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipTextEncodeSdxl

This node is designed to encode text input using a CLIP model specifically customized for the SDXL architecture.

This node is designed to encode text input using a CLIP model specifically customized for the SDXL architecture. It uses a dual encoder system (CLIP-L and CLIP-G) to process text descriptions, resulting in more accurate image generation.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `clip` | CLIP model instance used for text encoding. | CLIP |
| `width` | Specifies the image width in pixels, default 1024. | INT |
| `height` | Specifies the image height in pixels, default 1024. | INT |
| `crop_w` | Width of the crop area in pixels, default 0. | INT |
| `crop_h` | Height of the crop area in pixels, default 0. | INT |
| `target_width` | Target width for the output image, default 1024. | INT |
| `target_height` | Target height for the output image, default 1024. | INT |
| `text_g` | Global text description for overall scene description. | STRING |
| `text_l` | Local text description for detail description. | STRING |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Contains encoded text and conditional information needed for image generation. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeSDXL/en.md)


# CLIPTextEncodeSDXLRefiner - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipTextEncodeSdxlRefiner

This node is specifically designed for the SDXL Refiner model to convert text prompts into conditioning information by incorporating aesthetic scores and dimensional information to

This node is specifically designed for the SDXL Refiner model to convert text prompts into conditioning information by incorporating aesthetic scores and dimensional information to enhance the conditions for generation tasks, thereby improving the final refinement effect. It acts like a professional art director, not only conveying your creative intent but also injecting precise aesthetic standards and specification requirements into the work.

## About SDXL Refiner

SDXL Refiner is a specialized refinement model that focuses on enhancing image details and quality based on the SDXL base model. This process is like having an art retoucher:

1. First, it receives preliminary images or text descriptions generated by the base model
2. Then, it guides the refinement process through precise aesthetic scoring and dimensional parameters
3. Finally, it focuses on processing high-frequency image details to improve overall quality

Refiner can be used in two ways:

* As a standalone refinement step for post-processing images generated by the base model
* As part of an expert integration system, taking over processing during the low-noise phase of generation

## Inputs

| Parameter Name | Description | Data Type | Input Type | Default Value | Value Range |
| - | - | - | - | - | - |
| `clip` | CLIP model instance used for text tokenization and encoding, the core component for converting text into model-understandable format | CLIP | Required | - | - |
| `ascore` | Controls the visual quality and aesthetics of generated images, similar to setting quality standards for artwork:<br />- High scores(7.5-8.5): Pursues more refined, detail-rich effects<br />- Medium scores(6.0-7.0): Balanced quality control<br />- Low scores(2.0-3.0): Suitable for negative prompts | FLOAT | Optional | 6.0 | 0.0-1000.0 |
| `width` | Specifies output image width (pixels), must be multiple of 8. SDXL performs best when total pixel count is close to 1024×1024 (about 1M pixels) | INT | Required | 1024 | 64-16384 |
| `height` | Specifies output image height (pixels), must be multiple of 8. SDXL performs best when total pixel count is close to 1024×1024 (about 1M pixels) | INT | Required | 1024 | 64-16384 |
| `text` | Text prompt description, supports multi-line input and dynamic prompt syntax. In Refiner, text prompts should focus more on describing desired visual quality and detail characteristics | STRING | Required | - | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Refined conditional output containing integrated encoding of text semantics, aesthetic standards, and dimensional information, specifically for guiding SDXL Refiner model in precise image refinement | CONDITIONING |

## Notes

1. This node is specifically optimized for the SDXL Refiner model and differs from regular CLIPTextEncode nodes
2. An aesthetic score of 7.5 is recommended as the baseline, which is the standard setting used in SDXL training
3. All dimensional parameters must be multiples of 8, and total pixel count close to 1024×1024 (about 1M pixels) is recommended
4. The Refiner model focuses on enhancing image details and quality, so text prompts should emphasize desired visual effects rather than scene content
5. In practical use, Refiner is typically used in the later stages of generation (approximately the last 20% of steps), focusing on detail optimization

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeSDXLRefiner/en.md)


# ConditioningConcat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningConcat

The ConditioningConcat node is designed to concatenate conditioning vectors, specifically merging the 'conditioningfrom' vector into the 'conditioningto' vector.

The ConditioningConcat node is designed to concatenate conditioning vectors, specifically merging the 'conditioning\_from' vector into the 'conditioning\_to' vector. This operation is fundamental in scenarios where the conditioning information from two sources needs to be combined into a single, unified representation.

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `conditioning_to` | Represents the primary set of conditioning vectors to which the 'conditioning\_from' vectors will be concatenated. It serves as the base for the concatenation process. | `CONDITIONING` |
| `conditioning_from` | Consists of conditioning vectors that are to be concatenated to the 'conditioning\_to' vectors. This parameter allows for additional conditioning information to be integrated into the existing set. | `CONDITIONING` |

## Outputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `conditioning` | The output is a unified set of conditioning vectors, resulting from the concatenation of 'conditioning\_from' vectors into the 'conditioning\_to' vectors. | `CONDITIONING` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningConcat/en.md)


# ConditioningMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningMultiply

This node multiplies the conditioning values by a specified factor, allowing you to scale the influence of the conditioning on the generation process.

This node multiplies the conditioning values by a specified factor, allowing you to scale the influence of the conditioning on the generation process. It works by applying the multiplier to both the main conditioning tensor and the pooled output values.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `conditioning` | The conditioning data to be scaled | CONDITIONING | Yes | - |
| `multiplier` | The factor to multiply the conditioning values by (default: 1.0) | FLOAT | Yes | -100.0 to 100.0 (step: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The scaled conditioning data with multiplied values | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningMultiply/en.md)

***

**Source fingerprint (SHA-256):** `8d241e3d5d91e513c24ade5b4bece4bf879fe093a4be6d53dab11a5a0bf55616`


# ConditioningSetArea - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetArea

This node is designed to modify the conditioning information by setting specific areas within the conditioning context.

This node is designed to modify the conditioning information by setting specific areas within the conditioning context. It allows for the precise spatial manipulation of conditioning elements, enabling targeted adjustments and enhancements based on specified dimensions and strength.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The conditioning data to be modified. It serves as the base for applying spatial adjustments. | CONDITIONING |
| `width` | Specifies the width of the area to be set within the conditioning context, influencing the horizontal scope of the adjustment. | `INT` |
| `height` | Determines the height of the area to be set, affecting the vertical extent of the conditioning modification. | `INT` |
| `x` | The horizontal starting point of the area to be set, positioning the adjustment within the conditioning context. | `INT` |
| `y` | The vertical starting point for the area adjustment, establishing its position within the conditioning context. | `INT` |
| `strength` | Defines the intensity of the conditioning modification within the specified area, allowing for nuanced control over the adjustment's impact. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The modified conditioning data, reflecting the specified area settings and adjustments. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetArea/en.md)


# ConditioningSetAreaPercentage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetAreaPercentage

The ConditioningSetAreaPercentage node specializes in adjusting the area of influence for conditioning elements based on percentage values.

The ConditioningSetAreaPercentage node specializes in adjusting the area of influence for conditioning elements based on percentage values. It allows for the specification of the area's dimensions and position as percentages of the total image size, alongside a strength parameter to modulate the intensity of the conditioning effect.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Represents the conditioning elements to be modified, serving as the foundation for applying area and strength adjustments. | CONDITIONING |
| `width` | Specifies the width of the area as a percentage of the total image width, influencing how much of the image the conditioning affects horizontally. | `FLOAT` |
| `height` | Determines the height of the area as a percentage of the total image height, affecting the vertical extent of the conditioning's influence. | `FLOAT` |
| `x` | Indicates the horizontal starting point of the area as a percentage of the total image width, positioning the conditioning effect. | `FLOAT` |
| `y` | Specifies the vertical starting point of the area as a percentage of the total image height, positioning the conditioning effect. | `FLOAT` |
| `strength` | Controls the intensity of the conditioning effect within the specified area, allowing for fine-tuning of its impact. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Returns the modified conditioning elements with updated area and strength parameters, ready for further processing or application. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetAreaPercentage/en.md)


# ConditioningSetAreaPercentageVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetAreaPercentageVideo

The ConditioningSetAreaPercentageVideo node modifies conditioning data by defining a specific area and temporal region for video generation.

The ConditioningSetAreaPercentageVideo node modifies conditioning data by defining a specific area and temporal region for video generation. It uses percentage values relative to the overall dimensions to set the position, size, and duration of the area where the conditioning is applied. This is useful for focusing the generation on specific parts of a video sequence.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `conditioning` | The conditioning data to be modified | CONDITIONING | Yes | - |
| `width` | The width of the area as a percentage of the total width (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |
| `height` | The height of the area as a percentage of the total height (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |
| `temporal` | The temporal duration of the area as a percentage of the total video length (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |
| `x` | The horizontal starting position of the area as a percentage (default: 0.0) | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |
| `y` | The vertical starting position of the area as a percentage (default: 0.0) | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |
| `z` | The temporal starting position of the area as a percentage of the video timeline (default: 0.0) | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |
| `strength` | The strength multiplier applied to the conditioning within the defined area (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 (step 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `conditioning` | The modified conditioning data with the specified area and strength settings applied | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetAreaPercentageVideo/en.md)

***

**Source fingerprint (SHA-256):** `9c5ddae6a2b1da5907fb52ef625eefb12b0b228fd3bd52c3033b5c4226d76150`


# ConditioningSetAreaStrength - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetAreaStrength

This node is designed to modify the strength attribute of a given conditioning set, allowing for the adjustment of the influence or intensity of the conditioning on the generation

This node is designed to modify the strength attribute of a given conditioning set, allowing for the adjustment of the influence or intensity of the conditioning on the generation process.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The conditioning set to be modified, representing the current state of conditioning that influences the generation process. | CONDITIONING |
| `strength` | The strength value to be applied to the conditioning set, dictating the intensity of its influence. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The modified conditioning set with updated strength values for each element. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetAreaStrength/en.md)


# ConditioningSetMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetMask

This node is designed to modify the conditioning of a generative model by applying a mask with a specified strength to certain areas.

This node is designed to modify the conditioning of a generative model by applying a mask with a specified strength to certain areas. It allows for targeted adjustments within the conditioning, enabling more precise control over the generation process.

## Inputs

### Required

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The conditioning data to be modified. It serves as the basis for applying the mask and strength adjustments. | CONDITIONING |
| `mask` | A mask tensor that specifies the areas within the conditioning to be modified. | `MASK` |
| `strength` | The strength of the mask's effect on the conditioning, allowing for fine-tuning of the applied modifications. | `FLOAT` |
| `set_cond_area` | Determines whether the mask's effect is applied to the default area or bounded by the mask itself, offering flexibility in targeting specific regions. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The modified conditioning data, with the mask and strength adjustments applied. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetMask/en.md)


# ConditioningSetTimestepRange - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetTimestepRange

This node is designed to adjust the temporal aspect of conditioning by setting a specific range of timesteps.

This node is designed to adjust the temporal aspect of conditioning by setting a specific range of timesteps. It allows for the precise control over the start and end points of the conditioning process, enabling more targeted and efficient generation.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The conditioning input represents the current state of the generation process, which this node modifies by setting a specific range of timesteps. | CONDITIONING |
| `start` | The start parameter specifies the beginning of the timestep range as a percentage of the total generation process, allowing for fine-tuned control over when the conditioning effects begin. | `FLOAT` |
| `end` | The end parameter defines the endpoint of the timestep range as a percentage, enabling precise control over the duration and conclusion of the conditioning effects. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The output is the modified conditioning with the specified timestep range applied, ready for further processing or generation. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetTimestepRange/en.md)


# ConditioningStableAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningStableAudio

The ConditioningStableAudio node adds timing information to both positive and negative conditioning inputs for audio generation.

The ConditioningStableAudio node adds timing information to both positive and negative conditioning inputs for audio generation. It sets the start time and total duration parameters that help control when and how long audio content should be generated. This node modifies existing conditioning data by appending audio-specific timing metadata.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning input to be modified with audio timing information | CONDITIONING | Yes | - |
| `negative` | The negative conditioning input to be modified with audio timing information | CONDITIONING | Yes | - |
| `seconds_start` | The starting time in seconds for audio generation (default: 0.0) | FLOAT | Yes | 0.0 to 1000.0 (step 0.1) |
| `seconds_total` | The total duration in seconds for audio generation (default: 47.0) | FLOAT | Yes | 0.0 to 1000.0 (step 0.1) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning with audio timing information applied | CONDITIONING |
| `negative` | The modified negative conditioning with audio timing information applied | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningStableAudio/en.md)

***

**Source fingerprint (SHA-256):** `8bdf29514002837090c549b9921e8cb19c07d385881fe09a58885fcbfe968261`


# ConditioningZeroOut - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningZeroOut

This node zeroes out specific elements within the conditioning data structure, effectively neutralizing their influence in subsequent processing steps.

This node zeroes out specific elements within the conditioning data structure, effectively neutralizing their influence in subsequent processing steps. It's designed for advanced conditioning operations where direct manipulation of the conditioning's internal representation is required.

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `CONDITIONING` | The conditioning data structure to be modified. This node zeroes out the 'pooled\_output' elements within each conditioning entry, if present. | CONDITIONING |

## Outputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `CONDITIONING` | The modified conditioning data structure, with 'pooled\_output' elements set to zero where applicable. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningZeroOut/en.md)


# ControlNetApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ControlNetApply

Using controlNet requires preprocessing of input images.

Using controlNet requires preprocessing of input images. Since ComfyUI initial nodes do not come with preprocessors and controlNet models, please first install ControlNet preprocessors [download preprocessors here](https://github.com/Fannovel16/comfy_controlnet_preprocessors) and corresponding controlNet models.

## Inputs

| Parameter | Data Type | Function |
| - | - | - |
| `positive` | `CONDITIONING` | Positive conditioning data, from CLIP Text Encoder or other conditioning inputs |
| `negative` | `CONDITIONING` | Negative conditioning data, from CLIP Text Encoder or other conditioning inputs |
| `control_net` | `CONTROL_NET` | The controlNet model to apply, typically input from ControlNet Loader |
| `image` | `IMAGE` | Image for controlNet application, needs to be processed by preprocessor |
| `vae` | `VAE` | Vae model input |
| `strength` | `FLOAT` | Controls the strength of network adjustments, value range 0~~10. Recommended values between 0.5~~1.5 are reasonable. Lower values allow more model freedom, higher values impose stricter constraints. Too high values may result in strange images. You can test and adjust this value to fine-tune the control network's influence. |
| `start_percent` | `FLOAT` | Value 0.000\~1.000, determines when to start applying controlNet as a percentage, e.g., 0.2 means ControlNet guidance will start influencing image generation at 20% of the diffusion process |
| `end_percent` | `FLOAT` | Value 0.000\~1.000, determines when to stop applying controlNet as a percentage, e.g., 0.8 means ControlNet guidance will stop influencing image generation at 80% of the diffusion process |

### Outputs

| Parameter | Data Type | Function |
| - | - | - |
| `positive` | `CONDITIONING` | Positive conditioning data processed by ControlNet, can be output to next ControlNet or K Sampler nodes |
| `negative` | `CONDITIONING` | Negative conditioning data processed by ControlNet, can be output to next ControlNet or K Sampler nodes |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ControlNetApply/en.md)


# ControlNetApplyAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ControlNetApplyAdvanced

This node applies advanced control net transformations to conditioning data based on an image and a control net model.

This node applies advanced control net transformations to conditioning data based on an image and a control net model. It allows for fine-tuned adjustments of the control net's influence over the generated content, enabling more precise and varied modifications to the conditioning.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning data to which the control net transformations will be applied. It represents the desired attributes or features to enhance or maintain in the generated content. | `CONDITIONING` |
| `negative` | The negative conditioning data, representing attributes or features to diminish or remove from the generated content. The control net transformations are applied to this data as well, allowing for a balanced adjustment of the content's characteristics. | `CONDITIONING` |
| `control_net` | The control net model is crucial for defining the specific adjustments and enhancements to the conditioning data. It interprets the reference image and strength parameters to apply transformations, significantly influencing the final output by modifying attributes in both positive and negative conditioning data. | `CONTROL_NET` |
| `image` | The image serving as a reference for the control net transformations. It influences the adjustments made by the control net to the conditioning data, guiding the enhancement or suppression of specific features. | `IMAGE` |
| `strength` | A scalar value determining the intensity of the control net's influence on the conditioning data. Higher values result in more pronounced adjustments. | `FLOAT` |
| `start_percent` | The starting percentage of the control net's effect, allowing for gradual application of transformations over a specified range. | `FLOAT` |
| `end_percent` | The ending percentage of the control net's effect, defining the range over which the transformations are applied. This enables more nuanced control over the adjustment process. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning data after the application of control net transformations, reflecting the enhancements made based on the input parameters. | `CONDITIONING` |
| `negative` | The modified negative conditioning data after the application of control net transformations, reflecting the suppression or removal of specific features based on the input parameters. | `CONDITIONING` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ControlNetApplyAdvanced/en.md)


# ControlNetApplySD3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ControlNetApplySD3

This node applies ControlNet guidance to Stable Diffusion 3 conditioning.

This node applies ControlNet guidance to Stable Diffusion 3 conditioning. It takes positive and negative conditioning inputs along with a ControlNet model and an image, then applies the control guidance with adjustable strength and timing parameters to influence the generation process.

**Note:** This node has been marked as deprecated and may be removed in future versions.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning to apply ControlNet guidance to | CONDITIONING | Yes | - |
| `negative` | The negative conditioning to apply ControlNet guidance to | CONDITIONING | Yes | - |
| `control_net` | The ControlNet model to use for guidance | CONTROL\_NET | Yes | - |
| `vae` | The VAE model used in the process | VAE | Yes | - |
| `image` | The input image that ControlNet will use as guidance | IMAGE | Yes | - |
| `strength` | The strength of the ControlNet effect (default: 1.0). When set to 0.0, the node skips ControlNet application and returns the conditioning unchanged. | FLOAT | Yes | 0.0 - 10.0 |
| `start_percent` | The starting point in the generation process where ControlNet begins to apply (default: 0.0) | FLOAT | Yes | 0.0 - 1.0 |
| `end_percent` | The ending point in the generation process where ControlNet stops applying (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |

**Note:** When `strength` is set to 0.0, no ControlNet guidance is applied and the input conditioning is passed through unchanged to both outputs.

**Note:** If the same conditioning is reused elsewhere and already contains control information, the new ControlNet is linked after the previous one, so multiple ControlNets can be applied in sequence.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning with ControlNet guidance applied | CONDITIONING |
| `negative` | The modified negative conditioning with ControlNet guidance applied | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ControlNetApplySD3/en.md)

***

**Source fingerprint (SHA-256):** `b76b0683c05e38102280ca8b0bd23f39a9b9b1b4f52125c77c95686c0a06f398`


# ControlNetInpaintingAliMamaApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ControlNetInpaintingAliMamaApply

The ControlNetInpaintingAliMamaApply node applies ControlNet conditioning for inpainting tasks by combining positive and negative conditioning with a control image and mask.

The ControlNetInpaintingAliMamaApply node applies ControlNet conditioning for inpainting tasks by combining positive and negative conditioning with a control image and mask. It processes the input image and mask to create modified conditioning that guides the generation process, allowing control over which areas of the image are inpainted. The node supports strength adjustment and timing controls to fine-tune the ControlNet's influence during different stages of the generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning that guides the generation toward desired content | CONDITIONING | Yes | - |
| `negative` | The negative conditioning that guides the generation away from unwanted content | CONDITIONING | Yes | - |
| `control_net` | The ControlNet model that provides additional control over the generation | CONTROL\_NET | Yes | - |
| `vae` | The VAE (Variational Autoencoder) used for encoding and decoding images | VAE | Yes | - |
| `image` | The input image that serves as control guidance for the ControlNet | IMAGE | Yes | - |
| `mask` | The mask that defines which areas of the image should be inpainted | MASK | Yes | - |
| `strength` | The strength of the ControlNet effect (default: 1.0, step: 0.01) | FLOAT | Yes | 0.0 to 10.0 |
| `start_percent` | Advanced parameter. The starting point (as percentage) of when ControlNet influence begins during generation (default: 0.0, step: 0.001) | FLOAT | Yes | 0.0 to 1.0 |
| `end_percent` | Advanced parameter. The ending point (as percentage) of when ControlNet influence stops during generation (default: 1.0, step: 0.001) | FLOAT | Yes | 0.0 to 1.0 |

**Note:** When the ControlNet has `concat_mask` enabled, the mask is inverted and applied to the image before processing, and the inverted mask is included in the extra concatenation data sent to the ControlNet.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning with ControlNet applied for inpainting | CONDITIONING |
| `negative` | The modified negative conditioning with ControlNet applied for inpainting | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ControlNetInpaintingAliMamaApply/en.md)

***

**Source fingerprint (SHA-256):** `307b55c7b4936826b9e4424c172248fa4b41921c2362de724e5cfa2f1c25de68`


# CosmosImageToVideoLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CosmosImageToVideoLatent

The CosmosImageToVideoLatent node creates a video latent representation from input images.

The CosmosImageToVideoLatent node creates a video latent representation from input images. It builds a blank video latent with the requested width, height, and number of frames, then optionally encodes a start image into the beginning frames and/or an end image into the end frames. When images are provided, it also generates a noise mask so the encoded frames remain fixed during generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `vae` | The VAE model used to encode the images into the video latent space. | VAE | Yes | - |
| `width` | The width of the output video in pixels (default: 1280). | INT | Yes | 16 to MAX\_RESOLUTION (step: 16) |
| `height` | The height of the output video in pixels (default: 704). | INT | Yes | 16 to MAX\_RESOLUTION (step: 16) |
| `length` | The total number of frames in the video (default: 121). | INT | Yes | 1 to MAX\_RESOLUTION (step: 8) |
| `batch_size` | The number of video latents to generate (default: 1). | INT | Yes | 1 to 4096 |
| `start_image` | Optional image or image sequence to encode at the beginning of the video. | IMAGE | No | - |
| `end_image` | Optional image or image sequence to encode at the end of the video. | IMAGE | No | - |

**Note:**

* When neither `start_image` nor `end_image` is provided, the node returns a blank latent without a noise mask.
* When `start_image` is provided, it is encoded into the first frames of the latent and those frames are marked with noise mask value 0 (preserved). When `end_image` is provided, it is encoded into the last frames and those frames are marked with noise mask value 0. The remaining frames keep a mask value of 1.
* The latent has 16 channels and its spatial dimensions are `height / 8` by `width / 8`. The number of latent frames is `((length - 1) // 8) + 1`.
* `batch_size` repeats the latent and, when present, the noise mask.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latent` | The generated video latent containing the optional encoded start and/or end images and, when images are provided, a matching noise mask with value 0 on the preserved frames. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CosmosImageToVideoLatent/en.md)

***

**Source fingerprint (SHA-256):** `0b06ccfcb14c27c81eeebbbff519da1e187970d4cfc19c8796fc3da20688245c`


# CosmosPredict2ImageToVideoLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CosmosPredict2ImageToVideoLatent

Creates video latents for the Cosmos Predict2 image-to-video workflow.

Creates video latents for the Cosmos Predict2 image-to-video workflow. The node can produce an empty video latent of a given size and length, or insert encoded start and/or end images into the sequence so those frames are kept during generation. Any supplied image is resized to the requested `width` and `height` and encoded with the provided VAE before being placed at the beginning and/or end of the latent sequence.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `vae` | The VAE model used to encode the start and end images into latent space | VAE | Yes | - |
| `width` | Width of the output video in pixels (default: 848, must be a multiple of 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Height of the output video in pixels (default: 480, must be a multiple of 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames in the video sequence (default: 93) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of video sequences to generate (default: 1) | INT | Yes | 1 to 4096 |
| `start_image` | Optional starting image for the video sequence | IMAGE | No | - |
| `end_image` | Optional ending image for the video sequence | IMAGE | No | - |

**Note:** When neither `start_image` nor `end_image` is provided, the node simply returns an empty latent of the requested size and length. When one or both images are provided, they are resized to `width` and `height`, encoded with the `vae`, and placed at the beginning and/or end of the latent sequence. The corresponding regions are marked in the noise mask so they are preserved during generation. The encoded latents are converted with the Wan 2.1 latent format, and the resulting latent and mask are repeated `batch_size` times.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | The generated video latent containing `samples` (the video latent sequence) and, when at least one of `start_image` or `end_image` is provided, a `noise_mask` marking the frames that should be preserved during generation | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CosmosPredict2ImageToVideoLatent/en.md)

***

**Source fingerprint (SHA-256):** `842bd2b8cda438e7b938439d4eba280478939e3302dc1846d52595d40082ff05`


# FluxDisableGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxDisableGuidance

This node completely disables the guidance embed on Flux and Flux-like models.

This node completely disables the guidance embed on Flux and Flux-like models. It takes conditioning data as input and sets its guidance value to None, effectively turning off guidance-based conditioning for the generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `conditioning` | The conditioning data to process and remove guidance from | CONDITIONING | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `conditioning` | The modified conditioning data with guidance disabled | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxDisableGuidance/en.md)

***

**Source fingerprint (SHA-256):** `da3286194f9f5e7e49dd7047d6b0a0c97bb2570eaa9281abbd3992a743302fbf`


# FluxGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxGuidance

Documentation for FluxGuidance node.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| conditioning | Input conditioning data, typically from previous encoding or processing steps | CONDITIONING |
| guidance | Controls the influence of text prompts on image generation, adjustable range from 0.0 to 100.0 | FLOAT |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| CONDITIONING | Updated conditioning data, containing the new guidance value | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxGuidance/en.md)


# FluxKontextImageScale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxKontextImageScale

This node scales the input image to an optimal size used during Flux Kontext model training using the Lanczos algorithm, based on the input image's aspect ratio.

This node scales the input image to an optimal size used during Flux Kontext model training using the Lanczos algorithm, based on the input image's aspect ratio. This node is particularly useful when inputting large-sized images, as oversized inputs may lead to degraded model output quality or issues such as multiple subjects appearing in the output.

## Inputs

| Parameter Name | Description | Data Type | Input Type | Default Value | Value Range |
| - | - | - | - | - | - |
| `image` | Input image to be resized | IMAGE | Required | - | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | Resized image | IMAGE |

## Preset Size List

The following is a list of standard sizes used during model training. The node will select the size closest to the input image's aspect ratio:

| Width | Height | Aspect Ratio |
| - | - | - |
| 672 | 1568 | 0.429 |
| 688 | 1504 | 0.457 |
| 720 | 1456 | 0.494 |
| 752 | 1392 | 0.540 |
| 800 | 1328 | 0.603 |
| 832 | 1248 | 0.667 |
| 880 | 1184 | 0.743 |
| 944 | 1104 | 0.855 |
| 1024 | 1024 | 1.000 |
| 1104 | 944 | 1.170 |
| 1184 | 880 | 1.345 |
| 1248 | 832 | 1.500 |
| 1328 | 800 | 1.660 |
| 1392 | 752 | 1.851 |
| 1456 | 720 | 2.022 |
| 1504 | 688 | 2.186 |
| 1568 | 672 | 2.333 |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxKontextImageScale/en.md)


# FluxKontextMultiReferenceLatentMethod - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxKontextMultiReferenceLatentMethod

The FluxKontextMultiReferenceLatentMethod node updates conditioning data by storing a chosen reference latents method inside it.

The FluxKontextMultiReferenceLatentMethod node updates conditioning data by storing a chosen reference latents method inside it. The stored method is then used when reference latents are handled in later generation steps. This node is marked as experimental and belongs to the Flux conditioning system.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `conditioning` | The conditioning data to be modified with the reference latents method | CONDITIONING | Yes | - |
| `reference_latents_method` | The method used for reference latents processing. If a value containing "uxo" or "uso" is selected, it is converted to "uxo" before being stored. This parameter is marked as advanced. | COMBO | Yes | `"offset"`<br />`"index"`<br />`"uxo/uno"`<br />`"index_timestep_zero"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `conditioning` | The modified conditioning data with the reference latents method applied | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxKontextMultiReferenceLatentMethod/en.md)

***

**Source fingerprint (SHA-256):** `cbe069d0c9f8adbf7f8c909b1cd644d9cd3730e934f0e5856213ff06fa8ecc56`


# GLIGENTextBoxApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GLIGENTextBoxApply

The GLIGENTextBoxApply node is designed to integrate text-based conditioning into a generative model's input, specifically by applying text box parameters and encoding them using a

The `GLIGENTextBoxApply` node is designed to integrate text-based conditioning into a generative model's input, specifically by applying text box parameters and encoding them using a CLIP model. This process enriches the conditioning with spatial and textual information, facilitating more precise and context-aware generation.

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `conditioning_to` | Specifies the initial conditioning input to which the text box parameters and encoded text information will be appended. It plays a crucial role in determining the final output by integrating new conditioning data. | `CONDITIONING` |
| `clip` | The CLIP model used for encoding the provided text into a format that can be utilized by the generative model. It's essential for converting textual information into a compatible conditioning format. | `CLIP` |
| `gligen_textbox_model` | Represents the specific GLIGEN model configuration to be used for generating the text box. It's crucial for ensuring that the text box is generated according to the desired specifications. | `GLIGEN` |
| `text` | The text content to be encoded and integrated into the conditioning. It provides the semantic information that guides the generative model. | `STRING` |
| `width` | The width of the text box in pixels. It defines the spatial dimension of the text box within the generated image. | `INT` |
| `height` | The height of the text box in pixels. Similar to width, it defines the spatial dimension of the text box within the generated image. | `INT` |
| `x` | The x-coordinate of the top-left corner of the text box within the generated image. It specifies the text box's position horizontally. | `INT` |
| `y` | The y-coordinate of the top-left corner of the text box within the generated image. It specifies the text box's position vertically. | `INT` |

## Outputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `conditioning` | The enriched conditioning output, which includes the original conditioning data along with the newly appended text box parameters and encoded text information. It's used to guide the generative model in producing context-aware outputs. | `CONDITIONING` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GLIGENTextBoxApply/en.md)


# GenerateTracks - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GenerateTracks

The GenerateTracks node creates multiple parallel motion paths (tracks) for video generation.

The `GenerateTracks` node creates multiple parallel motion paths (tracks) for video generation. It defines a main path from a start position to an end position, then generates a set of tracks that run parallel to this path, spaced evenly apart. You can control the shape of the path (straight line or Bezier curve), the speed of movement along it, and which frames the tracks are visible in.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the video frame in pixels. The default value is 832. | INT | Yes | 16 - 4096 |
| `height` | The height of the video frame in pixels. The default value is 480. | INT | Yes | 16 - 4096 |
| `start_x` | Normalized X coordinate (0-1) for start position. The default value is 0.0. | FLOAT | Yes | 0.0 - 1.0 |
| `start_y` | Normalized Y coordinate (0-1) for start position. The default value is 0.0. | FLOAT | Yes | 0.0 - 1.0 |
| `end_x` | Normalized X coordinate (0-1) for end position. The default value is 1.0. | FLOAT | Yes | 0.0 - 1.0 |
| `end_y` | Normalized Y coordinate (0-1) for end position. The default value is 1.0. | FLOAT | Yes | 0.0 - 1.0 |
| `num_frames` | The total number of frames for which to generate track positions. The default value is 81. | INT | Yes | 1 - 1024 |
| `num_tracks` | The number of parallel tracks to generate. The default value is 5. | INT | Yes | 1 - 100 |
| `track_spread` | Normalized distance between tracks. Tracks are spread perpendicular to the motion direction. The default value is 0.025. | FLOAT | Yes | 0.0 - 1.0 |
| `bezier` | Enable Bezier curve path using the mid point as control point. The default value is False. | BOOLEAN | Yes | True / False |
| `mid_x` | Normalized X control point for Bezier curve. Only used when 'bezier' is enabled. The default value is 0.5. | FLOAT | Yes | 0.0 - 1.0 |
| `mid_y` | Normalized Y control point for Bezier curve. Only used when 'bezier' is enabled. The default value is 0.5. | FLOAT | Yes | 0.0 - 1.0 |
| `interpolation` | Controls the timing/speed of movement along the path (default: "linear"):<br />"linear" - constant speed<br />"ease\_in" - starts slow and speeds up<br />"ease\_out" - starts fast and slows down<br />"ease\_in\_out" - smooth acceleration and deceleration<br />"constant" - keeps all positions at the start point | COMBO | Yes | `"linear"`<br />`"ease_in"`<br />`"ease_out"`<br />`"ease_in_out"`<br />`"constant"` |
| `track_mask` | Optional mask to indicate visible frames. If provided, frames where the mask has any nonzero pixel are marked as visible for all tracks. | MASK | No | - |

**Note:** The `mid_x` and `mid_y` parameters are only used when the `bezier` parameter is set to `True`. When `bezier` is `False`, the path is a straight line from the start to the end point.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `TRACKS` | A tracks object containing the generated path coordinates and visibility information for all tracks across all frames. | TRACKS |
| `track_length` | The number of frames for which tracks were generated, matching the input `num_frames`. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GenerateTracks/en.md)

***

**Source fingerprint (SHA-256):** `4bd4d03a84f4b7ea260555b43f217af0b90dd4ca5196aca94e8f3886875ab912`


# GetICLoRAParameters - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GetICLoRAParameters

This node reads the metadata from a LoRA-loaded model to extract IC-LoRA parameters, such as the reference downscale factor.

This node reads the metadata from a LoRA-loaded model to extract IC-LoRA parameters, such as the reference downscale factor. It outputs these parameters as a structured object that can be connected to the LTXVAddGuide node when a LoRA requires special handling of the guides.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `iclora_model` | Direct output from a LoRA Loader for the specific IC-LoRA from which to extract the metadata. | MODEL | Yes | N/A |

Note: If the LoRA metadata is missing or does not contain a `reference_downscale_factor` entry, the node outputs a default value of 1. When present, the factor is rounded and set to a minimum of 1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `iclora_parameters` | IC-LoRA parameters extracted from the LoRA metadata (e.g., reference\_downscale\_factor). Connect to LTXVAddGuide if the LoRA requires special handling of the guides. | IC\_LORA\_PARAMETERS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GetICLoRAParameters/en.md)

***

**Source fingerprint (SHA-256):** `5f6becad0c7673b8cde1e099bd7ba5be7106da958b8967f8e693ba2a704baaef`


# HiDreamO1ReferenceImages - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HiDreamO1ReferenceImages

This node attaches reference images to both positive and negative conditioning, so downstream nodes can use them to guide generation.

This node attaches reference images to both positive and negative conditioning, so downstream nodes can use them to guide generation. Reference images are applied in the numeric order of their input sockets. If no reference images are connected, the positive and negative conditioning pass through unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning to attach reference images to. | CONDITIONING | Yes | - |
| `negative` | The negative conditioning to attach reference images to. | CONDITIONING | Yes | - |
| `images` | Reference images are used in numeric socket order. When images are supplied, they are attached to both the positive and negative conditioning. | IMAGE | No | 0 to 100 images (`image_1` to `image_100`) |

**Note on `images` parameter:** This is an autogrow input that provides numbered sockets `image_1` through `image_100`. Images are used in numeric socket order. The input is optional: if no reference images are connected, the node returns the `positive` and `negative` conditioning unchanged. When images are connected, the same set of reference images is attached to both outputs, and the negative conditioning is also marked as negative before the images are attached.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning with the reference images attached. | CONDITIONING |
| `negative` | The negative conditioning with the reference images attached. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HiDreamO1ReferenceImages/en.md)

***

**Source fingerprint (SHA-256):** `07f9f0ea19957523e95d04b9086dc994807bb0cd5262fe798dc784c1ecb4920d`


# Hunyuan3Dv2Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Hunyuan3Dv2Conditioning

The Hunyuan3Dv2Conditioning node processes CLIP vision output to generate conditioning data for 3D models.

The Hunyuan3Dv2Conditioning node processes CLIP vision output to generate conditioning data for 3D models. It extracts the last hidden state embeddings from the vision output and creates both positive and negative conditioning pairs. The positive conditioning uses the actual embeddings while the negative conditioning uses zero-valued embeddings of the same shape.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_vision_output` | The output from a CLIP vision model containing visual embeddings | CLIP\_VISION\_OUTPUT | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning data containing the CLIP vision embeddings | CONDITIONING |
| `negative` | Negative conditioning data containing zero-valued embeddings matching the positive embeddings shape | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Hunyuan3Dv2Conditioning/en.md)

***

**Source fingerprint (SHA-256):** `114d23574a93bd31013fc909568023c143bba2e4ea75b35a0ebb808c19e83867`


# Hunyuan3Dv2ConditioningMultiView - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Hunyuan3Dv2ConditioningMultiView

The Hunyuan3Dv2ConditioningMultiView node combines CLIP vision outputs from up to four views (front, left, back, and right) into a single multi-view conditioning.

The Hunyuan3Dv2ConditioningMultiView node combines CLIP vision outputs from up to four views (front, left, back, and right) into a single multi-view conditioning. Each provided view has a positional encoding added to its CLIP vision embedding, and the resulting embeddings are concatenated. The node outputs a positive conditioning based on the combined embeddings and a negative conditioning filled with zeros of the same shape.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `front` | CLIP vision output for the front view. Optional view input. | CLIP\_VISION\_OUTPUT | No | - |
| `left` | CLIP vision output for the left view. Optional view input. | CLIP\_VISION\_OUTPUT | No | - |
| `back` | CLIP vision output for the back view. Optional view input. | CLIP\_VISION\_OUTPUT | No | - |
| `right` | CLIP vision output for the right view. Optional view input. | CLIP\_VISION\_OUTPUT | No | - |

**Note:** At least one view input must be provided for the node to function. The node only processes views that contain valid CLIP vision output data and skips views that are not connected. Each view receives a fixed positional encoding based on its slot (front, left, back, right), and the processed embeddings from all provided views are joined together along the sequence dimension.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning containing the combined multi-view embeddings with positional encoding. | CONDITIONING |
| `negative` | Negative conditioning with zero values matching the positive conditioning shape. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Hunyuan3Dv2ConditioningMultiView/en.md)

***

**Source fingerprint (SHA-256):** `1492b51661d0bb8f2c142c1b1e8ef104beed1b9dae532a970e2928e27ad71d69`


# HunyuanImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanImageToVideo

The HunyuanImageToVideo node converts images into video latent representations using the Hunyuan video model.

The HunyuanImageToVideo node converts images into video latent representations using the Hunyuan video model. It takes conditioning inputs and optional starting images to generate video latents that can be further processed by video generation models. The node supports different guidance types for controlling how the starting image influences the video generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning input for guiding the video generation | CONDITIONING | Yes | - |
| `vae` | VAE model used for encoding images into latent space | VAE | Yes | - |
| `width` | Width of the output video in pixels (default: 848, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Height of the output video in pixels (default: 480, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames in the output video (default: 53, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of videos to generate simultaneously (default: 1) | INT | Yes | 1 to 4096 |
| `guidance_type` | Method for incorporating the starting image into video generation (default: "v1 (concat)"). Advanced option | COMBO | Yes | "v1 (concat)"<br />"v2 (replace)"<br />"custom" |
| `start_image` | Optional starting image (or image sequence) to initialize the video generation. Only the first `length` frames and the first 3 color channels are used | IMAGE | No | - |

**Note:** When `start_image` is provided, the node uses different guidance methods based on the selected `guidance_type`:

* "v1 (concat)": Concatenates the image latent with the video latent and applies a mask to blend the image into the video
* "v2 (replace)": Replaces initial video frames with the image latent and applies a noise mask
* "custom": Uses the image as a reference latent for guidance

If `start_image` is not provided, no guidance conditioning is added and the latent is returned as a plain block of zeros.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Modified positive conditioning with image guidance applied when start\_image is provided | CONDITIONING |
| `latent` | Video latent representation ready for further processing by video generation models | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `0ed00d59513492f31760a18ce3b0edf10b64cad848ba52c4e47d5f61fae9accc`


# HunyuanRefinerLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanRefinerLatent

The HunyuanRefinerLatent node prepares conditioning and latent data for the Hunyuan video refinement process.

The HunyuanRefinerLatent node prepares conditioning and latent data for the Hunyuan video refinement process. It attaches the input latent image data to both the positive and negative conditioning, applies a noise augmentation value to them, and creates a new zero-filled latent with 32 channels for further processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning input to be processed | CONDITIONING | Yes | - |
| `negative` | The negative conditioning input to be processed | CONDITIONING | Yes | - |
| `latent` | The latent representation input, used as the latent image data for the conditioning and to define the dimensions of the output latent | LATENT | Yes | - |
| `noise_augmentation` | The amount of noise augmentation to apply (default: 0.10). This parameter is shown in the advanced section of the node. | FLOAT | Yes | 0.0 - 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The processed positive conditioning with the latent image data attached and the noise augmentation applied | CONDITIONING |
| `negative` | The processed negative conditioning with the latent image data attached and the noise augmentation applied | CONDITIONING |
| `latent` | A new latent filled with zeros, with the same batch size and the same last three dimensions as the input latent, and 32 channels | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanRefinerLatent/en.md)

***

**Source fingerprint (SHA-256):** `4c5669cf2ad5ba00e176876741b7d8d3f092cc58d2163871a10fd769ee4ff84c`


# HunyuanVideo15ImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanVideo15ImageToVideo

The HunyuanVideo15ImageToVideo node prepares conditioning and latent space data for video generation based on the HunyuanVideo 1.5 model.

The HunyuanVideo15ImageToVideo node prepares conditioning and latent space data for video generation based on the HunyuanVideo 1.5 model. It creates an initial latent representation for a video sequence and can optionally integrate a starting image or a CLIP vision output to guide the generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning prompts that describe what the video should contain. | CONDITIONING | Yes | - |
| `negative` | The negative conditioning prompts that describe what the video should avoid. | CONDITIONING | Yes | - |
| `vae` | The VAE (Variational Autoencoder) model used to encode the starting image into the latent space. | VAE | Yes | - |
| `width` | The width of the output video frames in pixels. Must be divisible by 16. (default: 848) | INT | Yes | 16 to MAX\_RESOLUTION, step: 16 |
| `height` | The height of the output video frames in pixels. Must be divisible by 16. (default: 480) | INT | Yes | 16 to MAX\_RESOLUTION, step: 16 |
| `length` | The total number of frames in the video sequence. Values increase in steps of 4 starting from 1 (1, 5, 9, 13, ...). (default: 33) | INT | Yes | 1 to MAX\_RESOLUTION, step: 4 |
| `batch_size` | The number of video sequences to generate in a single batch. (default: 1) | INT | Yes | 1 to 4096 |
| `start_image` | An optional starting image to initialize the video generation. If provided, it is encoded and used to condition the first frames. Only the first `length` frames of the image are used. | IMAGE | No | - |
| `clip_vision_output` | Optional CLIP vision embeddings to provide additional visual conditioning for the generation. | CLIP\_VISION\_OUTPUT | No | - |

**Note:** When a `start_image` is provided, it is automatically resized to match the specified `width` and `height` using bilinear interpolation. The first `length` frames of the image batch are used, and only the first 3 color channels of each frame are encoded. The encoded image is then added to both the `positive` and `negative` conditioning as a `concat_latent_image` with a corresponding `concat_mask`. The mask is set to 0.0 for the frames covered by the starting image and 1.0 for the remaining frames. When a `clip_vision_output` is provided, it is also added to both the `positive` and `negative` conditioning.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning, which may now include the encoded starting image or CLIP vision output. | CONDITIONING |
| `negative` | The modified negative conditioning, which may now include the encoded starting image or CLIP vision output. | CONDITIONING |
| `latent` | An empty latent tensor with dimensions configured for the specified batch size, video length, width, and height. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanVideo15ImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `dbedf7f378ae9613c8f47fe9876a4576c815055b4cdb6bf687b7575fcd7ea80a`


# HunyuanVideo15SuperResolution - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanVideo15SuperResolution

The HunyuanVideo15SuperResolution node prepares conditioning data for a video super-resolution process.

The HunyuanVideo15SuperResolution node prepares conditioning data for a video super-resolution process. It takes a latent representation of a video and, optionally, a starting image, and packages them along with noise augmentation and CLIP vision data into a format that can be used by a model to generate a higher-resolution output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning input to be modified with latent and augmentation data. | CONDITIONING | Yes | N/A |
| `negative` | The negative conditioning input to be modified with latent and augmentation data. | CONDITIONING | Yes | N/A |
| `vae` | The VAE used to encode the optional `start_image`. Required if `start_image` is provided. | VAE | No | N/A |
| `start_image` | An optional starting image to guide the super-resolution. If provided, it is upscaled and encoded into the conditioning latent. | IMAGE | No | N/A |
| `clip_vision_output` | Optional CLIP vision embeddings to add to the conditioning. | CLIP\_VISION\_OUTPUT | No | N/A |
| `latent` | The input latent video representation that is incorporated into the conditioning. | LATENT | Yes | N/A |
| `noise_augmentation` | The strength of noise augmentation to apply to the conditioning (default: 0.70). This is an advanced parameter; a value is always supplied by the default. | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |

**Note:** If you provide a `start_image`, you must also connect a `vae` so it can be encoded. The `start_image` is automatically upscaled to 16 times the spatial dimensions (width and height) of the input `latent`, then encoded and placed into the conditioning latent. Only the RGB channels of the `start_image` are used for encoding.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning, now containing the concatenated latent, noise augmentation, and optional CLIP vision data. | CONDITIONING |
| `negative` | The modified negative conditioning, now containing the concatenated latent, noise augmentation, and optional CLIP vision data. | CONDITIONING |
| `latent` | The input latent is passed through unchanged. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanVideo15SuperResolution/en.md)

***

**Source fingerprint (SHA-256):** `c9e64092e78423f5e0dc43446a77240e09100242c25e4fccc91491049fe76be5`


# InstructPixToPixConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/InstructPixToPixConditioning

The InstructPixToPixConditioning node prepares conditioning data for InstructPix2Pix image editing by combining positive and negative text prompts with image data.

The InstructPixToPixConditioning node prepares conditioning data for InstructPix2Pix image editing by combining positive and negative text prompts with image data. It encodes the input image through a VAE into a latent representation and attaches that latent to both the positive and negative conditioning, while also returning a matching empty latent. Image dimensions are automatically cropped to multiples of 8 pixels so the VAE can process them.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning data containing text prompts and settings for desired image characteristics | CONDITIONING | Yes | - |
| `negative` | Negative conditioning data containing text prompts and settings for undesired image characteristics | CONDITIONING | Yes | - |
| `vae` | VAE model used for encoding input images into latent representations | VAE | Yes | - |
| `pixels` | Input image to be processed and encoded into latent space | IMAGE | Yes | - |

**Note:** The input image dimensions are automatically adjusted by center-cropping to multiples of 8 pixels in both width and height to ensure compatibility with the VAE encoding process.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning data with the encoded image latent attached as `concat_latent_image` | CONDITIONING |
| `negative` | Negative conditioning data with the encoded image latent attached as `concat_latent_image` | CONDITIONING |
| `latent` | Latent tensor of zeros with the same dimensions as the encoded image | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/InstructPixToPixConditioning/en.md)

***

**Source fingerprint (SHA-256):** `e9a5a05cdeafe9337ca2033111f1ad4f7314fa33d71a4764f62919857efc79f4`


# Kandinsky5ImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Kandinsky5ImageToVideo

The Kandinsky5ImageToVideo node prepares conditioning and latent data for video generation using the Kandinsky model.

The Kandinsky5ImageToVideo node prepares conditioning and latent data for video generation using the Kandinsky model. It creates an empty video latent sized to the requested width, height, length, and batch size, and can optionally encode a starting image to guide the initial frames of the generated video by updating the positive and negative conditioning.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning prompts to guide the video generation. | CONDITIONING | Yes | N/A |
| `negative` | The negative conditioning prompts to steer the video generation away from certain concepts. | CONDITIONING | Yes | N/A |
| `vae` | The VAE model used to encode the optional starting image into the latent space. | VAE | Yes | N/A |
| `width` | The width of the output video in pixels (default: 768). | INT | Yes | 16 to 16384 (step 16) |
| `height` | The height of the output video in pixels (default: 512). | INT | Yes | 16 to 16384 (step 16) |
| `length` | The number of frames in the video (default: 121). | INT | Yes | 1 to 16384 (step 4) |
| `batch_size` | The number of video sequences to generate simultaneously (default: 1). | INT | Yes | 1 to 4096 |
| `start_image` | An optional starting image or batch of frames. If provided, it is encoded and used to replace the noisy start of the model's output latents. | IMAGE | No | N/A |

**Note:** When a `start_image` is provided, it is automatically resized to match the specified `width` and `height` using bilinear interpolation. Only the first `length` frames of the image batch are used for encoding; any additional frames are ignored. If the image batch has fewer than `length` frames, only those frames are used. Only the RGB channels of the image are encoded. The encoded latent is then injected into both the `positive` and `negative` conditioning to guide the video's initial appearance, and the clean encoded frames replace the noisy start of the model's output latents.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning, updated with encoded start image data when a `start_image` is provided. | CONDITIONING |
| `negative` | The modified negative conditioning, updated with encoded start image data when a `start_image` is provided. | CONDITIONING |
| `latent` | Empty video latent. A latent tensor filled with zeros, shaped for the specified dimensions. | LATENT |
| `cond_latent` | Clean encoded start images, used to replace the noisy start of the model output latents. Empty when no `start_image` is provided. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Kandinsky5ImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `7212f0ea912578d3b72dddf1333a20054a881e3f22c2b8abd9645fc21e75a08b`


# LTXVAddGeneratedKeyframes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVAddGeneratedKeyframes

The LTXV Add Generated Keyframes node appends detailing keyframes to a video latent.

The LTXV Add Generated Keyframes node appends detailing keyframes to a video latent. Each keyframe is one latent frame of tokens positioned over a single pixel frame; it is denoised with the video and is not part of the decoded output. Placement is one slot every `interval_frames` pixels, skipping I2V frames, existing guides, and generated keyframes already on the conditioning; pull them back out with LTXV Separate Generated Keyframes. A checkpoint trained for generated keyframes (one carrying `keyframes_abs_pos_embedding`) is required.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning the keyframes are attached to. | CONDITIONING | Yes | N/A |
| `negative` | Negative conditioning the keyframes are attached to. | CONDITIONING | Yes | N/A |
| `vae` | Only used to read the latent scale factors. | VAE | Yes | N/A |
| `latent` | Plain 5D video latent to generate keyframes alongside. Add them before Concat AV Latent. | LATENT | Yes | N/A |
| `interval_frames` | Pixel-frame stride for auto placement. Default 24 is about one keyframe per second at 24 fps. Occupied pixels are skipped. Ignored when frame\_indices is set. (default: 24) | INT | No | 1-1024 |
| `keyframes` | Optional content to initialize the new keyframes with. Connect keyframes from an earlier Separate (same spatial size), or a plain video latent to copy the nearest frame at each new slot (e.g. after temporal upscale). These are still denoised, not pinned as guides. Recorded indices on a keyframes latent are ignored unless frame\_indices is set. Only has an effect when sampling starts below sigma 1. | LATENT | No | N/A |
| `frame_indices` | Optional pixel-frame indices. Leave empty to place from interval\_frames on the current canvas. When set, this list is the placement (connected keyframes are matched in order). The last frame is allowed; frame 0 is not (it is already a standalone token). (default: empty string) | STRING | No | Comma-separated integers; 1 to the last pixel frame (frame 0 excluded) |

**Note:** The `latent` must be a plain 5D video latent with generated keyframes added before Concat AV Latent. When `frame_indices` is set, each listed pixel frame must be unique and cannot already hold an image keyframe, a guide, or a generated keyframe. If `frame_indices` is empty, occupied pixels are skipped automatically; if no free detailing slot exists, the node raises an error. When appending to existing generated keyframes, the latent must still have the same tokens per frame and the existing block must end at the last latent frame.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with generated-keyframe attention attached. | CONDITIONING |
| `negative` | Negative conditioning with generated-keyframe attention attached. | CONDITIONING |
| `latent` | Video latent with generated keyframes appended on T. | LATENT |

## Notes

* The `interval_frames` parameter sets the spacing of auto-placed keyframes. A higher value results in fewer keyframes and wider spacing; a lower value produces more keyframes.
* The `keyframes` input allows you to initialize the new keyframes with existing keyframes or a video latent. If a longer plain video latent is provided, the nearest video frame is copied at each new slot. These keyframes are still denoised and are not pinned as guides.
* The `frame_indices` parameter allows you to specify exact pixel-frame indices where keyframes should be placed. When provided, `interval_frames` is ignored. The list must contain unique integers within the valid pixel range, and frame 0 is not allowed.
* The `positive` and `negative` outputs contain the conditioning with generated-keyframe attention attached.
* The `latent` output contains the video latent with generated keyframes appended on T.
* A checkpoint trained for generated keyframes (one carrying `keyframes_abs_pos_embedding`) is required.
* Pull generated keyframes back out with LTXV Separate Generated Keyframes.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVAddGeneratedKeyframes/en.md)

***

**Source fingerprint (SHA-256):** `43053d15eceb61f37223c46dd46417c71f0503ef3a412ee50a3b2f764f310a64`


# LTXVAddGuide - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVAddGuide

The LTXVAddGuide node encodes input images or videos through a VAE encoder and adds them as guide keyframes to a latent video sequence.

The LTXVAddGuide node encodes input images or videos through a VAE encoder and adds them as guide keyframes to a latent video sequence. It updates both positive and negative conditioning and returns the modified latent, with options to set the starting frame, conditioning strength, an optional attention mask, and optional IC-LoRA parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning input to be modified with keyframe guidance. | CONDITIONING | Yes | - |
| `negative` | Negative conditioning input to be modified with keyframe guidance. | CONDITIONING | Yes | - |
| `vae` | VAE model used for encoding the input image/video frames. | VAE | Yes | - |
| `latent` | Input latent sequence that will receive the conditioning frames. | LATENT | Yes | - |
| `image` | Image or video to condition the latent video on. Must be 8*n + 1 frames. If the video is not 8*n + 1 frames, it will be cropped to the nearest 8\*n + 1 frames. | IMAGE | Yes | - |
| `frame_idx` | Frame index to start the conditioning at. For single-frame images or videos with 1-8 frames, any frame\_idx value is acceptable. For videos with 9+ frames, frame\_idx must be divisible by 8, otherwise it will be rounded down to the nearest multiple of 8. Negative values are counted from the end of the video. Default: 0. | INT | Yes | -9999 to 9999 |
| `strength` | Strength of the conditioning influence, where 1.0 applies full conditioning and 0.0 applies no conditioning. Default: 1.0. | FLOAT | Yes | 0.0 to 10.0 |
| `attention_mask` | Optional pixel-space spatial mask. Controls per-region conditioning influence via self-attention, multiplied by strength. | MASK | No | - |
| `iclora_parameters` | Optional IC-LoRA parameters from a Get IC-LoRA Parameters node. Used for adjusting guide processing as required by certain IC-LoRAs (e.g., those with a reference\_downscale\_factor > 1). When chained, each LTXVAddGuide uses only the parameters connected to it. | IC\_LORA\_PARAMETERS | No | - |

**Note:** The input image/video must have a frame count following the 8\*n + 1 pattern (e.g., 1, 9, 17, 25 frames). If the input exceeds this pattern, it will be automatically cropped to the nearest valid frame count.

**Note on `iclora_parameters`:** When using IC-LoRA parameters with a `reference_downscale_factor` greater than 1, the latent spatial dimensions (width and height) must be divisible by that factor. The node will raise an error if this condition is not met.

**Note:** The encoded guide frames must fit within the latent sequence at the selected frame position. If the conditioned frames exceed the length of the latent sequence, the node raises an error.

**Note:** Adding a guide to a latent that combines audio and video channels is not supported and will raise an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning updated with keyframe guidance information. | CONDITIONING |
| `negative` | Negative conditioning updated with keyframe guidance information. | CONDITIONING |
| `latent` | Latent sequence with incorporated conditioning frames and updated noise mask. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVAddGuide/en.md)

***

**Source fingerprint (SHA-256):** `031bc9030dafed85b5ff1cbceae36234e9d5f77f7f4b040267067ecd16a27929`


# LTXVAddLatentGuide - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVAddLatentGuide

The LTXV Add Latent Guide node pins an already-encoded latent as a guide, for when the guide comes out of an earlier stage rather than an image.

The LTXV Add Latent Guide node pins an already-encoded latent as a guide, for when the guide comes out of an earlier stage rather than an image. It has the same effect as LTXV Add Guide without the VAE decode/encode round trip. A guide that is spatially smaller than the target (an IC-LoRA or detailing reference) is dilated onto a sparse grid, and its RoPE end positions are expanded by the same ratio so it covers the target canvas instead of addressing only the top-left corner of it.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning input. | CONDITIONING | Yes | N/A |
| `negative` | Negative conditioning input. | CONDITIONING | Yes | N/A |
| `vae` | The VAE model used to read the downscale index formula for frame placement. | VAE | Yes | N/A |
| `latent` | Target video latent the guide is pinned onto. | LATENT | Yes | N/A |
| `guiding_latent` | Guide latent. Its spatial size must divide the target's by the same whole number on both axes; equal size pins it as-is, half size is treated as an x2 IC-LoRA reference. | LATENT | Yes | N/A |
| `latent_idx` | Latent frame index to start the guide at, counted in latent frames rather than pixel frames. Negative values place the guide on frames before the start of the latent, not counted back from its end. Default: 0. | INT | Yes | -9999 to 9999 |
| `strength` | Capped at 1.0. A dilated guide marks its padding positions with a negative denoise mask so the model drops them; above 1.0 the kept positions would go negative too and the whole guide would be dropped. Amplify beyond 1.0 with attention\_mask instead. Default: 1.0. | FLOAT | Yes | 0.0 to 1.0, step 0.01 |
| `attention_mask` | Optional pixel-space spatial mask. Controls per-region conditioning influence via self-attention, multiplied by strength. | MASK | No | N/A |

### Notes

* Both `latent` and `guiding_latent` must be 5D video latents shaped (batch, channels, frames, height, width).
* The guide must fit inside the target latent: the guide's frame count added to `latent_idx` must not run past the end of the target latent. Negative `latent_idx` values are allowed and place the guide before the start of the latent.
* The guide's spatial size must divide the target's spatial size by a whole number on both the height and width axes.
* The height ratio and the width ratio must be the same value (a square ratio). A non-square ratio raises an error, because the dilation and RoPE placement use a single downscale factor for both axes.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with the guide attached. | CONDITIONING |
| `negative` | Negative conditioning with the guide attached. | CONDITIONING |
| `latent` | Latent output with the guide applied, including the updated `noise_mask`. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVAddLatentGuide/en.md)

***

**Source fingerprint (SHA-256):** `19542500484dbc57fdbeeab8ba05bc2978246b3be5decc413825f616cab46f73`


# LTXVConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVConditioning

The LTXVConditioning node adds frame rate information to both positive and negative conditioning inputs for video generation models.

The LTXVConditioning node adds frame rate information to both positive and negative conditioning inputs for video generation models. It takes existing conditioning data and applies the specified frame rate value to both conditioning sets, making them suitable for video model processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning input that will receive the frame rate information | CONDITIONING | Yes | - |
| `negative` | The negative conditioning input that will receive the frame rate information | CONDITIONING | Yes | - |
| `frame_rate` | The frame rate value to apply to both conditioning sets (default: 25.0) | FLOAT | Yes | 0.0 - 1000.0 (step: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning with frame rate information applied | CONDITIONING |
| `negative` | The negative conditioning with frame rate information applied | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVConditioning/en.md)

***

**Source fingerprint (SHA-256):** `c8546b691329f2934995f97a6db2e1393d2928bf1a7438fd079d52f87bee1c35`


# LTXVCropGuides - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVCropGuides

The LTXVCropGuides node removes keyframe guidance data from a video generation workflow.

The LTXVCropGuides node removes keyframe guidance data from a video generation workflow. It counts the keyframes recorded in the positive conditioning, crops that many frames off the end of the latent samples and noise mask, and clears the keyframe index and guide attention entries from both conditioning inputs. When no keyframes are found, the conditioning inputs are returned unchanged and the latent is passed through with a cloned sample tensor and its noise mask.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning input containing guidance information for generation. The number of keyframes it holds determines how many frames are cropped from the latent. | CONDITIONING | Yes | - |
| `negative` | The negative conditioning input containing guidance information for what to avoid in generation. Its keyframe data is cleared along with the positive conditioning. | CONDITIONING | Yes | - |
| `latent` | The latent representation containing image samples and noise mask data. When keyframes are present, the final keyframe frames are removed from both the samples and the noise mask. | LATENT | Yes | - |

Note: Cropping only occurs when keyframe indices are detected in the positive conditioning. If no keyframes are detected, the positive and negative conditioning are returned unchanged, while the latent is still returned with a cloned sample tensor and an explicit noise mask (a mask of all ones is created if the input latent has none).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The processed positive conditioning with keyframe indices and guide attention entries cleared | CONDITIONING |
| `negative` | The processed negative conditioning with keyframe indices and guide attention entries cleared | CONDITIONING |
| `latent` | The cropped latent representation with adjusted samples and noise mask, where keyframe sections have been removed | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVCropGuides/en.md)

***

**Source fingerprint (SHA-256):** `83e08bad281902e765ec18e06144b6a5fa730be2533932daa1d4076e6390b1e1`


# LTXVDurationPredictor - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVDurationPredictor

This node predicts the natural shot duration for a text prompt using an LTX 2.4 duration head loaded with ModelPatchLoader, then snaps the result to the VAE's 8k+1 frame grid.

This node predicts the natural shot duration for a text prompt using an LTX 2.4 duration head loaded with ModelPatchLoader, then snaps the result to the VAE's 8k+1 frame grid. The prediction is converted into a frame count using the selected frame rate and the minimum and maximum duration limits.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model used to preprocess the text embeddings and run the duration head. | MODEL | Yes | N/A |
| `positive` | The conditioning that provides the prompt's text embeddings and metadata for the duration prediction. | CONDITIONING | Yes | N/A |
| `duration_head` | LTX 2.4 duration head loaded with ModelPatchLoader. Must be an LTX duration head. | MODEL\_PATCH | Yes | N/A |
| `frame_rate` | Frame rate in frames per second used to convert seconds to frames (default: 24.0). | FLOAT | Yes | 1.0 to 120.0 |
| `min_seconds` | Minimum duration in seconds used when converting the prediction to a frame count (default: 1.0). | FLOAT | Yes | 0.5 to 120.0 |
| `max_seconds` | Maximum duration in seconds used when converting the prediction to a frame count (default: 20.0). | FLOAT | Yes | 0.5 to 120.0 |

Note: The `duration_head` input must be a model patch containing an LTX duration head. If the connected model patch is not an LTX duration head, the node raises a ValueError. Only the first conditioning entry is used — if `positive` contains a batch of more than one prompt, the node evaluates just the first one.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `num_frames` | The predicted duration converted to a number of frames and snapped to the VAE's 8k+1 frame grid. | INT |
| `seconds` | Raw (unclamped) predicted duration. This is the value before snapping to the frame grid. | FLOAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVDurationPredictor/en.md)

***

**Source fingerprint (SHA-256):** `a4abb43128b8fe396e4c986d75028aea6bfdd9bb6fda07e24c88f8e04a61669e`


# LTXVGeneratedKeyframesToGuides - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVGeneratedKeyframesToGuides

The LTXV Generated Keyframes to Guides node pins generated keyframes from an earlier stage as frozen image guides on a later canvas.

The LTXV Generated Keyframes to Guides node pins generated keyframes from an earlier stage as frozen image guides on a later canvas. It decodes the keyframes as standalone frames, resizes them if needed, and writes them with a noise mask of 0 so they are not denoised again. After a temporal upscale, recorded indices are scaled from the canvas they were generated on onto this one; use `override_frame_indices` to set positions explicitly.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning to add the keyframe guides to. | CONDITIONING | Yes | |
| `negative` | Negative conditioning to add the keyframe guides to. | CONDITIONING | Yes | |
| `vae` | The VAE used to decode the keyframes if resizing is needed. | VAE | Yes | |
| `latent` | The target video latent to add the guides to, e.g. the temporally upscaled one. | LATENT | Yes | |
| `keyframes` | The keyframes output of LTXV Separate Generated Keyframes, which carries the pixel frame index each keyframe was generated at. | LATENT | Yes | |
| `strength` | Guide strength. 1.0 is a hard pin; lower values relax it. (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 (step 0.01) |
| `override_frame_indices` | Optional — pin at these pixel frames instead of the recorded (or auto-scaled) positions. Provide one index per keyframe. Leave empty to reuse recorded positions, or to scale them when the target canvas is a different length (e.g. after temporal x2). (default: "") | STRING | No | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with the keyframes pinned as image guides. | CONDITIONING |
| `negative` | Negative conditioning with the keyframes pinned as image guides. | CONDITIONING |
| `latent` | Target video latent with the keyframes added as frozen guides. | LATENT |

## Notes

* The `keyframes` input must be connected to the keyframes output of LTXV Separate Generated Keyframes. The node raises an error if the latent does not carry generated keyframe positions.
* The `positive` and `negative` conditioning inputs must come from the positive and negative outputs of LTXV Separate Generated Keyframes. The node raises an error if the positive conditioning still carries generated keyframes.
* The `latent` input must be a plain video latent (5D tensor). Guides must be added before merging the video and audio latents with Concat AV Latent.
* Only a batch size of 1 is supported. Each guide is encoded from one image, so it cannot differ across batch elements.
* The number of keyframes in the `keyframes` latent must match the number of recorded positions; otherwise an error is raised.
* If `override_frame_indices` is left empty, recorded positions are used. If the target canvas has a different number of frames than the canvas the keyframes were generated on, the recorded indices are scaled automatically.
* If `override_frame_indices` is provided, it must contain one integer index per keyframe, separated by commas or spaces. Indices must be unique and lie between 1 and (number of pixel frames in the target latent - 1). Otherwise an error is raised.
* If any final keyframe index is greater than or equal to the number of pixel frames in the target latent, the node raises an error. This can happen when the target was resized temporally after the keyframes were generated.
* The `strength` parameter has a minimum of 0.0 and a maximum of 10.0.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVGeneratedKeyframesToGuides/en.md)

***

**Source fingerprint (SHA-256):** `b5dbf302fad5a7ffd3522d468d1a51b993145d90277592058315499f08e17e7b`


# LTXVImgToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVImgToVideo

LTXVImgToVideo converts an input image into a video latent representation for video generation models.

LTXVImgToVideo converts an input image into a video latent representation for video generation models. It resizes the image to the requested width and height, encodes it with the VAE, and places the encoded frames at the start of a video-sized latent of zeros. The strength control determines how much of the original image content is preserved versus modified during video generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning prompts for guiding the video generation | CONDITIONING | Yes | - |
| `negative` | Negative conditioning prompts for avoiding certain elements in the video | CONDITIONING | Yes | - |
| `vae` | VAE model used for encoding the input image into latent space | VAE | Yes | - |
| `image` | Input image to be converted into video frames | IMAGE | Yes | - |
| `width` | Output video width in pixels (default: 768, step: 32) | INT | Yes | 64 to MAX\_RESOLUTION |
| `height` | Output video height in pixels (default: 512, step: 32) | INT | Yes | 64 to MAX\_RESOLUTION |
| `length` | Number of frames in the generated video (default: 97, step: 8) | INT | Yes | 9 to MAX\_RESOLUTION |
| `batch_size` | Number of videos to generate simultaneously (default: 1) | INT | Yes | 1 to 4096 |
| `strength` | Control over how much of the original image content is preserved in the first frames of the generated video. A value of 1.0 preserves the original image completely, while 0.0 allows maximum modification (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |

Note: `width` and `height` change in steps of 32 pixels, and `length` changes in steps of 8 frames, matching the video latent compression (32x in the spatial dimensions and 8x in the temporal dimension). The video latent contains ((length - 1) // 8) + 1 frames. The input image is resized to `width` x `height` using bilinear scaling with center cropping, and only the first three channels are used for encoding.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning passed through unchanged for use with the generated latent | CONDITIONING |
| `negative` | The negative conditioning passed through unchanged for use with the generated latent | CONDITIONING |
| `latent` | Video latent representation containing the encoded image frames and a noise mask that controls how strongly the conditioning is applied during video generation | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVImgToVideo/en.md)

***

**Source fingerprint (SHA-256):** `4ebc7f80b4d9ac3329e3349c7048885de22b827b5bdd102976687afd7e07a16b`


# LTXVImgToVideoInplace - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVImgToVideoInplace

LTXVImgToVideoInplace encodes an input image into the latent space and places those encoded frames at the start of an existing latent video.

LTXVImgToVideoInplace encodes an input image into the latent space and places those encoded frames at the start of an existing latent video. The `strength` value controls how strongly the encoded image conditions those initial frames, and when `bypass` is enabled, the input latent is returned unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `vae` | The VAE model used to encode the input image into the latent space. | VAE | Yes | - |
| `image` | The input image to be encoded and used to condition the video latent. | IMAGE | Yes | - |
| `latent` | The target latent video representation to be modified. | LATENT | Yes | - |
| `strength` | Controls how strongly the encoded image conditions the initial frames of the latent. A value of 1.0 fully conditions the initial frames with the encoded image, while lower values condition them less strongly. The noise mask for the initial frames is set to `1.0 - strength`. (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `bypass` | Bypass the conditioning. When enabled, the node returns the input latent unchanged. (default: False) | BOOLEAN | Yes | True or False |

**Note:** The `image` will be automatically resized to match the spatial dimensions required by the `vae` for encoding, based on the `latent` input's width and height. Only the RGB channels of the `image` are used for encoding.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latent` | The resulting latent video representation. When bypass is disabled, it contains the updated `samples` and a `noise_mask` that applies the conditioning strength to the initial frames. When bypass is enabled, it is the input latent returned unchanged. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVImgToVideoInplace/en.md)

***

**Source fingerprint (SHA-256):** `69faa4b2e7b0fedeee531dc5a8809e23a79c9ce03e9760afb865160594fef30d`


# LTXVReferenceAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVReferenceAudio

LTXV Reference Audio transfers the voice identity of a speaker from a reference audio clip to generated audio.

LTXV Reference Audio transfers the voice identity of a speaker from a reference audio clip to generated audio. It encodes the reference audio into the conditioning and optionally patches the model with identity guidance, which runs an extra forward pass without the reference each step to amplify the speaker identity effect.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to be patched with identity guidance. | MODEL | Yes | - |
| `positive` | The positive conditioning input. | CONDITIONING | Yes | - |
| `negative` | The negative conditioning input. | CONDITIONING | Yes | - |
| `reference_audio` | Reference audio clip whose speaker identity to transfer. \~5 seconds recommended (training duration). Shorter or longer clips may degrade voice identity transfer. | AUDIO | Yes | - |
| `audio_vae` | LTXV Audio VAE for encoding. | VAE | Yes | - |
| `identity_guidance_scale` | Strength of identity guidance. Runs an extra forward pass without reference each step to amplify speaker identity. Set to 0 to disable (no extra pass). (default: 3.0) | FLOAT | Yes | 0.0 - 100.0 |
| `start_percent` | Start of the sigma range where identity guidance is active. (default: 0.0) | FLOAT | Yes | 0.0 - 1.0 |
| `end_percent` | End of the sigma range where identity guidance is active. (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |

Note: Identity guidance is only applied when `identity_guidance_scale` is greater than 0 and the current sampling step is within the range defined by `start_percent` and `end_percent`. The reference audio is resampled to the audio VAE's sample rate if the two differ.

Note: `start_percent` and `end_percent` are advanced parameters, shown only when advanced options are enabled in the interface.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The model patched with the identity guidance function. | MODEL |
| `positive` | The positive conditioning, now containing the encoded reference audio data. | CONDITIONING |
| `negative` | The negative conditioning, now containing the encoded reference audio data. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVReferenceAudio/en.md)

***

**Source fingerprint (SHA-256):** `ae15c5838656324667d099614b325b863341f05afda43054658999574522dd49`


# LTXVSeparateGeneratedKeyframes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVSeparateGeneratedKeyframes

Documentation for LTXVSeparateGeneratedKeyframes node.

## Overview

The LTXV Separate Generated Keyframes node splits the generated keyframes added by LTXV Add Generated Keyframes back out of a sampled latent and removes them from the conditioning. Use it before spatially upscaling the video latent. Do not run LTXV Crop Guides first — it treats generated keyframes as disposable guides and drops them.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning that holds the generated-keyframe metadata. The metadata is removed from it on output. | CONDITIONING | Yes | N/A |
| `negative` | Negative conditioning that holds the generated-keyframe metadata. The metadata is removed from it on output. | CONDITIONING | Yes | N/A |
| `latent` | Video latent that contains the generated keyframes. The keyframes are stripped from it on output. | LATENT | Yes | N/A |
| `keyframes_to_batch` | Return the keyframes as a batch of single-frame latents. Leave off to get them as one multi-frame latent, which is what the latent upsampler and a later Add Generated Keyframes expect. | BOOLEAN | No | default: False |

### Notes on Inputs

* `positive` must contain generated-keyframe metadata, otherwise the node raises an error telling you to add them with LTXV Add Generated Keyframes first.
* `latent` must be a plain video latent (a 5D tensor). If the video and audio latents are still combined, split them with Separate AV Latent first.
* The number of tokens per latent frame recorded when the keyframes were added must match the tokens per frame of the supplied `latent`. If the latent was rescaled after the keyframes were added, they no longer line up and the node raises an error — separate them before upscaling the latent.
* The recorded keyframe frame range must fit inside the supplied `latent`, otherwise the node raises an error that the keyframes were recorded against a different latent.
* The recorded guide attention entry index must still exist in the conditioning. If the conditioning was rebuilt after the keyframes were added, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with generated-keyframe metadata removed. | CONDITIONING |
| `negative` | Negative conditioning with generated-keyframe metadata removed. | CONDITIONING |
| `latent` | Video latent with the generated keyframes stripped. | LATENT |
| `keyframes` | The peeled keyframes, labeled with generated\_keyframe\_indices and generated\_keyframe\_num\_frames. Feed these to a later Add Generated Keyframes to initialize new slots, or to Generated Keyframes To Guides to pin them as frozen image guides (indices are remapped if the canvas length changed). | LATENT |

## Notes

* The `keyframes_to_batch` parameter determines whether the keyframes are returned as a batch of single-frame latents or as one multi-frame latent.
* The node ensures that the generated keyframes are removed from the conditioning and the latent before any further processing.
* The `keyframes` output can be used to initialize new slots for generated keyframes or to pin them as frozen image guides.
* The node raises a `ValueError` if the latent does not contain generated keyframes or if the keyframes do not match the expected format.
* The node assumes that the generated keyframes were added using the LTXV Add Generated Keyframes node and that they are compatible with the current latent.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVSeparateGeneratedKeyframes/en.md)

***

**Source fingerprint (SHA-256):** `295e49181e87445a1c47b2e9413d95b20585b12e89f26f13129ac5d97f913007`


# LotusConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LotusConditioning

The LotusConditioning node supplies fixed, pre-computed conditioning embeddings for the Lotus model.

The LotusConditioning node supplies fixed, pre-computed conditioning embeddings for the Lotus model. Because Lotus uses a frozen encoder with null conditioning, the node inlines the resulting prompt embeddings directly instead of running inference or loading large tensor files, so its output never changes. The returned conditioning can be plugged straight into a generation pipeline that expects Lotus-compatible conditioning.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| *No inputs* | This node does not accept any input parameters. | - | - | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `conditioning` | The pre-computed conditioning embeddings for the Lotus model. Returned as a conditioning list holding the fixed prompt embeddings together with an empty dictionary. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LotusConditioning/en.md)

***

**Source fingerprint (SHA-256):** `1fcb6530850341253c8acb47b2f26ee79d93f51eca84bef03a1fa5de33d6bc8d`


# MiniMaxH3AddGuide - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MiniMaxH3AddGuide

This node anchors an image, a short clip, audio, or a clip with its soundtrack at any frame of a MiniMax H3 video.

This node anchors an image, a short clip, audio, or a clip with its soundtrack at any frame of a MiniMax H3 video. It adds a guide keyframe to the conditioning at the chosen frame index, and you can chain several of these nodes to anchor several frames in the same video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The conditioning to which the guide keyframe is attached. | CONDITIONING | Yes | - |
| `vae` | Video VAE, needed when an image is connected. | VAE | No | - |
| `audio_vae` | Audio VAE, needed when an audio is connected. | VAE | No | - |
| `latent` | The MiniMax H3 audio-video latent that defines the target video. Must be a MiniMax H3 AV latent (nested, with two 5D tensors, the video tensor having 24 channels). | LATENT | Yes | - |
| `image` | Image or video frames to anchor. Multi-frame batches are anchored as a clip and cropped down to the model's valid clip lengths: 5, 22, 39... (17k + 5) frames. Batches shorter than 5 frames use only the first image. | IMAGE | No | - |
| `audio` | Soundtrack to anchor starting at the same frame index, cropped to the video's remaining duration. | AUDIO | No | - |
| `frame_idx` | Frame index to anchor the image or the clip's first frame at. Negative values are counted from the end of the video. (default: 0) | INT | Yes | -9999 to 9999 |

**Constraints:**

* At least one of `image` or `audio` must be provided; otherwise the node raises an error.
* `vae` is required when `image` is connected.
* `audio_vae` is required when `audio` is connected.
* `image` batches with fewer than 5 frames use only the first image; batches of 5 or more frames are cropped down to a valid clip length (5, 22, 39, etc.).
* `frame_idx` must place the guide within the video's frame range, and a multi-frame clip must fit entirely in the video; otherwise the node raises an error.
* When audio is connected, the frame index must not be past the end of the video's audio track.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The conditioning with the guide keyframe added, containing the resolved frame index and, when provided, the encoded image or audio latents. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MiniMaxH3AddGuide/en.md)

***

**Source fingerprint (SHA-256):** `7a2f742421cc2655bd9c914258801e4538f1554a7c5e2b0836b2df1577f5a104`


# MiniMaxH3ImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MiniMaxH3ImageToVideo

This node prepares the conditioning and empty latent needed to generate a video with the MiniMax H3 model.

This node prepares the conditioning and empty latent needed to generate a video with the MiniMax H3 model. It takes a text prompt and, optionally, images for the first and/or last frame of the video, and converts them into model inputs. Keyframe images are resized, encoded, and attached to the conditioning at the start and end of the video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | CLIP model used to tokenize the prompt and encode the keyframe images into conditioning. | CLIP | Yes | |
| `vae` | VAE model used to encode the keyframe images into latent space when keyframe images are provided. | VAE | Yes | |
| `prompt` | Text prompt describing the video to generate. Supports multiple lines and dynamic prompts. | STRING | Yes | |
| `width` | Width of the video in pixels (default: 1344). | INT | Yes | 32 to MAX\_RESOLUTION (step 32) |
| `height` | Height of the video in pixels (default: 768). | INT | Yes | 32 to MAX\_RESOLUTION (step 32) |
| `length` | Frame count at 24 fps, snapped up to the model's 17k+5 grid (124 = \~5s; trained range is \~124-362, longer is untested) (default: 124). | INT | Yes | 5 to 3600 (step 17) |
| `first_frame` | Optional image used as the first frame of the video. It is stretched to the full canvas size, so its aspect ratio is not preserved. Only the first image of the input batch is used. | IMAGE | No | |
| `last_frame` | Optional image used as the last frame of the video. It is cropped to cover the canvas while preserving its aspect ratio. Only the first image of the input batch is used. | IMAGE | No | |

When `first_frame` and/or `last_frame` are provided, the keyframe images are encoded with the VAE and attached to the conditioning at frame 0 and at the final frame, respectively. When neither is provided, the node works from the prompt alone. The requested `length` is snapped up to the nearest valid frame count (17k + 5), so the effective frame count may be slightly higher than requested.

The audio-video latent is created as an empty pair matching the requested `width`, `height`, and the snapped frame count. The audio portion is sized from the same frame count at 40 audio frames per second.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Conditioning containing the encoded prompt and, when keyframe images are provided, the encoded keyframes and frame count for the MiniMax H3 model. | CONDITIONING |
| `latent` | Empty audio-video latent representing the content to be generated, with the requested width, height, and frame count. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MiniMaxH3ImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `d1bdf3f8c66ef20ff11c35203d2c266a88dcf8cc00c65dbb0aea2b1dd16befd6`


# MiniMaxH3ReferenceToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MiniMaxH3ReferenceToVideo

MiniMax H3 Reference to Video creates the text conditioning and the empty audio-video latent needed for MiniMax H3 reference-to-video generation.

MiniMax H3 Reference to Video creates the text conditioning and the empty audio-video latent needed for MiniMax H3 reference-to-video generation. You provide a prompt plus optional reference images, videos, and audio clips, and the node encodes these references into conditioning the model can use while generating. The prompt refers to the references with `<Picture i>`, `<Video k>`, and `<Audio j>` tags.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | CLIP model used to tokenize the prompt and encode the reference media into conditioning tokens. | CLIP | Yes | |
| `vae` | Video VAE. Without it reference images/videos only condition the text encoder. | VAE | No | |
| `audio_vae` | Audio VAE. Without it reference audio only conditions the text encoder. | VAE | No | |
| `prompt` | Text prompt for the video. Reference media can be addressed with `<Picture i>`, `<Video k>`, and `<Audio j>` tags (1-based per type). Supports multiline and dynamic prompts. | STRING | Yes | |
| `width` | Width of the generated video in pixels (default: 1344). | INT | Yes | 32 to 16384 (step 32) |
| `height` | Height of the generated video in pixels (default: 768). | INT | Yes | 32 to 16384 (step 32) |
| `length` | Frame count at 24 fps, (124 = \~5s, trained range is \~124-362) (default: 124). | INT | Yes | 5 to 3600 (step 17) |
| `ref_image_size` | Reference image sizing. `match` scales each ref (down only, keeping aspect) to the generation's pixel area; `max` uses the reference pipeline's 2048px short edge for best identity fidelity. Reference tokens ride through every sampling step, so `max` can be several times slower (default: `match`). | COMBO | Yes | `"match"`<br />`"max"` |
| `ref_images` | Growable slot: connect up to 9 reference images (`ref_image_1` ... `ref_image_9`). Reference image (downscaled to 2048 short edge if larger, never upscaled). | IMAGE | No | 0 to 9 |
| `ref_videos` | Growable slot: connect up to 3 reference videos (`ref_video_1` ... `ref_video_3`). Reference video frames at 24 fps (2-15s). | IMAGE | No | 0 to 3 |
| `ref_video_audios` | Growable slot: connect up to 3 soundtracks (`ref_video_audio_1` ... `ref_video_audio_3`). Soundtrack of the same-numbered reference video. | AUDIO | No | 0 to 3 |
| `ref_audios` | Growable slot: connect up to 3 standalone reference audio clips (`ref_audio_1` ... `ref_audio_3`). Standalone reference audio. | AUDIO | No | 0 to 3 |

Notes:

* The prompt refers to reference media with 1-based tags per type: `<Picture i>` for images, `<Video k>` for videos, and `<Audio j>` for audio. References are presented to the model in a fixed order: images, then videos (with each soundtrack's `<Audio j>` label right before its `<Video k>`), then standalone audio.
* A soundtrack connected to `ref_video_audio_N` is used with the reference video connected to `ref_video_N`.
* Reference videos must contain at least 5 frames (\~0.2 seconds at 24 fps), otherwise the node raises an error. Frames beyond the requested `length` are trimmed, and the remaining frame count is adjusted to a value supported by the model.
* The requested `length` is aligned to a supported frame count before the latent is created.
* Without `vae`, reference images and videos only condition the text encoder (no reference latents are produced). Without `audio_vae`, reference audio only conditions the text encoder.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Conditioning containing the encoded prompt. When reference media and the relevant VAEs are provided, it also contains the encoded reference image, video, and audio content used by the MiniMax H3 model. | CONDITIONING |
| `latent` | Empty audio-video latent at the requested `width`, `height`, and `length` (frame count), including the aligned video latent and audio latent. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MiniMaxH3ReferenceToVideo/en.md)

***

**Source fingerprint (SHA-256):** `47df0d6d13cb02aa4f69b50a7f8d0f6c1639c1fb5e0f69bf8fc57dd4cb752db8`


# MiniMaxMusic3TextEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MiniMaxMusic3TextEncode

MiniMax Music3 Text Encode uses a MiniMax Music3 CLIP model to convert text captions and lyrics into an acoustic conditioning sequence for music generation.

MiniMax Music3 Text Encode uses a MiniMax Music3 CLIP model to convert text captions and lyrics into an acoustic conditioning sequence for music generation. The node returns the resulting CONDITIONING data, along with the actual audio duration in seconds calculated from the input maximum duration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The MiniMax Music3 CLIP model, used for text encoding and conditioning sequence generation. | CLIP | Yes | - |
| `caption` | Text describing the music to generate. Supports multi-line text and dynamic prompts. | STRING | Yes | - |
| `lyrics` | The lyrics text to be used for generating the music. Supports multi-line text and dynamic prompts. | STRING | Yes | - |
| `seed` | Reproducible random seed for the generation process. Default: 0. A control-after-generate widget is provided. | INT | Yes | 0 to 18446744073709551615 (0xffffffffffffffff) |
| `max_duration` | Maximum duration in seconds; the model can end the song earlier. Default: 120.0. | FLOAT | Yes | 0.04 to the model's maximum audio duration (MAX\_AUDIO\_FRAMES / AUDIO\_FRAMES\_PER\_SECOND), step 0.04 |
| `cfg_scale` | Classifier-free guidance scale. Default: model constant CFG\_SCALE. Advanced parameter. | FLOAT | Yes | 0.0 to 100.0, step 0.1 (keeps 2 decimal places) |
| `top_k` | Top-k sampling value used for acoustic token selection. Default: model constant CFG\_TOP\_K. Advanced parameter. | INT | Yes | 1 to the model's vocabulary size (C0\_VOCAB\_SIZE) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `conditioning` | The generated acoustic conditioning sequence, used to guide subsequent music generation. | CONDITIONING |
| `seconds` | The actual duration of the conditioning sequence, in seconds. | FLOAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MiniMaxMusic3TextEncode/en.md)

***

**Source fingerprint (SHA-256):** `c3fbfd189d0358ebf081dd4f9c32be9231a9d0b97fd767401ea4b7955224c25c`


# PhotoMakerEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PhotoMakerEncode

The PhotoMakerEncode node combines a reference image with a text prompt to create conditioning data for image generation.

The PhotoMakerEncode node combines a reference image with a text prompt to create conditioning data for image generation. When the text contains the word "photomaker", the node uses the PhotoMaker model to insert the visual identity of the reference image into the conditioning at that position in the prompt.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `photomaker` | The PhotoMaker model used to process the reference image and generate image-based embeddings | PHOTOMAKER | Yes | - |
| `image` | The reference image that provides the visual characteristics for the conditioning | IMAGE | Yes | - |
| `clip` | The CLIP model used for text tokenization and text encoding | CLIP | Yes | - |
| `text` | The text prompt for conditioning generation. Supports multiline text and dynamic prompts (default: "photograph of photomaker") | STRING | Yes | Any string |

**Note:** When the text contains "photomaker" as a standalone word, the node removes that word from the encoded prompt and applies the reference image's identity at that position using the PhotoMaker model. If "photomaker" is not found in the text, the node returns standard text conditioning without image influence.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Conditioning data containing the text and image embeddings that guide image generation, together with the pooled output from the CLIP text encoder | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PhotoMakerEncode/en.md)

***

**Source fingerprint (SHA-256):** `490a90c504ade253c2bb055e0efb1eb015ba6d7faf8f2370cac188871f678986`


# Pixal3DConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Pixal3DConditioning

The Pixal3DConditioning node prepares image conditioning for the Trellis2 3D generation pipeline.

The Pixal3DConditioning node prepares image conditioning for the Trellis2 3D generation pipeline. It uses a DINOv3 vision model to extract visual features from the input image at two resolutions (512 and 1024), then organizes them into per-stage feature maps that can be optionally enhanced by a NAF model. Camera information is derived from the horizontal field of view to build the projection transform matrix, and the node outputs a positive conditioning pair (image-derived features plus projection data) and a negative conditioning pair (zeroed feature tensors) for classifier-free guidance.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_vision_model` | DINOv3 ViT-L/16 ClipVision. | CLIP\_VISION | Yes | — |
| `image` | Preprocessed image from ImageCropToMask (pad\_factor=1.1 for Pixal3D). | IMAGE | Yes | — |
| `camera_angle_x` | Horizontal FOV in degrees (displayed as `fov`). Wire a MoGeGeometryToFOV (axis='horizontal', unit='degrees') for a per-image FoV (matches upstream default). Default: 49.13. | FLOAT | Yes | 1.0 – 170.0 (step 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning output containing the image-derived feature maps and projection data for Trellis2 generation. | CONDITIONING |
| `negative` | The negative conditioning output with zeroed feature tensors, used for classifier-free guidance. | CONDITIONING |

Note: The `camera_angle_x` value is converted from degrees to radians internally, and the camera distance is computed from it to build the projection transform matrix. When the supplied vision model includes a NAF component, the node also produces high-resolution feature maps for the shape and texture stages.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Pixal3DConditioning/en.md)

***

**Source fingerprint (SHA-256):** `88e82b48fbe297c8e32ddd1b6659f196bda6f77fd53480bc021e85170d1923c7`


# Pixal3DMultiViewConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Pixal3DMultiViewConditioning

The Pixal3D Multi-View Conditioning node builds conditioning data from a fixed orbit camera rig: front, left, back, and right views placed 90 degrees apart, used exactly as framed.

The Pixal3D Multi-View Conditioning node builds conditioning data from a fixed orbit camera rig: front, left, back, and right views placed 90 degrees apart, used exactly as framed. Connect at least one square view of the object and it prepares matching positive and negative conditioning for Pixal3D models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_vision_model` | DINOv3 ViT-L/16 ClipVision with bundled NAF weights. | CLIP\_VISION | Yes | N/A |
| `fov` | Horizontal FOV in degrees of the views as framed: 20 for rig renders and most multi-view generators, or MoGeGeometryToFOV on one of the views for photos. Default: 20.0. | FLOAT | Yes | 1.0 - 170.0 |
| `front` | Square view of the object's front side, with alpha or on a black background, framed like the rig: the object spans about 1/1.1 of the frame at its widest, the same scale in every view. The first connected view (front, left, back, right order) is the front the mesh is posed to. | IMAGE | No | N/A |
| `left` | Square view of the object's left side, with alpha or on a black background, framed like the rig: the object spans about 1/1.1 of the frame at its widest, the same scale in every view. The first connected view (front, left, back, right order) is the front the mesh is posed to. | IMAGE | No | N/A |
| `back` | Square view of the object's back side, with alpha or on a black background, framed like the rig: the object spans about 1/1.1 of the frame at its widest, the same scale in every view. The first connected view (front, left, back, right order) is the front the mesh is posed to. | IMAGE | No | N/A |
| `right` | Square view of the object's right side, with alpha or on a black background, framed like the rig: the object spans about 1/1.1 of the frame at its widest, the same scale in every view. The first connected view (front, left, back, right order) is the front the mesh is posed to. | IMAGE | No | N/A |

### Notes

* At least one view must be connected; the node raises an error if all four view inputs are empty.
* The first connected view, in front, left, back, right order, is treated as the front, and the mesh is posed to that view. If the first connected view is not `front`, a warning is logged stating that the mesh will be posed with that view as its front.
* Views are read in the order front, left, back, right, and are placed on the orbit at their fixed azimuths relative to the first connected view.
* Input views with an alpha channel have the alpha applied over black. Views that are not 1024 x 1024 are resized to 1024 x 1024.
* The batch size is taken from the first connected view. If the connected views have different batch sizes, the smaller ones are cycled to match.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning output, built from the encoded views and their projected features. | CONDITIONING |
| `negative` | The negative conditioning output, built from zeroed embeddings with the same projected features. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Pixal3DMultiViewConditioning/en.md)

***

**Source fingerprint (SHA-256):** `e6319ebd1a557dbb48269bab8a667e78e48f446d87fffbd9df4c4ebfb62b0fac`


# QwenImage21Cache - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QwenImage21Cache

The QwenImage21Cache node configures the KV prefix cache of the Qwen-Image 2.1 model: where the cached keys and values are stored and at what precision.

The QwenImage21Cache node configures the KV prefix cache of the Qwen-Image 2.1 model: where the cached keys and values are stored and at what precision. Text and reference tokens are computed once and reused across sampling steps, which is where most of the speedup on edit workflows comes from, and this node lets you trade memory for speed or rule the cache out entirely. This node is marked as experimental.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Qwen-Image 2.1 model whose prefix cache is configured. | MODEL | Yes | - |
| `device` | Where the cached keys and values are stored. `"auto"` (default) uses spare VRAM first and then RAM; `"gpu"` stores the cache in VRAM; `"cpu"` stores it in RAM and prefetches it behind compute, which costs little speed; `"off"` recomputes the prefix every step, which is slower but is the only way to rule the cache out. | COMBO | Yes | `"auto"`<br />`"gpu"`<br />`"cpu"`<br />`"off"` |
| `dtype` | Storage precision of the cache. `"default"` is lossless; `"int8"` halves the cache at about bf16 accuracy; `"int4"` quarters it but roughly doubles the per-step error. | COMBO | Yes | `"default"`<br />`"int8"`<br />`"int4"` |

When the cache does not fit, the model recomputes the prefix instead of evicting the other branch's slot, so an oversized setting degrades speed rather than failing the run.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The model with the cache device and precision applied, ready to be sampled. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/QwenImage21Cache/en.md)

***

**Source fingerprint (SHA-256):** `0c10cdb465d1ee4063273ffbb4913def3830f7e329694cd0a2e292d6f3c37ae4`


# SCAIL2ColoredMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SCAIL2ColoredMask

This node renders SAM3 tracking data into colored masks that are consumed by the WanSCAILToVideo node.

This node renders SAM3 tracking data into colored masks that are consumed by the WanSCAILToVideo node. It processes tracking data from a driving pose video and optionally a reference image, assigning consistent colors to each tracked person across both outputs.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `driving_track_data` | SAM3 track of the driving pose video. Will be rendered into the pose\_video\_mask output. | SAM3\_TRACK\_DATA | Yes | - |
| `ref_track_data` | SAM3 track of the reference image(s) (one identity per object, colored in batch order), or a plain MASK of the reference subject (rendered as a single identity). | SAM3\_TRACK\_DATA or MASK | No | - |
| `object_indices` | Comma-separated list of person indices to include (e.g. '0,2,3'). Applied to both reference and pose video masks. Empty = all. (default: "") | STRING | Yes | - |
| `sort_by` | Order in which palette colors are assigned to the tracked objects (applied to both reference and pose video so each identity keeps the same color). Objects that appear in earlier frames always come first; within a frame, left\_to\_right = leftmost object (by centroid at first appearance) gets the first color, area = biggest object (by mask area at first appearance) gets the first color; none = keep SAM3's order. (default: "left\_to\_right") | COMBO | Yes | `"none"`<br />`"left_to_right"`<br />`"area"` |
| `replacement_mode` | False = Animation Mode (pose\_video\_mask has black background, reference\_image\_mask has white background). True = Replacement Mode (pose\_video\_mask has white background, reference\_image\_mask has black background). (default: False) | BOOLEAN | Yes | False<br />True |

Note: `object_indices` only accepts comma-separated digits; non-numeric entries and out-of-range indices are ignored. When `ref_track_data` is not provided, the `reference_image_mask` output is a solid fill using the reference background color (white in Animation Mode, black in Replacement Mode).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `pose_video_mask` | Colored mask rendered from the driving pose video tracking data. Background color follows replacement\_mode setting. | IMAGE |
| `reference_image_mask` | Colored mask rendered from the reference image tracking data. Background is black in Replacement Mode, white in Animation Mode. If no reference data is provided, returns a solid fill matching the reference background color. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SCAIL2ColoredMask/en.md)

***

**Source fingerprint (SHA-256):** `ce0669ad0ed3c76cc18ef0ee7b620f5aa6eaa1e5b96c189941c0a5b744c3351f`


# SD_4XUpscale_Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SD_4XUpscale_Conditioning

The SD4XUpscaleConditioning node prepares conditioning data for upscaling images with diffusion models.

The SD\_4XUpscale\_Conditioning node prepares conditioning data for upscaling images with diffusion models. It scales the input images by a chosen ratio, adds optional noise augmentation, and returns modified positive and negative conditioning together with an empty latent for the upscaled size.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Input images to be upscaled. | IMAGE | Yes | - |
| `positive` | Positive conditioning data that guides the generation toward desired content. | CONDITIONING | Yes | - |
| `negative` | Negative conditioning data that steers the generation away from unwanted content. | CONDITIONING | Yes | - |
| `scale_ratio` | Multiplier applied to the input image dimensions when preparing the upscaled conditioning and latent (default: 4.0). | FLOAT | Yes | 0.0 - 10.0 (step 0.01) |
| `noise_augmentation` | Amount of noise to add during the upscaling process (default: 0.0). | FLOAT | Yes | 0.0 - 1.0 (step 0.001) |

Note: `noise_augmentation` is an advanced parameter, shown in the node interface under the "Advanced" toggle.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Modified positive conditioning with the scaled image data and noise augmentation settings applied. | CONDITIONING |
| `negative` | Modified negative conditioning with the scaled image data and noise augmentation settings applied. | CONDITIONING |
| `latent` | Empty latent representation matching the upscaled dimensions. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SD_4XUpscale_Conditioning/en.md)

***

**Source fingerprint (SHA-256):** `f215e890bd86f42d4da9c6f575fc92e65844e2e2056c5610310d8089e5d61902`


# SV3D_Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SV3D_Conditioning

SV3DConditioning prepares conditioning data for 3D video generation using the SV3D model.

SV3D\_Conditioning prepares conditioning data for 3D video generation using the SV3D model. It takes an initial image and processes it through CLIP vision and VAE encoders to create positive and negative conditioning, along with a latent representation. The node generates camera elevation and azimuth sequences for multi-frame video generation based on the specified number of video frames.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_vision` | The CLIP vision model used for encoding the input image | CLIP\_VISION | Yes | - |
| `init_image` | The initial image that serves as the starting point for 3D video generation | IMAGE | Yes | - |
| `vae` | The VAE model used for encoding the image into latent space | VAE | Yes | - |
| `width` | The output width for the generated video frames (default: 576, step of 8) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | The output height for the generated video frames (default: 576, step of 8) | INT | Yes | 16 to MAX\_RESOLUTION |
| `video_frames` | The number of frames to generate for the video sequence (default: 21) | INT | Yes | 1 to 4096 |
| `elevation` | The camera elevation angle in degrees for the 3D view (default: 0.0, step of 0.1) | FLOAT | Yes | -90.0 to 90.0 |

Note: The camera azimuth starts at 0 degrees and increases by a constant amount each frame so that the camera completes a full 360-degree orbit around the object across the generated frames. The per-frame increment is calculated as 360 divided by (`video_frames` - 1), using a minimum divisor of 2 when only one frame is requested. The `elevation` value stays constant for every frame.

The `init_image` is scaled to the specified `width` and `height` before VAE encoding, and the returned latent uses dimensions of `video_frames` x 4 x (`height` // 8) x (`width` // 8).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning data containing image embeddings and camera parameters for generation | CONDITIONING |
| `negative` | The negative conditioning data with zeroed embeddings and latents for contrastive generation | CONDITIONING |
| `latent` | An empty latent tensor with dimensions matching the specified video frames and resolution | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SV3D_Conditioning/en.md)

***

**Source fingerprint (SHA-256):** `e28173cfa560290e66b032687088cf0b981256ca5c21f6aa608e0fdaec886665`


# SetUnionControlNetType - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetUnionControlNetType

The SetUnionControlNetType node lets you choose which control type a control network uses.

The SetUnionControlNetType node lets you choose which control type a control network uses. It takes an existing control network and creates a modified copy with the selected control type, leaving the original control network unchanged. When "auto" is selected, the stored control type is cleared so the type can be detected automatically.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `control_net` | The control network to modify with a new type setting | CONTROL\_NET | Yes | - |
| `type` | The control network type to apply. Use "auto" for automatic type detection or select a specific control network type from the available options (default: "auto") | COMBO | Yes | `"auto"`<br />`"openpose"`<br />`"depth"`<br />`"hed/pidi/softedge"`<br />`"canny"`<br />`"scribble"`<br />`"seg"`<br />`"tile"`<br />`"inpaint"`<br />`"lineart"`<br />`"blur"`<br />`"mlsd"`<br />`"normalbae"`<br />`"mask"` |

When `type` is set to `"auto"`, the node clears the stored control type so the type can be detected automatically. When a specific type is selected, the node stores the matching control type in the copied control network. The input control network is never changed in place; a modified copy is returned instead.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `control_net` | The modified control network with the specified type setting applied | CONTROL\_NET |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetUnionControlNetType/en.md)

***

**Source fingerprint (SHA-256):** `db4b1a3cebafcff2be3172faa09cecbd5e19331376491c491cbe359013ed3da3`


# StableCascade_StageB_Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableCascade_StageB_Conditioning

The StableCascadeStageBConditioning node prepares conditioning data for Stable Cascade Stage B generation by combining existing conditioning information with the prior latent repre

The StableCascade\_StageB\_Conditioning node prepares conditioning data for Stable Cascade Stage B generation by combining existing conditioning information with the prior latent representation produced by Stage C. It copies each conditioning entry and stores the Stage C latent samples into it, so later generation steps can use this prior information for more coherent results.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `conditioning` | The conditioning data to be modified with the Stage C prior information. Each entry in the list is copied and given the Stage C samples. | CONDITIONING | Yes | - |
| `stage_c` | The latent representation from Stage C. Its `samples` value is used as the prior information added to the conditioning. | LATENT | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The modified conditioning data with the Stage C prior information integrated. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableCascade_StageB_Conditioning/en.md)

***

**Source fingerprint (SHA-256):** `3154457773465e5b93221b6d83d2064b565cb653403e12e88615652c7832d1e8`


# StableZero123_Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableZero123_Conditioning

The StableZero123Conditioning node processes an input image and camera angles to generate conditioning data and latent representations for 3D model generation.

The StableZero123\_Conditioning node processes an input image and camera angles to generate conditioning data and latent representations for 3D model generation. It uses a CLIP vision model to encode the image features, combines them with camera embedding information based on elevation and azimuth angles, and produces positive and negative conditioning along with a latent representation for downstream 3D generation tasks.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_vision` | The CLIP vision model used to encode image features | CLIP\_VISION | Yes | - |
| `init_image` | The input image to be processed and encoded | IMAGE | Yes | - |
| `vae` | The VAE model used for encoding pixels to latent space | VAE | Yes | - |
| `width` | Output width for the latent representation (default: 256, step: 8) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Output height for the latent representation (default: 256, step: 8) | INT | Yes | 16 to MAX\_RESOLUTION |
| `batch_size` | Number of samples to generate in the batch (default: 1) | INT | Yes | 1 to 4096 |
| `elevation` | Camera elevation angle in degrees (default: 0.0, step: 0.1) | FLOAT | Yes | -180.0 to 180.0 |
| `azimuth` | Camera azimuth angle in degrees (default: 0.0, step: 0.1) | FLOAT | Yes | -180.0 to 180.0 |

**Note:** The `width` and `height` parameters use a step of 8, so values are set in increments of 8. The node divides them by 8 to determine the latent representation dimensions. The image is rescaled to the given `width` and `height` using bilinear upscaling with center cropping before VAE encoding.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning data combining image features and camera embeddings, including the VAE-encoded input image as a latent to concatenate | CONDITIONING |
| `negative` | Negative conditioning data with zero-initialized features and a zero-initialized latent | CONDITIONING |
| `latent` | Zero-initialized latent representation with dimensions \[batch\_size, 4, height//8, width//8] | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableZero123_Conditioning/en.md)

***

**Source fingerprint (SHA-256):** `a694610c9f22fe0dab3ae02f4aabb33e3de8e5031c82dff5e8ba232c098f4a1d`


# StableZero123_Conditioning_Batched - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableZero123_Conditioning_Batched

The StableZero123ConditioningBatched node prepares conditioning data for generating a 3D model from a single input image.

The StableZero123\_Conditioning\_Batched node prepares conditioning data for generating a 3D model from a single input image. It encodes the image with a CLIP vision model and a VAE, combines the visual features with camera embeddings built from elevation and azimuth angles, and produces positive and negative conditioning plus a latent tensor for a batch of samples. When `batch_size` is greater than 1, the elevation and azimuth angles are increased by their batch increment values for each item in the batch.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_vision` | The CLIP vision model used for encoding the input image | CLIP\_VISION | Yes | - |
| `init_image` | The initial input image to be processed and encoded | IMAGE | Yes | - |
| `vae` | The VAE model used for encoding image pixels into latent space | VAE | Yes | - |
| `width` | The output width for the processed image (default: 256) | INT | Yes | 16 to MAX\_RESOLUTION (step of 8) |
| `height` | The output height for the processed image (default: 256) | INT | Yes | 16 to MAX\_RESOLUTION (step of 8) |
| `batch_size` | The number of conditioning samples to generate in the batch (default: 1) | INT | Yes | 1 to 4096 |
| `elevation` | The initial camera elevation angle in degrees (default: 0.0) | FLOAT | Yes | -180.0 to 180.0 (step of 0.1) |
| `azimuth` | The initial camera azimuth angle in degrees (default: 0.0) | FLOAT | Yes | -180.0 to 180.0 (step of 0.1) |
| `elevation_batch_increment` | The amount to increment elevation for each batch item (default: 0.0). Marked as an advanced input. | FLOAT | Yes | -180.0 to 180.0 (step of 0.1) |
| `azimuth_batch_increment` | The amount to increment azimuth for each batch item (default: 0.0). Marked as an advanced input. | FLOAT | Yes | -180.0 to 180.0 (step of 0.1) |

**Note:** The `width` and `height` values must be multiples of 8, since the node divides these dimensions by 8 internally when building the latent tensor.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning data containing the image embeddings and camera embeddings for each batch item | CONDITIONING |
| `negative` | The negative conditioning data with zero-initialized embeddings | CONDITIONING |
| `latent` | A zero-initialized latent tensor with dimensions batch\_size x 4 x height/8 x width/8, along with batch indexing information | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableZero123_Conditioning_Batched/en.md)

***

**Source fingerprint (SHA-256):** `94fc53dace8f294a746c47f8aa0da145f3e7beeb77a95912a38f0037ac094292`


# TextEncodeHunyuanVideo_ImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeHunyuanVideo_ImageToVideo

The TextEncodeHunyuanVideoImageToVideo node creates conditioning data for image-to-video generation by combining a text prompt with visual information from a reference image.

The TextEncodeHunyuanVideo\_ImageToVideo node creates conditioning data for image-to-video generation by combining a text prompt with visual information from a reference image. It uses a CLIP model to process both the text and the image embeddings from a CLIP vision output, then generates tokens that blend these two sources according to the `image_interleave` setting.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for tokenization and encoding. | CLIP | Yes | - |
| `clip_vision_output` | The visual embeddings from a CLIP vision model that provide image context for the reference image. | CLIP\_VISION\_OUTPUT | Yes | - |
| `prompt` | The text description to guide the video generation. Supports multiline input and dynamic prompts. The prompt is formatted using a template that asks the model to describe the video based on the reference image, covering aspects like main content, object details, actions, background, and camera angles. | STRING | Yes | - |
| `image_interleave` | How much the image influences things vs the text prompt. Higher number means more influence from the text prompt. This is an advanced setting (default: 2). | INT | Yes | 1-512 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The conditioning data that combines text and image information for video generation. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeHunyuanVideo_ImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `016b87ead6f7a6ca61eff220e57f59252018cc78e80ec8cff5b83223b8f90f73`


# TextEncodeJoyImageEdit - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeJoyImageEdit

This node encodes a text prompt and optional images into conditioning data for use with JoyImage models.

This node encodes a text prompt and optional images into conditioning data for use with JoyImage models. It combines a CLIP text encoder with optional image inputs to create rich conditioning that can guide image generation or editing tasks.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for encoding the text prompt | CLIP | Yes | - |
| `prompt` | The text prompt to encode, supporting multiline input and dynamic prompts | STRING | Yes | - |
| `vae` | A VAE model for encoding images into latent space | VAE | No | - |
| `images` | Optional images to include in the conditioning, up to a maximum of 6 images. Each image connects as a separate input (image\_0 to image\_5) | IMAGE | No | 0 to 6 images |

The `images` input is an autogrow group that accepts between 0 and 6 images. When no images are connected, the conditioning is based on the text prompt alone.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The encoded conditioning data combining the text prompt and any provided images | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeJoyImageEdit/en.md)

***

**Source fingerprint (SHA-256):** `ef48523aa9fc990b2839d755cef272bcdfbacef5af8d961736fde5200c6f082d`


# TextEncodeMageFlowEdit - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeMageFlowEdit

Documentation for TextEncodeMageFlowEdit node.

## Overview

This node encodes an edit instruction (prompt) along with one or more reference images for the Mage-Flow-Edit model. It resizes all reference images to the target output resolution, encodes them into latent space if a VAE is provided, and attaches the reference latents to the conditioning output. A blank latent tensor with the correct dimensions for sampling is also generated, ensuring the size always matches the output width and height.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used to tokenize and encode the text prompts. | CLIP | Yes | |
| `prompt` | The editing instruction (positive prompt) to apply. | STRING | Yes | multiline, dynamic prompts enabled |
| `negative_prompt` | The negative prompt to steer away from. Default: empty string (uses a space internally when blank). Shown in the advanced section of the UI. | STRING | No | multiline, dynamic prompts enabled |
| `vae` | VAE model to encode reference images into latent space. If not provided, no reference latents are added to the conditioning. | VAE | No | |
| `images` | Reference image(s) to edit. All references are resized to the output resolution before encoding. | IMAGE (autogrow) | No | Up to 16 images (named `image_1`…`image_16`), at least 0 |
| `width` | Output width in pixels. If set to 0, the width of the first reference image is used. Always rounded down to a multiple of 16. Default: 0. | INT | Yes | 0 to 8192 (step 16) |
| `height` | Output height in pixels. Same fallback behavior as width. Default: 0. | INT | Yes | 0 to 8192 (step 16) |
| `batch_size` | Number of latent samples to generate. Default: 1. | INT | Yes | 1 to 4096 |

**Notes on parameter dependencies:**

* If `width` and/or `height` are 0 and no reference images are provided, they fall back to 1024 each.
* If only one of `width` or `height` is 0, the missing dimension is taken from the first reference image while the explicitly set dimension is kept.
* The `vae` parameter is optional; reference latents are only generated and attached to conditioning when a VAE is connected.
* The `negative_prompt` field is optional – if left empty, a single space is used internally as the negative text.
* For the text conditioning, each reference image is resized so its longest edge is at most 384 pixels, matching training preprocessing. The VAE encoding branch instead resizes all references to the full output resolution.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Conditioning output containing the positive prompt tokens, plus (if a VAE was provided) the encoded reference latents. | CONDITIONING |
| `negative` | Conditioning output containing the negative prompt tokens, plus the same reference latents (if VAE provided). | CONDITIONING |
| `latent` | A blank latent tensor with shape `[batch_size, 128, height÷16, width÷16]` for use as the initial noise during sampling. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeMageFlowEdit/en.md)

***

**Source fingerprint (SHA-256):** `880d8856b7f6e656bc68ca953fbf892898d05bc5d65290ae3bf7a4405ee09be3`


# TextEncodeMingImageEdit - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeMingImageEdit

Text Encode Ming Image Edit encodes a text prompt into conditioning for Ming image editing, optionally mixing in reference images.

Text Encode Ming Image Edit encodes a text prompt into conditioning for Ming image editing, optionally mixing in reference images. The prompt and the reference images are tokenized by a CLIP model, and when a VAE is connected the reference images are also encoded into latent frames that are appended to the conditioning.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used to tokenize the prompt and the reference images. | CLIP | Yes | - |
| `vae` | Optional VAE that encodes the reference images into latent frames appended to the conditioning. Without a VAE the images only condition the text encoder through the vision tower. | VAE | No | - |
| `prompt` | Text prompt to encode. Supports multiline input and dynamic prompts. | STRING | Yes | Multiline text |
| `images` | Growable slot: optional reference images seen by the text encoder and appended to the latent sequence as clean frames. Connect 1..8 images (`image_1`, `image_2`, ...); later images are resized to the first one and the sampled latent should match its size. Only the RGB channels are used. | IMAGE | No | 0 to 8 |

**Note:** Reference images are read in numeric order of their slot names, and empty slots are ignored. Reference latents are only produced when both `vae` and at least one image are provided.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Conditioning containing the encoded prompt, plus the reference latents when a VAE and reference images are provided. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeMingImageEdit/en.md)

***

**Source fingerprint (SHA-256):** `675fb3cc0af006e1284fdb2a5ca2c268c540ee92e1ede90b2359f4e3fc8ba5ea`


# TextEncodeQwenImage21 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeQwenImage21

The TextEncodeQwenImage21 node encodes a prompt and a negative prompt for the Qwen-Image 2.1 model, optionally attaching reference images.

The TextEncodeQwenImage21 node encodes a prompt and a negative prompt for the Qwen-Image 2.1 model, optionally attaching reference images. Reference images are seen by the text encoder and, when a VAE is connected, are also encoded as latents that are spliced into the sequence, so the conditioning carries both the text instruction and the visual reference. The node returns positive and negative conditioning together with an empty latent sized to the first reference image, ready to be sampled.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The Qwen-Image 2.1 text encoder used to tokenize and encode the prompts. | CLIP | Yes | - |
| `prompt` | Text prompt describing the image to generate or the edit to apply. Supports multiline input and dynamic prompts. | STRING | Yes | Any text |
| `negative_prompt` | Text prompt describing what the result should avoid. Supports multiline input and dynamic prompts. | STRING | Yes | Any text |
| `vae` | VAE used to encode the reference images into reference latents. When omitted, the reference images condition the result through the text encoder only. | VAE | No | - |
| `resolution` | Reference images are resized to about `resolution` x `resolution` pixels, at multiples of 32, preserving aspect ratio. 0 keeps each reference at its own size, rounded to a multiple of 32 (default: 1024). | INT | Yes | 0 to 4096 (step 32) |
| `images` | Reference images, seen by the text encoder and spliced into the sequence as VAE latents. Growable slot: connect up to 16 images (`image_1` ... `image_16`). | IMAGE | No | 0 to 16 images |

The empty latent output is sized to the first connected reference image, or to `resolution` when no reference image is connected. Sample at the latent this node returns: any other size shifts the edit. When a VAE is connected, the same reference latents are attached to both the positive and the negative conditioning, so a single sampler step can denoise both.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Encoded conditioning for the prompt, carrying the reference latents when a VAE is connected. | CONDITIONING |
| `negative` | Encoded conditioning for the negative prompt, with the same reference latents. | CONDITIONING |
| `latent` | Empty latent on the first reference image's size, or 1024 x 1024 when no reference image is connected. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeQwenImage21/en.md)

***

**Source fingerprint (SHA-256):** `3870f04597d12b593498c12ca139428af2d717b65aa40c889de9373ae9eb475e`


# TextEncodeQwenImageEdit - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeQwenImageEdit

The TextEncodeQwenImageEdit node converts text prompts and optional images into conditioning data for image generation or editing.

The TextEncodeQwenImageEdit node converts text prompts and optional images into conditioning data for image generation or editing. It uses a CLIP model to tokenize the input and can optionally encode reference images with a VAE to create reference latents. When an image is provided, it is automatically resized to keep a consistent processing scale.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for text and image tokenization | CLIP | Yes | - |
| `prompt` | Text prompt for conditioning generation, supports multiline input and dynamic prompts | STRING | Yes | - |
| `vae` | Optional VAE model for encoding reference images into latents | VAE | No | - |
| `image` | Optional input image for reference or editing purposes | IMAGE | No | - |

**Note:** When an image is provided, it is resized so its total pixel count stays close to 1,048,576 (1024 × 1024), and only its RGB channels are used. The resized image is passed to the CLIP tokenizer together with the prompt. When both `image` and `vae` are provided, the node also encodes the image into reference latents and attaches them to the conditioning output.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Conditioning data containing text tokens and optional reference latents for image generation | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeQwenImageEdit/en.md)

***

**Source fingerprint (SHA-256):** `ec6980a63eab0d6c95be3abea00b2bf3018d30a1267f0b39a21be29a3e9228fe`


# TextEncodeQwenImageEditPlus - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeQwenImageEditPlus

The TextEncodeQwenImageEditPlus node processes a text prompt and up to three optional images to produce conditioning data for image generation or editing tasks.

The TextEncodeQwenImageEditPlus node processes a text prompt and up to three optional images to produce conditioning data for image generation or editing tasks. It uses a specialized template that first asks the model to describe the key features of the input images and then explain how the user's text instruction should change them, so the encoded result understands both the images and the requested modification. When a VAE is provided, the node also creates reference latents from the input images.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for tokenization and encoding | CLIP | Yes | - |
| `prompt` | Text instruction describing the desired image modification (supports multiline input and dynamic prompts) | STRING | Yes | - |
| `vae` | Optional VAE model for generating reference latents from input images | VAE | No | - |
| `image1` | First optional input image for analysis and modification | IMAGE | No | - |
| `image2` | Second optional input image for analysis and modification | IMAGE | No | - |
| `image3` | Third optional input image for analysis and modification | IMAGE | No | - |

**Note:** When a VAE is provided, the node generates reference latents from all provided input images. Up to three images can be processed at once. Images are scaled to a target area of 384x384 pixels (aspect ratio preserved) for vision-language processing, and to dimensions divisible by 8 (with a target area of 1024x1024 pixels) for VAE encoding.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Encoded conditioning data containing text tokens and optional reference latents for image generation | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeQwenImageEditPlus/en.md)

***

**Source fingerprint (SHA-256):** `5eea53a84045924b44d445244e6149b341188d22573aaaced87bac8a139dac96`


# Trellis2Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Trellis2Conditioning

Trellis2Conditioning converts an input image into conditioning data for the TRELLIS.2 model.

Trellis2Conditioning converts an input image into conditioning data for the TRELLIS.2 model. It uses a CLIP vision model to encode the image into two sets of features (at 512 and 1024 scales) and packages them as a positive conditioning pair, while also creating a matching zero-filled negative conditioning pair that serves as an empty reference.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_vision_model` | The CLIP vision model used to encode the image into conditioning features. | CLIP\_VISION | Yes | Any available CLIP vision model |
| `image` | Preprocessed image from ImageCropToMask (pad\_factor=1.0 for TRELLIS.2). | IMAGE | Yes | Any image |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Conditioning containing the encoded image features at 512 and 1024 scales, used as the positive conditioning for the TRELLIS.2 model. | CONDITIONING |
| `negative` | Zero-filled conditioning with the same shape as the positive conditioning, used as an empty negative reference. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Trellis2Conditioning/en.md)

***

**Source fingerprint (SHA-256):** `467698e58558ceca9ac633d63aacf360a1eb674ac4ebd47de7423f85e62c0fe6`


# Trellis2ShapeStage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Trellis2ShapeStage

This node sets up the first shape-generation sampling pass of the Trellis2 pipeline.

This node sets up the first shape-generation sampling pass of the Trellis2 pipeline. It takes the dense structure voxel produced by VaeDecodeStructureTrellis2, extracts the sparse coordinates of the filled voxels, creates an empty sparse latent, and attaches the sampling metadata to the conditioning so the model can read it during sampling. For the second shape pass after upsampling, use Trellis2UpsampleStage instead, which combines the cascade and the second-pass stage setup.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning to prepare for the shape stage. May be a standard Trellis2 conditioning or a Pixal3D conditioning that supplies a projection feature pack; when projection features are present, they are computed for the selected stage and attached to the output conditioning. | CONDITIONING | Yes | Any Trellis2 or Pixal3D conditioning |
| `negative` | The negative conditioning to prepare for the shape stage. The same shape-stage metadata is attached to it as to the positive conditioning. | CONDITIONING | Yes | Any Trellis2 or Pixal3D conditioning |
| `voxel` | Dense structure voxel from VaeDecodeStructureTrellis2. | VOXEL | Yes | Any voxel grid; the grid resolution (voxels per axis) selects the pipeline stage |

### Notes

* The voxel grid resolution selects the pipeline stage: a resolution of 32 or lower uses the `shape_generation_512` mode with the `shape_512` stage; a resolution greater than 32 uses the `shape_generation` mode with the `shape_1024` stage.
* The voxel must contain at least one filled voxel; an empty voxel raises an error. The batch indices derived from the voxel must be non-negative and contiguous.
* When the `positive` conditioning contains a `proj_feat_pack` (as supplied by Pixal3D conditioning), projection features are computed for the selected stage and the output latent's model frame is set to `y_up`. Otherwise, no projection features are attached and the model frame is set to `z_up`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning with the shape-stage metadata attached: generation mode, sparse coordinates, per-batch coordinate counts, and projection features when the source conditioning provides them. | CONDITIONING |
| `negative` | The negative conditioning with the same shape-stage metadata attached. | CONDITIONING |
| `latent` | An empty sparse latent tensor (shape: batch size, 32, token count, 1) together with the extracted sparse coordinates, per-batch coordinate counts, coordinate resolution, the type marker `trellis2`, and the model frame orientation. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Trellis2ShapeStage/en.md)

***

**Source fingerprint (SHA-256):** `7dbee8a5b6ef7111f07def4dbe1cc4908533e00ffcb775f5a284099360c7eed3`


# Trellis2TextureStage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Trellis2TextureStage

This node sets up the texture-stage sampling pass for Trellis2 generation.

This node sets up the texture-stage sampling pass for Trellis2 generation. It reads the coordinate layout and the per-voxel shape latent from the incoming shape latent, builds an empty sparse latent with 32 channels at the same coordinate layout, and attaches the required texture-stage metadata to the conditioning.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning used for the texture-generation pass. Texture-stage metadata is attached to it. | CONDITIONING | Yes | - |
| `negative` | The negative conditioning used for the texture-generation pass. Texture-stage metadata is attached to it. | CONDITIONING | Yes | - |
| `shape_latent` | The latent dict produced by Trellis2ShapeStage or Trellis2UpsampleStage. It must contain `coords` (the coordinate layout, shape \[N, 4]) and `samples` (the per-voxel shape latent); `coord_resolution` and `model_frame` are optional. | LATENT | Yes | - |

Notes:

* `shape_latent` must be the output of Trellis2ShapeStage or Trellis2UpsampleStage; it provides the coordinate layout and the per-voxel shape latent used by the texture pass.
* The coordinate layout is validated: batch ids in the first column of `coords` must be non-negative and contiguous, and the total row count must match the coordinate counts.
* The shape latent is accepted either as a 4D sparse tensor (which is flattened together with its coordinates) or already in flattened form.
* When `positive` carries a projection feature pack (Pixal3D conditioning) and `shape_latent` includes `coord_resolution`, projection features at 1024 texture resolution are computed and attached to the conditioning.
* The model frame is read from `shape_latent`; when absent, it defaults to `"y_up"` if projection features are present and `"z_up"` otherwise.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning with texture-stage metadata attached (generation mode, coordinates, coordinate counts, shape latent, model frame, and projection features when applicable). | CONDITIONING |
| `negative` | The negative conditioning with the same texture-stage metadata attached. | CONDITIONING |
| `latent` | A new empty sparse latent with 32 channels at the same coordinate layout as the incoming shape latent. Its dict includes `samples`, `type` ("trellis2"), `coords`, `coord_counts`, and `model_frame`; `coord_resolution` is included when available. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Trellis2TextureStage/en.md)

***

**Source fingerprint (SHA-256):** `ae612021af7c74cd09206d905e7b800fa48367a22daf9b0335b444c854a78b1e`


# Trellis2UpsampleStage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Trellis2UpsampleStage

This node upscales a 512-resolution shape latent into high-resolution sparse coordinates and prepares the second shape-stage sampling pass at the target resolution.

This node upscales a 512-resolution shape latent into high-resolution sparse coordinates and prepares the second shape-stage sampling pass at the target resolution. It attaches per-stage metadata to the conditioning so the model can consume it during generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning to which the upsampling-stage shape metadata is attached. | CONDITIONING | Yes | |
| `negative` | The negative conditioning to which the upsampling-stage shape metadata is attached. | CONDITIONING | Yes | |
| `shape_latent` | The 512-resolution shape latent output from the first shape-stage KSampler. | LATENT | Yes | |
| `vae` | The Trellis2 VAE used to decode the shape latent into high-resolution sparse coordinates. | VAE | Yes | |
| `target_resolution` | Voxel resolution of the upsampled shape. Higher = more detail, more VRAM. Default: 1024. | INT | Yes | 1024 - 2048 (step 128) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with the upsampling-stage shape metadata attached. | CONDITIONING |
| `negative` | Negative conditioning with the upsampling-stage shape metadata attached. | CONDITIONING |
| `latent` | Zero-filled latent prepared for the second shape-stage sampling pass at the target resolution, carrying the upsampled coordinates, per-sample coordinate counts, and coordinate resolution metadata. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Trellis2UpsampleStage/en.md)

***

**Source fingerprint (SHA-256):** `0582579bfab487718d69789de508a5ec243d98a0e06ad7165c406154a64677d6`


# TripoSplatConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoSplatConditioning

This node encodes an input image with the DINOv3 image encoder and the Flux2 VAE to produce positive and negative conditioning data for the TripoSplat model.

This node encodes an input image with the DINOv3 image encoder and the Flux2 VAE to produce positive and negative conditioning data for the TripoSplat model. It also creates a fixed-size noise target (latent plus camera data) that serves as the starting point for the KSampler.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_vision` | DINOv3 ViT-H/16+ image encoder | CLIP\_VISION | Yes | - |
| `vae` | Flux2 VAE | VAE | Yes | - |
| `image` | The input image to encode | IMAGE | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning data containing the DINOv3 feature sequence and the Flux2 VAE latent carried as a reference latent | CONDITIONING |
| `negative` | Negative conditioning data containing zero-filled DINOv3 features and a zero-filled Flux2 VAE reference latent | CONDITIONING |
| `latent` | The fixed size noise target (latent + camera) for the KSampler. The latent is a constant-shape shape-code sequence (8192 x 16) paired with a single camera token (1 x 5) | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoSplatConditioning/en.md)

***

**Source fingerprint (SHA-256):** `59ebeef272d125a2cc2045f4ff54f99268b1273d0a1fd46f7462e6d312f3a805`


# TripoSplatPreprocessImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoSplatPreprocessImage

This node crops each input image to a centered square on a black background and adds padding to reach the specified output size.

This node crops each input image to a centered square on a black background and adds padding to reach the specified output size. It is designed to prepare images for the TripoSplat 3D model by ensuring consistent square framing and optional alpha matte erosion to prevent border artifacts.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image(s) to preprocess. | IMAGE | Yes | - |
| `mask` | Alpha mask for the image, used to determine the crop region. | MASK | Yes | - |
| `erode_radius` | Erode the alpha matte by this pixel radius before cropping (avoids border bleed). Default: 1. Set to 0 to disable erosion. | INT | Yes | 0 to 16 |
| `size` | Square image size. The model is trained at 1024; other sizes run but are off-distribution. Default: 1024. | INT | Yes | 256 to 4096 (step of 16) |

**Note:** The `mask` input is required and must be provided. If the mask has a different batch size than the image, it is automatically repeated to match. If the mask dimensions differ from the image dimensions, the mask is resized to match the image using bilinear interpolation. The output size is automatically rounded down to the nearest multiple of 16 (minimum 16) to ensure compatibility with DINOv3 patch and Flux2 VAE stride requirements. The node raises an error if the mask contains no foreground pixels (empty mask). When `erode_radius` is 0, no erosion is applied. The square crop is centered on the mask's alpha bounding box and sized to 1.2 times the larger bounding box dimension; any area outside the image bounds is filled with black.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The preprocessed image(s) cropped to a centered square on a black background with padding, at the requested `size` resolution. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoSplatPreprocessImage/en.md)

***

**Source fingerprint (SHA-256):** `ec66941846398ee6637576b11ae9d2f9576f6b05ed2ef730cdbf99a68fe9b838`


# VOIDInpaintConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VOIDInpaintConditioning

The VOIDInpaintConditioning node prepares the conditioning data needed for inpainting with CogVideoX models.

The VOIDInpaintConditioning node prepares the conditioning data needed for inpainting with CogVideoX models. It takes a source video and a preprocessed quadmask, encodes them through the VAE, and combines them into a 32-channel conditioning signal (16 channels from the mask + 16 channels from the masked video) that the model uses to fill in the masked areas.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning to be augmented with the inpainting latent information | CONDITIONING | Yes | - |
| `negative` | The negative conditioning to be augmented with the inpainting latent information | CONDITIONING | Yes | - |
| `vae` | The VAE model used to encode the mask and masked video into latent space | VAE | Yes | - |
| `video` | Source video frames \[T, H, W, 3] | IMAGE | Yes | - |
| `quadmask` | Preprocessed quadmask from VOIDQuadmaskPreprocess \[T, H, W] | MASK | Yes | - |
| `width` | The width to resize the video and mask to (default: 672) | INT | Yes | 16 to MAX\_RESOLUTION (step: 8) |
| `height` | The height to resize the video and mask to (default: 384) | INT | Yes | 16 to MAX\_RESOLUTION (step: 8) |
| `length` | Number of pixel frames to process. For CogVideoX-Fun-V1.5 (patch\_size\_t=2), latent\_t must be even — lengths that produce odd latent\_t are rounded down (e.g. 49 → 45) (default: 45) | INT | Yes | 1 to MAX\_RESOLUTION (step: 1) |
| `batch_size` | The batch size for the output noise latent (default: 1) | INT | Yes | 1 to 64 |

**Note:** Because CogVideoX-Fun-V1.5 uses `patch_size_t=2`, the encoded latent must have an even temporal dimension. If `length` would produce an odd `latent_t`, the node automatically rounds it down to the nearest valid value and logs a warning. Using an odd `latent_t` corrupts the last frame through circular padding, which can cause visible jitter or disappearing subjects near the end of the decoded video.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning with the inpainting latent information added | CONDITIONING |
| `negative` | The negative conditioning with the inpainting latent information added | CONDITIONING |
| `latent` | A zero-filled noise latent tensor with shape \[batch\_size, 16, latent\_t, latent\_h, latent\_w] | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VOIDInpaintConditioning/en.md)

***

**Source fingerprint (SHA-256):** `885e462c0f17a3e9610146a05ba3b9c879db0112d3961c95a83f63ba2cd511f1`


# Wan22FunControlToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan22FunControlToVideo

The Wan22FunControlToVideo node prepares conditioning data and an empty latent tensor for video generation with the Wan video model.

The Wan22FunControlToVideo node prepares conditioning data and an empty latent tensor for video generation with the Wan video model. It encodes optional reference images and control videos into latent space, attaches them to the positive and negative conditioning, and creates a zero-filled latent tensor with the correct spatial and temporal dimensions for the requested video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning input for guiding the video generation | CONDITIONING | Yes | - |
| `negative` | Negative conditioning input for guiding the video generation | CONDITIONING | Yes | - |
| `vae` | VAE model used to encode images into latent space | VAE | Yes | - |
| `width` | Width of the output video in pixels (default: 832, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Height of the output video in pixels (default: 480, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames in the video sequence (default: 81, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of video sequences to generate (default: 1) | INT | Yes | 1 to 4096 |
| `ref_image` | Optional reference image that provides visual guidance for the generation | IMAGE | No | - |
| `control_video` | Optional control video that guides the generation process | IMAGE | No | - |

**Note:** The `length` parameter is processed in steps of 4 frames, and the node automatically applies temporal scaling when building the latent space. When `ref_image` is provided, only its first frame is encoded (resized to `width` x `height`) and attached to the conditioning as reference latents. When `control_video` is provided, it is trimmed to `length` frames, resized, encoded, and placed into the concat latent used by the conditioning. The concatenated latent is duplicated along the channel dimension and its channel layout depends on the VAE's latent channel count (48 channels uses the Wan 2.2 format, otherwise the Wan 2.1 format). The `start_image` parameter is referenced in the execution logic but is not exposed in the node's input schema, so it cannot be set from the node interface.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with video-specific latent data added, including the concat latent, mask, and optional reference latents | CONDITIONING |
| `negative` | Negative conditioning with video-specific latent data added, including the concat latent, mask, and optional reference latents | CONDITIONING |
| `latent` | Empty latent tensor prepared for video generation, sized according to the batch size, latent channels, length, height, and width | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan22FunControlToVideo/en.md)

***

**Source fingerprint (SHA-256):** `731b848f15c13ddc662f19230acb55d195f934bad7d9ae516a288e0ed8f8d899`


# WanAnimate2Cache - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanAnimate2Cache

Caches the pose-video's per-block activations once so they do not need to be recomputed on every sampling step, which roughly halves generation time.

Caches the pose-video's per-block activations once so they do not need to be recomputed on every sampling step, which roughly halves generation time. The tradeoff is extra memory usage: about 12.5 GB of system RAM at 480x832 resolution with 81 frames in bf16, scaling with resolution and video length.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Wan Animate2 model to attach the cache to. | MODEL | Yes | |
| `device` | Where to keep the cache. cpu (RAM) is the safe choice, the cache will not fit in VRAM alongside the model at typical sizes. gpu (VRAM) can be faster if it fits. (default: "cpu") | STRING | Yes | "cpu"<br />"gpu" |
| `dtype` | Storage precision. default stores the activations in the model's compute dtype. int8 halves the cache, int4 quarters it, convrot is used to retain accuracy. (default: "default") | STRING | Yes | "default"<br />"int8"<br />"int4" |

Note: When context windows are used, each window is cached separately, so memory usage scales with the window count. The static\_standard schedule should be used, because uniform schedules shift the windows on every step and the cache is never reused.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The cloned model with the pose-video activation cache attached. The cache is automatically freed when generation finishes. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanAnimate2Cache/en.md)

***

**Source fingerprint (SHA-256):** `06305432601afd7c797ef29ef4be3f2bb1aa660e05edde270499e94ccdd54f84`


# WanAnimate2ToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanAnimate2ToVideo

WanAnimate2ToVideo animates a character from a reference image by transferring the facial expressions, body motion, and hand gestures from a separate pose video.

WanAnimate2ToVideo animates a character from a reference image by transferring the facial expressions, body motion, and hand gestures from a separate pose video. It builds the conditioning data and a starting latent that a video generation sampler uses to create the animation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning for the video generation. | CONDITIONING | Yes | N/A |
| `negative` | The negative conditioning for the video generation. | CONDITIONING | Yes | N/A |
| `vae` | The VAE used to encode the reference image and video frames into latent space. | VAE | Yes | N/A |
| `width` | Output video width in pixels. (default: 832) | INT | Yes | 16 to MAX\_RESOLUTION (step 16) |
| `height` | Output video height in pixels. (default: 480) | INT | Yes | 16 to MAX\_RESOLUTION (step 16) |
| `length` | Number of frames to generate. (default: 81) | INT | Yes | 1 to MAX\_RESOLUTION (step 4) |
| `batch_size` | Number of videos to generate simultaneously. (default: 1) | INT | Yes | 1 to 4096 |
| `reference_image` | The character to animate. If omitted, a black image is used. | IMAGE | No | N/A |
| `pose_video` | The video whose motion is transferred to the reference character. If it has fewer frames than `length`, the last frame is repeated to fill the missing frames. | IMAGE | No | N/A |
| `clip_vision_output` | CLIP vision of the reference image. | CLIP\_VISION\_OUTPUT | No | N/A |
| `positive_pose` | Prompt for the pose-video branch, describing the motion rather than the character. Defaults to `positive`. Used for both the cond and uncond passes. | CONDITIONING | No | N/A |
| `clip_vision_output_pose` | CLIP vision of the pose video's first frame. Defaults to `clip_vision_output`. | CLIP\_VISION\_OUTPUT | No | N/A |
| `continue_motion` | Previous motion sequence to continue from for temporal consistency. Only the last frame of this sequence is used as the starting motion frame. | IMAGE | No | N/A |
| `video_frame_offset` | Frames to seek into the pose video. Connect to the `video_frame_offset` output of the previous node when extending. (default: 0) | INT | Yes | 0 to MAX\_RESOLUTION |
| `pose_strength` | Scales the pose video's influence on the motion. 1.0 is the trained behavior; below weakens adherence, above amplifies. 0.0 mutes it but does not fully remove it. (default: 1.0) | FLOAT | Yes | 0.00 to 10.00 (step 0.01) |
| `pose_start_percent` | Sampling percent at which the pose influence starts. Outside the window the pose branch is skipped entirely, which also speeds those steps up. (default: 0.0) | FLOAT | Yes | 0.00 to 1.00 (step 0.01) |
| `pose_end_percent` | Sampling percent at which the pose influence ends. Motion is mostly established early, so e.g. 0.7 can loosen fine detail while keeping the choreography. (default: 1.0) | FLOAT | Yes | 0.00 to 1.00 (step 0.01) |
| `reference_image_strength` | Scales how strongly generated frames attend to the reference image's latent frame. Below 1.0 loosens identity/appearance adherence (e.g. to let the prompt restyle), above tightens it against drift. (default: 1.0) | FLOAT | Yes | 0.00 to 10.00 (step 0.01) |

**Validation notes:**

* `pose_start_percent` must not be greater than `pose_end_percent`; otherwise the node raises a ValueError.
* If `pose_video` is provided, its frame count must be greater than `video_frame_offset`; otherwise the node raises a ValueError.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning for sampling, with the reference image, mask, and optional pose data attached. | CONDITIONING |
| `negative` | Negative conditioning for sampling, with the same reference image, mask, and optional pose data attached. | CONDITIONING |
| `latent` | Zero-filled starting latent for the video sampler; the first `trim_latent` frames should be removed before decoding. | LATENT |
| `trim_latent` | Number of latent frames that should be trimmed before decoding. | INT |
| `trim_image` | Number of overlapping image frames when extending a video. | INT |
| `video_frame_offset` | Frames to seek into the pose video; equals the adjusted input offset plus the number of frames generated. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanAnimate2ToVideo/en.md)

***

**Source fingerprint (SHA-256):** `7e1f497983ab63a68e5ef5439b3ef4e9295f79f78530c9dc5de16a8238475f05`


# WanAnimateToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanAnimateToVideo

WanAnimateToVideo prepares conditioning data and an initial latent for generating animated videos with Wan, using inputs such as a reference image, pose, face, background, and opti

WanAnimateToVideo prepares conditioning data and an initial latent for generating animated videos with Wan, using inputs such as a reference image, pose, face, background, and optional motion from a previous chunk. It also supports generating longer videos in chunks by reading and updating a `video_frame_offset` value. This node is marked as experimental.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning for guiding the generation towards desired content. | CONDITIONING | Yes | - |
| `negative` | Negative conditioning for steering the generation away from unwanted content. | CONDITIONING | Yes | - |
| `vae` | VAE model used for encoding image and video inputs into latent space. | VAE | Yes | - |
| `width` | Width of the generated video in pixels (default: 832, step: 16). | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Height of the generated video in pixels (default: 480, step: 16). | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames to generate (default: 77, step: 4). | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of videos to generate in one batch (default: 1). | INT | Yes | 1 to 4096 |
| `clip_vision_output` | Optional CLIP vision output added to both positive and negative conditioning. | CLIP\_VISION\_OUTPUT | No | - |
| `reference_image` | Reference image used as the appearance starting point for the generated video. If not provided, a black image is used. | IMAGE | No | - |
| `face_video` | Video input providing facial expression guidance. It is resized to 512x512 and scaled to the range -1.0 to 1.0 internally. | IMAGE | No | - |
| `pose_video` | Video input providing pose and motion guidance. | IMAGE | No | - |
| `continue_motion_max_frames` | Maximum number of frames carried over from a previous motion sequence (default: 5, step: 4). | INT | Yes | 1 to MAX\_RESOLUTION |
| `background_video` | Background video used to fill the non-character parts of the frames. | IMAGE | No | - |
| `character_mask` | Mask defining character regions, used to separate the character from the background. | MASK | No | - |
| `continue_motion` | Previous motion frames to continue from, keeping temporal consistency with earlier generated chunks. | IMAGE | No | - |
| `video_frame_offset` | The amount of frames to seek in all the input videos. Used for generating longer videos by chunk. Connect to the video\_frame\_offset output of the previous node for extending a video. (default: 0, step: 1) | INT | Yes | 0 to MAX\_RESOLUTION |

**Parameter Constraints:**

* When `continue_motion` is provided, only its last `continue_motion_max_frames` frames are used.
* Input videos (`face_video`, `pose_video`, `background_video`, `character_mask`) are offset by `video_frame_offset` before use. If the offset is greater than or equal to the input's frame count, that input is ignored, except for a single-frame `character_mask`.
* If `character_mask` has only one frame, that frame is repeated for every frame of the output.
* When `pose_video` is shorter than `length`, its last frame is repeated to fill the remaining frames; the output length is not changed.
* If `clip_vision_output` is provided, it is added to both positive and negative conditioning.
* If `reference_image` is not provided, a black image (all zero values) is used as the default reference.
* If `continue_motion` is not provided, the initial motion frames are filled with constant gray (0.5 intensity) frames.
* When `continue_motion` is used, `video_frame_offset` is reduced by the number of carried-over frames before the next chunk offset is calculated, so overlapping frames are not processed twice.
* `background_video` fills the motion frames after the reference-motion portion; it does not replace the reference image or the carried-over `continue_motion` frames.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Modified positive conditioning with additional video context, including CLIP vision output, pose video latent, face video pixels, concatenated latent image, and concatenated mask. | CONDITIONING |
| `negative` | Modified negative conditioning with additional video context, including CLIP vision output, pose video latent, blank face pixels, concatenated latent image, and concatenated mask. | CONDITIONING |
| `latent` | Initial latent tensor (all zero samples) for the generated video, with the shape `[batch_size, 16, latent_length + trim_latent, latent_height, latent_width]`. | LATENT |
| `trim_latent` | Number of latent frames to trim from the beginning of the latent, corresponding to the reference image frames. | INT |
| `trim_image` | Number of image frames to trim from the beginning, corresponding to the reference motion frames. | INT |
| `video_frame_offset` | Updated frame offset to use for the next chunk, based on the input offset and the number of frames processed. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanAnimateToVideo/en.md)

***

**Source fingerprint (SHA-256):** `a95bae4c7ae4ddc8a95bc9dafa2ca920b1d2166802615189537dce16949bfc03`


# WanCameraEmbedding - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanCameraEmbedding

This node generates a camera trajectory embedding using Plücker embeddings for the camera path you choose.

This node generates a camera trajectory embedding using Plücker embeddings for the camera path you choose. It builds a sequence of camera poses simulating movements such as panning, zooming, or rotating, and converts them into an embedding tensor that can be used in video generation pipelines.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `camera_pose` | The type of camera movement to simulate (default: "Static") | COMBO | Yes | "Static"<br />"Pan Up"<br />"Pan Down"<br />"Pan Left"<br />"Pan Right"<br />"Zoom In"<br />"Zoom Out"<br />"Anti Clockwise (ACW)"<br />"ClockWise (CW)" |
| `width` | The width of the output in pixels (default: 832, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | The height of the output in pixels (default: 480, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | The length of the camera trajectory sequence (default: 81, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `speed` | The speed of the camera movement (default: 1.0, step: 0.1) | FLOAT | No | 0.0 to 10.0 |
| `fx` | The focal length x parameter (default: 0.5, step: 0.000000001) | FLOAT | No | 0.0 to 1.0 |
| `fy` | The focal length y parameter (default: 0.5, step: 0.000000001) | FLOAT | No | 0.0 to 1.0 |
| `cx` | The principal point x coordinate (default: 0.5, step: 0.01) | FLOAT | No | 0.0 to 1.0 |
| `cy` | The principal point y coordinate (default: 0.5, step: 0.01) | FLOAT | No | 0.0 to 1.0 |

Note: `fx`, `fy`, `cx`, and `cy` are advanced camera intrinsic parameters. The `speed` parameter scales the rotation angle and translation distance of the selected camera motion.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `camera_embedding` | The generated camera embedding tensor containing the trajectory sequence | TENSOR |
| `width` | The width value that was used for processing | INT |
| `height` | The height value that was used for processing | INT |
| `length` | The length value that was used for processing | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanCameraEmbedding/en.md)

***

**Source fingerprint (SHA-256):** `1a2f98d83d18033581823dee61b5a3686d560c749c55223f81febca89654a29f`


# WanCameraImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanCameraImageToVideo

The WanCameraImageToVideo node prepares conditioning and latent data for camera-controlled video generation from images.

The WanCameraImageToVideo node prepares conditioning and latent data for camera-controlled video generation from images. It takes positive and negative conditioning prompts, along with optional inputs such as a starting image, CLIP vision output, and camera conditions, and outputs updated conditioning plus an empty latent tensor ready for a video model to fill in.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning prompts for video generation | CONDITIONING | Yes | - |
| `negative` | Negative conditioning prompts to avoid in video generation | CONDITIONING | Yes | - |
| `vae` | VAE model for encoding images to latent space | VAE | Yes | - |
| `width` | Output video width in pixels (default: 832, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Output video height in pixels (default: 480, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames in the video sequence (default: 81, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of videos to generate simultaneously (default: 1) | INT | Yes | 1 to 4096 |
| `clip_vision_output` | Optional CLIP vision output for additional conditioning | CLIP\_VISION\_OUTPUT | No | - |
| `start_image` | Optional starting image to initialize the video sequence. When provided, only the first `length` frames are used, and the image is resized to match the specified `width` and `height`. The first frames of the sequence are encoded into the latent and a mask is applied to blend the starting frames with generated content. | IMAGE | No | - |
| `camera_conditions` | Optional camera embedding conditions for video generation. When provided, these conditions are applied to both the positive and negative conditioning. | WAN\_CAMERA\_EMBEDDING | No | - |

**Note:** When `start_image` is provided, the node sets `concat_latent_image` and `concat_mask` values on both `positive` and `negative` conditioning. The `camera_conditions` and `clip_vision_output` parameters are optional, but when provided, they modify the conditioning for both the positive and negative prompts.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Modified positive conditioning with applied camera conditions, clip vision output, and/or starting image data | CONDITIONING |
| `negative` | Modified negative conditioning with applied camera conditions, clip vision output, and/or starting image data | CONDITIONING |
| `latent` | Empty video latent representation for use with video models. The latent tensor has dimensions \[batch\_size, 16, frames, height/8, width/8], where frames is calculated as ((length - 1) // 4) + 1. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanCameraImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `467a82be0dfd6ac1c3b2dd2a6cb02e0d0749de4536a7fbdb000456b817b20ebb`


# WanDancerEncodeAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanDancerEncodeAudio

This node analyzes an audio clip and turns it into a set of features that can guide a video generation model.

This node analyzes an audio clip and turns it into a set of features that can guide a video generation model. It estimates tempo and beats, extracts mel-spectrogram, MFCC, chroma, and onset features, then packages them together with a calculated frame rate for synchronization.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio input to be analyzed and encoded. If the audio has multiple channels, the channels are averaged to mono before feature extraction. | AUDIO | Yes | - |
| `video_frames` | The number of frames in the target video. Used to calculate the frame rate for synchronization (default: 149). | INT | Yes | Min: 1, Max: 16384 (MAX\_RESOLUTION), Step: 4 |
| `audio_inject_scale` | The scale for the audio features when injected into the video model (default: 1.0). | FLOAT | Yes | Min: 0.0, Max: 10.0, Step: 0.01 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio_encoder_output` | A dictionary containing the processed audio features, the calculated frame rate (fps), and the audio injection scale. This output is used to condition the video generation model. | AUDIO\_ENCODER\_OUTPUT |
| `fps_string` | A text string describing the calculated frame rate (fps) based on the audio length and the number of video frames. This string is intended to be used in the prompt for the video model. It is formatted in Chinese to match the reference pipeline. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanDancerEncodeAudio/en.md)

***

**Source fingerprint (SHA-256):** `ce27a3bdea2d9e3cf8875c24236a2a0a1429e9bc13a58581e372fb669d2c0018`


# WanDancerVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanDancerVideo

The WanDancerVideo node prepares conditioning data and an empty latent tensor for video generation with the WanDancer model.

The WanDancerVideo node prepares conditioning data and an empty latent tensor for video generation with the WanDancer model. It attaches optional starting images, masks, CLIP vision embeddings, and audio features to the positive and negative conditioning so they can guide the generated video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning to guide video generation. | CONDITIONING | Yes | |
| `negative` | The negative conditioning to guide video generation. | CONDITIONING | Yes | |
| `vae` | The VAE used to encode the start image into the latent space. | VAE | Yes | |
| `width` | The width of the generated video in pixels (default: 480). | INT | Yes | 16 to MAX\_RESOLUTION (step: 16) |
| `height` | The height of the generated video in pixels (default: 832). | INT | Yes | 16 to MAX\_RESOLUTION (step: 16) |
| `length` | The number of frames in the generated video. Should stay 149 for WanDancer (default: 149). | INT | Yes | 1 to MAX\_RESOLUTION (step: 4) |
| `clip_vision_output` | The CLIP vision embeds for the first frame. | CLIP\_VISION\_OUTPUT | No | |
| `clip_vision_output_ref` | The CLIP vision embeds for the reference image. | CLIP\_VISION\_OUTPUT | No | |
| `start_image` | The initial image(s) to be encoded, can be any number of frames. | IMAGE | No | |
| `mask` | Image conditioning mask for the start image(s). White is kept, black is generated. Used for the local generations. | MASK | No | |
| `audio_encoder_output` | An audio encoder output that provides audio features, frame rate, and inject scale values, which are attached to the conditioning when provided. | AUDIO\_ENCODER\_OUTPUT | No | |

### Notes on Parameter Behavior

* `start_image` is optional. When provided, it is resized to `width` and `height`, encoded by the `vae`, and attached to both the positive and negative conditioning. If `start_image` has more frames than `length`, the extra frames are dropped. If it has fewer frames, the missing frames are filled with zero values.
* `mask` only has an effect when `start_image` is also provided. White areas are kept, and black areas are generated.
* `clip_vision_output_ref` only has an effect when `clip_vision_output` is also provided.
* `audio_encoder_output`, when provided, attaches audio embeddings, frame rate, and injection scale to both the positive and negative conditioning.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning with any attached start-image latent, mask, CLIP vision, or audio data. | CONDITIONING |
| `negative` | The negative conditioning with any attached start-image latent, mask, CLIP vision, or audio data. | CONDITIONING |
| `latent` | An empty latent tensor sized for the requested video length, height, and width. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanDancerVideo/en.md)

***

**Source fingerprint (SHA-256):** `086a0ec361cf7f7ae7ce9505b55d31d92b025c6c7c9cde192009e6664011ad05`


# WanFunControlToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanFunControlToVideo

This node was added to support the Alibaba Wan Fun Control model for video generation, and was added after [this commit](https://github.com/comfyanonymous/ComfyUI/commit/3661c833bc

This node was added to support the Alibaba Wan Fun Control model for video generation, and was added after [this commit](https://github.com/comfyanonymous/ComfyUI/commit/3661c833bcc41b788a7c9f0e7bc48524f8ee5f82).

* **Purpose:** Prepare the conditioning information needed for video generation, using the Wan 2.1 Fun Control model.

The WanFunControlToVideo node is a ComfyUI addition designed to support Wan Fun Control models for video generation, aimed at utilizing WanFun control for video creation.

This node serves as a preparation point for essential conditioning information and initializes the center point of the latent space, guiding the subsequent video generation process using the Wan 2.1 Fun model. The node's name clearly indicates its function: it accepts various inputs and converts them into a format suitable for controlling video generation within the WanFun framework.

The node's position in the ComfyUI node hierarchy indicates that it operates in the early stages of the video generation pipeline, focusing on manipulating conditioning signals before actual sampling or decoding of video frames.

## Inputs

| Parameter Name | Description | Required | Data Type | Default Value |
| - | - | - | - | - |
| positive | Standard ComfyUI positive conditioning data, typically from a "CLIP Text Encode" node. The positive prompt describes the content, subject matter, and artistic style that the user envisions for the generated video. | Yes | CONDITIONING | N/A |
| negative | Standard ComfyUI negative conditioning data, typically generated by a "CLIP Text Encode" node. The negative prompt specifies elements, styles, or artifacts that the user wants to avoid in the generated video. | Yes | CONDITIONING | N/A |
| vae | Requires a VAE (Variational Autoencoder) model compatible with the Wan 2.1 Fun model family, used for encoding and decoding image/video data. | Yes | VAE | N/A |
| width | The desired width of output video frames in pixels, with a default value of 832, minimum value of 16, maximum value determined by nodes.MAX\_RESOLUTION, and a step size of 16. | Yes | INT | 832 |
| height | The desired height of output video frames in pixels, with a default value of 480, minimum value of 16, maximum value determined by nodes.MAX\_RESOLUTION, and a step size of 16. | Yes | INT | 480 |
| length | The total number of frames in the generated video, with a default value of 81, minimum value of 1, maximum value determined by nodes.MAX\_RESOLUTION, and a step size of 4. | Yes | INT | 81 |
| batch\_size | The number of videos generated in a single batch, with a default value of 1, minimum value of 1, and maximum value of 4096. | Yes | INT | 1 |
| clip\_vision\_output | (Optional) Visual features extracted by a CLIP vision model, allowing for visual style and content guidance. | No | CLIP\_VISION\_OUTPUT | None |
| start\_image | (Optional) An initial image that influences the beginning of the generated video. | No | IMAGE | None |
| control\_video | (Optional) Allows users to provide a preprocessed ControlNet reference video that will guide the motion and potential structure of the generated video. | No | IMAGE | None |

## Outputs

| Parameter Name | Description | Data Type |
| - | - | - |
| positive | Provides enhanced positive conditioning data, including encoded start\_image and control\_video. | CONDITIONING |
| negative | Provides negative conditioning data that has also been enhanced, containing the same concat\_latent\_image. | CONDITIONING |
| latent | A dictionary containing an empty latent tensor with the key "samples". | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanFunControlToVideo/en.md)


# WanFunInpaintToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanFunInpaintToVideo

The WanFunInpaintToVideo node prepares conditioning and latent data for inpainting-style video generation, using an optional start image and end image to guide the result.

The WanFunInpaintToVideo node prepares conditioning and latent data for inpainting-style video generation, using an optional start image and end image to guide the result. It works by passing the supplied conditioning, VAE, and image frames through the same logic used for first-and-last-frame video generation, and returns updated conditioning plus an empty latent for sampling.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning prompts for video generation | CONDITIONING | Yes | - |
| `negative` | Negative conditioning prompts to avoid in video generation | CONDITIONING | Yes | - |
| `vae` | VAE model used for encoding and decoding the video frames | VAE | Yes | - |
| `width` | Output video width in pixels (default: 832, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Output video height in pixels (default: 480, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames in the video sequence (default: 81, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of videos to generate in a batch (default: 1) | INT | Yes | 1 to 4096 |
| `clip_vision_output` | Optional CLIP vision output used as conditioning for the start image | CLIP\_VISION\_OUTPUT | No | - |
| `start_image` | Optional starting frame image for video generation | IMAGE | No | - |
| `end_image` | Optional ending frame image for video generation | IMAGE | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Processed positive conditioning output | CONDITIONING |
| `negative` | Processed negative conditioning output | CONDITIONING |
| `latent` | Generated video latent representation | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanFunInpaintToVideo/en.md)

***

**Source fingerprint (SHA-256):** `70b58e961c5df12f94183245ce320197439b2505b47d0bb3ff643b25c9fe6175`


# WanHuMoImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanHuMoImageToVideo

The WanHuMoImageToVideo node prepares conditioning data and an empty latent video for the Wan HuMo video generation pipeline.

The WanHuMoImageToVideo node prepares conditioning data and an empty latent video for the Wan HuMo video generation pipeline. It can attach a reference image and audio embeddings to the positive and negative conditioning inputs, and it creates a zero-filled latent sized from the requested width, height, length, and batch size.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning input that guides the video generation toward desired content. | CONDITIONING | Yes | - |
| `negative` | Negative conditioning input that steers the video generation away from unwanted content. | CONDITIONING | Yes | - |
| `vae` | VAE model used for encoding reference images into latent space. | VAE | Yes | - |
| `width` | Width of the output video frames in pixels. Default: 832. | INT | Yes | 16 to MAX\_RESOLUTION, step 16 |
| `height` | Height of the output video frames in pixels. Default: 480. | INT | Yes | 16 to MAX\_RESOLUTION, step 16 |
| `length` | Number of frames in the generated video sequence. Default: 97. | INT | Yes | 1 to MAX\_RESOLUTION, step 4 |
| `batch_size` | Number of video sequences to generate simultaneously. Default: 1. | INT | Yes | 1 to 4096 |
| `audio_encoder_output` | Optional audio encoding data that can influence video generation based on audio content. | AUDIOENCODEROUTPUT | No | - |
| `ref_image` | Optional reference image used to guide the video generation style and content. Only the first image in the batch is used. | IMAGE | No | - |

**Note:** When a reference image is provided, the first image in the batch is upscaled to the requested `width` and `height` using bilinear interpolation and encoded with the VAE. That reference latent is attached to the positive conditioning, while a zero-filled latent of the same shape is attached to the negative conditioning. When `audio_encoder_output` is provided, the audio embeddings are interpolated and attached to the positive conditioning, while a zero-filled audio embedding is attached to the negative conditioning. If either optional input is omitted, zero-filled placeholder tensors are used: a zero reference latent of shape `[batch_size, 16, 1, height // 8, width // 8]` and/or zero audio embeddings of shape `[batch_size, latent_t + 1, 8, 5, 1280]`, where `latent_t = ((length - 1) // 4) + 1`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Modified positive conditioning with reference image and/or audio embeddings incorporated. | CONDITIONING |
| `negative` | Modified negative conditioning with reference image and/or audio embeddings incorporated. | CONDITIONING |
| `latent` | Zero-initialized latent representation for the video sequence, sized according to `width`, `height`, `length`, and `batch_size`. Shape: `[batch_size, 16, latent_t, height // 8, width // 8]`, where `latent_t = ((length - 1) // 4) + 1`. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanHuMoImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `db674a4a00729a8715988030083e2858f958cd21de73bbbe4ed6d76f5f539419`


# WanInfiniteTalkToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanInfiniteTalkToVideo

WanInfiniteTalkToVideo generates video sequences from audio input.

WanInfiniteTalkToVideo generates video sequences from audio input. It uses a video diffusion model, conditioned on audio features extracted from one or two speakers, to produce a latent representation of a talking head video. The node can generate a new sequence or extend an existing one using previous frames for motion context.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mode` | The audio input mode. `single_speaker` uses one audio input. `two_speakers` enables the additional audio input and masks listed in the Two Speakers Inputs section. | DYNAMIC\_COMBO | Yes | `"single_speaker"`<br />`"two_speakers"` |
| `model` | The base video diffusion model. | MODEL | Yes | - |
| `model_patch` | The model patch containing audio projection layers. | MODEL\_PATCH | Yes | - |
| `positive` | The positive conditioning to guide the generation. | CONDITIONING | Yes | - |
| `negative` | The negative conditioning to guide the generation. | CONDITIONING | Yes | - |
| `vae` | The VAE used for encoding images to and from the latent space. | VAE | Yes | - |
| `width` | The width of the output video in pixels. Must be divisible by 16. (default: 832) | INT | Yes | 16 - MAX\_RESOLUTION (step 16) |
| `height` | The height of the output video in pixels. Must be divisible by 16. (default: 480) | INT | Yes | 16 - MAX\_RESOLUTION (step 16) |
| `length` | The number of frames to generate. (default: 81) | INT | Yes | 1 - MAX\_RESOLUTION (step 4) |
| `clip_vision_output` | Optional CLIP vision output for additional conditioning. | CLIP\_VISION\_OUTPUT | No | - |
| `start_image` | Optional starting image to initialize the video sequence. | IMAGE | No | - |
| `audio_encoder_output_1` | The primary audio encoder output containing features for the first speaker. | AUDIO\_ENCODER\_OUTPUT | Yes | - |
| `motion_frame_count` | Number of previous frames to use as motion context. (default: 9; advanced parameter) | INT | Yes | 1 - 33 (step 1) |
| `audio_scale` | A scaling factor applied to the audio conditioning. (default: 1.0) | FLOAT | Yes | -10.0 - 10.0 (step 0.01) |
| `previous_frames` | Optional previous video frames to extend from. The last `motion_frame_count` frames are used as motion context. | IMAGE | No | - |

### Two Speakers Inputs

The inputs in this section are shown when `mode` is set to `"two_speakers"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio_encoder_output_2` | The second audio encoder output containing features for the second speaker. | AUDIO\_ENCODER\_OUTPUT | No | - |
| `mask_1` | Mask for the first speaker, required if using two audio inputs. | MASK | No | - |
| `mask_2` | Mask for the second speaker, required if using two audio inputs. | MASK | No | - |

**Parameter Constraints:**

* When `mode` is set to `"two_speakers"`, `audio_encoder_output_2`, `mask_1`, and `mask_2` are required for the second speaker setup.
* If `audio_encoder_output_2` is provided, both `mask_1` and `mask_2` must also be provided.
* If both `mask_1` and `mask_2` are provided, `audio_encoder_output_2` must also be provided.
* If `previous_frames` is provided, it must contain at least as many frames as specified by `motion_frame_count`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The patched model with audio conditioning applied. | MODEL |
| `positive` | The positive conditioning, potentially modified with additional context such as a start image or CLIP vision output. | CONDITIONING |
| `negative` | The negative conditioning, potentially modified with additional context. | CONDITIONING |
| `latent` | The generated video sequence in latent space. | LATENT |
| `trim_image` | The number of frames from the start of the motion context that should be trimmed when extending a sequence. Equals `motion_frame_count` when `previous_frames` is provided, otherwise 0. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanInfiniteTalkToVideo/en.md)

***

**Source fingerprint (SHA-256):** `b7359490c1de86d9c82122bc227295b3b7f8a3493f629365ae0f22f9f34d9a66`


# WanMoveConcatTrack - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanMoveConcatTrack

The WanMoveConcatTrack node combines two sets of motion tracking data into a single, longer sequence.

The WanMoveConcatTrack node combines two sets of motion tracking data into a single, longer sequence. It works by joining the track paths and visibility masks from the input tracks along their respective dimensions. If only one track input is provided, it simply passes that data through unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `tracks_1` | The first set of motion tracking data to be concatenated. | TRACKS | Yes | |
| `tracks_2` | An optional second set of motion tracking data. If not provided, `tracks_1` is passed directly to the output. | TRACKS | No | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `tracks` | The concatenated motion tracking data, containing the combined `track_path` and `track_visibility` from the inputs. Returns `tracks_1` unchanged when `tracks_2` is not connected. | TRACKS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanMoveConcatTrack/en.md)

***

**Source fingerprint (SHA-256):** `0507c42dce5d481fe5dc5aa1116c9df279f236419f548ea3eff5d824d0d22653`


# WanMoveTrackToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanMoveTrackToVideo

The WanMoveTrackToVideo node prepares conditioning and latent space data for video generation, incorporating optional motion tracking information.

The WanMoveTrackToVideo node prepares conditioning and latent space data for video generation, incorporating optional motion tracking information. It encodes a starting image sequence into a latent representation and can blend in positional data from object tracks to guide the motion in the generated video. The node outputs modified positive and negative conditioning along with an empty latent tensor ready for a video model.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning input to be modified. | CONDITIONING | Yes | - |
| `negative` | The negative conditioning input to be modified. | CONDITIONING | Yes | - |
| `vae` | The VAE model used to encode the starting image into the latent space. | VAE | Yes | - |
| `tracks` | Optional motion tracking data containing object paths. Uses `track_path` and optionally `track_visibility`; if `track_visibility` is missing, all tracks are treated as visible. | TRACKS | No | - |
| `strength` | Strength of the track conditioning. (default: 1.0) | FLOAT | Yes | 0.0 - 100.0 |
| `width` | The width of the output video. Must be divisible by 16. (default: 832) | INT | Yes | 16 - MAX\_RESOLUTION |
| `height` | The height of the output video. Must be divisible by 16. (default: 480) | INT | Yes | 16 - MAX\_RESOLUTION |
| `length` | The number of frames in the video sequence, in increments of 4. (default: 81) | INT | Yes | 1 - MAX\_RESOLUTION |
| `batch_size` | The batch size for the latent output. (default: 1) | INT | Yes | 1 - 4096 |
| `start_image` | The starting image or image sequence to encode. | IMAGE | Yes | - |
| `clip_vision_output` | Optional CLIP vision model output to add to the conditioning. | CLIP\_VISION\_OUTPUT | No | - |

**Note:** The `strength` parameter only has an effect when `tracks` are provided and `strength` is greater than 0.0; track conditioning is applied only when `start_image` is also provided. If `tracks` are not provided or `strength` is 0.0, the track blending is skipped. When track blending is active, the positive conditioning receives the track-blended latent image, while the negative conditioning receives the unmodified latent image. If `start_image` is not provided, no latent image and mask conditioning is created; the positive and negative conditioning pass through unchanged (except that `clip_vision_output` is still added if provided), and the node outputs an empty latent.

**Note:** When `start_image` is provided, the image sequence is resized to the target `width` and `height` and truncated to the first `length` frames. If the sequence is shorter than `length`, the remaining frames are filled with neutral gray frames (value 0.5) before VAE encoding. The resulting conditioning includes a `concat_mask` with value 0 at the temporal positions corresponding to the start image frames and 1 elsewhere.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning, potentially containing `concat_latent_image`, `concat_mask`, and `clip_vision_output`. | CONDITIONING |
| `negative` | The modified negative conditioning, potentially containing `concat_latent_image`, `concat_mask`, and `clip_vision_output`. | CONDITIONING |
| `latent` | An empty latent tensor with shape `[batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8]`, determined by the `batch_size`, `length`, `height`, and `width` inputs. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanMoveTrackToVideo/en.md)

***

**Source fingerprint (SHA-256):** `b02a1a359d349a0136d84ed77a510c46cb2c8b565650ed54d5fca6c87cd0ab1f`


# WanMoveTracksFromCoords - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanMoveTracksFromCoords

The WanMoveTracksFromCoords node creates motion tracks from a JSON-formatted string of coordinates.

The WanMoveTracksFromCoords node creates motion tracks from a JSON-formatted string of coordinates. It converts the coordinate data into a track format that can be used by other video processing nodes, and can optionally apply a mask to control the visibility of the tracks over time.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `track_coords` | A JSON-formatted string containing the coordinate data for the tracks. The default value is an empty list (`"[]"`). This input is a forced input, so it must be connected in the UI. | STRING | No | N/A |
| `track_mask` | An optional mask. When provided, the node uses it to determine the visibility of tracks per frame: tracks are visible in frames where the mask contains any nonzero pixel. When not provided, all tracks are visible in all frames. | MASK | No | N/A |

**Note:** The `track_coords` input expects a specific JSON structure. It should be a list of tracks, where each track is a list of frames, and each frame is an object with `x` and `y` coordinates. The number of frames must be consistent across all tracks, and at least one track must be provided.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `tracks` | The generated track data, containing the path coordinates and visibility information for each track. | TRACKS |
| `track_length` | The total number of frames in the generated tracks. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanMoveTracksFromCoords/en.md)

***

**Source fingerprint (SHA-256):** `125187c96332fa81f0a30bcc4c927f405b56b578638ea565642a2b88dff808b7`


# WanMoveVisualizeTracks - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanMoveVisualizeTracks

The WanMoveVisualizeTracks node overlays motion tracking data onto a sequence of images or video frames.

The WanMoveVisualizeTracks node overlays motion tracking data onto a sequence of images or video frames. It draws visual representations of tracked points, including their movement paths and current positions, making the motion data visible and easier to analyze.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The sequence of input images or video frames to visualize the tracks on. | IMAGE | Yes | - |
| `tracks` | The motion tracking data containing point paths and visibility information. If not provided, the input images are passed through unchanged. | TRACKS | No | - |
| `line_resolution` | The number of previous frames to use when drawing the trailing path line for each track (default: 24). | INT | Yes | 1 - 1024 |
| `circle_size` | The size of the circle drawn at the current position of each track (default: 12). Marked as an advanced parameter. | INT | Yes | 1 - 128 |
| `opacity` | The opacity of the drawn track overlays (default: 0.75). | FLOAT | Yes | 0.0 - 1.0 |
| `line_width` | The width of the lines used to draw the track paths (default: 16). Marked as an advanced parameter. | INT | Yes | 1 - 128 |

**Note:** If the number of input images does not match the number of frames in the provided `tracks` data, the image sequence will be repeated to match the track length.

**Note:** Track points are drawn with a limited set of repeating colors, and a point is skipped in a frame when its visibility flag is zero for that frame.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The sequence of images with the motion tracking data visualized as overlays. If no `tracks` were provided, the original input images are returned. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanMoveVisualizeTracks/en.md)

***

**Source fingerprint (SHA-256):** `d94bfde28dfdad682edcc81b1c63408f1352e0dbc94af4d043d750e8cd4c099b`


# WanPhantomSubjectToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanPhantomSubjectToVideo

The WanPhantomSubjectToVideo node prepares conditioning data and a latent for Wan video generation.

The WanPhantomSubjectToVideo node prepares conditioning data and a latent for Wan video generation. It creates an empty latent video from the requested width, height, length, and batch size, and, when reference images are supplied, encodes them with the VAE and adds them to the conditionings as time-dimensional visual guidance.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning input for guiding video generation | CONDITIONING | Yes | - |
| `negative` | Negative conditioning input to avoid certain characteristics | CONDITIONING | Yes | - |
| `vae` | VAE model used to encode the reference images when they are provided | VAE | Yes | - |
| `width` | Output video width in pixels (default: 832) | INT | Yes | 16 to MAX\_RESOLUTION (step 16) |
| `height` | Output video height in pixels (default: 480) | INT | Yes | 16 to MAX\_RESOLUTION (step 16) |
| `length` | Number of frames in the generated video (default: 81) | INT | Yes | 1 to MAX\_RESOLUTION (step 4) |
| `batch_size` | Number of videos to generate simultaneously (default: 1) | INT | Yes | 1 to 4096 |
| `images` | Optional reference images used as time-dimensional visual guidance | IMAGE | No | - |

**Note:** When `images` are provided, they are automatically upscaled to match the specified `width` and `height`, and only the first `length` images are used for processing. Each image is encoded with the `vae` and concatenated along the time dimension, and only the RGB channels of each image are used. When `images` are not provided, all three conditioning outputs are returned unchanged from the input conditionings.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with time-dimensional concatenation of the encoded reference images when images are provided; otherwise the input `positive` is returned unchanged | CONDITIONING |
| `negative_text` | Negative conditioning with time-dimensional concatenation of the encoded reference images when images are provided; otherwise the input `negative` is returned unchanged | CONDITIONING |
| `negative_img_text` | Negative conditioning with a zeroed time-dimensional concatenation when images are provided; otherwise the input `negative` is returned unchanged | CONDITIONING |
| `latent` | Zero-filled latent video tensor with 16 channels; its frame count is derived from `length` and its spatial dimensions from `height` and `width` | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanPhantomSubjectToVideo/en.md)

***

**Source fingerprint (SHA-256):** `a1853382f6e564f66262b69dd7b06cc58e26b93386a460a98e6fcc2ff6acf12b`


# WanTrackToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanTrackToVideo

The WanTrackToVideo node converts motion tracking data into video sequences by processing track points and generating corresponding video frames.

The WanTrackToVideo node converts motion tracking data into video sequences by processing track points and generating corresponding video frames. It takes tracking coordinates as input and produces video conditioning and latent representations that can be used for video generation. When no tracks are provided, it falls back to standard image-to-video conversion.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning for video generation | CONDITIONING | Yes | - |
| `negative` | Negative conditioning for video generation | CONDITIONING | Yes | - |
| `vae` | VAE model for encoding and decoding | VAE | Yes | - |
| `tracks` | JSON-formatted tracking data as a multiline string (default: "\[]"). Each track is padded or truncated to a fixed length of 121 points. | STRING | Yes | - |
| `width` | Output video width in pixels (default: 832, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Output video height in pixels (default: 480, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames in the output video (default: 81, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of videos to generate simultaneously (default: 1) | INT | Yes | 1 to 4096 |
| `temperature` | Temperature parameter for motion patching (default: 220.0, step: 0.1). Advanced setting. | FLOAT | Yes | 1.0 to 1000.0 |
| `topk` | Top-k value for motion patching (default: 2). Advanced setting. | INT | Yes | 1 to 10 |
| `start_image` | Starting image for video generation | IMAGE | No | - |
| `clip_vision_output` | CLIP vision output for additional conditioning | CLIP\_VISION\_OUTPUT | No | - |

**Note:** When `tracks` contains valid tracking data, the node processes motion tracks to generate video. When `tracks` is empty, it switches to standard image-to-video mode. If `start_image` is provided, it initializes the first frame of the video sequence, and the motion patching result is added to both positive and negative conditioning. If `clip_vision_output` is provided, it is also added to both positive and negative conditioning.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with motion track information applied | CONDITIONING |
| `negative` | Negative conditioning with motion track information applied | CONDITIONING |
| `latent` | Generated video latent representation | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanTrackToVideo/en.md)

***

**Source fingerprint (SHA-256):** `e67fe326dd7e5ae63ddc35946d8144138d04d9523ec1ad2e08ea6bc1dc9325da`


# AudioEncoderEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioEncoderEncode

The AudioEncoderEncode node converts audio into an encoded representation using an audio encoder model.

The AudioEncoderEncode node converts audio into an encoded representation using an audio encoder model. It takes an audio encoder and an audio input, then extracts the waveform and sample rate from the audio and passes them to the encoder to produce an encoded output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio_encoder` | The audio encoder model used to process the audio input | AUDIO\_ENCODER | Yes | - |
| `audio` | The audio data containing the waveform and sample rate information | AUDIO | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The encoded audio representation produced by the audio encoder | AUDIO\_ENCODER\_OUTPUT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioEncoderEncode/en.md)

***

**Source fingerprint (SHA-256):** `85f77152ccc1e3f4687e2b655283e69e03d90b862d6a676dcb89ea973dd70a63`


# BatchLatentsNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BatchLatentsNode

The Batch Latents node combines multiple latent inputs into a single batch.

The Batch Latents node combines multiple latent inputs into a single batch. It takes a variable number of latent samples and merges them along the batch dimension so they can be processed together by subsequent nodes. The node also merges the batch index metadata of all inputs into the combined output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `latents` | A set of latent samples to be combined into a single batch. You must provide at least one latent, and you can add up to 50. The node automatically creates input slots (`latent_1`, `latent_2`, and so on) as you connect more latents. | LATENT | Yes | 1 to 50 inputs |

**Note:** You must provide at least one latent input for the node to function. The node automatically creates input slots as you connect more latents, up to a maximum of 50. Each input latent is reshaped to match the sample shape of the first latent before being combined, and any latent without batch index metadata is assigned a sequential batch index. The input latents are joined along the batch dimension to produce the combined result.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | A single latent output containing all the input latents combined into one batch, together with their merged batch index metadata. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BatchLatentsNode/en.md)

***

**Source fingerprint (SHA-256):** `38df5e6cfa391e054c663af1cc55728d115cebfbb804e1c2c51dfc2aab37df47`


# CLIPTextEncodeControlnet - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodeControlnet

The CLIP Text Encode (Controlnet) node encodes a text prompt with a CLIP model and adds the resulting text encoding to existing conditioning data.

The CLIP Text Encode (Controlnet) node encodes a text prompt with a CLIP model and adds the resulting text encoding to existing conditioning data. It stores the text embeddings as controlnet cross-attention parameters inside each conditioning entry, so the returned conditioning carries that extra controlnet information.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for text tokenization and encoding | CLIP | Yes | - |
| `conditioning` | Existing conditioning data to be combined with the CLIP text encoding | CONDITIONING | Yes | - |
| `text` | The text prompt to be processed by the CLIP model. Supports multiline text and dynamic prompts | STRING | Yes | - |

**Note:** All three inputs (`clip`, `conditioning`, and `text`) are required for this node to function. The `text` input supports multiline text and dynamic prompts for flexible text processing. This node is marked as experimental in the source code.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Enhanced conditioning data with the added controlnet cross-attention parameters (`cross_attn_controlnet` and `pooled_output_controlnet`) derived from the CLIP text encoding | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeControlnet/en.md)

***

**Source fingerprint (SHA-256):** `95a798684ca8734bfff53c7b979b320f6834dc1a9553163d0e567243761000f1`


# CLIPSetLastLayer - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipSetLastLayer

CLIP Set Last Layer is a core node in ComfyUI for controlling the processing depth of CLIP models.

`CLIP Set Last Layer` is a core node in ComfyUI for controlling the processing depth of CLIP models. It allows users to precisely control where the CLIP text encoder stops processing, affecting both the depth of text understanding and the style of generated images. The original CLIP model is left unchanged: the node works on a copy and returns the modified copy.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model to be modified | CLIP | Yes | - |
| `stop_at_clip_layer` | Specifies which layer to stop at. A value of -1 uses all layers, while -24 uses only the first layer (default: -1). This is an advanced parameter. | INT | Yes | -24 to -1 (step: 1) |

The values are negative and count backwards from the end of the model: -1 refers to the last (deepest) layer and -24 to the first (shallowest) layer, which is why the allowed range only covers -24 through -1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `clip` | The modified CLIP model (a clone of the input; the original CLIP model is not changed) with the specified layer set as the last one | CLIP |

## Why Set the Last Layer

* **Performance Optimization**: Like not needing a PhD to understand simple sentences, sometimes shallow understanding is enough and faster
* **Style Control**: Different levels of understanding produce different artistic styles
* **Compatibility**: Some models might perform better at specific layers

Imagine the CLIP model as a 24-layer intelligent brain:

* Shallow layers (1-8): Recognize basic letters and words
* Middle layers (9-16): Understand grammar and sentence structure
* Deep layers (17-24): Grasp abstract concepts and complex semantics

`CLIP Set Last Layer` works like a **"thinking depth controller"**:

* -1: Use all 24 layers (complete understanding)
* -2: Stop at layer 23 (slightly simplified)
* -12: Stop at layer 13 (medium understanding)
* -24: Use only layer 1 (basic understanding)

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPSetLastLayer/en.md)

***

**Source fingerprint (SHA-256):** `41a7feb9729dbb2a987a15a53c56641eae2a5611db8762ef2ce14b58970752fe`


# CLIPTextEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipTextEncode

Encodes a text prompt using a CLIP model into an embedding that can be used to guide the diffusion model towards generating specific images.

Encodes a text prompt using a CLIP model into an embedding that can be used to guide the diffusion model towards generating specific images.

`CLIP Text Encode (CLIPTextEncode)` acts as a translator, converting your text descriptions into a format that AI can understand. This helps the AI interpret your input and generate the desired image.

Think of it as communicating with an artist who speaks a different language. The CLIP model, trained on vast image-text pairs, bridges this gap by converting your descriptions into "instructions" that the AI model can follow.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | The text to be encoded. Supports multi-line input and dynamic prompts. | STRING | Yes | Any text |
| `clip` | The CLIP model used for encoding the text. | CLIP | Yes | Loaded CLIP models |

Note: If the `clip` input is None (for example, when it comes from a checkpoint loader whose checkpoint does not contain a valid CLIP or text encoder model), the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | A conditioning containing the embedded text used to guide the diffusion model. | CONDITIONING |

## Prompt Features

### Embedding Models

Embedding models allow you to apply specific artistic effects or styles. Supported formats include `.safetensors`, `.pt`, and `.bin`. To use an embedding model:

1. Place the file in the `ComfyUI/models/embeddings` folder.
2. Reference it in your text using `embedding:model_name`.

Example: If you have a model named `EasyNegative.pt` in your `ComfyUI/models/embeddings` folder, then you can use it like this:

```
worst quality, embedding:EasyNegative, bad quality
```

**IMPORTANT**: When using embedding models, verify that the file name matches and is compatible with your model's architecture. For example an embedding designed for SD1.5 will not work correctly for a SDXL model.

### Prompt Weight Adjustment

You can adjust the importance of certain parts of your description using parentheses. For example:

* `(beautiful:1.2)` increases the weight of "beautiful".
* `(beautiful:0.8)` decrease the weight of "beautiful".
* Plain parentheses `(beautiful)` will apply a default weight of 1.1.

You can use the keyboard shortcuts `ctrl + up/down arrow` to quickly adjust weights. The weight adjustment step size can be modified in the settings.

If you want to include literal parentheses in your prompt without changing the weight, you can escape them using a backslash e.g. `\(word\)`.

### Wildcard/Dynamic Prompts

Use `{}` to create dynamic prompts. For example, `{day|night|morning}` will randomly select one option each time the prompt is processed.

If you want to include literal curly braces in your prompt without triggering dynamic behavior, you can escape them using a backslash e.g. `\{word\}`.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncode/en.md)

***

**Source fingerprint (SHA-256):** `ace7988df7aaa3ac26419b16a9bd8908a327da6e82c21c2b2704af091d2e76e7`


# CLIPVisionEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipVisionEncode

The CLIP Vision Encode node is an image encoding node in ComfyUI, used to convert input images into visual feature vectors through the CLIP Vision model.

The `CLIP Vision Encode` node is an image encoding node in ComfyUI, used to convert input images into visual feature vectors through the CLIP Vision model. This node is an important bridge connecting image and text understanding, and is widely used in various AI image generation and processing workflows.

**Node Functionality**

* **Image feature extraction**: Converts input images into high-dimensional feature vectors
* **Multimodal bridging**: Provides a foundation for joint processing of images and text
* **Conditional generation**: Provides visual conditions for image-based conditional generation

## Inputs

| Parameter Name | Description | Data Type |
| - | - | - |
| `clip_vision` | CLIP vision model, usually loaded via the CLIPVisionLoader node | CLIP\_VISION |
| `image` | The input image to be encoded | IMAGE |
| `crop` | Image cropping method, options: center (center crop), none (no crop) | Dropdown |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| CLIP\_VISION\_OUTPUT | Encoded visual features | CLIP\_VISION\_OUTPUT |

This output object contains:

* `last_hidden_state`: The last hidden state
* `image_embeds`: Image embedding vector
* `penultimate_hidden_states`: The penultimate hidden state
* `mm_projected`: Multimodal projection result (if available)

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPVisionEncode/en.md)


# EmptyARVideoLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyARVideoLatent

The EmptyARVideoLatent node creates a blank latent representation for video generation.

The EmptyARVideoLatent node creates a blank latent representation for video generation. It builds a tensor of zeros using the requested width, height, frame count, and batch size, which can then be used to initialize a video generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the video frames in pixels (default: 832) | INT | Yes | 16 to 8192 (step: 16) |
| `height` | The height of the video frames in pixels (default: 480) | INT | Yes | 16 to 8192 (step: 16) |
| `length` | The number of frames in the video (default: 81) | INT | Yes | 1 to 1024 (step: 4) |
| `batch_size` | The number of videos to generate in a single batch (default: 1) | INT | Yes | 1 to 64 |

Note: The internal latent size is derived from these inputs. `width` and `height` are divided by 8, and the number of latent time steps is calculated as `((length - 1) // 4) + 1`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | A latent tensor filled with zeros, representing an empty video latent space with the specified dimensions, length, and batch size. The tensor shape is \[batch\_size, 16, lat\_t, height/8, width/8], where lat\_t = ((length - 1) // 4) + 1 is the number of latent time steps derived from the requested length. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyARVideoLatent/en.md)

***

**Source fingerprint (SHA-256):** `02ed3c96d94f2a3df9fb5315a5312e5280b9bee280369eb1218ba10bc122e609`


# EmptyAceStep1.5LatentAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyAceStep1.5LatentAudio

The Empty Ace Step 1.5 Latent Audio node creates an empty (silent) audio latent tensor for audio generation workflows.

The Empty Ace Step 1.5 Latent Audio node creates an empty (silent) audio latent tensor for audio generation workflows. It builds a latent with 64 channels whose temporal length is calculated from the requested duration, and tags it as audio data for use by downstream audio nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `seconds` | The duration of the audio to generate, in seconds (default: 120.0). The latent length is calculated as `seconds * 48000 / 1920`, rounded to the nearest whole number. | FLOAT | Yes | 1.0 - 1000.0 (step: 0.01) |
| `batch_size` | The number of latent images in the batch (default: 1). | INT | Yes | 1 - 4096 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | An empty latent tensor representing silent audio. The tensor has shape \[batch\_size, 64, length], where length is derived from `seconds`. The output also includes a type identifier of "audio" and a `downscale_ratio_temporal` value of 1764, which is used for temporal downscaling in audio processing. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyAceStep1.5LatentAudio/en.md)

***

**Source fingerprint (SHA-256):** `bb7120c91ce5d779147cb8553d6f96fa160d87468d4d87550fb6dd4ec89b1557`


# EmptyAceStepLatentAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyAceStepLatentAudio

The Empty Ace Step 1.0 Latent Audio node creates empty latent audio samples for a chosen duration.

The Empty Ace Step 1.0 Latent Audio node creates empty latent audio samples for a chosen duration. It fills a batch of silent (all-zero) audio latents, where the length is calculated from the `seconds` input using audio processing parameters. This is typically used to initialize audio workflows that need a latent representation as a starting point.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `seconds` | The duration of the audio in seconds (default: 120.0, step: 0.1) | FLOAT | Yes | 1.0 - 1000.0 |
| `batch_size` | The number of latent images in the batch (default: 1) | INT | Yes | 1 - 4096 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | Returns empty latent audio samples filled with zeros. The output contains a `samples` tensor and a `type` field set to "audio". | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyAceStepLatentAudio/en.md)

***

**Source fingerprint (SHA-256):** `8268eb582a28c7acc495c52831cc6edd8f8fdd1b294857451ce94abc37ca0d14`


# EmptyChromaRadianceLatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyChromaRadianceLatentImage

The EmptyChromaRadianceLatentImage node creates a blank latent image with the dimensions you specify, for use in chroma radiance workflows.

The EmptyChromaRadianceLatentImage node creates a blank latent image with the dimensions you specify, for use in chroma radiance workflows. It produces a tensor filled with zeros that acts as the starting point for latent space operations, letting you define the width, height, and batch size of the empty latent image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the latent image in pixels (default: 1024) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | The height of the latent image in pixels (default: 1024) | INT | Yes | 16 to MAX\_RESOLUTION |
| `batch_size` | The number of latent images to generate in a batch (default: 1) | INT | Yes | 1 to 4096 |

Note: `width` and `height` are defined with a step of 16, so the values are adjusted in multiples of 16.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | The generated empty latent image tensor filled with zeros, with the shape batch\_size x 3 x height x width | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyChromaRadianceLatentImage/en.md)

***

**Source fingerprint (SHA-256):** `870cc89fb021c258c214db153cda0a32a63da1b6bf92f09cbd3b8498c363096b`


# EmptyCosmosLatentVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyCosmosLatentVideo

EmptyCosmosLatentVideo creates an empty latent video tensor with the specified dimensions.

EmptyCosmosLatentVideo creates an empty latent video tensor with the specified dimensions. It generates a zero-filled latent representation that can be used as a starting point for video generation workflows, with configurable width, height, length, and batch size parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the latent video in pixels (default: 1280, increments of 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | The height of the latent video in pixels (default: 704, increments of 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | The number of frames in the latent video (default: 121, increments of 8) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | The number of latent videos to generate in a batch (default: 1) | INT | No | 1 to 4096 |

Note: The latent tensor is spatially downsampled by a factor of 8 in both height and width, and contains 16 channels. The number of latent temporal frames is calculated as `((length - 1) // 8) + 1`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | The generated empty latent video tensor with zero values | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyCosmosLatentVideo/en.md)

***

**Source fingerprint (SHA-256):** `7ee194324b02367ed853f6d36bc51742081bac6a9469c4a619586e0560a1b33b`


# EmptyFlux2LatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyFlux2LatentImage

The Empty Flux 2 Latent node creates a blank latent representation filled with zeros.

The Empty Flux 2 Latent node creates a blank latent representation filled with zeros. It is used as a starting point for the Flux model's denoising process. The latent dimensions are taken from the input width and height, each divided by 16.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the final image to generate. The latent width will be this value divided by 16. The default value is 1024. | INT | Yes | 16 to 16384 |
| `height` | The height of the final image to generate. The latent height will be this value divided by 16. The default value is 1024. | INT | Yes | 16 to 16384 |
| `batch_size` | The number of latent samples to generate in a single batch. The default value is 1. | INT | No | 1 to 4096 |

**Note:** The `width` and `height` inputs use a step of 16, so they must be divisible by 16. This is because the node divides them by this factor to create the latent dimensions.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | A latent tensor filled with zeros. The shape is `[batch_size, 128, height // 16, width // 16]`. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyFlux2LatentImage/en.md)

***

**Source fingerprint (SHA-256):** `f8356568f0ab521a3f246d1f672492e74f9a2f449694961b913bd14a5f0f3878`


# EmptyHiDreamO1LatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyHiDreamO1LatentImage

This node creates an empty latent image in pixel space for the HiDream-O1-Image model.

This node creates an empty latent image in pixel space for the HiDream-O1-Image model. It generates a blank tensor of zeros that acts as the starting point for image generation, with dimensions defined by the width, height, and batch size inputs.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the latent image in pixels. Default: 2048. The value must be a multiple of 32. The model was trained at about 4 megapixels; lower resolutions may reduce quality noticeably. | INT | Yes | 64 to 4096 (step: 32) |
| `height` | The height of the latent image in pixels. Default: 2048. The value must be a multiple of 32. The model was trained at about 4 megapixels; lower resolutions may reduce quality noticeably. | INT | Yes | 64 to 4096 (step: 32) |
| `batch_size` | The number of latent images to generate in a single batch. Default: 1. | INT | Yes | 1 to 64 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | A tensor filled with zeros representing the empty latent image, with shape (batch\_size, 3, height, width). | LATENT |

## Notes

* The HiDream-O1-Image model was trained at approximately 4 megapixels. Using significantly lower resolutions may result in noticeably reduced image quality.
* Trained resolutions include: 2048x2048, 2304x1728, 1728x2304, 2560x1440, 1440x2560, 2496x1664, 1664x2496, 3104x1312, 1312x3104, 2304x1792, 1792x2304.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyHiDreamO1LatentImage/en.md)

***

**Source fingerprint (SHA-256):** `7412639e261512d9174e60009143c8c06c354e2a20ada7271837d72053426be5`


# EmptyHunyuanImageLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyHunyuanImageLatent

The EmptyHunyuanImageLatent node creates a blank, all-zero latent space for Hunyuan image generation models.

The EmptyHunyuanImageLatent node creates a blank, all-zero latent space for Hunyuan image generation models. It produces an empty starting latent using the given width, height, and batch size, which can then be passed to downstream nodes in the workflow. The latent tensor contains 64 channels, and each spatial dimension equals the corresponding pixel dimension divided by 32.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the generated latent image in pixels (default: 2048, step: 32) | INT | Yes | 64 to MAX\_RESOLUTION |
| `height` | The height of the generated latent image in pixels (default: 2048, step: 32) | INT | Yes | 64 to MAX\_RESOLUTION |
| `batch_size` | The number of latent samples to generate in a batch (default: 1) | INT | Yes | 1 to 4096 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | An empty latent tensor with 64 channels and dimensions of height ÷ 32 by width ÷ 32, ready for Hunyuan image processing | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyHunyuanImageLatent/en.md)

***

**Source fingerprint (SHA-256):** `31fc10d43c224810709870cf40256b6fccd4743445ea9d98d148d443bc591d7a`


# EmptyHunyuanLatentVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyHunyuanLatentVideo

The EmptyHunyuanLatentVideo node is similar to the EmptyLatentImage node.

The `EmptyHunyuanLatentVideo` node is similar to the `EmptyLatentImage` node. You can consider it as a blank canvas for video generation, where width, height, and length define the properties of the canvas, and the batch size determines the number of canvases to create. This node creates empty canvases ready for subsequent video generation tasks.

## Inputs

| Parameter | Description | Comfy Type |
| - | - | - |
| `width` | Video width, default 848, minimum 16, maximum `nodes.MAX_RESOLUTION`, step size 16. | `INT` |
| `height` | Video height, default 480, minimum 16, maximum `nodes.MAX_RESOLUTION`, step size 16. | `INT` |
| `length` | Video length, default 25, minimum 1, maximum `nodes.MAX_RESOLUTION`, step size 4. | `INT` |
| `batch_size` | Batch size, default 1, minimum 1, maximum 4096. | `INT` |

## Outputs

| Parameter | Description | Comfy Type |
| - | - | - |
| `samples` | Generated latent video samples containing zero tensors, ready for processing and generation tasks. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyHunyuanLatentVideo/en.md)


# EmptyHunyuanVideo15Latent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyHunyuanVideo15Latent

This node creates an empty latent tensor specifically formatted for use with the HunyuanVideo 1.5 model.

This node creates an empty latent tensor specifically formatted for use with the HunyuanVideo 1.5 model. It generates a blank starting point for video generation by allocating a tensor of zeros with the correct channel count and spatial dimensions for the model's latent space.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the video frame in pixels. | INT | Yes | - |
| `height` | The height of the video frame in pixels. | INT | Yes | - |
| `length` | The number of frames in the video sequence. | INT | Yes | - |
| `batch_size` | The number of video samples to generate in a batch (default: 1). | INT | No | - |

**Note:** The spatial dimensions of the generated latent tensor are calculated by dividing the input `width` and `height` by 16 (this node uses a spatial scale factor of 16 rather than 8). The temporal dimension (frames) is calculated as `((length - 1) // 4) + 1`. These calculations use integer division, so `width` and `height` should be multiples of 16 to avoid truncation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | An empty latent tensor with dimensions suitable for the HunyuanVideo 1.5 model. The tensor has a shape of `[batch_size, 32, ((length - 1) // 4) + 1, height // 16, width // 16]`. The output also includes a `downscale_ratio_spacial` value of 16. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyHunyuanVideo15Latent/en.md)

***

**Source fingerprint (SHA-256):** `ce7ec75e8433c778d175a3e2ea260a4397aa5507428908b9a32f50fbe9e184c6`


# EmptyLTXVLatentVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyLTXVLatentVideo

The EmptyLTXVLatentVideo node creates an empty (zero-filled) latent video tensor using the width, height, length, and batch size you specify.

The EmptyLTXVLatentVideo node creates an empty (zero-filled) latent video tensor using the width, height, length, and batch size you specify. It provides a blank starting point for LTXV video generation workflows, with the latent dimensions automatically compressed relative to the requested video size.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the latent video tensor (default: 768, step: 32) | INT | Yes | 64 to MAX\_RESOLUTION |
| `height` | The height of the latent video tensor (default: 512, step: 32) | INT | Yes | 64 to MAX\_RESOLUTION |
| `length` | The number of frames in the latent video (default: 97, step: 8) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | The number of latent videos to generate in a batch (default: 1) | INT | Yes | 1 to 4096 |

Note: The latent video is compressed compared to the requested dimensions: the spatial dimensions (width and height) are divided by 32, and the frame count (length) is divided by 8 and rounded up to the nearest whole number. The step values for width, height, and length help keep these divisions even.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | The generated empty latent tensor with zero values in the specified dimensions, along with a spatial downscale ratio of 32 | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyLTXVLatentVideo/en.md)

***

**Source fingerprint (SHA-256):** `0b1e57baf9730d852b03b6bccbb8a033e2be9b9cd2420a0aa3638c31f6d3cd26`


# EmptyLatentAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyLatentAudio

Empty Latent Audio creates an empty latent tensor for audio processing.

Empty Latent Audio creates an empty latent tensor for audio processing. It generates a blank audio latent representation with a specified duration and batch size, which can be used as a starting point for audio generation or processing workflows. The node automatically calculates the appropriate latent dimensions based on the audio duration and sample rate.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `seconds` | The duration of the audio in seconds (default: 47.6) | FLOAT | Yes | 1.0 - 1000.0 |
| `batch_size` | The number of latent images in the batch (default: 1) | INT | Yes | 1 - 4096 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | Returns an empty latent tensor for audio processing with the specified duration and batch size. The tensor has a shape of \[batch\_size, 64, length], where length is calculated from the audio duration and sample rate. The output also includes metadata indicating the type is "audio" and a temporal downscale ratio of 2048. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyLatentAudio/en.md)

***

**Source fingerprint (SHA-256):** `6ca63d26febe2d87ff751a57044eb81b553b19756f4b3f9478ecb5a733ec0041`


# EmptyLatentHunyuan3Dv2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyLatentHunyuan3Dv2

This node creates a batch of empty (all-zero) latent samples formatted for Hunyuan3Dv2 3D generation models.

This node creates a batch of empty (all-zero) latent samples formatted for Hunyuan3Dv2 3D generation models. It produces the correctly shaped latent tensor that serves as the starting point for 3D generation workflows, with the latent tagged as type "hunyuan3dv2".

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `resolution` | The resolution dimension of the latent space to create (default: 3072) | INT | Yes | 1 - 8192 |
| `batch_size` | The number of latent images in the batch (default: 1) | INT | Yes | 1 - 4096 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | An empty latent tensor of shape \[batch\_size, 64, resolution] containing zero-filled samples, tagged with the type "hunyuan3dv2" | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyLatentHunyuan3Dv2/en.md)

***

**Source fingerprint (SHA-256):** `e9061301341ab84290cd2b16d5307636310a0772562cf485e3444876e4786ddd`


# EmptyLatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyLatentImage

The EmptyLatentImage node is designed to generate a blank latent space representation with specified dimensions and batch size.

The `EmptyLatentImage` node is designed to generate a blank latent space representation with specified dimensions and batch size. This node serves as a foundational step in generating or manipulating images in latent space, providing a starting point for further image synthesis or modification processes.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `width` | Specifies the width of the latent image to be generated. This parameter directly influences the spatial dimensions of the resulting latent representation. | `INT` |
| `height` | Determines the height of the latent image to be generated. This parameter is crucial for defining the spatial dimensions of the latent space representation. | `INT` |
| `batch_size` | Controls the number of latent images to be generated in a single batch. This allows for the generation of multiple latent representations simultaneously, facilitating batch processing. | `INT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a tensor representing a batch of blank latent images, serving as a base for further image generation or manipulation in latent space. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyLatentImage/en.md)


# EmptyMiniMaxH3LatentAV - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyMiniMaxH3LatentAV

This node creates an empty latent that combines both video and audio information for the MiniMax H3 model.

This node creates an empty latent that combines both video and audio information for the MiniMax H3 model. You define the width, height, and length of the content, and the node produces a blank latent that the model can use as a starting point for generation. The duration (length) is automatically adjusted to fit the model's required frame grid of 17k+5 frames at 24 fps.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the latent in pixels. Values must be multiples of 32. Default: 1344. | INT | Yes | 32 - MAX\_RESOLUTION (step 32) |
| `height` | The height of the latent in pixels. Values must be multiples of 32. Default: 768. | INT | Yes | 32 - MAX\_RESOLUTION (step 32) |
| `length` | Frame count at 24 fps, snapped up to the model's 17k+5 grid (124 = \~5s; trained range is \~124-362, longer is untested). Default: 124. | INT | Yes | 5 - 3600 (step 17) |

Note: The `length` value is snapped up to the next frame count that fits the model's 17k+5 grid (17 x k + 5 frames, such as 5, 22, 39, 56, 73, 90, 107, 124, and so on). The `width` and `height` values must be multiples of 32. The maximum resolution is the system-defined value in ComfyUI.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latent` | The generated empty joint video+audio latent for MiniMax H3, sized according to the input width, height, and length. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyMiniMaxH3LatentAV/en.md)

***

**Source fingerprint (SHA-256):** `ee24f4ac630858d87b9b98bb402689a5790e0ed882ec47dffe7b497216e37a5c`


# EmptyMiniMaxMusic3LatentAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyMiniMaxMusic3LatentAudio

This node creates an empty (zero-filled) audio latent for the MiniMax Music3 model.

This node creates an empty (zero-filled) audio latent for the MiniMax Music3 model. It converts the requested duration in seconds into the corresponding number of audio frames and produces a blank latent tensor of the correct size, ready to be used as the starting point for music generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `seconds` | The duration of the audio latent in seconds (default: 120.0). The value is converted to audio frames and clamped to the model's supported duration limits. | FLOAT | Yes | 0.04 to (MAX\_AUDIO\_FRAMES / AUDIO\_FRAMES\_PER\_SECOND), step 0.04 |
| `batch_size` | The number of audio latents to generate in one batch (default: 1). | INT | Yes | 1 to 4096 |

Note: The `seconds` value is rounded to the nearest audio frame and clamped to a minimum of 1 frame and a maximum of `MAX_AUDIO_FRAMES` frames, so the actual latent length may differ slightly from the exact value entered.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | A zero-filled audio latent tensor of shape (batch\_size, 128, latent\_length). Includes metadata that marks the sample as audio data with a temporal downscale ratio of 512. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyMiniMaxMusic3LatentAudio/en.md)

***

**Source fingerprint (SHA-256):** `77e6a69702a837c958c2954bba061c979152f034bc7774a5b6c97ea8d57bda4b`


# EmptyMochiLatentVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyMochiLatentVideo

EmptyMochiLatentVideo creates an empty latent video tensor with the dimensions you specify.

EmptyMochiLatentVideo creates an empty latent video tensor with the dimensions you specify. It generates a zero-filled latent representation that can be used as a starting point for video generation workflows. The node lets you define the width, height, length, and batch size of the latent video tensor.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the latent video in pixels (default: 848, values increase in steps of 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | The height of the latent video in pixels (default: 480, values increase in steps of 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | The number of frames in the latent video (default: 25, values increase in steps of 6, starting at 7) | INT | Yes | 7 to MAX\_RESOLUTION |
| `batch_size` | The number of latent videos to generate in a batch (default: 1) | INT | No | 1 to 4096 |

**Note:** The actual latent dimensions are calculated as width/8 and height/8, the temporal dimension is calculated as `((length - 1) // 6) + 1`, and the tensor has 12 channels. Because `length` advances in steps of 6 starting from 7, valid values are 7, 13, 19, 25, and so on.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | An empty latent video tensor with the specified dimensions, containing all zeros | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyMochiLatentVideo/en.md)

***

**Source fingerprint (SHA-256):** `1774e1b54b429a946172ba9f609b433d99c0ca2ced2d9e0e3b0b85c82e5141b2`


# EmptyQwenImageLayeredLatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyQwenImageLayeredLatentImage

Empty Qwen Image Layered Latent prepares the blank canvas that the Qwen-Image-Layered model paints onto.

Empty Qwen Image Layered Latent prepares the blank canvas that the Qwen-Image-Layered model paints onto. Think of it as a stack of clean tracing sheets clipped together in order: the model fills the first sheet with the complete picture, and each sheet after it with one part of that picture. This node decides how big the sheets are and how many of them there are. It does not draw anything itself.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the latent image to create. The value must be divisible by 16. (default: 640) | INT | Yes | 16 to MAX\_RESOLUTION (step 16) |
| `height` | The height of the latent image to create. The value must be divisible by 16. (default: 640) | INT | Yes | 16 to MAX\_RESOLUTION (step 16) |
| `layers` | How many layers to separate the picture into. One extra sheet is always reserved for the complete picture, so you get `layers + 1` images back, not `layers`. Set it to 2 and you get the complete picture plus 2 layers. Set it to 0 and you get the complete picture on its own. (default: 3) | INT | Yes | 0 to MAX\_RESOLUTION (step 1) |
| `batch_size` | The number of latent samples to generate in a batch. (default: 1) | INT | Yes | 1 to 4096 |

**Note:** The `width` and `height` parameters are internally divided by 8 to determine the spatial dimensions of the output latent tensor.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | A latent tensor filled with zeros. Its shape is `[batch_size, 16, layers + 1, height // 8, width // 8]`. | LATENT |

## Why you get one more image than you asked for

Qwen-Image-Layered does not only take a picture apart. It also repaints the complete picture, on its own sheet, alongside the layers. That is why the stack is always one sheet taller than the number of layers you asked for.

* **The first image is the complete picture, not a layer.** It is the same picture you already have, so throw it away when all you want are the layers.
* **Lay all the layers back on top of each other and you get the complete picture again.** If they do not add back up to that first image, the separation did not work the way you wanted, so this is a quick way to check the result.
* **Keep the sheets in order.** The stack is the only record of which layer sits on top of which. Nothing is written on the sheets themselves to say where they belong, so reordering or dropping images means reordering or losing layers.
* **The layers come out with transparency**, so they can be stacked without the lower ones being hidden behind an opaque background.

## Usage suggestions

Send the output to the sampler the way you would a normal empty latent, then put LatentCutToBatch with `dim` set to `t` before VAE Decode. That is the step that takes the stack apart into separate images, in order, starting with the complete picture.

Start with the default of 3 layers. Asking for more means a longer generation and a finer separation, and it is not worth raising until you have seen what the model does with a small number.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyQwenImageLayeredLatentImage/en.md)

***

**Source fingerprint (SHA-256):** `5ccac979fcbcefb65f28867a89401c095cb330e09c13270008c32feeeafb1287`


# EmptySD3LatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptySD3LatentImage

EmptySD3LatentImage creates a blank (all-zero) latent image in the layout that Stable Diffusion 3 models expect.

EmptySD3LatentImage creates a blank (all-zero) latent image in the layout that Stable Diffusion 3 models expect. Because the latent is empty, it is normally used as the starting point that a generation workflow fills in with an image. The width and height you choose determine the size of the final image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the latent image in pixels (default: 1024). Values are stepped in increments of 16. | INT | Yes | 16 to MAX\_RESOLUTION (step: 16) |
| `height` | The height of the latent image in pixels (default: 1024). Values are stepped in increments of 16. | INT | Yes | 16 to MAX\_RESOLUTION (step: 16) |
| `batch_size` | The number of latent images to generate in the batch (default: 1). | INT | Yes | 1 to 4096 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | A latent tensor containing blank (all-zero) samples in the SD3-compatible format. The tensor has 16 channels, is scaled down by a factor of 8 relative to `width` and `height`, and carries a spatial downscale ratio of 8. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptySD3LatentImage/en.md)

***

**Source fingerprint (SHA-256):** `694ede56f43e3f3889b4d23e636fa6b33b490bcbd214584557f0dc883fa0a32d`


# EmptyTrellis2LatentStructure - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyTrellis2LatentStructure

This node creates an empty latent structure for the Trellis2 model, where all values are set to zero.

This node creates an empty latent structure for the Trellis2 model, where all values are set to zero. It produces a blank 3D latent tensor with 32 channels at a resolution of 16×16×16, sized for the specified number of items in the batch.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `batch_size` | The number of latent images in the batch (default: 1). | INT | Yes | 1 to 4096 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | An empty Trellis2 latent structure. The samples are a zero-filled tensor with the shape (batch\_size, 32, 16, 16, 16), and the latent type is set to "trellis2". | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyTrellis2LatentStructure/en.md)

***

**Source fingerprint (SHA-256):** `a551f0e05e58b025df03a3babee36f57fd900b5e02926fbdbd67a512ebead078`


# EmptyYuE2LatentAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyYuE2LatentAudio

This node creates an empty audio latent for YuE2, sized to a chosen duration and batch count.

This node creates an empty audio latent for YuE2, sized to a chosen duration and batch count. It produces silent placeholder audio data that later nodes can fill in during audio generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `seconds` | Length of the audio latent to create, in seconds (default: 120.0). The number of latent frames is calculated from this value, with a minimum of 1 frame. | FLOAT | Yes | 0.04 to 1000.0 (step 0.04) |
| `batch_size` | Number of audio latents to create in one batch (default: 1). | INT | Yes | 1 to 4096 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | An empty audio latent containing a tensor of zeros, sized by `batch_size` and the frame count derived from `seconds`. It is tagged as audio type with a temporal downscale ratio of 1920. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyYuE2LatentAudio/en.md)

***

**Source fingerprint (SHA-256):** `3397e3feb534c87d9790bbfe36e8e641476d9b6aa00d75a4e6d0c32f4a948563`


# HunyuanVideo15LatentUpscaleWithModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanVideo15LatentUpscaleWithModel

The Hunyuan Video 15 Latent Upscale With Model node increases the resolution of a latent image representation.

The Hunyuan Video 15 Latent Upscale With Model node increases the resolution of a latent image representation. It first upscales the latent samples to a specified size using a chosen interpolation method, then refines the upscaled result using a specialized Hunyuan Video 1.5 upscale model to improve quality.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Hunyuan Video 1.5 latent upscale model used to refine the upscaled samples. | LATENT\_UPSCALE\_MODEL | Yes | N/A |
| `samples` | The latent image representation to be upscaled. | LATENT | Yes | N/A |
| `upscale_method` | The interpolation algorithm used for the initial upscaling step (default: `"bilinear"`). | COMBO | Yes | `"nearest-exact"`<br />`"bilinear"`<br />`"area"`<br />`"bicubic"`<br />`"bislerp"` |
| `width` | The target width for the upscaled latent, in pixels. A value of 0 will calculate the width automatically based on the target height and the original aspect ratio. The final output width will be a multiple of 16 (default: 1280). | INT | Yes | 0 to 16384 (step: 8) |
| `height` | The target height for the upscaled latent, in pixels. A value of 0 will calculate the height automatically based on the target width and the original aspect ratio. The final output height will be a multiple of 16 (default: 720). | INT | Yes | 0 to 16384 (step: 8) |
| `crop` | Determines how the upscaled latent is cropped to fit the target dimensions. | COMBO | Yes | `"disabled"`<br />`"center"` |

**Note on Dimensions:** If both `width` and `height` are set to 0, the node returns the input `samples` unchanged. If only one dimension is set to 0, the other dimension is calculated to preserve the original aspect ratio. Both values are clamped to a minimum of 64, and the upscale target passed to the interpolation step is `width // 16` by `height // 16`, so the requested dimensions are effectively rounded down to multiples of 16.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | The upscaled and model-refined latent image representation, returned as a float tensor on the CPU. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanVideo15LatentUpscaleWithModel/en.md)

***

**Source fingerprint (SHA-256):** `71af49eefb010aadd30f8699b751ad901b1ee385d6cbeedd3a83995a1a623516`


# InpaintModelConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/InpaintModelConditioning

The InpaintModelConditioning node is designed to facilitate the conditioning process for inpainting models, enabling the integration and manipulation of various conditioning inputs

The InpaintModelConditioning node is designed to facilitate the conditioning process for inpainting models, enabling the integration and manipulation of various conditioning inputs to tailor the inpainting output. It encompasses a broad range of functionalities, from loading specific model checkpoints and applying style or control net models, to encoding and combining conditioning elements, thereby serving as a comprehensive tool for customizing inpainting tasks.

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `positive` | Represents the positive conditioning information or parameters that are to be applied to the inpainting model. This input is crucial for defining the context or constraints under which the inpainting operation should be performed, affecting the final output significantly. | `CONDITIONING` |
| `negative` | Represents the negative conditioning information or parameters that are to be applied to the inpainting model. This input is essential for specifying the conditions or contexts to avoid during the inpainting process, thereby influencing the final output. | `CONDITIONING` |
| `vae` | Specifies the VAE model to be used in the conditioning process. This input is crucial for determining the specific architecture and parameters of the VAE model that will be utilized. | `VAE` |
| `pixels` | Represents the pixel data of the image to be inpainted. This input is essential for providing the visual context necessary for the inpainting task. | `IMAGE` |
| `mask` | Specifies the mask to be applied to the image, indicating the areas to be inpainted. This input is crucial for defining the specific regions within the image that require inpainting. | `MASK` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning information after processing, ready to be applied to the inpainting model. This output is essential for guiding the inpainting process according to the specified positive conditions. | `CONDITIONING` |
| `negative` | The modified negative conditioning information after processing, ready to be applied to the inpainting model. This output is essential for guiding the inpainting process according to the specified negative conditions. | `CONDITIONING` |
| `latent` | The latent representation derived from the conditioning process. This output is crucial for understanding the underlying features and characteristics of the image being inpainted. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/InpaintModelConditioning/en.md)


# LTXVAudioVAEDecode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVAudioVAEDecode

The LTXV Audio VAE Decode node converts a latent representation of audio back into an audio waveform.

The LTXV Audio VAE Decode node converts a latent representation of audio back into an audio waveform. It uses a specialized Audio VAE model to perform this decoding process, producing an audio output with its associated sample rate.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The latent to be decoded. | LATENT | Yes | N/A |
| `audio_vae` | The Audio VAE model used for decoding the latent. | VAE | Yes | N/A |

**Note:** If the provided latent is nested (contains multiple latents), the node automatically uses the last latent in the sequence for decoding.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `Audio` | The decoded audio waveform and its associated sample rate. The waveform is placed on the same device as the input latent, and the sample rate is determined by the Audio VAE model. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVAudioVAEDecode/en.md)

***

**Source fingerprint (SHA-256):** `fc94f3cb78ede86ada374444d613411cc9bb5849e5cdb8a24074babee50719b1`


# LTXVAudioVAEEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVAudioVAEEncode

The LTXV Audio VAE Encode node takes an audio input and compresses it into a smaller, latent representation using a specified Audio VAE model.

The LTXV Audio VAE Encode node takes an audio input and compresses it into a smaller, latent representation using a specified Audio VAE model. This process is essential for generating or manipulating audio within a latent space workflow, as it converts raw audio data into a format that other nodes in the pipeline can understand and process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio to be encoded. | AUDIO | Yes | - |
| `audio_vae` | The Audio VAE model to use for encoding. | VAE | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `Audio Latent` | The compressed latent representation of the input audio. The output includes the latent samples, the sample rate of the VAE model, and a type identifier. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVAudioVAEEncode/en.md)

***

**Source fingerprint (SHA-256):** `68f70e0f8048cd9ba723f52eefc93cc33564eb3e68c0cb9b677964dc99aecb97`


# LTXVConcatAVLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVConcatAVLatent

This node merges a video latent and an audio latent into a single joint audio-video (AV) latent, ready for AV models such as LTXV or MiniMax H3.

This node merges a video latent and an audio latent into a single joint audio-video (AV) latent, ready for AV models such as LTXV or MiniMax H3. If the video input is already an AV latent, its video stream is kept and only the audio stream is replaced with the supplied audio latent.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video_latent` | The latent representation of the video data. When it already contains both video and audio streams, the node keeps its video stream and swaps in the audio from `audio_latent`. | LATENT | Yes | |
| `audio_latent` | The latent representation of the audio data. Its length is adjusted to fit the video stream: longer audio is trimmed, shorter audio is zero-padded. | LATENT | Yes | |

**Note:** The samples from both inputs are combined as a pair of video and audio streams in a nested tensor. If either input contains a `noise_mask`, the output includes a combined one; a missing mask is replaced with an all-ones mask matching the shape of its samples. When shorter audio is padded, the padded region is left unmasked so the model can generate it. The node raises an error if the audio latent cannot be fitted to the video latent, for example when the two latents differ in more than one dimension or when they differ in the batch or channel dimensions.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latent` | A latent containing the video and audio samples packed together as two streams, plus a combined `noise_mask` when at least one input provides one. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVConcatAVLatent/en.md)

***

**Source fingerprint (SHA-256):** `0231f9db2ce73132d8555fbb33f295b68aa68a0c1c54e4a0c5d2e1f67b5611cb`


# LTXVEmptyLatentAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVEmptyLatentAudio

The LTXV Empty Latent Audio node creates a batch of empty (zero-filled) latent audio tensors.

The LTXV Empty Latent Audio node creates a batch of empty (zero-filled) latent audio tensors. It reads the configuration of a connected Audio VAE model to determine the correct latent dimensions, such as the number of channels and frequency bins, and calculates how many audio latents are needed from the frame count and frame rate. The resulting empty latent can be used as a starting point for audio generation or manipulation workflows.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `frames_number` | Number of frames. The default value is 97. | INT | Yes | 1 to 1000 |
| `frame_rate` | Number of frames per second. The default value is 25.0. This input accepts either FLOAT or INT values. | FLOAT | Yes | 1.0 to 1000.0 |
| `batch_size` | The number of latent audio samples in the batch. The default value is 1. | INT | Yes | 1 to 4096 |
| `audio_vae` | The Audio VAE model to get configuration from. Displayed as "Audio VAE". | VAE | Yes | N/A |

**Note:** The `audio_vae` input is mandatory. The node raises an error if it is not provided.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `Latent` | An empty latent audio tensor with the shape (batch\_size, z\_channels, num\_audio\_latents, audio\_freq), where the channel count and frequency bins come from the Audio VAE and the number of audio latents is derived from `frames_number` and `frame_rate`. The output also includes a `type` field set to "audio". | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVEmptyLatentAudio/en.md)

***

**Source fingerprint (SHA-256):** `3ac1bf17ebdba7c3a73bdd795f561b7bee31798d8a1efc11b972db1944f873a4`


# LTXVFreezeLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVFreezeLatent

The LTXV Freeze Latent node sets the noise mask of a latent to zero, which keeps that latent clean and unchanged while sampling runs.

The LTXV Freeze Latent node sets the noise mask of a latent to zero, which keeps that latent clean and unchanged while sampling runs. It works on both video and audio latents, so a latent can be frozen before it is concatenated with others or when it should not be denoised at all.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `latent` | Video or audio latent to freeze. Audio is 4D; video is 5D. | LATENT | Yes | N/A |

### Constraints

* The latent must contain a plain tensor. A concatenated audio-video latent is not accepted; it must be split with the Separate AV Latent node first.
* Only 4D latents (audio) and 5D latents (video) are supported. Any other shape causes an error.
* The generated noise mask is created with zeros using the same device as the input tensor. For video latents the mask has shape (batch, 1, frames, 1, 1); for audio latents it has shape (batch, 1, frames, 1).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latent` | The input latent with an added noise mask of zeros, so it remains clean during sampling. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVFreezeLatent/en.md)

***

**Source fingerprint (SHA-256):** `d5d228687f0a124644323c0448dcce53ed6eb2224d3f44d1756079b2a71539ca`


# LTXVLatentUpsampler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVLatentUpsampler

The LTXVLatentUpsampler node increases the spatial resolution of a video latent representation by a factor of two.

The LTXVLatentUpsampler node increases the spatial resolution of a video latent representation by a factor of two. It uses a dedicated upscale model to process the latent data, which is first un-normalized and then re-normalized using the provided VAE's channel statistics. This node is designed for video workflows within the latent space.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The input latent representation of the video to be upscaled. | LATENT | Yes | |
| `upscale_model` | The loaded model used to perform the 2x upscaling on the latent data. | LATENT\_UPSCALE\_MODEL | Yes | |
| `vae` | The VAE model used to un-normalize the input latents before upscaling and to normalize the output latents afterwards. | VAE | Yes | |

Note: This node is marked as experimental in ComfyUI.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | The upscaled latent representation, with spatial dimensions doubled compared to the input. The output latent has the same batch size, number of channels, and temporal length as the input. The `noise_mask` from the input, if present, is removed from the output. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVLatentUpsampler/en.md)

***

**Source fingerprint (SHA-256):** `7d7f0b733cb3758e9ec985cac30134d719b130b5b86c35bfdd14576a5b4575db`


# LTXVSeparateAVLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVSeparateAVLatent

The LTXVSeparateAVLatent node splits a combined audio-visual latent into two separate latents: one containing the video data and one containing the audio data.

The LTXVSeparateAVLatent node splits a combined audio-visual latent into two separate latents: one containing the video data and one containing the audio data. This works with any audio-visual model, such as LTXV or MiniMax H3. The samples tensor is split along its first dimension, with the first element becoming the video latent and the second element becoming the audio latent; if a noise mask is present, it is split in the same way.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `av_latent` | The combined audio-visual latent representation to be split into video and audio latents. | LATENT | Yes | N/A |

**Note:** The input latent's `samples` tensor is expected to have at least two elements along the first dimension (batch dimension). The first element is used for the video latent, and the second element is used for the audio latent. If a `noise_mask` is present, it is split in the same way.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video_latent` | The latent representation containing the separated video data. | LATENT |
| `audio_latent` | The latent representation containing the separated audio data. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVSeparateAVLatent/en.md)

***

**Source fingerprint (SHA-256):** `22ed38bbc1b5716cee380c35c50455810f79c273f51bbe6a535c9ae33192afe6`


# LatentAdd - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentAdd

The LatentAdd node is designed for the addition of two latent representations.

The LatentAdd node is designed for the addition of two latent representations. It facilitates the combination of features or characteristics encoded in these representations by performing element-wise addition.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples1` | The first set of latent samples to be added. It represents one of the inputs whose features are to be combined with another set of latent samples. | `LATENT` |
| `samples2` | The second set of latent samples to be added. It serves as the other input whose features are combined with the first set of latent samples through element-wise addition. | `LATENT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The result of the element-wise addition of two latent samples, representing a new set of latent samples that combines the features of both inputs. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentAdd/en.md)


# LatentApplyOperation - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentApplyOperation

The LatentApplyOperation node applies a specified latent operation to latent samples.

The LatentApplyOperation node applies a specified latent operation to latent samples. It takes latent data and an operation as inputs, processes the latent samples using the provided operation, and returns the modified latent data. This node allows you to transform or manipulate latent representations in your workflow. This node is currently marked as experimental.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The latent samples to be processed by the operation | LATENT | Yes | - |
| `operation` | The operation to apply to the latent samples | LATENT\_OPERATION | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The modified latent samples after applying the operation | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentApplyOperation/en.md)

***

**Source fingerprint (SHA-256):** `cba55d019793fde8dcc0d4aeb4eb6020b6149f523c6bffc65d73c533aa2e2c6c`


# LatentApplyOperationCFG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentApplyOperationCFG

The LatentApplyOperationCFG node applies a latent operation inside the classifier-free guidance (CFG) step of a model's sampling process.

The LatentApplyOperationCFG node applies a latent operation inside the classifier-free guidance (CFG) step of a model's sampling process. It intercepts the conditioning outputs produced before CFG, applies the connected operation to the latent values, and returns the model with this modified sampling behavior.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to which the CFG operation will be applied | MODEL | Yes | - |
| `operation` | The latent operation to apply during the CFG sampling process | LATENT\_OPERATION | Yes | - |

Note: This node is marked as experimental. The operation is applied to the model's conditioning outputs during the CFG sampling process. When two conditioning outputs are present, the operation is applied to the difference between the first and second output, and the second output is added back to the result. When only one conditioning output is present, the operation is applied directly to it.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with the CFG operation applied to its sampling process | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentApplyOperationCFG/en.md)

***

**Source fingerprint (SHA-256):** `e383684a785878bfa4004c2fac78ae562d8e035fdfe081f8e4ebbb2c50161987`


# LatentBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentBatch

The LatentBatch node is designed to merge two sets of latent samples into a single batch, potentially resizing one set to match the dimensions of the other before concatenation.

The LatentBatch node is designed to merge two sets of latent samples into a single batch, potentially resizing one set to match the dimensions of the other before concatenation. This operation facilitates the combination of different latent representations for further processing or generation tasks.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples1` | The first set of latent samples to be merged. It plays a crucial role in determining the final shape of the merged batch. | `LATENT` |
| `samples2` | The second set of latent samples to be merged. If its dimensions differ from the first set, it is resized to ensure compatibility before merging. | `LATENT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The merged set of latent samples, now combined into a single batch for further processing. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentBatch/en.md)


# LatentBatchSeedBehavior - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentBatchSeedBehavior

The LatentBatchSeedBehavior node is designed to modify the seed behavior of a batch of latent samples.

The LatentBatchSeedBehavior node is designed to modify the seed behavior of a batch of latent samples. It allows for either randomizing or fixing the seed across the batch, thereby influencing the generation process by either introducing variability or maintaining consistency in the generated outputs.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The 'samples' parameter represents the batch of latent samples to be processed. Its modification depends on the seed behavior chosen, affecting the consistency or variability of the generated outputs. | `LATENT` |
| `seed_behavior` | The 'seed\_behavior' parameter dictates whether the seed for the batch of latent samples should be randomized or fixed. This choice significantly impacts the generation process by either introducing variability or ensuring consistency across the batch. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a modified version of the input latent samples, with adjustments made based on the specified seed behavior. It either maintains or alters the batch index to reflect the chosen seed behavior. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentBatchSeedBehavior/en.md)


# LatentComposite - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentComposite

The LatentComposite node is designed to blend or merge two latent representations into a single output.

The LatentComposite node is designed to blend or merge two latent representations into a single output. This process is essential for creating composite images or features by combining the characteristics of the input latents in a controlled manner.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples_to` | The 'samples\_to' latent representation where the 'samples\_from' will be composited onto. It serves as the base for the composite operation. | `LATENT` |
| `samples_from` | The 'samples\_from' latent representation to be composited onto the 'samples\_to'. It contributes its features or characteristics to the final composite output. | `LATENT` |
| `x` | The x-coordinate (horizontal position) where the 'samples\_from' latent will be placed on the 'samples\_to'. It determines the horizontal alignment of the composite. | `INT` |
| `y` | The y-coordinate (vertical position) where the 'samples\_from' latent will be placed on the 'samples\_to'. It determines the vertical alignment of the composite. | `INT` |
| `feather` | A boolean indicating whether the 'samples\_from' latent should be resized to match the 'samples\_to' before compositing. This can affect the scale and proportion of the composite result. | `INT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a composite latent representation, blending the features of both 'samples\_to' and 'samples\_from' latents based on the specified coordinates and resizing option. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentComposite/en.md)


# LatentCompositeMasked - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentCompositeMasked

The LatentCompositeMasked node is designed for blending two latent representations together at specified coordinates, optionally using a mask for more controlled compositing.

The LatentCompositeMasked node is designed for blending two latent representations together at specified coordinates, optionally using a mask for more controlled compositing. This node enables the creation of complex latent images by overlaying parts of one image onto another, with the ability to resize the source image for a perfect fit.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `destination` | The latent representation onto which another latent representation will be composited. Acts as the base layer for the composite operation. | `LATENT` |
| `source` | The latent representation to be composited onto the destination. This source layer can be resized and positioned according to the specified parameters. | `LATENT` |
| `x` | The x-coordinate in the destination latent representation where the source will be placed. Allows for precise positioning of the source layer. | `INT` |
| `y` | The y-coordinate in the destination latent representation where the source will be placed, enabling accurate overlay positioning. | `INT` |
| `resize_source` | A boolean flag indicating whether the source latent representation should be resized to match the destination's dimensions before compositing. | `BOOLEAN` |
| `mask` | An optional mask that can be used to control the blending of the source onto the destination. The mask defines which parts of the source will be visible in the final composite. | `MASK` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The resulting latent representation after compositing the source onto the destination, potentially using a mask for selective blending. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentCompositeMasked/en.md)


# LatentConcat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentConcat

The LatentConcat node combines two latent samples by joining them together along a chosen dimension.

The LatentConcat node combines two latent samples by joining them together along a chosen dimension. It takes two latent inputs and concatenates them along the x, y, or t axis, with the option to control which sample comes first. The node automatically adjusts the batch size of the second input to match the first before performing the concatenation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples1` | The first latent sample to concatenate | LATENT | Yes | - |
| `samples2` | The second latent sample to concatenate | LATENT | Yes | - |
| `dim` | The dimension along which to concatenate the latent samples. Positive values (x, y, t) place samples1 before samples2 in the result. Negative values (-x, -y, -t) place samples2 before samples1. The dimension mapping is: x = width, y = height, t = time/frames | COMBO | Yes | `"x"`<br />`"-x"`<br />`"y"`<br />`"-y"`<br />`"t"`<br />`"-t"` |

**Note:** The second latent sample (`samples2`) is automatically repeated as needed to match the batch size of the first latent sample (`samples1`) before concatenation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The concatenated latent samples resulting from combining the two input samples along the specified dimension | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentConcat/en.md)

***

**Source fingerprint (SHA-256):** `dfe27f76ad12e16623d62c9e7f0b2772df6ecadb543a4eee430bc38ab04a12f2`


# LatentCrop - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentCrop

The LatentCrop node is designed to perform cropping operations on latent representations of images.

The LatentCrop node is designed to perform cropping operations on latent representations of images. It allows for the specification of the crop dimensions and position, enabling targeted modifications of the latent space.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The 'samples' parameter represents the latent representations to be cropped. It is crucial for defining the data on which the cropping operation will be performed. | `LATENT` |
| `width` | Specifies the width of the crop area. It directly influences the dimensions of the output latent representation. | `INT` |
| `height` | Specifies the height of the crop area, affecting the size of the resulting cropped latent representation. | `INT` |
| `x` | Determines the starting x-coordinate of the crop area, influencing the position of the crop within the original latent representation. | `INT` |
| `y` | Determines the starting y-coordinate of the crop area, setting the position of the crop within the original latent representation. | `INT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a modified latent representation with the specified crop applied. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentCrop/en.md)


# LatentCut - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentCut

The LatentCut node extracts a specific section from latent samples along a chosen dimension.

The LatentCut node extracts a specific section from latent samples along a chosen dimension. It cuts out a portion of the latent representation by specifying the dimension (x, y, or t), the starting position, and how much to extract. The node supports both positive and negative indexing and automatically adjusts the extraction amount so it stays within the available bounds.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The input latent samples to extract from | LATENT | Yes | - |
| `dim` | The dimension along which to cut the latent samples. "x" cuts along the last axis (typically width), "y" along the second-to-last axis (typically height), and "t" along the third-to-last axis (typically frames in video latents) | COMBO | Yes | "x"<br />"y"<br />"t" |
| `index` | The starting position for the cut (default: 0). Positive values count from the start, negative values count from the end. The node clamps the index to stay within the valid range of the latent samples | INT | Yes | -16384 to 16384 |
| `amount` | The number of elements to extract along the specified dimension (default: 1). Must be at least 1. The node automatically reduces this value if it would exceed the available data beyond the starting index | INT | Yes | 1 to 16384 |

Note: The `index` and `amount` values are adjusted to fit the actual size of the latent along the selected dimension. If `index` is larger than the dimension size, it is clamped to the last valid position. If `index` is negative, it is clamped to the dimension size in absolute terms, and `amount` is limited so it does not go past the end of the data.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The extracted portion of the latent samples | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentCut/en.md)

***

**Source fingerprint (SHA-256):** `7682de2644a4b85dba0571406f9f9802eca7caab09dc2ccf1ac91dc13b41bcdf`


# LatentCutToBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentCutToBatch

The LatentCutToBatch node splits a latent representation along a chosen dimension (time, width, or height) into slices of a specified size and stacks those slices into a new batch.

The LatentCutToBatch node splits a latent representation along a chosen dimension (time, width, or height) into slices of a specified size and stacks those slices into a new batch. Each slice becomes a separate item in the batch, so different parts of a latent sample can be processed independently.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The latent representation to be split and batched. | LATENT | Yes | - |
| `dim` | The dimension along which to cut the latent samples. `"t"` refers to the temporal (frame) dimension, `"x"` to the width, and `"y"` to the height. | COMBO | Yes | `"t"`<br />`"x"`<br />`"y"` |
| `slice_size` | The size of each slice to cut from the specified dimension. If the dimension's size is not perfectly divisible by this value, the remainder is discarded. (default: 1) | INT | Yes | 1 to 16384 (max resolution) |

Note: The `"t"` option only takes effect when the latent includes a temporal dimension. If the chosen dimension maps to the batch or channel position, or does not exist (for example, selecting `"t"` on a latent without frames), the node returns the input unchanged. If `slice_size` is larger than the size of the chosen dimension, the entire dimension is used as a single slice. When the dimension size is not evenly divisible by `slice_size`, the leftover portion at the end is discarded. The output batch size is the input batch size multiplied by the number of slices, and the sliced dimension itself is reduced to `slice_size`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | The resulting latent batch, containing the sliced and stacked samples. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentCutToBatch/en.md)

***

**Source fingerprint (SHA-256):** `873c9bc8391971887f1ab636c086cab86f5504a9c653bc80b54120ee53980bdf`


# LatentFlip - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentFlip

The LatentFlip node is designed to manipulate latent representations by flipping them either vertically or horizontally.

The LatentFlip node is designed to manipulate latent representations by flipping them either vertically or horizontally. This operation allows for the transformation of the latent space, potentially uncovering new variations or perspectives within the data.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The 'samples' parameter represents the latent representations to be flipped. The flipping operation alters these representations, either vertically or horizontally, depending on the 'flip\_method' parameter, thus transforming the data in the latent space. | `LATENT` |
| `flip_method` | The 'flip\_method' parameter specifies the axis along which the latent samples will be flipped. It can be either 'x-axis: vertically' or 'y-axis: horizontally', determining the direction of the flip and thus the nature of the transformation applied to the latent representations. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a modified version of the input latent representations, having been flipped according to the specified method. This transformation can introduce new variations within the latent space. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentFlip/en.md)


# LatentFromBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentFromBatch

This node is designed to extract a specific subset of latent samples from a given batch based on the specified batch index and length.

This node is designed to extract a specific subset of latent samples from a given batch based on the specified batch index and length. It allows for selective processing of latent samples, facilitating operations on smaller segments of the batch for efficiency or targeted manipulation.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The collection of latent samples from which a subset will be extracted. This parameter is crucial for determining the source batch of samples to be processed. | `LATENT` |
| `batch_index` | Specifies the starting index within the batch from which the subset of samples will begin. This parameter enables targeted extraction of samples from specific positions in the batch. | `INT` |
| `length` | Defines the number of samples to be extracted from the specified starting index. This parameter controls the size of the subset to be processed, allowing for flexible manipulation of batch segments. | `INT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The extracted subset of latent samples, now available for further processing or analysis. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentFromBatch/en.md)


# LatentInterpolate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentInterpolate

The LatentInterpolate node is designed to perform interpolation between two sets of latent samples based on a specified ratio, blending the characteristics of both sets to produce

The LatentInterpolate node is designed to perform interpolation between two sets of latent samples based on a specified ratio, blending the characteristics of both sets to produce a new, intermediate set of latent samples.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples1` | The first set of latent samples to be interpolated. It serves as the starting point for the interpolation process. | `LATENT` |
| `samples2` | The second set of latent samples to be interpolated. It serves as the endpoint for the interpolation process. | `LATENT` |
| `ratio` | A floating-point value that determines the weight of each set of samples in the interpolated output. A ratio of 0 produces a copy of the first set, while a ratio of 1 produces a copy of the second set. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a new set of latent samples that represent an interpolated state between the two input sets, based on the specified ratio. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentInterpolate/en.md)


# LatentMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentMultiply

The LatentMultiply node is designed to scale the latent representation of samples by a specified multiplier.

The LatentMultiply node is designed to scale the latent representation of samples by a specified multiplier. This operation allows for the adjustment of the intensity or magnitude of features within the latent space, enabling fine-tuning of generated content or the exploration of variations within a given latent direction.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The 'samples' parameter represents the latent representations to be scaled. It is crucial for defining the input data on which the multiplication operation will be performed. | `LATENT` |
| `multiplier` | The 'multiplier' parameter specifies the scaling factor to be applied to the latent samples. It plays a key role in adjusting the magnitude of the latent features, allowing for nuanced control over the generated output. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a modified version of the input latent samples, scaled by the specified multiplier. This allows for the exploration of variations within the latent space by adjusting the intensity of its features. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentMultiply/en.md)


# LatentOperationSharpen - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentOperationSharpen

The LatentOperationSharpen node creates a sharpening operation for latent representations using a Gaussian-based kernel.

The LatentOperationSharpen node creates a sharpening operation for latent representations using a Gaussian-based kernel. It normalizes the latent data, applies a custom sharpening kernel through convolution, and then restores the original luminance, which enhances details and edges in the latent space representation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `sharpen_radius` | The radius of the sharpening kernel, which controls the size of the area used for sharpening (default: 9) | INT | Yes | 1-31 |
| `sigma` | The standard deviation of the Gaussian kernel used to build the sharpening kernel (default: 1.0) | FLOAT | Yes | 0.1-10.0 |
| `alpha` | The sharpening intensity factor; higher values produce a stronger sharpening effect (default: 0.1) | FLOAT | Yes | 0.0-5.0 |

All three inputs are advanced parameters and have default values, so the node can be used without changing them. This node is marked as experimental.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `operation` | Returns a sharpening operation that can be applied to latent data | LATENT\_OPERATION |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentOperationSharpen/en.md)

***

**Source fingerprint (SHA-256):** `8f49b7e47d35547a7169e9ec209328adbe084ee861ac26b9f26e4e644ac14d6d`


# LatentOperationTonemapReinhard - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentOperationTonemapReinhard

This node creates a latent operation that applies Reinhard tonemapping to latent vectors.

This node creates a latent operation that applies Reinhard tonemapping to latent vectors. It normalizes each latent vector, measures the overall magnitude distribution (mean and standard deviation), and then compresses extreme magnitudes using the Reinhard curve, with the overall strength controlled by a multiplier. The node is marked as experimental (also searchable as "hdr latent").

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `multiplier` | Controls the intensity of the tonemapping effect (default: 1.0) | FLOAT | Yes | 0.0 to 100.0 (step 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `operation` | Returns a tonemapping operation that can be applied to latent vectors | LATENT\_OPERATION |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentOperationTonemapReinhard/en.md)

***

**Source fingerprint (SHA-256):** `19d58c288967ab27eb1e84e60bc35a6d6c8b4e643168de689132396ae0ee3cbe`


# LatentRotate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentRotate

The LatentRotate node is designed to rotate latent representations of images by specified angles.

The LatentRotate node is designed to rotate latent representations of images by specified angles. It abstracts the complexity of manipulating latent space to achieve rotation effects, enabling users to easily transform images in a generative model's latent space.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The 'samples' parameter represents the latent representations of images to be rotated. It is crucial for determining the starting point of the rotation operation. | `LATENT` |
| `rotation` | The 'rotation' parameter specifies the angle by which the latent images should be rotated. It directly influences the orientation of the resulting images. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a modified version of the input latent representations, rotated by the specified angle. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentRotate/en.md)


# LatentSubtract - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentSubtract

The LatentSubtract node is designed for subtracting one latent representation from another.

The LatentSubtract node is designed for subtracting one latent representation from another. This operation can be used to manipulate or modify the characteristics of generative models' outputs by effectively removing features or attributes represented in one latent space from another.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples1` | The first set of latent samples to be subtracted from. It serves as the base for the subtraction operation. | `LATENT` |
| `samples2` | The second set of latent samples that will be subtracted from the first set. This operation can alter the resulting generative model's output by removing attributes or features. | `LATENT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The result of subtracting the second set of latent samples from the first. This modified latent representation can be used for further generative tasks. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentSubtract/en.md)


# LatentUpscale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentUpscale

The LatentUpscale node is designed for upscaling latent representations of images.

The LatentUpscale node is designed for upscaling latent representations of images. It allows for the adjustment of the output image's dimensions and the method of upscaling, providing flexibility in enhancing the resolution of latent images.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The latent representation of an image to be upscaled. This parameter is crucial for determining the starting point of the upscaling process. | `LATENT` |
| `upscale_method` | Specifies the method used for upscaling the latent image. Different methods can affect the quality and characteristics of the upscaled image. | COMBO\[STRING] |
| `width` | The desired width of the upscaled image. If set to 0, it will be calculated based on the height to maintain the aspect ratio. | `INT` |
| `height` | The desired height of the upscaled image. If set to 0, it will be calculated based on the width to maintain the aspect ratio. | `INT` |
| `crop` | Determines how the upscaled image should be cropped, affecting the final appearance and dimensions of the output. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The upscaled latent representation of the image, ready for further processing or generation. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentUpscale/en.md)


# LatentUpscaleBy - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentUpscaleBy

The LatentUpscaleBy node is designed for upscaling latent representations of images.

The LatentUpscaleBy node is designed for upscaling latent representations of images. It allows for the adjustment of the scale factor and the method of upscaling, providing flexibility in enhancing the resolution of latent samples.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The latent representation of images to be upscaled. This parameter is crucial for determining the input data that will undergo the upscaling process. | `LATENT` |
| `upscale_method` | Specifies the method used for upscaling the latent samples. The choice of method can significantly affect the quality and characteristics of the upscaled output. | COMBO\[STRING] |
| `scale_by` | Determines the factor by which the latent samples are scaled. This parameter directly influences the resolution of the output, allowing for precise control over the upscaling process. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The upscaled latent representation, ready for further processing or generation tasks. This output is essential for enhancing the resolution of generated images or for subsequent model operations. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentUpscaleBy/en.md)


# LoadLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadLatent

The LoadLatent node loads previously saved latent representations from .latent files in the input directory.

The LoadLatent node loads previously saved latent representations from .latent files in the input directory. It reads the latent tensor data from the selected file and applies any necessary scaling adjustments before returning the latent data for use in other nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `latent` | Selects which .latent file to load from the available files in the input directory | COMBO | Yes | All .latent files in the input directory (dynamic list, sorted alphabetically) |

Note: The list of available files is generated dynamically and only includes files ending in .latent that are present in the input directory. If the selected file no longer exists, the node reports it as an invalid latent file.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | Returns the loaded latent representation data from the selected file as a float tensor. If the file does not contain the `latent_format_version_0` marker, the tensor is scaled by 1/0.18215 before being returned; files that contain the marker are returned at their stored scale. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadLatent/en.md)

***

**Source fingerprint (SHA-256):** `0938214361687a3a98e03878b8cbc0240100cbeacc0b157c4a299e59e7728a13`


# NormalizeVideoLatentStart - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/NormalizeVideoLatentStart

This node adjusts the first few frames of a video latent to make them look more like the frames that come after.

This node adjusts the first few frames of a video latent to make them look more like the frames that come after. It calculates the average and variation from a set of reference frames later in the video and applies those same characteristics to the starting frames. This helps reduce differences between the starting frames and the rest of the video, creating a smoother and more consistent transition.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `latent` | The video latent representation to process. | LATENT | Yes | - |
| `start_frame_count` | Number of latent frames to normalize, counted from the start (default: 4). | INT | Yes | 1 to 16384 (max resolution) |
| `reference_frame_count` | Number of latent frames after the start frames to use as reference (default: 5). | INT | Yes | 1 to 16384 (max resolution) |

**Note:** The reference frames are taken starting right after the `start_frame_count` frames. If there are fewer frames available than `reference_frame_count` requests, the node uses however many are available (at most one less than the total frame count of the latent). If the video latent has only 1 frame, no normalization is performed and the original latent is returned unchanged.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latent` | The processed video latent with the starting frames normalized. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/NormalizeVideoLatentStart/en.md)

***

**Source fingerprint (SHA-256):** `383e5a19ee4cd8bdea5983567ddbdc30bb09c373142a1a934cea985f1b9d1b0d`


# PiDConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PiDConditioning

Attaches a latent and a degradesigma value to a CONDITIONING so it can be used for PiD decoding or upscaling.

Attaches a latent and a degrade\_sigma value to a CONDITIONING so it can be used for PiD decoding or upscaling. This lets you control how much the latent is degraded before it is processed.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The conditioning data to attach the latent and degrade sigma to. | CONDITIONING | Yes | - |
| `latent` | The latent (from VAEEncode or a KSampler) to attach to the conditioning. | LATENT | Yes | - |
| `latent_format` | The format of the latent. Flux1 (16-ch) and Flux2 (128-ch) latents are auto-detected from the channel dimension under "flux". For SD3 (16-ch), SDXL (4-ch), or QwenImage (16-ch), select manually (default: "flux"). | COMBO | Yes | `"flux"`<br />`"sd3"`<br />`"sdxl"`<br />`"qwenimage"` |
| `degrade_sigma` | The amount of degradation to apply. 0 means a clean latent. Increase this value to denoise corrupted latent outputs (default: 0.0). | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |

Note: When `latent_format` is set to `"flux"`, the node automatically detects the latent type from the channel dimension: 128 channels are treated as Flux2 latents, while 16 channels are treated as Flux1 latents.

Note: An unsupported `latent_format` value raises an error, but all available options are handled by the node.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The original conditioning data with the latent and the degrade sigma value attached. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PiDConditioning/en.md)

***

**Source fingerprint (SHA-256):** `24f613b33e7872cb35f458aa5794a3cc4d37ceaecd43725039edef75f4a512bc`


# RebatchLatents - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RebatchLatents

The RebatchLatents node is designed to reorganize a batch of latent representations into a new batch configuration, based on a specified batch size.

The RebatchLatents node is designed to reorganize a batch of latent representations into a new batch configuration, based on a specified batch size. It ensures that the latent samples are grouped appropriately, handling variations in dimensions and sizes, to facilitate further processing or model inference.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `latents` | The 'latents' parameter represents the input latent representations to be rebatched. It is crucial for determining the structure and content of the output batch. | `LATENT` |
| `batch_size` | The 'batch\_size' parameter specifies the desired number of samples per batch in the output. It directly influences the grouping and division of the input latents into new batches. | `INT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a reorganized batch of latent representations, adjusted according to the specified batch size. It facilitates further processing or analysis. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RebatchLatents/en.md)


# ReferenceLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReferenceLatent

This node sets the guiding latent for an edit model.

This node sets the guiding latent for an edit model. It takes conditioning data and an optional latent input, then modifies the conditioning to include reference latent information. If the model supports it, you can chain multiple Set Reference Latent nodes to set multiple reference images.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `conditioning` | The conditioning data to be modified with reference latent information | CONDITIONING | Yes | - |
| `latent` | Optional latent data to use as reference for the edit model. If not provided, the conditioning is returned unchanged | LATENT | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The modified conditioning data containing reference latent information | CONDITIONING |

## Notes

* The reference latent is stored as a list of sample tensors, so connecting several Set Reference Latent nodes in sequence appends additional references rather than replacing the previous one.
* When no `latent` is connected, the node passes the incoming `conditioning` through without changes.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReferenceLatent/en.md)

***

**Source fingerprint (SHA-256):** `40b02df8ac436480f478fcfa929cc2e13181954507f4bdcd70aade051a25f7d5`


# ReferenceTimbreAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReferenceTimbreAudio

This node sets the reference audio for the "ace step 1.5" process.

This node sets the reference audio for the "ace step 1.5" process. It takes a conditioning input and optionally a latent representation of audio, then attaches that latent data to the conditioning so later nodes can use it as reference audio timbre latents. This node is marked as experimental.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `conditioning` | The conditioning data to which the reference audio information will be attached. | CONDITIONING | Yes | |
| `latent` | An optional latent representation of the reference audio (default: None). When provided, its samples are appended to the conditioning as reference audio timbre latents. | LATENT | No | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `conditioning` | The modified conditioning data, now containing the reference audio timbre latents if the optional `latent` input was provided. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReferenceTimbreAudio/en.md)

***

**Source fingerprint (SHA-256):** `2ddccb7676fc45a5324ba32dde0cd2f8f24388ceec20c88a475e1aa9d4276be0`


# RepeatLatentBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RepeatLatentBatch

The RepeatLatentBatch node is designed to replicate a given batch of latent representations a specified number of times, potentially including additional data like noise masks and 

The RepeatLatentBatch node is designed to replicate a given batch of latent representations a specified number of times, potentially including additional data like noise masks and batch indices. This functionality is crucial for operations that require multiple instances of the same latent data, such as data augmentation or specific generative tasks.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The 'samples' parameter represents the latent representations to be replicated. It is essential for defining the data that will undergo repetition. | `LATENT` |
| `amount` | The 'amount' parameter specifies the number of times the input samples should be repeated. It directly influences the size of the output batch, thereby affecting the computational load and the diversity of the generated data. | `INT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a modified version of the input latent representations, replicated according to the specified 'amount'. It may include replicated noise masks and adjusted batch indices, if applicable. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RepeatLatentBatch/en.md)


# ReplaceVideoLatentFrames - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReplaceVideoLatentFrames

ReplaceVideoLatentFrames replaces a range of frames in a destination latent video with frames from a source latent video, starting at a specified frame index.

ReplaceVideoLatentFrames replaces a range of frames in a destination latent video with frames from a source latent video, starting at a specified frame index. If no source latent is provided, the destination latent is returned unchanged. The node supports negative indexes and logs a warning when the source frames do not fit within the destination.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `destination` | The destination latent where frames will be replaced. | LATENT | Yes | - |
| `source` | The source latent providing frames to insert into the destination latent. If not provided, the destination latent is returned unchanged. | LATENT | No | - |
| `index` | The starting latent frame index in the destination latent where the source latent frames will be placed. Negative values count from the end (default: 0; step: 1). | INT | Yes | -MAX\_RESOLUTION to MAX\_RESOLUTION |

**Constraints:**

* A negative `index` is adjusted by adding it to the destination frame count, so it counts backward from the end of the destination latent.
* If `index` points beyond the destination frame count, or if the source frames do not fit within the destination starting at `index`, a warning is logged and the destination latent is returned unchanged.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The resulting latent video after the frame replacement operation. If the replacement cannot be performed, the destination latent is returned unchanged. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReplaceVideoLatentFrames/en.md)

***

**Source fingerprint (SHA-256):** `5b98d875bdeaec63521bff19fecbc5510036c8b4f90322d8296b216688b557bf`


# SaveConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveConditioning

This node saves a single conditioning to the output folder as a safetensors file.

This node saves a single conditioning to the output folder as a safetensors file. The saved file can be moved to the models/embeddings folder and loaded later with Load Conditioning, for example to skip the text encoder. The node passes the conditioning through unchanged so it can still be used later in the workflow.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `conditioning` | The conditioning to save. Only a single conditioning entry is supported. | CONDITIONING | Yes | - |
| `filename_prefix` | Prefix used to build the output filename. The file is written to the output folder with a numeric counter appended. Default: `conditioning/ComfyUI` | STRING | Yes | - |

**Notes:**

* If the `conditioning` input contains more than one entry (for example after combining conditionings), the node raises an error: "Save Conditioning supports a single conditioning entry, save it before combining."
* Conditioning options that are tensors, lists/tuples of tensors, booleans, integers, floats, or strings are saved alongside the conditioning. Options that are `None` are skipped. Any other option type raises an error stating the option cannot be saved.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `conditioning` | The same conditioning that was passed in, unchanged. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveConditioning/en.md)

***

**Source fingerprint (SHA-256):** `07b7d2be5262c4782f237138d034b130322507e62ae8775b9c94634df8e7a3fa`


# SaveLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveLatent

SaveLatent saves latent tensors to disk as .latent files so they can be reused or shared later.

SaveLatent saves latent tensors to disk as `.latent` files so they can be reused or shared later. It takes latent samples, writes them to the output folder with an automatically generated name, and can embed workflow metadata such as the prompt inside the saved file. The same latent samples are also passed through unchanged for further processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The latent samples to be saved to disk. | LATENT | Yes | - |
| `filename_prefix` | The prefix used to build the output filename. It can include subfolders, for example "latents/ComfyUI" (default: "latents/ComfyUI"). | STRING | Yes | - |
| `prompt` | The workflow prompt, serialized as JSON and stored in the saved file metadata (hidden parameter, supplied automatically). | PROMPT | No | - |
| `extra_pnginfo` | Additional workflow information, serialized as JSON and stored in the saved file metadata (hidden parameter, supplied automatically). | EXTRA\_PNGINFO | No | - |

Note: Each saved file is named using the prefix and a 5-digit counter, for example `ComfyUI_00001_.latent`, and is placed in the output directory. The file contains the latent tensor and a latent format version marker. Metadata is embedded in the saved file only when metadata support is enabled, that is, when ComfyUI is not started with the `--disable-metadata` option.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | The same latent samples that were provided as input, passed through unchanged. | LATENT |
| `ui` | Interface display data describing the saved file: its filename, subfolder, and output type ("output"). | UI |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveLatent/en.md)

***

**Source fingerprint (SHA-256):** `137d52d589d93d8229940a8572621ab6eeb25a4e13ac05172e9f8609f1af038a`


# SeedVR2Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SeedVR2Conditioning

Builds positive and negative conditioning from a VAE latent for use with the SeedVR2 model.

Builds positive and negative conditioning from a VAE latent for use with the SeedVR2 model. It validates the input latent and model structure, adds a mask channel to the latent, and returns both conditioning outputs.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The SeedVR2 model. | MODEL | Yes | - |
| `vae_conditioning` | The SeedVR2 VAE latent to build conditioning from (display name: latent). | LATENT | Yes | - |

Note: The `vae_conditioning` latent must be a 5-D tensor in Comfy channel-first layout (B, C, T, H, W), where C is the expected SeedVR2 VAE channel count. The node raises an error if the latent is not 5-D, if the channel count does not match, or if the tensor appears to be in channel-last layout. The `model` input must have the expected SeedVR2 structure; the node resolves its inner diffusion model and reads its positive and negative conditioning. Internally, the node appends a constant mask channel to the latent and attaches the resulting condition to both the positive and negative conditioning outputs.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The positive conditioning for sampling. | CONDITIONING |
| `negative` | The negative conditioning for sampling. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SeedVR2Conditioning/en.md)

***

**Source fingerprint (SHA-256):** `28e508bdd776e2e3f5f2f93bfc29a1a1d1c34a11dbdc7f421d197ddbfa85f0f5`


# SeedVR2TemporalChunk - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SeedVR2TemporalChunk

This node splits a SeedVR2 video latent into smaller temporal chunks that can be processed one at a time within available VRAM.

This node splits a SeedVR2 video latent into smaller temporal chunks that can be processed one at a time within available VRAM. It automatically calculates the optimal chunk size based on your GPU memory or lets you specify the chunk size manually, and outputs the chunks in sequence order for processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `latent` | The VAE-encoded SeedVR2 latent to split. Must be a 5-D tensor (B, C, T, H, W) with the expected SeedVR2 latent channel count. | LATENT | Yes | - |
| `temporal_overlap` | Latent frames shared between adjacent chunks and crossfaded at merge; 0 means no overlap (default: 0). The effective overlap is capped at one less than the chunk's latent frame count. | INT | No | 0 to 16384 |
| `chunking_mode` | Manual uses `frames_per_chunk` exactly; auto predicts the largest chunk that fits free VRAM. | COMBO | Yes | `"auto"`<br />`"manual"` |

When `chunking_mode` is set to `"manual"`, an additional parameter becomes available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `frames_per_chunk` | Pixel frames per temporal chunk (4n+1: 1, 5, 9, 13, 17, 21, ...); the UI steps by 4 (default: 21). | INT | Yes | 1 to 16384 |

Note: The `frames_per_chunk` parameter only appears when `chunking_mode` is set to `"manual"`. The value must satisfy the formula `(frames_per_chunk - 1) % 4 == 0`, meaning it must be one of: 1, 5, 9, 13, 17, 21, etc. The input latent must be 5-dimensional and contain the expected SeedVR2 latent channel count; otherwise the node raises an error. If the total pixel frames in the latent are equal to or less than the chosen chunk size (or the auto-computed size), the node returns the original latent as a single chunk with zero overlap.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latents` | The temporal chunks in sequence order. Each chunk is a LATENT with the same batch, channel, height, and width but a reduced temporal dimension. | LATENT |
| `temporal_overlap` | The effective latent-frame overlap between adjacent chunks, for Merge SeedVR2 Latents. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SeedVR2TemporalChunk/en.md)

***

**Source fingerprint (SHA-256):** `40af2b690f74555efbe38f4cf76825417f52735ce90296a9ad662f78cfe4c6bf`


# SeedVR2TemporalMerge - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SeedVR2TemporalMerge

This node recombines sampled SeedVR2 latent temporal chunks into a single full-length latent.

This node recombines sampled SeedVR2 latent temporal chunks into a single full-length latent. When a temporal overlap is specified, it crossfades each overlapping region with a Hann window to create smooth transitions between chunks; when the overlap is 0, it performs plain concatenation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `latents` | The sampled temporal chunks in sequence order. | LATENT | Yes | List of latents |
| `temporal_overlap` | The temporal\_overlap output of Split SeedVR2 Latent. 0 = plain concatenation. (default: 0) | INT | Yes | 0 to 16384 |

**Note:** The `temporal_overlap` value must be greater than or equal to 0. All chunks must be 5-dimensional video latents (B, C, T, H, W) and must match in every dimension except the temporal axis (T); only the final chunk may be shorter than the others. If only one chunk is provided, it is returned unchanged.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latent` | The recombined full-length latent. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SeedVR2TemporalMerge/en.md)

***

**Source fingerprint (SHA-256):** `647653fc651462f62bcc9dca2919cfcaa4b476b4c679b0a1111698facab83f28`


# SetLatentNoiseMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetLatentNoiseMask

This node is designed to apply a noise mask to a set of latent samples.

This node is designed to apply a noise mask to a set of latent samples. It modifies the input samples by integrating a specified mask, thereby altering their noise characteristics.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The latent samples to which the noise mask will be applied. This parameter is crucial for determining the base content that will be modified. | `LATENT` |
| `mask` | The mask to be applied to the latent samples. It defines the areas and intensity of noise alteration within the samples. | `MASK` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The modified latent samples with the applied noise mask. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetLatentNoiseMask/en.md)


# SheetSage2AudioToABC - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SheetSage2AudioToABC

This node transcribes vocal and instrumental melodies from music into ABC notation, a text-based format for writing down musical scores.

This node transcribes vocal and instrumental melodies from music into ABC notation, a text-based format for writing down musical scores. It analyzes the connected audio and returns the resulting notation as text, which can then be fed into the YuE2 Generate Music node using the matching mode.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio_encoder` | The audio encoder model used to analyze the audio and produce the ABC notation. | AUDIO\_ENCODER | Yes | - |
| `audio` | The music audio to transcribe into ABC notation. | AUDIO | Yes | - |
| `mode` | Controls what is transcribed. "full" generates melody and chords; "melody" generates melody only, recommended for covers. | COMBO | Yes | `"melody"`<br />`"full"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `abc` | The transcribed music in ABC notation, returned as a list of strings. Connect this to the YuE2 Generate Music node and use the matching mode. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SheetSage2AudioToABC/en.md)

***

**Source fingerprint (SHA-256):** `612d18dedd09b64210087c340b8f304ace8cd7b30b1a6e8e8ba7c749b355a497`


# StableCascade_EmptyLatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableCascade_EmptyLatentImage

The StableCascadeEmptyLatentImage node creates empty latent tensors for Stable Cascade models.

The StableCascade\_EmptyLatentImage node creates empty latent tensors for Stable Cascade models. It generates two separate latent representations - one for stage C and another for stage B - with dimensions calculated from the input resolution and compression settings. This node provides a starting point for the Stable Cascade generation pipeline.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | The width of the output image in pixels (default: 1024, step: 8) | INT | Yes | 256 to MAX\_RESOLUTION |
| `height` | The height of the output image in pixels (default: 1024, step: 8) | INT | Yes | 256 to MAX\_RESOLUTION |
| `compression` | The compression factor that determines the latent dimensions for stage C (default: 42, step: 1). This is an advanced parameter. | INT | Yes | 4 to 128 |
| `batch_size` | The number of latent samples to generate in a batch (default: 1) | INT | Yes | 1 to 4096 |

Note: The `compression` value controls the stage C latent size: its height and width are the input `height` and `width` divided by `compression`. The stage B latent always uses a fixed compression of 4.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `stage_c` | The stage C latent tensor with dimensions \[batch\_size, 16, height//compression, width//compression] | LATENT |
| `stage_b` | The stage B latent tensor with dimensions \[batch\_size, 4, height//4, width//4] | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableCascade_EmptyLatentImage/en.md)

***

**Source fingerprint (SHA-256):** `f336f87d0ec14b3716efda2cfaa194b1f80707d64821bb56ade7d88d9bd5b53f`


# StableCascade_StageC_VAEEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableCascade_StageC_VAEEncode

The StableCascadeStageCVAEEncode node processes an input image through a VAE encoder to generate latent representations for the Stable Cascade model.

The StableCascade\_StageC\_VAEEncode node processes an input image through a VAE encoder to generate latent representations for the Stable Cascade model. It first resizes the image based on a compression factor and the VAE's downscale ratio, then encodes the resized image. The node outputs two latent tensors: one for stage C (the actual encoded result) and one for stage B (a zero-filled placeholder).

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be encoded into latent space | IMAGE | Yes | - |
| `vae` | The VAE model used for encoding the image | VAE | Yes | - |
| `compression` | The compression factor applied to the image before encoding. The image dimensions are divided by this value, then multiplied by the VAE's downscale ratio. This is an advanced parameter. (default: 42) | INT | Yes | 4-128 (step: 1) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `stage_c` | The encoded latent representation for stage C of the Stable Cascade model | LATENT |
| `stage_b` | A placeholder latent representation for stage B. Currently returns a zero-filled tensor with dimensions calculated from the input image size. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableCascade_StageC_VAEEncode/en.md)

***

**Source fingerprint (SHA-256):** `1679aaac77057fcc359e5428906d5227f6c2dde721aabbfb5a32c08738ac376c`


# StyleModelApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StyleModelApply

This node applies a style model to a given conditioning, enhancing or altering its style based on the output of a CLIP vision model.

This node applies a style model to a given conditioning, enhancing or altering its style based on the output of a CLIP vision model. It integrates the style model's conditioning into the existing conditioning, allowing for a seamless blend of styles in the generation process.

## Inputs

### Required

| Parameter | Description | Comfy dtype |
| - | - | - |
| `conditioning` | The original conditioning data to which the style model's conditioning will be applied. It's crucial for defining the base context or style that will be enhanced or altered. | `CONDITIONING` |
| `style_model` | The style model used to generate new conditioning based on the CLIP vision model's output. It plays a key role in defining the new style to be applied. | `STYLE_MODEL` |
| `clip_vision_output` | The output from a CLIP vision model, which is used by the style model to generate new conditioning. It provides the visual context necessary for style application. | `CLIP_VISION_OUTPUT` |

## Outputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `conditioning` | The enhanced or altered conditioning, incorporating the style model's output. It represents the final, styled conditioning ready for further processing or generation. | `CONDITIONING` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StyleModelApply/en.md)


# T5TokenizerOptions - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/T5TokenizerOptions

Documentation for T5TokenizerOptions node.

## Overview

The T5TokenizerOptions node configures tokenizer settings for various T5 model types. It sets minimum padding and minimum length parameters for multiple T5 model variants including t5xxl, pile\_t5xl, t5base, mt5xl, and umt5xxl. The node takes a CLIP input, applies the settings to a copy of it, and returns the modified CLIP.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model to configure tokenizer options for | CLIP | Yes | - |
| `min_padding` | Minimum padding value to set for all T5 model types (default: 0) | INT | Yes | 0 to 10000 |
| `min_length` | Minimum length value to set for all T5 model types (default: 0) | INT | Yes | 0 to 10000 |

Note: This node is marked as experimental in ComfyUI. The settings are applied to all supported T5 variants at once: t5xxl, pile\_t5xl, t5base, mt5xl, and umt5xxl. The input `clip` is cloned before modification, so the original CLIP is not altered.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The modified CLIP model with updated tokenizer options applied to all T5 variants | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/T5TokenizerOptions/en.md)

***

**Source fingerprint (SHA-256):** `1c9a67781ddcc423fa3f6ed8ae1cb767a18681366aca9f1a4a6aff6b2eb38667`


# TextEncodeZImageOmni - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeZImageOmni

TextEncodeZImageOmni encodes a text prompt together with up to three optional reference images into a conditioning format for image generation models.

TextEncodeZImageOmni encodes a text prompt together with up to three optional reference images into a conditioning format for image generation models. The prompt is tokenized and encoded with the CLIP model, and each connected image can optionally be processed by a vision encoder and/or a VAE so that visual references are embedded alongside the text. This node is marked as experimental.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for tokenizing and encoding the text prompt. | CLIP | Yes | |
| `image_encoder` | An optional vision encoder model. If provided, it is used to encode the input images, and the resulting embeddings are added to the conditioning. | CLIP\_VISION | No | |
| `prompt` | The text prompt to be encoded. Supports multiline input and dynamic prompts. | STRING | Yes | |
| `auto_resize_images` | When enabled (default: True), input images are automatically resized before VAE encoding so their total pixel area is close to 1024x1024, with dimensions rounded to multiples of 8. | BOOLEAN | Yes | True<br />False |
| `vae` | An optional VAE model. If provided, it is used to encode the input images into latent representations, which are added to the conditioning as reference latents. | VAE | No | |
| `image1` | The first optional reference image. | IMAGE | No | |
| `image2` | The second optional reference image. | IMAGE | No | |
| `image3` | The third optional reference image. | IMAGE | No | |

**Note:** The node accepts a maximum of three images (`image1`, `image2`, `image3`). The `image_encoder` and `vae` inputs are only used when at least one image is provided; when both are connected, each image is processed by both. When `auto_resize_images` is True and a `vae` is connected, images are resized to have a total pixel area close to 1024x1024 before encoding. If no images are provided, only the text prompt is encoded.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The final conditioning output. It contains the encoded text prompt and, when images are provided, may include encoded image embeddings, reference latents, and extra text embeddings derived from the image placeholder template. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeZImageOmni/en.md)

***

**Source fingerprint (SHA-256):** `b40a3150f536b6f37e2b53e6d9992fcb4fd32dceb540c0a76773a7ba1af9a7b8`


# TrimVideoLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TrimVideoLatent

The TrimVideoLatent node removes frames from the beginning of a video latent representation.

The TrimVideoLatent node removes frames from the beginning of a video latent representation. It takes a latent video sample and trims off a specified number of frames from the start, returning the remaining portion of the video. This allows you to shorten video sequences by removing the initial frames.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The input latent video representation containing the video frames to be trimmed | LATENT | Yes | - |
| `trim_amount` | The number of frames to remove from the beginning of the video (default: 0) | INT | Yes | 0 to 99999 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The trimmed latent video representation with the specified number of frames removed from the beginning | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TrimVideoLatent/en.md)

***

**Source fingerprint (SHA-256):** `33b7a899f2002e9a7008f2ca93de853c08dd0629a4c6867fb42aae4ec2eb864b`


# TripoSplatSamplingPreview - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoSplatSamplingPreview

This node patches a TripoSplat model so that when used with the standard KSampler node, a live preview of the decoded gaussian splat is shown at each sampling step.

This node patches a TripoSplat model so that when used with the standard KSampler node, a live preview of the decoded gaussian splat is shown at each sampling step. It works by wrapping the sampler's callback to decode the model's output into a preview image after every step.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The TripoSplat model to patch for live preview (provides the conditioning token length used to estimate memory needs) | MODEL | Yes | |
| `vae` | TripoSplat VAE decoder | VAE | Yes | |
| `octree_level` | Octree depth for the preview decode (lower = cheaper/coarser). Default: 5 | INT | No | 2 to 8 |
| `num_gaussians` | Number of gaussians to produce for the preview (rounded to a multiple of 32). Default: 16384 | INT | No | 1024 to 262144 (step: 32) |
| `yaw` | Preview camera yaw in degrees. Default: 90.0 | FLOAT | No | -360.0 to 360.0 (step: 1.0) |
| `pitch` | Preview camera pitch in degrees. Default: 15.0 | FLOAT | No | -89.0 to 89.0 (step: 1.0) |
| `point_size` | Maximum splat radius in pixels. Each gaussian is sized from its scale and capped here; lower = finer/pointier, higher = chunkier. Default: 3 | INT | No | 1 to 16 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The patched TripoSplat model with live preview functionality added | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoSplatSamplingPreview/en.md)

***

**Source fingerprint (SHA-256):** `78678b65df325da964cfd3e8cd0dc07fa25b92d26bb2057117db413a205e9535`


# VAEDecode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecode

The VAEDecode node is designed for decoding latent representations into images using a specified Variational Autoencoder (VAE).

The VAEDecode node is designed for decoding latent representations into images using a specified Variational Autoencoder (VAE). It serves the purpose of generating images from compressed data representations, facilitating the reconstruction of images from their latent space encodings.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `samples` | The 'samples' parameter represents the latent representations to be decoded into images. It is crucial for the decoding process as it provides the compressed data from which the images are reconstructed. | `LATENT` |
| `vae` | The 'vae' parameter specifies the Variational Autoencoder model to be used for decoding the latent representations into images. It is essential for determining the decoding mechanism and the quality of the reconstructed images. | VAE |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `image` | The output is an image reconstructed from the provided latent representation using the specified VAE model. | `IMAGE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEDecode/en.md)


# VAEDecodeAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecodeAudio

This node converts an audio latent representation back into a playable audio waveform using a Variational Autoencoder (VAE).

This node converts an audio latent representation back into a playable audio waveform using a Variational Autoencoder (VAE). It takes the encoded samples, decodes them through the selected VAE, and then normalizes the resulting waveform so the overall volume level stays consistent. The output audio uses the VAE's audio sample rate (44100 Hz by default), or the sample rate stored in the input samples when one is present.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The encoded audio samples in latent space that will be decoded back into an audio waveform. If the samples carry their own sample rate, that value is used for the output. | LATENT | Yes | - |
| `vae` | The Variational Autoencoder model used to decode the latent samples into audio. Its audio output sample rate (default 44100 Hz) determines the resulting waveform's sample rate when the input samples do not specify one. | VAE | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `AUDIO` | The decoded audio waveform with normalized volume, returned together with its sample rate (the sample rate from the input `samples` if present, otherwise the VAE's audio sample rate, default 44100 Hz). | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEDecodeAudio/en.md)

***

**Source fingerprint (SHA-256):** `2a3f5c912d1d84eea7768979f6b8f0eaa9fe89041f3a3352434f38abd3c09fea`


# VAEDecodeAudioTiled - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecodeAudioTiled

This node converts a compressed audio representation (latent samples) back into an audio waveform using a Variational Autoencoder (VAE).

This node converts a compressed audio representation (latent samples) back into an audio waveform using a Variational Autoencoder (VAE). It processes the data in smaller, overlapping sections (tiles) to manage memory usage, making it suitable for handling longer audio sequences. The decoded audio is also normalized to keep its volume level consistent.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The compressed latent representation of the audio to be decoded. | LATENT | Yes | N/A |
| `vae` | The Variational Autoencoder model used to perform the decoding. | VAE | Yes | N/A |
| `tile_size` | The size of each processing tile. The audio is decoded in sections of this length to conserve memory (default: 512). Must be a multiple of 8. | INT | Yes | 32 to 8192 (step 8) |
| `overlap` | The number of samples that adjacent tiles overlap. This helps to reduce artifacts at the boundaries between tiles (default: 64). Must be a multiple of 8. | INT | Yes | 0 to 1024 (step 8) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The decoded audio waveform, including its sample rate information. | AUDIO |

The output sample rate is taken from the input `samples` when it contains one; otherwise, it is read from the VAE model (defaulting to 44100 Hz).

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEDecodeAudioTiled/en.md)

***

**Source fingerprint (SHA-256):** `5ddedf218ba27ab9f463646c1e5288091172f2d7fae8f2980bb2b5e4d3dca89c`


# VAEDecodeHunyuan3D - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecodeHunyuan3D

The VAEDecodeHunyuan3D node converts latent representations into 3D voxel data using a VAE decoder.

The VAEDecodeHunyuan3D node converts latent representations into 3D voxel data using a VAE decoder. It processes the latent samples through the VAE model with configurable chunking and resolution settings to generate volumetric data suitable for 3D applications.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The latent representation to be decoded into 3D voxel data | LATENT | Yes | - |
| `vae` | The VAE model used for decoding the latent samples | VAE | Yes | - |
| `num_chunks` | The number of chunks to split the processing into for memory management. Advanced parameter (default: 8000) | INT | Yes | 1000-500000 |
| `octree_resolution` | The resolution of the octree structure used for 3D voxel generation. Advanced parameter (default: 256) | INT | Yes | 16-512 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `voxels` | The generated 3D voxel data from the decoded latent representation | VOXEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEDecodeHunyuan3D/en.md)

***

**Source fingerprint (SHA-256):** `740e328e9e7817aa1a029c5fadddf5457c91bbb5ac12c7e8af2cd81bee6184a7`


# VAEDecodeTiled - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecodeTiled

The VAEDecodeTiled node decodes latent representations into images using a tiled approach to handle large images efficiently.

The VAEDecodeTiled node decodes latent representations into images using a tiled approach to handle large images efficiently. It processes the input in smaller tiles to manage memory usage while maintaining image quality. The node also supports video VAEs by processing temporal frames in chunks with overlap for smooth transitions.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The latent representation to be decoded into images | LATENT | Yes | - |
| `vae` | The VAE model used for decoding the latent samples | VAE | Yes | - |
| `tile_size` | The size of each tile for processing (default: 512) | INT | Yes | 64-4096 (step: 32) |
| `overlap` | The amount of overlap between adjacent tiles (default: 64) | INT | Yes | 0-4096 (step: 32) |
| `temporal_size` | Only used for video VAEs: Amount of frames to decode at a time (default: 64) | INT | Yes | 8-4096 (step: 4) |
| `temporal_overlap` | Only used for video VAEs: Amount of frames to overlap (default: 8) | INT | Yes | 4-4096 (step: 4) |

**Note:** The `tile_size`, `overlap`, `temporal_size`, and `temporal_overlap` inputs are marked as advanced settings.

**Note:** The node automatically adjusts overlap values if they exceed practical limits. If `tile_size` is less than 4 times the `overlap`, the overlap is reduced to one quarter of the tile size. Similarly, if `temporal_size` is less than twice the `temporal_overlap`, the temporal overlap is halved. The node also accounts for the VAE's internal compression ratios when calculating tile and overlap sizes for both spatial and temporal dimensions. If the input latent is a nested batch of latents, only the first item in the batch is decoded.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The decoded image or images generated from the latent representation. When decoding video latents, the output is a sequence of image frames. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEDecodeTiled/en.md)

***

**Source fingerprint (SHA-256):** `04136ba1abd0c74e780dc405f916a08b809630ae4f41c183049535488b40fd96`


# VAEDecodeTripoSplat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecodeTripoSplat

Decode a TripoSplat latent representation into a 3D gaussian splat.

Decode a TripoSplat latent representation into a 3D gaussian splat. This node takes the sampled latent from a TripoSplat model and reconstructs it as a set of 3D gaussians, which can be adjusted in density by modifying the number of gaussians produced.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The latent samples to decode. If the samples contain a nested camera stream alongside the latent, only the latent stream is decoded. | LATENT | Yes | - |
| `vae` | TripoSplat VAE decoder | VAE | Yes | - |
| `num_gaussians` | Number of gaussians to produce (rounded to a multiple of 32). 262144 matches the octree's point density; higher oversamples the same points (denser, but no new detail) and costs proportionally more VRAM/time. Default: 262144 | INT | Yes | 32 to 1048576 (step: 32) |
| `seed` | Seeds the octree point sampler (global RNG) for deterministic decodes. Default: 0 | INT | Yes | 0 to 18446744073709551615 |

**Note:** The `num_gaussians` value is automatically clamped to the allowed range and rounded to a multiple of the VAE decoder's gaussians-per-point setting. The actual number used may differ slightly from the input value.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `splat` | The decoded 3D gaussian splat containing positions, scales, rotations, opacities, and spherical harmonics coefficients | SPLAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEDecodeTripoSplat/en.md)

***

**Source fingerprint (SHA-256):** `5c2b21cee31c68a6440ab4c7156e0d5c041ce7264f6467a508dc41e2eb0dc598`


# VOIDWarpedNoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VOIDWarpedNoise

Generates temporally-correlated noise for the second pass of the VOID video refinement process.

Generates temporally-correlated noise for the second pass of the VOID video refinement process. It takes the Pass 1 output video and warps Gaussian noise along optical flow vectors, so the noise moves consistently with the video content. The resulting warped noise is used as the starting latent for Pass 2, which improves temporal consistency in the final output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `optical_flow` | Optical flow model from OpticalFlowLoader (RAFT-large). | OPTICAL\_FLOW | Yes | - |
| `video` | Pass 1 output video frames \[T, H, W, 3]. | IMAGE | Yes | - |
| `width` | Target width in pixels (default: 672). The input video is scaled to this width before the noise is generated, and the latent width is derived as width ÷ 8. | INT | Yes | 16 to MAX\_RESOLUTION (step 8) |
| `height` | Target height in pixels (default: 384). The input video is scaled to this height before the noise is generated, and the latent height is derived as height ÷ 8. | INT | Yes | 16 to MAX\_RESOLUTION (step 8) |
| `length` | Number of pixel frames. Rounded down to make latent\_t even (patch\_size\_t=2 requirement), e.g. 49 to 45 (default: 45). | INT | Yes | 1 to MAX\_RESOLUTION (step 1) |
| `batch_size` | Number of identical warped noise sequences to produce (default: 1). The generated noise is repeated this many times along the batch dimension. | INT | Yes | 1 to 64 |

**Note on the `length` parameter:** The `length` value is automatically rounded down to the nearest value that produces an even `latent_t` dimension, as required by the CogVideoX-Fun-V1.5 model's `patch_size_t=2` constraint (for example, 49 becomes 45). The node logs a warning when this rounding occurs. Frames beyond the adjusted `length` are ignored, and the noise is resampled to the resulting latent frame count.

**Note on `width` and `height`:** These values are used both to resize the incoming video frames (bilinear, center crop) and to determine the final latent resolution (divided by 8). If the generated noise does not match the requested latent size, it is resized to fit.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `warped_noise` | A 5D tensor (B, C, T, H, W) containing optical-flow warped Gaussian noise, ready for use as the initial latent in VOID Pass 2. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VOIDWarpedNoise/en.md)

***

**Source fingerprint (SHA-256):** `f46b0a73b09a5d2d0bc25676f9571563c6bb8bad8d835e7564ac092c72136107`


# VOIDWarpedNoiseSource - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VOIDWarpedNoiseSource

This node converts a LATENT (such as the output from the VOIDWarpedNoise node) into a NOISE source.

This node converts a LATENT (such as the output from the VOIDWarpedNoise node) into a NOISE source. This lets you feed pre-computed warped noise into nodes that expect a noise source, such as SamplerCustomAdvanced.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `warped_noise` | Warped noise latent from VOIDWarpedNoise | LATENT | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `NOISE` | A noise source wrapping the supplied latent, usable with SamplerCustomAdvanced | NOISE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VOIDWarpedNoiseSource/en.md)

***

**Source fingerprint (SHA-256):** `61d7c82cb8a2acba28f980c4c42c6d4be12788b27676a5d30885799cf9c36185`


# VaeDecodeShapeTrellis - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VaeDecodeShapeTrellis

This node decodes Trellis2 shape latent representations into a 3D mesh.

This node decodes Trellis2 shape latent representations into a 3D mesh. It uses a VAE to convert sparse shape latent data into mesh geometry and also outputs shape subdivision data generated during decoding. The node supports both single and batched latent inputs and automatically adjusts the mesh orientation to the expected coordinate frame.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The latent samples to decode, including the sample tensor and sparse coordinate data. The latent dictionary may also contain optional fields: `coord_counts` for batched shapes, `coord_resolution` to control mesh resolution, and `model_frame` for coordinate orientation. | LATENT | Yes | None |
| `vae` | The VAE model used to decode the shape latent into a mesh. | VAE | Yes | None |

### Notes on `samples`

* The `samples` input is a latent dictionary that must contain the `samples` tensor and the `coords` sparse coordinates.
* If `coord_counts` is present, it must be a 1D tensor of non-negative integers, and the sum of all counts must equal the total number of coordinate rows. Each count represents one shape in the batch.
* If `coord_resolution` is provided, the mesh resolution is calculated as `coord_resolution * 16`. Otherwise, the VAE's built-in resolution buffer is used (default value: 1024).
* If `model_frame` is set to `"z_up"`, the decoded mesh vertices are rotated from a Z-up coordinate system to the Y-up convention used by glTF. The default value is `"y_up"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `mesh` | The decoded 3D mesh, containing vertex positions and face indices. When decoding multiple shapes, the meshes are returned as a single stacked tensor if they all share the same shape, or as a packed variable-size batch otherwise. | MESH |
| `shape_subdivides` | Shape subdivision data produced at each stage of the decoding process. | SHAPE\_SUBDIVIDES |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VaeDecodeShapeTrellis/en.md)

***

**Source fingerprint (SHA-256):** `28bd0f69c0ea58ca499f6523471cf6071c041c21242126715d56f362484377a2`


# VaeDecodeStructureTrellis2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VaeDecodeStructureTrellis2

This node converts Trellis structure latent samples into a 3D voxel grid using a VAE's structure decoder.

This node converts Trellis structure latent samples into a 3D voxel grid using a VAE's structure decoder. It reads only the first 8 channels of the latent, reconstructs the voxel occupancy, and adjusts the output resolution to either 32 or 64 as requested.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The latent representation of the structure to decode. Only the first 8 channels of the latent are used for decoding. | LATENT | Yes | - |
| `vae` | The VAE whose structure decoder converts the latent into a voxel grid. Decoding is performed in batches. | VAE | Yes | - |
| `resolution` | The target spatial resolution of the output voxel grid (default: "32"). If the decoded grid has a different resolution, it is downsampled to match. | COMBO | Yes | "32"<br />"64" |

Note: When the decoded voxel grid resolution differs from the selected `resolution`, the grid is downsampled using 3D max pooling to the requested size.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `voxel` | A binary voxel occupancy grid as a float tensor with shape \[batch, depth, height, width]. Values are 1.0 for occupied voxels and 0.0 for empty voxels. | VOXEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VaeDecodeStructureTrellis2/en.md)

***

**Source fingerprint (SHA-256):** `37764ef7351b3619d4cddb57b11d9a0da24dadeedc0fc0f70d089038d37e03b0`


# VaeDecodeTextureTrellis - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VaeDecodeTextureTrellis

This node decodes a Trellis2 texture latent into voxel colors using a VAE.

This node decodes a Trellis2 texture latent into voxel colors using a VAE. The input latent contains sparse feature samples with coordinates; the node reconstructs the color for each voxel and returns the result as a voxel grid that downstream nodes, such as PaintMesh, can use to color a 3D mesh.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `samples` | The texture latent to decode. It contains the sample features and sparse coordinates, and may include optional metadata such as coordinate counts (`coord_counts`), model frame (`model_frame`, default: "y\_up"), and coordinate resolution (`coord_resolution`). | LATENT | Yes | — |
| `vae` | The Trellis2 VAE used to decode the texture latent into voxel colors. | VAE | Yes | — |
| `shape_subdivides` | Shape information used to guide higher-detail reconstruction during decoding. Helps preserve structure consistency at higher resolutions. | SHAPE\_SUBDIVIDES | Yes | — |

Note: When the `samples` latent includes `coord_counts`, the counts must be non-negative, their total must match the number of coordinate rows, and each batch must contain exactly the expected number of rows; otherwise the node raises an error. If the latent's `model_frame` is "z\_up", the decoded voxel coordinates are remapped to Y-up so they align with mesh vertices. When `coord_resolution` is supplied, the output texture resolution is that value multiplied by 16. Otherwise it is inferred from the largest voxel coordinate plus one, rounded up to one of 256, 512, 1024, 1536, or 2048; if the needed value exceeds 2048, that larger value is used. If no coordinates are available, the resolution defaults to 1024.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `voxel_colors` | Decoded voxel data containing coordinates, color features, and texture resolution. Each voxel has 6 color channels: base color (RGB), metallic, roughness, and alpha, all in the range \[0, 1]. Vertex-color consumers such as PaintMesh use the first 3 channels. | VOXEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VaeDecodeTextureTrellis/en.md)

***

**Source fingerprint (SHA-256):** `952ea7d7a0147519392bebe352a0da731462db278c8640fa527aa5b6f64e4aa7`


# Wan22ImageToVideoLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan22ImageToVideoLatent

Wan22ImageToVideoLatent creates video latent representations from images.

Wan22ImageToVideoLatent creates video latent representations from images. It generates a blank video latent space with the specified width, height, frame length, and batch size, and can optionally encode a starting image sequence into the beginning frames. When a start image is provided, the node encodes it into the latent space and creates a corresponding noise mask that marks which regions should be denoised during generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `vae` | The VAE model used to encode the start image into latent space | VAE | Yes | - |
| `width` | The width of the output video in pixels (default: 1280, step: 32) | INT | Yes | 32 to MAX\_RESOLUTION |
| `height` | The height of the output video in pixels (default: 704, step: 32) | INT | Yes | 32 to MAX\_RESOLUTION |
| `length` | The number of frames in the video sequence (default: 49, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | The number of video latents to generate (default: 1) | INT | Yes | 1 to 4096 |
| `start_image` | Optional starting image sequence to encode into the beginning frames of the video latent (uses the first `length` frames) | IMAGE | No | - |

**Note:** When `start_image` is provided, the image sequence is upscaled to the target `width` and `height`, encoded with the VAE, and placed into the first frames of the latent. The noise mask for those frames is set to 0 (preserved), while the remaining frames have a mask value of 1 (to be denoised). The latent always has 48 channels, spatial dimensions of `height / 16` by `width / 16`, and a temporal dimension of `((length - 1) // 4) + 1`. `width` and `height` must be divisible by 16 (enforced by the step of 32), and `length` increases the temporal dimension in steps of 4.

When `start_image` is not provided, a fully blank latent is returned with no noise mask, and the `batch_size` input is not applied to that blank latent.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `samples` | The generated video latent representation, repeated for each item in the batch | LATENT |
| `noise_mask` | The noise mask indicating which regions should be denoised (value 1) and which retain the encoded start image (value 0) | LATENT |

Both fields are returned together inside a single LATENT output.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan22ImageToVideoLatent/en.md)

***

**Source fingerprint (SHA-256):** `3d05980641eeef2e86df7a845aa8b2bd703882db98fe71adef2746ab34a9d717`


# WanFirstLastFrameToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanFirstLastFrameToVideo

The WanFirstLastFrameToVideo node prepares conditioning for video generation by combining a start frame and an end frame with text prompts.

The WanFirstLastFrameToVideo node prepares conditioning for video generation by combining a start frame and an end frame with text prompts. It encodes the frame images into latent space, creates a mask that tells the video model which frames are already known, and attaches CLIP vision features when they are provided. The node outputs updated positive and negative conditioning plus an empty latent that defines the size and length of the video to generate.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive text conditioning used to guide the video generation. | CONDITIONING | Yes | - |
| `negative` | Negative text conditioning used to guide the video generation. | CONDITIONING | Yes | - |
| `vae` | VAE model used to encode the combined frame images into latent space. | VAE | Yes | - |
| `width` | Width of the generated video in pixels (default: 832, step: 16). | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Height of the generated video in pixels (default: 480, step: 16). | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames in the video sequence (default: 81, step: 4). | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of videos to generate at once (default: 1). | INT | Yes | 1 to 4096 |
| `clip_vision_start_image` | CLIP vision features extracted from the start image. If both start and end CLIP vision inputs are provided, their features are combined. | CLIP\_VISION\_OUTPUT | No | - |
| `clip_vision_end_image` | CLIP vision features extracted from the end image. If both start and end CLIP vision inputs are provided, their features are combined. | CLIP\_VISION\_OUTPUT | No | - |
| `start_image` | Starting frame image for the video sequence. Its first `length` frames are used and resized to `width` × `height`. | IMAGE | No | - |
| `end_image` | Ending frame image for the video sequence. Its last `length` frames are used and resized to `width` × `height`. | IMAGE | No | - |

**Note:** When at least one of `start_image` or `end_image` is provided, the node builds a combined frame sequence where the start and end frames are filled in and the remaining frames use a neutral gray placeholder (0.5). A mask marks the filled regions as known and the placeholder regions as unknown, allowing the video model to generate the in-between frames. When a start image is provided, the known region also extends 3 extra frames beyond the image. The same encoded frame image and mask are attached to both `positive` and `negative` conditioning. If both CLIP vision inputs are provided, their hidden states are concatenated; if only one is provided, it is used on its own. The latent video length is derived from `length` after temporal compression: `((length - 1) // 4) + 1`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with the encoded frame image, mask, and (if provided) CLIP vision features attached. | CONDITIONING |
| `negative` | Negative conditioning with the encoded frame image, mask, and (if provided) CLIP vision features attached. | CONDITIONING |
| `latent` | Empty latent tensor (all zeros) shaped for the given batch size, video length, and resolution. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanFirstLastFrameToVideo/en.md)

***

**Source fingerprint (SHA-256):** `0072e441cb80334c3c961d1bbf2d081c78bc38ed1eacca840c577a2d01b36f05`


# WanImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanImageToVideo

The WanImageToVideo node prepares conditioning and latent representations for video generation.

The WanImageToVideo node prepares conditioning and latent representations for video generation. It creates an empty latent space for the video and can optionally incorporate a starting image and CLIP vision output to guide the generation. Both the positive and negative conditioning inputs are updated with the provided image and vision data.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning input used to guide the generation | CONDITIONING | Yes | - |
| `negative` | Negative conditioning input used to guide the generation | CONDITIONING | Yes | - |
| `vae` | VAE model used to encode images into latent space | VAE | Yes | - |
| `width` | Width of the generated video (default: 832, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Height of the generated video (default: 480, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames in the video (default: 81, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of videos to generate in one batch (default: 1) | INT | Yes | 1 to 4096 |
| `clip_vision_output` | Optional CLIP vision output added as extra conditioning to both the positive and negative inputs | CLIP\_VISION\_OUTPUT | No | - |
| `start_image` | Optional starting image used to initialize the video. When provided, it is resized to the specified `width` and `height` and placed at the beginning of the frame sequence; any frames beyond `length` are ignored. The remaining frames are filled with neutral gray (0.5) values. | IMAGE | No | - |

**Note:** When `start_image` is provided, the frame sequence is encoded with the VAE and a mask is applied to the conditioning. The mask is set to 0 for the frames covered by the starting image and 1 for the remaining frames, so generation continues from the provided image. Only the first three color channels (RGB) of the image are used during encoding. Both positive and negative conditioning receive the same concatenated latent image, mask, and (if supplied) CLIP vision output.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning, updated with the image and vision data | CONDITIONING |
| `negative` | Negative conditioning, updated with the image and vision data | CONDITIONING |
| `latent` | Empty latent tensor ready for video generation, with shape \[batch\_size, 16, ((length-1)//4)+1, height//8, width//8] | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `46779f9f2f3da16826b7b547761a96597a3b6b43ce51a9c13367987642f3d5b7`


# WanSCAILToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanSCAILToVideo

The WanSCAILToVideo node prepares conditioning and an empty latent space for video generation with SCAIL and SCAIL-2 video models.

The WanSCAILToVideo node prepares conditioning and an empty latent space for video generation with SCAIL and SCAIL-2 video models. It processes optional inputs such as reference images, pose videos, CLIP vision outputs, colored identity masks, and previous frame chunks, embedding them into the positive and negative conditioning. The node outputs the modified conditioning and a blank latent tensor of the specified video dimensions, ready for sampling.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | The positive conditioning input. | CONDITIONING | Yes | - |
| `negative` | The negative conditioning input. | CONDITIONING | Yes | - |
| `vae` | The VAE model used for encoding images and video frames. | VAE | Yes | - |
| `width` | The width of the output video in pixels (default: 512). Values step by 32. | INT | Yes | 32 to MAX\_RESOLUTION |
| `height` | The height of the output video in pixels (default: 896). Values step by 32. | INT | Yes | 32 to MAX\_RESOLUTION |
| `length` | The number of frames in the video (default: 81). Values step by 4. | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | The number of videos to generate in a batch (default: 1). | INT | Yes | 1 to 4096 |
| `pose_video` | Video used for pose conditioning. Will be downscaled to half the resolution of the main video. | IMAGE | No | - |
| `pose_video_mask` | SCAIL-2 only. Colored per-identity SAM3 mask video at the same resolution as pose\_video. | IMAGE | No | - |
| `replacement_mode` | SCAIL-2 only. False = Animation Mode (pose\_video\_mask should have black background). True = Replacement Mode (pose\_video\_mask should have white background). (default: False) | BOOLEAN | No | - |
| `pose_strength` | Strength of the pose latent. (default: 1.0) | FLOAT | Yes | 0.0 to 10.0 |
| `pose_start` | Start step of the pose conditioning. (default: 0.0) | FLOAT | Yes | 0.0 to 1.0 |
| `pose_end` | End step of the pose conditioning. (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `reference_image` | Reference image. The first image is the primary reference (composite all identities onto it). SCAIL-2: extra batch images are used as additional views (back view, close-up, occluded background), each needing a matching reference\_image\_mask in that identity's color. | IMAGE | No | - |
| `reference_image_mask` | SCAIL-2 only. Colored reference mask, batch matching reference\_image (first = primary reference mask, rest = identity masks for the additional reference\_image). | IMAGE | No | - |
| `clip_vision_output` | CLIP vision features for conditioning. Model is trained with stretch resize to aspect ratio. | CLIP\_VISION\_OUTPUT | No | - |
| `video_frame_offset` | Cumulative output frame this chunk begins at. Wire from the previous chunk's video\_frame\_offset output. (default: 0) | INT | Yes | 0 to MAX\_RESOLUTION |
| `previous_frame_count` | Tail frames of previous\_frames to anchor. SCAIL-2 trained at 5 (81-frame chunks, 76-frame step). (default: 5). Values step by 4. | INT | Yes | 1 to MAX\_RESOLUTION |
| `previous_frames` | SCAIL-2 only. Full decoded output of the previous chunk. Only the last previous\_frame\_count are used as the extension anchor. | IMAGE | No | - |

**Note:** The `pose_video` and `pose_video_mask` inputs are truncated together to the shorter of the two, and are processed only for the first `length` frames. If either input is shorter than or equal to `video_frame_offset`, it is ignored entirely. The `pose_video` is downscaled to half the resolution of the main video before encoding, and the encoded pose latent is multiplied by `pose_strength` and applied to the conditioning only between the `pose_start` and `pose_end` timestep steps. If `pose_video_mask` is provided, the colored mask video is downscaled to half resolution and converted into a 28-channel driving mask, which is added to both positive and negative conditioning.

**Note:** When `reference_image` is provided, each image in the batch is encoded individually into a latent and embedded into both positive and negative conditioning. The first image is the primary reference; additional images are used as additional views, each needing a matching `reference_image_mask`. `reference_image_mask` is only used when `reference_image` is also provided; when both are given, a 28-channel reference mask that binds the reference frames to identities is also built from the masks and added to the conditioning. In Replacement Mode (`replacement_mode=True`), the reference image is composited on a black background using the reference image mask as an alpha matte. When `clip_vision_output` is provided, it is applied to both positive and negative conditioning.

**Note:** When `previous_frames` is provided, only the last `previous_frame_count` frames are used as the extension anchor, and `video_frame_offset` is adjusted accordingly (reduced by the number of anchored frames, clamped at 0). The anchored frames are encoded and written into the beginning of the output latent, and a noise mask is included so those frames are kept unchanged during generation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | The modified positive conditioning, potentially containing embedded reference image latents, CLIP vision output, pose video latents, driving masks, reference masks, or previous frame latents. | CONDITIONING |
| `negative` | The modified negative conditioning, potentially containing embedded reference image latents, CLIP vision output, pose video latents, driving masks, reference masks, or previous frame latents. | CONDITIONING |
| `latent` | An empty latent tensor of shape `[batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8]`. When `previous_frames` is provided, the latent is partially filled with encoded previous frames and a noise mask is included. | LATENT |
| `video_frame_offset` | Adjusted offset + length. Wire into the next chunk for sequential video generation. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanSCAILToVideo/en.md)

***

**Source fingerprint (SHA-256):** `4a1a2201dfa94bd2f1330db02ec18a5e0a6aae9e9ac5ae97d456b7af1aa84b7b`


# WanSoundImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanSoundImageToVideo

The WanSoundImageToVideo node prepares conditioning and an empty latent video tensor for Wan sound-to-video generation.

The WanSoundImageToVideo node prepares conditioning and an empty latent video tensor for Wan sound-to-video generation. It can optionally incorporate audio encoding, a reference image, a control video, and a motion reference to guide the generated video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning prompts that guide what content should appear in the generated video | CONDITIONING | Yes | - |
| `negative` | Negative conditioning prompts that specify what content should be avoided in the generated video | CONDITIONING | Yes | - |
| `vae` | VAE model used for encoding reference images, motion references, and control video frames into latent representations | VAE | Yes | - |
| `width` | Width of the output video in pixels (default: 832, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Height of the output video in pixels (default: 480, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames in the generated video (default: 77, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of videos to generate simultaneously (default: 1) | INT | Yes | 1 to 4096 |
| `audio_encoder_output` | Optional audio encoding that can influence the video generation based on sound characteristics. When provided, the audio features are interpolated and used to condition the video generation. | AUDIO\_ENCODER\_OUTPUT | No | - |
| `ref_image` | Optional reference image that provides visual guidance for the video content. The image is upscaled to match the specified width and height, then encoded into a latent representation. Only the first image of the input is used as the reference. | IMAGE | No | - |
| `control_video` | Optional control video that guides the motion and structure of the generated video. The video is upscaled and encoded, then used to condition the output. Only the first `length` frames are used. | IMAGE | No | - |
| `ref_motion` | Optional motion reference that provides guidance for movement patterns in the video. If the input has more than 73 frames, only the last 73 are used. If fewer than 73 frames are provided, the sequence is padded with neutral frames. | IMAGE | No | - |

Note: All optional inputs can be used independently or together. The node modifies the provided `positive` and `negative` conditioning based on which optional inputs are connected.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Processed positive conditioning that has been modified for video generation, including audio embeddings, reference latents, motion references, and control video conditioning when the corresponding optional inputs are provided | CONDITIONING |
| `negative` | Processed negative conditioning that has been modified for video generation, including audio embeddings (set to zero), reference latents, motion references, and control video conditioning when the corresponding optional inputs are provided | CONDITIONING |
| `latent` | Empty latent video tensor used as the starting point for generation. The latent tensor has shape `[batch_size, 16, latent_t, height/8, width/8]`, where `latent_t` is calculated as `((length - 1) // 4) + 1`. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanSoundImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `b1148cd00d8999dd6842e3c2fb13655fda8f20d5befed975a6d1652688b2807c`


# WanSoundImageToVideoExtend - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanSoundImageToVideoExtend

The WanSoundImageToVideoExtend node extends an existing video latent by generating additional frames, optionally guided by audio, a reference image, and a control video.

The WanSoundImageToVideoExtend node extends an existing video latent by generating additional frames, optionally guided by audio, a reference image, and a control video. It takes a starting video latent and produces a longer video sequence, using the provided conditioning and audio cues to influence the new content.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning prompts that guide what the video should include | CONDITIONING | Yes | - |
| `negative` | Negative conditioning prompts that specify what the video should avoid | CONDITIONING | Yes | - |
| `vae` | Variational Autoencoder used to encode the reference image and control video into latent space | VAE | Yes | - |
| `length` | Total number of frames to generate for the video sequence (default: 77, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `video_latent` | Initial video latent that serves as the starting point for the extension. The output width, height, batch size, and frame offset are derived from this latent. Its last 19 frames are used as reference motion conditioning. | LATENT | Yes | - |
| `audio_encoder_output` | Optional audio embeddings that can influence the video generation based on sound characteristics. When provided, the audio is interpolated and converted into an audio embedding bucket that is added to the conditioning. | AUDIOENCODEROUTPUT | No | - |
| `ref_image` | Optional reference image that provides visual guidance for the video generation. The image is upscaled to match the target dimensions and encoded into a latent, which is then added to both positive and negative conditioning. Only the first image in the batch is used. | IMAGE | No | - |
| `control_video` | Optional control video that guides the motion and structure of the generated video. The video is upscaled, encoded, and added to both positive and negative conditioning. The control video is truncated to the specified `length`. | IMAGE | No | - |

Note: The output latent is initialized as zeros with the target dimensions. The input `video_latent` is not copied into this output; its last 19 frames are used as the reference motion instead.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Processed positive conditioning with video context applied, including audio embeddings, reference latents, reference motion, and control video if provided | CONDITIONING |
| `negative` | Processed negative conditioning with video context applied, including audio embeddings (zeroed out), reference latents, reference motion, and control video if provided | CONDITIONING |
| `latent` | Video latent representation of the extended sequence, initialized as zeros with dimensions derived from the input `video_latent` and the target `length` | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanSoundImageToVideoExtend/en.md)

***

**Source fingerprint (SHA-256):** `32b58aaba566f346a0388ba804fc92e7ad426bf2e9e7039e5fdb0bf6a746e972`


# WanVaceToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanVaceToVideo

The WanVaceToVideo node prepares video conditioning data for VACE-controlled video generation models.

The WanVaceToVideo node prepares video conditioning data for VACE-controlled video generation models. It combines positive and negative conditioning with an optional control video, control masks, and a reference image, encodes them through a VAE, and outputs updated conditioning, an empty latent tensor, and a trim value.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `positive` | Positive conditioning input for guiding the generation | CONDITIONING | Yes | - |
| `negative` | Negative conditioning input for guiding the generation | CONDITIONING | Yes | - |
| `vae` | VAE model used for encoding images and video frames | VAE | Yes | - |
| `width` | Output video width in pixels (default: 832, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `height` | Output video height in pixels (default: 480, step: 16) | INT | Yes | 16 to MAX\_RESOLUTION |
| `length` | Number of frames in the video (default: 81, step: 4) | INT | Yes | 1 to MAX\_RESOLUTION |
| `batch_size` | Number of videos to generate simultaneously (default: 1) | INT | Yes | 1 to 4096 |
| `strength` | Condition strength for VACE control (default: 1.0, step: 0.01). This is not a LoRA strength. LoRA weights are applied through separate LoRA nodes. | FLOAT | Yes | 0.0 to 1000.0 |
| `control_video` | Optional input video used for control conditioning. If not provided, a neutral gray video is created automatically. | IMAGE | No | - |
| `control_masks` | Optional masks that determine which parts of the control video are active. If not provided, a full white mask is used. | MASK | No | - |
| `reference_image` | Optional reference image for additional conditioning. When provided, it is encoded and prepended to the latent sequence. Only the first image is used. | IMAGE | No | - |

**Note:** When `control_video` is provided, it is truncated to `length` frames and upscaled to the specified `width` and `height`; if it has fewer frames than `length`, the missing frames are padded with neutral gray (value 0.5). When it is not provided, a neutral gray video of `length` frames is created automatically. `control_masks` are upscaled to the specified `width` and `height`, truncated to `length` frames, and padded with value 1.0 if shorter. The mask separates the control video into inactive and reactive parts, each VAE-encoded and concatenated along the channel dimension; the mask is also downsampled to latent resolution. When `reference_image` is provided, its first image is VAE-encoded and prepended to the latent sequence, and `trim_latent` reports the number of latent frames added. The latent frame count is calculated as `((length - 1) // 4) + 1`, and the latent spatial dimensions are `height / 8` and `width / 8`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `positive` | Positive conditioning with video control data (vace\_frames, vace\_mask, vace\_strength) applied | CONDITIONING |
| `negative` | Negative conditioning with video control data (vace\_frames, vace\_mask, vace\_strength) applied | CONDITIONING |
| `latent` | Empty latent tensor ready for video generation with shape \[batch\_size, 16, latent\_length, height/8, width/8] | LATENT |
| `trim_latent` | Number of latent frames to trim when a reference image is used; 0 if no reference image is provided | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanVaceToVideo/en.md)

***

**Source fingerprint (SHA-256):** `2039b7509ce5b731e9e41d9cd2dad022d4c5004751f571a4cf88c1ba0cae405b`


# YuE2GenerateABC - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/YuE2GenerateABC

This node generates ABC notation for a song based on a style description and lyrics, using a YuE2 text-and-lyrics model.

This node generates ABC notation for a song based on a style description and lyrics, using a YuE2 text-and-lyrics model. The resulting `abc` output can be connected to the YuE2 Generate Music node to produce audio.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The YuE2 model used to tokenize the style and lyrics and generate the ABC notation. | CLIP | Yes | - |
| `style` | Text describing the musical style of the song. Supports multiline input and dynamic prompts. | STRING | Yes | - |
| `lyrics` | Text containing the lyrics of the song. Supports multiline input and dynamic prompts. | STRING | Yes | - |
| `seed` | Random seed used for generation. Changing it produces different results. Default: 0. | INT | Yes | 0 to 18446744073709551615 |
| `mode` | full: generates melody and chords; melody: generates melody only, recommended for covers. | COMBO | Yes | "full"<br />"melody" |
| `max_abc_tokens` | Maximum number of tokens generated for the ABC notation. Default: 8192. Advanced setting. | INT | Yes | 1 to 20000 |
| `temperature` | Controls the randomness of the generated tokens. Higher values produce more varied output. Default: 0.7. Advanced setting. | FLOAT | Yes | 0.0 to 5.0 |
| `top_p` | Nucleus sampling threshold; only tokens within this cumulative probability are considered. Default: 0.9. Advanced setting. | FLOAT | Yes | 0.01 to 1.0 |
| `top_k` | Limits token selection to the K most likely tokens. Default: 30. Advanced setting. | INT | Yes | 1 to 32768 |
| `repetition_penalty` | Penalty applied to repeated tokens during generation. Default: 1.005. Advanced setting. | FLOAT | Yes | 0.01 to 10.0 |
| `penalty_window` | Number of recent ABC tokens used to penalize repetition. Default: 100. Advanced setting. | INT | Yes | 1 to 20000 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `abc` | The generated ABC notation of the song, which can be connected to the YuE2 Generate Music node. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/YuE2GenerateABC/en.md)

***

**Source fingerprint (SHA-256):** `2c1bf0841a044724ff0477f920972d70bbd97de49b56fbe6213a9ac134797130`


# YuE2GenerateMusic - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/YuE2GenerateMusic

Generates music tokens and acoustic conditioning from a style, lyrics, and an ABC notation.

Generates music tokens and acoustic conditioning from a style, lyrics, and an ABC notation. It returns the conditioning and the generated duration in seconds, which should be provided to the Empty YuE2 Latent Audio node. If the ABC input is left empty, the selected mode is ignored and off mode is used automatically.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used to tokenize and encode the music inputs. | CLIP | Yes | - |
| `style` | Text describing the musical style. Supports multiline input and dynamic prompts. | STRING | Yes | Multiline text |
| `lyrics` | Lyrics for the generated music. Supports multiline input and dynamic prompts. | STRING | Yes | Multiline text |
| `abc` | Connect the ABC generator or supply an edited score. Leave empty to use off mode automatically. default: "" | STRING | Yes | Multiline text |
| `seed` | Random seed for generation. default: 0 | INT | Yes | 0 to 18446744073709551615 |
| `mode` | full: generates melody and chords; melody: generates melody only, recommended for covers. default: "full" | COMBO | Yes | "full"<br />"melody" |
| `max_duration` | Maximum duration in seconds. Automatically reduced for long prompts; generation can stop earlier. default: 360.0 | FLOAT | Yes | 0.04 to 900.0 |
| `temperature` | Sampling temperature for generation. default: 1.0 (advanced) | FLOAT | Yes | 0.0 to 5.0 |
| `top_p` | Nucleus sampling probability threshold. default: 0.95 (advanced) | FLOAT | Yes | 0.01 to 1.0 |
| `top_k` | Top-k sampling limit. default: 100 (advanced) | INT | Yes | 1 to 32768 |
| `repetition_penalty` | Penalty applied to repeated tokens. default: 1.2 (advanced) | FLOAT | Yes | 0.01 to 10.0 |
| `cfg_scale` | Autoregressive guidance for style and lyrics. 1.0 disables CFG, matching the ABC workflow. Use 1.01 to match the original off-mode guidance. default: 1.0 (advanced, optional) | FLOAT | No | 0.0 to 100.0 |

Note: If `abc` is empty or contains only whitespace, the `mode` selection is ignored and off mode is used automatically.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | Acoustic conditioning generated from the music tokens. | CONDITIONING |
| `seconds` | The generated audio duration in seconds. Provide this value to the Empty YuE2 Latent Audio node. | FLOAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/YuE2GenerateMusic/en.md)

***

**Source fingerprint (SHA-256):** `5a88e185d2998c51acff7f0c76c8c35ca30b80b88cb541d97f9ab91566b5a3ed`


# unCLIPConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/unCLIPConditioning

This node is designed to integrate CLIP vision outputs into the conditioning process, adjusting the influence of these outputs based on specified strength and noise augmentation pa

This node is designed to integrate CLIP vision outputs into the conditioning process, adjusting the influence of these outputs based on specified strength and noise augmentation parameters. It enriches the conditioning with visual context, enhancing the generation process.

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `conditioning` | The base conditioning data to which the CLIP vision outputs are to be added, serving as the foundation for further modifications. | `CONDITIONING` |
| `clip_vision_output` | The output from a CLIP vision model, providing visual context that is integrated into the conditioning. | `CLIP_VISION_OUTPUT` |
| `strength` | Determines the intensity of the CLIP vision output's influence on the conditioning. | `FLOAT` |
| `noise_augmentation` | Specifies the level of noise augmentation to apply to the CLIP vision output before integrating it into the conditioning. | `FLOAT` |

## Outputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `conditioning` | The enriched conditioning data, now containing integrated CLIP vision outputs with applied strength and noise augmentation. | `CONDITIONING` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/unCLIPConditioning/en.md)


# AnimaLLLiteApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AnimaLLLiteApply

AnimaLLLiteApply applies a lightweight animation patch to a diffusion model, enabling controlled image-to-image generation with adjustable strength and timing.

AnimaLLLiteApply applies a lightweight animation patch to a diffusion model, enabling controlled image-to-image generation with adjustable strength and timing. It integrates a pre-configured model patch with an input image and optional mask, modifying the model's attention and MLP layers to influence the generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The base diffusion model to apply the patch to | MODEL | Yes | |
| `model_patch` | The pre-configured animation patch to apply | MODEL\_PATCH | Yes | |
| `image` | The reference image to guide the generation. Only the first 3 color channels (RGB) are used | IMAGE | Yes | |
| `strength` | The strength of the patch effect (default: 1.0, step: 0.01) | FLOAT | Yes | -10.0 to 10.0 |
| `start_percent` | The percentage of the denoising process at which the patch starts taking effect (default: 0.0, step: 0.001) | FLOAT | Yes | 0.0 to 1.0 |
| `end_percent` | The percentage of the denoising process at which the patch stops taking effect (default: 1.0, step: 0.001) | FLOAT | Yes | 0.0 to 1.0 |
| `mask` | An optional mask to limit the patch effect to specific areas of the image | MASK | No | |

**Note on parameter constraints:** If the `model_patch` has 4 input channels and no `mask` is provided, a zero mask is automatically created to match the image dimensions. If the `model_patch` does not have 4 input channels, the `mask` parameter is ignored and set to `None`. Only the first 3 color channels of the input image are used. This node is marked as experimental in ComfyUI.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The patched diffusion model with the animation patch applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AnimaLLLiteApply/en.md)

***

**Source fingerprint (SHA-256):** `48e455b767509a5a8c329365d5ffded86d6f4545d575c9fdc5ffbaf4da7c2287`


# AudioEncoderLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioEncoderLoader

Documentation for AudioEncoderLoader node.

## Overview

The AudioEncoderLoader node loads an audio encoder model from a file stored in your `audio_encoders` folder. It takes the filename of an audio encoder model as input and returns the loaded model, which can then be used for audio processing tasks in your workflow. If the selected file does not contain a valid audio encoder model, the node raises an error.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio_encoder_name` | Selects which audio encoder model file to load from the audio encoders folder | COMBO | Yes | List of available audio encoder files in the `audio_encoders` folder |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio_encoder` | The loaded audio encoder model, ready for use in audio processing workflows | AUDIO\_ENCODER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioEncoderLoader/en.md)

***

**Source fingerprint (SHA-256):** `780d0c7fcf571e5ef02d273791e5d2e894baa6d5900d845ed65e9ce669769f7e`


# BlockSparseAttention - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BlockSparseAttention

The Block Sparse Attention node modifies a model so its attention layers focus on only the most relevant parts of the input instead of everything at once, which reduces the computi

The **Block Sparse Attention** node modifies a model so its attention layers focus on only the most relevant parts of the input instead of everything at once, which reduces the computing work needed for long sequences. The savings grow with sequence length, since short sequences are usually faster with normal (dense) attention.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to patch. | MODEL | Yes | N/A |
| `selection` | Method used to choose key blocks for full token-level attention (displayed as `method`). <br />`sol-attn`: Sparsifying Online Attention uses a training-free adaptive threshold for each attention head and query block.<br />`sla`: Sparse-Linear Attention keeps a fixed percentage of the highest-scoring key blocks; use only with model weights trained for this pattern.<br />`vsa`: Video Sparse Attention (FastVideo) uses 3D video-cube tiling and a learned coarse attention branch; requires FastH3 model weights. | DYNAMIC\_COMBO | Yes | `"sol-attn"`<br />`"sla"`<br />`"vsa"` |
| `start_percent` | Percentage point when sparse attention begins. Before this point, attention stays dense. Default: 0.2. | FLOAT | No | min: 0.0, max: 1.0, step: 0.01 |
| `end_percent` | Percentage point when sparse attention ends. After this point, attention returns to dense. Default: 1.0. | FLOAT | No | min: 0.0, max: 1.0, step: 0.01 |
| `dense_blocks` | Transformer blocks that always run dense, e.g. '0, 1, 47-49'. Default: "" (empty). Advanced input. | STRING | No | Default: "" |
| `min_tokens` | Sequences shorter than this stay dense. Default: 12288. Advanced input. | INT | No | min: 0, max: 1048576, step: 512 |
| `extra_tokens` | Extra top-scoring tokens each query block attends beyond its selected blocks. Closer to dense for more attention time; 256 recommended, 0 disables. Ignored for VSA. Default: 256. Advanced input. | INT | No | min: 0, max: 256, step: 64 |
| `sink_conditioning` | MiniMax-H3 only. `exact_kv`: every query attends the packed text/audio/reference rows exactly (about 3% cost). `exact_kv_and_rows`: additionally runs the target-audio query rows dense (keeps generated audio intact). `off` disables this behavior. Default: "exact\_kv\_and\_rows". Advanced input. | COMBO | No | `"exact_kv"`<br />`"exact_kv_and_rows"`<br />`"off"` |
| `verbose` | Logs whether each attention shape used sparse attention or why it stayed dense. Default: False. Advanced input. | BOOLEAN | No | Default: False |

### sol-attn Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `tau` | Threshold in score-distribution sigmas. Higher is sparser: 1.0 keeps about 16% of key blocks exact, 1.5 about 7%, 2.0 about 2.7%. Default: 1.3. | FLOAT | No | min: 0.0, max: 4.0, step: 0.05 |

### sla Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `keep_percent` | Percent of key blocks each query block keeps exactly (sinks and the diagonal ride on top). The selection SLA-style LoRAs are distilled against; without such a LoRA higher is closer to dense. Default: 10.0. | FLOAT | No | min: 0.5, max: 95.0, step: 0.5 |

### vsa Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `keep_percent` | Percent of video cubes each query cube keeps; FastH3-VSA checkpoints are trained at 10. Uses the model's `to_gate_compress` layers for the coarse branch when present. Default: 10.0. | FLOAT | No | min: 0.5, max: 95.0, step: 0.5 |

**Note:** Only the parameters belonging to the currently selected method are shown in the interface.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The model with block-sparse attention applied. | MODEL |

## Constraints and Limitations

* Sequences shorter than `min_tokens`, blocks listed in `dense_blocks`, and sampling steps outside the `start_percent` to `end_percent` window fall back to the dense model attention backend selected by the Model Attention Backend node.
* `extra_tokens` is ignored when the `vsa` method is selected. A message is logged because VSA weights were trained against their sparse pattern.
* The `vsa` method requires a MiniMax-H3 model; any other model raises an error. If the model lacks `to_gate_compress` layers, the fine stage runs without the coarse branch and a warning is logged.
* `dense_blocks` is ignored for models that do not report block indices, which is noted in the log when `verbose` is enabled.
* `sink_conditioning` applies only to MiniMax-H3 models that report a layout matching the current sequence length.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BlockSparseAttention/en.md)

***

**Source fingerprint (SHA-256):** `0c34876b49a04db0ab265526e2bb5f784e150591aab631713ad2ab420a3327c4`


# CLIPMergeAdd - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPMergeAdd

The CLIPMergeAdd node combines two CLIP models by adding patches from the second model to the first model.

The CLIPMergeAdd node combines two CLIP models by adding patches from the second model to the first model. It creates a copy of the first CLIP model and selectively incorporates key patches from the second model, excluding position IDs and logit scale parameters. This allows you to merge CLIP model components while preserving the structure of the base model.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip1` | The base CLIP model that will be cloned and used as the foundation for merging | CLIP | Yes | - |
| `clip2` | The secondary CLIP model that provides key patches to be added to the base model | CLIP | Yes | - |

Keys ending in `.position_ids` or `.logit_scale` from `clip2` are skipped, so those parameters keep the values from `clip1`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CLIP` | A merged CLIP model containing the base model structure with added patches from the secondary model | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPMergeAdd/en.md)

***

**Source fingerprint (SHA-256):** `e6271ea9139598eb580f79ce63ff5d92307d7ed93f57cdc666c5e022b671a0dd`


# CLIPMergeSubtract - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPMergeSubtract

The CLIPMergeSubtract node performs model merging by subtracting the weights of one CLIP model from another.

The CLIPMergeSubtract node performs model merging by subtracting the weights of one CLIP model from another. It creates a new CLIP model by cloning the first model and then subtracting the key patches from the second model, with an adjustable multiplier to control the subtraction strength. This allows for fine-tuned model blending by removing specific characteristics from the base model.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip1` | The base CLIP model that will be cloned and modified | CLIP | Yes | - |
| `clip2` | The CLIP model whose key patches will be subtracted from the base model | CLIP | Yes | - |
| `multiplier` | Controls the strength of the subtraction operation (default: 1.0) | FLOAT | Yes | -10.0 to 10.0 (step: 0.01) |

**Note:** The node excludes `.position_ids` and `.logit_scale` parameters from the subtraction operation, regardless of the multiplier value.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `clip` | The resulting CLIP model after subtracting the second model's weights from the first | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPMergeSubtract/en.md)

***

**Source fingerprint (SHA-256):** `62a8cf719c34d9e2b7321f6eeb03c881f0767fd36b80e25e74feff4c0a29045e`


# CheckpointLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CheckpointLoader

The CheckpointLoader node loads a pre-trained model checkpoint together with its configuration file.

The CheckpointLoader node loads a pre-trained model checkpoint together with its configuration file. It takes a configuration file and a checkpoint file as inputs and returns the loaded model components — the main model, CLIP model, and VAE model — for use in the workflow. This node is deprecated.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `config_name` | The configuration file that defines the model architecture and settings | COMBO | Yes | Available config files |
| `ckpt_name` | The checkpoint file containing the trained model weights and parameters | COMBO | Yes | Available checkpoint files |

**Note:** This node requires both a configuration file and a checkpoint file to be selected. The configuration file must match the architecture of the checkpoint file being loaded.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The loaded main model component ready for inference | MODEL |
| `CLIP` | The loaded CLIP model component for text encoding | CLIP |
| `VAE` | The loaded VAE model component for image encoding and decoding | VAE |

**Important Note:** This node has been marked as deprecated and may be removed in future versions. Consider using alternative loading nodes for new workflows.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CheckpointLoader/en.md)

***

**Source fingerprint (SHA-256):** `820cd9f7a5ccd5a70d2b29906c8deca3632d2ccba84ca51022717e061afb72b3`


# CheckpointLoaderSimple - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CheckpointLoaderSimple

Loads a diffusion model checkpoint file and splits it into three core components: the main model used for denoising latents, the CLIP text encoder, and the VAE image encoder/decode

Loads a diffusion model checkpoint file and splits it into three core components: the main model used for denoising latents, the CLIP text encoder, and the VAE image encoder/decoder. The node automatically detects all model files in the `ComfyUI/models/checkpoints` folder and any additional paths configured in your `extra_model_paths.yaml` file.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `ckpt_name` | The name of the checkpoint (model) to load. Select the checkpoint model file name, which determines the AI model used for subsequent image generation. | COMBO | Yes | All model files found in the checkpoints folder |

**Note:** If new model files are added while ComfyUI is running, you need to refresh the browser (Ctrl+R) to see the new files in the dropdown list.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The model used for denoising latents. This is the core diffusion model used for image generation. | MODEL |
| `CLIP` | The CLIP model used for encoding text prompts, converting text descriptions into information that AI can understand. | CLIP |
| `VAE` | The VAE model used for encoding and decoding images to and from latent space. | VAE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CheckpointLoaderSimple/en.md)

***

**Source fingerprint (SHA-256):** `db99a8ba83a586491463df0d4e99ba5f77d4511c6d8337a721d76edd3450f310`


# CheckpointSave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CheckpointSave

The Save Checkpoint node is designed to save a complete Stable Diffusion model (including UNet, CLIP, and VAE components) as a .safetensors format checkpoint file.

The `Save Checkpoint` node is designed to save a complete Stable Diffusion model (including UNet, CLIP, and VAE components) as a **.safetensors** format checkpoint file.

The Save Checkpoint is primarily used in model merging workflows. After creating a new merged model through nodes like `ModelMergeSimple`, `ModelMergeBlocks`, etc., you can use this node to save the result as a reusable checkpoint file.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The model parameter represents the primary model whose state is to be saved. It is essential for capturing the current state of the model for future restoration or analysis. | MODEL |
| `clip` | The clip parameter is intended for the CLIP model associated with the primary model, allowing its state to be saved alongside the main model. | CLIP |
| `vae` | The vae parameter is for the Variational Autoencoder (VAE) model, enabling its state to be saved for future use or analysis alongside the main model and CLIP. | VAE |
| `filename_prefix` | This parameter specifies the prefix for the filename under which the checkpoint will be saved. | STRING |

Additionally, the node has two hidden inputs for metadata:

**prompt (PROMPT)**: Workflow prompt information
**extra\_pnginfo (EXTRA\_PNGINFO)**: Additional PNG information

## Outputs

This node will output a checkpoint file, and the corresponding output file path is `output/checkpoints/` directory

## Architecture Compatibility

* Currently fully supported: SDXL, SD3, SVD and other mainstream architectures, see [source code](https://github.com/comfyanonymous/ComfyUI/blob/master/comfy_extras/nodes_model_merging.py#L176-L189)
* Basic support: Other architectures can be saved but without standardized metadata information

## Related Links

Related source code: [nodes\_model\_merging.py#L227](https://github.com/comfyanonymous/ComfyUI/blob/master/comfy_extras/nodes_model_merging.py#L227)

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CheckpointSave/en.md)


# ChromaRadianceOptions - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ChromaRadianceOptions

The ChromaRadianceOptions node allows you to configure advanced settings for the Chroma Radiance model.

The ChromaRadianceOptions node allows you to configure advanced settings for the Chroma Radiance model. It attaches a wrapper to an existing model and applies the selected options during the denoising process only when the current sigma value falls within the configured range, giving control over NeRF tile size and text token ID handling.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply Chroma Radiance options to | MODEL | Yes | - |
| `preserve_wrapper` | When enabled, will delegate to an existing model function wrapper if it exists. Generally should be left enabled. (default: True) | BOOLEAN | No | - |
| `start_sigma` | First sigma that these options will be in effect. (default: 1.0) | FLOAT | No | 0.0 to 1.0 |
| `end_sigma` | Last sigma that these options will be in effect. (default: 0.0) | FLOAT | No | 0.0 to 1.0 |
| `nerf_tile_size` | Allows overriding the default NeRF tile size. -1 means use the default (32). 0 means use non-tiling mode (may require a lot of VRAM). (default: -1) | INT | No | -1 and above |
| `force_sequential_txt_ids` | Force usage of sequential text token IDs instead of zeroes. Should be used for checkpoints from 2026-05-22 to 2026-06-01 that are trained in this way but do not contain the **sequential** key in the state dict. (default: False) | BOOLEAN | No | - |

**Note:** The Chroma Radiance options only take effect when the current sigma value falls between `end_sigma` and `start_sigma` (inclusive). The `nerf_tile_size` option is only applied when set to 0 or a higher value (a value of -1 uses the default tile size of 32 and stores no override). The `force_sequential_txt_ids` option is only applied when set to True. When `nerf_tile_size` is -1 and `force_sequential_txt_ids` is False, no options are configured and the model is returned unchanged without any wrapper applied.

**Note:** All inputs other than `model` are advanced options.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The model with Chroma Radiance options applied, or the unchanged model if no options are active | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ChromaRadianceOptions/en.md)

***

**Source fingerprint (SHA-256):** `761f1946fe1fd77158e97f6f34d002e2445cc00e008741f8c37cde5673900409`


# CLIPLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipLoader

The CLIPLoader node loads a text encoder model (CLIP, T5, or similar) from a file, making it available for use in other nodes that need to convert text prompts into numerical repre

The CLIPLoader node loads a text encoder model (CLIP, T5, or similar) from a file, making it available for use in other nodes that need to convert text prompts into numerical representations. It supports a wide variety of model architectures, each requiring a specific encoder type.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_name` | The filename of the text encoder model to load. This must be a file located in the `ComfyUI/models/text_encoders/` directory. | STRING | Yes | List of files found in the `text_encoders` folder |
| `type` | The architecture type of the model being loaded. This determines which specific encoder variant to use (default: `"stable_diffusion"`). | COMBO | Yes | `"stable_diffusion"`<br />`"stable_cascade"`<br />`"sd3"`<br />`"stable_audio"`<br />`"mochi"`<br />`"ltxv"`<br />`"pixart"`<br />`"cosmos"`<br />`"lumina2"`<br />`"wan"`<br />`"hidream"`<br />`"chroma"`<br />`"ace"`<br />`"omnigen2"`<br />`"qwen_image"`<br />`"hunyuan_image"`<br />`"flux2"`<br />`"ovis"`<br />`"longcat_image"`<br />`"cogvideox"`<br />`"lens"`<br />`"pixeldit"`<br />`"ideogram4"`<br />`"boogu"`<br />`"krea2"`<br />`"joyimage"`<br />`"mage"`<br />`"minimax"`<br />`"yue2"` |
| `device` | The device to load the model onto. `"default"` uses the GPU if available, while `"cpu"` forces CPU loading. This is an advanced option (default: `"default"`). | COMBO | No | `"default"`<br />`"cpu"` |

### Supported Type-to-Encoder Mappings

The `type` parameter selects the correct encoder for a given model architecture. The following are common mappings:

| Type | Encoder |
| - | - |
| stable\_diffusion | clip-l |
| stable\_cascade | clip-g |
| sd3 | t5 xxl / clip-g / clip-l |
| stable\_audio | t5 base |
| mochi | t5 xxl |
| cogvideox | t5 xxl (226-token padding) |
| cosmos | old t5 xxl |
| lumina2 | gemma 2 2B |
| wan | umt5 xxl |
| hidream | llama-3.1 (recommended) or t5 |
| omnigen2 | qwen vl 2.5 3B |
| joyimage | qwen3-vl 8B |
| lens | gpt-oss-20b |
| pixeldit | gemma 2 2B elm |
| minimax | MiniMax H3 Qwen3-VL or Music3 Qwen/RVQ |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CLIP` | The loaded text encoder model, ready to be connected to other nodes for text encoding and conditioning. | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ClipLoader/en.md)

***

**Source fingerprint (SHA-256):** `6df608d500520d9414acd82d9fd509b1e211a8385202cefd5579e8a8f397bc64`


# CLIPMergeSimple - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipMergeSimple

CLIPMergeSimple is a model merging node that combines two CLIP text encoder models based on a specified ratio.

`CLIPMergeSimple` is a model merging node that combines two CLIP text encoder models based on a specified ratio. It clones the first CLIP model and applies weighted patches from the second CLIP model, skipping position IDs and logit scale components, to produce a hybrid model that blends features from both sources.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip1` | The first CLIP model to be merged. It serves as the base model for the merging process. | CLIP | Yes | - |
| `clip2` | The second CLIP model to be merged. Its key patches, except for position IDs and logit scale, are applied to the first model based on the specified ratio. | CLIP | Yes | - |
| `ratio` | Determines the proportion of features from the second model to blend into the first model. A ratio of 1.0 means fully adopting the second model's features, while 0.0 retains only the first model's features. Default: 1.0. | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `clip` | The resulting merged CLIP model, incorporating features from both input models according to the specified ratio. | CLIP |

## Merging Mechanism Explained

### Merging Algorithm

The node uses weighted averaging to merge the two models:

1. **Clone Base Model**: First clones `clip1` as the base model
2. **Get Patches**: Obtains all key patches from `clip2`
3. **Filter Special Keys**: Skips keys ending with `.position_ids` and `.logit_scale`
4. **Apply Weighted Merge**: Uses the formula `(1.0 - ratio) * clip1 + ratio * clip2`

### Ratio Parameter Explained

* **ratio = 0.0**: Fully uses clip1, ignores clip2
* **ratio = 0.5**: 50% contribution from each model
* **ratio = 1.0**: Fully uses clip2, ignores clip1

## Use Cases

1. **Model Style Fusion**: Combine characteristics of CLIP models trained on different data
2. **Performance Optimization**: Balance strengths and weaknesses of different models
3. **Experimental Research**: Explore combinations of different CLIP encoders

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPMergeSimple/en.md)

***

**Source fingerprint (SHA-256):** `42c4b2042c56c3f21a9416aa577e2d41fef1dcc749c4e5c7953851110a4fb6bc`


# CLIPSave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipSave

The CLIPSave node saves a CLIP text encoder model to disk in SafeTensors format.

The `CLIPSave` node saves a CLIP text encoder model to disk in SafeTensors format. It is designed for advanced model merging workflows and automatically separates the CLIP model into its component parts (such as CLIP-L, CLIP-G, or T5XXL) based on the model's internal structure, saving each component as a separate file.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model to be saved. | CLIP | Yes | - |
| `filename_prefix` | The prefix path and filename for the saved file(s). The node will append a component suffix (e.g., `_clip_l`, `_clip_g`) and a counter to create unique filenames (default: `clip/ComfyUI`). | STRING | Yes | - |
| `prompt` | The workflow prompt information, saved as metadata in the output file. This parameter is hidden in the UI. | PROMPT | No | - |
| `extra_pnginfo` | Additional metadata, saved as key-value pairs in the output file. This parameter is hidden in the UI. | EXTRA\_PNGINFO | No | - |

## Outputs

This node has no output connections. It saves the processed files directly to the `ComfyUI/output/` directory. The saved files include metadata (the format is set to "pt", plus the workflow prompt and any extra PNG info) unless ComfyUI is started with the `--disable-metadata` argument.

### Saved File Details

The node analyzes the CLIP model's state dictionary and saves separate SafeTensors files for each detected component. The component is identified by the prefix of its parameter keys. The following prefixes are checked:

* `clip_l.` (CLIP-L text encoder)
* `clip_g.` (CLIP-G text encoder)
* `clip_h.` (CLIP-H text encoder)
* `t5xxl.` (T5-XXL text encoder)
* `pile_t5xl.` (Pile-T5-XL text encoder)
* `mt5xl.` (mT5-XL text encoder)
* `umt5xxl.` (UMT5-XXL text encoder)
* `t5base.` (T5-Base text encoder)
* `gemma2_2b.` (Gemma 2 2B text encoder)
* `llama.` (LLaMA text encoder)
* `hydit_clip.` (Hydit CLIP text encoder)
* Empty prefix (other CLIP components)

For each detected component, the node creates a file with the name `{filename_prefix}_{counter:05}_.safetensors`, where the component prefix is appended to the filename prefix (e.g., `clip/ComfyUI_clip_l_00001_.safetensors`). The `transformer.` prefix is removed from parameter keys during saving.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPSave/en.md)

***

**Source fingerprint (SHA-256):** `4ab9171e4245b10f738f78bac8a5b564c0957dde352e207ec3f9865e4fac0cab`


# CLIPVisionLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipVisionLoader

This node automatically detects models located in the ComfyUI/models/clipvision folder, as well as any additional model paths configured in the extramodelpaths.yaml file.

This node automatically detects models located in the `ComfyUI/models/clip_vision` folder, as well as any additional model paths configured in the `extra_model_paths.yaml` file. If you add models after starting ComfyUI, please **refresh the ComfyUI interface** to ensure the latest model files are listed.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `clip_name` | Lists all supported model files in the `ComfyUI/models/clip_vision` folder. | COMBO\[STRING] |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `clip_vision` | Loaded CLIP Vision model, ready for encoding images or other vision-related tasks. | CLIP\_VISION |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPVisionLoader/en.md)


# ConditioningLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningLoader

This node loads a conditioning that was previously saved with the Save Conditioning node, or any safetensors file that contains a conditioning tensor, from the embeddings folder.

This node loads a conditioning that was previously saved with the Save Conditioning node, or any safetensors file that contains a `conditioning` tensor, from the embeddings folder. It also restores any extra options and numbered list values stored alongside the conditioning.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `conditioning_name` | The file to load from the embeddings folder. The list of choices is built from the files currently available in that folder. | COMBO | Yes | All files in the embeddings folder |

**Note:** The selected file must contain a `conditioning` tensor. Any additional keys stored in the file are restored: numbered keys (for example `key.0`, `key.1`) are grouped back into ordered lists, and other keys are restored as plain options. Extra options are read from the file's `conditioning_options` metadata when present.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CONDITIONING` | The conditioning loaded from the file, together with the restored options. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningLoader/en.md)

***

**Source fingerprint (SHA-256):** `08fc58bcaa2309fcf03d4e4cc634b930aaf6ccf8097181fd3d45924abda144eb`


# ContextWindowsManual - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ContextWindowsManual

The Context Windows (Manual) node allows you to manually configure context windows for a model during sampling, creating overlapping context segments with a specified length, overl

The Context Windows (Manual) node allows you to manually configure context windows for a model during sampling, creating overlapping context segments with a specified length, overlap, and scheduling pattern so data is processed in manageable chunks while maintaining continuity between segments. It provides advanced options for controlling how context windows are applied, including noise shuffling, conditioning retention, and causal window fixes. This node is experimental.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply context windows to during sampling. | MODEL | Yes | - |
| `context_length` | The length of the context window (default: 16). | INT | Yes | 1+ |
| `context_overlap` | The overlap of the context window (default: 4). | INT | Yes | 0+ |
| `context_schedule` | Step-dependent scheduling algorithm for context windows (default: STATIC\_STANDARD). | COMBO | Yes | `STATIC_STANDARD`<br />`UNIFORM_STANDARD`<br />`UNIFORM_LOOPED`<br />`BATCHED` |
| `context_stride` | The stride of the context window; only applicable to uniform schedules (default: 1). | INT | Yes | 1+ |
| `closed_loop` | Whether to close the context window loop; only applicable to looped schedules (default: False). | BOOLEAN | Yes | - |
| `fuse_method` | The method to use to fuse the context windows (default: PYRAMID). | COMBO | Yes | Static fuse methods (see `ContextFuseMethods.LIST_STATIC`) |
| `dim` | The dimension to apply the context windows to (default: 0). | INT | Yes | 0-5 |
| `freenoise` | Whether to apply FreeNoise noise shuffling, improves window blending (default: False). | BOOLEAN | Yes | - |
| `cond_retain_index_list` | List of latent indices to retain in the conditioning tensors for each window. For concat-style I2V models (e.g. Wan I2V, HunyuanVideo I2V, Cosmos I2V, SVD) the encoded start image lives in the c\_concat conditioning channels; setting this to '0' will retain that start image content at sub-pos 0 of every window (default: ""). | STRING | No | - |
| `split_conds_to_windows` | Whether to split multiple conditionings (created by ConditionCombine) to each window based on region index (default: False). | BOOLEAN | No | - |
| `latent_retain_index_list` | List of latent indices to retain in the noise latent itself for each window. Use for workflows where reference content (e.g. a start image) lives directly in the noise latent rather than in separate conditioning channels (e.g. inplace-style I2V like LTXV, AnimateDiff). Independent of cond\_retain\_index\_list (default: ""). | STRING | No | - |
| `causal_window_fix` | Whether to add a causal fix frame to non-0-indexed context windows (default: True). | BOOLEAN | No | - |

**Parameter Constraints:**

* `context_stride` is only used when a uniform schedule is selected (`UNIFORM_STANDARD` or `UNIFORM_LOOPED`).
* `closed_loop` is only applicable to looped schedules (`UNIFORM_LOOPED`).
* `dim` must be between 0 and 5 inclusive.
* `cond_retain_index_list` and `latent_retain_index_list` expect a comma-separated list of integer indices as a string (e.g., "0,1,2").
* `latent_retain_index_list` is independent of `cond_retain_index_list`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The model with context windows applied during sampling. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ContextWindowsManual/en.md)

***

**Source fingerprint (SHA-256):** `39dc39ece3d3c10c13ca8c4b85af4fbbebbcaba8a019145a6d4727c3df7b302b`


# DiffControlNetLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DiffControlNetLoader

This node will detect models located in the ComfyUI/models/controlnet folder, and it will also read models from additional paths configured in the extramodelpaths.yaml file.

This node will detect models located in the `ComfyUI/models/controlnet` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The DiffControlNetLoader node is designed for loading differential control networks, which are specialized models that can modify the behavior of another model based on control net specifications. This node allows for the dynamic adjustment of model behaviors by applying differential control nets, facilitating the creation of customized model outputs.

## Inputs

| Field | Description | Comfy dtype |
| - | - | - |
| `model` | The base model to which the differential control net will be applied, allowing for customization of the model's behavior. | `MODEL` |
| `control_net_name` | Identifies the specific differential control net to be loaded and applied to the base model for modifying its behavior. | `COMBO[STRING]` |

## Outputs

| Field | Description | Comfy dtype |
| - | - | - |
| `control_net` | A differential control net that has been loaded and is ready to be applied to a base model for behavior modification. | `CONTROL_NET` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DiffControlNetLoader/en.md)


# DiffusersLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DiffusersLoader

The DiffusersLoader node loads pre-trained models saved in the diffusers format.

The DiffusersLoader node loads pre-trained models saved in the diffusers format. It searches the configured `diffusers` folders for directories that contain a `model_index.json` file, lets you select one, and loads it as the MODEL, CLIP, and VAE components used in the pipeline. This node is deprecated, but remains available for compatibility with Hugging Face diffusers models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_path` | The path to the diffusers model directory to load. The node automatically scans the configured diffusers folders (including linked subfolders) for directories containing a `model_index.json` file and lists the available options. The selected path is validated before loading; an invalid or missing model raises an error. | COMBO | Yes | Auto-populated list of folders containing `model_index.json`<br />(relative paths inside the configured `diffusers` folders) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The loaded model component from the diffusers format. | MODEL |
| `CLIP` | The loaded CLIP model component from the diffusers format. | CLIP |
| `VAE` | The loaded VAE (Variational Autoencoder) component from the diffusers format. | VAE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DiffusersLoader/en.md)

***

**Source fingerprint (SHA-256):** `75238342d05eac7528f981a2d4544accb6053891cd078a77751cc838054225d4`


# DualCLIPLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DualCLIPLoader

The DualCLIPLoader node is designed for loading two CLIP models simultaneously, facilitating operations that require the integration or comparison of features from both models.

The DualCLIPLoader node is designed for loading two CLIP models simultaneously, facilitating operations that require the integration or comparison of features from both models.

This node will detect models located in the `ComfyUI/models/text_encoders` folder.

## Inputs

| Parameter | Description | Comfy dtype |
| - | - | - |
| `clip_name1` | Specifies the name of the first CLIP model to be loaded. This parameter is crucial for identifying and retrieving the correct model from a predefined list of available CLIP models. | COMBO\[STRING] |
| `clip_name2` | Specifies the name of the second CLIP model to be loaded. This parameter enables the loading of a second distinct CLIP model for comparative or integrative analysis alongside the first model. | COMBO\[STRING] |
| `type` | Choose from "sdxl", "sd3", "flux" to adapt to different models. | `option` |

* The order of loading does not affect the output effect

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `clip` | The output is a combined CLIP model that integrates the features or functionalities of the two specified CLIP models. | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DualCLIPLoader/en.md)


# Epsilon Scaling - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Epsilon Scaling

This node implements the Epsilon Scaling method from the research paper "Elucidating the Exposure Bias in Diffusion Models" (arxiv.org/2308.15321v6).

This node implements the Epsilon Scaling method from the research paper "Elucidating the Exposure Bias in Diffusion Models" (arxiv.org/2308.15321v6). It works by scaling the predicted noise during the sampling process to help reduce exposure bias, which can lead to improved quality in the generated images. This implementation uses the "uniform schedule" recommended by the paper for its practicality and effectiveness.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to which the epsilon scaling patch will be applied. | MODEL | Yes | - |
| `scaling_factor` | The factor by which the predicted noise is scaled. A value greater than 1.0 reduces the noise, while a value less than 1.0 increases it (default: 1.005). This is an advanced parameter. | FLOAT | No | 0.5 - 1.5 (step: 0.001) |

Note: If `scaling_factor` is set to 0, the node automatically replaces it with a very small value (1e-9) to prevent division by zero. The UI's minimum value of 0.5 normally prevents this from happening.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | A patched version of the input model with the epsilon scaling function applied to its sampling process. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! \[Edit on GitHub]\([https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui\_embedded\_docs/docs/Epsilon](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Epsilon) Scaling/en.md)

***

**Source fingerprint (SHA-256):** `8d258c7bb853940922402f1009d777bfc71e88704fd2f615f569c214ddbeac64`


# FrameInterpolationModelLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FrameInterpolationModelLoader

This node loads a frame interpolation model file and prepares it for use in the workflow.

This node loads a frame interpolation model file and prepares it for use in the workflow. It automatically detects whether the file is a FILM or RIFE model and configures the model for the available hardware.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | Select a frame interpolation model to load. Models must be placed in the 'frame\_interpolation' folder. | COMBO | Yes | List of model files in the `frame_interpolation` folder |

Note: The node supports FILM and RIFE model formats. If the selected file is not a recognized format, an error is raised.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `FRAME_INTERPOLATION_MODEL` | The loaded and configured frame interpolation model, ready for use in other nodes. | INTERP\_MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FrameInterpolationModelLoader/en.md)

***

**Source fingerprint (SHA-256):** `21f470ee2852dbd1b332ac4a506eaa20dc8578c04b63c4fe1a072878b57beaba`


# FreeU - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FreeU

The FreeU node applies frequency-domain modifications to a model's output blocks to enhance image generation quality.

The FreeU node applies frequency-domain modifications to a model's output blocks to enhance image generation quality. It works by scaling different channel groups and applying Fourier filtering to specific feature maps, allowing for fine-tuned control over the model's behavior during the generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply FreeU modifications to | MODEL | Yes | - |
| `b1` | Backbone scaling factor applied to feature maps with model\_channels × 4 channels (default: 1.1). Marked as an advanced setting. | FLOAT | Yes | 0.0 - 10.0 |
| `b2` | Backbone scaling factor applied to feature maps with model\_channels × 2 channels (default: 1.2). Marked as an advanced setting. | FLOAT | Yes | 0.0 - 10.0 |
| `s1` | Skip connection scaling factor applied to feature maps with model\_channels × 4 channels (default: 0.9). Marked as an advanced setting. | FLOAT | Yes | 0.0 - 10.0 |
| `s2` | Skip connection scaling factor applied to feature maps with model\_channels × 2 channels (default: 0.2). Marked as an advanced setting. | FLOAT | Yes | 0.0 - 10.0 |

Note: FreeU adjustments are applied only to feature maps whose channel count equals model\_channels × 4 (using `b1` and `s1`) or model\_channels × 2 (using `b2` and `s2`). The Fourier filter scales only the central low-frequency region (threshold of 1) of the skip connection feature maps; all other frequency components remain unchanged. All four scaling parameters accept values between 0.0 and 10.0 in steps of 0.01.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with FreeU patches applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FreeU/en.md)

***

**Source fingerprint (SHA-256):** `7f7bd34964218ed16c9e58caa446d0c1e69f116607334df4a114cdc4adaf047f`


# FreeU_V2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FreeU_V2

FreeUV2 enhances image generation quality by applying frequency-based modifications to a diffusion model's U-Net architecture.

FreeU\_V2 enhances image generation quality by applying frequency-based modifications to a diffusion model's U-Net architecture. It uses configurable scaling factors to adjust feature channels in different blocks, improving output without requiring additional training. The node works by patching the model's output blocks and filtering high-frequency components of the hidden states.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to apply FreeU enhancement to | MODEL | Yes | - |
| `b1` | Backbone feature scaling factor for the first block (default: 1.3) | FLOAT | Yes | 0.0 - 10.0 |
| `b2` | Backbone feature scaling factor for the second block (default: 1.4) | FLOAT | Yes | 0.0 - 10.0 |
| `s1` | Skip feature scaling factor for the first block (default: 0.9) | FLOAT | Yes | 0.0 - 10.0 |
| `s2` | Skip feature scaling factor for the second block (default: 0.2) | FLOAT | Yes | 0.0 - 10.0 |

Note: `b1`, `b2`, `s1`, and `s2` are advanced parameters hidden by default in the node's UI. They can be set in steps of 0.01 within the 0.0 - 10.0 range. `b1` and `s1` control the U-Net block with the most channels (four times the model's base channel count), while `b2` and `s2` control the block with half as many channels (twice the base channel count).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The enhanced diffusion model with FreeU modifications applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FreeU_V2/en.md)

***

**Source fingerprint (SHA-256):** `4cef2af9b04164a8ead25bea9c9bb3311be9224f2539a5cc6edbe97ad8465d65`


# GLIGENLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GLIGENLoader

This node will detect models located in the ComfyUI/models/gligen folder, and it will also read models from additional paths configured in the extramodelpaths.yaml file.

This node will detect models located in the `ComfyUI/models/gligen` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The `GLIGENLoader` node is designed for loading GLIGEN models, which are specialized generative models. It facilitates the process of retrieving and initializing these models from specified paths, making them ready for further generative tasks.

## Inputs

| Field | Description | Comfy dtype |
| - | - | - |
| `gligen_name` | The name of the GLIGEN model to be loaded, specifying which model file to retrieve and load, crucial for the initialization of the GLIGEN model. | `COMBO[STRING]` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `gligen` | The loaded GLIGEN model, ready for use in generative tasks, representing the fully initialized model loaded from the specified path. | `GLIGEN` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GLIGENLoader/en.md)


# HiDreamO1PatchSeamSmoothing - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HiDreamO1PatchSeamSmoothing

This node reduces visible seams in images generated by the HiDream-O1 model by averaging the model's output across multiple shifted patch-grid positions during the later part of th

This node reduces visible seams in images generated by the HiDream-O1 model by averaging the model's output across multiple shifted patch-grid positions during the later part of the sampling process. It runs the model several times with slightly different image alignments and blends the results together, which helps cancel out the grid-like artifacts that can appear at patch boundaries.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply seam smoothing to. | MODEL | Yes | - |
| `start_percent` | Sampling progress (0=start, 1=end) at which the blend turns ON. default: 0.8 | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `end_percent` | Sampling progress at which the blend turns OFF. default: 1.0 | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `pattern` | Shift layout. `single_shift`: one pass at the natural patch grid + others offset. `symmetric`: all passes off-grid, shifts split around origin. default: "single\_shift" | COMBO | Yes | `"single_shift"`<br />`"symmetric"` |
| `passes` | Number of passes per gated step. `2`/`4` = fixed. `ramp_*`: pass count increases as sampling approaches end (more smoothing where seams are most visible). default: "2" | COMBO | Yes | `"2"`<br />`"4"`<br />`"ramp_2_4"`<br />`"ramp_2_4_8"` |
| `blend` | `average`: equal-weight mean. `window`: Hann-windowed weighting favoring each pass away from its patch boundaries. `median`: per-pixel median, rejects wraparound-outlier passes. default: "average" | COMBO | Yes | `"average"`<br />`"window"`<br />`"median"` |
| `strength` | Interpolation between the natural-grid prediction (0) and the averaged result (1). default: 1.0 | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |

**Note on Parameter Constraints:**

* The smoothing effect is not applied if `strength` is 0.0 or less, or if `end_percent` is less than or equal to `start_percent`. In those cases the node returns the model unchanged.
* The `passes` parameter's ramp options (`ramp_2_4`, `ramp_2_4_8`) are only meaningful when `end_percent` is greater than `start_percent`, because the number of passes increases as sampling progresses through that range.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with the seam smoothing wrapper applied. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HiDreamO1PatchSeamSmoothing/en.md)

***

**Source fingerprint (SHA-256):** `02a2256fbf1868cc033a00f15066e9a896a7685ecdca0564ceec5b5b618b6a3c`


# HyperTile - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HyperTile

HyperTile applies a tiling technique to the attention mechanism inside diffusion models to reduce memory usage during image generation.

HyperTile applies a tiling technique to the attention mechanism inside diffusion models to reduce memory usage during image generation. It splits the latent space into smaller tiles, processes the attention for each tile separately, and then reassembles the results. This makes it possible to work with larger image sizes without running out of memory.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to apply the HyperTile optimization to | MODEL | Yes | - |
| `tile_size` | The target tile size for processing (default: 256). Internally, the value is clamped to a minimum of 32 and then divided by 8 to obtain the effective tile size. | INT | Yes | 1 - 2048 |
| `swap_size` | Controls how the tiles are rearranged during processing to improve efficiency. Larger values allow more variation in tile sizes (default: 2) | INT | Yes | 1 - 128 |
| `max_depth` | The maximum depth level (resolution scale) to apply tiling. A value of 0 applies tiling only at the highest resolution (default: 0) | INT | Yes | 0 - 10 |
| `scale_depth` | When enabled, the tile size is scaled proportionally at deeper depth levels. This can help maintain quality at lower resolutions (default: False) | BOOLEAN | Yes | True / False |

Note: `tile_size`, `swap_size`, `max_depth`, and `scale_depth` are marked as advanced inputs, so they are only shown when advanced options are enabled in the interface.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with HyperTile optimization applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HyperTile/en.md)

***

**Source fingerprint (SHA-256):** `fb2fa29a403b6b7de7d5263240cc51a74126078457a3ff9ea63aeded45b9b74a`


# HypernetworkLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HypernetworkLoader

This node will detect models located in the ComfyUI/models/hypernetworks folder, and it will also read models from additional paths configured in the extramodelpaths.yaml file.

This node will detect models located in the `ComfyUI/models/hypernetworks` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The HypernetworkLoader node is designed to enhance or modify the capabilities of a given model by applying a hypernetwork. It loads a specified hypernetwork and applies it to the model, potentially altering its behavior or performance based on the strength parameter. This process allows for dynamic adjustments to the model's architecture or parameters, enabling more flexible and adaptive AI systems.

## Inputs

| Field | Description | Comfy dtype |
| - | - | - |
| `model` | The base model to which the hypernetwork will be applied, determining the architecture to be enhanced or modified. | `MODEL` |
| `hypernetwork_name` | The name of the hypernetwork to be loaded and applied to the model, impacting the model's modified behavior or performance. | `COMBO[STRING]` |
| `strength` | A scalar adjusting the intensity of the hypernetwork's effect on the model, allowing fine-tuning of the alterations. | `FLOAT` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `model` | The modified model after the hypernetwork has been applied, showcasing the impact of the hypernetwork on the original model. | `MODEL` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HypernetworkLoader/en.md)


# ImageOnlyCheckpointLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageOnlyCheckpointLoader

This node will detect models located in the ComfyUI/models/checkpoints folder, and it will also read models from additional paths configured in the extramodelpaths.yaml file.

This node will detect models located in the `ComfyUI/models/checkpoints` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

This node specializes in loading checkpoints specifically for image-based models within video generation workflows. It efficiently retrieves and configures the necessary components from a given checkpoint, focusing on image-related aspects of the model.

## Inputs

| Field | Description | Data Type |
| - | - | - |
| `ckpt_name` | Specifies the name of the checkpoint to load, crucial for identifying and retrieving the correct checkpoint file from a predefined list. | COMBO\[STRING] |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `model` | Returns the main model loaded from the checkpoint, configured for image processing within video generation contexts. | MODEL |
| `clip_vision` | Provides the CLIP vision component from the checkpoint, tailored for image understanding and feature extraction. | `CLIP_VISION` |
| `vae` | Delivers the Variational Autoencoder (VAE) component, essential for image manipulation and generation tasks. | VAE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageOnlyCheckpointLoader/en.md)


# ImageOnlyCheckpointSave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageOnlyCheckpointSave

This node saves a checkpoint file that bundles a model together with its CLIP vision encoder and VAE.

This node saves a checkpoint file that bundles a model together with its CLIP vision encoder and VAE. The file is written in safetensors format to the output directory, using the given filename prefix, so the image-related components of a model can be stored as a single checkpoint.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to be saved in the checkpoint | MODEL | Yes | - |
| `clip_vision` | The CLIP vision encoder to be saved in the checkpoint | CLIP\_VISION | Yes | - |
| `vae` | The VAE (Variational Autoencoder) to be saved in the checkpoint | VAE | Yes | - |
| `filename_prefix` | The prefix for the output filename (default: "checkpoints/ComfyUI") | STRING | Yes | - |
| `prompt` | Hidden parameter that receives the workflow prompt data | PROMPT | No | - |
| `extra_pnginfo` | Hidden parameter that receives additional PNG metadata | EXTRA\_PNGINFO | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| - | This node does not return any outputs | - |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageOnlyCheckpointSave/en.md)

***

**Source fingerprint (SHA-256):** `8ff4b3a78d8da523eaa5f784f847e954ba73b4d6037e748dcce592b447fcdee9`


# LTXAVTextEncoderLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXAVTextEncoderLoader

This node loads a specialized text encoder for the LTXV audio model.

This node loads a specialized text encoder for the LTXV audio model. It combines a text encoder file with a checkpoint file to create a CLIP model used for text conditioning in audio generation. Per the node's description, the text encoder should be a Gemma 3 12B or a matching Gemma 4 model.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text_encoder` | The filename of the LTXV text encoder model to load. The available options are loaded from the `text_encoders` folder. | COMBO | Yes | Multiple options available |
| `ckpt_name` | The filename of the checkpoint to load. The available options are loaded from the `checkpoints` folder. | COMBO | Yes | Multiple options available |
| `device` | Specifies the device to load the model onto. Use `"cpu"` to force loading onto the CPU. The default behavior (`"default"`) uses the system's automatic device placement (default: `"default"`). This is an advanced parameter. | COMBO | No | `"default"`<br />`"cpu"` |

**Note:** The `text_encoder` and `ckpt_name` parameters work together. The node loads both specified files to create a single, functional CLIP model. The files must be compatible with the LTXV architecture, and the text encoder should be a Gemma 3 12B or matching Gemma 4 model.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `clip` | The loaded LTXV CLIP model, ready to be used for encoding text prompts for audio generation. | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXAVTextEncoderLoader/en.md)

***

**Source fingerprint (SHA-256):** `1f3df2c1791203ba849a87897de14052e0cb8370100dbca19df4cf30169a0a2a`


# LTXVAudioVAELoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVAudioVAELoader

The LTXV Audio VAE Loader node loads a pre-trained Audio Variational Autoencoder (VAE) model from a checkpoint file.

The LTXV Audio VAE Loader node loads a pre-trained Audio Variational Autoencoder (VAE) model from a checkpoint file. It reads the specified checkpoint, keeps the audio VAE and vocoder weights, and prepares the model for use in audio generation or processing workflows within ComfyUI.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `ckpt_name` | Audio VAE checkpoint to load. This is a dropdown list populated with all the files found in your ComfyUI `checkpoints` directory. | COMBO | Yes | All files in the `checkpoints` folder. The list is generated at runtime. |

The selected file must be a valid LTXV audio VAE checkpoint. The node keeps only the audio VAE and vocoder weights from the file and raises an error if the loaded model is not a valid VAE.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `Audio VAE` | The loaded Audio Variational Autoencoder model, ready to be connected to other audio processing nodes. | VAE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVAudioVAELoader/en.md)

***

**Source fingerprint (SHA-256):** `c91956645a9de0b8f56191f6c0c6bef43f13724ba59078ec9a885168bf2650e8`


# LTXVContextWindows - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVContextWindows

This node sets context windows for LTXV-like models during sampling.

This node sets context windows for LTXV-like models during sampling. It divides generation into overlapping windows to help manage memory usage and improve temporal coherence.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply context windows to during sampling. | MODEL | Yes | - |
| `context_length` | The length of the context window in real frames. Must be 8\*n + 1. (default: 145) | INT | Yes | Minimum: 1<br />Maximum: nodes.MAX\_RESOLUTION<br />Step: 8 |
| `context_overlap` | The overlap of the context window in real frames. (default: 40) | INT | Yes | Minimum: 0<br />Step: 8 |
| `context_schedule` | Step-dependent scheduling algorithm for context windows. (default: "UNIFORM\_STANDARD") | COMBO | Yes | `"STATIC_STANDARD"`<br />`"UNIFORM_STANDARD"`<br />`"UNIFORM_LOOPED"`<br />`"BATCHED"` |
| `context_stride` | The stride of the context window; only applicable to uniform schedules. (default: 1) | INT | Yes | Minimum: 1 |
| `closed_loop` | Whether to close the context window loop; only applicable to looped schedules. (default: False) | BOOLEAN | Yes | True<br />False |
| `fuse_method` | The method to use to fuse the context windows. Available options are defined by `ContextFuseMethods.LIST_STATIC`. (default: "PYRAMID") | COMBO | Yes | Defined by `ContextFuseMethods.LIST_STATIC` |
| `freenoise` | Whether to apply FreeNoise noise shuffling, improves window blending. (default: True) | BOOLEAN | Yes | True<br />False |
| `retain_first_frame` | Retain the first latent frame in every context window (may help retain initial reference). (default: False) | BOOLEAN | Yes | True<br />False |
| `split_conds_to_windows` | Whether to split multiple conditionings (created by ConditionCombine) to each window based on region index. (default: False) | BOOLEAN | Yes | True<br />False |

**Note:** The `context_length` value is provided in real frames and is internally converted to latent frames using the formula `((context_length - 1) // 8) + 1`, with a minimum of 1. The `context_overlap` value is also provided in real frames and is converted to latent frames using integer division by 8, with a minimum of 0. The tooltip for `context_length` indicates it must follow the pattern 8\*n + 1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The model with context windows applied for sampling. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVContextWindows/en.md)

***

**Source fingerprint (SHA-256):** `148649d0a938e08c932a163f5d7614332626fba37b8f79db7f92bbcf422e692f`


# LatentUpscaleModelLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentUpscaleModelLoader

The LatentUpscaleModelLoader node loads a model specialized in upscaling latent representations from a file stored in ComfyUI's latentupscalemodels folder.

The LatentUpscaleModelLoader node loads a model specialized in upscaling latent representations from a file stored in ComfyUI's `latent_upscale_models` folder. It automatically detects the model architecture from the file contents (Hunyuan Video 720p, Hunyuan Video 1080p, or a Latent Upsampler) and configures the matching internal model, so the result is ready to be used by other nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The name of the latent upscale model file to load. The available options are dynamically populated from the files present in ComfyUI's `latent_upscale_models` directory. | COMBO | Yes | All files in the `latent_upscale_models` folder |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The loaded latent upscale model, configured and ready for use. Depending on the detected file contents, this is a 720p Hunyuan Video upscaler, a 1080p Hunyuan Video upscaler, or a wrapped Latent Upsampler model. | LATENT\_UPSCALE\_MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentUpscaleModelLoader/en.md)

***

**Source fingerprint (SHA-256):** `7e23214b1b1fc11be84910a5a209c7990a5199120cb0e6b6c61302a442dcf153`


# LoadBackgroundRemovalModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadBackgroundRemovalModel

Loads a background removal model from a file.

Loads a background removal model from a file. This node prepares the model so it can be used by other nodes to remove backgrounds from images.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `bg_removal_name` | The model used to remove backgrounds from images. Select from the list of available background removal model files. | COMBO | Yes | List of available model files (sorted alphabetically) |

Note: If the selected file does not contain a valid background removal model, the node raises a RuntimeError.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `bg_model` | The loaded background removal model, ready to be used by other nodes for processing images. | BACKGROUND\_REMOVAL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadBackgroundRemovalModel/en.md)

***

**Source fingerprint (SHA-256):** `76f6536eae849a8b63f46f11c6afcf8c89774e4e89a5976e051253acc6108bcc`


# LoadDA3Model - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadDA3Model

The Load Depth Anything 3 node loads a Depth Anything 3 model from a file, preparing it for depth estimation tasks.

The **Load Depth Anything 3** node loads a Depth Anything 3 model from a file, preparing it for depth estimation tasks. You can select the model file and optionally choose the numerical precision (data type) for the model's weights.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The name of the Depth Anything 3 model file to load. | STRING | Yes | List of available model files in the `geometry_estimation` folder |
| `weight_dtype` | The numerical precision (data type) for the model weights. "default" uses the model's original precision, "fp16" uses 16-bit floating point, "bf16" uses bfloat16, and "fp32" uses 32-bit floating point. (default: "default") | STRING | No | `"default"`<br />`"fp16"`<br />`"bf16"`<br />`"fp32"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `DA3_MODEL` | The loaded Depth Anything 3 model, ready for use in depth estimation workflows. | DA3\_MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadDA3Model/en.md)

***

**Source fingerprint (SHA-256):** `b1b3f4075cd9172bc1f274848b9300bca20d3cbd53b23d3c4a9f0986b36e409e`


# LoadMediaPipeFaceLandmarker - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadMediaPipeFaceLandmarker

This node loads a MediaPipe Face Landmarker v2 model, which detects faces and facial landmarks (such as eyes, nose, and mouth) in images.

This node loads a MediaPipe Face Landmarker v2 model, which detects faces and facial landmarks (such as eyes, nose, and mouth) in images. The loaded model bundles two detection variants (short-range and full-range) together with shared mesh data, blendshapes, and canonical geometry used for facial analysis.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | Face detection model from models/detection/. | COMBO | Yes | List of available model filenames found in the `models/detection/` directory |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `FACE_DETECTION_MODEL` | A loaded FaceLandmarker model object containing both detection variants (short/full), connection sets for facial topology, canonical data, and model patchers for GPU management. | FACE\_DETECTION\_MODEL |

**Note:** The output is a complex object that can be used by other nodes for face detection and landmark extraction tasks. It contains two detection variants: "short" for close-range detection and "full" for full-range detection.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadMediaPipeFaceLandmarker/en.md)

***

**Source fingerprint (SHA-256):** `33dda845b572ccffc1bd4b64fb9c338ce4313783b092fe311d89741a211f18c9`


# LoadMoGeModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadMoGeModel

Loads a MoGe (Monocular Geometry) model from a file and prepares it for use in geometry estimation tasks.

Loads a MoGe (Monocular Geometry) model from a file and prepares it for use in geometry estimation tasks. The node reads the selected model file from the `geometry_estimation` folder and initializes the MoGe model with its stored weights.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The name of the MoGe model file to load. Select from the model files available in the `geometry_estimation` folder of your ComfyUI installation. | COMBO | Yes | List of available model files in the `geometry_estimation` folder |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MOGE_MODEL` | The loaded MoGe model instance, ready for use in geometry estimation workflows. | MOGE\_MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadMoGeModel/en.md)

***

**Source fingerprint (SHA-256):** `b5b55f94d3762852d5a1480c0b00d15da4e534adbeb544bf7c47da012e5a6353`


# LoraLoaderBypass - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraLoaderBypass

The LoraLoaderBypass node applies a LoRA (Low-Rank Adaptation) to a diffusion model and a CLIP model in a special "bypass" mode.

The LoraLoaderBypass node applies a LoRA (Low-Rank Adaptation) to a diffusion model and a CLIP model in a special "bypass" mode. Unlike a standard LoRA loader, this method does not permanently modify the base model's weights. Instead, it computes the result by adding the LoRA's contribution to the model's normal forward pass, which is useful for training or when working with models that have their weights offloaded.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model the LoRA will be applied to. | MODEL | Yes | - |
| `clip` | The CLIP model the LoRA will be applied to. | CLIP | Yes | - |
| `lora_name` | The name of the LoRA. Available LoRA files are loaded from the `loras` folder. | COMBO | Yes | List of available LoRA files |
| `strength_model` | How strongly to modify the diffusion model. This value can be negative (default: 1.0). | FLOAT | Yes | -100.0 to 100.0 (step: 0.01) |
| `strength_clip` | How strongly to modify the CLIP model. This value can be negative (default: 1.0). | FLOAT | Yes | -100.0 to 100.0 (step: 0.01) |

**Note:** If both `strength_model` and `strength_clip` are set to 0, the node returns the original, unmodified `model` and `clip` inputs without processing.

**Note:** The selected LoRA file is cached after it is first loaded. It is only re-read from disk when a different `lora_name` is chosen.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The modified diffusion model. | MODEL |
| `CLIP` | The modified CLIP model. | CLIP |

**Note:** This node is marked as experimental.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoraLoaderBypass/en.md)

***

**Source fingerprint (SHA-256):** `025f0638a6690a53b1a6c4548dac24fb7e7f26e04ff4b1c88d29b061430037a8`


# LoraLoaderBypassModelOnly - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraLoaderBypassModelOnly

This node applies a LoRA (Low-Rank Adaptation) to a model to modify its behavior, but only affects the model component itself.

This node applies a LoRA (Low-Rank Adaptation) to a model to modify its behavior, but only affects the model component itself. It loads a specified LoRA file and adjusts the model's weights by a given strength, leaving other components like the CLIP text encoder unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The base model to which the LoRA adjustments will be applied. | MODEL | Yes | - |
| `lora_name` | The name of the LoRA file to load and apply. The options are populated from the files in the `loras` directory. | STRING | Yes | (List of available LoRA files) |
| `strength_model` | The strength of the LoRA's effect on the model's weights. A positive value applies the LoRA, a negative value applies the inverse, and a value of 0 has no effect (default: 1.0). | FLOAT | Yes | -100.0 to 100.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with the LoRA adjustments applied to its weights. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoraLoaderBypassModelOnly/en.md)

***

**Source fingerprint (SHA-256):** `e0e1ad2d6481a1b9771d7eae833ffab0737a967d4af6e57b946d1b2223fe45bf`


# LoraModelLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraModelLoader

The LoraModelLoader node applies trained LoRA (Low-Rank Adaptation) weights to a diffusion model.

The LoraModelLoader node applies trained LoRA (Low-Rank Adaptation) weights to a diffusion model. It modifies the base model by loading LoRA weights from a trained LoRA model and adjusting their influence strength. This allows you to customize the behavior of diffusion models without retraining them from scratch, including a bypass mode that leaves the base model weights unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model the LoRA will be applied to. | MODEL | Yes | - |
| `lora` | The LoRA model to apply to the diffusion model. | LORA\_MODEL | Yes | - |
| `strength_model` | How strongly to modify the diffusion model. This value can be negative (default: 1.0). | FLOAT | Yes | -100.0 to 100.0 |
| `bypass` | When enabled, applies LoRA in bypass mode without modifying base model weights. Useful for training and when model weights are offloaded (default: False). | BOOLEAN | Yes | True or False |

**Note:** When `strength_model` is set to 0, the node returns the original model without applying any LoRA modifications.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified diffusion model with LoRA weights applied. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoraModelLoader/en.md)

***

**Source fingerprint (SHA-256):** `81eb2a9b0376fe7453f6e7e422414472e80a3d1b92bb6874b91df6de8aed0d9a`


# MiniMaxH3FunControlNetApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MiniMaxH3FunControlNetApply

This node applies a MiniMax H3 Fun ControlNet to a text-to-video model as a model patch.

This node applies a MiniMax H3 Fun ControlNet to a text-to-video model as a model patch. It can use an optional control video and an optional mask to steer generation, and it returns a patched copy of the model for further sampling. When the strength is set to 0, or when neither a control video nor a mask is provided, the input model is returned unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to which the MiniMax H3 Fun ControlNet patch is applied. | MODEL | Yes | N/A |
| `model_patch` | The MiniMax H3 Fun ControlNet patch whose control signals are injected into the model; it must be compatible with the given `model`. | MODEL\_PATCH | Yes | N/A |
| `vae` | VAE used to encode the control and source video frames into the latent space expected by the model. | VAE | Yes | N/A |
| `strength` | Overall strength of the ControlNet effect. When set to 0, the node does nothing and returns the input model unchanged. (default: 1.0) | FLOAT | Yes | min 0.0, max 10.0, step 0.01 |
| `start_percent` | Start of the sampling range, expressed as a percentage of the sampling schedule, during which the ControlNet is active. It is converted internally to the equivalent sigma value. This is an advanced setting. (default: 0.0) | FLOAT | Yes | min 0.0, max 1.0, step 0.001 |
| `end_percent` | End of the sampling range, expressed as a percentage of the sampling schedule, during which the ControlNet is active. It is converted internally to the equivalent sigma value. This is an advanced setting. (default: 1.0) | FLOAT | Yes | min 0.0, max 1.0, step 0.001 |
| `control_video` | Optional video frames used as the ControlNet visual hint. The frames are resized to match the generated video and encoded with the `vae`. | IMAGE | No | N/A |
| `mask` | 1 marks the regions to regenerate. Mask values above 0.5 are treated as marked regions. | MASK | No | N/A |
| `source_video` | Video behind the mask; only read when a mask is given. | IMAGE | No | N/A |

Note: For the patch to have an effect, `strength` must be greater than 0 and at least one of `control_video` or `mask` must be supplied. `source_video` is ignored unless `mask` is provided; if `mask` is given without `source_video`, the content behind the masked regions is treated as black. When both `control_video` and `mask` are provided, the control hint combines the control video features with the masked source content.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | A patched clone of the input model with the MiniMax H3 Fun ControlNet applied. If `strength` is 0, or no control video or mask is supplied, the original model is returned unchanged. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MiniMaxH3FunControlNetApply/en.md)

***

**Source fingerprint (SHA-256):** `e907fb8e5ae60663d1d10b315985695ee5d49397fef6bd76b0e723637457a74a`


# MiniMaxH3SigmaShift - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MiniMaxH3SigmaShift

Sets the video and audio flow shift values for a MiniMax H3 model.

Sets the video and audio flow shift values for a MiniMax H3 model. The video shift controls the sampler's sigma schedule, and both shift values are passed to the model's internal transformer, which uses them to derive the audio schedule from the shared base grid.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply the sigma shift patch to. The node clones the model, so the original remains unchanged. | MODEL | Yes | - |
| `shift_video` | The video flow shift value. It drives the sampler's sigma schedule. Default: 12.0. | FLOAT | Yes | 0.01 to 100.0 |
| `shift_audio` | The audio flow shift value. It is used by the model to derive the audio schedule. Default: 3.0. | FLOAT | Yes | 0.01 to 100.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The cloned model with the video and audio sigma shift settings applied. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MiniMaxH3SigmaShift/en.md)

***

**Source fingerprint (SHA-256):** `0f731585cc1a9c87a3e54341757c4cf4e490d1d4718ecf458bd2b9f4378af63f`


# ModelAttentionBackend - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelAttentionBackend

This node selects the dense attention implementation for a model, clones the model, applies the chosen backend, and returns the patched clone.

This node selects the dense attention implementation for a model, clones the model, applies the chosen backend, and returns the patched clone. When used with Block Sparse Attention, this backend is used whenever sparse attention is inactive or unsupported. If the selected backend is unavailable, the node automatically falls back to PyTorch attention.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to patch. | MODEL | Yes | |
| `attention` | The dense attention backend to apply. Comfy Kitchen attention uses quantized INT8 attention and is available only on Nvidia and AMD GPUs. Default: "pytorch attention". If the selected backend is unavailable, PyTorch attention is used as a fallback. | COMBO | Yes | "pytorch attention"<br />"comfy kitchen attention" |

Note: The "comfy kitchen attention" option is only listed when the Comfy Kitchen INT8 attention module is available in the current environment.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | A clone of the input model with the selected attention backend applied. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelAttentionBackend/en.md)

***

**Source fingerprint (SHA-256):** `4f6e4800c2a3bb09b47b7c8f0481e1b6de3070f57234e610df5d3ce60dfdb309`


# ModelMergeAdd - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeAdd

The ModelMergeAdd node is designed for merging two models by adding key patches from one model to another.

The ModelMergeAdd node is designed for merging two models by adding key patches from one model to another. This process involves cloning the first model and then applying patches from the second model, allowing for the combination of features or behaviors from both models.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model1` | The first model to be cloned and to which patches from the second model will be added. It serves as the base model for the merging process. | `MODEL` |
| `model2` | The second model from which key patches are extracted and added to the first model. It contributes additional features or behaviors to the merged model. | `MODEL` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The result of merging two models by adding key patches from the second model to the first. This merged model combines features or behaviors from both models. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeAdd/en.md)


# ModelMergeAuraflow - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeAuraflow

The ModelMergeAuraflow node blends two Auraflow models together by assigning a separate blending weight to each part of the model, from the initial layers down to the final output.

The ModelMergeAuraflow node blends two Auraflow models together by assigning a separate blending weight to each part of the model, from the initial layers down to the final output. Each weight controls how much of the second model is mixed into the first model at that specific component, giving precise control over the merge.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The first model to be merged | MODEL | Yes | - |
| `model2` | The second model to be merged | MODEL | Yes | - |
| `init_x_linear.` | Blending weight for the initial linear transformation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `positional_encoding` | Blending weight for positional encoding components (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `cond_seq_linear.` | Blending weight for conditional sequence linear layers (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `register_tokens` | Blending weight for token registration components (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `t_embedder.` | Blending weight for time embedding components (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `double_layers.0.` | Blending weight for double layer group 0 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `double_layers.1.` | Blending weight for double layer group 1 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `double_layers.2.` | Blending weight for double layer group 2 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `double_layers.3.` | Blending weight for double layer group 3 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.0.` | Blending weight for single layer 0 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.1.` | Blending weight for single layer 1 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.2.` | Blending weight for single layer 2 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.3.` | Blending weight for single layer 3 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.4.` | Blending weight for single layer 4 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.5.` | Blending weight for single layer 5 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.6.` | Blending weight for single layer 6 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.7.` | Blending weight for single layer 7 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.8.` | Blending weight for single layer 8 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.9.` | Blending weight for single layer 9 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.10.` | Blending weight for single layer 10 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.11.` | Blending weight for single layer 11 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.12.` | Blending weight for single layer 12 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.13.` | Blending weight for single layer 13 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.14.` | Blending weight for single layer 14 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.15.` | Blending weight for single layer 15 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.16.` | Blending weight for single layer 16 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.17.` | Blending weight for single layer 17 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.18.` | Blending weight for single layer 18 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.19.` | Blending weight for single layer 19 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.20.` | Blending weight for single layer 20 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.21.` | Blending weight for single layer 21 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.22.` | Blending weight for single layer 22 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.23.` | Blending weight for single layer 23 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.24.` | Blending weight for single layer 24 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.25.` | Blending weight for single layer 25 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.26.` | Blending weight for single layer 26 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.27.` | Blending weight for single layer 27 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.28.` | Blending weight for single layer 28 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.29.` | Blending weight for single layer 29 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.30.` | Blending weight for single layer 30 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `single_layers.31.` | Blending weight for single layer 31 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `modF.` | Blending weight for modF components (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `final_linear.` | Blending weight for final linear transformation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |

All blending weights are FLOAT values with a default of 1.0, a minimum of 0.0, a maximum of 1.0, and a step of 0.01.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining features from both input models according to the specified blending weights | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeAuraflow/en.md)

***

**Source fingerprint (SHA-256):** `e9d3d81b2a3f81b082f9dc9f662f4e51df66f1f077e2899a1fea9a7061c4a97b`


# ModelMergeBlocks - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeBlocks

ModelMergeBlocks is designed for advanced model merging operations, allowing for the integration of two models with customizable blending ratios for different parts of the models.

ModelMergeBlocks is designed for advanced model merging operations, allowing for the integration of two models with customizable blending ratios for different parts of the models. This node facilitates the creation of hybrid models by selectively merging components from two source models based on specified parameters.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model1` | The first model to be merged. It serves as the base model onto which patches from the second model are applied. | `MODEL` |
| `model2` | The second model from which patches are extracted and applied to the first model, based on the specified blending ratios. | `MODEL` |
| `input` | Specifies the blending ratio for the input layer of the models. It determines how much of the second model's input layer is merged into the first model. | `FLOAT` |
| `middle` | Defines the blending ratio for the middle layers of the models. This parameter controls the integration level of the models' middle layers. | `FLOAT` |
| `out` | Determines the blending ratio for the output layer of the models. It affects the final output by adjusting the contribution of the second model's output layer. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The resulting merged model, which is a hybrid of the two input models with patches applied according to the specified blending ratios. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeBlocks/en.md)


# ModelMergeCosmos14B - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeCosmos14B

The ModelMergeCosmos14B node merges two AI models using a block-based approach specifically designed for the Cosmos 14B model architecture.

The **ModelMergeCosmos14B** node merges two AI models using a block-based approach specifically designed for the Cosmos 14B model architecture. It allows you to blend different components of the models by adjusting weight values between 0.0 and 1.0 for each model block and embedding layer.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | First model to merge | MODEL | Yes | - |
| `model2` | Second model to merge | MODEL | Yes | - |
| `pos_embedder.` | Weight for the position embedder component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `extra_pos_embedder.` | Weight for the extra position embedder component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `x_embedder.` | Weight for the x embedder component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `t_embedder.` | Weight for the t embedder component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `affline_norm.` | Weight for the affine normalization component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block0.` | Weight for block 0 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block1.` | Weight for block 1 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block2.` | Weight for block 2 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block3.` | Weight for block 3 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block4.` | Weight for block 4 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block5.` | Weight for block 5 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block6.` | Weight for block 6 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block7.` | Weight for block 7 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block8.` | Weight for block 8 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block9.` | Weight for block 9 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block10.` | Weight for block 10 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block11.` | Weight for block 11 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block12.` | Weight for block 12 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block13.` | Weight for block 13 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block14.` | Weight for block 14 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block15.` | Weight for block 15 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block16.` | Weight for block 16 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block17.` | Weight for block 17 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block18.` | Weight for block 18 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block19.` | Weight for block 19 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block20.` | Weight for block 20 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block21.` | Weight for block 21 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block22.` | Weight for block 22 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block23.` | Weight for block 23 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block24.` | Weight for block 24 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block25.` | Weight for block 25 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block26.` | Weight for block 26 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block27.` | Weight for block 27 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block28.` | Weight for block 28 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block29.` | Weight for block 29 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block30.` | Weight for block 30 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block31.` | Weight for block 31 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block32.` | Weight for block 32 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block33.` | Weight for block 33 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block34.` | Weight for block 34 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.block35.` | Weight for block 35 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `final_layer.` | Weight for the final layer (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |

All weight parameters accept values from 0.0 to 1.0 in steps of 0.01, and every one of them defaults to 1.0. The block parameters cover 36 transformer blocks, numbered `blocks.block0.` through `blocks.block35.`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining features from both input models | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeCosmos14B/en.md)

***

**Source fingerprint (SHA-256):** `1d1e5dc176643f577723bb0bb9375748a392a6fafa5c9e5e78ef4c4d8289f77c`


# ModelMergeCosmos7B - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeCosmos7B

The ModelMergeCosmos7B node merges two AI models together using weighted blending of specific components.

The ModelMergeCosmos7B node merges two AI models together using weighted blending of specific components. It allows fine-grained control over how different parts of the models are combined by adjusting individual weights for position embeddings, transformer blocks, and final layers.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | First model to merge | MODEL | Yes | - |
| `model2` | Second model to merge | MODEL | Yes | - |
| `pos_embedder.` | Weight for position embedder component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `extra_pos_embedder.` | Weight for extra position embedder component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `x_embedder.` | Weight for x embedder component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `t_embedder.` | Weight for t embedder component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `affline_norm.` | Weight for affine normalization component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block0.` | Weight for transformer block 0 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block1.` | Weight for transformer block 1 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block2.` | Weight for transformer block 2 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block3.` | Weight for transformer block 3 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block4.` | Weight for transformer block 4 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block5.` | Weight for transformer block 5 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block6.` | Weight for transformer block 6 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block7.` | Weight for transformer block 7 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block8.` | Weight for transformer block 8 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block9.` | Weight for transformer block 9 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block10.` | Weight for transformer block 10 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block11.` | Weight for transformer block 11 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block12.` | Weight for transformer block 12 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block13.` | Weight for transformer block 13 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block14.` | Weight for transformer block 14 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block15.` | Weight for transformer block 15 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block16.` | Weight for transformer block 16 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block17.` | Weight for transformer block 17 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block18.` | Weight for transformer block 18 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block19.` | Weight for transformer block 19 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block20.` | Weight for transformer block 20 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block21.` | Weight for transformer block 21 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block22.` | Weight for transformer block 22 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block23.` | Weight for transformer block 23 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block24.` | Weight for transformer block 24 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block25.` | Weight for transformer block 25 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block26.` | Weight for transformer block 26 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.block27.` | Weight for transformer block 27 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `final_layer.` | Weight for final layer component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |

All weight parameters accept values from 0.0 to 1.0 in steps of 0.01 and default to 1.0.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining features from both input models | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeCosmos7B/en.md)

***

**Source fingerprint (SHA-256):** `2cc4dcaa3576c5383c630e233cef55dedc8d742c20197cc83f5832dc9e887dac`


# ModelMergeCosmosPredict2_14B - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeCosmosPredict2_14B

The ModelMergeCosmosPredict214B node combines two AI models into one by blending their matching internal components.

The ModelMergeCosmosPredict2\_14B node combines two AI models into one by blending their matching internal components. It lets you control how much of the second model is mixed into the first by adjusting a separate weight for each embedder, block, and the final layer.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The base model to merge with | MODEL | Yes | - |
| `model2` | The secondary model to merge into the base model | MODEL | Yes | - |
| `pos_embedder.` | Position embedder blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `x_embedder.` | Input embedder blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `t_embedder.` | Time embedder blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `t_embedding_norm.` | Time embedding normalization blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.0.` | Block 0 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.1.` | Block 1 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.2.` | Block 2 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.3.` | Block 3 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.4.` | Block 4 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.5.` | Block 5 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.6.` | Block 6 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.7.` | Block 7 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.8.` | Block 8 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.9.` | Block 9 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.10.` | Block 10 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.11.` | Block 11 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.12.` | Block 12 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.13.` | Block 13 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.14.` | Block 14 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.15.` | Block 15 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.16.` | Block 16 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.17.` | Block 17 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.18.` | Block 18 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.19.` | Block 19 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.20.` | Block 20 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.21.` | Block 21 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.22.` | Block 22 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.23.` | Block 23 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.24.` | Block 24 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.25.` | Block 25 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.26.` | Block 26 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.27.` | Block 27 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.28.` | Block 28 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.29.` | Block 29 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.30.` | Block 30 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.31.` | Block 31 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.32.` | Block 32 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.33.` | Block 33 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.34.` | Block 34 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.35.` | Block 35 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `final_layer.` | Final layer blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |

**Note:** All blending weight parameters accept values between 0.0 and 1.0 in steps of 0.01, where 0.0 means no contribution from model2 and 1.0 means full contribution from model2 for that specific component.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining features from both input models | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeCosmosPredict2_14B/en.md)

***

**Source fingerprint (SHA-256):** `a5f34deda62dc03f22613517e43996b908a8673dc5da10d8f1b7f6411ece2f0a`


# ModelMergeCosmosPredict2_2B - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeCosmosPredict2_2B

The ModelMergeCosmosPredict22B node merges two diffusion models using a block-based approach with fine-grained control over different model components.

The ModelMergeCosmosPredict2\_2B node merges two diffusion models using a block-based approach with fine-grained control over different model components. It allows you to blend specific parts of two models by adjusting interpolation weights for position embedders, time embedders, transformer blocks, and final layers. This provides precise control over how different architectural components from each model contribute to the final merged result.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The first model to merge | MODEL | Yes | - |
| `model2` | The second model to merge | MODEL | Yes | - |
| `pos_embedder.` | Position embedder interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `x_embedder.` | Input embedder interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `t_embedder.` | Time embedder interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `t_embedding_norm.` | Time embedding normalization interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.0.` | Transformer block 0 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.1.` | Transformer block 1 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.2.` | Transformer block 2 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.3.` | Transformer block 3 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.4.` | Transformer block 4 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.5.` | Transformer block 5 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.6.` | Transformer block 6 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.7.` | Transformer block 7 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.8.` | Transformer block 8 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.9.` | Transformer block 9 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.10.` | Transformer block 10 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.11.` | Transformer block 11 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.12.` | Transformer block 12 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.13.` | Transformer block 13 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.14.` | Transformer block 14 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.15.` | Transformer block 15 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.16.` | Transformer block 16 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.17.` | Transformer block 17 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.18.` | Transformer block 18 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.19.` | Transformer block 19 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.20.` | Transformer block 20 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.21.` | Transformer block 21 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.22.` | Transformer block 22 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.23.` | Transformer block 23 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.24.` | Transformer block 24 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.25.` | Transformer block 25 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.26.` | Transformer block 26 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.27.` | Transformer block 27 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `final_layer.` | Final layer interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining features from both input models | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeCosmosPredict2_2B/en.md)

***

**Source fingerprint (SHA-256):** `3586868201320ae9a326a08f6a9bd74511a5342bf8496e7efcb9f45cf4b7c55d`


# ModelMergeFlux1 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeFlux1

The ModelMergeFlux1 node merges two diffusion models by blending their components using weighted interpolation.

The ModelMergeFlux1 node merges two diffusion models by blending their components using weighted interpolation. It allows fine-grained control over how different parts of the models are combined, including image processing blocks, time embedding layers, guidance mechanisms, vector inputs, text encoders, and various transformer blocks. This enables creating hybrid models with customized characteristics from two source models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | First source model to merge | MODEL | Yes | - |
| `model2` | Second source model to merge | MODEL | Yes | - |
| `img_in.` | Image input interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `time_in.` | Time embedding interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `guidance_in` | Guidance mechanism interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `vector_in.` | Vector input interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `txt_in.` | Text encoder interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.0.` | Double block 0 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.1.` | Double block 1 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.2.` | Double block 2 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.3.` | Double block 3 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.4.` | Double block 4 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.5.` | Double block 5 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.6.` | Double block 6 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.7.` | Double block 7 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.8.` | Double block 8 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.9.` | Double block 9 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.10.` | Double block 10 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.11.` | Double block 11 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.12.` | Double block 12 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.13.` | Double block 13 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.14.` | Double block 14 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.15.` | Double block 15 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.16.` | Double block 16 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.17.` | Double block 17 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `double_blocks.18.` | Double block 18 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.0.` | Single block 0 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.1.` | Single block 1 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.2.` | Single block 2 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.3.` | Single block 3 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.4.` | Single block 4 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.5.` | Single block 5 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.6.` | Single block 6 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.7.` | Single block 7 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.8.` | Single block 8 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.9.` | Single block 9 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.10.` | Single block 10 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.11.` | Single block 11 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.12.` | Single block 12 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.13.` | Single block 13 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.14.` | Single block 14 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.15.` | Single block 15 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.16.` | Single block 16 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.17.` | Single block 17 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.18.` | Single block 18 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.19.` | Single block 19 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.20.` | Single block 20 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.21.` | Single block 21 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.22.` | Single block 22 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.23.` | Single block 23 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.24.` | Single block 24 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.25.` | Single block 25 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.26.` | Single block 26 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.27.` | Single block 27 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.28.` | Single block 28 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.29.` | Single block 29 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.30.` | Single block 30 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.31.` | Single block 31 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.32.` | Single block 32 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.33.` | Single block 33 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.34.` | Single block 34 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.35.` | Single block 35 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.36.` | Single block 36 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `single_blocks.37.` | Single block 37 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `final_layer.` | Final layer interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining characteristics from both input models | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeFlux1/en.md)

***

**Source fingerprint (SHA-256):** `4a1cc4dd2c253bbeb94144969e921af40a7f12a1ec23ed7c23da89107767dc26`


# ModelMergeKrea2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeKrea2

This node merges two models by blending their internal components at a fine-grained level, allowing you to control how much of each model's specific parts influence the final resul

This node merges two models by blending their internal components at a fine-grained level, allowing you to control how much of each model's specific parts influence the final result. It works by taking two input models and applying separate blend ratios to different sections of their architecture.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The first model to merge | MODEL | Yes | - |
| `model2` | The second model to merge | MODEL | Yes | - |
| `first.` | Blend ratio for the first layer block (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `tmlp.` | Blend ratio for the time MLP block (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `txtmlp.` | Blend ratio for the text MLP block (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `tproj.` | Blend ratio for the time projection block (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `txtfusion.layerwise_blocks.0.` | Blend ratio for the first text fusion layerwise block (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `txtfusion.layerwise_blocks.1.` | Blend ratio for the second text fusion layerwise block (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `txtfusion.projector.` | Blend ratio for the text fusion projector block (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `txtfusion.refiner_blocks.0.` | Blend ratio for the first text fusion refiner block (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `txtfusion.refiner_blocks.1.` | Blend ratio for the second text fusion refiner block (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `blocks.0.` through `blocks.27.` | Blend ratio for each of the 28 main blocks (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `last.` | Blend ratio for the last block (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |

Each blend ratio controls how much of `model2` is used for that specific component, where 0.0 means use only `model1`, 1.0 means use only `model2`, and values in between create a weighted blend.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The merged model resulting from blending the two input models according to the specified ratios | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeKrea2/en.md)

***

**Source fingerprint (SHA-256):** `ece35524f77fd906dc3109a0818d4d7d3986ec9debb518fd04893048843d7e88`


# ModelMergeLTXV - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeLTXV

The ModelMergeLTXV node merges two LTXV models by blending their matching components.

The ModelMergeLTXV node merges two LTXV models by blending their matching components. Each model part — such as transformer blocks, projection layers, and the scale shift table — can be blended separately with its own weight, giving fine control over how the two models are combined.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The first model to merge | MODEL | Yes | - |
| `model2` | The second model to merge | MODEL | Yes | - |
| `patchify_proj.` | Interpolation weight for patchify projection layers (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `adaln_single.` | Interpolation weight for adaptive layer normalization single layers (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `caption_projection.` | Interpolation weight for caption projection layers (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.0.` | Interpolation weight for transformer block 0 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.1.` | Interpolation weight for transformer block 1 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.2.` | Interpolation weight for transformer block 2 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.3.` | Interpolation weight for transformer block 3 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.4.` | Interpolation weight for transformer block 4 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.5.` | Interpolation weight for transformer block 5 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.6.` | Interpolation weight for transformer block 6 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.7.` | Interpolation weight for transformer block 7 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.8.` | Interpolation weight for transformer block 8 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.9.` | Interpolation weight for transformer block 9 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.10.` | Interpolation weight for transformer block 10 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.11.` | Interpolation weight for transformer block 11 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.12.` | Interpolation weight for transformer block 12 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.13.` | Interpolation weight for transformer block 13 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.14.` | Interpolation weight for transformer block 14 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.15.` | Interpolation weight for transformer block 15 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.16.` | Interpolation weight for transformer block 16 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.17.` | Interpolation weight for transformer block 17 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.18.` | Interpolation weight for transformer block 18 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.19.` | Interpolation weight for transformer block 19 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.20.` | Interpolation weight for transformer block 20 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.21.` | Interpolation weight for transformer block 21 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.22.` | Interpolation weight for transformer block 22 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.23.` | Interpolation weight for transformer block 23 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.24.` | Interpolation weight for transformer block 24 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.25.` | Interpolation weight for transformer block 25 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.26.` | Interpolation weight for transformer block 26 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `transformer_blocks.27.` | Interpolation weight for transformer block 27 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `scale_shift_table` | Interpolation weight for scale shift table (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `proj_out.` | Interpolation weight for projection output layers (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining features from both input models according to the specified interpolation weights | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeLTXV/en.md)

***

**Source fingerprint (SHA-256):** `0ff5f93aee831259066679a27fff8f7cbd4a9686242091f1bc7dd3805725566e`


# ModelMergeMochiPreview - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeMochiPreview

This node merges two Mochi AI models using a block-based approach with fine-grained control over different model components.

This node merges two Mochi AI models using a block-based approach with fine-grained control over different model components. It allows you to blend models by adjusting interpolation weights for specific sections, including positional frequencies, embedding layers, and each of the 48 individual transformer blocks. The merging process combines the architectures and parameters from both input models according to the specified weight values.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The first model to merge | MODEL | Yes | - |
| `model2` | The second model to merge | MODEL | Yes | - |
| `pos_frequencies.` | Weight for positional frequencies interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `t_embedder.` | Weight for time embedder interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `t5_y_embedder.` | Weight for T5-Y embedder interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `t5_yproj.` | Weight for T5-Y projection interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.0.` | Weight for block 0 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.1.` | Weight for block 1 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.2.` | Weight for block 2 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.3.` | Weight for block 3 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.4.` | Weight for block 4 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.5.` | Weight for block 5 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.6.` | Weight for block 6 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.7.` | Weight for block 7 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.8.` | Weight for block 8 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.9.` | Weight for block 9 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.10.` | Weight for block 10 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.11.` | Weight for block 11 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.12.` | Weight for block 12 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.13.` | Weight for block 13 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.14.` | Weight for block 14 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.15.` | Weight for block 15 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.16.` | Weight for block 16 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.17.` | Weight for block 17 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.18.` | Weight for block 18 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.19.` | Weight for block 19 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.20.` | Weight for block 20 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.21.` | Weight for block 21 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.22.` | Weight for block 22 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.23.` | Weight for block 23 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.24.` | Weight for block 24 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.25.` | Weight for block 25 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.26.` | Weight for block 26 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.27.` | Weight for block 27 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.28.` | Weight for block 28 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.29.` | Weight for block 29 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.30.` | Weight for block 30 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.31.` | Weight for block 31 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.32.` | Weight for block 32 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.33.` | Weight for block 33 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.34.` | Weight for block 34 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.35.` | Weight for block 35 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.36.` | Weight for block 36 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.37.` | Weight for block 37 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.38.` | Weight for block 38 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.39.` | Weight for block 39 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.40.` | Weight for block 40 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.41.` | Weight for block 41 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.42.` | Weight for block 42 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.43.` | Weight for block 43 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.44.` | Weight for block 44 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.45.` | Weight for block 45 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.46.` | Weight for block 46 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `blocks.47.` | Weight for block 47 interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `final_layer.` | Weight for final layer interpolation (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining features from both input models according to the specified weights | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeMochiPreview/en.md)

***

**Source fingerprint (SHA-256):** `8fdf5d023d97ef04bf2b40577be5dbc4c16f8f4437586a98adbdbf7f9fa8a359`


# ModelMergeQwenImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeQwenImage

This node merges two Qwen image models by blending their individual components with adjustable weights.

This node merges two Qwen image models by blending their individual components with adjustable weights. Each weight controls how much the corresponding part of the second model contributes to the merged result, letting you mix position embeddings, text processing layers, image input layers, all 60 transformer blocks, and the output projection separately. The final result is a single MODEL that you can use wherever a normal model is expected.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The first model to merge | MODEL | Yes | - |
| `model2` | The second model to merge | MODEL | Yes | - |
| `pos_embeds.` | Weight for positional embeddings blending (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `img_in.` | Weight for image input processing blending (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `txt_norm.` | Weight for text normalization blending (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `txt_in.` | Weight for text input processing blending (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `time_text_embed.` | Weight for time and text embedding blending (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `transformer_blocks.0.` to `transformer_blocks.59.` | Weight for each transformer block blending (default: 1.0). The node exposes one weight for each of the 60 transformer blocks. | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `proj_out.` | Weight for output projection blending (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |

Note: All weight inputs are required and share the same limits — a default of 1.0 with a valid range from 0.0 to 1.0, adjustable in steps of 0.01.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining components from both input models with the specified weights | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeQwenImage/en.md)

***

**Source fingerprint (SHA-256):** `5f31f91f3d54d4c5085c684a98f64afd0a0f704693b6dd4f19bc35d3c5f74529`


# ModelMergeSD1 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSD1

The ModelMergeSD1 node blends two Stable Diffusion 1.x models together by adjusting how much each model component contributes to the result.

The ModelMergeSD1 node blends two Stable Diffusion 1.x models together by adjusting how much each model component contributes to the result. It gives individual control over the time embedding, label embedding, and every input, middle, and output block, allowing fine-tuned model merging for specific use cases.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The first model to merge | MODEL | Yes | - |
| `model2` | The second model to merge | MODEL | Yes | - |
| `time_embed.` | Time embedding layer blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `label_emb.` | Label embedding layer blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.0.` | Input block 0 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.1.` | Input block 1 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.2.` | Input block 2 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.3.` | Input block 3 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.4.` | Input block 4 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.5.` | Input block 5 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.6.` | Input block 6 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.7.` | Input block 7 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.8.` | Input block 8 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.9.` | Input block 9 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.10.` | Input block 10 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `input_blocks.11.` | Input block 11 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `middle_block.0.` | Middle block 0 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `middle_block.1.` | Middle block 1 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `middle_block.2.` | Middle block 2 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.0.` | Output block 0 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.1.` | Output block 1 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.2.` | Output block 2 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.3.` | Output block 3 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.4.` | Output block 4 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.5.` | Output block 5 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.6.` | Output block 6 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.7.` | Output block 7 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.8.` | Output block 8 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.9.` | Output block 9 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.10.` | Output block 10 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `output_blocks.11.` | Output block 11 blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |
| `out.` | Output layer blending weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |

All blending weights accept values from 0.0 to 1.0 and are set to 1.0 by default, meaning each component of the first model is fully used unless adjusted.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The merged model combining features from both input models | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeSD1/en.md)

***

**Source fingerprint (SHA-256):** `b9d53f126139412fbd8b21be72e1dcdb02736519ab4dc9e28c7840d69acb7c87`


# ModelMergeSD35_Large - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSD35_Large

The ModelMergeSD35Large node merges two Stable Diffusion 3.5 Large models by blending specific internal components of the second model into the first.

The ModelMergeSD35\_Large node merges two Stable Diffusion 3.5 Large models by blending specific internal components of the second model into the first. Each component has an independent blend value, giving fine-grained control over how strongly that component contributes to the resulting merged model.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The base model that serves as the foundation for the merge | MODEL | Yes | - |
| `model2` | The secondary model whose components are blended into the base model | MODEL | Yes | - |
| `pos_embed.` | Controls how much of the position embedding from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `x_embedder.` | Controls how much of the x embedder from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `context_embedder.` | Controls how much of the context embedder from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `y_embedder.` | Controls how much of the y embedder from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `t_embedder.` | Controls how much of the t embedder from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.0.` | Controls how much of joint block 0 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.1.` | Controls how much of joint block 1 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.2.` | Controls how much of joint block 2 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.3.` | Controls how much of joint block 3 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.4.` | Controls how much of joint block 4 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.5.` | Controls how much of joint block 5 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.6.` | Controls how much of joint block 6 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.7.` | Controls how much of joint block 7 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.8.` | Controls how much of joint block 8 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.9.` | Controls how much of joint block 9 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.10.` | Controls how much of joint block 10 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.11.` | Controls how much of joint block 11 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.12.` | Controls how much of joint block 12 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.13.` | Controls how much of joint block 13 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.14.` | Controls how much of joint block 14 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.15.` | Controls how much of joint block 15 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.16.` | Controls how much of joint block 16 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.17.` | Controls how much of joint block 17 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.18.` | Controls how much of joint block 18 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.19.` | Controls how much of joint block 19 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.20.` | Controls how much of joint block 20 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.21.` | Controls how much of joint block 21 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.22.` | Controls how much of joint block 22 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.23.` | Controls how much of joint block 23 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.24.` | Controls how much of joint block 24 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.25.` | Controls how much of joint block 25 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.26.` | Controls how much of joint block 26 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.27.` | Controls how much of joint block 27 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.28.` | Controls how much of joint block 28 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.29.` | Controls how much of joint block 29 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.30.` | Controls how much of joint block 30 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.31.` | Controls how much of joint block 31 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.32.` | Controls how much of joint block 32 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.33.` | Controls how much of joint block 33 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.34.` | Controls how much of joint block 34 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.35.` | Controls how much of joint block 35 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.36.` | Controls how much of joint block 36 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `joint_blocks.37.` | Controls how much of joint block 37 from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `final_layer.` | Controls how much of the final layer from model2 is blended into the merged model (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |

**Note:** All blending parameters accept values from 0.0 to 1.0 with a step of 0.01. A value of 0.0 means no contribution from model2, and a value of 1.0 means full contribution from model2 for that specific component.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The resulting merged model combining features from both input models according to the specified blend parameters | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeSD35_Large/en.md)

***

**Source fingerprint (SHA-256):** `c489c710e18d01adcf4320d9c010ed587ca5e12babb468448f56d79acdc40f6c`


# ModelMergeSD3_2B - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSD3_2B

The ModelMergeSD32B node allows you to merge two Stable Diffusion 3 2B models by blending their components with adjustable weights.

The ModelMergeSD3\_2B node allows you to merge two Stable Diffusion 3 2B models by blending their components with adjustable weights. It provides individual control over embedding layers, transformer blocks, and the final layer, enabling fine-tuned combinations of two models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The first model to merge | MODEL | Yes | - |
| `model2` | The second model to merge | MODEL | Yes | - |
| `pos_embed.` | Position embedding interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `x_embedder.` | Input embedding interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `context_embedder.` | Context embedding interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `y_embedder.` | Y embedding interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `t_embedder.` | Time embedding interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.0.` | Joint block 0 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.1.` | Joint block 1 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.2.` | Joint block 2 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.3.` | Joint block 3 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.4.` | Joint block 4 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.5.` | Joint block 5 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.6.` | Joint block 6 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.7.` | Joint block 7 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.8.` | Joint block 8 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.9.` | Joint block 9 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.10.` | Joint block 10 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.11.` | Joint block 11 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.12.` | Joint block 12 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.13.` | Joint block 13 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.14.` | Joint block 14 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.15.` | Joint block 15 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.16.` | Joint block 16 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.17.` | Joint block 17 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.18.` | Joint block 18 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.19.` | Joint block 19 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.20.` | Joint block 20 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.21.` | Joint block 21 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.22.` | Joint block 22 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `joint_blocks.23.` | Joint block 23 interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `final_layer.` | Final layer interpolation weight (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining features from both input models | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeSD3_2B/en.md)

***

**Source fingerprint (SHA-256):** `db27b10ade457933f6225218bb806aafcf9fc4478cac85b1623a75d110103529`


# ModelMergeSDXL - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSDXL

The ModelMergeSDXL node allows you to blend two SDXL models together by adjusting the influence of each model on different parts of the architecture.

The ModelMergeSDXL node allows you to blend two SDXL models together by adjusting the influence of each model on different parts of the architecture. You can control how much each model contributes to time embeddings, label embeddings, and various blocks within the model structure. This creates a hybrid model that combines characteristics from both input models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | The first SDXL model to merge | MODEL | Yes | - |
| `model2` | The second SDXL model to merge | MODEL | Yes | - |
| `time_embed.` | Blending weight for time embedding layers (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `label_emb.` | Blending weight for label embedding layers (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `input_blocks.0` | Blending weight for input block 0 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `input_blocks.1` | Blending weight for input block 1 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `input_blocks.2` | Blending weight for input block 2 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `input_blocks.3` | Blending weight for input block 3 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `input_blocks.4` | Blending weight for input block 4 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `input_blocks.5` | Blending weight for input block 5 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `input_blocks.6` | Blending weight for input block 6 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `input_blocks.7` | Blending weight for input block 7 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `input_blocks.8` | Blending weight for input block 8 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `middle_block.0` | Blending weight for middle block 0 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `middle_block.1` | Blending weight for middle block 1 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `middle_block.2` | Blending weight for middle block 2 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `output_blocks.0` | Blending weight for output block 0 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `output_blocks.1` | Blending weight for output block 1 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `output_blocks.2` | Blending weight for output block 2 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `output_blocks.3` | Blending weight for output block 3 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `output_blocks.4` | Blending weight for output block 4 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `output_blocks.5` | Blending weight for output block 5 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `output_blocks.6` | Blending weight for output block 6 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `output_blocks.7` | Blending weight for output block 7 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `output_blocks.8` | Blending weight for output block 8 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `out.` | Blending weight for output layers (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged SDXL model combining characteristics from both input models | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeSDXL/en.md)

***

**Source fingerprint (SHA-256):** `9a1b0645ee19c2eddb274dd6ea3f9a05997115119cc654a7f055d58475745bb2`


# ModelMergeSimple - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSimple

The ModelMergeSimple node is designed for merging two models by blending their parameters based on a specified ratio.

The ModelMergeSimple node is designed for merging two models by blending their parameters based on a specified ratio. This node facilitates the creation of hybrid models that combine the strengths or characteristics of both input models.

The `ratio` parameter determines the blending ratio between the two models. When this value is 1, the output model is 100% `model1`, and when this value is 0, the output model is 100% `model2`.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model1` | The first model to be merged. It serves as the base model onto which patches from the second model are applied. | `MODEL` |
| `model2` | The second model whose patches are applied onto the first model, influenced by the specified ratio. | `MODEL` |
| `ratio` | When this value is 1, the output model is 100% `model1`, and when this value is 0, the output model is 100% `model2`. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The resulting merged model, incorporating elements from both input models according to the specified ratio. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeSimple/en.md)


# ModelMergeSubtract - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSubtract

This node is designed for advanced model merging operations, specifically to subtract the parameters of one model from another based on a specified multiplier.

This node is designed for advanced model merging operations, specifically to subtract the parameters of one model from another based on a specified multiplier. It enables the customization of model behaviors by adjusting the influence of one model's parameters over another, facilitating the creation of new, hybrid models.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model1` | The base model from which parameters will be subtracted. | `MODEL` |
| `model2` | The model whose parameters will be subtracted from the base model. | `MODEL` |
| `multiplier` | A floating-point value that scales the subtraction effect on the base model's parameters. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The resulting model after subtracting the parameters of one model from another, scaled by the multiplier. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeSubtract/en.md)


# ModelMergeWAN2_1 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeWAN2_1

The ModelMergeWAN21 node merges two WAN2.1 models by blending their components using weighted averages.

The ModelMergeWAN2\_1 node merges two WAN2.1 models by blending their components using weighted averages. It supports different model sizes, including 1.3B models with 30 blocks and 14B models with 40 blocks, with special handling for image-to-video models that include an extra image embedding component. Each component can be individually weighted to control the blending ratio between the two input models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model1` | First model to merge | MODEL | Yes | - |
| `model2` | Second model to merge | MODEL | Yes | - |
| `patch_embedding.` | Weight for patch embedding component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `time_embedding.` | Weight for time embedding component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `time_projection.` | Weight for time projection component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `text_embedding.` | Weight for text embedding component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `img_emb.` | Weight for image embedding component, used in image-to-video models (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.0.` | Weight for block 0 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.1.` | Weight for block 1 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.2.` | Weight for block 2 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.3.` | Weight for block 3 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.4.` | Weight for block 4 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.5.` | Weight for block 5 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.6.` | Weight for block 6 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.7.` | Weight for block 7 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.8.` | Weight for block 8 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.9.` | Weight for block 9 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.10.` | Weight for block 10 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.11.` | Weight for block 11 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.12.` | Weight for block 12 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.13.` | Weight for block 13 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.14.` | Weight for block 14 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.15.` | Weight for block 15 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.16.` | Weight for block 16 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.17.` | Weight for block 17 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.18.` | Weight for block 18 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.19.` | Weight for block 19 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.20.` | Weight for block 20 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.21.` | Weight for block 21 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.22.` | Weight for block 22 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.23.` | Weight for block 23 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.24.` | Weight for block 24 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.25.` | Weight for block 25 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.26.` | Weight for block 26 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.27.` | Weight for block 27 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.28.` | Weight for block 28 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.29.` | Weight for block 29 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.30.` | Weight for block 30 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.31.` | Weight for block 31 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.32.` | Weight for block 32 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.33.` | Weight for block 33 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.34.` | Weight for block 34 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.35.` | Weight for block 35 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.36.` | Weight for block 36 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.37.` | Weight for block 37 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.38.` | Weight for block 38 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `blocks.39.` | Weight for block 39 (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `head.` | Weight for head component (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |

**Note:** All weight parameters use a range from 0.0 to 1.0 with 0.01 step increments. The node provides up to 40 block weight inputs to accommodate different model sizes: 1.3B models use 30 blocks (`blocks.0.` through `blocks.29.`), while 14B models use 40 blocks (`blocks.0.` through `blocks.39.`). The `img_emb.` parameter is used by image-to-video models.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The merged model combining components from both input models according to the specified weights | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeWAN2_1/en.md)

***

**Source fingerprint (SHA-256):** `6a17defa25b1ef045b85af4a73e00d3a64c1948c0c47f355d1d488a75b09f224`


# ModelNoiseScale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelNoiseScale

This node adjusts the noise scale used during model sampling.

This node adjusts the noise scale used during model sampling. It creates a copy of the input model, applies the specified noise scale to its sampling configuration, and returns the modified model.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply the noise scale adjustment to. | MODEL | Yes | - |
| `noise_scale` | Absolute training noise scale. For example HiDream-O1 base: 8.0, dev: 7.5. (default: 1.0) | FLOAT | Yes | 0.0 to 64.0 (step: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The modified model with the new noise scale applied. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelNoiseScale/en.md)

***

**Source fingerprint (SHA-256):** `75b0b99323fc15ff3cafc23de05a9d6b52d059494fbc229e5fb685d2908dd5d3`


# ModelPatchLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelPatchLoader

The ModelPatchLoader node loads a model patch file from the modelpatches folder and prepares it for use in a workflow.

The ModelPatchLoader node loads a model patch file from the `model_patches` folder and prepares it for use in a workflow. It automatically detects the type of patch contained in the file, builds the matching architecture, loads the saved weights, and wraps everything in a model patcher so it can be applied to other models. It supports many specialized patch formats, including extra ControlNet branches, feature embedder models, adapters, animation/LLLite guidance modules, and similar modules.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `name` | The filename of the model patch to load from the `model_patches` folder. Select one of the available patch files from the list. | COMBO | Yes | Dynamically generated list of all model patch files found in the `model_patches` folder |

Note: This node is marked as experimental. The patch type is detected automatically from the file contents, so no manual type selection is required. The node reads the checkpoint metadata and inspects the weight keys to decide which architecture to build (for example Qwen Image block-wise ControlNet, Z-Image ControlNet, Wan Uni3C ControlNet, MiniMax H3 Fun ControlNet, SigLIP feature projection, Lightricks duration head, Anima LLLite, MultiTalk, or SUPIR). Weights are loaded with safe loading enabled, and the model is placed on the offload device inside a `CoreModelPatcher` so it can later be applied to another model.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL_PATCH` | The loaded model patch wrapped in a model patcher, ready to be applied to a model in the workflow | MODEL\_PATCH |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelPatchLoader/en.md)

***

**Source fingerprint (SHA-256):** `069f40b1f108ecd74fc58c12aa2f74edff07f743aa1ed6352ff7bcf0c39341d4`


# ModelSamplingAuraFlow - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingAuraFlow

The ModelSamplingAuraFlow node applies a specialized sampling configuration to diffusion models, specifically designed for AuraFlow model architectures.

The ModelSamplingAuraFlow node applies a specialized sampling configuration to diffusion models, specifically designed for AuraFlow model architectures. It modifies the model's sampling behavior by applying a shift value that adjusts the sampling distribution. This node inherits from the SD3 model sampling framework and provides fine control over the sampling process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to apply the AuraFlow sampling configuration to | MODEL | Yes | - |
| `shift` | The shift value to apply to the sampling distribution (default: 1.73, step: 0.01) | FLOAT | Yes | 0.0 - 100.0 |
| `sampling` | The sampling mode used when patching the model (default: "flow"). Marked as an advanced option. | COMBO | No | "flow"<br />"img\_to\_img\_velocity" |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with AuraFlow sampling configuration applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingAuraFlow/en.md)

***

**Source fingerprint (SHA-256):** `5c1381d2dec9ac84a7ee6cd134de444ab50f657eafd960263c63a055d0a139d6`


# ModelSamplingContinuousEDM - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingContinuousEDM

This node is designed to enhance a model's sampling capabilities by integrating continuous EDM (Energy-based Diffusion Models) sampling techniques.

This node is designed to enhance a model's sampling capabilities by integrating continuous EDM (Energy-based Diffusion Models) sampling techniques. It allows for the dynamic adjustment of the noise levels within the model's sampling process, offering a more refined control over the generation quality and diversity.

## Inputs

| Parameter | Description | Data Type | Python dtype |
| - | - | - | - |
| `model` | The model to be enhanced with continuous EDM sampling capabilities. It serves as the foundation for applying the advanced sampling techniques. | `MODEL` | `torch.nn.Module` |
| `sampling` | Specifies the type of sampling to be applied, either 'eps' for epsilon sampling or 'v\_prediction' for velocity prediction, influencing the model's behavior during the sampling process. | COMBO\[STRING] | `str` |
| `sigma_max` | The maximum sigma value for noise level, allowing for upper bound control in the noise injection process during sampling. | `FLOAT` | `float` |
| `sigma_min` | The minimum sigma value for noise level, setting the lower limit for noise injection, thus affecting the model's sampling precision. | `FLOAT` | `float` |

## Outputs

| Parameter | Description | Data Type | Python dtype |
| - | - | - | - |
| `model` | The enhanced model with integrated continuous EDM sampling capabilities, ready for further use in generation tasks. | MODEL | `torch.nn.Module` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingContinuousEDM/en.md)


# ModelSamplingContinuousV - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingContinuousV

The ModelSamplingContinuousV node adjusts a model's sampling behavior by applying continuous V-prediction sampling.

The ModelSamplingContinuousV node adjusts a model's sampling behavior by applying continuous V-prediction sampling. It creates a clone of the input model and configures it with custom minimum and maximum sigma values for finer control over the sampling process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The input model to be modified with continuous V-prediction sampling | MODEL | Yes | - |
| `sampling` | The sampling method to apply; currently V-prediction is the only available option (default: `"v_prediction"`) | COMBO | Yes | `"v_prediction"` |
| `sigma_max` | The maximum sigma value for sampling (advanced parameter, default: 500.0, step: 0.001) | FLOAT | Yes | 0.0 - 1000.0 |
| `sigma_min` | The minimum sigma value for sampling (advanced parameter, default: 0.03, step: 0.001) | FLOAT | Yes | 0.0 - 1000.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with continuous V-prediction sampling applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingContinuousV/en.md)

***

**Source fingerprint (SHA-256):** `8549be9dd2375374c20da7c74a756a90285716db0e52fed8a1a2b753cd6d75fe`


# ModelSamplingDiscrete - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingDiscrete

This node is designed to modify the sampling behavior of a model by applying a discrete sampling strategy.

This node is designed to modify the sampling behavior of a model by applying a discrete sampling strategy. It allows for the selection of different sampling methods, such as epsilon, v\_prediction, lcm, or x0, and optionally adjusts the model's noise reduction strategy based on the zero-shot noise ratio (zsnr) setting.

## Inputs

| Parameter | Description | Data Type | Python dtype |
| - | - | - | - |
| `model` | The model to which the discrete sampling strategy will be applied. This parameter is crucial as it defines the base model that will undergo modification. | MODEL | `torch.nn.Module` |
| `sampling` | Specifies the discrete sampling method to be applied to the model. The choice of method affects how the model generates samples, offering different strategies for sampling. | COMBO\[STRING] | `str` |
| `zsnr` | A boolean flag that, when enabled, adjusts the model's noise reduction strategy based on the zero-shot noise ratio. This can influence the quality and characteristics of the generated samples. | `BOOLEAN` | `bool` |

## Outputs

| Parameter | Description | Data Type | Python dtype |
| - | - | - | - |
| `model` | The modified model with the applied discrete sampling strategy. This model is now equipped to generate samples using the specified method and adjustments. | MODEL | `torch.nn.Module` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingDiscrete/en.md)


# ModelSamplingFlux - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingFlux

The ModelSamplingFlux node applies Flux model sampling to a given model by calculating a shift parameter based on image dimensions.

The ModelSamplingFlux node applies Flux model sampling to a given model by calculating a shift parameter based on image dimensions. It creates a specialized sampling configuration that adjusts the model's behavior according to the specified width, height, and shift parameters, then returns the modified model with the new sampling settings applied.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply Flux sampling to | MODEL | Yes | - |
| `max_shift` | Maximum shift value for sampling calculation (default: 1.15) | FLOAT | Yes | 0.0 - 100.0 (step 0.01) |
| `base_shift` | Base shift value for sampling calculation (default: 0.5) | FLOAT | Yes | 0.0 - 100.0 (step 0.01) |
| `width` | Width of the target image in pixels (default: 1024) | INT | Yes | 16 - MAX\_RESOLUTION (step 8) |
| `height` | Height of the target image in pixels (default: 1024) | INT | Yes | 16 - MAX\_RESOLUTION (step 8) |

`max_shift` and `base_shift` are advanced parameters. The shift applied to the sampling configuration is calculated from the image dimensions: the latent resolution is computed as `width × height / 256`, and the shift value is interpolated between `base_shift` at a latent resolution of 256 and `max_shift` at a latent resolution of 4096.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with Flux sampling configuration applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingFlux/en.md)

***

**Source fingerprint (SHA-256):** `04065b54ace30a2b20476ed085df871ea89794650e98ae30c40f750357663834`


# ModelSamplingLTXV - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingLTXV

The ModelSamplingLTXV node applies advanced sampling parameters to a model based on token count.

The ModelSamplingLTXV node applies advanced sampling parameters to a model based on token count. It calculates a shift value by linearly interpolating between `base_shift` and `max_shift` across a token range, then patches the input model with a specialized sampling configuration. If a latent is provided, its dimensions determine the token count; otherwise 4096 tokens are used.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The input model to apply sampling parameters to. | MODEL | Yes | - |
| `max_shift` | The maximum shift value used in the linear interpolation calculation (default: 2.05). | FLOAT | Yes | 0.0 to 100.0 (step: 0.01) |
| `base_shift` | The base shift value used in the linear interpolation calculation (default: 0.95). | FLOAT | Yes | 0.0 to 100.0 (step: 0.01) |
| `latent` | Optional latent input used to determine the token count for the shift calculation. If not provided, a default token count of 4096 is used. | LATENT | No | - |

The shift value is calculated by interpolating between `base_shift` at 1024 tokens and `max_shift` at 4096 tokens. When `latent` is supplied, the token count is the product of all dimensions after the first two in the latent samples (the spatial/temporal dimensions). If no `latent` is provided, the token count defaults to 4096.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with the applied sampling parameters. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingLTXV/en.md)

***

**Source fingerprint (SHA-256):** `aba596c5478e9d6ee821eec1eca15506935bcc765a368087ccc442fc2ed6671b`


# ModelSamplingSD3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingSD3

This node applies Stable Diffusion 3 style sampling settings to a model.

This node applies Stable Diffusion 3 style sampling settings to a model. It makes a copy of the model and replaces its sampling method with a flow-based sampling configuration that uses the given `shift` value, which controls how the sampling distribution is shaped.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The input model to apply SD3 sampling parameters to | MODEL | Yes | - |
| `shift` | Controls the sampling shift parameter (default: 3.0) | FLOAT | Yes | 0.0 - 100.0 (step: 0.01) |

Note: The `shift` value is applied together with a fixed internal multiplier of 1000. If the original model has a noise scale setting, that value is carried over to the modified model. The original model is not changed; a cloned and patched copy is returned.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with SD3 sampling parameters applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingSD3/en.md)

***

**Source fingerprint (SHA-256):** `a77e38c2cebf6f21f841a953ec5c59096eaf60ffc205c24f34f635e54c5718cb`


# ModelSamplingStableCascade - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingStableCascade

The ModelSamplingStableCascade node applies stable cascade sampling settings to a model by applying a shift value to the sampling parameters.

The ModelSamplingStableCascade node applies stable cascade sampling settings to a model by applying a shift value to the sampling parameters. It returns a patched copy of the input model with the custom stable cascade sampling configuration, leaving the original model unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The input model to apply stable cascade sampling to | MODEL | Yes | - |
| `shift` | The shift value applied to the sampling parameters (default: 2.0) | FLOAT | Yes | 0.0 - 100.0 (step 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with stable cascade sampling applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingStableCascade/en.md)

***

**Source fingerprint (SHA-256):** `358681a7c698d4335cde60780d5a8b134b75df4ea40102bf51544c53bbb08c42`


# ModelSave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSave

The ModelSave node saves a MODEL to your computer's storage as a .safetensors checkpoint file.

The ModelSave node saves a MODEL to your computer's storage as a `.safetensors` checkpoint file. It writes the file into ComfyUI's output directory using the filename prefix you provide, and embeds workflow prompt information and model metadata into the saved file when available.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to be saved to disk | MODEL | Yes | - |
| `filename_prefix` | The filename and path prefix for the saved model file (default: "diffusion\_models/ComfyUI") | STRING | Yes | - |
| `prompt` | Workflow prompt information (automatically provided) | PROMPT | No | - |
| `extra_pnginfo` | Additional workflow metadata (automatically provided) | EXTRA\_PNGINFO | No | - |

Note: The saved filename is built from the `filename_prefix` value followed by a five-digit counter (for example, `diffusion_models/ComfyUI_00001_.safetensors`). If a file with the same prefix already exists, the counter is increased so the new file gets a unique name. When available, the workflow prompt, additional metadata, and model architecture information (for example Stable Diffusion XL, SDXL Refiner, Stable Video Diffusion, or Stable Diffusion 3) are embedded in the saved file. If metadata saving is disabled through ComfyUI's command-line settings, the prompt and extra metadata are not written into the file.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| *None* | This node does not return any output values | - |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSave/en.md)

***

**Source fingerprint (SHA-256):** `943e60f2c596d9cbcaabe95029fd9d443df5b61c6137736a8b1b81ab78f200ea`


# OpticalFlowLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpticalFlowLoader

Loads an optical flow model from the models/opticalflow/ folder.

Loads an optical flow model from the `models/optical_flow/` folder. Currently, only torchvision's RAFT-large format is supported, which is the model used by the VOIDWarpedNoise node. ComfyUI does not download optical flow weights automatically; you must place the checkpoint file manually in the `models/optical_flow/` directory.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | Optical flow model to load. Files must be placed in the `optical_flow` folder. Today only torchvision's `raft_large.pth` is supported. | COMBO | Yes | List of files in the `models/optical_flow/` folder |

Note: The selected checkpoint must be a torchvision RAFT-large state dict containing keys prefixed with `feature_encoder.`, `context_encoder.`, and `update_block.`. If the file does not match this format, the node raises a ValueError.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `OPTICAL_FLOW` | The loaded optical flow model, set to evaluation mode and float32 precision, wrapped in a ModelPatcher for use with other nodes. | OPTICAL\_FLOW |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpticalFlowLoader/en.md)

***

**Source fingerprint (SHA-256):** `5e79551545ad7ee2fd4856a47da29808a404342d1d5e57da0980058db6b11c3b`


# PatchModelAddDownscale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PatchModelAddDownscale

PatchModelAddDownscale (Kohya Deep Shrink) applies the Kohya Deep Shrink technique to a model by shrinking intermediate features at a chosen block and then scaling them back to the

PatchModelAddDownscale (Kohya Deep Shrink) applies the Kohya Deep Shrink technique to a model by shrinking intermediate features at a chosen block and then scaling them back to their original size. The shrinking only happens during a selected part of the denoising process, which can reduce processing cost while keeping the final result close to the original.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply the downscale patch to | MODEL | Yes | - |
| `block_number` | The specific block number where downscaling will be applied (default: 3) | INT | Yes | 1-32 |
| `downscale_factor` | The factor by which to downscale the features (default: 2.0) | FLOAT | Yes | 0.1-9.0 |
| `start_percent` | The starting point in the denoising process where downscaling begins (default: 0.0) | FLOAT | Yes | 0.0-1.0 |
| `end_percent` | The ending point in the denoising process where downscaling stops (default: 0.35) | FLOAT | Yes | 0.0-1.0 |
| `downscale_after_skip` | Whether to apply downscaling after skip connections (default: True) | BOOLEAN | Yes | - |
| `downscale_method` | The interpolation method used for downscaling operations (default: "bicubic") | COMBO | Yes | "bicubic"<br />"nearest-exact"<br />"bilinear"<br />"area"<br />"bislerp" |
| `upscale_method` | The interpolation method used for upscaling operations (default: "bicubic") | COMBO | Yes | "bicubic"<br />"nearest-exact"<br />"bilinear"<br />"area"<br />"bislerp" |

The downscale patch is applied only when the current denoising step falls within the range defined by `start_percent` and `end_percent`, and only at the block selected by `block_number`. When `downscale_after_skip` is enabled, the patch is applied after the skip connection; when disabled, it is applied before the skip connection. Features are scaled back up to their original size afterwards, but only when the current feature size no longer matches the size recorded before downscaling.

The parameters `block_number`, `start_percent`, `end_percent`, and `downscale_after_skip` are marked as advanced options in the node interface.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with downscale patch applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PatchModelAddDownscale/en.md)

***

**Source fingerprint (SHA-256):** `aa9434a521ab585b290a3bd8db804469bd3bb02103a0d830b6be6eb8e8c26a5e`


# PerturbedAttentionGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PerturbedAttentionGuidance

The PerturbedAttentionGuidance node applies perturbed attention guidance to a diffusion model to improve generation quality.

The PerturbedAttentionGuidance node applies perturbed attention guidance to a diffusion model to improve generation quality. During sampling it makes an extra prediction in which the middle block's self-attention is replaced by a simplified version that passes the value projections straight through, then adds the scaled difference between the normal conditional prediction and this perturbed prediction to the denoised result. Setting `scale` to 0 disables the effect entirely.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to apply perturbed attention guidance to | MODEL | Yes | - |
| `scale` | The strength of the perturbed attention guidance effect (default: 3.0). When set to 0, the node has no effect and returns the original denoised result unchanged. | FLOAT | Yes | 0.0 - 100.0 (step: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with the perturbed attention guidance patch attached to its sampling process | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PerturbedAttentionGuidance/en.md)

***

**Source fingerprint (SHA-256):** `1cf824486ae695a9e563c70a4798aaf4c9c067ae3b53172c9767e3c5093d0096`


# PhotoMakerLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PhotoMakerLoader

The PhotoMakerLoader node loads a PhotoMaker model from the available model files.

The PhotoMakerLoader node loads a PhotoMaker model from the available model files. It reads the selected file, loads its ID encoder weights, and prepares the PhotoMaker ID encoder for use in identity-based image generation tasks. This node is marked as experimental and is intended for testing purposes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `photomaker_model_name` | The name of the PhotoMaker model file to load. The available options are determined by the model files present in the `photomaker` folder. | COMBO | Yes | Multiple options available (dynamically populated from the `photomaker` folder) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `photomaker_model` | The loaded PhotoMaker model containing the ID encoder, ready for use in identity encoding operations. | PHOTOMAKER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PhotoMakerLoader/en.md)

***

**Source fingerprint (SHA-256):** `1b26630fadbdc144cd42ca7393f743b079ee7463deb9c8b31b628b5dc7432317`


# QuadrupleCLIPLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QuadrupleCLIPLoader

The Quadruple CLIP Loader, QuadrupleCLIPLoader, is one of the core nodes of ComfyUI, first added to support the HiDream I1 version model.

The Quadruple CLIP Loader, QuadrupleCLIPLoader, is one of the core nodes of ComfyUI, first added to support the HiDream I1 version model. If you find this node missing, try updating ComfyUI to the latest version to ensure node support.

It requires 4 CLIP models, corresponding to the parameters `clip_name1`, `clip_name2`, `clip_name3`, and `clip_name4`, and will provide a CLIP model output for subsequent nodes.

This node will detect models located in the `ComfyUI/models/text_encoders` folder,
and it will also read models from additional paths configured in the extra\_model\_paths.yaml file.
Sometimes, after adding models, you may need to **reload the ComfyUI interface** to allow it to read the model files in the corresponding folder.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/QuadrupleCLIPLoader/en.md)


# QwenImageDiffsynthControlnet - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QwenImageDiffsynthControlnet

QwenImageDiffsynthControlnet applies a diffusion synthesis control network patch to a base model.

QwenImageDiffsynthControlnet applies a diffusion synthesis control network patch to a base model. It uses an input image and an optional mask to guide the model's generation process with adjustable strength, producing a patched model that incorporates the control network's influence for more controlled image synthesis.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The base model to be patched with the control network | MODEL | Yes | - |
| `model_patch` | The control network patch model to apply to the base model | MODEL\_PATCH | Yes | - |
| `vae` | The VAE (Variational Autoencoder) used in the diffusion process | VAE | Yes | - |
| `image` | The input image used to guide the control network. Only the first three color channels (RGB) are used; any additional channels are discarded | IMAGE | Yes | - |
| `strength` | The strength of the control network influence (default: 1.0) | FLOAT | Yes | -10.0 to 10.0 (step 0.01) |
| `mask` | Optional mask that defines areas where the control network should be applied. The mask is inverted internally before use | MASK | No | - |

**Note:** When a mask is provided, it is automatically inverted (1.0 - mask) and reshaped to match the expected dimensions for the control network processing. The node uses different internal processing methods depending on whether the model patch is a ZImage Control type or a standard DiffSynth control network. This node is flagged as experimental.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with the diffusion synthesis control network patch applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/QwenImageDiffsynthControlnet/en.md)

***

**Source fingerprint (SHA-256):** `56739c098933cb70d3bcb8d6b251da33e7879b464b2e8a7296da085aefc15698`


# RenormCFG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RenormCFG

The RenormCFG node modifies the classifier-free guidance (CFG) process in diffusion models by applying conditional scaling and normalization.

The RenormCFG node modifies the classifier-free guidance (CFG) process in diffusion models by applying conditional scaling and normalization. It adjusts the denoising process based on a specified timestep threshold and a renormalization factor, controlling the influence of conditional versus unconditional predictions during image generation. The resulting model is returned with this patched CFG behavior.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to apply renormalized CFG to | MODEL | Yes | - |
| `cfg_trunc` | Timestep threshold for applying CFG scaling. When the current timestep is below this value, CFG scaling and renormalization are applied; otherwise, only the conditional prediction is used (default: 100.0) | FLOAT | No | 0.0 - 100.0 (step 0.01) |
| `renorm_cfg` | Renormalization factor that limits the maximum norm of the CFG-scaled prediction relative to the original conditional prediction. A value of 0.0 disables renormalization (default: 1.0) | FLOAT | No | 0.0 - 100.0 (step 0.01) |

Note: `cfg_trunc` and `renorm_cfg` are advanced parameters. Renormalization only takes effect when `renorm_cfg` is greater than 0.0 and the current timestep is below `cfg_trunc`; if the new prediction norm is already below the computed maximum, no rescaling is performed.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with the renormalized CFG function applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RenormCFG/en.md)

***

**Source fingerprint (SHA-256):** `5925bdfe2d62ef7261d73cda661834102ae6600b1afe53f4093568a6e83ec2ab`


# RescaleCFG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RescaleCFG

The RescaleCFG node is designed to adjust the conditioning and unconditioning scales of a model's output based on a specified multiplier, aiming to achieve a more balanced and cont

The RescaleCFG node is designed to adjust the conditioning and unconditioning scales of a model's output based on a specified multiplier, aiming to achieve a more balanced and controlled generation process. It operates by rescaling the model's output to modify the influence of conditioned and unconditioned components, thereby potentially enhancing the model's performance or output quality.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The model parameter represents the generative model to be adjusted. It is crucial as the node applies a rescaling function to the model's output, directly influencing the generation process. | MODEL |
| `multiplier` | The multiplier parameter controls the extent of rescaling applied to the model's output. It determines the balance between the original and rescaled components, affecting the final output's characteristics. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The modified model with adjusted conditioning and unconditioning scales. This model is expected to produce outputs with potentially enhanced characteristics due to the applied rescaling. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RescaleCFG/en.md)


# SUPIRApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SUPIRApply

The SUPIRApply node applies a SUPIR model patch to a diffusion model.

The SUPIRApply node applies a SUPIR model patch to a diffusion model. It uses the patch to modify the model's behavior, allowing it to incorporate guidance from an input image during the sampling process. The node also provides controls for adjusting the strength of this guidance over time and includes an optional feature to help maintain fidelity to the original input.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The base diffusion model to which the SUPIR patch will be applied. | MODEL | Yes | - |
| `model_patch` | The SUPIR model patch containing the weights and configuration for modifying the model. | MODEL\_PATCH | Yes | - |
| `vae` | The VAE (Variational Autoencoder) used for encoding the input image into a latent representation. | VAE | Yes | - |
| `image` | The input image used to guide the generation process. Only the first three color channels (RGB) are used. | IMAGE | Yes | - |
| `strength_start` | Control strength at the start of sampling (high sigma). The influence of the image guidance begins at this value. (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 |
| `strength_end` | Control strength at the end of sampling (low sigma). Linearly interpolated from start. The influence of the image guidance ends at this value. (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 |
| `restore_cfg` | Pulls denoised output toward the input latent. Higher = stronger fidelity to input. 0 to disable. (default: 4.0, advanced setting) | FLOAT | Yes | 0.0 - 20.0 |
| `restore_cfg_s_tmin` | Sigma threshold below which `restore_cfg` is disabled. (default: 0.05, advanced setting) | FLOAT | Yes | 0.0 - 1.0 |

*Note:* The `image` input is processed to extract only the RGB channels. If an image with an alpha channel is provided, the alpha channel is ignored.

*Note:* If the SUPIR model patch provides denoise encoder weights, the input image is encoded with those weights instead of the regular VAE encoder.

*Note:* `restore_cfg` only takes effect when set to a value greater than 0. Setting it to 0 disables the restore post-processing entirely. When active, the correction is applied only while the current sigma value is above `restore_cfg_s_tmin`.

*Note:* This node is marked as experimental in ComfyUI.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | A cloned copy of the input model with the SUPIR patch applied and any additional post-CFG functions configured. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SUPIRApply/en.md)

***

**Source fingerprint (SHA-256):** `fa9f67f63777160863c44c620d8de11e92f79245c3f5b60e138975dfd0cc65c7`


# SaveLoRA - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveLoRA

The SaveLoRA node saves a LoRA (Low-Rank Adaptation) model to a file.

The SaveLoRA node saves a LoRA (Low-Rank Adaptation) model to a file. It takes a LoRA model as input and writes it to a `.safetensors` file in the output directory. You can specify a filename prefix and an optional step count to be included in the final filename.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `lora` | The LoRA model to save. Do not use the model with LoRA layers. | LORA\_MODEL | Yes | N/A |
| `prefix` | The prefix to use for the saved LoRA file (default: "loras/ComfyUI\_trained\_lora"). | STRING | Yes | N/A |
| `steps` | Optional: The number of steps the LoRA has been trained for, used to name the saved file. | INT | No | N/A |

**Note:** The `lora` input must be a pure LoRA model. Do not provide a base model that has LoRA layers applied to it.

**Note:** The file is saved in the ComfyUI output directory with a `.safetensors` extension. The filename is built from the `prefix` and a zero-padded counter (5 digits) to avoid overwriting existing files. When `steps` is provided, the step count is also included in the filename (for example, `1000_steps` for 1000 steps).

**Note:** This node is marked as experimental.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| *None* | This node does not output any data to the workflow. It is an output node that saves a file to disk. | N/A |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveLoRA/en.md)

***

**Source fingerprint (SHA-256):** `02f1d15dd7a5181666f2dbf06c45c07b12c4a178985464e07b5f613bd628f906`


# SenseNovaSamplingOptions - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SenseNovaSamplingOptions

SenseNova Sampling Options sets the SenseNova flow shift on a model.

SenseNova Sampling Options sets the SenseNova flow shift on a model. It clones the input model, attaches a SenseNova model sampling configuration using the chosen flow shift value, and returns the patched model for use during sampling.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to which the SenseNova flow shift sampling configuration is applied. | MODEL | Yes | - |
| `shift` | The flow shift value to set on the SenseNova model sampling (default: 3.0; UI step: 0.01). | FLOAT | Yes | No minimum or maximum defined |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | A clone of the input model with the SenseNova flow shift applied to its sampling configuration. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SenseNovaSamplingOptions/en.md)

***

**Source fingerprint (SHA-256):** `b0dea4a5c226bccb54bb1d70e8ea2791a645018853571429c556034351e9e75a`


# StyleModelLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StyleModelLoader

This node will detect models located in the ComfyUI/models/stylemodels folder, and it will also read models from additional paths configured in the extramodelpaths.yaml file.

This node will detect models located in the `ComfyUI/models/style_models` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The StyleModelLoader node is designed to load a style model from a specified path. It focuses on retrieving and initializing style models that can be used to apply specific artistic styles to images, thereby enabling the customization of visual outputs based on the loaded style model.

## Inputs

| Parameter Name | Description | Comfy dtype | Python dtype |
| - | - | - | - |
| `style_model_name` | Specifies the name of the style model to be loaded. This name is used to locate the model file within a predefined directory structure, allowing for the dynamic loading of different style models based on user input or application needs. | COMBO\[STRING] | `str` |

## Outputs

| Parameter Name | Description | Comfy dtype | Python dtype |
| - | - | - | - |
| `style_model` | Returns the loaded style model, ready for use in applying styles to images. This enables the dynamic customization of visual outputs by applying different artistic styles. | `STYLE_MODEL` | `StyleModel` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StyleModelLoader/en.md)


# TemporalScoreRescaling - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TemporalScoreRescaling

This node applies Temporal Score Rescaling (TSR) to a diffusion model.

This node applies Temporal Score Rescaling (TSR) to a diffusion model. It patches the model so that, during sampling, the predicted score or noise is rescaled to steer the diversity of generated results. This is implemented as a post-CFG (Classifier-Free Guidance) function.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to be patched with the TSR function. | MODEL | Yes | - |
| `tsr_k` | Controls the rescaling strength. Lower k produces more detailed results; higher k produces smoother results in image generation. Setting k = 1 disables rescaling. (default: 0.95) | FLOAT | Yes | 0.01 - 100.0 |
| `tsr_sigma` | Controls how early rescaling takes effect. Larger values take effect earlier. (default: 1.0) | FLOAT | Yes | 0.01 - 100.0 |

Note: Rescaling is skipped when `tsr_k` is set to 1, when the sigma value is 0, or when the signal-to-noise ratio is 0.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `patched_model` | The input model, now patched with the Temporal Score Rescaling function applied to its sampling process. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TemporalScoreRescaling/en.md)

***

**Source fingerprint (SHA-256):** `4d4e3c64fb6e3a3fe4725ea944a361b46d871943a10e65d72d70e0e6d757dfca`


# TomePatchModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TomePatchModel

TomePatchModel applies Token Merging (ToMe) to a diffusion model to reduce computational cost during inference.

TomePatchModel applies Token Merging (ToMe) to a diffusion model to reduce computational cost during inference. It works by merging similar tokens inside the model's attention mechanism, so the model processes fewer tokens while keeping output quality largely intact.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to apply token merging to | MODEL | Yes | - |
| `ratio` | The proportion of tokens to merge (default: 0.3). Higher values merge more tokens, which can give greater speedup but potentially lower quality. | FLOAT | Yes | 0.0 - 1.0 |

Note: If the number of tokens in an attention block is small enough that no downsampling is needed, the merging functions are replaced with no-ops, and the model runs unchanged for that block.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with token merging applied | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TomePatchModel/en.md)

***

**Source fingerprint (SHA-256):** `1202c0df17f357440cd156fa0920f70c18a318e32c41dc04cecff11613f0072f`


# TripleCLIPLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripleCLIPLoader

TripleCLIPLoader loads three text encoder models at the same time and combines them into a single CLIP model.

TripleCLIPLoader loads three text encoder models at the same time and combines them into a single CLIP model. It is used for workflows that need multiple text encoders working together, such as SD3, which uses clip-l, clip-g, and t5 models.

A common recipe for SD3 is: clip-l, clip-g, t5.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip_name1` | The first text encoder model to load from the available text encoders | COMBO | Yes | Multiple options available (all files in the text\_encoders folder) |
| `clip_name2` | The second text encoder model to load from the available text encoders | COMBO | Yes | Multiple options available (all files in the text\_encoders folder) |
| `clip_name3` | The third text encoder model to load from the available text encoders | COMBO | Yes | Multiple options available (all files in the text\_encoders folder) |

**Note:** All three parameters are required. The available options are the text encoder files in your text\_encoders folder. If a selected file cannot be found, the node raises an error. The node loads all three selected models and combines them into a single CLIP model.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `CLIP` | A combined CLIP model containing all three loaded text encoders | CLIP |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripleCLIPLoader/en.md)

***

**Source fingerprint (SHA-256):** `edb341093c4c86ec4d8e024dffa7e33311f600e61ec8ef1813da6d28474f8233`


# UNETLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UNETLoader

The UNETLoader node is designed for loading U-Net models by name, facilitating the use of pre-trained U-Net architectures within the system.

The UNETLoader node is designed for loading U-Net models by name, facilitating the use of pre-trained U-Net architectures within the system.

This node will detect models located in the `ComfyUI/models/diffusion_models` folder.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `unet_name` | Specifies the name of the U-Net model to be loaded. This name is used to locate the model within a predefined directory structure, enabling the dynamic loading of different U-Net models. | COMBO\[STRING] |
| `weight_dtype` | 🚧  fp8\_e4m3fn fp9\_e5m2 | ... |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | Returns the loaded U-Net model, allowing it to be utilized for further processing or inference within the system. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/UNETLoader/en.md)


# USOStyleReference - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/USOStyleReference

The USOStyleReference node applies a style reference to a model by combining CLIP vision features with a model patch, and returns a patched copy of the input model.

The USOStyleReference node applies a style reference to a model by combining CLIP vision features with a model patch, and returns a patched copy of the input model. The visual style information is combined with the model's text conditioning so it can influence generation. This node is intended for Flux models and is marked as experimental.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The base model to which the style reference patch is applied. | MODEL | Yes | - |
| `model_patch` | The model patch containing the projection model used to encode the reference image features. | MODEL\_PATCH | Yes | - |
| `clip_vision_output` | The encoded visual features extracted from CLIP vision processing of the reference image. | CLIP\_VISION\_OUTPUT | Yes | - |

Note: The `clip_vision_output` must come from a CLIP vision model that provides the full hidden states and the penultimate hidden state. The node combines the 20th-from-last, 11th-from-last, and penultimate hidden states into the style embedding. The `model_patch` must expose a projection model through its `model` attribute that converts these image features into the style embedding. During sampling, the style embedding is prepended to the text conditioning so it can influence generation, and matching zero-position text IDs are prepended to the text IDs so the identifier sequence stays aligned with the extended conditioning.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with the style reference patch applied. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/USOStyleReference/en.md)

***

**Source fingerprint (SHA-256):** `9033dddb76fafb388c67dcd09d96102a7ab3e5bc416cec61bf18d088da37a0f0`


# UpscaleModelLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UpscaleModelLoader

This node will detect models located in the ComfyUI/models/upscalemodels folder, and it will also read models from additional paths configured in the extramodelpaths.yaml file.

This node will detect models located in the `ComfyUI/models/upscale_models` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The UpscaleModelLoader node is designed for loading upscale models from a specified directory. It facilitates the retrieval and preparation of upscale models for image upscaling tasks, ensuring that the models are correctly loaded and configured for evaluation.

## Inputs

| Field | Description | Comfy dtype |
| - | - | - |
| `model_name` | Specifies the name of the upscale model to be loaded, identifying and retrieving the correct model file from the upscale models directory. | `COMBO[STRING]` |

## Outputs

| Field | Description | Comfy dtype |
| - | - | - |
| `upscale_model` | Returns the loaded and prepared upscale model, ready for use in image upscaling tasks. | `UPSCALE_MODEL` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/UpscaleModelLoader/en.md)


# VAEEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEEncode

This node is designed for encoding images into a latent space representation using a specified VAE model.

This node is designed for encoding images into a latent space representation using a specified VAE model. It abstracts the complexity of the encoding process, providing a straightforward way to transform images into their latent representations.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `pixels` | The 'pixels' parameter represents the image data to be encoded into the latent space. It plays a crucial role in determining the output latent representation by serving as the direct input for the encoding process. | `IMAGE` |
| `vae` | The 'vae' parameter specifies the Variational Autoencoder model to be used for encoding the image data into latent space. It is essential for defining the encoding mechanism and characteristics of the generated latent representation. | VAE |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output is a latent space representation of the input image, encapsulating its essential features in a compressed form. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEEncode/en.md)


# VAEEncodeAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEEncodeAudio

The VAE Encode Audio node converts audio data into a latent representation using a Variational Autoencoder (VAE).

The VAE Encode Audio node converts audio data into a latent representation using a Variational Autoencoder (VAE). It processes the incoming audio through the VAE to produce compressed latent samples that can be used for further audio generation or manipulation tasks. If the audio's sample rate differs from the VAE's expected sample rate, the audio is automatically resampled before encoding.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | The audio data to encode, containing waveform and sample rate information | AUDIO | Yes | - |
| `vae` | The Variational Autoencoder model used to encode the audio into latent space | VAE | Yes | - |

**Note:** The audio input is automatically resampled to match the VAE's expected sample rate (default: 44100 Hz) if the original sample rate differs from this value. If the input audio is None (for example, when the source video has no audio track), the node will raise an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | The encoded audio representation in latent space, containing compressed samples | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEEncodeAudio/en.md)

***

**Source fingerprint (SHA-256):** `224563af40a377a37209b26ec8becf035560da273b18293634f684e18c5e63ed`


# VAEEncodeForInpaint - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEEncodeForInpaint

This node is designed for encoding images into a latent representation suitable for inpainting tasks, incorporating additional preprocessing steps to adjust the input image and mas

This node is designed for encoding images into a latent representation suitable for inpainting tasks, incorporating additional preprocessing steps to adjust the input image and mask for optimal encoding by the VAE model.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `pixels` | The input image to be encoded. This image undergoes preprocessing and resizing to match the VAE model's expected input dimensions before encoding. | `IMAGE` |
| `vae` | The VAE model used for encoding the image into its latent representation. It plays a crucial role in the transformation process, determining the quality and characteristics of the output latent space. | VAE |
| `mask` | A mask indicating the regions of the input image to be inpainted. It is used to modify the image before encoding, ensuring that the VAE focuses on the relevant areas. | `MASK` |
| `grow_mask_by` | Specifies how much to expand the inpainting mask to ensure seamless transitions in the latent space. A larger value increases the area affected by inpainting. | `INT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output includes the encoded latent representation of the image and a noise mask, both crucial for subsequent inpainting tasks. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEEncodeForInpaint/en.md)


# VAEEncodeTiled - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEEncodeTiled

VAEEncodeTiled processes images by breaking them into smaller tiles and encoding them using a Variational Autoencoder.

VAEEncodeTiled processes images by breaking them into smaller tiles and encoding them using a Variational Autoencoder. This tiled approach allows handling large images that might otherwise exceed memory limitations. The node supports both image and video VAEs, with separate tiling controls for spatial and temporal dimensions.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `pixels` | The input image data to be encoded. | IMAGE | Yes | - |
| `vae` | The Variational Autoencoder model used for encoding. | VAE | Yes | - |
| `tile_size` | The size of each tile for spatial processing (default: 512). Advanced setting. | INT | Yes | 64-4096 (step: 64) |
| `overlap` | The amount of overlap between adjacent tiles (default: 64). Advanced setting. | INT | Yes | 0-4096 (step: 32) |
| `temporal_size` | Only used for video VAEs: Amount of frames to encode at a time (default: 64). Advanced setting. | INT | Yes | 8-4096 (step: 4) |
| `temporal_overlap` | Only used for video VAEs: Amount of frames to overlap (default: 8). Advanced setting. | INT | Yes | 4-4096 (step: 4) |

**Note:** The `temporal_size` and `temporal_overlap` parameters are only relevant when using video VAEs and have no effect on standard image VAEs.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | The encoded latent representation of the input image. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEEncodeTiled/en.md)

***

**Source fingerprint (SHA-256):** `c36b02f8eeed5c72f9efa2392e2013e89be7644c022d987d413d4da088dfbaad`


# VAELoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAELoader

This node will detect models located in the ComfyUI/models/vae folder, and it will also read models from additional paths configured in the extramodelpaths.yaml file.

This node will detect models located in the `ComfyUI/models/vae` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The VAELoader node is designed for loading Variational Autoencoder (VAE) models, specifically tailored to handle both standard and approximate VAEs. It supports loading VAEs by name, including specialized handling for 'taesd' and 'taesdxl' models, and dynamically adjusts based on the VAE's specific configuration.

## Inputs

| Field | Description | Comfy dtype |
| - | - | - |
| `vae_name` | Specifies the name of the VAE to be loaded, determining which VAE model is fetched and loaded, with support for a range of predefined VAE names including 'taesd' and 'taesdxl'. | `COMBO[STRING]` |

## Outputs

| Field | Description | Data Type |
| - | - | - |
| `vae` | Returns the loaded VAE model, ready for further operations such as encoding or decoding. The output is a model object encapsulating the loaded model's state. | `VAE` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAELoader/en.md)


# VAESave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAESave

The VAESave node is designed for saving VAE models along with their metadata, including prompts and additional PNG information, to a specified output directory.

The VAESave node is designed for saving VAE models along with their metadata, including prompts and additional PNG information, to a specified output directory. It encapsulates the functionality to serialize the model state and associated information into a file, facilitating the preservation and sharing of trained models.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `vae` | The VAE model to be saved. This parameter is crucial as it represents the model whose state is to be serialized and stored. | VAE |
| `filename_prefix` | A prefix for the filename under which the model and its metadata will be saved. This allows for organized storage and easy retrieval of models. | STRING |

## Outputs

The node doesn't have output types.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAESave/en.md)


# WanContextWindowsManual - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanContextWindowsManual

The WAN Context Windows (Manual) node lets you manually configure context windows for Wan-style video models.

The WAN Context Windows (Manual) node lets you manually configure context windows for Wan-style video models. It applies these settings during sampling, giving you control over the window length, overlap, scheduling, and fusion method used while the model processes video. Context length and overlap are specified in real frames and are converted internally for the model's 2D processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply context windows to during sampling. | MODEL | Yes | - |
| `context_length` | The length of the context window in real frames. Must be 4\*n + 1 (default: 81). | INT | Yes | 1 to 16384 (MAX\_RESOLUTION), step 4 |
| `context_overlap` | The overlap of the context window in real frames (default: 30). | INT | Yes | 0 or higher |
| `context_schedule` | Step-dependent scheduling algorithm for context windows (default: "uniform\_standard"). | COMBO | Yes | `"static_standard"`<br />`"uniform_standard"`<br />`"uniform_looped"`<br />`"batched"` |
| `context_stride` | The stride of the context window; only applicable to uniform schedules (default: 1). | INT | Yes | 1 or higher |
| `closed_loop` | Whether to close the context window loop; only applicable to looped schedules (default: False). | BOOLEAN | Yes | - |
| `fuse_method` | The method to use to fuse the context windows (default: "pyramid"). | COMBO | Yes | `"pyramid"`<br />`"gaussian"`<br />`"average"`<br />`"overlap"` |
| `freenoise` | Whether to apply FreeNoise noise shuffling, improves window blending (default: True). | BOOLEAN | Yes | - |
| `retain_first_frame` | Retain the first I2V frame in every context window (may help retain initial reference) (default: False). | BOOLEAN | Yes | - |
| `split_conds_to_windows` | Whether to split multiple conditionings (created by ConditionCombine) to each window based on region index (default: False). | BOOLEAN | Yes | - |

**Note:** `context_stride` only affects uniform schedules, and `closed_loop` only applies to looped schedules. The context length and overlap are specified in real frames and are automatically converted and clamped to minimum valid values during processing (`context_length` becomes ((length - 1) / 4) + 1, `context_overlap` becomes overlap / 4). `context_length` must follow the form 4\*n + 1. `retain_first_frame` is intended for image-to-video use. `split_conds_to_windows` expects multiple conditionings created by the ConditionCombine node. The `fuse_method` parameter includes several options beyond just "pyramid".

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The model with the applied context window configuration. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanContextWindowsManual/en.md)

***

**Source fingerprint (SHA-256):** `cf4927371e9d4b509f2e6e5319cd6109e3ef36da6b3faee278bcf8c906672857`


# WanUni3CControlnetApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanUni3CControlnetApply

Documentation for WanUni3CControlnetApply node.

## Overview

This node applies a Uni3C ControlNet to a Wan video diffusion model, using a rendered guidance video (e.g., warped point cloud renders) to influence the model's output. It injects control signals at specific block layers, enabling camera-trajectory-based guidance during video generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Wan diffusion model to patch. | MODEL | Yes | – |
| `model_patch` | A Uni3C ControlNet patch (must be an instance of `comfy.ldm.wan.uni3c.WanUni3CControlnet`). | MODEL\_PATCH | Yes | – |
| `vae` | The VAE used to encode the guidance video into latents. | VAE | Yes | – |
| `render_video` | The guidance video rendered from the camera trajectory, most commonly warped point cloud renders of the input image. | IMAGE | Yes | – |
| `strength` | The strength of the control signal applied. | FLOAT | Yes | -10.0 to 10.0 (default: 1.0) |
| `start_percent` | The percentage of the denoising process at which the control starts. | FLOAT | Yes | 0.0 to 1.0 (default: 0.0) |
| `end_percent` | The percentage of the denoising process at which the control ends. | FLOAT | Yes | 0.0 to 1.0 (default: 1.0) |

**Notes:**

* The `model_patch` must be a Uni3C ControlNet; otherwise the node raises an error.
* The Uni3C ControlNet only works with Wan models; an error is raised if the model is not Wan-based.
* The controlnet's internal dimension must match the Wan model's dimension – an error is raised if they differ.
* The `render_video` input image is expected to be in RGB format (only the first 3 channels are used).
* This node is experimental.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The patched Wan model with the Uni3C ControlNet applied. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanUni3CControlnetApply/en.md)

***

**Source fingerprint (SHA-256):** `f69253f06aba9208778f713ad36e9995f53a15d2e61243b853b9ac9131637371`


# ZImageFunControlnet - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ZImageFunControlnet

ZImageFunControlnet applies a control network patch to a base model so it can guide the image generation or editing process.

ZImageFunControlnet applies a control network patch to a base model so it can guide the image generation or editing process. It combines a model, a model patch, and a VAE, and lets you control how strongly the control effect influences the result. Optional image, inpainting image, and mask inputs allow more targeted edits.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The base model used for the generation process. | MODEL | Yes | - |
| `model_patch` | A specialized patch model that applies the control network's guidance. | MODEL\_PATCH | Yes | - |
| `vae` | The Variational Autoencoder used for encoding and decoding images. | VAE | Yes | - |
| `strength` | The strength of the control network's influence. Positive values apply the effect, while negative values can invert it (default: 1.0). | FLOAT | Yes | -10.0 to 10.0 (step 0.01) |
| `image` | An optional base image to guide the generation process. | IMAGE | No | - |
| `inpaint_image` | An optional image used specifically for inpainting areas defined by a mask. | IMAGE | No | - |
| `mask` | An optional mask that defines which areas of an image should be edited or inpainted. | MASK | No | - |

**Note:** The `inpaint_image` parameter is typically used in conjunction with a `mask` to specify the content for inpainting. The node's behavior may change based on which optional inputs are provided (e.g., using `image` for guidance or using `image`, `mask`, and `inpaint_image` for inpainting).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The model with the control network patch applied, ready for use in a sampling pipeline. | MODEL |
| `positive` | The positive conditioning, potentially modified by the control network inputs. | CONDITIONING |
| `negative` | The negative conditioning, potentially modified by the control network inputs. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ZImageFunControlnet/en.md)

***

**Source fingerprint (SHA-256):** `e1946190a06c52dd951078d9cb753962081957cb6c38accdea26eb4129a51793`


# unCLIPCheckpointLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/unCLIPCheckpointLoader

This node will detect models located in the ComfyUI/models/checkpoints folder, and it will also read models from additional paths configured in the extramodelpaths.yaml file.

This node will detect models located in the `ComfyUI/models/checkpoints` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The unCLIPCheckpointLoader node is designed for loading checkpoints specifically tailored for unCLIP models. It facilitates the retrieval and initialization of models, CLIP vision modules, and VAEs from a specified checkpoint, streamlining the setup process for further operations or analyses.

## Inputs

| Field | Description | Comfy dtype |
| - | - | - |
| `ckpt_name` | Specifies the name of the checkpoint to be loaded, identifying and retrieving the correct checkpoint file from a predefined directory, determining the initialization of models and configurations. | `COMBO[STRING]` |

## Outputs

| Field | Description | Comfy dtype | Python dtype |
| - | - | - | - |
| `model` | Represents the primary model loaded from the checkpoint. | `MODEL` | `torch.nn.Module` |
| `clip` | Represents the CLIP module loaded from the checkpoint, if available. | `CLIP` | `torch.nn.Module` |
| `vae` | Represents the VAE module loaded from the checkpoint, if available. | `VAE` | `torch.nn.Module` |
| `clip_vision` | Represents the CLIP vision module loaded from the checkpoint, if available. | `CLIP_VISION` | `torch.nn.Module` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/unCLIPCheckpointLoader/en.md)


# APG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/APG

The APG (Adaptive Projected Guidance) node modifies the sampling process by adjusting how guidance is applied during diffusion.

The APG (Adaptive Projected Guidance) node modifies the sampling process by adjusting how guidance is applied during diffusion. It separates the guidance vector into parallel and orthogonal components relative to the conditional output, allowing for more controlled image generation. The node provides parameters to scale the guidance, normalize its magnitude, and apply momentum for smoother transitions between diffusion steps.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model to apply adaptive projected guidance to | MODEL | Yes | - |
| `eta` | Controls the scale of the parallel guidance vector. Default CFG behavior at a setting of 1 (default: 1.0). | FLOAT | No | -10.0 to 10.0 |
| `norm_threshold` | Normalize guidance vector to this value, normalization disabled at a setting of 0 (default: 5.0). | FLOAT | No | 0.0 to 50.0 |
| `momentum` | Controls a running average of guidance during diffusion, disabled at a setting of 0 (default: 0.0). | FLOAT | No | -5.0 to 1.0 |

Note: When the noise level (`sigma`) increases during sampling, the momentum running average resets to zero. If the model provides only a single conditioning output (no separate unconditional conditioning), the guidance adjustment is skipped and the conditioning is left unchanged.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | Returns the modified model with adaptive projected guidance applied to its sampling process | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/APG/en.md)

***

**Source fingerprint (SHA-256):** `df0c76aee28479d49c4e471e54d1d32082adc6921a6a50b506675144a79e018a`


# AddNoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AddNoise

This node adds controlled noise to a latent image using a specified noise generator and sigma values.

This node adds controlled noise to a latent image using a specified noise generator and sigma values. It processes the input through the model's sampling system to apply noise scaling appropriate for the given sigma range, returning a new latent representation with the noise applied. This node is currently marked as experimental.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model containing sampling parameters and processing functions | MODEL | Yes | - |
| `noise` | The noise generator that produces the base noise pattern | NOISE | Yes | - |
| `sigmas` | Sigma values controlling the noise scaling intensity. If empty, the node returns the original latent image unchanged. When multiple sigmas are provided, the noise scale is calculated as the absolute difference between the first and last sigma values. When only one sigma is provided, that value is used directly as the scale. | SIGMAS | Yes | - |
| `latent_image` | The input latent representation to which noise will be added. Empty latent images (containing only zeros) are not shifted during processing. | LATENT | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `LATENT` | The modified latent representation with added noise. Any NaN or infinite values in the output are converted to zeros for stability. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AddNoise/en.md)

***

**Source fingerprint (SHA-256):** `6b11db10af9a2b8ea24dbf3b40c08d7e37de39df746e3966e5bfc94b84dee068`


# AlignYourStepsScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AlignYourStepsScheduler

The AlignYourStepsScheduler node generates sigma values (noise levels) for the denoising process based on different model types.

The AlignYourStepsScheduler node generates sigma values (noise levels) for the denoising process based on different model types. It calculates appropriate noise levels for each step of the sampling process and adjusts the total number of steps according to the `denoise` parameter, helping align the sampling steps with the specific requirements of different diffusion models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_type` | Specifies the type of model to use for sigma calculation (default: "SD1") | COMBO | Yes | `"SD1"`<br />`"SDXL"`<br />`"SVD"` |
| `steps` | The total number of sampling steps to generate (default: 10) | INT | Yes | 1 to 10000 |
| `denoise` | Controls how much to denoise the image, where 1.0 uses all steps and lower values use fewer steps (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |

Note: Each model type has a built-in noise level schedule containing 11 sigma values (for 10 steps). When `denoise` is 0.0, the node returns an empty sigma tensor. When `denoise` is between 0.0 and 1.0, the effective number of steps is calculated as `round(steps × denoise)`, and only the corresponding last portion of the sigma schedule is used. If the requested `steps` value does not match the built-in schedule length, the noise levels are log-linearly interpolated to match the requested step count. The final sigma value is always set to 0.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sigmas` | Returns the calculated sigma values for the denoising process | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AlignYourStepsScheduler/en.md)

***

**Source fingerprint (SHA-256):** `3adbe1016c1ff4b9b7ad3737f50b168f54444d4ca355488e60537d1136f85d3f`


# BasicGuider - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BasicGuider

The BasicGuider node creates a simple guidance mechanism for the sampling process.

The BasicGuider node creates a simple guidance mechanism for the sampling process. It takes a model and conditioning data as inputs and produces a guider object that can be used to guide the generation process during sampling. This node provides the fundamental guidance functionality needed for controlled generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to be used for guidance | MODEL | Yes | - |
| `conditioning` | The conditioning data that guides the generation process | CONDITIONING | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `GUIDER` | A guider object that can be used during the sampling process to guide generation | GUIDER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BasicGuider/en.md)

***

**Source fingerprint (SHA-256):** `8ea6b56be58ae99baaf13a04c4fadbf8ad921801d8f2ce2aecce768cc34a3b20`


# BasicScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BasicScheduler

The BasicScheduler node is designed to compute a sequence of sigma values for diffusion models based on the provided scheduler, model, and denoising parameters.

The `BasicScheduler` node is designed to compute a sequence of sigma values for diffusion models based on the provided scheduler, model, and denoising parameters. It dynamically adjusts the total number of steps based on the denoise factor to fine-tune the diffusion process, providing precise "recipes" for different stages in advanced sampling processes that require fine control (such as multi-stage sampling).

## Inputs

| Parameter | Metaphor Description | Data Type | Input Type | Default | Range | Technical Purpose |
| - | - | - | - | - | - | - |
| `model` | **Canvas Type**: Different canvas materials need different paint formulas | MODEL | Input | - | - | Diffusion model object, determines sigma calculation basis |
| `scheduler` | **Mixing Technique**: Choose how paint concentration changes | COMBO\[STRING] | Widget | - | 9 options | Scheduling algorithm, controls noise decay mode |
| `steps` | **Mixing Count**: 20 mixes vs 50 mixes precision difference | INT | Widget | 20 | 1-10000 | Sampling steps, affects generation quality and speed |
| `denoise` | **Creation Intensity**: Control level from fine-tuning to repainting | FLOAT | Widget | 1.0 | 0.0-1.0 | Denoising strength, supports partial repainting scenarios |

### Scheduler Types

Based on source code `comfy.samplers.SCHEDULER_NAMES`, supports the following 9 schedulers:

| Scheduler Name | Characteristics | Use Cases | Noise Decay Pattern |
| - | - | - | - |
| **normal** | Standard linear | General scenarios, balanced | Uniform decay |
| **karras** | Smooth transition | High quality, detail-rich | Smooth non-linear decay |
| **exponential** | Exponential decay | Fast generation, efficiency | Exponential rapid decay |
| **sgm\_uniform** | SGM uniform | Specific model optimization | SGM optimized decay |
| **simple** | Simple scheduling | Quick testing, basic use | Simplified decay |
| **ddim\_uniform** | DDIM uniform | DDIM sampling optimization | DDIM specific decay |
| **beta** | Beta distribution | Special distribution needs | Beta function decay |
| **linear\_quadratic** | Linear quadratic | Complex scenario optimization | Quadratic function decay |
| **kl\_optimal** | KL optimal | Theoretical optimization | KL divergence optimized decay |

## Outputs

| Parameter | Metaphor Description | Data Type | Output Type | Technical Meaning |
| - | - | - | - | - |
| `sigmas` | **Paint Recipe Chart**: Detailed paint concentration list for step-by-step use | SIGMAS | Output | Noise level sequence, guides diffusion model denoising process |

## Node Role: Artist's Color Mixing Assistant

Imagine you are an artist creating a clear image from a chaotic mixture of paint (noise). `BasicScheduler` acts like your **professional color mixing assistant**, whose job is to prepare a series of precise paint concentration recipes:

### Workflow

* **Step 1**: Use 90% concentration paint (high noise level)
* **Step 2**: Use 80% concentration paint
* **Step 3**: Use 70% concentration paint
* **...**
* **Final Step**: Use 0% concentration (clean canvas, no noise)

### Color Assistant's Special Skills

**Different mixing methods (scheduler)**:

* **"karras" mixing method**: Paint concentration changes very smoothly, like professional artist's gradient technique
* **"exponential" mixing method**: Paint concentration decreases rapidly, suitable for quick creation
* **"linear" mixing method**: Paint concentration decreases uniformly, stable and controllable

**Fine control (steps)**:

* **20 mixes**: Quick painting, efficiency priority
* **50 mixes**: Fine painting, quality priority

**Creation intensity (denoise)**:

* **1.0 = Complete new creation**: Start completely from blank canvas
* **0.5 = Half transformation**: Keep half of original painting, transform half
* **0.2 = Fine adjustment**: Only make subtle adjustments to original painting

### Collaboration with Other Nodes

`BasicScheduler` (Color Assistant) → Prepare Recipe → `SamplerCustom` (Artist) → Actual Painting → Completed Work

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BasicScheduler/en.md)


# BetaSamplingScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BetaSamplingScheduler

The BetaSamplingScheduler node generates a sequence of noise levels (sigmas) for the sampling process using a beta scheduling algorithm.

The BetaSamplingScheduler node generates a sequence of noise levels (sigmas) for the sampling process using a beta scheduling algorithm. It takes a model and configuration parameters to create a customized noise schedule that controls the denoising process during image generation. This scheduler allows fine-tuning of the noise reduction trajectory through alpha and beta parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model used for sampling, which provides the model sampling object | MODEL | Yes | - |
| `steps` | The number of sampling steps to generate sigmas for (default: 20) | INT | Yes | 1 to 10000 |
| `alpha` | Alpha parameter for the beta scheduler, controlling the scheduling curve (default: 0.6, advanced parameter) | FLOAT | Yes | 0.0 to 50.0 (step 0.01) |
| `beta` | Beta parameter for the beta scheduler, controlling the scheduling curve (default: 0.6, advanced parameter) | FLOAT | Yes | 0.0 to 50.0 (step 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `SIGMAS` | A sequence of noise levels (sigmas) used for the sampling process | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BetaSamplingScheduler/en.md)

***

**Source fingerprint (SHA-256):** `80adae3cbedff7fe544a1fbcf638af7965f1216e422931063ecf67da53ddff95`


# CFGGuider - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CFGGuider

The CFG Guider node creates a guidance system for controlling the sampling process in image generation.

The CFG Guider node creates a guidance system for controlling the sampling process in image generation. It takes a model along with positive and negative conditioning inputs, then applies a classifier-free guidance scale to steer the generation toward desired content while avoiding unwanted elements. This node outputs a guider object that can be used by sampling nodes to control the image generation direction.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to be used for guidance | MODEL | Yes | - |
| `positive` | The positive conditioning that guides the generation toward desired content | CONDITIONING | Yes | - |
| `negative` | The negative conditioning that steers the generation away from unwanted content | CONDITIONING | Yes | - |
| `cfg` | The classifier-free guidance scale that controls how strongly the conditioning influences the generation (default: 8.0) | FLOAT | Yes | 0.0 to 100.0 (step: 0.1) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `GUIDER` | A guider object that can be passed to sampling nodes to control the generation process | GUIDER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CFGGuider/en.md)

***

**Source fingerprint (SHA-256):** `73b57bfbb6d4fc083a8089bc0f786f82d03e0d7b2faeeb7a42b3d87e38047b9e`


# CFGOverride - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CFGOverride

The CFG Override node overrides the CFG (Classifier-Free Guidance) scale to a fixed value over a percentage (sigma) range of the sampling process.

The CFG Override node overrides the CFG (Classifier-Free Guidance) scale to a fixed value over a percentage (sigma) range of the sampling process. When multiple CFG Override nodes are used, the override nearest the sampler wins on overlapping ranges.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to apply the CFG override to. | MODEL | Yes | |
| `cfg` | The fixed CFG scale value to use during the override range. Default: 1.0. | FLOAT | Yes | 0.0 to 100.0 (step: 0.1) |
| `start_percent` | The starting point of the override range as a percentage of the sampling process. Default: 0.0. | FLOAT | Yes | 0.0 to 1.0 (step: 0.001) |
| `end_percent` | The ending point of the override range as a percentage of the sampling process. Default: 1.0. | FLOAT | Yes | 0.0 to 1.0 (step: 0.001) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `MODEL` | The model with the CFG override wrapper applied. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CFGOverride/en.md)

***

**Source fingerprint (SHA-256):** `94c7d3751d90b42479f9cec4bdb3c95eeda405f51224f85d313ff12ec071ec58`


# DisableNoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DisableNoise

This node provides an empty noise configuration that disables noise generation during sampling.

This node provides an empty noise configuration that disables noise generation during sampling. It outputs a special noise object containing no noise data, so any node connected to it skips noise-related operations. It is also searchable under the alias "zero noise".

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| *No input parameters* | This node does not require any input parameters. | - | - | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `NOISE` | Returns an empty noise configuration that can be used to disable noise generation in sampling processes. | NOISE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DisableNoise/en.md)

***

**Source fingerprint (SHA-256):** `b9edcda655dab3196233b6c66fdb41eb0585b153616b793016d532992b922934`


# DualCFGGuider - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DualCFGGuider

The Dual CFG Guider node creates a guidance system for sampling that uses two conditioning inputs together with one negative conditioning input.

The Dual CFG Guider node creates a guidance system for sampling that uses two conditioning inputs together with one negative conditioning input. It applies two separate guidance scales to control how strongly each conditioning influences the generated result, and it supports two ways of combining those scales: "regular" and "nested".

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to use for guidance | MODEL | Yes | - |
| `cond1` | The first positive conditioning input | CONDITIONING | Yes | - |
| `cond2` | The second conditioning input, used as the reference between the first positive conditioning and the negative conditioning | CONDITIONING | Yes | - |
| `negative` | The negative conditioning input | CONDITIONING | Yes | - |
| `cfg_conds` | Guidance scale applied to the first positive conditioning (default: 8.0) | FLOAT | Yes | 0.0 - 100.0 |
| `cfg_cond2_negative` | Guidance scale applied between the second conditioning and the negative conditioning (default: 8.0) | FLOAT | Yes | 0.0 - 100.0 |
| `style` | The guidance style to apply (default: "regular"). When set to "nested", the guidance is applied in a nested fashion | COMBO | Yes | "regular"<br />"nested" |

Note: In `regular` style, `cfg_cond2_negative` is applied between `cond2` and `negative`, and `cfg_conds` is applied between `cond1` and `cond2`. In `nested` style, `cfg_conds` is applied first between `cond1` and `cond2`, and the resulting prediction is then guided away from `negative` using `cfg_cond2_negative`.

Note: In `regular` style, when `cfg_cond2_negative` is equal to 1.0 the negative conditioning is skipped, and when `cfg_conds` is also equal to 1.0 the second conditioning is skipped as well. This reduces the number of model evaluations performed.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `GUIDER` | A configured guidance system ready for use with sampling | GUIDER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DualCFGGuider/en.md)

***

**Source fingerprint (SHA-256):** `ef28d109149cb545bcd76215fd99535905c1d395222149a029c1c210e2912e97`


# DualModelGuider - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DualModelGuider

This node allows you to use two different models during the guided CFG sampling process: one model for the positive (conditional) pass and a separate model for the negative (uncond

This node allows you to use two different models during the guided CFG sampling process: one model for the positive (conditional) pass and a separate model for the negative (unconditional) pass. When no negative model is provided, it behaves like a standard CFG guider using a single model.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model used for the positive (conditional) pass. | MODEL | Yes | |
| `model_negative` | Model used for the negative (unconditional) pass. Use the same model for ordinary CFG. | MODEL | No | |
| `positive` | The positive conditioning input. | CONDITIONING | Yes | |
| `cfg` | The CFG scale value (default: 4.0). | FLOAT | Yes | 0.0 to 100.0 (step: 0.1) |
| `negative` | Negative conditioning run on the negative model. Leave unconnected for a text-free (image-only) unconditional pass. | CONDITIONING | No | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `GUIDER` | A guider object configured with the specified models and conditioning for use in sampling. | GUIDER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DualModelGuider/en.md)

***

**Source fingerprint (SHA-256):** `a60803156e98d2ffe975d39922dfbeacafd1a2155d88dd2e285ac1426a1e7a33`


# ExponentialScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ExponentialScheduler

The ExponentialScheduler node is designed to generate a sequence of sigma values following an exponential schedule for diffusion sampling processes.

The `ExponentialScheduler` node is designed to generate a sequence of sigma values following an exponential schedule for diffusion sampling processes. It provides a customizable approach to control the noise levels applied at each step of the diffusion process, allowing for fine-tuning of the sampling behavior.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `steps` | Specifies the number of steps in the diffusion process. It influences the length of the generated sigma sequence and thus the granularity of the noise application. | INT |
| `sigma_max` | Defines the maximum sigma value, setting the upper limit of noise intensity in the diffusion process. It plays a crucial role in determining the range of noise levels applied. | FLOAT |
| `sigma_min` | Sets the minimum sigma value, establishing the lower boundary of noise intensity. This parameter helps in fine-tuning the starting point of the noise application. | FLOAT |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `sigmas` | A sequence of sigma values generated according to the exponential schedule. These values are used to control the noise levels at each step of the diffusion process. | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ExponentialScheduler/en.md)


# ExtendIntermediateSigmas - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ExtendIntermediateSigmas

The ExtendIntermediateSigmas node takes an existing sequence of sigma values and inserts additional intermediate sigma values between them.

The ExtendIntermediateSigmas node takes an existing sequence of sigma values and inserts additional intermediate sigma values between them. It allows you to specify how many extra steps to add, the spacing method for interpolation, and optional start and end sigma boundaries to control where the extension occurs within the sigma sequence.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `sigmas` | The input sigma sequence to extend with intermediate values | SIGMAS | Yes | - |
| `steps` | Controls the number of intermediate sigma values inserted between each pair of existing sigmas. The interval between two sigmas is divided into `steps` parts, producing `steps - 1` new values per pair (default: 2, which inserts one value per pair) | INT | Yes | 1 to 100 |
| `start_at_sigma` | Upper sigma boundary for extension. Only sigma intervals whose starting sigma is less than or equal to this value are extended. When set to -1.0, it is treated as infinity, meaning no upper limit is applied. Default: -1.0 | FLOAT | Yes | -1.0 to 20000.0 |
| `end_at_sigma` | Lower sigma boundary for extension. Only sigma intervals whose starting sigma is greater than or equal to this value are extended. Default: 12.0 | FLOAT | Yes | 0.0 to 20000.0 |
| `spacing` | The interpolation method for spacing the intermediate sigma values (default: "linear") | COMBO | Yes | `"linear"`<br />`"cosine"`<br />`"sine"` |

**Note:** The node only inserts intermediate sigmas for sigma intervals where the starting sigma is less than or equal to `start_at_sigma` and greater than or equal to `end_at_sigma`. When `start_at_sigma` is set to -1.0, it is treated as infinity, so only the `end_at_sigma` lower boundary applies.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sigmas` | The extended sigma sequence with additional intermediate values inserted | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ExtendIntermediateSigmas/en.md)

***

**Source fingerprint (SHA-256):** `d761e82ce055bc56a551d3e446117febb2cdbd6c0286ef620d0a078c96f047ba`


# FlipSigmas - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FlipSigmas

The FlipSigmas node is designed to manipulate the sequence of sigma values used in diffusion models by reversing their order and ensuring the first value is non-zero if originally 

The `FlipSigmas` node is designed to manipulate the sequence of sigma values used in diffusion models by reversing their order and ensuring the first value is non-zero if originally zero. This operation is crucial for adapting the noise levels in reverse order, facilitating the generation process in models that operate by gradually reducing noise from data.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `sigmas` | The 'sigmas' parameter represents the sequence of sigma values to be flipped. This sequence is crucial for controlling the noise levels applied during the diffusion process, and flipping it is essential for the reverse generation process. | `SIGMAS` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `sigmas` | The output is the modified sequence of sigma values, flipped and adjusted to ensure the first value is non-zero if originally zero, ready for use in subsequent diffusion model operations. | `SIGMAS` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FlipSigmas/en.md)


# Flux2Scheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Flux2Scheduler

Flux2Scheduler generates a sequence of noise levels (sigmas) for the denoising process, specifically tailored for the Flux model.

Flux2Scheduler generates a sequence of noise levels (sigmas) for the denoising process, specifically tailored for the Flux model. It calculates a schedule based on the number of denoising steps and the dimensions of the target image, which influences the progression of noise removal during image generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `steps` | The number of denoising steps to perform. A higher value typically leads to more detailed results but takes longer to process (default: 20). | INT | Yes | 1 to 4096 |
| `width` | The width of the image to be generated, in pixels. This value influences the noise schedule calculation (default: 1024). | INT | Yes | 16 to 16384 |
| `height` | The height of the image to be generated, in pixels. This value influences the noise schedule calculation (default: 1024). | INT | Yes | 16 to 16384 |

Note: The schedule is computed from the image sequence length, which is derived from `width` and `height` as `(width * height) / 256`, reflecting the model's 16x latent downsampling. Larger images produce longer sequences, which shifts the noise schedule accordingly.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sigmas` | A sequence of noise level values (sigmas) that define the denoising schedule for the sampler. | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Flux2Scheduler/en.md)

***

**Source fingerprint (SHA-256):** `9606177f37f7bc03aef524623f03b7f24bcdc3d9327dcdf74863fe2befeb2b65`


# GITSScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GITSScheduler

The GITSScheduler node generates noise schedule sigmas for the GITS (Generative Iterative Time Steps) sampling method.

The GITSScheduler node generates noise schedule sigmas for the GITS (Generative Iterative Time Steps) sampling method. It calculates sigma values based on a coefficient parameter and number of steps, with a denoising factor that can reduce the total steps used. The node uses pre-defined noise levels and interpolation to create the final sigma schedule.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `coeff` | Advanced parameter. The coefficient value that controls the noise schedule curve (default: 1.20). The value is rounded to two decimals and selects which pre-defined noise level table is used. | FLOAT | Yes | 0.80 - 1.50 (step 0.05) |
| `steps` | The total number of sampling steps to generate sigmas for (default: 10). | INT | Yes | 2 - 1000 |
| `denoise` | Denoising factor that reduces the number of steps used (default: 1.0). | FLOAT | Yes | 0.0 - 1.0 (step 0.01) |

**Note:** When `denoise` is 0.0 or less, the node returns an empty tensor. When `denoise` is less than 1.0, the actual number of steps used is calculated as `round(steps * denoise)`, and only the last corresponding part of the schedule is kept. For steps between 2 and 20, the node selects a matching pre-defined noise schedule. For steps greater than 20, the node uses log-linear interpolation to extend the pre-defined noise levels to the desired number of steps.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sigmas` | The generated sigma values for the noise schedule. For N sampling steps, N+1 sigma values are returned, and the last sigma is set to 0. | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GITSScheduler/en.md)

***

**Source fingerprint (SHA-256):** `f46681970fece985f6a4b62d0817d1ea306f1ca9a20189f937512dd5717f458b`


# Ideogram4Scheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Ideogram4Scheduler

The Ideogram 4 Scheduler node generates a sequence of sigma values (noise levels) for the diffusion sampling process, based on the Ideogram 4 reference schedule.

The Ideogram 4 Scheduler node generates a sequence of sigma values (noise levels) for the diffusion sampling process, based on the Ideogram 4 reference schedule. It creates a custom noise schedule that adapts to the image dimensions and allows fine-tuning through statistical parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `steps` | The number of sampling steps to generate the schedule for (default: 20). The output contains `steps + 1` sigma values. | INT | Yes | 1 to 200 |
| `width` | The width of the image in pixels (default: 1024). The resolution relative to a 512×512 reference shifts the noise schedule. | INT | Yes | 256 to 8192 (step: 16) |
| `height` | The height of the image in pixels (default: 1024). The resolution relative to a 512×512 reference shifts the noise schedule. | INT | Yes | 256 to 8192 (step: 16) |
| `mu` | The mean parameter for the logit-normal distribution, controlling the central noise level. Combined with the resolution term to form the logSNR shift (default: 0.0). | FLOAT | Yes | -10.0 to 10.0 (step: 0.05) |
| `std` | The standard deviation parameter for the logit-normal distribution, controlling the spread of noise levels (default: 1.75). | FLOAT | Yes | 0.1 to 5.0 (step: 0.05) |

Note: The schedule is derived from a logit-normal distribution over reference time. A resolution term equal to `0.5 * log((width × height) / (512 × 512))` is added to `mu`, so larger or smaller images shift the schedule relative to a 512×512 reference at the same `mu` value.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `SIGMAS` | A tensor of sigma values representing the noise schedule, with length equal to `steps + 1`. The values descend from high noise to low noise, with the final value set to 0.0 for complete denoising. | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Ideogram4Scheduler/en.md)

***

**Source fingerprint (SHA-256):** `af0749713ce223d2246fc24b5100f18aa68d56746480990282899c223578b8f4`


# KSampler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KSampler

The KSampler works like this: it modifies the provided original latent image information based on a specific model and both positive and negative conditions.

The KSampler works like this: it modifies the provided original latent image information based on a specific model and both positive and negative conditions.
First, it adds noise to the original image data according to the set **seed** and **denoise strength**, then inputs the preset **Model** combined with **positive** and **negative** guidance conditions to generate the image.

## Inputs

| Parameter Name | Description | Data Type | Required | Default | Range/Options |
| - | - | - | - | - | - |
| Model | Input model used for the denoising process | checkpoint | Yes | None | - |
| seed | Used to generate random noise, using the same "seed" generates identical images | Int | Yes | 0 | 0 \~ 18446744073709551615 |
| steps | Number of steps to use in denoising process, more steps mean more accurate results | Int | Yes | 20 | 1 \~ 10000 |
| cfg | Controls how closely the generated image matches input conditions, 6-8 recommended | float | Yes | 8.0 | 0.0 \~ 100.0 |
| sampler\_name | Choose sampler for denoising, affects generation speed and style | UI Option | Yes | None | Multiple algorithms |
| scheduler | Controls how noise is removed, affects generation process | UI Option | Yes | None | Multiple schedulers |
| Positive | Positive conditions guiding denoising, what you want to appear in the image | conditioning | Yes | None | - |
| Negative | Negative conditions guiding denoising, what you don't want in the image | conditioning | Yes | None | - |
| Latent\_Image | Latent image used for denoising | Latent | Yes | None | - |
| denoise | Determines noise removal ratio, lower values mean less connection to input image | float | No | 1.0 | 0.0 \~ 1.0 |
| control\_after\_generate | Provides ability to change seed after each prompt | UI Option | No | None | Random/Inc/Dec/Keep |

## Output

| Parameter | Function |
| - | - |
| Latent | Outputs the latent after sampler denoising |

## Source Code

\[Updated on May 15, 2025]

```Python theme={null}

def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False):
    latent_image = latent["samples"]
    latent_image = comfy.sample.fix_empty_latent_channels(model, latent_image)

    if disable_noise:
        noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
    else:
        batch_inds = latent["batch_index"] if "batch_index" in latent else None
        noise = comfy.sample.prepare_noise(latent_image, seed, batch_inds)

    noise_mask = None
    if "noise_mask" in latent:
        noise_mask = latent["noise_mask"]

    callback = latent_preview.prepare_callback(model, steps)
    disable_pbar = not comfy.utils.PROGRESS_BAR_ENABLED
    samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
                                  denoise=denoise, disable_noise=disable_noise, start_step=start_step, last_step=last_step,
                                  force_full_denoise=force_full_denoise, noise_mask=noise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed)
    out = latent.copy()
    out["samples"] = samples
    return (out, )
class KSampler:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "model": ("MODEL", {"tooltip": "The model used for denoising the input latent."}),
                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "control_after_generate": True, "tooltip": "The random seed used for creating the noise."}),
                "steps": ("INT", {"default": 20, "min": 1, "max": 10000, "tooltip": "The number of steps used in the denoising process."}),
                "cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0, "step":0.1, "round": 0.01, "tooltip": "The Classifier-Free Guidance scale balances creativity and adherence to the prompt. Higher values result in images more closely matching the prompt however too high values will negatively impact quality."}),
                "sampler_name": (comfy.samplers.KSampler.SAMPLERS, {"tooltip": "The algorithm used when sampling, this can affect the quality, speed, and style of the generated output."}),
                "scheduler": (comfy.samplers.KSampler.SCHEDULERS, {"tooltip": "The scheduler controls how noise is gradually removed to form the image."}),
                "positive": ("CONDITIONING", {"tooltip": "The conditioning describing the attributes you want to include in the image."}),
                "negative": ("CONDITIONING", {"tooltip": "The conditioning describing the attributes you want to exclude from the image."}),
                "latent_image": ("LATENT", {"tooltip": "The latent image to denoise."}),
                "denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "The amount of denoising applied, lower values will maintain the structure of the initial image allowing for image to image sampling."}),
            }
        }

    RETURN_TYPES = ("LATENT",)
    OUTPUT_TOOLTIPS = ("The denoised latent.",)
    FUNCTION = "sample"

    CATEGORY = "sampling"
    DESCRIPTION = "Uses the provided model, positive and negative conditioning to denoise the latent image."

    def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0):
        return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)

```

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KSampler/en.md)


# KSamplerAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KSamplerAdvanced

The KSamplerAdvanced node is designed to enhance the sampling process by providing advanced configurations and techniques.

The KSamplerAdvanced node is designed to enhance the sampling process by providing advanced configurations and techniques. It aims to offer more sophisticated options for generating samples from a model, improving upon the basic KSampler functionalities.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | Specifies the model from which samples are to be generated, playing a crucial role in the sampling process. | MODEL |
| `add_noise` | Determines whether noise should be added to the sampling process, affecting the diversity and quality of the generated samples. | COMBO\[STRING] |
| `noise_seed` | Sets the seed for noise generation, ensuring reproducibility in the sampling process. | INT |
| `steps` | Defines the number of steps to be taken in the sampling process, impacting the detail and quality of the output. | INT |
| `cfg` | Controls the conditioning factor, influencing the direction and space of the sampling process. | FLOAT |
| `sampler_name` | Selects the specific sampler to be used, allowing for customization of the sampling technique. | COMBO\[STRING] |
| `scheduler` | Chooses the scheduler for controlling the sampling process, affecting the progression and quality of samples. | COMBO\[STRING] |
| `positive` | Specifies the positive conditioning to guide the sampling towards desired attributes. | CONDITIONING |
| `negative` | Specifies the negative conditioning to steer the sampling away from certain attributes. | CONDITIONING |
| `latent_image` | Provides the initial latent image to be used in the sampling process, serving as a starting point. | LATENT |
| `start_at_step` | Determines the starting step of the sampling process, allowing for control over the sampling progression. | INT |
| `end_at_step` | Sets the ending step of the sampling process, defining the scope of the sampling. | INT |
| `return_with_leftover_noise` | Indicates whether to return the sample with leftover noise, affecting the final output's appearance. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `latent` | The output represents the latent image generated from the model, reflecting the applied configurations and techniques. | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KSamplerAdvanced/en.md)


# KSamplerSelect - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KSamplerSelect

The KSamplerSelect node is designed to select a specific sampler based on the provided sampler name.

The KSamplerSelect node is designed to select a specific sampler based on the provided sampler name. It abstracts the complexity of sampler selection, allowing users to easily switch between different sampling strategies for their tasks.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `sampler_name` | Specifies the name of the sampler to be selected. This parameter determines which sampling strategy will be used, impacting the overall sampling behavior and results. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `sampler` | Returns the selected sampler object, ready to be used for sampling tasks. | `SAMPLER` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KSamplerSelect/en.md)


# KarrasScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KarrasScheduler

The KarrasScheduler node is designed to generate a sequence of noise levels (sigmas) based on the Karras et al. (2022) noise schedule.

The KarrasScheduler node is designed to generate a sequence of noise levels (sigmas) based on the Karras et al. (2022) noise schedule. This scheduler is useful for controlling the diffusion process in generative models, allowing for fine-tuned adjustments to the noise levels applied at each step of the generation process.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `steps` | Specifies the number of steps in the noise schedule, affecting the granularity of the generated sigmas sequence. | INT |
| `sigma_max` | The maximum sigma value in the noise schedule, setting the upper bound of noise levels. | FLOAT |
| `sigma_min` | The minimum sigma value in the noise schedule, setting the lower bound of noise levels. | FLOAT |
| `rho` | A parameter that controls the shape of the noise schedule curve, influencing how noise levels progress from sigma\_min to sigma\_max. | FLOAT |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `sigmas` | The generated sequence of noise levels (sigmas) following the Karras et al. (2022) noise schedule. | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KarrasScheduler/en.md)


# LTXVDualCFGGuider - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVDualCFGGuider

This node creates a guided sampling object (CFG guider) for LTXV-AV models.

This node creates a guided sampling object (CFG guider) for LTXV-AV models. It applies a separate guidance scale to the video part and the audio part of a packed LTXV-AV latent, letting you control the influence of conditioning on each modality independently. If the two scales are equal, or if the latent does not contain separate video and audio components, a single overall scale is used instead.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to use when sampling. | MODEL | Yes | - |
| `positive` | Positive conditioning to guide generation toward. | CONDITIONING | Yes | - |
| `negative` | Negative conditioning to steer generation away from. | CONDITIONING | Yes | - |
| `video_cfg` | Guidance strength applied to the video modality of the latent (default: 3.0). | FLOAT | Yes | 0.0 to 100.0 |
| `audio_cfg` | Guidance strength applied to the audio modality of the latent (default: 7.0). | FLOAT | Yes | 0.0 to 100.0 |

Note: When `video_cfg` and `audio_cfg` are equal (or very close in value), the guider uses that value as a single CFG scale for the whole latent. If the latent is not a packed LTXV-AV latent, only the `video_cfg` value is used.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `guider` | The configured CFG guider to be passed to a sampler node. | GUIDER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVDualCFGGuider/en.md)

***

**Source fingerprint (SHA-256):** `8b5ea32d0e73ab4f9b9f053ac7513d621fcc047e1ff468b6d0b5dd2aa3ff791a`


# LTXVScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVScheduler

The LTXVScheduler node generates sigma values for a custom sampling process.

The LTXVScheduler node generates sigma values for a custom sampling process. It calculates the noise schedule from the number of tokens in the provided latent, or uses a default of 4096 tokens when no latent is connected, and can optionally stretch the sigma values so the final value matches the specified `terminal` value.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `steps` | Number of sampling steps (default: 20) | INT | Yes | 1-10000 |
| `max_shift` | Maximum shift value used in the sigma calculation (default: 2.05) | FLOAT | Yes | 0.0-100.0 (step: 0.01) |
| `base_shift` | Base shift value used in the sigma calculation (default: 0.95) | FLOAT | Yes | 0.0-100.0 (step: 0.01) |
| `stretch` | Stretch the sigmas to be in the range \[terminal, 1] (default: True) | BOOLEAN | Yes | True/False |
| `terminal` | The terminal value of the sigmas after stretching (default: 0.1). Used only when `stretch` is enabled. | FLOAT | Yes | 0.0-0.99 (step: 0.01) |
| `latent` | Optional latent input used to calculate the token count for sigma adjustment. When not provided, a default token count of 4096 is used. | LATENT | No | - |

**Note:** When `stretch` is enabled, the non-zero sigma values are rescaled so that the last non-zero sigma equals the `terminal` value.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sigmas` | Sigma values generated for the sampling process | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVScheduler/en.md)

***

**Source fingerprint (SHA-256):** `5b4907e905e27a951c332c400e24023ef089df7a5f4a17b1fc8ba42a41302399`


# LaplaceScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LaplaceScheduler

The LaplaceScheduler node generates a sequence of sigma values following a Laplace distribution for use in diffusion sampling.

The LaplaceScheduler node generates a sequence of sigma values following a Laplace distribution for use in diffusion sampling. It creates a schedule of noise levels that gradually decrease from a maximum to minimum value, using Laplace distribution parameters to control the progression. This scheduler is commonly used in custom sampling workflows to define the noise schedule for diffusion models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `steps` | Number of sampling steps in the schedule (default: 20) | INT | Yes | 1 to 10000 |
| `sigma_max` | Maximum sigma value at the start of the schedule (default: 14.614642) | FLOAT | Yes | 0.0 to 5000.0 |
| `sigma_min` | Minimum sigma value at the end of the schedule (default: 0.0291675) | FLOAT | Yes | 0.0 to 5000.0 |
| `mu` | Mean parameter for the Laplace distribution (default: 0.0) | FLOAT | Yes | -10.0 to 10.0 |
| `beta` | Scale parameter for the Laplace distribution (default: 0.5) | FLOAT | Yes | 0.0 to 10.0 |

Note: `sigma_max`, `sigma_min`, `mu`, and `beta` are advanced parameters.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `SIGMAS` | A sequence of sigma values following a Laplace distribution schedule | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LaplaceScheduler/en.md)

***

**Source fingerprint (SHA-256):** `8e5ca00f4797f863a2cf8b9b115ec27beb7f65981cbb04eb036150402fc19389`


# LoadTrainingDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadTrainingDataset

This node loads an encoded training dataset (latents and conditioning) that was previously saved to disk.

This node loads an encoded training dataset (latents and conditioning) that was previously saved to disk. It reads all `shard_*.pkl` data shard files from a selected dataset folder in the datasets directory and returns the combined latent vectors and conditioning data for use in training workflows.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `folder_name` | Saved dataset to load, from the datasets directory. | COMBO | Yes | One option per dataset folder found in the datasets directory |

Note: The `folder_name` options are built automatically by scanning the datasets directory. A subfolder is listed as a dataset when it contains a `metadata.json` file or at least one `.safetensors` file (the scan does not descend into a folder that matches). The selected dataset folder is searched across all configured dataset root directories, and the folder name must resolve to a subfolder inside one of those roots. The node reads all files named `shard_*.pkl` in the selected folder, in sorted order, and raises an error if no shard files are found or if the folder cannot be located.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latents` | List of latent dicts (output list), where each dict contains a `"samples"` key with a tensor. | LATENT |
| `conditioning` | List of conditioning lists (output list), where each inner list contains conditioning data for the corresponding sample. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadTrainingDataset/en.md)

***

**Source fingerprint (SHA-256):** `9f914b27f067460f6f3b54f3f2a7bb793c65b99c85e8aa14ab64894be26bd816`


# LossGraphNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LossGraphNode

The LossGraphNode creates a line chart of training loss values over training steps and shows it as a preview image.

The LossGraphNode creates a line chart of training loss values over training steps and shows it as a preview image. It reads loss values from a training node, plots them on a graph with labeled axes and min/max loss values, and returns the graph as an image preview in the UI. This node is marked as experimental and is an output node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `loss` | Loss map from training node. It must contain a `loss` key with a list of numeric loss values. | LOSS\_MAP | Yes | - |
| `filename_prefix` | Prefix for the saved loss graph image. (default: "loss\_graph") | STRING | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `ui.images` | The generated loss graph image displayed as a preview. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LossGraphNode/en.md)

***

**Source fingerprint (SHA-256):** `b1f0b72a03d4ce2d9461fc6e312bd1e847455f7dd5227667876a945494ea8cdb`


# MakeTrainingDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MakeTrainingDataset

This node prepares data for training by encoding images and text.

This node prepares data for training by encoding images and text. It takes a list of images and a corresponding list of text captions, then uses a VAE model to convert the images into latent representations and a CLIP model to convert the text into conditioning data. The resulting paired latents and conditioning are output as lists, ready for use in training workflows.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | List of images to encode. | IMAGE | Yes | N/A |
| `vae` | VAE model for encoding images to latents. | VAE | Yes | N/A |
| `clip` | CLIP model for encoding text to conditioning. | CLIP | Yes | N/A |
| `texts` | List of text captions. Can be length n (matching images), 1 (repeated for all), or omitted (uses empty string). | STRING | No | 0, 1, or n items (n = number of images) |

**Parameter Constraints:**

* This node uses list inputs: `images` and `texts` are processed as lists, while `vae` and `clip` accept a single model each (the first item of the supplied list is used).
* The number of items in the `texts` list must be 0, 1, or exactly match the number of items in the `images` list. If it is 0 or omitted, an empty string is used for all images. If it is 1, that single text is repeated for all images. Any other length raises an error.
* The output `latents` and `conditioning` lists always contain the same number of items as the `images` list, so each latent is paired with the conditioning for its corresponding caption.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latents` | List of latent dicts. | LATENT |
| `conditioning` | List of conditioning lists. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MakeTrainingDataset/en.md)

***

**Source fingerprint (SHA-256):** `244adc98810a874cfe42f834e89f96da300d883faeb5791dff19607c13d0c0db`


# ManualSigmas - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ManualSigmas

The ManualSigmas node allows you to manually define a custom sequence of noise levels (sigmas) for the sampling process.

The ManualSigmas node allows you to manually define a custom sequence of noise levels (sigmas) for the sampling process. You input a list of numbers as a string, and the node converts them into a SIGMAS tensor that can be used by other sampling nodes. This is useful for testing or creating specific noise schedules.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `sigmas` | A string containing the sigma values. The node extracts all numbers from this string, including decimals and negative values. For example, "1, 0.5, 0.1" or "1 0.5 0.1". Default: "1, 0.5". | STRING | Yes | Any comma- or space-separated numeric values |

Note: This node is marked as experimental.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sigmas` | A tensor containing the sequence of sigma values extracted from the input string. | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ManualSigmas/en.md)

***

**Source fingerprint (SHA-256):** `19d938ef0eac7343a3138393a039f63632b0763e3884636653c06b91b6f44ed6`


# MeshyAnimateModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyAnimateModelNode

This node applies a specific animation action to a previously rigged 3D character using the Meshy service.

This node applies a specific animation action to a previously rigged 3D character using the Meshy service. It takes a task ID from an earlier rigging operation and an action ID to select the desired animation from the library, then returns the animated model in both GLB and FBX file formats.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `rig_task_id` | The unique task ID from a previously completed Meshy character rigging operation. | MESHY\_RIGGED\_TASK\_ID | Yes | N/A |
| `action_id` | The ID number of the animation action to apply. Visit [https://docs.meshy.ai/en/api/animation-library](https://docs.meshy.ai/en/api/animation-library) for a list of available values. (default: 0) | INT | Yes | 0 to 696 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | A string identifier for the animated model. This output is provided for backward compatibility only. | STRING |
| `GLB` | The animated 3D model file in GLB format. | FILE3DGLB |
| `FBX` | The animated 3D model file in FBX format. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyAnimateModelNode/en.md)

***

**Source fingerprint (SHA-256):** `760e94d3a92910051d9b473545191842dc9672e6c4a59c3d1cd9cfdc5eb2589d`


# MeshyImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyImageToModelNode

The Meshy: Image to Model node uses the Meshy API to generate a 3D model from a single input image.

The Meshy: Image to Model node uses the Meshy API to generate a 3D model from a single input image. It uploads your image, submits a processing task, and returns the generated 3D model files (GLB and FBX) along with the task ID for reference.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Specifies the AI model version to use for generation. | COMBO | Yes | `"meshy-7.1"`<br />`"meshy-7"`<br />`"meshy-6"`<br />`"latest"` |
| `image` | The input image to convert into a 3D model. | IMAGE | Yes | - |
| `should_remesh` | When set to `"false"`, returns an unprocessed triangular mesh. | DYNAMIC\_COMBO | Yes | `"true"`<br />`"false"` |
| `topology` | The target polygon topology for the remeshed model. This input is only available when `should_remesh` is set to `"true"`. | COMBO | No\* | `"triangle"`<br />`"quad"` |
| `target_polycount` | The target number of polygons for the remeshed model. This input is only available when `should_remesh` is set to `"true"`. Default: 300000. | INT | No\* | 100 - 300000 |
| `symmetry_mode` | Controls the symmetry applied to the generated 3D model. | COMBO | Yes | `"auto"`<br />`"on"`<br />`"off"` |
| `should_texture` | Determines whether textures are generated. Setting it to `"false"` skips the texture phase and returns a mesh without textures. | DYNAMIC\_COMBO | Yes | `"true"`<br />`"false"` |
| `enable_pbr` | Generate PBR Maps (metallic, roughness, normal) in addition to the base color. This input is only available when `should_texture` is set to `"true"`. Default: `False`. | BOOLEAN | No\* | - |
| `texture_prompt` | Provide a text prompt to guide the texturing process. Maximum 600 characters. Cannot be used at the same time as `texture_image`. This input is only available when `should_texture` is set to `"true"`. Default: empty string. | STRING | No\* | - |
| `texture_image` | Only one of `texture_image` or `texture_prompt` may be used at the same time. This input is only available when `should_texture` is set to `"true"`. | IMAGE | No\* | - |
| `texture_resolution` | Base color texture resolution. Higher resolutions capture more surface detail. This input is only available when `should_texture` is set to `"true"`. | COMBO | No\* | `"2k"`<br />`"4k"`<br />`"8k"` |
| `pose_mode` | Specify the pose mode for the generated model. This is an advanced parameter. | COMBO | Yes | `""` (empty)<br />`"A-pose"`<br />`"T-pose"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. Default: 0. | INT | Yes | 0 - 2147483647 |
| `ultra_mode` | Run an extra refinement pass for higher-fidelity geometry with finer surface detail. Default: `False`. | BOOLEAN | Yes | - |
| `ultra_resolution` | Resolution of the ultra pass: `"2k"` runs it at 2048³, `"4k"` at 4096³ for the finest surface detail. 4k requires the `"meshy-7.1"` or `"latest"` model. Used only when `ultra_mode` is enabled (default: `"2k"`). | COMBO | No | `"2k"`<br />`"4k"` |

**Note on Parameter Constraints:**

* The `topology` and `target_polycount` inputs are only available when `should_remesh` is set to `"true"`.
* The `enable_pbr`, `texture_prompt`, `texture_image`, and `texture_resolution` inputs are only available when `should_texture` is set to `"true"`.
* When `should_texture` is set to `"true"`, `texture_prompt` and `texture_image` cannot be used at the same time. If both are provided, the node raises an error.
* `texture_prompt` has a maximum length of 600 characters.
* When `ultra_mode` is enabled, the `model` parameter must be set to `"meshy-7.1"`, `"meshy-7"` or `"latest"`; any other model raises an error. With `"meshy-7"` the ultra pass always runs at 2048³, and the `"4k"` ultra resolution requires `"meshy-7.1"` or `"latest"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The filename of the generated GLB model. Maintained for backward compatibility only. | STRING |
| `meshy_task_id` | The unique identifier for the Meshy API task, which can be used for reference or troubleshooting. | MESHY\_TASK\_ID |
| `GLB` | The generated 3D model in the GLB file format. | FILE3DGLB |
| `FBX` | The generated 3D model in the FBX file format. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyImageToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `38528b48c3f792a459008a52f65fae248ef1dadafb37fe4dc6b697d25bc89f4f`


# MeshyMultiImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyMultiImageToModelNode

This node uses the Meshy API to generate a 3D model from multiple input images.

This node uses the Meshy API to generate a 3D model from multiple input images. It uploads the provided images, submits a processing task, and returns the resulting 3D model files (GLB and FBX) along with the task ID for reference.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Specifies the AI model version to use. | COMBO | Yes | `"meshy-7.1"`<br />`"meshy-7"`<br />`"meshy-6"`<br />`"latest"` |
| `should_remesh` | Determines whether the generated mesh is processed. When set to `"false"`, the node returns an unprocessed triangular mesh. When set to `"true"`, the remesh settings below are shown. | DYNAMIC\_COMBO | Yes | `"true"`<br />`"false"` |
| `symmetry_mode` | Controls whether symmetry is applied to the generated model. | COMBO | Yes | `"auto"`<br />`"on"`<br />`"off"` |
| `should_texture` | Determines whether textures are generated. Setting it to `"false"` skips the texture phase and returns a mesh without textures. When set to `"true"`, the texture settings below are shown. | DYNAMIC\_COMBO | Yes | `"true"`<br />`"false"` |
| `pose_mode` | Specify the pose mode for the generated model. | COMBO | Yes | `""` (empty)<br />`"A-pose"`<br />`"T-pose"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | Yes | 0 to 2147483647 |
| `ultra_mode` | Run an extra refinement pass at 2048³ for higher-fidelity geometry with finer surface detail. Requires the `"meshy-7.1"`, `"meshy-7"` or `"latest"` model (default: `False`). | BOOLEAN | No | `True`<br />`False` |

### Remesh Settings (visible when `should_remesh` is `"true"`)

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `topology` | The target polygon type for the remeshed output. | COMBO | No | `"triangle"`<br />`"quad"` |
| `target_polycount` | The target number of polygons for the remeshed model (default: 300000). | INT | No | 100 to 300000 |

### Texture Settings (visible when `should_texture` is `"true"`)

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `enable_pbr` | Generate PBR Maps (metallic, roughness, normal) in addition to the base color. (default: False) | BOOLEAN | No | True / False |
| `texture_prompt` | Provide a text prompt to guide the texturing process. Maximum 600 characters. Cannot be used at the same time as `texture_image`. (default: empty) | STRING | No | Up to 600 characters |
| `texture_image` | Only one of `texture_image` or `texture_prompt` may be used at the same time. | IMAGE | No | - |
| `texture_resolution` | Base color texture resolution. Higher resolutions capture more surface detail. | COMBO | No | `"2k"`<br />`"4k"`<br />`"8k"` |

### Image Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Growable slot: connect 2 to 4 input images (`image_1`, `image_2`, `image_3`, `image_4`). These images are used to generate the 3D model. | IMAGE | Yes | 2 to 4 images |

**Notes**

* You must provide between 2 and 4 images for the `images` input.
* The `topology` and `target_polycount` parameters are only active when `should_remesh` is set to `"true"`.
* The `enable_pbr`, `texture_prompt`, `texture_image`, and `texture_resolution` parameters are only active when `should_texture` is set to `"true"`.
* `texture_prompt` and `texture_image` are mutually exclusive; you cannot use both at the same time. `texture_prompt` is limited to 600 characters.
* The `seed` value does not make results deterministic; changing it simply causes the node to re-run the generation task.
* `ultra_mode` requires the `"meshy-7.1"`, `"meshy-7"` or `"latest"` model; any other model raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The filename of the generated GLB model. This output is provided for backward compatibility only. | STRING |
| `meshy_task_id` | The unique identifier for the Meshy API task. | MESHY\_TASK\_ID |
| `GLB` | The generated 3D model in GLB format. | FILE3DGLB |
| `FBX` | The generated 3D model in FBX format. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyMultiImageToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `9475279c0990fc069b4fef2bf0e2e20218ca1a9591a261ce6d33a2b651782ddb`


# MeshyRefineNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyRefineNode

The Meshy: Refine Draft Model node takes a 3D draft model from a previous Meshy task and improves it, optionally adding textures using a text prompt or a reference image.

The Meshy: Refine Draft Model node takes a 3D draft model from a previous Meshy task and improves it, optionally adding textures using a text prompt or a reference image. It submits the refinement job to the Meshy API and returns the finished model as GLB and FBX files once the task is complete.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model used to refine the draft model. | COMBO | Yes | `"meshy-7.1"`<br />`"meshy-7"`<br />`"meshy-6"`<br />`"latest"` |
| `meshy_task_id` | The unique task ID of the draft model you want to refine. | MESHY\_TASK\_ID | Yes | - |
| `enable_pbr` | Generate PBR Maps (metallic, roughness, normal) in addition to the base color. Note: this should be set to false when using Sculpture style, as Sculpture style generates its own set of PBR maps. (default: False) | BOOLEAN | Yes | - |
| `texture_prompt` | Provide a text prompt to guide the texturing process. Maximum 600 characters. Cannot be used at the same time as `texture_image`. (default: empty string) | STRING | Yes | Maximum 600 characters |
| `texture_image` | Only one of `texture_image` or `texture_prompt` may be used at the same time. | IMAGE | No | - |
| `texture_resolution` | Base color texture resolution. Higher resolutions capture more surface detail. | COMBO | Yes | `"2k"`<br />`"4k"`<br />`"8k"` |

**Note:** The `texture_prompt` and `texture_image` inputs are mutually exclusive. You cannot provide both a text prompt and an image for texturing in the same operation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The filename of the generated GLB model. (For backward compatibility only) | STRING |
| `meshy_task_id` | The unique task ID for the submitted refinement job. | MESHY\_TASK\_ID |
| `GLB` | The final refined 3D model in GLB format. | FILE3DGLB |
| `FBX` | The final refined 3D model in FBX format. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyRefineNode/en.md)

***

**Source fingerprint (SHA-256):** `d9aac584e6abf9688c97bf01ea515bca13844d08c93923a672fb2853266926c8`


# MeshyRigModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyRigModelNode

The Meshy: Rig Model node takes a 3D model from a previous Meshy task and automatically creates a skeleton for it, producing a rigged character that can be posed and animated.

The Meshy: Rig Model node takes a 3D model from a previous Meshy task and automatically creates a skeleton for it, producing a rigged character that can be posed and animated. The node outputs the rigged model in both GLB and FBX file formats.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `meshy_task_id` | The unique task ID from a previous Meshy operation (e.g., text-to-3D or image-to-3D) that generated the model to be rigged. | MESHY\_TASK\_ID | Yes | N/A |
| `height_meters` | The approximate height of the character model in meters. This aids in scaling and rigging accuracy (default: 1.7). | FLOAT | Yes | 0.1 to 15.0 |
| `texture_image` | The model's UV-unwrapped base color texture image. | IMAGE | No | N/A |

**Note:** The auto-rigging process is currently not suitable for untextured meshes, non-humanoid assets, or humanoid assets with unclear limb and body structure.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | A legacy output kept for backward compatibility only, containing the filename of the GLB model. | STRING |
| `rig_task_id` | The unique task ID for this rigging operation, which can be used to reference the result in later Meshy nodes. | MESHY\_RIGGED\_TASK\_ID |
| `GLB` | The rigged 3D character model saved in the GLB file format. | FILE3DGLB |
| `FBX` | The rigged 3D character model saved in the FBX file format. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyRigModelNode/en.md)

***

**Source fingerprint (SHA-256):** `6ae79359fa54f36dd2491a952fe54fa56866038758e8cd475a2d2f8e9e47e3b3`


# MeshyTextToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyTextToModelNode

The Meshy: Text to Model node uses the Meshy API to generate a 3D model from a text description.

The Meshy: Text to Model node uses the Meshy API to generate a 3D model from a text description. It sends a request to the API with your prompt and settings, then waits for the generation to complete and downloads the resulting model files.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Specifies the AI model version to use for generation. | COMBO | Yes | `"meshy-7.1"`<br />`"meshy-7"`<br />`"meshy-6"`<br />`"latest"` |
| `prompt` | The text description of the 3D model you want to generate. Must be between 1 and 600 characters long. Default is an empty string. | STRING | Yes | 1 - 600 characters |
| `style` | The artistic style for the generated 3D model. | COMBO | Yes | `"realistic"` |
| `should_remesh` | When set to false, returns an unprocessed triangular mesh. Selecting "true" reveals additional parameters for topology and target polycount. | DYNAMIC\_COMBO | Yes | `"true"`<br />`"false"` |
| `topology` | The target polygon type for the remeshed model. This parameter is only available when `should_remesh` is set to "true". | COMBO | No\* | `"triangle"`<br />`"quad"` |
| `target_polycount` | The target number of polygons for the remeshed model. Default is 300000. This parameter is only available when `should_remesh` is set to "true". | INT | No\* | 100 - 300000 |
| `symmetry_mode` | Controls symmetry in the generated model. This is an advanced parameter. Options are `"auto"`, `"on"`, and `"off"`. | COMBO | Yes | `"auto"`<br />`"on"`<br />`"off"` |
| `pose_mode` | Specify the pose mode for the generated model. An empty string means no specific pose is requested. This is an advanced parameter. | COMBO | Yes | `""`<br />`"A-pose"`<br />`"T-pose"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. Default is 0. | INT | Yes | 0 - 2147483647 |
| `ultra_mode` | Run an extra refinement pass for higher-fidelity geometry with finer surface detail. Default is false. | BOOLEAN | Yes | true<br />false |
| `ultra_resolution` | Resolution of the ultra pass: `"2k"` runs it at 2048³, `"4k"` at 4096³ for the finest surface detail. 4k requires the `"meshy-7.1"` or `"latest"` model. Used only when `ultra_mode` is enabled (default: `"2k"`). | COMBO | No | `"2k"`<br />`"4k"` |

\*Note: The `topology` and `target_polycount` parameters are conditionally available. They only appear when the `should_remesh` parameter is set to "true".

When `ultra_mode` is enabled, the `model` parameter must be set to `"meshy-7.1"`, `"meshy-7"` or `"latest"`; any other model raises an error. With `"meshy-7"` the ultra pass always runs at 2048³, and the `"4k"` ultra resolution requires `"meshy-7.1"` or `"latest"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The filename of the generated GLB model. This output is provided for backward compatibility. | STRING |
| `meshy_task_id` | The unique identifier for the Meshy API task. | MESHY\_TASK\_ID |
| `GLB` | The generated 3D model file in GLB format. | FILE3DGLB |
| `FBX` | The generated 3D model file in FBX format. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyTextToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `a02a5ae28bcae343c628d11ba3efa952b61b8bdf867669f58f1beb0f7c9e49f9`


# MeshyTextureMultiViewNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyTextureMultiViewNode

This node textures a previously created 3D model using 1 to 4 reference views of the same object.

This node textures a previously created 3D model using 1 to 4 reference views of the same object. You provide the task ID of the original model and the reference images; the node sends them to the Meshy service, waits for the job to finish, and returns the textured model as GLB and FBX files.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model used for the texturing job. Only "meshy-7" is currently available. | COMBO | Yes | `"meshy-7"` |
| `meshy_task_id` | The task ID of the previously created 3D model to be textured. | MESHY\_TASK\_ID | Yes | — |
| `multiview_images` | Reference views of the same object. The first image is the primary (front) view; the order of the remaining views does not matter. Growable slot: connect 1 to 4 images (`image_1` to `image_4`). | IMAGE | Yes | 1 to 4 images |
| `enable_original_uv` | Use the original UV of the model instead of generating new UVs. When enabled, Meshy preserves existing textures from the uploaded model. If the model has no original UV, the quality of the output might not be as good. (default: True; advanced option) | BOOLEAN | No | True / False |
| `pbr` | Enables PBR (physically based rendering) texture generation. (default: False; advanced option) | BOOLEAN | No | True / False |
| `texture_resolution` | Base color texture resolution. Higher resolutions capture more surface detail. | COMBO | Yes | `"2k"`<br />`"4k"`<br />`"8k"` |

**Note:** `multiview_images` must contain between 1 and 4 images. The node validates this at runtime and raises an error if the count is outside this range. If a connected image contains a batch of multiple images, each image in the batch counts toward the limit. The first image is used as the primary (front) view; the order of the remaining images does not matter.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | Model file name. This output is kept for backward compatibility only. | STRING |
| `meshy_task_id` | Task ID of the texturing job. | MESHY\_TASK\_ID |
| `GLB` | The textured 3D model downloaded in GLB format. | FILE3DGLB |
| `FBX` | The textured 3D model downloaded in FBX format. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyTextureMultiViewNode/en.md)

***

**Source fingerprint (SHA-256):** `3a08d003683a182121471a064833c09b932c7c84c20fd5cb5ac0285e135b2b7e`


# MeshyTextureNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyTextureNode

The Meshy: Texture Model node applies AI-generated textures to an existing 3D model.

The Meshy: Texture Model node applies AI-generated textures to an existing 3D model. It uses a task ID from a previous Meshy 3D generation or conversion task and guides the texturing process with either a text style prompt or a reference image. The node returns the textured model in GLB and FBX file formats.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model version to use for texturing. | COMBO | Yes | `"meshy-7"`<br />`"meshy-6"`<br />`"latest"` |
| `meshy_task_id` | The unique identifier (task ID) from a previous Meshy 3D generation or conversion task. This provides the base 3D model to be textured. | MESHY\_TASK\_ID | Yes | - |
| `enable_original_uv` | Use the original UV of the model instead of generating new UVs. When enabled (default: `True`), Meshy preserves existing textures from the uploaded model. If the model has no original UV, the quality of the output might not be as good. This is an advanced option. | BOOLEAN | Yes | true / false |
| `pbr` | Enables Physically Based Rendering (PBR) material output for the textured model (default: `False`). This is an advanced option. | BOOLEAN | Yes | true / false |
| `text_style_prompt` | Describe your desired texture style of the object using text (default: empty string). Maximum 600 characters. Cannot be used at the same time as `image_style`. | STRING | Yes | - |
| `image_style` | A 2D image to guide the texturing process. Cannot be used at the same time with `text_style_prompt`. | IMAGE | No | - |
| `texture_resolution` | Base color texture resolution. Higher resolutions capture more surface detail. | COMBO | Yes | `"2k"`<br />`"4k"`<br />`"8k"` |

**Parameter Constraints:**

* You must provide either a `text_style_prompt` or an `image_style`, but you cannot provide both at the same time.
* The `text_style_prompt` is limited to a maximum of 600 characters.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The filename of the generated GLB model. This output is provided for backward compatibility only. | STRING |
| `meshy_task_id` | The unique task identifier for this texturing job, which can be used to reference the result. | MESHY\_TASK\_ID |
| `GLB` | The textured 3D model saved in the GLB file format. | FILE3DGLB |
| `FBX` | The textured 3D model saved in the FBX file format. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyTextureNode/en.md)

***

**Source fingerprint (SHA-256):** `30d51f6efe3602f27d99706840c974baf2c4397a4f9a191f3478e7eff372e319`


# OptimalStepsScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OptimalStepsScheduler

The OptimalStepsScheduler node creates a noise schedule (a sequence of sigma values) for use during diffusion sampling.

The OptimalStepsScheduler node creates a noise schedule (a sequence of sigma values) for use during diffusion sampling. It chooses the base noise levels from the selected model type, adjusts the schedule when denoising is only partially applied, and interpolates the levels so the returned sigmas match the requested step count.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_type` | The type of diffusion model to use for the noise level calculation. Each option uses its own predefined table of noise levels. | COMBO | Yes | "FLUX"<br />"Wan"<br />"Chroma" |
| `steps` | The total number of sampling steps to calculate (default: 20). | INT | Yes | 3 to 1000 |
| `denoise` | Controls the denoising strength, which adjusts the effective number of steps (default: 1.0). | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |

**Note:** The base noise level table for the selected `model_type` is resampled with log-linear interpolation whenever its length does not equal `steps + 1`, so the output always matches the requested step count.

**Note:** When `denoise` is less than 1.0, the node uses `round(steps * denoise)` as the total number of effective steps and keeps only the matching tail of the schedule. If `denoise` is 0.0 or lower, the node returns an empty tensor.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sigmas` | A sequence of sigma values representing the noise schedule for diffusion sampling. The final value in the sequence is always set to 0. | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OptimalStepsScheduler/en.md)

***

**Source fingerprint (SHA-256):** `fd48c94ca16c8a3d8e6f0138018e7b13c15d100d6147807bcb23d838899045b7`


# PolyexponentialScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PolyexponentialScheduler

The PolyexponentialScheduler node is designed to generate a sequence of noise levels (sigmas) based on a polyexponential noise schedule.

The PolyexponentialScheduler node is designed to generate a sequence of noise levels (sigmas) based on a polyexponential noise schedule. This schedule is a polynomial function in the logarithm of sigma, allowing for a flexible and customizable progression of noise levels throughout the diffusion process.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `steps` | Specifies the number of steps in the diffusion process, affecting the granularity of the generated noise levels. | INT |
| `sigma_max` | The maximum noise level, setting the upper bound of the noise schedule. | FLOAT |
| `sigma_min` | The minimum noise level, setting the lower bound of the noise schedule. | FLOAT |
| `rho` | A parameter that controls the shape of the polyexponential noise schedule, influencing how noise levels progress between the minimum and maximum values. | FLOAT |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `sigmas` | The output is a sequence of noise levels (sigmas) tailored to the specified polyexponential noise schedule. | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PolyexponentialScheduler/en.md)


# RandomNoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RandomNoise

The RandomNoise node creates a noise generator based on a seed value for use during the sampling process.

The RandomNoise node creates a noise generator based on a seed value for use during the sampling process. The same seed always produces the same noise pattern, allowing for consistent, reproducible results across multiple runs. Samplers use the generated noise when processing latent images.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `noise_seed` | The seed value used to generate the random noise pattern (default: 0). The same seed always produces the same noise output. This input includes a control-after-generate option to automatically update the seed after each generation. | INT | Yes | 0 to 18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `noise` | A noise object that generates random noise for latent samples based on the provided seed value. Used by samplers during the sampling process. | NOISE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RandomNoise/en.md)

***

**Source fingerprint (SHA-256):** `b55ff98c636c55f064ede82c6848ffa163d1fd9b0cf6195f4a35603cfbe2bc1e`


# ResolutionBucket - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResolutionBucket

This node organizes a list of latent images and their corresponding conditioning data by their resolution.

This node organizes a list of latent images and their corresponding conditioning data by their resolution. It groups together items that share the same height and width, creating separate batches for each unique resolution. This process is useful for preparing data for efficient training, as it allows models to process multiple items of the same size together.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `latents` | List of latent dicts to bucket by resolution. | LATENT | Yes | N/A |
| `conditioning` | List of conditioning lists (must match latents length). | CONDITIONING | Yes | N/A |

**Note:** Both inputs are list-type inputs, meaning the node receives a list of items for each. The number of items in the `latents` list must exactly match the number of items in the `conditioning` list; if the counts do not match, the node raises an error. Each latent dictionary can contain a batch of samples, and the corresponding conditioning list must contain a matching number of conditioning items for that batch, since each sample in the batch is paired with its own conditioning entry. Latent samples may have a shape of (B, C, H, W) for images or (B, T, C, H, W) for videos; the node groups them by height and width only.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `latents` | List of batched latent dicts, one per resolution bucket. | LATENT |
| `conditioning` | List of condition lists, one per resolution bucket. | CONDITIONING |

**Note:** Both outputs are list-type outputs. Each output list contains one entry per unique resolution (height and width) found in the input, in the order the resolutions were first encountered. Latents within each bucket are stacked along a new batch dimension.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResolutionBucket/en.md)

***

**Source fingerprint (SHA-256):** `11687f9916895136c7c5b8146cd7519cbf6c296720e453bac52fe4da237403cd`


# Rodin3D_Detail - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Detail

The Rodin 3D Detail node generates detailed 3D assets using the Rodin API.

The Rodin 3D Detail node generates detailed 3D assets using the Rodin API. It takes input images and processes them through the Rodin service to create high-quality 3D models with detailed geometry and materials. The node handles the entire workflow from task creation to downloading the final 3D model file.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `Images` | Input images used for 3D model generation. A minimum of 1 image is required, and a maximum of 5 images can be provided. | IMAGE | Yes | - |
| `Seed` | Random seed value for reproducible results (default: 0) | INT | No | 0 to 65535 |
| `Material_Type` | Type of material to apply to the 3D model (default: "PBR") | STRING | No | `"PBR"`<br />`"Shaded"` |
| `Polygon_count` | Target polygon count for the generated 3D model. Determines the mesh quality level (default: "18K-Quad") | STRING | No | `"4K-Quad"`<br />`"8K-Quad"`<br />`"18K-Quad"`<br />`"50K-Quad"`<br />`"200K-Triangle"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `3D Model Path` | File path to the generated 3D model (for backward compatibility only) | STRING |
| `GLB` | The generated 3D model in GLB format | FILE3DGLB |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Detail/en.md)

***

**Source fingerprint (SHA-256):** `941265733c20d27d67621a83a05be822731696f4dd376299510d4279a35f51ee`


# Rodin3D_Gen2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Gen2

The Rodin3DGen2 node generates 3D assets using the Rodin API.

The Rodin3D\_Gen2 node generates 3D assets using the Rodin API. It takes input images and converts them into 3D models with various material types and polygon counts. The node handles the entire generation process including task creation, status polling, and file downloading automatically.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `Images` | Input images to use for 3D model generation. Accepts 1 to 5 images. | IMAGE | Yes | - |
| `Seed` | Random seed value for generation (default: 0) | INT | No | 0-65535 |
| `Material_Type` | Type of material to apply to the 3D model (default: "PBR") | COMBO | No | "PBR"<br />"Shaded" |
| `Polygon_count` | Target polygon count and mesh type for the generated 3D model. "Quad" options use quad-based meshes, "Triangle" options use triangle-based meshes (default: "500K-Triangle") | COMBO | No | "4K-Quad"<br />"8K-Quad"<br />"18K-Quad"<br />"50K-Quad"<br />"2K-Triangle"<br />"20K-Triangle"<br />"150K-Triangle"<br />"500K-Triangle" |
| `TAPose` | Whether to apply TAPose processing (default: False). This is an advanced parameter. | BOOLEAN | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `3D Model Path` | File path to the generated 3D model (for backward compatibility) | STRING |
| `GLB` | The generated 3D model in GLB format | FILE3DGLB |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Gen2/en.md)

***

**Source fingerprint (SHA-256):** `6ee8b52152e84cca48c7875ce066ab19805a42e5cccc84865c6027a4f6fd3b16`


# Rodin3D_Gen25_Image - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Gen25_Image

Documentation for Rodin3DGen25Image node.

## Overview

This node generates a 3D model from one to five reference images using the Rodin Gen-2.5 API. You can choose between Fast, Regular, or Extreme-High quality modes to balance generation speed and cost.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | One to five input images. The first image is used for materials when multiple images are provided. | IMAGE | Yes | 1 to 5 images |
| `mode` | The generation quality mode. Higher quality modes produce better results but cost more. | COMBO | Yes | `"Fast"`<br />`"Regular"`<br />`"Extreme-High"` |
| `material` | The material type for the generated 3D model. | COMBO | Yes | `"PBR"`<br />`"Matte"` |
| `geometry_file_format` | The output file format for the 3D model geometry. | COMBO | Yes | `"glb"`<br />`"obj"`<br />`"stl"`<br />`"usdz"` |
| `texture_mode` | The texture generation mode. "Original" preserves input textures, "Clean" removes them, and "Style" applies a stylized texture. | COMBO | Yes | `"Original"`<br />`"Clean"`<br />`"Style"` |
| `seed` | A random seed for reproducible results. Use the same seed to get the same output. | INT | Yes | 0 to 2147483647 |
| `TAPose` | Whether to apply T-pose to the generated model. | BOOLEAN | Yes | True / False |
| `hd_texture` | Whether to generate a high-definition texture map. | BOOLEAN | Yes | True / False |
| `texture_delight` | Whether to remove lighting from the input images before texture generation. | BOOLEAN | Yes | True / False |
| `use_original_alpha` | Whether to use the original alpha channel from the input images. | BOOLEAN | Yes | True / False |
| `addon_highpack` | Whether to generate a high-polygon version of the model in addition to the standard one. | BOOLEAN | Yes | True / False |
| `bbox_width` | The width of the bounding box for the generated model in centimeters. | INT | Yes | 1 to 1000 |
| `bbox_height` | The height of the bounding box for the generated model in centimeters. | INT | Yes | 1 to 1000 |
| `bbox_length` | The length of the bounding box for the generated model in centimeters. | INT | Yes | 1 to 1000 |
| `height_cm` | The height of the generated model in centimeters. | INT | Yes | 1 to 300 |

**Note on Image Count:** The node accepts between 1 and 5 images. If you provide a batch of images (e.g., a 4-image batch), each image in the batch is treated as a separate input image. Providing more than 5 images will result in an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The generated 3D model file in the selected geometry format. | FILE3D |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Gen25_Image/en.md)

***

**Source fingerprint (SHA-256):** `6437f8d34624fccfb92505bcdc627db2df2f4159c929a4f7b00352906c609a25`


# Rodin3D_Gen25_Text - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Gen25_Text

Documentation for Rodin3DGen25Text node.

## Overview

Generate a 3D model from a text prompt using the Rodin Gen-2.5 API. You can choose between different quality modes (Fast, Regular, or Extreme-High) to balance generation speed and output quality.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for the 3D model. | STRING | Yes | 1 to 2500 characters |
| `mode` | The generation quality and speed mode. "Fast" is quickest, "Extreme-High" produces the highest quality but takes longer. | COMBO | Yes | `"Fast"`<br />`"Regular"`<br />`"Extreme-High"` |
| `material` | The material style for the generated 3D model. | COMBO | Yes | `"PBR"`<br />`"Matte"`<br />`"Shiny"` |
| `geometry_file_format` | The file format for the output 3D model. | COMBO | Yes | `"glb"`<br />`"obj"`<br />`"stl"`<br />`"usdz"` |
| `texture_mode` | Texture generation mode. "None" produces no textures, "Generated" creates standard textures, "Generated+HD" creates high-definition textures. | COMBO | Yes | `"None"`<br />`"Generated"`<br />`"Generated+HD"` |
| `seed` | Random seed for reproducible results. Using the same seed with the same inputs will produce the same output. | INT | Yes | 0 to 2147483647 |
| `TAPose` | Whether to apply T-pose (arms outstretched) to the generated model. | BOOLEAN | Yes | True / False |
| `hd_texture` | Whether to generate high-definition textures for the model. | BOOLEAN | Yes | True / False |
| `texture_delight` | Whether to apply texture delight (enhanced texture quality) to the model. | BOOLEAN | Yes | True / False |
| `addon_highpack` | Whether to generate a high-polygon version of the model in addition to the standard one. | BOOLEAN | Yes | True / False |
| `bbox_width` | The width of the bounding box in world units. | INT | Yes | 1 to 1000 |
| `bbox_height` | The height of the bounding box in world units. | INT | Yes | 1 to 1000 |
| `bbox_length` | The length of the bounding box in world units. | INT | Yes | 1 to 1000 |
| `height_cm` | The height of the generated model in centimeters. | INT | Yes | 1 to 300 |

**Note:** The `prompt` parameter must be between 1 and 2500 characters long. The `seed` parameter defaults to 0 (random) if not specified.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The generated 3D model file in the specified format. | FILE3DANY |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Gen25_Text/en.md)

***

**Source fingerprint (SHA-256):** `7e71532203290e21e13d345b09330a1c00aff9d3754e63f5eff65f37f3fa2403`


# Rodin3D_Regular - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Regular

The Rodin 3D Regular node generates 3D assets using the Rodin API.

The Rodin 3D Regular node generates 3D assets using the Rodin API. It takes input images and processes them through the Rodin service to create 3D models. The node handles the entire workflow from task creation to downloading the final 3D model files.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `Images` | Input images used for 3D model generation. Up to 5 images can be provided. At least 1 image is required. | IMAGE | Yes | - |
| `Seed` | Random seed value for reproducible results (default: 0). | INT | No | 0 to 65535 |
| `Material_Type` | Type of material to apply to the 3D model (default: "PBR"). | STRING | No | `"PBR"`<br />`"Shaded"` |
| `Polygon_count` | Target polygon count and mesh type for the generated 3D model (default: "18K-Quad"). | STRING | No | `"4K-Quad"`<br />`"8K-Quad"`<br />`"18K-Quad"`<br />`"50K-Quad"<br>`"200K-Triangle"\` |

**Note:** At least 1 image is required for 3D model generation. A maximum of 5 images can be provided.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `3D Model Path` | File path to the generated 3D model (maintained for backward compatibility). | STRING |
| `GLB` | The generated 3D model in GLB format. | FILE3DGLB |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Regular/en.md)

***

**Source fingerprint (SHA-256):** `e0bd8ef311f33481fec877801dea80302eba076f2d9e12f52467e889242a9637`


# Rodin3D_Sketch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Sketch

This node generates 3D assets using the Rodin API.

This node generates 3D assets using the Rodin API. It takes input images and converts them into 3D models through an external service. The node handles the entire process from task creation to downloading the final 3D model files.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `Images` | Input images to be converted into 3D models. You can provide between 1 and 5 images. | IMAGE | Yes | 1 to 5 images |
| `Seed` | Random seed value for generation (default: 0). Set to 0 for a random seed. | INT | No | 0 to 65535 |

**Note:** The node requires at least 1 image and supports a maximum of 5 images. If no images are provided, the node will raise an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `3D Model Path` | File path to the generated 3D model (for backward compatibility only) | STRING |
| `GLB` | The generated 3D model in GLB format | FILE3DGLB |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Sketch/en.md)

***

**Source fingerprint (SHA-256):** `0b77ce871e267450af63f3e2fe0e36fe81ababc25cbb11498546ad8f487b65e5`


# Rodin3D_Smooth - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Smooth

The Rodin 3D Smooth node generates 3D assets using the Rodin API by processing input images and converting them into smooth 3D models.

The Rodin 3D Smooth node generates 3D assets using the Rodin API by processing input images and converting them into smooth 3D models. It takes multiple images as input and produces a downloadable 3D model file. The node handles the entire generation process including task creation, status polling, and file downloading automatically.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `Images` | Input images to use for 3D model generation. Multiple images can be provided (up to 5). | IMAGE | Yes | - |
| `Seed` | Random seed value for generation consistency (default: 0). | INT | No | 0 to 65535 |
| `Material_Type` | Type of material to apply to the 3D model (default: "PBR"). | STRING | No | "PBR"<br />"Shaded" |
| `Polygon_count` | Target polygon count for the generated 3D model. Determines the mesh quality and detail level (default: "18K-Quad"). | STRING | No | "4K-Quad"<br />"8K-Quad"<br />"18K-Quad"<br />"50K-Quad"<br />"200K-Triangle" |

**Note:** The node accepts up to 5 input images. If no images are provided, an error will be raised.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `3D Model Path` | File path to the downloaded 3D model (for backward compatibility only). | STRING |
| `GLB` | The generated 3D model in GLB format. | FILE3DGLB |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Smooth/en.md)

***

**Source fingerprint (SHA-256):** `c7dc23d2a7a8e2d425fc389476ef381f4ebf974f522c6e3774222866eee064e9`


# SDTurboScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SDTurboScheduler

SDTurboScheduler is designed to generate a sequence of sigma values for image sampling, adjusting the sequence based on the denoise level and the number of steps specified.

SDTurboScheduler is designed to generate a sequence of sigma values for image sampling, adjusting the sequence based on the denoise level and the number of steps specified. It leverages a specific model's sampling capabilities to produce these sigma values, which are crucial for controlling the denoising process during image generation.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The model parameter specifies the generative model to be used for sigma value generation. It is crucial for determining the specific sampling behavior and capabilities of the scheduler. | `MODEL` |
| `steps` | The steps parameter determines the length of the sigma sequence to be generated, directly influencing the granularity of the denoising process. | `INT` |
| `denoise` | The denoise parameter adjusts the starting point of the sigma sequence, allowing for finer control over the denoising level applied during image generation. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `sigmas` | A sequence of sigma values generated based on the specified model, steps, and denoise level. These values are essential for controlling the denoising process in image generation. | `SIGMAS` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SDTurboScheduler/en.md)


# SamplerARVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerARVideo

The Sampler AR Video node provides a specialized sampling method for autoregressive video models, such as those using Causal Forcing or Self-Forcing techniques.

The Sampler AR Video node provides a specialized sampling method for autoregressive video models, such as those using Causal Forcing or Self-Forcing techniques. It manages all parameters related to the autoregressive (AR) loop directly within the workflow, making it easy to configure how the model generates video frames one step at a time.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `num_frame_per_block` | Frames per autoregressive block. A value of 1 means the model generates one frame at a time (framewise), while a value of 3 means it generates three frames together (chunkwise). This setting must match the checkpoint's training mode. Default: 1. | INT | Yes | 1 to 64 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `SAMPLER` | A configured sampler object that uses the "ar\_video" sampling function with the specified autoregressive parameters. | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerARVideo/en.md)

***

**Source fingerprint (SHA-256):** `9ec72f52f5b77746f1587e64966bfa6cfd80ce8bb40a4fcb267f5197d09189fc`


# SamplerCustom - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerCustom

The SamplerCustom node is designed to provide a flexible and customizable sampling mechanism for various applications.

The SamplerCustom node is designed to provide a flexible and customizable sampling mechanism for various applications. It enables users to select and configure different sampling strategies tailored to their specific needs, enhancing the adaptability and efficiency of the sampling process.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The 'model' input type specifies the model to be used for sampling, playing a crucial role in determining the sampling behavior and output. | `MODEL` |
| `add_noise` | The 'add\_noise' input type allows users to specify whether noise should be added to the sampling process, influencing the diversity and characteristics of the generated samples. | `BOOLEAN` |
| `noise_seed` | The 'noise\_seed' input type provides a seed for the noise generation, ensuring reproducibility and consistency in the sampling process when adding noise. | `INT` |
| `cfg` | The 'cfg' input type sets the configuration for the sampling process, allowing for fine-tuning of the sampling parameters and behavior. | `FLOAT` |
| `positive` | The 'positive' input type represents positive conditioning information, guiding the sampling process towards generating samples that align with specified positive attributes. | `CONDITIONING` |
| `negative` | The 'negative' input type represents negative conditioning information, steering the sampling process away from generating samples that exhibit specified negative attributes. | `CONDITIONING` |
| `sampler` | The 'sampler' input type selects the specific sampling strategy to be employed, directly impacting the nature and quality of the generated samples. | `SAMPLER` |
| `sigmas` | The 'sigmas' input type defines the noise levels to be used in the sampling process, affecting the exploration of the sample space and the diversity of the output. | `SIGMAS` |
| `latent_image` | The 'latent\_image' input type provides an initial latent image for the sampling process, serving as a starting point for sample generation. | `LATENT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `output` | The 'output' represents the primary result of the sampling process, containing the generated samples. | `LATENT` |
| `denoised_output` | The 'denoised\_output' represents the samples after a denoising process has been applied, potentially enhancing the clarity and quality of the generated samples. | `LATENT` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerCustom/en.md)


# SamplerCustomAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerCustomAdvanced

The SamplerCustomAdvanced node performs advanced latent space sampling using custom noise, guidance, and sampling configurations.

The SamplerCustomAdvanced node performs advanced latent space sampling using custom noise, guidance, and sampling configurations. It processes a latent image through a guided sampling process with a customizable noise generator and sigma schedule, producing both the final sampled output and a denoised version when available.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `noise` | The noise generator that provides the initial noise pattern and seed for the sampling process | NOISE | Yes | - |
| `guider` | The guidance model that directs the sampling process toward the desired output | GUIDER | Yes | - |
| `sampler` | The sampling algorithm that defines how the latent space is traversed during generation | SAMPLER | Yes | - |
| `sigmas` | The sigma schedule that controls the noise levels throughout the sampling steps | SIGMAS | Yes | - |
| `latent_image` | The initial latent representation that serves as the starting point for sampling. Supports an optional `noise_mask` key for selective denoising, and optional `downscale_ratio_spacial` and `downscale_ratio_temporal` keys for advanced latent handling | LATENT | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The final sampled latent representation after completing the sampling process. Any `downscale_ratio_spacial` or `downscale_ratio_temporal` keys from the input latent are removed from this output | LATENT |
| `denoised_output` | A denoised version of the output when the sampling process produces an intermediate clean prediction (x0), otherwise returns the same as `output`. When available, this represents the model's best estimate of the clean latent | LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerCustomAdvanced/en.md)

***

**Source fingerprint (SHA-256):** `23cffad0f7cf74dcd494c2828b2116bb4d00a1e55e42ded074b587ac20183290`


# SamplerDPMAdaptative - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDPMAdaptative

The SamplerDPMAdaptative node implements an adaptive DPM (Diffusion Probabilistic Model) sampler that automatically adjusts step sizes during the sampling process.

The SamplerDPMAdaptative node implements an adaptive DPM (Diffusion Probabilistic Model) sampler that automatically adjusts step sizes during the sampling process. It uses tolerance-based error control to determine optimal step sizes, balancing computational efficiency with sampling accuracy. This adaptive approach helps maintain quality while potentially reducing the number of steps needed.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `order` | The order of the sampler method (default: 3) | INT | Yes | 2-3 |
| `rtol` | Relative tolerance for error control (default: 0.05) | FLOAT | Yes | 0.0-100.0 |
| `atol` | Absolute tolerance for error control (default: 0.0078) | FLOAT | Yes | 0.0-100.0 |
| `h_init` | Initial step size (default: 0.05) | FLOAT | Yes | 0.0-100.0 |
| `pcoeff` | Proportional coefficient for step size control (default: 0.0) | FLOAT | Yes | 0.0-100.0 |
| `icoeff` | Integral coefficient for step size control (default: 1.0) | FLOAT | Yes | 0.0-100.0 |
| `dcoeff` | Derivative coefficient for step size control (default: 0.0) | FLOAT | Yes | 0.0-100.0 |
| `accept_safety` | Safety factor for step acceptance (default: 0.81) | FLOAT | Yes | 0.0-100.0 |
| `eta` | Stochasticity parameter (default: 0.0) | FLOAT | Yes | 0.0-100.0 |
| `s_noise` | Noise scaling factor (default: 1.0) | FLOAT | Yes | 0.0-100.0 |

All inputs are advanced parameters used to fine-tune the adaptive sampling behavior. All numeric inputs allow decimal values and accept a minimum of 0.0 and a maximum of 100.0, except `order`, which is limited to the integer values 2 or 3.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | Returns a configured DPM adaptive sampler instance | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDPMAdaptative/en.md)

***

**Source fingerprint (SHA-256):** `07b2e5b9f21ec101eabccc6be245d043e64a996a14db10434b03eaae0a91b1d8`


# SamplerDPMPP_2M_SDE - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDPMPP_2M_SDE

The SamplerDPMPP2MSDE node creates a DPM++ 2M SDE sampler for diffusion models.

The SamplerDPMPP\_2M\_SDE node creates a DPM++ 2M SDE sampler for diffusion models. This sampler uses second-order differential equation solvers with stochastic differential equations to generate samples. It provides different solver types and noise handling options to control the sampling process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `solver_type` | The type of differential equation solver to use for the sampling process (default: "midpoint") | COMBO | Yes | `"midpoint"`<br />`"heun"` |
| `eta` | Controls the stochasticity of the sampling process (default: 1.0) | FLOAT | Yes | 0.0 - 100.0 |
| `s_noise` | Controls the amount of noise added during sampling (default: 1.0) | FLOAT | Yes | 0.0 - 100.0 |
| `noise_device` | The device where noise calculations are performed. When set to "cpu", the sampler uses CPU-based noise generation; when set to "gpu", it uses GPU-based noise generation for potentially faster performance (default: "gpu") | COMBO | Yes | `"gpu"`<br />`"cpu"` |

Note: `eta`, `s_noise`, and `noise_device` are marked as advanced parameters and appear in the advanced section of the node's UI.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | A configured sampler object ready for use in the sampling pipeline | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDPMPP_2M_SDE/en.md)

***

**Source fingerprint (SHA-256):** `42f5f098fa7573ca8a1a6085b72675ee6cb0ae8e7865c5793a815a6ef2495f82`


# SamplerDPMPP_2S_Ancestral - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDPMPP_2S_Ancestral

The SamplerDPMPP2SAncestral node creates a sampler that uses the DPM++ 2S Ancestral sampling method for generating images.

The SamplerDPMPP\_2S\_Ancestral node creates a sampler that uses the DPM++ 2S Ancestral sampling method for generating images. This sampler combines deterministic and stochastic elements to produce varied results while maintaining some consistency. It allows you to control the randomness and noise levels during the sampling process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `eta` | Controls the amount of stochastic noise added during sampling (default: 1.0) | FLOAT | Yes | 0.0 - 100.0 (step 0.01) |
| `s_noise` | Controls the scale of noise applied during the sampling process (default: 1.0) | FLOAT | Yes | 0.0 - 100.0 (step 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | Returns a configured sampler object that can be used in the sampling pipeline | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDPMPP_2S_Ancestral/en.md)

***

**Source fingerprint (SHA-256):** `8d20ec21e6c699965753413d9ef8b6191553c4b7b606d93c10470aa9d988a308`


# SamplerDPMPP_3M_SDE - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDPMPP_3M_SDE

The SamplerDPMPP3MSDE node creates a DPM++ 3M SDE sampler for use in the sampling process.

The SamplerDPMPP\_3M\_SDE node creates a DPM++ 3M SDE sampler for use in the sampling process. This sampler uses a third-order multistep stochastic differential equation method with configurable noise parameters. The node allows you to choose whether noise calculations are performed on the GPU or CPU.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `eta` | Controls the stochasticity of the sampling process (default: 1.0) | FLOAT | Yes | 0.0 - 100.0 |
| `s_noise` | Controls the amount of noise added during sampling (default: 1.0) | FLOAT | Yes | 0.0 - 100.0 |
| `noise_device` | Selects the device for noise calculations, either GPU or CPU (default: "gpu") | COMBO | Yes | "gpu"<br />"cpu" |

Note: All three inputs are advanced parameters.

When `noise_device` is set to "cpu", the standard `dpmpp_3m_sde` sampler is created; when set to "gpu", the GPU-accelerated `dpmpp_3m_sde_gpu` sampler is created.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | Returns a configured sampler object for use in sampling workflows | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDPMPP_3M_SDE/en.md)

***

**Source fingerprint (SHA-256):** `0f624398c67e50639fc41384b50b91bab93797bd785dda25f1f5fc649e46825b`


# SamplerDPMPP_SDE - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDPMPP_SDE

Documentation for SamplerDPMPPSDE node.

## Overview

SamplerDPMPP\_SDE creates a DPM++ SDE (Stochastic Differential Equation) sampler for use in the sampling process. This sampler provides a stochastic sampling method with configurable noise parameters and device selection. It returns a sampler object that can be used in the sampling pipeline.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `eta` | Controls the stochasticity of the sampling process (default: 1.0) | FLOAT | Yes | 0.0 - 100.0 |
| `s_noise` | Controls the amount of noise added during sampling (default: 1.0) | FLOAT | Yes | 0.0 - 100.0 |
| `r` | A parameter that influences the sampling behavior (default: 0.5) | FLOAT | Yes | 0.0 - 100.0 |
| `noise_device` | Selects the device where noise calculations are performed. When set to "cpu", the `dpmpp_sde` sampler is created; when set to "gpu", the `dpmpp_sde_gpu` sampler is created (default: "gpu") | COMBO | Yes | "gpu"<br />"cpu" |

Note: All inputs are marked as advanced parameters. The `noise_device` selection changes which sampler variant is created: "cpu" maps to `dpmpp_sde` and "gpu" maps to `dpmpp_sde_gpu`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | Returns a configured DPM++ SDE sampler object for use in sampling pipelines | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDPMPP_SDE/en.md)

***

**Source fingerprint (SHA-256):** `56949712f245abfcc48c09d7d14a1a7778e80ba58535e538484c382d7e0d02c6`


# SamplerER_SDE - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerER_SDE

The SamplerERSDE node provides specialized sampling methods for diffusion models, offering different solver types: ER-SDE, Reverse-time SDE, and ODE.

The SamplerER\_SDE node provides specialized sampling methods for diffusion models, offering different solver types: ER-SDE, Reverse-time SDE, and ODE. It lets you control the stochastic behavior and the number of computational stages of the sampling process. The node automatically adjusts settings based on the chosen solver type to keep the sampler working correctly.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `solver_type` | The type of solver to use for sampling. Determines the mathematical approach for the diffusion process (default: "ER-SDE"). | COMBO | Yes | "ER-SDE"<br />"Reverse-time SDE"<br />"ODE" |
| `max_stage` | The maximum number of stages for the sampling process (default: 3). Controls the computational complexity and quality. This is an advanced parameter. | INT | Yes | 1-3 |
| `eta` | Stochastic strength of SDEs.<br />When eta=0, they reduce to deterministic ODE.<br />Large eta may cause invalid outputs. If this occurs, try decreasing this value. (default: 1.0). This is an advanced parameter. | FLOAT | Yes | 0.0-10.0 (step: 0.01) |
| `s_noise` | Noise scaling factor for the sampling process (default: 1.0). Controls the amount of noise applied during sampling. This is an advanced parameter. | FLOAT | Yes | 0.0-100.0 (step: 0.01) |

**Parameter Constraints:**

* When `solver_type` is set to "ODE" or when `eta` is 0, the node switches to ODE mode and sets `s_noise` to 0.0, regardless of the value entered for `s_noise`.
* The `eta` parameter controls the stochastic strength of both the "ER-SDE" and "Reverse-time SDE" solver types. It has no effect when the solver runs in ODE mode.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | A configured sampler object that can be used in the sampling pipeline with the specified solver settings. | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerER_SDE/en.md)

***

**Source fingerprint (SHA-256):** `5299ae9b45444cdc7c36bcb3c5e5a0600f9f904e57ae614554033434afdffd30`


# SamplerEulerAncestral - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerEulerAncestral

The SamplerEulerAncestral node creates an Euler Ancestral sampler that can be used during image generation.

The SamplerEulerAncestral node creates an Euler Ancestral sampler that can be used during image generation. This sampler combines Euler integration with ancestral sampling, which adds a degree of randomness at each step to produce varied results. The node lets you adjust how much randomness is applied through its settings.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `eta` | Controls the step size and stochasticity of the sampling process (default: 1.0). This is an advanced parameter. | FLOAT | Yes | 0.0 - 100.0 |
| `s_noise` | Controls the amount of noise added during sampling (default: 1.0). This is an advanced parameter. | FLOAT | Yes | 0.0 - 100.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | Returns a configured Euler Ancestral sampler that can be used in the sampling pipeline. | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerEulerAncestral/en.md)

***

**Source fingerprint (SHA-256):** `0d3c1f0ffe01eb6cc17fd53e743713f659218ec19001c670440472ae7d0d3887`


# SamplerEulerAncestralCFGPP - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerEulerAncestralCFGPP

The SamplerEulerAncestralCFG++ node creates a sampler that uses the Euler Ancestral method with classifier-free guidance (CFG++) for image generation.

The SamplerEulerAncestralCFG++ node creates a sampler that uses the Euler Ancestral method with classifier-free guidance (CFG++) for image generation. This sampler combines ancestral sampling techniques with guidance conditioning to produce diverse image variations while maintaining coherence, and allows fine-tuning through parameters that control noise and step size adjustments.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `eta` | Controls the step size during sampling, with higher values resulting in more aggressive updates (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 |
| `s_noise` | Adjusts the amount of noise added during the sampling process (default: 1.0) | FLOAT | Yes | 0.0 - 10.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | Returns a configured sampler object that can be used in the image generation pipeline | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerEulerAncestralCFGPP/en.md)

***

**Source fingerprint (SHA-256):** `de83cb4c3e9aeee60f1554ad1af8181adb4fa62e3d23cec02a6f4396b96500c1`


# SamplerLCM - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerLCM

This node provides an LCM (Latent Consistency Model) sampler with adjustable per-step noise.

This node provides an LCM (Latent Consistency Model) sampler with adjustable per-step noise. It lets you control how much noise is applied during sampling: `s_noise` acts as a multiplier on the model's training noise scale, and the noise level can vary from the first step to the last step. The configured sampler can then be plugged into a sampling workflow.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `s_noise` | Per-step noise multiplier at the first step (1.0 = match training). Default: 1.0. | FLOAT | Yes | 0.0 to 64.0 (step: 0.01) |
| `s_noise_end` | Per-step noise multiplier at the last step. Set equal to `s_noise` for a constant schedule. Default: 1.0. | FLOAT | Yes | 0.0 to 64.0 (step: 0.01) |
| `noise_clip_std` | Clamp per-step noise to +/- N\*std. 0 disables. Default: 0.0. | FLOAT | Yes | 0.0 to 10.0 (step: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `SAMPLER` | The configured LCM sampler object, ready to be used in a sampling workflow. | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerLCM/en.md)

***

**Source fingerprint (SHA-256):** `0d18f2f977ddadeedcd7807233b48ebcc4e94c6213f8540b9037a45a9c70c6cf`


# SamplerLCMUpscale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerLCMUpscale

This node provides a specialized sampling method that combines Latent Consistency Model (LCM) sampling with progressive image upscaling.

This node provides a specialized sampling method that combines Latent Consistency Model (LCM) sampling with progressive image upscaling. During sampling, the image is upscaled step by step toward a target scale ratio using a chosen interpolation method, allowing higher-resolution results in a single sampling pass. The node outputs a configured sampler object that can be connected to a sampling node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `scale_ratio` | The total scaling factor to apply during upscaling. A value of 1.0 keeps the original resolution (default: 1.0) | FLOAT | Yes | 0.1 - 20.0 |
| `scale_steps` | The number of steps to use for the upscaling process. Use -1 for automatic calculation based on the sampling schedule (default: -1) | INT | Yes | -1 - 1000 |
| `upscale_method` | The interpolation method used for upscaling the image at each upscaling step (default: "bislerp") | COMBO | Yes | "bislerp"<br />"nearest-exact"<br />"bilinear"<br />"area"<br />"bicubic" |

`scale_ratio` and `scale_steps` are advanced parameters. The image is upscaled gradually from its original size to the target `scale_ratio` over the upscaling steps. When `scale_steps` is -1, the number of upscaling steps is calculated automatically as about half the number of sampling steps, with a minimum of 2; when a positive value is given, the node adjusts it internally and limits it based on the total number of sampling steps.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | A configured sampler object that performs LCM sampling with progressive upscaling, ready to be used in the sampling pipeline | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerLCMUpscale/en.md)

***

**Source fingerprint (SHA-256):** `5d6f6472fbb4d2c66a8a8b9d6dc34dcc52ac8272589fd6c29e4084d6cab3141b`


# SamplerLMS - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerLMS

The SamplerLMS node creates a Least Mean Squares (LMS) sampler for use in diffusion models.

The SamplerLMS node creates a Least Mean Squares (LMS) sampler for use in diffusion models. It generates a sampler object that can be used in the sampling process, allowing you to control the order of the LMS algorithm for numerical stability and accuracy.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `order` | The order parameter for the LMS sampler algorithm, which controls the numerical method's accuracy and stability (default: 4). This parameter is shown in the advanced section of the node interface. | INT | Yes | 1 to 100 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | A configured LMS sampler object that can be used in the sampling pipeline | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerLMS/en.md)

***

**Source fingerprint (SHA-256):** `3d59fbbd5b9b0bfa2ee3b384aca08855988d0b7a2a94d805f978b9dd7caa0f39`


# SamplerSASolver - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerSASolver

The SamplerSASolver node creates and configures a custom sampler for diffusion models.

The SamplerSASolver node creates and configures a custom sampler for diffusion models. It uses the "sa\_solver" sampling algorithm with a configurable predictor-corrector scheme and stochastic differential equation (SDE) settings, returning a sampler object that can be plugged into a sampling node. The `sde_start_percent` and `sde_end_percent` values are converted into sigma values using the connected model's sampling schedule to define the interval in which the stochastic component is applied.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The diffusion model whose sampling schedule is used to build the sampler | MODEL | Yes | - |
| `eta` | Controls the step size scaling factor of the SDE solver (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `sde_start_percent` | Starting percentage of the sampling process where the stochastic (SDE) component begins; converted to a sigma value using the model's schedule (default: 0.2) | FLOAT | No | 0.0 - 1.0 |
| `sde_end_percent` | Ending percentage of the sampling process where the stochastic (SDE) component stops; converted to a sigma value using the model's schedule (default: 0.8) | FLOAT | No | 0.0 - 1.0 |
| `s_noise` | Controls the amount of noise added during sampling (default: 1.0) | FLOAT | No | 0.0 - 100.0 |
| `predictor_order` | The order of the predictor component in the solver (default: 3) | INT | No | 1 - 6 |
| `corrector_order` | The order of the corrector component in the solver (default: 4) | INT | No | 0 - 6 |
| `use_pece` | Enables the PECE (Predict-Evaluate-Correct-Evaluate) method (default: disabled) | BOOLEAN | No | - |
| `simple_order_2` | Enables simplified second-order calculations (default: disabled) | BOOLEAN | No | - |

All optional inputs are marked as advanced in the interface.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | A configured sampler object (using the `sa_solver` algorithm) that can be used by sampling nodes | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerSASolver/en.md)

***

**Source fingerprint (SHA-256):** `31da2d436665bf533c28b32248f632edab8f6d92372402904702ae954230f98d`


# SamplerSEEDS2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerSEEDS2

This node provides a configurable sampler for image generation.

This node provides a configurable sampler for image generation. It is based on a stochastic differential equation (SDE) solver and can behave like several specific samplers depending on its settings, including `seeds_2`, `exp_heun_2_x0`, and `exp_heun_2_x0_sde`.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `solver_type` | Selects the underlying solver algorithm for the sampler. | COMBO | Yes | "phi\_1"<br />"phi\_2" |
| `eta` | Stochastic strength (default: 1.0). | FLOAT | No | 0.0 - 100.0 |
| `s_noise` | SDE noise multiplier (default: 1.0). | FLOAT | No | 0.0 - 100.0 |
| `r` | Relative step size for the intermediate stage (c2 node) (default: 0.5). | FLOAT | No | 0.01 - 1.0 |

**Note:** The node description defines the following sampler presets:

* `seeds_2`: default settings
* `exp_heun_2_x0`: `solver_type` = "phi\_2", `r` = 1.0, `eta` = 0.0
* `exp_heun_2_x0_sde`: `solver_type` = "phi\_2", `r` = 1.0, `eta` = 1.0, `s_noise` = 1.0

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sampler` | A configured sampler object that can be passed to other sampling nodes. | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerSEEDS2/en.md)

***

**Source fingerprint (SHA-256):** `f48744a706a49ef93d41845bf8c308af971853f6150afd00ded45f0317ffc4f9`


# SamplingPercentToSigma - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplingPercentToSigma

Converts a sampling percentage into the matching sigma value using the selected model's sampling settings.

Converts a sampling percentage into the matching sigma value using the selected model's sampling settings. It maps a percentage between 0.0 and 1.0 onto the model's noise schedule, and can optionally return the model's true maximum or minimum sigma at the two end points.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model containing the sampling parameters used for the conversion | MODEL | Yes | - |
| `sampling_percent` | The sampling percentage to convert to a sigma value (default: 0.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.0001) |
| `return_actual_sigma` | Return the actual sigma value instead of the value used for interval checks. This only affects results at 0.0 and 1.0. (default: False) | BOOLEAN | Yes | - |

When `return_actual_sigma` is enabled, a `sampling_percent` of 0.0 returns the model's maximum sigma value (sigma\_max), and a `sampling_percent` of 1.0 returns the minimum sigma value (sigma\_min). For all other percentages, the result is the same whether or not this option is enabled.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sigma_value` | The sigma value corresponding to the input sampling percentage | FLOAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplingPercentToSigma/en.md)

***

**Source fingerprint (SHA-256):** `30decf1d4804accbdf2a70eba1a773b41ef0e09cfb74f2a9388044dadf0a1ac1`


# SaveTrainingDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveTrainingDataset

This node saves an encoded training dataset to disk for efficient loading during training.

This node saves an encoded training dataset to disk for efficient loading during training. It takes image latents and their matching text conditioning, splits them into smaller files called shards, and stores them in a folder inside the datasets directory. It also writes a metadata file describing the dataset.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `latents` | List of latent dicts from MakeTrainingDataset. | LATENT | Yes | N/A |
| `conditioning` | List of conditioning lists from MakeTrainingDataset. | CONDITIONING | Yes | N/A |
| `folder_name` | Name of folder to save the dataset into, inside the datasets directory. Subfolders like 'project/run1' are allowed. (default: "training\_dataset") | STRING | Yes | N/A |
| `shard_size` | Number of samples per shard file. (default: 1000) | INT | Yes | 1 to 100000 |

**Note:** The number of items in `latents` must exactly match the number of items in `conditioning`; the node raises an error if these counts do not match. The `folder_name` must name a subfolder of the datasets directory (for example `my_dataset`) — it cannot be the datasets directory itself, and folder names that would resolve outside the datasets directory are rejected. The `shard_size` parameter is an advanced setting.

## Outputs

This node does not produce any output data. Its function is to save files to your disk. Each shard is saved as a `shard_XXXX.pkl` file in the chosen folder, and a `metadata.json` file records the total number of samples, the number of shards, and the shard size.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveTrainingDataset/en.md)

***

**Source fingerprint (SHA-256):** `6d7b63a24ac42907b0f4a1358712cd0ed085982ecd308bce87e5376d9bbc2274`


# ScaleROPE - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ScaleROPE

The ScaleROPE node allows you to modify the Rotary Position Embedding (ROPE) of a model by applying separate scaling and shifting factors to its X, Y, and T (time) components.

The ScaleROPE node allows you to modify the Rotary Position Embedding (ROPE) of a model by applying separate scaling and shifting factors to its X, Y, and T (time) components. It is an advanced, experimental node used to adjust the model's positional encoding behavior.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model whose ROPE parameters will be modified. | MODEL | Yes | - |
| `scale_x` | The scaling factor to apply to the X component of the ROPE (default: 1.0). | FLOAT | Yes | 0.0 - 100.0 (step 0.1) |
| `shift_x` | The shift value to apply to the X component of the ROPE (default: 0.0). | FLOAT | Yes | -256.0 - 256.0 (step 0.1) |
| `scale_y` | The scaling factor to apply to the Y component of the ROPE (default: 1.0). | FLOAT | Yes | 0.0 - 100.0 (step 0.1) |
| `shift_y` | The shift value to apply to the Y component of the ROPE (default: 0.0). | FLOAT | Yes | -256.0 - 256.0 (step 0.1) |
| `scale_t` | The scaling factor to apply to the T (time) component of the ROPE (default: 1.0). | FLOAT | Yes | 0.0 - 100.0 (step 0.1) |
| `shift_t` | The shift value to apply to the T (time) component of the ROPE (default: 0.0). | FLOAT | Yes | -256.0 - 256.0 (step 0.1) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The model with the new ROPE scaling and shifting parameters applied. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ScaleROPE/en.md)

***

**Source fingerprint (SHA-256):** `5d5ab0182b78c8c12ceaf44685a91e666ce15fa099fd194e3605bbdb9cc3c961`


# SetFirstSigma - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetFirstSigma

The SetFirstSigma node changes a sigma sequence by replacing only its first value with a custom sigma value.

The SetFirstSigma node changes a sigma sequence by replacing only its first value with a custom sigma value. It takes an existing sigma sequence and a new sigma value, then returns a new sigma sequence where all values except the first remain unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `sigmas` | The input sequence of sigma values to be modified | SIGMAS | Yes | - |
| `sigma` | The new sigma value to set as the first element in the sequence (default: 136.0) | FLOAT | Yes | 0.0 to 20000.0 (step: 0.001) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `sigmas` | The modified sigma sequence with the first element replaced by the custom sigma value | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetFirstSigma/en.md)

***

**Source fingerprint (SHA-256):** `5302bc61a7ca094fee9ee2ad8c9dc32997ef0bbf27c9945acd7287e7df6b6db3`


# SplitSigmas - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplitSigmas

The SplitSigmas node is designed for dividing a sequence of sigma values into two parts based on a specified step.

The SplitSigmas node is designed for dividing a sequence of sigma values into two parts based on a specified step. This functionality is crucial for operations that require different handling or processing of the initial and subsequent parts of the sigma sequence, enabling more flexible and targeted manipulation of these values.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `sigmas` | The 'sigmas' parameter represents the sequence of sigma values to be split. It is essential for determining the division point and the resulting two sequences of sigma values, impacting the node's execution and results. | `SIGMAS` |
| `step` | The 'step' parameter specifies the index at which the sigma sequence should be split. It plays a critical role in defining the boundary between the two resulting sigma sequences, influencing the node's functionality and the characteristics of the output. | `INT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `sigmas` | The node outputs two sequences of sigma values, each representing a part of the original sequence divided at the specified step. These outputs are crucial for subsequent operations that require differentiated handling of sigma values. | `SIGMAS` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SplitSigmas/en.md)


# SplitSigmasDenoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplitSigmasDenoise

The SplitSigmasDenoise node divides a sequence of sigma values into two parts based on a denoising strength parameter.

The SplitSigmasDenoise node divides a sequence of sigma values into two parts based on a denoising strength parameter. It splits the input sigmas into high and low sigma sequences, where the split point is determined by multiplying the total steps (one less than the number of sigma values) by the denoise factor. This allows for separating the noise schedule into different intensity ranges for specialized processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `sigmas` | The input sequence of sigma values representing the noise schedule | SIGMAS | Yes | - |
| `denoise` | The denoising strength factor that determines where to split the sigma sequence (default: 1.0) | FLOAT | Yes | 0.0 - 1.0 (step: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `high_sigmas` | The first portion of the sigma sequence, containing the higher sigma values up to the split point | SIGMAS |
| `low_sigmas` | The second portion of the sigma sequence, containing the lower sigma values from the split point onward | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SplitSigmasDenoise/en.md)

***

**Source fingerprint (SHA-256):** `6198cdbc07b5c9aacf1137a5d6350e090ffd14050abbcc37ff79ff5e975a8c20`


# Tencent3DPartNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Tencent3DPartNode

This node uses the Tencent Hunyuan3D API to automatically identify and generate components of a 3D model based on its structure.

This node uses the Tencent Hunyuan3D API to automatically identify and generate components of a 3D model based on its structure. It accepts an FBX model, processes it, and returns a new FBX file.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | 3D model in FBX format. Model should have less than 30000 faces. | FILE3D | Yes | FBX, Any |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | Yes | 0 to 2147483647 |

**Note:** The `model_3d` input only supports files in the FBX format. If a different 3D file format is provided, the node will raise an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `FBX` | The processed 3D model, returned as an FBX file. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Tencent3DPartNode/en.md)

***

**Source fingerprint (SHA-256):** `827b42559f4b2c341f08c58f53778d27c1c6afce607c36c8d1eae7c208c6a738`


# Tencent3DTextureEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Tencent3DTextureEditNode

This node uses the Tencent Hunyuan3D API to edit the textures of a 3D model.

This node uses the Tencent Hunyuan3D API to edit the textures of a 3D model. You provide a 3D model and a text description of the desired changes, and the node returns a new version of the model with its textures redrawn according to your prompt.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | 3D model in FBX format. Model should have less than 100000 faces. | FILE3D | Yes | FBX, Any |
| `prompt` | Describes texture editing. Supports up to 1024 UTF-8 characters. | STRING | Yes | |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | No | 0 to 2147483647 |

**Note:** The `model_3d` input must be a file in the FBX format. Other 3D file formats are not supported by this node. The `prompt` parameter is required and must be between 1 and 1024 characters in length.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `GLB` | The processed 3D model in GLB format. | FILE3D |
| `OBJ` | The processed 3D model in OBJ format. | FILE3D |
| `texture_image` | The newly generated texture image for the 3D model. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Tencent3DTextureEditNode/en.md)

***

**Source fingerprint (SHA-256):** `eedddc8bd47a4af6e45a516f2817e7c1dded575d9e28ea9b66a1d7a39b93526c`


# TencentImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TencentImageToModelNode

This node uses Tencent's Hunyuan3D Pro API to generate a 3D model from one or more input images.

This node uses Tencent's Hunyuan3D Pro API to generate a 3D model from one or more input images. It processes the images, sends them to the API, and returns the generated 3D model files in GLB and OBJ formats, along with optional texture maps.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The version of the Hunyuan3D model to use. The LowPoly option is unavailable for the `3.1` model. | COMBO | Yes | `"3.0"`<br />`"3.1"` |
| `image` | The primary input image used to generate the 3D model. Must be at least 128x128 pixels. | IMAGE | Yes | - |
| `image_left` | An optional image of the object's left side for multi-view generation. Must be at least 128x128 pixels. | IMAGE | No | - |
| `image_right` | An optional image of the object's right side for multi-view generation. Must be at least 128x128 pixels. | IMAGE | No | - |
| `image_back` | An optional image of the object's back side for multi-view generation. Must be at least 128x128 pixels. | IMAGE | No | - |
| `face_count` | The target number of faces for the generated 3D model (default: 500000). | INT | Yes | 3000 - 1500000 |
| `generate_type` | The type of 3D model to generate. Selecting an option reveals additional related parameters. | DYNAMICCOMBO | Yes | `"Normal"`<br />`"LowPoly"`<br />`"Geometry"` |
| `generate_type.pbr` | Enables Physically Based Rendering (PBR) material generation. This parameter is only visible when `generate_type` is set to "Normal" or "LowPoly" (default: False). | BOOLEAN | No | - |
| `generate_type.polygon_type` | The type of polygon to use for the mesh. This parameter is only visible when `generate_type` is set to "LowPoly". | COMBO | No | `"triangle"`<br />`"quadrilateral"` |
| `seed` | A seed value for the generation process. Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). | INT | Yes | 0 - 2147483647 |

**Note:** All input images must have a minimum width and height of 128 pixels. Images are automatically downscaled if they exceed 4900 pixels on their longest side.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | A legacy output for backward compatibility. | STRING |
| `GLB` | The generated 3D model in the GLB (Binary GL Transmission Format) file format. | FILE3DGLB |
| `OBJ` | The generated 3D model in the OBJ (Wavefront) file format. | FILE3DOBJ |
| `texture_image` | The texture image for the generated 3D model. | IMAGE |
| `optional_metallic` | The metallic map for PBR materials. Returns a black image if not available. | IMAGE |
| `optional_normal` | The normal map for PBR materials. Returns a black image if not available. | IMAGE |
| `optional_roughness` | The roughness map for PBR materials. Returns a black image if not available. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TencentImageToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `fe422cfa714dbff7cd5dabb286d93d59afe9a01daf711ca09ebcf47ef100a52e`


# TencentModelTo3DUVNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TencentModelTo3DUVNode

This node uses the Tencent Hunyuan3D API to perform UV unfolding on a 3D model.

This node uses the Tencent Hunyuan3D API to perform UV unfolding on a 3D model. It takes a 3D model file as input, sends it to the API for processing, and returns the processed model in OBJ and FBX formats along with a generated UV texture image. The input model must have fewer than 30,000 faces.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | Input 3D model (GLB, OBJ, or FBX). The model must have less than 30000 faces. | FILE3D | Yes | GLB<br />OBJ<br />FBX |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 1) | INT | No | 0 to 2147483647 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `OBJ` | The processed 3D model file in OBJ format. | FILE3D |
| `FBX` | The processed 3D model file in FBX format. | FILE3D |
| `uv_image` | The generated UV texture image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TencentModelTo3DUVNode/en.md)

***

**Source fingerprint (SHA-256):** `b69519df055043555ab7f4d75cfb3b77b9011d5a8e93d0b3ba30c7a8674bd2cb`


# TencentSmartTopologyNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TencentSmartTopologyNode

This node performs smart retopology on a 3D model, automatically creating a new, cleaner mesh with optimized polygon count.

This node performs smart retopology on a 3D model, automatically creating a new, cleaner mesh with optimized polygon count. It connects to a Tencent Hunyuan 3D API to process the model, supporting GLB and OBJ file formats up to 200MB. The node returns the processed model as an OBJ file.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | Input 3D model (GLB or OBJ). The file must be in GLB or OBJ format and cannot exceed 200MB. | FILE3D | Yes | - |
| `polygon_type` | Surface composition type. | STRING | Yes | `"triangle"`<br />`"quadrilateral"` |
| `face_level` | Polygon reduction level. | STRING | Yes | `"medium"`<br />`"high"`<br />`"low"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | No | 0 to 2147483647 |

**Note:** The `seed` parameter is used to trigger a re-run of the node, but the final output is not guaranteed to be the same for the same seed value.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `OBJ` | The processed 3D model with optimized topology, returned in OBJ format. | FILE3D |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TencentSmartTopologyNode/en.md)

***

**Source fingerprint (SHA-256):** `effbccb4d239ffb6b575fc547dd54cbb61aa4508502345cb5bef1d66b320926b`


# TencentTextToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TencentTextToModelNode

This node uses Tencent's Hunyuan3D Pro API to generate a 3D model from a text description.

This node uses Tencent's Hunyuan3D Pro API to generate a 3D model from a text description. It sends a request to create a generation task, polls for the result, and downloads the final model files in GLB and OBJ formats.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The version of the Hunyuan3D model to use. The LowPoly option is unavailable for the `3.1` model. | COMBO | Yes | `"3.0"`<br />`"3.1"` |
| `prompt` | The text description of the 3D model to generate. Supports up to 1024 characters. | STRING | Yes | - |
| `face_count` | The target number of faces for the generated 3D model. Default: 500000. | INT | Yes | 3000 - 1500000 |
| `generate_type` | The type of 3D model to generate. The available options and their associated parameters are:<br />- **Normal**: Generates a standard model. Includes a `pbr` parameter (default: `False`).<br />- **LowPoly**: Generates a low-polygon model. Includes `polygon_type` (`"triangle"` or `"quadrilateral"`) and `pbr` (default: `False`) parameters.<br />- **Geometry**: Generates a geometry-only model. | DYNAMICCOMBO | Yes | `"Normal"`<br />`"LowPoly"`<br />`"Geometry"` |
| `seed` | A seed value for the generation. Results are non-deterministic regardless of seed. Setting a new seed controls whether the node should re-run. Default: 0. | INT | No | 0 - 2147483647 |

**Note:** The `generate_type` parameter is dynamic. Selecting `"LowPoly"` will reveal additional inputs for `polygon_type` and `pbr`. Selecting `"Normal"` will reveal an input for `pbr`. Selecting `"Geometry"` will not reveal any additional inputs.

**Constraint:** The `"LowPoly"` generate type cannot be used with the `"3.1"` model.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | A legacy output for backward compatibility. | STRING |
| `GLB` | The generated 3D model in the GLB file format. | FILE3DGLB |
| `OBJ` | The generated 3D model in the OBJ file format. | FILE3DOBJ |
| `texture_image` | The texture image extracted from the generated OBJ file, if available. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TencentTextToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `8110b6a70cdd26d5d0dcb791e654a6292895693e25076b982951c65f787422d6`


# TrainLoraNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TrainLoraNode

The TrainLoraNode creates and trains a LoRA (Low-Rank Adaptation) model on a diffusion model using provided latents and conditioning data.

The TrainLoraNode creates and trains a LoRA (Low-Rank Adaptation) model on a diffusion model using provided latents and conditioning data. It allows you to fine-tune a model with custom training parameters, optimizers, and loss functions. The node outputs the trained LoRA weights, a loss history map, and the total training steps completed.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to train the LoRA on. | MODEL | Yes | - |
| `latents` | The Latents to use for training, serve as dataset/input of the model. | LATENT | Yes | - |
| `positive` | The positive conditioning to use for training. | CONDITIONING | Yes | - |
| `batch_size` | The batch size to use for training (default: 1). | INT | Yes | 1-10000 |
| `grad_accumulation_steps` | The number of gradient accumulation steps to use for training (default: 1). | INT | Yes | 1-1024 |
| `steps` | The number of steps to train the LoRA for (default: 16). | INT | Yes | 1-100000 |
| `learning_rate` | The learning rate to use for training (default: 0.0005). | FLOAT | Yes | 0.0000001-1.0 |
| `rank` | The rank of the LoRA layers (default: 8). | INT | Yes | 1-128 |
| `optimizer` | The optimizer to use for training (default: "AdamW"). | COMBO | Yes | "AdamW"<br />"Adam"<br />"SGD"<br />"RMSprop" |
| `loss_function` | The loss function to use for training (default: "MSE"). | COMBO | Yes | "MSE"<br />"L1"<br />"Huber"<br />"SmoothL1" |
| `seed` | The seed to use for training (used in generator for LoRA weight initialization and noise sampling) (default: 0). | INT | Yes | 0-18446744073709551615 |
| `training_dtype` | The dtype to use for training. 'none' preserves the model's native compute dtype instead of overriding it. For fp16 models, GradScaler is automatically enabled (default: "bf16"). | COMBO | Yes | "bf16"<br />"fp32"<br />"none" |
| `lora_dtype` | The dtype to use for lora (default: "bf16"). | COMBO | Yes | "bf16"<br />"fp32" |
| `quantized_backward` | When using training\_dtype 'none' and training on quantized model, doing backward with quantized matmul when enabled (default: False). | BOOLEAN | Yes | - |
| `algorithm` | The algorithm to use for training. | COMBO | Yes | Multiple options available |
| `gradient_checkpointing` | Use gradient checkpointing for training (default: True). | BOOLEAN | Yes | - |
| `checkpoint_depth` | Depth level for gradient checkpointing (default: 1). | INT | Yes | 1-5 |
| `offloading` | Offload model weights to CPU during training to save GPU memory (default: False). | BOOLEAN | Yes | - |
| `existing_lora` | The existing LoRA to append to. Set to None for new LoRA (default: "\[None]"). | COMBO | Yes | Multiple options available |
| `bucket_mode` | Enable resolution bucket mode. When enabled, expects pre-bucketed latents from ResolutionBucket node (default: False). | BOOLEAN | Yes | - |
| `bypass_mode` | Enable bypass mode for training. When enabled, adapters are applied via forward hooks instead of weight modification. Useful for quantized models where weights cannot be directly modified (default: False). | BOOLEAN | Yes | - |

**Note:** The number of positive conditioning inputs must match the number of latent images. If only one positive conditioning is provided with multiple images, it will be automatically repeated for all images.

**Note on `training_dtype`:** When set to "none", the model's native compute dtype is preserved. For fp16 models, GradScaler is automatically enabled to prevent underflow during gradient computation. If `fp16_accumulation` is also enabled (via `--fast` flags), this combination can be numerically unstable and may cause NaN values.

**Note on `quantized_backward`:** This parameter is only relevant when `training_dtype` is set to "none" and the model is a quantized model. It enables quantized matrix multiplication during the backward pass.

**Note on `bypass_mode`:** When enabled, adapters are applied via forward hooks instead of modifying the model weights directly. This is particularly useful for quantized models where weights cannot be directly modified.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `lora` | The trained LoRA weights that can be saved or applied to other models. | LORA\_MODEL |
| `loss_map` | A dictionary containing the training loss values over time. | LOSS\_MAP |
| `steps` | The total number of training steps completed (including any previous steps from existing LoRA). | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TrainLoraNode/en.md)

***

**Source fingerprint (SHA-256):** `39e88045270d36855442024b62d6a225a58b34842f45ac04fbc6c1ade6768a76`


# TripoConversionNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoConversionNode

This node converts an existing Tripo 3D model into another 3D file format.

This node converts an existing Tripo 3D model into another 3D file format. It takes the task ID of a model previously created or processed by a Tripo operation (such as model generation, rigging, retargeting, or segmentation), submits a conversion task to the Tripo API, waits for that task to finish, and then returns the converted model file.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `original_model_task_id` | Task ID of the Tripo model to convert. It must come from an earlier Tripo model generation, rigging, retargeting, or segmentation task. If the ID is missing or empty, the node raises an error. | STRING | Yes | MODEL\_TASK\_ID<br />RIG\_TASK\_ID<br />RETARGET\_TASK\_ID<br />SEGMENT\_TASK\_ID |
| `format` | Target file format for the converted 3D model. | COMBO | Yes | GLTF<br />USDZ<br />FBX<br />OBJ<br />STL<br />3MF |
| `quad` | Convert triangles to quads when enabled (default: False). | BOOLEAN | No | True or False |
| `face_limit` | Maximum number of faces in the converted model. Set to -1 for no limit (default: -1). | INT | No | -1 to 2000000 |
| `texture_size` | Resolution of the output textures in pixels (default: 4096). | INT | No | 128 to 8192 |
| `texture_format` | File format used for exported textures (default: JPEG). | COMBO | No | BMP<br />DPX<br />HDR<br />JPEG<br />OPEN\_EXR<br />PNG<br />TARGA<br />TIFF<br />WEBP |
| `force_symmetry` | Force the model to be symmetrical when enabled (default: False). | BOOLEAN | No | True or False |
| `flatten_bottom` | Flatten the bottom of the model when enabled (default: False). | BOOLEAN | No | True or False |
| `flatten_bottom_threshold` | Flattening depth used with `flatten_bottom` (default: 0.01). This value is only applied when `flatten_bottom` is enabled. | FLOAT | No | 0.01 to 1.0 |
| `pivot_to_center_bottom` | Move the pivot point to the center bottom of the model when enabled (default: False). | BOOLEAN | No | True or False |
| `scale_factor` | Scale factor applied to the converted model (default: 1.0). | FLOAT | No | 0.01 and above |
| `with_animation` | Keep the skeleton and animation of rigged or retargeted models (default: True). | BOOLEAN | No | True or False |
| `pack_uv` | Repack the UV coordinates when enabled (default: False). | BOOLEAN | No | True or False |
| `bake` | Bake advanced materials into the base textures for broader compatibility (default: True). | BOOLEAN | No | True or False |
| `part_names` | Comma-separated list of model part names to send to the conversion. Empty entries are ignored and duplicate names are removed. Leave empty to omit this option (default: empty). | STRING | No | Comma-separated list of part names |
| `fbx_preset` | FBX compatibility preset. bake\_scale bakes the scale transform into the geometry (default: blender). | COMBO | No | blender<br />mixamo<br />3dsmax<br />bake\_scale |
| `export_vertex_colors` | Export vertex colors when enabled (default: False). | BOOLEAN | No | True or False |
| `export_orientation` | Forward axis of the exported model. default keeps Tripo's +x (default: default). | COMBO | No | default<br />+x<br />-x<br />+y<br />-y |
| `animate_in_place` | Animate the model in place when enabled (default: False). | BOOLEAN | No | True or False |

**Note:** Except for `original_model_task_id` and `format`, all inputs are optional advanced settings. Most settings left at their default values are omitted from the conversion request so the Tripo API can use its standard behavior. The `with_animation` and `bake` options are always sent. `flatten_bottom_threshold` is only applied when `flatten_bottom` is enabled.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_3d` | Converted model in the requested format. OBJ is delivered by Tripo as a ZIP archive (mesh, material and textures). | FILE\_3D |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoConversionNode/en.md)

***

**Source fingerprint (SHA-256):** `b6be09bf6b1c5ccd6de5ae56ed28bfe1f0b81c1ca8ff61623e3094917c98d68a`


# TripoEditMultiviewNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoEditMultiviewNode

Edits the views of a Tripo: Image to Multiview result using a separate text instruction for each view.

Edits the views of a Tripo: Image to Multiview result using a separate text instruction for each view. Views without an instruction stay unchanged. The edited images are intended to be connected to Tripo: Multiview to Model to create a 3D model; an edited multiview set cannot be edited again.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `multiview_task_id` | Task ID of the Tripo: Image to Multiview result whose views will be edited. Must come from the Tripo: Image to Multiview node. | MULTIVIEW\_TASK\_ID | Yes | Task ID |
| `front_prompt` | Text instruction describing the edit to apply to the front view. When empty, the front view stays unchanged. Default: empty string. | STRING | No | Multiline text |
| `left_prompt` | Text instruction describing the edit to apply to the left view. When empty, the left view stays unchanged. Default: empty string. | STRING | No | Multiline text |
| `back_prompt` | Text instruction describing the edit to apply to the back view. When empty, the back view stays unchanged. Default: empty string. | STRING | No | Multiline text |
| `right_prompt` | Text instruction describing the edit to apply to the right view. When empty, the right view stays unchanged. Default: empty string. | STRING | No | Multiline text |

Note: At least one of the four prompts (`front_prompt`, `left_prompt`, `back_prompt`, `right_prompt`) must contain non-empty text; whitespace-only text is treated as empty, and if all prompts are empty the node raises an error.

Note: The cost is approximately 0.05 USD per view that has an edit instruction.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `front` | Edited front view image. | IMAGE |
| `left` | Edited left view image. | IMAGE |
| `back` | Edited back view image. | IMAGE |
| `right` | Edited right view image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoEditMultiviewNode/en.md)

***

**Source fingerprint (SHA-256):** `db8b0a3ffe4332fcbcaac4da0d7b07217d01d2f05526750540f6036293e013ab`


# TripoImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoImageToModelNode

Generates 3D models synchronously based on a single image using Tripo's API.

Generates 3D models synchronously based on a single image using Tripo's API. Provide an input image, and the node creates a finished 3D model from it, with optional controls for model version, texture generation, level of detail, and output format. This is the legacy version of the image-to-model node, kept for older workflows.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image used to generate the 3D model. An image must be provided, otherwise the node raises an error. | IMAGE | Yes | - |
| `model_version` | The model version to use for generation. | COMBO | No | `"v1.4"`<br />`"v3.0"`<br />`"v3.5"`<br />`"v3.6"` |
| `style` | No longer supported by Tripo and ignored. Kept for older workflows. (default: `"None"`) | COMBO | No | `"None"`<br />`"realistic"`<br />`"cartoon"`<br />`"sculpture"`<br />`"low_poly"` |
| `texture` | Generate texture maps. Off returns bare geometry and ignores `pbr`. (default: True) | BOOLEAN | No | True<br />False |
| `pbr` | PBR material maps (base color, metallic, roughness, normal). Requires `texture`. (default: True) | BOOLEAN | No | True<br />False |
| `model_seed` | Random seed for model generation. (default: 42) | INT | No | 0 to 2147483647 |
| `orientation` | Orientation setting for the generated model. (default: `"default"`) | COMBO | No | `"default"`<br />`"front"`<br />`"back"`<br />`"left"`<br />`"right"`<br />`"top"`<br />`"bottom"` |
| `texture_seed` | Random seed for texture generation. (default: 42) | INT | No | 0 to 2147483647 |
| `texture_quality` | Quality level for texture generation: `detailed` = HD textures, `extreme` = 8K Ultra textures. (default: `"standard"`) | COMBO | No | `"standard"`<br />`"detailed"`<br />`"extreme"` |
| `texture_alignment` | Alignment method for texture mapping. (default: `"original_image"`) | COMBO | No | `"original_image"`<br />`"geometry"` |
| `face_limit` | Maximum face count. -1 lets Tripo pick adaptively (about 1.4M faces on v3.x standard, 2M on detailed). Tripo clamps silently: v2.5 at 500,000, quad meshes at 150,000. (default: -1) | INT | No | -1 to 2000000 |
| `quad` | Quad mesh output. Tripo delivers quad meshes as FBX, so the result arrives on the FBX output and the GLB output stays empty. (default: False) | BOOLEAN | No | True<br />False |
| `geometry_quality` | Quality level for geometry generation. (default: `"standard"`) | COMBO | No | `"standard"`<br />`"detailed"` |
| `smart_low_poly` | Low-poly mesh with clean, hand-crafted style topology (500-20,000 faces, quad 500-10,000). Best for simple subjects; complex ones may fail. (default: False) | BOOLEAN | No | True<br />False |
| `auto_size` | Scale textured models to their real-world size in meters. Tripo stores the size as the model's scene transform and bakes it in when the model is converted, rigged or retargeted; ignored without texture. (default: True) | BOOLEAN | No | True<br />False |

Note: An `image` is required; if it is missing, the node raises a RuntimeError. When `texture` is False, the model contains bare geometry only and `pbr` is forced to False. When `smart_low_poly` is enabled, `face_limit` must be between 500 and 20,000 for triangle meshes, or between 500 and 10,000 when `quad` is also enabled; if the limit is invalid, the node raises a ValueError. Setting `face_limit` to -1 (the default) sends no explicit face limit to the API, letting Tripo choose adaptively.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The generated 3D model file (for backward compatibility only). | STRING |
| `model task_id` | The task ID for tracking the model generation process. | MODEL\_TASK\_ID |
| `GLB` | The generated 3D model in GLB format. Empty when `quad` is enabled. | FILE3DGLB |
| `FBX` | The generated 3D model in FBX format. Only populated when `quad` is enabled. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoImageToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `3b278abfd13329ee58ebab1bfeb47d32d09f4797f3d8628a35a028c3d15a7314`


# TripoImageToModelNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoImageToModelNodeV2

The Tripo: Image to Model node turns a single reference image into a 3D model using Tripo's image-to-model service.

The Tripo: Image to Model node turns a single reference image into a 3D model using Tripo's image-to-model service. It uploads the image, submits a generation task, waits for the task to finish, and returns the resulting 3D file together with the task ID. This is an API node, so it requires a valid Comfy API key.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The reference image used to generate the 3D model. | IMAGE | Yes | — |
| `model_version` | The model version to use for generation. If left unset, the node falls back to Tripo's v3.1 (20260211) version. | COMBO | No | List of Tripo model versions |
| `texture` | Generate texture maps. Off returns bare geometry and ignores `pbr` (default: true). | BOOLEAN | No | true<br />false |
| `pbr` | PBR material maps (base color, metallic, roughness, normal). Requires `texture` (default: true). | BOOLEAN | No | true<br />false |
| `model_seed` | Seed used for the geometry generation step (default: 42). | INT | No | 0 to 2147483647 |
| `orientation` | Orientation setting applied to the generated model (default: DEFAULT). | COMBO | No | Tripo orientation options, default `DEFAULT` |
| `texture_seed` | Seed used for the texture generation step (default: 42). | INT | No | 0 to 2147483647 |
| `texture_quality` | detailed = HD textures, extreme = 8K Ultra textures (default: "standard"). | COMBO | No | "standard"<br />"detailed"<br />"extreme" |
| `texture_alignment` | How textures are aligned on the generated geometry (default: "original\_image"). | COMBO | No | "original\_image"<br />"geometry" |
| `face_limit` | Maximum face count. -1 lets Tripo pick adaptively (about 1.4M faces on v3.x standard, 2M on detailed). Tripo clamps silently: v2.5 at 500,000, quad meshes at 150,000 (default: -1). | INT | No | -1 to 2000000 |
| `quad` | Quad mesh output. Tripo delivers quad meshes as FBX, so the result arrives on the FBX output and the GLB output stays empty (default: false). | BOOLEAN | No | true<br />false |
| `geometry_quality` | The quality level of the generated geometry (default: "standard"). | COMBO | No | "standard"<br />"detailed" |
| `smart_low_poly` | Low-poly mesh with clean, hand-crafted style topology (500-20,000 faces, quad 500-10,000). Best for simple subjects; complex ones may fail (default: false). | BOOLEAN | No | true<br />false |
| `auto_size` | Scale textured models to their real-world size in meters. Tripo stores the size as the model's scene transform and bakes it in when the model is converted, rigged or retargeted; ignored without texture (default: true). | BOOLEAN | No | true<br />false |

**Notes:**

* `image` is required; the node raises an error if no image is supplied.
* When `smart_low_poly` is enabled and `face_limit` is set to a value other than -1, the limit must be between 500 and 20,000 for triangle meshes, or between 500 and 10,000 when `quad` is enabled. Other values raise an error.
* When `texture` is disabled, `pbr` is forced off regardless of its setting, and `auto_size` has no effect.
* A `face_limit` of -1 is sent to Tripo as "no limit", letting the service choose adaptively.
* A new 3D file format the node cannot return (anything other than GLB or FBX) causes an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model task_id` | The Tripo task ID of the generation job. | MODEL\_TASK\_ID |
| `GLB` | The generated model as a GLB file. Empty when `quad` is enabled. | FILE3DGLB |
| `FBX` | The generated model as an FBX file. Only populated when `quad` is enabled. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoImageToModelNodeV2/en.md)

***

**Source fingerprint (SHA-256):** `c8c069432f67a019995b9f4dedbf5ca3f7594ae4004104277068106821189c11`


# TripoImageToMultiviewNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoImageToMultiviewNode

Generates front, left, back and right views of the subject from a single input image using the Tripo API.

Generates front, left, back and right views of the subject from a single input image using the Tripo API. The image is uploaded, a multiview generation task is started and polled until it completes, and the four resulting views are returned together with the task ID. This is a paid task billed at approximately 0.10 USD.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The source image of the subject from which Tripo generates the front, left, back and right views. Only one image is used for the request, even if a batch is supplied. | IMAGE | Yes | Single image |

Note: The node calls Tripo's cloud API and waits for the generation task to finish. A typical task takes around 25 seconds. Authentication is handled automatically through the node's hidden inputs, so no Tripo API key needs to be provided in the workflow. The node requires all four view URLs in the Tripo response (`front_view_url`, `left_view_url`, `back_view_url`, `right_view_url`); if any view is missing, execution fails with an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `multiview task_id` | The task identifier returned by Tripo for the multiview image generation request. It can be used to reference the completed task, for example when refining the views with Tripo: Edit Multiview. | MULTIVIEW\_TASK\_ID |
| `front` | The generated front view of the subject. | IMAGE |
| `left` | The generated left-side view of the subject. | IMAGE |
| `back` | The generated back view of the subject. | IMAGE |
| `right` | The generated right-side view of the subject. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoImageToMultiviewNode/en.md)

***

**Source fingerprint (SHA-256):** `7e96d327940f1f09a3e84031c773c1439380f20afae49c79fd4350fcf0aba5da`


# TripoImportModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoImportModelNode

This node imports an external 3D model into Tripo so that Tripo post-processing nodes, such as Texture, Rig, and Convert, can use it.

This node imports an external 3D model into Tripo so that Tripo post-processing nodes, such as Texture, Rig, and Convert, can use it. The node uploads the file to Tripo and returns a task ID that identifies the imported model for use by those nodes. GLB is recommended because textures are preserved only when embedded in the file, and texturing an imported model requires a texture prompt. This node is free to use.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_3d` | 3D model to import (GLB / FBX / OBJ / STL, up to 150 MB). OBJ and STL files carry no embedded textures. | FILE3D | Yes | GLB<br />FBX<br />OBJ<br />STL<br />Any 3D format |

**Note:** Only GLB, FBX, OBJ, and STL formats are supported. GLTF (.gltf) cannot be imported because it references external files; export a single-file GLB instead. The model file must be 150 MB or smaller. GLB is recommended because textures survive import only when embedded in the file. OBJ and STL files do not carry embedded textures. Texturing an imported model requires a texture prompt.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model task_id` | A task ID that identifies the imported model, for use with Tripo post-processing nodes | MODEL\_TASK\_ID |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoImportModelNode/en.md)

***

**Source fingerprint (SHA-256):** `bf91e964c5705f7377868dd06bbf5d57b41cc3607fc377cd45886d3d6c5ceddc`


# TripoMeshCompleteNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoMeshCompleteNode

Completes the parts of a segmented 3D model and repairs missing or damaged regions of the mesh.

Completes the parts of a segmented 3D model and repairs missing or damaged regions of the mesh. It takes the task ID of a Tripo mesh segmentation result, requests the completion job from Tripo, and waits for it to finish. You can optionally limit the work to specific part names. The completed model is returned as a GLB file.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `segment_task_id` | Task ID of a Tripo mesh segmentation task. The parts of the segmented model from this task are completed. Connect the SEGMENT\_TASK\_ID output of a previous Tripo mesh segmentation node. | SEGMENT\_TASK\_ID | Yes | Single task ID |
| `part_names` | Comma-separated part names to complete. Empty completes every part. Default: empty string. Extra spaces around names are removed and duplicate names are ignored. | STRING | No | Free text or empty |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | File name of the completed model. This output exists for backward compatibility only. | STRING |
| `model task_id` | Task ID of the completed Tripo mesh completion task. Can be used as input by other Tripo nodes that expect a model task ID. | MODEL\_TASK\_ID |
| `GLB` | The completed 3D model with repaired parts, downloaded as a GLB file. | GLB |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoMeshCompleteNode/en.md)

***

**Source fingerprint (SHA-256):** `c5709231fa2e33e6f3c9b25669acca1d4ae9adb882b90210d703aeddc0d11ecc`


# TripoMultiviewToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoMultiviewToModelNode

This node generates 3D models synchronously using Tripo's API by processing up to four images showing different views of an object (front, left, back, right).

This node generates 3D models synchronously using Tripo's API by processing up to four images showing different views of an object (front, left, back, right). It requires a front image and at least one additional view (left, back, or right) to build the 3D model. Texture, PBR material, geometry quality, and output format can be controlled from the node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Front view image of the object. | IMAGE | Yes | - |
| `image_left` | Left view image of the object. | IMAGE | No | - |
| `image_back` | Back view image of the object. | IMAGE | No | - |
| `image_right` | Right view image of the object. | IMAGE | No | - |
| `model_version` | The model version to use for generation. | COMBO | No | Multiple options available |
| `orientation` | Orientation setting for the 3D model (default: `"default"`). | COMBO | No | Multiple options available |
| `texture` | Generate texture maps. Off returns bare geometry and ignores pbr. (default: True) | BOOLEAN | No | - |
| `pbr` | PBR material maps (base color, metallic, roughness, normal). Requires texture. (default: True) | BOOLEAN | No | - |
| `model_seed` | Random seed for model generation (default: 42). | INT | No | 0 to 2,147,483,647 |
| `texture_seed` | Random seed for texture generation (default: 42). | INT | No | 0 to 2,147,483,647 |
| `texture_quality` | Quality level for texture generation (default: `"standard"`). `"detailed"` = HD textures, `"extreme"` = 8K Ultra textures. | COMBO | No | `"standard"`<br />`"detailed"`<br />`"extreme"` |
| `texture_alignment` | Method used for aligning textures to the model (default: `"original_image"`). | COMBO | No | `"original_image"`<br />`"geometry"` |
| `face_limit` | Maximum face count. -1 lets Tripo pick adaptively (about 1.4M faces on v3.x standard, 2M on detailed). Tripo clamps silently: v2.5 at 500,000, quad meshes at 150,000. (default: -1) | INT | No | -1 to 2,000,000 |
| `quad` | Quad mesh output. Tripo delivers quad meshes as FBX, so the result arrives on the FBX output and the GLB output stays empty. (default: False) | BOOLEAN | No | - |
| `geometry_quality` | Quality level for geometry generation (default: `"standard"`). | COMBO | No | `"standard"`<br />`"detailed"` |
| `smart_low_poly` | Low-poly mesh with clean, hand-crafted style topology (500-20,000 faces, quad 500-10,000). Best for simple subjects; complex ones may fail. (default: False) | BOOLEAN | No | - |
| `auto_size` | Scale textured models to their real-world size in meters. Tripo stores the size as the model's scene transform and bakes it in when the model is converted, rigged or retargeted; ignored without texture. (default: False) | BOOLEAN | No | - |

**Note:** The front image (`image`) is always required, and at least one of `image_left`, `image_back`, or `image_right` must also be provided. Turning `texture` off automatically turns `pbr` off as well, since `pbr` requires texture. When `smart_low_poly` is enabled and `face_limit` is not left at -1, `face_limit` must be between 500 and 20,000 for triangle meshes or between 500 and 10,000 for quad meshes.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | File path or identifier for the generated 3D model (for backward compatibility only). | STRING |
| `model task_id` | Task identifier for tracking the model generation process. | MODEL\_TASK\_ID |
| `GLB` | The generated 3D model file in GLB format. Empty when `quad` is enabled. | FILE3DGLB |
| `FBX` | The generated 3D model file in FBX format. Only populated when `quad` is enabled. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoMultiviewToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `b66df4cad6167fa27edf1fe21b96cb47af90027b3fbe0a3c9c14101506281ed7`


# TripoP1ImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoP1ImageToModelNode

Tripo P1: Image to Model converts a single 2D image into a 3D model using the Tripo P1 API.

Tripo P1: Image to Model converts a single 2D image into a 3D model using the Tripo P1 API. It is optimized for generating low-polygon, game-ready meshes, and lets you choose between a geometry-only mesh or a textured model with PBR maps. The finished model is returned as a GLB file.

## Inputs

### Common Inputs

These parameters are always available.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `output_mode` | Chooses the type of result. "Geometry only" returns an untextured mesh; "Textured" adds color/PBR maps and reveals extra texture settings. | DYNAMIC\_COMBO | Yes | `"Geometry only"`<br />`"Textured"` |
| `image` | The source 2D image used to generate the 3D model. A single image is required; the node raises an error if none is provided. | IMAGE | Yes | - |
| `enable_image_autofix` | Pre-process the input image for better generation quality. (default: False) | BOOLEAN | No | True<br />False |
| `face_limit` | Target face count, 48-20000. -1 lets Tripo pick adaptively. (default: -1) | INT | No | -1 to 20000 |
| `model_seed` | Seed used for the geometry generation so results can be reproduced. (default: 42) | INT | No | 0 to 2147483647 |
| `auto_size` | Scale the output to approximate real-world meters. (default: False) | BOOLEAN | No | True<br />False |
| `export_uv` | UV unwrap during generation. Turn off for faster geometry-only runs. (default: True) | BOOLEAN | No | True<br />False |
| `compress_geometry` | Apply meshopt geometry compression (EXT\_meshopt\_compression). Smaller files, but ComfyUI's 3D preview cannot display them; decompress before editing. (default: False) | BOOLEAN | No | True<br />False |

### Geometry only Inputs

No additional parameters. The output is an untextured mesh.

### Textured Inputs

These parameters appear when `output_mode` is set to "Textured".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `pbr` | Include PBR maps. When on, base texture is forced on too. (default: True) | BOOLEAN | Yes | True<br />False |
| `texture_quality` | detailed = HD textures, extreme = 8K Ultra textures. (default: "standard") | COMBO | Yes | `"standard"`<br />`"detailed"`<br />`"extreme"` |
| `texture_alignment` | Prioritize visual fidelity to the source image, or alignment to the mesh geometry. (default: "original\_image") | COMBO | Yes | `"original_image"`<br />`"geometry"` |
| `orientation` | Rotate the output to match the source image. Only applies when textured. (default: "default") | COMBO | Yes | `"default"`<br />`"align_image"` |
| `texture_seed` | Seed used for the texture generation so textured results can be reproduced. (default: 42) | INT | Yes | 0 to 2147483647 |

Note: When `output_mode` is "Geometry only", texturing is disabled for the request. In "Textured" mode, a color texture is always requested; disabling `pbr` removes the PBR maps but keeps the base color texture, while enabling `pbr` forces the base texture on as well. `texture_alignment` and `orientation` are only available in "Textured" mode.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | A string containing the generated model file name (`<task_id>.glb`). Kept for backward compatibility only. | STRING |
| `model task_id` | The unique task ID returned by the Tripo API for the completed generation job. | MODEL\_TASK\_ID |
| `GLB` | The generated 3D model in GLB format. | FILE3DGLB |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoP1ImageToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `1369da2ef732556896bce3415e7b99023f310544b8077ea4c6b1730bec59ee99`


# TripoP1MultiviewToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoP1MultiviewToModelNode

This node generates a 3D model from two to four reference images of an object or character.

This node generates a 3D model from two to four reference images of an object or character. Provide the front view plus any combination of left, back, and right views, and the node returns the reconstructed subject as a GLB mesh.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Front view (0°). Required. | IMAGE | Yes | - |
| `image_left` | Left view (90°), i.e. the subject's left side. | IMAGE | No | - |
| `image_back` | Back view (180°). | IMAGE | No | - |
| `image_right` | Right view (270°), i.e. the subject's right side. | IMAGE | No | - |
| `output_mode` | Choose the type of model to generate. "Geometry only" returns an untextured mesh. "Textured" adds color/PBR maps. | DYNAMIC\_COMBO | Yes | "Geometry only"<br />"Textured" |
| `face_limit` | Target face count, 48-20000. -1 lets Tripo pick adaptively. (default: -1) | INT | No | -1 to 20000 |
| `model_seed` | Seed for reproducible model generation. (default: 42) | INT | No | 0 to 2147483647 |
| `auto_size` | Scale the output to approximate real-world meters. (default: False) | BOOLEAN | No | True<br />False |
| `export_uv` | UV unwrap during generation. Turn off for faster geometry-only runs. (default: True) | BOOLEAN | No | True<br />False |
| `compress_geometry` | Apply meshopt geometry compression (EXT\_meshopt\_compression). Smaller files, but ComfyUI's 3D preview cannot display them; decompress before editing. (default: False) | BOOLEAN | No | True<br />False |

### Geometry only Inputs

No additional inputs are shown for this mode. The generated model is returned without a texture.

### Textured Inputs

These inputs appear when `output_mode` is set to `"Textured"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `pbr` | Include PBR maps. When on, base texture is forced on too. (default: True) | BOOLEAN | Yes | True<br />False |
| `texture_quality` | Texture quality level. `detailed` = HD textures, `extreme` = 8K Ultra textures. (default: "standard") | COMBO | Yes | "standard"<br />"detailed"<br />"extreme" |
| `texture_alignment` | Prioritize visual fidelity to the source image, or alignment to the mesh geometry. (default: "original\_image") | COMBO | Yes | "original\_image"<br />"geometry" |
| `orientation` | Rotate the output to match the source image. Only applies when textured. (default: "default") | COMBO | Yes | "default"<br />"align\_image" |
| `texture_seed` | Seed used for texture generation. (default: 42) | INT | Yes | 0 to 2147483647 |

**Note:** You must provide at least 2 images: the front view (`image`) plus at least one of the other views (`image_left`, `image_back`, or `image_right`). If fewer than 2 images are provided, the node will raise an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The filename of the generated GLB model (for backward compatibility only). | STRING |
| `model task_id` | The unique task ID for this model generation request. | MODEL\_TASK\_ID |
| `GLB` | The generated 3D model in GLB format. | FILE3DGLB |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoP1MultiviewToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `1153f74ac76603829142959844e701f3c8f16be080e3de849951cffdda322d12`


# TripoP1TextToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoP1TextToModelNode

Tripo P1 text-to-3D.

Tripo P1 text-to-3D. This node generates a 3D model from a text description using the Tripo P1 API. It is optimized for creating low-poly, game-ready meshes with stable topology, making it suitable for real-time applications.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `output_mode` | Controls whether the generated model contains only geometry or also color/PBR textures. "Geometry only" returns an untextured mesh. "Textured" adds color/PBR maps and reveals the texture options below. | DYNAMIC\_COMBO | Yes | `"Geometry only"`<br />`"Textured"` |
| `prompt` | The text description of the 3D model you want to generate. Up to 1024 characters. Required and cannot be empty. | STRING | Yes | Up to 1024 characters |
| `negative_prompt` | A text description of what you do not want in the generated model. Up to 255 characters. Default: not set. | STRING | No | Up to 255 characters |
| `image_seed` | A seed value used to control randomness. Default: 42. | INT | No | 0 to 2147483647 |
| `face_limit` | Target face count, 48-20000. -1 lets Tripo pick adaptively. Default: -1. | INT | No | -1 to 20000 |
| `model_seed` | A seed value used to control randomness. Default: 42. | INT | No | 0 to 2147483647 |
| `auto_size` | Scale the output to approximate real-world meters. Default: False. | BOOLEAN | No | True / False |
| `export_uv` | UV unwrap during generation. Turn off for faster geometry-only runs. Default: True. | BOOLEAN | No | True / False |
| `compress_geometry` | Apply meshopt geometry compression (EXT\_meshopt\_compression). Smaller files, but ComfyUI's 3D preview cannot display them; decompress before editing. Default: False. | BOOLEAN | No | True / False |

### Geometry only Inputs

No extra inputs are available when `output_mode` is set to `"Geometry only"`. Texture-related parameters are not sent to Tripo in this mode.

### Textured Inputs

These inputs appear only when `output_mode` is set to `"Textured"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `pbr` | Include PBR maps. When on, base texture is forced on too. Default: True. | BOOLEAN | Yes | True / False |
| `texture_quality` | Texture quality preset. detailed = HD textures, extreme = 8K Ultra textures. Default: "standard". | COMBO | Yes | `"standard"`<br />`"detailed"`<br />`"extreme"` |
| `texture_seed` | A seed value for texture generation, used to control randomness. Default: 42. | INT | Yes | 0 to 2147483647 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The generated model file name, kept for backward compatibility only. | STRING |
| `model task_id` | The unique task ID for the model generation request. | MODEL\_TASK\_ID |
| `GLB` | The generated 3D model in GLB format. | FILE3DGLB |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoP1TextToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `53a5573384294612b912558436e82f3481717d2ba3d50b73f1e40c3065aff2a0`


# TripoPSeriesImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoPSeriesImageToModelNode

Generates a low-poly 3D model with clean topology from a single image using Tripo's P2 model.

Generates a low-poly 3D model with clean topology from a single image using Tripo's P2 model. The result comes back as a triangle mesh (GLB) or, when `model.quad` is enabled, as a quad-dominant mesh (FBX).

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Tripo P-series model to use. Selecting a model reveals its own inputs below. | DYNAMIC\_COMBO | Yes | `"P2"` |

### P2 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.image` | The image the model is generated from. | IMAGE | Yes | - |
| `model.quad` | Return a quad-dominant mesh on the FBX output instead of a triangle mesh on the GLB output (default: False). | BOOLEAN | Yes | True/False |
| `model.face_limit` | Target face count. `-1` lets Tripo choose. With `model.quad` enabled the limit is 48 to 25,000, otherwise 48 to 50,000 (default: -1). | INT | Yes | -1, or 48 to 50000 |
| `model.texture` | Base color texture resolution: standard is 2K, detailed 4K and extreme 8K. `"none"` returns an untextured mesh (default: `"standard"`). | COMBO | Yes | `"standard"`<br />`"detailed"`<br />`"extreme"`<br />`"none"` |
| `model.pbr` | Add metallic, roughness and normal maps to the base color. Ignored when `model.texture` is `"none"` (default: True). | BOOLEAN | Yes | True/False |
| `model.model_seed` | Seed for the geometry (default: 42). | INT | Yes | 0 to 2147483647 |
| `model.texture_alignment` | Match the colors of the input image, or fit the textures to the generated geometry. Ignored when `model.texture` is `"none"` (default: `"original_image"`). Advanced setting. | COMBO | Yes | `"original_image"`<br />`"geometry"` |
| `model.orientation` | `"align_image"` rotates the model to the viewpoint of the input image. Ignored when `model.texture` is `"none"` (default: `"default"`). Advanced setting. | COMBO | Yes | `"default"`<br />`"align_image"` |
| `model.enable_image_autofix` | Let Tripo enhance a low-resolution or low-quality image before modeling (default: False). Advanced setting. | BOOLEAN | Yes | True/False |
| `model.texture_seed` | Seed for the textures (default: 42). Advanced setting. | INT | Yes | 0 to 2147483647 |
| `model.auto_size` | Scale the model to its real-world size in meters through its scene transform. Ignored when `model.texture` is `"none"` (default: False). Advanced setting. | BOOLEAN | Yes | True/False |
| `model.export_uv` | UV unwrap the mesh when it is untextured. Textured meshes are always unwrapped (default: True). Advanced setting. | BOOLEAN | Yes | True/False |
| `model.compress_geometry` | Apply meshopt geometry compression: much smaller files, but ComfyUI's 3D preview cannot display them. Ignored for quad meshes (default: False). Advanced setting. | BOOLEAN | Yes | True/False |

**Notes:**

* `model.image` is required and only the first image of the batch is used.
* `model.face_limit` is a target rather than a hard cap, so the result can contain more faces than requested. `-1` leaves the choice to Tripo.
* `model.quad` decides which output carries the mesh. With it enabled the model arrives on the FBX output and the GLB output stays empty; with it disabled the model arrives on GLB and FBX stays empty. The node raises an error if the empty output is the one you connected.
* `model.texture`, `model.pbr`, `model.texture_seed`, `model.auto_size`, `model.texture_alignment` and `model.orientation` only apply to textured models: with `"none"` the node sends no texture settings and returns bare geometry.
* `model.compress_geometry` has no effect on quad meshes.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model task_id` | The unique task ID for the model generation request. | MODEL\_TASK\_ID |
| `GLB` | The generated 3D model in GLB format. Empty when `model.quad` is enabled. | FILE3DGLB |
| `FBX` | The generated 3D model in FBX format. Only populated when `model.quad` is enabled. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoPSeriesImageToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `9bfad31ee00546d0603ce3273502cfc93c79e3b125941fed255866aa83f770a5`


# TripoPSeriesMultiviewToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoPSeriesMultiviewToModelNode

Generates a low-poly 3D model with clean topology from several views of the same subject using Tripo's P2 model.

Generates a low-poly 3D model with clean topology from several views of the same subject using Tripo's P2 model. The front view is required and one to three of the left, back and right views can be added to improve the result. The model comes back as a triangle mesh (GLB) or, when `model.quad` is enabled, as a quad-dominant mesh (FBX).

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Tripo P-series model to use. Selecting a model reveals its own inputs below. | DYNAMIC\_COMBO | Yes | `"P2"` |

### P2 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.image` | Front view (0°) of the subject. | IMAGE | Yes | - |
| `model.image_left` | Left view (90°), the subject's own left side. | IMAGE | No | - |
| `model.image_back` | Back view (180°). | IMAGE | No | - |
| `model.image_right` | Right view (270°), the subject's own right side. | IMAGE | No | - |
| `model.quad` | Return a quad-dominant mesh on the FBX output instead of a triangle mesh on the GLB output (default: False). | BOOLEAN | Yes | True/False |
| `model.face_limit` | Target face count. `-1` lets Tripo choose. With `model.quad` enabled the limit is 48 to 25,000, otherwise 48 to 50,000 (default: -1). | INT | Yes | -1, or 48 to 50000 |
| `model.texture` | Base color texture resolution: standard is 2K, detailed 4K and extreme 8K. `"none"` returns an untextured mesh (default: `"standard"`). | COMBO | Yes | `"standard"`<br />`"detailed"`<br />`"extreme"`<br />`"none"` |
| `model.pbr` | Add metallic, roughness and normal maps to the base color. Ignored when `model.texture` is `"none"` (default: True). | BOOLEAN | Yes | True/False |
| `model.model_seed` | Seed for the geometry (default: 42). | INT | Yes | 0 to 2147483647 |
| `model.texture_alignment` | Match the colors of the input images, or fit the textures to the generated geometry. Ignored when `model.texture` is `"none"` (default: `"original_image"`). Advanced setting. | COMBO | Yes | `"original_image"`<br />`"geometry"` |
| `model.orientation` | `"align_image"` rotates the model to the viewpoint of the input images. Ignored when `model.texture` is `"none"` (default: `"default"`). Advanced setting. | COMBO | Yes | `"default"`<br />`"align_image"` |
| `model.texture_seed` | Seed for the textures (default: 42). Advanced setting. | INT | Yes | 0 to 2147483647 |
| `model.auto_size` | Scale the model to its real-world size in meters through its scene transform. Ignored when `model.texture` is `"none"` (default: False). Advanced setting. | BOOLEAN | Yes | True/False |
| `model.export_uv` | UV unwrap the mesh when it is untextured. Textured meshes are always unwrapped (default: True). Advanced setting. | BOOLEAN | Yes | True/False |
| `model.compress_geometry` | Apply meshopt geometry compression: much smaller files, but ComfyUI's 3D preview cannot display them. Ignored for quad meshes (default: False). Advanced setting. | BOOLEAN | Yes | True/False |

**Notes:**

* `model.image` is required, and at least one of `model.image_left`, `model.image_back` or `model.image_right` has to be connected as well; the node raises an error if the front view is the only image.
* Only the first image of each batch is used.
* `model.face_limit` is a target rather than a hard cap, so the result can contain more faces than requested. `-1` leaves the choice to Tripo.
* `model.quad` decides which output carries the mesh. With it enabled the model arrives on the FBX output and the GLB output stays empty; with it disabled the model arrives on GLB and FBX stays empty. The node raises an error if the empty output is the one you connected.
* `model.texture`, `model.pbr`, `model.texture_seed`, `model.auto_size`, `model.texture_alignment` and `model.orientation` only apply to textured models: with `"none"` the node sends no texture settings and returns bare geometry.
* `model.compress_geometry` has no effect on quad meshes.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model task_id` | The unique task ID for the model generation request. | MODEL\_TASK\_ID |
| `GLB` | The generated 3D model in GLB format. Empty when `model.quad` is enabled. | FILE3DGLB |
| `FBX` | The generated 3D model in FBX format. Only populated when `model.quad` is enabled. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoPSeriesMultiviewToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `cea0a65ca001bc8298af9fbe2a83f592abf497987e634b0126482f3d2a18571c`


# TripoPSeriesTextToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoPSeriesTextToModelNode

Generates a low-poly 3D model with clean topology from a text prompt using Tripo's P2 model.

Generates a low-poly 3D model with clean topology from a text prompt using Tripo's P2 model. The result comes back as a triangle mesh (GLB) or, when `model.quad` is enabled, as a quad-dominant mesh (FBX).

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Tripo P-series model to use. Selecting a model reveals its own inputs below. | DYNAMIC\_COMBO | Yes | `"P2"` |

### P2 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.prompt` | Text description of the 3D model to generate. Must not be empty, up to 1024 characters (default: empty). | STRING | Yes | Up to 1024 characters |
| `model.negative_prompt` | Text description of what to avoid in the generated model (default: empty). | STRING | No | Up to 255 characters |
| `model.quad` | Return a quad-dominant mesh on the FBX output instead of a triangle mesh on the GLB output (default: False). | BOOLEAN | Yes | True/False |
| `model.face_limit` | Target face count. `-1` lets Tripo choose. With `model.quad` enabled the limit is 48 to 25,000, otherwise 48 to 50,000 (default: -1). | INT | Yes | -1, or 48 to 50000 |
| `model.texture` | Base color texture resolution: standard is 2K, detailed 4K and extreme 8K. `"none"` returns an untextured mesh (default: `"standard"`). | COMBO | Yes | `"standard"`<br />`"detailed"`<br />`"extreme"`<br />`"none"` |
| `model.pbr` | Add metallic, roughness and normal maps to the base color. Ignored when `model.texture` is `"none"` (default: True). | BOOLEAN | Yes | True/False |
| `model.model_seed` | Seed for the geometry (default: 42). | INT | Yes | 0 to 2147483647 |
| `model.image_seed` | Seed for the image Tripo draws from the prompt before modeling (default: 42). Advanced setting. | INT | Yes | 0 to 2147483647 |
| `model.texture_seed` | Seed for the textures (default: 42). Advanced setting. | INT | Yes | 0 to 2147483647 |
| `model.auto_size` | Scale the model to its real-world size in meters through its scene transform. Ignored when `model.texture` is `"none"` (default: False). Advanced setting. | BOOLEAN | Yes | True/False |
| `model.export_uv` | UV unwrap the mesh when it is untextured. Textured meshes are always unwrapped (default: True). Advanced setting. | BOOLEAN | Yes | True/False |
| `model.compress_geometry` | Apply meshopt geometry compression: much smaller files, but ComfyUI's 3D preview cannot display them. Ignored for quad meshes (default: False). Advanced setting. | BOOLEAN | Yes | True/False |

**Notes:**

* `model.prompt` is required; `model.negative_prompt` is optional and limited to 255 characters.
* `model.face_limit` is a target rather than a hard cap, so the result can contain more faces than requested. `-1` leaves the choice to Tripo.
* `model.quad` decides which output carries the mesh. With it enabled the model arrives on the FBX output and the GLB output stays empty; with it disabled the model arrives on GLB and FBX stays empty. The node raises an error if the empty output is the one you connected.
* `model.texture`, `model.pbr`, `model.texture_seed` and `model.auto_size` only apply to textured models: with `"none"` the node sends no texture settings and returns bare geometry.
* `model.compress_geometry` has no effect on quad meshes.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model task_id` | The unique task ID for the model generation request. | MODEL\_TASK\_ID |
| `GLB` | The generated 3D model in GLB format. Empty when `model.quad` is enabled. | FILE3DGLB |
| `FBX` | The generated 3D model in FBX format. Only populated when `model.quad` is enabled. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoPSeriesTextToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `e55596c1a237cf6b92e3bdead4359f380c6cba60992dcc61b5ee4e6b1bdd843b`


# TripoRetargetNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoRetargetNode

The TripoRetargetNode applies a preset animation to an existing rigged 3D model.

The TripoRetargetNode applies a preset animation to an existing rigged 3D model. It takes the task ID of a model that was previously rigged, sends a retarget request to the Tripo API, and downloads the resulting animated file. The animated model can be returned as GLB or FBX, with optional mesh geometry and optional in-place playback.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `original_model_task_id` | The task ID of the previously rigged 3D model to retarget. The referenced task must be a rig task. | RIG\_TASK\_ID | Yes | - |
| `animation` | The animation preset to apply to the rigged model. `preset:*` animations work with both rig models. `preset:biped:*` animations are made for rigs from model v1.0-20240301; a v2.5 rig accepts only chop, climb, dive, fall, hurt, idle, jump, run, shoot, slash, turn and walk. | COMBO | Yes | `"preset:idle"`<br />`"preset:walk"`<br />`"preset:run"`<br />`"preset:dive"`<br />`"preset:climb"`<br />`"preset:jump"`<br />`"preset:slash"`<br />`"preset:shoot"`<br />`"preset:hurt"`<br />`"preset:fall"`<br />`"preset:turn"`<br />`"preset:quadruped:walk"`<br />`"preset:hexapod:walk"`<br />`"preset:octopod:walk"`<br />`"preset:serpentine:march"`<br />`"preset:aquatic:march"`<br />plus additional `"preset:biped:*"` options shown in the UI |
| `out_format` | Output file format; the result arrives on the matching output. (default: glb) | COMBO | No | `"glb"`<br />`"fbx"` |
| `export_with_geometry` | Include the mesh in the export; off exports the animated skeleton only. (default: True) | BOOLEAN | No | True<br />False |
| `animate_in_place` | Play the animation in place, without root displacement. (default: False) | BOOLEAN | No | True<br />False |
| `auth_token_comfy_org` | Authentication token for Comfy.org API access (hidden parameter). | AUTH\_TOKEN\_COMFY\_ORG | No | - |
| `api_key_comfy_org` | API key for Comfy.org service access (hidden parameter). | API\_KEY\_COMFY\_ORG | No | - |
| `unique_id` | Unique identifier for tracking the operation (hidden parameter). | UNIQUE\_ID | No | - |

Note: Animations in the `preset:*` group work with both rig models. Animations in the `preset:biped:*` group are made for rigs from model v1.0-20240301; a v2.5 rig accepts only chop, climb, dive, fall, hurt, idle, jump, run, shoot, slash, turn and walk. If the referenced rig was created with the Mixamo spec and a model version starting with `v1.0`, the retargeting call fails with an error. The requested output format must be GLB or FBX; if the service returns any other file type, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The generated animated 3D model file (for backward compatibility only). | STRING |
| `retarget task_id` | The task ID for tracking the retargeting operation. | RETARGET\_TASK\_ID |
| `GLB` | The animated 3D model in GLB format. Populated when `out_format` is glb. | FILE3DGLB |
| `FBX` | The animated 3D model in FBX format. Populated when `out_format` is fbx. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoRetargetNode/en.md)

***

**Source fingerprint (SHA-256):** `4814858b940ece13f85010ff81fcdac0258fe8550aebd914be2613e8f40c0e5a`


# TripoRetopologyNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoRetopologyNode

Tripo: Retopology takes a high-poly 3D model that was generated by an earlier Tripo node and rebuilds it as a low-poly version with clean topology.

Tripo: Retopology takes a high-poly 3D model that was generated by an earlier Tripo node and rebuilds it as a low-poly version with clean topology. It submits the model to the Tripo retopology service, waits for the task to finish, then downloads the finished model and exposes its task ID for use by other Tripo nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_task_id` | Task ID of the source high-poly model. Accepts a model task ID from a Tripo generation node or a segment task ID from Tripo: Segment Model. | STRING | Yes | Tripo task ID |
| `face_limit` | Target face count: 500-20,000 triangles or 500-10,000 quads. -1 lets Tripo choose. (default: -1) | INT | Yes | -1 (automatic)<br />500 to 20,000 (triangles)<br />500 to 10,000 (quads) |
| `quad` | Quad mesh output. Tripo delivers quad meshes as FBX, so the result arrives on the FBX output and the GLB output stays empty. (default: False) | BOOLEAN | Yes | True<br />False (default) |
| `bake` | Bake the source textures onto the low-poly mesh. (default: True) | BOOLEAN | No | True (default)<br />False |
| `part_names` | Comma-separated part names from Tripo: Segment Model. Empty processes the whole model. (default: "") | STRING | No | Model part names or empty |

Note: When `face_limit` is set to -1, Tripo decides the face count automatically. When `quad` is enabled, the maximum face limit is 10,000 quads instead of 20,000 triangles, and the result is provided as FBX (the GLB output stays empty). When `part_names` is empty, the whole model is processed. If `face_limit` is anything other than -1 and falls outside the allowed range, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | Backward-compatible output that identifies the completed model file. Newer workflows should use the GLB or FBX outputs instead. | STRING |
| `model task_id` | Task ID of the finished retopology result. Can be passed to other Tripo nodes to reference this model. | STRING |
| `GLB` | The retopologized low-poly model in GLB format. Empty when `quad` is enabled. | GLB FILE |
| `FBX` | The retopologized low-poly model in FBX format. Only populated when `quad` is enabled. | FBX FILE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoRetopologyNode/en.md)

***

**Source fingerprint (SHA-256):** `b0e967eb4987a70242b6cfce93f09e0caffb7f4bdd3e4f1439e68f33f9138bb5`


# TripoRigCheckNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoRigCheckNode

This node sends the ID of a completed Tripo 3D model task to the Tripo API and checks whether that model can be rigged.

This node sends the ID of a completed Tripo 3D model task to the Tripo API and checks whether that model can be rigged. It waits for the check to finish and then returns a yes/no result plus the skeleton type Tripo recommends for the model.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_task_id` | The Tripo task ID of the model to analyze. It identifies a model that was previously generated, imported, or otherwise created through a Tripo task. | MODEL\_TASK\_ID | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `riggable` | Whether the model can be rigged. | BOOLEAN |
| `rig_type` | Recommended skeleton: biped, quadruped, hexapod, octopod, avian, serpentine or aquatic; 'others' when the model is not riggable. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoRigCheckNode/en.md)

***

**Source fingerprint (SHA-256):** `3aa0bc194e887804b92ca1f9f2b12997c73e111fb282c5de96e55f664c21545e`


# TripoRigNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoRigNode

This node takes an existing Tripo 3D model and creates a rigged version of it, meaning the model gets a skeleton so it can be animated.

This node takes an existing Tripo 3D model and creates a rigged version of it, meaning the model gets a skeleton so it can be animated. You provide the task ID of the model to rig, choose the rig version, skeleton type, bone-naming style, and output file format, and the node sends the job to Tripo, waits until it finishes, then returns the downloaded result.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `original_model_task_id` | The task ID of the original 3D model to be rigged. This is usually the ID produced by an earlier Tripo model-generation node. | MODEL\_TASK\_ID | Yes | - |
| `model_version` | Rig model version to use. v1.0: humanoid (biped) characters only, 90+ animation presets. v2.5: non-humanoid creatures (quadruped, hexapod, octopod, avian, serpentine, aquatic). Default: `v1.0-20240301`. | COMBO | No | "v1.0-20240301"<br />"v2.5-20260210" |
| `rig_type` | Skeleton type. "auto" runs Tripo's free rig check first and uses the recommended type. Default: "auto". | COMBO | No | "auto"<br />"biped"<br />"quadruped"<br />"hexapod"<br />"octopod"<br />"avian"<br />"serpentine"<br />"aquatic" |
| `spec` | Bone naming: Tripo native or Mixamo-compatible. Tripo cannot retarget its animation presets onto a v1.0 rig made with the mixamo spec; use tripo for Tripo: Retarget rigged model. Default: "tripo". | COMBO | No | "tripo"<br />"mixamo" |
| `out_format` | Output file format; the result arrives on the matching output. Default: "glb". | COMBO | No | "glb"<br />"fbx" |

**Note:** The v1.0 model version (`v1.0-20240301`) only supports biped skeletons. If a non-biped `rig_type` is used with this version, the node raises an error and instructs you to use `v2.5-20260210` instead.

**Note:** When `rig_type` is "auto", Tripo first checks whether the model can be rigged and picks the recommended skeleton type. If Tripo reports that the model cannot be rigged, the node fails with an error.

**Note:** The node expects Tripo to return a GLB or FBX file. If Tripo returns any other file type, the node raises an error.

**Note:** Only the output matching `out_format` is populated: `GLB` when `out_format` is "glb", and `FBX` when `out_format` is "fbx". The other 3D output is empty.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The generated rigged model file name (task ID plus format extension). Kept for backward compatibility only. | STRING |
| `rig task_id` | The task ID for tracking the rig generation process. | RIG\_TASK\_ID |
| `GLB` | The rigged model as a GLB 3D file. Populated when `out_format` is "glb". | FILE3DGLB |
| `FBX` | The rigged model as an FBX 3D file. Populated when `out_format` is "fbx". | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoRigNode/en.md)

***

**Source fingerprint (SHA-256):** `b9c1b6d27b6278bcee4fc22e11c11e65cd22ea92cab3fc6c74f84d3deb2024d6`


# TripoSegmentNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoSegmentNode

This node splits a 3D model into individual parts.

This node splits a 3D model into individual parts. It sends the model to the Tripo segmentation service, waits for the job to finish, and returns the segmented model in GLB format along with a comma-separated list of part names. These part names feed downstream steps such as Tripo: Complete Mesh Parts, Tripo: Retopology and Tripo: Convert model.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_task_id` | The task ID of the 3D model to be segmented into parts. | MODEL\_TASK\_ID | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | Output file name of the segmented GLB model, in the form `<task_id>.glb`. Kept for backward compatibility only. | STRING |
| `segment task_id` | The task ID of the segmentation job that produced the result. | SEGMENT\_TASK\_ID |
| `GLB` | The segmented 3D model, as a GLB file. | GLB |
| `part_names` | Comma-separated names of the parts. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoSegmentNode/en.md)

***

**Source fingerprint (SHA-256):** `3218f87bfdc347d58b639cbe57b01cf7625c95c753bf381e35b4a28376eeb0e8`


# VOIDSampler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VOIDSampler

VOIDSampler is a specialized DDIM sampler designed for VOID inpainting models.

VOIDSampler is a specialized DDIM sampler designed for VOID inpainting models. It reproduces the exact denoising process VOID was trained with, skipping the noise scaling that standard KSamplers apply. Use this node together with SamplerCustom or SamplerCustomAdvanced, paired with RandomNoise or VOIDWarpedNoiseSource.

## Inputs

This node has no configurable input parameters. It is a self-contained sampler that applies a fixed DDIM sampling algorithm.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| *No inputs* | This node does not accept any input parameters. | - | - | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `SAMPLER` | A sampler object implementing the VOID DDIM algorithm, ready to be connected to SamplerCustom or SamplerCustomAdvanced nodes. | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VOIDSampler/en.md)

***

**Source fingerprint (SHA-256):** `b8bb6d3d7220cca4a6dd252efe9c92953b1c5c67c14365e5e0583bc9bdb133be`


# VPScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VPScheduler

The VPScheduler node is designed to generate a sequence of noise levels (sigmas) based on the Variance Preserving (VP) scheduling method.

The VPScheduler node is designed to generate a sequence of noise levels (sigmas) based on the Variance Preserving (VP) scheduling method. This sequence is crucial for guiding the denoising process in diffusion models, allowing for controlled generation of images or other data types.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `steps` | Specifies the number of steps in the diffusion process, affecting the granularity of the generated noise levels. | INT |
| `beta_d` | Determines the overall noise level distribution, influencing the variance of the generated noise levels. | FLOAT |
| `beta_min` | Sets the minimum boundary for the noise level, ensuring the noise does not fall below a certain threshold. | FLOAT |
| `eps_s` | Adjusts the starting epsilon value, fine-tuning the initial noise level in the diffusion process. | FLOAT |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `sigmas` | A sequence of noise levels (sigmas) generated based on the VP scheduling method, used to guide the denoising process in diffusion models. | SIGMAS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VPScheduler/en.md)


# VideoLinearCFGGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VideoLinearCFGGuidance

The VideoLinearCFGGuidance node applies a linear conditioning guidance scale to a video model, adjusting the influence of conditioned and unconditioned components over a specified 

The VideoLinearCFGGuidance node applies a linear conditioning guidance scale to a video model, adjusting the influence of conditioned and unconditioned components over a specified range. This enables dynamic control over the generation process, allowing for fine-tuning of the model's output based on the desired level of conditioning.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The model parameter represents the video model to which the linear CFG guidance will be applied. It is crucial for defining the base model that will be modified with the guidance scale. | MODEL |
| `min_cfg` | The min\_cfg parameter specifies the minimum conditioning guidance scale to be applied, serving as the starting point for the linear scale adjustment. It plays a key role in determining the lower bound of the guidance scale, influencing the model's output. | `FLOAT` |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `model` | The output is a modified version of the input model, with the linear CFG guidance scale applied. This adjusted model is capable of generating outputs with varying degrees of conditioning, based on the specified guidance scale. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VideoLinearCFGGuidance/en.md)


# VideoTriangleCFGGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VideoTriangleCFGGuidance

The VideoTriangleCFGGuidance node applies a triangular classifier-free guidance (CFG) scaling pattern to a video model.

The VideoTriangleCFGGuidance node applies a triangular classifier-free guidance (CFG) scaling pattern to a video model. It varies the conditioning scale using a triangular wave that oscillates between `min_cfg` and the model's original conditioning scale. This creates a dynamic guidance pattern that can help improve video generation consistency and quality.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The video model to apply triangular CFG guidance to. | MODEL | Yes | - |
| `min_cfg` | The minimum CFG scale value for the triangular pattern. This parameter is shown in the advanced section of the node interface (default: 1.0). | FLOAT | Yes | 0.0 - 100.0 (step: 0.5, round: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The modified model with triangular CFG guidance applied. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VideoTriangleCFGGuidance/en.md)

***

**Source fingerprint (SHA-256):** `412d84d402f8c9a4852ee7b3f0ca0ab5650658fc26a37d10333a653e92e0294e`


# BeebleSwitchXImageEdit - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BeebleSwitchXImageEdit

Edit a single image with Beeble SwitchX.

Edit a single image with Beeble SwitchX. This node can switch anything in the scene (background, lighting, costume) while preserving the original subject's pixels. Provide a reference image and/or text prompt to describe the new look. Maximum resolution is approximately 2.77 megapixels.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The source image to edit. | IMAGE | Yes | - |
| `prompt` | A text description of the desired new look (e.g., "a knight in shining armor"). | STRING | Yes | - |
| `alpha_mode` | How to handle the alpha matte. "select" uses a keyframe to select the subject, "fill" replaces the entire image without a separate matte, "custom" uses a user-provided mask. | COMBO | Yes | `"select"`<br />`"fill"`<br />`"custom"` |
| `max_resolution` | The maximum resolution for the output image. Higher resolution costs more credits. | COMBO | Yes | `"1080p"`<br />`"720p"` |
| `seed` | A seed value for reproducibility. | INT | Yes | - |
| `reference_image` | An optional reference image to guide the style or appearance of the new scene elements. | IMAGE | No | - |

**Note on `alpha_mode`:** When `alpha_mode` is set to `"select"`, you must also provide an `alpha_keyframe` (a keyframe image used to select the subject). When set to `"custom"`, you must provide an `alpha_mask` (a user-created mask). When set to `"fill"`, no alpha input is needed.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The edited image with the scene elements switched. | IMAGE |
| `alpha` | The alpha matte used by Beeble. Empty for "fill" mode, which has no separate matte. | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BeebleSwitchXImageEdit/en.md)

***

**Source fingerprint (SHA-256):** `6fd10dff6ac4f1a15fd05de7a6ff6eda988e60dd4ef32bc8c792480fbbf0c92b`


# BriaAddObject - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaAddObject

This node inserts an object described in plain text into an image using Bria.

This node inserts an object described in plain text into an image using Bria. Bria re-renders the whole frame at about 1 megapixel, so the result is not pixel-aligned with the input.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image the described object is added to. The alpha channel is dropped before the image is uploaded. | IMAGE | Yes | - |
| `instruction` | What to add and where, such as 'Place a red vase with flowers on the table'. Must not be empty. Default: "" (empty string). | STRING | Yes | - |
| `seed` | Bria takes no seed here and re-imagines the edit on each call, so repeated runs can differ. The value is never sent: it only changes this node's cache key, so that an otherwise identical graph runs the edit again instead of returning the cached result. Default: 42. | INT | Yes | 0 to 2147483647 |
| `moderation` | Moderation settings. Choose "true" to reveal the moderation flags below. | DYNAMIC\_COMBO | Yes | "false"<br />"true" |

### Moderation Enabled Inputs

Available when `moderation` is set to "true".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `visual_input_moderation` | Enables content moderation on the input image. Default: False. | BOOLEAN | No | True / False |
| `visual_output_moderation` | Enables content moderation on the generated output image. Default: False. | BOOLEAN | No | True / False |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The edited image with the described object added. | IMAGE |
| `structured_prompt` | Structured description of the edited image, for a follow-up edit with Bria FIBO Image Edit. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaAddObject/en.md)

***

**Source fingerprint (SHA-256):** `41c9a3e511763372d8dc8be9da4f70158e53d5156a88eb3c66f81149efdbd566`


# BriaEraseByText - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaEraseByText

This node removes an object described in plain text from an image using Bria.

This node removes an object described in plain text from an image using Bria. Bria re-renders the whole frame at about 1 megapixel, so the result is not pixel-aligned with the input.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image from which the named object should be removed. | IMAGE | Yes | - |
| `object_name` | Name of the object to remove, such as 'the lamp'. Several objects can be named at once, such as 'the phone and the pencils'. Naming something that is not in the picture still returns a re-rendered image, and the request is still billed. Must be at least 1 character long (default: empty). | STRING | Yes | - |
| `moderation` | Moderation settings. Selects whether the optional moderation controls are shown. | DYNAMIC\_COMBO | Yes | `"false"`<br />`"true"` |

### Moderation Inputs

These parameters appear when `moderation` is set to `"true"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `visual_input_moderation` | Enables content moderation on the input image (default: false). | BOOLEAN | No | true<br />false |
| `visual_output_moderation` | Enables content moderation on the generated output image (default: false). | BOOLEAN | No | true<br />false |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The re-rendered image with the named object removed. | IMAGE |
| `structured_prompt` | Structured description of the edited image, for a follow-up edit with Bria FIBO Image Edit. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaEraseByText/en.md)

***

**Source fingerprint (SHA-256):** `51ac362bea731251c99905172c41cdebb5165e7564c508f13aa43cf9072964ef`


# BriaEraseForeground - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaEraseForeground

This node removes the foreground of an image with Bria and generates a new background in its place.

This node removes the foreground of an image with Bria and generates a new background in its place. Everything Bria identifies as foreground is removed, not only people, and the untouched pixels are preserved. The result is re-rendered at a standard size close to 1 megapixel.

This is a paid API node that runs on Bria's service, so your Comfy API credentials are used for each run.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image whose foreground is removed and replaced with a generated background. Only the color channels are sent; any alpha channel is discarded before upload. | IMAGE | Yes | - |
| `moderation` | Moderation settings. Select `"false"` to send the image without moderation flags, or `"true"` to reveal the content-moderation toggles below. Default: `"false"`. | DYNAMIC\_COMBO | Yes | `"false"`<br />`"true"` |

### `"false"` Inputs

No additional inputs. The request is sent without content-moderation flags.

### `"true"` Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `visual_input_moderation` | Enables content moderation on the input image. Default: false. | BOOLEAN | Yes | true<br />false |
| `visual_output_moderation` | Enables content moderation on the generated output image. Default: false. | BOOLEAN | Yes | true<br />false |

### Notes

* The output is re-rendered at a standard size close to 1 megapixel, so the returned image may differ in dimensions from the input.
* This node is a paid API node; each run costs approximately 0.0572 USD.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The input image with its foreground erased and a newly generated background in its place. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaEraseForeground/en.md)

***

**Source fingerprint (SHA-256):** `4d8c3c5eed97c648b1191ec41931c97caa17e98a8edd1c054ed63e80cc671b05`


# BriaEraser - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaEraser

Bria Eraser removes objects or areas from an image using the Bria API.

Bria Eraser removes objects or areas from an image using the Bria API. You provide an image and a mask that outlines the regions to remove; the node uploads both to Bria, runs the erase job, waits for it to complete, and returns the edited image with the masked areas erased.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image containing the objects or areas to remove. | IMAGE | Yes | - |
| `mask` | White areas are erased, black areas are preserved. The mask is binarized before sending with a 50% cutoff: only areas painted above 50% opacity count as white. Must have the same aspect ratio as the image. | MASK | Yes | - |
| `mask_type` | The mask source type. "manual" is for hand-drawn or brush masks; "automatic" is for masks produced by segmentation models such as SAM. | COMBO | Yes | "manual"<br />"automatic" |
| `moderation` | Moderation settings. Set to "true" to enable visual content moderation on the input and/or output images. | DYNAMIC\_COMBO | Yes | "false"<br />"true" |

When `moderation` is set to "true", two additional boolean settings become available:

* `visual_input_moderation` — applies visual content moderation to the input image (default: false)
* `visual_output_moderation` — applies visual content moderation to the output image (default: false)

Note: The mask must match the aspect ratio of the image, otherwise the request fails. The mask is converted to a binary (black and white) mask before being sent to the API: areas painted at less than half opacity are ignored, and partially painted areas are treated as white and will be erased. The mask must contain at least some white area; an empty mask causes the request to fail because there is nothing to erase.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The edited image with the masked objects or areas removed. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaEraser/en.md)

***

**Source fingerprint (SHA-256):** `5528b7a3cb4d0a7b1b28acbc642a8bd21e2eacf5aa225403d6344c29f0cdba80`


# BriaExpandImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaExpandImage

Bria Expand Image expands an image beyond its original borders by generating new content with Bria.

Bria Expand Image expands an image beyond its original borders by generating new content with Bria. It lets you choose a target aspect ratio, a custom ratio, or define a canvas with manual placement of the original image. The expansion can be guided with a text prompt, and Bria will generate one automatically if the prompt is left empty.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be expanded. | IMAGE | Yes | — |
| `expand_mode` | Target shape of the expanded image: a preset aspect ratio, a custom ratio, or manual placement of the original image on a canvas. Manual is the only mode that can reach a canvas taller than 1:2. Selecting `custom_ratio` reveals `ratio_width` and `ratio_height`. Selecting `manual` reveals the canvas and image placement parameters. | DYNAMIC\_COMBO | Yes | `"1:1"`<br />`"2:3"`<br />`"3:2"`<br />`"3:4"`<br />`"4:3"`<br />`"4:5"`<br />`"5:4"`<br />`"9:16"`<br />`"16:9"`<br />`"custom_ratio"`<br />`"manual"` |
| `prompt` | Optional description of the expanded scene; when empty, Bria generates one from the image. Default: empty string. | STRING | Yes | Any string |
| `negative_prompt` | An optional negative prompt for the expansion. Default: empty string. | STRING | Yes | Any string |
| `seed` | Seed for the random generation process. Default: 42. | INT | Yes | 1–2147483647 |
| `moderation` | Moderation settings. When set to `true`, additional moderation options are shown. | DYNAMIC\_COMBO | Yes | `"false"`<br />`"true"` |

### Custom Ratio Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `ratio_width` | Width side of the target ratio: 21 and 9 give 21:9. Default: 21. | INT | Yes | 1–100 |
| `ratio_height` | Height side of the target ratio: 21 and 9 give 21:9. Bria only accepts width/height between 0.5 and 3.0, so anything taller than 1:2 needs the manual mode. Default: 9. | INT | Yes | 1–100 |

### Manual Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `canvas_width` | Width of the output canvas in pixels. Default: 1000. | INT | Yes | 64–5000 |
| `canvas_height` | Height of the output canvas in pixels. Default: 1000. | INT | Yes | 64–5000 |
| `image_width` | Width of the original image inside the canvas. Default: 500. | INT | Yes | 1–5000 |
| `image_height` | Height of the original image inside the canvas. Default: 500. | INT | Yes | 1–5000 |
| `image_x` | X position of the image's top-left corner inside the canvas; may fall outside the canvas, cropping the image. Default: 250. | INT | Yes | -5000–5000 |
| `image_y` | Y position of the image's top-left corner inside the canvas; may fall outside the canvas, cropping the image. Default: 250. | INT | Yes | -5000–5000 |

### Moderation Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt_content_moderation` | If enabled, moderates the prompt content. Default: false. Only available when `moderation` is `true`. | BOOLEAN | Yes | true/false |
| `visual_input_moderation` | If enabled, moderates the visual input. Default: false. Only available when `moderation` is `true`. | BOOLEAN | Yes | true/false |
| `visual_output_moderation` | If enabled, moderates the visual output. Default: false. Only available when `moderation` is `true`. | BOOLEAN | Yes | true/false |

Preset aspect ratio options (`1:1`, `2:3`, `3:2`, `3:4`, `4:3`, `4:5`, `5:4`, `9:16`, `16:9`) have no additional inputs.

When `expand_mode` is `custom_ratio`, `ratio_width` and `ratio_height` define a target aspect ratio. Bria only accepts width-to-height ratios between 0.5 and 3.0. If the ratio is outside this range, an error is raised and the `manual` mode should be used instead.

When `expand_mode` is `manual`, the original image is placed on a canvas at the specified size and position. The image may extend outside the canvas, in which case the outside portion is cropped.

When `moderation` is `true`, the three moderation booleans are sent to Bria. When `moderation` is `false`, they are ignored.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The expanded image generated by Bria. | IMAGE |
| `prompt` | The prompt used for the expansion; auto-generated by Bria when the prompt input is empty. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaExpandImage/en.md)

***

**Source fingerprint (SHA-256):** `d2c9431837f200ccbcb39037f7b26013494c4dea3d40d899db4e717ddbbea71c`


# BriaGenFill - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaGenFill

This node generates objects or scenery inside a masked region of an image using Bria.

This node generates objects or scenery inside a masked region of an image using Bria. It uploads the image and mask, sends the prompt to the Bria generative fill service, waits for the operation to complete, and returns the edited image. This is a paid API operation (US\$0.0429 per request).

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to edit. | IMAGE | Yes | - |
| `mask` | White areas are filled with generated content, black areas are preserved. The mask is binarized before sending with a 50% cutoff: only areas painted above 50% opacity count as white. Must have the same aspect ratio as the image. | MASK | Yes | - |
| `prompt` | Description of what to generate inside the masked region. Must contain at least 1 character. (default: "") | STRING | Yes | - |
| `negative_prompt` | A prompt describing content to avoid in the generated result. If left empty, it is not sent to the API. (default: "") | STRING | Yes | - |
| `refine_prompt` | Automatically adjust the prompt for better results; disable to use the prompt exactly as written. (default: true) | BOOLEAN | Yes | true<br />false |
| `seed` | Seed for the generation process. (default: 42) | INT | Yes | 1 to 2147483647 |
| `moderation` | Moderation settings. When set to "true", the moderation options below are applied. (default: "false") | DYNAMIC\_COMBO | Yes | "false"<br />"true" |

### Moderation Inputs (when `moderation` = "true")

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt_content_moderation` | Applies content moderation to the prompt. (default: false) | BOOLEAN | No | true<br />false |
| `visual_input_moderation` | Applies content moderation to the input image. (default: false) | BOOLEAN | No | true<br />false |
| `visual_output_moderation` | Applies content moderation to the output image. (default: false) | BOOLEAN | No | true<br />false |

**Note:** The `prompt` must not be empty. The `mask` must have the same aspect ratio as the `image`. The mask is binarized at 50% opacity, so areas painted at less than half opacity are ignored; if the mask contains no white areas after binarization, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resulting image with the masked region filled by the generated content. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaGenFill/en.md)

***

**Source fingerprint (SHA-256):** `b23e29d4457f859181d68eaeb4b0238de28f4b18932d68438fa2954739cdc66a`


# BriaImageEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaImageEditNode

The Bria FIBO Image Edit node edits an existing image using a text instruction.

The Bria FIBO Image Edit node edits an existing image using a text instruction. It sends the image and your prompt to the Bria API, where the FIBO model creates an edited version. An optional mask can limit the changes to a specific area.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model version to use for image editing. | COMBO | Yes | `"FIBO"` |
| `image` | The input image you want to edit. | IMAGE | Yes | - |
| `prompt` | Instruction to edit image (default: empty). | STRING | Yes | - |
| `negative_prompt` | Text describing what you do not want to appear in the edited image (default: empty). | STRING | Yes | - |
| `structured_prompt` | A string containing the structured edit prompt in JSON format. Use this instead of usual prompt for precise, programmatic control (default: empty). | STRING | Yes | - |
| `seed` | A number used to initialize the random generation, ensuring reproducible results (default: 1). | INT | Yes | 1 to 2147483647 |
| `guidance_scale` | Higher value makes the image follow the prompt more closely (default: 3). | FLOAT | Yes | 3.0 to 5.0 |
| `steps` | The number of denoising steps performed by the model (default: 50). | INT | Yes | 20 to 50 |
| `moderation` | Moderation settings. Selecting `"true"` reveals additional moderation options. | DYNAMIC\_COMBO | Yes | `"false"`<br />`"true"` |
| `mask` | If omitted, the edit applies to the entire image. | MASK | No | - |

### Moderation Inputs

When `moderation` is set to `"true"`, these additional inputs become available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt_content_moderation` | Whether to moderate the prompt text for inappropriate content (default: false). | BOOLEAN | No | `true`<br />`false` |
| `visual_input_moderation` | Whether to moderate the input image for inappropriate content (default: false). | BOOLEAN | No | `true`<br />`false` |
| `visual_output_moderation` | Whether to moderate the edited output image for inappropriate content (default: true). | BOOLEAN | No | `true`<br />`false` |

**Important Constraints:**

* At least one of `prompt` or `structured_prompt` must be non-empty. If both are empty, the node raises an error.
* When `moderation` is set to `"true"`, the three moderation inputs above are shown.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The edited image returned by the Bria API. | IMAGE |
| `structured_prompt` | The structured prompt used or generated during the editing process. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaImageEditNode/en.md)

***

**Source fingerprint (SHA-256):** `e66aaa563a82407408f25b289011a491c8b158822fc2db8912daf73731750081`


# BriaIncreaseResolution - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaIncreaseResolution

Bria Increase Resolution upscales an input image by 2x or 4x using Bria's image upscaling service while preserving the original content.

Bria Increase Resolution upscales an input image by 2x or 4x using Bria's image upscaling service while preserving the original content. The node uploads the image, submits it for processing on the Bria service, waits for the result, and returns the upscaled image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to upscale. | IMAGE | Yes | Single image |
| `desired_increase` | Resolution multiplier. The output must fit within 8192 pixels on each side. | COMBO | Yes | "2"<br />"4" |
| `auto_downscale` | Automatically lower the multiplier, and downscale the input image if that is still not enough, when the output would exceed the limit. (default: False) | BOOLEAN | Yes | True<br />False |
| `moderation` | Moderation settings. When set to "true", enables the `visual_input_moderation` and `visual_output_moderation` sub-options, both defaulting to False. | DYNAMIC\_COMBO | Yes | "false"<br />"true" |

Notes:

* When `moderation` is set to "true", the sub-options `visual_input_moderation` and `visual_output_moderation` become available, both defaulting to False. They control moderation of the input image and the output image content.
* The node enforces a maximum output side of 8192 pixels. If the selected multiplier would exceed this limit and `auto_downscale` is disabled, an error is raised. Enabling `auto_downscale` allows the node to automatically use a lower multiplier or downscale the input image instead.
* Bria first enlarges the short side of the input image to at least 224 pixels before upscaling. Images that are too elongated may trigger an error asking to crop them to a squarer shape.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The upscaled image returned by the Bria service. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaIncreaseResolution/en.md)

***

**Source fingerprint (SHA-256):** `6db9bf6c0d8a79903893b352658d3a8e02f67d375f3d604e9ab2a69624142885`


# BriaRelight - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaRelight

This node changes the lighting atmosphere and direction of an image using Bria.

This node changes the lighting atmosphere and direction of an image using Bria. The image is re-rendered by Bria, so the result is not pixel-aligned with the input; the whole frame is regenerated at about 1 megapixel.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image whose lighting is changed. Any alpha channel is dropped before the image is uploaded. | IMAGE | Yes | - |
| `light_type` | Lighting atmosphere to apply. | COMBO | Yes | `"midday"`<br />`"blue hour light"`<br />`"low-angle sunlight"`<br />`"sunrise light"`<br />`"spotlight on subject"`<br />`"overcast light"`<br />`"soft overcast daylight lighting"`<br />`"cloud-filtered lighting"`<br />`"fog-diffused lighting"`<br />`"moonlight lighting"`<br />`"starlight nighttime"`<br />`"soft bokeh lighting"`<br />`"harsh studio lighting"` |
| `light_direction` | Where the light comes from. Hard-light atmospheres such as midday, spotlight on subject and harsh studio lighting react to it the most. | COMBO | Yes | `"front"`<br />`"side"`<br />`"bottom"`<br />`"top-down"` |
| `moderation` | Moderation settings. Select `"true"` to reveal the moderation options, or `"false"` to run without them. | DYNAMIC\_COMBO | Yes | `"false"`<br />`"true"` |

### Moderation Inputs

These options appear when `moderation` is set to `"true"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `visual_input_moderation` | Enables content moderation on the input image. Default: false. | BOOLEAN | No | `true`<br />`false` |
| `visual_output_moderation` | Enables content moderation on the generated output image. Default: false. | BOOLEAN | No | `true`<br />`false` |

Note: Bria re-renders the whole frame at about 1 megapixel, so the result is not pixel-aligned with the input.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The relit image returned by Bria. | IMAGE |
| `structured_prompt` | Structured description of the edited image, for a follow-up edit with Bria FIBO Image Edit. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaRelight/en.md)

***

**Source fingerprint (SHA-256):** `21fbe2186c99a7e8d99d5659ac25c3ab1a757492916dba4135487d4b293cb4f6`


# BriaRemoveImageBackground - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaRemoveImageBackground

This node removes the background from an image using the Bria RMBG 2.0 service.

This node removes the background from an image using the Bria RMBG 2.0 service. It sends the image to an external API for processing and returns the result with the background removed.

## Inputs

The `moderation` selector reveals additional moderation options when set to `"true"`.

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image from which the background will be removed. | IMAGE | Yes | - |
| `moderation` | Moderation settings. When set to `"true"`, additional moderation options become available. | DYNAMIC\_COMBO | Yes | `"false"`<br />`"true"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. Default: `0`. | INT | Yes | 0 to 2147483647 |

### Moderation "true" Inputs

These parameters appear only when `moderation` is set to `"true"`. The `"false"` option adds no additional inputs.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `visual_input_moderation` | Enables visual content moderation on the input image. Default: `False`. | BOOLEAN | No | - |
| `visual_output_moderation` | Enables visual content moderation on the output image. Default: `True`. | BOOLEAN | No | - |

**Note:** The `visual_input_moderation` and `visual_output_moderation` parameters are dependent on the `moderation` parameter. They are only active when `moderation` is set to `"true"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The processed image with its background removed. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaRemoveImageBackground/en.md)

***

**Source fingerprint (SHA-256):** `f62dcd5c9406ec09f5aab44585dd7f25ae0f7d9a934faa10a58e46ef116df110`


# BriaReplaceImageBackground - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaReplaceImageBackground

This node replaces the background of an image with a new one generated by Bria.

This node replaces the background of an image with a new one generated by Bria. The new background can be described with a text prompt or guided by reference images. The subject's pixels are preserved while the background is generated around them.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image whose background will be replaced. | IMAGE | Yes | |
| `background` | Describe the new background with a prompt, or guide it with reference images. | DYNAMIC\_COMBO | Yes | `"prompt"`<br />`"reference images"` |
| `original_quality` | Return the input's exact pixel size instead of scaling the result to about 1 megapixel. A large input then returns a large image. (default: false) | BOOLEAN | No | `true`<br />`false` |
| `seed` | The same seed usually returns the same background; the automatic prompt refinement can still vary it. (default: 42) | INT | No | 0 to 2147483647 |
| `moderation` | Moderation settings. (default: "false") | DYNAMIC\_COMBO | No | `"false"`<br />`"true"` |

### Prompt Inputs

Shown when `background` is set to `"prompt"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Description of the new background. A hex color code such as #FF5733 produces a solid color background. Must be at least 1 character long. | STRING | Yes | |
| `mode` | `high_control` follows the prompt most closely, `base` is a balanced default and `fast` trades detail for speed. | COMBO | Yes | `"high_control"`<br />`"base"`<br />`"fast"` |
| `refine_prompt` | Rewrite the prompt for better results, which also translates non-English prompts. Turn it off to send the prompt exactly as written. (default: true) | BOOLEAN | No | `true`<br />`false` |

### Reference Images Inputs

Shown when `background` is set to `"reference images"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `ref_images` | Growable slot: connect 1 to 10 images guiding the new background; they do not need to share a size. Every reference changes the result, so a few consistent ones beat many conflicting ones. A batched input counts once per image. | IMAGE | Yes | 1 to 10 images |
| `enhance_ref_images` | Extra processing of the reference images for better results. (default: true) | BOOLEAN | No | `true`<br />`false` |

### Moderation Inputs

Shown when `moderation` is set to `"true"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt_content_moderation` | Enable moderation for prompt content. (default: false) | BOOLEAN | No | `true`<br />`false` |
| `visual_input_moderation` | Enable moderation for visual input. (default: false) | BOOLEAN | No | `true`<br />`false` |
| `visual_output_moderation` | Enable moderation for visual output. (default: false) | BOOLEAN | No | `true`<br />`false` |

**Note:** The `ref_images` input accepts a maximum of 10 images; providing more than 10 returns an error. The `prompt` field must contain at least 1 character. When `original_quality` is false, the input image is downscaled to about 1 megapixel before processing.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The image with the new background. | IMAGE |
| `refined_prompt` | The prompt Bria generated from, empty on the reference-image path. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaReplaceImageBackground/en.md)

***

**Source fingerprint (SHA-256):** `62c29d61983c9656d2ea2954518404c62d76961c3deba0e10d63e787d0b0b106`


# BriaReplaceObject - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaReplaceObject

Replaces an object in an image with a different one described in plain text, using Bria's text-guided image editing.

Replaces an object in an image with a different one described in plain text, using Bria's text-guided image editing. Bria re-renders the whole frame at about 1 megapixel, so the result is not pixel-aligned with the input.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image containing the object to be replaced. The alpha channel is dropped before the image is uploaded. | IMAGE | Yes | - |
| `instruction` | What to replace with what, such as "Replace the red apple with a green pear". Must be at least 1 character long. | STRING | Yes | Multiline text; default: "" (empty) |
| `seed` | Bria takes no seed here and re-imagines the edit on each call, so repeated runs can differ. The value is never sent: it only changes this node's cache key, so that an otherwise identical graph runs the edit again instead of returning the cached result. | INT | Yes | 0 to 2147483647, step 1; default: 42; control after generate enabled |

### Moderation Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `moderation` | Moderation settings. Selecting "true" reveals the moderation sub-options below, which are otherwise not shown. | DYNAMIC\_COMBO | Yes | `"false"`<br />`"true"` |
| `visual_input_moderation` | Enables moderation of the input image. Only available when `moderation` is set to "true". | BOOLEAN | No | `true` / `false`; default: false |
| `visual_output_moderation` | Enables moderation of the generated output image. Only available when `moderation` is set to "true". | BOOLEAN | No | `true` / `false`; default: false |

Note: `instruction` is validated before the request is sent and must contain at least 1 character. The `seed` value is not transmitted to Bria; it only affects whether the node re-runs the edit or returns a cached result.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The edited image with the described object replacement applied. | IMAGE |
| `structured_prompt` | Structured description of the edited image, for a follow-up edit with Bria FIBO Image Edit. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaReplaceObject/en.md)

***

**Source fingerprint (SHA-256):** `75a45d5c0d6cde96a1e961db627edc1a59c07cc37b974402745cefc62864cc26`


# BriaReseason - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaReseason

This node moves an image into a different season using Bria.

This node moves an image into a different season using Bria. The whole scene is re-rendered, so scenery can change beyond the season itself. Bria re-renders the whole frame at about 1 megapixel, so the result is not pixel-aligned with the input.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image to move to another season. Any alpha channel is removed before the image is sent. | IMAGE | Yes | - |
| `season` | Season to apply. | COMBO | Yes | `"spring"`<br />`"summer"`<br />`"autumn"`<br />`"winter"` |
| `moderation` | Moderation settings. Selects whether content moderation options are configured for this request. | DYNAMIC\_COMBO | Yes | `"false"`<br />`"true"` |

### Moderation Inputs

These options appear when `moderation` is set to `"true"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `visual_input_moderation` | Enables content moderation on the input image (default: false). | BOOLEAN | No | true<br />false |
| `visual_output_moderation` | Enables content moderation on the generated output image (default: false). | BOOLEAN | No | true<br />false |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The re-rendered image in the selected season. | IMAGE |
| `structured_prompt` | Structured description of the edited image, for a follow-up edit with Bria FIBO Image Edit. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaReseason/en.md)

***

**Source fingerprint (SHA-256):** `3bb9ee1c00c91759cc6f972e2ba8708ae73a186f4b66bf6669937e561efad0a4`


# BriaRestorePhoto - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaRestorePhoto

This node repairs old or damaged photographs through the Bria API.

This node repairs old or damaged photographs through the Bria API. It removes grain, scratches, and blur, neutralizes age-related color casts, may crop away card mounts and studio borders, and re-draws faces. The result is re-rendered at about 1 megapixel, so it is not pixel-aligned with the input.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The photograph to repair. The alpha channel is dropped before upload. | IMAGE | Yes | - |
| `moderation` | Moderation settings for the request. Selecting `"true"` reveals two additional boolean toggles; selecting `"false"` sends no moderation flags. Default: `"false"`. | DYNAMIC\_COMBO | Yes | `"false"`<br />`"true"` |

### Moderation Inputs

These inputs appear only when `moderation` is set to `"true"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `visual_input_moderation` | Enables visual content moderation on the input image. Default: false. | BOOLEAN | No | true<br />false |
| `visual_output_moderation` | Enables visual content moderation on the output image. Default: false. | BOOLEAN | No | true<br />false |

**Note:** The node re-renders the whole frame at about 1 megapixel, so the result is not pixel-aligned with the input. Use the Bria Increase Resolution node to enlarge the image instead of this node.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The repaired photograph returned by Bria. | IMAGE |
| `structured_prompt` | Structured description of the edited image, for a follow-up edit with Bria FIBO Image Edit. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaRestorePhoto/en.md)

***

**Source fingerprint (SHA-256):** `387ec3e049464f185e27f79d160ade2a4170ab238853064c008892d84523fa68`


# ByteDanceCreateImageAsset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceCreateImageAsset

This node creates a personal image asset for ByteDance's Seedance 2.0 service.

This node creates a personal image asset for ByteDance's Seedance 2.0 service. It uploads an input image and registers it within a specified asset group. If no group ID is provided, it will initiate a real-person authentication process in your browser to create a new group before adding the asset.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image to be registered as a personal asset. | IMAGE | Yes | |
| `group_id` | Reuse an existing Seedance asset group ID to skip repeated human verification for the same person. Leave empty to run real-person authentication in the browser and create a new group (default: empty). | STRING | No | |

**Image Constraints:**

* The image width must be between 300 and 6000 pixels.
* The image height must be between 300 and 6000 pixels.
* The image aspect ratio must be between 0.4:1 and 2.5:1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `asset_id` | The unique identifier for the newly created image asset. | STRING |
| `group_id` | The identifier for the asset group. This will be the provided `group_id` or a newly created one. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceCreateImageAsset/en.md)

***

**Source fingerprint (SHA-256):** `44d2bc880cbd8780ce1deb27eee5e41dc43973653751b0022a2631df725b155d`


# ByteDanceSeedAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceSeedAudio

Generate speech, music, sound effects and multi-speaker dialogue from a single prompt with ByteDance Seed Audio 1.0.

Generate speech, music, sound effects and multi-speaker dialogue from a single prompt with ByteDance Seed Audio 1.0. Describe the voice(s), emotion, ambience, background music and sound effects in the prompt, and include the lines to speak. Optionally pick a built-in preset voice, clone voices from up to 3 reference clips (tagged @Audio1-3 in the prompt), or derive a voice from a character image. Up to 2 minutes of audio per run. The multilingual model supports 20 languages and timestamp-based timing control.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text_prompt` | Describe the voice(s), emotion, pacing, ambience, background music and sound effects, and include the lines to speak (name characters inline for dialogue). In "audio reference" mode, refer to connected clips by order as @Audio1, @Audio2, @Audio3. With the multilingual model, a quoted line can start with a timestamp range that controls when and how long it is spoken, e.g. `[5.5s:8.0s] Wait for me!`. Write the prompt in the same language as the lines to speak. Minimum 1 character, maximum 3000 characters. | STRING | Yes | 1 to 3000 characters |
| `reference_mode` | How to condition the voice: "text only" (describe everything in the prompt), "audio reference" (clone up to 3 voices, tagged @Audio1-3), "image reference" (derive a voice from one character image), or "preset voice" (pick a built-in named voice that reads the prompt). | COMBO | Yes | `"text only"`<br />`"audio reference"`<br />`"image reference"`<br />`"preset voice"` |
| `reference_audio_1` | Reference clip for voice cloning, tagged @Audio1 in the prompt. Up to 30s. Available only when `reference_mode` is "audio reference". | AUDIO | No | Up to 30 seconds |
| `reference_audio_2` | Reference clip tagged @Audio2 in the prompt. Up to 30s. Available only when `reference_mode` is "audio reference". | AUDIO | No | Up to 30 seconds |
| `reference_audio_3` | Reference clip tagged @Audio3 in the prompt. Up to 30s. Available only when `reference_mode` is "audio reference". | AUDIO | No | Up to 30 seconds |
| `reference_image` | A single character image; the model derives a voice from it. Cannot be combined with reference audio. Available only when `reference_mode` is "image reference". | IMAGE | No | - |
| `preset_voice` | A built-in TTS 2.0 voice that reads the prompt. No reference clip needed, and @AudioN tags are not used in this mode. Required when `reference_mode` is "preset voice". | COMBO | No | Multiple built-in preset voice options (first option selected by default) |
| `sample_rate` | Output sample rate in Hz. (default: "24000") | COMBO | Yes | `"8000"`<br />`"16000"`<br />`"24000"`<br />`"32000"`<br />`"44100"`<br />`"48000"` |
| `speech_rate` | Speaking speed. 0 = normal, 100 = 2.0x, -50 = 0.5x. (default: 0) | INT | Yes | -50 to 100 |
| `loudness_rate` | Loudness. 0 = normal, 100 = 2.0x, -50 = 0.5x. (default: 0) | INT | Yes | -50 to 100 |
| `pitch_rate` | Pitch shift in semitones (-12 to 12). (default: 0) | INT | Yes | -12 to 12 |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 42) | INT | Yes | 0 to 2147483647 |
| `model` | Model version. `seed-audio-1.0-multilingual` supports 20 languages and per-sentence timing control via `[5.5s:8.0s]` timestamps. `seed-audio-1.0` supports English and Chinese only, without timing control. (default: "seed-audio-1.0-multilingual") | COMBO | No | `"seed-audio-1.0-multilingual"`<br />`"seed-audio-1.0"` |

### Parameter Constraints

* **Reference mode dependencies**: The `reference_mode` parameter determines which other inputs are required:
  * **"text only"**: No additional inputs required. The prompt must not contain @AudioN tags.
  * **"audio reference"**: Requires at least one of `reference_audio_1`, `reference_audio_2`, or `reference_audio_3` to be connected. Reference clips must be connected in order without gaps. Each clip is limited to 30 seconds maximum duration. If @AudioN tags are used in the prompt, the highest tag number must not exceed the number of connected reference clips.
  * **"image reference"**: Requires `reference_image` to be connected. @AudioN tags are not used; the prompt should contain only the text to synthesize.
  * **"preset voice"**: Requires a preset voice to be selected. The whole prompt is read in the selected voice; @AudioN tags are not used as references, and tags such as @Audio2 or higher are rejected.

* **Audio reference ordering**: In "audio reference" mode, reference audio inputs must be connected sequentially starting from `reference_audio_1` without gaps. For example, you can connect `reference_audio_1` and `reference_audio_2`, but not `reference_audio_1` and `reference_audio_3` without `reference_audio_2`.

* **Maximum audio tags**: In "audio reference" mode, up to 3 reference clips can be connected (@Audio1, @Audio2, @Audio3), and the highest @AudioN tag in the prompt cannot exceed the number of connected reference audio inputs.

* **Model differences**: The `seed-audio-1.0-multilingual` model supports 20 languages (English, Chinese, Japanese, Korean, Mexican & Castilian Spanish, Indonesian, German, Brazilian Portuguese, French, Thai, Vietnamese, Malay, Filipino, Italian, Russian, Dutch, Polish, Turkish, Swedish) plus per-sentence timing control using timestamps in the format `[5.5s:8.0s]`. The `seed-audio-1.0` model supports English and Chinese only, without timing control.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `AUDIO` | The generated audio output from ByteDance Seed Audio 1.0, containing speech, music, sound effects, or multi-speaker dialogue as described in the prompt. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceSeedAudio/en.md)

***

**Source fingerprint (SHA-256):** `e86e4edde424b4427d864350a9d3b082e271fbd2b1e335175637a9cc3ad51163`


# ByteDanceSeedreamLayerSeparationNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceSeedreamLayerSeparationNode

ByteDance Seedream 5.0 Pro Layer Separation decomposes an image into a background plate plus up to 16 repositionable transparent layers, each with stacking order, bounding box, nam

ByteDance Seedream 5.0 Pro Layer Separation decomposes an image into a background plate plus up to 16 repositionable transparent layers, each with stacking order, bounding box, name, and description. It returns the background, per-layer images with masks, placement boxes, and a ready-to-edit layer stack.

**Note:** This node is marked as deprecated in the source code.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image to separate. Exactly one image, at least 512x512 pixels, aspect ratio between 1:16 and 16:1. Inputs larger than about 4MP are downscaled before upload. | IMAGE | Yes | Single image |
| `prompt` | How to separate the image. Leave empty to auto-detect and separate all major elements. Describe elements in natural language to control the separation, or target exact regions with `<bbox>left top right bottom</bbox>` tags (0-1000 per-mille coordinates). Default: empty string. | STRING | Yes | Multiline text |
| `size` | Output resolution level. "auto" follows the input image size (clamped to the 1K-2K range). Default: "auto". | COMBO | Yes | "auto"<br />"1K"<br />"1.5K"<br />"2K" |
| `seed` | Seed to use for generation. Default: 0. | INT | Yes | 0 to 2147483647 |
| `prompt_optimization` | Prompt-optimization mode: "standard" gives higher quality, "fast" shorter generation time. Default: "standard". | COMBO | No | "standard"<br />"fast" |
| `watermark` | Whether to add an "AI generated" watermark to the images. Default: false. | BOOLEAN | No | false<br />true |
| `crop_layers` | Geometry of the layers/masks batch outputs (layer\_stack is unaffected and always tight). Full canvas: each layer on a base-sized canvas at its bounding-box position - recompose directly with ImageCompositeMasked. Minimal size: each layer cropped to its bounding box (padded to the largest layer for batching) - much smaller tensors; rebuild placement with Layers From Bounding Boxes using the bboxes output. Default: false (full canvas). | BOOLEAN | No | false (full canvas)<br />true (minimal size) |

Note: The input `image` must be a single image; batches are not supported. The image must be at least 512x512 pixels with an aspect ratio between 1:16 and 16:1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `base_image` | The base image (background plate) the layers stack onto. | IMAGE |
| `base_mask` | Transparency of the base image (1 = transparent, LoadImage convention); currently always fully opaque. | MASK |
| `layers` | Transparent layers ordered bottom to top. Full canvas mode: placed on a black base-sized canvas at their bounding-box position. Minimal size mode: cropped to their bounding box, anchored top-left, padded to the largest layer. | IMAGE |
| `masks` | Per-layer transparency, index-aligned with the layers batch (1 = transparent, LoadImage convention). For ImageCompositeMasked-style compositing, add InvertMask first. | MASK |
| `bboxes` | One placement box per layer, index-aligned with the layers batch (feed both, plus masks, into Layers From Bounding Boxes to rebuild per-layer placement): `{x, y, width, height, metadata: {name, desc, z_index, native_size, content_rect, flags}}`. `content_rect = [left, top, width, height]` is the layer's content region within its own frame; it lands on the canvas at the box position plus that offset. | BOUNDING\_BOX |
| `layer_stack` | Ready-to-edit layer document for Create Layered Image: the base plate plus each element as its own named, tight-cropped layer at its true position and stacking order. Connect directly, or extend with Add Layer. | LAYERS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceSeedreamLayerSeparationNode/en.md)

***

**Source fingerprint (SHA-256):** `7c0d8ca76ee4b8d6a34fec2edbb753982a05160540ae1d1867efb79c9f9c5498`


# ByteDanceSeedreamLayerSeparationNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceSeedreamLayerSeparationNodeV2

ByteDance Seedream 5.0 Layer Separation decomposes an image into a background plate plus up to 16 repositionable transparent layers, each with stacking order, bounding box, name, a

ByteDance Seedream 5.0 Layer Separation decomposes an image into a background plate plus up to 16 repositionable transparent layers, each with stacking order, bounding box, name, and description. It returns the background, per-layer images with masks, placement boxes, and a ready-to-edit layer stack. The `model` selector chooses between Seedream 5.0 Pro and the faster Seedream 5.0 Flash.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Seedream model used for the separation. "seedream 5.0 pro" (default) gives the highest separation quality and also exposes a `prompt_optimization` control; "seedream 5.0 flash" is faster and cheaper and has no prompt-optimization control. | DYNAMIC\_COMBO | Yes | "seedream 5.0 pro"<br />"seedream 5.0 flash" |

### Seedream 5.0 Pro and 5.0 Flash Inputs

These inputs are available with both models.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image to separate. Exactly one image, at least 512x512 pixels, aspect ratio between 1:16 and 16:1. Inputs larger than about 4MP are downscaled before upload. | IMAGE | Yes | Single image |
| `prompt` | How to separate the image. Leave empty to auto-detect and separate all major elements. Describe elements in natural language to control the separation, or target exact regions with `<bbox>left top right bottom</bbox>` tags (0-1000 per-mille coordinates). Default: empty string. | STRING | Yes | Multiline text |
| `size` | Output resolution level. "auto" follows the input image size (clamped to the 1K-2K range). Default: "auto". | COMBO | Yes | "auto"<br />"1K"<br />"1.5K"<br />"2K" |
| `seed` | Seed to use for generation. Default: 42. | INT | Yes | 0 to 2147483647 |
| `watermark` | Whether to add an "AI generated" watermark to the images. Default: false. | BOOLEAN | Yes | false<br />true |
| `crop_layers` | Geometry of the layers/masks batch outputs (layer\_stack is unaffected and always tight). Full canvas: each layer on a base-sized canvas at its bounding-box position - recompose directly with ImageCompositeMasked. Minimal size: each layer cropped to its bounding box (padded to the largest layer for batching) - much smaller tensors; rebuild placement with Layers From Bounding Boxes using the bboxes output. Default: false (full canvas). | BOOLEAN | Yes | false (full canvas)<br />true (minimal size) |

### Seedream 5.0 Pro Only Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt_optimization` | Prompt-optimization mode: "standard" gives higher quality, "fast" shorter generation time. Only available with Seedream 5.0 Pro. Default: "standard". | COMBO | Yes | "standard"<br />"fast" |

**Note:** The input `image` must be a single image; batches are not supported. The image must be at least 512x512 pixels with an aspect ratio between 1:16 and 16:1. Seedream 5.0 Flash has no `prompt_optimization` input.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `base_image` | The base image (background plate) the layers stack onto. | IMAGE |
| `base_mask` | Transparency of the base image (1 = transparent, LoadImage convention); currently always fully opaque. | MASK |
| `layers` | Transparent layers ordered bottom to top. Full canvas mode: placed on a black base-sized canvas at their bounding-box position. Minimal size mode: cropped to their bounding box, anchored top-left, padded to the largest layer. | IMAGE |
| `masks` | Per-layer transparency, index-aligned with the layers batch (1 = transparent, LoadImage convention). For ImageCompositeMasked-style compositing, add InvertMask first. | MASK |
| `bboxes` | One placement box per layer, index-aligned with the layers batch (feed both, plus masks, into Layers From Bounding Boxes to rebuild per-layer placement): `{x, y, width, height, metadata: {name, desc, z_index, native_size, content_rect, flags}}`. `content_rect = [left, top, width, height]` is the layer's content region within its own frame; it lands on the canvas at the box position plus that offset. | BOUNDING\_BOX |
| `layer_stack` | Ready-to-edit layer document for Create Layered Image: the base plate plus each element as its own named, tight-cropped layer at its true position and stacking order. Connect directly, or extend with Add Layer. | LAYERS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceSeedreamLayerSeparationNodeV2/en.md)

***

**Source fingerprint (SHA-256):** `b106ca63d37aea68079f0032a1f7dfeefee9f759c71bb1605bbfe66c3d9dad62`


# ByteDanceSeedreamNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceSeedreamNode

The ByteDance Seedream 4.5 & 5.0 node provides unified text-to-image generation and precise single-sentence editing capabilities at up to 4K resolution.

The ByteDance Seedream 4.5 & 5.0 node provides unified text-to-image generation and precise single-sentence editing capabilities at up to 4K resolution. It can create new images from text prompts or edit existing images using text instructions. The node supports both single image generation and sequential generation of multiple related images.

**Note:** This node is marked as deprecated in the source code.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Seedream model to use for generation. | STRING | Yes | "seedream 5.0 pro"<br />"seedream 5.0 lite"<br />"seedream-4-5-251128"<br />"seedream-4-0-250828" |
| `prompt` | Text prompt for creating or editing an image. Must be at least 1 character long. | STRING | Yes | - |
| `image` | Input image(s) for image-to-image generation. Reference image(s) for single or multi-reference generation. Maximum of 14 reference images for seedream-5-0-260128, or 10 for other models. | IMAGE | No | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. | STRING | No | Multiple options available |
| `width` | Custom width for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 6240 (step 2) |
| `height` | Custom height for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 4992 (step 2) |
| `sequential_image_generation` | Group image generation mode. "disabled" generates a single image. "auto" lets the model decide whether to generate multiple related images (e.g., story scenes, character variations). Default: "disabled". | STRING | No | "disabled"<br />"auto" |
| `max_images` | Maximum number of images to generate when sequential\_image\_generation='auto'. Total images (input + generated) cannot exceed 15. Default: 1. | INT | No | 1 to 15 (step 1) |
| `seed` | Seed to use for generation. Default: 0. | INT | No | 0 to 2147483647 (step 1) |
| `watermark` | Whether to add an "AI generated" watermark to the image. Default: False. | BOOLEAN | No | - |
| `fail_on_partial` | If enabled, abort execution if any requested images are missing or return an error. Default: True. | BOOLEAN | No | - |

**Notes on parameter constraints:**

* The minimum image resolution depends on the selected model: 3.68MP for seedream-4-5 and seedream-5-0 models, 0.92MP for seedream-4-0 models.
* The maximum image resolution is 10.4MP for seedream-5-0 models and 16.78MP for other models.
* Reference images must have an aspect ratio between 1:3 and 3:1.
* When `sequential_image_generation` is set to "auto", the total number of input images plus `max_images` cannot exceed 15.
* The `width` and `height` parameters are only used when `size_preset` is set to "Custom".

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | Generated image(s) based on the input parameters and prompt. Returns a single image tensor or a batch of image tensors if multiple images are generated. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceSeedreamNode/en.md)

***

**Source fingerprint (SHA-256):** `78086df431c887c241796ddb5db1ebbfe5b57faab0839da842be81480f1e113b`


# ByteDanceSeedreamNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceSeedreamNodeV2

This node generates or edits images using ByteDance's Seedream models (versions 4.0, 4.5, 5.0 Lite, and 5.0 Pro).

This node generates or edits images using ByteDance's Seedream models (versions 4.0, 4.5, 5.0 Lite, and 5.0 Pro). It provides unified text-to-image generation and precise single-sentence image editing at up to 4K resolution. This is the legacy (V2) version of the Seedream node.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Seedream model version to use for generation. Each model has different capabilities and pricing. | DYNAMIC\_COMBO | Yes | `"seedream 5.0 pro"`<br />`"seedream 5.0 lite"`<br />`"seedream-4-5-251128"`<br />`"seedream-4-0-250828"` |
| `prompt` | Text prompt for creating or editing an image (default: empty string). | STRING | Yes | N/A |
| `seed` | Seed to use for generation (default: 0). | INT | Yes | 0 to 2147483647 |
| `watermark` | Whether to add an "AI generated" watermark to the image (default: False). | BOOLEAN | Yes | True / False |
| `thinking` | Enable the model's prompt-optimization reasoning ('thinking') for better adherence. Can substantially increase generation time — notably on Seedream 5.0 Pro. Can only be disabled for text-to-image (not when reference images are provided) (default: True). | BOOLEAN | No | True / False |

### `seedream 5.0 pro` Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. | COMBO | Yes | Multiple model-specific presets available, includes `Custom` |
| `width` | Custom width for image. Value is working only if `size_preset` is set to `Custom` (default: 2048). | INT | Yes | 1024 to 3136 (step 2) |
| `height` | Custom height for image. Value is working only if `size_preset` is set to `Custom` (default: 2048). | INT | Yes | 1024 to 2496 (step 2) |

### `seedream 5.0 lite` Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. | COMBO | Yes | Multiple model-specific presets available, includes `Custom` |
| `width` | Custom width for image. Value is working only if `size_preset` is set to `Custom` (default: 2048). | INT | Yes | 1024 to 6240 (step 2) |
| `height` | Custom height for image. Value is working only if `size_preset` is set to `Custom` (default: 2048). | INT | Yes | 1024 to 4992 (step 2) |
| `max_images` | Maximum number of images to generate. With 1, exactly one image is produced. With >1, the model generates between 1 and max\_images related images (e.g., story scenes, character variations). Total images (input + generated) cannot exceed 15. (default: 1) | INT | Yes | 1 to 14 |
| `fail_on_partial` | If enabled, abort execution if any requested images are missing or return an error. (default: False) | BOOLEAN | Yes | True / False |

### `seedream-4-5-251128` Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. | COMBO | Yes | Multiple model-specific presets available, includes `Custom` |
| `width` | Custom width for image. Value is working only if `size_preset` is set to `Custom` (default: 2048). | INT | Yes | 1024 to 6240 (step 2) |
| `height` | Custom height for image. Value is working only if `size_preset` is set to `Custom` (default: 2048). | INT | Yes | 1024 to 4992 (step 2) |
| `max_images` | Maximum number of images to generate. With 1, exactly one image is produced. With >1, the model generates between 1 and max\_images related images (e.g., story scenes, character variations). Total images (input + generated) cannot exceed 15. (default: 1) | INT | Yes | 1 to 10 |
| `fail_on_partial` | If enabled, abort execution if any requested images are missing or return an error. (default: False) | BOOLEAN | Yes | True / False |

### `seedream-4-0-250828` Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. | COMBO | Yes | Multiple model-specific presets available, includes `Custom` |
| `width` | Custom width for image. Value is working only if `size_preset` is set to `Custom` (default: 2048). | INT | Yes | 1024 to 6240 (step 2) |
| `height` | Custom height for image. Value is working only if `size_preset` is set to `Custom` (default: 2048). | INT | Yes | 1024 to 4992 (step 2) |
| `max_images` | Maximum number of images to generate. With 1, exactly one image is produced. With >1, the model generates between 1 and max\_images related images (e.g., story scenes, character variations). Total images (input + generated) cannot exceed 15. (default: 1) | INT | Yes | 1 to 10 |
| `fail_on_partial` | If enabled, abort execution if any requested images are missing or return an error. (default: False) | BOOLEAN | Yes | True / False |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Growable slot: connect 1..N items (e.g. `image_1`, `image_2`, ...); the count limit depends on the selected model (see model sections). Optional reference image(s) for image-to-image or multi-reference generation. With no reference images, the node works in text-to-image mode. | IMAGE | No | 0 to 10 images (`seedream 5.0 pro`, `seedream-4-5-251128`, `seedream-4-0-250828`)<br />0 to 14 images (`seedream 5.0 lite`) |

### Notes on constraints

* `width` and `height` only take effect when `size_preset` is set to `Custom`.
* The total number of reference images plus generated images cannot exceed 15.
* `thinking` can only be disabled for text-to-image generation, not when reference images are provided.
* Seedream 5.0 Pro does not support batch generation: it always produces a single image, so `max_images` and `fail_on_partial` are not available for this model.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated or edited image as a tensor. If multiple images were requested, they are concatenated into a single batch. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceSeedreamNodeV2/en.md)

***

**Source fingerprint (SHA-256):** `f1a84171d94c602ec5417e43857ddf511ab1e54caa089b1928f740d3a38423f8`


# ByteDanceSeedreamNodeV3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceSeedreamNodeV3

ByteDance Seedream 4.5 & 5.0 generates images from a text prompt (text-to-image) or generates/edits images guided by optional reference images, using ByteDance Seedream 4.0, 4.5, a

ByteDance Seedream 4.5 & 5.0 generates images from a text prompt (text-to-image) or generates/edits images guided by optional reference images, using ByteDance Seedream 4.0, 4.5, and 5.0 models at up to 4K resolution. The node sends the prompt and any reference images to the ByteDance API, waits for the generation task to complete, and returns the resulting image tensor or tensors.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for creating or editing an image. Must not be empty after trimming whitespace. | STRING | Yes | Multiline text |
| `model` | Selects the Seedream model to use. Each model exposes its own set of sub-parameters and limits below. | DYNAMIC\_COMBO | Yes | "seedream 5.0 pro"<br />"seedream 5.0 flash"<br />"seedream 5.0 lite"<br />"seedream-4-5-251128"<br />"seedream-4-0-250828" |

### Seedream 5.0 Pro Inputs (seedream 5.0 pro)

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. Default: first recommended preset for this model. | COMBO | No | Model-specific recommended size presets<br />"Custom" |
| `width` | Custom width for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 4514 (step 2) |
| `height` | Custom height for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 4514 (step 2) |
| `prompt_optimization` | Prompt-optimization mode when reference images are provided: 'standard' gives higher quality, 'fast' shorter generation time. Default: "standard". | COMBO | No | "standard"<br />"fast" |
| `seed` | Seed to use for generation. Default: 42. | INT | No | 0 to 2147483647 |
| `watermark` | Whether to add an "AI generated" watermark to the image. Default: false. | BOOLEAN | No | true / false |
| `thinking` | Enable the model's prompt-optimization reasoning ('thinking') for better adherence. Can substantially increase generation time — notably on Seedream 5.0 Pro. Can only be disabled for text-to-image (not when reference images are provided). Default: true. | BOOLEAN | No | true / false |

### Seedream 5.0 Flash Inputs (seedream 5.0 flash)

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. Default: first recommended preset for this model. | COMBO | No | Model-specific recommended size presets<br />"Custom" |
| `width` | Custom width for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 4514 (step 2) |
| `height` | Custom height for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 4514 (step 2) |
| `seed` | Seed to use for generation. Default: 42. | INT | No | 0 to 2147483647 |
| `watermark` | Whether to add an "AI generated" watermark to the image. Default: false. | BOOLEAN | No | true / false |

### Seedream 5.0 Lite Inputs (seedream 5.0 lite)

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. Default: first recommended preset for this model. | COMBO | No | Model-specific recommended size presets<br />"Custom" |
| `width` | Custom width for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 6240 (step 2) |
| `height` | Custom height for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 4992 (step 2) |
| `max_images` | Maximum number of images to generate. With 1, exactly one image is produced. With >1, the model generates between 1 and max\_images related images (e.g., story scenes, character variations). Total images (input + generated) cannot exceed 15. Default: 1. | INT | No | 1 to 14 |
| `fail_on_partial` | If enabled, abort execution if any requested images are missing or return an error. Default: false. | BOOLEAN | No | true / false |
| `seed` | Seed to use for generation. Default: 42. | INT | No | 0 to 2147483647 |
| `watermark` | Whether to add an "AI generated" watermark to the image. Default: false. | BOOLEAN | No | true / false |
| `thinking` | Enable the model's prompt-optimization reasoning ('thinking') for better adherence. Can substantially increase generation time — notably on Seedream 5.0 Pro. Can only be disabled for text-to-image (not when reference images are provided). Default: true. | BOOLEAN | No | true / false |

### Seedream 4.5 Inputs (seedream-4-5-251128)

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. Default: first recommended preset for this model. | COMBO | No | Model-specific recommended size presets<br />"Custom" |
| `width` | Custom width for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 6240 (step 2) |
| `height` | Custom height for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 4992 (step 2) |
| `max_images` | Maximum number of images to generate. With 1, exactly one image is produced. With >1, the model generates between 1 and max\_images related images (e.g., story scenes, character variations). Total images (input + generated) cannot exceed 15. Default: 1. | INT | No | 1 to 10 |
| `fail_on_partial` | If enabled, abort execution if any requested images are missing or return an error. Default: false. | BOOLEAN | No | true / false |
| `seed` | Seed to use for generation. Default: 42. | INT | No | 0 to 2147483647 |
| `watermark` | Whether to add an "AI generated" watermark to the image. Default: false. | BOOLEAN | No | true / false |
| `thinking` | Enable the model's prompt-optimization reasoning ('thinking') for better adherence. Can substantially increase generation time — notably on Seedream 5.0 Pro. Can only be disabled for text-to-image (not when reference images are provided). Default: true. | BOOLEAN | No | true / false |

### Seedream 4.0 Inputs (seedream-4-0-250828)

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size_preset` | Pick a recommended size. Select Custom to use the width and height below. Default: first recommended preset for this model. | COMBO | No | Model-specific recommended size presets<br />"Custom" |
| `width` | Custom width for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 6240 (step 2) |
| `height` | Custom height for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048. | INT | No | 1024 to 4992 (step 2) |
| `max_images` | Maximum number of images to generate. With 1, exactly one image is produced. With >1, the model generates between 1 and max\_images related images (e.g., story scenes, character variations). Total images (input + generated) cannot exceed 15. Default: 1. | INT | No | 1 to 10 |
| `fail_on_partial` | If enabled, abort execution if any requested images are missing or return an error. Default: false. | BOOLEAN | No | true / false |
| `seed` | Seed to use for generation. Default: 42. | INT | No | 0 to 2147483647 |
| `watermark` | Whether to add an "AI generated" watermark to the image. Default: false. | BOOLEAN | No | true / false |
| `thinking` | Enable the model's prompt-optimization reasoning ('thinking') for better adherence. Can substantially increase generation time — notably on Seedream 5.0 Pro. Can only be disabled for text-to-image (not when reference images are provided). Default: true. | BOOLEAN | No | true / false |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Growable slot: optional reference image(s) for image-to-image or multi-reference generation. Connect 1..N images (e.g., `image_1`, `image_2`, ...); the count limit is per model (see notes below). If a connected image contains a batch of images, every image in the batch counts toward the limit. | IMAGE | No | 0 to 10 (Seedream 5.0 Pro, Seedream 5.0 Flash, Seedream 4.5, Seedream 4.0)<br />0 to 14 (Seedream 5.0 Lite) |

**Notes:**

* The `prompt` must not be empty after trimming whitespace.
* Maximum number of reference images: 10 for Seedream 5.0 Pro, Seedream 5.0 Flash, Seedream 4.5, and Seedream 4.0; 14 for Seedream 5.0 Lite.
* Each reference image must have an aspect ratio between 1:16 and 16:1.
* When `max_images` is greater than 1 (not available on Seedream 5.0 Pro or Seedream 5.0 Flash), the total number of reference images plus generated images cannot exceed 15.
* `thinking` can only be disabled for text-to-image generation. When reference images are provided, `thinking` must be enabled. Seedream 5.0 Flash has no `thinking` input.
* `width` and `height` are only used when `size_preset` is set to "Custom".
* `prompt_optimization` is only available on Seedream 5.0 Pro.
* `max_images` and `fail_on_partial` are only available on Seedream 5.0 Lite, Seedream 4.5, and Seedream 4.0; Seedream 5.0 Pro and Seedream 5.0 Flash always request a single image.
* Resolution requirements (width x height):
  * Seedream 5.0 Pro and Seedream 5.0 Flash: between 0.92MP (921,600 pixels) and 4.62MP (4,624,220 pixels).
  * Seedream 5.0 Lite and Seedream 4.5: at least 3.68MP (3,686,400 pixels).
  * Seedream 4.0: at least 0.92MP (921,600 pixels).
  * Seedream 5.0 Lite, Seedream 4.5, and Seedream 4.0: at most 16.78MP (16,777,216 pixels).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated image tensor. When multiple images are generated, they are concatenated into a single batched IMAGE tensor. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceSeedreamNodeV3/en.md)

***

**Source fingerprint (SHA-256):** `1c1f40b202ccbb3e0f73cd072170e1c16b833e007f26e63505b54c42b004a8a6`


# ElevenLabsAudioIsolation - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsAudioIsolation

The ElevenLabs Voice Isolation node removes background noise from an audio file, isolating the vocals or speech.

The ElevenLabs Voice Isolation node removes background noise from an audio file, isolating the vocals or speech. It sends the audio to the ElevenLabs API for processing and returns the cleaned audio.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | Audio to process for background noise removal. | AUDIO | Yes | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The processed audio with background noise removed. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsAudioIsolation/en.md)

***

**Source fingerprint (SHA-256):** `9527f6cc976a72c787985d866dade272f3fcdc485d2bd9e3ceaaaf625822f3e1`


# ElevenLabsInstantVoiceClone - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsInstantVoiceClone

The ElevenLabs Instant Voice Clone node creates a new, unique voice model by analyzing 1 to 8 audio recordings of a person's voice.

The ElevenLabs Instant Voice Clone node creates a new, unique voice model by analyzing 1 to 8 audio recordings of a person's voice. It sends these samples to the ElevenLabs API, which processes them to generate a voice clone that can be used for text-to-speech synthesis.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio_*` | Audio recordings for voice cloning. You must provide between 1 and 8 audio files. | AUDIO | Yes | 1 to 8 files |
| `remove_background_noise` | Remove background noise from voice samples using audio isolation. (default: False) | BOOLEAN | No | True / False |

**Note:** You must provide at least one audio file, and you can provide up to eight. The node will automatically create input slots for the audio files you add.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `voice` | The unique identifier for the newly created cloned voice model. This output can be connected to other ElevenLabs text-to-speech nodes. | ELEVENLABS\_VOICE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsInstantVoiceClone/en.md)

***

**Source fingerprint (SHA-256):** `5b109dfff8cdbc51d9e2684b9508b0998aaa014459b973acf29c204835a8db95`


# ElevenLabsSpeechToSpeech - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsSpeechToSpeech

The ElevenLabs Speech to Speech node transforms an input audio file from one voice to another.

The ElevenLabs Speech to Speech node transforms an input audio file from one voice to another. It uses the ElevenLabs API to convert speech while preserving the original content and emotional tone of the audio.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for speech-to-speech transformation. The selected model determines the available voice settings listed below. | DYNAMIC\_COMBO | Yes | `eleven_multilingual_sts_v2`<br />`eleven_english_sts_v2` |
| `voice` | Target voice for the transformation. Connect from Voice Selector or Instant Voice Clone. | CUSTOM | Yes | - |
| `audio` | Source audio to transform. | AUDIO | Yes | - |
| `stability` | Voice stability. Lower values give broader emotional range, higher values produce more consistent but potentially monotonous speech (default: 0.5). | FLOAT | Yes | 0.0 - 1.0 |
| `output_format` | Audio output format. | COMBO | Yes | `"mp3_44100_192"`<br />`"opus_48000_192"` |
| `seed` | Seed for reproducibility (default: 0). | INT | Yes | 0 - 4294967295 |
| `remove_background_noise` | Remove background noise from input audio using audio isolation (default: False). | BOOLEAN | Yes | - |

### eleven\_multilingual\_sts\_v2 and eleven\_english\_sts\_v2 Inputs

Both models provide the same set of voice settings below.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `speed` | Speech speed. 1.0 is normal, \<1.0 slower, >1.0 faster (default: 1.0). | FLOAT | Yes | 0.7 - 1.3 |
| `similarity_boost` | Similarity boost. Higher values make the voice more similar to the original (default: 0.75). | FLOAT | Yes | 0.0 - 1.0 |
| `use_speaker_boost` | Boost similarity to the original speaker voice (default: False). | BOOLEAN | Yes | - |
| `style` | Style exaggeration. Higher values increase stylistic expression but may reduce stability (default: 0.0). | FLOAT | Yes | 0.0 - 0.2 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The transformed audio file in the specified output format. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsSpeechToSpeech/en.md)

***

**Source fingerprint (SHA-256):** `a3cd602181d134b9ab517bfac092ea30b62ef5a9942a905c0c3e6959b34370ca`


# ElevenLabsSpeechToText - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsSpeechToText

The ElevenLabs Speech to Text node transcribes audio into text using the ElevenLabs API.

The ElevenLabs Speech to Text node transcribes audio into text using the ElevenLabs API. It supports automatic language detection, speaker diarization (identifying different speakers), and audio event tagging (annotating sounds like laughter or music in the transcript).

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for transcription. Selecting this model reveals additional parameters. | DYNAMIC\_COMBO | Yes | `"scribe_v2"` |
| `audio` | Audio to transcribe. | AUDIO | Yes | - |
| `language_code` | ISO-639-1 or ISO-639-3 language code (e.g., 'en', 'es', 'fra'). Leave empty for automatic detection. (default: "") | STRING | No | - |
| `num_speakers` | Maximum number of speakers to predict. Set to 0 for automatic detection. (default: 0) | INT | No | 0 - 32 |
| `seed` | Seed for reproducibility (determinism not guaranteed). (default: 1) | INT | No | 0 - 2147483647 |

### Scribe v2 Inputs

These parameters are shown when the `"scribe_v2"` model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `tag_audio_events` | Annotate sounds like (laughter), (music), etc. in transcript. (default: False) | BOOLEAN | No | - |
| `diarize` | Annotate which speaker is talking. (default: False) | BOOLEAN | No | - |
| `diarization_threshold` | Speaker separation sensitivity. Lower values are more sensitive to speaker changes. Only used when `diarize` is enabled. (default: 0.22) | FLOAT | No | 0.1 - 0.4 |
| `temperature` | Randomness control. 0.0 uses model default. Higher values increase randomness. (default: 0.0) | FLOAT | No | 0.0 - 2.0 |
| `timestamps_granularity` | Timing precision for transcript words. (default: "word") | COMBO | No | `"word"`<br />`"character"`<br />`"none"` |

**Note:** `num_speakers` cannot be set to a value greater than 0 when `diarize` is enabled. You must either disable `diarize` or set `num_speakers` to 0.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `text` | The transcribed text from the audio. | STRING |
| `language_code` | The detected language code of the audio. | STRING |
| `words_json` | A JSON-formatted string containing detailed word-level information, including timestamps and speaker labels if enabled. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsSpeechToText/en.md)

***

**Source fingerprint (SHA-256):** `7eb5d72615aa8a9e4a8014e45b39cf83dc8d8432d7ce0dccba20489be80a5830`


# ElevenLabsTextToDialogue - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsTextToDialogue

The ElevenLabs Text to Dialogue node generates a multi-speaker audio dialogue from text.

The ElevenLabs Text to Dialogue node generates a multi-speaker audio dialogue from text. It allows you to create a conversation by specifying different text lines and distinct voices for each participant. The node sends the dialogue request to the ElevenLabs API and returns the generated audio.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `stability` | Voice stability. Lower values give broader emotional range, higher values produce more consistent but potentially monotonous speech. (default: 0.5) | FLOAT | Yes | 0.0 - 1.0 |
| `apply_text_normalization` | Text normalization mode. 'auto' lets the system decide, 'on' always applies normalization, 'off' skips it. | COMBO | Yes | `"auto"`<br />`"on"`<br />`"off"` |
| `model` | Model to use for dialogue generation. | COMBO | Yes | `"eleven_v3"` |
| `inputs` | Number of dialogue entries. Selecting a number creates that many text and voice input pairs. | DYNAMIC\_COMBO | Yes | `"1"`<br />`"2"`<br />`"3"`<br />`"4"`<br />`"5"`<br />`"6"`<br />`"7"`<br />`"8"`<br />`"9"`<br />`"10"` |
| `language_code` | ISO-639-1 or ISO-639-3 language code (e.g., 'en', 'es', 'fra'). Leave empty for automatic detection. (default: empty) | STRING | Yes | - |
| `seed` | Seed for reproducibility. (default: 1) | INT | Yes | 0 - 4294967295 |
| `output_format` | Audio output format. | COMBO | Yes | `"mp3_44100_192"`<br />`"opus_48000_192"` |

### Dialogue Entry Inputs

Shared by all `inputs` options.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text1` ... `text10` | Text content for the corresponding dialogue entry. The node creates one `text` field for each selected dialogue entry. Each text value must contain at least one character. | STRING | Yes | - |
| `voice1` ... `voice10` | Voice for the corresponding dialogue entry. Connect from a Voice Selector or Instant Voice Clone node. The node creates one `voice` field for each selected dialogue entry. | ELEVENLABS\_VOICE | Yes | - |

**Note:** The `inputs` selector can create up to 10 dialogue entries. Each entry requires both a `text` field and a `voice` field. The `text` value cannot be empty. The `voice` input expects a voice ID provided by a compatible ElevenLabs voice node.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The generated multi-speaker dialogue audio in the selected output format. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsTextToDialogue/en.md)

***

**Source fingerprint (SHA-256):** `95b16143391a2282c58ebc66561b85338a8ce1f87e0ec769405225599d2c76ae`


# ElevenLabsTextToSoundEffects - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsTextToSoundEffects

The ElevenLabs Text to Sound Effects node generates audio sound effects from a text description.

The ElevenLabs Text to Sound Effects node generates audio sound effects from a text description. It uses the ElevenLabs API to create sound effects based on your prompt, allowing you to control the duration, looping behavior, and how closely the sound follows the text.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for sound effect generation. Only one model is currently available: `eleven_sfx_v2`. | DYNAMIC\_COMBO | Yes | `"eleven_sfx_v2"` |
| `text` | Text description of the sound effect to generate. (default: empty) | STRING | Yes | N/A |
| `output_format` | Audio output format. | COMBO | Yes | `"mp3_44100_192"`<br />`"opus_48000_192"` |

### eleven\_sfx\_v2 Inputs

These parameters are shown when the `eleven_sfx_v2` model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `duration` | Duration of generated sound in seconds. (default: 5.0) | FLOAT | Yes | 0.5 to 30.0 |
| `loop` | Create a smoothly looping sound effect. (default: False) | BOOLEAN | No | True<br />False |
| `prompt_influence` | How closely generation follows the prompt. Higher values make the sound follow the text more closely. (default: 0.3) | FLOAT | Yes | 0.0 to 1.0 |

**Note:** The `text` parameter must not be empty; it is validated before the sound generation request is sent.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The generated sound effect audio file. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsTextToSoundEffects/en.md)

***

**Source fingerprint (SHA-256):** `218ff617256cea33f310c1bcfc6407c46aaadc59201a0324b0ec64583166ce58`


# ElevenLabsTextToSpeech - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsTextToSpeech

The ElevenLabs Text to Speech node converts written text into spoken audio using the ElevenLabs API.

The ElevenLabs Text to Speech node converts written text into spoken audio using the ElevenLabs API. It allows you to select a specific voice and fine-tune various speech characteristics like stability, speed, and style to generate a customized audio output. The text must contain at least one character.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for text-to-speech. Selecting a model reveals its specific parameters. | DYNAMIC\_COMBO | No | `"eleven_multilingual_v2"`<br />`"eleven_v3"` |
| `voice` | Voice to use for speech synthesis. Connect from Voice Selector or Instant Voice Clone. | CUSTOM | Yes | N/A |
| `text` | The text to convert to speech. Must contain at least one character. | STRING | Yes | N/A |
| `stability` | Voice stability. Lower values give broader emotional range, higher values produce more consistent but potentially monotonous speech (default: 0.5). | FLOAT | No | 0.0 - 1.0 |
| `apply_text_normalization` | Text normalization mode. 'auto' lets the system decide, 'on' always applies normalization, 'off' skips it. | COMBO | No | `"auto"`<br />`"on"`<br />`"off"` |
| `language_code` | ISO-639-1 or ISO-639-3 language code (e.g., 'en', 'es', 'fra'). Leave empty for automatic detection (default: ""). | STRING | No | N/A |
| `seed` | Seed for reproducibility (determinism not guaranteed) (default: 1). | INT | No | 0 - 2147483647 |
| `output_format` | Audio output format. | COMBO | No | `"mp3_44100_192"`<br />`"opus_48000_192"` |

### eleven\_multilingual\_v2 Inputs

These parameters become available when `model` is set to `"eleven_multilingual_v2"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `speed` | Speech speed. 1.0 is normal, \<1.0 slower, >1.0 faster (default: 1.0). | FLOAT | No | 0.7 - 1.3 |
| `similarity_boost` | Similarity boost. Higher values make the voice more similar to the original (default: 0.75). | FLOAT | No | 0.0 - 1.0 |
| `use_speaker_boost` | Boost similarity to the original speaker voice (default: False). | BOOLEAN | No | True / False |
| `style` | Style exaggeration. Higher values increase stylistic expression but may reduce stability (default: 0.0). | FLOAT | No | 0.0 - 0.2 |

### eleven\_v3 Inputs

These parameters become available when `model` is set to `"eleven_v3"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `speed` | Speech speed. 1.0 is normal, \<1.0 slower, >1.0 faster (default: 1.0). | FLOAT | No | 0.7 - 1.3 |
| `similarity_boost` | Similarity boost. Higher values make the voice more similar to the original (default: 0.75). | FLOAT | No | 0.0 - 1.0 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The generated audio from the text-to-speech conversion. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsTextToSpeech/en.md)

***

**Source fingerprint (SHA-256):** `78ed1c6af2d0b1cc0293d725492a8b104b6d0c6bc18d9971b75047db946cdd33`


# ElevenLabsVoiceSelector - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsVoiceSelector

The ElevenLabs Voice Selector node allows you to choose a specific voice from a predefined list of ElevenLabs text-to-speech voices.

The ElevenLabs Voice Selector node allows you to choose a specific voice from a predefined list of ElevenLabs text-to-speech voices. It takes a voice name as input and outputs the corresponding voice identifier needed for audio generation. This node simplifies the process of selecting a compatible voice for use with other ElevenLabs audio nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `voice` | Choose a voice from the predefined ElevenLabs voices. | STRING | Yes | `"Adam (male, american)"`<br />`"Antoni (male, british)"`<br />`"Arnold (male, american)"`<br />`"Bella (female, american)"`<br />`"Domi (female, american)"`<br />`"Elli (female, american)"`<br />`"Josh (male, american)"`<br />`"Rachel (female, american)"`<br />`"Sam (male, american)"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `voice` | The unique identifier for the selected ElevenLabs voice, which can be passed to other nodes for text-to-speech generation. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsVoiceSelector/en.md)

***

**Source fingerprint (SHA-256):** `72e2239bb0da15a88cd346ede2051b4fb717f3bf49faaf5d63c0622b03ccd80d`


# FishAudioInstantVoiceClone - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FishAudioInstantVoiceClone

This node creates a private cloned voice from your audio recordings using the Fish Audio API.

This node creates a private cloned voice from your audio recordings using the Fish Audio API. You provide one or more audio samples, and the node builds a custom voice that can be immediately used for text-to-speech. It accepts 1 to 20 recordings, with a recommended length of 10 to 30 seconds each and a total limit of 270 seconds.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `files` | Audio recordings for voice cloning. This is a growable input: connect one or more audio items (for example `audio_1`, `audio_2`, ...) to provide the voice samples. | AUDIO | Yes | 1 to 20 recordings |
| `enhance_audio_quality` | Enhance reference audio quality before training (default: True). | BOOLEAN | Yes | True<br />False |

**Note:** The total duration of all reference audio combined must be under 270 seconds. If the combined duration reaches or exceeds 270 seconds, the node returns an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `voice` | The newly created cloned voice, identified by a unique voice ID returned by the Fish Audio API. This voice can be used for text-to-speech. | FISHAUDIO\_VOICE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FishAudioInstantVoiceClone/en.md)

***

**Source fingerprint (SHA-256):** `6c4f011a4611a076b2488152591efeb61c029d6dfae2b079ba74689891c84803`


# FishAudioSpeechToText - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FishAudioSpeechToText

This node transcribes audio into text using the Fish Audio speech-to-text service.

This node transcribes audio into text using the Fish Audio speech-to-text service. It automatically detects the language of the audio and can optionally return word-level timestamped segments as JSON.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | Audio to transcribe. | AUDIO | Yes | — |
| `language` | ISO 639-1 language hint (e.g. 'en', 'zh'). The language is auto-detected regardless. Default: "" (empty string). | STRING | No | Any ISO 639-1 language code, e.g. `en`, `zh`; empty string for auto-detection |
| `precise_timestamps` | Return word-level timestamped segments. Default: false. | BOOLEAN | No | true or false |

Note: The `language` parameter is only a hint — the language is always auto-detected from the audio. When `precise_timestamps` is false (the default), word-level timestamps are not returned; when true, the output segments include word-level timestamps.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `text` | The transcribed text. | STRING |
| `language_code` | The ISO 639-1 language code detected for the audio. | STRING |
| `segments_json` | JSON string containing the transcription segments. Includes word-level timestamps when `precise_timestamps` is enabled. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FishAudioSpeechToText/en.md)

***

**Source fingerprint (SHA-256):** `eaf1c9a9d2b90ec962a408615cc417b552864354c3f272144b8e239b23961920`


# FishAudioTextToSpeech - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FishAudioTextToSpeech

This node converts written text into spoken audio using Fish Audio text-to-speech models.

This node converts written text into spoken audio using Fish Audio text-to-speech models. It supports emotion cues embedded in the text (\[happy], \[whispering] on s2.1-pro; (happy) on s1) and multi-speaker dialogue using @Voice1/@Voice2 tags when multiple voices are connected. Two models are available: s2.1-pro, which supports up to five voices and multi-speaker dialogue, and s1, which uses a single optional voice.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | The text to convert to speech. With two or more voices connected, mark speaker changes with @Voice1, @Voice2, etc. (default: empty) | STRING | Yes | Any non-empty text |
| `model` | Model to use for text-to-speech. | DYNAMIC\_COMBO | Yes | "s2.1-pro"<br />"s1" |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 42) | INT | Yes | 0 to 2147483647 |

### s2.1-pro Inputs

These inputs appear when the s2.1-pro model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `voices` | Growable slot: connect 0 to 5 voice items (`voice_1`, `voice_2`, ...). Voices for synthesis. Leave empty for the default voice. With two or more voices, mark speaker changes in the text with @Voice1, @Voice2, etc. | FISHAUDIO\_VOICE | No | 0 to 5 voices |
| `temperature` | Expressiveness. Higher values are more varied, lower values are more consistent. (default: 0.7) | FLOAT | Yes | 0.0 to 1.0 |
| `top_p` | Diversity via nucleus sampling. (default: 0.7) | FLOAT | Yes | 0.01 to 1.0 |
| `speed` | Speaking rate. 1.0 is normal, \<1.0 slower, >1.0 faster. (default: 1.0) | FLOAT | Yes | 0.5 to 2.0 |
| `volume` | Volume adjustment in decibels. 0 is no change. (default: 0.0) | FLOAT | Yes | -10.0 to 10.0 |
| `normalize` | Normalize numbers and text for English and Chinese, improving stability for numbers and dates. (default: true) | BOOLEAN | Yes | true / false |

### s1 Inputs

These inputs appear when the s1 model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `voice` | Voice for synthesis. Leave unconnected for the default voice. | FISHAUDIO\_VOICE | No | Optional single voice |
| `temperature` | Expressiveness. Higher values are more varied, lower values are more consistent. (default: 0.7) | FLOAT | Yes | 0.0 to 1.0 |
| `top_p` | Diversity via nucleus sampling. (default: 0.7) | FLOAT | Yes | 0.01 to 1.0 |
| `speed` | Speaking rate. 1.0 is normal, \<1.0 slower, >1.0 faster. (default: 1.0) | FLOAT | Yes | 0.5 to 2.0 |
| `volume` | Volume adjustment in decibels. 0 is no change. (default: 0.0) | FLOAT | Yes | -10.0 to 10.0 |
| `normalize` | Normalize numbers and text for English and Chinese, improving stability for numbers and dates. (default: true) | BOOLEAN | Yes | true / false |

**Note:** The `text` input must not be empty. Speaker tags (@Voice1, @Voice2, etc.) are case-insensitive and must refer to a connected voice; tagging a voice that is not connected raises an error. When two or more voices are connected, the text must reference every connected voice at least once, or the node reports the missing tags. On s2.1-pro, connecting 0 voices uses the default voice, 1 voice uses that voice alone, and 2 or more voices enable multi-speaker dialogue. On s1, a single optional voice is used and leaving it unconnected uses the default voice. Emotion cues can be placed in the text: \[happy] and \[whispering] on s2.1-pro, and (happy) on s1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The generated speech as an audio file. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FishAudioTextToSpeech/en.md)

***

**Source fingerprint (SHA-256):** `6cc005ae76fc7b60d9399b1b0a3c5de40a6eff47cd6f0f0b73b4212c0270ae29`


# FishAudioVoiceSelector - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FishAudioVoiceSelector

The Fish Audio Voice Selector node selects a voice from the Fish Audio library for text-to-speech generation.

The Fish Audio Voice Selector node selects a voice from the Fish Audio library for text-to-speech generation. You can pick one of the built-in preset voices, or choose "custom" to enter any voice model ID from fish.audio.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `voice` | Choose a voice, or 'custom' to enter any fish.audio voice model ID. | DYNAMIC\_COMBO | Yes | "Energetic Male (en)"<br />"Friendly Women (en)"<br />"Sarah (en)"<br />"Verity (en)"<br />"Polo (en)"<br />"Adrian (en)"<br />"E-girl (en)"<br />"Narrator (en)"<br />"Warm Conversational Voice (en)"<br />"Warm Storyteller (en)"<br />"Dramatic Character Male (en)"<br />"News Narrator (zh)"<br />"Lively Female (zh)"<br />"Gentle Female (zh)"<br />"Energetic Female (ja)"<br />"Calm Female (ja)"<br />"Calm Male (ja)"<br />"custom" |

The preset voice options cover English (en), Chinese (zh), and Japanese (ja) voices and do not require any additional inputs.

### Custom Inputs

These inputs appear when `voice` is set to "custom".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `voice_id` | Voice model ID from fish.audio, e.g. the ID in [https://fish.audio/m/\&lt;id>/](https://fish.audio/m/\&lt;id>/). Default: empty string. | STRING | Yes | Any valid Fish Audio voice model ID |

Note: When `voice` is set to "custom", `voice_id` must not be empty after whitespace is trimmed; otherwise the node raises a "Custom voice ID is empty." error. If an unrecognized voice option is passed, the node raises an "Unknown voice" error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `voice` | The selected Fish Audio voice model ID. For a preset voice, the corresponding voice ID from the Fish Audio library is returned; for "custom", the entered `voice_id` value is returned. | FISHAUDIO\_VOICE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FishAudioVoiceSelector/en.md)

***

**Source fingerprint (SHA-256):** `4f99a58aa7e6054f58fe84e61e4e1008b17828bd97d71ef0a4009c4de4052bbd`


# Flux2ImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Flux2ImageNode

Generate images using the Flux.2 [pro] or Flux.2 [max] model from a text prompt and optional reference images.

Generate images using the Flux.2 \[pro] or Flux.2 \[max] model from a text prompt and optional reference images. The node sends the request to the BFL API, polls until the result is ready, and returns the generated image.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Flux.2 model version to use. Selecting a model unlocks additional parameters for width, height, and optional reference images. | DYNAMIC\_COMBO | Yes | "Flux.2 \[pro]"<br />"Flux.2 \[max]" |
| `prompt` | Prompt for the image generation or edit (default: empty string). | STRING | Yes | N/A |
| `seed` | The random seed used for creating the noise (default: 0). Supports the control-after-generate option to randomize the value after each run. | INT | Yes | 0 to 18446744073709551615 |

### Flux.2 \[pro] and Flux.2 \[max] Inputs

Shared by both models — the parameter sets are identical.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.width` | The width of the generated image in pixels (default: 1024). | INT | Yes | 256 to 2048 (step 32) |
| `model.height` | The height of the generated image in pixels (default: 768). | INT | Yes | 256 to 2048 (step 32) |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.images` | Optional reference image(s) for image-to-image generation. Up to 8 images. Growable slot: connect 1..8 items (`image_1`...`image_8`). | IMAGE | No | 0 to 8 images |

**Note:**

* The maximum number of reference images is 8. If more than 8 images are provided, an error is raised. Batch images count toward this limit, since each image in a batch is counted individually.
* Reference images are resized so that the total pixel count does not exceed 2048 x 2048 before being sent to the API.
* The `model.width` and `model.height` values affect the generation cost. The cost also depends on the selected model and on whether reference images are provided.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated image as a tensor, downloaded from the BFL API result. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Flux2ImageNode/en.md)

***

**Source fingerprint (SHA-256):** `2994564757e1c66ac6da7b45d227b27ceb0020ac6fc9e8cbe2b53fe9f70bc195`


# FluxEraseNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxEraseNode

Removes the masked object from an image and reconstructs the background.

Removes the masked object from an image and reconstructs the background. Paint the mask over what you want to erase, and the node fills in the area with plausible background content.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to process | IMAGE | Yes | - |
| `mask` | White areas are removed; black areas are preserved | MASK | Yes | - |
| `dilate_pixels` | Expands the mask boundaries to ensure clean coverage of the object's edges (default: 10) | INT | Yes | 0 to 25 |
| `seed` | The random seed used for creating the noise (default: 0) | INT | No | 0 to 2147483647 |

**Note:** The input image must be at least 256x256 pixels in both dimensions. The mask is automatically resized to match the image dimensions, and the image's alpha channel is removed before processing.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The resulting image with the masked object removed and the background reconstructed | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxEraseNode/en.md)

***

**Source fingerprint (SHA-256):** `124be59b9829aa9f865d7ec76cd68f7978e2010cd3a84f25742a1c17f2d70b76`


# FluxProExpandNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProExpandNode

Outpaints image based on prompt.

Outpaints image based on prompt. This node expands an image by adding pixels to the top, bottom, left, and right sides while generating new content that matches the provided text description.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be expanded | IMAGE | Yes | - |
| `prompt` | Prompt for the image generation (default: "") | STRING | No | - |
| `prompt_upsampling` | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: False) | BOOLEAN | No | - |
| `top` | Number of pixels to expand at the top of the image (default: 0) | INT | No | 0-2048 |
| `bottom` | Number of pixels to expand at the bottom of the image (default: 0) | INT | No | 0-2048 |
| `left` | Number of pixels to expand at the left of the image (default: 0) | INT | No | 0-2048 |
| `right` | Number of pixels to expand at the right of the image (default: 0) | INT | No | 0-2048 |
| `guidance` | Guidance strength for the image generation process (default: 60) | FLOAT | No | 1.5-100 |
| `steps` | Number of steps for the image generation process (default: 50) | INT | No | 15-50 |
| `seed` | The random seed used for creating the noise. (default: 0) | INT | No | 0-18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The expanded output image | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProExpandNode/en.md)

***

**Source fingerprint (SHA-256):** `faff1e1311a3208066a499a358923c6e335ea1785baeafe3761484641f7f12d6`


# FluxProFillNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProFillNode

Inpaints image based on mask and prompt.

Inpaints image based on mask and prompt. This node uses the Flux.1 model to fill in masked areas of an image according to the provided text description, generating new content that matches the surrounding image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be inpainted | IMAGE | Yes | - |
| `mask` | The mask defining which areas of the image should be filled | MASK | Yes | - |
| `prompt` | Prompt for the image generation (default: empty string) | STRING | No | - |
| `prompt_upsampling` | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: false) | BOOLEAN | No | - |
| `guidance` | Guidance strength for the image generation process (default: 60) | FLOAT | No | 1.5-100 |
| `steps` | Number of steps for the image generation process (default: 50) | INT | No | 15-50 |
| `seed` | The random seed used for creating the noise. (default: 0) | INT | No | 0-18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output_image` | The generated image with the masked areas filled according to the prompt | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProFillNode/en.md)

***

**Source fingerprint (SHA-256):** `11aa071c52897788d9d7dae4105ffdf747d3cb91d75a0ad7cfacd7ca1ddd2ac1`


# FluxProUltraImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProUltraImageNode

Generates images using Flux Pro 1.1 Ultra via API based on prompt and resolution.

Generates images using Flux Pro 1.1 Ultra via API based on prompt and resolution. This node connects to an external service to create images according to your text description and specified dimensions.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the image generation (default: empty string) | STRING | Yes | - |
| `prompt_upsampling` | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: False) | BOOLEAN | No | - |
| `seed` | The random seed used for creating the noise. (default: 0) | INT | No | 0 to 18446744073709551615 |
| `aspect_ratio` | Aspect ratio of image; must be between 1:4 and 4:1. (default: "16:9") | STRING | No | - |
| `raw` | When True, generate less processed, more natural-looking images. (default: False) | BOOLEAN | No | - |
| `image_prompt` | Optional reference image to guide generation | IMAGE | No | - |
| `image_prompt_strength` | Blend between the prompt and the image prompt. (default: 0.1) | FLOAT | No | 0.0 to 1.0 |

**Note:** The `aspect_ratio` parameter must be between 1:4 and 4:1. When `image_prompt` is provided, `image_prompt_strength` becomes active and controls how much the reference image influences the final output. If `image_prompt` is not provided, the `prompt` parameter is validated to ensure it is not empty.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output_image` | The generated image from Flux Pro 1.1 Ultra | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProUltraImageNode/en.md)

***

**Source fingerprint (SHA-256):** `6c9292ea666055ccd309d9e5d6d7cf8985f7b8f1e1faeda1e961b429b249f494`


# FluxVTONode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxVTONode

This node performs a virtual try-on by dressing a person in a supplied garment image.

This node performs a virtual try-on by dressing a person in a supplied garment image. It sends the person and garment images to the BFL Flux VTO service, which generates a realistic image of the person wearing the garment. An optional text instruction can describe how the garment should fit or look.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `person` | Image of the person to dress. | IMAGE | Yes | - |
| `garment` | Image of the garment to apply. | IMAGE | Yes | - |
| `prompt` | Optional natural-language styling instruction (e.g. how the garment should fit). Default is an empty string. | STRING | No | - |
| `seed` | The random seed used for creating the noise. Default: 0. | INT | No | 0 to 18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resulting image showing the person wearing the provided garment. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxVTONode/en.md)

***

**Source fingerprint (SHA-256):** `5e0777dedcbd6275e31a16f6f5d78f4166147266c0c88531c5843a027702e594`


# GeminiImage2Node - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiImage2Node

Generate or edit images synchronously through the Google Vertex AI Gemini API.

Generate or edit images synchronously through the Google Vertex AI Gemini API. You provide a text prompt and can optionally attach reference images or Gemini input files. The node returns the generated image and, depending on the selected response mode, a text response.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt describing the image to generate or the edits to apply. Include any constraints, styles, or details the model should follow. The prompt must contain at least one character after whitespace is removed. | STRING | Yes | N/A |
| `model` | The Gemini model to use for generation. The "Nano Banana 2 (Gemini 3.1 Flash Image)" option is sent as `gemini-3.1-flash-image`; "gemini-3-pro-image-preview" is sent as `gemini-3-pro-image`. | COMBO | Yes | "gemini-3-pro-image-preview"<br />"Nano Banana 2 (Gemini 3.1 Flash Image)" |
| `seed` | When the seed is fixed to a specific value, the model makes a best effort to provide the same response for repeated requests. Deterministic output isn't guaranteed. Also, changing the model or parameter settings, such as the temperature, can cause variations in the response even when you use the same seed value. By default, a random seed value is used. Default: 42. | INT | Yes | 0 to 18446744073709551615 |
| `aspect_ratio` | If set to 'auto', matches your input image's aspect ratio; if no image is provided, a 16:9 square is usually generated. Default: "auto". | COMBO | Yes | "auto"<br />"1:1"<br />"2:3"<br />"3:2"<br />"3:4"<br />"4:3"<br />"4:5"<br />"5:4"<br />"9:16"<br />"16:9"<br />"21:9" |
| `resolution` | Target output resolution. For 2K/4K the native Gemini upscaler is used. | COMBO | Yes | "1K"<br />"2K"<br />"4K" |
| `response_modalities` | Choose 'IMAGE' for image-only output, or 'IMAGE+TEXT' to return both the generated image and a text response. Advanced setting. | COMBO | Yes | "IMAGE+TEXT"<br />"IMAGE" |
| `images` | Optional reference image(s). To include multiple images, use the Batch Images node (up to 14). | IMAGE | No | N/A |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Generate Content Input Files node. | GEMINI\_INPUT\_FILES | No | N/A |
| `system_prompt` | Foundational instructions that dictate an AI's behavior. Default: a pre-defined system prompt for image generation. Advanced setting. | STRING | No | N/A |

**Constraints:**

* The `images` input supports a maximum of 14 images. If more are provided, an error is raised.
* When more than 10 images are provided, the first 10 are uploaded as URL references and the remaining images are sent inline in the request.
* The `files` input must be connected to a node that outputs the `GEMINI_INPUT_FILES` data type.
* When `response_modalities` is set to `"IMAGE"`, only the image is returned and the text output is empty.
* The `prompt` input is validated and must contain at least one character after whitespace is removed.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The image generated or edited by the Gemini model. | IMAGE |
| `string` | The text response from the model. This output is empty if `response_modalities` is set to `"IMAGE"`. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiImage2Node/en.md)

***

**Source fingerprint (SHA-256):** `02293dad786d4b441da3174fa76f6c5847f122d294bd7e1f765ffd72420034a4`


# GeminiImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiImageNode

The GeminiImage node generates text and image responses from Google's Gemini AI models.

The GeminiImage node generates text and image responses from Google's Gemini AI models. It allows you to provide multimodal inputs including text prompts, images, and files to create coherent text and image outputs. The node handles all API communication and response parsing with the latest Gemini models.

## Inputs

| Parameter | Description | Data Type | Input Type | Default | Range |
| - | - | - | - | - | - |
| `prompt` | Text prompt for generation | STRING | required | "" | - |
| `model` | The Gemini model to use for generating responses | COMBO | required | gemini\_2\_5\_flash\_image\_preview | Available Gemini models<br />Options extracted from GeminiImageModel enum |
| `seed` | When seed is fixed to a specific value, the model makes a best effort to provide the same response for repeated requests. Deterministic output isn't guaranteed. Also, changing the model or parameter settings, such as the temperature, can cause variations in the response even when you use the same seed value. By default, a random seed value is used | INT | required | 42 | 0 to 18446744073709551615 |
| `images` | Optional image(s) to use as context for the model. To include multiple images, you can use the Batch Images node | IMAGE | optional | None | - |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Generate Content Input Files node | GEMINI\_INPUT\_FILES | optional | None | - |

*Note: The node includes hidden parameters (`auth_token`, `comfy_api_key`, `unique_id`) that are automatically handled by the system and do not require user input.*

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated image response from the Gemini model | IMAGE |
| `STRING` | The generated text response from the Gemini model | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiImageNode/en.md)


# GeminiNanoBanana2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiNanoBanana2

The Nano Banana 2 node generates or edits images synchronously via the Google Vertex API using the Gemini 3.1 Flash Image model.

The Nano Banana 2 node generates or edits images synchronously via the Google Vertex API using the Gemini 3.1 Flash Image model. It sends a text prompt, along with optional reference images or files, and returns the generated image, any accompanying text, and optionally an image from the model's thinking process. This node is marked as deprecated.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt describing the image to generate or the edits to apply. Include any constraints, styles, or details the model should follow. Cannot be empty or whitespace only. (default: empty) | STRING | Yes | N/A |
| `model` | The Gemini model to use for image generation. | COMBO | Yes | "Nano Banana 2 (Gemini 3.1 Flash Image)" |
| `seed` | When the seed is fixed to a specific value, the model makes a best effort to provide the same response for repeated requests. Deterministic output isn't guaranteed. Also, changing the model or parameter settings, such as the temperature, can cause variations in the response even when you use the same seed value. By default, a random seed value is used. (default: 42) | INT | Yes | 0 to 18446744073709551615 |
| `aspect_ratio` | If set to 'auto', matches your input image's aspect ratio; if no image is provided, a 16:9 square is usually generated. (default: "auto") | COMBO | Yes | "auto"<br />"1:1"<br />"2:3"<br />"3:2"<br />"3:4"<br />"4:3"<br />"4:5"<br />"5:4"<br />"9:16"<br />"16:9"<br />"21:9" |
| `resolution` | Target output resolution. For 2K/4K the native Gemini upscaler is used. | COMBO | Yes | "1K"<br />"2K"<br />"4K" |
| `response_modalities` | Determines the type of content the model returns: "IMAGE" returns only an image, "IMAGE+TEXT" also returns text. (advanced) | COMBO | Yes | "IMAGE"<br />"IMAGE+TEXT" |
| `thinking_level` | Controls the depth of the model's reasoning process. | COMBO | Yes | "MINIMAL"<br />"HIGH" |
| `images` | Optional reference image(s). To include multiple images, use the Batch Images node (up to 14). | IMAGE | No | 1 to 14 images |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Generate Content Input Files node. | CUSTOM | No | N/A |
| `system_prompt` | Foundational instructions that dictate an AI's behavior. (default: a preset prompt that instructs the model to always produce an image) (advanced) | STRING | No | N/A |

**Note:** The `images` input supports a maximum of 14 images. If more are provided, the node raises an error. The `prompt` input must not be empty or whitespace-only.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The primary image generated or edited by the model. | IMAGE |
| `string` | Any text content returned by the model. | STRING |
| `thought_image` | First image from the model's thinking process. Only available with `thinking_level` set to HIGH and the IMAGE+TEXT modality. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiNanoBanana2/en.md)

***

**Source fingerprint (SHA-256):** `d781c92f04d420985f8a5a593eb5f28f1f7b2af13abd11f2a7f6f285edcd9900`


# GeminiNanoBanana2V2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiNanoBanana2V2

This node generates or edits images by sending a text prompt to Google's Vertex AI API through Gemini image models.

This node generates or edits images by sending a text prompt to Google's Vertex AI API through Gemini image models. It creates new images from a description or modifies existing images using optional reference images.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Selects the Gemini image model to use. The chosen model determines the available resolution options and model-specific inputs. | DYNAMIC\_COMBO | Yes | `"Nano Banana 2 (Gemini 3.1 Flash Image)"`<br />`"Nano Banana 2 Lite"` |
| `prompt` | Text prompt describing the image to generate or the edits to apply. Include any constraints, styles, or details the model should follow. Must not be empty. (default: empty) | STRING | Yes | N/A |
| `seed` | When the seed is fixed to a specific value, the model makes a best effort to provide the same response for repeated requests. Deterministic output isn't guaranteed. Also, changing the model or parameter settings, such as the temperature, can cause variations in the response even when you use the same seed value. By default, a random seed value is used. (default: 42) | INT | Yes | 0 to 18446744073709551615 |
| `response_modalities` | Determines the response format. IMAGE returns only an image; IMAGE+TEXT returns an image and a text response. (default: IMAGE) Advanced parameter. | COMBO | Yes | `"IMAGE"`<br />`"IMAGE+TEXT"` |
| `system_prompt` | Foundational instructions that dictate an AI's behavior. Defaults to a built-in prompt that instructs the model to always produce an image. Advanced parameter. | STRING | No | N/A |
| `temperature` | Controls randomness in generation. Lower is more focused/deterministic. (default: 1.0) Advanced parameter. | FLOAT | No | 0.0 to 2.0 (step 0.01) |
| `top_p` | Nucleus sampling threshold. Lower is more focused, higher more diverse. (default: 0.95) Advanced parameter. | FLOAT | No | 0.0 to 1.0 (step 0.01) |

### Nano Banana 2 (Gemini 3.1 Flash Image) Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `aspect_ratio` | If set to 'auto', matches your input image's aspect ratio; if no image is provided, a 16:9 square is usually generated. (default: auto) | COMBO | Yes | `"auto"`<br />`"1:1"`<br />`"2:3"`<br />`"3:2"`<br />`"3:4"`<br />`"4:3"`<br />`"4:5"`<br />`"5:4"`<br />`"9:16"`<br />`"16:9"`<br />`"21:9"`<br />`"1:4"`<br />`"4:1"`<br />`"8:1"`<br />`"1:8"` |
| `resolution` | Target output resolution. | COMBO | Yes | `"1K"`<br />`"2K"`<br />`"4K"` |
| `thinking_level` | Selects the thinking level used by the model. | COMBO | Yes | `"MINIMAL"`<br />`"HIGH"` |

### Nano Banana 2 Lite Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `aspect_ratio` | If set to 'auto', matches your input image's aspect ratio; if no image is provided, a 16:9 square is usually generated. (default: auto) | COMBO | Yes | `"auto"`<br />`"1:1"`<br />`"2:3"`<br />`"3:2"`<br />`"3:4"`<br />`"4:3"`<br />`"4:5"`<br />`"5:4"`<br />`"9:16"`<br />`"16:9"`<br />`"21:9"`<br />`"1:4"`<br />`"4:1"`<br />`"8:1"`<br />`"1:8"` |
| `resolution` | Target output resolution. | COMBO | Yes | `"1K"` |
| `thinking_level` | Selects the thinking level used by the model. | COMBO | Yes | `"MINIMAL"`<br />`"HIGH"` |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Optional reference image(s). Up to 14 images total. Growable slot: connect `image_1` through `image_14`. | IMAGE | No | 0 to 14 images |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Generate Content Input Files node. | GEMINI\_INPUT\_FILES | No | N/A |

**Note:** A maximum of 14 reference images can be connected to the `images` input; exceeding this limit raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated or edited image. | IMAGE |
| `STRING` | A text description or caption generated by the model. Empty when no text is returned, such as when `response_modalities` is set to `IMAGE`. | STRING |
| `thought_image` | First image from the model's thinking process. Only available with `thinking_level` HIGH and IMAGE+TEXT modality. | IMAGE |

**Note:** The `STRING` output is empty when `response_modalities` is set to `IMAGE`. If the model does not generate an image in this mode, the node raises an error suggesting switching to IMAGE+TEXT to view the model's reasoning.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiNanoBanana2V2/en.md)

***

**Source fingerprint (SHA-256):** `347d28aeb46aa91f7515a31c385a3e3f805a1861116a21dd2ef6575ab7fd4f3e`


# GrokImageEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokImageEditNode

The Grok Image Edit node modifies an existing image based on a text prompt.

The Grok Image Edit node modifies an existing image based on a text prompt. It sends the input image(s) and your description to the Grok API and returns one or more newly generated images that follow the prompt. This node is marked as deprecated.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The specific AI model to use for image editing. | COMBO | Yes | `"grok-imagine-image-quality"`<br />`"grok-imagine-image-pro"`<br />`"grok-imagine-image"` |
| `image` | The input image(s) to be edited. | IMAGE | Yes | |
| `prompt` | The text prompt used to generate the image. Multiline text; must contain at least one non-whitespace character. | STRING | Yes | |
| `resolution` | The resolution for the output image. | COMBO | Yes | `"1K"`<br />`"2K"` |
| `number_of_images` | Number of edited images to generate (default: 1). | INT | Yes | 1 to 10 |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). | INT | Yes | 0 to 2147483647 |
| `aspect_ratio` | The aspect ratio for the output image. Only allowed when multiple images are connected to the image input (default: "auto"). | COMBO | No | `"auto"`<br />`"1:1"`<br />`"2:3"`<br />`"3:2"`<br />`"3:4"`<br />`"4:3"`<br />`"9:16"`<br />`"16:9"`<br />`"9:19.5"`<br />`"19.5:9"`<br />`"9:20"`<br />`"20:9"`<br />`"1:2"`<br />`"2:1"` |

**Important constraints:**

* The `image` input supports up to 3 images, except when using the `grok-imagine-image-pro` model, which supports only 1 input image.
* The `aspect_ratio` parameter can only be set to a custom value (not "auto") when multiple images are connected to the `image` input. Setting a custom aspect ratio with a single input image will cause an error.
* The `prompt` must contain at least one non-whitespace character.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The edited image(s) generated by the node. If more than one image is generated, the images are concatenated into a single batch. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokImageEditNode/en.md)

***

**Source fingerprint (SHA-256):** `e2ace07d10901c4e57086da8e3294a5d04e379103e9740131f5355cd4b07625d`


# GrokImageEditNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokImageEditNodeV2

Modify one or more existing images based on a text prompt.

Modify one or more existing images based on a text prompt. The node sends the connected reference image(s) and the prompt to the Grok image editing API using the selected model, then returns the edited image(s).

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Grok image model to use. The sub-parameters shown below change depending on the selected model. | DYNAMIC\_COMBO | Yes | "grok-imagine-image-2.0"<br />"grok-imagine-image-quality"<br />"grok-imagine-image-pro"<br />"grok-imagine-image" |
| `prompt` | The text prompt used to generate the image. (default: "") | STRING | Yes | N/A |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. (default: 0) | INT | Yes | 0 to 2147483647 |

### grok-imagine-image-2.0 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `resolution` | Output resolution of the edited images. | COMBO | Yes | "1K"<br />"2K" |
| `number_of_images` | Number of edited images to generate. (default: 1) | INT | Yes | 1 to 10 |
| `quality` | Quality level of the generated images. | COMBO | Yes | "medium"<br />"low" |
| `aspect_ratio` | Aspect ratio of the edited image. (default: "auto") | COMBO | Yes | "auto"<br />"1:1"<br />"2:3"<br />"3:2"<br />"3:4"<br />"4:3"<br />"9:16"<br />"16:9"<br />"9:19.5"<br />"19.5:9"<br />"9:20"<br />"20:9"<br />"1:2"<br />"2:1" |

### grok-imagine-image-quality and grok-imagine-image Inputs

Shared by grok-imagine-image-quality and grok-imagine-image.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `resolution` | Output resolution of the edited images. | COMBO | Yes | "1K"<br />"2K" |
| `number_of_images` | Number of edited images to generate. (default: 1) | INT | Yes | 1 to 10 |
| `aspect_ratio` | Only allowed when multiple images are connected. (default: "auto") | COMBO | Yes | "auto"<br />"1:1"<br />"2:3"<br />"3:2"<br />"3:4"<br />"4:3"<br />"9:16"<br />"16:9"<br />"9:19.5"<br />"19.5:9"<br />"9:20"<br />"20:9"<br />"1:2"<br />"2:1" |

### grok-imagine-image-pro Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `resolution` | Output resolution of the edited images. | COMBO | Yes | "1K"<br />"2K" |
| `number_of_images` | Number of edited images to generate. (default: 1) | INT | Yes | 1 to 10 |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Growable slot: connect 1 to N reference images to edit. The slots use the template names `image_1`, `image_2`, `image_3`; the maximum number of slots depends on the selected model. | IMAGE | Yes | 1 image for `grok-imagine-image-pro`<br />1 to 3 images for `grok-imagine-image-2.0`, `grok-imagine-image-quality`, and `grok-imagine-image` |

**Note on constraints:**

* `prompt` must contain at least 1 non-whitespace character.
* At least one reference image is required for editing; the node raises an error if no image is connected.
* The maximum number of input images is 1 for `grok-imagine-image-pro` and 3 for `grok-imagine-image-2.0`, `grok-imagine-image-quality`, and `grok-imagine-image`. Connecting more images than the model supports raises an error.
* The image limit counts every image in the connected inputs, so a batch containing several images counts as several images toward the limit.
* For `grok-imagine-image-quality` and `grok-imagine-image`, a custom `aspect_ratio` (anything other than "auto") is only allowed when multiple images are connected. With a single image, `aspect_ratio` must be "auto".
* For `grok-imagine-image-2.0`, `aspect_ratio` can be set freely even with a single image.
* The `quality` sub-parameter is only available with `grok-imagine-image-2.0`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The edited image(s) returned by the Grok API. If a single image is generated, it is returned directly. If multiple images are generated, they are concatenated into a single batch tensor. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokImageEditNodeV2/en.md)

***

**Source fingerprint (SHA-256):** `7d75b1cb8405c5024567b1119bcbd5e4b318152605f74b62bdd5173dda75949f`


# GrokImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokImageNode

The Grok Image node generates one or more images from a text description using the Grok AI model.

The Grok Image node generates one or more images from a text description using the Grok AI model. It sends your prompt to an external service and returns the generated images as tensors that can be used in your workflow.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The specific Grok model to use for image generation. Different models may offer varying quality, speed, or features. | COMBO | Yes | `"grok-imagine-image-2.0"`<br />`"grok-imagine-image-quality"`<br />`"grok-imagine-image-pro"`<br />`"grok-imagine-image"` |
| `prompt` | The text prompt used to generate the image. This description guides the AI on what to create. Must be at least 1 character long (whitespace-only text is not accepted). | STRING | Yes | N/A |
| `aspect_ratio` | The desired width-to-height ratio for the generated image. | COMBO | Yes | `"1:1"`<br />`"2:3"`<br />`"3:2"`<br />`"3:4"`<br />`"4:3"`<br />`"9:16"`<br />`"16:9"`<br />`"9:19.5"`<br />`"19.5:9"`<br />`"9:20"`<br />`"20:9"`<br />`"1:2"`<br />`"2:1"` |
| `number_of_images` | Number of images to generate (default: 1). | INT | Yes | 1 to 10 |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). | INT | Yes | 0 to 2147483647 |
| `resolution` | The desired output resolution for the generated images (default: "1K"). | COMBO | No | `"1K"`<br />`"2K"` |
| `quality` | Quality level, supported only by the `grok-imagine-image-2.0` model (default: "medium"; "low" is one of the available options). For all other models, this setting is ignored. | COMBO | No | Multiple options available |

**Note:** The `seed` parameter is primarily used to control when the node re-executes within a workflow. Due to the nature of the external AI service, the generated images will not be reproducible or identical across runs, even with an identical seed.

**Note on pricing:** The cost of generating images depends on the selected `model`, `resolution`, `quality`, and `number_of_images`. For the `grok-imagine-image-2.0` model, "low" quality costs $0.04 per image at 1K resolution and $0.06 per image at 2K resolution; other quality levels cost $0.06 per image at 1K and $0.08 per image at 2K. The `grok-imagine-image-quality` model costs $0.05 per image at 1K resolution and $0.07 per image at 2K resolution. The `grok-imagine-image-pro` model costs $0.07 per image. The `grok-imagine-image` model costs $0.02 per image.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated image or a batch of images. If `number_of_images` is 1, a single image tensor is returned. If greater than 1, a batch of image tensors is returned. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokImageNode/en.md)

***

**Source fingerprint (SHA-256):** `a89f5df0d4827f45013f1af92541d36b5b8c8edc8626e07af4fe2d85ee5486e7`


# HeyGenTextToSpeechNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HeyGenTextToSpeechNode

Synthesize speech audio from text using HeyGen's Starfish TTS engine.

Synthesize speech audio from text using HeyGen's Starfish TTS engine. This node includes HeyGen's most popular voices across 17 languages.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | Text to synthesize (up to 5000 characters). The generated speech must be at least 1 second long. | STRING | Yes | 1 to 5000 characters |
| `voice` | Voice to use (curated from HeyGen's most popular Starfish-compatible voices). | STRING | Yes | Multiple options available |
| `custom_voice_id` | Optional HeyGen voice ID. When set, overrides the voice selected above. The voice must support the Starfish engine (default: empty). | STRING | No | Any valid HeyGen voice ID |
| `speed` | Speech speed multiplier (default: 1.0). | FLOAT | No | 0.5 to 2.0 (step: 0.05) |
| `ssml` | Treat the text as SSML markup (for pauses, emphasis, and pronunciation control) (default: False). | BOOLEAN | No | True / False |
| `seed` | Not sent to HeyGen; change it to force a re-run (default: 42). | INT | No | 0 to 2147483647 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `AUDIO` | The synthesized speech audio generated from the input text. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HeyGenTextToSpeechNode/en.md)

***

**Source fingerprint (SHA-256):** `82300626657db8ab16e96ae96b7dfe3291b77bf75efec35971dc772e5123cce7`


# HitPawGeneralImageEnhance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HitPawGeneralImageEnhance

This node enhances low-resolution images by upscaling them to super-resolution while removing artifacts and noise.

This node enhances low-resolution images by upscaling them to super-resolution while removing artifacts and noise. It sends the image to an external API for processing, and it can automatically adjust the input size to stay within the allowed output limit. The maximum allowed output size is 32 megapixels.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The enhancement model to use. The `generative_portrait` model is optimized for portraits, while `generative` is a general-purpose model. | COMBO | Yes | `"generative_portrait"`<br />`"generative"` |
| `image` | The input image to be enhanced. | IMAGE | Yes | - |
| `upscale_factor` | The factor by which to upscale the image's dimensions. A factor of 1 means no upscaling, 2 doubles the dimensions, and 4 quadruples them. | COMBO | Yes | `1`<br />`2`<br />`4` |
| `auto_downscale` | Automatically downscale input image if output would exceed the limit. (default: `False`) | BOOLEAN | No | - |

**Note:** The node raises an error if the calculated output size (input width × upscale\_factor × input height × upscale\_factor) exceeds 32,000,000 pixels (32MP) and `auto_downscale` is disabled. When `auto_downscale` is enabled, the node automatically reduces the input image size or the upscale factor (or both) so the output fits within the 32MP limit. The selected `model` and `upscale_factor` are combined into the model name sent to the service.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The enhanced and upscaled output image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HitPawGeneralImageEnhance/en.md)

***

**Source fingerprint (SHA-256):** `eb9adc1ac94c5fb943e3dd8f6617b21c5d3203f0d9ddb93ba1c9d4b4e63bd421`


# IdeogramPImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/IdeogramPImage

Ideogram & Pruna P-Image generates images from a text prompt using Ideogram's fast text-to-image model, which is known for strong typography and photorealism.

Ideogram & Pruna P-Image generates images from a text prompt using Ideogram's fast text-to-image model, which is known for strong typography and photorealism. It also supports Ideogram 4.0 structured JSON captions for exact control over text strings, colors, and layout. The node returns the generated image(s) along with the final prompt the image was actually generated from.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt. Also accepts an Ideogram 4.0 structured JSON caption (exact colors as #RRGGBB hexes, exact text strings, bounding-box layout) — set prompt\_upsampling to OFF to use it verbatim. Must not be empty. (default: "") | STRING | Yes | Any non-empty text |
| `quality` | Speed/price/quality tier. MEDIUM is the everyday default; HIGH for complex prompts, fine detail and difficult text; VERY\_LOW/LOW for drafts at scale. Difficult text renders poorly below MEDIUM. (default: "MEDIUM") | COMBO | Yes | "VERY\_LOW"<br />"LOW"<br />"MEDIUM"<br />"HIGH" |
| `resolution` | Output size class (exact pixels follow the aspect ratio, e.g. 16:9 gives 1280x720 at 1K and 2560x1440 at 2K). Prefer HIGH + 2K for crisp typography. (default: "1K") | COMBO | Yes | "1K"<br />"2K" |
| `aspect_ratio` | The aspect ratio for image generation. (default: "1:1") | COMBO | Yes | "1:3"<br />"3:1"<br />"1:2"<br />"2:1"<br />"9:16"<br />"16:9"<br />"10:16"<br />"16:10"<br />"2:3"<br />"3:2"<br />"3:4"<br />"4:3"<br />"4:5"<br />"5:4"<br />"1:1" |
| `prompt_upsampling` | Expands short prompts into a detailed structured caption before generation (the rewritten prompt is returned as final\_prompt). Set OFF when supplying your own JSON caption or exact wording. (default: "AUTO") | COMBO | Yes | "AUTO"<br />"ON"<br />"OFF" |
| `seed` | Seed for reproducible generation. With prompt\_upsampling OFF, the same seed and settings return the same image; with ON/AUTO the prompt rewrite varies per run — reproduce a result by reusing its final\_prompt output with prompt\_upsampling OFF and the same seed. (default: 42) | INT | No | 0 to 2147483647 |

**Note on constraints:** The prompt must contain at least one non-whitespace character, otherwise the node fails. Set `prompt_upsampling` to OFF when supplying your own structured JSON caption or exact wording. When `prompt_upsampling` is ON or AUTO, the prompt is rewritten before generation, so the same seed may not reproduce the same image; to reproduce an image, reuse its `final_prompt` output with `prompt_upsampling` OFF and the same seed.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated image(s) returned as a batch of images. If Ideogram's content safety filter blocks the generation, an error is raised instead. | IMAGE |
| `final_prompt` | The prompt the image was actually generated from (the rewritten structured caption when prompt\_upsampling ran, else your prompt). Feed it back with prompt\_upsampling OFF and the same seed to reproduce this image. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/IdeogramPImage/en.md)

***

**Source fingerprint (SHA-256):** `6b014c2f097c49b5930f38869a4e2da0ebb19863763ae5817d6e566a36d2b8e8`


# IdeogramV3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/IdeogramV3

The Ideogram V3 node generates images using the Ideogram V3 model.

The Ideogram V3 node generates images using the Ideogram V3 model. It supports both regular image generation from text prompts and image editing when both an image and mask are provided. The node offers various controls for aspect ratio, resolution, generation speed, and optional character reference images.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the image generation or editing (default: empty) | STRING | Yes | - |
| `image` | Optional reference image for image editing | IMAGE | No | - |
| `mask` | Optional mask for inpainting (white areas will be replaced) | MASK | No | - |
| `aspect_ratio` | The aspect ratio for image generation. Ignored if resolution is not set to Auto (default: "1:1") | COMBO | No | "1:1"<br />"1:3"<br />"3:1"<br />"1:2"<br />"2:1"<br />"9:16"<br />"16:9"<br />"10:16"<br />"16:10"<br />"2:3"<br />"3:2"<br />"3:4"<br />"4:3"<br />"4:5"<br />"5:4" |
| `resolution` | The resolution for image generation. If not set to Auto, this overrides the aspect\_ratio setting (default: "Auto") | COMBO | No | "Auto"<br />"512x1536"<br />"576x1408"<br />"576x1472"<br />"576x1536"<br />"640x1344"<br />"640x1408"<br />"640x1472"<br />"640x1536"<br />"704x1152"<br />"704x1216"<br />"704x1280"<br />"704x1344"<br />"704x1408"<br />"704x1472"<br />"736x1312"<br />"768x1088"<br />"768x1216"<br />"768x1280"<br />"768x1344"<br />"800x1280"<br />"832x960"<br />"832x1024"<br />"832x1088"<br />"832x1152"<br />"832x1216"<br />"832x1248"<br />"864x1152"<br />"896x960"<br />"896x1024"<br />"896x1088"<br />"896x1120"<br />"896x1152"<br />"960x832"<br />"960x896"<br />"960x1024"<br />"960x1088"<br />"1024x832"<br />"1024x896"<br />"1024x960"<br />"1024x1024"<br />"1088x768"<br />"1088x832"<br />"1088x896"<br />"1088x960"<br />"1120x896"<br />"1152x704"<br />"1152x832"<br />"1152x864"<br />"1152x896"<br />"1216x704"<br />"1216x768"<br />"1216x832"<br />"1248x832"<br />"1280x704"<br />"1280x768"<br />"1280x800"<br />"1312x736"<br />"1344x640"<br />"1344x704"<br />"1344x768"<br />"1408x576"<br />"1408x640"<br />"1408x704"<br />"1472x576"<br />"1472x640"<br />"1472x704"<br />"1536x512"<br />"1536x576"<br />"1536x640" |
| `magic_prompt_option` | Determine if MagicPrompt should be used in generation (default: "AUTO") | COMBO | No | "AUTO"<br />"ON"<br />"OFF" |
| `seed` | Random seed for generation (default: 0) | INT | No | 0-2147483647 |
| `num_images` | Number of images to generate (default: 1) | INT | No | 1-8 |
| `rendering_speed` | Controls the trade-off between generation speed and quality (default: "DEFAULT") | COMBO | No | "DEFAULT"<br />"TURBO"<br />"QUALITY" |
| `character_image` | Image to use as character reference | IMAGE | No | - |
| `character_mask` | Optional mask for character reference image | MASK | No | - |

**Parameter Constraints:**

* When both `image` and `mask` are provided, the node switches to editing mode
* If only one of `image` or `mask` is provided, an error will occur
* `character_mask` requires `character_image` to be present
* The `aspect_ratio` parameter is ignored when `resolution` is not set to "Auto"
* White areas in the mask will be replaced during inpainting
* Character mask and character image must be the same size

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated or edited image(s) | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/IdeogramV3/en.md)

***

**Source fingerprint (SHA-256):** `d5005a9cdbdad79762dfd24eaa73e6c293d28b72813e96883ecdfccb8339ca75`


# IdeogramV4 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/IdeogramV4

Generates images using the Ideogram 4.0 model from a text prompt.

Generates images using the Ideogram 4.0 model from a text prompt. This node sends your text description to the Ideogram API and returns the generated image as an output tensor.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for the image generation. | STRING | Yes | No restrictions |
| `resolution` | The resolution of the generated image. Default: "Auto" which lets the model choose the best resolution. | COMBO | Yes | `"Auto"`<br />`"2048x2048 (1:1)"`<br />`"1440x2880 (1:2)"`<br />`"2880x1440 (2:1)"`<br />`"1664x2496 (2:3)"`<br />`"2496x1664 (3:2)"`<br />`"1792x2240 (4:5)"`<br />`"2240x1792 (5:4)"`<br />`"1440x2560 (9:16)"`<br />`"2560x1440 (16:9)"`<br />`"1600x2560 (5:8)"`<br />`"2560x1600 (8:5)"`<br />`"1728x2304 (3:4)"`<br />`"2304x1728 (4:3)"`<br />`"1296x3168 (9:22)"`<br />`"3168x1296 (22:9)"`<br />`"1152x2944 (9:23)"`<br />`"2944x1152 (23:9)"`<br />`"1248x3328 (3:8)"`<br />`"3328x1248 (8:3)"`<br />`"1280x3072 (5:12)"`<br />`"3072x1280 (12:5)"` |
| `rendering_speed` | Controls the trade-off between generation speed and quality. Default: "DEFAULT". | COMBO | Yes | `"DEFAULT"`<br />`"TURBO"`<br />`"QUALITY"` |
| `seed` | Seed for reproducible generation. Default: 0. | INT | Yes | Min: 0<br />Max: 2147483647 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated image as a tensor. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/IdeogramV4/en.md)

***

**Source fingerprint (SHA-256):** `47a486824211d34b9109c5038b0b094d192c4e243c0a6c4ceab13af3bdabe6e4`


# KlingImageGenerationNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingImageGenerationNode

Kling Image Generation Node generates images from text prompts with the option to use a reference image for guidance.

Kling Image Generation Node generates images from text prompts with the option to use a reference image for guidance. It creates one or more images based on your text description and reference settings, then returns the generated images as output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Positive text prompt. Required, must be between 1 and 500 characters. | STRING | Yes | Maximum 500 characters |
| `negative_prompt` | Negative text prompt. | STRING | Yes | Maximum 500 characters |
| `image_type` | Image reference type selection (advanced). Required when a reference image is provided. | COMBO | Yes | `"subject_reference"`<br />`"style_reference"` |
| `image_fidelity` | Reference intensity for user-uploaded images (default: 0.5, advanced) | FLOAT | Yes | 0.0 - 1.0 |
| `human_fidelity` | Subject reference similarity (default: 0.45, advanced) | FLOAT | Yes | 0.0 - 1.0 |
| `model_name` | Model selection for image generation (default: "kling-v3") | COMBO | Yes | `"kling-v3"` |
| `aspect_ratio` | Aspect ratio for generated images (default: "16:9") | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"`<br />`"21:9"`<br />`"9:21"` |
| `n` | Number of generated images (default: 1) | INT | Yes | 1 - 9 |
| `image` | Optional reference image | IMAGE | No | - |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0) | INT | No | 0 - 2147483647 |

**Parameter Constraints:**

* The `image` parameter is optional. When a reference image is provided, the `image_type` parameter determines whether the reference is used as a subject reference or a style reference.
* When no reference image is provided, the reference-related settings (`image_type`, `image_fidelity`, `human_fidelity`) have no effect on the result.
* `prompt` and `negative_prompt` have a maximum length of 500 characters.
* The `seed` parameter is optional and does not guarantee deterministic results.
* The `n` parameter controls how many images are produced and also determines the price of the request.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | Generated image(s) based on the input parameters. When `n` is greater than 1, multiple images are returned as a batch. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingImageGenerationNode/en.md)

***

**Source fingerprint (SHA-256):** `fd344519346f63ac03975b93f03725749ed9697245d6dfa2378884c59a5325cd`


# KlingOmniProImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProImageNode

The Kling Omni Image (Pro) node creates or edits images using the latest Kling AI model.

The Kling Omni Image (Pro) node creates or edits images using the latest Kling AI model. It generates images based on a text description and can optionally use reference images to guide the style or content. The node sends a request to an external API, which processes the task and returns the final image(s).

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The specific Kling AI model to use for image generation. | COMBO | Yes | `"kling-v3-omni"`<br />`"kling-image-o1"` |
| `prompt` | A text prompt describing the image content. This can include both positive and negative descriptions. The text must be between 1 and 2500 characters long. You can use `@image`, `@image1`, `@image2`, etc. or `@video`, `@video1`, `@video2`, etc. to reference uploaded images or videos in the prompt. | STRING | Yes | - |
| `resolution` | The target resolution for the generated image. Note: 4K resolution is not supported for the `kling-image-o1` model. | COMBO | Yes | `"1K"`<br />`"2K"`<br />`"4K"` |
| `aspect_ratio` | The desired aspect ratio (width to height) for the generated image. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"`<br />`"3:2"`<br />`"2:3"`<br />`"21:9"` |
| `series_amount` | Generate a series of images. This feature is not supported for the `kling-image-o1` model. (default: "disabled") | COMBO | Yes | `"disabled"`<br />`"2"`<br />`"3"`<br />`"4"`<br />`"5"`<br />`"6"`<br />`"7"`<br />`"8"`<br />`"9"` |
| `reference_images` | Up to 10 additional reference images. Each image must be at least 300 pixels in both width and height, and its aspect ratio must be between 1:2.5 and 2.5:1. | IMAGE | No | - |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | No | 0 to 2147483647 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The final image(s) generated or edited by the Kling AI model. If a series was requested, multiple images are returned as a batch. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProImageNode/en.md)

***

**Source fingerprint (SHA-256):** `923db96e956e0f11c9290478ceb105304893f28d35af9f0e13077ca0f88dff79`


# Krea2ImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Krea2ImageNode

Documentation for Krea2ImageNode node.

## Overview

The Krea 2 Image node generates images using the Krea 2 AI model. It supports two model variants: Medium for expressive illustrations and Large for expressive photorealism, with an additional Medium Turbo option for faster generation. You can optionally include a moodboard and up to 10 image style references to influence the generated image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for the image. | STRING | Yes | N/A |
| `model` | Krea 2 Medium is best for expressive illustrations; Krea 2 Large is best for expressive photorealism. | DICT | Yes | See below |
| `seed` | Random seed for reproducibility (default: 0). | INT | Yes | 0 to 2147483647 |

The `model` parameter is a dictionary with the following sub-parameters:

| Sub-Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Selects the Krea 2 model variant. | STRING | Yes | `"krea 2 medium turbo"`<br />`"krea 2 medium"`<br />`"krea 2 large"` |
| `aspect_ratio` | The aspect ratio for the generated image. | STRING | Yes | N/A |
| `resolution` | The resolution for the generated image. | STRING | Yes | N/A |
| `creativity` | Controls the creativity level of the generation. | FLOAT | Yes | N/A |
| `moodboard_id` | The UUID of a Krea moodboard to influence the image. Must be a valid UUID. | STRING | No | N/A |
| `moodboard_strength` | The strength of the moodboard influence (default: 0.35). | FLOAT | No | N/A |
| `style_reference` | A list of image style references. Each reference must have a `url` (STRING) and `strength` (FLOAT). | LIST | No | 0 to 10 items |

**Constraints:**

* `moodboard_id` must be a valid UUID (e.g., `"123e4567-e89b-12d3-a456-426614174000"`). Copy it from the Krea website.
* `style_reference` accepts a maximum of 10 image style references.
* The `prompt` must be at least 1 character long.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated image as a tensor. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Krea2ImageNode/en.md)

***

**Source fingerprint (SHA-256):** `645b404fe2c7653662803f1630125bdef912429c95d7b3a1268b0e0d7f533277`


# Krea2StyleReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Krea2StyleReferenceNode

The Krea 2 Style Reference node lets you add a reference image to influence the style of a Krea 2 image generation.

The Krea 2 Style Reference node lets you add a reference image to influence the style of a Krea 2 image generation. You can chain multiple style references together (up to 10 total) and feed the combined result into a Krea 2 Image node. Each image you provide is uploaded to ComfyAPI storage and passed as a URL.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Reference image whose style influences the generation. | IMAGE | Yes | - |
| `strength` | Reference strength; negative values invert the style influence (default: 1.0). | FLOAT | Yes | -2.0 to 2.0 (step: 0.05) |
| `style_reference` | Optional incoming chain of style references; this node appends one more. | STYLE\_REF | No | - |

**Note on constraints:** You can chain a maximum of 10 style references in total. If you try to add an 11th reference, the node will raise an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `style_reference` | A list of style reference entries, each containing a URL and strength value. Feed this output into a Krea 2 Image node. | STYLE\_REF |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Krea2StyleReferenceNode/en.md)

***

**Source fingerprint (SHA-256):** `a7e52408245b6a3caaca558c8d4d07d090686f32f5d5c7df77ab07311c9c1c6e`


# LumaImageEditNode2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaImageEditNode2

This node edits an existing image using a text prompt, powered by the Luma UNI-1 model.

This node edits an existing image using a text prompt, powered by the Luma UNI-1 model. It takes a source image and a description of the desired change, then generates a new edited version of the image. You can choose between the `uni-1` and `uni-1-max` models, adjust the style, enable web search, and optionally provide up to 8 reference images.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for editing. Selecting a model reveals the model-specific options below. | DYNAMIC\_COMBO | Yes | `"uni-1"`<br />`"uni-1-max"` |
| `source` | Source image to edit. | IMAGE | Yes | - |
| `prompt` | Description of the desired edit. 1–6000 characters. Default: "" (empty string; the request is invalid until at least one character is entered). | STRING | Yes | 1 to 6000 characters |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. Default: 0. | INT | Yes | 0 to 2147483647 |

### uni-1 and uni-1-max Inputs

These options are shared by both the `uni-1` and `uni-1-max` models.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `style` | Style preset. `"auto"` picks based on the prompt; `"manga"` applies a manga/anime aesthetic and requires a portrait aspect ratio (2:3, 9:16, 1:2, 1:3). Default: `"auto"`. | COMBO | Yes | `"auto"`<br />`"manga"` |
| `web_search` | Search the web for visual references before generating. Default: false. | BOOLEAN | Yes | `true`<br />`false` |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image_ref` | Growable slot: connect up to 8 reference images (`image_1` through `image_8`) for style/content guidance. Optional. | IMAGE | No | 0 to 8 images |

**Notes:**

* The `prompt` must be between 1 and 6000 characters.
* The `style`, `web_search`, and `image_ref` inputs appear when `model` is set to either `"uni-1"` or `"uni-1-max"`.
* Both models support the same model-specific options, including up to 8 reference images.
* The `"manga"` style requires a portrait aspect ratio (2:3, 9:16, 1:2, or 1:3).
* Connecting more than 8 reference images raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The edited image generated by the Luma UNI-1 model, returned in PNG format. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaImageEditNode2/en.md)

***

**Source fingerprint (SHA-256):** `66f62bb2807759edb405c2caeeefe32c341920924e267c32449a620190b9a7ab`


# LumaImageModifyNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaImageModifyNode

Modifies images synchronously based on a text prompt and the original image's aspect ratio.

Modifies images synchronously based on a text prompt and the original image's aspect ratio. This node takes an input image and transforms it according to the provided prompt, using a configurable image weight to control how much the original image is altered.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be modified | IMAGE | Yes | - |
| `prompt` | Prompt for the image generation (default: "") | STRING | Yes | - |
| `image_weight` | Weight of the image; the closer to 1.0, the less the image will be modified (default: 0.1). Internally, this value is inverted (1.0 - image\_weight) and clamped between 0.0 and 0.98. | FLOAT | No | 0.0-0.98 |
| `model` | The Luma model to use for image modification. Different models have different costs. | STRING | Yes | `"photon-flash-1"`<br />`"photon-1"`<br />`"photon"` |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0) | INT | No | 0-18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The modified image generated by the Luma model | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaImageModifyNode/en.md)

***

**Source fingerprint (SHA-256):** `56b13600f6fb8cd6ff80bc8c8184db059273c2ef648630ff1ef10a7ed6b04b7c`


# LumaImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaImageNode

Generates images synchronously based on a text prompt and aspect ratio.

Generates images synchronously based on a text prompt and aspect ratio. This node creates images using text descriptions and allows you to control the image dimensions and style through various reference inputs, including character and style images.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the image generation (default: empty string). Must be at least 3 characters long. | STRING | Yes | - |
| `model` | Model selection for image generation. Different models have different costs. | COMBO | Yes | `photon-flash-1`<br />`photon-1`<br />`photon` |
| `aspect_ratio` | Aspect ratio for the generated image (default: `16:9`) | COMBO | Yes | `16:9`<br />`1:1`<br />`4:3`<br />`3:2`<br />`21:9`<br />`9:16`<br />`3:4`<br />`2:3`<br />`9:21` |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0) | INT | Yes | 0 to 18446744073709551615 |
| `style_image_weight` | Weight of style image. Ignored if no `style_image` is provided (default: 1.0) | FLOAT | No | 0.0 to 1.0 |
| `image_luma_ref` | Luma Reference node connection to influence generation with input images; up to 4 images can be considered. | LUMA\_REF | No | - |
| `style_image` | Style reference image; only 1 image will be used. | IMAGE | No | - |
| `character_image` | Character reference images; can be a batch of multiple, up to 4 images can be considered. | IMAGE | No | - |

**Parameter Constraints:**

* The `prompt` must be at least 3 characters long after stripping whitespace.
* The `image_luma_ref` parameter can accept up to 4 reference images.
* The `character_image` parameter can accept up to 4 character reference images.
* The `style_image` parameter accepts only 1 style reference image.
* The `style_image_weight` parameter is only used when `style_image` is provided.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated image based on the input parameters. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaImageNode/en.md)

***

**Source fingerprint (SHA-256):** `cde0fc1ace28523d658b757d7f829b0d20071bed391964d2d8caa81801265b46`


# LumaImageNode2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaImageNode2

This node generates images from text descriptions using the Luma UNI-1 model.

This node generates images from text descriptions using the Luma UNI-1 model. It takes a text prompt and optional settings like aspect ratio and style, then sends the request to the Luma API to create an image. Two model variants are available: `uni-1` and `uni-1-max`.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text description of the desired image. 1–6000 characters. (default: "") | STRING | Yes | 1 to 6000 characters |
| `model` | Model to use for generation. Selecting a model reveals additional settings for that model. (default: first option, `"uni-1"`) | DYNAMIC\_COMBO | Yes | `"uni-1"`<br />`"uni-1-max"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | Yes | 0 to 2147483647 |

### uni-1 and uni-1-max Inputs

Shared by the `uni-1` and `uni-1-max` model options. These settings appear when either model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `aspect_ratio` | Output image aspect ratio. `"auto"` lets the model pick based on the prompt. (default: `"auto"`) | COMBO | Yes | `"auto"`<br />`"3:1"`<br />`"2:1"`<br />`"16:9"`<br />`"3:2"`<br />`"1:1"`<br />`"2:3"`<br />`"9:16"`<br />`"1:2"`<br />`"1:3"` |
| `style` | Style preset. `"auto"` picks based on the prompt; `"manga"` applies a manga/anime aesthetic and requires a portrait aspect ratio (2:3, 9:16, 1:2, 1:3). (default: `"auto"`) | COMBO | Yes | `"auto"`<br />`"manga"` |
| `web_search` | Search the web for visual references before generating. (default: False) | BOOLEAN | Yes | True / False |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image_ref` | Growable slot: connect 1 to 9 items (e.g. `image_1` to `image_9`). Up to 9 reference images for style/content guidance. | IMAGE | No | Up to 9 images |

**Note:** If `style` is set to `"manga"`, the `aspect_ratio` must be either `"auto"` or one of the portrait ratios `"2:3"`, `"9:16"`, `"1:2"`, `"1:3"`. Using any other ratio with `"manga"` style will cause an error. The maximum number of reference images is 9 for both `uni-1` and `uni-1-max`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaImageNode2/en.md)

***

**Source fingerprint (SHA-256):** `27254fe4627fd340426a68f651cab4513ffb6668cafc0accd17f2c442f7d3125`


# LumaReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaReferenceNode

This node holds an image and weight value for use with the Luma Generate Image node.

This node holds an image and weight value for use with the Luma Generate Image node. It creates a reference chain that can be passed to other Luma nodes to influence image generation. The node can either start a new reference chain or add to an existing one.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Image to use as reference. | IMAGE | Yes | - |
| `weight` | Weight of image reference (default: 1.0). | FLOAT | Yes | 0.0 - 1.0 |
| `luma_ref` | Optional existing Luma reference chain to add to. | LUMA\_REF | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `luma_ref` | The Luma reference chain containing the image and weight. | LUMA\_REF |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaReferenceNode/en.md)

***

**Source fingerprint (SHA-256):** `f7e7789f2f19cac41cb9e55d21f10fef3012b10dcdbd59eb79f97fe5c2a944b7`


# MagnificImageRelightNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MagnificImageRelightNode

The Magnific Image Relight node adjusts the lighting of an input image.

The Magnific Image Relight node adjusts the lighting of an input image. It can apply stylistic lighting based on a text prompt or transfer the lighting characteristics from an optional reference image. The node offers various controls for fine-tuning the brightness, contrast, and overall mood of the final output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image to relight. Exactly one image is required. Minimum dimensions are 160x160 pixels. Aspect ratio must be between 1:3 and 3:1. | IMAGE | Yes | N/A |
| `prompt` | Descriptive guidance for lighting. Supports emphasis notation (1-1.4). Default is an empty string. | STRING | No | N/A |
| `light_transfer_strength` | Intensity of light transfer application. Default: 100. | INT | Yes | 0 to 100 |
| `style` | Stylistic output preference. | COMBO | Yes | `"standard"`<br />`"darker_but_realistic"`<br />`"clean"`<br />`"smooth"`<br />`"brighter"`<br />`"contrasted_n_hdr"`<br />`"just_composition"` |
| `interpolate_from_original` | Restricts generation freedom to match original more closely. Default: False. | BOOLEAN | Yes | N/A |
| `change_background` | Modifies background based on prompt/reference. Default: True. | BOOLEAN | Yes | N/A |
| `preserve_details` | Maintains texture and fine details from original. Default: True. | BOOLEAN | Yes | N/A |
| `advanced_settings` | Fine-tuning options for advanced lighting control. When set to `"enabled"`, additional parameters become available. | DYNAMICCOMBO | Yes | `"disabled"`<br />`"enabled"` |
| `reference_image` | Optional reference image to transfer lighting from. If provided, exactly one image is required. Minimum dimensions are 160x160 pixels. Aspect ratio must be between 1:3 and 3:1. | IMAGE | No | N/A |

**Note on Advanced Settings:** When `advanced_settings` is set to `"enabled"`, the following nested parameters become active:

* `whites`: Adjusts the brightest tones in the image. Range: 0 to 100. Default: 50.
* `blacks`: Adjusts the darkest tones in the image. Range: 0 to 100. Default: 50.
* `brightness`: Overall brightness adjustment. Range: 0 to 100. Default: 50.
* `contrast`: Contrast adjustment. Range: 0 to 100. Default: 50.
* `saturation`: Color saturation adjustment. Range: 0 to 100. Default: 50.
* `engine`: Processing engine selection. Options: `"automatic"`, `"balanced"`, `"cool"`, `"real"`, `"illusio"`, `"fairy"`, `"colorful_anime"`, `"hard_transform"`, `"softy"`.
* `transfer_light_a`: The intensity of light transfer. Options: `"automatic"`, `"low"`, `"medium"`, `"normal"`, `"high"`, `"high_on_faces"`.
* `transfer_light_b`: Also modifies light transfer intensity. Can be combined with the previous control for varied effects. Options: `"automatic"`, `"composition"`, `"straight"`, `"smooth_in"`, `"smooth_out"`, `"smooth_both"`, `"reverse_both"`, `"soft_in"`, `"soft_out"`, `"soft_mid"`, `"style_shift"`, `"strong_shift"`.
* `fixed_generation`: Ensures consistent output with the same settings. Default: True.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The relit image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MagnificImageRelightNode/en.md)

***

**Source fingerprint (SHA-256):** `45fe68b21e1da7c367800915c803ad4cf1c5b80e9a2e91d80cae51b8a9531144`


# MagnificImageSkinEnhancerNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MagnificImageSkinEnhancerNode

The Magnific Image Skin Enhancer node applies specialized AI processing to portrait images to improve skin appearance.

The Magnific Image Skin Enhancer node applies specialized AI processing to portrait images to improve skin appearance. It offers three distinct modes for different enhancement goals: creative for artistic effects, faithful for preserving the original look, and flexible for targeted improvements like lighting or realism. The node uploads the image to an external API for processing and returns the enhanced result.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The portrait image to enhance. | IMAGE | Yes | - |
| `sharpen` | Sharpening intensity level (default: 0). | INT | No | 0 to 100 |
| `smart_grain` | Smart grain intensity level (default: 2). | INT | No | 0 to 100 |
| `mode` | The processing mode to use. `"creative"` is for artistic enhancement, `"faithful"` for preserving the original appearance, and `"flexible"` for targeted optimization. | COMBO | Yes | `"creative"`<br />`"faithful"`<br />`"flexible"` |
| `skin_detail` | Skin detail enhancement level. This input is only available when the `mode` is set to `"faithful"` (default: 80). | INT | No | 0 to 100 |
| `optimized_for` | Enhancement optimization target. This input is only available when the `mode` is set to `"flexible"`. | COMBO | No | `"enhance_skin"`<br />`"improve_lighting"`<br />`"enhance_everything"`<br />`"transform_to_real"`<br />`"no_make_up"` |

**Constraints:**

* The node accepts exactly one input image.
* The input image must have a minimum height and width of 160 pixels.
* The input image aspect ratio must be between 1:3 and 3:1 (non-strict validation).
* The `skin_detail` parameter is only active when `mode` is set to `"faithful"`.
* The `optimized_for` parameter is only active when `mode` is set to `"flexible"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The enhanced portrait image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MagnificImageSkinEnhancerNode/en.md)

***

**Source fingerprint (SHA-256):** `2430cc0fb1d2042a8eda78f7f5a5794fa6b4e555d3957616ae6891374b556a76`


# MagnificImageStyleTransferNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MagnificImageStyleTransferNode

This node applies the visual style from a reference image to your input image.

This node applies the visual style from a reference image to your input image. It uses an external AI service to process the images, allowing you to control the strength of the style transfer and the preservation of the original image's structure.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image to apply style transfer to. | IMAGE | Yes | - |
| `reference_image` | The reference image to extract style from. | IMAGE | Yes | - |
| `prompt` | An optional text prompt to guide the style transfer. | STRING | No | - |
| `style_strength` | Percentage of style strength (default: 100). | INT | No | 0 to 100 |
| `structure_strength` | Maintains the structure of the original image (default: 50). | INT | No | 0 to 100 |
| `flavor` | Style transfer flavor. | COMBO | No | "faithful"<br />"gen\_z"<br />"psychedelia"<br />"detaily"<br />"clear"<br />"donotstyle"<br />"donotstyle\_sharp" |
| `engine` | Processing engine selection. | COMBO | No | "balanced"<br />"definio"<br />"illusio"<br />"3d\_cartoon"<br />"colorful\_anime"<br />"caricature"<br />"real"<br />"super\_real"<br />"softy" |
| `portrait_mode` | Enable portrait mode for facial enhancements. | COMBO | No | "disabled"<br />"enabled" |
| `portrait_style` | Visual style applied to portrait images. This input is only available when `portrait_mode` is set to "enabled". | COMBO | No | "standard"<br />"pop"<br />"super\_pop" |
| `portrait_beautifier` | Facial beautification intensity on portraits. This input is only available when `portrait_mode` is set to "enabled". | COMBO | No | "none"<br />"beautify\_face"<br />"beautify\_face\_max" |
| `fixed_generation` | When disabled, expect each generation to introduce a degree of randomness, leading to more diverse outcomes (default: True). | BOOLEAN | No | - |

**Constraints:**

* Exactly one `image` and one `reference_image` are required.
* Both images must have an aspect ratio between 1:3 and 3:1.
* Both images must have a minimum height and width of 160 pixels.
* The `portrait_style` and `portrait_beautifier` parameters are only active when `portrait_mode` is set to "enabled".

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resulting image after style transfer has been applied. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MagnificImageStyleTransferNode/en.md)

***

**Source fingerprint (SHA-256):** `edffec024ebe7cbf7c42008e14c1b99d6fafcf5b9da62b0b560d194a585dc9ad`


# MagnificImageUpscalerCreativeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MagnificImageUpscalerCreativeNode

This node uses the Magnific AI service to upscale and creatively enhance an image.

This node uses the Magnific AI service to upscale and creatively enhance an image. It allows you to guide the enhancement with a text prompt, choose a specific style to optimize for, and control various aspects of the creative process like detail, resemblance to the original, and stylization strength. The node outputs an upscaled image at your chosen factor (2x, 4x, 8x, or 16x), with a maximum output size of 25.3 megapixels.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be upscaled and enhanced. | IMAGE | Yes | - |
| `prompt` | A text description to guide the creative enhancement of the image. Default is an empty string (no prompt is sent in that case). | STRING | Yes | - |
| `scale_factor` | The factor by which to upscale the image's dimensions. | COMBO | Yes | `"2x"`<br />`"4x"`<br />`"8x"`<br />`"16x"` |
| `optimized_for` | The style or content type to optimize the enhancement process for. | COMBO | Yes | `"standard"`<br />`"soft_portraits"`<br />`"hard_portraits"`<br />`"art_n_illustration"`<br />`"videogame_assets"`<br />`"nature_n_landscapes"`<br />`"films_n_photography"`<br />`"3d_renders"`<br />`"science_fiction_n_horror"` |
| `creativity` | Controls the level of creative interpretation applied to the image (default: 0). | INT | Yes | -10 to 10 |
| `hdr` | The level of definition and detail (default: 0). | INT | Yes | -10 to 10 |
| `resemblance` | The level of resemblance to the original image (default: 0). | INT | Yes | -10 to 10 |
| `fractality` | The strength of the prompt and intricacy per square pixel (default: 0). | INT | Yes | -10 to 10 |
| `engine` | The specific AI engine to use for processing. This is an advanced parameter. | COMBO | Yes | `"automatic"`<br />`"magnific_illusio"`<br />`"magnific_sharpy"`<br />`"magnific_sparkle"` |
| `auto_downscale` | Automatically downscale input image if output would exceed maximum pixel limit (default: False). This is an advanced parameter. | BOOLEAN | Yes | - |

**Constraints:**

* The input `image` must be exactly one image.
* The input image must have a minimum height and width of 160 pixels.
* The input image's aspect ratio must be between 1:3 and 3:1.
* The final output size (input dimensions multiplied by the `scale_factor`) cannot exceed 25,300,000 pixels. If this limit would be exceeded:
  * When `auto_downscale` is enabled, the node automatically reduces the input image size (the additional downscaling is kept to at most 2x) or uses a lower `scale_factor` so the output stays within the limit.
  * When `auto_downscale` is disabled, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The creatively enhanced and upscaled output image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MagnificImageUpscalerCreativeNode/en.md)

***

**Source fingerprint (SHA-256):** `36c38e87f9f1e568c78cf794aeb0a268c6d25d639006eb2cf18ee040d3071ad4`


# MagnificImageUpscalerPreciseV2Node - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MagnificImageUpscalerPreciseV2Node

The Magnific Image Upscale (Precise V2) node performs high-fidelity image upscaling with fine control over sharpness, grain, and detail enhancement.

The Magnific Image Upscale (Precise V2) node performs high-fidelity image upscaling with fine control over sharpness, grain, and detail enhancement. It processes images through an external API, supporting up to a maximum output resolution of 10060×10060 pixels. The node offers different processing styles and can automatically downscale the input if the requested output would exceed the maximum allowed size.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be upscaled. Exactly one image is required. Minimum dimensions are 160x160 pixels. The aspect ratio must be between 1:3 and 3:1. | IMAGE | Yes | - |
| `scale_factor` | The desired upscaling multiplier. | COMBO | Yes | `"2x"`<br />`"4x"`<br />`"8x"`<br />`"16x"` |
| `flavor` | Processing style: sublime for general use, photo for photographs, photo\_denoiser for noisy photos. | COMBO | Yes | `"sublime"`<br />`"photo"`<br />`"photo_denoiser"` |
| `sharpen` | Image sharpness intensity. Higher values increase edge definition and clarity. Default: 7. | INT | Yes | 0 to 100 |
| `smart_grain` | Intelligent grain/texture enhancement to prevent the image from looking too smooth or artificial. Default: 7. | INT | Yes | 0 to 100 |
| `ultra_detail` | Controls fine detail, textures, and micro-details added during upscaling. Default: 30. | INT | Yes | 0 to 100 |
| `auto_downscale` | Automatically downscale input image if output would exceed maximum resolution. Default: False. This is an advanced setting. | BOOLEAN | Yes | - |

**Note:** If `auto_downscale` is disabled and the requested output size (input dimensions × `scale_factor`) exceeds 10060x10060 pixels, the node will raise an error. When `auto_downscale` is enabled, the node will attempt to find an optimal scale factor that keeps quality loss minimal.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resulting upscaled image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MagnificImageUpscalerPreciseV2Node/en.md)

***

**Source fingerprint (SHA-256):** `aeb2b3569fd7b1d2417890586b8ac84ff921c4405f63f190188af93044ccfd28`


# MetaMuseImageEditApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MetaMuseImageEditApi

Edits or combines up to 10 reference images using a text prompt and Meta's Muse Image model.

Edits or combines up to 10 reference images using a text prompt and Meta's Muse Image model. Describe the desired edit in the prompt and, when needed, refer to the reference images as `@Image1`, `@Image2`, and so on. The node uploads the reference images, calls the Meta Muse Image API, and returns the edited result as an image.

## Inputs

The node is controlled by a `model` selector. The model-specific inputs described below appear when a model is selected, and the reference images you connect can be grown or shortened as needed.

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use. | DYNAMIC\_COMBO | Yes | "muse-image-1.0" |

### muse-image-1.0 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Editing instructions. Supports `@Image1`-style references to the input images. Default: empty string. The prompt must contain at least one character. | STRING | Yes | Any text with a minimum length of 1 character |
| `aspect_ratio` | Aspect ratio of the output. Images are rendered at about 2.5 megapixels (1:1 is 1600x1600, 16:9 is 2048x1152); "auto" keeps the aspect ratio of the input. | COMBO | Yes | "auto"<br />"1:1"<br />"3:2"<br />"2:3"<br />"4:3"<br />"3:4"<br />"5:4"<br />"4:5"<br />"16:9"<br />"9:16"<br />"21:9"<br />"9:21"<br />"2:1"<br />"1:2" |
| `reasoning_strength` | How much the model thinks, plans and self-refines before rendering. | COMBO | Yes | "high"<br />"low" |
| `enable_web_search` | Lets the model search the web for facts and live information while planning the image. Default: true. | BOOLEAN | Yes | true or false (default: true) |
| `enable_image_search` | Lets the model search for reference images while planning the image. Default: true. | BOOLEAN | Yes | true or false (default: true) |
| `enable_shell` | Lets the model run code while planning, for precise layouts, charts and diagrams; when off, quantities and alignment are approximated. Default: true. | BOOLEAN | Yes | true or false (default: true) |
| `seed` | Seed to determine if node should re-run; the API has no seed, so actual results are nondeterministic regardless of this value. Default: 42. | INT | Yes | 0 to 2147483647 (step 1) |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Growable slot: connect 1 to 10 reference images (`image_1` through `image_10`) to edit or combine. Refer to them in the prompt as `@Image1`, `@Image2`, ..., numbered in input order; a batched input counts once per image. | IMAGE | Yes | 1 to 10 reference images |

Note: the prompt may not be empty, and each `@ImageN` reference it contains must match one of the connected images in input order (for example, `@Image1` is the first connected reference image). If the prompt references an image number that is not connected, or if more than 10 reference images are connected, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The edited or combined image returned by the Muse Image model. If the API returns multiple images, they are returned as a batch. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MetaMuseImageEditApi/en.md)

***

**Source fingerprint (SHA-256):** `5c009ca45199f9c70465f12d48a46b685abebd0194c3d437121b9df0636dbea7`


# MetaMuseImageTextToImageApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MetaMuseImageTextToImageApi

Meta Muse Image Text to Image generates images from a text prompt using Meta's Muse Image model.

Meta Muse Image Text to Image generates images from a text prompt using Meta's Muse Image model. The model reasons about the prompt before rendering, and can use web search, image search, and code execution while planning the image. The node calls the Muse Image API and returns the resulting image or images.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use. | DYNAMIC\_COMBO | Yes | `"muse-image-1.0"` |

Selecting a model in the list shows the settings that model supports. The only available model is `muse-image-1.0`; its settings are listed below.

### muse-image-1.0 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the image. The model reasons about the prompt, and may use its built-in web and image search, before rendering. | STRING | Yes | Multiline text, minimum 1 character |
| `aspect_ratio` | Aspect ratio of the output. Images are rendered at about 2.5 megapixels (1:1 is 1600x1600, 16:9 is 2048x1152); "auto" lets the model choose from the prompt. | COMBO | Yes | `"auto"`<br />`"1:1"`<br />`"3:2"`<br />`"2:3"`<br />`"4:3"`<br />`"3:4"`<br />`"5:4"`<br />`"4:5"`<br />`"16:9"`<br />`"9:16"`<br />`"21:9"`<br />`"9:21"`<br />`"2:1"`<br />`"1:2"` |
| `reasoning_strength` | How much the model thinks, plans and self-refines before rendering. | COMBO | Yes | `"high"`<br />`"low"` |
| `enable_web_search` | Lets the model search the web for facts and live information while planning the image. | BOOLEAN | No | True<br />False (default: True) |
| `enable_image_search` | Lets the model search for reference images while planning the image. | BOOLEAN | No | True<br />False (default: True) |
| `enable_shell` | Lets the model run code while planning, for precise layouts, charts and diagrams; when off, quantities and alignment are approximated. | BOOLEAN | No | True<br />False (default: True) |
| `seed` | Seed to determine if node should re-run; the API has no seed, so actual results are nondeterministic regardless of this value. | INT | Yes | 0 – 2147483647 (default: 42) |

Note: The prompt must contain at least one character. When `aspect_ratio` is set to "auto", no explicit size is sent to the API and the model decides the output size from the prompt. The `seed` parameter only controls when the node re-runs; it is not sent to the API, so the generated results are nondeterministic.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated image returned by the API, decoded and provided as a batched image. If the API response contains multiple images, they are combined into one batch. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MetaMuseImageTextToImageApi/en.md)

***

**Source fingerprint (SHA-256):** `59ebd72fab3db44a35ceac723606de4eabb5fe2b690d0b701db50e0e22a9e699`


# OpenAIGPTImage1 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIGPTImage1

Generates images synchronously through OpenAI's GPT Image endpoint.

Generates images synchronously through OpenAI's GPT Image endpoint. It can create new images from a text prompt or edit existing images when an input image and optional mask are provided. The node supports the `gpt-image-1`, `gpt-image-1.5`, and `gpt-image-2` models and is marked as deprecated.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for GPT Image (default: "") | STRING | Yes | - |
| `seed` | Random seed for generation; not implemented yet in backend (default: 0) | INT | No | 0 to 2147483647 |
| `quality` | Image quality, affects cost and generation time (default: "low") | COMBO | No | "low"<br />"medium"<br />"high" |
| `background` | Return image with or without background (default: "auto") | COMBO | No | "auto"<br />"opaque"<br />"transparent" |
| `size` | Image size. Select "Custom" to use the custom width and height (GPT Image 2 only) (default: "auto") | COMBO | No | "auto"<br />"1024x1024"<br />"1024x1536"<br />"1536x1024"<br />"2048x2048"<br />"2048x1152"<br />"1152x2048"<br />"3840x2160"<br />"2160x3840"<br />"Custom" |
| `n` | How many images to generate (default: 1) | INT | No | 1 to 8 |
| `image` | Optional reference image for image editing | IMAGE | No | - |
| `mask` | Optional mask for inpainting (white areas will be replaced) | MASK | No | - |
| `model` | GPT Image model to use (default: "gpt-image-2") | COMBO | No | "gpt-image-1"<br />"gpt-image-1.5"<br />"gpt-image-2" |
| `custom_width` | Used only when `size` is "Custom". Must be a multiple of 16 (GPT Image 2 only) (default: 1024) | INT | No | 1024 to 3840, step 16 |
| `custom_height` | Used only when `size` is "Custom". Must be a multiple of 16 (GPT Image 2 only) (default: 1024) | INT | No | 1024 to 3840, step 16 |

**Parameter Constraints:**

* When `image` is provided, the node uses the image editing endpoint.
* `mask` can only be used when `image` is provided.
* When using `mask`, only single images are supported (batch size must be 1).
* `mask` and `image` must be the same size.
* Custom resolution (`size` = "Custom") is only supported by the `gpt-image-2` model.
* Custom width and height must be multiples of 16.
* The longest edge of a custom resolution must be 3840 or less.
* Custom resolution aspect ratio must not exceed 3:1.
* Custom resolution total pixels must be between 655,360 and 8,294,400.
* The `gpt-image-1` and `gpt-image-1.5` models only support the sizes `auto`, `1024x1024`, `1024x1536`, and `1536x1024`. Other sizes are only supported by the `gpt-image-2` model.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | Generated or edited image(s). Multiple images are returned as a batch; if returned images have different dimensions, they are resized to match the first image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIGPTImage1/en.md)

***

**Source fingerprint (SHA-256):** `f0f0db7fd2cdf8efd2155522b289aa8f3f939fa79a6e9060b0ffbb2dd20efa1e`


# OpenAIGPTImageNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIGPTImageNodeV2

This node generates images using OpenAI's GPT Image API.

This node generates images using OpenAI's GPT Image API. It supports five models — `gpt-image-2.5-flare`, `gpt-image-2.5-sunburst`, `gpt-image-2`, `gpt-image-1.5`, and `gpt-image-1` — lets you attach reference images for image editing, and can use a mask to specify which parts of an image to replace.

## Inputs

### Common Inputs

These inputs are always visible.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The OpenAI GPT Image model to use. Selecting a model reveals additional parameters specific to that model. | DYNAMIC\_COMBO | Yes | `"gpt-image-2.5-flare"`<br />`"gpt-image-2.5-sunburst"`<br />`"gpt-image-2"`<br />`"gpt-image-1.5"`<br />`"gpt-image-1"` |
| `prompt` | Text prompt for GPT Image (default: `""`). | STRING | Yes | N/A |
| `n` | How many images to generate (default: `1`). | INT | Yes | 1 to 8 |
| `seed` | Seed for reproducibility (default: `0`). Not implemented yet in backend. | INT | Yes | 0 to 2147483647 |

### gpt-image-2.5-flare and gpt-image-2.5-sunburst Inputs

These inputs appear when `model` is set to `gpt-image-2.5-flare` or `gpt-image-2.5-sunburst`. Both models share the same parameter set.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.size` | Image size. Select "Custom" to use the custom width and height (default: `"auto"`). | COMBO | Yes | `"auto"`<br />`"1024x1024"`<br />`"1024x1536"`<br />`"1536x1024"`<br />`"2048x2048"`<br />`"2048x1152"`<br />`"1152x2048"`<br />`"3840x2160"`<br />`"2160x3840"`<br />`"Custom"` |
| `model.custom_width` | Used only when `model.size` is "Custom". Must be a multiple of 16 (default: `1024`). | INT | No | 480 to 3840 (step 16) |
| `model.custom_height` | Used only when `model.size` is "Custom". Must be a multiple of 16 (default: `1024`). | INT | No | 480 to 3840 (step 16) |
| `model.background` | Return image with or without background (default: `"auto"`). | COMBO | Yes | `"auto"`<br />`"opaque"`<br />`"transparent"` |
| `model.quality` | Image quality, affects cost and generation time (default: `"low"`). | COMBO | Yes | `"low"`<br />`"medium"`<br />`"high"`<br />`"xhigh"`<br />`"max"` |
| `model.images` | Optional reference image(s) for image editing. Up to 16 images. See Reference Inputs for details. | IMAGE | No | 0 to 16 |
| `model.mask` | Optional mask for inpainting (white areas will be replaced). Requires exactly one reference image. | MASK | No | N/A |

### gpt-image-2 Inputs

These inputs appear when `model` is set to `gpt-image-2`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.size` | Image size. Select "Custom" to use the custom width and height (default: `"auto"`). | COMBO | Yes | `"auto"`<br />`"1024x1024"`<br />`"1024x1536"`<br />`"1536x1024"`<br />`"2048x2048"`<br />`"2048x1152"`<br />`"1152x2048"`<br />`"3840x2160"`<br />`"2160x3840"`<br />`"Custom"` |
| `model.custom_width` | Used only when `model.size` is "Custom". Must be a multiple of 16 (default: `1024`). | INT | No | 480 to 3840 (step 16) |
| `model.custom_height` | Used only when `model.size` is "Custom". Must be a multiple of 16 (default: `1024`). | INT | No | 480 to 3840 (step 16) |
| `model.background` | Return image with or without background (default: `"auto"`). | COMBO | Yes | `"auto"`<br />`"opaque"`<br />`"transparent"` |
| `model.quality` | Image quality, affects cost and generation time (default: `"low"`). | COMBO | Yes | `"low"`<br />`"medium"`<br />`"high"` |
| `model.images` | Optional reference image(s) for image editing. Up to 16 images. See Reference Inputs for details. | IMAGE | No | 0 to 16 |
| `model.mask` | Optional mask for inpainting (white areas will be replaced). Requires exactly one reference image. | MASK | No | N/A |

### gpt-image-1.5 and gpt-image-1 Inputs

These inputs appear when `model` is set to `gpt-image-1.5` or `gpt-image-1`. Both models share the same parameter set.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.size` | Image size (default: `"auto"`). | COMBO | Yes | `"auto"`<br />`"1024x1024"`<br />`"1024x1536"`<br />`"1536x1024"` |
| `model.background` | Return image with or without background (default: `"auto"`). | COMBO | Yes | `"auto"`<br />`"opaque"`<br />`"transparent"` |
| `model.quality` | Image quality, affects cost and generation time (default: `"low"`). | COMBO | Yes | `"low"`<br />`"medium"`<br />`"high"` |
| `model.images` | Optional reference image(s) for image editing. Up to 16 images. See Reference Inputs for details. | IMAGE | No | 0 to 16 |
| `model.mask` | Optional mask for inpainting (white areas will be replaced). Requires exactly one reference image. | MASK | No | N/A |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.images` | Growable slot: connect 1..N items (e.g. `image_1`...`image_16`); up to 16 reference images for all models. | IMAGE | No | 0 to 16 |
| `model.mask` | Optional mask for inpainting (white areas will be replaced). Requires exactly one reference image. | MASK | No | N/A |

**Parameter Constraints and Limitations:**

* When `model.size` is "Custom" (`gpt-image-2.5-flare`, `gpt-image-2.5-sunburst`, and `gpt-image-2` only), `model.custom_width` and `model.custom_height` must both be multiples of 16, the longest edge must not exceed 3840, the aspect ratio must not exceed 3:1, and the total pixel count must be between 655,360 and 8,294,400.
* `model.mask` requires exactly one reference image in `model.images`: it cannot be used without an image, and it cannot be used with more than one image.
* When `model.mask` is used, its height and width must match the height and width of the reference image.
* When `model.images` is provided, the node runs in image editing mode; without `model.images`, it generates images from the prompt alone.
* Reference images and the mask are downscaled before being sent to the API.
* `"xhigh"` and `"max"` quality levels are only available for `gpt-image-2.5-flare` and `gpt-image-2.5-sunburst`.
* `seed` is currently not implemented in the backend.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated image or images. All returned images are stacked into one batch; if their dimensions differ, they are resized to match the first image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIGPTImageNodeV2/en.md)

***

**Source fingerprint (SHA-256):** `804ea35d0e2aa0b2993a293cb10cb41e2f9c6a3732304306253f7f7b1eb59b8a`


# OpenRouterImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenRouterImageNode

This node generates or edits images through OpenRouter using Microsoft's MAI-Image-2.6 models.

This node generates or edits images through OpenRouter using Microsoft's MAI-Image-2.6 models. It supports text-to-image generation as well as image-guided editing with up to five reference images, in seven aspect ratios at either 1K or 1.5K resolution.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The OpenRouter image model used to generate the image. Selecting a model reveals the model-specific options listed below. | DYNAMIC\_COMBO | Yes | `microsoft/mai-image-2.6`<br />`microsoft/mai-image-2.6-flash` |

### Mai Image 2.6 and Mai Image 2.6 Flash Inputs

Shared by both model options (`microsoft/mai-image-2.6` and `microsoft/mai-image-2.6-flash`), which expose the same set of parameters.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Describes the image to generate, or the edit to apply to the reference images. Up to 20000 characters. Default: `""` (empty). At least 1 character is required after removing surrounding whitespace. | STRING | Yes | 1 to 20000 characters |
| `aspect_ratio` | Aspect ratio of the generated image, also applied when reference images are connected. Default: `"1:1"`. `"auto"` lets the model choose the ratio for text to image (rendered at the 1.5K size) and keeps the aspect ratio of the first reference image when editing. | COMBO | Yes | `"1:1"`<br />`"16:9"`<br />`"9:16"`<br />`"3:2"`<br />`"2:3"`<br />`"4:3"`<br />`"3:4"`<br />`"auto"` |
| `resolution` | Output size tier. 1K is about 1 megapixel (1:1 is 1024x1024, 16:9 is 1360x768); 1.5K is about 2.3 megapixels (1:1 is 1536x1536, 16:9 is 2048x1152). Default: `"1K"`. Ignored when `aspect_ratio` is `"auto"`. | COMBO | Yes | `"1K"`<br />`"1.5K"` |
| `seed` | Seed to determine if the node should re-run; the API has no seed, so actual results are nondeterministic regardless of this value. Default: `42`. | INT | Yes | 0 to 2147483647 |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image_1` ... `image_5` | Growable slot: connect 1 to 5 reference images for image-guided editing; a batched input counts once per image. Slots are optional and can be left empty (minimum 0 connected). | IMAGE | No | 0 to 5 images |

**Notes:**

* A maximum of 5 reference images is supported in total across all connected slots; a batched input counts once per image.
* The `prompt` must contain at least 1 character after surrounding whitespace is removed, and cannot exceed 20000 characters.
* Reference images are sent as PNG data and are limited to a total of 2048 x 2048 pixels.
* The `aspect_ratio` setting is applied to the output even when reference images are connected.
* When `aspect_ratio` is `"auto"`, the `resolution` setting is ignored. With no reference images the model picks the ratio for text to image and renders at the 1.5K size; with reference images connected the aspect ratio of the first reference image is kept.
* The seed value does not affect the API result; it only determines whether the node re-runs.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated or edited image. If the service returns several images, they are combined into a single batched IMAGE output. An error is raised if no image is returned or if a returned image cannot be decoded. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenRouterImageNode/en.md)

***

**Source fingerprint (SHA-256):** `d201c18deccd2523041a24427996f51127ca201dfe10fad60c6f768ab79bf852`


# QuiverImageToSVGNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QuiverImageToSVGNode

This node converts a raster image into a scalable vector graphic (SVG) using Quiver AI's vectorization models.

This node converts a raster image into a scalable vector graphic (SVG) using Quiver AI's vectorization models. It sends the image to an external API which processes it and returns the vectorized result.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Input image to vectorize. | IMAGE | Yes | N/A |
| `auto_crop` | Automatically crop to the dominant subject (default: False). | BOOLEAN | Yes | True<br />False |
| `model` | Model to use for SVG vectorization. Selecting a model reveals additional parameters specific to that model: `target_size` (square resize target in pixels; 0 keeps the source image size, otherwise 128 to 4096), `temperature`, `top_p`, and `presence_penalty`. | DYNAMIC\_COMBO | Yes | `"arrow-2"`<br />`"arrow-2-telos"`<br />`"arrow-1.1"`<br />`"arrow-1.1-max"`<br />`"arrow-preview"` |
| `seed` | Seed to determine if the node should re-run; the actual results are nondeterministic regardless of the seed value. This parameter has "control after generate" functionality (default: 0). | INT | Yes | 0 to 2147483647 |
| `reasoning_effort` | How much reasoning the model spends before drawing. Higher levels improve detail and cost more tokens. Only used by the Arrow 2 models (default: "high"). | COMBO | No | `"low"`<br />`"medium"`<br />`"high"`<br />`"xhigh"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `SVG` | The vectorized SVG output. | SVG |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/QuiverImageToSVGNode/en.md)

***

**Source fingerprint (SHA-256):** `d32225207ede8f15fd54780778c6b23b1ce1880be8cb416c341e73afbd9b8aa0`


# QuiverTextToSVGNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QuiverTextToSVGNode

The Quiver Text to SVG node generates a Scalable Vector Graphic (SVG) image from a text description using Quiver AI's models.

The Quiver Text to SVG node generates a Scalable Vector Graphic (SVG) image from a text description using Quiver AI's models. You can optionally provide reference images and style instructions to guide the generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text description of the desired SVG output. This is the main instruction for what to generate. | STRING | Yes | N/A |
| `instructions` | Additional style or formatting guidance. This is an optional, advanced parameter. | STRING | No | N/A |
| `reference_images` | Up to 4 reference images to guide the generation. This is an optional input. | IMAGE | No | 0 to 4 images |
| `model` | Model to use for SVG generation. Selecting a model reveals additional parameters specific to that model: `temperature`, `top_p`, and `presence_penalty`. | DYNAMIC\_COMBO | Yes | `"arrow-2"`<br />`"arrow-2-telos"`<br />`"arrow-1.1"`<br />`"arrow-1.1-max"`<br />`"arrow-preview"` |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. Default: 0. | INT | Yes | 0 to 2147483647 |
| `reasoning_effort` | How much reasoning the model spends before drawing. Higher levels improve detail and cost more tokens. Only used by the Arrow 2 models (default: "high"). | COMBO | No | `"low"`<br />`"medium"`<br />`"high"`<br />`"xhigh"` |

**Note:** The `reference_images` input accepts a maximum of 4 images.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `SVG` | The generated Scalable Vector Graphic (SVG) image. | SVG |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/QuiverTextToSVGNode/en.md)

***

**Source fingerprint (SHA-256):** `8b6f21c26748f48eddf2eddaed785a2331a29364744edf30e86e420b0c117e49`


# QwenImageEditApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QwenImageEditApi

This node uses the Qwen-Image 3.0 models to edit or combine up to 3 reference images guided by a text prompt.

This node uses the Qwen-Image 3.0 models to edit or combine up to 3 reference images guided by a text prompt. You select a model, provide the prompt and reference images, and the node returns one or more generated images.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use. This selection also includes the text prompt, up to 3 reference image inputs, and an optional negative prompt. | DYNAMIC\_COMBO | Yes | "qwen-image-3.0-pro"<br />"qwen-image-3.0" |
| `size` | Output resolution. "match input" reuses the first reference image's size, "auto" lets the model pick a size with the same aspect ratio, "custom" sets an explicit width and height. | DYNAMIC\_COMBO | Yes | "match input"<br />"auto"<br />"custom" |
| `n` | Number of images to generate, returned as a batch. (default: 1) | INT | No | 1 to 6 |
| `seed` | Seed to use for generation. (default: 42) | INT | No | 0 to 2147483647 |
| `prompt_extend` | Whether to enhance the prompt with AI assistance. (default: True) | BOOLEAN | No | True<br />False |
| `watermark` | Whether to add an AI-generated watermark to the result. (default: False) | BOOLEAN | No | True<br />False |

### qwen-image-3.0-pro and qwen-image-3.0 Inputs

Both models share the same sub-parameters.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Editing instructions. Supports English and Chinese, and @Image1-style references to the input images. (default: "") | STRING | Yes | - |
| `negative_prompt` | Negative prompt describing what to avoid. (default: "") | STRING | No | - |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Growable slot: connect 1 to 3 reference images (`image_1`, `image_2`, `image_3`). Refer to them in the prompt as @Image1, @Image2, @Image3, numbered in input order; a batched input counts once per image. | IMAGE | Yes | 1 to 3 |

### Custom Size Inputs

Shown when `size` is set to "custom".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `width` | Output width. The total pixel area must be between 512x512 and 2560x2560; any aspect ratio within that area works. (default: 1024) | INT | Yes (when `size` is "custom") | 256 to 2560, step 16 |
| `height` | Output height. The total pixel area must be between 512x512 and 2560x2560; any aspect ratio within that area works. (default: 1024) | INT | Yes (when `size` is "custom") | 256 to 2560, step 16 |

### Constraints

* The text prompt is required and must contain at least one character.
* A maximum of 3 reference images is supported; an error is raised if more are provided (a batched input counts once per image).
* When `size` is set to "custom", explicit width and height values must be provided and are validated: the total pixel area must be between 262,144 (512x512) and 6,553,600 (2560x2560) pixels, and the aspect ratio must be between 1:8 and 8:1.
* When `size` is set to "match input", at least one reference image is required because the first reference image's dimensions are used; the dimensions are scaled to fit the supported area and aspect ratio range.
* When `size` is set to "auto", the model picks the output size (1.9-4.2 megapixels) while preserving the input aspect ratio.
* Prompt references use @Image1, @Image2, @Image3, numbered in input order; a reference to an index higher than the number of connected images raises an error. Tags are recognized only at word boundaries, so addresses like [user@image1.com](mailto:user@image1.com) are left unchanged.
* Input reference images are downscaled to at most 2048x2048 pixels before being sent to the API. If the PNG encoding exceeds the API size limit, a JPEG encoding is used instead.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated image or images returned as a batch. Up to `n` images are returned. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/QwenImageEditApi/en.md)

***

**Source fingerprint (SHA-256):** `efa8d2b1a039a7b91789c0332b751a5f90ab8dad755ef0e25124d7d1c44d9abb`


# QwenImageTextToImageApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QwenImageTextToImageApi

Qwen Image 3 Text to Image generates one or more images from a text prompt using the Qwen-Image 3.0 models.

Qwen Image 3 Text to Image generates one or more images from a text prompt using the Qwen-Image 3.0 models. You select a model and provide a prompt, and the node returns the generated images as a batch.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use (default: "qwen-image-3.0-pro"). This composite selector also provides the prompt, negative prompt, image width, and image height. | DYNAMIC\_COMBO | Yes | "qwen-image-3.0-pro"<br />"qwen-image-3.0" |
| `n` | Number of images to generate, returned as a batch (default: 1). | INT | No | 1 to 6 |
| `seed` | Seed to use for generation (default: 42). Can be set to update automatically after each generation. | INT | No | 0 to 2147483647 |
| `prompt_extend` | Whether to enhance the prompt with AI assistance (default: true). Advanced option. | BOOLEAN | No | true<br />false |
| `watermark` | Whether to add an AI-generated watermark to the result (default: false). Advanced option. | BOOLEAN | No | true<br />false |

### qwen-image-3.0-pro and qwen-image-3.0 Inputs

Shared by qwen-image-3.0-pro and qwen-image-3.0.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the image. Supports English and Chinese. Must contain at least 1 character. | STRING | Yes | Free text |
| `negative_prompt` | Negative prompt describing what to avoid (default: ""). | STRING | No | Free text |
| `width` | The total pixel area must be between 512x512 and 2560x2560; any aspect ratio within that area works. (default: 1024) | INT | No | 256 to 2560 (step 16) |
| `height` | The total pixel area must be between 512x512 and 2560x2560; any aspect ratio within that area works. (default: 1024) | INT | No | 256 to 2560 (step 16) |

Note: The `model` input is a composite selector with the sub-fields `model` (model ID), `prompt` (required, must contain at least 1 character), `negative_prompt` (optional), `width`, and `height`. The combined pixel area of `width` and `height` must be between 262,144 pixels (512x512) and 6,553,600 pixels (2560x2560), and the aspect ratio must stay between 1:8 and 8:1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated image or images, returned as a batch. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/QwenImageTextToImageApi/en.md)

***

**Source fingerprint (SHA-256):** `c58454d26360a78b795b28dd776fa8650ec0ec7b1e4a902e81b6561f292e0fa2`


# RecraftColorRGB - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftColorRGB

Create a Recraft color by specifying individual red, green, and blue values.

Create a Recraft color by specifying individual red, green, and blue values. This node takes RGB integer values (0-255) and converts them into a Recraft color format that can be used in other Recraft operations. You can also optionally provide an existing Recraft color chain to extend it with the new color.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `r` | Red value of color (default: 0) | INT | Yes | 0-255 |
| `g` | Green value of color (default: 0) | INT | Yes | 0-255 |
| `b` | Blue value of color (default: 0) | INT | Yes | 0-255 |
| `recraft_color` | Optional existing Recraft color chain to extend with the new RGB color | COLOR | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `recraft_color` | The created Recraft color object containing the specified RGB values, or the extended color chain if an existing one was provided | COLOR |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftColorRGB/en.md)

***

**Source fingerprint (SHA-256):** `2246d266bc36d1aa7f115402b049f895f2b15d0085b84d1b0a813cdfb1b6e2fc`


# RecraftControls - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftControls

Creates Recraft Controls for customizing Recraft generation.

Creates Recraft Controls for customizing Recraft generation. This node allows you to configure color settings that will be used during the Recraft image generation process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `colors` | Color settings for the main elements | COLOR | No | - |
| `background_color` | Background color setting | COLOR | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `recraft_controls` | The configured Recraft controls containing color settings | CONTROLS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftControls/en.md)

***

**Source fingerprint (SHA-256):** `d6237821472e5305303c25119601b1c8eb5781d3e1aee4f6b3b80060a4fdc8cf`


# RecraftCreateStyleNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftCreateStyleNode

This node creates a custom style for image generation by uploading reference images.

This node creates a custom style for image generation by uploading reference images. You can upload between 1 and 5 images to define the new style, and the node will return a unique style ID that can be used with other Recraft nodes. The total combined file size of all uploaded images must not exceed 5 MB.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `style` | The base style of the generated images. | STRING | Yes | `"realistic_image"`<br />`"digital_illustration"` |
| `images` | A set of 1 to 5 reference images used to create the custom style. | IMAGE | Yes | 1 to 5 images |

**Note:** The total file size of all images in the `images` input must be less than 5 MB. The node will fail if this limit is exceeded.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `style_id` | The unique identifier for the newly created custom style. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftCreateStyleNode/en.md)

***

**Source fingerprint (SHA-256):** `36edcb0b96eed5930d9d7ff00a1812d129b7cd9b7ab0f0d758594a20791826b2`


# RecraftCreativeUpscaleNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftCreativeUpscaleNode

The Recraft Creative Upscale Image node enhances a raster image by increasing its resolution.

The Recraft Creative Upscale Image node enhances a raster image by increasing its resolution. It uses a "creative upscale" process that focuses on improving small details and faces within the image. This operation is performed synchronously through an external API.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be upscaled. | IMAGE | Yes | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The resulting upscaled image with enhanced details. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftCreativeUpscaleNode/en.md)

***

**Source fingerprint (SHA-256):** `52e19f6dfb3846cdea2b150f3008fa49c98bc5fced94ffb362846d3a5fba57df`


# RecraftCrispUpscaleNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftCrispUpscaleNode

This node upscales an image synchronously using the "crisp upscale" tool.

This node upscales an image synchronously using the "crisp upscale" tool. It enhances a given raster image by increasing its resolution, making the image sharper and cleaner. When a batch of images is provided, each image is processed independently and the upscaled results are returned as a batch.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be upscaled. Accepts a batch of images; each image is processed independently. | IMAGE | Yes | — |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The upscaled image with enhanced resolution and clarity. Returns a batch of images if a batch was provided as input. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftCrispUpscaleNode/en.md)

***

**Source fingerprint (SHA-256):** `7a60c563504df7a81ce5d50e989bc4a8853f4bb30805a014c9fb567d8ec83e33`


# RecraftImageInpaintingNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftImageInpaintingNode

This node modifies specific areas of an image based on a text prompt and a mask.

This node modifies specific areas of an image based on a text prompt and a mask. It uses the Recraft API to intelligently edit only the masked regions while keeping the rest of the image unchanged.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be modified | IMAGE | Yes | - |
| `mask` | The mask defining which areas of the image should be modified | MASK | Yes | - |
| `prompt` | Prompt for the image generation (default: empty string, maximum length: 1000 characters) | STRING | Yes | - |
| `n` | The number of images to generate (default: 1, minimum: 1, maximum: 6) | INT | Yes | 1-6 |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0) | INT | Yes | 0-18446744073709551615 |
| `recraft_style` | Optional style parameter for the Recraft API. If not provided, defaults to "realistic\_image" style | STYLEV3 | No | - |
| `negative_prompt` | An optional text description of undesired elements on an image (default: empty string) | STRING | No | - |

*Note: The `image` and `mask` must be provided together for the inpainting operation to work. The mask will be automatically resized to match the image dimensions. The `prompt` is validated and has a maximum length of 1000 characters. If a `style_id` from the Infinite Style Library is used, ensure it is not a Vector art style, as this may cause the API to return SVG data instead of an image.*

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The modified image(s) generated based on the prompt and mask. Returns one image per input image multiplied by the `n` parameter | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftImageInpaintingNode/en.md)

***

**Source fingerprint (SHA-256):** `539a49aec582f529a13059388222c3998e22d52618738843d9b2b6e0fb1ea5c3`


# RecraftImageToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftImageToImageNode

This node modifies an existing image based on a text prompt and a strength setting.

This node modifies an existing image based on a text prompt and a strength setting. It sends the image to the Recraft V3 API and returns a new image that follows the prompt while staying more or less similar to the original, depending on the strength value.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be modified. When a batch of images is provided, each image is processed individually. | IMAGE | Yes | - |
| `prompt` | Prompt for the image generation. Default: empty string. Maximum length: 1000 characters. | STRING | Yes | - |
| `n` | The number of images to generate. Default: 1. | INT | Yes | 1-6 |
| `strength` | Defines the difference with the original image, should lie in \[0, 1], where 0 means almost identical, and 1 means miserable similarity. Default: 0.5. | FLOAT | Yes | 0.0-1.0 (step 0.01) |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. Default: 0. | INT | Yes | 0-18446744073709551615 |
| `recraft_style` | Optional style selection for the image generation. If not provided, defaults to `realistic_image`. | STYLEV3 | No | - |
| `negative_prompt` | An optional text description of undesired elements on an image. Default: empty string. Provided as an input socket. | STRING | No | - |
| `recraft_controls` | Optional additional controls over the generation via the Recraft Controls node. | CONTROLS | No | - |

**Note:** The `seed` parameter only triggers re-execution of the node but does not guarantee deterministic results. The `strength` parameter is rounded to 2 decimal places internally. The `prompt` is validated and must not exceed 1000 characters. An empty `negative_prompt` is treated as no negative prompt. If `recraft_style` is not provided, the node defaults to the `realistic_image` style. If you use a `style_id` from the Infinite Style Library, ensure it is not a Vector art style, as this may cause the node to receive SVG data instead of an image, resulting in an error. When the input `image` is a batch, each image in the batch is processed individually and all results are returned together.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated image(s) based on the input image, prompt, and strength. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftImageToImageNode/en.md)

***

**Source fingerprint (SHA-256):** `1932e55d1dc392e6bd42a0bd29f5aaba44b65997b597648a927fba38a27c90ad`


# RecraftRemoveBackgroundNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftRemoveBackgroundNode

This node removes the background from images using the Recraft API service.

This node removes the background from images using the Recraft API service. It processes each image in the input batch individually and returns both the processed images with transparent backgrounds and corresponding alpha masks that indicate the removed background areas.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image(s) to process for background removal. Each image in the batch is processed individually. | IMAGE | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | Processed images with transparent backgrounds (RGBA format) | IMAGE |
| `mask` | Alpha channel masks indicating the removed background areas, in B,H,W format | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftRemoveBackgroundNode/en.md)

***

**Source fingerprint (SHA-256):** `702dfdf2751d5ca33f23e10c0968496887514a21da7a0c42e3636a0ed4e82311`


# RecraftReplaceBackgroundNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftReplaceBackgroundNode

Replace background on image, based on provided prompt.

Replace background on image, based on provided prompt. This node uses the Recraft API to generate new backgrounds for your images according to your text description, allowing you to completely transform the background while keeping the main subject intact. Each image in the input batch is processed separately, and the results are combined into a single output batch.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to process | IMAGE | Yes | - |
| `prompt` | Prompt for the image generation (default: empty) | STRING | Yes | - |
| `n` | The number of images to generate (default: 1) | INT | Yes | 1-6 |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0) | INT | Yes | 0-18446744073709551615 |
| `recraft_style` | Optional style selection for the generated background. If not provided, defaults to "realistic\_image" style | STYLEV3 | No | - |
| `negative_prompt` | An optional text description of undesired elements on an image (default: empty) | STRING | No | - |

**Notes:**

* The `seed` parameter controls when the node re-executes but does not guarantee deterministic results due to the nature of the external API.
* When `recraft_style` is not connected or left empty, the node falls back to the `realistic_image` style.
* When `negative_prompt` is left empty, it is not sent with the request.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated image(s) with replaced background. For each input image, the number of generated results is determined by `n`. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftReplaceBackgroundNode/en.md)

***

**Source fingerprint (SHA-256):** `45a2607ae73cc67caa98d33bf536feda83a2021d960dec7cca76cbe0b9fc47ef`


# RecraftStyleV3DigitalIllustration - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftStyleV3DigitalIllustration

This node configures a style for use with the Recraft API, specifically selecting the "digitalillustration" style.

This node configures a style for use with the Recraft API, specifically selecting the "digital\_illustration" style. It allows you to choose an optional substyle to further refine the artistic direction of the generated image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `substyle` | An optional substyle to specify a particular type of digital illustration. If not selected, the base "digital\_illustration" style is used. | STRING | No | `"digital_illustration"`<br />`"digital_illustration_anime"`<br />`"digital_illustration_cartoon"`<br />`"digital_illustration_comic"`<br />`"digital_illustration_concept_art"`<br />`"digital_illustration_fantasy"`<br />`"digital_illustration_futuristic"`<br />`"digital_illustration_graffiti"`<br />`"digital_illustration_graphic_novel"`<br />`"digital_illustration_hyperrealistic"`<br />`"digital_illustration_ink"`<br />`"digital_illustration_manga"`<br />`"digital_illustration_minimalist"`<br />`"digital_illustration_pixel_art"`<br />`"digital_illustration_pop_art"`<br />`"digital_illustration_retro"`<br />`"digital_illustration_sci_fi"`<br />`"digital_illustration_sticker"`<br />`"digital_illustration_street_art"`<br />`"digital_illustration_surreal"`<br />`"digital_illustration_vector"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `recraft_style` | A configured style object containing the selected "digital\_illustration" style and optional substyle, ready to be passed to other Recraft API nodes. | STYLEV3 |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftStyleV3DigitalIllustration/en.md)

***

**Source fingerprint (SHA-256):** `b6901d81bc11c3226d847ed61386b9bcf4ece90f6a95b6ad9888f102ef355594`


# RecraftStyleV3InfiniteStyleLibrary - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftStyleV3InfiniteStyleLibrary

This node allows you to select a style from Recraft's Infinite Style Library using a preexisting UUID.

This node allows you to select a style from Recraft's Infinite Style Library using a preexisting UUID. It retrieves the style information based on the provided style identifier and returns it for use in other Recraft nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `style_id` | UUID of style from Infinite Style Library. | STRING | Yes | Any valid UUID |

**Note:** The `style_id` input cannot be empty. If an empty string is provided, the node will raise an exception.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `recraft_style` | The selected style object from Recraft's Infinite Style Library | STYLEV3 |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftStyleV3InfiniteStyleLibrary/en.md)

***

**Source fingerprint (SHA-256):** `4554acaaba9e83373d6fb44ea5465175182efcf7c9220c2328c4749c2febd40f`


# RecraftStyleV3LogoRaster - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftStyleV3LogoRaster

This node selects the logo raster style and a specific substyle for generating logo images.

This node selects the logo raster style and a specific substyle for generating logo images. It specializes in creating logo designs with raster-based visual treatments. The chosen style is returned as a Recraft style setting that can be passed to other Recraft nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `substyle` | The specific logo raster substyle to apply for logo generation | COMBO | Yes | `"bold"`<br />`"minimal"`<br />`"vibrant"`<br />`"handdrawn"`<br />`"geometric"`<br />`"vintage"`<br />`"neon"`<br />`"gradient"`<br />`"flat"`<br />`"outline"`<br />`"mascot"`<br />`"badge"`<br />`"abstract"`<br />`"retro"`<br />`"modern"`<br />`"playful"`<br />`"luxury"`<br />`"tech"`<br />`"nature"`<br />`"food"`<br />`"sport"`<br />`"fashion"`<br />`"music"`<br />`"travel"`<br />`"education"`<br />`"health"`<br />`"finance"`<br />`"realestate"`<br />`"nonprofit"` |

Note: A substyle must always be selected; there is no "none" option.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `recraft_style` | The selected Recraft style configuration, including the logo raster style and chosen substyle | CUSTOM |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftStyleV3LogoRaster/en.md)

***

**Source fingerprint (SHA-256):** `59c3af980261d2b20b6d401980639c6bbc3a8b7c4e2370ca048ccb07535b10e7`


# RecraftStyleV3RealisticImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftStyleV3RealisticImage

This node creates a style configuration for generating realistic images using Recraft's API.

This node creates a style configuration for generating realistic images using Recraft's API. It selects the `realistic_image` style and lets you choose an optional substyle to fine-tune the output appearance.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `substyle` | The specific substyle to apply to the realistic\_image style. If set to "None", no substyle will be applied. | STRING | Yes | Multiple options available (determined by Recraft API) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `recraft_style` | A Recraft style configuration object containing the `realistic_image` style and the selected substyle settings. This output can be connected to other Recraft nodes that accept a style input. | STYLEV3 |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftStyleV3RealisticImage/en.md)

***

**Source fingerprint (SHA-256):** `df3a09ae0956dd5807b7475248359085fdbe5abb5c40291e37db3ceabafef2ac`


# RecraftStyleV3VectorIllustrationNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftStyleV3VectorIllustrationNode

This node selects a style for the Recraft API, specifically the vector illustration style category.

This node selects a style for the Recraft API, specifically the vector illustration style category. You can optionally pick a more specific substyle within that category. The node outputs a style configuration object that can be passed to other Recraft nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `substyle` | A more specific style within the vector illustration category. The available options are the substyles defined for the `vector_illustration` style by the Recraft API. If no substyle is chosen, the base `vector_illustration` style is used. | COMBO | Yes | Multiple options available (dynamically loaded substyle list for the `vector_illustration` style) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `recraft_style` | A Recraft style configuration object containing the selected vector illustration style and optional substyle. This can be connected to other Recraft nodes. | STYLEV3 |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftStyleV3VectorIllustrationNode/en.md)

***

**Source fingerprint (SHA-256):** `e88e7ea35b18acb55ec59814981cb36451d922d3287d23dcdb504289ea9f541b`


# RecraftTextToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftTextToImageNode

Generates images synchronously based on prompt and resolution.

Generates images synchronously based on prompt and resolution. This node connects to the Recraft API to create images from text descriptions with specified dimensions and optional style and control parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the image generation. (default: "") | STRING | Yes | 1-1000 characters |
| `size` | The size of the generated image. (default: "1024x1024") | COMBO | Yes | "1024x1024"<br />"1152x896"<br />"896x1152"<br />"1216x832"<br />"832x1216"<br />"1344x768"<br />"768x1344"<br />"1536x640"<br />"640x1536" |
| `n` | The number of images to generate. (default: 1) | INT | Yes | 1-6 |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. (default: 0) | INT | Yes | 0-18446744073709551615 |
| `recraft_style` | Optional style selection for image generation. When not provided, defaults to a "realistic\_image" style. | RECRAFT\_STYLE | No | Multiple options available |
| `negative_prompt` | An optional text description of undesired elements on an image. (default: "") | STRING | No | - |
| `recraft_controls` | Optional additional controls over the generation via the Recraft Controls node. | RECRAFT\_CONTROLS | No | Multiple options available |

**Note:** The `seed` parameter only controls when the node re-runs but does not make the image generation deterministic. The actual output images will vary even with the same seed value.

**Note:** The `prompt` parameter must be between 1 and 1000 characters in length.

**Note:** If you use a `style_id` from the Infinite Style Library, ensure it is not a Vector art style, as this will return SVG data instead of an image and cause an error.

**Note:** This is a paid API node. The cost is \$0.04 per generated image, based on the `n` value.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated image(s) as a batched tensor output. When multiple images are generated (n > 1), they are concatenated along the batch dimension. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftTextToImageNode/en.md)

***

**Source fingerprint (SHA-256):** `d75b7dd2d8cee70c3bc1d2c64fb07ce814a3672619e8647f4c4c2cdc2635945c`


# RecraftTextToVectorNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftTextToVectorNode

Generates SVG vector illustrations synchronously based on a text prompt and resolution.

Generates SVG vector illustrations synchronously based on a text prompt and resolution. This node sends your prompt to the Recraft API and returns the generated SVG content.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the image generation. (default: "", maximum 1000 characters) | STRING | Yes | - |
| `substyle` | The specific vector illustration style to use for generation. | COMBO | Yes | `"2d_character"`<br />`"2d_gradient"`<br />`"2d_illustration"`<br />`"2d_flat_character"`<br />`"2d_flat_illustration"`<br />`"2d_art"`<br />`"2d_art_character"`<br />`"2d_pattern"`<br />`"2d_pixel_art"`<br />`"2d_cyberpunk"`<br />`"2d_engraving"`<br />`"2d_black_and_white"`<br />`"2d_ink"`<br />`"2d_sketch"`<br />`"2d_watercolor"`<br />`"2d_animation"`<br />`"2d_comic"`<br />`"2d_children_illustration"`<br />`"2d_vintage"`<br />`"2d_retro"`<br />`"2d_hand_drawn"`<br />`"2d_psychedelic"`<br />`"2d_graffiti"`<br />`"2d_ukiyo_e"`<br />`"2d_woodcut"`<br />`"2d_art_deco"`<br />`"2d_art_nouveau"`<br />`"2d_bauhaus"`<br />`"2d_constructivism"`<br />`"2d_cubism"`<br />`"2d_futurism"`<br />`"2d_glitch"`<br />`"2d_impressionism"`<br />`"2d_naive"`<br />`"2d_pointillism"`<br />`"2d_pop_art"`<br />`"2d_realism"`<br />`"2d_renaissance"`<br />`"2d_rococo"`<br />`"2d_romanticism"`<br />`"2d_surrealism"`<br />`"2d_suprematism"`<br />`"2d_symbolism"`<br />`"2d_expressionism"`<br />`"2d_abstract"`<br />`"2d_minimalism"`<br />`"2d_contemporary"`<br />`"2d_modern"`<br />`"2d_brutalism"`<br />`"2d_metaphysical"`<br />`"2d_mannerism"`<br />`"2d_baroque"`<br />`"2d_neoclassicism"`<br />`"2d_orientalism"`<br />`"2d_primitivism"`<br />`"2d_fauvism"`<br />`"2d_rayonism"`<br />`"2d_orphism"`<br />`"2d_vorticism"`<br />`"2d_dadaism"`<br />`"2d_neo_expressionism"`<br />`"2d_transavantgarde"`<br />`"2d_new_wild"`<br />`"2d_graffiti_classic"`<br />`"2d_graffiti_modern"`<br />`"2d_graffiti_wildstyle"`<br />`"2d_graffiti_bubble"`<br />`"2d_graffiti_throwup"`<br />`"2d_graffiti_tag"`<br />`"2d_graffiti_blockbuster"`<br />`"2d_graffiti_mural"`<br />`"2d_graffiti_stencil"`<br />`"2d_graffiti_3d"`<br />`"2d_graffiti_character"`<br />`"2d_graffiti_abstract"`<br />`"2d_graffiti_urban"`<br />`"2d_graffiti_neo_muralism"`<br />`"2d_graffiti_post_graffiti"`<br />`"2d_graffiti_street_art"` |
| `size` | The size of the generated image. (default: "1024x1024") | COMBO | Yes | `"1024x1024"`<br />`"1024x2048"`<br />`"2048x1024"`<br />`"2048x2048"`<br />`"512x512"`<br />`"512x1024"`<br />`"1024x512"`<br />`"2048x512"`<br />`"512x2048"` |
| `n` | The number of images to generate. (default: 1, min: 1, max: 6) | INT | Yes | 1-6 |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. (default: 0, min: 0, max: 18446744073709551615) | INT | Yes | 0-18446744073709551615 |
| `negative_prompt` | An optional text description of undesired elements on an image. (default: "", when empty no negative prompt is used) | STRING | No | - |
| `recraft_controls` | Optional additional controls over the generation via the Recraft Controls node. | CONTROLS | No | - |

**Note:** The `seed` parameter only controls when the node re-runs but does not make the generation results deterministic.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `SVG` | The generated vector illustration in SVG format | SVG |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftTextToVectorNode/en.md)

***

**Source fingerprint (SHA-256):** `aec7e96e339047e75dfe419d94d23a613595bc22e7f187895c52b143780fcbf3`


# RecraftV4CreateStyleNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftV4CreateStyleNode

This node creates a reusable Recraft V4 style from 1 to 10 reference images.

This node creates a reusable Recraft V4 style from 1 to 10 reference images. The returned style ID works with every Recraft V4 and V4.1 model of the same output type (raster or vector) and can be reused in later image generation steps. The total size of all reference images is limited to 10 MB.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model the style is created for. Standard and Pro share one style pool: raster styles work with every Recraft V4 and V4.1 raster model, vector styles (\*\_vector) with every V4 and V4.1 vector model. | COMBO | Yes | "recraftv4\_styles"<br />"recraftv4\_styles\_vector"<br />"recraftv4\_styles\_pro"<br />"recraftv4\_styles\_pro\_vector" |
| `images` | Reference images defining the style. Similar references sharpen the match, varied references widen it. Growable slot: connect 1 to 10 images (`image_1` through `image_10`). | IMAGE | Yes | 1 to 10 images |

### Notes

* At least one reference image is required; the node raises an error if none are provided.
* At most 10 reference images are allowed; the node raises an error if more are provided.
* The total encoded size of all reference images must not exceed 10 MB; the node raises an error if the limit is exceeded.
* Each reference image is downscaled to at most 2048×2048 pixels and encoded as WebP before being sent to the Recraft API.
* Models ending in `_vector` create vector styles; the other options create raster styles. Standard and Pro models share the same style pools within each output type.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `style_id` | Unique identifier of the created style, usable with every Recraft V4 and V4.1 model of the same output type. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftV4CreateStyleNode/en.md)

***

**Source fingerprint (SHA-256):** `7b907a975ed88dcca6bf1e0431ef7a9b561852ca7263a4f3298df980fe9431e5`


# RecraftV4TextToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftV4TextToImageNode

Generates images from text prompts using Recraft V4 and V4.1 models.

Generates images from text prompts using Recraft V4 and V4.1 models. It sends the prompt and selected settings to the Recraft API and returns the generated image or images. If style reference images are used, the created style ID is also returned.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to use for generation. The recraftv4\_styles models are built for style-consistent generation and always require a style\_id or style\_references. `recraftv4_1_flash` is the fastest and cheapest model and supports no styles at all. | DYNAMIC\_COMBO | Yes | "recraftv4\_1"<br />"recraftv4\_1\_flash"<br />"recraftv4\_1\_utility"<br />"recraftv4\_1\_pro"<br />"recraftv4\_1\_utility\_pro"<br />"recraftv4"<br />"recraftv4\_pro"<br />"recraftv4\_styles"<br />"recraftv4\_styles\_pro" |
| `prompt` | Prompt for the image generation. Maximum 10,000 characters. | STRING | Yes | 1 to 10000 characters |
| `negative_prompt` | This input is ignored: negative prompt is not supported by Recraft V4 and V4.1 models. | STRING | Yes | N/A |
| `n` | The number of images to generate (default: 1). | INT | Yes | 1 to 6 |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). | INT | Yes | 0 to 18446744073709551615 |
| `recraft_controls` | Optional additional controls over the generation via the Recraft Controls node. | CUSTOM | No | N/A |
| `style_id` | UUID of a Recraft V4 style to apply, e.g. from the Recraft V4 Create Style node or the style\_id output of a previous run. Cannot be combined with style\_references (default: empty). | STRING | No | Valid UUID string |
| `style_match` | How closely to follow the style: precise reproduces it in detail, flexible matches the general look. Only used when a style is provided (default: "precise"). | COMBO | No | "precise"<br />"flexible" |

### recraftv4\_1, recraftv4\_1\_flash, recraftv4\_1\_utility, recraftv4, and recraftv4\_styles Inputs

These models share the same `size` parameter.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size` | The size of the generated image (default: "1024x1024"). | COMBO | Yes | Multiple options available (standard Recraft V4 sizes; includes "1024x1024") |

### recraftv4\_1\_pro, recraftv4\_1\_utility\_pro, recraftv4\_pro, and recraftv4\_styles\_pro Inputs

These models share the same `size` parameter.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size` | The size of the generated image (default: "2048x2048"). | COMBO | Yes | Multiple options available (pro Recraft V4 sizes; includes "2048x2048") |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `style_references` | Reference images to create a style from on the fly, billed on top of the generation. The created style is returned as style\_id for reuse. Cannot be combined with style\_id. Growable slot: connect 1..N images (style\_reference\_1, style\_reference\_2, ...). | IMAGE | No | 0 to the maximum number of reference images allowed by the Recraft API; total encoded size must not exceed 10 MB |

**Note:** The `size` parameter is a dynamic input whose available options change based on the selected `model`. The `recraftv4_styles` and `recraftv4_styles_pro` models always require a style: connect style reference images or provide a `style_id`. The `style_id` and `style_references` inputs are mutually exclusive — provide only one of them. A `style_id` must be a valid UUID. The `style_match` input is only used when a style is provided. Style reference images are billed on top of the generation and their total encoded size must not exceed 10 MB. The `seed` value does not guarantee reproducible image outputs. If you use a style ID from the Infinite Style Library, make sure it is not a Vector art style, as this may return SVG data instead of an image.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated image or batch of images. | IMAGE |
| `style_id` | The style ID used or created by this generation. When style reference images are provided, the created style is returned here for reuse; empty string when no style is used. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftV4TextToImageNode/en.md)

***

**Source fingerprint (SHA-256):** `690286e663f27b525e58f81a7f883e490dacd48c1a34ee7b8e9ad4efd9935ff1`


# SoniloTextToMusic - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SoniloTextToMusic

The Sonilo Text to Music node generates music from a text description using Sonilo's AI model.

The Sonilo Text to Music node generates music from a text description using Sonilo's AI model. You provide a prompt describing the music you want, and the node sends a request to the Sonilo service to create an audio file. You can set a target duration for the generated clip.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt describing the music to generate. Must contain 1 to 1000 characters after trimming whitespace. | STRING | Yes | 1 to 1000 characters |
| `duration` | Target duration in seconds. Maximum: 6 minutes. Default: 30. | INT | No | 1 to 360 |
| `seed` | Seed for reproducibility. Currently ignored by the Sonilo service but kept for graph consistency. Default: 0. | INT | No | 0 to 18446744073709551615 |

**Notes:**

* The `seed` input is provided for workflow consistency but does not currently affect the output of the Sonilo service.
* The `prompt` input is required and must be non-empty; the node validates that it contains at least 1 character (after trimming whitespace) and no more than 1000 characters.
* Usage is billed at \$0.0025 per second of the requested `duration`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The generated music as an audio file. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SoniloTextToMusic/en.md)

***

**Source fingerprint (SHA-256):** `9dd1503428b0f23e0fb316ca97e3b64ddf11bcb4a82fc34fd248f481a60c1afe`


# SoniloVideoToMusic - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SoniloVideoToMusic

Generate music from video using Sonilo's AI model.

Generate music from video using Sonilo's AI model. This node analyzes the content of an input video and creates a matching piece of music. It uses an external AI service to process the video and generate the audio.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Input video to generate music from. Maximum duration: 6 minutes. | VIDEO | Yes | - |
| `prompt` | Optional text prompt to guide music generation. Leave empty for best quality - the model will fully analyze the video content. (default: empty string) | STRING | No | - |
| `seed` | Seed for reproducibility. Currently ignored by the Sonilo service but kept for graph consistency. (default: 0) | INT | No | 0 to 18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `audio` | The generated music as an audio file. | AUDIO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SoniloVideoToMusic/en.md)

***

**Source fingerprint (SHA-256):** `ed118d346add099f41a99635638ecb9aa4026b2210b17628c34cdad6bb919767`


# TripoSmartSegmentNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoSmartSegmentNode

Splits a 3D model into semantically meaningful parts and gives each part a name.

Splits a 3D model into semantically meaningful parts and gives each part a name. It can either segment an existing model (provided through a task ID) or first generate a model from an image and then segment it. The resulting `segment task_id` can be used by other Tripo nodes, such as Complete Mesh Parts, Retopology, Texture model, and Convert model, in the same way as a Tripo: Segment Model result.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `source` | Segment an existing model, or generate a model from an image and segment it. The selected option determines which additional inputs appear. | DYNAMIC\_COMBO | Yes | `"model"`<br />`"image"` |

### Model Inputs

Shown when `source` is set to `"model"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_task_id` | A GLB result. Quad (FBX) meshes must go through Tripo: Convert model (GLTF) first. | MODEL\_TASK\_ID | Yes | - |
| `granularity` | How finely the model is split into parts (default: "medium"). | COMBO | No | `"coarse"`<br />`"medium"`<br />`"fine"` |
| `hint` | Optional text naming the parts to look for, e.g. 'game character with sword and armor' (default: empty). | STRING | No | - |

### Image Inputs

Shown when `source` is set to `"image"`. Tripo first generates a model from the image, then segments it.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image used to generate the model that will be segmented. | IMAGE | Yes | - |
| `granularity` | How finely the model is split into parts (default: "medium"). | COMBO | No | `"coarse"`<br />`"medium"`<br />`"fine"` |
| `hint` | Optional text naming the parts to look for, e.g. 'game character with sword and armor' (default: empty). | STRING | No | - |

**Notes:**

* `granularity` and `hint` are shared by both `source` options and are optional. When `hint` is left empty, no hint is sent to the service.
* When `source` is `"model"`, only GLB models are accepted. Other formats, such as quad (FBX) meshes, must be converted first with Tripo: Convert model (GLTF).
* The task is polled until it reaches a terminal state, with an estimated duration of about 180 seconds. If Tripo returns an incomplete segmentation result, the node reports an error.
* Price badge: approximately 0.85 USD when `source` is `"image"` and approximately 0.55 USD when `source` is `"model"` (values shown as approximate).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `segment task_id` | Task ID of the segmentation task, usable as input for other Tripo nodes. | SEGMENT\_TASK\_ID |
| `model task_id` | The model that was segmented (generated from the image, or imported). | MODEL\_TASK\_ID |
| `GLB` | The segmented 3D model file. | FILE3DGLB |
| `part_names` | Comma-separated names of the parts. | STRING |
| `parts` | Tripo's description of the parts it found. | STRING |
| `mask` | Mask image produced by the segmentation. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoSmartSegmentNode/en.md)

***

**Source fingerprint (SHA-256):** `ba041da49e20b1ac085770078cce6ac87ef70eee927ba0ee9e5655a058893f1c`


# TripoTextToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoTextToModelNode

This legacy node generates finished 3D models from a text description using Tripo's API.

This legacy node generates finished 3D models from a text description using Tripo's API. It waits for generation to complete and then returns the model file, optionally with textures and PBR materials. It is marked as deprecated and is kept for older workflows.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text description of the 3D model to generate (multiline). This parameter is required and cannot be empty. | STRING | Yes | - |
| `negative_prompt` | Text description of what to avoid in the generated model (multiline). Up to 255 characters. Sent to the API only when non-empty. | STRING | No | Up to 255 characters |
| `model_version` | Version of the Tripo model to use for generation (default: v3\_1\_20260211). | COMBO | No | Multiple options available |
| `style` | No longer supported by Tripo and ignored. Kept for older workflows (default: "None"). | COMBO | No | Multiple options available |
| `texture` | Generate texture maps. Off returns bare geometry and ignores `pbr` (default: True). | BOOLEAN | No | true / false |
| `pbr` | PBR material maps (base color, metallic, roughness, normal). Requires `texture`; forced off when `texture` is off (default: True). | BOOLEAN | No | true / false |
| `image_seed` | Seed used for the image generation stage (default: 42). | INT | No | 0 to 2147483647 |
| `model_seed` | Seed used for the model generation stage (default: 42). | INT | No | 0 to 2147483647 |
| `texture_seed` | Seed used for the texture generation stage (default: 42). | INT | No | 0 to 2147483647 |
| `texture_quality` | Quality of the generated textures. detailed = HD textures, extreme = 8K Ultra textures (default: standard). | COMBO | No | "standard"<br />"detailed"<br />"extreme" |
| `face_limit` | Maximum face count. -1 lets Tripo pick adaptively (about 1.4M faces on v3.x standard, 2M on detailed). Tripo clamps silently: v2.5 at 500,000, quad meshes at 150,000. (default: -1) | INT | No | -1 to 2000000 |
| `quad` | Quad mesh output. Tripo delivers quad meshes as FBX, so the result arrives on the FBX output and the GLB output stays empty. (default: False) | BOOLEAN | No | true / false |
| `geometry_quality` | Quality of the generated geometry (default: standard). | COMBO | No | "standard"<br />"detailed" |
| `smart_low_poly` | Low-poly mesh with clean, hand-crafted style topology (500-20,000 faces, quad 500-10,000). Best for simple subjects; complex ones may fail. (default: False) | BOOLEAN | No | true / false |
| `auto_size` | Scale textured models to their real-world size in meters. Tripo stores the size as the model's scene transform and bakes it in when the model is converted, rigged or retargeted; ignored without texture. (default: True) | BOOLEAN | No | true / false |

**Notes:**

* This node is deprecated and marked as a legacy node. It is kept for backward compatibility with older workflows.
* The `prompt` parameter is mandatory: an empty prompt causes the node to raise an error.
* `pbr` requires `texture`. When `texture` is off, the node forces `pbr` to off and ignores its value. `auto_size` also has no effect without `texture`.
* When `smart_low_poly` is enabled and `face_limit` is set to a value other than -1, the face limit must be between 500 and 20,000 for triangle output, or between 500 and 10,000 when `quad` is enabled; otherwise the node raises an error.
* When `quad` is enabled, the generated quad mesh is delivered as FBX, so the FBX output is populated and the GLB output stays empty.
* The `style` parameter is accepted but ignored.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The generated 3D model filename in the format `<task_id>.<format>`, kept for backward compatibility only. | STRING |
| `model task_id` | The unique task identifier for the model generation process. | MODEL\_TASK\_ID |
| `GLB` | The generated 3D model in GLB format. Empty when `quad` is enabled. | FILE3DGLB |
| `FBX` | The generated 3D model in FBX format. Only populated when `quad` is enabled. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoTextToModelNode/en.md)

***

**Source fingerprint (SHA-256):** `c26c8437ea66d08f7f39865fedeaaf4cf8583ca64b368f3b767ea18918dd6c08`


# TripoTextToModelNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoTextToModelNodeV2

Generates a 3D model from a text description using the Tripo service.

Generates a 3D model from a text description using the Tripo service. The node sends the prompt and settings to Tripo, waits for the generation task to finish, and returns the finished 3D file together with the task identifier.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | The text description of the model to generate. Must not be empty. | STRING | Yes | Multiline text |
| `negative_prompt` | Text describing what should not appear in the generated model. Up to 255 characters. | STRING | No | Multiline text, max 255 characters |
| `model_version` | The Tripo model version used for generation (default: `v3.1_20260211`). | COMBO | No | List of supported Tripo model versions |
| `texture` | Generate texture maps. Off returns bare geometry and ignores `pbr` (default: True). | BOOLEAN | No | True<br />False |
| `pbr` | PBR material maps (base color, metallic, roughness, normal). Requires `texture` (default: True). | BOOLEAN | No | True<br />False |
| `image_seed` | Seed value for image generation (default: 42). | INT | No | 0 to 2147483647 |
| `model_seed` | Seed value for model generation (default: 42). | INT | No | 0 to 2147483647 |
| `texture_seed` | Seed value for texture generation (default: 42). | INT | No | 0 to 2147483647 |
| `texture_quality` | Texture detail level (default: "standard"). "detailed" = HD textures, "extreme" = 8K Ultra textures. | COMBO | No | `"standard"`<br />`"detailed"`<br />`"extreme"` |
| `face_limit` | Maximum face count. -1 lets Tripo pick adaptively (about 1.4M faces on v3.x standard, 2M on detailed). Tripo clamps silently: v2.5 at 500,000, quad meshes at 150,000 (default: -1). | INT | No | -1 to 2000000 |
| `quad` | Quad mesh output. Tripo delivers quad meshes as FBX, so the result arrives on the FBX output and the GLB output stays empty (default: False). | BOOLEAN | No | True<br />False |
| `geometry_quality` | Geometry detail level (default: "standard"). | COMBO | No | `"standard"`<br />`"detailed"` |
| `smart_low_poly` | Low-poly mesh with clean, hand-crafted style topology (500-20,000 faces, quad 500-10,000). Best for simple subjects; complex ones may fail (default: False). | BOOLEAN | No | True<br />False |
| `auto_size` | Scale textured models to their real-world size in meters. Tripo stores the size as the model's scene transform and bakes it in when the model is converted, rigged or retargeted; ignored without texture (default: True). | BOOLEAN | No | True<br />False |

### Notes

* `prompt` is required and cannot be empty or whitespace only.
* When `texture` is set to False, `pbr` is forced off, and `auto_size` has no effect.
* When `smart_low_poly` is enabled and `face_limit` is not -1, `face_limit` must be between 500 and 20,000 for triangle meshes, or between 500 and 10,000 when `quad` is enabled.
* With `quad` enabled, Tripo returns an FBX file, so the `GLB` output stays empty and the `FBX` output is populated.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model task_id` | Identifier of the Tripo generation task that produced the model. | MODEL\_TASK\_ID |
| `GLB` | The generated model in GLB format. Empty when `quad` is enabled. | FILE3D\_GLB |
| `FBX` | The generated model in FBX format. Only populated when `quad` is enabled. | FILE3D\_FBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoTextToModelNodeV2/en.md)

***

**Source fingerprint (SHA-256):** `8af7044188c6dbb87d23298bf7b99fe826bdc7bd7ba0948db2066887274faa00`


# TripoTextureNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoTextureNode

This node is marked as deprecated (legacy) in the source; the display name is "Tripo: Texture model (Legacy)".

This node is marked as deprecated (legacy) in the source; the display name is "Tripo: Texture model (Legacy)". The existing documentation's parameter tables remain accurate against the current source. I'll keep them and note the legacy status in the overview.

The Tripo: Texture model (Legacy) node adds textures to an existing Tripo 3D model through the Tripo API. It takes the task ID of a model created by another Tripo node and returns a textured GLB or FBX model once the texture job finishes. You can control the material maps, texture quality, alignment, and seed, and guide the textures with a text prompt, a style image, or reference images. This node is a legacy version of the texture tool.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_task_id` | The Tripo task ID of the model to texture. Accepts model task IDs and segmentation task IDs. | MODEL\_TASK\_ID, SEGMENT\_TASK\_ID | Yes | - |
| `texture` | Ignored: this node always generates textures. Kept for older workflows. (default: True) | BOOLEAN | No | true<br />false |
| `pbr` | PBR material maps (base color, metallic, roughness, normal); off gives a plain color texture. (default: True) | BOOLEAN | No | true<br />false |
| `texture_seed` | Random seed for texture generation. (default: 42) | INT | No | 0 – 2147483647 |
| `texture_quality` | Texture resolution quality: detailed = HD textures, extreme = 8K Ultra textures. (default: "standard"). Approximate cost: standard $0.10, detailed $0.20, extreme \$0.30. | COMBO | No | "standard"<br />"detailed"<br />"extreme" |
| `texture_alignment` | Method used to align the generated textures to the model. (default: "original\_image") | COMBO | No | "original\_image"<br />"geometry" |
| `texture_prompt` | Optional text guidance for texturing. Required in practice for imported models (Tripo: Import Model), which carry no source image to infer colors from. Cannot be combined with reference images. (default: "") | STRING | No | - |
| `model_version` | Texture model: v3.0 for meshes generated with v3.x, v2.5 for meshes generated with v2.5. (default: v3.0\_20250812) | COMBO | No | Multiple options available |
| `style_image` | Reference image for the artistic style of the textures. Only used together with `texture_prompt`. | IMAGE | No | - |
| `reference` | Reference images guiding the textures. Cannot be combined with `texture_prompt` or `style_image`. (default: "none") | DYNAMIC\_COMBO | No | "none"<br />"image"<br />"multiview" |
| `part_names` | Comma-separated part names from Tripo: Segment Model to texture. Empty textures every part. (default: "") | STRING | No | - |

### `image` Reference Inputs

These inputs are available when `reference` is set to `"image"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_image` | Single reference image the textures should follow. | IMAGE | Yes | - |

### `multiview` Reference Inputs

These inputs are available when `reference` is set to `"multiview"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image_front` | Front view (0°). | IMAGE | Yes | - |
| `image_left` | Left view (90°). | IMAGE | Yes | - |
| `image_back` | Back view (180°). | IMAGE | Yes | - |
| `image_right` | Right view (270°). | IMAGE | Yes | - |

**Note:** The `"image"` and `"multiview"` reference modes cannot be combined with a non-empty `texture_prompt` or with `style_image`. The `style_image` input requires a non-empty `texture_prompt`. When `texture_prompt` is left empty, the source model must already have its own source image (for example, models produced by text-to-model, image-to-model, multiview-to-model, or an earlier texturing task). Models that carry no source image — such as imported, segmented, completed, or retopologized models — must be textured with a `texture_prompt`; reference images are accepted only for models the Tripo API generated itself. The `part_names` input can be left empty to texture every part.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model_file` | The generated model file (for backward compatibility only). | STRING |
| `model task_id` | The task ID of the completed texture generation task, usable as input for other Tripo nodes. | MODEL\_TASK\_ID |
| `GLB` | The generated textured model in GLB format. Empty when the source is a quad mesh or an FBX import. | FILE3DGLB |
| `FBX` | The generated textured model in FBX format. Tripo returns FBX for quad meshes and FBX imports; empty otherwise. | FILE3DFBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoTextureNode/en.md)

***

**Source fingerprint (SHA-256):** `850685123b5f14cded5829d86a7307452a1e812e78d11f52806e64ea41d66350`


# TripoTextureNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoTextureNodeV2

This node adds textures to an existing 3D model from a Tripo workflow, identified by a task ID from a previous generation step.

This node adds textures to an existing 3D model from a Tripo workflow, identified by a task ID from a previous generation step. It can produce PBR material maps or a plain color texture, and the result can be guided by a text prompt, a style image, or reference images.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_task_id` | Task ID of the source model produced by an earlier Tripo node (model generation or model segmentation). | MODEL\_TASK\_ID / SEGMENT\_TASK\_ID | Yes | - |
| `pbr` | PBR material maps (base color, metallic, roughness, normal); off gives a plain color texture. (default: true) | BOOLEAN | No | true<br />false |
| `texture_seed` | Seed used for texture generation. (default: 42) Advanced input. | INT | No | 0 to 2147483647 |
| `texture_quality` | Quality of the generated textures. `detailed` = HD textures, `extreme` = 8K Ultra textures. (default: "standard") Advanced input. | COMBO | No | "standard"<br />"detailed"<br />"extreme" |
| `texture_alignment` | How the textures are aligned to the model. (default: "original\_image") Advanced input. | COMBO | No | "original\_image"<br />"geometry" |
| `texture_prompt` | Optional text guidance for texturing. Required in practice for imported models (Tripo: Import Model), which carry no source image to infer colors from. Cannot be combined with reference images. (default: empty) | STRING | No | - |
| `model_version` | Texture model: v3.0 for meshes generated with v3.x, v2.5 for meshes generated with v2.5. (default: v3\_0\_20250812) | COMBO | No | Tripo texture model versions, default "v3\_0\_20250812" |
| `style_image` | Reference image for the artistic style of the textures. Only used together with `texture_prompt`. | IMAGE | No | - |
| `reference` | Reference images guiding the textures. Cannot be combined with `texture_prompt` or `style_image`. (default: "none") | DYNAMIC\_COMBO | No | "none"<br />"image"<br />"multiview" |
| `part_names` | Comma-separated part names from Tripo: Segment Model to texture. Empty textures every part. (default: empty) Advanced input. | STRING | No | - |

### Image Reference Inputs

Shown when `reference` is set to "image".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_image` | Single reference image the textures should follow. | IMAGE | Yes | - |

### Multiview Reference Inputs

Shown when `reference` is set to "multiview".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image_front` | Front view (0°). | IMAGE | Yes | - |
| `image_left` | Left view (90°). | IMAGE | Yes | - |
| `image_back` | Back view (180°). | IMAGE | Yes | - |
| `image_right` | Right view (270°). | IMAGE | Yes | - |

**Notes on parameter constraints:**

* Reference images (reference modes "image" or "multiview") cannot be combined with `texture_prompt` or `style_image`.
* `style_image` requires a `texture_prompt` to be provided.
* When no `texture_prompt` is given, the source model must come from a text-to-model, image-to-model, multiview-to-model, or texture-model task. Models with no source image (imported, segmented, completed, or retopologized models) require a `texture_prompt`, because Tripo accepts reference images only for models it generated itself.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model task_id` | Task ID of the texture operation, which can be passed to other Tripo nodes. | MODEL\_TASK\_ID |
| `GLB` | Textured model in GLB format. Empty when the source is a quad mesh or an FBX import. | FILE\_3D\_GLB |
| `FBX` | Textured model in FBX format. Tripo returns FBX for quad meshes and FBX imports; empty otherwise. | FILE\_3D\_FBX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoTextureNodeV2/en.md)

***

**Source fingerprint (SHA-256):** `dd9b05e37fcdd29896a50451b92a267862ad94b59abfb8680c8b648390cca091`


# BeebleSwitchXVideoEdit - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BeebleSwitchXVideoEdit

Edit a video with Beeble SwitchX.

Edit a video with Beeble SwitchX. This node can switch anything in the scene (background, lighting, costume) while preserving the original subject's pixels and motion. Provide a reference image and/or text prompt to describe the new look. Maximum 240 frames, maximum approximately 2.77 megapixels per frame.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The input video to edit. | VIDEO | Yes | N/A |
| `prompt` | A text description of the desired new look for the scene. | STRING | Yes | N/A |
| `alpha_mode` | The alpha matte mode. "fill" mode has no separate matte and fills the entire frame. "select" mode uses a single keyframe image to define the area to edit. "custom" mode uses a full alpha video to define the area to edit frame by frame. | COMBO | Yes | `"fill"`<br />`"select"`<br />`"custom"` |
| `max_resolution` | The maximum resolution for the output video (default: "1080p"). | COMBO | Yes | `"720p"`<br />`"1080p"` |
| `seed` | A seed value for reproducibility. Using the same seed with the same inputs will produce the same result. | INT | Yes | 0 to 2147483647 |
| `reference_image` | An optional reference image that describes the desired new look for the scene. | IMAGE | No | N/A |

### Alpha Mode Details

The `alpha_mode` parameter controls which parts of the video are edited:

* **fill**: The entire video frame is edited. No separate alpha matte is produced.
* **select**: You provide a single keyframe image that defines the area to edit. The node will use this to determine which parts of the video to change.
* **custom**: You provide a full alpha video that defines the area to edit frame by frame. This gives you precise control over which parts of each frame are edited.

When using `select` mode, you must provide the `alpha_keyframe` image. When using `custom` mode, you must provide the `alpha_mask` video.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The edited video with the scene changes applied. | VIDEO |
| `alpha` | The alpha matte used by Beeble. This is empty for "fill" mode, which has no separate matte. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BeebleSwitchXVideoEdit/en.md)

***

**Source fingerprint (SHA-256):** `a92e78e6a08ac01466d953562a250b812eb8b1a5fb37efce6fddd7aa1ef380a2`


# BriaRemoveVideoBackground - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaRemoveVideoBackground

This node removes the background from a video using the Bria AI service.

This node removes the background from a video using the Bria AI service. It processes the input video and replaces the original background with a solid color of your choice. The operation is performed through an external API, and the result is returned as a new video file.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The input video file from which the background will be removed. | VIDEO | Yes | N/A |
| `background_color` | Background color for the output video. | COMBO | Yes | `"Black"`<br />`"White"`<br />`"Gray"`<br />`"Red"`<br />`"Green"`<br />`"Blue"`<br />`"Yellow"`<br />`"Cyan"`<br />`"Magenta"`<br />`"Orange"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | Yes | 0 to 2147483647 |

**Note:** The input video must have a duration of 60 seconds or less. Results are non-deterministic even if the seed value is unchanged.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The processed video file with the background removed and replaced by the selected color, encoded as MP4 with H.264 codec. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaRemoveVideoBackground/en.md)

***

**Source fingerprint (SHA-256):** `dbd6b7393f893be5a40322fc96b90bb3d5f1818bdda7b8109b28f48baac44d59`


# BriaTransparentVideoBackground - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaTransparentVideoBackground

This node removes the background from a video using Bria's AI service and outputs the cut-out frames along with an alpha mask.

This node removes the background from a video using Bria's AI service and outputs the cut-out frames along with an alpha mask. Connect both outputs to a compositing node, or feed them to a Save WEBM node to write a transparent video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The input video to process. The video must be 60 seconds or shorter. | VIDEO | Yes | - |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0) | INT | Yes | 0 to 2147483647 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The video frames with the background removed, as RGB images in the range 0.0 to 1.0 | IMAGE |
| `mask` | The alpha mask for the video frames, following the Load Image convention where 1 means transparent | MASK |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaTransparentVideoBackground/en.md)

***

**Source fingerprint (SHA-256):** `536bd52af29218d2a342086e92799d3d9310da5ae5cbf02d705ba7503a4d73c8`


# BriaVideoEraser - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaVideoEraser

Erases whatever a per-frame mask covers from a video with Bria and fills the gap in.

Erases whatever a per-frame mask covers from a video with Bria and fills the gap in. The mask must be white on what should go and black elsewhere. Bria accepts clips of at most 5.1 seconds at 20 to 30 frames per second with even pixel dimensions; audio is kept by default. The returned clip can be a few frames shorter than the input.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Clip to erase from. | VIDEO | Yes | - |
| `mask` | One mask per frame of the video, white where the object to erase is. Provide either a mask or a mask video, not both. | MASK | No | - |
| `mask_video` | An already encoded mask video with the same dimensions and frame count as the video. Provide either a mask or a mask video, not both. | VIDEO | No | - |
| `preserve_audio` | Keep the input's audio track. Default: true. | BOOLEAN | No | `true`<br />`false` |

**Notes on constraints:**

* Exactly one of `mask` or `mask_video` must be connected. An error is raised if neither is provided, or if both are provided.
* The video must be at most 5.1 seconds long and must run at 20 to 30 frames per second. Re-time the clip with Get Video Components and Create Video if needed.
* The video must have even pixel dimensions (width and height divisible by 2). Crop or scale it first otherwise.
* When using `mask`, it must contain one mask frame per video frame, and its aspect ratio must match the video. Masks are binarized at 50%: areas painted at less than half opacity are ignored, and an empty mask raises an error. If the mask resolution differs from the video, it is resized to the video dimensions.
* When using `mask_video`, it must have the same dimensions and the same frame count as the video.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The edited clip with the masked areas erased and the gaps filled in. The output may be a few frames shorter than the input clip. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaVideoEraser/en.md)

***

**Source fingerprint (SHA-256):** `525b90013b9d9ea4b224caf1f32479493c96f90e28acbf3cf7a4d16a6ca91a45`


# BriaVideoGreenScreen - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaVideoGreenScreen

This node replaces a video's background with a solid chroma-key screen using the Bria API.

This node replaces a video's background with a solid chroma-key screen using the Bria API. It processes the input video and returns a new video where the original background has been removed and replaced with a uniform green or blue screen color.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The input video to process | VIDEO | Yes | Video file |
| `green_shade` | Solid chroma-key shade applied behind the foreground: `broadcast_green` (#00B140), `chroma_green` (#00FF00), or `blue_screen` (#0000FF). | COMBO | Yes | `"broadcast_green"`<br />`"chroma_green"`<br />`"blue_screen"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). | INT | Yes | 0 to 2147483647 |

**Note:** The input video must not exceed 60 seconds in duration.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The processed video (MP4, H.264) with the original background replaced by the selected chroma-key shade | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaVideoGreenScreen/en.md)

***

**Source fingerprint (SHA-256):** `70d2951d0adbbe7492b2bc97d04be6591b65f040ca4b414754ad6365c5db45cf`


# BriaVideoReplaceBackground - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaVideoReplaceBackground

This node replaces the background of a video with a supplied image or video using Bria's API.

This node replaces the background of a video with a supplied image or video using Bria's API. The output keeps the foreground video's resolution and frame rate; a background with a different aspect ratio is stretched to fit, so matching aspect ratios produces undistorted results.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Foreground video whose background is replaced. | VIDEO | Yes | - |
| `background_image` | Background image to composite behind the foreground. Provide either a background image or a background video, not both. | IMAGE | No | - |
| `background_video` | Background video to composite behind the foreground. Provide either a background image or a background video, not both. | VIDEO | No | - |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | Yes | 0 to 2147483647 |

**Note:** You must provide exactly one of `background_image` or `background_video` — not both and not neither. The foreground video and the background video (if used) must each be 60 seconds or shorter. When `background_image` is used, its alpha channel is removed before processing.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The resulting video with the background replaced, encoded as MP4 (H.264). | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaVideoReplaceBackground/en.md)

***

**Source fingerprint (SHA-256):** `c487cf7dd434b8523ce64f241c2171c82bb5e0abdc5c3ca3e8b1a1259aeab490`


# ByteDance2DraftToFinalVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDance2DraftToFinalVideoNode

This node renders the 1080p final video of a Seedance 2.5 Draft.

This node renders the 1080p final video of a Seedance 2.5 Draft. A draft is a fast 480p preview: in a Seedance 2.5 video node (text to video, first-last-frame to video, or reference to video), set `model` to `Seedance 2.5 Draft`, run it, and connect its `draft_task_id` output here. The final keeps the draft's scene and motion, and reuses the prompt, references, duration, aspect ratio, and audio setting that produced the draft.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `draft_task_id` | The `draft_task_id` output of a Seedance 2.5 node run with the Seedance 2.5 Draft model, or a pasted draft task ID. When you rerun the producer node, set its seed control to fixed, otherwise the next run generates a new draft instead of reusing the one you reviewed. | STRING | Yes | - |
| `watermark` | Whether to add a watermark to the video. Default is False. This is an advanced setting. | BOOLEAN | No | True / False |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The rendered 1080p final video, downloaded from the provider once the render task completes. | VIDEO |

**Note:** A draft can be rendered for 7 days after it was created. The draft task ID identifies the draft on its own, so the prompt, references, duration, aspect ratio, and audio setting do not need to be passed again.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDance2DraftToFinalVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `c9a607826915f09ec199748964010a00a239b5efab3647a3b97fdceee6b04cde`


# ByteDance2FirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDance2FirstLastFrameNode

This node generates a video from a required first frame image and an optional last frame image using ByteDance Seedance models.

This node generates a video from a required first frame image and an optional last frame image using ByteDance Seedance models. You describe the video with a text prompt; the first frame guides the start of the video and the last frame guides the end. It supports Seedance 2.5 and the Seedance 2.0 family (Seedance 2.0, Seedance 2.0 Fast, and Seedance 2.0 Mini). Selecting the `Seedance 2.5 Draft` model renders a fast 480p preview instead; connect the resulting `draft_task_id` to the ByteDance Seedance 2.5 Draft to Final Video node to render the 1080p final.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Seedance 2.5 for the newest model, videos up to 30 seconds and mp4 output; Seedance 2.5 Draft for a fast 480p preview whose `draft_task_id` output renders the 1080p final in the ByteDance Seedance 2.5 Draft to Final Video node; Seedance 2.0 for maximum quality and 4k; Fast for speed optimization; Mini for the fastest, lowest-cost generation. Selecting a model reveals model-specific inputs below. | DYNAMIC\_COMBO | Yes | `"Seedance 2.5"`<br />`"Seedance 2.5 Draft"`<br />`"Seedance 2.0"`<br />`"Seedance 2.0 Fast"`<br />`"Seedance 2.0 Mini"` |
| `first_frame` | First frame image for the video. | IMAGE | No | - |
| `last_frame` | Last frame image for the video. | IMAGE | No | - |
| `first_frame_asset_id` | Seedance asset\_id to use as the first frame. Mutually exclusive with the `first_frame` image input. Default is an empty string. | STRING | No | - |
| `last_frame_asset_id` | Seedance asset\_id to use as the last frame. Mutually exclusive with the `last_frame` image input. Default is an empty string. | STRING | No | - |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. Default is 0. | INT | Yes | 0 to 2147483647 |
| `watermark` | Whether to add a watermark to the video. Default is False. | BOOLEAN | Yes | False<br />True |

### Seedance 2.5 Inputs

These inputs appear when `Seedance 2.5` is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Put spoken lines in double quotes to steer the generated dialogue. | STRING | Yes | - |
| `resolution` | Resolution of the output video. Default is 720p. | COMBO | Yes | `"480p"`<br />`"720p"`<br />`"1080p"` |
| `duration` | Duration of the output video in seconds (4-30). Default is 5. | INT | Yes | 4 to 30 |
| `generate_audio` | Enable audio generation for the output video. Default is True. | BOOLEAN | Yes | False<br />True |
| `output_format` | Container format of the output video. Default is mp4. | COMBO | Yes | `"mp4"` |

### Seedance 2.5 Draft Inputs

These inputs appear when `Seedance 2.5 Draft` is selected. The parameter set matches Seedance 2.5 above, except that `resolution` offers only `"480p"` (default `"480p"`).

### Seedance 2.0 Inputs

These inputs appear when `Seedance 2.0` is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. | STRING | Yes | - |
| `resolution` | Resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"`<br />`"1080p"`<br />`"4k"` |
| `ratio` | Aspect ratio of the output video. Default is `adaptive`, which uses the nearest supported ratio to the input frame's aspect ratio. | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`<br />`"adaptive"` |
| `duration` | Duration of the output video in seconds (4-15). Default is 7. | INT | Yes | 4 to 15 |
| `generate_audio` | Enable audio generation for the output video. Default is True. | BOOLEAN | Yes | False<br />True |

### Seedance 2.0 Fast and Seedance 2.0 Mini Inputs

Shared by `Seedance 2.0 Fast` and `Seedance 2.0 Mini`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. | STRING | Yes | - |
| `resolution` | Resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"` |
| `ratio` | Aspect ratio of the output video. Default is `adaptive`, which uses the nearest supported ratio to the input frame's aspect ratio. | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`<br />`"adaptive"` |
| `duration` | Duration of the output video in seconds (4-15). Default is 7. | INT | Yes | 4 to 15 |
| `generate_audio` | Enable audio generation for the output video. Default is True. | BOOLEAN | Yes | False<br />True |

**Parameter Constraints**

* You must provide the first frame either as a `first_frame` image or as a `first_frame_asset_id`. Providing both raises an error; providing neither also raises an error.
* The `last_frame` and `last_frame_asset_id` inputs are optional, but you cannot provide both for the same frame.
* Asset IDs must reference existing, active Seedance Image assets.
* The `prompt` input is required and cannot be empty.
* Every run returns its task ID as `draft_task_id`, but only a `Seedance 2.5 Draft` run's ID can be rendered by the ByteDance Seedance 2.5 Draft to Final Video node. With any other model the output must be left unconnected, otherwise the run fails.
* With `Seedance 2.5`, the output aspect ratio is always adaptive and follows the first frame's own aspect ratio, so no `ratio` input is shown.
* With Seedance 2.0 family models and local frame images, the images are center-cropped and resized to the target output resolution and ratio before generation. When `ratio` is `adaptive`, the nearest supported ratio to the input image is used.
* Local frame images are validated for supported aspect ratio and dimensions; oversized images are downscaled.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video. | VIDEO |
| `draft_task_id` | Task ID returned by the run. Only a `Seedance 2.5 Draft` run produces a draft that the ByteDance Seedance 2.5 Draft to Final Video node can render; with any other model the output must be left unconnected, otherwise the run fails. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDance2FirstLastFrameNode/en.md)

***

**Source fingerprint (SHA-256):** `363f1baac1685c2dada0e64a0b339f6ab2671161dccb002eb81f6b4f0d0aa243`


# ByteDance2ReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDance2ReferenceNode

This node generates, edits, or extends videos using ByteDance's Seedance 2.5 or Seedance 2.0 AI models.

This node generates, edits, or extends videos using ByteDance's Seedance 2.5 or Seedance 2.0 AI models. You describe the video in a text prompt and can attach reference images, videos, and audio to guide the result, with support for multimodal reference, video editing, and video extension. This is the legacy, deprecated version of the Seedance reference-to-video node.

## Inputs

Selecting a `model` determines which of the parameters below are available. `video_editing` and `output_format` appear only when Seedance 2.5 is selected. The growable reference slots and the reference-video auto-resize options are shared by all models and are described under Reference Inputs.

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model used to generate the video. Seedance 2.5 for the newest model, videos up to 30 seconds and mp4/mov output; Seedance 2.0 for maximum quality and 4k; Fast for speed optimization; Mini for the fastest, lowest-cost generation. Selecting a model reveals the model-specific inputs listed below. | DYNAMIC\_COMBO | Yes | `"Seedance 2.5"`<br />`"Seedance 2.0"`<br />`"Seedance 2.0 Fast"`<br />`"Seedance 2.0 Mini"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). | INT | Yes | 0 to 2147483647<br />Step: 1 |
| `watermark` | Whether to add a watermark to the video (default: False). Advanced setting. | BOOLEAN | Yes | `True`<br />`False` |

### Seedance 2.5 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Put spoken lines in double quotes to steer the generated dialogue. Must contain at least one non-whitespace character (default: empty). | STRING | Yes | Any text |
| `resolution` | Resolution of the output video (default: `"720p"`). | COMBO | Yes | `"480p"`<br />`"720p"`<br />`"1080p"` |
| `ratio` | Aspect ratio of the output video (default: `"16:9"`). | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`<br />`"adaptive"` |
| `duration` | Duration of the output video in seconds (default: 5). | INT | Yes | 4 to 30<br />Step: 1 |
| `generate_audio` | Enable audio generation for the output video (default: True). | BOOLEAN | Yes | `True`<br />`False` |
| `video_editing` | Enable when the prompt edits a connected reference video, for example replacing an object in it. The output then keeps the source clip's own length and aspect ratio, and the duration and ratio widgets are ignored. Leave disabled to generate a new video, or to extend one to the duration you set (default: False). | BOOLEAN | Yes | `True`<br />`False` |
| `output_format` | Container format of the output video (default: `"mp4"`). | COMBO | Yes | `"mp4"` |

### Seedance 2.0 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Must contain at least one non-whitespace character (default: empty). | STRING | Yes | Any text |
| `resolution` | Resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"`<br />`"1080p"`<br />`"4k"` |
| `ratio` | Aspect ratio of the output video (default: `"adaptive"`). | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`<br />`"adaptive"` |
| `duration` | Duration of the output video in seconds (default: 7). | INT | Yes | 4 to 15<br />Step: 1 |
| `generate_audio` | Enable audio generation for the output video (default: True). | BOOLEAN | Yes | `True`<br />`False` |

### Seedance 2.0 Fast and Seedance 2.0 Mini Inputs

Shared by Seedance 2.0 Fast and Seedance 2.0 Mini. These two models expose the same input set as Seedance 2.0, except that `resolution` is limited to 480p and 720p.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Must contain at least one non-whitespace character (default: empty). | STRING | Yes | Any text |
| `resolution` | Resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"` |
| `ratio` | Aspect ratio of the output video (default: `"adaptive"`). | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`<br />`"adaptive"` |
| `duration` | Duration of the output video in seconds (default: 7). | INT | Yes | 4 to 15<br />Step: 1 |
| `generate_audio` | Enable audio generation for the output video (default: True). | BOOLEAN | Yes | `True`<br />`False` |

### Reference Inputs

Available for all models. The maximum number of slots depends on the selected model: Seedance 2.5 supports more references than the Seedance 2.0 models.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect one or more reference images (`image_1`, `image_2`, ...) that guide the video generation. Images are auto-downscaled to a maximum side of 6000 pixels and must be at least 300x300 pixels with an aspect ratio between 0.4 and 2.5. | IMAGE | No | Up to 30 (Seedance 2.5)<br />Up to 9 (Seedance 2.0 models) |
| `reference_videos` | Growable slot: connect one or more reference videos (`video_1`, `video_2`, ...) that guide the video generation; used for video editing and extension. | VIDEO | No | Up to 10 (Seedance 2.5)<br />Up to 3 (Seedance 2.0 models) |
| `reference_audios` | Growable slot: connect one or more reference audio clips (`audio_1`, `audio_2`, ...) that guide the video generation. | AUDIO | No | Up to 10 (Seedance 2.5)<br />Up to 3 (Seedance 2.0 models) |
| `auto_downscale` | Automatically downscale reference videos that exceed the model's pixel budget for the selected resolution. Aspect ratio is preserved; videos already within limits are untouched (default: True). | BOOLEAN | No | `True`<br />`False` |
| `auto_upscale` | Advanced setting. Automatically upscale reference videos that are below the model's minimum pixel count for the selected resolution. Aspect ratio is preserved; videos already meeting the minimum are untouched. Note: upscaling a low-resolution source does not add real detail and may produce lower-quality generations (default: False). | BOOLEAN | No | `True`<br />`False` |
| `reference_assets` | Growable slot: IDs of previously created Seedance virtual-library assets (Image, Video, or Audio) to use as references (`asset_1`, `asset_2`, ...). Each asset must exist and have an Active status. In the prompt, assets can be referred to as `asset1`, `asset 1`, etc.; the node replaces these tokens with labels such as "Image 2". | STRING | No | Up to 30 (Seedance 2.5)<br />Up to 9 (Seedance 2.0 models) |

**Important Constraints:**

* At least one reference is required. For Seedance 2.0, 2.0 Fast, and 2.0 Mini, you must provide at least one image or video reference (via `reference_images`, `reference_videos`, or an image or video entry in `reference_assets`). Seedance 2.5 additionally accepts audio-only references (via `reference_audios` or an audio `reference_assets` entry).
* Reference counts are model-dependent and are validated across direct inputs and asset references combined: Seedance 2.5 allows up to 30 `reference_images`, 10 `reference_videos`, 10 `reference_audios`, and 30 `reference_assets`; the Seedance 2.0 models allow up to 9 images, 3 videos, 3 audio clips, and 9 assets.
* Each reference video must be at least 1.8 seconds long, and each reference audio clip must be at least 1.8 seconds long. The total duration of all reference videos and of all reference audios must stay within the selected model's limit (15.1 seconds for the Seedance 2.0 models).
* Reference videos must also meet the model's pixel-count limits for the selected resolution. With `auto_downscale` enabled (default), oversized videos are automatically resized; with `auto_upscale` enabled, undersized videos are enlarged. If either automatic adjustment is disabled, videos outside the corresponding limit raise an error.
* When `video_editing` is enabled on Seedance 2.5, the `duration` and `ratio` inputs are ignored; the output matches the reference video's own length and aspect ratio. If the provider interprets the prompt as editing a reference video, generation fails unless `video_editing` is enabled or the prompt is reworded to describe a new video.
* If the provider rejects the audio track generated for the video (for example, a possible copyright match), the task fails; disabling `generate_audio` produces a silent video.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDance2ReferenceNode/en.md)

***

**Source fingerprint (SHA-256):** `4a1b62f65ff3515cdb749c9b3916e631e53523fe144e8cdf71ca020825196ae6`


# ByteDance2ReferenceNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDance2ReferenceNodeV2

ByteDance Seedance 2.5 Reference to Video generates, edits, or extends videos using ByteDance Seedance models (Seedance 2.5, 2.5 Draft, 2.0, 2.0 Fast, and 2.0 Mini) guided by a tex

ByteDance Seedance 2.5 Reference to Video generates, edits, or extends videos using ByteDance Seedance models (Seedance 2.5, 2.5 Draft, 2.0, 2.0 Fast, and 2.0 Mini) guided by a text prompt and optional reference images, videos, audio, or previously uploaded library assets. It uploads the references, submits a generation task, waits for completion, and returns the finished video file. Selecting `Seedance 2.5 Draft` renders a fast 480p preview instead; connect the resulting `draft_task_id` to the ByteDance Seedance 2.5 Draft to Final Video node to render the 1080p final.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model selector. Seedance 2.5 for the newest model, videos up to 30 seconds and mp4 output; Seedance 2.5 Draft for a fast 480p preview whose `draft_task_id` output renders the 1080p final in the ByteDance Seedance 2.5 Draft to Final Video node; Seedance 2.0 for maximum quality and 4k; Fast for speed optimization; Mini for the fastest, lowest-cost generation. Selecting a model changes the input widgets shown below. | DYNAMIC\_COMBO | Yes | "Seedance 2.5"<br />"Seedance 2.5 Draft"<br />"Seedance 2.0"<br />"Seedance 2.0 Fast"<br />"Seedance 2.0 Mini" |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. Default: 0. | INT | Yes | 0 to 2147483647 |
| `watermark` | Whether to add a watermark to the video. Default: False. Advanced setting. | BOOLEAN | Yes | true<br />false |

### Seedance 2.5 Inputs

These inputs appear when `model` is set to "Seedance 2.5".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Put spoken lines in double quotes to steer the generated dialogue. Default: empty string. | STRING | Yes | Multiline text |
| `resolution` | Resolution of the output video. Default: 720p. | COMBO | Yes | "480p"<br />"720p"<br />"1080p" |
| `ratio` | Aspect ratio of the output video. Default: 16:9. | COMBO | Yes | "16:9"<br />"4:3"<br />"1:1"<br />"3:4"<br />"9:16"<br />"21:9"<br />"adaptive" |
| `duration` | Duration of the output video in seconds (4-30). Default: 5. | INT | Yes | 4 to 30 |
| `generate_audio` | Enable audio generation for the output video. Default: True. | BOOLEAN | Yes | true<br />false |
| `task_type` | What to do with the reference media. Every value except auto is validated when the task is submitted, so mismatched settings fail before generation starts.<br />auto: the model infers the task from the prompt and inputs, and settings that conflict with its reading fail only after generation has started.<br />reference: generate a new video guided by the reference images, videos, and audio.<br />edit: change a connected reference video (add, remove, replace); the output keeps the source clip's own length and aspect ratio, and the duration and ratio widgets are ignored.<br />extend: continue a connected reference video forward or backward; the prompt should say "extend forward", "extend backward", or "continue", the aspect ratio follows the source clip, and the output contains only the newly generated segment of the duration you set, not the source clip. Default: auto. | COMBO | Yes | "auto"<br />"reference"<br />"edit"<br />"extend" |
| `output_format` | Container format of the output video. Default: mp4. | COMBO | Yes | "mp4" |

### Seedance 2.5 Draft Inputs

These inputs appear when `model` is set to "Seedance 2.5 Draft". The parameter set matches Seedance 2.5 above, except that `resolution` offers only `"480p"` (default `"480p"`).

### Seedance 2.0 Inputs

These inputs appear when `model` is set to "Seedance 2.0".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Default: empty string. | STRING | Yes | Multiline text |
| `resolution` | Resolution of the output video. | COMBO | Yes | "480p"<br />"720p"<br />"1080p"<br />"4k" |
| `ratio` | Aspect ratio of the output video. Default: adaptive. | COMBO | Yes | "16:9"<br />"4:3"<br />"1:1"<br />"3:4"<br />"9:16"<br />"21:9"<br />"adaptive" |
| `duration` | Duration of the output video in seconds (4-15). Default: 7. | INT | Yes | 4 to 15 |
| `generate_audio` | Enable audio generation for the output video. Default: True. | BOOLEAN | Yes | true<br />false |

### Seedance 2.0 Fast and Seedance 2.0 Mini Inputs

These inputs appear when `model` is set to "Seedance 2.0 Fast" or "Seedance 2.0 Mini". Both models share the same input set.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Default: empty string. | STRING | Yes | Multiline text |
| `resolution` | Resolution of the output video. | COMBO | Yes | "480p"<br />"720p" |
| `ratio` | Aspect ratio of the output video. Default: adaptive. | COMBO | Yes | "16:9"<br />"4:3"<br />"1:1"<br />"3:4"<br />"9:16"<br />"21:9"<br />"adaptive" |
| `duration` | Duration of the output video in seconds (4-15). Default: 7. | INT | Yes | 4 to 15 |
| `generate_audio` | Enable audio generation for the output video. Default: True. | BOOLEAN | Yes | true<br />false |

### Reference Inputs

These growable reference slots are available for all models. The maximum number of slots differs per model: Seedance 2.5 supports up to 30 images, 10 videos, 10 audios, and 30 assets; Seedance 2.0, 2.0 Fast, and 2.0 Mini support up to 9 images, 3 videos, 3 audios, and 9 assets.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect 1..N reference images that guide the output. The count limit is per model (see model sections). Images are validated for aspect ratio (0.4 to 2.5) and auto-downscaled to a maximum side of 6000 pixels. | IMAGE | No | 1..9 slots (Seedance 2.0 family)<br />1..30 slots (Seedance 2.5) |
| `reference_videos` | Growable slot: connect 1..N reference videos. The count limit is per model (see model sections). Each video must be at least 1.8 seconds long and must fit the pixel limits for the selected model and resolution. | VIDEO | No | 1..3 slots (Seedance 2.0 family)<br />1..10 slots (Seedance 2.5) |
| `reference_audios` | Growable slot: connect 1..N reference audio tracks. The count limit is per model (see model sections). Each audio must be at least 1.8 seconds long. | AUDIO | No | 1..3 slots (Seedance 2.0 family)<br />1..10 slots (Seedance 2.5) |
| `reference_assets` | Growable slot: connect 1..N asset ID strings for media already uploaded to the Seedance virtual library. Each asset must be Active. You can refer to an asset in the prompt with tokens such as `asset1` or `asset 1`; the node replaces them with the asset's positional label (for example "Image 2" or "Video 1"). | STRING | No | 1..9 slots (Seedance 2.0 family)<br />1..30 slots (Seedance 2.5) |
| `auto_downscale` | Automatically downscale reference videos that exceed the model's pixel budget for the selected resolution. Aspect ratio is preserved; videos already within limits are untouched. Default: True. | BOOLEAN | No | true<br />false |
| `auto_upscale` | Automatically upscale reference videos that are below the model's minimum pixel count for the selected resolution. Aspect ratio is preserved; videos already meeting the minimum are untouched. Note: upscaling a low-resolution source does not add real detail and may produce lower-quality generations. Default: False. Advanced setting. | BOOLEAN | No | true<br />false |

**Note:** At least one reference image, video, or asset is required to run the node (Seedance 2.5 also accepts audio-only references). Reference videos and audios must each be at least 1.8 seconds long, and the combined duration of all reference videos (and separately, all reference audios) must not exceed the selected model's maximum total seconds. Reference images must have an aspect ratio between roughly 2:5 and 5:2 (0.4 to 2.5), be at least 300x300 pixels, and are automatically downscaled to a maximum side of 6000 pixels. The `task_type` "edit" and "extend" options are only available with Seedance 2.5 and both require at least one reference video; when "edit" is used, the output keeps the source clip's own length and aspect ratio and the `duration` and `ratio` widgets are ignored, and when "extend" is used, the output contains only the newly generated segment at the duration you set. Referenced assets must be in Active status, otherwise the task fails. Every run returns its task ID as `draft_task_id`, but only a `Seedance 2.5 Draft` run's ID can be rendered by the ByteDance Seedance 2.5 Draft to Final Video node, so with any other model the output must be left unconnected, otherwise the run fails.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video, downloaded from the provider once the generation task completes. Contains audio when audio generation is enabled. | VIDEO |
| `draft_task_id` | Task ID returned by the run. Only a `Seedance 2.5 Draft` run produces a draft that the ByteDance Seedance 2.5 Draft to Final Video node can render; with any other model the output must be left unconnected, otherwise the run fails. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDance2ReferenceNodeV2/en.md)

***

**Source fingerprint (SHA-256):** `12fee29b280ff71e29f268f52131d1c15cf3066e0804356b735b61d97c80a6a9`


# ByteDance2TextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDance2TextToVideoNode

This node generates a video from a text prompt using ByteDance's Seedance 2.5 or 2.0 models.

This node generates a video from a text prompt using ByteDance's Seedance 2.5 or 2.0 models. It sends the prompt to the selected model, waits for the video to finish processing, and returns the resulting video file. Selecting the `Seedance 2.5 Draft` model renders a fast 480p preview instead; connect the resulting `draft_task_id` to the ByteDance Seedance 2.5 Draft to Final Video node to render the 1080p final.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Seedance model to use for video generation. Seedance 2.5 is the newest model, supporting videos up to 30 seconds and mp4 output; Seedance 2.5 Draft renders a fast 480p preview whose `draft_task_id` output renders the 1080p final in the ByteDance Seedance 2.5 Draft to Final Video node; Seedance 2.0 is for maximum quality and 4k; Seedance 2.0 Fast is for speed optimization; Seedance 2.0 Mini is for the fastest, lowest-cost generation. Selecting a model reveals additional inputs for the prompt, resolution, aspect ratio, duration, and audio generation. | DYNAMIC\_COMBO | Yes | `"Seedance 2.5"`<br />`"Seedance 2.5 Draft"`<br />`"Seedance 2.0"`<br />`"Seedance 2.0 Fast"`<br />`"Seedance 2.0 Mini"` |
| `seed` | Controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | No | 0 to 2147483647 |
| `watermark` | Whether to add a watermark to the video. (default: False) This is an advanced setting. | BOOLEAN | No | True / False |

### Seedance 2.5 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Put spoken lines in double quotes to steer the generated dialogue. | STRING | Yes | — |
| `resolution` | Resolution of the output video. (default: `"720p"`) | COMBO | Yes | `"480p"`<br />`"720p"`<br />`"1080p"` |
| `ratio` | Aspect ratio of the output video. (default: `"16:9"`) | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`<br />`"adaptive"` |
| `duration` | Duration of the output video in seconds. (default: 5) | INT | Yes | 4 to 30 |
| `generate_audio` | Enable audio generation for the output video. (default: True) | BOOLEAN | Yes | True / False |
| `output_format` | Container format of the output video. (default: `"mp4"`) | COMBO | Yes | `"mp4"` |

### Seedance 2.5 Draft Inputs

These inputs appear when `Seedance 2.5 Draft` is selected. The parameter set matches Seedance 2.5 above, except that `resolution` offers only `"480p"` (default `"480p"`).

### Seedance 2.0 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. | STRING | Yes | — |
| `resolution` | Resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"`<br />`"1080p"`<br />`"4k"` |
| `ratio` | Aspect ratio of the output video. (default: `"16:9"`) | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`<br />`"adaptive"` |
| `duration` | Duration of the output video in seconds. (default: 7) | INT | Yes | 4 to 15 |
| `generate_audio` | Enable audio generation for the output video. (default: True) | BOOLEAN | Yes | True / False |

### Seedance 2.0 Fast and Seedance 2.0 Mini Inputs

Shared by Seedance 2.0 Fast and Seedance 2.0 Mini; both models expose the same parameters.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. | STRING | Yes | — |
| `resolution` | Resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"` |
| `ratio` | Aspect ratio of the output video. (default: `"16:9"`) | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`<br />`"adaptive"` |
| `duration` | Duration of the output video in seconds. (default: 7) | INT | Yes | 4 to 15 |
| `generate_audio` | Enable audio generation for the output video. (default: True) | BOOLEAN | Yes | True / False |

**Note:** The `model` selector is dynamic; the inputs shown under each model section appear when that model is selected. The prompt must be at least 1 character long after removing whitespace. Resolution and duration limits depend on the selected model: Seedance 2.5 supports 480p/720p/1080p and 4 to 30 seconds, Seedance 2.0 supports 480p/720p/1080p/4k and 4 to 15 seconds, and Seedance 2.0 Fast and Seedance 2.0 Mini support only 480p/720p and 4 to 15 seconds; Seedance 2.5 Draft supports 480p only and 4 to 30 seconds. Every run returns its task ID as `draft_task_id`, but only a `Seedance 2.5 Draft` run's ID can be rendered by the ByteDance Seedance 2.5 Draft to Final Video node, so with any other model the output must be left unconnected, otherwise the run fails. The `seed` value only controls whether the node re-runs; it does not make results deterministic.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video file. | VIDEO |
| `draft_task_id` | Task ID returned by the run. Only a `Seedance 2.5 Draft` run produces a draft that the ByteDance Seedance 2.5 Draft to Final Video node can render; with any other model the output must be left unconnected, otherwise the run fails. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDance2TextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `2abad0c4eab5a1286c8da9237bcec52b275c40188b3b7dc9eede5d5f4cbb11d3`


# ByteDanceCreateVideoAsset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceCreateVideoAsset

This node creates a personal video asset for Seedance 2.0.

This node creates a personal video asset for Seedance 2.0. It uploads your input video and registers it within a specified asset group. If you don't provide a group ID, it will guide you through a real-person verification process in your browser to create a new group first.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Video to register as a personal asset. | VIDEO | Yes | - |
| `group_id` | Reuse an existing Seedance asset group ID to skip repeated human verification for the same person. Leave empty to run real-person authentication in the browser and create a new group. (default: empty string) | STRING | No | - |

**Video Constraints:**

* **Duration:** Must be between 2 and 15 seconds.
* **Dimensions:** Width and height must each be between 300 and 6000 pixels.
* **Aspect Ratio:** The width-to-height ratio must be between 0.4 and 2.5.
* **Total Pixels:** The total number of pixels (width × height) must be between 409,600 and 927,408.
* **Frame Rate:** Must be between 24 and 60 frames per second (FPS).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `asset_id` | The unique identifier for the newly created video asset. | STRING |
| `group_id` | The identifier of the asset group containing the new video. This will be the provided `group_id` or a newly created one. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceCreateVideoAsset/en.md)

***

**Source fingerprint (SHA-256):** `2c7376185f3273a80c763c2c9bd41305575b58e7902200ff77bebb609aea58b8`


# ByteDanceFirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceFirstLastFrameNode

This node generates a video using a text prompt along with first and last frame images.

This node generates a video using a text prompt along with first and last frame images. It takes your description and the two key frames to create a complete video sequence that transitions between them. The node provides various options to control the video's resolution, aspect ratio, duration, and other generation parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model used for video generation (default: `"seedance-1-5-pro-251215"`). | COMBO | Yes | `"seedance-1-5-pro-251215"`<br />`"seedance-1-0-pro-250528"` |
| `prompt` | The text prompt used to generate the video. Must not be empty and must not contain reserved parameter keywords (`resolution`, `ratio`, `duration`, `seed`, `camerafixed`, `watermark`). | STRING | Yes | - |
| `first_frame` | First frame to be used for the video. Must be between 300x300 and 6000x6000 pixels, with an aspect ratio between 0.4 and 2.5. | IMAGE | Yes | - |
| `last_frame` | Last frame to be used for the video. Must be between 300x300 and 6000x6000 pixels, with an aspect ratio between 0.4 and 2.5. | IMAGE | Yes | - |
| `resolution` | The resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"`<br />`"1080p"` |
| `aspect_ratio` | The aspect ratio of the output video. | COMBO | Yes | `"adaptive"`<br />`"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"` |
| `duration` | The duration of the output video in seconds. When using `seedance-1-5-pro-251215`, the minimum duration is 4 seconds. (default: 5) | INT | Yes | 3 - 12 |
| `seed` | Seed to use for generation. (default: 0) | INT | No | 0 - 2147483647 |
| `camera_fixed` | Specifies whether to fix the camera. The platform appends an instruction to fix the camera to your prompt, but does not guarantee the actual effect. (default: False) | BOOLEAN | No | - |
| `watermark` | Whether to add an "AI generated" watermark to the video. (default: False) | BOOLEAN | No | - |
| `generate_audio` | This parameter is ignored for any model except `seedance-1-5-pro-251215`. (default: False) | BOOLEAN | No | - |

**Note:** For the `seedance-1-5-pro-251215` model, `duration` must be 4 seconds or greater. Both `first_frame` and `last_frame` must be between 300x300 and 6000x6000 pixels and have an aspect ratio between 0.4 and 2.5. The `prompt` is checked and rejected if it contains reserved parameter keywords.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceFirstLastFrameNode/en.md)

***

**Source fingerprint (SHA-256):** `ae0f3a34a21baad7f04f6917e98d16dc64496479a050896869ec6693a9a9ebaf`


# ByteDanceImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceImageToVideoNode

The ByteDance Image to Video node generates videos using ByteDance models through an API based on an input image and text prompt.

The ByteDance Image to Video node generates videos using ByteDance models through an API based on an input image and text prompt. It takes a starting image frame and creates a video sequence that follows the provided description. The node offers various customization options for video resolution, aspect ratio, duration, and other generation parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The ByteDance model to use for video generation (default: `"seedance-1-0-pro-fast-251015"`). | COMBO | Yes | `"seedance-1-5-pro-251215"`<br />`"seedance-1-0-pro-250528"`<br />`"seedance-1-0-pro-fast-251015"` |
| `prompt` | The text prompt used to generate the video. Must be at least 1 character long after trimming whitespace. | STRING | Yes | - |
| `image` | First frame to be used for the video. Must be between 300x300 and 6000x6000 pixels, with an aspect ratio between 0.4 and 2.5. | IMAGE | Yes | - |
| `resolution` | The resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"`<br />`"1080p"` |
| `aspect_ratio` | The aspect ratio of the output video. | COMBO | Yes | `"adaptive"`<br />`"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"` |
| `duration` | The duration of the output video in seconds (default: 5). For the `seedance-1-5-pro-251215` model, the minimum supported duration is 4 seconds. | INT | Yes | 3 - 12 |
| `seed` | Seed to use for generation (default: 0). | INT | No | 0 - 2147483647 |
| `camera_fixed` | Specifies whether to fix the camera. The platform appends an instruction to fix the camera to your prompt, but does not guarantee the actual effect (default: False). | BOOLEAN | No | `False`<br />`True` |
| `watermark` | Whether to add an "AI generated" watermark to the video (default: False). | BOOLEAN | No | `False`<br />`True` |
| `generate_audio` | This parameter is ignored for any model except `seedance-1-5-pro-251215` (default: False). | BOOLEAN | No | `False`<br />`True` |

**Note:** The prompt must not contain the following words (case-insensitive): `resolution`, `ratio`, `duration`, `seed`, `camerafixed`, `watermark`. These parameters are set via their dedicated inputs.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file based on the input image and prompt parameters. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `9f4ad18642533689f9c664f2ca6a4ce8e92c8698754cdf9b6bb2d2735bc80415`


# ByteDanceSeedNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceSeedNode

Generate text responses with ByteDance's Seed 2.0 models.

Generate text responses with ByteDance's Seed 2.0 models. Provide a text prompt and optionally connect images or videos to give the model extra context. The model is chosen from the available Seed 2.0 variants, and the node returns the model's text answer.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text input to the model. (default: "") | STRING | Yes | N/A |
| `model` | The Seed model used to generate the response. This selector also exposes the model's sub-parameters. | DYNAMIC\_COMBO | Yes | `"Seed 2.0 Pro"`<br />`"Seed 2.0 Lite"`<br />`"Seed 2.0 Mini"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | Yes | 0 to 2147483647 |
| `system_prompt` | Foundational instructions that dictate the model's behavior. (default: "") | STRING | No | N/A |

### Model Inputs (Shared by Seed 2.0 Pro, Seed 2.0 Lite, and Seed 2.0 Mini)

All three Seed models expose the same sub-parameters when selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `temperature` | Controls randomness. 0.0 is deterministic, higher values are more random. (default: 1.0) | FLOAT | Yes | 0.0 to 2.0 (step: 0.01) |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Optional image(s) to use as context for the model. Up to 20 images. Growable slot: connect 1..20 items, e.g. `image_1` through `image_20`. | IMAGE | No | 0 to 20 images |
| `videos` | Optional video(s) to use as context for the model. Up to 4 videos. Growable slot: connect 1..4 items, e.g. `video_1` through `video_4`. | VIDEO | No | 0 to 4 videos |

**Note:** The `model` parameter is a dynamic combo that reveals the reference and temperature sub-parameters once a model is selected. The `images` and `videos` slots are growable, so you can connect several inputs for multimodal context.

* `prompt` is required and must contain at least one non-whitespace character; otherwise an error is raised.
* A maximum of 20 images is supported per request. This limit counts all images across connected batches.
* A maximum of 4 videos is supported per request.
* An error is raised if the model returns an empty response, or if the model refuses to respond (the refusal text is reported).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated text response from the Seed model. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceSeedNode/en.md)

***

**Source fingerprint (SHA-256):** `23c9b0e9983a65ce859e2e92acfe71604297f16d711fa094a6617a9915a46020`


# ByteDanceTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceTextToVideoNode

The ByteDance Text to Video node generates a video using ByteDance models through an API based on a text prompt.

The ByteDance Text to Video node generates a video using ByteDance models through an API based on a text prompt. You provide a prompt and choose settings such as the model, resolution, aspect ratio, and duration; the node submits the generation request and returns the generated video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The ByteDance model used to generate the video (default: `"seedance-1-0-pro-fast-251015"`). | COMBO | Yes | `"seedance-1-5-pro-251215"`<br />`"seedance-1-0-pro-250528"`<br />`"seedance-1-0-pro-fast-251015"` |
| `prompt` | The text prompt used to generate the video. | STRING | Yes | - |
| `resolution` | The resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"`<br />`"1080p"` |
| `aspect_ratio` | The aspect ratio of the output video. | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"` |
| `duration` | The duration of the output video in seconds (default: 5). | INT | Yes | 3 to 12 |
| `seed` | Seed to use for generation (default: 0). | INT | No | 0 to 2147483647 |
| `camera_fixed` | Specifies whether to fix the camera. The platform appends an instruction to fix the camera to your prompt, but does not guarantee the actual effect (default: False). | BOOLEAN | No | - |
| `watermark` | Whether to add an "AI generated" watermark to the video (default: False). | BOOLEAN | No | - |
| `generate_audio` | This parameter is ignored for any model except `seedance-1-5-pro-251215` (default: False). | BOOLEAN | No | - |

**Parameter Constraints:**

* The `prompt` parameter must contain at least 1 character after whitespace removal.
* The `prompt` parameter cannot contain the following text parameters: "resolution", "ratio", "duration", "seed", "camerafixed", "watermark".
* The node builds the final prompt by appending the selected `resolution`, `aspect_ratio`, `duration`, `seed`, `camera_fixed`, and `watermark` settings to the prompt text.
* The `duration` parameter is limited to values between 3 and 12 seconds. For the `seedance-1-5-pro-251215` model, the minimum supported duration is 4 seconds.
* The `seed` parameter accepts values from 0 to 2,147,483,647.
* The `generate_audio` parameter only has an effect when the `model` is set to `seedance-1-5-pro-251215`; it is ignored for all other models.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceTextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `83b805b63e59a76cae378b0407b409e1bfe900677ef1e01fc836fede47283eee`


# ByteDanceVideoEnhanceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceVideoEnhanceNode

This node upscales and restores videos using ByteDance vCube.

This node upscales and restores videos using ByteDance vCube. It can increase resolution up to 8K, remove compression artifacts and noise, enhance colour and sharpness, and optionally interpolate frames for a higher frame rate. The video is uploaded to the vCube service, processed with the selected enhancement preset, and returned as an enhanced video file.

## Inputs

### Common Inputs

These inputs are always visible.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Video to enhance. The source resolution must be at most 2560x1440 (2K); the output size is set by the resolution input. | VIDEO | Yes | At most 2560x1440 (2K) |
| `tool_version` | 'standard' balances speed and quality with 10+ enhancement algorithms. 'professional' uses 30+ algorithms for cinema-grade restoration, takes about 3x longer and costs 10x more. | DYNAMIC\_COMBO | Yes | "standard"<br />"professional" |
| `resolution` | Output resolution. The short side is set to the chosen level and the long side follows the source aspect ratio. 'source' keeps the source size, 'custom' sets the short side in pixels. Sources wider or taller than about 2.2:1 are billed one resolution tier higher. | DYNAMIC\_COMBO | Yes | "720p"<br />"1080p"<br />"2k"<br />"4k"<br />"8k"<br />"source"<br />"custom" |
| `fps` | Output frame rate. A higher rate than the source enables AI frame interpolation; a lower one drops frames. 'source' keeps the source rate, up to 120 fps. Rates above 30 fps cost 2x, above 60 fps 4x. (default: "source") | COMBO | Yes | "source" (default)<br />Numeric frame rates up to 120 fps |
| `bitrate_level` | Target bitrate of the delivered file, scaled to the output resolution and frame rate. (default: "medium") | COMBO | Yes | "low"<br />"medium"<br />"high" |

### Standard Inputs

Shown when `tool_version` is set to "standard".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `scene` | Preset tuned to the content: 'aigc' for AI-generated footage, 'common' for general video, 'ugc' for compressed phone clips, 'short\_series' for drama with faces, 'old\_film' for scratched or flickering archive footage. (default: "aigc") | COMBO | Yes | "aigc"<br />"common"<br />"ugc"<br />"short\_series"<br />"old\_film" |
| `enhance_style` | 'hd' applies a sharper enhancement; 'natural' reduces the strength for a softer, less sharpened look. (default: "hd") | COMBO | Yes | "hd"<br />"natural" |

### Professional Inputs

Shown when `tool_version` is set to "professional".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `enhance_style` | 'hd' applies a sharper enhancement; 'natural' reduces the strength for a softer, less sharpened look. (default: "hd") | COMBO | Yes | "hd"<br />"natural" |

### Custom Resolution Inputs

Shown when `resolution` is set to "custom".

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `short_side` | Short side of the output in pixels; the long side follows the source aspect ratio. (default: 1080) | INT | Yes | Default 1080; bounded by the vCube minimum and maximum short-side limits |

### Notes

* The source video must be at most 2560x1440 (2K). Videos larger than this are rejected and must be scaled down before enhancing.
* The source video duration is limited to the maximum duration supported by the vCube service.
* When `tool_version` is "standard", both `scene` and `enhance_style` are available. When it is "professional", only `enhance_style` is available.
* When `resolution` is "custom", the `short_side` value is required. The resolution presets and "source" do not use `short_side`.
* When `resolution` is "source" and the source short side is at least the minimum short-side limit, the output keeps the source resolution.
* When `fps` is "source", the output frame rate matches the source frame rate, up to 120 fps.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The enhanced video, upscaled and restored at the requested resolution and frame rate. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceVideoEnhanceNode/en.md)

***

**Source fingerprint (SHA-256):** `bfdd55ce12cabd6e6504129084e86dcf96abd8db4ff64abbe5974c0da7a42bda`


# ClaudeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClaudeNode

Generate text responses from Anthropic's Claude models.

Generate text responses from Anthropic's Claude models. Provide a text prompt and optionally one or more images for multimodal context, and the node returns the model's generated text response.

## Inputs

Inputs are grouped into common settings, model-specific settings that appear when a model is selected, and optional reference images.

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Claude model used to generate the response. Selecting a model reveals model-specific settings below. | DYNAMIC\_COMBO | Yes | `"Opus 5.5"`<br />`"Opus 5"`<br />`"Opus 4.8"`<br />`"Fable 5.1"`<br />`"Fable 5"`<br />`"Sonnet 5"`<br />`"Opus 4.7"`<br />`"Opus 4.6"`<br />`"Sonnet 4.6"`<br />`"Sonnet 4.5"`<br />`"Haiku 4.5"` |
| `prompt` | Text input to the model. (default: empty string) | STRING | Yes | N/A |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | Yes | 0 to 2147483647 |
| `system_prompt` | Foundational instructions that dictate the model's behavior. (default: empty string) | STRING | No | N/A |

### Opus 5.5, Opus 5, Fable 5.1, and Fable 5 Inputs

These four models share the same settings. They do not expose a temperature setting, and reasoning is always enabled.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `max_tokens` | Maximum number of tokens to generate (includes reasoning tokens when enabled). (default: 32768) | INT | Yes | 4096 to 64000 |
| `reasoning_effort` | Extended thinking effort. Reasoning is always enabled for this model. (default: "high") | COMBO | Yes | `"low"`<br />`"medium"`<br />`"high"`<br />`"xhigh"`<br />`"max"` |

### Opus 4.8 and Sonnet 5 Inputs

These two models share the same settings. They do not expose a temperature setting.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `max_tokens` | Maximum number of tokens to generate (includes reasoning tokens when enabled). (default: 32768) | INT | Yes | 4096 to 64000 |
| `reasoning_effort` | Extended thinking effort. `"off"` disables reasoning. (default: "off") | COMBO | Yes | `"off"`<br />`"low"`<br />`"medium"`<br />`"high"`<br />`"xhigh"`<br />`"max"` |

### Opus 4.7, Opus 4.6, Sonnet 4.6, and Sonnet 4.5 Inputs

These four models share the same settings.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `max_tokens` | Maximum number of tokens to generate (includes reasoning tokens when enabled). (default: 32768) | INT | Yes | 4096 to 64000 |
| `temperature` | Controls randomness. 0.0 is deterministic, 1.0 is most random. Ignored for Opus 4.7 and any model when `reasoning_effort` is set. (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |
| `reasoning_effort` | Extended thinking effort. `"off"` disables reasoning. (default: "off") | COMBO | Yes | `"off"`<br />`"low"`<br />`"medium"`<br />`"high"` |

`reasoning_effort` offers `"off"`, `"low"`, `"medium"`, and `"high"` on all four models. Opus 4.7, Opus 4.6, and Sonnet 4.6 additionally accept `"max"`, and Opus 4.7 also accepts `"xhigh"`.

### Haiku 4.5 Inputs

This model does not expose a `reasoning_effort` setting.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `max_tokens` | Maximum number of tokens to generate (includes reasoning tokens when enabled). (default: 32768) | INT | Yes | 4096 to 64000 |
| `temperature` | Controls randomness. 0.0 is deterministic, 1.0 is most random. Ignored for Opus 4.7 and any model when `reasoning_effort` is set. (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Optional image(s) to use as context for the model. Up to 20 images. Growable slot: connect 1 to 20 items (`image_1` ... `image_20`). | IMAGE | No | 0 to 20 images |

### Parameter Constraints

* **Image limit:** A maximum of 20 images can be provided per request. Connecting more than 20 images raises an error.
* **Prompt required:** The prompt must contain at least one non-whitespace character. An empty prompt raises a validation error.
* **Temperature handling:** When thinking is enabled, the Anthropic API requires temperature to be unset (it defaults to 1.0). Opus 5.5, Opus 5, Opus 4.8, Fable 5.1, Fable 5, and Sonnet 5 do not expose a temperature setting. Opus 4.7 ignores `temperature`, and any model with `reasoning_effort` set to anything other than `"off"` also ignores it.
* **Reasoning/thinking behavior:** The `reasoning_effort` setting controls whether thinking is enabled. Opus 5.5, Opus 5, Fable 5.1, and Fable 5 always have reasoning enabled. Haiku 4.5 does not support reasoning. When thinking is enabled, the node uses the appropriate thinking mode for the selected model, either adaptive or budget-based. In budget mode, the reasoning token budget is capped to leave at least 1024 tokens for the actual response.
* **Safety refusal:** If Claude declines to answer the request for safety reasons, the node raises an error asking you to rephrase the prompt or try a different model.
* **Output text:** Thinking and reasoning blocks are not included in the output; only generated text is returned.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated text response from the Claude model. Thinking/reasoning blocks are not included. If no text is generated, returns "Empty response from Claude model." | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ClaudeNode/en.md)

***

**Source fingerprint (SHA-256):** `f6d9353025598bbed1aca7bdeb56ac59f5e4c26dd5b8e29359e97ef29e35bee7`


# Flux3ImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Flux3ImageToVideoNode

Flux 3 Image to Video animates 1 to 10 images with FLUX 3.

Flux 3 Image to Video animates 1 to 10 images with FLUX 3. Each image becomes a frame of the clip: one image opens it, two morph from the first to the second, and more are spread across it or pinned to times you choose.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `placement` | "spread across the clip" lets FLUX 3 place the images (one opens the clip, two become its start and end); "at times" pins every image to a second you choose. | DYNAMIC\_COMBO | Yes | `"spread across the clip"` (default)<br />`"at times"` |
| `prompt` | How the scene should move and sound; the prompt is interpreted and expanded before generation. Must contain at least one character. | STRING | Yes | Multiline text (default: empty) |
| `aspect_ratio` | Output aspect ratio. "auto" picks one from the prompt and inputs. | COMBO | Yes | `"auto"` (default)<br />other available aspect ratios |
| `duration` | Clip length in seconds. "auto" fits the length to the content. | COMBO | Yes | `"auto"` (default)<br />other available durations |
| `resolution` | Output resolution. | COMBO | Yes | `"720p"` (default)<br />`"1080p"` |
| `generate_audio` | Generate synchronized audio (ambient, speech, effects). Off produces a video with no audio track. | BOOLEAN | Yes | true / false (default: true) |
| `safety_tolerance` | Moderation tolerance, 0 is the strictest. Requests that send images or video are capped at 2 whatever you set here. | INT | Yes | 0 to 4 (default: 2, advanced setting) |
| `seed` | Seed to determine if node should re-run; FLUX 3 picks its own seed, so actual results are nondeterministic regardless of this value. | INT | Yes | 0 to 4294967295 (default: 42, control-after-generate) |

### spread across the clip Inputs

This placement option has no additional parameters.

### at times Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `times` | One time in seconds per image, comma-separated and increasing, e.g. "0, 2.5, 5". Only appears when `placement` is "at times"; one time is required for each keyframe image. | STRING | No | Comma-separated seconds (default: "0") |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `keyframes` | Growable slot: connect 1 to 10 keyframe images in playback order, e.g. `image_1`, `image_2`, and so on. Each image becomes a frame of the clip. Minimum 256x256 pixels each; aspect ratio cannot be more extreme than 64:1. | IMAGE | Yes | 1 to 10 images |

Note: `keyframes` must contain at least one image; the node raises an error if none are connected. Each keyframe image must be at least 256x256 pixels and its aspect ratio cannot be more extreme than 64:1.

When `placement` is "spread across the clip" and 3 or more keyframes are connected, `duration` must be set to an explicit value, not "auto"; otherwise the node raises an error.

When `placement` is "at times", `times` must provide one time in seconds per image. The times must increase, cannot be negative, and the last time cannot be past the end of the clip (up to 20 seconds when `duration` is "auto").

Because this node sends images, `safety_tolerance` is capped at 2 regardless of the value you set.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video clip built from the keyframe images at the chosen aspect ratio, duration, resolution, and audio setting. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Flux3ImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `1c49838dfa13adc2ed70a51094f0dd860df7207970b8dceab6bb273653d7161c`


# Flux3TextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Flux3TextToVideoNode

Generates a video with synchronized audio from a text prompt using FLUX 3.

Generates a video with synchronized audio from a text prompt using FLUX 3. The node sends your prompt to the FLUX 3 service, waits for the generation to finish, and returns the completed video clip.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | What you want, in plain language; the prompt is interpreted and expanded before generation. Describe ambient sound, music and speech separately for layered audio. (default: "") | STRING | Yes | Multiline text |
| `aspect_ratio` | Output aspect ratio. 'auto' picks one from the prompt and inputs. (default: "auto") | COMBO | Yes | Multiple options available, including `"auto"` |
| `duration` | Clip length in seconds. 'auto' fits the length to the content. (default: "auto") | COMBO | Yes | Multiple options available, including `"auto"` |
| `resolution` | Output resolution. (default: "720p") | COMBO | Yes | `"720p"`<br />`"1080p"` |
| `generate_audio` | Generate synchronized audio (ambient, speech, effects). Off produces a video with no audio track. (default: True) | BOOLEAN | Yes | True<br />False |
| `safety_tolerance` | Moderation tolerance, 0 is the strictest. Requests that send images or video are capped at 2 whatever you set here. (default: 2) | INT | Yes | 0 to 4 |
| `seed` | Seed to determine if node should re-run; FLUX 3 picks its own seed, so actual results are nondeterministic regardless of this value. (default: 42) | INT | Yes | 0 to 4294967295 |

Note: `safety_tolerance` is an advanced input. The `seed` input includes Control After Generate controls in the UI. The displayed price is based on `resolution` and `duration`: HD (720p) is charged at $0.2431 per second and FHD (1080p) at $0.4147 per second. When a fixed duration is chosen, the total estimated cost for the clip is shown; when `duration` is "auto", the per-second rate is shown.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video clip, with synchronized audio when `generate_audio` is enabled. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Flux3TextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `9957c78291c320b1a8a6a9c0edeefae5f1ccc21a6b58f0b39069c2df8decd100`


# Flux3VideoContinuationNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Flux3VideoContinuationNode

This node continues an existing video clip with FLUX 3: the new clip carries on from the final frames of the video you provide.

This node continues an existing video clip with FLUX 3: the new clip carries on from the final frames of the video you provide. It uploads your source clip, sends the prompt and settings to the generation service, and returns the resulting continuation video once it is ready.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The clip to continue. | VIDEO | Yes | Single video clip |
| `prompt` | What the continuation should show; the prompt is interpreted and expanded before generation. (default: "") | STRING | Yes | Non-empty text (minimum 1 character) |
| `aspect_ratio` | Output aspect ratio. 'auto' picks one from the prompt and inputs. (default: "auto") | COMBO | Yes | "auto" (default)<br />Multiple predefined options |
| `duration` | Clip length in seconds. 'auto' fits the length to the content. (default: "auto") | COMBO | Yes | "auto" (default)<br />Numeric values in seconds |
| `resolution` | Output resolution. (default: "720p") | COMBO | Yes | "720p" (default)<br />"1080p"<br />Other predefined options |
| `generate_audio` | Generate synchronized audio (ambient, speech, effects). Off produces a video with no audio track. (default: true) | BOOLEAN | Yes | true<br />false |
| `safety_tolerance` | Moderation tolerance, 0 is the strictest. Requests that send images or video are capped at 2 whatever you set here. (advanced parameter, default: 2) | INT | Yes | 0 - 4 (effective maximum: 2 for video requests) |
| `seed` | Seed to determine if node should re-run; FLUX 3 picks its own seed, so actual results are nondeterministic regardless of this value. (default: 42) | INT | Yes | 0 - 4294967295 (0xFFFFFFFF) |

### Notes

* `prompt` must contain at least one character, otherwise generation fails. Although the field defaults to an empty string, a non-empty prompt is required to run the node.
* `safety_tolerance` accepts any value from 0 to 4, but since this node sends a video to the API, the effective tolerance is capped at 2 regardless of the selected value.
* When `duration` is set to a number, it is converted to an integer number of seconds. The special value "auto" lets the service fit the length to the content.
* The exact option lists for `aspect_ratio`, `duration`, and `resolution` are defined internally by the node. Resolution options include at least "720p" (the default) and "1080p". Pricing is calculated from the selected `resolution` and `duration`; "1080p" is billed at $0.7579 per second, while other resolutions are billed at $0.5863 per second.
* `seed` only controls whether the node re-runs; it is not sent to the generation service.
* Authentication and node identification fields (`auth_token_comfy_org`, `api_key_comfy_org`, `unique_id`) are hidden and handled automatically by the platform.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated continuation clip produced by FLUX 3, which carries on from the end of the source video. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Flux3VideoContinuationNode/en.md)

***

**Source fingerprint (SHA-256):** `129ad0eb62c368854cebb010cc886aecac4caab00f9111143b883d028d7c30d9`


# FluxVideoEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxVideoEditNode

Edits an existing video clip from a written instruction.

Edits an existing video clip from a written instruction. You can remove, add, or replace objects, change the setting, restyle the footage, change on-screen text, or replace the spoken dialogue. The length, framing, camera motion, and audio come from the source clip, so anything you do not mention in the prompt is meant to stay as it was.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Source clip of 0.7 to 15 seconds, at least 160x160 pixels. The output is rendered at 24 fps and capped at about 0.9 megapixels per frame, so a larger source comes back smaller. | VIDEO | Yes | 0.7 to 15 seconds; minimum 160x160 pixels |
| `prompt` | What to change, in plain language, up to 4096 characters. Anything you do not mention is meant to stay as it was. Replacement dialogue has to fit the time the original speech takes, and a silent clip stays silent. Default: empty string. | STRING | Yes | 1 to 4096 characters |
| `auto_downscale` | Automatically downscale sources larger than 1280x704 pixels in area before upload. Aspect ratio is preserved; smaller videos are untouched. Default: true. | BOOLEAN | No | true<br />false |
| `safety_tolerance` | Moderation tolerance, 0 is the strictest. Default: 4. | INT | No | 0 to 4 |
| `seed` | Seed to determine if node should re-run; FLUX picks its own seed, so actual results are nondeterministic regardless of this value. Default: 42. | INT | No | 0 to 4294967295 |

**Note:** The `prompt` must contain at least 1 character and no more than 4096 characters. The source `video` must be between 0.7 and 15 seconds long and at least 160x160 pixels; uploads that fall outside these limits are rejected before the request is sent.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The edited video clip returned by the FLUX service. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxVideoEditNode/en.md)

***

**Source fingerprint (SHA-256):** `169b14700acfee3f6ccc247f08f3ae8c5f3c4610062a447e8215246460299b6a`


# FluxVideoUpscaleNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxVideoUpscaleNode

Flux Video Upscale upscales a video clip by 1.5 to 3 times using FLUX super-resolution.

Flux Video Upscale upscales a video clip by 1.5 to 3 times using FLUX super-resolution. In creative mode it restores and invents fine detail; in precise mode it sharpens the source without changing it.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Source clip of 1 to 20 seconds with an aspect ratio between 1:4 and 4:1. The output is rendered at 24 fps and capped at about 14.4 megapixels per frame. | VIDEO | Yes | 1 to 20 seconds duration; aspect ratio between 1:4 and 4:1; minimum 64x64 pixels |
| `upscale_factor` | Output size relative to the source. Very large sources are upscaled by less than the requested factor because of the per-frame cap. (default: 2.0) | FLOAT | Yes | 1.5 to 3.0 (step 0.1) |
| `mode` | 'creative' restores and invents fine detail, best for generated footage, textures and scenery. 'precise' sharpens the source without changing it, for faces, products and real footage. (default: "creative") | COMBO | Yes | "creative"<br />"precise" |
| `prompt` | Optional description of the clip that steers the enhanced detail. Leave empty for a neutral upscale. (default: empty) | STRING | Yes | Multiline text |
| `auto_downscale` | Automatically downscale sources larger than 3840x2160 pixels in area to fit the input limit. Aspect ratio is preserved; smaller videos are untouched. (default: true) | BOOLEAN | Yes | true<br />false |
| `safety_tolerance` | Moderation tolerance, 0 is the strictest. (default: 2, advanced parameter) | INT | Yes | 0 to 4 |
| `seed` | Seed to determine if node should re-run; FLUX picks its own seed, so actual results are nondeterministic regardless of this value. (default: 42) | INT | Yes | 0 to 4294967295 |

Note: The source video must be between 1 and 20 seconds long, at least 64x64 pixels in size, and have an aspect ratio between 1:4 and 4:1. If `auto_downscale` is disabled and the video area exceeds 3840x2160 pixels, the node raises an error. The output video is rendered at 24 fps and capped at about 14.4 megapixels per frame, so very large sources may be upscaled by less than the requested factor.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The upscaled video clip. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxVideoUpscaleNode/en.md)

***

**Source fingerprint (SHA-256):** `22dcf7c176705ce21a9032b1c9f4fe82ee6aa153f5057b90dac653b37281a677`


# GeminiInputFiles - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiInputFiles

Loads and formats input files for use with the Gemini API.

Loads and formats input files for use with the Gemini API. This node allows users to include text (.txt) and PDF (.pdf) files as input context for the Gemini model. Files are converted to the appropriate format required by the API and can be chained together to include multiple files in a single request.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `file` | Input files to include as context for the model. Only accepts text (.txt) and PDF (.pdf) files for now. Files must be smaller than the maximum input file size limit (20 MB). | COMBO | Yes | Multiple options available (only .txt and .pdf files under 20 MB) |
| `GEMINI_INPUT_FILES` | An optional additional file(s) to batch together with the file loaded from this node. Allows chaining of input files so that a single message can include multiple input files. | GEMINI\_INPUT\_FILES | No | N/A |

**Note:** The `file` parameter only displays text (.txt) and PDF (.pdf) files that are smaller than 20 MB. Files are automatically filtered and sorted by name.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `GEMINI_INPUT_FILES` | Formatted file data ready for use with Gemini LLM nodes, containing the loaded file content in the appropriate API format. | GEMINI\_INPUT\_FILES |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiInputFiles/en.md)

***

**Source fingerprint (SHA-256):** `1c80a87746c7ac73379f5c1e2d5c4d22f0fc44d3241fafb0297e087e436df7d6`


# GeminiNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiNode

This node allows users to interact with Google's Gemini AI models to generate text responses.

This node allows users to interact with Google's Gemini AI models to generate text responses. You can provide multiple types of inputs including text, images, audio, video, and files as context for the model to generate more relevant and meaningful responses. The node handles all API communication and response parsing automatically.

**Note:** This node is marked as deprecated in the source code.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text inputs to the model, used to generate a response. You can include detailed instructions, questions, or context for the model. Default: empty string. | STRING | Yes | - |
| `model` | The Gemini model to use for generating responses. Default: gemini-3-1-pro. | COMBO | Yes | "gemini-2.5-pro"<br />"gemini-2.5-flash"<br />"gemini-3-pro-preview"<br />"gemini-3-1-pro"<br />"gemini-3-1-flash-lite" |
| `seed` | When seed is fixed to a specific value, the model makes a best effort to provide the same response for repeated requests. Deterministic output isn't guaranteed. Also, changing the model or parameter settings, such as the temperature, can cause variations in the response even when you use the same seed value. By default, a random seed value is used. Default: 42. | INT | Yes | 0 to 18446744073709551615 |
| `images` | Optional image(s) to use as context for the model. To include multiple images, you can use the Batch Images node. Default: None. | IMAGE | No | - |
| `audio` | Optional audio to use as context for the model. Default: None. | AUDIO | No | - |
| `video` | Optional video to use as context for the model. Default: None. | VIDEO | No | - |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Generate Content Input Files node. Default: None. | GEMINI\_INPUT\_FILES | No | - |
| `system_prompt` | Foundational instructions that dictate an AI's behavior. Default: empty string. This is an advanced parameter. | STRING | No | - |

All connected images are used as context. When more than 10 images are provided, the first 10 are uploaded as file references and the remaining images are sent inline to the API.

The node uses the selected model name as given in the list; some entries are internally mapped to their current API model identifiers before the request is sent.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `STRING` | The text response generated by the Gemini model. If the model produces no text, the node returns "Empty response from Gemini model...". | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiNode/en.md)

***

**Source fingerprint (SHA-256):** `d1c53a5d80182085a36302867c8875df696adec6aaea9a9519a21bd6b9543d8f`


# GeminiNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiNodeV2

Generate text responses with Google's Gemini models.

Generate text responses with Google's Gemini models. Provide a text prompt and, optionally, one or more images, audio clips, videos, or files as multimodal context. The node sends the prompt and any attached media to the selected model and returns the model's text answer.

**Note:** This node is marked as deprecated in the source code.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Gemini model used to generate the response. Selecting a model reveals its own set of inputs below. | DYNAMIC\_COMBO | Yes | `"Gemini 3.8 Flash"`<br />`"Gemini 3.7 Flash"`<br />`"Gemini 3.5 Flash"`<br />`"Gemini 3.1 Pro"`<br />`"Gemini 3.1 Flash-Lite"` |
| `prompt` | Text input to the model. Include detailed instructions, questions, or context. (default: "") | STRING | Yes | Must contain at least one non-whitespace character |
| `seed` | Seed for sampling. Set to 0 for a random seed. Deterministic output isn't guaranteed. (default: 42) | INT | Yes | 0 to 2147483647 |
| `system_prompt` | Foundational instructions that dictate the model's behavior. (default: "") | STRING | No | |

### Gemini 3.8 Flash Inputs

These inputs appear when `model` is set to `"Gemini 3.8 Flash"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `thinking_level` | How hard the model reasons internally before answering. HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower. (default: "MEDIUM") | COMBO | Yes | `"LOW"`<br />`"MEDIUM"`<br />`"HIGH"` |
| `max_output_tokens` | Maximum tokens to generate, including the model's internal thinking. With thinking\_level HIGH, a low value can leave no room for the answer; raise this if responses come back empty or truncated. The model stops early when finished, so a higher cap costs nothing extra for short replies. (default: 32768) | INT | Yes | 16 to 65536 |

**Note:** This model does not expose `temperature` or `top_p` sampling controls.

### Gemini 3.7 Flash Inputs

These inputs appear when `model` is set to `"Gemini 3.7 Flash"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `thinking_level` | How hard the model reasons internally before answering. HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower. (default: "MEDIUM") | COMBO | Yes | `"LOW"`<br />`"MEDIUM"`<br />`"HIGH"` |
| `temperature` | Controls randomness. Lower is more focused/deterministic, higher is more creative. (default: 1.0) | FLOAT | Yes | 0.0 to 2.0 |
| `top_p` | Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top\_p. (default: 0.95) | FLOAT | Yes | 0.0 to 1.0 |
| `max_output_tokens` | Maximum tokens to generate, including the model's internal thinking. With thinking\_level HIGH, a low value can leave no room for the answer; raise this if responses come back empty or truncated. The model stops early when finished, so a higher cap costs nothing extra for short replies. (default: 32768) | INT | Yes | 16 to 65536 |

### Gemini 3.5 Flash Inputs

These inputs appear when `model` is set to `"Gemini 3.5 Flash"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `thinking_level` | How hard the model reasons internally before answering. HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower. (default: "MEDIUM") | COMBO | Yes | `"MINIMAL"`<br />`"LOW"`<br />`"MEDIUM"`<br />`"HIGH"` |
| `temperature` | Controls randomness. Lower is more focused/deterministic, higher is more creative. (default: 1.0) | FLOAT | Yes | 0.0 to 2.0 |
| `top_p` | Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top\_p. (default: 0.95) | FLOAT | Yes | 0.0 to 1.0 |
| `max_output_tokens` | Maximum tokens to generate, including the model's internal thinking. With thinking\_level HIGH, a low value can leave no room for the answer; raise this if responses come back empty or truncated. The model stops early when finished, so a higher cap costs nothing extra for short replies. (default: 32768) | INT | Yes | 16 to 65536 |

### Gemini 3.1 Pro Inputs

These inputs appear when `model` is set to `"Gemini 3.1 Pro"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `thinking_level` | How hard the model reasons internally before answering. HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower. (default: "HIGH") | COMBO | Yes | `"LOW"`<br />`"HIGH"` |
| `temperature` | Controls randomness. Lower is more focused/deterministic, higher is more creative. (default: 1.0) | FLOAT | Yes | 0.0 to 2.0 |
| `top_p` | Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top\_p. (default: 0.95) | FLOAT | Yes | 0.0 to 1.0 |
| `max_output_tokens` | Maximum tokens to generate, including the model's internal thinking. With thinking\_level HIGH, a low value can leave no room for the answer; raise this if responses come back empty or truncated. The model stops early when finished, so a higher cap costs nothing extra for short replies. (default: 32768) | INT | Yes | 16 to 65536 |

### Gemini 3.1 Flash-Lite Inputs

These inputs appear when `model` is set to `"Gemini 3.1 Flash-Lite"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `thinking_level` | How hard the model reasons internally before answering. HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower. (default: "LOW") | COMBO | Yes | `"LOW"`<br />`"HIGH"` |
| `temperature` | Controls randomness. Lower is more focused/deterministic, higher is more creative. (default: 1.0) | FLOAT | Yes | 0.0 to 2.0 |
| `top_p` | Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top\_p. (default: 0.95) | FLOAT | Yes | 0.0 to 1.0 |
| `max_output_tokens` | Maximum tokens to generate, including the model's internal thinking. With thinking\_level HIGH, a low value can leave no room for the answer; raise this if responses come back empty or truncated. The model stops early when finished, so a higher cap costs nothing extra for short replies. (default: 32768) | INT | Yes | 16 to 65536 |

### Media and File Inputs

The following inputs are shared by all models and appear alongside the model-specific inputs.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Growable slot: connect 1 to 16 images (`image_1` ... `image_16`). Optional image(s) to use as context for the model. Up to 16 images. | IMAGE | No | 0 to 16 images |
| `audio` | Growable slot: connect one audio clip (`audio_1`). Optional audio clip to use as context for the model. | AUDIO | No | 0 to 1 clip |
| `video` | Growable slot: connect one video clip (`video_1`). Optional video clip to use as context for the model. | VIDEO | No | 0 to 1 clip |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Input Files node. | GEMINI\_INPUT\_FILES | No | |

**Note:** When media (images, audio, or video) is attached, the node uploads the first 10 media items to ComfyAPI storage and passes them as URLs; this URL budget is shared across all media types and is consumed in order (video first, then audio, then images). Any remaining media is encoded inline as base64 data, with a maximum combined inline payload of 18 MB. If the inline payload would exceed 18 MB, the node raises an error. The `prompt` parameter must contain at least one non-whitespace character. Setting `seed` to 0 requests a random seed.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated text response from the Gemini model. If the model produces no text, the string "Empty response from Gemini model..." is returned. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiNodeV2/en.md)

***

**Source fingerprint (SHA-256):** `8ae14c6465569695e1e99b0040cb2c745e5f3d9ddcd3b03013530dc7e7135b87`


# GeminiNodeV3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiNodeV3

Generate text responses with Google's Gemini models.

Generate text responses with Google's Gemini models. Provide a text prompt and, optionally, one or more images, audio clips, videos, or files as multimodal context. The selected model determines which additional settings appear.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Gemini model used to generate the response. The selected model determines which additional inputs are shown. | DYNAMIC\_COMBO | Yes | `"Gemini 3.8 Flash"`<br />`"Gemini 3.7 Flash"`<br />`"Gemini 3.5 Flash"`<br />`"Gemini 3.1 Pro"`<br />`"Gemini 3.1 Flash-Lite"` |

### Media Inputs

These growable media inputs are available for every model option.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Optional image(s) to use as context for the model. Up to 16 images. Growable slot: connect images to `image_1` through `image_16`. | IMAGE | No | Up to 16 images |
| `audio` | Optional audio clip to use as context for the model. Growable slot: `audio_1`. | AUDIO | No | 1 audio clip |
| `video` | Optional video clip to use as context for the model. Growable slot: `video_1`. | VIDEO | No | 1 video clip |

### Gemini 3.8 Flash Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text input to the model. Include detailed instructions, questions, or context. Must not be empty. | STRING | Yes | Multiline text (must contain at least one non-whitespace character) |
| `video_processing` | How the model reads the attached video. `static` samples frames at a fixed rate and sends all of them as context; `agentic` lets the model navigate the timeline itself and load only the frames, audio or transcript it needs, which costs far fewer input tokens on long videos. | COMBO | Yes | `"static"`<br />`"agentic"` (default: `"static"`) |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Input Files node. | GEMINI\_INPUT\_FILES | No | N/A |
| `thinking_level` | How hard the model reasons internally before answering. HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower. | COMBO | Yes | `"LOW"`<br />`"MEDIUM"`<br />`"HIGH"` (default: `"MEDIUM"`) |
| `max_output_tokens` | Maximum tokens to generate, including the model's internal thinking. With thinking\_level HIGH, a low value can leave no room for the answer; raise this if responses come back empty or truncated. The model stops early when finished, so a higher cap costs nothing extra for short replies. | INT | Yes | 16-65536 (default: 32768) |
| `seed` | Seed for sampling. Set to 0 for a random seed. Deterministic output isn't guaranteed. | INT | Yes | 0-2147483647 (default: 42) |
| `system_prompt` | Foundational instructions that dictate the model's behavior. | STRING | Yes | Multiline text (default: empty) |

### Gemini 3.7 Flash Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text input to the model. Include detailed instructions, questions, or context. Must not be empty. | STRING | Yes | Multiline text (must contain at least one non-whitespace character) |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Input Files node. | GEMINI\_INPUT\_FILES | No | N/A |
| `thinking_level` | How hard the model reasons internally before answering. HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower. | COMBO | Yes | `"LOW"`<br />`"MEDIUM"`<br />`"HIGH"` (default: `"MEDIUM"`) |
| `temperature` | Controls randomness. Lower is more focused/deterministic, higher is more creative. | FLOAT | Yes | 0.0-2.0 (default: 1.0) |
| `top_p` | Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top\_p. | FLOAT | Yes | 0.0-1.0 (default: 0.95) |
| `max_output_tokens` | Maximum tokens to generate, including the model's internal thinking. With thinking\_level HIGH, a low value can leave no room for the answer; raise this if responses come back empty or truncated. The model stops early when finished, so a higher cap costs nothing extra for short replies. | INT | Yes | 16-65536 (default: 32768) |
| `seed` | Seed for sampling. Set to 0 for a random seed. Deterministic output isn't guaranteed. | INT | Yes | 0-2147483647 (default: 42) |
| `system_prompt` | Foundational instructions that dictate the model's behavior. | STRING | Yes | Multiline text (default: empty) |

### Gemini 3.5 Flash Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text input to the model. Include detailed instructions, questions, or context. Must not be empty. | STRING | Yes | Multiline text (must contain at least one non-whitespace character) |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Input Files node. | GEMINI\_INPUT\_FILES | No | N/A |
| `thinking_level` | How hard the model reasons internally before answering. HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower. | COMBO | Yes | `"MINIMAL"`<br />`"LOW"`<br />`"MEDIUM"`<br />`"HIGH"` (default: `"MEDIUM"`) |
| `temperature` | Controls randomness. Lower is more focused/deterministic, higher is more creative. | FLOAT | Yes | 0.0-2.0 (default: 1.0) |
| `top_p` | Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top\_p. | FLOAT | Yes | 0.0-1.0 (default: 0.95) |
| `max_output_tokens` | Maximum tokens to generate, including the model's internal thinking. With thinking\_level HIGH, a low value can leave no room for the answer; raise this if responses come back empty or truncated. The model stops early when finished, so a higher cap costs nothing extra for short replies. | INT | Yes | 16-65536 (default: 32768) |
| `seed` | Seed for sampling. Set to 0 for a random seed. Deterministic output isn't guaranteed. | INT | Yes | 0-2147483647 (default: 42) |
| `system_prompt` | Foundational instructions that dictate the model's behavior. | STRING | Yes | Multiline text (default: empty) |

### Gemini 3.1 Pro Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text input to the model. Include detailed instructions, questions, or context. Must not be empty. | STRING | Yes | Multiline text (must contain at least one non-whitespace character) |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Input Files node. | GEMINI\_INPUT\_FILES | No | N/A |
| `thinking_level` | How hard the model reasons internally before answering. HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower. | COMBO | Yes | `"LOW"`<br />`"HIGH"` (default: `"HIGH"`) |
| `temperature` | Controls randomness. Lower is more focused/deterministic, higher is more creative. | FLOAT | Yes | 0.0-2.0 (default: 1.0) |
| `top_p` | Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top\_p. | FLOAT | Yes | 0.0-1.0 (default: 0.95) |
| `max_output_tokens` | Maximum tokens to generate, including the model's internal thinking. With thinking\_level HIGH, a low value can leave no room for the answer; raise this if responses come back empty or truncated. The model stops early when finished, so a higher cap costs nothing extra for short replies. | INT | Yes | 16-65536 (default: 32768) |
| `seed` | Seed for sampling. Set to 0 for a random seed. Deterministic output isn't guaranteed. | INT | Yes | 0-2147483647 (default: 42) |
| `system_prompt` | Foundational instructions that dictate the model's behavior. | STRING | Yes | Multiline text (default: empty) |

### Gemini 3.1 Flash-Lite Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text input to the model. Include detailed instructions, questions, or context. Must not be empty. | STRING | Yes | Multiline text (must contain at least one non-whitespace character) |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Input Files node. | GEMINI\_INPUT\_FILES | No | N/A |
| `thinking_level` | How hard the model reasons internally before answering. HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower. | COMBO | Yes | `"LOW"`<br />`"HIGH"` (default: `"LOW"`) |
| `temperature` | Controls randomness. Lower is more focused/deterministic, higher is more creative. | FLOAT | Yes | 0.0-2.0 (default: 1.0) |
| `top_p` | Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top\_p. | FLOAT | Yes | 0.0-1.0 (default: 0.95) |
| `max_output_tokens` | Maximum tokens to generate, including the model's internal thinking. With thinking\_level HIGH, a low value can leave no room for the answer; raise this if responses come back empty or truncated. The model stops early when finished, so a higher cap costs nothing extra for short replies. | INT | Yes | 16-65536 (default: 32768) |
| `seed` | Seed for sampling. Set to 0 for a random seed. Deterministic output isn't guaranteed. | INT | Yes | 0-2147483647 (default: 42) |
| `system_prompt` | Foundational instructions that dictate the model's behavior. | STRING | Yes | Multiline text (default: empty) |

Note: For Gemini 3.8 Flash, `temperature` and `top_p` are not available, and `video_processing` is only available for this model option. The `thinking_level` options and default differ by model as listed above.

Note: The `prompt` input must not be empty. The node validates that it contains at least one non-whitespace character.

Note: The node uploads up to the first 10 media items as URLs, prioritizing video, then audio, then images. Any remaining media are sent inline as base64. Total inline media is limited to 18 MB; if exceeded, the node raises an error asking you to reduce the number or size of attached media.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `STRING` | The text response generated by the selected Gemini model. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiNodeV3/en.md)

***

**Source fingerprint (SHA-256):** `d04d1e97a9c213297899291ad30db14a9f946b07506d0377fead4e29510c5ad9`


# GeminiVideoOmni - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiVideoOmni

Generate a video with audio from a text prompt using Google's Gemini Omni Flash model.

Generate a video with audio from a text prompt using Google's Gemini Omni Flash model. Optionally provide reference images and/or videos to guide or edit the result. Describe the desired length (3-10s) and aspect ratio (16:9 or 9:16) directly in the prompt.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Gemini video model used to generate the video. | DYNAMIC\_COMBO | Yes | "Omni Flash" |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 42). | INT | Yes | 0 to 2147483647 |

### Omni Flash Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Describe the video to generate. Specify the length and aspect ratio directly in the prompt, e.g. "a 6-second clip in 16:9". Length may be 3-10 seconds; the aspect ratio must be 16:9 (landscape) or 9:16 (portrait). The output is 720p, 24 FPS, with audio. | STRING | Yes | Minimum 1 character after stripping whitespace |
| `temperature` | Controls randomness. Lower is more focused/deterministic, higher is more varied (default: 1.0). | FLOAT | No | 0.0 to 2.0 |
| `top_p` | Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top\_p (default: 0.95). | FLOAT | No | 0.0 to 1.0 |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Growable slot: connect one or more reference images (`image_1`...`image_14`) to guide or animate the video. Up to 14 images in total. | IMAGE | No | 0 to 14 images |
| `videos` | Growable slot: connect one or more reference videos (`video_1`...`video_3`) to guide or edit. Up to 3 videos, each up to 10 seconds long. | VIDEO | No | 0 to 3 videos, each max 10 seconds |

Notes:

* If an image input contains multiple frames, each frame counts toward the maximum of 14 images.
* When reference images or videos are provided, the total encoded media size must stay under about 90 MB; otherwise the node raises an error.
* When no reference images or videos are provided, the node generates the video from the text prompt alone.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `VIDEO` | The generated video with audio from the Gemini model. | VIDEO |
| `STRING` | Any text response from the model, such as reasoning or explanations. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiVideoOmni/en.md)

***

**Source fingerprint (SHA-256):** `648844868affb68298d2eac8ac20095bfe378d32e721396781de330ef6a6d69f`


# GeminiVideoOmniV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiVideoOmniV2

Google Gemini Omni (Video) generates a video with audio from a text prompt using Google's Gemini Omni Flash models.

Google Gemini Omni (Video) generates a video with audio from a text prompt using Google's Gemini Omni Flash models. You can optionally attach reference images and/or videos to guide the result or to edit existing footage. Describe the desired length (3-10 seconds) directly in the prompt.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Gemini video model used to generate the video. | DYNAMIC\_COMBO | Yes | "Omni Flash 1.1"<br />"Omni Flash" |

### Omni Flash 1.1 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Describe the video to generate, or the edit to apply to an attached video. Specify the length directly in the prompt, e.g. "a 6-second clip" or, for the 'extend' task, "extend by 5 seconds"; the generated length may be 3-10 seconds and defaults to 10. The output has audio. (default: "") | STRING | Yes | - |
| `resolution` | Output resolution. (default: "720p") | COMBO | Yes | "360p"<br />"720p"<br />"1080p"<br />"4k" |
| `aspect_ratio` | Output aspect ratio: 16:9 (landscape) or 9:16 (portrait). The 'edit' and 'extend' tasks keep the aspect ratio of the input video instead. (default: "16:9") | COMBO | Yes | "16:9"<br />"9:16" |
| `task_type` | What to do with the prompt and the attached media. With 'auto' the model decides. 'text\_to\_video' generates from the prompt alone and rejects attached media. 'image\_to\_video' animates one image, or interpolates from a starting frame to an ending frame when two are attached. 'reference\_to\_video' treats the attached media as subject references. 'edit' rewrites exactly one attached video, and 'extend' appends new footage to it, so the output starts with the input video. (default: "auto") | COMBO | Yes | "auto"<br />"text\_to\_video"<br />"image\_to\_video"<br />"reference\_to\_video"<br />"edit"<br />"extend" |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 42) | INT | Yes | 0 to 2147483647 |

### Omni Flash Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Describe the video to generate, or the edit to apply to an attached video. Specify the length directly in the prompt, e.g. "a 6-second clip"; length may be 3-10 seconds. The output is 720p, 24 FPS, with audio. (default: "") | STRING | Yes | - |
| `aspect_ratio` | Output aspect ratio: 16:9 (landscape) or 9:16 (portrait). The 'edit' task keeps the aspect ratio of the input video instead. (default: "16:9") | COMBO | Yes | "16:9"<br />"9:16" |
| `task_type` | What to do with the prompt and the attached media. With 'auto' the model decides. 'text\_to\_video' generates from the prompt alone and rejects attached media. 'image\_to\_video' animates one image, or interpolates from a starting frame to an ending frame when two are attached. 'reference\_to\_video' treats the attached media as subject references. 'edit' rewrites exactly one attached video. (default: "auto") | COMBO | Yes | "auto"<br />"text\_to\_video"<br />"image\_to\_video"<br />"reference\_to\_video"<br />"edit" |
| `temperature` | Controls randomness. Lower is more focused/deterministic, higher is more varied. (default: 1.0) | FLOAT | Yes | 0.0 to 2.0 (step 0.01) |
| `top_p` | Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top\_p. (default: 0.95) | FLOAT | Yes | 0.0 to 1.0 (step 0.01) |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 42) | INT | Yes | 0 to 2147483647 |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Growable slot: connect up to 14 images (`image_1`...`image_14`). Optional reference image(s) to guide or animate the video. With the 'image\_to\_video' task the first one is the starting frame and an optional second one is the ending frame. | IMAGE | No | 0 to 14 images |
| `videos` | Growable slot: connect up to 3 videos (`video_1`...`video_3`). Optional reference video(s) to guide or edit. Each up to 10 seconds long. | VIDEO | No | 0 to 3 videos |

**Notes:**

* The `prompt` must not be empty; the node raises an error if it is.
* The `text_to_video` task generates from the prompt alone — attaching images or videos raises an error.
* The `image_to_video` task accepts images only (no videos) and requires exactly 1 or 2 images: the first is the starting frame and the optional second is the ending frame.
* The `edit` task (both models) and the `extend` task (Omni Flash 1.1 only) require exactly one input video and keep the aspect ratio of that input video, overriding `aspect_ratio`.
* At most 14 images and 3 videos can be attached, and each attached video must be 10 seconds or shorter.
* Omni Flash always outputs 720p 24 FPS video with audio; resolution selection is only available with Omni Flash 1.1.
* `temperature` and `top_p` controls are only available with the Omni Flash model; Omni Flash 1.1 uses fixed generation settings.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` (first output) | The generated video with audio. For Omni Flash: 720p, 24 FPS. For Omni Flash 1.1: the resolution selected in the `resolution` input. | VIDEO |
| `text` (second output) | The text content generated by the model along with the video (may be empty). | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiVideoOmniV2/en.md)

***

**Source fingerprint (SHA-256):** `7a0dda4bcd662c9df3c680297ec9de7886d35e618de8b3ce0cd95b9afd13a892`


# GrokVideoEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokVideoEditNode

This node uses the Grok API to edit an existing video based on a text prompt.

This node uses the Grok API to edit an existing video based on a text prompt. It uploads your video, sends a request to the AI model to modify it according to your description, and returns the newly generated video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for video editing (default: "grok-imagine-video"). | COMBO | Yes | "grok-imagine-video" |
| `prompt` | Text description of the desired video. | STRING | Yes | N/A |
| `video` | The input video to be edited. Maximum supported duration is 8.7 seconds and 50MB file size. | VIDEO | Yes | N/A |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). | INT | No | 0 to 2147483647 |

**Constraints:**

* The `prompt` must not be empty.
* The input `video` must be between 1 and 8.7 seconds in duration.
* The input `video` file size must not exceed 50MB.

**Note:** This node is an API node and requires a Comfy.org account and API key to run. Usage is billed at approximately \$0.06 per second of video.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The edited video generated by the AI model. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokVideoEditNode/en.md)

***

**Source fingerprint (SHA-256):** `7ceedff2f858bc0849b5e0d92d10ed51e7fdccd1391c6a6966561cb05999b4b1`


# GrokVideoExtendNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokVideoExtendNode

The Grok Video Extend node extends an existing video with a seamless continuation based on a text prompt.

The Grok Video Extend node extends an existing video with a seamless continuation based on a text prompt. Provide a short source video and describe what should happen next; the node returns a new video clip that continues from the original.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to use for video extension. Selecting the `"grok-imagine-video"` option reveals its model-specific settings. | DYNAMIC\_COMBO | Yes | `"grok-imagine-video"` |
| `prompt` | Text description of what should happen next in the video. | STRING | Yes | N/A |
| `video` | Source video to extend. MP4 format, 2-15 seconds. | VIDEO | Yes | MP4, 2-15 seconds, maximum 50MB |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). | INT | Yes | 0 to 2147483647 |

### grok-imagine-video Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `duration` | Length of the extension in seconds (default: 8). | INT | Yes | 2 to 10 |

**Parameter Constraints:**

* The `video` input must be an MP4 file between 2 and 15 seconds in length and cannot exceed 50MB in file size.
* The `prompt` must contain at least one character after whitespace is trimmed.
* The `model` parameter is a dynamic combo. Selecting the `"grok-imagine-video"` option reveals the nested `duration` parameter.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The newly generated video extension. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokVideoExtendNode/en.md)

***

**Source fingerprint (SHA-256):** `5009c007b6f93cd44f2742b024b65f1ac92ab9bca3b85a55554b1d99649e323b`


# GrokVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokVideoNode

The Grok Video node generates a short video from a text description.

The Grok Video node generates a short video from a text description. It can create a video from scratch using a prompt, or generate a video from a single input image. The node sends the request to an external API and returns the generated video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to use for video generation. | COMBO | Yes | `"grok-imagine-video"`<br />`"grok-imagine-video-1.5"` |
| `prompt` | Text description of the desired video. Optional for grok-imagine-video-1.5 when an input image is provided. | STRING | Yes | - |
| `resolution` | The resolution of the output video. 1080p is only available for grok-imagine-video-1.5. | COMBO | Yes | `"480p"`<br />`"720p"`<br />`"1080p"` |
| `aspect_ratio` | The aspect ratio of the output video. | COMBO | Yes | `"auto"`<br />`"16:9"`<br />`"4:3"`<br />`"3:2"`<br />`"1:1"`<br />`"2:3"`<br />`"3:4"`<br />`"9:16"` |
| `duration` | The duration of the output video in seconds (default: 6). | INT | Yes | 1 to 15 |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). | INT | Yes | 0 to 2147483647 |
| `image` | Optional starting image. If omitted, the video is generated from the text prompt alone. | IMAGE | No | - |

**Note:** When an `image` is provided, only one input image is supported; providing multiple images will cause an error. The `prompt` must be non-empty after stripping whitespace when no image is provided, or when using `grok-imagine-video` even with an image. For `grok-imagine-video-1.5`, the `prompt` is optional only when an input image is provided. The `1080p` resolution is available only for `grok-imagine-video-1.5`. When `aspect_ratio` is set to `"auto"`, the aspect ratio is chosen automatically by the service.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `c7d07b7bf9a776892873698abb97c7d936c7770aab397d031a287b7ecfad0b71`


# GrokVideoReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokVideoReferenceNode

The Grok Reference-to-Video node generates a video from a text prompt, using up to seven reference images to guide the style and content of the output.

The Grok Reference-to-Video node generates a video from a text prompt, using up to seven reference images to guide the style and content of the output. With the `grok-imagine-video-1.5` model, you can also attach up to three preset voice references and refer to images and voices directly in the prompt using `@ImageN` and `@AudioN` tags. The node sends the request to an external API, waits for the generation to complete, and downloads the resulting video.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to use for video generation. | DYNAMIC\_COMBO | Yes | `"grok-imagine-video-1.5"`<br />`"grok-imagine-video"` |
| `prompt` | Text description of the desired video. Must be a non-empty string. | STRING | Yes | N/A |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). | INT | Yes | 0 to 2147483647 |

### Grok Imagine Video 1.5 Inputs

Available when `model` is set to `grok-imagine-video-1.5`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `voice_1` | Optional preset voice reference; refer to it in the prompt as @Audio1. The API supports only these preset voices, not custom audio (default: none). | COMBO | No | Preset voice options, including `"none"` |
| `voice_2` | Optional second voice reference; @Audio2 in the prompt (default: none). | COMBO | No | Preset voice options, including `"none"` |
| `voice_3` | Optional third voice reference; @Audio3 in the prompt (default: none). | COMBO | No | Preset voice options, including `"none"` |
| `resolution` | The resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"` |
| `aspect_ratio` | The aspect ratio of the output video. | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"3:2"`<br />`"1:1"`<br />`"2:3"`<br />`"3:4"`<br />`"9:16"` |
| `duration` | The duration of the output video in seconds (default: 6). | INT | Yes | 1 to 15 |

### Grok Imagine Video Inputs

Available when `model` is set to `grok-imagine-video`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `resolution` | The resolution of the output video. | COMBO | Yes | `"480p"`<br />`"720p"` |
| `aspect_ratio` | The aspect ratio of the output video. | COMBO | Yes | `"16:9"`<br />`"4:3"`<br />`"3:2"`<br />`"1:1"`<br />`"2:3"`<br />`"3:4"`<br />`"9:16"` |
| `duration` | The duration of the output video in seconds (default: 6). | INT | Yes | 2 to 10 |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect 1 to 7 reference images to guide the video generation. With `grok-imagine-video-1.5`, refer to them in the prompt as @Image1 ... @Image7, numbered in input order; a batched input counts once per image. | IMAGE | Yes | 1 to 7 images |

**Note:** The sub-parameters shown depend on the selected `model`; `grok-imagine-video-1.5` adds the `voice_1`, `voice_2`, and `voice_3` inputs. At least one reference image is required, and the total is capped at 7 (a batched input counts once per image). With `grok-imagine-video-1.5`, the prompt can reference connected images as `@Image1` ... `@Image7` and voice slots as `@Audio1`, `@Audio2`, `@Audio3`; an unnumbered `@image` or `@audio` refers to the first one. `@AudioN` refers to the `voice_N` widget, not the order of enabled voices. Referencing an image that is not connected or a voice slot set to `none` causes an error. The API supports only preset voices, not custom audio.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokVideoReferenceNode/en.md)

***

**Source fingerprint (SHA-256):** `e584c450563eaa7fcb7751d2325f9ef847fa34a4342df01f2bd9ce2e4ff8f2c3`


# HeyGenAvatarVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HeyGenAvatarVideoNode

Generate a talking-presenter video from a HeyGen avatar.

Generate a talking-presenter video from a HeyGen avatar. This node creates a video of an AI avatar speaking your provided text or lip-syncing to your own audio, using HeyGen's rendering engines.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `engine` | Rendering engine; each choice lists only the avatars that support it. "auto" offers every avatar and picks its best engine (Avatar IV preferred). Avatar V is highest fidelity, Avatar III is the most affordable. | DYNAMIC\_COMBO | Yes | `"auto"`<br />`"avatar_iv"`<br />`"avatar_iii"`<br />`"avatar_v"` |
| `custom_avatar_id` | Optional HeyGen avatar look ID. When set, overrides the avatar selected above. Any of HeyGen's 3000+ public looks (or your private avatars) can be used. Default: `""`. | STRING | No | |
| `speech` | Drive the avatar with a text script (HeyGen text-to-speech) or your own audio. Display name: "speech source". | DYNAMIC\_COMBO | Yes | `"script"`<br />`"audio"` |
| `resolution` | Output video resolution. Default: `"1080p"`. | COMBO | No | `"720p"`<br />`"1080p"` |
| `aspect_ratio` | Output aspect ratio. "auto" follows the avatar's source footage. Default: `"auto"`. | COMBO | No | `"auto"`<br />`"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:5"`<br />`"5:4"` |
| `background_color` | Optional solid background color as a hex code (e.g. `"#00ff00"`). Leave empty for the avatar's own background. If provided, the value must start with `#`. Default: `""`. | STRING | No | |
| `seed` | Not sent to HeyGen; change it to force a re-run. Default: `42`. | INT | No | Min: 0<br />Max: 2147483647 |

### `auto` Inputs

When `engine` is `"auto"`, the following sub-parameter is available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `avatar` | Avatar look to present the video (curated from HeyGen's public library). The best engine the look supports is chosen automatically. | COMBO | Yes | Multiple options available |

### `avatar_iv` Inputs

When `engine` is `"avatar_iv"`, the following sub-parameter is available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `avatar` | Avatar looks that support the Avatar IV engine. | COMBO | Yes | Multiple options available |

### `avatar_iii` Inputs

When `engine` is `"avatar_iii"`, the following sub-parameter is available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `avatar` | Avatar looks that support the Avatar III engine. | COMBO | Yes | Multiple options available |

### `avatar_v` Inputs

When `engine` is `"avatar_v"`, the following sub-parameter is available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `avatar` | Avatar looks that support the Avatar V engine. | COMBO | Yes | Multiple options available |

### `script` Inputs

When `speech` is `"script"`, the following sub-parameters are available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | Text for the avatar to speak (up to 5000 characters). The generated speech must be at least 1 second long. Default: `""`. | STRING | Yes | Min: 1 character<br />Max: 5000 characters |
| `voice` | Voice for the script. The default option uses the voice HeyGen assigned to the avatar. Ignored if `custom_voice_id` is set. | COMBO | Yes | `"(avatar's default voice)"`<br />Multiple general voice options available |
| `custom_voice_id` | Optional HeyGen voice ID. When set, overrides the voice selected above. Any voice from HeyGen's library (2000+) can be used. Default: `""`. | STRING | No | |
| `voice_speed` | Speech speed multiplier. Default: `1.0`. | FLOAT | No | Min: 0.5<br />Max: 1.5<br />Step: 0.05 |

### `audio` Inputs

When `speech` is `"audio"`, the following sub-parameter is available:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | Audio for the avatar to lip-sync, up to 10 minutes. | AUDIO | Yes | |

Note: `engine` and `speech` are selectors that reveal different sub-parameters depending on the chosen value. The `speech` selector has two mutually exclusive modes: in `"script"` mode, `text` is required; if `custom_voice_id` is provided, it overrides `voice`. In `"audio"` mode, the avatar lip-syncs to the provided audio clip. `background_color` must be a hex color code starting with `#` when provided. When `custom_avatar_id` is set, it overrides the `avatar` selection, and the selected `engine` must be supported by that avatar look; otherwise an error is raised unless `engine` is `"auto"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `VIDEO` | The generated avatar presenter video. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HeyGenAvatarVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `86dc799d3a8cf2666449b0d422853b12feffb81ce002f84594f9b925d58b522a`


# HeyGenCreateAvatarNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HeyGenCreateAvatarNode

Create a reusable HeyGen avatar from a photo of a person or from a text prompt describing a character to generate.

Create a reusable HeyGen avatar from a photo of a person or from a text prompt describing a character to generate. The resulting `avatar_id` can be used with the HeyGen Avatar Video node, and should be saved to reuse the avatar in future workflows.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `source` | Generate a new character from a text prompt, or create the avatar from a connected photo of a person. | DYNAMIC\_COMBO | Yes | `"prompt"`<br />`"photo"` |

### Prompt Inputs

Available when `source` is set to `"prompt"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Description of the avatar to generate (up to 1000 characters). Must contain at least 1 non-whitespace character. Default: empty string. | STRING | Yes | 1 to 1000 characters |

### Photo Inputs

Available when `source` is set to `"photo"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `identity_photo` | Photo of the person to turn into an avatar. Downscaled automatically if larger than 2K. | IMAGE | Yes | Single image |

### Reference Inputs

Available when `source` is set to `"prompt"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect up to 3 images (`ref_image_1`...`ref_image_3`) guiding the generated look. Images are downscaled automatically if larger than 2K. | IMAGE | No | 0 to 3 images |

**Note:** The `source` parameter switches between two mutually exclusive modes. In `"prompt"` mode, `prompt` is required and up to 3 reference images can optionally be connected. In `"photo"` mode, `identity_photo` is required. Photos and reference images are downscaled automatically when larger than 2K; more than 3 reference images are not accepted.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `avatar_id` | Avatar look ID. Pass it to HeyGen Avatar Video's `custom_avatar_id`; save it to reuse the avatar later. | STRING |
| `preview` | Preview image of the generated avatar. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HeyGenCreateAvatarNode/en.md)

***

**Source fingerprint (SHA-256):** `3669686fc6d089909bd5d2d75292ceef05702ed3cc7b14e561bcb444c30a4e63`


# HeyGenTalkingPhotoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HeyGenTalkingPhotoNode

Animate a still image of a person into a lip-synced talking video using HeyGen's Avatar IV technology.

Animate a still image of a person into a lip-synced talking video using HeyGen's Avatar IV technology. You can drive the animation with a text script that HeyGen converts to speech, or provide your own audio for the avatar to lip-sync.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Image of a person to animate. Downscaled automatically if larger than 2K. | IMAGE | Yes | - |
| `speech` | Drive the avatar with a text script (HeyGen text-to-speech) or your own audio. | DYNAMIC\_COMBO | Yes | `"script"`<br />`"audio"` |
| `resolution` | Output video resolution (default: `"1080p"`). | COMBO | No | `"720p"`<br />`"1080p"` |
| `aspect_ratio` | Output aspect ratio. `"auto"` follows the input image (default: `"auto"`). | COMBO | No | `"auto"`<br />`"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:5"`<br />`"5:4"` |
| `expressiveness` | How expressive the animated face and gestures are (default: `"low"`). | COMBO | No | `"low"`<br />`"medium"`<br />`"high"` |
| `seed` | Not sent to HeyGen; change it to force a re-run (default: 42). | INT | No | 0 to 2147483647 |

### Script Inputs

Shown when `speech` is `"script"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | Text for the avatar to speak (up to 5000 characters). The generated speech must be at least 1 second long. (default: empty) | STRING | Yes | 1 to 5000 characters |
| `voice` | Voice for the script (HeyGen's most popular voices). | COMBO | Yes | Multiple options available |
| `custom_voice_id` | Optional HeyGen voice ID. When set, overrides the voice selected above. Any voice from HeyGen's library (2000+) can be used. (default: empty) | STRING | No | - |
| `voice_speed` | Speech speed multiplier (default: 1.0). | FLOAT | No | 0.5 to 1.5 (step 0.05) |

### Audio Inputs

Shown when `speech` is `"audio"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | Audio for the avatar to lip-sync, up to 10 minutes. | AUDIO | Yes | Up to 10 minutes |

Note: When `speech` is `"script"`, `text` must be specified, and a voice is required via the `voice` selector (choosing anything other than the avatar's default voice) or a `custom_voice_id`. When `speech` is `"audio"`, `audio` is required instead.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | Generated video of the animated talking photo with lip-synced speech. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HeyGenTalkingPhotoNode/en.md)

***

**Source fingerprint (SHA-256):** `2181066a8c6191cfcaa15ece4f89a16c37e76aa22763d6df4007baa20336f05a`


# HeyGenVideoTranslateNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HeyGenVideoTranslateNode

Translate a spoken video into another language with voice cloning and lip sync.

Translate a spoken video into another language with voice cloning and lip sync. This node clones the original speaker's voice and re-animates the mouth to match the translated speech, producing a natural-looking result.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Video with speech to translate. | VIDEO | Yes | - |
| `output_language` | Target language for the translated video. | COMBO | Yes | "Arabic"<br />"Bengali"<br />"Chinese"<br />"Danish"<br />"Dutch"<br />"English"<br />"French"<br />"German"<br />"Greek"<br />"Hindi"<br />"Indonesian"<br />"Italian"<br />"Japanese"<br />"Korean"<br />"Malay"<br />"Polish"<br />"Portuguese"<br />"Russian"<br />"Spanish"<br />"Swedish"<br />"Tamil"<br />"Telugu"<br />"Thai"<br />"Turkish"<br />"Ukrainian"<br />"Vietnamese" |
| `mode` | 'speed' is faster; 'precision' produces higher-quality lip sync at a higher price. (default: "speed") | COMBO | Yes | "speed"<br />"precision" |
| `translate_audio_only` | Only swap the audio track, keeping the original mouth movements (no lip sync). (default: False) | BOOLEAN | No | True<br />False |
| `speaker_count` | Number of speakers in the video. 0 = detect automatically. Values above 0 are sent to the API as the number of speakers. (default: 0) | INT | No | 0 to 10 |
| `seed` | Not sent to HeyGen; change it to force a re-run. (default: 42) | INT | No | 0 to 2147483647 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The translated video with voice cloning and lip sync applied. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HeyGenVideoTranslateNode/en.md)

***

**Source fingerprint (SHA-256):** `709438c0c713d6db750643cc48f75352c6f293ae1ff2fd82c1bacb03b2581923`


# HitPawVideoEnhance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HitPawVideoEnhance

The HitPaw Video Enhance node uses an external API to improve the quality of videos.

The HitPaw Video Enhance node uses an external API to improve the quality of videos. It upscales low-resolution videos to a higher resolution, removes visual artifacts, and reduces noise. The processing cost is calculated per second of the input video.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for video enhancement. Selecting a model reveals a nested `resolution` parameter. The available models and their supported resolutions vary. | DYNAMIC\_COMBO | Yes | `"Portrait Restore Model (1x)"`<br />`"Portrait Restore Model (2x)"`<br />`"General Restore Model (1x)"`<br />`"General Restore Model (2x)"`<br />`"General Restore Model (4x)"`<br />`"Ultra HD Model (2x)"`<br />`"Generative Model (1x)"` |
| `video` | The input video file to be enhanced. | VIDEO | Yes | N/A |

### Portrait Restore, General Restore, and Ultra HD Model Inputs

These resolution options are shared by Portrait Restore Model (1x), Portrait Restore Model (2x), General Restore Model (1x), General Restore Model (2x), General Restore Model (4x), and Ultra HD Model (2x).

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.resolution` | The target resolution for the enhanced video. Selecting `"original"` keeps the input video's resolution. | COMBO | Yes | `"original"`<br />`"720p"`<br />`"1080p"`<br />`"2K/QHD"`<br />`"4K/UHD"`<br />`"8K"` |

### Generative Model (1x) Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.resolution` | The target resolution for the enhanced video. Selecting `"original"` keeps the input video's resolution. The `"8K"` option is not available for this model. | COMBO | Yes | `"original"`<br />`"720p"`<br />`"1080p"`<br />`"2K/QHD"`<br />`"4K/UHD"` |

**Notes:**

* The input `video` must be between 0.5 seconds and 60 minutes (3600 seconds) in duration.
* The selected `resolution` must be at least as large as the input video's dimensions. For square videos, it must be at least as large as the video's width and height. For non-square videos, it must be at least as large as the video's shorter dimension. If the target resolution is smaller, an error is raised. Selecting `"original"` keeps the input video's resolution.
* When a resolution other than `"original"` is selected, non-square videos are scaled so that their shorter dimension matches the selected resolution while preserving the aspect ratio. Square videos are scaled so that both dimensions match the square target size of the selected resolution (for example, `"4K/UHD"` produces 2048×2048).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The enhanced video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HitPawVideoEnhance/en.md)

***

**Source fingerprint (SHA-256):** `42803c7137d62dbce5021cd2bd9b9fba1a89c80e7b3f237f8a0eb03858c49967`


# HunyuanImageEditApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanImageEditApi

The Tencent HY Image: Edit node edits or combines reference images from a text instruction with Tencent's Hunyuan Image model.

The Tencent HY Image: Edit node edits or combines reference images from a text instruction with Tencent's Hunyuan Image model. Connect one to five images, describe the change in the prompt and refer to the images as `@Image1`, `@Image2` and so on. The node uploads the reference images, sends the request to the API, and returns the edited result.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model used for editing. The selected model determines which additional inputs are shown. | DYNAMIC\_COMBO | Yes | `"hy-image-3.5-preview"` |

### hy-image-3.5-preview Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | The editing instructions. Supports `@Image1`-style references to the connected images. Must not be empty (default: empty). | STRING | Yes | Any text |
| `aspect_ratio` | Aspect ratio of the output. `"auto"` follows the aspect ratio of the first reference image and is not available at 4K. Ignored when `resolution` is `"custom"`. | COMBO | Yes | `"auto"`<br />`"1:1"`<br />`"3:2"`<br />`"2:3"`<br />`"4:3"`<br />`"3:4"`<br />`"16:9"`<br />`"9:16"`<br />`"21:9"`<br />`"9:21"` (default: `"auto"`) |
| `resolution` | Pixel area of the output: 1K is about 1024x1024, 2K about 2048x2048 and 4K about 4096x4096. Anything above 2K is rendered at 2K and upscaled by the model. Set to `"custom"` to use `width` and `height` instead of a preset area. | COMBO | Yes | `"1K"`<br />`"2K"`<br />`"4K"`<br />`"custom"` (default: `"2K"`) |
| `width` | Width of the output in pixels. Used only when `resolution` is `"custom"`. | INT | Yes | 256-8192, steps of 16 (default: 2048) |
| `height` | Height of the output in pixels. Used only when `resolution` is `"custom"`. | INT | Yes | 256-8192, steps of 16 (default: 2048) |
| `seed` | Seed used for generation. Results still vary between runs with the same seed. | INT | Yes | 0-2147483647 (default: 42) |
| `reference_detail` | How much detail of the reference images the model sees: `"standard"` allows up to 1024x1024 pixels per image, `"high"` up to 2048x2048 and preserves small text and fine detail better, but takes longer. This is an advanced parameter. | COMBO | No | `"standard"`<br />`"high"` (default: `"standard"`) |
| `watermark` | Whether to add an AI-generated watermark to the result. This is an advanced parameter. | BOOLEAN | No | true<br />false (default: false) |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The reference images to edit or combine. Growable slot: connect 1 to 5 images (`image_1` through `image_5`). Refer to them in the prompt as `@Image1` ... `@Image5`, numbered in input order; a batched input counts once per image. | IMAGE | Yes | 1-5 images |

`prompt` must not be empty, and a prompt reference such as `@Image3` raises an error when only 1 or 2 images are connected. At most 5 reference images can be used in total, counting each image of a batch separately. With the `"custom"` resolution, `width` and `height` must both be multiples of 16 and their product must not exceed the 4096 x 4096 pixel area limit (about 16.7 megapixels); any aspect ratio works, although beyond roughly 6:1 the model starts repeating the subject. The `"auto"` aspect ratio only works within the 2K area limit, so at 4K pick an explicit aspect ratio or use `"custom"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The edited image produced from the reference images and the prompt. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanImageEditApi/en.md)

***

**Source fingerprint (SHA-256):** `46c112347b51a2983521f87bbeb047289515f4073c48ba5d909fd3bae4597633`


# HunyuanImageTextToImageApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanImageTextToImageApi

The Tencent HY Image: Text to Image node generates an image from a text description with Tencent's Hunyuan Image model.

The Tencent HY Image: Text to Image node generates an image from a text description with Tencent's Hunyuan Image model. The prompt is sent to the API, which rewrites and expands it before rendering, and the finished image is returned as an image batch.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model used for generation. The selected model determines which additional inputs are shown. | DYNAMIC\_COMBO | Yes | `"hy-image-3.5-preview"` |

### hy-image-3.5-preview Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Describes the image to generate. The model rewrites and expands it before rendering. Must not be empty (default: empty). | STRING | Yes | Any text |
| `aspect_ratio` | Aspect ratio of the output. `"auto"` lets the model pick the ratio from the prompt and is not available at 4K. Ignored when `resolution` is `"custom"`. | COMBO | Yes | `"auto"`<br />`"1:1"`<br />`"3:2"`<br />`"2:3"`<br />`"4:3"`<br />`"3:4"`<br />`"16:9"`<br />`"9:16"`<br />`"21:9"`<br />`"9:21"` (default: `"auto"`) |
| `resolution` | Pixel area of the image: 1K is about 1024x1024, 2K about 2048x2048 and 4K about 4096x4096. Anything above 2K is rendered at 2K and upscaled by the model. Set to `"custom"` to use `width` and `height` instead of a preset area. | COMBO | Yes | `"1K"`<br />`"2K"`<br />`"4K"`<br />`"custom"` (default: `"2K"`) |
| `width` | Width of the image in pixels. Used only when `resolution` is `"custom"`. | INT | Yes | 256-8192, steps of 16 (default: 2048) |
| `height` | Height of the image in pixels. Used only when `resolution` is `"custom"`. | INT | Yes | 256-8192, steps of 16 (default: 2048) |
| `seed` | Seed used for generation. Results still vary between runs with the same seed. | INT | Yes | 0-2147483647 (default: 42) |
| `watermark` | Whether to add an AI-generated watermark to the result. This is an advanced parameter. | BOOLEAN | No | true<br />false (default: false) |

`prompt` must not be empty. With the `"custom"` resolution, `width` and `height` must both be multiples of 16 and their product must not exceed the 4096 x 4096 pixel area limit (about 16.7 megapixels); any aspect ratio works, although beyond roughly 6:1 the model starts repeating the subject. The `"auto"` aspect ratio needs the model to choose a size, so it only works within the 2K area limit: at 4K, pick an explicit aspect ratio or use `"custom"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The generated image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanImageTextToImageApi/en.md)

***

**Source fingerprint (SHA-256):** `1d4e70d688c5aa4e79b81447da559e201078454077da34769f2a4f544fbba63f`


# KlingAvatarNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingAvatarNode

The Kling Avatar 2.0 node generates broadcast-style digital human videos from a single reference photo and an audio file.

The Kling Avatar 2.0 node generates broadcast-style digital human videos from a single reference photo and an audio file. It creates a talking avatar video with an optional text prompt to define the avatar's actions, emotions, and camera movements.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Avatar reference image. Width and height must be at least 300px. Aspect ratio must be between 1:2.5 and 2.5:1. | IMAGE | Yes | - |
| `sound_file` | Audio input. Must be between 2 and 300 seconds in duration. | AUDIO | Yes | - |
| `mode` | The generation mode to use. | COMBO | Yes | `"std"`<br />`"pro"` |
| `prompt` | Optional prompt to define avatar actions, emotions, and camera movements. (default: empty string) | STRING | No | - |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | Yes | 0 to 2147483647 |

**Note:** The `image` and `sound_file` inputs have specific validation requirements. The image must be at least 300x300 pixels with an aspect ratio between 1:2.5 and 2.5:1. The audio file must be between 2 and 300 seconds long.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated digital human video. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingAvatarNode/en.md)

***

**Source fingerprint (SHA-256):** `34f64d168d6c407d9ab474e2637513c172090a0f0c219675d32f8e70ff84f2ae`


# KlingFirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingFirstLastFrameNode

This node uses the Kling 3.0 model to generate a video.

This node uses the Kling 3.0 model to generate a video. It creates the video based on a text prompt, a specified duration, and two provided images: a starting frame and an ending frame. The node can also generate accompanying audio for the video.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model and generation settings. Selecting this option reveals a nested `resolution` parameter. | DYNAMIC\_COMBO | Yes | `"kling-v3"` |
| `prompt` | The text description that guides the video generation. Must be between 1 and 2500 characters long. | STRING | Yes | N/A |
| `duration` | The length of the video in seconds (default: 5). | INT | Yes | 3 to 15 |
| `first_frame` | The starting image for the video. Must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1. | IMAGE | Yes | N/A |
| `end_frame` | The ending image for the video. Must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1. | IMAGE | Yes | N/A |
| `generate_audio` | Controls whether to generate audio for the video (default: True). | BOOLEAN | Yes | N/A |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). | INT | Yes | 0 to 2147483647 |

### Kling V3 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `resolution` | The resolution for the generated video (default: `"1080p"`). | COMBO | Yes | `"4k"`<br />`"1080p"`<br />`"720p"` |

**Note:** The `first_frame` and `end_frame` images must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1 for the node to function correctly. The `prompt` must be between 1 and 2500 characters. The `resolution` option maps to a Kling generation mode: `"4k"`, `"1080p"` (pro), and `"720p"` (standard).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingFirstLastFrameNode/en.md)

***

**Source fingerprint (SHA-256):** `b71119c3267e2a74d2180e5182463c78828e892bfcf1eeb7c33a0f4d7019997f`


# KlingImage2VideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingImage2VideoNode

The Kling Image to Video Node generates a short video using a starting image as the first frame.

The Kling Image to Video Node generates a short video using a starting image as the first frame. It combines the image with text prompts and generation settings, then returns the resulting video along with its ID and duration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `start_frame` | The reference image used to generate the video. The image must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1. | IMAGE | Yes | - |
| `prompt` | Positive text prompt. Must not be empty. Maximum 500 characters. | STRING | Yes | - |
| `negative_prompt` | Negative text prompt. Maximum 500 characters. Leave empty if not used. | STRING | Yes | - |
| `model_name` | The model used for video generation. | COMBO | Yes | `"kling-v2-5-turbo"` |
| `cfg_scale` | Controls how closely the video follows the prompt. Higher values mean stronger adherence (default: 0.8). | FLOAT | Yes | 0.0 to 1.0 |
| `mode` | The generation mode. | COMBO | Yes | `"pro"` |
| `aspect_ratio` | The aspect ratio of the generated video (default: `"16:9"`). | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"` |
| `duration` | The duration of the generated video in seconds (default: `"5"`). | COMBO | Yes | `"5"`<br />`"10"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video output. | VIDEO |
| `video_id` | Unique identifier for the generated video. | STRING |
| `duration` | Duration information for the generated video. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingImage2VideoNode/en.md)

***

**Source fingerprint (SHA-256):** `f4a461819bc05f92d867bddcc78a66ad7beaa10707ef8cae3e7eb9e6f72c890a`


# KlingImageToVideoWithAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingImageToVideoWithAudio

The Kling Image(First Frame) to Video with Audio node uses the Kling AI model to generate a short video from a single starting image and a text prompt.

The Kling Image(First Frame) to Video with Audio node uses the Kling AI model to generate a short video from a single starting image and a text prompt. It creates a video sequence that begins with the provided image and can optionally include AI-generated audio to accompany the visuals.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The specific version of the Kling AI model to use for video generation. | COMBO | Yes | `"kling-v2-6"` |
| `start_frame` | The image that will serve as the first frame of the generated video. The image must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1. | IMAGE | Yes | - |
| `prompt` | Positive text prompt. This describes the video content you want to generate. The prompt must be between 1 and 2500 characters long. | STRING | Yes | - |
| `mode` | The operational mode for the video generation. | COMBO | Yes | `"pro"` |
| `duration` | The length of the video to generate, in seconds. | COMBO | Yes | `5`<br />`10` |
| `generate_audio` | When enabled, the node will generate audio to accompany the video. When disabled, the video will be silent. (default: True) | BOOLEAN | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video file, which may include audio depending on the `generate_audio` input. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingImageToVideoWithAudio/en.md)

***

**Source fingerprint (SHA-256):** `e0b834a297f7afd72cfb779a92557f0dc680eacd4d0e18bab0e7c59ae8624965`


# KlingLipSyncAudioToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingLipSyncAudioToVideoNode

Kling Lip Sync Audio to Video Node synchronizes mouth movements in a video file to match the audio content of an audio file.

Kling Lip Sync Audio to Video Node synchronizes mouth movements in a video file to match the audio content of an audio file. This node analyzes the vocal patterns in the audio and adjusts the facial movements in the video to create realistic lip-syncing. The process requires both a video containing a distinct face and an audio file with clearly distinguishable vocals.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The video file containing a face to be lip-synced | VIDEO | Yes | - |
| `audio` | The audio file containing vocals to sync with the video | AUDIO | Yes | - |
| `voice_language` | The language of the voice in the audio file (default: "en") | COMBO | Yes | `"en"`<br />`"zh"`<br />`"es"`<br />`"fr"`<br />`"de"`<br />`"it"`<br />`"pt"`<br />`"pl"`<br />`"tr"`<br />`"ru"`<br />`"nl"`<br />`"cs"`<br />`"ar"`<br />`"ja"`<br />`"hu"`<br />`"ko"` |

**Important Constraints:**

* The audio file should not be larger than 5MB
* The video file should not be larger than 100MB
* Video dimensions should be between 720px and 1920px in height/width
* Video duration should be between 2 seconds and 10 seconds
* The audio must contain clearly distinguishable vocals
* The video must contain a distinct face

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The processed video with lip-synced mouth movements | VIDEO |
| `video_id` | The unique identifier for the processed video | STRING |
| `duration` | The duration of the processed video | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingLipSyncAudioToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `2f88af3191ac4f9c5c9fa1aaa5b744a12620b66e55a1fe0ab16b8b3b61110128`


# KlingLipSyncTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingLipSyncTextToVideoNode

Kling Lip Sync Text to Video Node synchronizes mouth movements in a video file to match a text prompt.

Kling Lip Sync Text to Video Node synchronizes mouth movements in a video file to match a text prompt. It takes an input video and generates a new video where the character's lip movements are aligned with the provided text. The node uses voice synthesis to create natural-looking speech synchronization.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Input video file for lip synchronization. Video must be between 720px and 1920px in height/width, between 2s and 10s in duration, and no larger than 100MB. | VIDEO | Yes | - |
| `text` | Text Content for Lip-Sync Video Generation. Required when mode is text2video. Maximum length is 120 characters. | STRING | Yes | - |
| `voice` | Voice selection for the lip-sync audio (default: "Melody"). Includes both English and Chinese voice options. | COMBO | No | "Melody"<br />"Sunny"<br />"Sage"<br />"Ace"<br />"Blossom"<br />"Peppy"<br />"Dove"<br />"Shine"<br />"Anchor"<br />"Lyric"<br />"Tender"<br />"Siren"<br />"Zippy"<br />"Bud"<br />"Sprite"<br />"Candy"<br />"Beacon"<br />"Rock"<br />"Titan"<br />"Grace"<br />"Helen"<br />"Lore"<br />"Crag"<br />"Prattle"<br />"Hearth"<br />"The Reader"<br />"Commercial Lady"<br />"阳光少年"<br />"懂事小弟"<br />"运动少年"<br />"青春少女"<br />"温柔小妹"<br />"元气少女"<br />"阳光男生"<br />"幽默小哥"<br />"文艺小哥"<br />"甜美邻家"<br />"温柔姐姐"<br />"职场女青"<br />"活泼男童"<br />"俏皮女童"<br />"稳重老爸"<br />"温柔妈妈"<br />"严肃上司"<br />"优雅贵妇"<br />"慈祥爷爷"<br />"唠叨爷爷"<br />"唠叨奶奶"<br />"和蔼奶奶"<br />"东北老铁"<br />"重庆小伙"<br />"四川妹子"<br />"潮汕大叔"<br />"台湾男生"<br />"西安掌柜"<br />"天津姐姐"<br />"新闻播报男"<br />"译制片男"<br />"撒娇女友"<br />"刀片烟嗓"<br />"乖巧正太" |
| `voice_speed` | Speech Rate. Valid range: 0.8\~2.0, accurate to one decimal place. (default: 1) | FLOAT | No | 0.8-2.0 |

**Video Requirements:**

* Video file should not be larger than 100MB
* Height/width should be between 720px and 1920px
* Duration should be between 2s and 10s

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | Generated video with lip-synchronized audio | VIDEO |
| `video_id` | Unique identifier for the generated video | STRING |
| `duration` | Duration information for the generated video | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingLipSyncTextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `28a7be92d7e8a57efeb7e2913124e4373dfc75fbdba6ff7036fafb3a8ae43a60`


# KlingMotionControl - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingMotionControl

The Kling Motion Control node generates a video by applying the motion, expressions, and camera movements from a reference video to a character defined by a reference image and a t

The Kling Motion Control node generates a video by applying the motion, expressions, and camera movements from a reference video to a character defined by a reference image and a text prompt. It allows you to control whether the character's final orientation comes from the reference video or the reference image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | A text description of the desired video. Maximum length is 2500 characters. | STRING | Yes | N/A |
| `reference_image` | An image of the character to animate. Minimum dimensions are 340x340 pixels. The aspect ratio must be between 1:2.5 and 2.5:1. | IMAGE | Yes | N/A |
| `reference_video` | Motion reference video used to drive movement/expression. Duration limits depend on `character_orientation` setting. Minimum dimensions are 340x340 pixels, maximum dimensions are 3850x3850 pixels. | VIDEO | Yes | N/A |
| `keep_original_sound` | Determines if the original audio from the reference video is kept in the output. Default is `True`. | BOOLEAN | No | N/A |
| `character_orientation` | Controls where the character's facing/orientation comes from. `"video"`: movements, expressions, camera moves, and orientation follow the motion reference video (other details via prompt). `"image"`: movements and expressions still follow the motion reference video, but the character orientation matches the reference image (camera/other details via prompt). | COMBO | No | `"video"`<br />`"image"` |
| `mode` | The generation mode to use. | COMBO | No | `"pro"`<br />`"std"` |
| `model` | The Kling model version to use. Default is `"kling-v2-6"`. | COMBO | No | `"kling-v3"`<br />`"kling-v2-6"` |

**Constraints:**

* The `reference_video` duration must be between 3 and 30 seconds when `character_orientation` is set to `"video"`.
* The `reference_video` duration must be between 3 and 10 seconds when `character_orientation` is set to `"image"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video with the character performing the motion from the reference video. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingMotionControl/en.md)

***

**Source fingerprint (SHA-256):** `a61e55fabe53f4e13fa993c3d891db40024709ea4fb6b16b5716d893b2bd23b5`


# KlingOmniProEditVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProEditVideoNode

The Kling Omni Edit Video (Pro) node uses an AI model to edit an existing video based on a text description.

The Kling Omni Edit Video (Pro) node uses an AI model to edit an existing video based on a text description. You provide a source video and a prompt, and the node generates a new video of the same length with the requested changes. It can optionally use reference images to guide the style and keep the original audio from the source video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The AI model to use for video editing (default: `"kling-v3-omni"`). | COMBO | Yes | `"kling-v3-omni"`<br />`"kling-video-o1"` |
| `prompt` | A text prompt describing the video content. This can include both positive and negative descriptions. | STRING | Yes | |
| `video` | Video for editing. The output video length will be the same. | VIDEO | Yes | |
| `keep_original_sound` | Determines if the original audio from the input video is kept in the output (default: True). | BOOLEAN | Yes | |
| `reference_images` | Up to 4 additional reference images. | IMAGE | No | |
| `resolution` | The resolution for the output video (default: `"1080p"`). | COMBO | No | `"1080p"`<br />`"720p"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). | INT | No | 0 to 2147483647 |

**Constraints and Limitations:**

* The `prompt` must be between 1 and 2500 characters long.
* The input `video` must be between 3.0 and 10.05 seconds in duration.
* The input `video` dimensions must be between 720x720 and 2160x2160 pixels.
* A maximum of 4 `reference_images` can be provided when a video is used.
* Each `reference_image` must be at least 300x300 pixels.
* Each `reference_image` must have an aspect ratio between 1:2.5 and 2.5:1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The edited video generated by the AI model. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProEditVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `4aa7779a30183c80f025e15ae693ba23021013c68d247753e7e9a4c3a64762da`


# KlingOmniProFirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProFirstLastFrameNode

This node uses the latest Kling AI model to generate a video from a start frame, an optional end frame, or reference images.

This node uses the latest Kling AI model to generate a video from a start frame, an optional end frame, or reference images. It can create a single video or a multi-shot storyboard with individual prompts and durations for each segment. The node processes these inputs to produce a video of a specified length and resolution, with optional audio generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The specific Kling AI model to use for video generation. | COMBO | Yes | `"kling-v3-omni"`<br />`"kling-video-o1"` |
| `prompt` | A text prompt describing the video content. This can include both positive and negative descriptions. Ignored when storyboards are enabled. | STRING | Yes | - |
| `duration` | The desired length of the generated video in seconds (default: 5). | INT | Yes | 3 to 15 |
| `first_frame` | The starting image for the video sequence. | IMAGE | Yes | - |
| `end_frame` | An optional end frame for the video. This cannot be used simultaneously with `reference_images`. Does not work with storyboards. | IMAGE | No | - |
| `reference_images` | Up to 6 additional reference images. | IMAGE | No | - |
| `resolution` | The output resolution for the generated video (default: "1080p"). | COMBO | No | `"4k"`<br />`"1080p"`<br />`"720p"` |
| `storyboards` | Generate a series of video segments with individual prompts and durations. Only supported for `kling-v3-omni`. | DYNAMIC\_COMBO | No | `"disabled"`<br />`"1 storyboard"`<br />`"2 storyboards"`<br />`"3 storyboards"`<br />`"4 storyboards"`<br />`"5 storyboards"`<br />`"6 storyboards"` |
| `generate_audio` | Generate audio for the video (default: False). Only supported for `kling-v3-omni`. | BOOLEAN | No | True / False |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). | INT | No | 0 to 2147483647 |

### Storyboard Inputs

When `storyboards` is set to a value other than `"disabled"`, the following inputs are added for each selected segment (N ranges from 1 to the selected number of storyboards):

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `storyboard_N_prompt` | Prompt for storyboard segment N. Max 512 characters. (default: "") | STRING | Yes | - |
| `storyboard_N_duration` | Duration for storyboard segment N in seconds (default: 4). | INT | Yes | 1 to 15 |

**Important Constraints:**

* The `end_frame` input cannot be used at the same time as the `reference_images` input.
* The `end_frame` input cannot be used simultaneously with storyboards.
* The `kling-video-o1` model does not support durations greater than 10 seconds, audio generation, 4k resolution, or storyboards.
* If you do not provide an `end_frame` or any `reference_images` with the `kling-video-o1` model, the `duration` can only be set to 5 or 10 seconds.
* All input images (`first_frame`, `end_frame`, and any `reference_images`) must have a minimum dimension of 300 pixels in both width and height.
* The aspect ratio of all input images must be between 1:2.5 and 2.5:1.
* A maximum of 6 images can be provided via the `reference_images` input.
* The `prompt` text must be between 1 and 2500 characters in length (0 characters allowed when storyboards are enabled).
* The prompt can reference the input images using the placeholders `@image`, `@image1`, `@image2`, etc.; these are automatically converted to the API-compatible image reference format.
* When storyboards are enabled, the total duration of all storyboard segments must equal the global `duration` value.
* Each storyboard prompt must be between 1 and 512 characters in length.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProFirstLastFrameNode/en.md)

***

**Source fingerprint (SHA-256):** `2b26914ba29c3d877a981e41acb44d15dfacc604d86d7cc232ebfa7fda0ae3b8`


# KlingOmniProImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProImageToVideoNode

This node uses the Kling AI model to generate a video based on a text prompt and up to seven reference images.

This node uses the Kling AI model to generate a video based on a text prompt and up to seven reference images. It lets you control the video's aspect ratio, duration, and resolution, and optionally use storyboards or generate audio. The node sends the request to an external API and returns the generated video.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The specific Kling model to use for video generation (default: `"kling-v3-omni"`). | COMBO | Yes | `"kling-v3-omni"`<br />`"kling-video-o1"` |
| `prompt` | A text prompt describing the video content. This can include both positive and negative descriptions. Ignored when storyboards are enabled. Placeholders such as `@image` or `@video` (optionally numbered) are automatically converted to the API-compatible format. Must be between 1 and 2500 characters (can be empty when storyboards are enabled). | STRING | Yes | 1 to 2500 characters (0 to 2500 when storyboards are enabled) |
| `aspect_ratio` | The desired aspect ratio for the generated video. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"` |
| `duration` | The length of the video in seconds, adjusted with a slider (default: 5). | INT | Yes | 3 to 15 |
| `reference_images` | Up to 7 reference images. Each image must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1. | IMAGE | Yes | 1 to 7 images |
| `resolution` | The output resolution of the video (default: `"1080p"`). | COMBO | No | `"4k"`<br />`"1080p"`<br />`"720p"` |
| `storyboards` | Generate a series of video segments with individual prompts and durations. Only supported for `kling-v3-omni`. When enabled, the global `prompt` is ignored, and the total duration of all storyboard segments must equal the global `duration` (default: `"disabled"`). | DYNAMIC\_COMBO | No | `"disabled"`<br />`"1 storyboard"`<br />`"2 storyboards"`<br />`"3 storyboards"`<br />`"4 storyboards"`<br />`"5 storyboards"`<br />`"6 storyboards"` |
| `generate_audio` | Generate audio for the video. Only supported for `kling-v3-omni` (default: false). | BOOLEAN | No | `true`<br />`false` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). | INT | No | 0 to 2147483647 |

### Storyboard Inputs

When `storyboards` is enabled, the following inputs appear for each selected storyboard segment. N ranges from 1 up to the selected number of storyboards.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `storyboard_N_prompt` | Prompt for storyboard segment N. Max 512 characters. | STRING | Yes | 1 to 512 characters |
| `storyboard_N_duration` | Duration for storyboard segment N in seconds (default: 4). | INT | Yes | 1 to 15 |

**Note:** The `reference_images` input accepts a maximum of 7 images. If more are provided, the node raises an error. Each image is validated for minimum dimensions (300x300 pixels) and aspect ratio (between 1:2.5 and 2.5:1).

**Model-specific constraints:**

* `kling-video-o1` does not support durations greater than 10 seconds.
* `kling-video-o1` does not support audio generation.
* `kling-video-o1` does not support 4k resolution.
* `kling-video-o1` does not support storyboards.

**Storyboard constraint:** The total duration of all storyboard segments must equal the global `duration` value. If the sum does not match, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `ccf7881065d2a365cdaa0e164b8b1d46c67985067866ab0fe91d492a62015f07`


# KlingOmniProTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProTextToVideoNode

This node generates a video from a text description using the latest Kling AI model.

This node generates a video from a text description using the latest Kling AI model. It sends your prompt to a remote API and returns the generated video. You can control the video's length, shape, and quality, and optionally build multi-shot storyboards.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The specific Kling model to use for video generation (default: `"kling-v3-omni"`). | COMBO | Yes | `"kling-v3-omni"`<br />`"kling-video-o1"` |
| `prompt` | A text prompt describing the video content. This can include both positive and negative descriptions. Ignored when storyboards are enabled. | STRING | Yes | 0 to 2500 characters |
| `aspect_ratio` | The shape or dimensions of the video to generate. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"` |
| `duration` | The length of the video in seconds (default: 5). | INT | Yes | 3 to 15 seconds |
| `resolution` | The quality or pixel resolution of the video (default: `"1080p"`). Internally maps to standard, pro, or 4k quality. | COMBO | No | `"4k"`<br />`"1080p"`<br />`"720p"` |
| `storyboards` | Generate a series of video segments with individual prompts and durations. Ignored for the o1 model. | DYNAMIC\_COMBO | No | `"disabled"`<br />`"1 storyboard"`<br />`"2 storyboards"`<br />`"3 storyboards"`<br />`"4 storyboards"`<br />`"5 storyboards"`<br />`"6 storyboards"` |
| `generate_audio` | Whether to generate audio for the video (default: False). | BOOLEAN | No | True / False |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). | INT | No | 0 to 2147483647 |

### Storyboard Sub-Inputs

When `storyboards` is set to a value other than `"disabled"`, the following inputs appear for each storyboard segment. In the parameter names below, `{i}` is the segment number, from 1 up to the selected storyboard count.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `storyboard_{i}_prompt` | Prompt for storyboard segment \{i}. Max 512 characters. | STRING | Yes | 1 to 512 characters |
| `storyboard_{i}_duration` | Duration for storyboard segment \{i} in seconds (default: 4). | INT | Yes | 1 to 15 seconds |

### Parameter Constraints and Limitations

* **Model-specific limitations:**
  * The `kling-video-o1` model only supports durations of **5 or 10 seconds**.
  * The `kling-video-o1` model does **not** support audio generation.
  * The `kling-video-o1` model does **not** support 4k resolution.
  * The `kling-video-o1` model does **not** support storyboards.
* **Storyboard constraints:**
  * When storyboards are enabled, the `prompt` field is ignored.
  * Each storyboard requires its own prompt (1 to 512 characters) and duration.
  * The total duration of all storyboards must exactly equal the global `duration` parameter.
* **Prompt requirements:**
  * When storyboards are **disabled**, the `prompt` field is required (minimum 1 character).
  * When storyboards are **enabled**, the `prompt` field can be empty (0 characters).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The video generated based on the provided text prompt and settings. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProTextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `d2fbbe7c6aae283eb3fa7f73d788b809098a9a4dd6e8ada54697d43fd5bf10f2`


# KlingOmniProVideoToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProVideoToVideoNode

This node uses the Kling AI model to generate a new video based on an input video and optional reference images.

This node uses the Kling AI model to generate a new video based on an input video and optional reference images. You provide a text prompt describing the desired content, and the node transforms the reference video accordingly. It can also incorporate up to four additional reference images to guide the style and content of the output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The specific Kling model to use for video generation (default: "kling-v3-omni"). | COMBO | Yes | `"kling-v3-omni"`<br />`"kling-video-o1"` |
| `prompt` | A text prompt describing the video content. This can include both positive and negative descriptions. | STRING | Yes | N/A |
| `aspect_ratio` | The desired aspect ratio for the generated video. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"` |
| `duration` | The length of the generated video in seconds (default: 3). | INT | Yes | 3 to 10 |
| `reference_video` | Video to use as a reference. | VIDEO | Yes | N/A |
| `keep_original_sound` | Determines if the audio from the reference video is kept in the output (default: True). | BOOLEAN | Yes | N/A |
| `reference_images` | Up to 4 additional reference images. | IMAGE | No | N/A |
| `resolution` | The resolution for the generated video (default: "1080p"). | COMBO | No | `"1080p"`<br />`"720p"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). | INT | No | 0 to 2147483647 |

**Parameter Constraints:**

* The `prompt` must be between 1 and 2500 characters long.
* The `reference_video` must be between 3.0 and 10.05 seconds in duration.
* The `reference_video` must have dimensions between 720x720 and 2160x2160 pixels.
* A maximum of 4 `reference_images` can be provided. Each image must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The newly generated video. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProVideoToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `3dc2e3d153ddd9e6da705b764c51b4a859d66464b893fdebb0689d2ad5e870c7`


# KlingStartEndFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingStartEndFrameNode

This node creates a video sequence that transitions between your provided start and end images.

This node creates a video sequence that transitions between your provided start and end images. It generates all the frames in between to produce a smooth transformation from the first frame to the last frame. This node calls the image-to-video API but only supports the input options that work with the `image_tail` request field.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `start_frame` | Reference Image - URL or Base64 encoded string, cannot exceed 10MB, resolution not less than 300\*300px, aspect ratio between 1:2.5 \~ 2.5:1. Base64 should not include data:image prefix. | IMAGE | Yes | - |
| `end_frame` | Reference Image - End frame control. URL or Base64 encoded string, cannot exceed 10MB, resolution not less than 300\*300px. Base64 should not include data:image prefix. | IMAGE | Yes | - |
| `prompt` | Positive text prompt. Must not be empty and cannot exceed 500 characters. | STRING | Yes | - |
| `negative_prompt` | Negative text prompt. Cannot exceed 500 characters. If left empty, it is omitted from the request. | STRING | Yes | - |
| `cfg_scale` | Controls the strength of the prompt guidance (default: 0.5). | FLOAT | Yes | 0.0-1.0 |
| `aspect_ratio` | The aspect ratio for the generated video (default: "16:9"). | COMBO | Yes | "16:9"<br />"9:16"<br />"1:1" |
| `mode` | The configuration to use for the video generation following the format: mode / duration / model\_name. (default: "pro mode / 5s duration / kling-v2-5-turbo") | COMBO | Yes | "pro mode / 5s duration / kling-v2-5-turbo"<br />"pro mode / 10s duration / kling-v2-5-turbo" |

**Image Constraints:**

* Both `start_frame` and `end_frame` are required and cannot exceed 10MB in file size.
* Minimum resolution: 300×300 pixels for both images.
* `start_frame` aspect ratio must be between 1:2.5 and 2.5:1.
* Base64 encoded images should not include the "data:image" prefix.

**Prompt Constraints:**

* `prompt` must not be empty and cannot exceed 500 characters.
* `negative_prompt` cannot exceed 500 characters; when empty, it is not sent with the request.

**Mode Notes:**

* Both mode options use pro mode with the kling-v2-5-turbo model and differ only in duration (5 seconds or 10 seconds).
* Pricing per generation, as shown in the node's price badge: 5s mode costs $0.35 USD and 10s mode costs $0.70 USD.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video sequence. | VIDEO |
| `video_id` | Unique identifier for the generated video. | STRING |
| `duration` | Duration of the generated video. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingStartEndFrameNode/en.md)

***

**Source fingerprint (SHA-256):** `a27977226360a425614255f8330ce7fd8ba94b8c3020eb8fdddc01eb74f035c1`


# KlingTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingTextToVideoNode

The Kling Text to Video node generates videos from text descriptions using the Kling video generation API.

The Kling Text to Video node generates videos from text descriptions using the Kling video generation API. It sends the prompt and settings (aspect ratio, generation mode, and CFG scale) to the API, waits for the generation task to complete, and then returns the resulting video along with its ID and duration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Positive text prompt | STRING | Yes | Maximum 2500 characters |
| `negative_prompt` | Negative text prompt | STRING | No | Maximum 2500 characters |
| `cfg_scale` | Configuration scale value that controls how closely the video follows the prompt (default: 1.0) | FLOAT | No | 0.0 to 1.0 |
| `aspect_ratio` | Video aspect ratio setting (default: "16:9") | COMBO | No | "16:9"<br />"9:16"<br />"1:1" |
| `mode` | The configuration to use for the video generation following the format: mode / duration / model\_name (default: "pro mode / 5s duration / kling-v2-5-turbo") | COMBO | No | "pro mode / 5s duration / kling-v2-5-turbo"<br />"pro mode / 10s duration / kling-v2-5-turbo" |

Note: The `prompt` parameter is required and must not be empty. Both `prompt` and `negative_prompt` are limited to a maximum of 2500 characters. The 10-second `mode` option costs more than the 5-second option.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video output | VIDEO |
| `video_id` | Unique identifier for the generated video | STRING |
| `duration` | Duration information for the generated video | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingTextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `6a63b0b8bc45dc5a6300cdfe7a373399eeead36de6727f7aae2c026ba0deaea8`


# KlingTextToVideoWithAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingTextToVideoWithAudio

The Kling Text to Video with Audio node generates a short video from a text description.

The Kling Text to Video with Audio node generates a short video from a text description. It sends a request to the Kling AI service, which processes the prompt and returns a video file. The node can also generate accompanying audio for the video based on the text.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model_name` | The specific AI model to use for video generation. | COMBO | Yes | `"kling-v2-6"` |
| `prompt` | Positive text prompt. The description used to generate the video. Must be between 1 and 2500 characters. | STRING | Yes | - |
| `mode` | The operational mode for the video generation. | COMBO | Yes | `"pro"` |
| `aspect_ratio` | The desired width-to-height ratio for the generated video. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"` |
| `duration` | The length of the video in seconds. | COMBO | Yes | `5`<br />`10` |
| `generate_audio` | Controls whether audio is generated for the video. When enabled, the AI will create sound based on the prompt (default: `True`). | BOOLEAN | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingTextToVideoWithAudio/en.md)

***

**Source fingerprint (SHA-256):** `ddd2f3c1799abac067a05f3f5d6442ad4fe023d2f4f9afbde2894ca66854977e`


# KlingVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingVideoNode

This node generates videos with the Kling V3 model.

This node generates videos with the Kling V3 model. It supports text-to-video, where a video is created from a text description, and image-to-video, where an existing image is animated. It can also create multi-segment videos using storyboard prompts and optionally generate audio.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `multi_shot` | Generate a series of video segments with individual prompts and durations. When set to a storyboard option, additional inputs for each storyboard's prompt and duration appear. | DYNAMIC\_COMBO | Yes | `"disabled"`<br />`"1 storyboard"`<br />`"2 storyboards"`<br />`"3 storyboards"`<br />`"4 storyboards"`<br />`"5 storyboards"`<br />`"6 storyboards"` |
| `generate_audio` | When enabled, the node generates audio for the video. Note: `"kling-3.0-turbo"` always generates native audio, so the audio toggle is ignored for that model. Default is True. | BOOLEAN | Yes | True<br />False |
| `model` | Model and generation settings. Selecting a model reveals its resolution and aspect ratio sub-parameters. | DYNAMIC\_COMBO | Yes | `"kling-v3"`<br />`"kling-3.0-turbo"` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. Default is 0. | INT | Yes | 0 to 2147483647 |
| `start_frame` | Optional start frame image. When connected, switches to image-to-video mode. | IMAGE | No | - |

### kling-v3 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.resolution` | The resolution for the generated video. Default is `"1080p"`. | COMBO | Yes | `"4k"`<br />`"1080p"`<br />`"720p"` |
| `model.aspect_ratio` | The aspect ratio for the generated video. Ignored in image-to-video mode. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"` |

### kling-3.0-turbo Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.resolution` | The resolution for the generated video. Default is `"720p"`. | COMBO | Yes | `"1080p"`<br />`"720p"` |
| `model.aspect_ratio` | The aspect ratio for the generated video. Ignored in image-to-video mode. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"` |

### Multi-shot Inputs

**When `multi_shot` is set to `"disabled"`:**

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | The main text description for the video. Must be between 1 and 2500 characters. | STRING | Yes | 1 to 2500 characters |
| `negative_prompt` | Text describing what should not appear in the video. Can be left empty. | STRING | No | - |
| `duration` | The length of the video in seconds. Default is 5. | INT | Yes | 3 to 15 |

**When `multi_shot` is set to a storyboard option (e.g., `"3 storyboards"`):**

For each storyboard segment N (from 1 up to the selected storyboard count), the following inputs appear:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `storyboard_N_prompt` | Prompt for storyboard segment N. Max 512 characters. | STRING | Yes | 1 to 512 characters |
| `storyboard_N_duration` | Duration for storyboard segment N in seconds. Default is 4. | INT | Yes | 1 to 15 |

**Constraints and behavior:**

* Text-to-video mode is used when `start_frame` is not connected; image-to-video mode is used when `start_frame` is connected. In image-to-video mode, `model.aspect_ratio` is ignored and the input image must be at least 300x300 pixels with an aspect ratio between 1:2.5 and 2.5:1.
* In storyboard mode, the main `prompt` and `negative_prompt` are not used. The total sum of all storyboard durations must be between 3 and 15 seconds.
* `negative_prompt` is only used with `kling-v3`; it is ignored when `kling-3.0-turbo` is selected.
* For `kling-v3`, each storyboard is sent to the API as a separate segment. For `kling-3.0-turbo`, the storyboard prompts and durations are combined into a single multi-shot prompt.
* For `kling-3.0-turbo`, `generate_audio` is ignored because this model always generates native audio.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `2863d7a971a1978b6009e5321ed2112a9c04809281acd5f65d85ab72c4b49f08`


# LtxApi25AudioToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LtxApi25AudioToVideo

This node generates a video that follows an audio track using the LTX 2.5 model.

This node generates a video that follows an audio track using the LTX 2.5 model. The audio determines the video duration (between 2 and 20 seconds), and you can optionally provide an image to use as the first frame. The video is generated through the LTX 2.5 API service.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `audio` | Audio track driving the video. Its length (2-20 seconds) sets the video duration. | AUDIO | Yes | 2-20 seconds |
| `model` | The LTX 2.5 model version to use. Selecting a model also reveals the `resolution` sub-option for that model. | COMBO | Yes | "LTX-2.5 (Fast)"<br />"LTX-2.5 (Pro)" |
| `resolution` | The output resolution of the generated video. This sub-option is shown under the selected `model` (default: "1920x1080"). Both models offer the same resolution options. | COMBO | Yes | "1920x1080"<br />"1080x1920" |
| `prompt` | A text description that guides the content of the generated video (default: ""). Must contain at least 1 character and at most 10000 characters. | STRING | Yes | 1-10000 characters |
| `seed` | A number that controls the randomness of the generation. The same seed produces the same result (default: 42). | INT | Yes | Any integer |
| `image` | Optional first frame to be used for the video. Only one image is supported. | IMAGE | No | Single image |

Notes on constraints:

* The audio duration must be between 2 and 20 seconds; the node raises an error if it is outside this range.
* The prompt is required and cannot be empty; it must be between 1 and 10000 characters.
* Only a single input image is accepted when `image` is provided.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video driven by the provided audio track. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LtxApi25AudioToVideo/en.md)

***

**Source fingerprint (SHA-256):** `ae0d0123c0421f645448496d30a53a21aba1728310180719a4c4599eca8351c5`


# LtxApi25ImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LtxApi25ImageToVideo

This node generates a professional-quality video from a starting image using an LTX 2.5 model.

This node generates a professional-quality video from a starting image using an LTX 2.5 model. You describe the video content with a text prompt, select a model variant, and adjust duration, resolution, frame rate, and audio generation. An optional final frame can be supplied to define the end of the video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | First frame to be used for the video. | IMAGE | Yes | Exactly one image |
| `model` | Model settings group. Selects the LTX 2.5 model variant to use. | COMBO | Yes | "LTX-2.5 (Fast)"<br />"LTX-2.5 (Pro)" |
| `model.duration` | Length of the generated video in seconds. | INT | Yes | Integer |
| `model.resolution` | Resolution of the generated video. Available options may depend on the selected model. | COMBO | Yes | "1280x720"<br />"720x1280"<br />"1920x1080"<br />"1080x1920"<br />"2560x1440"<br />"1440x2560"<br />"3840x2160"<br />"2160x3840" |
| `model.fps` | Frame rate of the generated video. | INT | Yes | Integer (default: 25) |
| `model.generate_audio` | Whether to generate audio for the video. | BOOLEAN | Yes | True<br />False (default: True) |
| `prompt` | Text description of the video content to generate. Must be between 1 and 10000 characters. | STRING | Yes | 1 to 10000 characters |
| `seed` | Seed value for reproducible generation. Using the same seed with the same settings produces the same result. | INT | Yes | Integer (default: 42) |
| `last_frame` | Last frame to be used for the video. | IMAGE | No | Exactly one image |

**Note:** Only one image is supported for `image`. If `last_frame` is provided, it must also contain exactly one image. The available `model.resolution` options may vary depending on the selected `model` variant. The price of a run depends on the selected `model`, `model.duration`, and `model.resolution`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video based on the provided start image and generation settings. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LtxApi25ImageToVideo/en.md)

***

**Source fingerprint (SHA-256):** `13db42e5e0d4237424b30b960ec12f5dd16808d21b85e100e5861c095b351c79`


# LtxApi25TextToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LtxApi25TextToVideo

LTX 2.5 Text To Video is an API node that generates professional-quality videos from a text description using the LTX 2.5 model.

LTX 2.5 Text To Video is an API node that generates professional-quality videos from a text description using the LTX 2.5 model. You provide a prompt and choose generation settings such as the model tier, duration, resolution, frame rate, and whether to include audio; the node submits the task to the LTX API and returns the resulting video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The LTX 2.5 model tier to use for video generation. | STRING | Yes | "LTX-2.5 (Fast)"<br />"LTX-2.5 (Pro)" |
| `model.duration` | The length of the generated video. | INT | Yes | Integer |
| `model.resolution` | The output resolution of the video. Available options depend on the selected `model`. | STRING | Yes | With "LTX-2.5 (Fast)":<br />"1280x720"<br />"720x1280"<br />"1920x1080"<br />"1080x1920"<br />"2560x1440"<br />"1440x2560"<br />"3840x2160"<br />"2160x3840"<br />With "LTX-2.5 (Pro)":<br />"1280x720"<br />"720x1280"<br />"1920x1080"<br />"1080x1920" |
| `model.fps` | Frame rate of the generated video (default: 25). | INT | No | Integer |
| `model.generate_audio` | Whether to generate audio together with the video (default: True). | BOOLEAN | No | True<br />False |
| `prompt` | The text description of the video to generate. A non-empty prompt of up to 10,000 characters is required (default: ""). | STRING | Yes | 1 to 10000 characters |
| `seed` | Seed value used for reproducible generation (default: 42). | INT | No | Integer |

Note: The available `model.resolution` options depend on the selected `model`. "LTX-2.5 (Fast)" supports resolutions up to 2160x3840, while "LTX-2.5 (Pro)" supports resolutions up to 1920x1080.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video returned by the LTX API, ready for further use in the workflow. If audio generation was enabled, the video includes synchronized audio. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LtxApi25TextToVideo/en.md)

***

**Source fingerprint (SHA-256):** `02e131116fb0760cce2cea1e9bc49fa16dd7e4e296903fef5e44b7942b6e84c9`


# LumaConceptsNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaConceptsNode

Holds one or more Camera Concepts for use with Luma Text to Video and Luma Image to Video nodes.

Holds one or more Camera Concepts for use with Luma Text to Video and Luma Image to Video nodes. This node allows you to select up to four camera concepts and optionally combine them with existing concept chains.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `concept1` | First camera concept selection from available Luma concepts | STRING | Yes | Multiple options available<br />Includes "None" option |
| `concept2` | Second camera concept selection from available Luma concepts | STRING | Yes | Multiple options available<br />Includes "None" option |
| `concept3` | Third camera concept selection from available Luma concepts | STRING | Yes | Multiple options available<br />Includes "None" option |
| `concept4` | Fourth camera concept selection from available Luma concepts | STRING | Yes | Multiple options available<br />Includes "None" option |
| `luma_concepts` | Optional Camera Concepts to add to the ones chosen here | LUMA\_CONCEPTS | No | N/A |

**Note:** All concept parameters (`concept1` through `concept4`) can be set to "None" if you don't want to use all four concept slots. The node will merge any provided `luma_concepts` with the selected concepts to create a combined concept chain.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `luma_concepts` | Combined camera concept chain containing all selected concepts | LUMA\_CONCEPTS |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaConceptsNode/en.md)

***

**Source fingerprint (SHA-256):** `e684f7d9d2975d4168701e4f6a79dc6b22854d62b58ce016477a05c66dd6e058`


# LumaImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaImageToVideoNode

Generates videos synchronously based on a text prompt and optional starting/ending images.

Generates videos synchronously based on a text prompt and optional starting/ending images. This node uses the Luma API to create videos, allowing you to define the video's content through a prompt and optionally specify the first and/or last frame to control the video's structure.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the video generation (default: "") | STRING | Yes | - |
| `model` | Selects the video generation model from available Luma models | COMBO | Yes | `"ray-1-6"`<br />`"ray-2"` |
| `resolution` | Output resolution for the generated video (default: "540p"). This parameter is ignored when using the `ray-1-6` model. | COMBO | Yes | `"540p"`<br />`"720p"`<br />`"1080p"`<br />`"4k"` |
| `duration` | Duration of the generated video. This parameter is ignored when using the `ray-1-6` model. | COMBO | Yes | `"5s"`<br />`"9s"` |
| `loop` | Whether the generated video should loop (default: False) | BOOLEAN | Yes | - |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. (default: 0) | INT | Yes | 0 to 18446744073709551615 |
| `first_image` | First frame of generated video. (optional) | IMAGE | No | - |
| `last_image` | Last frame of generated video. (optional) | IMAGE | No | - |
| `luma_concepts` | Optional Camera Concepts to dictate camera motion via the Luma Concepts node. (optional) | CUSTOM | No | - |

**Note:** At least one of `first_image` or `last_image` must be provided. The node will raise an exception if both are missing. The `resolution` and `duration` parameters are ignored when the `model` is set to `ray-1-6`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `2eea8934bcce20b093b88c52e430d21077705d57ab259bf620a94e46eac65e6e`


# LumaRay32ExtendVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaRay32ExtendVideoNode

Luma Ray 3.2 Extend Video continues a previous Luma Ray 3.2 video generation by creating a new 5-second segment either after the original clip (forward) or before it (backward).

Luma Ray 3.2 Extend Video continues a previous Luma Ray 3.2 video generation by creating a new 5-second segment either after the original clip (forward) or before it (backward). Connect the `generation_id` output from an earlier Luma Ray 3.2 node to use that clip as the starting frame (forward) or ending frame (backward) of the extension. Extensions are always 5 seconds long.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `source_generation_id` | Generation ID of the prior Ray 3.2 video to extend. Connect the `generation_id` output of another Luma Ray 3.2 node. Default: "" (empty). This value is required and must not be empty. | STRING | Yes | – |
| `direction` | Forward continues after the prior clip; backward is prepended before it. Forward uses the source clip as the starting frame; backward uses it as the ending frame. Selecting "Forward (continue after)" adds the `loop` option. | DYNAMIC\_COMBO | Yes | "Forward (continue after)"<br />"Backward (lead-in before)" |
| `prompt` | Text prompt for the new content. Default: "" (empty). Must be between 1 and 6000 characters. | STRING | Yes | 1 to 6000 characters |
| `resolution` | Output resolution for the extended video segment. Default: "720p". | COMBO | Yes | "540p"<br />"720p"<br />"1080p" |
| `seed` | Seed to determine if node should re-run; results are nondeterministic regardless of seed. Default: 0. | INT | Yes | 0 to 0xFFFFFFFFFFFFFFFF (18446744073709551615) |

### Forward (continue after) Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `loop` | Loop the extended video seamlessly (forward extend only). Default: False. | BOOLEAN | No | True<br />False |

### Backward (lead-in before) Inputs

This direction adds no additional parameters.

**Note:** Extensions are always 5 seconds. The `loop` parameter is only available when `direction` is "Forward (continue after)"; when using "Backward (lead-in before)", the `loop` option is not available. The `prompt` must be between 1 and 6000 characters. The `source_generation_id` is required and must be connected from a prior Luma Ray 3.2 node's `generation_id` output.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `VIDEO` | The generated 5-second extended video segment. | VIDEO |
| `generation_id` | Unique identifier for this generation, which can be connected to another Luma Ray 3.2 Extend Video node for further extensions. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaRay32ExtendVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `a67ca53d4bcb9f3fd82bc0482b579f5f7fe4bf866f8d83cb922e1082ad320057`


# LumaRay32ImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaRay32ImageToVideoNode

Generate a video from a start and/or end frame using Luma's Ray 3.2 model.

Generate a video from a start and/or end frame using Luma's Ray 3.2 model. Image-anchored generations are always 5 seconds in duration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for the video generation. | STRING | Yes | 1 to 6000 characters |
| `resolution` | The output resolution of the generated video (default: "720p"). | COMBO | Yes | "360p"<br />"540p"<br />"720p"<br />"1080p" |
| `loop` | Make the video loop seamlessly. Not available when an end\_frame is set. | BOOLEAN | Yes | True<br />False |
| `seed` | Seed value for reproducible generation. | INT | Yes | 0 to 2147483647 |
| `start_frame` | First frame of the generated video. | IMAGE | No | - |
| `end_frame` | Last frame of the generated video. | IMAGE | No | - |

**Note:** At least one of `start_frame` or `end_frame` must be provided. If both are provided, the generated video will transition from the start frame to the end frame. The `loop` option cannot be enabled when an `end_frame` is set.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video output. | VIDEO |
| `generation_id` | The unique identifier for the generation request. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaRay32ImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `ff479c196f10153ffa09af6acfb4e286d1934aa28a5e9b413613097a2cfb5f2a`


# LumaRay32KeyframeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaRay32KeyframeNode

This node anchors a guide image to a specific position on the Luma Ray 3.2 output video timeline.

This node anchors a guide image to a specific position on the Luma Ray 3.2 output video timeline. Connect this node to the "keyframes" input of the Luma Ray 3.2 Keyframes to Video node, and chain several keyframes together by connecting the optional "keyframes" input.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Guide image to place at the chosen moment of the output video. | IMAGE | Yes | - |
| `position` | How to place this image on the output video's timeline. | DYNAMIC\_COMBO | Yes | "Fraction of duration (0.0-1.0)"<br />"Absolute time (seconds)" |
| `keyframes` | Optional earlier keyframes to chain with this one. | LUMA\_RAY32\_KEYFRAME | No | - |

### Fraction of duration (0.0-1.0) Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `fraction` | Where in the output video this image applies (0.0 = start, 1.0 = end). Default: 0.0. | FLOAT | Yes | 0.0 to 1.0 (step: 0.01) |

### Absolute time (seconds) Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `seconds` | Time in seconds from the start of the output video where this image applies. Default: 0.0. | FLOAT | Yes | 0.0 to 10.0 (step: 0.1) |

The `position` parameter determines which value is used to place the image on the timeline. Only the sub-parameter belonging to the selected option is shown and used: `fraction` for "Fraction of duration (0.0-1.0)" and `seconds` for "Absolute time (seconds)".

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `keyframes` | A keyframe chain that includes the new keyframe combined with any optional earlier keyframes. | LUMA\_RAY32\_KEYFRAME |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaRay32KeyframeNode/en.md)

***

**Source fingerprint (SHA-256):** `b49d879888e6e83d6937068e799ea583ed5c90284e829ac496821eea330fe9c7`


# LumaRay32KeyframesToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaRay32KeyframesToVideoNode

This node generates a video that interpolates through a sequence of guide images, each anchored to a specific position on the timeline, using Luma Ray 3.2.

This node generates a video that interpolates through a sequence of guide images, each anchored to a specific position on the timeline, using Luma Ray 3.2. Build the keyframe sequence using Luma Ray 3.2 Keyframe nodes, connecting at least 2 keyframes to define the animation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for the video generation (default: empty string). | STRING | Yes | 1 to 6000 characters |
| `resolution` | The output resolution of the generated video (default: "720p"). | STRING | Yes | `"360p"`<br />`"540p"`<br />`"720p"`<br />`"1080p"` |
| `duration` | The duration of the generated video (default: "5s"). | STRING | Yes | `"5s"`<br />`"10s"` |
| `seed` | Seed for random number generation to control reproducibility. | INT | Yes | 0 to 4294967295 |
| `keyframes` | Keyframe sequence from Luma Ray 3.2 Keyframe nodes (at least 2). | LUMA\_RAY32\_KEYFRAME | Yes | 2 to 64 keyframes |

**Note:** The keyframe sequence must contain at least 2 keyframes and at most 64 keyframes. Each keyframe must have a distinct position on the timeline. Keyframe positions are resolved to output frame indices based on the selected duration (120 frames for 5s, 240 frames for 10s). Keyframe positions in seconds mode must not exceed the total video duration.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video output. | VIDEO |
| `generation_id` | The unique identifier for the generation request. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaRay32KeyframesToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `28099e5990942860a20e23cfd5c71a36b23a6264b44097ca617f8bdd06e7857a`


# LumaRay32TextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaRay32TextToVideoNode

This node generates a video from a text prompt using Luma's Ray 3.2 model.

This node generates a video from a text prompt using Luma's Ray 3.2 model. It sends your prompt and video settings to the Luma API and returns the generated video along with a generation ID.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for the video generation. | STRING | Yes | 1 to 6000 characters |
| `aspect_ratio` | The aspect ratio of the generated video. | STRING | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"`<br />`"21:9"` |
| `resolution` | The output resolution of the video (default: "720p"). | STRING | Yes | `"360p"`<br />`"540p"`<br />`"720p"`<br />`"1080p"` |
| `duration` | The duration of the generated video. | STRING | Yes | `"5s"`<br />`"10s"` |
| `loop` | Make the video loop seamlessly. Only available with 5s duration. | BOOLEAN | No | True/False (default: False) |
| `seed` | Seed for reproducible generation. | INT | No | 0 to 2147483647 |

**Note:** The `loop` parameter can only be enabled when `duration` is set to "5s". If you set `duration` to "10s" and enable `loop`, the node returns an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `VIDEO` | The generated video file. | VIDEO |
| `generation_id` | The unique identifier for the video generation request. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaRay32TextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `04358a872530e5a2622bf0f148a694f2c707ce8535586d8f860bdf9911e1fa6a`


# LumaRay32VideoEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaRay32VideoEditNode

Documentation for LumaRay32VideoEditNode node.

## Overview

This node re-renders an existing video under a new prompt using Luma Ray 3.2, allowing you to restyle, relight, add, or remove elements while keeping the original motion. The source video can be up to 18 seconds, and the edited video retains the source's original length.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Source video to edit. Up to 18 seconds. | VIDEO | Yes | - |
| `prompt` | Describes the desired edit. | STRING | Yes | - |
| `resolution` | The output resolution for the edited video. (default: "720p") | COMBO | Yes | `"360p"`<br />`"540p"`<br />`"720p"`<br />`"1080p"` |
| `strength` | How strongly to preserve vs. reimagine the source. "auto" lets Ray 3.2 choose; adhere\_\* preserves the most, flex\_\* is balanced, reimagine\_\* changes the most. (default: "auto") | COMBO | Yes | `"auto"`<br />`"adhere_1"`<br />`"adhere_2"`<br />`"adhere_3"`<br />`"flex_1"`<br />`"flex_2"`<br />`"flex_3"`<br />`"reimagine_1"`<br />`"reimagine_2"`<br />`"reimagine_3"` |
| `seed` | Seed for reproducibility. | INT | Yes | - |

**Note:** The `prompt` must be between 1 and 6000 characters. The source video must not exceed 18 seconds in duration.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `VIDEO` | The edited video output. | VIDEO |
| `generation_id` | The unique identifier for the generation request. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaRay32VideoEditNode/en.md)

***

**Source fingerprint (SHA-256):** `936d9d7da3fdee9b0b468781fd470751db01f772f3c5c20582da7fb1ff85e6e6`


# LumaRay32VideoReframeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaRay32VideoReframeNode

This node changes the aspect ratio of an existing video using Luma Ray 3.2, which fills the newly exposed canvas areas with generated content.

This node changes the aspect ratio of an existing video using Luma Ray 3.2, which fills the newly exposed canvas areas with generated content. The source video can be up to 30 seconds long, and billing is per second of output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Source video to reframe. Up to 30 seconds. | VIDEO | Yes | - |
| `prompt` | Describes how the newly exposed canvas areas should be filled. | STRING | Yes | Min length: 1 character<br />Max length: 6000 characters |
| `aspect_ratio` | The target aspect ratio for the reframed video (default: "16:9"). | STRING | Yes | "16:9"<br />"9:16"<br />"1:1"<br />"4:3"<br />"3:4"<br />"21:9" |
| `resolution` | The output resolution of the reframed video (default: "720p"). | STRING | Yes | "360p"<br />"540p"<br />"720p"<br />"1080p" |
| `seed` | Seed for reproducible generation. | INT | Yes | - |

**Note:** The `1080p` resolution is not available for vertical aspect ratios (`9:16` and `3:4`) when reframing.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The reframed video with the new aspect ratio and filled canvas areas. | VIDEO |
| `generation_id` | The unique identifier for the generation request. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaRay32VideoReframeNode/en.md)

***

**Source fingerprint (SHA-256):** `d35ff5b63a850e4e44a40857188918ab5cde00b9159e3720a189a81807cfa7cb`


# LumaVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaVideoNode

Generates videos synchronously based on a text prompt and output settings.

Generates videos synchronously based on a text prompt and output settings. This node creates video content using text descriptions and various generation parameters, producing the final video output once the generation process is complete.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the video generation (default: empty string). Must be at least 3 characters long. | STRING | Yes | - |
| `model` | The video generation model to use. | COMBO | Yes | `"ray_1_6"`<br />`"ray_2"` |
| `aspect_ratio` | The aspect ratio for the generated video (default: "16:9"). | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"`<br />`"21:9"`<br />`"9:21"` |
| `resolution` | The output resolution for the video (default: "540p"). This parameter is ignored when using the `ray_1_6` model. | COMBO | Yes | `"540p"`<br />`"720p"`<br />`"1080p"` |
| `duration` | The duration of the generated video. This parameter is ignored when using the `ray_1_6` model. | COMBO | Yes | `"5s"`<br />`"9s"` |
| `loop` | Whether the video should loop (default: False). | BOOLEAN | Yes | - |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). | INT | Yes | 0 to 18446744073709551615 |
| `luma_concepts` | Optional Camera Concepts to dictate camera motion via the Luma Concepts node. | CUSTOM | No | - |

**Note:** When using the `ray_1_6` model, the `duration` and `resolution` parameters are automatically ignored and do not affect the generation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `3ce9db0780dbe7a752a6b1c35a02b9511f532e81a28d5d83b2bf3be9e35e2e6b`


# MinimaxHailuo03ContextIRNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxHailuo03ContextIRNode

Documentation for MinimaxHailuo03ContextIRNode node.

## Overview

This node uses MiniMax H3 Context IR to analyze your text description and any attached media, then produces a stronger, structured video prompt. The returned prompt is designed to be connected to the prompt input of a MiniMax H3 video node; if you attach media there, attach the same media in the same order, because the enhanced prompt refers to media by position.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for prompt enhancement. | DYNAMIC\_COMBO | Yes | `"MiniMax H3"` |
| `first_frame` | First frame of the video you intend to generate. Cannot be combined with reference media. | IMAGE | No | Single image |
| `last_frame` | Last frame of the video you intend to generate. Cannot be combined with reference media. | IMAGE | No | Single image |

### MiniMax H3 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Description of the video you intend to generate. Cannot be empty. (default: `""`) | STRING | Yes | Any text (cannot be empty) |
| `duration` | Duration of the video you intend to generate, in seconds (4-15). (default: 5) | INT | Yes | 4 to 15 |
| `ratio` | Aspect ratio of the video you intend to generate. `"adaptive"` requires at least one image, video, or audio input. (default: `"adaptive"`) | COMBO | Yes | `"adaptive"`<br />`"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"` |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Subject or style reference images, referred to in the prompt as "Image 1".."Image 9" in connection order. Up to 9 images. Growable slot: connect `image_1`...`image_9`. | IMAGE | No | 0 to 9 images |
| `reference_videos` | Motion or scene reference videos, referred to in the prompt as "Video 1".."Video 3" in connection order. Up to 3 videos, 2-15 seconds each, 15 seconds in total. Growable slot: connect `video_1`...`video_3`. | VIDEO | No | 0 to 3 videos |
| `reference_audios` | Audio references, referred to in the prompt as "Audio 1".."Audio 3" in connection order. Up to 3 clips, 2-15 seconds each, 15 seconds in total. Cannot be used without a reference image or video. Growable slot: connect `audio_1`...`audio_3`. | AUDIO | No | 0 to 3 clips |

### Parameter constraints

* The `prompt`, `duration`, `ratio`, `reference_images`, `reference_videos`, and `reference_audios` inputs are part of the `model` option group and appear when "MiniMax H3" is selected.
* `first_frame` and `last_frame` cannot be combined with any reference media.
* `reference_audios` cannot be used unless at least one `reference_image` or `reference_video` is also connected.
* When no frames and no reference media are connected, `ratio` cannot be set to `"adaptive"`.
* Reference videos must be approximately 2-15 seconds each, with a total duration of no more than 15 seconds. Their frame rate must be between 23.9 and 60.5 FPS.
* Reference audios must be approximately 2-15 seconds each, with a total duration of no more than 15 seconds.
* `first_frame`, `last_frame`, and every reference image must be at least 256x256 pixels and have an aspect ratio between 0.4 and 2.5.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `STRING` | The enhanced, structured video prompt generated by MiniMax H3 Context IR. It can be connected to the prompt input of a MiniMax H3 video generation node. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxHailuo03ContextIRNode/en.md)

***

**Source fingerprint (SHA-256):** `73015517f9c0f55f0aceeef935508a372e0d95668e4733d1c8100b53e4afa7e2`


# MinimaxHailuo03FirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxHailuo03FirstLastFrameNode

This node generates a video from a first frame image and, optionally, a last frame image using the MiniMax H3 models.

This node generates a video from a first frame image and, optionally, a last frame image using the MiniMax H3 models. The `model` selector changes which generation settings and constraints apply, and the aspect ratio of the generated video follows the supplied images.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for video generation. Selecting a model reveals its model-specific settings below. | DYNAMIC\_COMBO | Yes | "MiniMax H3"<br />"MiniMax H3 Max"<br />"MiniMax H3 Max Turbo" |
| `first_frame` | First frame image for the video. The generated video follows the aspect ratio of this image. | IMAGE | Yes | - |
| `last_frame` | Optional last frame image for the video. When provided, the video is generated from the first frame toward this last frame. | IMAGE | No | - |
| `seed` | Random seed. The same request with the same seed gives similar, but not guaranteed identical, results. Includes a "control after generate" option. Default: 42. | INT | Yes | 0 to 4294967295 |
| `watermark` | Whether to add an AIGC watermark to the video. This is an advanced parameter. Only supported by the `MiniMax H3` model. Default: False. | BOOLEAN | Yes | True<br />False |

### MiniMax H3 Inputs

These settings are shown when `MiniMax H3` is selected in the `model` selector.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Must contain at least one non-whitespace character. | STRING | Yes | Multiline text |
| `resolution` | Resolution of the output video. | COMBO | Yes | "768P"<br />"2K" |
| `duration` | Duration of the output video in seconds. Default: 5. | INT | Yes | 4 to 15 |

### MiniMax H3 Max and MiniMax H3 Max Turbo Inputs

These settings are shared by both `MiniMax H3 Max` and `MiniMax H3 Max Turbo`. Selecting either model reveals the same settings.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Must not be empty or whitespace-only, and is limited to 50,000 characters. | STRING | Yes | Multiline text |
| `resolution` | Resolution of the output video. Default: 768P. | COMBO | Yes | "480P"<br />"768P" |
| `duration` | Duration of the output video in seconds. Default: 5. | INT | Yes | 5 to 15 |
| `prompt_expansion_mode` | How much effort is spent rewriting the prompt before generation. Default: balanced. | COMBO | Yes | "balanced"<br />"quality" |

**Notes on constraints:**

* The prompt must contain text: empty or whitespace-only prompts are rejected.
* Any supplied frame image must be at least 256 pixels wide and 256 pixels tall, with a width-to-height aspect ratio between 0.4 and 2.5 (approximately 2:5 to 5:2). This requirement applies to `first_frame` and, when provided, `last_frame`.
* When `last_frame` is omitted, the video is generated from the first frame only.
* The output video follows the aspect ratio of the supplied images.
* `watermark` is only supported by `MiniMax H3`. Enabling it with `MiniMax H3 Max` or `MiniMax H3 Max Turbo` raises an error.
* Duration ranges from 4 to 15 seconds for `MiniMax H3` and from 5 to 15 seconds for `MiniMax H3 Max` and `MiniMax H3 Max Turbo`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video created from the first frame and optional last frame using the selected MiniMax H3 model. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxHailuo03FirstLastFrameNode/en.md)

***

**Source fingerprint (SHA-256):** `6eaf895e6e9e46b9a1efb1dd13e951040e12e865cc73d7741ab7546f5f8f9ec0`


# MinimaxHailuo03ReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxHailuo03ReferenceNode

This node generates a video using the MiniMax H3 models, conditioned on reference images, videos, and audio.

This node generates a video using the MiniMax H3 models, conditioned on reference images, videos, and audio. References are referred to in the prompt by their connection order: "Image 1", "Image 2", "Video 1", "Audio 1", and so on. Two models are available: "MiniMax H3" and "MiniMax H3 Max".

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for video generation (default: "MiniMax H3"). Selecting "MiniMax H3" provides the MiniMax H3 generation and reference inputs below. Selecting "MiniMax H3 Max" provides the MiniMax H3 Max generation and reference inputs below. | DYNAMIC\_COMBO | Yes | "MiniMax H3"<br />"MiniMax H3 Max" |
| `seed` | Random seed. The same request with the same seed gives similar, but not guaranteed identical, results (default: 42). | INT | Yes | 0 to 4294967295 |
| `watermark` | Whether to add an AIGC watermark to the video (default: false). Only supported by the MiniMax H3 model. | BOOLEAN | No | true<br />false |

### MiniMax H3 Inputs

These inputs are available when "MiniMax H3" is selected as the model.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Reference media can be referred to by their order, for example "Image 1", "Image 2", "Video 1", or "Audio 1". | STRING | Yes | Minimum 1 character |
| `resolution` | Resolution of the output video (default: "768P"). | COMBO | Yes | "768P"<br />"2K" |
| `ratio` | Aspect ratio of the output video (default: "adaptive"). | COMBO | Yes | "adaptive"<br />"16:9"<br />"4:3"<br />"1:1"<br />"3:4"<br />"9:16"<br />"21:9" |
| `duration` | Duration of the output video in seconds (default: 5). | INT | Yes | 4 to 15 |

### MiniMax H3 Max Inputs

These inputs are available when "MiniMax H3 Max" is selected as the model.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Reference media can be referred to by their order, for example "Image 1", "Image 2", "Video 1", or "Audio 1". | STRING | Yes | 1 to 50000 characters |
| `resolution` | Resolution of the output video (default: "768P"). | COMBO | Yes | "480P"<br />"768P" |
| `ratio` | Aspect ratio of the output video (default: "adaptive"). | COMBO | Yes | "adaptive"<br />"16:9"<br />"4:3"<br />"1:1"<br />"3:4"<br />"9:16"<br />"21:9" |
| `duration` | Duration of the output video in seconds (default: 5). | INT | Yes | 5 to 15 |
| `prompt_expansion_mode` | How much effort is spent rewriting the prompt before generation (default: "balanced"). | COMBO | Yes | "balanced"<br />"quality" |
| `reference_detail` | Detail level at which reference images are sent. "high" sends them at the largest size the model uses (up to a 2048 pixel short side); "standard" downsizes them to at most 2048x1024 to reduce the reference cost (default: "standard"). | COMBO | Yes | "high"<br />"standard" |

### Reference Inputs

These reference inputs are shared by both models. Each is a growable slot.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect up to 9 items (`image_1`...`image_9`). Subject or style reference images, referred to in the prompt as "Image 1".."Image 9" in connection order. Up to 9 images. | IMAGE | No | 0 to 9 images |
| `reference_videos` | Growable slot: connect up to 3 items (`video_1`...`video_3`). Motion or scene reference videos, referred to in the prompt as "Video 1".."Video 3" in connection order. Up to 3 videos, 2-15 seconds each, 15 seconds in total. | VIDEO | No | 0 to 3 videos |
| `reference_audios` | Growable slot: connect up to 3 items (`audio_1`...`audio_3`). Audio references, referred to in the prompt as "Audio 1".."Audio 3" in connection order. Up to 3 clips, 2-15 seconds each, 15 seconds in total. Cannot be used without a reference image or video. | AUDIO | No | 0 to 3 clips |

### Parameter Constraints

* At least one reference image or one reference video is required. Reference audio alone is not accepted.
* Each reference image must have an aspect ratio between approximately 0.4 and 2.5 (2:5 to 5:2) and a minimum width and height of 256 pixels.
* Each reference video must be between 2 and 15 seconds long with a frame rate between 23.976 and 60 FPS. The total duration of all reference videos cannot exceed 15 seconds.
* Each reference audio clip must be between 2 and 15 seconds long. The total duration of all reference audio clips cannot exceed 15 seconds.
* When "MiniMax H3 Max" is selected, the `watermark` setting must be disabled.
* When "MiniMax H3 Max" is selected, the total number of reference files (images, videos, and audio combined) cannot exceed 12.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxHailuo03ReferenceNode/en.md)

***

**Source fingerprint (SHA-256):** `b77eedb1f7757e60518c04484f1cc24c27cf6886b3ae31c15207ea49fd436a73`


# MinimaxHailuo03RegenerateNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxHailuo03RegenerateNode

This node re-renders a MiniMax H3 768P video output at 2K resolution.

This node re-renders a MiniMax H3 768P video output at 2K resolution. It uploads the unmodified 768P video and the exact prompt used to generate it, starts a MiniMax H3 regeneration job, and returns the re-rendered 2K video. If the original generation used first or last frames or reference media, attach the same inputs.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to use for video regeneration. Selecting "MiniMax H3" reveals the prompt, resolution, and reference media settings. | DYNAMIC\_COMBO | Yes | "MiniMax H3" |
| `video` | The MiniMax H3 768P output video to re-render. Connect the unmodified output of a MiniMax H3 video node (24 FPS, 4-15 seconds). 2K outputs cannot be used. | VIDEO | Yes | 24 FPS, 4-15 seconds |
| `first_frame` | First frame image from the original generation, if one was used. | IMAGE | No | Image |
| `last_frame` | Last frame image from the original generation, if one was used. | IMAGE | No | Image |
| `watermark` | Whether to add an AIGC watermark to the video. Default is false. | BOOLEAN | Yes | false / true |

### MiniMax H3 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | The exact prompt used to generate the source video. Must not be empty. | STRING | Yes | Text (multiline) |
| `resolution` | Resolution to re-render the source video at. | COMBO | Yes | "2K" |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect `image_1` through `image_9` (up to 9 images). Reference images from the original generation, in the same order. | IMAGE | No | 0-9 images |
| `reference_videos` | Growable slot: connect `video_1` through `video_3` (up to 3 videos). Reference videos from the original generation, in the same order. | VIDEO | No | 0-3 videos |
| `reference_audios` | Growable slot: connect `audio_1` through `audio_3` (up to 3 clips). Audio references from the original generation, in the same order. Cannot be used without a reference image or video. | AUDIO | No | 0-3 clips |

### Constraints

* The `prompt` must not be empty.
* The source `video` must be an unmodified MiniMax H3 768P output: 24 FPS, width and height divisible by 32, at most 1,032,192 total pixels, and 107 to 362 frames in steps of 17 (4 to 15 seconds at 24 FPS). 2K outputs cannot be used as the source.
* `first_frame` and `last_frame` are mutually exclusive with reference media (`reference_images`, `reference_videos`, `reference_audios`). Use frames for an image-to-video prompt, or reference media for a reference-to-video prompt.
* `reference_audios` requires at least one `reference_images` or `reference_videos` input.
* `first_frame`, `last_frame`, and each `reference_image` must have an aspect ratio between 0.4 and 2.5 and be at least 256x256 pixels.
* `reference_videos`: each video must be 23.976 to 60 FPS and 2-15 seconds long; total duration cannot exceed 15 seconds.
* `reference_audios`: each clip must be 2-15 seconds long; total duration cannot exceed 15 seconds.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The re-rendered MiniMax H3 video at 2K resolution. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxHailuo03RegenerateNode/en.md)

***

**Source fingerprint (SHA-256):** `4b5aa6dee12364cf6f44e7ee78b984c3568529b97051637a6ac62db9761d3a77`


# MinimaxHailuo03TextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxHailuo03TextToVideoNode

This node generates a video from a text prompt using the MiniMax H3 family of models: MiniMax H3, MiniMax H3 Max, and MiniMax H3 Max Turbo.

This node generates a video from a text prompt using the MiniMax H3 family of models: MiniMax H3, MiniMax H3 Max, and MiniMax H3 Max Turbo. You select the model, enter a text prompt, and adjust settings such as resolution, aspect ratio, and duration. The node sends the request to the MiniMax API, waits for the generation task to complete, and returns the resulting video.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for video generation (default: "MiniMax H3"). Selecting a model also shows the model-specific settings described in the sections below. | DYNAMIC\_COMBO | Yes | "MiniMax H3"<br />"MiniMax H3 Max"<br />"MiniMax H3 Max Turbo" |
| `seed` | Random seed. The same request with the same seed gives similar, but not guaranteed identical, results (default: 42). | INT | Yes | 0 to 4294967295 |
| `watermark` | Whether to add an AIGC watermark to the video (default: false). When enabled, only the "MiniMax H3" model is supported. | BOOLEAN | No | true<br />false |

### MiniMax H3 Inputs

These settings appear when the "MiniMax H3" model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Must contain at least one non-whitespace character. | STRING | Yes | Any text |
| `resolution` | Resolution of the output video. | COMBO | Yes | "768P"<br />"2K" |
| `ratio` | Aspect ratio of the output video (default: "16:9"). | COMBO | Yes | "16:9"<br />"4:3"<br />"1:1"<br />"3:4"<br />"9:16"<br />"21:9" |
| `duration` | Duration of the output video in seconds (4-15) (default: 5). | INT | Yes | 4 to 15 |

### MiniMax H3 Max and MiniMax H3 Max Turbo Inputs

These settings are shared by the "MiniMax H3 Max" and "MiniMax H3 Max Turbo" models and appear when either model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for video generation. Must contain at least one non-whitespace character and can be up to 50,000 characters long. | STRING | Yes | Up to 50000 characters |
| `resolution` | Resolution of the output video (default: "768P"). | COMBO | Yes | "480P"<br />"768P" |
| `ratio` | Aspect ratio of the output video (default: "16:9"). | COMBO | Yes | "16:9"<br />"4:3"<br />"1:1"<br />"3:4"<br />"9:16"<br />"21:9" |
| `duration` | Duration of the output video in seconds (5-15) (default: 5). | INT | Yes | 5 to 15 |
| `prompt_expansion_mode` | How much effort is spent rewriting the prompt before generation (default: "balanced"). | COMBO | Yes | "balanced"<br />"quality" |

### Notes

* For all models, the prompt must contain at least one non-whitespace character.
* The `watermark` setting is only supported by "MiniMax H3". Enabling it with "MiniMax H3 Max" or "MiniMax H3 Max Turbo" causes an error.
* The "MiniMax H3 Max" and "MiniMax H3 Max Turbo" models limit the prompt to 50,000 characters.
* Resolution and duration limits depend on the selected model: "MiniMax H3" supports "768P" and "2K" resolution and 4-15 second videos, while "MiniMax H3 Max" and "MiniMax H3 Max Turbo" support "480P" and "768P" resolution and 5-15 second videos.
* The estimated price shown for this node is calculated from the selected model, resolution, and duration.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `VIDEO` | The generated video created from the provided text prompt. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxHailuo03TextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `4d3de190d18de4370aff878279755e881841d2ada28320a7c1d7c52061071c05`


# MinimaxHailuoVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxHailuoVideoNode

Generates videos from text prompts using the MiniMax Hailuo-02 model.

Generates videos from text prompts using the MiniMax Hailuo-02 model. You can optionally provide a starting image to use as the first frame, which creates a video that continues from that image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt_text` | Text prompt to guide the video generation (default: empty). | STRING | Yes | - |
| `seed` | The random seed used for creating the noise (default: 0). | INT | No | 0 to 18446744073709551615 |
| `first_frame_image` | Optional image to use as the first frame to generate a video. | IMAGE | No | - |
| `prompt_optimizer` | Optimize prompt to improve generation quality when needed (default: True). | BOOLEAN | No | True<br />False |
| `duration` | The length of the output video in seconds (default: 6). | COMBO | No | 6<br />10 |
| `resolution` | The dimensions of the video display. 1080p is 1920x1080, 768p is 1366x768 (default: "768P"). | COMBO | No | "768P"<br />"1080P" |

**Note:** When `resolution` is set to "1080P", `duration` is limited to 6 seconds. When `first_frame_image` is not provided, `prompt_text` must not be empty.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxHailuoVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `f371aae15cfbe7353236bc679c8a6d558703c5037e49ab7ddb9bdf5c50ef0995`


# MinimaxImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxImageToVideoNode

Generates videos synchronously based on an image and prompt, and optional parameters using MiniMax's API.

Generates videos synchronously based on an image and prompt, and optional parameters using MiniMax's API. This node takes an input image and text description to create a video sequence, with various model options and configuration settings available.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Image to use as first frame of video generation | IMAGE | Yes | - |
| `prompt_text` | Text prompt to guide the video generation (default: empty string) | STRING | Yes | - |
| `model` | Model to use for video generation (default: "I2V-01") | COMBO | Yes | "I2V-01-Director"<br />"I2V-01"<br />"I2V-01-live" |
| `seed` | The random seed used for creating the noise (default: 0) | INT | No | 0 to 18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video output | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `90eef1d58fa0ae4897ab19d702ecad707948eb79181ac4927dba650056e954c8`


# MinimaxSubjectToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxSubjectToVideoNode

Generates a video synchronously based on a subject image and a text prompt using MiniMax's API.

Generates a video synchronously based on a subject image and a text prompt using MiniMax's API. This node takes an image of a subject and a description to create a video that animates or features that subject according to the prompt.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `subject` | Image of subject to reference for video generation | IMAGE | Yes | - |
| `prompt_text` | Text prompt to guide the video generation (default: empty string) | STRING | Yes | - |
| `model` | Model to use for video generation (default: "S2V-01") | COMBO | No | `"S2V-01"` |
| `seed` | The random seed used for creating the noise (default: 0) | INT | No | 0 to 18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video based on the input subject image and prompt | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxSubjectToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `e7d496d8e24a776bbea4afe102858e7d31c4f2e273889703eb02cc61e8389055`


# MinimaxTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxTextToVideoNode

Generates videos synchronously based on a text prompt and optional parameters using MiniMax's API.

Generates videos synchronously based on a text prompt and optional parameters using MiniMax's API. This node creates video content from text descriptions by connecting to MiniMax's text-to-video service.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt_text` | Text prompt to guide the video generation | STRING | Yes | - |
| `model` | Model to use for video generation (default: "T2V-01") | COMBO | No | "T2V-01"<br />"T2V-01-Director" |
| `seed` | The random seed used for creating the noise (default: 0) | INT | No | 0 to 18446744073709551615 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video based on the input prompt | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxTextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `1d389bdcc48f903e04dad043a8609250f34466b9084b1319c411e155a8040422`


# OpenAIChatConfig - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIChatConfig

The OpenAIChatConfig node defines advanced options that control how the OpenAI Chat Node generates responses.

The OpenAIChatConfig node defines advanced options that control how the OpenAI Chat Node generates responses. It lets you set the truncation strategy, limit the number of output tokens, provide custom instructions, and choose how much reasoning effort the model should apply before answering.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `truncation` | The truncation strategy to use for the model response. auto: If the context of this response and previous ones exceeds the model's context window size, the model will truncate the response to fit the context window by dropping input items in the middle of the conversation. disabled: If a model response will exceed the context window size for a model, the request will fail with a 400 error (default: "auto") | COMBO | Yes | "auto"<br />"disabled" |
| `max_output_tokens` | An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens (default: 4096) | INT | No | 16 to 16384 |
| `instructions` | Instructions for the model on how to generate the response (multiline input supported) | STRING | No | - |
| `reasoning_effort` | How much the model reasons before answering. "default" leaves the choice to the model. Supported levels differ per model: GPT-6 Astra low-max, GPT-6 Sol/Luna and GPT-5.6 none-max (no minimal), GPT-5.5 none-xhigh, GPT-5.5 Pro medium-xhigh, GPT-5 minimal-high, o-series low-high; GPT-4.1 has no reasoning. Unsupported levels are rejected before the request is sent. (default: "default") | COMBO | No | "default"<br />"none"<br />"minimal"<br />"low"<br />"medium"<br />"high"<br />"xhigh"<br />"max" |

Note: While `top_p` and `temperature` are listed as properties in the API specification, they are not supported for all models and are therefore not exposed as inputs.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `OPENAI_CHAT_CONFIG` | Configuration object containing the specified advanced settings, for use with OpenAI Chat Nodes | OPENAI\_CHAT\_CONFIG |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIChatConfig/en.md)

***

**Source fingerprint (SHA-256):** `4237ad464230c464223c184eab38c7d707a29ba5f47da04c2ec2034cd4347207`


# OpenAIChatNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIChatNode

This node generates text responses from an OpenAI model.

This node generates text responses from an OpenAI model. It sends your text prompt, and optionally images or files, to an OpenAI model and returns the generated text response.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text inputs to the model, used to generate a response (default: empty string). | STRING | Yes | - |
| `persist_context` | This parameter is deprecated and has no effect (default: False). | BOOLEAN | Yes | - |
| `model` | The model used to generate the response (default: `gpt-5`) | COMBO | Yes | `gpt-6-astra`<br />`gpt-6-sol`<br />`gpt-6-luna`<br />`gpt-5.6-sol`<br />`gpt-5.6-terra`<br />`gpt-5.6-luna`<br />`gpt-5.5-pro`<br />`gpt-5.5`<br />`gpt-5`<br />`gpt-5-mini`<br />`gpt-5-nano`<br />`gpt-4.1`<br />`gpt-4.1-mini`<br />`gpt-4.1-nano`<br />`o4-mini`<br />`o3`<br />`o1-pro`<br />`o1` |
| `images` | Optional image(s) to use as context for the model. To include multiple images, you can use the Batch Images node. | IMAGE | No | - |
| `files` | Optional file(s) to use as context for the model. Accepts inputs from the OpenAI Chat Input Files node. | OPENAI\_INPUT\_FILES | No | - |
| `advanced_options` | Optional configuration for the model. Accepts inputs from the OpenAI Chat Advanced Options node. | OPENAI\_CHAT\_CONFIG | No | - |

Note: When an `advanced_options` configuration that sets a reasoning effort is connected, the selected `model` must support that effort value. For example, the gpt-4.1 family of models does not support any reasoning effort, `gpt-6-sol` and `gpt-6-luna` support none, low, medium, high, xhigh and max, `gpt-5.5` supports none, low, medium, high and xhigh, and `gpt-5.5-pro` supports medium, high and xhigh. If the reasoning effort is not supported by the selected model, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output_text` | The text response generated by the OpenAI model. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIChatNode/en.md)

***

**Source fingerprint (SHA-256):** `46b4558f1368191e2b4eb68f79e098f289c9eb80e1e05f7a516123c098295f2b`


# OpenAIInputFiles - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIInputFiles

Loads and formats input files for the OpenAI API.

Loads and formats input files for the OpenAI API. This node prepares text (.txt) and PDF (.pdf) files to include as context inputs for the OpenAI Chat Node. The files will be read by the OpenAI model when generating a response. Multiple OpenAI Input Files nodes can be chained together to include several files in a single message.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `file` | Input files to include as context for the model. Only accepts text (.txt) and PDF (.pdf) files for now. Files must be smaller than 32MB. | COMBO | Yes | Multiple options available (all .txt and .pdf files in the input directory under 32MB) |
| `OPENAI_INPUT_FILES` | An optional additional file(s) to batch together with the file loaded from this node. Allows chaining of input files so that a single message can include multiple input files. | OPENAI\_INPUT\_FILES | No | N/A |

**File Constraints:**

* Only .txt and .pdf files are supported
* Maximum file size: 32MB
* Files are loaded from the ComfyUI input directory

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `OPENAI_INPUT_FILES` | Formatted input files ready to be used as context for OpenAI API calls. | OPENAI\_INPUT\_FILES |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIInputFiles/en.md)

***

**Source fingerprint (SHA-256):** `6554e685184ced830ee27aa96efefc8bb9616bd0504685bdb643c715ebc6dd98`


# OpenRouterLLMNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenRouterLLMNode

The OpenRouter LLM node sends a text prompt to a curated set of popular language models available through the OpenRouter service and returns the generated text response.

The OpenRouter LLM node sends a text prompt to a curated set of popular language models available through the OpenRouter service and returns the generated text response. It supports models from Anthropic (Claude), OpenAI (GPT), Google (Gemini), xAI (Grok), DeepSeek, Qwen, Mistral, Z.AI (GLM), Moonshot (Kimi), and Perplexity Sonar, and can optionally include images or videos as reference inputs in the request.

## Inputs

When a model is selected in the `model` selector, the node shows model-specific widgets on top of the common inputs — reasoning effort, web search size, and/or reference media slots — depending on the capabilities of the chosen model.

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text input to the model. | STRING | Yes | N/A |
| `model` | The OpenRouter model used to generate the response. | DYNAMIC\_COMBO | Yes | Multiple options available (see model sections below) |
| `seed` | Seed for sampling. Set to 0 to omit. Most models treat this as a hint only. (default: 0) | INT | Yes | 0 to 2147483647 |
| `system_prompt` | Foundational instructions that dictate the model's behavior. (default: "") | STRING | No | N/A |

### Anthropic Claude Models Inputs

Shared by `anthropic/claude-opus-5`, `anthropic/claude-opus-4.8`, `anthropic/claude-opus-4.7`, `anthropic/claude-fable-5`, `anthropic/claude-sonnet-5`, and `anthropic/claude-haiku-4.5`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

These models support up to 20 reference images (see Reference Inputs).

### OpenAI GPT Models Inputs

Shared by `openai/gpt-5.6-sol-pro`, `openai/gpt-5.6-sol`, `openai/gpt-5.6-terra-pro`, `openai/gpt-5.6-terra`, `openai/gpt-5.6-luna-pro`, `openai/gpt-5.6-luna`, `openai/gpt-5.5-pro`, and `openai/gpt-5.5`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

These models support up to 20 reference images (see Reference Inputs).

### Google Gemini 3.5 Flash Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

This model supports up to 20 reference images and up to 4 reference videos (see Reference Inputs).

### xAI Grok Models Inputs

Shared by `x-ai/grok-4.5`, `x-ai/grok-4.20`, and `x-ai/grok-4.3`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

These models support up to 20 reference images (see Reference Inputs).

### DeepSeek Models Inputs

Shared by `deepseek/deepseek-v4-pro`, `deepseek/deepseek-v4-flash`, and `deepseek/deepseek-v3.2`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

Text-only models — no reference images or videos.

### Qwen 3.6 Max Preview Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

Text-only model — no reference images or videos.

### Qwen 3.6 Plus and Qwen 3.6 Flash Inputs

Shared by `qwen/qwen3.6-plus` and `qwen/qwen3.6-flash`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

These models support up to 10 reference images and up to 4 reference videos (see Reference Inputs).

### Mistral Large 2512 Inputs

No profile-specific inputs (standard profile). This model supports up to 8 reference images (see Reference Inputs).

### Mistral Medium 3.5 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

This model supports up to 8 reference images (see Reference Inputs).

### Z.AI GLM Models Inputs

Shared by `z-ai/glm-4.6` and `z-ai/glm-5`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

Text-only models — no reference images or videos.

### Moonshot Kimi K3 and K2.6 Inputs

Shared by `moonshotai/kimi-k3` and `moonshotai/kimi-k2.6`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

These models support up to 10 reference images (see Reference Inputs).

### Moonshot Kimi K2 Thinking Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

Text-only model — no reference images or videos.

### Perplexity Sonar Pro Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `search_context_size` | How much web search context to retrieve. Larger = more grounded but slower/pricier. (default: "medium") | COMBO | No | "low"<br />"medium"<br />"high" |

Text-only model — no reference images or videos.

### Perplexity Sonar Reasoning Pro and Sonar Deep Research Inputs

Shared by `perplexity/sonar-reasoning-pro` and `perplexity/sonar-deep-research`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `search_context_size` | How much web search context to retrieve. Larger = more grounded but slower/pricier. (default: "medium") | COMBO | No | "low"<br />"medium"<br />"high" |
| `reasoning_effort` | Reasoning effort. 'off' disables reasoning entirely. (default: "off") | COMBO | No | "off"<br />"low"<br />"medium"<br />"high" |

Text-only models — no reference images or videos.

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | Optional reference image(s), sent as URLs. Growable slot: connect 1..N image inputs (`image_1`, `image_2`, ...); the count limit depends on the selected model (see model sections). | IMAGE | No | 0 to 20 (model-dependent: 8, 10, or 20) |
| `videos` | Optional reference video(s), sent as URLs. Growable slot: connect 1..N video inputs (`video_1`, `video_2`, ...); the count limit depends on the selected model (see model sections). | VIDEO | No | 0 to 4 (model-dependent) |

**Notes:**

* **Available models:** The available model options are dynamically built and include models with different capabilities. The full list of 34 models is:
  * Anthropic: `anthropic/claude-opus-5`, `anthropic/claude-opus-4.8`, `anthropic/claude-opus-4.7`, `anthropic/claude-fable-5`, `anthropic/claude-sonnet-5`, `anthropic/claude-haiku-4.5`
  * OpenAI: `openai/gpt-5.6-sol-pro`, `openai/gpt-5.6-sol`, `openai/gpt-5.6-terra-pro`, `openai/gpt-5.6-terra`, `openai/gpt-5.6-luna-pro`, `openai/gpt-5.6-luna`, `openai/gpt-5.5-pro`, `openai/gpt-5.5`
  * Google: `google/gemini-3.5-flash`
  * xAI: `x-ai/grok-4.5`, `x-ai/grok-4.20`, `x-ai/grok-4.3`
  * DeepSeek: `deepseek/deepseek-v4-pro`, `deepseek/deepseek-v4-flash`, `deepseek/deepseek-v3.2`
  * Qwen: `qwen/qwen3.6-max-preview`, `qwen/qwen3.6-plus`, `qwen/qwen3.6-flash`
  * Mistral: `mistralai/mistral-large-2512`, `mistralai/mistral-medium-3-5`
  * Z.AI: `z-ai/glm-4.6`, `z-ai/glm-5`
  * Moonshot: `moonshotai/kimi-k3`, `moonshotai/kimi-k2.6`, `moonshotai/kimi-k2-thinking`
  * Perplexity: `perplexity/sonar-pro`, `perplexity/sonar-reasoning-pro`, `perplexity/sonar-deep-research`

* **Image and video constraints:** The maximum number of reference images and videos depends on the selected model. The node raises an error if the total number of images or videos provided exceeds the model's limit. Models without image or video support do not show the corresponding reference slots.

* **Reasoning behavior:** When `reasoning_effort` is set to anything other than "off", the request asks the provider to reason internally without returning the reasoning trace.

* **Seed behavior:** The `seed` parameter has a "control\_after\_generate" behavior, meaning it can be set to automatically change (e.g., randomize, increment, or fixed) after each node execution, depending on the user's widget settings.

* **System prompt:** The `system_prompt` parameter is optional and is marked as an advanced parameter in the user interface.

* **Error cases:** The node raises an error if the prompt is empty after trimming whitespace, if OpenRouter returns an error, if the selected model refuses to respond, or if the response contains no choices or message. A price badge on the node shows an approximate cost estimate per 1K tokens based on the selected model.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated text response from the OpenRouter model. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenRouterLLMNode/en.md)

***

**Source fingerprint (SHA-256):** `534ab9ecc12e35a23a4d8f3e10f4f82d95db8e902ac8a2f2ee0ea68246516f62`


# PixverseImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseImageToVideoNode

Generates a video from a still image and a text prompt using PixVerse.

Generates a video from a still image and a text prompt using PixVerse. The node uploads the input image, applies the selected quality, duration, and motion settings, and then returns the resulting video once generation finishes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | Input image to transform into video | IMAGE | Yes | - |
| `prompt` | Prompt for the video generation (default: empty string) | STRING | Yes | - |
| `quality` | Video quality setting (default: res\_540p) | COMBO | Yes | `res_540p`<br />`res_1080p` |
| `duration_seconds` | Duration of the generated video in seconds | COMBO | Yes | `dur_2`<br />`dur_5`<br />`dur_10` |
| `motion_mode` | Motion style applied to the video generation | COMBO | Yes | `normal`<br />`fast`<br />`slow`<br />`zoom_in`<br />`zoom_out`<br />`pan_left`<br />`pan_right`<br />`pan_up`<br />`pan_down`<br />`tilt_up`<br />`tilt_down`<br />`roll_clockwise`<br />`roll_counterclockwise` |
| `seed` | Seed for video generation (default: 0) | INT | Yes | 0-2147483647 |
| `negative_prompt` | An optional text description of undesired elements on an image (default: empty string) | STRING | No | - |
| `pixverse_template` | An optional template to influence style of generation, created by the PixVerse Template node | CUSTOM | No | - |

**Note:** When using 1080p quality, the motion mode is automatically set to normal and duration is limited to 5 seconds. For durations other than 5 seconds, the motion mode is also automatically set to normal.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | Generated video based on the input image and parameters | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `93ea662a27159f55bf12e49ea230f0005813614ad07f5189d1fd61e7b937fd4b`


# PixverseTemplateNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseTemplateNode

The PixVerse Template node allows you to select from available templates for PixVerse video generation.

The PixVerse Template node allows you to select from available templates for PixVerse video generation. It converts your selected template name into the corresponding template ID that the PixVerse API requires for video creation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `template` | The template to use for PixVerse video generation. The available options correspond to predefined templates in the PixVerse system. | STRING | Yes | Multiple options available |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `pixverse_template` | The template ID corresponding to the selected template name, which can be used by other PixVerse nodes for video generation. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseTemplateNode/en.md)

***

**Source fingerprint (SHA-256):** `618f9203127c55e8b65802fe3711c6d7c7dc6b631e9050f9685419c1b23bc138`


# PixverseTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseTextToVideoNode

Generates videos from a text prompt using the PixVerse API.

Generates videos from a text prompt using the PixVerse API. The node lets you control the video's shape, quality, length, and motion style, and can optionally apply a saved style template. It submits the request, waits for the generation to finish, and returns the finished video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the video generation (default: "") | STRING | Yes | Must contain at least 1 character |
| `aspect_ratio` | Aspect ratio for the generated video | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"` |
| `quality` | Video quality setting (default: "540p") | COMBO | Yes | `"540p"`<br />`"1080p"` |
| `duration_seconds` | Duration of the generated video in seconds | COMBO | Yes | `"5"`<br />`"10"` |
| `motion_mode` | Motion style for the video generation | COMBO | Yes | `"normal"`<br />`"fast"` |
| `seed` | Seed for video generation (default: 0) | INT | Yes | 0 to 2147483647 |
| `negative_prompt` | An optional text description of undesired elements on an image (default: "") | STRING | No | - |
| `pixverse_template` | An optional template to influence style of generation, created by the PixVerse Template node | CUSTOM | No | - |

**Note:** The `prompt` must contain at least 1 character. When 1080p quality is selected, the motion mode is automatically set to `normal` and the duration is limited to 5 seconds. For any duration other than 5 seconds, the motion mode is also automatically set to `normal`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseTextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `cb95579dc6c9afa17455b0216ec46571ad2c0455606cf3b9c725ca512c45f938`


# PixverseTransitionVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseTransitionVideoNode

Generates a transition video between two input images using the PixVerse API.

Generates a transition video between two input images using the PixVerse API. You provide a starting image and an ending image, and the node creates a smooth video that transitions from one to the other, guided by your text prompt and chosen settings.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `first_frame` | The starting image for the video transition | IMAGE | Yes | - |
| `last_frame` | The ending image for the video transition | IMAGE | Yes | - |
| `prompt` | Prompt for the video generation (default: empty string) | STRING | Yes | - |
| `quality` | Video quality setting (default: `"540p"`) | COMBO | Yes | `"360p"`<br />`"540p"`<br />`"720p"`<br />`"1080p"` |
| `duration_seconds` | Video duration in seconds | COMBO | Yes | `5`<br />`8` |
| `motion_mode` | Motion style for the transition (default: `"normal"`) | COMBO | Yes | `"normal"`<br />`"fast"` |
| `seed` | Seed for video generation (default: 0) | INT | Yes | 0 to 2147483647 |
| `negative_prompt` | An optional text description of undesired elements on an image (default: empty string) | STRING | No | - |

**Note on parameter constraints:** When using 1080p quality, the motion mode is automatically set to `"normal"` and duration is limited to 5 seconds. For any non-5 second duration, the motion mode is also automatically set to `"normal"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated transition video | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseTransitionVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `9774f15ae93377d4768cee9f51ce004a791ecaad3cadd0a2467d354c4dbc6f23`


# PixverseV6ExtendVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseV6ExtendVideoNode

This node continues an existing video using the PixVerse V6 model, optionally generating a native audio track alongside the continuation.

This node continues an existing video using the PixVerse V6 model, optionally generating a native audio track alongside the continuation. The source video must be shorter than 40 seconds and no larger than 1920 pixels on either side. The output keeps the source video's resolution, so the quality setting controls how well the continuation is rendered rather than the frame size.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Video to continue. | VIDEO | Yes | Shorter than 40 seconds; at most 1920 pixels width and height |
| `model` | Model and generation settings. | DYNAMIC\_COMBO | Yes | "PixVerse V6" |

### PixVerse V6 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing how the video should continue. (default: empty) | STRING | Yes | 1–5000 characters |
| `quality` | Render quality of the generated continuation: 1080p looks markedly better than 540p or 360p. It never resizes - the output keeps the source video's resolution. (default: "720p") | COMBO | Yes | "360p"<br />"540p"<br />"720p"<br />"1080p" |
| `duration_seconds` | Length of the generated video in seconds. (default: 5) | INT | Yes | 1–15 |
| `generate_audio` | Generate a native audio track together with the video. (default: true) | BOOLEAN | Yes | true / false |
| `seed` | Seed for video generation. PixVerse records it but does not reproduce a run from it. (default: 42) | INT | Yes | 0–2147483647 |
| `negative_prompt` | An optional text description of undesired elements in the video. (default: empty) | STRING | No | Up to 2048 characters |
| `style` | An optional visual style applied to the whole video. (default: "none") | COMBO | No | Multiple options available; "none" is the default |

**Note:** The source `video` must be shorter than 40 seconds and at most 1920 pixels on both width and height; longer or larger videos are rejected. The generated output keeps the source video's resolution, so `quality` changes rendering fidelity, not the output frame size. The `prompt` is required and must contain between 1 and 5000 characters after trimming whitespace. The `negative_prompt`, when provided, is limited to 2048 characters. The `seed` is recorded by PixVerse but cannot be used to reproduce the same run.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated continuation video, at the same resolution as the source video. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseV6ExtendVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `8bd2a04a5da95b39fb963922e2e54a7aa4efb670260fa38313d21db3af295029`


# PixverseV6FirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseV6FirstLastFrameNode

PixVerse V6 First-Last-Frame to Video generates a video that transitions from a first frame to a last frame using PixVerse, optionally with native audio.

PixVerse V6 First-Last-Frame to Video generates a video that transitions from a first frame to a last frame using PixVerse, optionally with native audio. The two provided images are sent to the PixVerse API, which produces the transition video and returns it as a video file. The output keeps the aspect ratio of the first frame.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `first_frame` | The starting image of the video. | IMAGE | Yes | — |
| `last_frame` | The ending image of the video. | IMAGE | Yes | — |
| `model` | Model and generation settings. Selects the PixVerse model and shows its generation parameters. | DYNAMIC\_COMBO | Yes | "PixVerse V6" |

### PixVerse V6 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the transition. | STRING | Yes | Up to 5000 characters |
| `quality` | Output resolution. Sets the long edge: 360p is 640px, 540p 1024px, 720p 1280px, 1080p 1920px. (default: 720p) | COMBO | Yes | "360p"<br />"540p"<br />"720p"<br />"1080p" |
| `duration_seconds` | Length of the generated video in seconds. (default: 5) | INT | Yes | 1 to 15 |
| `generate_audio` | Generate a native audio track together with the video. (default: true) | BOOLEAN | Yes | true<br />false |
| `seed` | Seed for video generation. PixVerse records it but does not reproduce a run from it. (default: 42) | INT | Yes | 0 to 2147483647 |
| `negative_prompt` | An optional text description of undesired elements in the video. | STRING | No | Up to 2048 characters |
| `style` | An optional visual style applied to the whole video. (default: none) | COMBO | No | Multiple options available (default: "none") |

Note: The prompt must not be empty after removing whitespace, and is limited to 5000 characters. The negative prompt, when provided, is limited to 2048 characters. The duration must be between 1 and 15 seconds. The output video keeps the aspect ratio of the first frame.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video that transitions from the first frame to the last frame, including an audio track when `generate_audio` is enabled. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseV6FirstLastFrameNode/en.md)

***

**Source fingerprint (SHA-256):** `cdb5e45e9de2b429b9d43bbff90b6529af246911ecae8c2809c8abd539101aaa`


# PixverseV6FusionVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseV6FusionVideoNode

PixVerse V6 Fusion (Reference to Video) composes a video from reference subjects, backgrounds and videos with PixVerse.

PixVerse V6 Fusion (Reference to Video) composes a video from reference subjects, backgrounds and videos with PixVerse. Place a reference in the scene by naming it in the prompt, for example '@Subject1 walks through @Background1'. Connecting a reference video switches the model to Omni mode, where the output length matches the longest reference video.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model and generation settings. Selects the model and exposes its generation settings below. The only available option is "PixVerse V6". | DYNAMIC\_COMBO | Yes | "PixVerse V6" |

### PixVerse V6 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the video generation. Refer to connected references as @Subject1, @Background1, @Video1. Default: empty. | STRING | Yes | 1 to 5000 characters |
| `aspect_ratio` | Output aspect ratio. The "auto" option is only allowed when at least one reference video is connected. | COMBO | Yes | "auto"<br />plus the predefined PixVerse V6 aspect ratios |
| `quality` | Output resolution. Sets the long edge: 360p is 640px, 540p 1024px, 720p 1280px, 1080p 1920px. Default: "720p". | COMBO | Yes | "360p"<br />"540p"<br />"720p"<br />"1080p" |
| `duration_seconds` | Length of the generated video in seconds. When reference videos are connected, the output length instead follows the longest reference video and this setting is ignored. Default: 5. | INT | Yes | 1 to 15 |
| `generate_audio` | Generate a native audio track together with the video. Default: True. | BOOLEAN | Yes | True<br />False |
| `seed` | Seed for video generation. PixVerse records it but does not reproduce a run from it. Default: 42. | INT | Yes | 0 to 2147483647 |
| `negative_prompt` | An optional text description of undesired elements in the video. Default: empty. | STRING | No | Up to 2048 characters |
| `style` | An optional visual style applied to the whole video. Default: "none". | COMBO | No | "none"<br />plus the predefined PixVerse V6 styles |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `subjects` | Growable slot: connect reference images of the subjects to place in the scene. Slots are named subject1 to subject8; reference them in the prompt as @Subject1, @Subject2, and so on. | IMAGE | No | 0 to 8 images |
| `backgrounds` | Growable slot: connect reference images of the scene the subjects are placed into. Slots are named background1 to background2; reference them in the prompt as @Background1, @Background2. | IMAGE | No | 0 to 2 images |
| `videos` | Growable slot: connect reference videos to borrow subjects, motion, framing or style from. Slots are named video1 to video2; reference them in the prompt as @Video1, @Video2. Each video must be at most 15 seconds long, and the total duration must not exceed 15 seconds. Connecting at least one video switches the node to Omni mode. | VIDEO | No | 0 to 2 videos<br />15 seconds max each<br />15 seconds total |

Note: Connect at least one subject, background or reference video. Reference tags in the prompt (for example @Subject1, @Background1, @Video1) must match connected slots, otherwise the request is rejected. When at least one reference video is connected (Omni mode), the output length matches the longest reference video, `duration_seconds` is ignored, `aspect_ratio` can be set to "auto", and up to 10 reference images are accepted. Without a reference video, at most 7 reference images (subjects and backgrounds combined) are accepted, and "auto" aspect ratio is not allowed.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated fusion video, downloaded from PixVerse. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseV6FusionVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `a83ef07f6f1918921e93fa67c2eca351754794f629aa216ccff21ce80901aebd`


# RecraftV4TextToVectorNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftV4TextToVectorNode

The Recraft V4 Text to Vector node generates Scalable Vector Graphics (SVG) illustrations from a text description using Recraft V4 and V4.1 models.

The Recraft V4 Text to Vector node generates Scalable Vector Graphics (SVG) illustrations from a text description using Recraft V4 and V4.1 models. It connects to the Recraft API to generate one or more SVG files based on your prompt, and can apply an existing vector style or create a new one from reference images — when reference images are used, the created style is returned as a `style_id` for reuse.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to use for generation. The recraftv4\_styles models are built for style-consistent generation and always require a style\_id or style\_references. Selecting a model changes the available `size` options. | DYNAMIC\_COMBO | Yes | `"recraftv4_1_vector"`<br />`"recraftv4_1_utility_vector"`<br />`"recraftv4_1_pro_vector"`<br />`"recraftv4_1_utility_pro_vector"`<br />`"recraftv4"`<br />`"recraftv4_pro"`<br />`"recraftv4_styles_vector"`<br />`"recraftv4_styles_pro_vector"` |
| `prompt` | Prompt for the image generation. Maximum 10,000 characters. | STRING | Yes | N/A |
| `negative_prompt` | This input is ignored: negative prompt is not supported by Recraft V4 and V4.1 models. | STRING | Yes | N/A |
| `n` | The number of images to generate (default: 1). | INT | Yes | 1 to 6 |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). | INT | Yes | 0 to 18446744073709551615 |
| `recraft_controls` | Optional additional controls over the generation via the Recraft Controls node. | CUSTOM | No | N/A |
| `style_id` | UUID of a Recraft V4 vector style to apply, e.g. from the Recraft V4 Create Style node or the style\_id output of a previous run. Cannot be combined with style\_references. | STRING | No | N/A |
| `style_match` | How closely to follow the style: precise reproduces it in detail, flexible matches the general look. Only used when a style is provided (default: "precise"). | COMBO | No | `"precise"`<br />`"flexible"` |

### recraftv4\_1\_vector, recraftv4\_1\_utility\_vector, recraftv4, and recraftv4\_styles\_vector Inputs

These models share the same `size` options.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size` | The size of the generated image. Default is `"1024x1024"`. | COMBO | Yes | `"1024x1024"`<br />`"1152x896"`<br />`"896x1152"`<br />`"1216x832"`<br />`"832x1216"`<br />`"1344x768"`<br />`"768x1344"`<br />`"1536x640"`<br />`"640x1536"` |

### recraftv4\_1\_pro\_vector, recraftv4\_1\_utility\_pro\_vector, recraftv4\_pro, and recraftv4\_styles\_pro\_vector Inputs

These models share the same `size` options.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `size` | The size of the generated image. Default is `"2048x2048"`. | COMBO | Yes | `"2048x2048"`<br />`"2304x1792"`<br />`"1792x2304"`<br />`"2432x1664"`<br />`"1664x2432"`<br />`"2688x1536"`<br />`"1536x2688"`<br />`"3072x1280"`<br />`"1280x3072"` |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `style_references` | Reference images to create a vector style from on the fly, billed on top of the generation. The created style is returned as style\_id for reuse. Cannot be combined with style\_id. | IMAGE | No | Growable slot: connect 1..N reference images (up to the node's maximum) |

**Note:** The `size` parameter is a dynamic input whose available options change based on the selected `model`. The `seed` value does not guarantee reproducible results from the external API. The `recraftv4_styles_vector` and `recraftv4_styles_pro_vector` models always require a style: provide a `style_id` or connect at least one `style_references` image. `style_id` and `style_references` cannot be used together — providing both raises an error, and `style_id` must be a valid UUID. Style reference images are limited in number, and their total encoded size must not exceed 10 MB.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated Scalable Vector Graphics (SVG) image(s). | SVG |
| `style_id` | The style UUID returned by the Recraft API. When reference images are provided, the created style is returned here for reuse; otherwise an empty string. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftV4TextToVectorNode/en.md)

***

**Source fingerprint (SHA-256):** `182a40b206b164cf2e96c7344d23e4906b7d61b90e3000743a3fd31941e08539`


# RecraftVectorizeImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftVectorizeImageNode

Generates SVG vector graphics from an input image.

Generates SVG vector graphics from an input image. This node converts raster images into scalable vector format by sending each image to the Recraft API and combining the results into a single SVG output.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to convert to SVG format. Supports batch processing of multiple images. | IMAGE | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `SVG` | The generated vector graphics output combining all processed images into a single SVG document. | SVG |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftVectorizeImageNode/en.md)

***

**Source fingerprint (SHA-256):** `bda74d9f11cc79217c61ecb8ba597a671133baa4380386428c4d9e9b68006713`


# ReveImageCreateNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReveImageCreateNode

The Reve Image Create node generates images from a text description using the Reve AI model.

The Reve Image Create node generates images from a text description using the Reve AI model. It sends the prompt to the Reve API and returns the resulting image, with optional post-processing for upscaling and background removal. This node is deprecated.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model version to use for generation. | DYNAMIC\_COMBO | Yes | `"reve-create@20250915"` |
| `prompt` | Text description of the desired image. Maximum 2560 characters. Default: "" (empty). | STRING | Yes | 1 to 2560 characters |
| `upscale` | Upscale the generated image. May add additional cost. Default: "disabled". | DYNAMIC\_COMBO | No | `"disabled"`<br />`"enabled"` |
| `remove_background` | Remove the background from the generated image. May add additional cost. Default: False. | BOOLEAN | No | N/A |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. Default: 0. | INT | No | 0 to 2147483647 |

### reve-create\@20250915 Inputs

Options available when `model` is set to `"reve-create@20250915"`:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `aspect_ratio` | Aspect ratio of the output image. | COMBO | Yes | `"3:2"`<br />`"16:9"`<br />`"9:16"`<br />`"2:3"`<br />`"4:3"`<br />`"3:4"`<br />`"1:1"` |
| `test_time_scaling` | Higher values produce better images but cost more credits. Default: 1. Advanced option. | INT | No | 1 to 5 |

### Upscale Inputs

Options available when `upscale` is set to `"enabled"`:

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `upscale_factor` | Upscale factor (2x, 3x, or 4x). Default: 2. | INT | No | 2 to 4 |

**Note:** The `prompt` must contain between 1 and 2560 characters. The `upscale_factor` input only appears when `upscale` is set to `"enabled"`. The `seed` parameter does not guarantee deterministic outputs — results are non-deterministic regardless of the seed value. Both `upscale` and `remove_background` may add additional cost.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The image generated by the Reve model based on the input prompt. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReveImageCreateNode/en.md)

***

**Source fingerprint (SHA-256):** `69178bc7d11e32ca179be5f598fbe60c4d41955b87e1c797e79cf224917a930c`


# ReveImageEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReveImageEditNode

The Reve Image Edit node modifies an existing image based on a natural language text instruction.

The Reve Image Edit node modifies an existing image based on a natural language text instruction. It sends the input image and your instruction to the Reve API, which returns a new image with the requested edits applied.

## Inputs

The `model` selector determines which model-specific inputs are shown. The `upscale` selector controls whether the upscale factor input is available.

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The image to edit. | IMAGE | Yes | - |
| `edit_instruction` | Text description of how to edit the image. Maximum 2560 characters. | STRING | Yes | - |
| `model` | Model version to use for editing. | DYNAMIC\_COMBO | Yes | `"reve-edit@20250915"`<br />`"reve-edit-fast@20251030"` |
| `upscale` | Upscale the generated image. May add additional cost. (default: "disabled") | DYNAMIC\_COMBO | No | `"disabled"`<br />`"enabled"` |
| `remove_background` | Remove the background from the generated image. May add additional cost. (default: False) | BOOLEAN | No | `true`<br />`false` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | No | 0 to 2147483647 |

### Model Inputs (shared by `reve-edit@20250915` and `reve-edit-fast@20251030`)

Both model versions expose the same model-specific inputs.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.aspect_ratio` | Aspect ratio of the output image. When set to "auto", the aspect ratio is determined automatically. | COMBO | No | `"auto"`<br />`"16:9"`<br />`"9:16"`<br />`"3:2"`<br />`"2:3"`<br />`"4:3"`<br />`"3:4"`<br />`"1:1"` |
| `model.test_time_scaling` | Advanced option. Higher values produce better images but cost more credits. (default: 1) | INT | No | 1 to 5 |

### Upscale Inputs (when `upscale` is set to "enabled")

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `upscale.upscale_factor` | Upscale factor (2x, 3x, or 4x). (default: 2) | INT | No | 2 to 4 |

**Note:**

* `upscale.upscale_factor` only applies when `upscale` is set to "enabled". Upscaling and background removal can be enabled together or independently.
* `edit_instruction` must not be empty and cannot exceed 2560 characters.
* When `model.aspect_ratio` is set to "auto", no fixed aspect ratio is sent to the API and the aspect ratio is chosen automatically.
* `model.test_time_scaling` is only sent to the API when its value is greater than 1; the default value of 1 keeps the API's default behavior.
* Results are non-deterministic regardless of the seed value; the seed only controls whether the node re-runs.
* This node is marked as deprecated.
* Approximate cost in USD (per the node's price badge): `$0.01001` for `reve-edit-fast@20251030`; `$0.0572` for `reve-edit@20250915` without upscaling; `$0.0686` with 2x upscaling, `$0.0819` with 3x upscaling, and `$0.0991` with 4x upscaling.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The edited image generated based on the instruction. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReveImageEditNode/en.md)

***

**Source fingerprint (SHA-256):** `4001f3ab4cc4e705c235f578e90e497bb30d22110ef69b16fb072a91a65d15df`


# ReveImageRemixNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReveImageRemixNode

The Reve Image Remix node uses the Reve API to generate a new image.

The Reve Image Remix node uses the Reve API to generate a new image. It combines one or more reference images with a text prompt to create a new, remixed image based on the provided description.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model version to use for remixing. | DYNAMIC\_COMBO | Yes | `"reve-remix@20250915"`<br />`"reve-remix-fast@20251030"` |
| `prompt` | Text description of the desired image. May include XML img tags to reference specific images by index, e.g. `<img>0</img>`, `<img>1</img>`, etc. (default: empty) | STRING | Yes | 1 to 2560 characters |
| `upscale` | Upscale the generated image. May add additional cost. (default: "disabled") | DYNAMIC\_COMBO | No | `"disabled"`<br />`"enabled"` |
| `remove_background` | Remove the background from the generated image. May add additional cost. (default: false) | BOOLEAN | No | `true`<br />`false` |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | No | 0 to 2147483647 |

### Model Inputs (Shared by reve-remix\@20250915 and reve-remix-fast\@20251030)

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `aspect_ratio` | Aspect ratio of the output image. (default: "auto") | COMBO | Yes | `"auto"`<br />`"16:9"`<br />`"9:16"`<br />`"3:2"`<br />`"2:3"`<br />`"4:3"`<br />`"3:4"`<br />`"1:1"` |
| `test_time_scaling` | Higher values produce better images but cost more credits. (default: 1) | INT | No | 1 to 5 |

### Upscale Inputs (Appear When `upscale` Is Set to "enabled")

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `upscale_factor` | Upscale factor (2x, 3x, or 4x). (default: 2) | INT | No | 2 to 4 |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect 1 to 6 images (`image_1` to `image_6`) to use as the visual base for the remix. At least one reference image is required. | IMAGE | Yes | 1 to 6 images |

**Note:** The prompt must contain between 1 and 2560 characters. When `aspect_ratio` is set to "auto", the service determines the aspect ratio of the output image. A `test_time_scaling` value of 1 applies standard processing; higher values improve image quality but consume more credits. The `upscale_factor` widget only appears when `upscale` is set to "enabled". The remix results are non-deterministic regardless of the seed value. This node is deprecated.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The new image generated by the Reve remix process. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReveImageRemixNode/en.md)

***

**Source fingerprint (SHA-256):** `9cf0c6653aa620179ed5d888a455fe248a240b0db04687eade6652730eb5f003`


# RunwayTextToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayTextToImageNode

The Runway Text to Image node generates images from text prompts using Runway's Gen 4 model.

The Runway Text to Image node generates images from text prompts using Runway's Gen 4 model. You can provide a text description and optionally include a reference image to guide the image generation process. The node handles the API communication and returns the generated image.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for the generation (default: "") | STRING | Yes | - |
| `ratio` | Aspect ratio for the generated image | COMBO | Yes | "16:9"<br />"1:1"<br />"21:9"<br />"2:3"<br />"3:2"<br />"4:5"<br />"5:4"<br />"9:16"<br />"9:21" |
| `reference_image` | Optional reference image to guide the generation | IMAGE | No | - |

**Note:** The reference image must have dimensions not exceeding 7999x7999 pixels and an aspect ratio between 0.5 and 2.0. When a reference image is provided, it guides the image generation process.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated image based on the text prompt and optional reference image | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayTextToImageNode/en.md)

***

**Source fingerprint (SHA-256):** `c9403da2e9ad8f663d3eea32eb549843696262e4472fc8d58c1f56ef9cc5aa7d`


# TopazImageEnhance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TopazImageEnhance

The Topaz Image Enhance node provides industry-standard upscaling and image enhancement.

The Topaz Image Enhance node provides industry-standard upscaling and image enhancement. It processes a single input image using a cloud-based AI model to improve quality, detail, and resolution. The node offers fine-grained control over the enhancement process, including options for creative guidance, subject focus, and facial preservation.

This node is a legacy version and is marked as deprecated in the interface.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for image enhancement. | COMBO | Yes | `"Reimagine"` |
| `image` | The input image to be enhanced. Only one image is supported. | IMAGE | Yes | - |
| `prompt` | Optional text prompt for creative upscaling guidance (default: empty). | STRING | No | - |
| `subject_detection` | Controls which part of the image the enhancement focuses on (default: "All"). | COMBO | No | `"All"`<br />`"Foreground"`<br />`"Background"` |
| `face_enhancement` | Enhance faces (if present) during processing (default: True). | BOOLEAN | No | - |
| `face_enhancement_creativity` | Set the creativity level for face enhancement (default: 0.0). | FLOAT | No | 0.0 - 1.0 |
| `face_enhancement_strength` | Controls how sharp enhanced faces are relative to the background (default: 1.0). | FLOAT | No | 0.0 - 1.0 |
| `crop_to_fill` | By default, the image is letterboxed when the output aspect ratio differs. Enable to crop the image to fill the output dimensions (default: False). | BOOLEAN | No | - |
| `output_width` | Zero value means to calculate automatically (usually it will be original size or output\_height if specified) (default: 0). | INT | No | 0 - 32000 |
| `output_height` | Zero value means to output in the same height as original or output width (default: 0). | INT | No | 0 - 32000 |
| `creativity` | Controls the overall creativity level of the enhancement (default: 3). | INT | No | 1 - 9 |
| `face_preservation` | Preserve subjects' facial identity (default: True). | BOOLEAN | No | - |
| `color_preservation` | Preserve the original colors (default: True). | BOOLEAN | No | - |

**Note:** This node can only process a single input image. Providing a batch of multiple images will result in an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The enhanced output image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TopazImageEnhance/en.md)

***

**Source fingerprint (SHA-256):** `1a0e708cdea9ec4f92f7f3aaabbdeea06a8fdab2f91a45ad2dea15f2bc2e8fa3`


# TopazImageEnhanceV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TopazImageEnhanceV2

Topaz Image Enhance applies industry-standard upscaling and image enhancement to a single input image using Topaz models.

Topaz Image Enhance applies industry-standard upscaling and image enhancement to a single input image using Topaz models. It sends the image to the Topaz API, processes it with the selected model, and returns the enhanced result. You can choose from three models: Reimagine, Bloom 2, and Wonder 3.5.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to enhance. Only one input image is supported. | IMAGE | Yes | Single image |
| `model` | The Topaz enhancement model to use. The selected model determines which model-specific settings appear. | DYNAMIC\_COMBO | Yes | `"Reimagine"`<br />`"Bloom 2"`<br />`"Wonder 3.5"` |
| `output_width` | Zero value means to calculate automatically (usually it will be original size or scaled proportionally to `output_height` if specified). Wonder 3.5 supports upscale factors from 1x to 6x only. Bloom 2 and Wonder 3.5 preserve the input aspect ratio and treat the requested size as a target. (default: 0) | INT | No | 0 to 32000 |
| `output_height` | Zero value means to output in the same height as original or scaled proportionally to `output_width` if specified. Wonder 3.5 supports upscale factors from 1x to 6x only. Bloom 2 and Wonder 3.5 preserve the input aspect ratio and treat the requested size as a target. (default: 0) | INT | No | 0 to 32000 |

### Reimagine Inputs

These settings apply when `model` is set to `"Reimagine"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Optional text prompt for creative upscaling guidance. (default: "") | STRING | Yes | Any text |
| `creativity` | Creativity level for the enhancement. (default: 3) | INT | Yes | 1 to 9 |
| `subject_detection` | Subject detection mode (advanced). | COMBO | Yes | `"All"`<br />`"Foreground"`<br />`"Background"` |
| `face_enhancement` | Enhance faces (if present) during processing. (default: True) | BOOLEAN | Yes | true<br />false |
| `face_enhancement_creativity` | Set the creativity level for face enhancement. (default: 0.0) | FLOAT | Yes | 0.0 to 1.0 |
| `face_enhancement_strength` | Controls how sharp enhanced faces are relative to the background. (default: 1.0) | FLOAT | Yes | 0.0 to 1.0 |
| `face_preservation` | Preserve subjects' facial identity. (default: True) | BOOLEAN | Yes | true<br />false |
| `color_preservation` | Preserve the original colors. (default: True) | BOOLEAN | Yes | true<br />false |
| `crop_to_fill` | By default, the image is letterboxed when the output aspect ratio differs. Enable to crop the image to fill the output dimensions. (default: False) | BOOLEAN | Yes | true<br />false |

### Bloom 2 Inputs

These settings apply when `model` is set to `"Bloom 2"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Optional text prompt for generation. Leave empty to auto-generate a prompt from the input image. (default: "") | STRING | Yes | Any text |
| `creativity` | 1 is restrained enhancement, 9 is pronounced reinterpretation with newly generated detail. (default: 3) | INT | Yes | 1 to 9 |
| `seed` | Seed for reproducible generation. (default: 2) | INT | Yes | 1 to 2000 |
| `color_preservation` | Preserve the original colors. (default: True) | BOOLEAN | Yes | true<br />false |
| `grain` | Add grain to the output image. (default: False) | BOOLEAN | Yes | true<br />false |
| `grain_model` | Grain model to use. Is ignored if grain is disabled. | COMBO | Yes | `"silver"`<br />`"gaussian"`<br />`"grey"` |
| `grain_strength` | Strength of the grain effect. Is ignored if grain is disabled. (default: 0.5) | FLOAT | Yes | 0.0 to 1.0 |
| `grain_size` | Size of the grain particles. Is ignored if grain is disabled. (default: 1.0) | FLOAT | Yes | 1.0 to 5.0 |
| `grain_density` | Intensity of the grain effect. Is ignored if grain is disabled. (default: 0.5) | FLOAT | Yes | 0.0 to 1.0 |

### Wonder 3.5 Inputs

These settings apply when `model` is set to `"Wonder 3.5"`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `enhancement_strength` | Enhancement level for varying input conditions. (default: "high") | COMBO | Yes | `"low"`<br />`"medium"`<br />`"high"` |
| `grain` | Add grain to the output image. (default: False) | BOOLEAN | Yes | true<br />false |
| `grain_model` | Grain model to use. Is ignored if grain is disabled. | COMBO | Yes | `"silver"`<br />`"gaussian"`<br />`"grey"` |
| `grain_strength` | Strength of the grain effect. Is ignored if grain is disabled. (default: 0.5) | FLOAT | Yes | 0.0 to 1.0 |
| `grain_size` | Size of the grain particles. Is ignored if grain is disabled. (default: 1.0) | FLOAT | Yes | 1.0 to 5.0 |
| `grain_density` | Intensity of the grain effect. Is ignored if grain is disabled. (default: 0.5) | FLOAT | Yes | 0.0 to 1.0 |

**Note:** Only one input image is supported; the node raises an error if the input batch contains more than one image. Grain settings (`grain_model`, `grain_strength`, `grain_size`, `grain_density`) are ignored unless `grain` is enabled. For Bloom 2, leaving `prompt` empty automatically generates a prompt from the input image. Wonder 3.5 supports upscale factors from 1x to 6x only; Bloom 2 and Wonder 3.5 preserve the input aspect ratio and treat the requested size as a target.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | The enhanced and upscaled image returned by the Topaz API. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TopazImageEnhanceV2/en.md)

***

**Source fingerprint (SHA-256):** `19bb03ca7354f1b0d1e559b742b83939678fce6d5f490b1030717b846043e0e6`


# WanImageToImageApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanImageToImageApi

The Wan Image to Image node generates an image from one or two input images and a text prompt.

The Wan Image to Image node generates an image from one or two input images and a text prompt. It transforms your input images based on the description you provide, creating a new image that maintains the aspect ratio of your original input. The output image is fixed at 1.6 megapixels regardless of the input size.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use (default: "wan2.5-i2i-preview"). | COMBO | Yes | "wan2.5-i2i-preview" |
| `image` | Single-image editing or multi-image fusion. Maximum 2 images. | IMAGE | Yes | - |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese (default: empty). | STRING | Yes | - |
| `negative_prompt` | Negative prompt describing what to avoid (default: empty). | STRING | No | - |
| `seed` | Seed to use for generation (default: 0). | INT | No | 0 to 2147483647 |
| `watermark` | Whether to add an AI-generated watermark to the result (default: false). | BOOLEAN | No | - |

**Note:** This node accepts exactly 1 or 2 input images. If you provide more than 2 images or no images at all, the node will return an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The generated image based on the input images and text prompts. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanImageToImageApi/en.md)

***

**Source fingerprint (SHA-256):** `e78e5fb43d92c839448d3449b89445fb5db081ee8c947e44edcc048b8740f45d`


# WanTextToImageApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanTextToImageApi

The Wan Text to Image node generates images based on text descriptions.

The Wan Text to Image node generates images based on text descriptions. It uses AI models to create visual content from written prompts, supporting both English and Chinese text input. The node provides various controls to adjust the output image size, quality, and style preferences.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use (default: "wan2.5-t2i-preview") | STRING | Yes | "wan2.5-t2i-preview" |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese (default: empty) | STRING | Yes | - |
| `negative_prompt` | Negative prompt describing what to avoid (default: empty) | STRING | No | - |
| `width` | Image width in pixels (default: 1024, step: 32) | INT | No | 768-1440 |
| `height` | Image height in pixels (default: 1024, step: 32) | INT | No | 768-1440 |
| `seed` | Seed to use for generation (default: 0) | INT | No | 0-2147483647 |
| `prompt_extend` | Whether to enhance the prompt with AI assistance (default: True) | BOOLEAN | No | - |
| `watermark` | Whether to add an AI-generated watermark to the result (default: False) | BOOLEAN | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated image based on the text prompt | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanTextToImageApi/en.md)

***

**Source fingerprint (SHA-256):** `208b7c839da45316aeb1a14a3e9d176eeb09b2f931f764fb8a296da15ae3bd4e`


# WavespeedImageUpscaleNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WavespeedImageUpscaleNode

The WaveSpeed Image Upscale node uses an external AI service to increase the resolution and quality of an image.

The WaveSpeed Image Upscale node uses an external AI service to increase the resolution and quality of an image. It takes a single input photo and upscales it to a higher target resolution, such as 2K, 4K, or 8K, producing a sharper and more detailed result.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for upscaling. "SeedVR2" and "Ultimate" offer different quality and pricing tiers. | STRING | Yes | `"SeedVR2"`<br />`"Ultimate"` |
| `image` | The input image to be upscaled. Exactly one image is required. | IMAGE | Yes | |
| `target_resolution` | The desired output resolution for the upscaled image. | STRING | Yes | `"2K"`<br />`"4K"`<br />`"8K"` |

**Note:** This node requires exactly one input image. Providing a batch of images will result in an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `image` | The upscaled, high-resolution output image. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WavespeedImageUpscaleNode/en.md)

***

**Source fingerprint (SHA-256):** `1d715431efb690d30d9fc3b4769047a9d568b49c62eb318615e2748c780b8c20`


# AddTextPrefix - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AddTextPrefix

The Add Text Prefix node modifies text by adding a specified string to the beginning of each input text.

The Add Text Prefix node modifies text by adding a specified string to the beginning of each input text. It takes the text and a prefix as input, then returns the combined result.

**Note:** This node is deprecated and superseded by the Concatenate Text node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | The text to which the prefix will be added. | STRING | Yes | |
| `prefix` | The string to add to the beginning of the text (default: ""). | STRING | No | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `text` | The resulting text with the prefix added to the front. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AddTextPrefix/en.md)

***

**Source fingerprint (SHA-256):** `71744a8dc3056b8f20eb2cb7ac16002ce86e214a660aa1d145f501d6d7dc5b53`


# AddTextSuffix - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AddTextSuffix

This node appends a specified suffix to the end of an input text string.

This node appends a specified suffix to the end of an input text string. It takes the original text and the suffix as inputs, then returns the combined result. **This node is deprecated** and superseded by the Concatenate Text node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | The original text to which the suffix will be added. | STRING | Yes | |
| `suffix` | The suffix to add to the text (default: ""). | STRING | No | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `text` | The resulting text after the suffix has been appended. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AddTextSuffix/en.md)

***

**Source fingerprint (SHA-256):** `9b73a9352d21feb5041de550cc4463222c9ccbc1ef4937415d4dc8c5648d3a90`


# AutogrowNamesTestNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AutogrowNamesTestNode

This node is a test for the Autogrow input feature.

This node is a test for the Autogrow input feature. It accepts a dynamic group of float inputs, each with a predefined name, and combines their values into a single comma-separated string.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `autogrow` | A dynamic input group. You can add multiple float inputs, each with a predefined name from the list: "a", "b", or "c". The node accepts any combination of these named inputs. | FLOAT | Yes | Named slots: `a`, `b`, `c` |

**Note:** The `autogrow` input is dynamic. Individual float inputs named "a", "b", and "c" can be added or removed as needed. All provided values are processed by the node.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | A single string containing the values from all provided float inputs, joined together with commas. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AutogrowNamesTestNode/en.md)

***

**Source fingerprint (SHA-256):** `dac384c9486ac645d0d292fc891603cbfa6d362baa0a1e939c43257bbc0b06a0`


# AutogrowPrefixTestNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AutogrowPrefixTestNode

The AutogrowPrefixTestNode is a logic node that tests the autogrow input feature.

The AutogrowPrefixTestNode is a logic node that tests the autogrow input feature. It accepts a dynamic number of float inputs, converts each value into text, combines them into a comma-separated string, and outputs that string.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `autogrow` | A dynamic input group that accepts between 1 and 10 float values. Each value is a floating-point number, and the generated inputs are named with the prefix `float`. | AUTOGROW | Yes | 1 to 10 inputs |

**Note:** The `autogrow` input is a special dynamic input. You can add multiple float inputs to this group, from a minimum of 1 up to a maximum of 10. The node processes all provided values and includes every connected input in the output string.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | A single string containing all the input float values, separated by commas. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AutogrowPrefixTestNode/en.md)

***

**Source fingerprint (SHA-256):** `9b815f59961a4c661815f44b9c78e15e9084db1e4be89d502b9d92438f18e70b`


# BuildJsonPromptIdeogram - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BuildJsonPromptIdeogram

This node constructs a structured JSON prompt specifically formatted for the Ideogram 4 image generation model.

This node constructs a structured JSON prompt specifically formatted for the Ideogram 4 image generation model. It organizes your text instructions, style preferences, camera or art details, lighting, medium, and optional color palette into the required JSON structure that the model expects.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `element` | Prompt elements from the node Create Bounding Boxes. | ARRAY | Yes | - |
| `high_level_description` | Optional description of the image in one or two sentences. Strongly recommended. (default: empty) | STRING | No | - |
| `background` | Mandatory description of the image background or environment. Providing a value is strongly recommended – the node will run with an empty string but results may be unpredictable. (default: empty) | STRING | No | - |
| `style` | The visual style category for the generated image. Select one of the options. (default: "none") | COMBO | Yes | `"none"`<br />`"photo"`<br />`"art_style"` |
| `photo` | Camera or lens details for photographic outputs (e.g. 35mm, f/1.4, bokeh). Only available when `style` is set to "photo". (default: empty) | STRING | No | - |
| `art_style` | Art style description (e.g. flat vector illustration, bold outlines). Only available when `style` is set to "art\_style". (default: empty) | STRING | No | - |
| `aesthetics` | Mandatory aesthetic keywords (e.g. moody, cinematic, desaturated). Providing a value is strongly recommended. (default: empty) | STRING | No | - |
| `lighting` | Mandatory lighting description (e.g. golden hour, rim light, dramatic shadows). Providing a value is strongly recommended. (default: empty) | STRING | No | - |
| `medium` | Mandatory medium type (e.g. photograph, illustration, 3d\_render, painting, graphic\_design). When style = photo, set to photograph. Providing a value is strongly recommended. (default: empty) | STRING | No | - |
| `color_palette` | Hex color codes that steer the image's dominant colors. Up to 16 entries. | COLORS | No | - |

**Note:** When `style` is set to "photo", the `photo` input becomes available and you should usually set `medium` to "photograph". When `style` is set to "art\_style", the `art_style` input becomes available. The `background`, `aesthetics`, `lighting`, and `medium` parameters have default empty strings but are considered mandatory for reliable image generation; providing values is strongly recommended.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `prompt` | A structured JSON dictionary containing the high-level description, style description (if a style other than "none" is selected), and compositional deconstruction with background and elements. | DICT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BuildJsonPromptIdeogram/en.md)

***

**Source fingerprint (SHA-256):** `56a045e0c7c19531e6443696c0bdf3946df066d03eea7d2d217b7d92f052592f`


# CaseConverter - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CaseConverter

The Case Converter node transforms text strings into different letter case formats.

The Case Converter node transforms text strings into different letter case formats. It takes an input string and converts it based on the selected mode, producing an output string with the specified case formatting applied. The node supports four different case conversion options to modify the capitalization of your text.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | The text string to be converted to a different case format | STRING | Yes | - |
| `mode` | The case conversion mode to apply (default: `"UPPERCASE"`) | STRING | Yes | `"UPPERCASE"`<br />`"lowercase"`<br />`"Capitalize"`<br />`"Title Case"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The input string converted to the specified case format | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CaseConverter/en.md)

***

**Source fingerprint (SHA-256):** `6cc933ec8a245ff454195b699ab7d72d2a014ec9a6e920a8c875acf7eb77e01a`


# ColorToRGBInt - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ColorToRGBInt

The ColorToRGBInt node converts a color given in hexadecimal format (like FF5733) into a single RGB integer value.

The **ColorToRGBInt** node converts a color given in hexadecimal format (like `#FF5733`) into a single RGB integer value. It extracts the red, green, and blue components from the color string, combines them into one integer, and also returns the original hexadecimal representation and the alpha (opacity) value.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `color` | A color value in the hexadecimal format `#RRGGBB` or `#RRGGBBAA`. Must be 7 or 9 characters long and start with `#`. | COLOR | Yes | `#RRGGBB`<br />`#RRGGBBAA` |

**Note:** The input `color` string must follow the format `#RRGGBB` or `#RRGGBBAA`. If it is not 7 or 9 characters long, does not start with `#`, or contains invalid hexadecimal characters, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `rgb_int` | The calculated RGB integer value, derived from the formula: `(Red * 65536) + (Green * 256) + Blue`. | INT |
| `hex` | The hexadecimal color string in the format `#RRGGBB`. If the input included an alpha channel, it is removed from this output. | COLOR |
| `alpha` | The alpha (opacity) value between 0.0 and 1.0. Equals 1.0 when the input is `#RRGGBB`, or the alpha channel value divided by 255 when the input is `#RRGGBBAA`. | FLOAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ColorToRGBInt/en.md)

***

**Source fingerprint (SHA-256):** `4e64616d168beee73bca4364d47e2a089418b5046a76bfcfa061dfab9a5e49ed`


# ComboOptionTestNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComboOptionTestNode

This node takes two combo box selections and passes them straight through to its outputs without changing them.

This node takes two combo box selections and passes them straight through to its outputs without changing them.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `combo` | The first selection, chosen from a set of three test options. | COMBO | Yes | `"option1"`<br />`"option2"`<br />`"option3"` |
| `combo2` | The second selection, chosen from a different set of three test options. | COMBO | Yes | `"option4"`<br />`"option5"`<br />`"option6"` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output_1` | Returns the value selected in the first combo box (`combo`), unchanged. | COMBO |
| `output_2` | Returns the value selected in the second combo box (`combo2`), unchanged. | COMBO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComboOptionTestNode/en.md)

***

**Source fingerprint (SHA-256):** `fe0b6a35680de55767af2c0d8a293010ddb4c4282cfdde7f9dff7a3a11ff1e5c`


# ComfyAndNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyAndNode

The And node performs a logical AND operation on a group of input values.

The And node performs a logical AND operation on a group of input values. It returns `true` only when every connected value is considered truthy according to Python's truthiness rules, which makes it useful for checking that several conditions are all met at the same time.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `values` | A growable group of values to evaluate. The node starts with one slot and you can add more by clicking the "+" button on the node. Accepts any data type. | ANY | Yes | Minimum 1 (no maximum) |

**Note:** This input is a growable slot group. Slots are added individually (for example `value_1`, `value_2`, and so on), and at least one slot must be present.

**Note:** The node uses Python's truthiness rules to decide whether a value is `true` or `false`. For example, an empty string, the number 0, an empty list, and `None` are all treated as `false`. All other values are treated as `true`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `BOOLEAN` | Returns `true` if all input values are truthy, otherwise returns `false`. | BOOLEAN |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyAndNode/en.md)

***

**Source fingerprint (SHA-256):** `e7359c46da62f9859ea4f4a239cf20c565b5f7de22d280afc00c7ca321f1c89d`


# ComfyMathExpression - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyMathExpression

The ComfyMathExpression node evaluates a mathematical formula that you write as text.

The ComfyMathExpression node evaluates a mathematical formula that you write as text. The formula can reference the node's input values using letter names such as `a`, `b`, `c`, and you can add as many input values as needed through the growable `values` group. The calculation result is returned simultaneously as a floating-point number, an integer, and a boolean value.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `expression` | The mathematical formula to evaluate, written as text (for example `a + b`), using the letter names of the input values as variables. Multiline input. (default: "a + b") | STRING | Yes | N/A |
| `values` | Growable group of input values that provides the variables for the expression. Each value added to the group automatically gets the next lowercase letter name starting at `a` (`a`, `b`, `c`, ...), and that name can then be used inside `expression`. Each item accepts a number (INT or FLOAT) or a boolean (TRUE/FALSE). | FLOAT, INT, BOOLEAN | Yes | 1 to 26 values, named `a` to `z` |

### Notes and constraints

* `expression` cannot be empty or contain only whitespace.
* The expression must evaluate to a numeric result (INT or FLOAT) or a boolean result (TRUE/FALSE). Boolean results are treated as 1 for TRUE and 0 for FALSE. If the result is a different type, such as text, the node raises an error.
* The numeric result must be finite and convertible to a float. Results that are too large or non-finite cause an error.
* The whole set of input values is also available inside the expression under the variable name `values` (as a list), so expressions such as `sum(values)` are possible.
* The following math functions are available inside the expression: `sum`, `min`, `max`, `abs`, `round`, `pow`, `sqrt`, `ceil`, `floor`, `log`, `log2`, `log10`, `sin`, `cos`, `tan`, `int`, `float`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `FLOAT` | The result of the expression as a floating-point number. | FLOAT |
| `INT` | The result of the expression converted to an integer, with the decimal part truncated. | INT |
| `BOOL` | The result converted to a boolean value: TRUE when the numeric result is not zero, FALSE when it is zero. | BOOLEAN |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyMathExpression/en.md)

***

**Source fingerprint (SHA-256):** `4c77e9834fe7341143352f95ed8808dc81def3361b197c67e33a531bb3696d71`


# ComfyNotNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyNotNode

The Not node performs a logical NOT operation on any input value.

The Not node performs a logical NOT operation on any input value. It returns True when the input value is considered falsy (such as 0, an empty string, None, or False) and returns False when the input value is truthy, following Python's standard rules for truthiness.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `value` | The input value to be inverted. Any data type is accepted and evaluated using Python's truthiness rules. | ANY | Yes | Any value |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The logical inverse of the input value. Returns True if the input is falsy, False if the input is truthy. | BOOLEAN |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyNotNode/en.md)

***

**Source fingerprint (SHA-256):** `24bbe667a0800b187d991b24894794e2ce710256200a2667ff391c1e644963a5`


# ComfyNumberConvert - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyNumberConvert

The Number Convert node transforms various input data types into numeric values.

The Number Convert node transforms various input data types into numeric values. It accepts a single input of type integer, float, string, or boolean and produces two outputs: a floating-point number and an integer. This is useful for converting text or logical values into a format that can be used by other mathematical or processing nodes in your workflow.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `value` | The value to be converted into numeric outputs. Accepts an integer, a floating-point number, a text string, or a true/false boolean. | INT, FLOAT, STRING, BOOLEAN | Yes | N/A |

**Note:** When the input is a string, it must not be empty and must contain a valid representation of a number (e.g., `"123"`, `"3.14"`). The node will raise an error for empty strings, text that cannot be parsed as a number, or values that are not finite (like `"inf"` or `"nan"`). For boolean inputs, `true` converts to 1.0 (FLOAT) and 1 (INT), while `false` converts to 0.0 (FLOAT) and 0 (INT). For float inputs and for strings that contain a decimal number, the integer output is obtained by truncating the decimal portion.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `FLOAT` | The input value converted to a floating-point number. | FLOAT |
| `INT` | The input value converted to an integer. For float inputs and decimal strings, this performs a truncation. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyNumberConvert/en.md)

***

**Source fingerprint (SHA-256):** `d6a774bf7c3ad9482b2275adc6ccc9e47c82b1f35f11c5a241b00efd29526f94`


# ComfyOrNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyOrNode

The Or node performs a logical OR operation on a set of input values.

The Or node performs a logical OR operation on a set of input values. It returns `true` if any of the provided values are considered truthy according to Python's standard truthiness rules.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `values` | A growable collection of values to evaluate for truthiness. Each added input slot is named `value_1`, `value_2`, and so on. The node returns `true` if any of these values is truthy. | ANY | Yes | 1 or more values |

**Note:** The node accepts a minimum of 1 input value. You can add more inputs as needed using the autogrow feature.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `BOOLEAN` | Returns `true` if any of the input values is truthy; returns `false` if all input values are falsy. | BOOLEAN |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyOrNode/en.md)

***

**Source fingerprint (SHA-256):** `f673aa2b0d754f55c51ba9c9ceea7d9de9a21d2e7308bd1281b4d4461243e4ad`


# ComfySoftSwitchNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfySoftSwitchNode

The Soft Switch node selects between two possible input values based on a boolean condition.

The Soft Switch node selects between two possible input values based on a boolean condition. It outputs the value from the `on_true` input when the `switch` is true, and the value from the `on_false` input when the `switch` is false. This node is designed to be lazy, meaning it only evaluates the input that is actually needed based on the switch state.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `switch` | The boolean condition that determines which input to pass through. When true, the `on_true` input is selected. When false, the `on_false` input is selected. | BOOLEAN | Yes | True or False |
| `on_false` | The value to output when the `switch` condition is false. This input is optional, but at least one of `on_false` or `on_true` must be connected. | MATCH\_TYPE | No | Same data type as `on_true` |
| `on_true` | The value to output when the `switch` condition is true. This input is optional, but at least one of `on_false` or `on_true` must be connected. | MATCH\_TYPE | No | Same data type as `on_false` |

**Note:** The `on_false` and `on_true` inputs must be of the same data type, as defined by the node's internal template. At least one of these two inputs must be connected, otherwise the node returns the validation message "At least one of on\_false or on\_true must be connected to Switch node". Because the node is lazy, when only one input is connected, the node always outputs that input's value regardless of the `switch` state.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The selected value. It matches the data type of the connected `on_false` or `on_true` input. When both inputs are connected, it outputs `on_true` if `switch` is true, and `on_false` if `switch` is false. | MATCH\_TYPE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfySoftSwitchNode/en.md)

***

**Source fingerprint (SHA-256):** `7bf4bed69d8fd8c360e971ab8068382cd8ebaa02004d5df44312977a7309ae00`


# ComfySwitchNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfySwitchNode

The If/Else Switch node selects between two possible inputs based on a boolean condition.

The If/Else Switch node selects between two possible inputs based on a boolean condition. When `switch` is enabled (true), it passes the `on_true` input through to the output; when disabled (false), it passes `on_false`. The inputs are lazy, so only the selected branch is evaluated and the other input does not need to be connected.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `switch` | A boolean condition that determines which input is passed to the output. When enabled (true), the `on_true` input is selected. When disabled (false), the `on_false` input is selected. | BOOLEAN | Yes | |
| `on_false` | The data to be passed to the output when `switch` is disabled (false). This input is requested only when `switch` is false. | MATCH\_TYPE | No | |
| `on_true` | The data to be passed to the output when `switch` is enabled (true). This input is requested only when `switch` is true. | MATCH\_TYPE | No | |

**Note on Input Requirements:** The `on_false` and `on_true` inputs are conditionally requested. The node asks for `on_true` only when `switch` is true, and asks for `on_false` only when `switch` is false. Both inputs must be of the same data type, and that type must match the output data type. If the selected input is not connected, the node outputs no value.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The selected data: the value from `on_true` when `switch` is true, or the value from `on_false` when `switch` is false. | MATCH\_TYPE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfySwitchNode/en.md)

***

**Source fingerprint (SHA-256):** `42c442efeda0197d950702c52647233dee1a30216fb07e1ce4bc844784a6c5f2`


# ConvertArrayToString - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConvertArrayToString

The Convert Array to String node takes an array (list) of items and converts it into a formatted JSON string.

The Convert Array to String node takes an array (list) of items and converts it into a formatted JSON string. This is useful when you need to serialize array data for display, logging, or passing to other systems that expect string input.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `array` | The array to convert to a JSON string | ARRAY | Yes | - |
| `indent` | Spaces per indent level. 0 produces compact single-line string (default: 2) | INT | No | 0 to 8 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `STRING` | The array converted to a JSON-formatted string | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConvertArrayToString/en.md)

***

**Source fingerprint (SHA-256):** `ac8397fed0336f546403ee3e1f17d7e8f5973190b102e74943f098bf6905f726`


# ConvertDictionaryToString - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConvertDictionaryToString

This node converts a dictionary (a collection of key-value pairs) into a text string in JSON format.

This node converts a dictionary (a collection of key-value pairs) into a text string in JSON format. You can control the indentation level to make the output more readable or compact.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `dictionary` | The dictionary to convert to a string | DICT | Yes | - |
| `indent` | Spaces per indent level. 0 produces compact single-line string (default: 2) | INT | No | 0 to 8 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `STRING` | The dictionary converted to a JSON-formatted string | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConvertDictionaryToString/en.md)

***

**Source fingerprint (SHA-256):** `ae4e9889d5347acfc69166bac66f2ba63f5cd37dafab25a9e0aff6bfe7381219`


# ConvertStringToComboNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConvertStringToComboNode

The Convert String to Combo node takes a text string as input and converts it into a Combo data type.

The Convert String to Combo node takes a text string as input and converts it into a Combo data type. This allows you to use a text value as a selection for other nodes that require a Combo input. It simply passes the string value through unchanged but changes its data type.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | The text string to be converted into a Combo type. | STRING | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The input string, now formatted as a Combo data type. | COMBO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConvertStringToComboNode/en.md)

***

**Source fingerprint (SHA-256):** `39bec69dccf4598aff0ae76ad5d68ae60d352ca464cfe54858fc1592ac923f13`


# CreateBoundingBoxes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateBoundingBoxes

This node provides a canvas interface for drawing bounding boxes around objects or text regions in an image.

This node provides a canvas interface for drawing bounding boxes around objects or text regions in an image. It outputs the bounding box coordinates in pixel space, structured element data compatible with Ideogram prompt formatting, and a preview image showing the drawn boxes with labels and color palettes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `background` | Optional image used as background in the canvas and preview. | IMAGE | No | - |
| `bboxes` | Bounding boxes, elements, or a JSON string to initialize the canvas. A new upstream value initializes the canvas; edits made on the canvas take priority and are kept until the upstream value changes again. | BOUNDING\_BOX, ARRAY, STRING | No | - |
| `width` | Width of the canvas and the pixel grid for the bounding boxes (default: 1024). | INT | Yes | 64 to 16384 (step: 16) |
| `height` | Height of the canvas and the pixel grid for the bounding boxes (default: 1024). | INT | Yes | 64 to 16384 (step: 16) |
| `editor_state` | Draw bounding boxes and set each box type, text, description, color palette. Start with background element first and foreground last. | BOUNDING\_BOXES | Yes | - |
| `last_incoming` | Internal state managed by the canvas: the upstream bboxes value that last initialized it. Leave empty to re-initialize the canvas from the bboxes input on the next run. | BOUNDING\_BOXES | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `preview` | An RGB image showing the canvas with all bounding boxes rendered, including labels, color palette swatches, and descriptive text. | IMAGE |
| `bboxes` | A list of bounding boxes in pixel coordinates, with each box containing x, y, width, and height values. | BOUNDING\_BOX |
| `elements` | A structured array of element objects, each containing type, bounding box coordinates (normalized 0-1000), text (for text type), description, and color palette. | ARRAY |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateBoundingBoxes/en.md)

***

**Source fingerprint (SHA-256):** `dc5545dffefdccf14f3919ff4d9966dbfd1a497dcd64e1863556d5728659ee94`


# CreateList - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateList

The Create List node combines multiple inputs into a single, sequential list.

The Create List node combines multiple inputs into a single, sequential list. It accepts any number of input slots that share the same data type and concatenates their items in the order the slots are connected. The result is one list containing all connected items.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `inputs` | A variable number of input slots named `input`, `input_2`, `input_3`, and so on. Each slot accepts a list of items of the same data type (for example, all IMAGE or all STRING). New slots are created automatically as needed. The node concatenates the lists in slot order. | Any | Yes | Any number of slots; each slot accepts any number of items |

**Note:** All connected inputs must share the same data type. Each connected slot provides a list of items, and the node combines the lists in slot order (`input`, then `input_2`, then `input_3`, ...). The node is also searchable under the aliases "Image Iterator", "Text Iterator", and "Iterator".

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `list` | A single list containing all items from the connected inputs, concatenated in the order the slots were provided. The output data type matches the input data type. | Any |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateList/en.md)

***

**Source fingerprint (SHA-256):** `4824fa6af46ab08cd3c10b033dbb3e43682b468e1dbd934fffb571349e025b96`


# CurveEditor - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CurveEditor

The Curve Editor node provides a visual interface for adjusting and fine-tuning a curve.

The Curve Editor node provides a visual interface for adjusting and fine-tuning a curve. You can modify the shape of an input curve directly in the node's interface and optionally display a histogram alongside it for visual reference. The node supports intermediate output during editing, allowing you to see live results as you make changes, and outputs the modified curve for use in other parts of your workflow.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `curve` | The input curve to be edited. | CURVE | Yes | N/A |
| `histogram` | An optional histogram to display alongside the curve for visual reference. | HISTOGRAM | No | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `curve` | The edited curve after adjustments have been made in the node's interface. | CURVE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CurveEditor/en.md)

***

**Source fingerprint (SHA-256):** `6c4459998b1a3dd3a53f84cb1c231c448c64aa55b96444bc4ac7470556a3b915`


# DCTestNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DCTestNode

DCTestNode is a logic node that returns different types of data based on a user's selection from a dynamic combo box.

DCTestNode is a logic node that returns different types of data based on a user's selection from a dynamic combo box. It acts as a conditional router, where the chosen option determines which input field is active and what type of value the node will output. The node is flagged as an output node in ComfyUI.

## Inputs

The node uses a dynamic combo selector: the `combo` parameter is always visible, and the other input fields appear only when their corresponding option is selected.

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `combo` | The main selection that determines which input field is active and what the node will output. | DYNAMIC\_COMBO | Yes | `"option1"`<br />`"option2"`<br />`"option3"`<br />`"option4"` |

### option1 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | A text input field. This field is only active and required when `combo` is set to `"option1"`. | STRING | Yes | - |

### option2 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `integer` | A whole number input field. This field is only active and required when `combo` is set to `"option2"`. | INT | Yes | - |

### option3 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | An image input field. This field is only active and required when `combo` is set to `"option3"`. | IMAGE | Yes | - |

### option4 Inputs

When `combo` is set to `"option4"`, the node shows a second dynamic combo selector (`subcombo`) that controls a nested set of input fields.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `subcombo` | A secondary dynamic combo selection that appears when `combo` is set to `"option4"`. It determines which nested input fields are active. | DYNAMIC\_COMBO | Yes | `"opt1"`<br />`"opt2"` |
| `float_x` | A decimal number input. This field is only active and required when `combo` is set to `"option4"` and `subcombo` is set to `"opt1"`. | FLOAT | Yes | - |
| `float_y` | A decimal number input. This field is only active and required when `combo` is set to `"option4"` and `subcombo` is set to `"opt1"`. | FLOAT | Yes | - |
| `mask1` | A mask input field. This field is only active when `combo` is set to `"option4"` and `subcombo` is set to `"opt2"`. It is optional. | MASK | No | - |

**Parameter Constraints:**

* The `combo` parameter controls the visibility and requirement of all other input fields. Only the inputs associated with the selected `combo` option will be shown and are required (except for `mask1`, which is optional).
* When `combo` is set to `"option4"`, the `subcombo` parameter becomes required and controls a second set of nested inputs (`float_x`/`float_y` or `mask1`).
* If `combo` receives a value that is not one of the four listed options, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The output depends on the selected `combo` option. It can be a STRING (`"option1"`), an INT (`"option2"`), an IMAGE (`"option3"`), or a string representation of the `subcombo` value (`"option4"`). | ANYTYPE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DCTestNode/en.md)

***

**Source fingerprint (SHA-256):** `9dd616a427a56eddb78b48d6eea6f71419b7097d417afae5557132b333641e69`


# EndLoop - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EndLoop

End Loop marks the end of a loop block.

End Loop marks the end of a loop block. It collects the value produced by the last node in the loop body and returns either only the final iteration or every iteration, depending on the `accumulate` setting, while also passing a value back to Start Loop so the next iteration can begin.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `output_value` | Value returned by End Loop. It returns the final iteration or all iterations according to accumulate. | ANY | No | Any value type |
| `next_iteration_value` | Value sent from End Loop back to Start Loop for the next iteration. | ANY | No | Any value type |
| `accumulate` | Return output\_value from every iteration when enabled; otherwise return only the final iteration. | BOOLEAN | No | `true`<br />`false` (default: `false`) |
| `terminations` | Connect outputs that must execute on every iteration. Their values are not returned. Growable slots named `termination_1`, `termination_2`, and so on. | ANY | No | 0 to 50 slots |

Note: `terminations` is a growable list of slots with a minimum of 0 and a maximum of 50 connections. Values connected here force execution on every iteration but are not part of the returned result.

Note: This node is an input list node, so its inputs receive the collected values from every loop iteration.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `outputs` | The final iteration's output\_value, or values accumulated across iterations when accumulate is enabled. | ANY (list) |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EndLoop/en.md)

***

**Source fingerprint (SHA-256):** `142840dca7f238eb00c72074d265478c548ad5c047e05744d0c3715e452f795a`


# HappyHorseImageToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HappyHorseImageToVideoApi

This node generates a short video from a single starting image using the HappyHorse model.

This node generates a short video from a single starting image using the HappyHorse model. You provide a first frame image and a text prompt describing the desired motion and scene, and the node creates a video that continues from that image.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The HappyHorse model to use for video generation. | DYNAMIC\_COMBO | Yes | `"happyhorse-1.1-i2v"`<br />`"happyhorse-1.0-i2v"` |
| `first_frame` | First frame image. The output aspect ratio is derived from this image. | IMAGE | Yes | 300×300 px min; 1:2.5 to 2.5:1 |
| `seed` | Seed to use for generation. (default: 0) | INT | Yes | 0 to 2147483647 |
| `watermark` | Whether to add an AI-generated watermark to the result. (advanced option; default: False) | BOOLEAN | Yes | True / False |

### happyhorse-1.1-i2v and happyhorse-1.0-i2v Inputs

Both model versions share the same set of parameters.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese. (default: "") | STRING | No | N/A |
| `resolution` | The output video resolution. (default: `"720P"`) | COMBO | Yes | `"720P"`<br />`"1080P"` |
| `duration` | The duration of the generated video in seconds. (default: 5) | INT | Yes | 3 to 15 |

Note: The `first_frame` image must be at least 300x300 pixels, and its aspect ratio must be between 1:2.5 and 2.5:1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HappyHorseImageToVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `4bf6eece0d1b4104ce2d84e29b2c918a0a6ba782da1dd801b66cbfa1666d150b`


# HappyHorseReferenceVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HappyHorseReferenceVideoApi

This node generates a video featuring a person or object from reference images using the HappyHorse model.

This node generates a video featuring a person or object from reference images using the HappyHorse model. It supports single-character performances and multi-character interactions. The reference images are uploaded and used to represent the characters in the generated video.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The HappyHorse reference-to-video model to use for generation. | DYNAMIC\_COMBO | Yes | `"happyhorse-1.1-r2v"`<br />`"happyhorse-1.0-r2v"` |
| `seed` | Seed to use for generation (default: 0). Can be set to automatically change after each generation. | INT | Yes | 0 to 2147483647 |
| `watermark` | Whether to add an AI-generated watermark to the result (default: False). | BOOLEAN | Yes | True or False |

### HappyHorse 1.1 Inputs (happyhorse-1.1-r2v)

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the video. Use identifiers such as 'character1' and 'character2' to refer to the reference characters. | STRING | Yes | N/A |
| `resolution` | The resolution of the generated video. | COMBO | Yes | `"720P"`<br />`"1080P"` |
| `ratio` | The aspect ratio of the generated video. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"`<br />`"21:9"`<br />`"9:21"`<br />`"5:4"`<br />`"4:5"` |
| `duration` | The duration of the generated video in seconds (default: 5). | INT | Yes | 3 to 15 |

### HappyHorse 1.0 Inputs (happyhorse-1.0-r2v)

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the video. Use identifiers such as 'character1' and 'character2' to refer to the reference characters. | STRING | Yes | N/A |
| `resolution` | The resolution of the generated video. | COMBO | Yes | `"720P"`<br />`"1080P"` |
| `ratio` | The aspect ratio of the generated video. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"` |
| `duration` | The duration of the generated video in seconds (default: 5). | INT | Yes | 3 to 15 |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect 1 to 9 reference images of the person or object to feature in the video. At least one reference image must be provided. | IMAGE | Yes | 1 to 9 (per model) |

Note: At least one reference image must be provided, otherwise the node raises an error. Each reference image must be at least 400 x 400 pixels and have an aspect ratio between 1:2.5 and 2.5:1. The prompt must not be empty.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `VIDEO` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HappyHorseReferenceVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `252c918afc4cf38be9c7d09b7112075b9adb23490ec9fed1717a8548519d2554`


# HappyHorseTextToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HappyHorseTextToVideoApi

Generates a video based on a text prompt using the HappyHorse model.

Generates a video based on a text prompt using the HappyHorse model. This node sends your prompt and settings to the HappyHorse API, waits for the video to be generated, and then downloads the result.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The HappyHorse model used for generation, along with its sub-parameters. Selecting a model determines which sub-parameters are available (see the model sections below). | DYNAMIC\_COMBO | Yes | "happyhorse-1.1-t2v"<br />"happyhorse-1.0-t2v" |
| `seed` | Seed to use for generation. Using the same seed with the same inputs will produce the same result. (default: 0). | INT | Yes | 0 to 2147483647 |
| `watermark` | Whether to add an AI-generated watermark to the result. (default: False). | BOOLEAN | Yes | True / False |

### happyhorse-1.1-t2v Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese. (default: ""). | STRING | Yes | - |
| `resolution` | The resolution of the output video. | COMBO | Yes | "720P"<br />"1080P" |
| `ratio` | The aspect ratio of the output video. | COMBO | Yes | "16:9"<br />"9:16"<br />"1:1"<br />"4:3"<br />"3:4"<br />"21:9"<br />"9:21"<br />"5:4"<br />"4:5" |
| `duration` | The length of the video in seconds. (default: 5, min: 3, max: 15, step: 1). | INT | Yes | 3 to 15 |

### happyhorse-1.0-t2v Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese. (default: ""). | STRING | Yes | - |
| `resolution` | The resolution of the output video. | COMBO | Yes | "720P"<br />"1080P" |
| `ratio` | The aspect ratio of the output video. | COMBO | Yes | "16:9"<br />"9:16"<br />"1:1"<br />"4:3"<br />"3:4" |
| `duration` | The length of the video in seconds. (default: 5, min: 3, max: 15, step: 1). | INT | Yes | 3 to 15 |

Note: The prompt must not be empty; an error is raised if no prompt is provided. Both models support video durations from 3 to 15 seconds. The `happyhorse-1.1-t2v` model offers additional aspect ratios (`21:9`, `9:21`, `5:4`, `4:5`) that are not available with `happyhorse-1.0-t2v`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `VIDEO` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HappyHorseTextToVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `b60cfc3ce4935d7eb36bb28f9bd268446c4df5b437e06278b7e6d91d349d0238`


# HappyHorseVideoEditApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HappyHorseVideoEditApi

Edit a video using text instructions or reference images with the HappyHorse model.

Edit a video using text instructions or reference images with the HappyHorse model. Output duration is 3-15 seconds and matches the input video; inputs longer than 15 seconds are truncated.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The HappyHorse video editing model to use. This selection determines which prompt, resolution, ratio, and reference image options are available. | DYNAMIC\_COMBO | Yes | "happyhorse-1.0-video-edit" |
| `video` | The video to edit. | VIDEO | Yes | 3 to 60 seconds |
| `seed` | Seed to use for generation (default: 0). | INT | Yes | 0 to 2147483647 |
| `watermark` | Whether to add an AI-generated watermark to the result (default: False). Advanced parameter. | BOOLEAN | Yes | True<br />False |

### happyhorse-1.0-video-edit Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Editing instructions or style transfer requirements. Must be at least 1 character long. | STRING | Yes | - |
| `resolution` | The output resolution. | COMBO | Yes | "720P"<br />"1080P" |
| `ratio` | Aspect ratio. If not changed, approximates the input video ratio. | COMBO | Yes | "16:9"<br />"9:16"<br />"1:1"<br />"4:3"<br />"3:4" |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect 0 to 5 reference images (`image1`...`image5`) to guide the edit. | IMAGE | No | 0 to 5 images |

**Note:** The input video must be 3 to 60 seconds long. The output duration is 3-15 seconds and matches the input video; input videos longer than 15 seconds are truncated. The `prompt` must be at least 1 character long.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The edited video output. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HappyHorseVideoEditApi/en.md)

***

**Source fingerprint (SHA-256):** `396cad4b5a06d457746a421050df98c892fa9db6019e3de983b4d0c417842b57`


# InvertBooleanNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/InvertBooleanNode

This node takes a single boolean (true/false) input and outputs the opposite value.

This node takes a single boolean (true/false) input and outputs the opposite value. It performs a logical NOT operation, turning `true` into `false` and `false` into `true`.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `boolean` | The input boolean value to be inverted. | BOOLEAN | Yes | `true`<br />`false` |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The inverted boolean value. | BOOLEAN |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/InvertBooleanNode/en.md)

***

**Source fingerprint (SHA-256):** `7e28bb375a25249bc237870bf281321375c4be7b7782b217b3e0f70afc2e0c53`


# JsonExtractString - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/JsonExtractString

The JsonExtractString node scans a text string for the first valid JSON object and extracts the value associated with a specific key, converted to a string.

The JsonExtractString node scans a text string for the first valid JSON object and extracts the value associated with a specific key, converted to a string. Any text before or after the JSON object is ignored, so the node also works on Markdown code blocks and on model replies that wrap the JSON in extra prose. If no valid JSON object is found, the key is not found, or the value is null, the node returns an empty string.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `json_string` | The text to search for a JSON object. This field supports multiline input and may contain surrounding prose or Markdown code fences. | STRING | Yes | N/A |
| `key` | The specific key whose value you want to extract from the JSON object. This field supports single-line input only. | STRING | Yes | N/A |

**Note:** The node extracts values only from JSON objects (dictionaries). It tries each `{` in the input in order and decodes from the first position that yields a valid JSON object, so leading or trailing text is skipped. If no JSON object can be decoded or the specified key does not exist within it, the output is an empty string. If the value associated with the key is `null`, the node also returns an empty string. Values that are not strings are returned as their string representation.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The string value extracted from the JSON for the specified key, or an empty string if the extraction fails. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/JsonExtractString/en.md)

***

**Source fingerprint (SHA-256):** `ca697fd3bd2d4de764372470ad1102b345d9d60f6df1c151fa0573e85fab2382`


# MergeTextLists - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MergeTextLists

This node merges multiple text lists into a single, combined list.

This node merges multiple text lists into a single, combined list. It is designed to receive text inputs as lists and concatenates them together. The node logs the total number of texts in the merged list.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `texts` | The text lists to be merged. Multiple lists can be connected to the input, and they will be concatenated into one. | STRING | Yes | N/A |

**Note:** This node is configured as a group process (`is_group_process = True`), meaning it automatically handles multiple list inputs by concatenating them before the main processing function runs.

**Note:** This node is deprecated and superseded by the Create List node.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `texts` | The single, merged list containing all the input texts. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MergeTextLists/en.md)

***

**Source fingerprint (SHA-256):** `bb7f45725c2c41a18d8cd3040d093c11be2ceb03cf1849385aa55d12fd9eb555`


# OpenAIVideoSora2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIVideoSora2

The OpenAIVideoSora2 node generates videos with OpenAI's Sora models.

The OpenAIVideoSora2 node generates videos with OpenAI's Sora models. It takes a text prompt along with an optional single reference image, sends the request to OpenAI, waits for generation to finish, and returns the resulting video. Supported durations and resolutions depend on the selected model.

**DEPRECATION NOTICE:** OpenAI will stop serving the Sora v2 API in September 2026. This node will be removed from ComfyUI at that time.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The OpenAI Sora model to use for video generation (default: "sora-2") | COMBO | Yes | "sora-2"<br />"sora-2-pro" |
| `prompt` | Guiding text; may be empty if an input image is present (default: empty string) | STRING | Yes | - |
| `size` | The resolution of the generated video (default: "1280x720") | COMBO | Yes | "720x1280"<br />"1280x720"<br />"1024x1792"<br />"1792x1024" |
| `duration` | The duration of the generated video in seconds (default: 8) | COMBO | Yes | 4<br />8<br />12 |
| `image` | Optional input reference image used for video generation; only a single image is supported | IMAGE | No | - |
| `seed` | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0) | INT | No | 0 to 2147483647 |

**Constraints and Limitations:**

* The "sora-2" model only supports the "720x1280" and "1280x720" sizes; selecting "1024x1792" or "1792x1024" with "sora-2" raises an error. The larger sizes are available only with "sora-2-pro".
* When an image is connected, it must contain exactly one image; connecting more than one image raises an error.
* Results are nondeterministic regardless of the seed value.
* The displayed price estimate depends on the selected `model`, `size`, and `duration`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video from OpenAI Sora | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIVideoSora2/en.md)

***

**Source fingerprint (SHA-256):** `d19eb6b65d7f712278828e4b1f7105068cc5e7cb72813b7549ab24520e7719fc`


# PixverseV6ImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseV6ImageToVideoNode

This node animates an input image with the PixVerse V6 model and returns a video, optionally with a native audio track.

This node animates an input image with the PixVerse V6 model and returns a video, optionally with a native audio track. The output video keeps the aspect ratio of the input image.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to animate. | IMAGE | Yes | Single image |
| `model` | Model and generation settings. | DYNAMIC\_COMBO | Yes | "PixVerse V6" |

### PixVerse V6 Inputs

These settings appear when the "PixVerse V6" model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the video generation (default: empty). | STRING | Yes | 1 to 5000 characters |
| `quality` | Output resolution. Sets the long edge: 360p is 640px, 540p 1024px, 720p 1280px, 1080p 1920px (default: "720p"). | COMBO | Yes | "360p"<br />"540p"<br />"720p"<br />"1080p" |
| `duration_seconds` | Length of the generated video in seconds (default: 5). | INT | Yes | 1 to 15 |
| `generate_audio` | Generate a native audio track together with the video (default: true). | BOOLEAN | Yes | true or false |
| `multi_clip` | Let the model cut the video into several shots instead of one continuous take (default: false). | BOOLEAN | Yes | true or false |
| `seed` | Seed for video generation. PixVerse records it but does not reproduce a run from it (default: 42, control after generate is enabled). | INT | Yes | 0 to 2147483647 |
| `negative_prompt` | An optional text description of undesired elements in the video (default: empty). | STRING | No | Up to 2048 characters |
| `style` | An optional visual style applied to the whole video (default: none). | COMBO | No | Multiple options available (PixVerse V6 style presets) |

Note: The prompt must contain at least one non-whitespace character and at most 5000 characters; the negative prompt, if provided, must be at most 2048 characters. The output video always matches the aspect ratio of the input image, so no aspect ratio setting is needed. Only a single input image is accepted. PixVerse may reject a request when content moderation fails, when the provider account is out of credits, or when the maximum number of simultaneous generations is already running.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video, including the native audio track when `generate_audio` is enabled. The aspect ratio matches the input image. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseV6ImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `6ecf958e510e7afc43f5f0e4e5dfd2b789aea02bec882d928326732501cee7b3`


# PixverseV6TextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseV6TextToVideoNode

PixVerse V6 Text to Video generates a video from a text prompt using PixVerse's V6 model.

PixVerse V6 Text to Video generates a video from a text prompt using PixVerse's V6 model. The node sends the prompt along with your chosen aspect ratio, resolution, duration, and other settings to PixVerse, waits for the generation to finish, and then returns the resulting video — including a native audio track when audio generation is enabled.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model and generation settings. Select the model and configure its generation options. | DYNAMIC\_COMBO | Yes | "PixVerse V6" |

### PixVerse V6 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt for the video generation. (default: "") | STRING | Yes | 1–5000 characters |
| `aspect_ratio` | Output aspect ratio. Select one of the aspect ratios supported by PixVerse V6. | COMBO | Yes | Multiple options available |
| `quality` | Output resolution. Sets the long edge: 360p is 640px, 540p 1024px, 720p 1280px, 1080p 1920px. (default: "720p") | COMBO | Yes | "360p"<br />"540p"<br />"720p"<br />"1080p" |
| `duration_seconds` | Length of the generated video in seconds. (default: 5) | INT | Yes | 1–15 |
| `generate_audio` | Generate a native audio track together with the video. (default: True) | BOOLEAN | Yes | True<br />False |
| `multi_clip` | Let the model cut the video into several shots instead of one continuous take. (default: False) | BOOLEAN | Yes | True<br />False |
| `seed` | Seed for video generation. PixVerse records it but does not reproduce a run from it. Supports randomization after generation. (default: 42) | INT | Yes | 0–2147483647 |
| `negative_prompt` | An optional text description of undesired elements in the video. (default: "") | STRING | No | 0–2048 characters |
| `style` | An optional visual style applied to the whole video. (default: "none") | COMBO | No | Multiple options available |

**Note:** The `prompt` is required and, after trimming whitespace, must not be empty; its maximum length is 5000 characters. The `negative_prompt` is limited to 2048 characters. Setting `style` to "none" (the default) means no visual style is applied. The `seed` is recorded by PixVerse but cannot be used to reproduce the same run. The node waits for PixVerse to finish generating the video and then downloads it; if the request fails — for example because PixVerse is already at its maximum number of simultaneous generations, the provider account is out of credits, or content moderation rejects the prompt — the node returns an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `VIDEO` | The generated video. If `generate_audio` is enabled, the video includes the native audio track. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseV6TextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `4c268be9720a4606e77a9347570ac26b489625fc6b9528b9d3cceb4497d8683b`


# PrimitiveBoolean - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveBoolean

The Boolean node passes a boolean (true/false) value through your workflow.

The Boolean node passes a boolean (true/false) value through your workflow. It takes a boolean input and returns the same value unchanged, so you can feed a true/false setting into other nodes that need one.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `value` | The boolean value to pass through the node | BOOLEAN | Yes | true<br />false |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The same boolean value that was provided as input | BOOLEAN |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveBoolean/en.md)

***

**Source fingerprint (SHA-256):** `2f4bd009a927f0c7f511db3455e74d3dfc7eb54f642cda1aa3159d495b6452db`


# PrimitiveBoundingBox - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveBoundingBox

The PrimitiveBoundingBox node creates a simple rectangular area defined by its position and size.

The PrimitiveBoundingBox node creates a simple rectangular area defined by its position and size. It takes X and Y coordinates for the top-left corner, along with width and height values, and outputs a bounding box data structure that can be used by other nodes in a workflow.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `x` | The X-coordinate for the top-left corner of the bounding box (default: 0). | INT | Yes | 0 to 16384 |
| `y` | The Y-coordinate for the top-left corner of the bounding box (default: 0). | INT | Yes | 0 to 16384 |
| `width` | The width of the bounding box (default: 512). | INT | Yes | 1 to 16384 |
| `height` | The height of the bounding box (default: 512). | INT | Yes | 1 to 16384 |

Note: All maximum values follow ComfyUI's MAX\_RESOLUTION constant, which defines the largest image dimension the node accepts.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `bounding_box` | A data structure containing the `x`, `y`, `width`, and `height` properties of the defined rectangle. | BOUNDING\_BOX |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveBoundingBox/en.md)

***

**Source fingerprint (SHA-256):** `dc50286b09b8aaf7ff21eb699b9a04317f099b3deedb6cb7d4a1ec7668edeb97`


# PrimitiveFloat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveFloat

The PrimitiveFloat node creates a floating-point number value that can be used in your workflow.

The PrimitiveFloat node creates a floating-point number value that can be used in your workflow. It takes a single numeric input and outputs that same value, allowing you to define and pass float values between different nodes in your ComfyUI pipeline.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `value` | The floating-point number value to output (default: 0.0) | FLOAT | Yes | -sys.maxsize to sys.maxsize (step: 0.1) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The input floating-point number value | FLOAT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveFloat/en.md)

***

**Source fingerprint (SHA-256):** `df57e5900e972e17da365fbbdb7b7db777dda6f9f938e1074f1a89451d4b7c73`


# PrimitiveInt - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveInt

The PrimitiveInt node provides a simple way to work with integer values in your workflow.

The PrimitiveInt node provides a simple way to work with integer values in your workflow. It takes an integer input and outputs the same value, making it useful for passing integer parameters between nodes or setting specific numeric values for other operations.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `value` | The integer value to output (default: 0). The value stays fixed and does not change automatically after generation. | INT | Yes | -9223372036854775807 to 9223372036854775807 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The input integer value passed through unchanged | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveInt/en.md)

***

**Source fingerprint (SHA-256):** `b928ec40c781043c1c8652de3aebedc755d9b63be9e2c773e3fb26ce4d594bba`


# PrimitiveString - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveString

The Text node provides a simple way to input and pass through text data in your workflow.

The Text node provides a simple way to input and pass through text data in your workflow. It takes a text string as input and outputs the same string unchanged, making it useful for providing text inputs to other nodes that require string parameters.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `value` | The text string to be passed through the node | STRING | Yes | Any text |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The same text string that was provided as input | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveString/en.md)

***

**Source fingerprint (SHA-256):** `0f5276c386bc1cb62ade2b5d29b45126e7ec9e116b1b9cc76b207a76d5dbbb0d`


# PrimitiveStringMultiline - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveStringMultiline

The Text (Multiline) node provides a multiline text input field for entering and passing string values through your workflow.

The Text (Multiline) node provides a multiline text input field for entering and passing string values through your workflow. It accepts text that spans multiple lines and outputs the same string value unchanged. This node is useful when you need to provide longer text content or formatted, multi-line text.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `value` | The text input value that can span multiple lines | STRING | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The same string value that was provided as input | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveStringMultiline/en.md)

***

**Source fingerprint (SHA-256):** `7e50ab0c4adfb68b3fe2ad4e31f9dec059224555d68cd53335f89ff0b83a83b6`


# PrunaImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrunaImageToVideoNode

Animates an image into a video with Pruna's P-Video-2 model.

Animates an image into a video with Pruna's P-Video-2 model. The first frame is required and fixes the aspect ratio of the output; an optional last frame gives the video an end point to interpolate towards. The prompt describes how the scene moves, and the node either generates its own soundtrack or takes an audio clip that drives the motion.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Pruna video model to use. Selecting a model reveals its own inputs below. | DYNAMIC\_COMBO | Yes | `"p-video-2"` |

### P-Video-2 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.first_frame` | Image the video starts from. The output keeps the aspect ratio of this image. | IMAGE | Yes | - |
| `model.last_frame` | Image the video ends on. Its aspect ratio must be close to the first frame's. | IMAGE | No | - |
| `model.prompt` | Describes how the scene moves and sounds. Must contain at least one non-whitespace character, up to 5000 characters (default: empty). | STRING | Yes | Up to 5000 characters |
| `model.duration` | Length of the video in seconds. `"auto"` lets the model choose the length from the prompt. Ignored when `model.audio` is connected: the video then follows the audio length, rounded up to a whole second, up to 20 seconds (default: `"5"`). | COMBO | Yes | `"auto"`<br />`"1"`<br />`"2"`<br />`"3"`<br />`"4"`<br />`"5"`<br />`"6"`<br />`"7"`<br />`"8"`<br />`"9"`<br />`"10"`<br />`"11"`<br />`"12"`<br />`"13"`<br />`"14"`<br />`"15"`<br />`"16"`<br />`"17"`<br />`"18"`<br />`"19"`<br />`"20"` |
| `model.resolution` | Output resolution. 720p renders about 0.9 megapixels (1280x704 at 16:9), 1080p about 2 megapixels (1920x1088 at 16:9) (default: `"720p"`). | COMBO | Yes | `"720p"`<br />`"1080p"` |
| `model.fps` | Frames per second. 48 fps is not available with draft at 1080p (default: `"24"`). | COMBO | Yes | `"24"`<br />`"48"` |
| `model.draft` | Faster, less detailed render, billed at a lower rate than a standard render (default: False). | BOOLEAN | Yes | True/False |
| `model.generate_audio` | Generate a soundtrack for the video. Ignored when `model.audio` is connected, which becomes the soundtrack instead (default: True). | BOOLEAN | Yes | True/False |
| `model.enhance_prompt` | Rewrite the prompt with more detail before generation; short prompts need it. Turn it off to reproduce a result exactly with the same seed (default: True). Advanced setting. | BOOLEAN | Yes | True/False |
| `model.audio` | Audio that drives the motion and becomes the soundtrack. At least 1 second long; audio longer than 20 seconds is truncated. Sets the video length instead of `model.duration`. | AUDIO | No | - |
| `model.seed` | Seed for the generation. The same seed reproduces a result exactly only when `model.enhance_prompt` is off (default: 42). | INT | Yes | 0 to 2147483647 |

**Notes:**

* `model.first_frame` is required and fixes the output aspect ratio, so this node has no aspect ratio input.
* `model.last_frame` is optional, but its aspect ratio has to be close to the first frame's or the node raises an error.
* `model.prompt` is required and limited to 5000 characters.
* Draft at 1080p cannot be combined with 48 fps: the node raises an error, so either turn draft off or use 24 fps.
* Connected audio must be at least 1 second long; anything past 20 seconds is ignored.
* With `model.audio` connected the audio sets the video length, so `model.duration` and `model.generate_audio` have no effect.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video with its soundtrack. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrunaImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `da8952e478eee593543fa7ae1aa329ad5bd5078024f905cdba185d18e76db130`


# PrunaTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrunaTextToVideoNode

Generates a video from a text prompt with Pruna's P-Video-2 model.

Generates a video from a text prompt with Pruna's P-Video-2 model. The prompt describes the scene, its motion and its sound, and the node either generates its own soundtrack or takes an audio clip that drives the motion and becomes the soundtrack.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Pruna video model to use. Selecting a model reveals its own inputs below. | DYNAMIC\_COMBO | Yes | `"p-video-2"` |

### P-Video-2 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model.prompt` | Describes the video, its motion and its sound. Must contain at least one non-whitespace character, up to 5000 characters (default: empty). | STRING | Yes | Up to 5000 characters |
| `model.aspect_ratio` | Aspect ratio of the output video (default: `"16:9"`). | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"4:3"`<br />`"3:4"`<br />`"3:2"`<br />`"2:3"`<br />`"1:1"` |
| `model.duration` | Length of the video in seconds. `"auto"` lets the model choose the length from the prompt. Ignored when `model.audio` is connected: the video then follows the audio length, rounded up to a whole second, up to 20 seconds (default: `"5"`). | COMBO | Yes | `"auto"`<br />`"1"`<br />`"2"`<br />`"3"`<br />`"4"`<br />`"5"`<br />`"6"`<br />`"7"`<br />`"8"`<br />`"9"`<br />`"10"`<br />`"11"`<br />`"12"`<br />`"13"`<br />`"14"`<br />`"15"`<br />`"16"`<br />`"17"`<br />`"18"`<br />`"19"`<br />`"20"` |
| `model.resolution` | Output resolution. 720p renders about 0.9 megapixels (1280x704 at 16:9), 1080p about 2 megapixels (1920x1088 at 16:9) (default: `"720p"`). | COMBO | Yes | `"720p"`<br />`"1080p"` |
| `model.fps` | Frames per second. 48 fps is not available with draft at 1080p (default: `"24"`). | COMBO | Yes | `"24"`<br />`"48"` |
| `model.draft` | Faster, less detailed render, billed at a lower rate than a standard render (default: False). | BOOLEAN | Yes | True/False |
| `model.generate_audio` | Generate a soundtrack for the video. Ignored when `model.audio` is connected, which becomes the soundtrack instead (default: True). | BOOLEAN | Yes | True/False |
| `model.enhance_prompt` | Rewrite the prompt with more detail before generation; short prompts need it. Turn it off to reproduce a result exactly with the same seed (default: True). Advanced setting. | BOOLEAN | Yes | True/False |
| `model.audio` | Audio that drives the motion and becomes the soundtrack. At least 1 second long; audio longer than 20 seconds is truncated. Sets the video length instead of `model.duration`. | AUDIO | No | - |
| `model.seed` | Seed for the generation. The same seed reproduces a result exactly only when `model.enhance_prompt` is off (default: 42). | INT | Yes | 0 to 2147483647 |

**Notes:**

* `model.prompt` is required and limited to 5000 characters.
* Draft at 1080p cannot be combined with 48 fps: the node raises an error, so either turn draft off or use 24 fps.
* Connected audio must be at least 1 second long; anything past 20 seconds is ignored.
* With `model.audio` connected the audio sets the video length, so `model.duration` and `model.generate_audio` have no effect.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video with its soundtrack. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrunaTextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `bb7bacf2591618220c72525c1e32382174abe3a55069720adbc84fc1d8081718`


# RegexExtract - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RegexExtract

The RegexExtract node searches for patterns in text using regular expressions.

The RegexExtract node searches for patterns in text using regular expressions. It can find the first match, all matches, specific groups from matches, or all groups across multiple matches. The node supports various regex flags for case sensitivity, multiline matching, and dotall behavior.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | The input text to search for patterns | STRING | Yes | - |
| `regex_pattern` | The regular expression pattern to search for | STRING | Yes | - |
| `mode` | The extraction mode determines what parts of matches are returned (default: "First Match") | COMBO | Yes | "First Match"<br />"All Matches"<br />"First Group"<br />"All Groups" |
| `case_insensitive` | Whether to ignore case when matching (default: True) | BOOLEAN | No | - |
| `multiline` | Whether to treat the string as multiple lines (default: False) | BOOLEAN | No | - |
| `dotall` | Whether the dot (.) matches newlines (default: False) | BOOLEAN | No | - |
| `group_index` | The capture group index to extract when using group modes (default: 1) | INT | No | 0-100 |

**Note:** When using "First Group" or "All Groups" modes, the `group_index` parameter specifies which capture group to extract. Group 0 represents the entire match, while groups 1+ represent the numbered capture groups in your regex pattern.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The extracted text based on the selected mode and parameters | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RegexExtract/en.md)

***

**Source fingerprint (SHA-256):** `a879e4fd7429edfada44b2f5778bb71e537a000be6c25d3f67359b9ee802812f`


# RegexMatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RegexMatch

The RegexMatch node checks if a text string contains a match for a given regular expression pattern.

The RegexMatch node checks if a text string contains a match for a given regular expression pattern. It searches the input string and returns a simple yes/no result indicating whether the pattern was found anywhere in the text. You can adjust how the search works by enabling options like case-insensitive matching or multiline mode.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | The text string to search for matches | STRING | Yes | - |
| `regex_pattern` | The regular expression pattern to match against the string | STRING | Yes | - |
| `case_insensitive` | Whether to ignore case when matching (default: True) | BOOLEAN | No | - |
| `multiline` | Whether to enable multiline mode for regex matching (default: False) | BOOLEAN | No | - |
| `dotall` | Whether to enable dotall mode for regex matching (default: False) | BOOLEAN | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `matches` | Returns True if the regex pattern matches any part of the input string, False otherwise | BOOLEAN |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RegexMatch/en.md)

***

**Source fingerprint (SHA-256):** `4f0fa717bde7406e42d9a99599eab546690140166d2bb01bb4fde3c5d60e0397`


# RegexReplace - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RegexReplace

The RegexReplace node finds and replaces text in strings using regular expression patterns.

The RegexReplace node finds and replaces text in strings using regular expression patterns. It allows you to search for text patterns and replace them with new text, with options to control how the pattern matching works including case sensitivity, multiline matching, and limiting the number of replacements.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | The input text string to search and replace within | STRING | Yes | - |
| `regex_pattern` | The regular expression pattern to search for in the input string | STRING | Yes | - |
| `replace` | The replacement text to substitute for matched patterns | STRING | Yes | - |
| `case_insensitive` | When enabled, makes the pattern matching ignore case differences (default: True) | BOOLEAN | No | - |
| `multiline` | When enabled, changes the behavior of ^ and \$ to match at the start/end of each line rather than just the start/end of the entire string (default: False) | BOOLEAN | No | - |
| `dotall` | When enabled, the dot (.) character will match any character including newline characters. When disabled, dots won't match newlines (default: False) | BOOLEAN | No | - |
| `count` | Maximum number of replacements to make. Set to 0 to replace all occurrences (default). Set to 1 to replace only the first match, 2 for the first two matches, etc. (default: 0) | INT | No | 0-100 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The modified string with the specified replacements applied | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RegexReplace/en.md)

***

**Source fingerprint (SHA-256):** `58d4ec055aa5901b0e536bb2ca6993053ea85a9269d09cdcdf584df935d6876d`


# ReplaceText - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReplaceText

The Replace Text node performs a simple text substitution.

The Replace Text node performs a simple text substitution. It searches for a specified piece of text within the input and replaces every occurrence with a new piece of text. The operation is applied to all text inputs provided to the node.

**Note:** This node is deprecated and superseded by the other Replace Text node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | The text to process. | STRING | Yes | - |
| `find` | Text to find (default: empty string). | STRING | Yes | - |
| `replace` | Text to replace with (default: empty string). | STRING | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `text` | The processed text with all occurrences of the `find` text replaced by the `replace` text. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReplaceText/en.md)

***

**Source fingerprint (SHA-256):** `38beeabc232b19efedf2dcf4e2490f537d9a07d60c89de2811b7a4bddb98cf57`


# RunwayAleph2KeyframeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayAleph2KeyframeNode

Runway Aleph2 Keyframe node anchors a guidance image to a specific moment of your input video, so the Aleph2 model steers the edit at that point in your footage.

Runway Aleph2 Keyframe node anchors a guidance image to a specific moment of your input video, so the Aleph2 model steers the edit at that point in your footage. Connect this node to the "keyframes" input of the Runway Aleph2 Video to Video node, and chain several together (up to 5) via the optional "keyframes" input.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The guidance image to apply at the chosen moment of the input video. | IMAGE | Yes | - |
| `timing` | How to place this image on the input video's timeline. | COMBO | Yes | "Absolute seconds"<br />"Fraction of duration" |
| `keyframes` | Optional earlier keyframes to chain with this one. | KEYFRAME | No | - |

### Timing Parameter Details

The `timing` parameter has two modes:

* **"Absolute seconds"**: When selected, a `seconds` sub-parameter appears. This specifies the time in seconds from the start of the input video where the image applies (default: 0.0, range: 0.0 to 30.0, step 0.1).
* **"Fraction of duration"**: When selected, a `fraction` sub-parameter appears. This specifies where in the input video the image applies as a fraction of its duration, where 0.0 is the start and 1.0 is the end (default: 0.0, range: 0.0 to 1.0, step 0.01).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `keyframes` | A chain of keyframes including this one and any previously connected keyframes. | KEYFRAME |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayAleph2KeyframeNode/en.md)

***

**Source fingerprint (SHA-256):** `b5ac6553166b7366fd35f97740861be163f91bc2353f5f83bdc2f04bf40f8478`


# RunwayAleph2PromptImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayAleph2PromptImageNode

This node anchors a guidance image to a specific moment in the output video, controlling what the edited video looks like at that point.

This node anchors a guidance image to a specific moment in the output video, controlling what the edited video looks like at that point. Connect this node to the `prompt_images` input of the Runway Aleph2 Video to Video node, and chain several together (up to 5) using the optional `prompt_images` input.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The guidance image to place at the chosen moment of the output video. | IMAGE | Yes | - |
| `position` | How to place this image on the output video's timeline. Choose between absolute timing (seconds from start) or fractional timing (fraction of video duration). Selecting an option reveals the corresponding sub-parameter. | COMBO | Yes | `Absolute (seconds)`<br />`Fraction (0.0 to 1.0)` |
| `prompt_images` | Optional earlier prompt images to chain with this one. Connect the output of another Runway Aleph2 Prompt Image node here to build a chain of up to 5 guidance images. | PROMPT\_IMAGE\_CHAIN | No | - |

**Position mode details:**

* **Absolute (seconds):** When selected, you must provide a `seconds` value (default: 0.0, range: 0.0 to 30.0, step: 0.1). This specifies the time in seconds from the start of the output video where this image applies.
* **Fraction (0.0 to 1.0):** When selected, you must provide a `fraction` value (default: 0.0, range: 0.0 to 1.0, step: 0.01). This specifies the point in the output video as a fraction of its total duration (0.0 = start, 1.0 = end).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `prompt_images` | A chain of prompt images that can be connected to the `prompt_images` input of the Runway Aleph2 Video to Video node. Chaining multiple prompt image nodes builds a sequence of up to 5 guidance images. | PROMPT\_IMAGE\_CHAIN |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayAleph2PromptImageNode/en.md)

***

**Source fingerprint (SHA-256):** `a8b86fb5d73d27cc58aa59c195ca058eec8a5c9433ea09522ff3e905f6b88193`


# RunwayAleph2VideoToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayAleph2VideoToVideoNode

Documentation for RunwayAleph2VideoToVideoNode node.

## Overview

This node edits a video using a text prompt with Runway's Aleph2 model. It transforms your footage by restyling, relighting, adding or removing elements, or changing the viewpoint while preserving the original motion and timing. The output resolution matches the input video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Describes what should appear in the output (1-1000 characters). | STRING | Yes | 1-1000 characters |
| `video` | Input video to edit. Must be 2-30 seconds at 30 fps or lower. | VIDEO | Yes | 2-30 seconds duration, 30 fps max |
| `seed` | Random seed for generation (default: 0). | INT | Yes | 0 to 4294967295 |
| `public_figure_threshold` | Content moderation for recognizable public figures (default: "low"). | COMBO | Yes | `"auto"`<br />`"low"` |
| `keyframes` | Guidance images anchored to the input video, from Aleph2 Keyframe nodes (up to 5). Use keyframes or prompt images, not both. | KEYFRAME | No | Up to 5 items |
| `prompt_images` | Guidance images anchored to the output video, from Aleph2 Prompt Image nodes (up to 5). Use keyframes or prompt images, not both. | PROMPT\_IMAGE | No | Up to 5 items |

**Important constraints:**

* The input video must be between 2 and 30 seconds long and have a frame rate of 30 fps or lower.
* You can use either `keyframes` or `prompt_images` for guidance, but not both at the same time.
* Each guidance input (keyframes or prompt images) supports a maximum of 5 items.
* Keyframe timestamps and prompt image timestamps must not exceed the input video duration.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The edited video generated by the Aleph2 model. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayAleph2VideoToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `bda4d0f49843c1a8f311ddbce5911a2a157cae798a26f7a183b31fe41686d0b7`


# RunwayFirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayFirstLastFrameNode

The Runway First-Last-Frame to Video node generates a video using a start frame, an end frame, and a text prompt.

The Runway First-Last-Frame to Video node generates a video using a start frame, an end frame, and a text prompt. It creates a smooth transition between the two provided keyframes using Runway's gen3a\_turbo model. It is especially useful for complex transitions where the end frame is completely different from the start frame.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for the generation (default: empty string) | STRING | Yes | N/A |
| `start_frame` | Start frame to be used for the video | IMAGE | Yes | N/A |
| `end_frame` | End frame to be used for the video. Supported for gen3a\_turbo only. | IMAGE | Yes | N/A |
| `duration` | Duration of the generated video in seconds. The longer 10s duration gives the generation more time to smoothly transition between the start and end frames (default: "5"). | COMBO | Yes | `"5"`<br />`"10"` |
| `ratio` | Aspect ratio for the generated video (default: "768:1280") | COMBO | Yes | `"768:1280"`<br />`"1280:768"` |
| `seed` | Random seed for generation (default: 0) | INT | Yes | 0 to 4294967295 |

**Parameter Constraints:**

* The `prompt` must contain at least 1 character
* Both `start_frame` and `end_frame` must have maximum dimensions of 7999x7999 pixels
* Both `start_frame` and `end_frame` must have aspect ratios between 0.5 and 2.0
* The `end_frame` parameter is only supported when using the gen3a\_turbo model

**Notes:**

* The generation cost is based on the selected duration: USD 0.0715 per second (USD 0.3575 for 5 seconds, USD 0.715 for 10 seconds)
* This node is marked as deprecated

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video transitioning between the start and end frames | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayFirstLastFrameNode/en.md)

***

**Source fingerprint (SHA-256):** `1d8720aba833348583d2aa37e13a1ad43d9055b0201c9cb6ad9c95dada7e5056`


# RunwayImageToVideoNodeGen3a - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayImageToVideoNodeGen3a

Runway Image to Video (Gen3a Turbo) node generates a video from a single starting frame using Runway's Gen3a Turbo model.

Runway Image to Video (Gen3a Turbo) node generates a video from a single starting frame using Runway's Gen3a Turbo model. It takes a text prompt and an initial image frame, then creates a video sequence based on the specified duration and aspect ratio. The generation is processed remotely through Runway's API. This node is marked as deprecated.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for the generation (default: "") | STRING | Yes | N/A |
| `start_frame` | Start frame to be used for the video | IMAGE | Yes | N/A |
| `duration` | Duration of the generated video, in seconds (default: "5") | COMBO | Yes | `"5"`<br />`"10"` |
| `ratio` | Aspect ratio of the generated video (default: "768:1280") | COMBO | Yes | `"768:1280"`<br />`"1280:768"` |
| `seed` | Random seed for generation (default: 0) | INT | Yes | 0 to 4294967295 |

**Parameter Constraints:**

* The `prompt` must contain at least one character (it cannot be empty).
* The `start_frame` accepts a single image (maximum of 1).
* The `start_frame` must not exceed 7999 x 7999 pixels in dimensions.
* The `start_frame` must have an aspect ratio between 1:2 and 2:1 (0.5 to 2.0).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video sequence | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayImageToVideoNodeGen3a/en.md)

***

**Source fingerprint (SHA-256):** `ff66cbdfa80aabeaf96d43e7822dd0c700ee027d13fb430a9dc2079e1a23f38e`


# RunwayImageToVideoNodeGen4 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayImageToVideoNodeGen4

The Runway Image to Video (Gen4 Turbo) node generates a video from a single starting frame using Runway's Gen4 Turbo model.

The Runway Image to Video (Gen4 Turbo) node generates a video from a single starting frame using Runway's Gen4 Turbo model. It takes a text prompt and an initial image frame, then creates a video sequence based on the provided duration and aspect ratio settings. The node handles uploading the starting frame to Runway's API and returns the generated video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text prompt for the generation (default: empty string) | STRING | Yes | - |
| `start_frame` | Start frame to be used for the video | IMAGE | Yes | - |
| `duration` | Video duration in seconds | COMBO | Yes | `"5"`<br />`"10"` |
| `ratio` | Aspect ratio for the generated video (default: "1280:720") | COMBO | Yes | `"1280:720"`<br />`"720:1280"`<br />`"1104:832"`<br />`"832:1104"`<br />`"960:960"`<br />`"1584:672"` |
| `seed` | Random seed for generation (default: 0) | INT | No | 0 to 4294967295 |

**Parameter Constraints:**

* The `start_frame` image must have dimensions not exceeding 7999x7999 pixels
* The `start_frame` image must have an aspect ratio between 0.5 and 2.0
* The `prompt` must contain at least one character

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video based on the input frame and prompt | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayImageToVideoNodeGen4/en.md)

***

**Source fingerprint (SHA-256):** `1cbf70391f1dfd0f40a3085dad68b98ec20e964eab7d4a17b2fb3cd07a035277`


# SamplerDpmpp2mSde - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDpmpp2mSde

This node is designed to generate a sampler for the DPMPP2MSDE model, allowing for the creation of samples based on specified solver types, noise levels, and computational device p

This node is designed to generate a sampler for the DPMPP\_2M\_SDE model, allowing for the creation of samples based on specified solver types, noise levels, and computational device preferences. It abstracts the complexities of sampler configuration, providing a streamlined interface for generating samples with customized settings.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `solver_type` | Specifies the solver type to be used in the sampling process, offering options between 'midpoint' and 'heun'. This choice influences the numerical integration method applied during sampling. | COMBO\[STRING] |
| `eta` | Determines the step size in the numerical integration, affecting the granularity of the sampling process. A higher value indicates a larger step size. | `FLOAT` |
| `s_noise` | Controls the level of noise introduced during the sampling process, influencing the variability of the generated samples. | `FLOAT` |
| `noise_device` | Indicates the computational device ('gpu' or 'cpu') on which the noise generation process is executed, affecting performance and efficiency. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `sampler` | The output is a sampler configured according to the specified parameters, ready for generating samples. | `SAMPLER` |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDpmpp2mSde/en.md)


# SamplerDpmppSde - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDpmppSde

This node is designed to generate a sampler for the DPM++ SDE (Stochastic Differential Equation) model.

This node is designed to generate a sampler for the DPM++ SDE (Stochastic Differential Equation) model. It adapts to both CPU and GPU execution environments, optimizing the sampler's implementation based on the available hardware.

## Inputs

| Parameter | Description | Data Type |
| - | - | - |
| `eta` | Specifies the step size for the SDE solver, influencing the granularity of the sampling process. | FLOAT |
| `s_noise` | Determines the level of noise to be applied during the sampling process, affecting the diversity of the generated samples. | FLOAT |
| `r` | Controls the ratio of noise reduction in the sampling process, impacting the clarity and quality of the generated samples. | FLOAT |
| `noise_device` | Selects the execution environment (CPU or GPU) for the sampler, optimizing performance based on available hardware. | COMBO\[STRING] |

## Outputs

| Parameter | Description | Data Type |
| - | - | - |
| `sampler` | The generated sampler configured with the specified parameters, ready for use in sampling operations. | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDpmppSde/en.md)


# SaveText - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveText

The Save Text node writes text content to a file in the output directory.

The Save Text node writes text content to a file in the output directory. It supports saving in .txt, .csv, .md, or .json format, and automatically handles JSON pretty-printing when valid JSON is provided.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | The text content to save to a file. This input must be connected from another node. | STRING | Yes | - |
| `filename_prefix` | Prefix for the output filename. A 5-digit counter is appended to prevent overwriting existing files (default: "ComfyUI"). | STRING | No | - |
| `format` | The file format to save the text as (default: "txt"). When "json" is selected, valid JSON text is pretty-printed with 2-space indentation; otherwise, the text is saved as-is. | COMBO | No | `"txt"`<br />`"csv"`<br />`"md"`<br />`"json"` |

### Notes

* `text` is a forced input and must be connected to another node; it cannot be typed directly.
* The saved file is named `<filename_prefix>_<5-digit counter>.<extension>` and is written into the ComfyUI output directory (in a subfolder derived from the prefix).
* Selecting the `"json"` format attempts to parse the text as JSON. If parsing succeeds, the content is written pretty-printed with 2-space indentation; if parsing fails, the raw text is written unchanged.
* The node reports the saved file back to the interface so it appears with the other generated output files.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `text` | The original text content that was saved to the file | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveText/en.md)

***

**Source fingerprint (SHA-256):** `09bd896cab770358132834892c1b37efd2ffa0cb0aa7b02b7ef91163331dc9b1`


# StartLoop - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StartLoop

The Start Loop node starts a looping structure inside a workflow.

The Start Loop node starts a looping structure inside a workflow. It runs the connected loop body one time per iteration and can count iterations in three ways: a fixed number of repetitions (simple), a numeric index range (For), or one pass per item in a list (List). Each pass exposes the current index, first/last flags, and an optional carried value that can be passed from one iteration to the next.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `mode` | The loop iteration mode (default: "simple"). The selected mode determines which additional parameters are shown. | DYNAMIC\_COMBO | Yes | `"simple"`<br />`"For"`<br />`"List"` |
| `cache_iterations` | Reuse unchanged iteration results from previous executions. Disable to execute every iteration again. Default: false. | BOOLEAN | Yes | true<br />false |
| `parent_iteration` | Connect iteration\_index from an outer Start Loop to nest this loop. This input is force-input only (a link is required). | INT | No | Any integer |
| `initial_iteration_value` | Value exposed as current\_iteration\_value on the first iteration. | ANY (type-matched) | No | Any value |

### Simple Mode Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `num_iterations` | Number of times to execute the loop body. Default: 4. | INT | Yes | Minimum 0 |

### For Mode Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `start_iteration_index` | Index of the first iteration when using For loop mode. Default: 0. | INT | Yes | Any integer |
| `max_iteration` | The exclusive stopping value for iteration\_index in For mode. Default: 4. | INT | Yes | Maximum 0xffffffffffffffff |
| `step` | The index step size between each iteration when using For loop mode. Default: 1. | INT | Yes | Minimum 1 |

### List Mode Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `list` | List of items the loop iterates on. The loop body executes once per item. | ANY (type-matched list item) | Yes | Any list |

Notes:

* Only the parameters belonging to the currently selected `mode` are shown and used.
* In Simple mode, the iteration indices run from 0 up to `num_iterations` minus 1. In For mode, indices run from `start_iteration_index` up to (but not including) `max_iteration`, increasing by `step`. In List mode, one iteration runs per item in `list`.
* `step` must not be 0; a value of 0 raises an error. Values below 1 are not allowed.
* If the computed number of iterations is zero, the `is_last` output is reported as true and the loop body does not run.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `iteration_index` | Index of the current loop iteration. | INT |
| `is_first` | True during the first iteration of the loop. | BOOLEAN |
| `is_last` | True during the last iteration of the loop. | BOOLEAN |
| `list_item` | Current item from the list when using List mode. None in Simple and For modes. | ANY (type-matched) |
| `current_iteration_value` | Loop-carried value for the current iteration: initial\_iteration\_value on the first iteration, then next\_iteration\_value from End Loop on each subsequent iteration. | ANY (type-matched) |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StartLoop/en.md)

***

**Source fingerprint (SHA-256):** `be34fedd4db9d4f4cc795855c87f6489f294e029da316b5dc66e5af7dff004a9`


# StringCompare - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringCompare

The StringCompare node compares two text strings using different comparison methods.

The StringCompare node compares two text strings using different comparison methods. It can check if one string starts with another, ends with another, or if both strings are exactly equal. The comparison can be performed with or without considering letter case differences.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string_a` | The first string to compare | STRING | Yes | - |
| `string_b` | The second string to compare against | STRING | Yes | - |
| `mode` | The comparison method to use (default: "Starts With") | COMBO | Yes | "Starts With"<br />"Ends With"<br />"Equal" |
| `case_sensitive` | Whether to consider letter case during comparison (default: true) | BOOLEAN | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | Returns true if the comparison condition is met, false otherwise | BOOLEAN |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringCompare/en.md)

***

**Source fingerprint (SHA-256):** `18599228c31543f270afde0f3b838512ee12d1998b8de42c4d3e7852b1a5d8b2`


# StringConcatenate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringConcatenate

The StringConcatenate node combines two text strings into one by joining them with a specified delimiter.

The StringConcatenate node combines two text strings into one by joining them with a specified delimiter. It takes two input strings and a delimiter character or string, then outputs a single string where the two inputs are connected with the delimiter placed between them.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string_a` | The first text string to concatenate | STRING | Yes | - |
| `string_b` | The second text string to concatenate | STRING | Yes | - |
| `delimiter` | The character or string to insert between the two input strings (default: empty string) | STRING | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The combined string with the delimiter inserted between string\_a and string\_b | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringConcatenate/en.md)

***

**Source fingerprint (SHA-256):** `ea6fa7948d07e87b7ea3aeaf4f38c4cfdbfa5c5bd56d9f2935f94f1775686d08`


# StringContains - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringContains

The StringContains node checks if a given string contains a specified substring.

The StringContains node checks if a given string contains a specified substring. It can perform this check with either case-sensitive or case-insensitive matching, returning a boolean result indicating whether the substring was found within the main string.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | The main text string to search within | STRING | Yes | - |
| `substring` | The text to search for within the main string | STRING | Yes | - |
| `case_sensitive` | Determines whether the search should be case-sensitive (default: true) | BOOLEAN | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `contains` | Returns true if the substring is found in the string, false otherwise | BOOLEAN |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringContains/en.md)

***

**Source fingerprint (SHA-256):** `9e85e51bc32c4041a66de8d5b11475aba3120eee1e8c5a37fedfaa470746888c`


# StringFormat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringFormat

Documentation for StringFormat node.

## Overview

This node formats text using Python's string format method. It works like a template where you define a text pattern with placeholders, and then provide values to fill those placeholders. It supports all of Python's format options and features.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `f_string` | The format string template with placeholders (default: `{a}`). Supports multiline input. | STRING | Yes | N/A |
| `values` | Dynamic input for providing values to fill placeholders in the format string. Multiple value inputs can be added as needed. | STRING | Yes | N/A |

**Note on `values` input:** This input is dynamic and can be expanded to include multiple named values. Each value input is labeled with a letter (a, b, c, etc.) and corresponds to a placeholder in the format string (e.g., `{a}`, `{b}`, `{c}`). You can add or remove value inputs as needed.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `STRING` | The formatted text string with all placeholders replaced by their corresponding values. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringFormat/en.md)

***

**Source fingerprint (SHA-256):** `72625287533829a8087687bb47f39bc265aced3d5f43066f615326d729725122`


# StringLength - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringLength

The StringLength node calculates the number of characters in a text string.

The StringLength node calculates the number of characters in a text string. It takes any text input and returns the total count of characters, including spaces and punctuation. This is useful for measuring text length or validating string size requirements.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | The text string to measure the length of. Supports multiline input. | STRING | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `length` | The total number of characters in the input string, including spaces and special characters. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringLength/en.md)

***

**Source fingerprint (SHA-256):** `bfb0cae513e4bd5c179b3cd0071a71a6ad7d67e71891cf1152f8ff9632e6d217`


# StringReplace - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringReplace

The StringReplace node performs text replacement operations on input strings.

The StringReplace node performs text replacement operations on input strings. It searches for a specified substring within the input text and replaces all occurrences with a different substring. This node returns the modified string with all replacements applied.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | The input text string where replacements will be performed | STRING | Yes | - |
| `find` | The substring to search for within the input text | STRING | Yes | - |
| `replace` | The replacement text that will substitute all found occurrences | STRING | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The modified string with all occurrences of the find text replaced by the replace text | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringReplace/en.md)

***

**Source fingerprint (SHA-256):** `7f384aff132eb6919b58f04163c4611a7b5545e1af9217f9aca60dc416c06d60`


# StringSubstring - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringSubstring

The StringSubstring node extracts a portion of text from a larger string.

The StringSubstring node extracts a portion of text from a larger string. It takes a starting position and ending position to define the section you want to extract, then returns the text between those two positions.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | The input text string to extract from. Supports multi-line text. | STRING | Yes | - |
| `start` | The starting position index for the substring. The first character is at index 0. | INT | Yes | - |
| `end` | The ending position index for the substring. The character at this index is not included in the result. | INT | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The extracted substring from the input text, containing all characters from the `start` position up to (but not including) the `end` position. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringSubstring/en.md)

***

**Source fingerprint (SHA-256):** `fd3ec23bbfe3a51f5481f1b0fe8b77f66e08469bb2a4bd3e266a7607f014e544`


# StringTrim - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringTrim

The StringTrim node removes whitespace characters (such as spaces, tabs, and newlines) from the beginning, end, or both sides of a text string.

The StringTrim node removes whitespace characters (such as spaces, tabs, and newlines) from the beginning, end, or both sides of a text string. You can choose to trim from the left side, right side, or both sides of the string. This is useful for cleaning up text inputs by removing unwanted whitespace.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `string` | The text string to process. Supports multiline input. | STRING | Yes | - |
| `mode` | Specifies which side(s) of the string to trim. "Both" removes whitespace from both ends, "Left" removes from the beginning only, "Right" removes from the end only. | COMBO | Yes | "Both"<br />"Left"<br />"Right" |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The trimmed text string with whitespace removed according to the selected mode. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringTrim/en.md)

***

**Source fingerprint (SHA-256):** `b7d0694b752f3017a5f8ee9a6ca1d88260f761576b5960f2cb210e34efb09d18`


# StripWhitespace - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StripWhitespace

This node removes any extra spaces, tabs, or newlines from the beginning and end of a text string.

This node removes any extra spaces, tabs, or newlines from the beginning and end of a text string. It takes a text input and returns a cleaned version with the leading and trailing whitespace trimmed off.

**Note: This node is deprecated and superseded by the Trim Text node.**

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | The text string from which to remove leading and trailing whitespace. | STRING | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `text` | The processed text with all leading and trailing whitespace characters removed. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StripWhitespace/en.md)

***

**Source fingerprint (SHA-256):** `182f01e15050b35cc33de7792886721873daf387a934befbe1ff37cbcd766143`


# SyncLipSyncNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SyncLipSyncNode

This node re-syncs mouth movement in a video to new speech audio using the sync.so API.

This node re-syncs mouth movement in a video to new speech audio using the sync.so API. It handles close-ups, profiles and obstructions automatically while preserving the speaker's expression. Cost scales with output duration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Footage of the speaker to re-sync. Up to 4K (4096x2160); a constant frame rate of 24/25/30 fps works best. | VIDEO | Yes | - |
| `audio` | Speech audio to sync the mouth to. | AUDIO | Yes | - |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 42). | INT | Yes | 0 to 2147483647 |
| `model` | sync.so generation model. | COMBO | Yes | "sync-3" |

The `model` parameter is a dynamic combo that includes the following sub-parameters:

| Sub-parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `sync_mode` | How to handle a duration mismatch between video and audio; this also sets the output length. bounce: video plays forward then backward until the audio ends (output = audio length). loop: video restarts until the audio ends (output = audio length). remap: video is time-stretched to match the audio (output = audio length). cut\_off: the longer track is trimmed (output = shorter length). silence: nothing is trimmed; the shorter track is padded (output = longer length). (default: "bounce") | COMBO | Yes | "bounce"<br />"cut\_off"<br />"loop"<br />"silence"<br />"remap" |
| `speaker_selection` | Which face to lipsync when several people are visible. default: let the model decide. auto-detect: detect and follow the active speaker. coordinates: target the face at pixel (speaker\_x, speaker\_y) in the frame chosen by speaker\_frame. (default: "default") | COMBO | Yes | "default"<br />"auto-detect"<br />"coordinates" |
| `speaker_frame` | Video frame used to locate the speaker. Only used when `speaker_selection` is 'coordinates'. (default: 0) | INT | No | 0 to 1,000,000 |
| `speaker_x` | X pixel coordinate of the speaker's face. Only used when `speaker_selection` is 'coordinates'. (default: 0) | INT | No | 0 to 4096 |
| `speaker_y` | Y pixel coordinate of the speaker's face. Only used when `speaker_selection` is 'coordinates'. (default: 0) | INT | No | 0 to 4096 |

**Constraints:**

* Video resolution must not exceed 4K (4096x2160). Videos above this limit will raise an error.
* Video and audio durations must not exceed 600 seconds (10 minutes).
* The `speaker_frame`, `speaker_x`, and `speaker_y` parameters are only used when `speaker_selection` is set to "coordinates".

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The re-synced video with mouth movement matched to the provided audio. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SyncLipSyncNode/en.md)

***

**Source fingerprint (SHA-256):** `b41f8c9bf0d55059f081a66af20636ec96462c3fd9caeb685cab10278f84678a`


# SyncTalkingImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SyncTalkingImageNode

Animate a still portrait into a talking video driven by speech audio, using sync.so's sync-3 model.

Animate a still portrait into a talking video driven by speech audio, using sync.so's sync-3 model. The output duration matches the audio duration, and cost scales with output duration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | A single image with a clearly visible face, up to 4K (4096x2160). | IMAGE | Yes | Exactly one image required |
| `audio` | Speech audio driving the talking video; the output duration matches it. Chain any TTS node here to drive the animation from text. | AUDIO | Yes | Maximum duration: 600 seconds |
| `prompt` | Optional guidance for how the portrait comes to life, e.g. 'make the subject smile and look at the camera'. Leave empty for natural talking motion. (default: "") | STRING | No | Multiline text |
| `seed` | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) | INT | No | 0 to 2147483647 |
| `model` | sync.so generation model. Image input is exclusive to sync-3. | COMBO | Yes | `"sync-3"` |
| `speaker_selection` | Which face to animate when several people are visible. `default`: let the model decide. `coordinates`: target the face at pixel (`speaker_x`, `speaker_y`) in the image. Auto-detection is not supported for images. (default: "default") | COMBO | No | `"default"`<br />`"coordinates"` |
| `speaker_x` | X pixel coordinate of the speaker's face. Only used when `speaker_selection` is `"coordinates"`. (default: 0) | INT | No | 0 to 4096 |
| `speaker_y` | Y pixel coordinate of the speaker's face. Only used when `speaker_selection` is `"coordinates"`. (default: 0) | INT | No | 0 to 4096 |
| `auto_downscale` | Automatically downscale the image if it exceeds the 4K (4096x2160) input limit; speaker coordinates are scaled to match. When disabled, an oversized image raises an error instead. (default: True) | BOOLEAN | No | True<br />False |

**Note:** The `speaker_x` and `speaker_y` parameters are only used when `speaker_selection` is set to `"coordinates"`. When `auto_downscale` is enabled, speaker coordinates are automatically scaled to match the downscaled image dimensions.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated talking video with the animated portrait synchronized to the input audio. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SyncTalkingImageNode/en.md)

***

**Source fingerprint (SHA-256):** `21f722cdcc5ff017949887ed2252854feebb9b913034dc6a6c3ce196ad089468`


# TextGenerate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextGenerate

The TextGenerate node uses a CLIP model to create text based on a user's prompt.

The TextGenerate node uses a CLIP model to create text based on a user's prompt. It can optionally use images, video, or audio as additional context to guide the text generation. You can control the length of the output, enable a thinking mode for supported models, and choose whether to use random sampling with various settings or to generate text without sampling.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `sampling_mode` | Controls whether random sampling is used during text generation. When set to "on", additional sampling parameters become available. When set to "off", the node generates text without random sampling. | DYNAMIC\_COMBO | Yes | `"on"`<br />`"off"` |
| `clip` | The CLIP model used for tokenizing the prompt and generating text. | CLIP | Yes | N/A |
| `prompt` | The text prompt that guides the generation. This field supports multiple lines and dynamic prompts. The default value is an empty string. | STRING | Yes | N/A |
| `image` | An optional image that can be used alongside the text prompt to influence the generated text. | IMAGE | No | N/A |
| `video` | Video frames as an image batch. Assumed to be 24 FPS; subsampled to 1 FPS internally. | IMAGE | No | N/A |
| `audio` | An optional audio input that can be used alongside the text prompt to influence the generated text. | AUDIO | No | N/A |
| `max_length` | The maximum number of tokens the model will generate. The default value is 512. | INT | Yes | 1 to 32768 |
| `thinking` | Operate in thinking mode if the model supports it. The default value is False. | BOOLEAN | No | True or False |
| `use_default_template` | Use the built in system prompt/template if the model has one. The default value is True. This is an advanced parameter. | BOOLEAN | No | True or False |
| `mtp` | Speculative decoding with the checkpoint's multi-token-prediction head. Has no effect without MTP weights. `"auto"` adapts the draft depth, `"2"` to `"5"` pin it. Sampled output stays correctly distributed but differs from non-MTP output for the same seed (default: `"auto"`). | COMBO | No | `"auto"`<br />`"off"`<br />`"2"`<br />`"3"`<br />`"4"`<br />`"5"` |
| `system_prompt` | Replaces the system prompt in the model's chat template. Ignored when the default template is not used. Connect a STRING input instead of typing in the node (default: empty). | STRING | No | N/A |

### Sampling Parameters (when `sampling_mode` is "on")

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `temperature` | Controls the randomness of the output. Lower values make the output more predictable, higher values make it more creative. The default value is 0.7. | FLOAT | Yes | 0.01 to 2.0 |
| `top_k` | Limits the sampling pool to the top K most likely next tokens. A value of 0 disables this filter. The default value is 64. | INT | Yes | 0 to 1000 |
| `top_p` | Uses nucleus sampling: it keeps the smallest set of most likely tokens whose cumulative probability reaches this value. The default value is 0.95. | FLOAT | Yes | 0.0 to 1.0 |
| `min_p` | Sets a minimum probability threshold for tokens to be considered. The default value is 0.05. | FLOAT | Yes | 0.0 to 1.0 |
| `repetition_penalty` | Penalizes tokens that have already been generated to reduce repetition. A value of 1.0 applies no penalty. The default value is 1.05. | FLOAT | Yes | 0.0 to 5.0 |
| `seed` | A number used to initialize the random number generator for reproducible results. The default value is 0. | INT | Yes | 0 to 18446744073709551615 |
| `presence_penalty` | Penalizes new tokens based on whether they have appeared in the text so far, encouraging the model to talk about new topics. The default value is 0.0. | FLOAT | No | 0.0 to 5.0 |

**Note:** The sampling parameters above are only active and visible in the node interface when `sampling_mode` is set to "on". When `sampling_mode` is set to "off", no sampling parameters are available and the node generates text without random sampling.

**Note:** When the generated text contains a reasoning block (it opens with `<think>` or the prompt ends with it), the reasoning is returned separately: `generated_text` carries the answer and `thinking` carries the reasoning with the opening tag removed. Otherwise `generated_text` carries everything the model produced and `thinking` is empty.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `generated_text` | The text generated by the model based on the input prompt and optional image, video, or audio, with any reasoning block separated out into the `thinking` output. | STRING |
| `thinking` | The reasoning block the model produced, with the opening `<think>` tag removed. Empty when the model produced no reasoning block. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextGenerate/en.md)

***

**Source fingerprint (SHA-256):** `80813781c06dfb0c3b59ee72c8bd6ebced69a4de8152de916ebc15153a0757fa`


# TextGenerateLTX2Prompt - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextGenerateLTX2Prompt

The TextGenerateLTX2Prompt node expands a short user prompt into a detailed, audio-visual description suitable for generating video with the LTX-2 series of video models.

The TextGenerateLTX2Prompt node expands a short user prompt into a detailed, audio-visual description suitable for generating video with the LTX-2 series of video models. It automatically adds task-specific system instructions, sends the formatted prompt to a language model, and returns the enhanced text. When an optional reference image is supplied, the node switches to image-to-video mode and expands the prompt starting from that image's content.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `clip` | The CLIP model used for text encoding. The node checks the model's tokenizer name to select the matching instructions: Gemma 4 based models use the LTX-2.4 format, while other models use the LTX-2 (Gemma 3) format. | CLIP | Yes | - |
| `prompt` | The raw text input describing the scene or concept to be expanded into a detailed video generation prompt. | STRING | Yes | - |
| `image` | An optional input image used as the first frame of the video. When provided, the node switches to image-to-video mode and uses a system prompt that expands the user prompt based on the image's content. | IMAGE | No | - |
| `video` | An optional video input used as additional context. Passed to the language model as an image batch; assumed to be 24 FPS and subsampled to 1 FPS internally. | IMAGE | No | - |
| `audio` | An optional audio input that can be used as additional context for generation. | AUDIO | No | - |
| `max_length` | The maximum number of tokens the language model is allowed to generate (default: 512). | INT | Yes | 1 to 32768 |
| `sampling_mode` | Controls whether random sampling is used during text generation. When set to `"on"`, the sampling parameters below become available; with `"off"` the node generates text without random sampling. | DYNAMIC\_COMBO | Yes | `"on"`<br />`"off"` |
| `thinking` | When enabled, the model is instructed to reason before answering. Any reasoning block is returned on the `thinking` output instead of in `generated_text` (default: False). | BOOLEAN | No | True/False |
| `use_default_template` | When enabled, the node uses the default chat template for formatting (default: True). Advanced setting. | BOOLEAN | No | True/False |
| `mtp` | Speculative decoding with the checkpoint's multi-token-prediction head. Has no effect without MTP weights. `"auto"` adapts the draft depth, `"2"` to `"5"` pin it. Sampled output stays correctly distributed but differs from non-MTP output for the same seed (default: `"auto"`). | COMBO | No | `"auto"`<br />`"off"`<br />`"2"`<br />`"3"`<br />`"4"`<br />`"5"` |
| `system_prompt` | Replaces the built-in LTX-2 system prompt. When left empty, the node uses its own instructions: the image-to-video prompt when an `image` is connected, otherwise the text-to-video prompt. Connect a STRING input instead of typing in the node (default: empty). | STRING | No | - |

### Sampling Parameters (when `sampling_mode` is "on")

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `temperature` | Controls the randomness of the output. Lower values make the output more predictable, higher values make it more creative (default: 0.7). | FLOAT | Yes | 0.01 to 2.0 |
| `top_k` | Limits the sampling pool to the top K most likely next tokens. A value of 0 disables this filter (default: 64). | INT | Yes | 0 to 1000 |
| `top_p` | Uses nucleus sampling: it keeps the smallest set of most likely tokens whose cumulative probability reaches this value. (default: 0.95) | FLOAT | Yes | 0.0 to 1.0 |
| `min_p` | Sets a minimum probability threshold for tokens to be considered (default: 0.05). | FLOAT | Yes | 0.0 to 1.0 |
| `repetition_penalty` | Penalizes tokens that have already been generated to reduce repetition. A value of 1.0 applies no penalty (default: 1.05). | FLOAT | Yes | 0.0 to 5.0 |
| `seed` | A number used to initialize the random number generator for reproducible results (default: 0). | INT | Yes | 0 to 18446744073709551615 |
| `presence_penalty` | Penalizes new tokens based on whether they have appeared in the text so far, encouraging the model to talk about new topics (default: 0.0). | FLOAT | No | 0.0 to 5.0 |

**Note:** The sampling parameters above are only active and visible in the node interface when `sampling_mode` is set to "on". When it is set to "off", no sampling parameters are available and the node generates text without random sampling.

**Note:** The behavior of the node changes based on its inputs:

* If an `image` is provided, the generated prompt is formatted for an image-to-video task using a system prompt that describes how to expand the prompt based on the image's content. If no image is provided, the formatting is for a text-to-video task using a system prompt that expands the prompt into a detailed video generation description.
* If the CLIP tokenizer's name contains "gemma4", the node uses the LTX-2.4 system prompts and the Gemma 4 chat format. Otherwise, it uses the LTX-2 (Gemma 3) system prompts and chat format.
* When `thinking` is enabled with a Gemma 4 model, the model is opened on its reasoning channel; when disabled, the model is opened directly on the final-answer channel. For non-Gemma 4 models, `thinking` is passed through to the underlying generation step.
* A `system_prompt` replaces the built-in instructions for the selected mode (image-to-video or text-to-video); when it is empty, the built-in prompt is used.
* Any reasoning block is returned on the `thinking` output instead of `generated_text`.
* If the language model produces no usable text, the node returns the original `prompt` instead.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `generated_text` | The enhanced video-generation prompt produced by the language model, with any reasoning block separated out into the `thinking` output. If the result is empty, the original user prompt is returned. | STRING |
| `thinking` | The reasoning block the model produced, with the opening `<think>` tag removed. Empty when the model produced no reasoning block; with Gemma 4 models a reasoning block is only expected when `thinking` is enabled. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextGenerateLTX2Prompt/en.md)

***

**Source fingerprint (SHA-256):** `a601a8bff65e8ee148d09f04ac0afc201dbc9ba5e09a65856400e9be37e085bb`


# TextOverlay - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextOverlay

This node draws text on top of an image or a batch of images.

This node draws text on top of an image or a batch of images. It creates a text overlay using a configurable font size, color, vertical position, horizontal alignment, and optional black outline, then combines the overlay with the original image pixels.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The input image or batch of images to draw text on | IMAGE | Yes | |
| `text` | The text to overlay on the image (default: ""). Supports multiple lines: the `\n` and `\t` escape sequences are converted to newlines and tabs, and long lines are automatically wrapped to fit within the image width. | STRING | Yes | |
| `font_size` | Font size as a percentage of the image height (default: 5.0) | FLOAT | Yes | 0.5 to 50.0 (step 0.5) |
| `color` | Color of the text (default: "#ffffff") | COLOR | Yes | |
| `position` | Vertical position of the text on the image (default: "top") | COMBO | Yes | "top"<br />"bottom" |
| `align` | Horizontal alignment of the text (default: "left") | COMBO | Yes | "left"<br />"center"<br />"right" |
| `outline` | Draw a black outline around the text (default: True) | BOOLEAN | Yes | |

Note: If `text` is empty or contains only whitespace, the node returns the input images unchanged. The text overlay is rendered once and applied to every image in the batch. If the rendered text block is taller than the available image area, the font size is reduced automatically until it fits or reaches a minimum size.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The input images with the text overlay composited on top | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextOverlay/en.md)

***

**Source fingerprint (SHA-256):** `b347f563fa26e098a310892f3e7fff41b83722800d67e5af9debad14fc9d01e7`


# TextToLowercase - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextToLowercase

The Text to Lowercase node takes a text string as input and converts all of its characters to lowercase.

The Text to Lowercase node takes a text string as input and converts all of its characters to lowercase. It is a simple utility for standardizing text case.

> **Note:** This node is deprecated and superseded by the Convert Text Case node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | The text string to be converted to lowercase. | STRING | Yes | Any text string |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `text` | The input text with all characters converted to lowercase. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextToLowercase/en.md)

***

**Source fingerprint (SHA-256):** `7ebafc952672510cbadf4549d37c5566bef474b8d1d159af4086cde64bcad849`


# TextToUppercase - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextToUppercase

The Text to Uppercase node takes a text input and converts all of its characters to uppercase.

The Text to Uppercase node takes a text input and converts all of its characters to uppercase. It is a simple text processing utility that modifies the case of the provided string.

**Note:** This node is deprecated and superseded by the Convert Text Case node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | The text string to be converted to uppercase. | STRING | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `text` | The resulting text with all characters converted to uppercase. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextToUppercase/en.md)

***

**Source fingerprint (SHA-256):** `b1d8c05aceda4dfd95400b40fdf01b16dccaa4e093e62d298b12753bfc0278a2`


# TopazVideoEnhance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TopazVideoEnhance

The Topaz Video Enhance node breathes new life into video with powerful upscaling and recovery technology, using an external API to improve video quality.

The Topaz Video Enhance node breathes new life into video with powerful upscaling and recovery technology, using an external API to improve video quality. It can upscale video resolution, increase frame rate through interpolation, and apply compression. The node processes an input MP4 video and returns an enhanced version based on the selected settings. This node is marked as deprecated (legacy).

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The input video file to be enhanced. | VIDEO | Yes | - |
| `upscaler_enabled` | Enables or disables the video upscaling feature (default: True). | BOOLEAN | Yes | - |
| `upscaler_model` | The AI model used for upscaling the video. | COMBO | Yes | `"Starlight (Astra) Fast"`<br />`"Starlight (Astra) Creative"`<br />`"Starlight Precise 2.5"` |
| `upscaler_resolution` | The target resolution for the upscaled video. | COMBO | Yes | `"FullHD (1080p)"`<br />`"4K (2160p)"` |
| `upscaler_creativity` | Creativity level (applies only to Starlight (Astra) Creative). (default: "low") | COMBO | No | `"low"`<br />`"middle"`<br />`"high"` |
| `interpolation_enabled` | Enables or disables the frame interpolation feature (default: False). | BOOLEAN | No | - |
| `interpolation_model` | The model used for frame interpolation (default: "apo-8"). | COMBO | No | `"apo-8"` |
| `interpolation_slowmo` | Slow-motion factor applied to the input video. For example, 2 makes the output twice as slow and doubles the duration. (default: 1) | INT | No | 1 to 16 |
| `interpolation_frame_rate` | Output frame rate. (default: 60) | INT | No | 15 to 240 |
| `interpolation_duplicate` | Analyze the input for duplicate frames and remove them. (default: False) | BOOLEAN | No | - |
| `interpolation_duplicate_threshold` | Detection sensitivity for duplicate frames. (default: 0.01) | FLOAT | No | 0.001 to 0.1 |
| `dynamic_compression_level` | CQP level. (default: "Low") | COMBO | No | `"Low"`<br />`"Mid"`<br />`"High"` |

**Note:** At least one enhancement feature must be enabled. The node will raise an error if both `upscaler_enabled` and `interpolation_enabled` are set to False. The input video must be in MP4 format. The `upscaler_creativity` setting applies only when `upscaler_model` is set to "Starlight (Astra) Creative". Very large video files that require multi-part uploads are not supported.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The enhanced output video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TopazVideoEnhance/en.md)

***

**Source fingerprint (SHA-256):** `b3b14a301b529256ddf04b7e3a9b99814ad5bfa149366b2a5c51c396dbffb190`


# TopazVideoEnhanceV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TopazVideoEnhanceV2

The Topaz Video Enhance V2 node breathes new life into video with powerful upscaling and recovery technology.

The **Topaz Video Enhance V2** node breathes new life into video with powerful upscaling and recovery technology. It can increase the resolution of a video using different Topaz upscaler models, adjust the frame rate through frame interpolation, and apply creative or realistic enhancement settings.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The input video to be processed. Must be in MP4 container format. | VIDEO | Yes | - |
| `upscaler_model` | The AI model used to upscale the video. The available sub-parameters depend on the selected model. Selecting `"Disabled"` disables upscaling. | DYNAMIC\_COMBO | Yes | `"Astra 2"`<br />`"Starlight (Astra) Fast"`<br />`"Starlight (Astra) Creative"`<br />`"Starlight Precise 2.5"`<br />`"Disabled"` |
| `interpolation_model` | The AI model used for frame interpolation. The available sub-parameters depend on the selected model. Selecting `"Disabled"` disables interpolation. | DYNAMIC\_COMBO | Yes | `"Disabled"`<br />`"apo-8"` |
| `dynamic_compression_level` | CQP level used for video compression (default: `"Low"`). | COMBO | No | `"Low"`<br />`"Mid"`<br />`"High"` |

The following sections describe the sub-parameters that appear for each option of the `upscaler_model` and `interpolation_model` selectors. The `"Disabled"` options do not show any additional parameters.

### Astra 2 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `upscaler_model.upscaler_resolution` | Target output resolution of the upscale. | COMBO | Yes (when "Astra 2" is selected) | `"FullHD (1080p)"`<br />`"4K (2160p)"` |
| `upscaler_model.creativity` | Creative strength of the upscale (default: 0.5). | FLOAT | No | 0.0 to 1.0 (step 0.1) |
| `upscaler_model.prompt` | Optional descriptive (not instructive) scene prompt. Capping input at 450 frames (\~15s @ 30fps) when set (default: empty). | STRING | No | - |
| `upscaler_model.sharp` | Pre-enhance sharpness: 0.0=Gaussian blur, 0.5=passthrough (default), 1.0=USM sharpening. | FLOAT | No | 0.0 to 1.0 (step 0.01) |
| `upscaler_model.realism` | Pulls output toward photographic realism. Leave at 0 for the model default (default: 0.0). | FLOAT | No | 0.0 to 1.0 (step 0.01) |

### Starlight (Astra) Fast Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `upscaler_model.upscaler_resolution` | Target output resolution of the upscale. | COMBO | Yes (when this model is selected) | `"FullHD (1080p)"`<br />`"4K (2160p)"` |

### Starlight (Astra) Creative Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `upscaler_model.upscaler_resolution` | Target output resolution of the upscale. | COMBO | Yes (when this model is selected) | `"FullHD (1080p)"`<br />`"4K (2160p)"` |
| `upscaler_model.creativity` | Creative strength of the upscale (default: `"low"`). | COMBO | No | `"low"`<br />`"middle"`<br />`"high"` |

### Starlight Precise 2.5 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `upscaler_model.upscaler_resolution` | Target output resolution of the upscale. | COMBO | Yes (when this model is selected) | `"FullHD (1080p)"`<br />`"4K (2160p)"` |

### apo-8 Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `interpolation_model.interpolation_frame_rate` | Output frame rate (default: 60). | INT | Yes (when "apo-8" is selected) | 15 to 240 |
| `interpolation_model.interpolation_slowmo` | Slow-motion factor applied to the input video. For example, 2 makes the output twice as slow and doubles the duration (default: 1). | INT | No | 1 to 16 |
| `interpolation_model.interpolation_duplicate` | Analyze the input for duplicate frames and remove them (default: False). | BOOLEAN | No | True<br />False |
| `interpolation_model.interpolation_duplicate_threshold` | Detection sensitivity for duplicate frames (default: 0.01). | FLOAT | No | 0.001 to 0.1 (step 0.001) |

**Important Constraints:**

* At least one of `upscaler_model` or `interpolation_model` must be enabled. If both are set to `"Disabled"`, the node raises an error because there is nothing to process.
* The input `video` must be in MP4 container format.
* The `"Astra 2"` model is limited to 9000 input frames. When a `prompt` is set, the limit is 450 input frames (\~15 seconds at 30 fps). The node raises an error if the video exceeds the applicable limit.
* `upscaler_model.upscaler_resolution` is required whenever an upscaler model other than `"Disabled"` is selected. `"FullHD (1080p)"` targets a 1080p result and `"4K (2160p)"` targets a 2160p result; the exact output width and height are computed from the input aspect ratio, capped to a maximum long side of 1920 or 3840 pixels respectively, and rounded to an even number.
* `interpolation_model.interpolation_frame_rate` is required whenever `interpolation_model` is `"apo-8"`.
* Very large files are not currently supported; uploads are limited to a single part, otherwise the node raises an error.
* Several parameters (`sharp`, `realism`, `interpolation_slowmo`, `interpolation_duplicate`, `interpolation_duplicate_threshold`) are marked as advanced in the UI and may be hidden by default.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The enhanced video after applying the selected upscaling and/or interpolation filters. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TopazVideoEnhanceV2/en.md)

***

**Source fingerprint (SHA-256):** `14627dc772a6a46a645517bd34b545e0986a84561e24bdfe810b67f791ee47e3`


# TruncateText - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TruncateText

This node shortens text by cutting it off at a specified maximum length.

This node shortens text by cutting it off at a specified maximum length. It takes any input text and returns only the first part, up to the number of characters you set. It is a simple way to ensure text does not exceed a certain size.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `text` | The text string to be truncated. | STRING | Yes | N/A |
| `max_length` | Maximum text length. The text will be cut off after this many characters (default: 77). | INT | Yes | 1 to 10000 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `string` | The truncated text, containing only the first `max_length` characters from the input. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TruncateText/en.md)

***

**Source fingerprint (SHA-256):** `b23c92af425be8f7b15d793bbe7f321cab6f7f3137a995bb9724948ae00145e4`


# Veo3FirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Veo3FirstLastFrameNode

The Veo3FirstLastFrameNode uses Google's Veo 3 model to generate a video based on a text prompt, with a provided first and last frame that define the start and end of the video seq

The Veo3FirstLastFrameNode uses Google's Veo 3 model to generate a video based on a text prompt, with a provided first and last frame that define the start and end of the video sequence.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text description of the video (default: empty string). | STRING | Yes | N/A |
| `negative_prompt` | Negative text prompt to guide what to avoid in the video (default: empty string). | STRING | No | N/A |
| `resolution` | The resolution of the output video. | COMBO | Yes | `"720p"`<br />`"1080p"`<br />`"4k"` |
| `aspect_ratio` | Aspect ratio of the output video (default: "16:9"). | COMBO | No | `"16:9"`<br />`"9:16"` |
| `duration` | Duration of the output video in seconds (default: 8, step: 2). | INT | No | 4 to 8 |
| `seed` | Seed for video generation (default: 0). | INT | No | 0 to 4294967295 |
| `first_frame` | The start frame for the video. | IMAGE | Yes | N/A |
| `last_frame` | The end frame for the video. | IMAGE | Yes | N/A |
| `model` | The specific Veo model to use for generation (default: "veo-3.1-generate"). | COMBO | No | `"veo-3.1-generate"`<br />`"veo-3.1-fast-generate"`<br />`"veo-3.1-lite"` |
| `generate_audio` | Generate audio for the video (default: True). | BOOLEAN | No | N/A |

**Note:** The `veo-3.1-lite` model does not support 4K resolution. If you select `veo-3.1-lite` and `4k` resolution, an error will occur.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Veo3FirstLastFrameNode/en.md)

***

**Source fingerprint (SHA-256):** `2fe55d2a1d018e58fd290c901c596708898acda835d2358adf36ed80103aeb6e`


# Veo3VideoGenerationNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Veo3VideoGenerationNode

Generates videos from text prompts using Google's Veo 3 API.

Generates videos from text prompts using Google's Veo 3 API. This node supports multiple Veo 3 models, including fast and lite variants, and allows you to specify video resolution, duration, and audio generation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Text description of the video (default: "") | STRING | Yes | - |
| `aspect_ratio` | Aspect ratio of the output video (default: "16:9") | COMBO | Yes | "16:9"<br />"9:16" |
| `resolution` | Output video resolution. 4K is not available for the veo-3.1-lite model. (default: "720p") | COMBO | No | "720p"<br />"1080p"<br />"4k" |
| `negative_prompt` | Negative text prompt to guide what to avoid in the video (default: "") | STRING | No | - |
| `duration_seconds` | Duration of the output video in seconds (default: 8) | INT | No | 4 - 8 (step 2) |
| `enhance_prompt` | This parameter is deprecated and ignored. (default: True) | BOOLEAN | No | - |
| `person_generation` | Whether to allow generating people in the video (default: "ALLOW") | COMBO | No | "ALLOW"<br />"BLOCK" |
| `seed` | Seed for video generation (0 for random) (default: 0) | INT | No | 0 - 4294967295 |
| `image` | Optional reference image to guide video generation | IMAGE | No | - |
| `model` | Veo 3 model to use for video generation (default: "veo-3.1-generate") | COMBO | No | "veo-3.1-generate"<br />"veo-3.1-fast-generate"<br />"veo-3.1-lite" |
| `generate_audio` | Generate audio for the video. Supported by all Veo 3 models. (default: False) | BOOLEAN | No | - |

**Note:** The `enhance_prompt` parameter is deprecated and its value is ignored. The node always enhances the prompt internally. If you select "4k" resolution with the veo-3.1-lite model, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Veo3VideoGenerationNode/en.md)

***

**Source fingerprint (SHA-256):** `5320736448ad854e2f93e08ccaa870e977e06497666cb305f314bc76ff917740`


# Vidu2ImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu2ImageToVideoNode

The Vidu2 Image-to-Video Generation node creates a video sequence starting from a single input image.

The Vidu2 Image-to-Video Generation node creates a video sequence starting from a single input image. It uses a specified Vidu2 model to animate the scene based on an optional text prompt, controlling the video's length, resolution, and the intensity of motion.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Vidu2 model to use for video generation. Different models offer varying speed and quality trade-offs. | COMBO | Yes | `"viduq2-pro-fast"`<br />`"viduq2-pro"`<br />`"viduq2-turbo"` |
| `image` | An image to be used as the start frame of the generated video. Only one image is allowed. | IMAGE | Yes | - |
| `prompt` | An optional text prompt for video generation (max 2000 characters). Default is an empty string. | STRING | No | - |
| `duration` | The length of the generated video in seconds. Default is 5. | INT | Yes | 1 to 10 |
| `seed` | A seed value for random number generation to ensure reproducible results. Default is 1. | INT | No | 0 to 2147483647 |
| `resolution` | The output resolution of the generated video. This parameter is advanced. | COMBO | Yes | `"720p"`<br />`"1080p"` |
| `movement_amplitude` | The movement amplitude of objects in the frame. This parameter is advanced. | COMBO | Yes | `"auto"`<br />`"small"`<br />`"medium"`<br />`"large"` |

**Constraints:**

* The `image` input must contain exactly one image.
* The input image's aspect ratio must be between 1:4 and 4:1.
* The `prompt` text is limited to a maximum of 2000 characters.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu2ImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `4cf56654286561f3d211ce50d0dce141880fe0e0a63aa45ab41ae0ff5ab6ccc3`


# Vidu2ReferenceVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu2ReferenceVideoNode

The Vidu2 Reference-to-Video Generation node creates a video from a text prompt and multiple reference images.

The Vidu2 Reference-to-Video Generation node creates a video from a text prompt and multiple reference images. You can define up to seven subjects, each with its own set of reference images, and reference them in the prompt using `@subject{subject_id}`. The node generates a video with configurable duration, aspect ratio, and movement.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for video generation. | COMBO | Yes | `"viduq2"` |
| `subjects` | For each subject, provide up to 3 reference images (7 images total across all subjects). Reference them in prompts via `@subject{subject_id}`. | AUTOGROW | Yes | N/A |
| `prompt` | The text description used to guide the video generation. When the `audio` parameter is enabled, the video will include generated speech and background music based on this prompt. | STRING | Yes | N/A |
| `audio` | When enabled, the video will contain generated speech and background music based on the prompt (default: `False`). | BOOLEAN | No | N/A |
| `duration` | The length of the generated video in seconds (default: `5`). | INT | No | 1 to 10 |
| `seed` | A number used to control the randomness of the generation for reproducible results (default: `1`). | INT | No | 0 to 2147483647 |
| `aspect_ratio` | The shape of the video frame. | COMBO | No | `"16:9"`<br />`"9:16"`<br />`"4:3"`<br />`"3:4"`<br />`"1:1"` |
| `resolution` | The pixel resolution of the output video (default: `"720p"`). | COMBO | No | `"720p"`<br />`"1080p"` |
| `movement_amplitude` | Controls the movement amplitude of objects in the frame (default: `"auto"`). | COMBO | No | `"auto"`<br />`"small"`<br />`"medium"`<br />`"large"` |

**Constraints:**

* The `prompt` must be between 1 and 2000 characters long.
* You can define multiple subjects, but the total number of reference images across all subjects must not exceed 7.
* Each individual subject can have a maximum of 3 reference images.
* Each reference image must have a width-to-height ratio between 1:4 and 4:1.
* Each reference image must be at least 128 pixels in both width and height.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu2ReferenceVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `da4b0a24e186f24cff8031c786bb765299b00bbfa13cc4161d53d3a68e466744`


# Vidu2StartEndToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu2StartEndToVideoNode

This node generates a video by interpolating between a provided start frame and an end frame, guided by a text prompt.

This node generates a video by interpolating between a provided start frame and an end frame, guided by a text prompt. It uses a specified Vidu model to create a smooth transition between the two images over a set duration.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Vidu model to use for video generation. | COMBO | Yes | `"viduq2-pro-fast"`<br />`"viduq2-pro"`<br />`"viduq2-turbo"` |
| `first_frame` | The starting image for the video sequence. Only a single image is allowed. | IMAGE | Yes | - |
| `end_frame` | The ending image for the video sequence. Only a single image is allowed. | IMAGE | Yes | - |
| `prompt` | Prompt description (max 2000 characters). | STRING | Yes | - |
| `duration` | The length of the generated video in seconds (default: 5). | INT | No | 2 to 8 |
| `seed` | A number used to initialize the random generation for reproducible results (default: 1). | INT | No | 0 to 2147483647 |
| `resolution` | The output resolution of the generated video. | COMBO | No | `"720p"`<br />`"1080p"` |
| `movement_amplitude` | The movement amplitude of objects in the frame. | COMBO | No | `"auto"`<br />`"small"`<br />`"medium"`<br />`"large"` |

**Note:** The `first_frame` and `end_frame` images must have similar aspect ratios. The node validates that their aspect ratios are within a relative range of 0.8 to 1.25. Only one image is allowed for each input.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu2StartEndToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `01316d15f95f264cadfb33978565fc320a9f42917693faa87c1367c0f31ca400`


# Vidu2TextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu2TextToVideoNode

The Vidu2 Text-to-Video Generation node creates a video from a text description.

The Vidu2 Text-to-Video Generation node creates a video from a text description. It connects to an external API to generate video content based on your prompt, allowing you to control the video's length, visual style, and format.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for video generation. Currently, only one model is available. | COMBO | Yes | `"viduq2"` |
| `prompt` | A textual description for video generation, with a maximum length of 2000 characters. | STRING | Yes | - |
| `duration` | The length of the generated video in seconds. The value can be adjusted using a slider (default: 5). | INT | No | 1 to 10 |
| `seed` | A number used to control the randomness of the generation, allowing for reproducible results. It can be controlled after generation (default: 1). | INT | No | 0 to 2147483647 |
| `aspect_ratio` | The proportional relationship between the video's width and height. | COMBO | No | `"16:9"`<br />`"9:16"`<br />`"3:4"`<br />`"4:3"`<br />`"1:1"` |
| `resolution` | The pixel dimensions of the generated video. This is an advanced parameter. | COMBO | No | `"720p"`<br />`"1080p"` |
| `background_music` | Whether to add background music to the generated video (default: False). This is an advanced parameter. | BOOLEAN | No | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu2TextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `27b7c05ae1b3b23d07e775f67474ecef1ffc0bd8240f4aa2219e15949d854f27`


# Vidu3ImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu3ImageToVideoNode

The Vidu Q3 Image-to-Video Generation node creates a video sequence starting from an input image.

The Vidu Q3 Image-to-Video Generation node creates a video sequence starting from an input image. It uses a Vidu Q3 model to animate the image, optionally guided by a text prompt, and outputs a video file.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for video generation. | DYNAMIC\_COMBO | Yes | `"viduq3-pro"`<br />`"viduq3-turbo"` |
| `image` | An image to be used as the start frame of the generated video. | IMAGE | Yes | - |
| `prompt` | An optional text prompt for video generation (max 2000 characters) (default: empty). | STRING | Yes | - |
| `seed` | The seed value used to control the randomness of the generation (default: 1). | INT | Yes | 0 to 2147483647 |

### viduq3-pro Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `resolution` | Resolution of the output video. | COMBO | Yes | `"720p"`<br />`"1080p"`<br />`"2K"` |
| `duration` | Duration of the output video in seconds (default: 5). | INT | Yes | 1 to 16 |
| `audio` | When enabled, outputs video with sound (including dialogue and sound effects) (default: False). | BOOLEAN | Yes | `True`<br />`False` |

### viduq3-turbo Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `resolution` | Resolution of the output video. | COMBO | Yes | `"720p"`<br />`"1080p"` |
| `duration` | Duration of the output video in seconds (default: 5). | INT | Yes | 1 to 16 |
| `audio` | When enabled, outputs video with sound (including dialogue and sound effects) (default: False). | BOOLEAN | Yes | `True`<br />`False` |

**Note:** The `image` must have an aspect ratio between 1:4 and 4:1 (portrait to landscape). The `prompt` is optional but cannot exceed 2000 characters. The available `resolution` options depend on the selected model: `"viduq3-pro"` supports `"720p"`, `"1080p"`, and `"2K"`; `"viduq3-turbo"` supports `"720p"` and `"1080p"`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu3ImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `77500d1e19928128decc010540670e311cd8ec4fcad913412517f47f0e27e15f`


# Vidu3StartEndToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu3StartEndToVideoNode

This node generates a video by creating a transition between a start frame and an end frame, guided by a text prompt.

This node generates a video by creating a transition between a start frame and an end frame, guided by a text prompt. It uses the Vidu Q3 model to interpolate between the two images and produces a video at the chosen duration and resolution.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for video generation. Selecting an option reveals additional configuration parameters for `resolution`, `duration`, and `audio`. | DYNAMIC\_COMBO | Yes | `"viduq3-pro"`<br />`"viduq3-turbo"` |
| `first_frame` | The starting image of the video sequence. | IMAGE | Yes | - |
| `end_frame` | The ending image of the video sequence. | IMAGE | Yes | - |
| `prompt` | Prompt description (max 2000 characters). | STRING | Yes | Up to 2000 characters |
| `seed` | Seed value used to control the randomness of the generation. Has a control-after-generate option (default: 1). | INT | Yes | 0 to 2147483647 |

### viduq3-pro and viduq3-turbo Inputs

The following parameters are shared by both model options (`viduq3-pro` and `viduq3-turbo`). They appear after a model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `resolution` | Resolution of the output video. | COMBO | Yes | `"720p"`<br />`"1080p"` |
| `duration` | Duration of the output video in seconds (default: 5). | INT | Yes | 1 to 16 |
| `audio` | When enabled, outputs video with sound (including dialogue and sound effects) (default: False). | BOOLEAN | Yes | `True`<br />`False` |

**Note:** The `first_frame` and `end_frame` images must have similar aspect ratios. The aspect ratio of the two images must stay within 80% to 125% of each other (relative closeness between 0.8 and 1.25).

**Note:** For `viduq3-turbo`, the price is 0.06 USD per second at 720p and 0.08 USD per second at 1080p. For `viduq3-pro`, the price is 0.15 USD per second at 720p and 0.16 USD per second at 1080p.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu3StartEndToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `c917867c5a7b68a1286f445025070f9a55d8d10091d9562960e0428cbedf25e4`


# Vidu3TextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu3TextToVideoNode

The Vidu Q3 Text-to-Video Generation node creates a video from a text description.

The Vidu Q3 Text-to-Video Generation node creates a video from a text description. It uses the Vidu Q3 Pro or Q3 Turbo model to generate video content based on your prompt, allowing you to control the video's length, resolution, aspect ratio, and whether it includes audio.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for video generation. Selecting a model reveals additional configuration parameters for aspect ratio, resolution, duration, and audio. | DYNAMIC\_COMBO | Yes | `"viduq3-pro"`<br />`"viduq3-turbo"` |
| `prompt` | A textual description for video generation, with a maximum length of 2000 characters. | STRING | Yes | N/A |
| `seed` | A seed value for controlling the randomness of the generation (default: 1). | INT | Yes | 0 to 2147483647 |

### viduq3-pro and viduq3-turbo Inputs

The following configuration parameters are shared by the `viduq3-pro` and `viduq3-turbo` models.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `aspect_ratio` | The aspect ratio of the output video. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"3:4"`<br />`"4:3"`<br />`"1:1"` |
| `resolution` | Resolution of the output video. | COMBO | Yes | `"720p"`<br />`"1080p"` |
| `duration` | Duration of the output video in seconds (default: 5). | INT | Yes | 1 to 16 |
| `audio` | When enabled, outputs video with sound (including dialogue and sound effects) (default: False). | BOOLEAN | Yes | True/False |

**Note:** The parameters `aspect_ratio`, `resolution`, `duration`, and `audio` are required once a `model` is selected, as they are part of its configuration. The `prompt` must not be empty and cannot exceed 2000 characters.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu3TextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `89c23454375a43cdfaf46c9e0e55a8a8166d02ada47ca2e237bd9f73fa4d78db`


# ViduExtendVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduExtendVideoNode

The Vidu Video Extension node generates additional frames to extend the length of an existing video.

The Vidu Video Extension node generates additional frames to extend the length of an existing video. It uses a specified AI model to create a continuation based on the source video and an optional text prompt.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use for video extension. Selecting a model reveals its specific duration and resolution settings. | DYNAMIC\_COMBO | Yes | `"viduq2-pro"`<br />`"viduq2-turbo"` |
| `video` | The source video to extend. | VIDEO | Yes | - |
| `prompt` | An optional text prompt for the extended video (max 2000 characters; default: empty). | STRING | Yes | - |
| `seed` | A seed value for controlling the randomness of the generation (default: 1). | INT | Yes | 0 to 2147483647 |
| `end_frame` | An optional image to use as the target end frame for the extension. | IMAGE | No | - |

### viduq2-pro and viduq2-turbo Inputs

These settings are shared by both models.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `duration` | Duration of the extended video in seconds (default: 4). This setting appears after selecting a model. | INT | Yes | 1 to 7 |
| `resolution` | Resolution of the output video. This setting appears after selecting a model. | COMBO | Yes | `"720p"`<br />`"1080p"` |

**Note:** The source `video` must have a duration between 4 and 55 seconds. If `end_frame` is provided, its aspect ratio must be between 1:4 and 4:1, and its width and height must each be at least 128 pixels.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The newly generated video file containing the extended footage. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduExtendVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `bfa79dd1aee8a3e56d95fe7a899454b5c5f93679e098f59fc3bf58d93d290819`


# ViduImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduImageToVideoNode

The Vidu Image To Video Generation node creates a short video from a starting image and an optional text description.

The Vidu Image To Video Generation node creates a short video from a starting image and an optional text description. It uses an AI model to generate video content that continues from the provided image frame, and returns the resulting video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model name (default: viduq1) | COMBO | Yes | `viduq1` |
| `image` | An image to be used as the start frame of the generated video | IMAGE | Yes | - |
| `prompt` | A textual description for video generation (default: empty) | STRING | No | - |
| `duration` | Duration of the output video in seconds (default: 5, fixed at 5 seconds) | INT | No | 5-5 |
| `seed` | Seed for video generation (0 for random) (default: 0) | INT | No | 0-2147483647 |
| `resolution` | Supported values may vary by model & duration (default: 1080p) | COMBO | No | `1080p` |
| `movement_amplitude` | The movement amplitude of objects in the frame (default: auto) | COMBO | No | `auto`<br />`small`<br />`medium`<br />`large` |

**Constraints:**

* Only one input image is allowed (cannot process multiple images).
* The input image must have an aspect ratio between 1:4 and 4:1.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video output | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduImageToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `9e3b1ba325c44fcd03207f93030eba1a66507f9613d93135546ab7b6f37f7699`


# ViduMultiFrameVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduMultiFrameVideoNode

This node generates a video by creating transitions between multiple keyframes.

This node generates a video by creating transitions between multiple keyframes. It starts from an initial image and animates through a sequence of user-defined end images and prompts, producing a single video file as output.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The Vidu model to use for video generation. | COMBO | Yes | "viduq2-pro"<br />"viduq2-turbo" |
| `start_image` | The starting frame image. Aspect ratio must be between 1:4 and 4:1. | IMAGE | Yes | Aspect ratio 1:4 to 4:1 |
| `seed` | A seed value for random number generation to ensure reproducible results (default: 1). | INT | Yes | 0 to 2147483647 |
| `resolution` | The resolution of the output video. | COMBO | Yes | "720p"<br />"1080p" |
| `frames` | Number of keyframe transitions (2-9). Selecting a value dynamically reveals the required inputs for each frame. | DYNAMIC\_COMBO | Yes | "2"<br />"3"<br />"4"<br />"5"<br />"6"<br />"7"<br />"8"<br />"9" |

### Frame Inputs (shared by all frame count options)

When `frames` is set to a number, the following three inputs are shown for each frame `i` from 1 to that number. For example, choosing "3" adds `prompt1` / `end_image1` / `duration1`, `prompt2` / `end_image2` / `duration2`, and `prompt3` / `end_image3` / `duration3`.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt{i}` | Text prompt for frame \{i} transition. Multiline text field. Maximum 2000 characters. | STRING | Yes | Up to 2000 characters |
| `end_image{i}` | End frame image for segment \{i}. Aspect ratio must be between 1:4 and 4:1. | IMAGE | Yes | Aspect ratio 1:4 to 4:1 |
| `duration{i}` | Duration for segment \{i} in seconds (default: 4). | INT | Yes | 2 to 7 |

**Notes:**

* All inputs are required. `seed` has a default value but is still a required input.
* `start_image` and every `end_image{i}` must have an aspect ratio between 1:4 and 4:1.
* Every `prompt{i}` has a maximum length of 2000 characters.
* Every `duration{i}` must be between 2 and 7 seconds.
* The number of frames can be between 2 and 9, so the possible frame indices run from 1 to 9.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file containing all the animated transitions. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduMultiFrameVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `ad877532ba27444938b7b2e4634ac7f8a47db0f7fb53967d874ad38b44336dcf`


# ViduReferenceVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduReferenceVideoNode

The Vidu Reference Video Node generates videos from multiple reference images and a text prompt.

The Vidu Reference Video Node generates videos from multiple reference images and a text prompt. It uses AI models to create consistent video content based on the provided images and description. The node supports various video settings including duration, aspect ratio, resolution, and movement control.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model name for video generation (default: "viduq1") | COMBO | Yes | `"viduq1"` |
| `images` | Images to use as references to generate a video with consistent subjects (maximum 7 images) | IMAGE | Yes | - |
| `prompt` | A textual description for video generation | STRING | Yes | - |
| `duration` | Duration of the output video in seconds (default: 5) | INT | No | 5-5 |
| `seed` | Seed for video generation (0 for random) (default: 0) | INT | No | 0-2147483647 |
| `aspect_ratio` | The aspect ratio of the output video | COMBO | No | `"16:9"`<br />`"9:16"`<br />`"1:1"` |
| `resolution` | Supported values may vary by model & duration (default: "1080p") | COMBO | No | `"1080p"` |
| `movement_amplitude` | The movement amplitude of objects in the frame (default: "auto") | COMBO | No | `"auto"`<br />`"small"`<br />`"medium"`<br />`"large"` |

**Constraints and Limitations:**

* The `prompt` field is required and cannot be empty
* Maximum of 7 images allowed for reference
* Each image must have an aspect ratio between 1:4 and 4:1
* Each image must have minimum dimensions of 128x128 pixels
* Duration is fixed at 5 seconds

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video based on the reference images and prompt | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduReferenceVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `087ce07dbf0bdad9dcb1f1487dd95cf1b50d627cc8b1f8a17ff26d74016c2c3e`


# ViduStartEndToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduStartEndToVideoNode

The Vidu Start End To Video Generation node creates a video by generating frames between a starting frame and an ending frame.

The Vidu Start End To Video Generation node creates a video by generating frames between a starting frame and an ending frame. It uses a text prompt to guide the video generation process and supports various video models with different resolution and movement settings. The node validates that the start and end frames have compatible aspect ratios before processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model name | COMBO | Yes | `"viduq1"` |
| `first_frame` | Start frame | IMAGE | Yes | - |
| `end_frame` | End frame | IMAGE | Yes | - |
| `prompt` | A textual description for video generation | STRING | No | - |
| `duration` | Duration of the output video in seconds (default: 5, fixed at 5 seconds) | INT | No | 5-5 |
| `seed` | Seed for video generation (0 for random) (default: 0) | INT | No | 0-2147483647 |
| `resolution` | Supported values may vary by model & duration (default: "1080p") | COMBO | No | `"1080p"` |
| `movement_amplitude` | The movement amplitude of objects in the frame (default: "auto") | COMBO | No | `"auto"`<br />`"small"`<br />`"medium"`<br />`"large"` |

**Note:** The start and end frames must have compatible aspect ratios (validated with min\_rel=0.8, max\_rel=1.25 ratio tolerance).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduStartEndToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `5e8a566373fac84111e90d00c00a6932a23e827f9b4669950c223256c08dd96c`


# ViduTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduTextToVideoNode

The Vidu Text To Video Generation node creates videos from text descriptions.

The Vidu Text To Video Generation node creates videos from text descriptions. It uses the Vidu video generation model to transform your text prompts into video content with customizable settings for duration, aspect ratio, and visual style.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model name | COMBO | Yes | `viduq1` |
| `prompt` | A textual description for video generation | STRING | Yes | - |
| `duration` | Duration of the output video in seconds (default: 5) | INT | No | 5-5 |
| `seed` | Seed for video generation (0 for random) (default: 0) | INT | No | 0-2147483647 |
| `aspect_ratio` | The aspect ratio of the output video | COMBO | No | `16:9`<br />`9:16`<br />`1:1` |
| `resolution` | Supported values may vary by model & duration | COMBO | No | `1080p` |
| `movement_amplitude` | The movement amplitude of objects in the frame | COMBO | No | `auto`<br />`small`<br />`medium`<br />`large` |

**Note:** The `prompt` field is required and cannot be empty. The `duration` parameter is currently fixed at 5 seconds.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video based on the text prompt | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduTextToVideoNode/en.md)

***

**Source fingerprint (SHA-256):** `913efbb516c40e03ced1fef59905c7efa7737f0506368c9afcacb3b65aa4af66`


# Wan2ImageToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan2ImageToVideoApi

The Wan 2.7 Image to Video node generates a video starting from a first-frame image.

The Wan 2.7 Image to Video node generates a video starting from a first-frame image. You can optionally provide a last-frame image to create a transition between the two, or provide an audio file to guide the video's motion and timing. The node uses an AI model to animate the scene based on your text description.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The AI model to use for video generation. | DYNAMIC\_COMBO | Yes | `"wan2.7-i2v"` |
| `first_frame` | First frame image. The output aspect ratio is derived from this image. | IMAGE | Yes | - |
| `last_frame` | Last frame image. The model generates a video transitioning from first to last frame. | IMAGE | No | - |
| `audio` | Audio for driving video generation (e.g., lip sync, beat-matched motion). Duration: 2s-30s. If not provided, the model automatically generates matching background music or sound effects. | AUDIO | No | - |
| `seed` | Seed to use for generation (default: 0). | INT | Yes | 0 to 2147483647 |
| `prompt_extend` | Whether to enhance the prompt with AI assistance (default: True). This is an advanced setting. | BOOLEAN | Yes | True<br />False |
| `watermark` | Whether to add an AI-generated watermark to the result (default: False). This is an advanced setting. | BOOLEAN | Yes | True<br />False |

### wan2.7-i2v Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese. (default: empty) | STRING | Yes | - |
| `negative_prompt` | Negative prompt describing what to avoid. (default: empty) | STRING | Yes | - |
| `resolution` | The resolution of the output video. | COMBO | Yes | `"720P"`<br />`"1080P"` |
| `duration` | The length of the generated video in seconds (default: 5). | INT | Yes | 2 to 15 |

**Note:** The `audio` input has a duration constraint. If provided, the audio file must be between 2 and 30 seconds long.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan2ImageToVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `81b0dc9500ff00e1428422d3d9c8df8f790c1d9dec547dcba0d1aa239f8a8beb`


# Wan2ReferenceVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan2ReferenceVideoApi

This node generates a video featuring a person or object based on provided reference materials.

This node generates a video featuring a person or object based on provided reference materials. It uses the Wan 2.7 model to create videos from a text prompt, supporting single-character performances and multi-character interactions. You must provide at least one reference video or reference image for the generation to work.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The specific model to use for video generation. | DYNAMIC\_COMBO | Yes | "wan2.7-r2v" |
| `seed` | Seed to use for generation, which helps control the randomness of the output (default: 0). | INT | Yes | 0 to 2147483647 |
| `watermark` | Whether to add an AI-generated watermark to the result (default: False). This is an advanced setting. | BOOLEAN | Yes | True<br />False |

### wan2.7-r2v Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the video. Use identifiers such as 'character1' and 'character2' to refer to the reference characters. Must contain at least one character. | STRING | Yes | - |
| `negative_prompt` | Negative prompt describing what to avoid (default: empty). | STRING | No | - |
| `resolution` | The resolution of the output video. | COMBO | Yes | "720P"<br />"1080P" |
| `ratio` | The aspect ratio of the output video. | COMBO | Yes | "16:9"<br />"9:16"<br />"1:1"<br />"4:3"<br />"3:4" |
| `duration` | The length of the generated video in seconds (default: 5). | INT | Yes | 2 to 10 |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_videos` | Growable slot: connect up to 3 reference videos (slots `video1` to `video3`). At least one reference video or image is required overall. | VIDEO | No | 0 to 3 items |
| `reference_images` | Growable slot: connect up to 5 reference images (slots `image1` to `image5`). At least one reference video or image is required overall. | IMAGE | No | 0 to 5 items |

**Important Constraints:**

* You must provide at least one reference video or reference image in the `reference_videos` or `reference_images` inputs. Otherwise the node raises an error.
* The total combined number of reference videos and reference images cannot exceed 5.
* The `prompt` input must contain at least one character.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan2ReferenceVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `52ac550522bf3fe8f57444ce8586fe83be470b893ff8c01292743553cfbd623d`


# Wan2TextToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan2TextToVideoApi

This node generates a video from a text description using the Wan 2.7 model.

This node generates a video from a text description using the Wan 2.7 model. It sends your prompt to the Wan video-generation API, waits for the task to finish, and returns the resulting video. You can optionally connect an audio clip to influence the video's motion and timing; if no audio is provided, the model automatically generates matching audio.

## Inputs

### Common Inputs

These inputs are always available at the top level of the node.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The specific model to use for video generation. | DYNAMIC\_COMBO | Yes | `"wan2.7-t2v"` |
| `audio` | Audio for driving video generation (e.g., lip sync, beat-matched motion). Duration: 3s-30s. If not provided, the model automatically generates matching background music or sound effects. | AUDIO | No | - |
| `seed` | Seed to use for generation (default: 0). | INT | Yes | 0 to 2147483647 |
| `prompt_extend` | Whether to enhance the prompt with AI assistance (default: True). | BOOLEAN | Yes | True<br />False |
| `watermark` | Whether to add an AI-generated watermark to the result (default: False). | BOOLEAN | Yes | True<br />False |

### wan2.7-t2v Inputs

These settings appear when the `wan2.7-t2v` model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese. | STRING | Yes | - |
| `negative_prompt` | Negative prompt describing what to avoid. Default is an empty string. | STRING | No | - |
| `resolution` | The resolution of the output video (default: "720P"). | COMBO | Yes | `"720P"`<br />`"1080P"` |
| `ratio` | The aspect ratio of the output video. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"` |
| `duration` | The length of the video in seconds (default: 5). | INT | Yes | 2 to 15 |

**Note:** The `prompt` input must not be empty. The `audio` input is optional; if provided, the node accepts audio between 1.5 and 60 seconds, even though the tooltip recommends 3s-30s. If no audio is supplied, the model automatically generates matching audio. When `negative_prompt` is left empty, it is not sent to the API. `prompt_extend` and `watermark` are advanced options.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan2TextToVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `2b35fb3e897f8c5fb9786576f4e314cb6709527a3cdc4f2eb9f0600d09076835`


# Wan2VideoContinuationApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan2VideoContinuationApi

The Wan 2.7 Video Continuation node generates a new video segment that continues from the end of an input video clip.

The Wan 2.7 Video Continuation node generates a new video segment that continues from the end of an input video clip. It uses the Wan 2.7 model to synthesize the continuation based on a text prompt and can optionally guide the ending towards a specific target frame.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The video generation model to use. The selected option determines which additional settings appear below. | DYNAMIC\_COMBO | Yes | `"wan2.7-i2v"` |
| `first_clip` | Input video to continue from. Duration: 2s-10s. The output aspect ratio is derived from this video. | VIDEO | Yes | 2s to 10s |
| `last_frame` | Last frame image. The continuation will transition towards this frame. | IMAGE | No | - |
| `seed` | Seed to use for generation. (default: 0) | INT | Yes | 0 to 2147483647 |
| `prompt_extend` | Whether to enhance the prompt with AI assistance. (default: True) | BOOLEAN | Yes | - |
| `watermark` | Whether to add an AI-generated watermark to the result. (default: False) | BOOLEAN | Yes | - |

### wan2.7-i2v Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese. (default: empty string) | STRING | Yes | - |
| `negative_prompt` | Negative prompt describing what to avoid. (default: empty string) | STRING | Yes | - |
| `resolution` | The output resolution for the generated video. | COMBO | Yes | `"720P"`<br />`"1080P"` |
| `duration` | Total output duration in seconds. The model generates continuation to fill the remaining time after the input clip. (default: 5) | INT | Yes | 2 to 15 |

**Note:** The `first_clip` input video must be between 2 and 10 seconds in duration.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video continuation. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan2VideoContinuationApi/en.md)

***

**Source fingerprint (SHA-256):** `591e551676969bc1fedb5f820f6866512c132bb98ee8ef1766d1e0b389e2dc11`


# Wan2VideoEditApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan2VideoEditApi

The Wan 2.7 Video Edit node edits a video using text instructions, reference images, or style transfer.

The Wan 2.7 Video Edit node edits a video using text instructions, reference images, or style transfer. It sends the input video (plus any reference images) to the Wan 2.7 video-edit service and returns a newly generated video based on the chosen resolution, aspect ratio, and duration settings.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to use for video editing. Each option exposes its own set of sub-parameters. | DYNAMIC\_COMBO | Yes | `"wan2.7-videoedit"` |
| `video` | The video to edit. | VIDEO | Yes | - |
| `seed` | Seed to use for generation. (default: 0) | INT | Yes | 0 to 2147483647 |
| `audio_setting` | 'auto': model decides whether to regenerate audio based on the prompt. 'origin': preserve the original audio from the input video. (default: "auto") | COMBO | Yes | `"auto"`<br />`"origin"` |
| `watermark` | Whether to add an AI-generated watermark to the result. (default: False) | BOOLEAN | Yes | - |

### wan2.7-videoedit Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Editing instructions or style transfer requirements. (default: empty string) | STRING | Yes | - |
| `resolution` | The resolution for the output video. | COMBO | Yes | `"720P"`<br />`"1080P"` |
| `ratio` | Aspect ratio. If not changed, approximates the input video ratio. | COMBO | Yes | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"` |
| `duration` | Output duration in seconds. 'auto' matches the input video duration. A specific value truncates from the start of the video. (default: "auto") | COMBO | Yes | `"auto"`<br />`"2"`<br />`"3"`<br />`"4"`<br />`"5"`<br />`"6"`<br />`"7"`<br />`"8"`<br />`"9"`<br />`"10"` |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect 0 to 4 images (`image1`...`image4`) to guide the edit. The count limit is 4 for the wan2.7-videoedit model. | IMAGE | No | 0 to 4 items |

**Constraints:**

* `audio_setting` and `watermark` are advanced options.
* The `prompt` must contain at least 1 character.
* The input `video` must be between 2 and 10 seconds in duration.
* The `reference_images` growable slot accepts a maximum of 4 images.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The edited video generated by the model. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan2VideoEditApi/en.md)

***

**Source fingerprint (SHA-256):** `27283273ee56c90903db103a3e9bc17dc4df0914676c9aedd2a115b07937dc10`


# Wan3ImageToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan3ImageToVideoApi

This node generates a video from a first-frame image using the Wan 3.0 model.

This node generates a video from a first-frame image using the Wan 3.0 model. You can optionally provide a last-frame image to control how the video ends; the model then creates a video that transitions from the first frame to the last frame.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Selects the Wan 3.0 model variant to use and determines which model-specific settings are shown below. | DYNAMIC\_COMBO | Yes | "wan3.0-video"<br />"wan3.0-video-prime" |
| `first_frame` | First frame image. Exactly one image is required. | IMAGE | Yes | Single image |
| `last_frame` | Last frame image. The model generates a video transitioning from first to last frame. Optional; if provided, exactly one image is required. | IMAGE | No | Single image |
| `seed` | Seed to use for generation (default: 42). | INT | Yes | 0 - 2147483647 |
| `watermark` | Whether to add an AI-generated watermark to the result (default: false). | BOOLEAN | Yes | true<br />false |

### wan3.0-video and wan3.0-video-prime Inputs

These model-specific settings are shared by both model options and appear when a model is selected.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese. Can be left empty (default: empty). | STRING | Yes | Up to 20000 characters |
| `resolution` | Resolution of the output video. | COMBO | Yes | "1080P"<br />"720P"<br />"480P" |
| `ratio` | Aspect ratio of the output video. With "adaptive", the output dimensions are derived from the first frame. | COMBO | Yes | "adaptive"<br />"16:9"<br />"9:16"<br />"1:1"<br />"4:3"<br />"3:4" |
| `duration` | Output duration in seconds. With "auto", the model chooses a duration that fits the prompt. | COMBO | Yes | "auto"<br />"2" - "30" |
| `audio` | Whether the output video contains an audio track (default: true). | BOOLEAN | Yes | true<br />false |
| `prompt_extend` | Whether to enhance the prompt with AI assistance (default: true). | BOOLEAN | Yes | true<br />false |

Note: The node accepts exactly one `first_frame` image and optionally one `last_frame` image. If more than one image is connected to either input, an error is raised. When `last_frame` is provided, the generated video transitions from the first frame to the last frame. The `prompt` is limited to 20,000 characters. The price of a run depends on the selected `model`, `resolution`, and `duration`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video. Contains an audio track when the `audio` option is enabled. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan3ImageToVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `ff9fce554fa7aa5fc8729b5f84b2f8bf89e8e7772ce1c32b1307d0dc4882200c`


# Wan3ReferenceToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan3ReferenceToVideoApi

This node generates a video from a text prompt and optional reference images, videos, and audio using the Wan 3.0 model.

This node generates a video from a text prompt and optional reference images, videos, and audio using the Wan 3.0 model. Reference media can be combined freely and mentioned in the prompt as @Image1, @Video1, and @Audio1. The node submits the generation request to the Wan API and returns the finished video.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Selects the Wan 3.0 model variant used for generation. | DYNAMIC\_COMBO | Yes | `wan3.0-video`<br />`wan3.0-video-prime` |
| `seed` | Seed to use for generation. Default: 42. | INT | Yes | 0 to 2147483647 |
| `watermark` | Whether to add an AI-generated watermark to the result. Default: false. | BOOLEAN | Yes | true<br />false |

### wan3.0-video and wan3.0-video-prime Inputs

Both model options share the same parameter set.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese. Refer to connected reference media as @Image1, @Video1, @Audio1, numbered per type in input order. Default: empty. | STRING | Yes | Up to 20,000 characters |
| `resolution` | Resolution of the output video. | COMBO | Yes | "1080P"<br />"720P"<br />"480P" |
| `ratio` | Aspect ratio of the output video. With "adaptive", the output dimensions are derived from the input media. | COMBO | Yes | "adaptive"<br />"16:9"<br />"9:16"<br />"1:1"<br />"4:3"<br />"3:4" |
| `duration` | Output duration in seconds. With "auto", the model chooses a duration that fits the prompt and reference media. The combined duration of reference videos and output must not exceed 30 seconds. | COMBO | Yes | "auto"<br />"2" through "30" (integer seconds) |
| `audio` | Whether the output video contains an audio track. Default: true. | BOOLEAN | Yes | true<br />false |
| `prompt_extend` | Whether to enhance the prompt with AI assistance. Default: true. | BOOLEAN | Yes | true<br />false |

### Reference Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `reference_images` | Growable slot: connect 1 to 10 reference images. References are numbered as image1 to image10 in input order. | IMAGE | No | 0 to 10 images |
| `reference_videos` | Growable slot: connect 1 to 5 reference videos. References are numbered as video1 to video5 in input order. | VIDEO | No | 0 to 5 videos |
| `reference_audios` | Growable slot: connect 1 to 5 reference audio clips. References are numbered as audio1 to audio5 in input order. | AUDIO | No | 0 to 5 audio clips |

**Constraints:**

* The prompt must contain at least one non-empty character, or at least one reference image, video, or audio input must be connected.
* Reference tags in the prompt must match connected inputs. For example, @Image1 refers to the first connected reference image, @Video2 to the second connected reference video, and @Audio1 to the first connected reference audio. Tags are numbered separately per type in input order.
* Each connected reference image must contain exactly one image, not a batch.
* Each reference video must be 15 seconds or shorter. The total duration of all reference videos must not exceed 15 seconds.
* Each reference audio must be 15 seconds or shorter. The total duration of all reference audios must not exceed 15 seconds.
* When `duration` is not "auto", the total duration of all reference videos plus the selected output duration must not exceed 30 seconds.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The generated video file. Includes an audio track when the `audio` parameter is enabled. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan3ReferenceToVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `09caa8142d71235417a3dfc5676c5f6accc2af1287fad3b7050844dd9453cc64`


# WanImageToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanImageToVideoApi

The Wan Image to Video node generates a video from a single input image and a text prompt.

The Wan Image to Video node generates a video from a single input image and a text prompt. It uses the provided image as the first frame and creates a video sequence based on the description, with options for resolution, duration, audio, and other advanced settings.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use (default: "wan2.6-i2v") | COMBO | Yes | "wan2.5-i2v-preview"<br />"wan2.6-i2v" |
| `image` | Input image that serves as the first frame for video generation. Exactly one image is required. | IMAGE | Yes | - |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese (default: empty). | STRING | Yes | - |
| `negative_prompt` | Negative prompt describing what to avoid (default: empty). | STRING | No | - |
| `resolution` | Video resolution quality (default: "720P"). The Wan 2.6 model does not support 480P. | COMBO | No | "480P"<br />"720P"<br />"1080P" |
| `duration` | Duration of the generated video in seconds. A 15-second duration is supported only by the Wan 2.6 model (default: 5). | INT | No | 5-15 (step: 5) |
| `audio` | Audio must contain a clear, loud voice, without extraneous noise or background music. When provided, audio duration must be between 3.0 and 29.0 seconds. | AUDIO | No | - |
| `seed` | Seed to use for generation (default: 0). | INT | No | 0-2147483647 |
| `generate_audio` | If no audio input is provided, generate audio automatically (default: False). | BOOLEAN | No | - |
| `prompt_extend` | Whether to enhance the prompt with AI assistance (default: True). | BOOLEAN | No | - |
| `watermark` | Whether to add an AI-generated watermark to the result (default: False). | BOOLEAN | No | - |
| `shot_type` | Specifies the shot type for the generated video, that is, whether the video is a single continuous shot or multiple shots with cuts. This parameter takes effect only when prompt\_extend is True (default: "single"). | COMBO | No | "single"<br />"multi" |

**Constraints:**

* Exactly one input image is required for video generation.
* The Wan 2.6 model (`wan2.6-i2v`) does not support 480P resolution.
* A 15-second duration is supported only by the Wan 2.6 model (`wan2.6-i2v`).
* When audio is provided, it must be between 3.0 and 29.0 seconds in duration.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | Generated video based on the input image and prompt. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanImageToVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `dabcbfa3118669d9ff5b40b79ef643ffcf7ac5e510e61d6ad859d80360061673`


# WanReferenceVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanReferenceVideoApi

The Wan Reference to Video node uses the visual appearance and voice from one or more input reference videos, along with a text prompt, to generate a new video.

The Wan Reference to Video node uses the visual appearance and voice from one or more input reference videos, along with a text prompt, to generate a new video. It maintains consistency with the characters from the reference material while creating new content based on your description.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The specific AI model to use for video generation. | COMBO | Yes | `"wan2.6-r2v"` |
| `prompt` | A description of the elements and visual features for the new video. Supports English and Chinese. Use identifiers like `character1` and `character2` to refer to the characters from the reference videos. | STRING | Yes | - |
| `negative_prompt` | A description of elements or features to avoid in the generated video. | STRING | No | - |
| `reference_videos` | A list of video inputs used as references for character appearance and voice. You must provide at least one video. Each video can be assigned a name like `character1`, `character2`, or `character3`. | AUTOGROW | Yes | - |
| `size` | The resolution and aspect ratio for the output video. | COMBO | Yes | `"720p: 1:1 (960x960)"`<br />`"720p: 16:9 (1280x720)"`<br />`"720p: 9:16 (720x1280)"`<br />`"720p: 4:3 (1088x832)"`<br />`"720p: 3:4 (832x1088)"`<br />`"1080p: 1:1 (1440x1440)"`<br />`"1080p: 16:9 (1920x1080)"`<br />`"1080p: 9:16 (1080x1920)"`<br />`"1080p: 4:3 (1632x1248)"`<br />`"1080p: 3:4 (1248x1632)"` |
| `duration` | The length of the generated video in seconds (default: 5). | INT | Yes | 5 to 10 |
| `seed` | A random seed value for reproducible results. A value of 0 will generate a random seed. | INT | No | 0 to 2147483647 |
| `shot_type` | Specifies whether the generated video is a single continuous shot or contains multiple shots with cuts. | COMBO | Yes | `"single"`<br />`"multi"` |
| `watermark` | When enabled, an AI-generated watermark is added to the final video (default: False). | BOOLEAN | No | - |

**Constraints:**

* Each video provided in `reference_videos` must be between 2 and 30 seconds in duration.
* The `duration` parameter is limited to values of 5 or 10 seconds.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The newly generated video file. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanReferenceVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `65ca81a7b5e83f8d8f4c00db41e24d5238ef438887362838351464e77a3af0c2`


# WanTextToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanTextToVideoApi

The Wan Text to Video node generates video content based on text descriptions.

The Wan Text to Video node generates video content based on text descriptions. It uses AI models to create videos from prompts and supports various video sizes, durations, and optional audio inputs. The node can automatically generate audio when needed and provides options for prompt enhancement and watermarking.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | Model to use (default: "wan2.6-t2v") | COMBO | Yes | "wan2.5-t2v-preview"<br />"wan2.6-t2v" |
| `prompt` | Prompt describing the elements and visual features. Supports English and Chinese (default: "") | STRING | Yes | - |
| `negative_prompt` | Negative prompt describing what to avoid (default: "") | STRING | No | - |
| `size` | Video resolution and aspect ratio (default: "720p: 1:1 (960x960)") | COMBO | No | "480p: 1:1 (624x624)"<br />"480p: 16:9 (832x480)"<br />"480p: 9:16 (480x832)"<br />"720p: 1:1 (960x960)"<br />"720p: 16:9 (1280x720)"<br />"720p: 9:16 (720x1280)"<br />"720p: 4:3 (1088x832)"<br />"720p: 3:4 (832x1088)"<br />"1080p: 1:1 (1440x1440)"<br />"1080p: 16:9 (1920x1080)"<br />"1080p: 9:16 (1080x1920)"<br />"1080p: 4:3 (1632x1248)"<br />"1080p: 3:4 (1248x1632)" |
| `duration` | Duration of the video in seconds. A 15-second duration is available only for the Wan 2.6 model (default: 5) | INT | No | 5-15 (in steps of 5) |
| `audio` | Audio must contain a clear, loud voice, without extraneous noise or background music | AUDIO | No | - |
| `seed` | Seed to use for generation (default: 0) | INT | No | 0-2147483647 |
| `generate_audio` | If no audio input is provided, generate audio automatically (default: False) | BOOLEAN | No | - |
| `prompt_extend` | Whether to enhance the prompt with AI assistance (default: True) | BOOLEAN | No | - |
| `watermark` | Whether to add an AI-generated watermark to the result (default: False) | BOOLEAN | No | - |
| `shot_type` | Specifies the shot type for the generated video, that is, whether the video is a single continuous shot or multiple shots with cuts. This parameter takes effect only when prompt\_extend is True (default: "single") | COMBO | No | "single"<br />"multi" |

**Note:** The Wan 2.6 model does not support 480p resolutions. A 15-second duration is only supported by the Wan 2.6 model. When providing audio input, it must be between 3.0 and 29.0 seconds in duration and contain clear voice without background noise or music.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video based on the input parameters | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanTextToVideoApi/en.md)

***

**Source fingerprint (SHA-256):** `105ff4b575dc6cd319448b0f4c0e9cfab360df025480190ae6bccc324d351525`


# WavespeedFlashVSRNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WavespeedFlashVSRNode

The WavespeedFlashVSRNode is a fast, high-quality video upscaler that boosts resolution and restores clarity for low-resolution or blurry footage.

The WavespeedFlashVSRNode is a fast, high-quality video upscaler that boosts resolution and restores clarity for low-resolution or blurry footage. It processes a video input and outputs a new video at a user-selected higher resolution.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The input video file to be upscaled. Must be in MP4 container format with a duration between 5 seconds and 10 minutes. | VIDEO | Yes | N/A |
| `target_resolution` | The desired resolution for the upscaled output video. | STRING | Yes | `"720p"`<br />`"1080p"`<br />`"2K"`<br />`"4K"` |

**Input Constraints:**

* The input `video` file must be in the MP4 container format.
* The duration of the input `video` must be between 5 seconds and 10 minutes (600 seconds).

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The upscaled video file at the selected target resolution. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WavespeedFlashVSRNode/en.md)

***

**Source fingerprint (SHA-256):** `d7885eeb2dacfc2bc398d1bc991620be479f45d8edbdca7eb046a21500581529`


# Create asset reference from existing hash
Source: https://docs.comfy.org/api-reference/cloud/asset/create-asset-reference-from-existing-hash

/openapi-cloud.yaml post /api/assets/from-hash
Creates a new asset reference using an existing hash from cloud storage.
This avoids re-uploading file content when the underlying data already exists,
which is useful for large files or when referencing well-known assets.
The user provides their own metadata and tags for the new reference.




# Get asset details
Source: https://docs.comfy.org/api-reference/cloud/asset/get-asset-details

/openapi-cloud.yaml get /api/assets/{id}
Retrieves detailed information about a specific asset



# Get asset metadata from remote URL
Source: https://docs.comfy.org/api-reference/cloud/asset/get-asset-metadata-from-remote-url

/openapi-cloud.yaml get /api/assets/remote-metadata
Retrieves metadata for an asset from a remote download URL without downloading the entire file.
Supports various sources including CivitAI and other model repositories.
Uses HEAD requests or API calls to fetch metadata efficiently.
This endpoint is for previewing metadata before downloading, not for getting metadata of existing assets.




# Initiate background download for large files
Source: https://docs.comfy.org/api-reference/cloud/asset/initiate-background-download-for-large-files

/openapi-cloud.yaml post /api/assets/download
Initiates a background download job for large files from Huggingface or Civitai.

If the file already exists in storage, the asset record is created immediately and returned (200 OK).
If the file doesn't exist, a background task is created and the task ID is returned (202 Accepted).
The frontend can track progress using GET /api/tasks/{task_id}.




# List user assets
Source: https://docs.comfy.org/api-reference/cloud/asset/list-user-assets

/openapi-cloud.yaml get /api/assets
Retrieves a paginated list of assets belonging to the authenticated user.
Supports filtering by tags, name, metadata, and sorting options.




# Update asset metadata
Source: https://docs.comfy.org/api-reference/cloud/asset/update-asset-metadata

/openapi-cloud.yaml put /api/assets/{id}
Updates an asset's metadata. At least one field must be provided.
Only name, tags, and user_metadata can be updated.




# Upload a new asset
Source: https://docs.comfy.org/api-reference/cloud/asset/upload-a-new-asset

/openapi-cloud.yaml post /api/assets
Uploads a new asset to the system with associated metadata.
Supports two upload methods:
1. Direct file upload (multipart/form-data)
2. URL-based upload (application/json with source: "url")

If an asset with the same hash already exists, returns the existing asset.




# Get related mask layer files
Source: https://docs.comfy.org/api-reference/cloud/file/get-related-mask-layer-files

/openapi-cloud.yaml get /api/files/mask-layers
Given a mask file (any of the 4 layers), returns all related mask layer files.
This is used by the mask editor to load the paint, mask, and painted layers
when reopening a previously edited mask.




# Upload a mask image
Source: https://docs.comfy.org/api-reference/cloud/file/upload-a-mask-image

/openapi-cloud.yaml post /api/upload/mask
Upload a mask image to be applied to an existing image.

Image limits apply to both the uploaded mask and the referenced
original image:
  - Maximum file size: 50 MB
  - Maximum width/height per edge: 16384 px
  - Maximum total pixel count: 64 megapixels (67108864 pixels)

Uploads that exceed any of these limits are rejected with HTTP 400.




# Upload an image file
Source: https://docs.comfy.org/api-reference/cloud/file/upload-an-image-file

/openapi-cloud.yaml post /api/upload/image
Upload an image file to cloud storage.

Image limits:
  - Maximum file size: 50 MB
  - Maximum width/height per edge: 16384 px
  - Maximum total pixel count: 64 megapixels (67108864 pixels)

Uploads that exceed any of these limits are rejected with HTTP 400.




# View a file
Source: https://docs.comfy.org/api-reference/cloud/file/view-a-file

/openapi-cloud.yaml get /api/view
Retrieve and view a file from the ComfyUI file system.
This endpoint is typically used to view generated images or other output files.




# Get execution history (v2)
Source: https://docs.comfy.org/api-reference/cloud/job/get-execution-history-v2

/openapi-cloud.yaml get /api/history_v2
**Deprecated.** Use [`/api/jobs`](#tag/job/GET/api/jobs) instead. This endpoint is maintained for ComfyUI compatibility but will be removed in a future release; no removal date set.

Retrieve execution history for the authenticated user with pagination support.
Returns a lightweight history format with filtered prompt data (workflow removed from extra_pnginfo).




# Get full job details
Source: https://docs.comfy.org/api-reference/cloud/job/get-full-job-details

/openapi-cloud.yaml get /api/jobs/{job_id}
Retrieve complete details for a specific job including workflow and outputs.
Used for detail views, workflow re-execution, and debugging.




# Get history for specific prompt
Source: https://docs.comfy.org/api-reference/cloud/job/get-history-for-specific-prompt

/openapi-cloud.yaml get /api/history_v2/{prompt_id}
**Deprecated.** Use [`/api/jobs/{job_id}`](#tag/job/GET/api/jobs/{job_id}) instead — the `prompt_id` returned by `/api/prompt` is the same value as `job_id`. This endpoint is maintained for ComfyUI compatibility but will be removed in a future release; no removal date set.

Retrieve detailed execution history for a specific prompt ID.
Returns full history data including complete prompt information.




# Get job status
Source: https://docs.comfy.org/api-reference/cloud/job/get-job-status

/openapi-cloud.yaml get /api/job/{job_id}/status
Returns the current status of a specific job by ID



# Get queue information
Source: https://docs.comfy.org/api-reference/cloud/job/get-queue-information

/openapi-cloud.yaml get /api/queue
Returns information about running and pending items in the queue



# Interrupt currently running jobs
Source: https://docs.comfy.org/api-reference/cloud/job/interrupt-currently-running-jobs

/openapi-cloud.yaml post /api/interrupt
Cancel all currently RUNNING jobs for the authenticated user.
This will interrupt any job that is currently in 'in_progress' status.
Note: This endpoint only affects running jobs. To cancel pending jobs, use /api/queue.




# List jobs with pagination and filtering
Source: https://docs.comfy.org/api-reference/cloud/job/list-jobs-with-pagination-and-filtering

/openapi-cloud.yaml get /api/jobs
Retrieve a paginated list of jobs for the authenticated user.
Returns lightweight job data optimized for list views.
Workflow and full outputs are excluded to reduce payload size.




# Manage execution history
Source: https://docs.comfy.org/api-reference/cloud/job/manage-execution-history

/openapi-cloud.yaml post /api/history
Clear all history for the authenticated user or delete specific job IDs.
Supports clearing all history or deleting specific job IDs.




# Manage queue operations
Source: https://docs.comfy.org/api-reference/cloud/job/manage-queue-operations

/openapi-cloud.yaml post /api/queue
Cancel specific PENDING jobs by ID or clear all pending jobs in the queue.
Note: This endpoint only affects pending jobs. To cancel running jobs, use /api/interrupt.




# Get available model folders
Source: https://docs.comfy.org/api-reference/cloud/model/get-available-model-folders

/openapi-cloud.yaml get /api/experiment/models
Returns a list of model folders available in the system.
This is an experimental endpoint that replaces the legacy /models endpoint.




# Get model preview image
Source: https://docs.comfy.org/api-reference/cloud/model/get-model-preview-image

/openapi-cloud.yaml get /api/experiment/models/preview/{folder}/{path_index}/{filename}
Returns a preview image for the specified model.
The image is returned in WebP format for optimal performance.




# Get models in a specific folder
Source: https://docs.comfy.org/api-reference/cloud/model/get-models-in-a-specific-folder

/openapi-cloud.yaml get /api/experiment/models/{folder}
Returns a list of models available in the specified folder.
This is an experimental endpoint that provides enhanced model information.




# Get all node information
Source: https://docs.comfy.org/api-reference/cloud/node/get-all-node-information

/openapi-cloud.yaml get /api/object_info
Returns information about all available nodes



# Get server feature flags
Source: https://docs.comfy.org/api-reference/cloud/node/get-server-feature-flags

/openapi-cloud.yaml get /api/features
Returns the server's feature capabilities



# Get a specific subgraph blueprint
Source: https://docs.comfy.org/api-reference/cloud/workflow/get-a-specific-subgraph-blueprint

/openapi-cloud.yaml get /api/global_subgraphs/{id}
Returns the full data for a specific subgraph blueprint by ID



# Get available subgraph blueprints
Source: https://docs.comfy.org/api-reference/cloud/workflow/get-available-subgraph-blueprints

/openapi-cloud.yaml get /api/global_subgraphs
Returns a list of globally available subgraph blueprints.
These are pre-built workflow components that can be used as nodes.
The data field contains a promise that resolves to the full subgraph JSON.




# Get available workflow templates
Source: https://docs.comfy.org/api-reference/cloud/workflow/get-available-workflow-templates

/openapi-cloud.yaml get /api/workflow_templates
Returns available workflow templates



# Get information about current prompt executions
Source: https://docs.comfy.org/api-reference/cloud/workflow/get-information-about-current-prompt-executions

/openapi-cloud.yaml get /api/prompt
Returns information about current prompts in the execution queue



# Submit a workflow for execution
Source: https://docs.comfy.org/api-reference/cloud/workflow/submit-a-workflow-for-execution

/openapi-cloud.yaml post /api/prompt
Submit a workflow to be executed by the backend.
The workflow is a JSON object describing the nodes and their connections.




# Asset bytes
Source: https://docs.comfy.org/api-reference/v2/assets/asset-bytes

/openapi-v2.yaml get /api/v2/assets/{id}/content
Serves the bytes directly on surfaces where the platform stores blobs
itself (self-hosted); on Cloud and serverless issues a `302` to a
fresh signed URL. Range requests are supported for resumable
downloads of large outputs.




# Asset metadata
Source: https://docs.comfy.org/api-reference/v2/assets/asset-metadata

/openapi-v2.yaml get /api/v2/assets/{id}
Returns the asset object with a fresh short-lived `url` for the content. Re-fetching always yields fresh URLs.



# Delete an asset record
Source: https://docs.comfy.org/api-reference/v2/assets/delete-an-asset-record

/openapi-v2.yaml delete /api/v2/assets/{id}
Deletes the asset RECORD. The underlying content-addressed blob is
untouched while any other asset still references it (hash dedup means
blobs are shared) — deleting an asset never destroys another asset's
bytes.

A second delete of the same id returns `404`, indistinguishable from
an id that never existed or belongs to another account.




# Existence check for a blob by blake3 hash
Source: https://docs.comfy.org/api-reference/v2/assets/existence-check-for-a-blob-by-blake3-hash

/openapi-v2.yaml head /api/v2/assets/by-hash/{hash}
`200` if the calling account can mint from this blob, `404` otherwise. Same account-scoping as `from-hash`; lets a client decide between the dedup fast-path and a full upload before sending bytes.



# Mint an asset over existing bytes (dedup fast-path)
Source: https://docs.comfy.org/api-reference/v2/assets/mint-an-asset-over-existing-bytes-dedup-fast-path

/openapi-v2.yaml post /api/v2/assets/from-hash
Zero-byte fast-path: mints a new asset UUID over a blob the platform
already has, identified by its blake3 hash.

Trust boundary: resolves only against blobs the platform itself
ingested and hashed, and only those the calling account is authorized
to use — the client hash is a lookup key, never an authority to
register new content. A miss and "exists but not yours" are
deliberately indistinguishable (`404` `blob_not_found`).




# Upload an asset (single-call multipart)
Source: https://docs.comfy.org/api-reference/v2/assets/upload-an-asset-single-call-multipart

/openapi-v2.yaml post /api/v2/assets
Single-call `multipart/form-data` upload. The platform streams the
bytes through its trusted byte-path, dedups by the server-computed
hash, and mints the asset record.

The blake3 hash is always computed server-side from the received
bytes — a client-declared `expected_hash` is verified, never trusted.
The uploaded asset is referenceable immediately; any content scanning
runs in the background and does not block the response.

~100 MB single-request expectation for v1; chunked/resumable large
uploads are a deliberate open question.




# Job status (the polling workhorse)
Source: https://docs.comfy.org/api-reference/v2/jobs/job-status-the-polling-workhorse

/openapi-v2.yaml get /api/v2/jobs/{id}
Returns the full job object: current status, the latest progress
snapshot, and every output committed so far (`outputs` populates
incrementally while the job runs). This is the authoritative,
resumable view of a job; everything on the SSE stream is derived
from it.




# Live event stream (SSE)
Source: https://docs.comfy.org/api-reference/v2/jobs/live-event-stream-sse

/openapi-v2.yaml get /api/v2/jobs/{id}/events
Server-Sent Events stream of the job's live state. On connect the
client receives the current snapshot (a `status` event, the latest
`progress`, and the most recent `preview` if any), then future
updates. The stream ends after either the terminal `status` event
or a terminal `error` event (see the `error` event below).

Live push only — NOT a replayable log: events carry no `id`, there
is no `Last-Event-ID` resume, and frames emitted while disconnected
are gone. Each `progress` event is a complete snapshot, so a single
one fully re-syncs a reconnecting client; the authoritative state is
always `GET /api/v2/jobs/{id}`.




# Request cancellation
Source: https://docs.comfy.org/api-reference/v2/jobs/request-cancellation

/openapi-v2.yaml post /api/v2/jobs/{id}/cancel
Requests cancellation and returns the current job object —
`canceling` (interruption takes effect at node/step boundaries),
`canceled` where the provider's record already shows the interrupt, or
already-terminal. Idempotent: canceling a finished job is a no-op
returning the terminal state. On serverless, GPU seconds consumed
before the interrupt takes effect are still billed.




# Submit a workflow for execution
Source: https://docs.comfy.org/api-reference/v2/jobs/submit-a-workflow-for-execution

/openapi-v2.yaml post /api/v2/jobs
Accepts the API-format workflow graph verbatim. Validation is
synchronous: graph structure, unknown node classes, and asset
references (`core/ASSET` objects — every referenced `id` must exist
and be owned by the caller). A `201` means the job is durably
recorded and queued.

UI-format workflow JSON (the export with `nodes`/`links`) is
rejected with `workflow_format_ui`.

`Idempotency-Key` is single-use (reject-on-duplicate, NOT
record-and-replay): the first request to present a given key is
processed normally; ANY later request presenting the same key — a
retry, a concurrent duplicate, or a same-key request with a different
body — is rejected `422` `idempotency_key_reuse` and is never
re-executed. The key is claimed only for a request that actually
reaches submission and is released if that submission definitively
fails without creating a job (a validation error, or an upstream
reject such as out-of-credits or queue-full), so a legitimate retry
with the same key can proceed. If a submission's outcome is unknown
(an upstream timeout or 5xx where the job may or may not have been
created), the key stays claimed and the retry is rejected: poll or
list your jobs to find the possibly-created job rather than
resubmitting. Keys expire after 24h. There is no response replay and
no `Idempotency-Replayed` header.

Reserved for post-MVP and rejected if present today: `webhook_url`,
`inputs`.




# The workflow behind a job — authoring version if pinned, executed graph otherwise
Source: https://docs.comfy.org/api-reference/v2/jobs/the-workflow-behind-a-job-—-authoring-version-if-pinned-executed-graph-otherwise

/openapi-v2.yaml get /api/v2/jobs/{id}/workflow
Returns the workflow behind a job. The response's `format` field says
which of two different shapes `workflow` is in:

- `format: save` — the original authoring workflow exactly as saved
  in the Comfy Cloud editor at the version the job ran, including
  canvas layout and frontend-only nodes (e.g. Note nodes; Get/Set
  nodes not yet expanded). Returned only when the job is pinned to a
  specific workflow version — see the "when you get which" note
  below.
- `format: api` — the executed API-format prompt graph the job
  actually ran: frontend-only constructs are gone and Get/Set nodes
  are expanded. This is the same shape `POST /api/v2/jobs`'s
  `workflow` request field takes, and never includes the
  submission's `extra_data`, which can carry a live credential.

Always branch on `format`, never assume one or the other — which
shape comes back depends on how the job was submitted, not on
anything the caller controls per-request.

A deliberate sub-resource, not a field on `GET /api/v2/jobs/{id}` —
so the polling workhorse stays cheap and a caller pays for this only
when it actually wants the workflow (for example, to recover what
produced a given output).

Tied to the job's own retention: this 404s under the same conditions
`GET /api/v2/jobs/{id}` does (unknown, not-yours, or past its
retention deadline) — there is no separate lifetime for the
workflow.

**When you get which:** a job only carries a pinned workflow version
when it was submitted with that association. Today that means jobs
submitted from the Comfy Cloud frontend/editor. Jobs submitted
directly through this v2 API (`POST /api/v2/jobs`) do not carry that
association — v2 job submission has no version-linking fields yet —
so they always get `format: api`. This is expected, not a bug: it
will change once v2 submission grows the same version pinning.

A job pinned to a version also falls back to `format: api` if that
version, or the workflow it belongs to, is no longer readable by the
caller — for example the caller deleted the workflow since the job
ran. This is the same fallback as an unpinned job, and for the same
reason: it is preferable to the alternative of erroring the whole
request over data that is genuinely gone.




# What the run printed
Source: https://docs.comfy.org/api-reference/v2/jobs/what-the-run-printed

/openapi-v2.yaml get /api/v2/jobs/{id}/logs
Returns the job's captured execution log. Fetched on demand: a log
is a debugging artifact a caller wants occasionally, while
`GET /api/v2/jobs/{id}` is polled to terminal on every run, so the
log is a resource of its own rather than a field that would ride
every one of those polls to be read at most once.

Captured whenever the worker reports its own outcome, success and
failure alike, since a job that succeeds while producing the wrong
thing is exactly what a failure-only log cannot explain. A run the
platform or the provider killed — out of memory, a crashed worker, a
timeout, a job past its maximum runtime — never gets that far, so it
reaches a terminal status carrying no log at all. That is a real gap
and worth stating: the failures a caller most wants a log for are
the ones least likely to have produced one.

**`204` is the normal answer for a job with no log**, and the cases
behind it are deliberately not distinguished: this surface does not
capture logs at all, the job has not finished, the job predates log
capture, the run was killed before the worker could report one,
capture was attempted and failed, or the job ran on the public demo
deployment, which captures and stores the log like every other
serverless deployment but withholds it on read, because that surface
takes callers with no credential and a job id would otherwise be the
only thing between one anonymous caller and another's run.

Because a `204` never says which of those it is, do not branch on the
reason — but do note that one of them resolves itself. A job that has
not finished may have a log once it does, so a caller that wants one
reads again after a terminal status. A `204` on a job already in a
terminal state is final, and so is a missing `urls.logs`; both mean
stop asking.

**Only jobs run on the serverless platform** (a
`{deployment}.run.comfy.app` host) have one today. An implementation
that captures no logs must still serve this operation, answering
`204` for every job it can read, so that the two answers stay
distinct — Comfy Cloud does. A self-hosted deployment on a build
predating this operation has not implemented it yet and will answer
a routing `404` instead, which is the case `job.urls.logs` exists to
keep a client out of: its absence says the surface has no logs at
all, without a request.

Tied to the job's own retention: this `404`s under the same
conditions `GET /api/v2/jobs/{id}` does (unknown, not-yours, or past
its retention deadline). Nothing ages a log out ahead of the job's
own `expires_at`, so a job never outlives its log.

Live tailing is not offered here yet. When it is, it arrives on this
same path under `Accept: text/event-stream`, leaving this
JSON snapshot the default; its resume semantics will be defined
then, against a capture that is incremental. Until then the SSE
`log` event on `GET /api/v2/jobs/{id}/events` is the reserved live
rail, and this is the authoritative snapshot it reconciles against.




# Comfy API v2 Overview
Source: https://docs.comfy.org/api-reference/v2/overview

Reference for the official Comfy API v2: run ComfyUI workflows from external applications by uploading inputs, submitting jobs, and polling for results.

<Warning>
  **Beta:** Comfy API v2 is at `0.1.x` and the surface may still change. Changes within v2 will be additive; anything breaking would ship as v3.
</Warning>

The official, versioned HTTP API for running ComfyUI workflows from external applications: upload inputs, submit a workflow, observe execution, retrieve results.

Most people should start with the [Comfy SDKs](/development/api-development/sdks), which wrap this API in Python and TypeScript. Call these endpoints directly if you are working in another language. The full endpoint documentation is in the API Reference pages of this section, generated from the OpenAPI specification.

## Where v2 Runs

The same API is served by three surfaces, so one integration can move between them by changing the base URL.

**Comfy Cloud.** The managed, multi-tenant service at `https://cloud.comfy.org`. Create an [API key](/development/api-development/getting-an-api-key) and you can submit any workflow. Cloud-specific features such as credits, model browsing, and queue management live on the [v1 Cloud API](/development/cloud/overview), not on v2.

**Comfy API deployments.** An environment you deploy through the [Developer Platform](https://platform.comfy.org) gets its own dedicated endpoint at `https://{deployment}.run.comfy.app`, serving the same v2 API with the same API key. A Comfy API deployment runs workflows against one pinned environment, so it scales independently and `GET /workflow` returns the executed graph. See the [Comfy API deployment guide](/development/serverless/overview) for building and deploying.

**Open-source ComfyUI, via the proxy.** During the beta, a self-hosted ComfyUI speaks v2 through [comfy-api-proxy](https://github.com/Comfy-Org/comfy-api-proxy), a small open-source service that runs alongside it:

```bash theme={null}
pip install comfy-api-proxy
comfy-api-proxy
```

By default it proxies the ComfyUI on `127.0.0.1:8188` and serves the v2 API on `127.0.0.1:8189`, binding to loopback only. Authentication is off by default, with an optional static bearer token. The proxy is a stopgap: once v2 stabilizes it moves into ComfyUI core and the proxy is no longer needed. See [Your own ComfyUI](/development/api-development/sdks#your-own-comfyui) in the SDK guide for configuration details.

## Design Principles

* **Poll first.** Every capability is reachable via plain GET polling. The SSE stream is a live enhancement, never the source of truth.
* **Everything is resumable.** Submission is idempotent, and job state and outputs are retrievable by ID until `expires_at`. The URL you get back for an output is shorter-lived than that: see [Output URLs and How Long They Last](#output-urls-and-how-long-they-last).
* **Content-addressed assets.** Assets are UUID-identified records over blobs keyed by a server-computed blake3 hash, so identical inputs are not uploaded twice.
* **Follow links, do not build URLs.** Responses embed their follow-up URLs.

See [Design Notes](/development/api-development/sdks-design) for the reasoning behind these.

## Base URLs

| Surface | URL | Authentication |
| - | - | - |
| Comfy Cloud | `https://cloud.comfy.org` | `Authorization: Bearer <api-key>` |
| Comfy API deployment | `https://{deployment}.run.comfy.app` | `Authorization: Bearer <api-key>` |
| Self-hosted, via [comfy-api-proxy](https://github.com/Comfy-Org/comfy-api-proxy) | `http://127.0.0.1:8189` | None by default, optional static bearer token |

## Endpoint Categories

| Category | Description |
| - | - |
| Assets | UUID-identified records over content-addressed blobs. Upload inputs, download outputs. |
| Jobs | One execution of a workflow. Durable, pollable, and cancelable. |

## Output URLs and How Long They Last

Three different lifetimes govern "the URL for my output" and they are not the same number. Any application that shows outputs to its own users has to plan for all three.

### The Two URL Shapes

| Shape | Where you get it | Can a third party open it? | How long it lasts |
| - | - | - | - |
| Content endpoint, `{base}/api/v2/assets/{id}/content` | `url` on each entry of a job's `outputs` | No. It is an authenticated route and answers `401` without your API key. | Stable. It resolves for as long as the asset exists. |
| Signed storage URL | `url` on an `Asset` response, the `302` `Location` the content endpoint redirects to, and `getDownloadUrl()` in both SDKs | Yes. It carries its own authorization, so a browser or another service reads it with no key of its own. | Short. Roughly 6 hours on Comfy Cloud today. |

The practical consequence: `Output.url` is not a shareable link. Put it in an `<img src>` that your users' browsers load and they get a `401`, because their browser does not carry your API key. The signed URL is the one you can hand out.

Self-hosted ComfyUI behind [comfy-api-proxy](https://github.com/Comfy-Org/comfy-api-proxy) has no signed URLs at all. The proxy serves the bytes from the content endpoint, normal authentication applies, and the SDKs report the expiry as `null` (Python: `None`).

### Reading the Signed URL's Expiry

On Comfy Cloud and Comfy API deployments a signed URL is minted with a validity of **approximately 6 hours**. That number is a server-side setting rather than part of the API contract, so treat it as an order of magnitude and never hard-code it. Read the expiry off the response you were given:

* `url_expires_at` on an `Asset` response is the real expiry of the `url` in that same response.
* `getDownloadUrl()` returns it alongside the URL, as `expiresAt` in TypeScript and `expires_at` in Python.

### `url_expires_at` on a Job Output Is a Different Number

`url_expires_at` on an entry of a job's `outputs` is **not** the signed URL's expiry. On Comfy Cloud it repeats the job's own `expires_at`, which today is the job's `created_at` plus a fixed 30 day window.

That window is a placeholder. The platform has no job retention or garbage-collection policy behind it yet, so the 30 days is a stand-in that lets the field be non-null, not a commitment about how long an output stays fetchable. Do not read it as a promise, and do not key a cache off it. This page will be updated if a real retention policy replaces it.

### Showing an Output in Your Own Product

To still be showing an output a day later, do one of these:

* **Re-host the bytes.** Download the output once and copy it into your own storage. Most applications end up here.
* **Re-mint on demand.** Persist the asset `id`, then resolve it to a fresh URL (`GET /api/v2/assets/{id}`, or `getDownloadUrl()`) at the moment you render, and use that URL immediately.
* **Proxy it.** Fetch `Output.url` from your own backend, which already holds the API key, and stream the bytes to your user.

What does not work is persisting a signed URL. It is good for hours, not days, so a stored copy keeps working through local testing and then breaks for your users once it expires.

## Comfy Router

Comfy API v2 runs workflows as durable jobs you submit and poll. For direct model calls (one partner model, one request, the model's native input and output), see the [Comfy Router](/development/comfy-router/quickstart). Review the [Router limitations](/development/comfy-router/limitations) first. Router is not generally available yet.


# BatchImagesMasksLatentsNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BatchImagesMasksLatentsNode

The Batch Images/Masks/Latents node combines multiple inputs of the same type into a single batch.

The Batch Images/Masks/Latents node combines multiple inputs of the same type into a single batch. It automatically detects whether the inputs are images, masks, or latent representations and uses the appropriate batching method. This is useful for preparing multiple items for processing by nodes that accept batched inputs.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `inputs` | A dynamic list of inputs to be combined into a batch. You can add between 1 and 50 items. All items must be of the same type (all images, all masks, or all latents). | IMAGE, MASK, or LATENT | Yes | 1 to 50 inputs |

**Note:** The node automatically determines the data type (IMAGE, MASK, or LATENT) based on the first item in the `inputs` list. All subsequent items must match this type. The node will fail if you try to mix different data types.

**Additional behavior based on input type:**

* **Images**: When batching images, the node pads images with fewer color channels to match the maximum channel count among all inputs (padding value is 1.0). It also resizes all images to match the dimensions of the first image using bilinear interpolation.
* **Masks**: When batching masks, the node resizes all masks to match the dimensions of the first mask using bilinear interpolation.
* **Latents**: When batching latents, the node reshapes all latent tensors to match the dimensions of the first latent's samples. It also combines the `batch_index` values from each latent, extending the list with sequential indices if a latent lacks a `batch_index`.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | A single batched output. The data type matches the input type (batched IMAGE, batched MASK, or batched LATENT). | IMAGE, MASK, or LATENT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BatchImagesMasksLatentsNode/en.md)

***

**Source fingerprint (SHA-256):** `9f82b036c99577ebcda6de647c662def572ae1f01bd78dca1a0ab32f4698e09e`


# ConcatenateVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConcatenateVideo

Concatenates multiple video segments into a single video, preserving the order in which they are connected.

Concatenates multiple video segments into a single video, preserving the order in which they are connected. Compatible encoded inputs are combined without being decoded, and an optional separate audio track can be supplied to replace the original audio.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `videos` | Video segments to concatenate in input order. Connect 1 to 100 videos; each video appears as a separate input slot labeled `video_1`, `video_2`, etc. | VIDEO | Yes | 1 to 100 segments |
| `codec` | Codec used to encode video tensors. Auto uses H.264; already encoded videos remain unchanged. Default: "auto" | COMBO | Yes | `"auto"`<br />Other options are defined by the available video codec types. |
| `complete_audio` | Optional complete soundtrack for the concatenated video. Overrides audio carried by the input videos. | AUDIO | No | N/A |

**Note:** The `videos` input accepts between 1 and 100 video segments. If `complete_audio` is provided, it replaces the audio of all input videos. When `codec` is set to "auto", compatible encoded inputs are concatenated without decoding.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `VIDEO` | The concatenated video. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConcatenateVideo/en.md)

***

**Source fingerprint (SHA-256):** `f591aecb83754127e1c86ed0488548f9e7d99f3559c95a1c86c55fa5d430713d`


# CreateVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateVideo

The Create Video node combines a sequence of images into a video.

The Create Video node combines a sequence of images into a video. You can set the playback speed in frames per second, optionally add audio, and choose the compression format, bit depth, and color space of the resulting video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | The images to create a video from. | IMAGE | Yes | - |
| `fps` | The frames per second for the video playback speed (default: 30.0). | FLOAT | Yes | 1.0 - 120.0 |
| `audio` | The audio to add to the video. | AUDIO | No | - |
| `bit_depth` | Auto uses 8-bit for sRGB and 10-bit for HDR and HDR PQ. Explicit 8-bit and 10-bit choices are independent of colorspace. (default: "auto") | COMBO | No | `"auto"`<br />8<br />10 |
| `color_space` | Colorspace of the input images. HDR selects BT.2020/HLG and HDR PQ selects BT.2020/PQ. (default: "sRGB") | COMBO | No | `"sRGB"`<br />`"HDR"`<br />`"HDR PQ"` |
| `codec` | Optionally encode the video immediately. None keeps the images in tensor form; Auto uses H.264. (default: "none") | COMBO | No | `"none"`<br />Available video codec options from the video codec list (e.g. `"auto"` and other supported codecs) |

Note: When `bit_depth` is set to `"auto"`, the node automatically uses 10-bit for the HDR and HDR PQ color spaces, and 8-bit for sRGB.

Note: The `codec` parameter is an advanced option. When it is left at `"none"`, the output stays in tensor form; selecting any other codec encodes the video immediately.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output` | The generated video containing the input images and optional audio. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateVideo/en.md)

***

**Source fingerprint (SHA-256):** `9274559caabbafbcaad47883bf017967f9685f155ea1031e66cf22ee8d0d14c3`


# CustomCombo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CustomCombo

The Custom Combo node lets you define your own list of text options for a dropdown menu instead of choosing from fixed values.

The Custom Combo node lets you define your own list of text options for a dropdown menu instead of choosing from fixed values. It is a frontend-focused node that also has a backend representation, so workflows that contain it stay compatible. When you select an option, the node outputs the selected text and its index position.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `choice` | The text option selected from the custom dropdown. The list of available options is defined by the user in the node's frontend interface. | COMBO | Yes | User-defined |
| `index` | An integer value that can be used to specify an index. Default: 0. | INT | No | Any integer (default: 0) |

**Note:** Validation for this node's inputs is intentionally disabled. This allows you to write any custom text options in the frontend without the backend checking whether your selection matches a predefined list. Widgets other than the combo dropdown are fully defined in the frontend. This node is marked as experimental.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `STRING` | The text string of the option selected from the custom combo box. | STRING |
| `INDEX` | The index position of the selected option in the dropdown list. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CustomCombo/en.md)

***

**Source fingerprint (SHA-256):** `143eafcf32de7ebaf72b5387537154b5deee7d3e3a520a0b2c12ac4fb67890f8`


# FrameInterpolate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FrameInterpolate

The Frame Interpolate node creates new frames between existing ones in a sequence of images, effectively increasing the frame rate.

The Frame Interpolate node creates new frames between existing ones in a sequence of images, effectively increasing the frame rate. It uses an AI model to predict what the intermediate frames should look like, which can be used to create smooth slow-motion effects or to increase the smoothness of a video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `interp_model` | The frame interpolation model to use for generating intermediate frames | INTERP\_MODEL | Yes | - |
| `images` | A batch of consecutive images (frames) to interpolate between. Requires at least 2 images. If fewer than 2 frames are provided, the node returns the input images unchanged. | IMAGE | Yes | - |
| `multiplier` | The number of times to multiply the frame count. For example, a multiplier of 2 doubles the number of frames. (default: 2) | INT | Yes | 2 to 16 |

**Note:** The node requires at least 2 input frames and a `multiplier` of at least 2. If either condition is not met, the input images are returned unchanged.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `IMAGE` | A new batch of images with the interpolated frames inserted between the original frames, resulting in a smoother sequence. The total number of output frames is `(number of input frames - 1) * multiplier + 1`. | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FrameInterpolate/en.md)

***

**Source fingerprint (SHA-256):** `e0b9dd6ec3b09e665bcc0f95d2b7a0209d9045ba9b96828e46f126e6914f049c`


# GetItemFromList - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GetItemFromList

This node returns a single item from a list, selected by its position.

This node returns a single item from a list, selected by its position. You provide the list and the index number of the item you want, and the node outputs that item. This makes it useful for picking one specific element out of a group of values, such as a particular image from a batch.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `list` | The list of values to select from. Because this node is marked as taking a list input, the connected value is handled as a group of items. | Any Type | Yes | Any list of values |
| `index` | The position of the item to return. The value starts at 0, so `0` returns the first item, `1` returns the second item, and so on (default: 0). | INT | Yes | Any integer index |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `OUTPUT` | The single item located at the given `index` within the provided `list`. | Any Type |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GetItemFromList/en.md)

***

**Source fingerprint (SHA-256):** `11c1c90fed0e29f1110b4c1dda64d60797aff38d7f3af69f76b74e94fe94e976`


# GetVideoComponents - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GetVideoComponents

The Get Video Components node extracts all the main elements from a video file.

The Get Video Components node extracts all the main elements from a video file. It separates the video into individual frames, extracts the audio track, and provides the video's frame rate, bit depth, and color space. This allows you to work with each component independently for further processing or analysis.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The video to extract components from. | VIDEO | Yes | - |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The individual frames extracted from the video as separate images. | IMAGE |
| `audio` | The audio track extracted from the video. | AUDIO |
| `fps` | The frame rate of the video in frames per second. | FLOAT |
| `bit_depth` | The bit depth of the video. | COMBO |
| `color_space` | The color space of the video. | COMBO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GetVideoComponents/en.md)

***

**Source fingerprint (SHA-256):** `b57dbf1120105885d17361f07ec96c078aac9ae9a84beb63319885df679e4f81`


# ImageHistogram - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageHistogram

The ImageHistogram node analyzes the color distribution of an input image.

The ImageHistogram node analyzes the color distribution of an input image. It calculates and outputs several histograms, which are graphs showing how many pixels in the image have each possible intensity value. It generates separate histograms for the red, green, and blue color channels, a composite RGB histogram, and a luminance histogram based on a standard brightness formula. Each histogram contains 256 bins, covering intensity levels from 0 to 255.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to analyze. The node processes the first image in the batch. | IMAGE | Yes | N/A |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `rgb` | A composite histogram representing the average pixel intensity across the red, green, and blue channels. | HISTOGRAM |
| `luminance` | A histogram of the image's perceived brightness, calculated using the ITU-R BT.709 standard luminance formula. | HISTOGRAM |
| `red` | A histogram showing the distribution of pixel intensities in the red color channel. | HISTOGRAM |
| `green` | A histogram showing the distribution of pixel intensities in the green color channel. | HISTOGRAM |
| `blue` | A histogram showing the distribution of pixel intensities in the blue color channel. | HISTOGRAM |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageHistogram/en.md)

***

**Source fingerprint (SHA-256):** `5020f5cedd325250a207a00950011f4b6dc19ddfe4d172665ffca4982731dd5e`


# LTXVPreprocess - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVPreprocess

The LTXVPreprocess node applies video compression preprocessing to images.

The LTXVPreprocess node applies video compression preprocessing to images. It simulates the quality loss of video compression by encoding an image as a single-frame MP4 video and then decoding it back, allowing you to control the compression level.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `image` | The input image to be processed | IMAGE | Yes | - |
| `img_compression` | Amount of compression to apply on image. A value of 0 disables compression entirely (default: 35) | INT | No | 0-100 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `output_image` | The processed output image with applied compression artifacts | IMAGE |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVPreprocess/en.md)

***

**Source fingerprint (SHA-256):** `4381837f2778948e6d8b710cf1857ce9e579b3cc630223d97266162b9799342b`


# LoadVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadVideo

The Load Video node loads video files from the input directory and makes them available for processing in the workflow.

The Load Video node loads video files from the input directory and makes them available for processing in the workflow. It reads video files from the designated input folder and outputs them as video data that can be connected to other video processing nodes.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `file` | The video file to load from the input directory. The dropdown list is dynamically populated with all video files found in the ComfyUI input folder, and new video files can be uploaded directly through the file picker. | COMBO | Yes | Multiple options available (all video files in the input directory) |

**Note:** The available options for the `file` parameter are dynamically populated from the video files present in the input directory. Only files matching supported video content types are displayed, and the list is sorted alphabetically. You can also upload a new video file directly through the node's file picker interface. If a previously selected video file can no longer be found, the node reports an invalid file error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The loaded video data that can be passed to other video processing nodes for further manipulation or analysis. | VIDEO |

**Note:** The node also produces a preview of the loaded video, which is displayed directly on the node.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadVideo/en.md)

***

**Source fingerprint (SHA-256):** `dcdd252792ade2a106c11826bbe7344011f0bc08506b80d634043a4dc156e076`


# LoadVideoDataSetFromFolder - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadVideoDataSetFromFolder

Loads a dataset of videos from a selected folder inside the ComfyUI input directory and returns them as a list of lazy video references.

Loads a dataset of videos from a selected folder inside the ComfyUI input directory and returns them as a list of lazy video references. This node loads a dataset of videos: frames are decoded only when another node actually needs them. Supported formats are MP4, AVI, MOV, WEBM, MKV, and FLV.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `folder` | The folder containing video files. | COMBO | Yes | All subfolders available in the ComfyUI input directory (populated dynamically) |

**Note:** The selected folder must be a subfolder of the ComfyUI input directory and must contain at least one supported video file. Supported extensions are MP4, AVI, MOV, WEBM, MKV, and FLV. If no supported video files are found, or if the folder path resolves outside the input directory, the node raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `videos` | A list of lazy video references, one for each supported video file in the selected folder, sorted alphabetically by file name. Video frames are decoded only when the output is consumed by another node. | VIDEO (list) |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadVideoDataSetFromFolder/en.md)

***

**Source fingerprint (SHA-256):** `6a7e6115872bb994fa554bb9de84bcd419106485403a3d2db654cbdd6c72bbe5`


# LoadVideoTextDataSetFromFolder - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadVideoTextDataSetFromFolder

This node loads video files and their matching text captions from a folder inside the ComfyUI input directory, and returns them as two lists: videos and captions.

This node loads video files and their matching text captions from a folder inside the ComfyUI input directory, and returns them as two lists: videos and captions. The video entries are lazy references, so frames are decoded only when a downstream node needs them. Supported formats are MP4, AVI, MOV, WEBM, MKV, and FLV, and nested folders with a repeat-count prefix (for example `5_classname/`, as used by tools like kohya-ss/sd-scripts) are also supported.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `folder` | The folder containing video files and .txt captions. | COMBO | Yes | Dynamically lists all subfolders inside the ComfyUI input directory |

The selected folder must be a subfolder of the ComfyUI input directory; a folder name that resolves outside of that directory raises an error. If the selected folder contains no files with a supported video extension (MP4, AVI, MOV, WEBM, MKV, FLV), the node raises an error. For nested folders whose name starts with a number followed by an underscore (for example `5_classname`), each video inside that folder is included in the dataset the number of times given by that prefix. Each video's caption is read from a `.txt` file with the same base name; if no matching `.txt` file exists, the caption is an empty string.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `videos` | Lazy video references; frames are decoded only when needed downstream. One entry per video file found in the folder. | VIDEO (list) |
| `texts` | List of text captions. One caption per video; if a video has no matching `.txt` file, its caption is an empty string. | STRING (list) |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadVideoTextDataSetFromFolder/en.md)

***

**Source fingerprint (SHA-256):** `21ed21bc3189e96be5c7f0415c65e8749d6591cf19bddf4350a3b0af48b92841`


# MarkdownNote - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MarkdownNote

Node to add annotations to a workflow.

Node to add annotations to a workflow. It supports text formatting using Markdown syntax.

## Inputs

## Outputs

The node doesn't have outputs.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MarkdownNote/en.md)


# Note - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Note

Node to add annotations to a workflow.

Node to add annotations to a workflow.

## Inputs

## Outputs

The node doesn't have outputs.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Note/en.md)


# PreviewAny - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PreviewAny

PreviewAny converts any input value into readable text so you can inspect it.

PreviewAny converts any input value into readable text so you can inspect it. Strings pass through unchanged, numbers and booleans become plain text, and other data types are serialized to JSON when possible (falling back to their plain string form if serialization fails). The resulting text is shown in the user interface and also returned as a string output for further processing.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `source` | Accepts any input data type for preview display. If no value is provided, the preview shows 'None'. | ANY | Yes | Any data type |

**Conversion behavior**

* Values of type STRING are shown exactly as provided.
* Values of type INT, FLOAT, or BOOLEAN are converted to plain text.
* Any other non-empty value is converted to JSON text with an indent of 4 spaces; if that conversion fails, the node falls back to the value's plain text form. If that also fails, the preview shows the message 'source exists, but could not be serialized.'
* If no value is connected or the value is empty, the preview shows 'None'.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `result` | The input value converted to text format. The same text is also displayed in the user interface. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PreviewAny/en.md)

***

**Source fingerprint (SHA-256):** `66b5283b2d7d43e679c0bc6cdcad54c92539a986763333972e722b39c7963be8`


# Reroute - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Reroute

Node Name: Reroute Node Node Purpose: Mainly used to organize the logic of overly long connection lines in the ComfyUI workflow.

Node Name: Reroute Node
Node Purpose: Mainly used to organize the logic of overly long connection lines in the ComfyUI workflow.

## How to Use Reroute Nodes

| Menu Options | Description |
| - | - |
| Show Type | Display the node's type property |
| Hide Type By Default | Hide the node's type property by default |
| Set Vertical | Set the node's wiring direction to vertical |
| Set Horizontal | Set the node's wiring direction to horizontal |

When your wiring logic is too long and complex, and you want to tidy up the interface, you can insert a `Reroute` node between two connection points. The input and output of this node are not type-restricted, and the default style is horizontal. You can change the wiring direction to vertical through the right-click menu.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Reroute/en.md)


# ResolutionSelector - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResolutionSelector

The Resolution Selector node calculates pixel width and height based on a chosen aspect ratio and a target total resolution in megapixels.

The Resolution Selector node calculates pixel width and height based on a chosen aspect ratio and a target total resolution in megapixels. It is useful for generating consistent dimensions for other nodes, such as the Empty Latent Image node.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `aspect_ratio` | The aspect ratio for the output dimensions (default: `"1:1 (Square)"`). | COMBO | Yes | `"1:1 (Square)"`<br />`"2:3 (Portrait Photo)"`<br />`"3:2 (Photo)"`<br />`"3:4 (Portrait Standard)"`<br />`"4:3 (Standard)"`<br />`"9:16 (Portrait Widescreen)"`<br />`"16:9 (Widescreen)"`<br />`"21:9 (Ultrawide)"` |
| `megapixels` | Target total megapixels. 1.0 MP ≈ 1024x1024 for square (default: 1.0). | FLOAT | Yes | 0.1 - 16.0 (step: 0.1) |
| `preview` | Live preview of the calculated output resolution. This read-only widget updates automatically and does not accept user input. | RESOLUTION\_PREVIEW | No | N/A |
| `multiple` | Nearest multiple of the result to set the selected resolution to (default: 8). | INT | No | 8 - 128 (step: 4) |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `width` | Calculated width in pixels multiplied by the selected multiple. | INT |
| `height` | Calculated height in pixels multiplied by the selected multiple. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResolutionSelector/en.md)

***

**Source fingerprint (SHA-256):** `dd4c7f977ed69a873a48da4b01c5c8f0b6563cfd743740235fc0ad5762579697`


# SaveVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveVideo

The Save Video node saves the input video to your ComfyUI output directory.

The Save Video node saves the input video to your ComfyUI output directory. You can choose the file name prefix, the container format, the video codec, and encoding options such as quality. The node automatically generates a unique file name using a counter and can embed workflow metadata in the saved file.

## Inputs

### Common Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The video to save. | VIDEO | Yes | - |
| `filename_prefix` | The prefix for the file to save. This may include formatting information such as `%date:yyyy-MM-dd%` or `%Empty Latent Image.width%` to include values from nodes (default: `video/ComfyUI`). | STRING | Yes | - |
| `format` | The output container. Auto uses MP4 for Auto/H.264 and WebM for AV1. MP4, MKV, and WebM select a specific container. Selecting a format also determines which codec options are available (default: `auto`). | DYNAMIC\_COMBO | Yes | `"auto"`<br />`"mp4"`<br />`"mkv"`<br />`"webm"` |
| `codec` | The output video codec. Auto preserves a compatible source stream. H.264 and AV1 re-encoding support SDR, HDR (HLG), and HDR PQ. This selector is nested under the chosen format (default: `auto`). | DYNAMIC\_COMBO | No | `"auto"`<br />`"h264"`<br />`"av1"` (not available with the `webm` format) |

### H.264 Inputs

These inputs appear when `codec` is `"h264"` and are available with the `auto`, `mp4`, and `mkv` formats.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `encoding` | Automatic preserves compatible H.264 streams. Re-encode applies custom encoding options. | DYNAMIC\_COMBO | No | `"auto"`<br />`"re-encode"` |
| `crf` | Lower values produce higher quality and larger files. Appears when `encoding` is `"re-encode"` (default: 23.0). | FLOAT | No | 0.0 to 51.0 |

### AV1 Inputs

These inputs appear when `codec` is `"av1"` and are available with the `auto`, `mp4`, `mkv`, and `webm` formats.

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `encoding` | Automatic preserves compatible AV1 streams. Re-encode applies custom encoding options. | DYNAMIC\_COMBO | No | `"auto"`<br />`"re-encode"` |
| `crf` | Lower values produce higher quality and larger files. Appears when `encoding` is `"re-encode"` (default: 30.0). | FLOAT | No | 0.0 to 63.0 |

Note: When `format` is `"auto"`, the saved container is chosen automatically: `av1` produces WebM, while `auto` and `h264` produce MP4. The `webm` format only allows the `auto` and `av1` codecs. When `codec` is `"auto"`, the source video stream is preserved rather than re-encoded. The saved file uses a counter suffix to avoid overwriting existing files. The file extension is determined by the resolved container. Workflow metadata (the prompt and extra node information) is embedded in the saved file unless metadata saving is disabled at startup.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The input video, unchanged. | VIDEO |
| `ui` | A preview of the saved video file, including the file path and subfolder information for display in the UI. | PREVIEW\_VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveVideo/en.md)

***

**Source fingerprint (SHA-256):** `8078f692b5c366447a1b08f351637baff901e489f2389e7a26c945661f75c37a`


# SaveWEBM - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveWEBM

The SaveWEBM node saves a sequence of images as a WEBM video file.

The SaveWEBM node saves a sequence of images as a WEBM video file. It takes multiple input images and encodes them into a video using either the VP9 or AV1 codec with configurable quality settings and frame rate. The resulting video file is saved to the output directory with metadata including prompt information.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `images` | RGBA images are saved with their alpha channel as transparency (vp9 codec only). | IMAGE | Yes | - |
| `filename_prefix` | Prefix for the output filename (default: "ComfyUI"). | STRING | No | - |
| `codec` | Video codec to use for encoding. | COMBO | Yes | "vp9"<br />"av1" |
| `fps` | Frame rate for the output video (default: 24.0). | FLOAT | No | 0.01-1000.0 |
| `crf` | Higher crf means lower quality with a smaller file size, lower crf means higher quality higher filesize (default: 32.0). | FLOAT | No | 0-63.0 |

**Note on alpha channel:** The alpha channel from RGBA images is only preserved when using the VP9 codec. When using the AV1 codec, the alpha channel is ignored and only RGB data is encoded.

**Note on file naming:** Videos are saved to the output directory as `{filename_prefix}_{counter:05}_.webm`, where the counter automatically increments to avoid overwriting existing files.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `images` | The input images, passed through unchanged after the video is saved. | IMAGE |
| UI preview | Video preview showing the saved WEBM file. | PREVIEW |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveWEBM/en.md)

***

**Source fingerprint (SHA-256):** `55496b10af66a908ef035d236f8fab8193c1ae44408dab9d202deadff3be2715`


# SeedNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SeedNode

The Seed node provides an integer value that can be used as a seed to control the reproducibility of random operations in other nodes.

The Seed node provides an integer value that can be used as a seed to control the reproducibility of random operations in other nodes. By supplying a consistent starting value, it helps keep generated results repeatable when needed.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `seed` | The seed value to use. The control after generate option determines whether the value stays fixed or changes after each generation; in this node it is set to fixed. | INT | Yes | 0 to 9223372036854775807 |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `seed` | The generated seed value. | INT |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SeedNode/en.md)

***

**Source fingerprint (SHA-256):** `19f9b22945bb152ff5066195067f1b6b4c006589f26c7533fad905044ac3b7fa`


# ShuffleVideoDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ShuffleVideoDataset

This node takes a list of videos and randomly reorders them.

This node takes a list of videos and randomly reorders them. It uses a random seed to make the shuffle reproducible, so the same seed always produces the same output order.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `videos` | List of videos to shuffle. | VIDEO | Yes | List of video inputs |
| `seed` | Random seed for shuffling (default: 0). | INT | No | 0 to 18446744073709551615 |

Note: The seed value is reduced modulo 4294967295 (2^32 - 1) before being used. As a result, seeds that differ by a multiple of 4294967295 produce the same output order.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `videos` | Shuffled list of videos in random order. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ShuffleVideoDataset/en.md)

***

**Source fingerprint (SHA-256):** `0bd32b664197d3bbd4c53f65e29ef38fba836579f07f05cb7fb85f3b8a1024ac`


# ShuffleVideoTextDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ShuffleVideoTextDataset

This node randomly shuffles the order of pairs of video-text in a list, keeping each video paired with its corresponding text.

This node randomly shuffles the order of pairs of video-text in a list, keeping each video paired with its corresponding text. It takes two lists of equal length and applies the same random permutation to both, ensuring that the original pairings are preserved after shuffling. A seed value controls the shuffle order so results can be reproduced.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `videos` | List of videos to shuffle. | VIDEO | Yes | List of video items |
| `texts` | List of texts to shuffle (the captions paired with the videos). | STRING | Yes | List of text strings |
| `seed` | Random seed that determines the shuffle order (default: 0). | INT | Yes | 0 to 18446744073709551615 |

Note: `videos` and `texts` must have the same length, since the node pairs each video with the text at the same position and preserves those pairings when shuffling. Internally, the `seed` value is reduced using modulo 4294967295 (2^32 - 1) before the random order is generated, so very large seed values may produce the same shuffle as smaller ones.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `videos` | Shuffled videos in the new random order. | VIDEO |
| `texts` | Shuffled texts in the same new order as the videos. | STRING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ShuffleVideoTextDataset/en.md)

***

**Source fingerprint (SHA-256):** `834305718cd53a86211363750e887ffccdb54bc3b628dc17f049e546c234f9cb`


# TerminalLog - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TerminalLog

Terminal Log (Manager) node is primarily used to display the running information of ComfyUI in the terminal within the ComfyUI interface.

Terminal Log (Manager) node is primarily used to display the running information of ComfyUI in the terminal within the ComfyUI interface. To use it, you need to set the `mode` to **logging** mode. This will allow it to record corresponding log information during the image generation task. If the `mode` is set to **stop** mode, it will not record log information.
When you access and use ComfyUI via remote connections or local area network connections, Terminal Log (Manager) node becomes particularly useful. It allows you to directly view error messages from the CMD within the ComfyUI interface, making it easier to understand the current status of ComfyUI's operation.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TerminalLog/en.md)


# Video Slice - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Video Slice

The Video Slice node allows you to extract a specific segment from a video.

The Video Slice node allows you to extract a specific segment from a video. You can define a start time and a duration to trim the video, or simply skip the beginning frames. If the requested duration is longer than the remaining video, the node can either return what's available or raise an error.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The input video to be sliced. | VIDEO | Yes | - |
| `start_time` | Start time in seconds (default: 0.0). | FLOAT | Yes | -1e5 to 1e5 |
| `duration` | Duration in seconds, or 0 for unlimited duration (default: 0.0). | FLOAT | Yes | 0.0 and above |
| `strict_duration` | If True, when the specified duration is not possible, an error will be raised (default: False). | BOOLEAN | Yes | - |

**Note:** If the video cannot be sliced for the given `start_time` and `duration`, the node raises an error. When `strict_duration` is False, the node returns the available portion of the video when the requested duration exceeds the remaining length; when True, it raises an error instead.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The trimmed video segment. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! \[Edit on GitHub]\([https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui\_embedded\_docs/docs/Video](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Video) Slice/en.md)

***

**Source fingerprint (SHA-256):** `439b76528742c1fbe230eee9502e945847ae99a58a9bd81a7a7dc3b20e15d450`


# VideoCrop - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VideoCrop

This node crops a video to a rectangular region defined in pixels, keeping only the area inside that rectangle.

This node crops a video to a rectangular region defined in pixels, keeping only the area inside that rectangle. It saves a temporary MP4 preview of the cropped result and outputs the cropped video.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The source video that will be cropped. | VIDEO | Yes | Any video |
| `crop` | Crop region in pixels. Zero width/height keeps the full frame. The crop rectangle provides `x`, `y`, `width`, and `height` values, all with a default of 0. | VIDEO\_EDIT | Yes | `x` ≥ 0<br />`y` ≥ 0<br />`width` ≥ 0<br />`height` ≥ 0<br />All values default to 0 |

Note: The crop region is described in pixel coordinates. When the width and height are 0, no cropping is applied and the node outputs the full input video.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The video cropped to the selected rectangular region. When the crop width and height are 0, the output is the full input video. The cropped result is also saved as a temporary MP4 file and shown as a video preview. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VideoCrop/en.md)

***

**Source fingerprint (SHA-256):** `0c4ebd51027669fc232fe42a5e8840b5e4e95083b6794cd7b4c43123ddc0341b`


# VideoFrameSample - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VideoFrameSample

The VideoFrameSample node extracts a fixed number of frames from a video using one of four strategies.

The `VideoFrameSample` node extracts a fixed number of frames from a video using one of four strategies. For the contiguous strategies "head" and "tail", the output is a lazy video reference (frames are not decoded); for the non-contiguous strategies "uniform" and "random", only the selected frames are decoded.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Input video. | VIDEO | Yes | – |
| `num_frames` | Number of frames to sample (default: 16). | INT | Yes | 1 – 9999 |
| `strategy` | uniform: evenly spaced, head: first N, tail: last N, random: random sorted (default: "uniform"). | COMBO | Yes | "uniform"<br />"head"<br />"tail"<br />"random" |
| `seed` | Random seed, only used with the "random" strategy (default: 0). | INT | Yes | 0 – 18446744073709551615 |

* `num_frames` is automatically clamped to the total frame count of the input video.
* The `seed` parameter has no effect unless `strategy` is set to `"random"`.
* When `strategy` is `"uniform"` and `num_frames` is 1, the middle frame of the video is selected.
* An unrecognized `strategy` value raises an error.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | Sampled video. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VideoFrameSample/en.md)

***

**Source fingerprint (SHA-256):** `727504a9cf7fe5505c33da071cb8f21a38e1b7c0f964c5da172d9cedfc2f2300`


# VideoRandomTemporalCrop - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VideoRandomTemporalCrop

Randomly crop a continuous range of frames from an input video.

Randomly crop a continuous range of frames from an input video. The number of frames to keep is set by the `length` parameter, and the start position is chosen randomly using the `seed` parameter. The node operates lazily, meaning it does not process the entire video until the output is used downstream.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Input video. | VIDEO | Yes | – |
| `length` | Number of frames to keep. If `length` is greater than the total number of frames in the video, the entire video is kept. (default: 16) | INT | Yes | min: 1, max: 99999 |
| `seed` | Random seed. (default: 0) | INT | Yes | min: 0, max: 0xFFFFFFFFFFFFFFFF |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | Cropped video (lazy). | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VideoRandomTemporalCrop/en.md)

***

**Source fingerprint (SHA-256):** `8249feb5ac3607fcabf3de0ec4d2eb90ab4aa46c18613040c341b825c9db1b1e`


# VideoTemporalCrop - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VideoTemporalCrop

This node crops a continuous range of frames from a video.

This node crops a continuous range of frames from a video. It works in a fully lazy manner, meaning it only processes the selected portion of the video as needed later in the workflow.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | Input video. | VIDEO | Yes | – |
| `start_frame` | Starting frame index (default: 0). | INT | Yes | 0 to 99999 |
| `length` | Number of frames to keep (default: 16). | INT | Yes | 1 to 99999 |

Note: `start_frame` is limited to the last frame of the video, and `length` is reduced if it would extend beyond the available frames.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | Cropped video (lazy). | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VideoTemporalCrop/en.md)

***

**Source fingerprint (SHA-256):** `1d28a55399c9fe7ca47f0aaa872751ac89c5419a6f6be6636fbf7f020a02749d`


# VideoTrim - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VideoTrim

This node cuts a video to a chosen time window by setting a start time and a duration.

This node cuts a video to a chosen time window by setting a start time and a duration. It also offers a strict mode that raises an error when the requested duration cannot be achieved.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `video` | The video to trim. | VIDEO | Yes | — |
| `trim` | Trim window using start/end frames. The window is converted into a start time (in seconds from the beginning of the video) and a duration (in seconds). When both the start time and the duration are 0, the video is returned without any trimming. | VIDEO\_EDIT | Yes | start\_time: >= 0, default 0<br />duration: >= 0, default 0 |
| `strict_duration` | If True, when the specified duration is not possible, an error will be raised. (default: False) | BOOLEAN | No | true<br />false |

Note: The trim duration must be >= 0; negative values raise an error. The requested trim window must fit inside the source video. If the trim cannot be applied, an error is raised that reports the source duration, start time, and target duration.

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `video` | The trimmed video. When the trim window is empty (start time and duration both 0), the original video is returned unchanged. | VIDEO |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VideoTrim/en.md)

***

**Source fingerprint (SHA-256):** `ba8f8ccbae7e8aebda553810b81ccaa427d45523142bd00746c4e2f4e5b41a1b`


# wanBlockSwap - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/wanBlockSwap

This node is deprecated and serves no function.

This node is deprecated and serves no function. It accepts a model as input and returns the same model unchanged. The description "NOP" indicates it performs no operation.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| - | - | - | - | - |
| `model` | The model to pass through the node. | MODEL | Yes | |

## Outputs

| Output Name | Description | Data Type |
| - | - | - |
| `model` | The same model that was provided as input, unchanged. | MODEL |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/wanBlockSwap/en.md)

***

**Source fingerprint (SHA-256):** `7acf88d1c42d90e645bb557c7fdc93e659182927ee7b3e3ef15b0ccf7c3f471a`


# Getting an API Key
Source: https://docs.comfy.org/development/api-development/getting-an-api-key

Learn how to create and manage your Comfy Platform API Key for accessing Cloud APIs, Partner Nodes, and more.

An API Key is your credential for accessing Comfy Platform services, including:

* [Cloud API](/development/cloud/overview) — call Comfy Cloud endpoints programmatically
* [Partner Node API Integration](/development/comfyui-server/api-key-integration) — use paid Partner Nodes in your local workflows
* [Agent Tools / MCP](/agent-tools) — connect to Comfy through MCP
* [Login to ComfyUI locally](/interface/user#logging-in-with-an-api-key) — authenticate with an API Key instead of email

## Creating an API Key

<Steps>
  <Step title="Visit the Comfy Platform and Log In">
    Please visit the [Comfy Platform login page](https://platform.comfy.org/login) and log in with the corresponding account

    <img alt="Visit Platform Login Page" />
  </Step>

  <Step title="Click `+ New` in API Keys to Create an API Key">
    Click `+ New` in API Keys to create an API Key

    <img alt="Create API Key" />
  </Step>

  <Step title="Enter API Key Name">
    <img alt="Enter API Key Name" />

    1. (Required) Enter the API Key name,
    2. Click `Generate` to create
  </Step>

  <Step title="Save the Obtained API Key">
    <img alt="Obtain API Key" />

    <Warning>
      Since the API Key is only visible upon first creation, please save it immediately after creation. It cannot be viewed later, so please keep it safe.
      Please note that you should not share your API Key with others. Once it leaked, you can delete it and create a new one.
    </Warning>
  </Step>
</Steps>

## Managing your API Keys

You can view and manage all your API Keys on [platform.comfy.org](https://platform.comfy.org) after logging in.

* **View existing keys**: See the name and creation date of each key
* **Delete a key**: If a key is compromised or no longer needed, delete it immediately
* **Create additional keys**: You can have multiple API Keys for different applications

<Warning>
  API Keys are only shown once upon creation. Save it immediately in a secure location. If you lose a key, delete it and create a new one.
</Warning>

## Using your API Key

Once you have an API Key, you can:

1. **Log in to ComfyUI locally** — go to **Settings → User** and select "Comfy API Key" login
2. **Call Partner Node APIs** — include the key in `extra_data.api_key_comfy_org` when sending workflows
3. **Use Cloud API** — include the key in request headers for Cloud API endpoints

For security, never share your API Key or commit it to version control.


# Run your first workflow
Source: https://docs.comfy.org/development/api-development/quickstart

Run a sample workflow on Comfy Cloud and download its output with Python or TypeScript.

Run a complete workflow from code and save its output as `first-result.png`. This sample creates a **512 × 512 solid blue image** using two built-in nodes. It verifies authentication, workflow execution, and output download without requiring a model, an input image, or custom nodes.

To generate an image by calling a hosted model directly, start with the [Comfy Router quickstart](/development/comfy-router/quickstart).

This sample runs on Comfy Cloud. For other hosting options, including Comfy API deployments and self-hosting, see [Deploying ComfyUI](/development/deploy/overview).

## Before you start

* A [Comfy API key](/development/api-development/getting-an-api-key).
* A [paid Comfy Cloud subscription](/development/deploy/cloud). Cloud workflow API access is not included in the free tier.
* Python 3.10 or newer, or Node.js 22.18 or newer for the TypeScript example.

This guide uses Comfy Cloud, the SDKs' default target. If you previously set `COMFY_BASE_URL`, unset it to use Cloud. For an existing Comfy API deployment or a self-hosted instance, see [Choosing a base URL](/development/api-development/sdks#choosing-a-base-url).

## 1. Download the sample

Create a folder for the example. Download [workflow\_api.json](/files/api-first-result/workflow_api.json) and the script for your language into that folder:

* [Python: first\_workflow.py](/files/api-first-result/first_workflow.py)
* [TypeScript: first\_workflow.mts](/files/api-first-result/first_workflow.mts)

The workflow is already in API format. Node `"1"` creates the blue image and node `"2"` saves it. The scripts read outputs from that exact SaveImage node, so you do not need to find or edit a node ID.

## 2. Install the SDK and set your key

Open a terminal in the folder where you saved the files.

<CodeGroup>
  ```bash Python theme={null}
  python -m venv .venv
  source .venv/bin/activate
  python -m pip install comfy-sdk
  ```

  ```bash TypeScript theme={null}
  npm init -y
  npm install @comfyorg/sdk
  ```
</CodeGroup>

On Windows, activate the Python environment with `.venv\Scripts\Activate.ps1` in PowerShell.

Set your key in the same terminal:

<CodeGroup>
  ```bash macOS / Linux theme={null}
  export COMFY_API_KEY="comfyui-your-key"
  ```

  ```powershell Windows PowerShell theme={null}
  $env:COMFY_API_KEY = "comfyui-your-key"
  ```
</CodeGroup>

Keep your API key in your server environment. Do not include it in browser code or commit it to source control.

## 3. Run and view the result

<CodeGroup>
  ```bash Python theme={null}
  python first_workflow.py
  ```

  ```bash TypeScript theme={null}
  node first_workflow.mts
  ```
</CodeGroup>

The script submits the workflow, waits for it to finish, and downloads the image. When it prints `Saved` followed by a path, open `first-result.png` from that location. You should see a solid blue square. Running the sample again replaces that local file.

<Note>
  This is a workflow connection check. It does not use a generative model. The same submit, wait, and download steps work with your own generation workflows.
</Note>

### If the request fails

* **Missing key or unauthorized:** check that `COMFY_API_KEY` is set in the terminal running the script and contains an active key.
* **Access or credit error:** check your Cloud subscription and available credits before retrying.
* **Workflow file not found:** keep `workflow_api.json` next to the downloaded script.
* **Unexpected endpoint:** check `COMFY_BASE_URL`. Unset it for this Cloud example.

For error handling and job progress, see the [SDK guide](/development/api-development/sdks).

## 4. Run your own generation workflow

Build or choose a workflow in the ComfyUI editor, run it successfully there, and [export it in API format](/development/api-development/workflow-api-format). Replace `workflow_api.json` with your export and update `get_outputs("2")` in Python or `getOutputs("2")` in TypeScript to use your workflow's SaveImage node ID. Check that the target environment has the models and custom nodes your workflow uses.

To host workflows with your own models and custom nodes, follow the [Comfy API Quickstart](/development/serverless/quickstart). To change workflow inputs, upload files, or watch progress, continue to [Comfy SDKs](/development/api-development/sdks).


# Comfy SDKs
Source: https://docs.comfy.org/development/api-development/sdks

Run ComfyUI workflows from Python or TypeScript against Comfy Cloud, a deployment or your own ComfyUI: assets, jobs, live events and idempotent retries.

<Warning>
  **Beta.** The SDKs and the Comfy API v2 they call are still pre-1.0. The shape of the API can change before it stabilizes. Report problems through [Feedback](#feedback).
</Warning>

**One package, two surfaces.** `comfy-sdk` (PyPI) and `@comfyorg/sdk` (npm) ship two clients that talk to two different services. Method names repeat across them (`run`, `submit`, `events`) and mean different things in each, so check which client a snippet builds before you copy it.

| Surface | What it does | How you reach it | Base URL | Auth |
| - | - | - | - | - |
| **[Comfy Router](/development/comfy-router/quickstart)** | Calls a partner model (Flux, Veo, Gemini, Kling) with that provider's own request body and hands back its native response | Python: `client.models` on a `Comfy()`. TypeScript: `comfy.models` on the module-level `comfy` namespace | `https://api.comfy.org`, route `/v2/models/{provider}/{model}` | `COMFY_API_KEY`, or `comfy.config({ credentials })` |
| **[Comfy Cloud and Comfy API v2](/development/api-development/sdks)** | Runs an API-format ComfyUI workflow end to end: upload assets, submit the graph, follow the job, download outputs | `Comfy(api_key=...)` / `new Comfy({ apiKey })`, then `client.workflows`, `client.assets`, `client.jobs` | `https://cloud.comfy.org` by default, or whatever `COMFY_BASE_URL` names | `api_key` / `apiKey` on the constructor |

Neither surface wraps the other, and one API key created in [your Comfy workspace](https://platform.comfy.org/profile/api-keys) works for both.

<Note>
  The two languages expose the Router surface differently. In Python, `Comfy()` carries both: `client.models.run(...)` for Router and `client.workflows` / `client.assets` / `client.jobs` for Cloud. In TypeScript they are separate exports with deliberately similar names: `comfy` (lowercase, the module-level namespace) holds `comfy.models`, while `Comfy` (the class) is the Cloud client and has no `.models`.
</Note>

This page documents the second row: the Comfy Cloud and Comfy API v2 client. For the model router, start at the [Comfy Router quickstart](/development/comfy-router/quickstart).

The Comfy SDKs let your application run ComfyUI workflows and get the results back. You submit a workflow, ComfyUI executes it, and you download the outputs. The same code runs against Comfy Cloud or against a ComfyUI instance you host yourself. Only the base URL changes.

The SDKs are clients for the [Comfy API v2](/api-reference/v2/overview), a versioned HTTP API that we intend to support long term. New releases of ComfyUI will not break integrations built on it.

Things people build this way:

* Plugins that generate content inside another application, such as Blender or Krita
* Consumer apps that run generation on behalf of their users
* Batch pipelines, for example running one workflow over every frame of a video
* Backend services that need many workflows in flight at once

<Note>
  These SDKs drive ComfyUI **from the outside**. If you are writing custom nodes or frontend extensions that run **inside** ComfyUI, you want [Develop Custom Nodes](/custom-nodes/overview) instead. Those are a separate set of APIs.
</Note>

## Install

<CodeGroup>
  ```bash Python theme={null}
  pip install comfy-sdk
  ```

  ```bash TypeScript theme={null}
  npm i @comfyorg/sdk
  ```
</CodeGroup>

Python 3.10 or newer. Node 22 or newer.

<Note>
  **Current release: 0.4.0.** [`comfy-sdk`](https://pypi.org/project/comfy-sdk/) on PyPI and [`@comfyorg/sdk`](https://www.npmjs.com/package/@comfyorg/sdk) on npm are released together and share a version number. Install the latest (`pip install comfy-sdk`, `npm install @comfyorg/sdk`) or state a range rather than an exact pin. The two ecosystems spell that differently: `comfy-sdk>=0.4` is a floor and accepts later minors, while `@comfyorg/sdk@^0.4` is npm's compatible range for `0.4.x` and stops short of `0.5.0`, so a caret range needs raising when a new minor ships. Use `@comfyorg/sdk@>=0.4.0` if you want the npm side to track later minors too. The registry pages are authoritative if this note is behind.
</Note>

## Quickstart

Upload an input image, run a workflow, and write the results to disk.

<CodeGroup>
  ```python Python theme={null}
  from comfy_sdk import Comfy

  # Comfy Cloud
  client = Comfy(api_key="comfyui-...")

  wf = client.workflows.from_file("workflow_api.json")

  asset = client.assets.from_file("photo.png")
  wf.set_input("10", "image", asset)

  job = client.run(wf)
  for output in job.get_outputs("9"):
      output.to_file(output.name)
  ```

  ```typescript TypeScript theme={null}
  import { Comfy } from "@comfyorg/sdk";

  // Comfy Cloud
  const client = new Comfy({ apiKey: "comfyui-..." });

  const wf = await client.workflows.fromFile("workflow_api.json");

  const asset = client.assets.fromFile("photo.png");
  wf.setInput("10", "image", asset);

  const job = await client.run(wf);
  await job.getOutputs("9")[0].toFile("out.png");
  ```
</CodeGroup>

`workflow_api.json` is a workflow saved in [API format](/development/api-development/workflow-api-format). `"10"` and `"9"` are node IDs from that file: the node the input image feeds into, and the output node whose results you want.

Asset handles are lazy. `photo.png` is hashed locally and only uploaded if the server does not already have those bytes, so re-running with the same input costs nothing.

`run()` submits the job and waits for it to reach a terminal state. To do work while it executes, use `submit()` instead and watch the [event stream](#watching-a-job-run).

To run against your own ComfyUI instead, set `COMFY_BASE_URL` and drop the key. See below.

## Choosing a base URL

| Surface | Base URL | API key |
| - | - | - |
| **Comfy Cloud** | `https://cloud.comfy.org` (the default) | Required |
| **Comfy API deployment** | `https://<deployment>.run.comfy.app` | Required |
| **Your own ComfyUI** | `http://127.0.0.1:8189` (the local proxy) | None by default. Optional static bearer token |

The base URL comes from the `COMFY_BASE_URL` environment variable, not a constructor argument:

```bash theme={null}
export COMFY_BASE_URL="https://<deployment>.run.comfy.app"  # Comfy API deployment
export COMFY_BASE_URL="http://127.0.0.1:8189"               # self-hosted proxy
```

It is read each time a client is constructed, must be an `http(s)` URL, and unset or blank means Comfy Cloud. So the client itself is the same everywhere:

<CodeGroup>
  ```python Python theme={null}
  client = Comfy(api_key="comfyui-...")
  ```

  ```typescript TypeScript theme={null}
  const client = new Comfy({ apiKey: "comfyui-..." });
  ```
</CodeGroup>

<Note>
  Upgrading from an early build? `Comfy("<url>", "<key>")` is now `Comfy(api_key="<key>")` with `COMFY_BASE_URL` set. `api_key` is keyword-only, so the old positional call raises `TypeError` rather than quietly reading a URL as a key.
</Note>

### Comfy Cloud

Works out of the box. Create an [API key](/development/api-development/getting-an-api-key) and pass it to the client.

<Note>
  API access requires a paid Comfy Cloud subscription. The free tier does not include it. How many jobs you can run at once depends on your tier. See [Concurrent jobs](/development/deploy/cloud-usage#concurrent-jobs).
</Note>

### Comfy API deployment

A workflow you deployed through the [developer platform](https://platform.comfy.org) gets its own endpoint. Point `COMFY_BASE_URL` at it and use your API key, exactly as with Comfy Cloud. Everything in this guide works the same way.

A Comfy API deployment can run multiple workflows with the models and custom nodes included in its Build. For each job, `get_workflow()` returns a workflow response with `format: "api"` and the executed graph in its `.graph` property.

### Your own ComfyUI

During the beta, the v2 API is served by [comfy-api-proxy](https://github.com/Comfy-Org/comfy-api-proxy), a small open-source service that runs alongside your ComfyUI. Install it, run it, and set `COMFY_BASE_URL="http://127.0.0.1:8189"`:

```bash theme={null}
pip install comfy-api-proxy
comfy-api-proxy
export COMFY_BASE_URL="http://127.0.0.1:8189"
```

See [API Proxy for Self-Hosted ComfyUI](/development/comfyui-server/api-proxy) for configuration, authentication, and why the proxy exists. It is a stopgap: once the v2 API stabilizes it moves into ComfyUI core and the proxy is no longer needed.

## Retrying a submit: the idempotency key

`submit()` and `run()` send an `Idempotency-Key` with every submission, and the Comfy API v2 contract for that key is **reject-on-duplicate, not record-and-replay**. Read this before you wrap a submit in a retry loop.

* **Each call mints a fresh key.** Calling `submit()` twice with the same workflow is two submissions, two jobs and two charges. A naive `for attempt in range(3)` around `submit()` is a double-bill, not a retry.
* **A reused key is rejected, not replayed.** Pass your own `idempotency_key` (`idempotencyKey` in TypeScript) to make a retry idempotent, and the second request with that key fails `422 idempotency_key_reuse` instead of returning the first job. The SDKs raise `IdempotencyKeyReuse`. That is the opposite of what "idempotent retry" usually means, so handle it explicitly.
* **Recovery is to go and find the job, not to resubmit.** On `IdempotencyKeyReuse` the first attempt may well have created a job. Fetch it with `client.jobs.get(job_id)`. That lookup needs an id you already stored, so it only recovers the case where the submit returned and you persisted the id before the failure. If the connection dropped before the id was recorded there is nothing to look up and no automatic recovery: the examples below re-raise for manual handling rather than resubmitting under a claimed key.
* **The key is released when the submission definitively failed.** A validation error, an out-of-credits reject or a queue-full reject creates no job and frees the key, so resubmitting under it is fine. After an *ambiguous* failure (a read timeout, a connection dropped mid-request) the key stays claimed: look for the job rather than resubmitting.
* **Keys expire after 24 hours** and must be non-empty, printable ASCII and within the length bound. An invalid key raises `ValueError` before any request is made, so an explicit `""` never silently falls back to a minted key.

A retry that is safe to run more than once therefore has to carry two things across attempts: the key, so the server can tell a retry from a new submission, and the job id, so you can find the job a claimed key already created.

<CodeGroup>
  ```python Python theme={null}
  import uuid
  from comfy_sdk import IdempotencyKeyReuse

  # Both values belong in your own store, keyed by whatever the request means to
  # you. `key` is minted once, on the first attempt; `job_id` is filled in as soon
  # as a submit returns.
  state = load_submission_state()  # {"key": ..., "job_id": ...} or {}
  key = state.get("key") or str(uuid.uuid4())
  save_submission_state(key=key)

  try:
      job = client.submit(wf, idempotency_key=key)
      save_submission_state(key=key, job_id=job.id)
  except IdempotencyKeyReuse:
      # An earlier attempt under this key already reached submission, so a job
      # may exist. Do not resubmit: go and find it.
      job_id = state.get("job_id")
      if job_id is None:
          raise  # nothing recorded to look up; this needs a human
      job = client.jobs.get(job_id)
  ```

  ```typescript TypeScript theme={null}
  import { IdempotencyKeyReuse } from "@comfyorg/sdk";

  // Both values belong in your own store, keyed by whatever the request means to
  // you. `key` is minted once, on the first attempt; `jobId` is filled in as soon
  // as a submit returns.
  const state = await loadSubmissionState(); // { key?, jobId? }
  const key = state.key ?? crypto.randomUUID();
  await saveSubmissionState({ key });

  let job;
  try {
    job = await client.submit(wf, { idempotencyKey: key });
    await saveSubmissionState({ key, jobId: job.id });
  } catch (err) {
    // An earlier attempt under this key already reached submission, so a job
    // may exist. Do not resubmit: go and find it.
    if (!(err instanceof IdempotencyKeyReuse) || !state.jobId) throw err;
    job = await client.jobs.get(state.jobId);
  }
  ```
</CodeGroup>

`client.jobs.get(job_id)` is the SDK's rehydration path, and it needs an id, which is why recording the id the moment a submit returns is what makes this recoverable at all. See [Comfy API v2](/api-reference/v2/overview) for the full key contract on `POST /api/v2/jobs`.

<Note>
  Comfy Router's `Idempotency-Key` behaves **differently**. On Router the key is a replay handle rather than a single-use token: re-sending a queued submit under the same key returns the original request instead of queueing a second one. See [queued idempotency and billing](/development/comfy-router/queue#idempotency-and-billing) and [Router retry outcomes](/development/comfy-router/errors#retry-outcomes). The two surfaces share a header name, not a contract.
</Note>

## Watching a job run

`job.events()` gives you a live stream of the job's state: node and step progress, preview frames, and each output the moment it is committed. It reconnects on its own if the connection drops.

<CodeGroup>
  ```python Python theme={null}
  from comfy_sdk import Progress, Preview, OutputReady, StatusChange

  job = client.submit(wf)

  for event in job.events():
      match event:
          case Progress() as p:
              print(f"{p.value:.0%} {p.message}")
          case Preview() as pv:
              image = pv.to_pil()
          case OutputReady() as o:
              o.output.to_file(f"partial/{o.output.name}")
          case StatusChange(status="succeeded"):
              break

  result = job.result()
  ```

  ```typescript TypeScript theme={null}
  const job = await client.submit(wf);

  // The label is required: a bare `break` inside a switch leaves the switch,
  // not the loop.
  eventLoop: for await (const event of job.events()) {
    switch (event.kind) {
      case "progress":
        console.log(event.value);
        break;
      case "outputReady":
        await event.output.toFile(`${event.output.name}`);
        break;
      case "statusChange":
        if (event.status === "succeeded") break eventLoop;
    }
  }
  ```
</CodeGroup>

`Preview.to_pil()` requires the optional Pillow extra: `pip install "comfy-sdk[pil]"`.

`result()` returns the finished job, or raises `JobFailed` with the node-level detail if execution failed. See the [SDK README](#reference) for your language for the full event catalog.

### `events()` is not `subscribe()`

Three similarly named things exist across the two surfaces, and only one of them is on this page:

| Call | Surface | What it yields |
| - | - | - |
| `job.events()` | Comfy Cloud (this page) | A live SSE stream of one workflow job: `Progress`, `Preview`, `OutputReady`, `StatusChange`. Auto-reconnects, falls back to polling. |
| `handle.events()` (TypeScript) / `handle.iter_events()` (Python) | [Comfy Router queued delivery](/development/comfy-router/queue) | Queue observations for one Router request: status and queue position. It polls the status route; there is no stream and there are no progress or preview events. |
| `comfy.models.subscribe(...)` | [Comfy Router queued delivery](/development/comfy-router/queue) | Not an iterator. Submit, poll and collect in one call, with an `on_queue_update` / `onQueueUpdate` callback, resolving to the result. |

There is no `subscribe()` on the Comfy Cloud client, and no `job.subscribe()` anywhere. The Cloud equivalent of `subscribe` is `run()`: submit and wait for a terminal state.

The stream is a live feed, not a replayable log. It exists so you can render progress, not so you can rely on it for results. Polling the job is what is authoritative, and `run()`, `wait()`, and `result()` fall back to polling automatically. See [Design Notes](/development/api-development/sdks-design#poll-first-stream-for-progress) for why.

## Tracing an output back to its workflow

Outputs carry the id of the job that produced them, so you can start from a file and work backwards without keeping a side table.

<CodeGroup>
  ```python Python theme={null}
  output = job.outputs[0]
  output.job_id          # the job that produced this file
  ```

  ```typescript TypeScript theme={null}
  const output = job.outputs[0];
  output.jobId; // the job that produced this file
  ```
</CodeGroup>

The same id is on an asset fetched on its own, so a file you found later still leads back to its job. It is `None` (TypeScript: `undefined`) for an asset you uploaded, which has no producing job.

From the job you can ask for the workflow behind it. This works for a job you did not submit in this process, rehydrated by id:

<CodeGroup>
  ```python Python theme={null}
  wf = job.get_workflow()

  if wf.format == "save":
      ...  # the workflow as authored, canvas layout and Note nodes intact
  else:
      ...  # the executed API-format graph
  ```

  ```typescript TypeScript theme={null}
  const wf = await job.getWorkflow();

  if (wf.format === "save") {
    // the workflow as authored, canvas layout and Note nodes intact
  } else {
    // the executed API-format graph
  }
  ```
</CodeGroup>

**Always branch on `format`.** Which shape comes back depends on how the job was submitted, not on anything you control per request:

| `format` | What you get | When |
| - | - | - |
| `save` | The authoring workflow at the version the job ran, with canvas layout and editor-only nodes such as Note | Jobs submitted from the Comfy Cloud editor, which pins a workflow version |
| `api` | The executed graph. Editor-only constructs are gone and Get/Set nodes are expanded | Everything else, including every job submitted through these SDKs today |

Jobs you submit through the SDK always return `api`, because v2 submission has no version-pinning fields yet. That will change; the discriminator is there so your code does not have to.

## What the SDKs cover today

The first version does one thing properly: run a workflow and get the results back.

* **Assets.** Create input handles from a file, bytes, a stream, or a URL. Handles are lazy and content addressed, so re-running with the same input does not re-upload it.
* **Submission.** Submit an API-format graph. Submission is idempotent, and a full queue is retried for you within a bounded budget.
* **Execution.** Poll with `wait()`, or follow `events()` for live progress.
* **Outputs.** Write to disk, buffer into memory, fetch a byte range, or get a short-lived download URL. `getDownloadUrl()` hands back a signed URL that anyone can read without an API key, valid for roughly 6 hours. Read [Output URLs and How Long They Last](/api-reference/v2/overview#output-urls-and-how-long-they-last) before you store one: to keep showing an output later, re-host the bytes or re-mint the URL on demand.
* **Traceability.** Every output carries the id of the job that produced it, and a job can hand back the workflow behind it.
* **Deleting assets.** Remove an asset you uploaded, by handle or by id.
* **Errors.** Typed exceptions such as `JobFailed`, `Unauthorized`, `InsufficientCredits`, and `QueueFull`, rather than raw status codes.
* **Cancellation.** Jobs can be canceled while running. TypeScript additionally accepts an `AbortSignal` on any call.

Python ships both a synchronous `Comfy` client and an `AsyncComfy` client with the same surface. TypeScript is async only.

Not in this version: managing saved workflows, the model library, node introspection, and named workflow parameters. [Design Notes](/development/api-development/sdks-design#scope-of-the-first-version) explains why the surface starts this small.

## Reference

The SDK READMEs are the full reference for each language, including auth, assets, errors, and the low-level escape hatches.

<CardGroup>
  <Card title="Python SDK" icon="python" href="https://github.com/Comfy-Org/comfy-python-sdk">
    <code>comfy-sdk</code> on PyPI. Sync and async clients.
  </Card>

  <Card title="TypeScript SDK" icon="js" href="https://github.com/Comfy-Org/comfy-typescript-sdk">
    <code>@comfyorg/sdk</code> on npm. Typed, async, with a low-level client.
  </Card>

  <Card title="Comfy API v2 Reference" icon="code" href="/api-reference/v2/overview">
    The HTTP API underneath both SDKs. Use it directly from any language.
  </Card>

  <Card title="Design Notes" icon="compass" href="/development/api-development/sdks-design">
    Why this API exists, how it relates to the existing ComfyUI APIs, and what comes next.
  </Card>

  <Card title="Comfy Router" icon="shuffle" href="/development/comfy-router/quickstart">
    The other surface in the same package: <code>comfy.models.run</code> against partner models such as Flux, Veo and Gemini.
  </Card>
</CardGroup>

## Feedback

The SDKs are pre-1.0. Method names, the client shape, the event catalog, the error taxonomy and asset handling can all still change, and the surface is expected to stabilize over the next few weeks. Once it does, the long-term support commitment constrains what can be changed.

Report what is awkward, what you expected to find and did not, and what you had to work around. The `#developer-platform` channel in [our Discord](https://discord.com/invite/comfyorg) is the place for it.

If you want a first-party SDK in another language, say so there. Both SDKs sit on the same documented HTTP contract, so any language can talk to the API today, but we would rather know where the demand is.


# Design Notes
Source: https://docs.comfy.org/development/api-development/sdks-design

Why the Comfy API v2 exists, how it relates to the existing ComfyUI APIs, and what is coming next

Background for the [Comfy SDKs](/development/api-development/sdks) and the [Comfy API v2](/api-reference/v2/overview) they call. You do not need any of this to use the SDKs. Read it if you are deciding whether to build on the new API or the existing ones.

## Why a new API

You can already drive ComfyUI over HTTP by calling `/prompt` and `/history`. Those endpoints exist to serve the ComfyUI web UI, and building on them means depending on internals that were never promised to you. The v2 API adds three things they cannot give you.

**A commitment.** v2 is versioned, documented, and supported. Changes within v2 are additive; anything breaking would ship as v3. New releases of ComfyUI will not break your integration.

**Portability.** The same behavior against local ComfyUI, against Comfy Cloud, and against a Comfy API deployment. Same code, different base URL.

**A shape that survives production.** Durable job IDs, idempotent submission, typed errors, normalized outputs, and real backpressure, instead of every integration reinventing all five on top of `prompt_id` and `/history`.

## Why not wrap the endpoints that already exist

Because they assume one ComfyUI instance running one workflow at a time, and that assumption is welded into `prompt_id`, `/history`, and the websocket protocol.

The v2 API does not assume it. Many workflows in flight at once, each addressed by a durable job ID, is the default case rather than the exception.

## Poll first, stream for progress

Every capability in v2 is reachable with plain GET requests. `GET /api/v2/jobs/{id}` returns the current status, the latest progress snapshot, and every output committed so far. It is the authoritative view of a job, and it stays available until the job's `expires_at`.

The SSE stream at `GET /api/v2/jobs/{id}/events`, exposed as `job.events()` in both SDKs, is a live enhancement on top of that. Use it to drive a progress bar. Do not use it as your source of truth: it carries no event IDs, has no resume cursor, and frames emitted while you were disconnected are gone.

Two reasons the authoritative path is a poll rather than a stream or a webhook:

* Workflows can run for a long time. A connection that blips for three seconds should never cost you a result.
* Webhooks work well for a service with a public address. They do not work for a Blender plugin on someone's desktop that is not listening on a port, and should not be.

The practical effect is that every step is resumable. If your process crashes mid-job, you can come back an hour later and `GET /api/v2/jobs/{id}` still has the status and the outputs. Other transports may be added later for cases that suit them; this is the one that works everywhere.

## Relationship to the existing APIs

Existing APIs, including the [Cloud API](/development/cloud/overview), will continue to work. `/prompt`, `/history`, `/ws`, and the rest keep working. If your integration works today, none of this breaks it. The two live side by side.

| | Comfy API v2 | Existing APIs |
| - | - | - |
| **Compatibility** | Versioned. Additive changes only within v2 | No compatibility guarantee across releases |
| **Concurrency model** | Many jobs in flight, each with a durable ID | One instance, one workflow at a time |
| **Runs against** | Comfy Cloud, Comfy API deployments, and self-hosted ComfyUI, same contract | Cloud API and ComfyUI Server API differ |
| **Official clients** | Python and TypeScript SDKs | None |
| **Best for** | New integrations | Integrations that already work |

## Scope of the first version

One thing, properly: run a workflow and get the results back. Upload inputs, submit an API-format graph, watch it execute, pull down outputs.

That is the whole scope on purpose. Saved workflows, model library management, node introspection, and named workflow parameters are not here yet. We would rather ship a small surface we can genuinely commit to across every way ComfyUI gets deployed than a large one that only holds together in one of them. It will grow from here.

## The local proxy

During the beta, self-hosted ComfyUI speaks v2 through [comfy-api-proxy](https://github.com/Comfy-Org/comfy-api-proxy), which runs alongside your instance and serves the v2 contract in front of it. It is open source and explicitly a stopgap. Once the API stabilizes this moves into ComfyUI core and the proxy stops being necessary.

## Why Python and TypeScript first

That is where the demand was when we asked people already running ComfyUI at scale. Both SDKs sit on the same documented HTTP contract, so any language can talk to the API right now. If you want a first-party SDK in another language, tell us in the `#developer-platform` channel in [our Discord](https://discord.com/invite/comfyorg).

## What we want from you

The API is at `0.1.x` for a reason, and we plan to lock the surface down over the next few weeks. Method names, the client shape, the event catalog, the error taxonomy, and how asset handling feels in practice are all still cheap to change right now. See [Feedback](/development/api-development/sdks#feedback).


# Workflow API Format
Source: https://docs.comfy.org/development/api-development/workflow-api-format

Understanding the API format for ComfyUI workflows and how to export them

ComfyUI workflows are JSON objects that describe a graph of nodes. When calling ComfyUI programmatically — whether through the Cloud API or running your own server — the workflow must be submitted in **API format**, a specialized JSON structure that differs from the regular save format used in the browser.

This page explains the differences and how to export your workflows correctly.

***

## Save Format vs API Format

The ComfyUI frontend can save workflows in two formats:

| | Save Format | API Format |
| - | - | - |
| **File menu** | `File → Save` or `Ctrl+S` | `File → Export Workflow (API)` |
| **File extension** | `.json` | `.json` |
| **Node keys** | Node titles or labels | Numeric node IDs |
| **Widget values** | Included | Included |
| **Position/layout data** | Included (x, y, width) | **Excluded** |
| **Colors/groups** | Included | **Excluded** |
| **Usage** | Re-opening in the frontend | API submission |
| **Can be loaded in UI** | Yes | Yes, but without layout |

The key difference: **API format omits UI metadata** (positions, colors, groups, node sizes) that is only needed for visual editing in the frontend. This keeps the JSON smaller and cleaner for programmatic use.

***

## How to Export

Open your workflow in the ComfyUI frontend, then navigate to `File → Export Workflow (API)`:

<Frame>
  <img alt="Saving a workflow in API format" />
</Frame>

This will download a `.json` file containing only the API-relevant data:

```json theme={null}
{
  "3": {
    "inputs": {
      "seed": 156680208700286,
      "steps": 20,
      "cfg": 8,
      "sampler_name": "euler",
      "scheduler": "normal",
      "denoise": 1,
      "model": [
        "4",
        0
      ],
      "positive": [
        "6",
        0
      ],
      "negative": [
        "7",
        0
      ],
      "latent_image": [
        "5",
        0
      ]
    },
    "class_type": "KSampler",
    "_meta": {
      "title": "KSampler"
    }
  },
  "4": {
    "inputs": {
      "ckpt_name": "v1-5-pruned-emaonly-fp16.safetensors"
    },
    "class_type": "CheckpointLoaderSimple",
    "_meta": {
      "title": "Load Checkpoint"
    }
  },
  "5": {
    "inputs": {
      "width": 512,
      "height": 512,
      "batch_size": 1
    },
    "class_type": "EmptyLatentImage",
    "_meta": {
      "title": "Empty Latent Image"
    }
  },
  "6": {
    "inputs": {
      "text": "beautiful scenery nature glass bottle landscape, , purple galaxy bottle,",
      "clip": [
        "4",
        1
      ]
    },
    "class_type": "CLIPTextEncode",
    "_meta": {
      "title": "CLIP Text Encode (Prompt)"
    }
  },
  "7": {
    "inputs": {
      "text": "text, watermark",
      "clip": [
        "4",
        1
      ]
    },
    "class_type": "CLIPTextEncode",
    "_meta": {
      "title": "CLIP Text Encode (Prompt)"
    }
  },
  "8": {
    "inputs": {
      "samples": [
        "3",
        0
      ],
      "vae": [
        "4",
        2
      ]
    },
    "class_type": "VAEDecode",
    "_meta": {
      "title": "VAE Decode"
    }
  },
  "9": {
    "inputs": {
      "filename_prefix": "ComfyUI",
      "images": [
        "8",
        0
      ]
    },
    "class_type": "SaveImage",
    "_meta": {
      "title": "Save Image"
    }
  }
}
```

***

## Converting Between Formats

If you have a save-format workflow and need it in API format, the simplest method is:

1. Open the `.json` file using `File → Load` in the frontend
2. Export it via `File → Export Workflow (API)`

***

## Related Pages

* [Running Workflows](/development/run-workflows/overview): compare the API and deployment options
* [Cloud API Overview](/development/cloud/overview): submit API-format workflows to Comfy Cloud
* [API Examples](/development/comfyui-server/api-examples): see API-format workflows in action
* [Getting an API Key](/development/api-development/getting-an-api-key): required for Cloud API and Partner Nodes


# Workflow Metadata
Source: https://docs.comfy.org/development/api-development/workflow-metadata

Learn how ComfyUI embeds workflows in generated files and how to read the embedded metadata

## Overview

When ComfyUI saves an output file, it can store the workflow that produced the file inside the file itself.

You can think of this as saving a generated image together with its recipe. The image is the result, and the embedded workflow describes the steps used to create it.

Embedded workflow metadata allows you to:

* Reopen a generated file in ComfyUI and recover its workflow.
* Share a generated file together with the workflow used to create it.
* Inspect generation settings in an automated workflow.
* Build tools that read ComfyUI workflow metadata from output files.

The metadata is stored inside the file format. It does not change the visible image or video content.

## Embedded fields

ComfyUI commonly stores two JSON fields:

| Field | Description |
| - | - |
| `workflow` | The complete workflow graph, including nodes, links, and layout information. |
| `prompt` | The API prompt used to execute the workflow. It contains the nodes and inputs required for execution. |

A simplified example looks like this:

```json theme={null}
{
  "workflow": {
    "nodes": [],
    "links": []
  },
  "prompt": {
    "3": {
      "class_type": "KSampler",
      "inputs": {}
    }
  }
}
```

The actual contents depend on the workflow and the ComfyUI version. Custom nodes can also add fields through `extra_pnginfo`.

The two fields serve different purposes. `workflow` is intended to restore the workflow in the frontend. `prompt` is the execution-oriented representation used when submitting a workflow to a ComfyUI server. A file may contain one field without the other.

## Supported formats

Built-in save nodes embed metadata in the following output formats:

| Output | Metadata location |
| - | - |
| PNG | PNG `tEXt` chunks |
| Animated PNG | PNG text metadata |
| Animated WebP | EXIF tags |
| MP4 | Container metadata tags |
| WebM | Container metadata tags |
| `.latent` | Safetensors metadata |
| `.safetensors` | Safetensors metadata, when written by a node that includes workflow metadata |

The exact metadata support depends on the save node and the file-writing path. A file that has been re-encoded by another application may no longer contain the metadata.

Animated WebP files store the values in EXIF tags. The tags contain strings such as `workflow:{JSON}` and `prompt:{JSON}`. This is different from MP4 and WebM, which store the values as container metadata tags.

## How ComfyUI writes metadata

Built-in output nodes receive the API prompt and additional workflow information when ComfyUI executes a workflow. Unless metadata saving is disabled, the save node serializes these values as JSON and writes them to the output file.

For PNG output, the values are written as text entries. The standard field names are `prompt` and `workflow`.

The metadata is not a separate sidecar file. It is written into the output file during the save operation. This means that copying the file also copies its embedded workflow, but any operation that rewrites the file may remove or replace the metadata.

To disable metadata when starting ComfyUI, use:

```bash theme={null}
python main.py --disable-metadata
```

In ComfyUI Desktop, open **Settings** > **Server-Config** and enable **Disable saving prompt metadata in files.**

Files created while this option is enabled cannot be used to recover a workflow from embedded metadata.

## How ComfyUI reads metadata

To recover a workflow in the ComfyUI interface, drag a generated file onto the canvas. You can also open a file from **File** > **Open**.

If the file contains both `workflow` and `prompt`, ComfyUI uses the embedded `workflow` to rebuild the canvas. If the file does not contain a workflow, ComfyUI treats supported media files as regular input media.

When building an integration, check for the field before parsing it. Metadata may be missing because the file was created with `--disable-metadata`, because the save node did not receive workflow information, or because another application re-encoded the file.

For a browser-based way to inspect or edit embedded workflows, see the [ComfyUI Embedded Workflow Editor](https://comfyui-embedded-workflow-editor.vercel.app/).

## Limitations

* Embedded metadata is not a digital signature. It does not prove who created or modified a file.
* The workflow does not include the model files, input assets, or custom node packages it depends on.
* Moving or renaming a model, input asset, or custom node can prevent a recovered workflow from running.
* Image and video editors may remove metadata when they re-encode a file.
* Files created with `--disable-metadata` do not contain the standard ComfyUI workflow metadata.
* Treat embedded metadata as optional and untrusted input. Validate that a value is valid JSON before using it, and do not assume that a workflow contains every model or custom node required to run it.


# Cloud API Reference
Source: https://docs.comfy.org/development/cloud/api-reference

Complete API reference with code examples for Comfy Cloud

<Warning>
  **Deprecated:** The v1 Cloud API is deprecated in favor of [Comfy API v2](/api-reference/v2/overview). Endpoints, request/response formats, and behavior may be modified without notice. Some endpoints are maintained for compatibility with local ComfyUI but may have different semantics (e.g., ignored fields).
</Warning>

This page provides complete examples for common Comfy Cloud API operations.

<Note>
  **Subscription Required:** Running workflows via the API requires an active Comfy Cloud subscription. See [pricing plans](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=cloud-api) for details.
</Note>

## Setup

All examples use these common imports and configuration:

<CodeGroup>
  ```bash curl theme={null}
  export COMFY_CLOUD_API_KEY="your-api-key"
  export BASE_URL="https://cloud.comfy.org"
  ```

  ```typescript TypeScript theme={null}
  import { readFile, writeFile } from "fs/promises";

  const BASE_URL = "https://cloud.comfy.org";
  const API_KEY = process.env.COMFY_CLOUD_API_KEY!;

  function getHeaders(): HeadersInit {
    return {
      "X-API-Key": API_KEY,
      "Content-Type": "application/json",
    };
  }
  ```

  ```python Python theme={null}
  import os
  import requests
  import json
  import time
  import asyncio
  import aiohttp

  BASE_URL = "https://cloud.comfy.org"
  API_KEY = os.environ["COMFY_CLOUD_API_KEY"]

  def get_headers():
      return {
          "X-API-Key": API_KEY,
          "Content-Type": "application/json"
      }
  ```
</CodeGroup>

***

## Object Info

Retrieve available node definitions. This is useful for understanding what nodes are available and their input/output specifications.

<CodeGroup>
  ```bash curl theme={null}
  curl -X GET "$BASE_URL/api/object_info" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY"
  ```

  ```typescript TypeScript theme={null}
  async function getObjectInfo(): Promise<Record<string, any>> {
    const response = await fetch(`${BASE_URL}/api/object_info`, {
      headers: getHeaders(),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  const objectInfo = await getObjectInfo();
  console.log(`Available nodes: ${Object.keys(objectInfo).length}`);

  const ksampler = objectInfo["KSampler"] ?? {};
  console.log(`KSampler inputs: ${Object.keys(ksampler.input?.required ?? {})}`);
  ```

  ```python Python theme={null}
  def get_object_info():
      """Fetch all available node definitions from cloud."""
      response = requests.get(
          f"{BASE_URL}/api/object_info",
          headers=get_headers()
      )
      response.raise_for_status()
      return response.json()

  # Get all nodes
  object_info = get_object_info()
  print(f"Available nodes: {len(object_info)}")

  # Get a specific node's definition
  ksampler = object_info.get("KSampler", {})
  inputs = list(ksampler.get('input', {}).get('required', {}).keys())
  print(f"KSampler inputs: {inputs}")
  ```
</CodeGroup>

***

## Uploading Inputs

Upload images, masks, or other files for use in workflows.

### Direct Upload (Multipart)

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/upload/image" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -F "image=@my_image.png" \
    -F "type=input" \
    -F "overwrite=true"
  ```

  ```typescript TypeScript theme={null}
  async function uploadInput(
    filePath: string,
    inputType: string = "input"
  ): Promise<{ name: string; subfolder: string }> {
    const file = await readFile(filePath);
    const formData = new FormData();
    formData.append("image", new Blob([file]), filePath.split("/").pop());
    formData.append("type", inputType);
    formData.append("overwrite", "true");

    const response = await fetch(`${BASE_URL}/api/upload/image`, {
      method: "POST",
      headers: { "X-API-Key": API_KEY },
      body: formData,
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  const result = await uploadInput("my_image.png");
  console.log(`Uploaded: ${result.name} to ${result.subfolder}`);
  ```

  ```python Python theme={null}
  def upload_input(file_path: str, input_type: str = "input") -> dict:
      """Upload a file directly to cloud.
      
      Args:
          file_path: Path to the file to upload
          input_type: "input" for images, "temp" for temporary files
          
      Returns:
          Upload response with filename and subfolder
      """
      with open(file_path, "rb") as f:
          files = {"image": f}
          data = {"type": input_type, "overwrite": "true"}
          
          response = requests.post(
              f"{BASE_URL}/api/upload/image",
              headers={"X-API-Key": API_KEY},  # No Content-Type for multipart
              files=files,
              data=data
          )
      response.raise_for_status()
      return response.json()

  # Upload an image
  result = upload_input("my_image.png")
  print(f"Uploaded: {result['name']} to {result['subfolder']}")
  ```
</CodeGroup>

### Upload Mask

<Note>
  The `subfolder` parameter is accepted for API compatibility but ignored in cloud storage. All files are stored in a flat, content-addressed namespace.
</Note>

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/upload/mask" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -F "image=@mask.png" \
    -F "type=input" \
    -F "subfolder=clipspace" \
    -F 'original_ref={"filename":"my_image.png","subfolder":"","type":"input"}'
  ```

  ```typescript TypeScript theme={null}
  async function uploadMask(
    filePath: string,
    originalRef: { filename: string; subfolder: string; type: string }
  ): Promise<{ name: string; subfolder: string }> {
    const file = await readFile(filePath);
    const formData = new FormData();
    formData.append("image", new Blob([file]), filePath.split("/").pop());
    formData.append("type", "input");
    formData.append("subfolder", "clipspace");
    formData.append("original_ref", JSON.stringify(originalRef));

    const response = await fetch(`${BASE_URL}/api/upload/mask`, {
      method: "POST",
      headers: { "X-API-Key": API_KEY },
      body: formData,
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  const maskResult = await uploadMask("mask.png", {
    filename: "my_image.png",
    subfolder: "",
    type: "input",
  });
  console.log(`Uploaded mask: ${maskResult.name}`);
  ```

  ```python Python theme={null}
  def upload_mask(file_path: str, original_ref: dict) -> dict:
      """Upload a mask associated with an original image.
      
      Args:
          file_path: Path to the mask file
          original_ref: Reference to the original image {"filename": "...", "subfolder": "...", "type": "..."}
      """
      with open(file_path, "rb") as f:
          files = {"image": f}
          data = {
              "type": "input",
              "subfolder": "clipspace",
              "original_ref": json.dumps(original_ref)
          }
          
          response = requests.post(
              f"{BASE_URL}/api/upload/mask",
              headers={"X-API-Key": API_KEY},
              files=files,
              data=data
          )
      response.raise_for_status()
      return response.json()
  ```
</CodeGroup>

***

## Running Workflows

Submit a workflow for execution.

<Info>
  **Concurrent submissions supported:** Depending on your subscription tier, you can submit multiple workflows without waiting for previous jobs to complete. Jobs run in parallel up to your tier's limit. Additional jobs queue automatically. See [Concurrent jobs](/development/deploy/cloud-usage#concurrent-jobs) for details and concurrency limits.
</Info>

### Submit Workflow

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/prompt" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{"prompt": '"$(cat workflow_api.json)"'}'
  ```

  ```typescript TypeScript theme={null}
  async function submitWorkflow(workflow: Record<string, any>): Promise<string> {
    const response = await fetch(`${BASE_URL}/api/prompt`, {
      method: "POST",
      headers: getHeaders(),
      body: JSON.stringify({ prompt: workflow }),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    const result = await response.json();

    if (result.error) {
      throw new Error(`Workflow error: ${result.error}`);
    }
    return result.prompt_id;
  }

  const workflow = JSON.parse(await readFile("workflow_api.json", "utf-8"));
  const promptId = await submitWorkflow(workflow);
  console.log(`Submitted job: ${promptId}`);
  ```

  ```python Python theme={null}
  def submit_workflow(workflow: dict) -> str:
      """Submit a workflow and return the prompt_id (job ID).
      
      Args:
          workflow: ComfyUI workflow in API format
          
      Returns:
          prompt_id for tracking the job
      """
      response = requests.post(
          f"{BASE_URL}/api/prompt",
          headers=get_headers(),
          json={"prompt": workflow}
      )
      response.raise_for_status()
      result = response.json()
      
      if "error" in result:
          raise ValueError(f"Workflow error: {result['error']}")
      
      return result["prompt_id"]

  # Load and submit a workflow
  with open("workflow_api.json") as f:
      workflow = json.load(f)

  prompt_id = submit_workflow(workflow)
  print(f"Submitted job: {prompt_id}")
  ```
</CodeGroup>

### Using Partner Nodes

If your workflow contains [Partner Nodes](/tutorials/partner-nodes/overview) (nodes that call external AI services like Flux Pro, Ideogram, etc.), you must include your [Comfy API key](/development/api-development/getting-an-api-key) in the `extra_data` field of the request payload.

<Note>
  The ComfyUI frontend automatically packages your API key into `extra_data` when running workflows in the browser. This section is only relevant when calling the API directly.
</Note>

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/prompt" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "prompt": '"$(cat workflow_api.json)"',
      "extra_data": {
        "api_key_comfy_org": "your-comfy-api-key"
      }
    }'
  ```

  ```typescript TypeScript theme={null}
  async function submitWorkflowWithPartnerNodes(
    workflow: Record<string, any>,
    apiKey: string
  ): Promise<string> {
    const response = await fetch(`${BASE_URL}/api/prompt`, {
      method: "POST",
      headers: getHeaders(),
      body: JSON.stringify({
        prompt: workflow,
        extra_data: {
          api_key_comfy_org: apiKey,
        },
      }),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    const result = await response.json();
    return result.prompt_id;
  }

  // Use when workflow contains Partner Nodes (e.g., Flux Pro, Ideogram, etc.)
  const promptId = await submitWorkflowWithPartnerNodes(workflow, API_KEY);
  ```

  ```python Python theme={null}
  def submit_workflow_with_partner_nodes(workflow: dict, api_key: str) -> str:
      """Submit a workflow that uses Partner Nodes.
      
      Args:
          workflow: ComfyUI workflow in API format
          api_key: Your API key from platform.comfy.org
          
      Returns:
          prompt_id for tracking the job
      """
      response = requests.post(
          f"{BASE_URL}/api/prompt",
          headers=get_headers(),
          json={
              "prompt": workflow,
              "extra_data": {
                  "api_key_comfy_org": api_key
              }
          }
      )
      response.raise_for_status()
      return response.json()["prompt_id"]

  # Use when workflow contains Partner Nodes
  prompt_id = submit_workflow_with_partner_nodes(workflow, API_KEY)
  ```
</CodeGroup>

<Info>
  Generate your API key at [platform.comfy.org](https://platform.comfy.org/login). This is the same key used for Cloud API authentication (`X-API-Key` header). See [Getting an API Key](/development/api-development/getting-an-api-key) for step-by-step instructions.
</Info>

### Modify Workflow Inputs

<CodeGroup>
  ```typescript TypeScript theme={null}
  function setWorkflowInput(
    workflow: Record<string, any>,
    nodeId: string,
    inputName: string,
    value: any
  ): Record<string, any> {
    if (workflow[nodeId]) {
      workflow[nodeId].inputs[inputName] = value;
    }
    return workflow;
  }

  // Example: Set seed and prompt
  let workflow = JSON.parse(await readFile("workflow_api.json", "utf-8"));
  workflow = setWorkflowInput(workflow, "3", "seed", 12345);
  workflow = setWorkflowInput(workflow, "6", "text", "a beautiful landscape");
  ```

  ```python Python theme={null}
  def set_workflow_input(workflow: dict, node_id: str, input_name: str, value) -> dict:
      """Modify a workflow input value.
      
      Args:
          workflow: The workflow dict
          node_id: ID of the node to modify
          input_name: Name of the input field
          value: New value
          
      Returns:
          Modified workflow
      """
      if node_id in workflow:
          workflow[node_id]["inputs"][input_name] = value
      return workflow

  # Example: Set seed and prompt
  workflow = set_workflow_input(workflow, "3", "seed", 12345)
  workflow = set_workflow_input(workflow, "6", "text", "a beautiful landscape")
  ```
</CodeGroup>

***

## Checking Job Status

Poll for job completion.

**Job Status Values:**

The API returns one of the following status values:

| Status | Description |
| - | - |
| `success` | Job finished successfully. Terminal |
| `error` | Job failed. Terminal |
| `non_retryable_error` | Job failed and retrying will not help. Terminal |
| `lost` | Job disappeared before it could finish. Terminal |
| `cancelled` | Job was cancelled. Terminal |

Those five are the terminal states. Everything else means the job is still in flight, including `submitted`, `queued_waiting`, `preparing`, `executing`, and transitional states such as `cancel_requested`. Poll until you see a terminal value rather than matching on the in-flight names.

<CodeGroup>
  ```bash curl theme={null}
  # Poll for job completion
  curl -X GET "$BASE_URL/api/job/{prompt_id}/status" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY"

  # Response examples:
  # {"status": "queued_waiting"}       - Job is queued
  # {"status": "executing"}            - Job is currently running
  # {"status": "success"}              - Job finished successfully
  # {"status": "error"}                - Job encountered an error
  # {"status": "non_retryable_error"}  - Job failed, retrying will not help
  # {"status": "lost"}                 - Job disappeared before finishing
  # {"status": "cancelled"}            - Job was cancelled
  ```

  ```typescript TypeScript theme={null}
  interface JobStatus {
    status: string;
  }

  async function getJobStatus(promptId: string): Promise<JobStatus> {
    const response = await fetch(`${BASE_URL}/api/job/${promptId}/status`, {
      headers: getHeaders(),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  async function pollForCompletion(
    promptId: string,
    timeout: number = 300,
    pollInterval: number = 2000
  ): Promise<void> {
    const startTime = Date.now();

    while (Date.now() - startTime < timeout * 1000) {
      const { status } = await getJobStatus(promptId);

      if (status === "success") {
        return;
      } else if (
        ["error", "non_retryable_error", "lost", "cancelled"].includes(status)
      ) {
        throw new Error(`Job failed with status: ${status}`);
      }

      await new Promise((resolve) => setTimeout(resolve, pollInterval));
    }

    throw new Error(`Job ${promptId} did not complete within ${timeout}s`);
  }

  await pollForCompletion(promptId);
  console.log("Job completed!");
  ```

  ```python Python theme={null}
  def get_job_status(prompt_id: str) -> str:
      """Get the current status of a job."""
      response = requests.get(
          f"{BASE_URL}/api/job/{prompt_id}/status",
          headers=get_headers()
      )
      response.raise_for_status()
      return response.json()["status"]

  def poll_for_completion(prompt_id: str, timeout: int = 300, poll_interval: float = 2.0) -> None:
      """Poll until job completes or times out."""
      start_time = time.time()

      while time.time() - start_time < timeout:
          status = get_job_status(prompt_id)

          if status == "success":
              return
          elif status in ("error", "non_retryable_error", "lost", "cancelled"):
              raise RuntimeError(f"Job failed with status: {status}")

          time.sleep(poll_interval)

      raise TimeoutError(f"Job {prompt_id} did not complete within {timeout}s")

  poll_for_completion(prompt_id)
  print("Job completed!")
  ```
</CodeGroup>

***

## WebSocket for Real-Time Progress

Connect to the WebSocket for real-time execution updates.

<Note>
  The `clientId` parameter is currently ignored—all connections for a user receive the same messages. Pass a unique `clientId` for forward compatibility.
</Note>

<CodeGroup>
  ```typescript TypeScript theme={null}
  async function listenForCompletion(
    promptId: string,
    timeout: number = 300000
  ): Promise<Record<string, any>> {
    const wsUrl = `wss://cloud.comfy.org/ws?clientId=${crypto.randomUUID()}&token=${API_KEY}`;
    const outputs: Record<string, any> = {};

    return new Promise((resolve, reject) => {
      const ws = new WebSocket(wsUrl);
      const timer = setTimeout(() => {
        ws.close();
        reject(new Error(`Job did not complete within ${timeout / 1000}s`));
      }, timeout);

      ws.onmessage = (event) => {
        // Binary frames carry preview images, not JSON.
        if (typeof event.data !== "string") return;

        const data = JSON.parse(event.data);
        const msgType = data.type;
        const msgData = data.data ?? {};

        // Filter to our job
        if (msgData.prompt_id !== promptId) return;

        if (msgType === "executing") {
          const node = msgData.node;
          if (node) {
            console.log(`Executing node: ${node}`);
          } else {
            console.log("Execution complete");
          }
        } else if (msgType === "progress") {
          console.log(`Progress: ${msgData.value}/${msgData.max}`);
        } else if (msgType === "executed" && msgData.output) {
          outputs[msgData.node] = msgData.output;
        } else if (msgType === "execution_success") {
          console.log("Job completed successfully!");
          clearTimeout(timer);
          ws.close();
          resolve(outputs);
        } else if (msgType === "execution_error") {
          const errorMsg = msgData.exception_message ?? "Unknown error";
          clearTimeout(timer);
          ws.close();
          reject(new Error(`Execution error: ${errorMsg}`));
        }
      };

      ws.onerror = (err) => {
        clearTimeout(timer);
        reject(err);
      };
    });
  }

  // Wait for completion and collect outputs
  const outputs = await listenForCompletion(promptId);
  ```

  ```python Python theme={null}
  import asyncio
  import aiohttp
  import json
  import uuid

  async def listen_for_completion(prompt_id: str, timeout: float = 300.0) -> dict:
      """Connect to WebSocket and listen for job completion.

      Returns:
          Final outputs from the job
      """
      ws_url = BASE_URL.replace("https://", "wss://")
      client_id = str(uuid.uuid4())
      ws_url = f"{ws_url}/ws?clientId={client_id}&token={API_KEY}"

      outputs = {}

      async with aiohttp.ClientSession() as session:
          async with session.ws_connect(ws_url) as ws:
              async def receive_messages():
                  async for msg in ws:
                      if msg.type == aiohttp.WSMsgType.TEXT:
                          data = json.loads(msg.data)
                          msg_type = data.get("type")
                          msg_data = data.get("data", {})

                          # Filter to our job
                          if msg_data.get("prompt_id") != prompt_id:
                              continue

                          if msg_type == "executing":
                              node = msg_data.get("node")
                              if node:
                                  print(f"Executing node: {node}")

                          elif msg_type == "progress":
                              value = msg_data.get("value", 0)
                              max_val = msg_data.get("max", 100)
                              print(f"Progress: {value}/{max_val}")

                          elif msg_type == "executed":
                              node_id = msg_data.get("node")
                              output = msg_data.get("output", {})
                              if output:
                                  outputs[node_id] = output

                          elif msg_type == "execution_success":
                              print("Job completed successfully!")
                              return outputs

                          elif msg_type == "execution_error":
                              error_msg = msg_data.get("exception_message", "Unknown error")
                              raise RuntimeError(f"Execution error: {error_msg}")

                      elif msg.type == aiohttp.WSMsgType.ERROR:
                          raise RuntimeError(f"WebSocket error: {ws.exception()}")

              try:
                  return await asyncio.wait_for(receive_messages(), timeout=timeout)
              except asyncio.TimeoutError:
                  raise TimeoutError(f"Job did not complete within {timeout}s")

  # Wait for completion and collect outputs
  outputs = await listen_for_completion(prompt_id)
  ```
</CodeGroup>

### WebSocket Message Types

Messages are sent as JSON text frames unless otherwise noted.

| Type | Description |
| - | - |
| `status` | Queue status update with `queue_remaining` count |
| `notification` | User-friendly status message (`value` field contains text like "Executing workflow\...") |
| `execution_start` | Workflow execution has started |
| `executing` | A specific node is now executing (node ID in `node` field) |
| `progress` | Step progress within a node (`value`/`max` for sampling steps) |
| `progress_state` | Extended progress state with node metadata (nested `nodes` object) |
| `executed` | Node completed with outputs (images, video, etc. in `output` field) |
| `execution_cached` | Nodes skipped because outputs are cached (`nodes` array) |
| `execution_success` | Entire workflow completed successfully |
| `execution_error` | Workflow failed (includes `exception_type`, `exception_message`, `traceback`) |
| `execution_interrupted` | Workflow was cancelled by user |

#### Binary Messages (Preview Images)

During image generation, ComfyUI sends **binary WebSocket frames** containing preview images. These are raw binary data (not JSON):

| Binary Type | Value | Description |
| - | - | - |
| `PREVIEW_IMAGE` | `1` | In-progress preview during diffusion sampling |
| `TEXT` | `3` | Text output from nodes (progress text) |
| `PREVIEW_IMAGE_WITH_METADATA` | `4` | Preview image with node context metadata |

**Binary frame formats** (all integers are big-endian):

<Tabs>
  <Tab title="PREVIEW_IMAGE (1)">
    | Offset | Size | Field | Description |
    | - | - | - | - |
    | 0 | 4 bytes | `type` | `0x00000001` |
    | 4 | 4 bytes | `image_type` | Format code (1=JPEG, 2=PNG) |
    | 8 | variable | `image_data` | Raw image bytes |
  </Tab>

  <Tab title="TEXT (3)">
    | Offset | Size | Field | Description |
    | - | - | - | - |
    | 0 | 4 bytes | `type` | `0x00000003` |
    | 4 | 4 bytes | `node_id_len` | Length of node\_id string |
    | 8 | N bytes | `node_id` | UTF-8 encoded node ID |
    | 8+N | variable | `text` | UTF-8 encoded progress text |
  </Tab>

  <Tab title="PREVIEW_WITH_METADATA (4)">
    | Offset | Size | Field | Description |
    | - | - | - | - |
    | 0 | 4 bytes | `type` | `0x00000004` |
    | 4 | 4 bytes | `metadata_len` | Length of metadata JSON |
    | 8 | N bytes | `metadata` | UTF-8 JSON (see below) |
    | 8+N | variable | `image_data` | Raw JPEG/PNG bytes |

    **Metadata JSON structure:**

    ```json theme={null}
    {
      "node_id": "3",
      "display_node_id": "3",
      "real_node_id": "3",
      "prompt_id": "abc-123",
      "parent_node_id": null
    }
    ```
  </Tab>
</Tabs>

<Note>
  See the [OpenAPI Specification](/development/cloud/openapi) for complete schema definitions of each JSON message type.
</Note>

***

## Downloading Outputs

Retrieve generated files after job completion.

<CodeGroup>
  ```bash curl theme={null}
  # Step 1: read the 302 target. Do not use -L here: following the redirect
  # would resend your API key to the storage host.
  SIGNED_URL=$(curl -s -o /dev/null -w '%{redirect_url}' \
    "$BASE_URL/api/view?filename=output.png&subfolder=&type=output" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY")

  # Step 2: the signed URL carries its own authorization, so send no headers.
  curl -s "$SIGNED_URL" -o output.png
  ```

  ```typescript TypeScript theme={null}
  import { mkdir, writeFile } from "fs/promises";

  async function downloadOutput(
    filename: string,
    subfolder: string = "",
    outputType: string = "output"
  ): Promise<ArrayBuffer> {
    const params = new URLSearchParams({ filename, subfolder, type: outputType });
    // Get the redirect URL
    const response = await fetch(`${BASE_URL}/api/view?${params}`, {
      headers: { "X-API-Key": API_KEY },
      redirect: "manual",
    });
    if (response.status !== 302) throw new Error(`HTTP ${response.status}`);
    const signedUrl = response.headers.get("location")!;

    // Fetch from signed URL
    const fileResponse = await fetch(signedUrl);
    if (!fileResponse.ok) throw new Error(`HTTP ${fileResponse.status}`);
    return fileResponse.arrayBuffer();
  }

  async function saveOutputs(
    outputs: Record<string, any>,
    outputDir: string = "."
  ): Promise<void> {
    await mkdir(outputDir, { recursive: true });
    for (const nodeOutputs of Object.values(outputs)) {
      for (const key of ["images", "video", "audio"]) {
        for (const fileInfo of (nodeOutputs as any)[key] ?? []) {
          const data = await downloadOutput(
            fileInfo.filename,
            fileInfo.subfolder ?? "",
            fileInfo.type ?? "output"
          );
          const path = `${outputDir}/${fileInfo.filename}`;
          await writeFile(path, Buffer.from(data));
          console.log(`Saved: ${path}`);
        }
      }
    }
  }

  // Download all outputs
  await saveOutputs(outputs, "./my_outputs");
  ```

  ```python Python theme={null}
  def download_output(filename: str, subfolder: str = "", output_type: str = "output") -> bytes:
      """Download an output file.

      Args:
          filename: Name of the file
          subfolder: Subfolder path (usually empty)
          output_type: "output" for final outputs, "temp" for previews

      Returns:
          File bytes
      """
      params = {
          "filename": filename,
          "subfolder": subfolder,
          "type": output_type
      }

      # Do not follow the redirect. requests drops Authorization on a cross-host
      # redirect but keeps custom headers, so X-API-Key would reach the storage
      # host. The signed URL carries its own authorization.
      response = requests.get(
          f"{BASE_URL}/api/view",
          headers=get_headers(),
          params=params,
          allow_redirects=False
      )
      if response.status_code != 302:
          raise RuntimeError(f"Expected a 302 redirect, got {response.status_code}")
      signed_url = response.headers["Location"]

      file_response = requests.get(signed_url)
      file_response.raise_for_status()
      return file_response.content

  def save_outputs(outputs: dict, output_dir: str = "."):
      """Save all outputs from a job to disk.

      Args:
          outputs: Outputs dict from job (node_id -> output_data)
          output_dir: Directory to save files to
      """
      import os
      os.makedirs(output_dir, exist_ok=True)

      for node_id, node_outputs in outputs.items():
          for key in ("images", "video", "audio"):
              for file_info in node_outputs.get(key, []):
                  filename = file_info["filename"]
                  subfolder = file_info.get("subfolder", "")
                  output_type = file_info.get("type", "output")

                  data = download_output(filename, subfolder, output_type)

                  output_path = os.path.join(output_dir, filename)
                  with open(output_path, "wb") as f:
                      f.write(data)
                  print(f"Saved: {output_path}")

  # Download all outputs
  save_outputs(outputs, "./my_outputs")
  ```
</CodeGroup>

***

## Complete End-to-End Example

Here's a full example that ties everything together:

<CodeGroup>
  ```typescript TypeScript theme={null}
  import { mkdir, readFile, writeFile } from "fs/promises";

  const BASE_URL = "https://cloud.comfy.org";
  const API_KEY = process.env.COMFY_CLOUD_API_KEY!;

  function getHeaders(): HeadersInit {
    return { "X-API-Key": API_KEY, "Content-Type": "application/json" };
  }

  async function submitWorkflow(workflow: Record<string, any>): Promise<string> {
    const response = await fetch(`${BASE_URL}/api/prompt`, {
      method: "POST",
      headers: getHeaders(),
      body: JSON.stringify({ prompt: workflow }),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return (await response.json()).prompt_id;
  }

  async function waitForCompletion(
    promptId: string,
    timeout: number = 300000
  ): Promise<Record<string, any>> {
    const wsUrl = `wss://cloud.comfy.org/ws?clientId=${crypto.randomUUID()}&token=${API_KEY}`;
    const outputs: Record<string, any> = {};

    return new Promise((resolve, reject) => {
      const ws = new WebSocket(wsUrl);
      const timer = setTimeout(() => {
        ws.close();
        reject(new Error("Job timed out"));
      }, timeout);

      ws.onmessage = (event) => {
        // Binary frames carry preview images, not JSON.
        if (typeof event.data !== "string") return;

        const data = JSON.parse(event.data);
        if (data.data?.prompt_id !== promptId) return;

        const msgType = data.type;
        const msgData = data.data ?? {};

        if (msgType === "progress") {
          console.log(`Progress: ${msgData.value}/${msgData.max}`);
        } else if (msgType === "executed" && msgData.output) {
          outputs[msgData.node] = msgData.output;
        } else if (msgType === "execution_success") {
          clearTimeout(timer);
          ws.close();
          resolve(outputs);
        } else if (msgType === "execution_error") {
          clearTimeout(timer);
          ws.close();
          reject(new Error(msgData.exception_message ?? "Unknown error"));
        }
      };

      ws.onerror = (err) => {
        clearTimeout(timer);
        reject(err);
      };
    });
  }

  async function downloadOutputs(
    outputs: Record<string, any>,
    outputDir: string
  ): Promise<void> {
    await mkdir(outputDir, { recursive: true });
    for (const nodeOutputs of Object.values(outputs)) {
      for (const key of ["images", "video", "audio"]) {
        for (const fileInfo of (nodeOutputs as any)[key] ?? []) {
          const params = new URLSearchParams({
            filename: fileInfo.filename,
            subfolder: fileInfo.subfolder ?? "",
            type: fileInfo.type ?? "output",
          });
          // Get redirect URL (don't follow to avoid sending auth to storage)
          const response = await fetch(`${BASE_URL}/api/view?${params}`, {
            headers: { "X-API-Key": API_KEY },
            redirect: "manual",
          });
          if (response.status !== 302) throw new Error(`HTTP ${response.status}`);
          const signedUrl = response.headers.get("location")!;
          // Fetch from signed URL without auth headers
          const fileResponse = await fetch(signedUrl);
          if (!fileResponse.ok) throw new Error(`HTTP ${fileResponse.status}`);

          const path = `${outputDir}/${fileInfo.filename}`;
          await writeFile(path, Buffer.from(await fileResponse.arrayBuffer()));
          console.log(`Downloaded: ${path}`);
        }
      }
    }
  }

  async function main() {
    // 1. Load workflow
    const workflow = JSON.parse(await readFile("workflow_api.json", "utf-8"));

    // 2. Modify workflow parameters
    workflow["3"].inputs.seed = 42;
    workflow["6"].inputs.text = "a beautiful sunset over mountains";

    // 3. Submit workflow
    const promptId = await submitWorkflow(workflow);
    console.log(`Job submitted: ${promptId}`);

    // 4. Wait for completion with progress
    const outputs = await waitForCompletion(promptId);
    console.log(`Job completed! Found ${Object.keys(outputs).length} output nodes`);

    // 5. Download outputs
    await downloadOutputs(outputs, "./outputs");
    console.log("Done!");
  }

  main();
  ```

  ```python Python theme={null}
  import os
  import requests
  import json
  import asyncio
  import aiohttp
  import uuid

  BASE_URL = "https://cloud.comfy.org"
  API_KEY = os.environ["COMFY_CLOUD_API_KEY"]

  def get_headers():
      return {"X-API-Key": API_KEY, "Content-Type": "application/json"}

  def upload_image(file_path: str) -> dict:
      """Upload an image and return the reference for use in workflows."""
      with open(file_path, "rb") as f:
          response = requests.post(
              f"{BASE_URL}/api/upload/image",
              headers={"X-API-Key": API_KEY},
              files={"image": f},
              data={"type": "input", "overwrite": "true"}
          )
      response.raise_for_status()
      return response.json()

  def submit_workflow(workflow: dict) -> str:
      """Submit workflow and return prompt_id."""
      response = requests.post(
          f"{BASE_URL}/api/prompt",
          headers=get_headers(),
          json={"prompt": workflow}
      )
      response.raise_for_status()
      return response.json()["prompt_id"]

  async def wait_for_completion(prompt_id: str, timeout: float = 300.0) -> dict:
      """Wait for job completion via WebSocket."""
      ws_url = BASE_URL.replace("https://", "wss://") + f"/ws?clientId={uuid.uuid4()}&token={API_KEY}"
      outputs = {}
      
      async with aiohttp.ClientSession() as session:
          # receive_timeout bounds each wait for a frame, so a silent
          # connection cannot hang past the deadline
          async with session.ws_connect(ws_url, receive_timeout=timeout) as ws:
              start = asyncio.get_event_loop().time()
              async for msg in ws:
                  if asyncio.get_event_loop().time() - start > timeout:
                      raise TimeoutError("Job timed out")
                  
                  if msg.type != aiohttp.WSMsgType.TEXT:
                      continue
                      
                  data = json.loads(msg.data)
                  if data.get("data", {}).get("prompt_id") != prompt_id:
                      continue
                  
                  msg_type = data.get("type")
                  msg_data = data.get("data", {})
                  
                  if msg_type == "progress":
                      print(f"Progress: {msg_data.get('value')}/{msg_data.get('max')}")
                  elif msg_type == "executed":
                      if output := msg_data.get("output"):
                          outputs[msg_data["node"]] = output
                  elif msg_type == "execution_success":
                      return outputs
                  elif msg_type == "execution_error":
                      raise RuntimeError(msg_data.get("exception_message", "Unknown error"))
      
      return outputs

  def download_outputs(outputs: dict, output_dir: str):
      """Download all output files."""
      os.makedirs(output_dir, exist_ok=True)
      
      for node_outputs in outputs.values():
          for key in ["images", "video", "audio"]:
              for file_info in node_outputs.get(key, []):
                  params = {
                      "filename": file_info["filename"],
                      "subfolder": file_info.get("subfolder", ""),
                      "type": file_info.get("type", "output")
                  }
                  response = requests.get(f"{BASE_URL}/api/view", headers=get_headers(), params=params)
                  response.raise_for_status()
                  
                  path = os.path.join(output_dir, file_info["filename"])
                  with open(path, "wb") as f:
                      f.write(response.content)
                  print(f"Downloaded: {path}")

  async def main():
      # 1. Load workflow
      with open("workflow_api.json") as f:
          workflow = json.load(f)
      
      # 2. Optionally upload input images
      # image_ref = upload_image("input.png")
      # workflow["1"]["inputs"]["image"] = image_ref["name"]
      
      # 3. Modify workflow parameters
      workflow["3"]["inputs"]["seed"] = 42
      workflow["6"]["inputs"]["text"] = "a beautiful sunset over mountains"
      
      # 4. Submit workflow
      prompt_id = submit_workflow(workflow)
      print(f"Job submitted: {prompt_id}")
      
      # 5. Wait for completion with progress
      outputs = await wait_for_completion(prompt_id)
      print(f"Job completed! Found {len(outputs)} output nodes")
      
      # 6. Download outputs
      download_outputs(outputs, "./outputs")
      print("Done!")

  if __name__ == "__main__":
      asyncio.run(main())
  ```
</CodeGroup>

***

## Queue Management

### Get Queue Status

<CodeGroup>
  ```bash curl theme={null}
  curl -X GET "$BASE_URL/api/queue" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY"
  ```

  ```typescript TypeScript theme={null}
  async function getQueue(): Promise<{
    queue_running: any[];
    queue_pending: any[];
  }> {
    const response = await fetch(`${BASE_URL}/api/queue`, {
      headers: getHeaders(),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  const queue = await getQueue();
  console.log(`Running: ${queue.queue_running.length}`);
  console.log(`Pending: ${queue.queue_pending.length}`);
  ```

  ```python Python theme={null}
  def get_queue():
      """Get current queue status."""
      response = requests.get(
          f"{BASE_URL}/api/queue",
          headers=get_headers()
      )
      response.raise_for_status()
      return response.json()

  queue = get_queue()
  print(f"Running: {len(queue.get('queue_running', []))}")
  print(f"Pending: {len(queue.get('queue_pending', []))}")
  ```
</CodeGroup>

### Cancel a Job

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/queue" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{"delete": ["PROMPT_ID_HERE"]}'
  ```

  ```typescript TypeScript theme={null}
  async function cancelJob(promptId: string): Promise<void> {
    const response = await fetch(`${BASE_URL}/api/queue`, {
      method: "POST",
      headers: getHeaders(),
      body: JSON.stringify({ delete: [promptId] }),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
  }
  ```

  ```python Python theme={null}
  def cancel_job(prompt_id: str):
      """Cancel a pending or running job."""
      response = requests.post(
          f"{BASE_URL}/api/queue",
          headers=get_headers(),
          json={"delete": [prompt_id]}
      )
      response.raise_for_status()
      return response.json()
  ```
</CodeGroup>

### Interrupt Current Execution

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/interrupt" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY"
  ```

  ```typescript TypeScript theme={null}
  async function interrupt(): Promise<void> {
    const response = await fetch(`${BASE_URL}/api/interrupt`, {
      method: "POST",
      headers: getHeaders(),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
  }
  ```

  ```python Python theme={null}
  def interrupt():
      """Interrupt the currently running job."""
      response = requests.post(
          f"{BASE_URL}/api/interrupt",
          headers=get_headers()
      )
      response.raise_for_status()
  ```
</CodeGroup>

***

## Error Handling

### HTTP Errors

REST API endpoints return standard HTTP status codes:

| Status | Description |
| - | - |
| `400` | Invalid request (bad workflow, missing fields) |
| `401` | Unauthorized (invalid or missing API key) |
| `402` | Insufficient credits |
| `429` | Subscription inactive |
| `500` | Internal server error |

### Execution Errors

During workflow execution, errors are delivered via the `execution_error` WebSocket message. The `exception_type` field identifies the error category:

| Exception Type | Description |
| - | - |
| `ValidationError` | Invalid workflow or inputs |
| `ModelDownloadError` | Required model not available or failed to download |
| `ImageDownloadError` | Failed to download input image from URL |
| `OOMError` | Out of GPU memory |
| `InsufficientFundsError` | Account balance too low (for Partner Nodes) |
| `InactiveSubscriptionError` | Subscription not active |


# OpenAPI Specification
Source: https://docs.comfy.org/development/cloud/openapi

/openapi-cloud.yaml
Machine-readable OpenAPI specification for Comfy Cloud API

<Warning>
  **Deprecated:** The v1 Cloud API is deprecated in favor of [Comfy API v2](/api-reference/v2/overview). Endpoints, request/response formats, and behavior may be modified without notice.
</Warning>

# Comfy Cloud API Specification

This page provides the complete OpenAPI 3.0 specification for the Comfy Cloud API.

<Note>
  **Subscription Required:** Running workflows via the API requires an active Comfy Cloud subscription. See [pricing plans](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=cloud-api) for details.
</Note>

## Interactive API Reference

Explore the full API with interactive documentation:

<Card title="Cloud API Reference" icon="code" href="/api-reference/cloud/overview">
  Browse endpoints, view schemas, and try requests
</Card>

## Using the Specification

The OpenAPI spec can be used to:

* **Generate client libraries** in any language using tools like [OpenAPI Generator](https://openapi-generator.tech/)
* **Import into API tools** like Postman, Insomnia, or Paw
* **Generate documentation** using tools like Redoc or Swagger UI
* **Validate requests** in your application

## Download

You can download the raw OpenAPI specification file:

<Card title="openapi-cloud.yaml" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/docs/main/openapi-cloud.yaml">
  Download the OpenAPI 3.0 specification
</Card>

## Authentication

All API requests require an API key passed in the `X-API-Key` header.

### Getting an API Key

See [Getting an API Key](/development/api-development/getting-an-api-key) for step-by-step instructions with screenshots.

### Using the API Key

```yaml theme={null}
X-API-Key: your-api-key
```

## Base URL

| Environment | URL |
| - | - |
| Production | `https://cloud.comfy.org` |

## WebSocket Connection

For real-time updates, connect to the WebSocket endpoint:

```
wss://cloud.comfy.org/ws?clientId={uuid}&token={api_key}
```

See the [Cloud API Reference](/development/cloud/api-reference#websocket-for-real-time-progress) for message types and handling.


# v1 Cloud API Overview
Source: https://docs.comfy.org/development/cloud/overview

The deprecated v1 Cloud API surface: authentication and the Cloud-specific endpoints Comfy API v2 does not expose

<Warning>
  **Deprecated:** The v1 Cloud API is deprecated in favor of [Comfy API v2](/api-reference/v2/overview). It remains available for existing integrations and for Cloud capabilities v2 does not expose yet, but endpoints and behavior may change without notice.
</Warning>

The v1 Cloud API provides programmatic access to [Comfy Cloud](/development/deploy/cloud), Comfy's managed service for running workflows on cloud infrastructure.

Comfy Cloud is a stateful application. Your account carries state that persists across jobs: credits and subscription tier, uploaded assets and generated outputs, the job queue, and the set of installed models and nodes. The v1 API is the surface for that whole application, so it contains functionality not supported in the portable [Comfy API v2](/api-reference/v2/overview), such as queue management, model browsing, node definitions, and account endpoints. Use v2 (or the SDKs that wrap it) to submit workflows and retrieve results in a way that also works against Comfy API deployments and self-hosted ComfyUI. Use v1 for the Cloud-specific capabilities around it.

To run workflows, start with the [Comfy Cloud Quickstart](/development/deploy/cloud) and the [Comfy SDKs](/development/api-development/sdks). Credits and concurrency limits are covered in [Usage and Limits](/development/deploy/cloud-usage); runnable v1 examples are in the [Cloud API Reference](/development/cloud/api-reference). This page covers the v1-specific surface: authentication and the endpoints v2 does not expose.

<Note>
  **Subscription required:** API access requires a paid Comfy Cloud subscription; the Free tier does not include it. See the [pricing plans](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=cloud-api).
</Note>

## Base URL

```
https://cloud.comfy.org
```

## Authentication

All v1 requests require an API key passed in the `X-API-Key` header:

```bash theme={null}
curl -X GET "https://cloud.comfy.org/api/user" \
  -H "X-API-Key: $COMFY_CLOUD_API_KEY"
```

See [Getting an API Key](/development/api-development/getting-an-api-key) for instructions on creating and managing keys. An invalid or missing key returns `401`. A key on an inactive subscription returns `429`.

The same key is used for [Partner Nodes](/tutorials/partner-nodes/overview). Over HTTP you pass it again in `extra_data.api_key_comfy_org`; see [Using Partner Nodes](/development/cloud/api-reference#using-partner-nodes) for examples.

## What the SDKs Don't Cover Yet

The SDKs cover running a workflow, getting the results back, and canceling a job. The rest of the Cloud surface is reachable over HTTP only, so call these endpoints directly even if you use an SDK for execution.

| Capability | Endpoint | Reference |
| - | - | - |
| Queue status, running and pending jobs | `GET /api/queue` | [Queue Management](/development/cloud/api-reference#queue-management) |
| Interrupt the current execution | `POST /api/interrupt` | [Queue Management](/development/cloud/api-reference#queue-management) |
| Node definitions and input specs | `GET /api/object_info` | [Object Info](/development/cloud/api-reference#object-info) |
| Browse available models | Model endpoints | [OpenAPI Specification](/development/cloud/openapi) |
| Account and user information | `GET /api/user` | [OpenAPI Specification](/development/cloud/openapi) |
| Mask uploads that reference an existing image | `POST /api/upload/mask` | [Uploading Inputs](/development/cloud/api-reference#uploading-inputs) |

Canceling a job is covered by both: the SDKs cancel a job you hold a handle to, and `POST /api/queue` cancels by ID.

## Available Endpoints

| Category | Description |
| - | - |
| [Workflows](/development/cloud/api-reference#running-workflows) | Submit workflows, check status |
| [Jobs](/development/cloud/api-reference#checking-job-status) | Monitor job status and queue |
| [Inputs](/development/cloud/api-reference#uploading-inputs) | Upload images, masks, and other inputs |
| [Outputs](/development/cloud/api-reference#downloading-outputs) | Download generated content |
| [WebSocket](/development/cloud/api-reference#websocket-for-real-time-progress) | Real-time progress updates |
| [Object Info](/development/cloud/api-reference#object-info) | Available nodes and their definitions |

## Error Handling

REST endpoints return standard HTTP status codes:

| Status | Description |
| - | - |
| `400` | Invalid request (bad workflow, missing fields) |
| `401` | Unauthorized (invalid or missing API key) |
| `402` | Insufficient credits |
| `429` | Subscription inactive |
| `500` | Internal server error |

The SDKs raise these as typed exceptions instead, including `Unauthorized`, `InvalidWorkflow`, `InsufficientCredits`, `QueueFull`, and `JobFailed`, all extending `ComfyError`.

Execution failures are separate from HTTP errors. See [Error Handling](/development/cloud/api-reference#error-handling) for the `exception_type` values delivered during execution.

## Next Steps

<CardGroup>
  <Card title="Comfy Cloud Quickstart" icon="cloud" href="/development/deploy/cloud">
    Run a workflow from Python or TypeScript.
  </Card>

  <Card title="Usage and Limits" icon="gauge" href="/development/deploy/cloud-usage">
    Review Cloud credits, concurrency, and existing v1 integrations.
  </Card>

  <Card title="Cloud API Reference" icon="book" href="/development/cloud/api-reference">
    Complete endpoint documentation with curl, Python, and TypeScript examples.
  </Card>

  <Card title="Comfy API v2 Reference" icon="cloud" href="/api-reference/v2/overview">
    The versioned HTTP API underneath both SDKs. Use it from any language.
  </Card>

  <Card title="OpenAPI Specification" icon="file-code" href="/development/cloud/openapi">
    Machine-readable API spec for code generation.
  </Card>
</CardGroup>


# Comfy API
Source: https://docs.comfy.org/development/comfy-api/overview

The public API for running ComfyUI workflows headlessly

The public API for running ComfyUI headlessly has evolved over time. For new integrations, use [Comfy API v2](/api-reference/v2/overview). It is supported on open-source ComfyUI (during the beta, via the [API Proxy](/development/comfyui-server/api-proxy)), Comfy Cloud, and [Comfy API deployments on the Developer Platform](/development/serverless/overview). Older versions include the [v1 Cloud API](/development/cloud/overview), which is deprecated.

<CardGroup>
  <Card title="Comfy API v2" icon="cloud" href="/api-reference/v2/overview">
    The versioned HTTP API for running workflows from any language, on any surface. Start here.
  </Card>

  <Card title="v1 Cloud API (deprecated)" icon="clock-rotate-left" href="/development/cloud/overview">
    The older Comfy Cloud API, still available for existing integrations.
  </Card>
</CardGroup>

See also: [Comfy API deployments](/development/serverless/overview) · [Comfy SDKs](/development/api-development/sdks) · [Getting an API Key](/development/api-development/getting-an-api-key)


# API Examples
Source: https://docs.comfy.org/development/comfyui-server/api-examples

Three common patterns for calling the ComfyUI Server API

This page demonstrates three ways to interact with the ComfyUI Server API, from a simple HTTP submission to a full WebSocket integration with real-time image output.

All examples use the [default SD1.5 workflow](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples) for illustration. Before using the API, you need to export your workflow in [API format](/development/api-development/workflow-api-format).

<Note>
  These examples use Python with the standard library and the `websocket-client` package (`pip install websocket-client`). The underlying API protocol is the same regardless of language. See the [Cloud API Reference](/development/cloud/api-reference) for TypeScript and curl equivalents.
</Note>

***

## Method 1: Submit and Forget (HTTP only)

Source: [`basic_api_example.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples/basic_api_example.py)

The simplest approach: submit a workflow and don't wait for results. Useful for fire-and-forget jobs where you check outputs later.

```python theme={null}
"""basic_api_example.py — Submit a workflow via HTTP only."""

import json
from urllib import request

SERVER_ADDRESS = "127.0.0.1:8188"


def queue_prompt(prompt):
    p = {"prompt": prompt}
    data = json.dumps(p).encode("utf-8")
    req = request.Request(
        f"http://{SERVER_ADDRESS}/prompt", data=data
    )
    request.urlopen(req)


if __name__ == "__main__":
    # Load a workflow exported in API format
    prompt_text = """{
        "3": {
            "class_type": "KSampler",
            "inputs": {
                "cfg": 8, "denoise": 1,
                "latent_image": ["5", 0],
                "model": ["4", 0],
                "negative": ["7", 0],
                "positive": ["6", 0],
                "sampler_name": "euler",
                "scheduler": "normal",
                "seed": 8566257, "steps": 20
            }
        },
        "4": {
            "class_type": "CheckpointLoaderSimple",
            "inputs": {"ckpt_name": "v1-5-pruned-emaonly.safetensors"}
        },
        "5": {
            "class_type": "EmptyLatentImage",
            "inputs": {"batch_size": 1, "height": 512, "width": 512}
        },
        "6": {
            "class_type": "CLIPTextEncode",
            "inputs": {"clip": ["4", 1], "text": "masterpiece best quality man"}
        },
        "7": {
            "class_type": "CLIPTextEncode",
            "inputs": {"clip": ["4", 1], "text": "bad hands"}
        },
        "8": {
            "class_type": "VAEDecode",
            "inputs": {"samples": ["3", 0], "vae": ["4", 2]}
        },
        "9": {
            "class_type": "SaveImage",
            "inputs": {"filename_prefix": "ComfyUI", "images": ["8", 0]}
        }
    }"""

    prompt = json.loads(prompt_text)
    # Modify inputs before submitting
    prompt["3"]["inputs"]["seed"] = 5
    prompt["6"]["inputs"]["text"] = "masterpiece best quality man"

    queue_prompt(prompt)
    print("Prompt submitted successfully.")
```

<Info>
  This method uses the `SaveImage` node, which saves images to disk on the server. To retrieve them, you'd need to follow up with a call to `GET /view?filename=...`.
</Info>

***

## Method 2: WebSocket + History (Monitor Completion)

Source: [`websockets_api_example.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples/websockets_api_example.py)

Use WebSocket to wait for execution to finish, then retrieve outputs via the `/history` endpoint. This is the recommended pattern for most use cases.

```python theme={null}
"""websockets_api_example.py — Monitor execution via WebSocket, download via /history."""

import websocket  # pip install websocket-client
import uuid
import json
import urllib.request
import urllib.parse

SERVER_ADDRESS = "127.0.0.1:8188"
client_id = str(uuid.uuid4())


def queue_prompt(prompt, prompt_id):
    p = {"prompt": prompt, "client_id": client_id, "prompt_id": prompt_id}
    data = json.dumps(p).encode("utf-8")
    req = urllib.request.Request(
        f"http://{SERVER_ADDRESS}/prompt", data=data
    )
    urllib.request.urlopen(req)


def get_image(filename, subfolder, folder_type):
    params = urllib.parse.urlencode({
        "filename": filename,
        "subfolder": subfolder,
        "type": folder_type,
    })
    with urllib.request.urlopen(
        f"http://{SERVER_ADDRESS}/view?{params}"
    ) as response:
        return response.read()


def get_history(prompt_id):
    with urllib.request.urlopen(
        f"http://{SERVER_ADDRESS}/history/{prompt_id}"
    ) as response:
        return json.loads(response.read())


def get_images(ws, prompt):
    prompt_id = str(uuid.uuid4())
    queue_prompt(prompt, prompt_id)

    while True:
        out = ws.recv()
        if isinstance(out, str):
            message = json.loads(out)
            if message["type"] == "executing":
                data = message["data"]
                if data["node"] is None and data["prompt_id"] == prompt_id:
                    break  # Execution done
        # Binary frames are preview images — skip them here
        continue

    history = get_history(prompt_id)[prompt_id]
    output_images = {}
    for node_id in history["outputs"]:
        node_output = history["outputs"][node_id]
        images_output = []
        if "images" in node_output:
            for image in node_output["images"]:
                image_data = get_image(
                    image["filename"], image["subfolder"], image["type"]
                )
                images_output.append(image_data)
        output_images[node_id] = images_output
    return output_images


if __name__ == "__main__":
    prompt_text = """{
        "3": { ... }, "4": { ... }, "5": { ... },
        "6": { ... }, "7": { ... }, "8": { ... },
        "9": { "class_type": "SaveImage", "inputs": { ... } }
    }"""
    prompt = json.loads(prompt_text)
    prompt["3"]["inputs"]["seed"] = 5
    prompt["6"]["inputs"]["text"] = "masterpiece best quality man"

    ws = websocket.WebSocket()
    ws.connect(f"ws://{SERVER_ADDRESS}/ws?clientId={client_id}")
    images = get_images(ws, prompt)
    ws.close()

    print(f"Got {len(images)} output node(s) with images.")

    # Display the images (requires Pillow):
    # for node_id in images:
    #     for image_data in images[node_id]:
    #         from PIL import Image
    #         import io
    #         img = Image.open(io.BytesIO(image_data))
    #         img.show()
```

<Tip>
  The WebSocket binary frames contain in-progress preview images during generation. You can decode them for live previews (see the [Server Messages](/development/comfyui-server/comms_messages) page for the binary format).
</Tip>

***

## Method 3: WebSocket with SaveImageWebsocket (Real-time Images)

Source: [`websockets_api_example_ws_images.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples/websockets_api_example_ws_images.py)

For scenarios where you don't want images saved to disk, use the `SaveImageWebsocket` node. Images are delivered directly via WebSocket binary frames.

```python theme={null}
"""websockets_api_example_ws_images.py — Receive images directly via WebSocket."""

import websocket  # pip install websocket-client
import uuid
import json
import urllib.request
import urllib.parse

SERVER_ADDRESS = "127.0.0.1:8188"
client_id = str(uuid.uuid4())


def queue_prompt(prompt):
    p = {"prompt": prompt, "client_id": client_id}
    data = json.dumps(p).encode("utf-8")
    req = urllib.request.Request(
        f"http://{SERVER_ADDRESS}/prompt", data=data
    )
    return json.loads(urllib.request.urlopen(req).read())


def get_images(ws, prompt):
    prompt_id = queue_prompt(prompt)["prompt_id"]
    output_images = {}
    current_node = ""

    while True:
        out = ws.recv()
        if isinstance(out, str):
            message = json.loads(out)
            if message["type"] == "executing":
                data = message["data"]
                if data["prompt_id"] == prompt_id:
                    if data["node"] is None:
                        break  # Execution done
                    current_node = data["node"]
        else:
            # Binary frame — image data from SaveImageWebsocket
            if current_node == "save_image_websocket_node":
                images_output = output_images.get(current_node, [])
                # The first 8 bytes are type/meta, rest is image data
                images_output.append(out[8:])
                output_images[current_node] = images_output

    return output_images


if __name__ == "__main__":
    prompt_text = """{
        "3": { "class_type": "KSampler", "inputs": { ... } },
        ...
        "save_image_websocket_node": {
            "class_type": "SaveImageWebsocket",
            "inputs": {"images": ["8", 0]}
        }
    }"""
    prompt = json.loads(prompt_text)
    prompt["3"]["inputs"]["seed"] = 5

    ws = websocket.WebSocket()
    ws.connect(f"ws://{SERVER_ADDRESS}/ws?clientId={client_id}")
    images = get_images(ws, prompt)
    ws.close()

    print(f"Received {len(images)} image(s) via WebSocket.")

    # Display (requires Pillow):
    # for image_data in images.get("save_image_websocket_node", []):
    #     from PIL import Image
    #     import io
    #     img = Image.open(io.BytesIO(image_data))
    #     img.show()
```

<Info>
  The workflow must use a node with `class_type: "SaveImageWebsocket"` (a built-in node) instead of the regular `SaveImage` node.
</Info>

***

## Which Method Should I Use?

<CardGroup>
  <Card title="Method 1: HTTP Only" icon="paper-plane">
    **Fire and forget.** Use when you don't need immediate output, or when retrieving results later is acceptable.
  </Card>

  <Card title="Method 2: WebSocket + History" icon="chart-line" href="#method-2-websocket-+-history-monitor-completion">
    **Recommended.** Wait for completion, then download outputs. Best balance of simplicity and reliability.
  </Card>

  <Card title="Method 3: SaveImageWebsocket" icon="images" href="#method-3-websocket-with-saveimagewebsocket-real-time-images">
    **Real-time images.** Best for interactive apps where you want images delivered without disk writes.
  </Card>
</CardGroup>

For the full API reference (endpoints, payload formats, error handling), see the [Server Routes](/development/comfyui-server/comms_routes) and [Server Messages](/development/comfyui-server/comms_messages) pages.


# ComfyUI Account API Key Integration
Source: https://docs.comfy.org/development/comfyui-server/api-key-integration

This article explains how to use ComfyUI Account API Key to call paid Partner Nodes in headless mode

Starting from [PR #8041](https://github.com/Comfy-Org/ComfyUI/pull/8041), ComfyUI supports directly using built-in paid Partner Nodes through your ComfyUI Account API Key, without requiring a specific frontend interface (you can even run without a frontend).

This means you can create workflows that combine:

* local OS models
* tools from the custom node community
* popular paid models

Then run everything together by simply sending the prompt to the Comfy webserver API, letting it handle all the orchestration.

This is helpful for users who want to use Comfy as a backend service, via the command line, with their own frontend, etc.

## Prerequisites

Using your ComfyUI Account API Key to call paid Partner Nodes requires:

* A [ComfyUI Account API Key](/development/api-development/getting-an-api-key)
* Sufficient account credits

<Note>
  **Important:** This page describes the **ComfyUI Account API Key** used for accessing paid Partner Nodes in workflows. If you're looking to publish custom nodes to the registry instead, see [Publishing Nodes](/registry/publishing).
</Note>

To use your ComfyUI Account API Key to call paid Partner Nodes, you need to first register an account on [ComfyUI Platform](https://platform.comfy.org/login) and [create an API key](/development/api-development/getting-an-api-key)

You need to ensure your ComfyUI account has sufficient credits to test the corresponding features.

<Card title="Credits" icon="link" href="/interface/credits">
  Please refer to the Credits section to learn how to purchase credits for your account
</Card>

## Python Example

Here is an example of how to send a workflow containing Partner Nodes to the ComfyUI API using Python code:

```python theme={null}
"""Using Partner Nodes when running ComfyUI headless or with alternative frontend

You can execute a ComfyUI workflow that contains Partner Nodes by including an API key in the prompt.
The API key should be added to the `extra_data` field of the payload.
Below we show an example of how to do this.

See more:

- Partner Nodes overview: https://docs.comfy.org/tutorials/partner-nodes/overview
- To generate an API key, login here: https://platform.comfy.org/login
"""

import json
from urllib import request

SERVER_URL = "http://127.0.0.1:8188"

# We have a prompt/job (workflow in "API format") that contains Partner Nodes.
workflow_with_api_nodes = """{
  "11": {
    "inputs": {
      "prompt": "A dreamy, surreal half-body portrait of a young woman meditating. She has a short, straight bob haircut dyed in pastel pink, with soft bangs covering her forehead. Her eyes are gently closed, and her hands are raised in a calm, open-palmed meditative pose, fingers slightly curved, as if levitating or in deep concentration. She wears a colorful dress made of patchwork-like pastel tiles, featuring clouds, stars, and rainbows. Around her float translucent, iridescent soap bubbles reflecting the rainbow hues. The background is a fantastical sky filled with cotton-candy clouds and vivid rainbow waves, giving the entire scene a magical, dreamlike atmosphere. Emphasis on youthful serenity, whimsical ambiance, and vibrant soft lighting.",
      "prompt_upsampling": false,
      "seed": 589991183902375,
      "aspect_ratio": "1:1",
      "raw": false,
      "image_prompt_strength": 0.4000000000000001,
      "image_prompt": [
        "14",
        0
      ]
    },
    "class_type": "FluxProUltraImageNode",
    "_meta": {
      "title": "Flux 1.1 [pro] Ultra Image"
    }
  },
  "12": {
    "inputs": {
      "filename_prefix": "ComfyUI",
      "images": [
        "11",
        0
      ]
    },
    "class_type": "SaveImage",
    "_meta": {
      "title": "Save Image"
    }
  },
  "14": {
    "inputs": {
      "image": "example.png"
    },
    "class_type": "LoadImage",
    "_meta": {
      "title": "Load Image"
    }
  }
}"""


prompt = json.loads(workflow_with_api_nodes)
payload = {
    "prompt": prompt,
    # Add the `api_key_comfy_org` to the payload.
    # You can first get the key from the associated user if handling multiple clients.
    "extra_data": {
        "api_key_comfy_org": "comfyui-87d01e28d*******************************************************"  # replace with actual key
    },
}
data = json.dumps(payload).encode("utf-8")
req = request.Request(f"{SERVER_URL}/prompt", data=data)
request.urlopen(req)

```

## Related Documentation

* [Partner Nodes overview](https://docs.comfy.org/tutorials/partner-nodes/overview)
* [Account management](https://docs.comfy.org/interface/user)
* [Credits](https://docs.comfy.org/interface/credits)


# API Proxy for Self-Hosted ComfyUI
Source: https://docs.comfy.org/development/comfyui-server/api-proxy

Serve the Comfy API v2 in front of your own ComfyUI so the official SDKs can run workflows against it

The [Comfy SDKs](/development/api-development/sdks) speak [Comfy API v2](/api-reference/v2/overview). During the beta, a self-hosted ComfyUI does not serve v2 itself. [comfy-api-proxy](https://github.com/Comfy-Org/comfy-api-proxy) is a small open-source service that runs alongside your instance and serves the v2 contract in front of it.

<Note>
  The proxy is a stopgap. Once the v2 API stabilizes it moves into ComfyUI core and the proxy is no longer needed.
</Note>

## Install and run

```bash theme={null}
pip install comfy-api-proxy
comfy-api-proxy
```

By default it proxies the ComfyUI on `127.0.0.1:8188` and serves the v2 API on `127.0.0.1:8189`. Use `--comfyui` and `--port` to change either.

Run it with `--comfyui-base-dir /path/to/ComfyUI` if you also want to upload model files into your install.

## Point the SDK at it

Set the base URL and construct the client as usual:

```bash theme={null}
export COMFY_BASE_URL="http://127.0.0.1:8189"
```

<CodeGroup>
  ```python Python theme={null}
  from comfy_sdk import Comfy

  client = Comfy()
  ```

  ```typescript TypeScript theme={null}
  import { Comfy } from "@comfyorg/sdk";

  const client = new Comfy();
  ```
</CodeGroup>

Everything in the [SDK guide](/development/api-development/sdks) works the same way against the proxy as against Comfy Cloud.

## Authentication

Authentication is not required by default. If the proxy is configured with a static bearer token, pass that token as the SDK API key: `Comfy(api_key="...")`.

<Warning>
  The proxy binds to loopback only by default. If you expose it beyond loopback, for example in front of a ComfyUI on a rented GPU, configure a bearer token or put an authenticating reverse proxy in front of it.
</Warning>

## Next steps

* [Comfy SDKs](/development/api-development/sdks): the client guide
* [Comfy API v2 Reference](/api-reference/v2/overview): the HTTP contract the proxy serves
* [Self-Hosting Options](/development/deploy/self-hosting): where to run the ComfyUI behind it
* [Design Notes](/development/api-development/sdks-design#the-local-proxy): why the proxy exists


# ComfyUI Server Messages (WebSocket API)
Source: https://docs.comfy.org/development/comfyui-server/comms_messages

How ComfyUI's PromptExecutor sends WebSocket messages to the client, built-in types like execution_start and progress, and registering custom message types.

## Messages

During execution (or when the state of the queue changes), the `PromptExecutor` sends messages back to the client
through the `send_sync` method of `PromptServer`.

These messages are received by a socket event listener defined in `api.js` (at time of writing around line 90, or search for `this.socket.addEventListener`),
which creates a `CustomEvent` object for any known message type, and dispatches it to any registered listeners.

An extension can register to receive events (normally done in the `setup()` function) following the standard Javascript idiom:

```Javascript theme={null}
api.addEventListener(message_type, messageHandler);
```

If the `message_type` is not one of the built in ones, it will be added to the list of known message types automatically. The message `messageHandler`
will be called with a `CustomEvent` object, which extends the event raised by the socket to add a `.detail` property, which is a dictionary of
the data sent by the server. So usage is generally along the lines of:

```Javascript theme={null}
function messageHandler(event) {
    if (event.detail.node == aNodeIdThatIsInteresting) {
        // do something with event.detail.other_things
    }
}
```

### Built in message types

During execution (or when the state of the queue changes), the `PromptExecutor` sends the following messages back to the client
through the `send_sync` method of `PromptServer`. An extension can register as a listener for any of these.

| event | when | data |
| - | - | - |
| `execution_start` | When a prompt is about to run | `prompt_id` |
| `execution_error` | When an error occurs during execution | `prompt_id`, plus additional information |
| `execution_interrupted` | When execution is stopped by a node raising `InterruptProcessingException` | `prompt_id`, `node_id`, `node_type` and `executed` (a list of executed nodes) |
| `execution_cached` | At the start of execution | `prompt_id`, `nodes` (a list of nodes which are being skipped because their cached outputs can be used) |
| `execution_success` | When all nodes from the prompt have been successfully executed | `prompt_id`, `timestamp` |
| `executing` | When a new node is about to be executed | `node` (node id or `None` to indicate completion), `prompt_id` |
| `executed` | When a node returns a ui element | `node` (node id), `prompt_id`, `output` |
| `progress` | During execution of a node that implements the required hook | `node` (node id), `prompt_id`, `value`, `max` |
| `status` | When the state of the queue changes | `exec_info`, a dictionary holding `queue_remaining`, the number of entries in the queue |

### Using executed

Despite the name, an `executed` message is not sent whenever a node completes execution (unlike `executing`), but only when the node
returns a ui update.

To do this, the main function needs to return a dictionary instead of a tuple:

```python theme={null}
# at the end of my main method
        return { "ui":a_new_dictionary, "result": the_tuple_of_output_values }
```

`a_new_dictionary` will then be sent as the value of `output` in an `executed` message.
The `result` key can be omitted if the node has no outputs (see, for instance, the code for `SaveImage` in `nodes.py`)

### Custom message types

As indicated above, on the client side, a custom message type can be added simply by registering as a listener for a unique message type name.

```Javascript theme={null}
api.addEventListener("my.custom.message", messageHandler);
```

On the server, the code is equally simple:

```Python theme={null}
from server import PromptServer
# then, in your main execution function (normally)
        PromptServer.instance.send_sync("my.custom.message", a_dictionary)
```

#### Getting node\_id

Most of the built-in messages include the current node id in the value of `node`. It's likely that you will want to do the same.

The node\_id is available on the server side through a hidden input, which is obtained with the `hidden` key in the `INPUT_TYPES` dictionary:

```Python theme={null}
    @classmethod    
    def INPUT_TYPES(s):
        return {"required" : { }, # whatever your required inputs are 
                "hidden": { "node_id": "UNIQUE_ID" } } # Add the hidden key

    def my_main_function(self, required_inputs, node_id):
        # do some things
        PromptServer.instance.send_sync("my.custom.message", {"node": node_id, "other_things": etc})
```


# Server Overview
Source: https://docs.comfy.org/development/comfyui-server/comms_overview

Run ComfyUI as a server and interact with it programmatically via REST and WebSocket APIs

ComfyUI runs as an HTTP server on your machine by default. You can call it programmatically to submit workflows, upload files, download outputs, and monitor progress — all without opening the browser.

## Starting the Server

When you launch ComfyUI, it automatically starts an HTTP server at `http://127.0.0.1:8188`.

To run ComfyUI as a headless server (no browser):

<CodeGroup>
  ```bash theme={null}
  # Run without opening the browser
  python main.py --disable-auto-launch
  ```

  ```bash theme={null}
  # Specify a custom port
  python main.py --port 8288
  ```

  ```bash theme={null}
  # Listen on all network interfaces (for remote access)
  python main.py --listen 0.0.0.0
  ```
</CodeGroup>

<Tip>
  For a full list of startup flags, run `python main.py --help` or see the [Startup Flags reference](/development/comfyui-server/startup-flags).
</Tip>

## Key Pages in This Section

<CardGroup>
  <Card title="Startup Flags" icon="terminal" href="/development/comfyui-server/startup-flags">
    Complete reference for all main.py command-line arguments.
  </Card>

  <Card title="API Routes" icon="route" href="/development/comfyui-server/comms_routes">
    Available HTTP endpoints for submitting workflows, uploading files, and querying status.
  </Card>

  <Card title="API Examples" icon="code" href="/development/comfyui-server/api-examples">
    Code examples for calling the API: HTTP-only, WebSocket + History, and SaveImageWebsocket.
  </Card>

  <Card title="Server Messages" icon="comments" href="/development/comfyui-server/comms_messages">
    WebSocket message types the server sends to the client during execution.
  </Card>

  <Card title="Execution Model Inversion" icon="code-branch" href="/development/comfyui-server/execution_model_inversion_guide">
    Advanced: invert execution for custom control flows.
  </Card>
</CardGroup>

## Using Partner Nodes

If your workflow contains paid Partner Nodes, you can include your API key in the payload. See the [Partner Node API Integration](/development/comfyui-server/api-key-integration) guide for details.

***

## How the Server Works

The Comfy server runs on top of the [aiohttp framework](https://docs.aiohttp.org/), which in turn uses [asyncio](https://pypi.org/project/asyncio/).

Messages from the server to the client are sent by socket messages through the `send_sync` method of the server, which is an instance of `PromptServer` (defined in `server.py`). They are processed by a socket event listener registered in `api.js`. See [messages](/development/comfyui-server/comms_messages).

Messages from the client to the server are sent by the `api.fetchApi()` method defined in `api.js`, and are handled by HTTP routes defined by the server. See [routes](/development/comfyui-server/comms_routes).

<Tip>
  The client submits the whole workflow (widget values and all) when you queue a request.
  The server does not receive any changes you make after you send a request to the queue.
  If you want to modify server behavior during execution, you'll need routes.
</Tip>


# ComfyUI Server Routes (HTTP and WebSocket API)
Source: https://docs.comfy.org/development/comfyui-server/comms_routes

ComfyUI Server API routes: built-in GET, POST, and WebSocket endpoints for prompts, queue, history, models, and user data, plus how to add custom routes.

## Routes

The server defines a series of `get` and `post` methods
which can be found by searching for `@routes` in `server.py`. When you submit a workflow
in the web client, it is posted to `/prompt` which validates the prompt and adds it to an execution queue,
returning either a `prompt_id` and `number` (the position in the queue), or `error` and `node_errors` if validation fails.
The prompt queue is defined in `execution.py`, which also defines the `PromptExecutor` class.

### Built in routes

`server.py` defines the following routes:

#### Core API Routes

| path | get/post/ws | purpose |
| - | - | - |
| `/` | get | load the comfy webpage |
| `/ws` | websocket | WebSocket endpoint for real-time communication with the server |
| `/embeddings` | get | retrieve a list of the names of embeddings available |
| `/extensions` | get | retrieve a list of the extensions registering a `WEB_DIRECTORY` |
| `/features` | get | retrieve server features and capabilities |
| `/models` | get | retrieve a list of available model types |
| `/models/{folder}` | get | retrieve models in a specific folder |
| `/workflow_templates` | get | retrieve a map of custom node modules and associated template workflows |
| `/upload/image` | post | upload an image |
| `/upload/mask` | post | upload a mask |
| `/view` | get | view an image. Lots of options, see `@routes.get("/view")` in `server.py` |
| `/view_metadata`/ | get | retrieve metadata for a model |
| `/system_stats` | get | retrieve information about the system (python version, devices, vram etc) |
| `/prompt` | get | retrieve current queue status and execution information |
| `/prompt` | post | submit a prompt to the queue |
| `/object_info` | get | retrieve details of all node types |
| `/object_info/{node_class}` | get | retrieve details of one node type |
| `/history` | get | retrieve the queue history |
| `/history/{prompt_id}` | get | retrieve the queue history for a specific prompt |
| `/history` | post | clear history or delete history item |
| `/queue` | get | retrieve the current state of the execution queue |
| `/queue` | post | manage queue operations (clear pending/running) |
| `/interrupt` | post | stop the current workflow execution |
| `/free` | post | free memory by unloading specified models |
| `/userdata` | get | list user data files in a specified directory |
| `/v2/userdata` | get | enhanced version that lists files and directories in structured format |
| `/userdata/{file}` | get | retrieve a specific user data file |
| `/userdata/{file}` | post | upload or update a user data file |
| `/userdata/{file}` | delete | delete a specific user data file |
| `/userdata/{file}/move/{dest}` | post | move or rename a user data file |
| `/users` | get | get user information |
| `/users` | post | create a new user (multi-user mode only) |

### WebSocket Communication

The `/ws` endpoint provides real-time bidirectional communication between the client and server. This is used for:

* Receiving execution progress updates
* Getting node execution status in real-time
* Receiving error messages and debugging information
* Live updates when queue status changes

The WebSocket connection sends JSON messages with different types such as:

* `status` - Overall system status updates
* `execution_start` - When a prompt execution begins
* `execution_cached` - When cached results are used
* `executing` - Updates during node execution
* `progress` - Progress updates for long-running operations
* `executed` - When a node completes execution

### Custom routes

If you want to send a message from the client to the server during execution, you will need to add a custom route to the server.
For anything complicated, you will need to dive into the [aiohttp framework docs](https://docs.aiohttp.org/), but most cases can
be handled as follows:

```Python theme={null}
from server import PromptServer
from aiohttp import web
routes = PromptServer.instance.routes
@routes.post('/my_new_path')
async def my_function(request):
    the_data = await request.post()
    # the_data now holds a dictionary of the values sent
    MyClass.handle_my_message(the_data)
    return web.json_response({})
```

<Tip>Unless you know what you are doing, don't try to define `my_function` within a class.
The `@routes.post` decorator does a lot of work! Instead, define the function as above
and then call a classmethod.</Tip>

<Tip>You can also define a `@routes.get` if you aren't changing anything.</Tip>

The client can use this new route by sending a `FormData` object with code something like this,
which would result in `the_data`, in the above code, containing `message` and `node_id` keys:

```Javascript theme={null}
import { api } from "../../scripts/api.js";
function send_message(node_id, message) {
    const body = new FormData();
    body.append('message',message);
    body.append('node_id', node_id);
    api.fetchApi("/my_new_path", { method: "POST", body, });
}
```


# Startup Flags
Source: https://docs.comfy.org/development/comfyui-server/startup-flags

ComfyUI startup flags reference: every main.py command-line argument from comfy/cli_args.py, plus how to add flags to Windows Portable .bat launchers.

ComfyUI accepts command-line arguments when started with `python main.py`. This page documents every flag defined in [`comfy/cli_args.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/comfy/cli_args.py).

<Note>
  **Windows Portable** users can add flags to the `.bat` launch files (for example, `run_nvidia_gpu.bat`). See the [Windows Portable guide](/installation/comfyui_portable_windows) for details.
</Note>

Run `python main.py --help` in your ComfyUI directory for the built-in help text. Combine multiple flags as needed:

```bash theme={null}
python main.py --listen 0.0.0.0 --port 8288 --disable-auto-launch --lowvram
```

## Network & Server

| Flag | Default | Description |
| - | - | - |
| `--listen` `[IP]` | `127.0.0.1` | IP address to listen on. Comma-separated list supported (e.g. `127.2.2.2,127.3.3.3`). If provided without a value, defaults to `0.0.0.0,::` (all IPv4 and IPv6 interfaces). |
| `--port` | `8188` | Port to listen on. |
| `--tls-keyfile` `PATH` | — | Path to TLS (SSL) key file. Enables HTTPS. Requires `--tls-certfile`. |
| `--tls-certfile` `PATH` | — | Path to TLS (SSL) certificate file. Enables HTTPS. Requires `--tls-keyfile`. |
| `--enable-cors-header` `[ORIGIN]` | disabled | Enable CORS. Optional origin, or `*` for all origins when no value is given. |
| `--max-upload-size` | `100` | Maximum upload size in MB. |
| `--enable-compress-response-body` | disabled | Enable compressing the HTTP response body. |

<CodeGroup>
  ```bash theme={null}
  # Listen on all interfaces (LAN access)
  python main.py --listen

  # Listen on a specific IP
  python main.py --listen 0.0.0.0

  # Custom port with HTTPS
  python main.py --port 8443 --tls-keyfile key.pem --tls-certfile cert.pem
  ```
</CodeGroup>

## Directories

| Flag | Default | Description |
| - | - | - |
| `--base-directory` `PATH` | ComfyUI root | Base directory for models, custom\_nodes, input, output, temp, and user directories. |
| `--models-directory` `PATH` | ComfyUI root/models | Models directory. Overrides the models folder in `--base-directory`. |
| `--extra-model-paths-config` `PATH` | — | Load one or more `extra_model_paths.yaml` files. Can be specified multiple times. |
| `--output-directory` `PATH` | — | Output directory. Overrides `--base-directory`. |
| `--temp-directory` `PATH` | — | Temp directory. Overrides `--base-directory`. |
| `--input-directory` `PATH` | — | Input directory. Overrides `--base-directory`. |
| `--user-directory` `PATH` | — | User directory (absolute path). Overrides `--base-directory`. Path must exist and be readable. |

## Launch & Browser

| Flag | Default | Description |
| - | - | - |
| `--auto-launch` | disabled | Automatically open ComfyUI in the default browser on startup. |
| `--disable-auto-launch` | disabled | Disable auto-launching the browser. |
| `--windows-standalone-build` | disabled | Windows portable build convenience mode. Enables auto-launch on startup (equivalent to `--auto-launch`). |

<Note>
  `--windows-standalone-build` sets `auto_launch` to `true`. `--disable-auto-launch` overrides it. To run as a server without opening a browser, use `--disable-auto-launch`.
</Note>

```bash theme={null}
# Run server without opening browser
python main.py --disable-auto-launch
```

## Devices & CUDA

| Flag | Default | Description |
| - | - | - |
| `--cuda-device` `DEVICE_ID` | — | CUDA device IDs to use, comma-separated (e.g. `0` or `0,1`), or `all` to keep all currently visible devices. Other devices are hidden. |
| `--default-device` `ID` | — | Default device ID. All other devices remain visible. |
| `--cuda-malloc` | auto (torch 2.0+) | Enable cudaMallocAsync. Mutually exclusive with `--disable-cuda-malloc`. |
| `--disable-cuda-malloc` | — | Disable cudaMallocAsync. Mutually exclusive with `--cuda-malloc`. |
| `--directml` `[DEVICE]` | — | Use torch-directml. Optional device index; defaults to `-1` when no value is given. |
| `--oneapi-device-selector` `STRING` | — | oneAPI device selector string for Intel devices. |

<Note>
  On Windows, ComfyUI uses GPU 0 only by default. To restore all GPUs, pass `--cuda-device all`.
</Note>

## Precision & Inference

<Note>
  Flags in the **Global**, **UNET**, **VAE**, and **Text Encoder** groups below are mutually exclusive within each group. Only one flag per group can be used at a time.
</Note>

### Global floating point

| Flag | Description |
| - | - |
| `--force-fp32` | Force fp32 globally. Report if this improves GPU performance. |
| `--force-fp16` | Force fp16 globally. Also sets `--fp16-unet`. |

### UNET precision

| Flag | Description |
| - | - |
| `--fp32-unet` | Run the diffusion model in fp32. |
| `--fp64-unet` | Run the diffusion model in fp64. |
| `--bf16-unet` | Run the diffusion model in bf16. |
| `--fp16-unet` | Run the diffusion model in fp16. |
| `--fp8_e4m3fn-unet` | Store UNet weights in fp8 (e4m3fn). |
| `--fp8_e5m2-unet` | Store UNet weights in fp8 (e5m2). |
| `--fp8_e8m0fnu-unet` | Store UNet weights in fp8 (e8m0fnu). |

Each FP8 flag suffix names an 8-bit float layout from the industry FP8 spec (ONNX / OCP):

* **e4m3fn**: 4 exponent bits, 3 mantissa bits. Good balance of precision and range for model weights on NVIDIA Ada Lovelace and newer GPUs.
* **e5m2**: 5 exponent bits, 2 mantissa bits. Wider dynamic range but lower precision than e4m3fn. Useful when weight magnitudes vary widely.
* **e8m0fnu**: 8 exponent bits, 0 mantissa bits. Maximum dynamic range with no fractional precision. Typically used as a block scaling factor (powers of two only).

### VAE precision

| Flag | Description |
| - | - |
| `--fp16-vae` | Run the VAE in fp16. May cause black images. |
| `--fp32-vae` | Run the VAE in full precision fp32. |
| `--bf16-vae` | Run the VAE in bf16. |
| `--cpu-vae` | Run the VAE on the CPU (not mutually exclusive with VAE precision flags). |

### Text encoder precision

| Flag | Description |
| - | - |
| `--fp8_e4m3fn-text-enc` | Store text encoder weights in fp8 (e4m3fn). |
| `--fp8_e5m2-text-enc` | Store text encoder weights in fp8 (e5m2). |
| `--fp16-text-enc` | Store text encoder weights in fp16. |
| `--fp32-text-enc` | Store text encoder weights in fp32. |
| `--bf16-text-enc` | Store text encoder weights in bf16. |

See the [UNET precision](#unet-precision) section for the explanation of each FP8 format suffix.

### Other inference options

| Flag | Default | Description |
| - | - | - |
| `--fp16-intermediates` | disabled | Experimental: use fp16 for intermediate tensors between nodes instead of fp32. |
| `--force-channels-last` | disabled | Force channels-last memory format during inference. |
| `--supports-fp8-compute` | disabled | Act as if the device supports fp8 compute. |
| `--enable-triton-backend` | disabled | Enable Triton backend in comfy-kitchen. Disabled by default at launch. |
| `--disable-triton-backend` | disabled | Force-disable the comfy-kitchen Triton backend, overriding `--enable-triton-backend`. |

## Preview

| Flag | Default | Description |
| - | - | - |
| `--preview-method` | `none` | Preview method for sampler nodes. Choices: `none`, `auto`, `latent2rgb`, `taesd`. |
| `--preview-size` | `512` | Maximum preview image size in pixels. |

## Cache

<Note>
  Cache mode flags are mutually exclusive. Only one of `--cache-ram`, `--cache-classic`, `--high-ram`, `--cache-lru`, or `--cache-none` should be used.
</Note>

| Flag | Default | Description |
| - | - | - |
| `--cache-ram` `[GB] [GB]` | enabled (default mode) | RAM pressure caching. First value: active-cache threshold in GB. Optional second value: inactive-cache/pin threshold in GB. When no values given: active = 10% of system RAM (min 2 GB, max 10 GB); inactive = 100% of system RAM (max 128 GB). Accepts at most two values. |
| `--cache-classic` | — | Use the old aggressive caching style. |
| `--high-ram` | disabled | Can improve performance slightly on systems with plenty of RAM or where pagefile use is preferred over reloading models. Also enables classic caching. |
| `--cache-lru` `N` | `0` (disabled) | LRU caching with a maximum of N node results cached. No hard upper limit; bounded by available RAM/VRAM. May use more RAM/VRAM. |
| `--cache-none` | — | Reduced RAM/VRAM usage; re-executes every node on each run. |

<Note>
  ComfyUI reuses cached node results between runs in the same session, which is what makes repeat runs faster. Use `--cache-none` when you would rather every run start from a clean cache, for example while debugging a workflow or ruling out cached reuse between runs. Every node re-executes, so generations take longer. It is a startup flag, so restart ComfyUI for it to take effect.
</Note>

## Attention

<Note>
  Cross-attention method flags are mutually exclusive. Split and quad attention are ignored when xformers is used.
</Note>

| Flag | Description |
| - | - |
| `--use-split-cross-attention` | Use split cross attention optimization. |
| `--use-quad-cross-attention` | Use sub-quadratic cross attention optimization. |
| `--use-pytorch-cross-attention` | Use PyTorch 2.0 cross attention. |
| `--use-sage-attention` | Use Sage attention. |
| `--use-flash-attention` | Use FlashAttention. |
| `--use-ck-attention` | Use Comfy Kitchen attention. Requires hardware support for its INT8 kernels. |
| `--disable-xformers` | Disable xformers. |
| `--force-upcast-attention` | Force attention upcasting. Report if this fixes black images. Mutually exclusive with `--dont-upcast-attention`. |
| `--dont-upcast-attention` | Disable all attention upcasting. For debugging only. |

## VRAM & Memory

Async weight offloading is on by default on Nvidia and AMD GPUs, and dynamic VRAM is enabled automatically where it is supported. The flags below override those defaults.

<Note>
  VRAM mode flags (`--gpu-only`, `--highvram`, `--lowvram`, `--novram`, `--cpu`) are mutually exclusive.
</Note>

| Flag | Default | Description |
| - | - | - |
| `--gpu-only` | — | Store and run everything on the GPU (text encoders, CLIP, etc.). |
| `--highvram` | — | Keep models in GPU memory instead of unloading to CPU after use. |
| `--lowvram` | — | No effect when dynamic VRAM is enabled. Otherwise, runs text encoders on CPU. |
| `--novram` | — | Minimal VRAM usage when `--lowvram` is not enough. |
| `--cpu` | — | Use CPU for everything (slow). |
| `--reserve-vram` `GB` | OS-dependent | VRAM in GB to reserve for the OS and other software. |
| `--vram-headroom` `GB` | `0` | Extra VRAM in GB for dynamic VRAM to keep free above the default headroom. ComfyUI tries to keep this much VRAM completely free and unused, even counting VRAM used by other apps. |
| `--disable-nvml-pressure` | disabled | Use CUDA instead of NVML to report dynamic VRAM memory pressure. |
| `--async-offload` `[NUM_STREAMS]` | enabled on Nvidia and AMD | Async weight offloading. Optional stream count (default: 2). |
| `--disable-async-offload` | — | Disable async weight offloading. |
| `--disable-dynamic-vram` | — | Disable dynamic VRAM; use estimate-based model loading. |
| `--enable-dynamic-vram` | auto on Nvidia, ROCm 7.14+ | Enable dynamic VRAM on systems where it is not enabled by default. |
| `--fast-disk` | disabled | Prefer disk-backed dynamic loading over unpinned RAM. Useful with fast NVMe. |
| `--disable-fast-disk` | disabled | Disable disk-backed dynamic loading and offload, so unpinned RAM is used instead. Overrides `--fast-disk`. |
| `--disable-cuda-graphs` | disabled | Disable CUDA graphs. |
| `--disable-comfy-compiler` | disabled | Disable the Comfy model compiler, including its CUDA graph subfeature. |
| `--assert-graph-breaks` | disabled | Fail on Comfy model compiler graph breaks. |
| `--force-non-blocking` | disabled | Force non-blocking tensor operations. May help on non-Nvidia systems; can break some workflows. |
| `--disable-smart-memory` | disabled | Aggressively offload to RAM instead of keeping models in VRAM. |
| `--disable-pinned-memory` | disabled | Disable pinned memory use. |
| `--mmap-torch-files` | disabled | Use mmap when loading ckpt/pt files. |
| `--disable-mmap` | disabled | Do not use mmap when loading safetensors. |

## Performance & Debugging

| Flag | Default | Description |
| - | - | - |
| `--fast` `[OPT...]` | disabled | Enable experimental optimizations that may affect quality or stability. `--fast` alone enables all. Specific options: `fp16_accumulation`, `fp8_matrix_mult`, `cublas_ops`, `autotune`. |
| `--deterministic` | disabled | Use slower deterministic PyTorch algorithms where possible. Does not guarantee identical images in all cases. |
| `--default-hashing-function` | `sha256` | Hash function for duplicate filename/content comparison. Choices: `md5`, `sha1`, `sha256`, `sha512`. |
| `--debug-hang` | disabled | Enable stack trace dumps on Ctrl-C for debugging hangs. |

```bash theme={null}
# Enable all fast optimizations (experimental)
python main.py --fast

# Enable specific optimizations only
python main.py --fast fp16_accumulation cublas_ops
```

## ComfyUI Manager

See [ComfyUI-Manager Installation](/manager/install) for setup instructions.

| Flag | Description |
| - | - |
| `--enable-manager` | Enable ComfyUI-Manager. |
| `--disable-manager-ui` | Disable Manager UI and endpoints only. Background tasks (scheduled installs, etc.) continue. Requires `--enable-manager`. |
| `--enable-manager-legacy-ui` | Use the legacy Manager UI. Implies `--enable-manager`. Mutually exclusive with `--disable-manager-ui`. |

## Custom Nodes & API Nodes

| Flag | Default | Description |
| - | - | - |
| `--disable-all-custom-nodes` | disabled | Disable loading all custom nodes. |
| `--whitelist-custom-nodes` `FOLDER...` | — | Custom node folders to load even when `--disable-all-custom-nodes` is set. |
| `--disable-partner-nodes` | disabled | Disable loading Partner Nodes (the paid API nodes). The frontend keeps its internet access. |
| `--offline` | disabled | Prevent the frontend from communicating with the internet by adding a restrictive Content-Security-Policy. Also disables Partner Nodes. |
| `--disable-api-nodes` | disabled | Deprecated alias for `--offline`. Use `--offline`, or `--disable-partner-nodes` to only disable Partner Nodes. |
| `--disable-metadata` | disabled | Disable saving prompt metadata in output files. |

<Note>
  `--offline` also changes what the browser is allowed to load. The flag adds a Content-Security-Policy that keeps the page on resources served by ComfyUI itself, so images, fonts, media, frames, and network requests from other origins are blocked, and Partner Nodes (API nodes) are not registered at all. If a preview or a thumbnail that normally loads goes missing after a restart, check the launch arguments for this flag before troubleshooting the node. `--disable-partner-nodes` only stops Partner Nodes from loading and leaves the rest of the frontend's internet access intact.
</Note>

```bash theme={null}
# Troubleshoot custom node issues
python main.py --disable-all-custom-nodes

# Allow only specific custom nodes
python main.py --disable-all-custom-nodes --whitelist-custom-nodes ComfyUI-Manager
```

## Frontend & API

| Flag | Default | Description |
| - | - | - |
| `--front-end-version` | `comfyanonymous/ComfyUI@latest` | Frontend version in `[owner]/[repo]@[version]` format. Requires internet to download from GitHub releases. Version can be `latest` or a semver (e.g. `1.0.0`). |
| `--front-end-root` `PATH` | — | Local filesystem path to the frontend directory. Overrides `--front-end-version`. |
| `--comfy-api-base` | `https://api.comfy.org` | Base URL for the ComfyUI API. |
| `--database-url` | `sqlite:///<ComfyUI>/user/comfyui.db` | Database URL. Use `sqlite:///:memory:` for in-memory. |
| `--enable-assets` | disabled | Enable the assets system (API routes, database sync, background scanning). |
| `--enable-asset-hashing` | disabled | Compute blake3 content hashes when scanning assets. Enables future asset portability features such as deduplication and cross-machine model resolution, at the cost of startup time and per-output hashing on large model directories. Off by default. |
| `--feature-flag` `KEY[=VALUE]` | — | Set a server feature flag. Bare `KEY` sets true. Can be repeated. Booleans and numbers are auto-converted. |
| `--list-feature-flags` | — | Print known CLI-settable feature flags as JSON and exit. |

```bash theme={null}
# List available feature flags
python main.py --list-feature-flags

# Set feature flags
python main.py --feature-flag show_signin_button=true
```

## Logging & Misc

| Flag | Default | Description |
| - | - | - |
| `--verbose` `[LEVEL] [FILE]` | `INFO` | Logging level. Choices: `DEBUG`, `DETAIL`, `INFO`, `WARNING`, `ERROR`, `CRITICAL`. `--verbose` alone sets `DEBUG`. Add a level followed by a file path to write that level to a file as well; the flag can be repeated to configure the console and file outputs together. |
| `--log-stdout` | disabled | Send normal process output to stdout instead of stderr. |
| `--dont-print-server` | disabled | Do not print server output to the console. |
| `--multi-user` | disabled | Enable per-user storage. |
| `--quick-test-for-ci` | disabled | Quick startup test for CI. Exits immediately after initialization. |

***

<Note>
  This reference is based on ComfyUI [`comfy/cli_args.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/comfy/cli_args.py). When upgrading ComfyUI, run `python main.py --help` or compare your local [`cli_args.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/comfy/cli_args.py) against this page to check for new or changed flags.
</Note>


# Comfy Cloud Quickstart
Source: https://docs.comfy.org/development/deploy/cloud

Run an API-format workflow on Comfy Cloud with a paid subscription, API key, and the Comfy SDK.

Comfy Cloud is a fully managed, always-available ComfyUI environment. Build workflows in the browser or run them through the SDK. There is no Build or deployment to create.

<Note>
  New to Comfy Cloud? Start with the [Comfy Cloud introduction](/get_started/cloud). This quickstart shows how to run workflows from an app.
</Note>

## Quickstart

Requires a paid subscription, an [API key](/development/api-development/getting-an-api-key), and an API-format workflow. The [Comfy SDKs](/development/api-development/sdks) target Cloud by default.

<Steps>
  <Step title="Create an API key">
    Create an API key at [platform.comfy.org](https://platform.comfy.org). See [Getting an API Key](/development/api-development/getting-an-api-key) for details.
  </Step>

  <Step title="Install the SDK">
    <CodeGroup>
      ```bash Python theme={null}
      pip install comfy-sdk
      ```

      ```bash TypeScript theme={null}
      npm i @comfyorg/sdk
      ```
    </CodeGroup>
  </Step>

  <Step title="Export a workflow in API format">
    In the Cloud editor, save your tested workflow as `workflow_api.json` with `File → Export Workflow (API)`. See [Workflow API Format](/development/api-development/workflow-api-format).
  </Step>

  <Step title="Run it">
    <CodeGroup>
      ```python Python theme={null}
      from comfy_sdk import Comfy

      client = Comfy(api_key="comfyui-...")  # Comfy Cloud is the default target

      wf = client.workflows.from_file("workflow_api.json")

      job = client.run(wf)
      for output in job.get_outputs("9"):
          output.to_file(output.name)
      ```

      ```typescript TypeScript theme={null}
      import { Comfy } from "@comfyorg/sdk";

      const client = new Comfy({ apiKey: "comfyui-..." }); // Comfy Cloud is the default target

      const wf = await client.workflows.fromFile("workflow_api.json");

      const job = await client.run(wf);
      await job.getOutputs("9")[0].toFile("out.png");
      ```
    </CodeGroup>

    `"9"` is the output node ID. See the [SDK guide](/development/api-development/sdks) for inputs, progress, and error handling.
  </Step>
</Steps>

The same SDK code can target [Comfy API deployments](/development/serverless/quickstart) and [self-hosted ComfyUI](/development/deploy/self-hosting). See [Running Workflows](/development/run-workflows/overview).

## Next steps

<Card title="Usage and Limits" icon="gauge" href="/development/deploy/cloud-usage">
  Check how Cloud credits and concurrent jobs work.
</Card>


# Usage and Limits
Source: https://docs.comfy.org/development/deploy/cloud-usage

Understand Comfy Cloud credits, concurrent jobs, and the limits that apply when running workflows through the SDK.

Workflows submitted through the Comfy Cloud API use the same credits and concurrency limits as other Cloud workflows.

## Credits and usage

API requests draw from the same monthly credit allocation as the Comfy Cloud web UI. There is no separate API credit pool. Each tier's included credits, top-up options, and per-workflow runtime caps apply to API jobs in the same way as UI jobs.

See the [pricing page](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=cloud-api) for monthly credit amounts and top-up options. You can purchase top-ups from your account dashboard.

## Concurrent jobs

You can submit multiple workflows without waiting for previous jobs to complete. Jobs run in parallel up to your subscription tier's limit. Check [platform.comfy.org](https://platform.comfy.org) for your current concurrency limit. Additional jobs queue and run as slots become available.

If the queue is full, the SDKs retry within a bounded budget before raising `QueueFull`.

<Info>
  Parallel execution is available through the API. See the [pricing plans](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=cloud-api) for subscription details.
</Info>

## Existing v1 integrations

The deprecated [v1 Cloud API](/development/cloud/overview) also runs against Comfy Cloud. Use it for existing integrations or Cloud capabilities not yet available in [Comfy API v2](/api-reference/v2/overview). Runnable examples are in the deprecated [Cloud API Reference](/development/cloud/api-reference).

## Next steps

<Card title="Comfy Cloud Quickstart" icon="play" href="/development/deploy/cloud">
  Set up the SDK and run your first Cloud workflow.
</Card>


# Deploying ComfyUI
Source: https://docs.comfy.org/development/deploy/overview

Compare Comfy Cloud, managed Comfy API deployments, and self-hosting to choose how to run ComfyUI.

Choose Comfy Cloud for an always-available managed ComfyUI, Comfy API for a versioned environment deployed as an endpoint, or self-hosting for infrastructure you manage.

<CardGroup>
  <Card title="Comfy Cloud" icon="cloud" href="/development/deploy/cloud">
    Run workflows without creating a Build or deployment.
  </Card>

  <Card title="Comfy API" icon="cloud-arrow-up" href="/development/serverless/quickstart">
    Package models and custom nodes into a managed, autoscaling endpoint.
  </Card>

  <Card title="Self-Host" icon="server" href="/development/deploy/self-hosting">
    Run ComfyUI on your own hardware, rented GPUs, or containers.
  </Card>
</CardGroup>

All three options run [API-format workflows](/development/api-development/workflow-api-format). Choose based on whether you want Comfy to manage the environment or want to manage it yourself.

## Next step: run workflows against it

Once a deployment is live, see [Running Workflows](/development/run-workflows/overview) to call it from your application. The [Comfy SDKs](/development/api-development/sdks) work against every deployment target; self-hosted instances additionally need the [API Proxy](/development/comfyui-server/api-proxy) during the v2 beta.


# Self-Hosting Options
Source: https://docs.comfy.org/development/deploy/self-hosting

Run your own ComfyUI deployment: bare metal, GPU cloud providers like Runpod and Vast.ai, or community Docker images

Self-hosting means running ComfyUI yourself and calling it as an API. You manage the hardware, the models, and the custom nodes, and in return you get full control: any GPU, any model, any node pack, and your data never leaves your infrastructure.

ComfyUI runs as an HTTP server by default, so any working install is already an API endpoint. The options below differ only in where that install lives.

## Your own hardware

The simplest deployment is the machine in front of you. Install ComfyUI and it serves `http://127.0.0.1:8188` out of the box:

* [Manual install](/installation/manual_install) for Linux, macOS, and Windows, and the standard choice for servers
* [Comfy Desktop](/installation/desktop/overview) or the [portable Windows build](/installation/comfyui_portable_windows) for local development

To run it headless (no browser) or listen on a non-default address, see the [server startup flags](/development/comfyui-server/startup-flags). For example:

```bash theme={null}
python main.py --listen 0.0.0.0 --port 8188
```

<Warning>
  The ComfyUI server has no authentication by default. Only bind to a non-loopback address on a network you trust, or put a reverse proxy with authentication in front of it.
</Warning>

## GPU cloud providers

If you do not own a GPU, you can rent one and run ComfyUI on it. Providers commonly used by the community include:

* **[Runpod](https://www.runpod.io)**: GPU pods with community ComfyUI templates that come pre-configured.
* **[Vast.ai](https://vast.ai)**: a GPU marketplace; community ComfyUI templates are available here too.

On these providers you typically start from a community template or image, then add your models and custom nodes. The result is a normal self-hosted ComfyUI with a public URL or an SSH tunnel in front of it.

<Note>
  These templates are community-maintained, not published or supported by the ComfyUI team. Review what a template installs before putting credentials or private models on it.
</Note>

If you want a managed version of this workflow, follow the [Comfy API Quickstart](/development/serverless/quickstart) to build and deploy it on the Developer Platform.

## Community Docker images

<Note>
  **Docker:** ComfyUI does not provide an official Docker image. If you want to run ComfyUI in a container, search [Docker Hub](https://hub.docker.com) for community-maintained images. Note that **none of these are official ComfyUI images**, and they are not supported by the ComfyUI team. Use them at your own risk.
</Note>

A containerized ComfyUI behaves like any other self-hosted install: expose the server port and call it as usual.

## Next step: run workflows against it

A self-hosted deployment can be called in two ways:

<CardGroup>
  <Card title="Comfy SDKs + API Proxy" icon="code" href="/development/comfyui-server/api-proxy">
    Use the official SDKs against your instance. During the v2 beta this requires the API Proxy, a small service that runs alongside ComfyUI.
  </Card>

  <Card title="ComfyUI Server API" icon="server" href="/development/comfyui-server/comms_overview">
    Call the raw REST and WebSocket API directly, with no extra service. Full local surface, but no compatibility guarantee across releases.
  </Card>
</CardGroup>


# Comfy API and Router examples
Source: https://docs.comfy.org/development/examples

Starting points for calling hosted models with Comfy Router, deploying ComfyUI workflows, and browsing community apps.

Pick the path that matches what you want to run.

## Comfy Router

Use Comfy Router to call hosted partner models with one Comfy API key.

<CardGroup>
  <Card title="Generate an image" icon="image" href="/development/comfy-router/quickstart">
    Make your first image with Flux in Python, TypeScript, or cURL.
  </Card>

  <Card title="Browse available models" icon="magnifying-glass" href="https://comfy.org/models">
    Find a model, inspect its inputs, and copy its model ID.
  </Card>

  <Card title="Use a model's schema" icon="list-tree" href="/development/comfy-router/models/black-forest-labs/flux-2-pro/code">
    See the request and response shape for a Router model.
  </Card>

  <Card title="Call Router over HTTP" icon="terminal" href="/development/comfy-router/reference">
    Look up the shared Router endpoints and headers.
  </Card>
</CardGroup>

## Comfy API

Package your own ComfyUI workflow, deploy it to managed GPU infrastructure, and run it through the Comfy API.

<CardGroup>
  <Card title="Deploy a workflow" icon="cloud-arrow-up" href="/development/serverless/quickstart">
    Create a Build, release it, and start a managed deployment.
  </Card>

  <Card title="Choose compute" icon="microchip" href="/development/serverless/overview#regions-and-gpu-availability">
    Find the available regions and GPU classes before you deploy.
  </Card>

  <Card title="Run a deployed workflow" icon="play" href="/development/serverless/quickstart#quick-start">
    Submit an API-format workflow and download its outputs.
  </Card>

  <Card title="Use the SDK" icon="code" href="/development/api-development/sdks#serverless-deployment">
    Point the Python or TypeScript SDK at your deployment.
  </Card>
</CardGroup>

## Example Applications

<CardGroup>
  <Card title="Browse Example Applications" icon="grid-2" href="https://comfy.org/models?type=apps">
    Explore community apps built with ComfyUI.
  </Card>
</CardGroup>


# ComfyUI for Developers: SDKs, Server API, and Cloud
Source: https://docs.comfy.org/development/overview

Build on ComfyUI with official Python and TypeScript SDKs, run it as a server, call Cloud APIs, or connect AI agents via MCP.

ComfyUI is a modular GenAI inference engine that can be run as a server, accessed via API, extended with custom nodes, and managed from the command line. Most API work follows two steps: get ComfyUI running somewhere, then run workflows against it from your application.

## Use cases

<CardGroup>
  <Card title="Run Models" icon="rocket" href="/development/comfy-router/quickstart">
    Generate with hosted models through Comfy Router.
  </Card>

  <Card title="Browse models" icon="search" href="http://comfy.org/models">
    Browse the models available on Comfy.org.
  </Card>

  <Card title="Deploy ComfyUI workflows" icon="server" href="/development/deploy/overview">
    Run your own workflows on managed infrastructure or self-hosted ComfyUI.
  </Card>
</CardGroup>


# Running Workflows
Source: https://docs.comfy.org/development/run-workflows/overview

How to run ComfyUI workflows against a live deployment, and which client works with which deployment

Once ComfyUI is [deployed somewhere](/development/deploy/overview), your application runs workflows against it: submit a workflow, wait for execution, download the outputs. This page maps out which client to use for which deployment.

## Start here: the Comfy SDKs

For a new integration, use the official **Comfy SDKs** (Python and TypeScript) and the [Comfy API v2](/api-reference/v2/overview) they call. The same code runs against every deployment target; only the base URL changes.

<Card title="Comfy SDKs" icon="code" href="/development/api-development/sdks">
  Install the SDK, submit a workflow, and download the outputs. Currently in beta.
</Card>

## What works against what

| Deployment | Comfy SDKs / API v2 | Notes |
| - | - | - |
| **Comfy API deployment** | Yes | Point `COMFY_BASE_URL` at `https://<deployment>.run.comfy.app` with your API key |
| **Comfy Cloud** | Yes | The default base URL. Requires an API key and a paid subscription |
| **Self-hosted** | Yes, via the [API Proxy](/development/comfyui-server/api-proxy) | During the v2 beta, a small service alongside ComfyUI serves the v2 API |

Self-hosted instances can also skip the SDK entirely and use the raw [ComfyUI Server API](/development/comfyui-server/comms_overview) (REST + WebSocket). It exposes the full local surface, including the queue and node info, but has no compatibility guarantee across releases.

## Which API should I use?

| | Comfy API v2 + SDKs | v1 Cloud API | ComfyUI Server API |
| - | - | - | - |
| **Where it runs** | Comfy API deployments, Comfy Cloud, or self-hosted via the API Proxy | Comfy Cloud only | Self-hosted only |
| **Compatibility** | Versioned, additive changes only within v2 | Deprecated, may change without notice | No guarantee across releases |
| **Authentication** | `Authorization: Bearer` on Comfy Cloud and Comfy API deployments. Self-hosted: none by default, optional static bearer token | `X-API-Key` header (Comfy Cloud account) | None (local) or API key for Partner Nodes |
| **Official clients** | Python and TypeScript SDKs | None, call over HTTP | None, call over HTTP |
| **Protocol** | REST + SSE | REST + WebSocket | REST + WebSocket |
| **Scope** | Run a workflow and get results | Full Cloud surface, including models and account | Full local surface, including queue and node info |
| **Best for** | New integrations that should keep working | Existing integrations and Cloud features v2 does not cover yet | Full control, custom tooling against your own instance |

All of them accept the same workflow format ([API format](/development/api-development/workflow-api-format)), so you can develop and test workflows locally and move them to another deployment without changes.

## Getting started

<CardGroup>
  <Card title="Comfy SDKs" icon="code" href="/development/api-development/sdks">
    Run workflows from Python or TypeScript, against any deployment target.
  </Card>

  <Card title="API Proxy for Self-Hosted" icon="plug" href="/development/comfyui-server/api-proxy">
    Serve the v2 API in front of your own ComfyUI so the SDKs can reach it.
  </Card>

  <Card title="Workflow API Format" icon="file-code" href="/development/api-development/workflow-api-format">
    Export workflows in the JSON format the APIs accept.
  </Card>

  <Card title="ComfyUI Server API" icon="server" href="/development/comfyui-server/comms_overview">
    The raw REST and WebSocket API of a self-hosted instance.
  </Card>
</CardGroup>

## Prerequisites

* An [API key](/development/api-development/getting-an-api-key) for anything that touches Comfy Cloud, a Comfy API deployment, or Partner Nodes. A purely local ComfyUI does not need one.
* A workflow exported in [API format](/development/api-development/workflow-api-format).


# Other Ways to Create a Comfy API Build
Source: https://docs.comfy.org/development/serverless/build-sources

Create a Comfy API Build from a Comfy Desktop snapshot or saved workflow JSON.

Already have a Desktop snapshot or workflow? Use the matching path below to start a Build, then review its contents before you release it.

## Comfy Desktop snapshot

Use a snapshot to carry a Desktop instance's ComfyUI version, custom nodes, and Python packages into a Build.

1. In Comfy Desktop, open the instance's **Manage** panel and select **Snapshots**. Choose the snapshot for the environment you want to build and click its **Export** button. If the current state is not listed, create a manual snapshot first. See [Desktop snapshot steps](/installation/desktop/usage/snapshots#snapshots-tab-overview).
2. Open the [Comfy API Build Wizard](https://platform.comfy.org/?onboarding=comfyapi) and import the snapshot file.
3. Review the Build contents and add or correct any missing models or dependencies before creating a release.

<img alt="Comfy Desktop Snapshots tab with the selected snapshot's Export button highlighted" />

## Workflow JSON

Use a saved workflow file to configure a Build in the Build Wizard:

1. Open the [Comfy API Build Wizard](https://platform.comfy.org/?onboarding=comfyapi).
2. Drag the workflow JSON into the import step.
3. Review the Build contents and add or correct any missing models or dependencies before creating a release.

<img alt="Comfy API Build Wizard with an imported workflow JSON and build setup steps" />

The wizard inspects the workflow and suggests Build settings before you continue.

## Next steps

<CardGroup>
  <Card title="Comfy API Quickstart" icon="play" href="/development/serverless/quickstart">
    Create a release, deploy it, and run a workflow with an agent or the CLI.
  </Card>

  <Card title="Comfy API Deployment Guide" icon="book" href="/development/serverless/overview">
    Manage Build files, updates, releases, scaling, billing, and troubleshooting.
  </Card>
</CardGroup>


# Comfy API Deployment Guide
Source: https://docs.comfy.org/development/serverless/overview

Manage Comfy API Builds, releases, deployments, scaling, billing, and troubleshooting.

Comfy API runs workflows on managed, autoscaling GPU endpoints. A **Build** describes the ComfyUI environment, including its models, custom nodes, and settings. The CLI creates releases from a Build and deploys them as endpoints.

<Card title="Comfy API Quickstart" icon="play" href="/development/serverless/quickstart">
  Start with an agent or choose another way to provide your environment or workflow.
</Card>

For Desktop snapshots and workflow JSON imports, see [Build Sources](/development/serverless/build-sources).

## The Build file

`comfy-build.yaml` stores the Build definition and last known remote state. The CLI uses that state to detect when the remote Build has changed. Keep the file with the project. It describes the environment but does not contain model files.

Check how the local Build compares with the install and remote version before pushing changes:

```bash theme={null}
comfy build status
```

## Update and release

After changing the local install, refresh the Build definition:

```bash theme={null}
comfy build update --yes
```

To create another release from an existing Build, check the supported targets and select one:

```bash theme={null}
comfy build refs build-targets
comfy build release create --target linux/nvidia --watch
```

Follow one release's build log with:

```bash theme={null}
comfy build release logs rel_123456 --target linux/nvidia --follow
```

## Regions and GPU availability

Region capacity changes, so check the platform catalog when choosing a deployment target. Filter the results with `--region <region>`:

```bash theme={null}
comfy deploy refs compute --region <region>
```

The catalog is the source of truth for which GPU classes are available in each region at deployment time.

## Workspace limits

See [Limits](https://platform.comfy.org/profile/limits) for your workspace's usage and plan limits. Keep `--max` within the worker limit per deployment.

## Monitor and call a deployment

The `--min` and `--max` options set the worker bounds. Run `comfy deploy status --watch` to follow deployment health, release freshness, and serving activity.

You can also call the endpoint with the [Comfy SDKs](/development/api-development/sdks). Set `COMFY_BASE_URL` to the deployment URL and provide an API key. See [Choosing a base URL](/development/api-development/sdks#choosing-a-base-url).

## Operate a deployment

```bash theme={null}
# Change the worker bounds
comfy deploy scale --deployment dep_123456 --min 2 --max 5

# Pause or resume while retaining the deployment record
comfy deploy stop --deployment dep_123456
comfy deploy start --deployment dep_123456
```

## Inspect and clean up

```bash theme={null}
# Build state
comfy build ls
comfy build show --id bld_123456
comfy build release ls
comfy build release show rel_123456

# Deployment state
comfy deploy ls --workspace --status ready
comfy deploy logs --deployment dep_123456
comfy deploy events --deployment dep_123456
```

<Warning>
  Deleting a deployment and deleting a Build are separate irreversible operations. Confirm the target before using `comfy deploy delete --yes` or `comfy build delete --id bld_123456 --yes`.
</Warning>

## FAQ

<AccordionGroup>
  <Accordion title="Can one Build come from multiple workflows?">
    Yes. In the Builder, upload one or more workflows to preselect their models and custom nodes. Include the dependencies needed by all the workflows you plan to run, then submit each API-format workflow to the deployed endpoint.

    Each deployment uses one GPU type. To run workflows on different GPU types, create separate deployments of the same Build.
  </Accordion>

  <Accordion title="Am I charged for storing Builds that are not deployed?">
    No. Builds and their releases are stored on your account at no charge. You are not billed for the storage footprint of a Build until you deploy it.

    Storage billing starts with a deployment:

    * When you deploy a release, its models are staged onto network storage shared by the deployment's workers. The storage is read-only after deployment and billed per GB-month for as long as any deployment of the Build exists in that region, including while a deployment is paused with `comfy deploy stop`.
    * Each worker also gets a fixed 50 GB container disk. It is ephemeral and is only billed while the worker is running, as part of the worker's compute cost.
    * Deleting a deployment releases its compute. Staged network storage is cleaned up shortly after the last deployment using it in that region is deleted, and billing for it ends.

    For current storage rates, see the [Comfy pricing page](https://www.comfy.org/pricing). The compute catalog (`comfy deploy refs compute`) and the deploy dialog also show the rates that apply to a deployment.
  </Accordion>

  <Accordion title="How are active workers billed, and at what hourly rates?">
    `--min` sets the number of **active workers**: workers that stay running at all times so requests never wait for a cold start. An active worker is billed per second for the entire time it is running, whether or not it is processing jobs.

    Workers above `--min`, up to `--max`, are **flex workers**. A flex worker is billed per second from the moment it starts (including startup and model loading), through job processing, plus a short idle window (currently 30 seconds) before it scales back down. When flex workers are scaled down, they cost nothing. With `--min 0` the whole deployment scales to zero and bills no compute while idle, at the cost of a cold start on the first request.

    Billing meters actual per-second worker usage, multiplied by the number of workers running. If your workspace runs out of credits, deployments are stopped automatically.

    For current per-worker GPU rates, see the [Comfy pricing page](https://www.comfy.org/pricing). Rates are quoted per worker-hour and billed per second. GPU availability per region comes from the compute catalog: run `comfy deploy refs compute` for the current list.
  </Accordion>

  <Accordion title="How does a deployment handle multiple requests?">
    A deployment automatically distributes requests across its workers and scales within the configured `--min` and `--max` bounds. Requests that cannot run immediately are queued and processed as worker capacity becomes available.
  </Accordion>

  <Accordion title="What should I do if provisioning takes a long time?">
    Follow the deployment state, then inspect its logs and events for the cause:

    ```bash theme={null}
    comfy deploy status --deployment <deployment-id> --watch
    comfy deploy logs --deployment <deployment-id>
    comfy deploy events --deployment <deployment-id>
    ```

    If the selected GPU or region has no capacity, retry later or run `comfy deploy refs compute` and choose an available region and GPU pair. Include the Build, release, and deployment IDs when asking for help.
  </Accordion>

  <Accordion title="What happens when I delete a deployment?">
    Deleting a deployment removes its endpoint and releases its compute. It does not delete the Build or its releases. After you delete the last deployment using that Build in a region, its staged network storage is cleaned up and storage billing ends shortly afterward.

    Deleting the Build is a separate operation: `comfy build delete --id <build-id> --yes`.
  </Accordion>
</AccordionGroup>

## Next steps

<CardGroup>
  <Card title="Comfy SDKs" icon="code" href="/development/api-development/sdks">
    Use from a Python or TypeScript app to submit workflows and handle inputs, progress, and outputs.
  </Card>

  <Card title="Comfy API v2" icon="cloud" href="/api-reference/v2/overview">
    Use from any language when calling the HTTP API directly or checking its request and response formats.
  </Card>

  <Card title="Workflow API Format" icon="file-code" href="/development/api-development/workflow-api-format">
    Use when preparing a workflow JSON for an API request or troubleshooting its inputs and outputs.
  </Card>

  <Card title="Comfy CLI Reference" icon="terminal" href="/comfy-cli/reference">
    Use to automate Build, release, deployment, and workflow commands from a terminal.
  </Card>
</CardGroup>


# Comfy API Quickstart
Source: https://docs.comfy.org/development/serverless/quickstart

Use an AI coding agent and comfy-cli to build, release, and deploy a local ComfyUI environment as a managed endpoint.

## Start with an agent (recommended)

Start your coding agent in the folder for the local ComfyUI install you want to deploy. Paste this prompt:

```text theme={null}
Install or update comfy-cli, then read its Build and Deploy skills:

pip install -U comfy-cli
comfy skills show comfy-build
comfy skills show comfy-deploy

Use comfy-build to inspect this local ComfyUI install and package its models, custom nodes, and pinned dependencies into a Comfy API Build. Show me what will be included and create a Linux/NVIDIA release. Then use comfy-deploy to show the available GPU and region options, worker bounds, and current rates. Wait for my approval before creating a deployment. After approval, deploy it and explain how to run a workflow.
```

## Quick start

Use these commands when the local install and an [API-format workflow](/development/api-development/workflow-api-format) saved as `workflow_api.json` are ready.

<Steps>
  <Step title="Initialize">
    ```bash theme={null}
    comfy build init --name "my-comfy-build" --models-dir ./models --custom-nodes-dir ./custom_nodes
    ```
  </Step>

  <Step title="Push and create a release">
    Push the Build and its assets, check the available targets, then wait for the Linux/NVIDIA release to finish:

    ```bash theme={null}
    comfy build push
    comfy build refs build-targets
    comfy build release create --target linux/nvidia --watch
    ```
  </Step>

  <Step title="Start a deployment">
    Check the catalog for available GPU and region pairs, then replace the GPU, region, and worker-bound placeholders with your settings:

    ```bash theme={null}
    comfy deploy refs compute
    comfy deploy up --gpu <gpu> --region <region> --min <min-workers> --max <max-workers> --watch
    ```
  </Step>

  <Step title="Run the workflow">
    Use the deployment ID printed by `comfy deploy up` with `--deployment`:

    ```bash theme={null}
    comfy deploy run \
      --workflow workflow_api.json \
      --deployment <deployment-id> \
      --output-dir ./results
    ```
  </Step>
</Steps>

## Other ways to start

Use these paths if your environment or workflow already exists in Comfy Desktop or a workflow file.

<CardGroup>
  <Card title="Comfy Desktop snapshot" icon="camera" href="/development/serverless/build-sources#comfy-desktop-snapshot">
    Export a snapshot from Desktop, then import it into the Build Wizard.
  </Card>

  <Card title="Import workflow JSON" icon="file-import" href="/development/serverless/build-sources#workflow-json">
    Start a Build by importing a saved workflow into the Build Wizard.
  </Card>
</CardGroup>

## Next steps

<CardGroup>
  <Card title="Comfy Workflows" icon="magnifying-glass" href="https://comfy.org/models?type=workflows">
    Browse ComfyUI workflows shared by the community.
  </Card>

  <Card title="Apps" icon="grid-2" href="https://comfy.org/models?type=apps">
    Explore community apps built with ComfyUI.
  </Card>
</CardGroup>


# Add tags to asset
Source: https://docs.comfy.org/api-reference/cloud/asset/add-tags-to-asset

/openapi-cloud.yaml post /api/assets/{id}/tags
Adds one or more tags to an existing asset



# Check if asset exists by hash
Source: https://docs.comfy.org/api-reference/cloud/asset/check-if-asset-exists-by-hash

/openapi-cloud.yaml head /api/assets/hash/{hash}
Checks if content with the given hash exists in cloud storage.
Returns 200 if the content exists, 404 if it doesn't.
Useful for checking availability before using `/api/assets/from-hash`.




# Delete asset
Source: https://docs.comfy.org/api-reference/cloud/asset/delete-asset

/openapi-cloud.yaml delete /api/assets/{id}
Deletes an asset and its content from storage.
Both the database record and storage content are deleted.




# Get tag histogram for filtered assets
Source: https://docs.comfy.org/api-reference/cloud/asset/get-tag-histogram-for-filtered-assets

/openapi-cloud.yaml get /api/assets/tags/refine
Returns a histogram of tags appearing on assets matching the given filters.
Useful for refining asset searches by showing available tags and their counts.
Only returns tags with non-zero counts (tags that exist on matching assets).




# List all tags
Source: https://docs.comfy.org/api-reference/cloud/asset/list-all-tags

/openapi-cloud.yaml get /api/tags
Retrieves a list of all tags used across assets.
Includes usage counts and filtering options.




# Remove tags from asset
Source: https://docs.comfy.org/api-reference/cloud/asset/remove-tags-from-asset

/openapi-cloud.yaml delete /api/assets/{id}/tags
Removes one or more tags from an existing asset



# Get workspace usage over time
Source: https://docs.comfy.org/api-reference/cloud/billing/get-workspace-usage-over-time

/openapi-cloud.yaml get /api/billing/usage/timeseries
Returns billed usage for the workspace the API key belongs to, split into
time buckets and grouped by model, endpoint, or product. Use it to
reconcile spend, attribute cost across models, or feed an internal cost
report.

**Units.** `cost_micros` and `spend_micros` are millionths of a US dollar,
so divide by 1,000,000 to get dollars. The fields under `summary.balance`
are the exception: despite their `_micros` suffix they are **cents**, so
divide those by 100.

**Freshness.** Figures are drawn from your invoices rather than from live
request traffic, so very recent usage may not appear yet. Treat this as a
reporting surface, not a real-time meter.

**Empty results.** A workspace that has not been billed yet returns empty
`groups`, `buckets`, and `breakdown` arrays with a 200, not an error.




# Get system statistics
Source: https://docs.comfy.org/api-reference/cloud/system/get-system-statistics

/openapi-cloud.yaml get /api/system_stats
Returns system statistics including ComfyUI version, device info, and system resources



# Delete a user data file
Source: https://docs.comfy.org/api-reference/cloud/user/delete-a-user-data-file

/openapi-cloud.yaml delete /api/userdata/{file}
Delete a user data file from the database. The file parameter should be
the relative path within the user's data directory.




# Get current user information
Source: https://docs.comfy.org/api-reference/cloud/user/get-current-user-information

/openapi-cloud.yaml get /api/user
Returns information about the currently authenticated user



# Get user data file
Source: https://docs.comfy.org/api-reference/cloud/user/get-user-data-file

/openapi-cloud.yaml get /api/userdata/{file}
Returns the requested user data file if it exists.



# List user data files
Source: https://docs.comfy.org/api-reference/cloud/user/list-user-data-files

/openapi-cloud.yaml get /api/userdata
Returns a list of user data files in the specified directory, optionally recursively and with full metadata.



# Upload or update a user data file
Source: https://docs.comfy.org/api-reference/cloud/user/upload-or-update-a-user-data-file

/openapi-cloud.yaml post /api/userdata/{file}
Upload a file to a user's data directory. Optional query parameters allow
control over overwrite behavior and response detail.




# Ask for one submitted request to be cancelled.
Source: https://docs.comfy.org/api-reference/router/comfy-router/ask-for-one-submitted-request-to-be-cancelled

/router-openapi.yaml put /v2/models/{provider}/{model}/requests/{request_id}/cancel
Asks Comfy to stop a request that has not finished. It is a request, not a guarantee, and the `202` says exactly that: `CANCELLATION_REQUESTED` means the ask was accepted, not that the run has stopped. A run already on the wire at a partner may complete anyway - and a partner generation that completes is charged, whether or not anyone collected it - so a caller who needs to know what actually happened reads the status endpoint afterwards, where a cancellation that took effect is `COMPLETED` carrying an `error_type` like every other terminal outcome.



# Collect the result of one submitted request.
Source: https://docs.comfy.org/api-reference/router/comfy-router/collect-the-result-of-one-submitted-request

/router-openapi.yaml get /v2/models/{provider}/{model}/requests/{request_id}
The collect endpoint. On a request that has finished successfully it returns the partner model's own native output, byte for byte what the synchronous route's `200` carries for the same model and the same input - so the two delivery modes produce one result shape and a caller can move between them without a second parser.



# List the models Comfy Router can run.
Source: https://docs.comfy.org/api-reference/router/comfy-router/list-the-models-comfy-router-can-run

/router-openapi.yaml get /v2/models
Comfy Router's model catalog - one page of the canonical model IDs that `POST /v2/models/{provider}/{model}` accepts. An SDK calls this on cold start to discover what is runnable, and the `model_not_found` suggestions come from the same catalog, so an ID listed here that then 404s on invocation would be worse than either failure alone. That agreement is structural rather than a promise: an entry's `provider` and `model` are the two path segments of the invocation route and reference the same schema components that route's path parameters do, and `id` is those two segments joined by `/`.



# Read one partner model's catalog entry by canonical model ID.
Source: https://docs.comfy.org/api-reference/router/comfy-router/read-one-partner-models-catalog-entry-by-canonical-model-id

/router-openapi.yaml get /v2/models/{provider}/{model}
Per-model detail for a single Comfy Router model, so a caller can check one model without walking the whole paginated catalog. The SDKs use it to look a model up immediately before invoking it.



# Read one partner model's input and output schemas as an OpenAPI document.
Source: https://docs.comfy.org/api-reference/router/comfy-router/read-one-partner-models-input-and-output-schemas-as-an-openapi-document

/router-openapi.yaml get /v2/models/{provider}/{model}/openapi.json
The per-model input and output schemas for a single Comfy Router model, served as a standalone OpenAPI document, so a caller - an SDK, a codegen tool, or an agent - can discover a model's arguments, and the shape of what it returns, without reading Comfy's prose docs. It is the discovery mechanism the SDK quickstart depends on.



# Read the queue state of one submitted request.
Source: https://docs.comfy.org/api-reference/router/comfy-router/read-the-queue-state-of-one-submitted-request

/router-openapi.yaml get /v2/models/{provider}/{model}/requests/{request_id}/status
The poll endpoint. It answers with the request's current state and never with the result, so a client can watch a long generation without transferring its output on every poll - the result is collected once, from the read below, when this says `COMPLETED`.



# Run a partner model synchronously by canonical model ID.
Source: https://docs.comfy.org/api-reference/router/comfy-router/run-a-partner-model-synchronously-by-canonical-model-id

/router-openapi.yaml post /v2/models/{provider}/{model}
Comfy Router's canonical, model-ID-addressed entry point. The request body is the partner model's own native JSON input and the success response is that model's own native JSON output: Router forwards both unchanged instead of imposing a Comfy-shaped envelope, so a caller can move between the partner's API and Router by changing the host. This is the synchronous path: the response carries the finished result.



# Submit a partner model run to the queue and return immediately.
Source: https://docs.comfy.org/api-reference/router/comfy-router/submit-a-partner-model-run-to-the-queue-and-return-immediately

/router-openapi.yaml post /v2/models/{provider}/{model}/requests
Comfy Router's queued delivery mode. The request body is the same partner-native JSON input `POST /v2/models/{provider}/{model}` accepts for this model - one body shape, one per-model schema, two delivery modes - but this route does not hold the connection for the result. It admits the run, answers `201` with a handle, and the caller collects the result later through the three reads below.



# Comfy Router API overview
Source: https://docs.comfy.org/development/comfy-router/api

How the Comfy Router API works: one route per model ID, with guides for discovery, schemas, queued requests, errors, and billing.

Choose a model, inspect its schema, and call `POST /v2/models/{provider}/{model}`. The route and authentication stay the same across models. Each model accepts its own native request body and returns its own native result.

## Guides

<CardGroup>
  <Card title="Discover models" icon="magnifying-glass" href="/development/comfy-router/discover-models">
    List the catalog, page through it, and read one model's entry.
  </Card>

  <Card title="Schemas and results" icon="brackets-curly" href="/development/comfy-router/schemas">
    Fetch a model's input and output schema and read its result.
  </Card>

  <Card title="Queued requests" icon="list-check" href="/development/comfy-router/queue">
    Submit a run now, then poll, collect, or cancel it later.
  </Card>

  <Card title="Errors and retries" icon="rotate" href="/development/comfy-router/errors">
    Read error responses and retry without a second charge.
  </Card>

  <Card title="Billing" icon="receipt" href="/development/comfy-router/billing">
    What is charged, policy-refusal billing, and reconciling usage.
  </Card>
</CardGroup>

## Per-model examples

* [Google Gemini](/development/comfy-router/models/google/gemini/code)
* [Nano Banana 2](/development/comfy-router/models/google/nano-banana-2/code)
* [Nano Banana 2 Lite](/development/comfy-router/models/google/nano-banana-2-lite/code)
* [Nano Banana Pro](/development/comfy-router/models/google/nano-banana-pro/code)
* [FLUX 1.1 Pro Ultra](/development/comfy-router/models/black-forest-labs/flux-1-1-pro-ultra-image/code)
* [FLUX Kontext](/development/comfy-router/models/black-forest-labs/flux-1-kontext/code)
* [FLUX Video Upscale](/development/comfy-router/models/black-forest-labs/flux-video-upscale/code)
* [FLUX 3 Video](/development/comfy-router/models/black-forest-labs/flux-3-video/code)
* [Ideogram 4](/development/comfy-router/models/ideogram/ideogram-v4/code)

## Next

* [Quickstart](/development/comfy-router/quickstart): installation, invocation, and saving the image.
* [Models](/development/comfy-router/models): browse the catalog and inspect model-specific request examples.
* [Headers](/development/comfy-router/headers): authentication, idempotency, request IDs, and retry pacing.
* [API reference](/development/comfy-router/reference): endpoint parameters, schemas, and response codes.


# Comfy Router billing
Source: https://docs.comfy.org/development/comfy-router/billing

How Comfy Router charges for model calls, what the catalog's policy-refusal billing field means, and how to reconcile usage.

You are billed when the provider bills Comfy. The same rule applies to synchronous and [queued](/development/comfy-router/queue#idempotency-and-billing) calls, and a same-key [retry](/development/comfy-router/errors#retry-outcomes) that replays a result is not a second charge.

## Model billing facts

`GET /v2/models` and the model detail response include `billing.charges_on_policy_rejection`. This describes a policy refusal, not every failure or a price estimate.

| Value | Meaning |
| - | - |
| `yes` | A policy refusal is charged. |
| `no` | A policy refusal is not charged. |
| `unknown` | Nobody has established the behavior yet. Treat it as maybe charged. |

Compare these strings explicitly: `"no"` is truthy in Python and JavaScript. Treat any unrecognized value as `unknown`. A request refused for lack of credits reports `insufficient_credits`.

## Reconcile charges

Provider payloads may include their own cost or usage numbers; those are not the Comfy charge. `X-Comfy-Credits-Used` is available only for some models and successful responses. When Router replays a result for the same `Idempotency-Key`, it repeats the original header with `Idempotent-Replayed: true`. The call is still charged once, so do not count a replayed header again. An absent header does not mean the call was free. Use [workspace usage and invoices](https://platform.comfy.org) for reconciliation, and preserve the request ID when investigating a charge.

## Next

* [Limitations](/development/comfy-router/limitations#comfy-charges-and-usage): what Router does and does not report about charges.
* [Errors and retries](/development/comfy-router/errors): retry without creating a second billable call.


# Discover Comfy Router models
Source: https://docs.comfy.org/development/comfy-router/discover-models

List the Comfy Router catalog with GET /v2/models, page through it with cursors, and fetch one model's entry by its ID.

Every Router model is addressed by an ID of the form `{provider}/{model}`. Use the catalog to find that ID, then call `POST /v2/models/{provider}/{model}`.

## Discover the catalog

List models with the same API key used for generation:

```bash theme={null}
curl -H "X-API-Key: $COMFY_API_KEY" \
  "https://api.comfy.org/v2/models?limit=50"
```

An abbreviated catalog response:

```json theme={null}
{
  "data": [
    {
      "id": "bfl/flux-2-pro",
      "provider": "bfl",
      "model": "flux-2-pro",
      "billing": { "charges_on_policy_rejection": "no" }
    }
  ],
  "has_more": true,
  "next_cursor": "example-cursor",
  "limit": 50
}
```

Use `id` in the invocation path. The `billing` object contains billing facts, not a price. Read [policy-refusal billing](/development/comfy-router/billing#model-billing-facts) before relying on it.

### Pagination

* When `has_more` is `true`, pass the returned `next_cursor` as `cursor`. Stop when `has_more` is `false`, even if an earlier page was shorter than requested.
* Treat cursors as opaque. URL-encode the value, for example with cURL `--get --data-urlencode "cursor=$NEXT_CURSOR"`; do not calculate offsets or modify the cursor.
* `limit` defaults to 20 and is capped at 100. Values above the cap are clamped; zero and negative values select the default. The response reports the limit actually used.
* An invalid cursor returns `400` / `invalid_input`. It does not silently restart the list.
* A cursor can remain valid across catalog updates, but traversal is not a snapshot: a model added before your current position may not appear in that walk.

`503` / `service_unavailable` is temporary. Retry with backoff; do not treat it as an empty catalog. SDK run methods call the selected model directly.

## Read one model

Fetch a catalog entry directly when you know the model ID:

```bash theme={null}
curl -H "X-API-Key: $COMFY_API_KEY" \
  https://api.comfy.org/v2/models/bfl/flux-2-pro
```

The model detail endpoint avoids walking the entire catalog. Use the [API reference](/development/comfy-router/reference) for the complete entry fields.

## Next

* [Schemas and results](/development/comfy-router/schemas): read a model's input and output schema before calling it.
* [All models](/development/comfy-router/models): browse the catalog with a working request for each model.


# Comfy Router errors and retries
Source: https://docs.comfy.org/development/comfy-router/errors

Read Comfy Router error responses and validation details, retry with the same Idempotency-Key, and recover after timeouts.

A failed Router call carries its HTTP status, an error bucket in `X-Comfy-Error-Type`, and a request ID in `X-Comfy-Request-Id`. Keep all three, and keep the `Idempotency-Key` you sent, before deciding whether to retry.

## Read errors defensively

A failed request can return a proxy's HTML error page, truncated JSON, or plain text. Do not let a JSON parsing error hide the HTTP status or request ID. These helpers use an `httpx.Response` in Python and a Fetch `Response` in TypeScript; the SDKs already expose error fields for normal SDK calls.

<CodeGroup>
  ```python theme={null}
  def read_router_error(response):
      body = None
      if response.headers.get("content-type", "").startswith("application/json"):
          try:
              body = response.json()
          except ValueError:
              body = None

      detail = body.get("detail") if isinstance(body, dict) else None
      return {
          "status": response.status_code,
          "request_id": response.headers.get("X-Comfy-Request-Id"),
          "error_type": response.headers.get("X-Comfy-Error-Type", "internal_error"),
          "message": detail if isinstance(detail, str) else f"HTTP {response.status_code}",
          "validation": detail if isinstance(detail, list) else [],
      }
  ```

  ```typescript theme={null}
  async function readRouterError(response: Response) {
    let body: unknown;
    try {
      body = JSON.parse(await response.text());
    } catch {
      body = undefined;
    }

    const detail =
      typeof body === "object" && body !== null ? (body as { detail?: unknown }).detail : undefined;

    return {
      status: response.status,
      requestId: response.headers.get("X-Comfy-Request-Id"),
      errorType: response.headers.get("X-Comfy-Error-Type") ?? "internal_error",
      message: typeof detail === "string" ? detail : `HTTP ${response.status}`,
      validation: Array.isArray(detail) ? detail : [],
    };
  }
  ```

  ```swift theme={null}
  // Add to your Package.swift:
  //   .package(url: "https://github.com/Comfy-Org/comfy-swift-sdk.git", from: "0.5.0")
  import ComfySwiftSDK

  // The SDK reads the response defensively for you: a Router failure is thrown as
  // ComfyError.router with the HTTP status, request ID, error bucket and any
  // per-field validation detail already extracted, even when the body was an HTML
  // error page or truncated JSON. Catch it from any client.models call.
  struct RouterErrorInfo {
      let status: Int
      let requestId: String?
      let errorType: String
      let message: String
      let validation: [RouterValidationErrorDetail]
  }

  // `client.models.run` is `async throws`, so an untyped `catch` binds `Error`.
  // Take `Error` here so the caught value can be passed straight in.
  func readRouterError(_ error: Error) -> RouterErrorInfo? {
      guard let comfyError = error as? ComfyError,
            case .router(let router) = comfyError else { return nil }
      return RouterErrorInfo(
          status: router.httpStatus,
          requestId: router.requestId,
          errorType: router.errorType.rawValue,
          message: router.detail,
          validation: router.validationErrors
      )
  }
  ```
</CodeGroup>

## Validation errors

A Router `422` means validation failed before the provider call and is not billed. Its body has a `detail[]` array, with one entry per rejected field. The error category is in `X-Comfy-Error-Type`, not in the body. For example:

```json theme={null}
{"detail": [{"loc": ["body", "prompt"], "msg": "Field required", "type": "missing"}]}
```

This is an example shape. Models with a permissive input schema may forward a missing field to the provider instead of returning a Router `422`.

| Field | Meaning |
| - | - |
| `loc` | Path to the rejected field, outermost segment first. |
| `msg` | Human-readable reason for the failure. |
| `type` | Provider-specific reason, such as `missing`, `greater_than` or `image_too_small`. |
| `ctx` | Optional bound or extra data for that provider error. |

`400` describes a request-level problem, such as a malformed cursor, rather than this per-field validation body. The [error reference](/development/comfy-router/reference#error-buckets) lists the supported categories. Treat an unknown category as `internal_error` for control flow, but keep the original value for diagnostics. Do not hard-reject a new error value or implement forecast error categories as though they already occur.

## Retry safely

Persist the key with the model ID and request body **before sending**. Reuse it for every attempt of that logical call. Router does not return the `Idempotency-Key` to you in its response. The Python SDK includes its key on raised exceptions; in TypeScript, keep your supplied key yourself.

Keys are shared within the workspace carried by the credential, or scoped to the user when it carries no workspace. Use a UUID unique across that scope and retry with the same credential. Reusing another workspace member's key can return their recorded result or a conflict; changing credentials can start a separate, billable call.

Router retains keyed response or collection state for 24 hours; a retry does not start a new retention window. Once that state expires, do not expect the old key to recover a result or prevent a new dispatch. A key also does not make an expired asset URL usable again.

## Retry outcomes

| Status | Bucket | What it means | What to do |
| - | - | - | - |
| `200` | `Idempotent-Replayed: true` header | Router replayed a result or returned a collected generation. | Use the result; the replay is not a second Comfy charge. |
| `409` | `concurrency_limit_exceeded` | The original call for that key is still running. | Wait `Retry-After`, then resend the same key. |
| `504` | `deadline_exceeded`, with `Retry-After` | Router retained a handle to accepted provider work. | Wait the stated interval and resend the same request and key to collect it. It may still be running. |
| `429` | `rate_limited` | The request allowance is exhausted. | Wait `Retry-After`, then retry with the same key. |
| `429` | `concurrency_limit_exceeded` | The concurrent-call or committed-spend limit refused the request. | Reduce concurrency and retry with the same key. Inspect the spend headers. |
| `409` | `invalid_input` | The request differs from the key's original request, or its record cannot be replayed. | Inspect the conflict. Restore the original request if it changed. Start a new key only when you intend a new, potentially billable call. |
| `504` without a collection hint, another `5xx`, or no response | Varies | The status alone does not identify whether work was accepted, retained, or released. | Preserve the same key and request. Use a bounded retry policy; recovery is not guaranteed. |

Conflicts compare the method, model path, query, and body. A key can become non-replayable after an oversized response, failed response write, or an asset that cannot be safely replayed. Waiting does not recover a consumed result. A new key starts a new call; it does not retrieve the old output.

A refusal before provider dispatch releases the key. A dispatched call can retain a provider handle or become non-replayable. Do not infer key state or billing from the status code alone.

Do not mint a brand-new key just because a call timed out or the connection dropped. If Router already accepted the generation, a new key can create a second logical run and therefore a second billable outcome. Reuse the same key until you know the original call is unrecoverable.

## Timeouts and collection

One Router call may hold the connection for 10 minutes by default. Set your client timeout above that bound so you keep the typed `504` and the request ID rather than an opaque local abort. If your application cannot hold a connection that long, [queued delivery](/development/comfy-router/queue) returns a `request_id` at once and lets you collect the result later.

`deadline_exceeded` is Router's waiting limit; `provider_timeout` is the provider's deadline. A provider generation that completes can be billed even if the caller received a timeout or disconnected. Client cancellation stops the wait and SDK retries, but does not necessarily cancel accepted provider work.

For submit-and-poll providers, a retained handle lets a same-key request continue collecting the original generation. Dispatched calls cut off without a recoverable handle can consume the key without a replayable result; a same-key retry then returns `409`. Provider-attributed transient failures without a captured success can still release the key for another attempt. The absence of a handle alone does not tell you which outcome applies.

The SDKs retry some failures within a bounded budget. Once they return an error, keep the request and key rather than generating a new one. For raw HTTP, this example retries only the two explicit collection hints:

```python theme={null}
import os
import time

import httpx


def collect(model, arguments, key, attempts=3):
    with httpx.Client(timeout=httpx.Timeout(660.0, connect=10.0)) as client:
        for attempt in range(attempts):
            response = client.post(
                f"https://api.comfy.org/v2/models/{model}",
                headers={"X-API-Key": os.environ["COMFY_API_KEY"],
                         "Idempotency-Key": key},
                json=arguments,
            )
            if response.is_success:
                return response.json()

            category = response.headers.get("X-Comfy-Error-Type")
            collecting = (response.status_code, category) in {
                (409, "concurrency_limit_exceeded"),
                (504, "deadline_exceeded"),
            }
            delay = response.headers.get("Retry-After", "")
            if not collecting or not delay.isdigit() or attempt == attempts - 1:
                response.raise_for_status()
            time.sleep(int(delay))
    raise ValueError("attempts must be positive")
```

Pass the original model, body, and saved key. This limits attempts, not total wall time: each call can last up to the client timeout and each wait follows `Retry-After`. HTTP errors retain the response for inspection; transport errors propagate without replacing the key. Schedule later collection with the saved key if your application needs a longer recovery window.

## Next

* [Billing](/development/comfy-router/billing): what a refusal, timeout, or replay costs.
* [Headers](/development/comfy-router/headers): idempotency, request IDs, and retry pacing headers.
* [API reference](/development/comfy-router/reference#error-buckets): every error bucket Router returns.


# Comfy Router headers
Source: https://docs.comfy.org/development/comfy-router/headers

The request headers you can send to Comfy Router and the response headers it returns, for every model: authentication, idempotency, request IDs, error buckets, retry pacing and spend limits.

Every Router model uses `POST /v2/models/{provider}/{model}` with its own JSON body. This page covers the headers shared across models; the [API reference](/development/comfy-router/reference) lists the generated contract.

The Comfy SDKs (`comfy-sdk` for Python, `@comfyorg/sdk` for TypeScript) handle authentication and generate idempotency keys. They expose selected response metadata as described below. Raw HTTP clients must send and read the headers themselves.

## Request headers

<ParamField type="string">
  A Comfy API key, `comfyui-...`, created in [your Comfy workspace](https://platform.comfy.org/profile/api-keys?onboarding=router). It uses your workspace's model access and credit balance. You can also send it as `Authorization: Bearer comfyui-...`; if both headers are present, `X-API-Key` wins.
</ParamField>

<ParamField type="string">
  `Bearer <token>`. A `comfyui-` value is an API key. Any other value is treated as a Comfy Cloud JWT.
</ParamField>

<ParamField type="string">
  Identifies one logical generation. Generate and store a UUID before the call, then reuse it for retries of the unchanged request. The key can replay a result or collect accepted work for up to 24 hours. The SDKs generate keys and let you supply your own (`idempotency_key=` in Python, `idempotencyKey` in TypeScript). See [retry outcomes](/development/comfy-router/errors#retry-outcomes) for conflicts, expiry, and non-replayable results.
</ParamField>

<ParamField type="string">
  `application/json`. Send the model's native JSON input. Fields and validation requirements vary by model; see [Using the Router API](/development/comfy-router/api).
</ParamField>

<ParamField type="string">
  On `GET /v2/models/{provider}/{model}/openapi.json` only. Send the `ETag` you hold from an earlier `200`; when it still matches, the answer is a bodyless `304` with the same `ETag`. Cache a model's schema for the life of your process and revalidate it this way rather than re-reading it before every call.
</ParamField>

## Response headers

<ResponseField name="X-Comfy-Request-Id" type="string">
  Identifies this HTTP request. Include it when contacting support. TypeScript exposes it as `requestId`; Python exposes `request_id` on errors.
</ResponseField>

<ResponseField name="X-Comfy-Error-Type" type="string">
  The machine-readable error category. On a `422`, use this header because the validation body has `detail[]` and no `error_type`. Combine it with the HTTP status to decide what to do. Treat an unknown value as `internal_error` for control flow and preserve it for diagnostics.
</ResponseField>

<ResponseField name="Idempotent-Replayed" type="boolean">
  Present and `true` when Router serves a stored result instead of running the model again. It is absent on a fresh run. On the queued submit route, a replayed `201` returns the original request handle rather than queueing a second run.
</ResponseField>

<ResponseField name="Retry-After" type="integer">
  Seconds to wait before retrying. On `409` / `concurrency_limit_exceeded` or `504` / `deadline_exceeded`, retry the same request and key after the wait. On `429` / `rate_limited`, it tells you when the rate limit resets. On a queued request's status read and its `202` result read, it is Router's hint for when polling again is worth the round trip.
</ResponseField>

<ResponseField name="X-Committed-Spend-Limit" type="integer">
  The ceiling on partner spend committed to calls still running, in USD cents. An enforcing spend gate can return it on admitted responses and on its `429` refusals. It is absent when the gate is not enforcing or a different control refused the request.
</ResponseField>

<ResponseField name="X-Committed-Spend-Current" type="integer">
  USD cents currently committed to calls in flight. An admitted response includes its own call; a `429` excludes the refused call. Sent alongside `X-Committed-Spend-Limit`.
</ResponseField>

<ResponseField name="X-Committed-Spend-Remaining" type="integer">
  USD cents left below the committed-spend ceiling. It can be positive on a refusal when the requested call costs more than the remaining amount.
</ResponseField>

<ResponseField name="ETag" type="string">
  On `GET /v2/models/{provider}/{model}/openapi.json`. Store it and send it back as `If-None-Match` to revalidate a cached schema.
</ResponseField>

<ResponseField name="Cache-Control" type="string">
  On the schema route: `private, must-revalidate`. Keep the response in a private cache and revalidate stale copies with the `ETag`.
</ResponseField>

## Status codes that carry two meanings

Three statuses are shared by two buckets, and the header is what tells them apart:

| Status | `X-Comfy-Error-Type` | What to do |
| - | - | - |
| `409` | `concurrency_limit_exceeded` | The original call for this key is still running. Wait `Retry-After`, re-send the same key. |
| `409` | `invalid_input` | Inspect the conflict. Restore the original request if you changed it. A consumed, non-replayable key cannot recover the result; use a new key only if you intend a new, potentially billable generation. |
| `429` | `concurrency_limit_exceeded` | Too many calls in flight, or the committed-spend ceiling (see the `X-Committed-Spend-*` headers). Clears when one of your own calls finishes. |
| `429` | `rate_limited` | Wait for `Retry-After` before retrying. |
| `504` | `deadline_exceeded` | Router's own 10-minute bound. With `Retry-After`, re-send the same key to collect the running generation. |
| `504` | `provider_timeout` | The partner timed out. Follow the [retry and billing guidance](/development/comfy-router/errors#retry-outcomes); do not treat this as a guarantee of no charge. |

## Next

* [Quickstart](/development/comfy-router/quickstart): send a request and read the result.
* [Using the Comfy Router API](/development/comfy-router/api): model discovery, schemas, errors, retries, and billing.
* [API reference](/development/comfy-router/reference): the generated contract these headers are defined in.
* [Limitations](/development/comfy-router/limitations): what Router does not do today, and what to use instead.


# Comfy Router capabilities and limits
Source: https://docs.comfy.org/development/comfy-router/limitations

Choose Router or a partner proxy, plan for long-running calls, and understand recovery, rate limits, and asset storage.

Router runs a partner model through one synchronous HTTP call or through a queued request that you submit and collect later. Use it when your application can wait for a finished result or collect one later, and can handle the model's own input and output fields.

## What Router supports

| Requirement | Router support | Alternative or next step |
| - | - | - |
| Generate with one request | `POST /v2/models/{provider}/{model}` returns the finished result. | Start with the [Quickstart](/development/comfy-router/quickstart). |
| Submit a job and collect it later | Queued delivery: `POST /v2/models/{provider}/{model}/requests` returns a `request_id` to poll and collect. No completion webhook. | Use [queued delivery](/development/comfy-router/queue). A partner proxy with submit-and-poll operations exposes the provider's own controls. |
| Show progress or stream output | No live progress, streaming, or preview frames during the call. | Show an indeterminate state, or use a supported proxy operation. |
| Recover after a lost connection | Same-key collection is available when Router retained a handle to an accepted generation. | Preserve the key and follow [retry guidance](/development/comfy-router/errors#retry-outcomes). |
| Reconcile Comfy charges | No universal Comfy cost or credit-balance field on the response. | Use [workspace billing](https://platform.comfy.org). |
| Store results permanently | Asset URLs can expire, including rehosted and replayed URLs. | Download the assets; see [result assets](/development/comfy-router/reference#result-assets). |
| Send large media inline | The request body is capped, and base64-encoded media counts against that cap. | Keep bodies under the cap; see [request body size](#request-bodies-are-capped). |

<span />

## Queued submission

The synchronous route holds the connection while the model runs; for asynchronous providers, Router submits the job and polls internally. Queued delivery (submit, get a `request_id`, poll, collect) is the alternative: see [Queued delivery](/development/comfy-router/queue). It is scoped to the workspace behind the credential, so it needs a key created in your Comfy workspace. A legacy key with no workspace, a bring-your-own-key request, or a model the queue cannot run answers `403` with `not_enabled` on the submit route. Neither mode offers a callback or webhook.

If your request cannot stay open long enough, queue it. Use a [partner proxy](#router-does-not-cover-every-partner-operation) when you need the provider's own submit-and-poll controls.

Four models are synchronous-only for now and are refused with `403` / `not_enabled` if you submit them to the queue: `elevenlabs/eleven_sfx_v2`, `elevenlabs/eleven_v3`, `elevenlabs/eleven_v4` and `elevenlabs/eleven_v4_turbo`. They answer raw audio bytes rather than a JSON result document, which queued delivery has nowhere to store. Run them on the synchronous route, which returns those bytes normally.

The LTX v1 text-to-video and image-to-video operations answer raw video bytes for the same reason, and queued delivery cannot store them either — but they are reachable only through the [partner proxy](#router-does-not-cover-every-partner-operation) at `/proxy/ltx/v1/…`, not through a Router model id: every `ltx/*` catalog model resolves to the queueable v2 submit-and-poll operation.

## Calls are cut off at a server deadline

Router's default deadline is **10 minutes**, configurable by the deployment. Set your client timeout above it so Router can return its error and request ID first.

`504` / `deadline_exceeded` means Router stopped waiting; `504` / `provider_timeout` means the provider timed out. A timeout or lost connection does not prove that a generation was unbilled, and it does not cancel accepted provider work. Read [timeouts and collection](/development/comfy-router/errors#timeouts-and-collection) before retrying.

<span />

## Recovery depends on the provider

Router can retain a provider handle for an accepted submit-and-poll generation. Reuse the same `Idempotency-Key` to collect it later; completed replayable responses can also come from the key record.

Not every disconnected call is recoverable. Preserve the request and key before sending, then use the [retry outcome table](/development/comfy-router/errors#retry-outcomes). A new key creates a new call and may incur another charge.

## Request bodies are capped

Router refuses a request whose body is larger than **100 MiB (104,857,600 bytes)**. The bound is on the raw bytes you send, measured before Router parses anything, so it applies to every route and to both synchronous and queued delivery.

Inline media is where callers meet it. Base64 encoding inflates binary data by about 4/3, so a body carrying encoded media clears the cap at roughly **75 MB of actual image, audio, or video bytes**. Size the encoded string, not the file on disk, and count every input in one call: a request carrying two reference images spends the allowance on both, and the prompt, parameters, and JSON structure count too.

**What the refusal looks like.** `413`, with `invalid_input` on `X-Comfy-Error-Type` and `X-Comfy-Request-Id` set as on any other response. The body is a [`RouterErrorResponse`](/development/comfy-router/reference#routererrorresponse) whose `detail` describes the bound that was exceeded. Branch on `error_type` rather than parsing `detail`, and treat what the API returns as authoritative if it and this page ever disagree about the figure. Router raises the refusal before dispatching anything, so no generation ran and nothing was charged.

The cap applies to every request, whether or not it carries an `Idempotency-Key`. It is not an idempotency limit, and re-sending the same key does not change the outcome: a body that is too large is too large on every attempt.

**A provider can impose a lower limit of its own, and at this cap it usually does.** Providers publish their own bounds on inline media, and the binding constraint is whichever is smaller. Google's models, for example, accept up to 20 MB (decimal, 20,000,000 bytes) of inline payload, and the `Size limit: 20MB` line on the Google model pages is that per-field Google bound quoted from Google's own specification, not Router's bound on the whole request body. Router's cap sits above every partner bound it fronts deliberately, so for a single inline asset the provider's own limit is normally what you meet first; Router's cap binds across several assets in one body. A body that clears Router's cap but exceeds a provider's own limit is refused by the provider rather than by Router, and it comes back as a provider error rather than a `413`.

## Requests are rate limited per caller

| Response | Cause | Action |
| - | - | - |
| `429` / `concurrency_limit_exceeded` | Too many concurrent calls, or insufficient headroom under the committed-spend ceiling. | Reduce concurrent work. The spend headers distinguish the spend ceiling from the call-count limit. |
| `429` / `rate_limited` | The request allowance is exhausted. | Wait for `Retry-After` before retrying. |

The request-rate limit applies to invocation and catalog/schema reads, including requests refused before generation. It follows the authenticated caller, not the source IP. Calls with the caller's provider key are exempt; provider limits still apply.

Cache catalog and schema reads. Revalidate schemas with `ETag` and `If-None-Match`. See [Headers](/development/comfy-router/headers) for retry and committed-spend fields.

## No progress while a call runs

Router returns a final response, with no streamed tokens, server-sent events, percentage updates, or intermediate preview frames. A provider's internal polling state is not forwarded during the request.

Show an indeterminate progress indicator. If you need progress or streaming, use a partner-proxy operation that exposes it.

<span />

## Comfy charges and usage

The response can contain provider usage or cost fields. They do not represent a universal Comfy charge. `X-Comfy-Credits-Used` is optional: a missing header means the cost was not reported, not that the run was free. A replayed response (`Idempotent-Replayed: true`) is never charged again but may restate the original run's figure, so do not add the header up across retries of one `Idempotency-Key`. Use the Comfy platform for balances, usage, and invoices.

The catalog provides billing facts, including `billing.charges_on_policy_rejection`, rather than prices. Handle `yes`, `no`, and `unknown` explicitly. See [billing](/development/comfy-router/billing#model-billing-facts).

## Router does not cover every partner operation

Router runs models. File uploads, account reads, asset management, streaming, and provider job controls can require partner-proxy routes under `/proxy/…`, which sit outside Router and are not described by its contract. Router's own surface is the [Comfy Router specification](/router-openapi.yaml); support varies by provider.

## Model outputs and stored assets

Input and output fields vary by model. Moving from a provider SDK or proxy can change both the route and how you read the result.

Some assets are rehosted on Comfy storage; others are provider URLs or inline bytes. See [Result assets](/development/comfy-router/reference#result-assets) for lifetimes and replay behavior.

## Next

<CardGroup>
  <Card title="Quickstart" icon="rocket" href="/development/comfy-router/quickstart">
    Generate your first image through Comfy Router.
  </Card>

  <Card title="Using the Router API" icon="code" href="/development/comfy-router/api">
    Choose a model, inspect its schema, and handle results and retries.
  </Card>
</CardGroup>


# Comfy Router models
Source: https://docs.comfy.org/development/comfy-router/models

Every model available through Comfy Router, grouped by provider, with the input and output modality of each.

Every model below is served by the same route, `POST /v2/models/{provider}/{model}`, with the model's own JSON body. Each page shows a working request in Python, TypeScript, and cURL. For discovery, schemas, errors, retries, and billing, see [Using the Comfy Router API](/development/comfy-router/api).

Some of these models can also be served by an aggregator on the same route and the same model ID. [Serving providers](/development/comfy-router/providers) lists which provider covers which model, and how to select one.

## Find by output

<AccordionGroup>
  <Accordion title="Video (67)">
    * [SwitchX](/development/comfy-router/models/beeble/switchx/code): `beeble/switchx`
    * [FLUX 3 Video](/development/comfy-router/models/black-forest-labs/flux-3-video/code): `bfl/flux-3-video`
    * [FLUX Video Upscale](/development/comfy-router/models/black-forest-labs/flux-video-upscale/code): `bfl/video-upscale-v1`
    * [Video Edit V1](/development/comfy-router/models/black-forest-labs/video-edit-v1/code): `bfl/video-edit-v1`
    * [Video Edit Erase](/development/comfy-router/models/bria/video-edit-erase/code): `bria/video-edit-erase`
    * [Video Edit Green Screen](/development/comfy-router/models/bria/video-edit-green-screen/code): `bria/video-edit-green-screen`
    * [Video Edit Remove Background](/development/comfy-router/models/bria/video-edit-remove-background/code): `bria/video-edit-remove-background`
    * [Video Edit Replace Background](/development/comfy-router/models/bria/video-edit-replace-background/code): `bria/video-edit-replace-background`
    * [Dreamina Seedance 2.0 260128](/development/comfy-router/models/byteplus/dreamina-seedance-2-0-260128/code): `byteplus/dreamina-seedance-2-0-260128`
    * [Dreamina Seedance 2.0 Fast 260128](/development/comfy-router/models/byteplus/dreamina-seedance-2-0-fast-260128/code): `byteplus/dreamina-seedance-2-0-fast-260128`
    * [Dreamina Seedance 2.0 Mini](/development/comfy-router/models/byteplus/dreamina-seedance-2-0-mini/code): `byteplus/dreamina-seedance-2-0-mini`
    * [Dreamina Seedance 2.5 260628](/development/comfy-router/models/byteplus/dreamina-seedance-2-5-260628/code): `byteplus/dreamina-seedance-2-5-260628`
    * [Seedance 1.0 Pro 250528](/development/comfy-router/models/byteplus/seedance-1-0-pro-250528/code): `byteplus/seedance-1-0-pro-250528`
    * [Seedance 1.0 Pro Fast 251015](/development/comfy-router/models/byteplus/seedance-1-0-pro-fast-251015/code): `byteplus/seedance-1-0-pro-fast-251015`
    * [Seedance 1.5 Pro 251215](/development/comfy-router/models/byteplus/seedance-1-5-pro-251215/code): `byteplus/seedance-1-5-pro-251215`
    * [H3 Max Turbo](/development/comfy-router/models/fal/h3-max-turbo/code): `fal/h3-max-turbo`
    * [H3 Max](/development/comfy-router/models/fal/h3-max/code): `fal/h3-max`
    * [Higgsfield Kling 3.4k](/development/comfy-router/models/higgsfield/higgsfield-kling-3-4k/code): `higgsfield/higgsfield-kling-3-4k`
    * [Higgsfield Kling 3 Pro](/development/comfy-router/models/higgsfield/higgsfield-kling-3-pro/code): `higgsfield/higgsfield-kling-3-pro`
    * [Kling 3.0 Turbo](/development/comfy-router/models/kling/kling-3-0-turbo/code): `kling/kling-3.0-turbo`
    * [Kling V2.5 Turbo](/development/comfy-router/models/kling/kling-v2-5-turbo/code): `kling/kling-v2-5-turbo`
    * [Kling V2.6](/development/comfy-router/models/kling/kling-v2-6/code): `kling/kling-v2-6`
    * [Kling V3 Omni](/development/comfy-router/models/kling/kling-v3-omni/code): `kling/kling-v3-omni`
    * [Kling V3](/development/comfy-router/models/kling/kling-v3/code): `kling/kling-v3`
    * [Kling Video O1](/development/comfy-router/models/kling/kling-video-o1/code): `kling/kling-video-o1`
    * [Videos Avatar Image 2video](/development/comfy-router/models/kling/videos-avatar-image2video/code): `kling/videos-avatar-image2video`
    * [Videos Lip Sync](/development/comfy-router/models/kling/videos-lip-sync/code): `kling/videos-lip-sync`
    * [Videos Video Extend](/development/comfy-router/models/kling/videos-video-extend/code): `kling/videos-video-extend`
    * [LTX 2.5 Fast](/development/comfy-router/models/ltx/ltx-2-5-fast/code): `ltx/ltx-2-5-fast`
    * [LTX 2.5 Pro](/development/comfy-router/models/ltx/ltx-2-5-pro/code): `ltx/ltx-2-5-pro`
    * [Ray 2](/development/comfy-router/models/luma/ray-2/code): `luma/ray-2`
    * [Ray Flash 2](/development/comfy-router/models/luma/ray-flash-2/code): `luma/ray-flash-2`
    * [MiniMax H3](/development/comfy-router/models/minimax/minimax-h3/code): `minimax/minimax-h3`
    * [Image To Video](/development/comfy-router/models/moonvalley/image-to-video/code): `moonvalley/image-to-video`
    * [Text To Video](/development/comfy-router/models/moonvalley/text-to-video/code): `moonvalley/text-to-video`
    * [Video To Video Resize](/development/comfy-router/models/moonvalley/video-to-video-resize/code): `moonvalley/video-to-video-resize`
    * [Video To Video](/development/comfy-router/models/moonvalley/video-to-video/code): `moonvalley/video-to-video`
    * [P Video 2](/development/comfy-router/models/pruna/p-video-2/code): `pruna/p-video-2`
    * [Aleph 2](/development/comfy-router/models/runway/aleph2/code): `runway/aleph2`
    * [Gen 4 Turbo](/development/comfy-router/models/runway/gen4-turbo/code): `runway/gen4_turbo`
    * [Sync 3](/development/comfy-router/models/synclabs/sync-3/code): `synclabs/sync-3`
    * [Veo 3.1 Fast Generate 001](/development/comfy-router/models/veo/veo-3-1-fast-generate-001/code): `veo/veo-3.1-fast-generate-001`
    * [Veo 3.1 Generate 001](/development/comfy-router/models/veo/veo-3-1-generate-001/code): `veo/veo-3.1-generate-001`
    * [Veo 3.1 Lite Generate 001](/development/comfy-router/models/veo/veo-3-1-lite-generate-001/code): `veo/veo-3.1-lite-generate-001`
    * [HappyHorse 1.0 I2V](/development/comfy-router/models/wan/happyhorse-1-0-i2v/code): `wan/happyhorse-1.0-i2v`
    * [HappyHorse 1.0 R2V](/development/comfy-router/models/wan/happyhorse-1-0-r2v/code): `wan/happyhorse-1.0-r2v`
    * [HappyHorse 1.0 T2V](/development/comfy-router/models/wan/happyhorse-1-0-t2v/code): `wan/happyhorse-1.0-t2v`
    * [HappyHorse 1.0 Video Edit](/development/comfy-router/models/wan/happyhorse-1-0-video-edit/code): `wan/happyhorse-1.0-video-edit`
    * [HappyHorse 1.1 I2V](/development/comfy-router/models/wan/happyhorse-1-1-i2v/code): `wan/happyhorse-1.1-i2v`
    * [HappyHorse 1.1 R2V](/development/comfy-router/models/wan/happyhorse-1-1-r2v/code): `wan/happyhorse-1.1-r2v`
    * [HappyHorse 1.1 T2V](/development/comfy-router/models/wan/happyhorse-1-1-t2v/code): `wan/happyhorse-1.1-t2v`
    * [Wan 2.5 I2V Preview](/development/comfy-router/models/wan/wan2-5-i2v-preview/code): `wan/wan2.5-i2v-preview`
    * [Wan 2.5 T2V Preview](/development/comfy-router/models/wan/wan2-5-t2v-preview/code): `wan/wan2.5-t2v-preview`
    * [Wan 2.6 I2V](/development/comfy-router/models/wan/wan2-6-i2v/code): `wan/wan2.6-i2v`
    * [Wan 2.6 R2V](/development/comfy-router/models/wan/wan2-6-r2v/code): `wan/wan2.6-r2v`
    * [Wan 2.6 T2V](/development/comfy-router/models/wan/wan2-6-t2v/code): `wan/wan2.6-t2v`
    * [Wan 2.7 I2V](/development/comfy-router/models/wan/wan2-7-i2v/code): `wan/wan2.7-i2v`
    * [Wan 2.7 R2V](/development/comfy-router/models/wan/wan2-7-r2v/code): `wan/wan2.7-r2v`
    * [Wan 2.7 T2V](/development/comfy-router/models/wan/wan2-7-t2v/code): `wan/wan2.7-t2v`
    * [Wan 2.7 Video Edit](/development/comfy-router/models/wan/wan2-7-videoedit/code): `wan/wan2.7-videoedit`
    * [Wan 3.0 Video Prime](/development/comfy-router/models/wan/wan3-0-video-prime/code): `wan/wan3.0-video-prime`
    * [Wan 3.0 Video](/development/comfy-router/models/wan/wan3-0-video/code): `wan/wan3.0-video`
    * [Flashvsr](/development/comfy-router/models/wavespeed/flashvsr/code): `wavespeed/flashvsr`
    * [Grok Imagine Video 1.5 Lite](/development/comfy-router/models/xai/grok-imagine-video-1-5-lite/code): `xai/grok-imagine-video-1.5-lite`
    * [Grok Imagine Video 1.5 Preview](/development/comfy-router/models/xai/grok-imagine-video-1-5-preview/code): `xai/grok-imagine-video-1.5-preview`
    * [Grok Imagine Video 1.5](/development/comfy-router/models/xai/grok-imagine-video-1-5/code): `xai/grok-imagine-video-1.5`
    * [Grok Imagine Video](/development/comfy-router/models/xai/grok-imagine-video/code): `xai/grok-imagine-video`
  </Accordion>

  <Accordion title="Image (89)">
    * [SwitchX](/development/comfy-router/models/beeble/switchx/code): `beeble/switchx`
    * [Erase V1](/development/comfy-router/models/black-forest-labs/erase-v1/code): `bfl/erase-v1`
    * [Flux 1.1 Pro Ultra Image](/development/comfy-router/models/black-forest-labs/flux-1-1-pro-ultra-image/code): `bfl/flux-pro-1.1-ultra`
    * [FLUX.1 Kontext](/development/comfy-router/models/black-forest-labs/flux-1-kontext/code): `bfl/flux-kontext-pro`
    * [FLUX 2 Max](/development/comfy-router/models/black-forest-labs/flux-2-max/code): `bfl/flux-2-max`
    * [FLUX 2 Pro](/development/comfy-router/models/black-forest-labs/flux-2-pro/code): `bfl/flux-2-pro`
    * [FLUX 3 Image](/development/comfy-router/models/black-forest-labs/flux-3-image/code): `bfl/flux-3-image`
    * [FLUX Pro 1.0 Expand](/development/comfy-router/models/black-forest-labs/flux-pro-1-0-expand/code): `bfl/flux-pro-1.0-expand`
    * [FLUX Pro 1.0 Fill](/development/comfy-router/models/black-forest-labs/flux-pro-1-0-fill/code): `bfl/flux-pro-1.0-fill`
    * [VTO V1](/development/comfy-router/models/black-forest-labs/vto-v1/code): `bfl/vto-v1`
    * [Fibo](/development/comfy-router/models/bria/fibo/code): `bria/fibo`
    * [Image Edit Add Object By Text](/development/comfy-router/models/bria/image-edit-add-object-by-text/code): `bria/image-edit-add-object-by-text`
    * [Image Edit Erase By Text](/development/comfy-router/models/bria/image-edit-erase-by-text/code): `bria/image-edit-erase-by-text`
    * [Image Edit Erase Foreground](/development/comfy-router/models/bria/image-edit-erase-foreground/code): `bria/image-edit-erase-foreground`
    * [Image Edit Erase](/development/comfy-router/models/bria/image-edit-erase/code): `bria/image-edit-erase`
    * [Image Edit Expand](/development/comfy-router/models/bria/image-edit-expand/code): `bria/image-edit-expand`
    * [Image Edit Gen Fill](/development/comfy-router/models/bria/image-edit-gen-fill/code): `bria/image-edit-gen-fill`
    * [Image Edit Increase Resolution](/development/comfy-router/models/bria/image-edit-increase-resolution/code): `bria/image-edit-increase-resolution`
    * [Image Edit Relight](/development/comfy-router/models/bria/image-edit-relight/code): `bria/image-edit-relight`
    * [Image Edit Remove Background](/development/comfy-router/models/bria/image-edit-remove-background/code): `bria/image-edit-remove-background`
    * [Image Edit Replace Background](/development/comfy-router/models/bria/image-edit-replace-background/code): `bria/image-edit-replace-background`
    * [Image Edit Replace Object By Text](/development/comfy-router/models/bria/image-edit-replace-object-by-text/code): `bria/image-edit-replace-object-by-text`
    * [Image Edit Reseason](/development/comfy-router/models/bria/image-edit-reseason/code): `bria/image-edit-reseason`
    * [Image Edit Restore](/development/comfy-router/models/bria/image-edit-restore/code): `bria/image-edit-restore`
    * [Seedream 4.0 250828](/development/comfy-router/models/byteplus/seedream-4-0-250828/code): `byteplus/seedream-4-0-250828`
    * [Seedream 4.5 251128](/development/comfy-router/models/byteplus/seedream-4-5-251128/code): `byteplus/seedream-4-5-251128`
    * [Seedream 5.0 260128](/development/comfy-router/models/byteplus/seedream-5-0-260128/code): `byteplus/seedream-5-0-260128`
    * [Seedream 5.0 Flash 260915](/development/comfy-router/models/byteplus/seedream-5-0-flash-260915/code): `byteplus/seedream-5-0-flash-260915`
    * [Seedream 5.0 Pro 260628](/development/comfy-router/models/byteplus/seedream-5-0-pro-260628/code): `byteplus/seedream-5-0-pro-260628`
    * [Patina](/development/comfy-router/models/fal/patina/code): `fal/patina`
    * [AI Image Upscaler Precision V2](/development/comfy-router/models/freepik/ai-image-upscaler-precision-v2/code): `freepik/ai-image-upscaler-precision-v2`
    * [AI Skin Enhancer Creative](/development/comfy-router/models/freepik/ai-skin-enhancer-creative/code): `freepik/ai-skin-enhancer-creative`
    * [AI Skin Enhancer Faithful](/development/comfy-router/models/freepik/ai-skin-enhancer-faithful/code): `freepik/ai-skin-enhancer-faithful`
    * [AI Skin Enhancer Flexible](/development/comfy-router/models/freepik/ai-skin-enhancer-flexible/code): `freepik/ai-skin-enhancer-flexible`
    * [Gemini Omni 1.1 Flash](/development/comfy-router/models/gemini-interactions/gemini-omni-1-1-flash/code): `gemini-interactions/gemini-omni-1.1-flash`
    * [Gemini Omni Flash Preview](/development/comfy-router/models/gemini-interactions/gemini-omni-flash-preview/code): `gemini-interactions/gemini-omni-flash-preview`
    * [Gemini 2.5 Flash Image](/development/comfy-router/models/google/gemini-2-5-flash-image/code): `vertexai/gemini-2.5-flash-image`
    * [Imagen 3.0 Fast Generate 001](/development/comfy-router/models/google/imagen-3-0-fast-generate-001/code): `vertexai/imagen-3.0-fast-generate-001`
    * [Imagen 3.0 Generate 001](/development/comfy-router/models/google/imagen-3-0-generate-001/code): `vertexai/imagen-3.0-generate-001`
    * [Imagen 3.0 Generate 002](/development/comfy-router/models/google/imagen-3-0-generate-002/code): `vertexai/imagen-3.0-generate-002`
    * [Nano Banana 2 Lite](/development/comfy-router/models/google/nano-banana-2-lite/code): `vertexai/gemini-3.1-flash-lite-image`
    * [Nano Banana 2](/development/comfy-router/models/google/nano-banana-2/code): `vertexai/gemini-3.1-flash-image`
    * [Nano Banana Pro](/development/comfy-router/models/google/nano-banana-pro/code): `vertexai/gemini-3-pro-image`
    * [Ideogram 4.5](/development/comfy-router/models/ideogram/ideogram-4-5/code): `ideogram/ideogram-4-5`
    * [Ideogram V3](/development/comfy-router/models/ideogram/ideogram-v3/code): `ideogram/ideogram-v3`
    * [Ideogram 4.0](/development/comfy-router/models/ideogram/ideogram-v4/code): `ideogram/ideogram-v4`
    * [P Image Ideogram](/development/comfy-router/models/ideogram/p-image-ideogram/code): `ideogram/p-image-ideogram`
    * [Kling Image O1](/development/comfy-router/models/kling/kling-image-o1/code): `kling/kling-image-o1`
    * [Krea 2 Large](/development/comfy-router/models/krea/krea-2-large/code): `krea/krea-2-large`
    * [Krea 2 Medium Turbo](/development/comfy-router/models/krea/krea-2-medium-turbo/code): `krea/krea-2-medium-turbo`
    * [Krea 2 Medium](/development/comfy-router/models/krea/krea-2-medium/code): `krea/krea-2-medium`
    * [Krea 2](/development/comfy-router/models/krea/krea-2/code): `krea/krea-2`
    * [Uni 1 Max](/development/comfy-router/models/luma_2/uni-1-max/code): `luma_2/uni-1-max`
    * [Uni 1](/development/comfy-router/models/luma_2/uni-1/code): `luma_2/uni-1`
    * [Photon 1](/development/comfy-router/models/luma/photon-1/code): `luma/photon-1`
    * [Photon Flash 1](/development/comfy-router/models/luma/photon-flash-1/code): `luma/photon-flash-1`
    * [Text To Image](/development/comfy-router/models/moonvalley/text-to-image/code): `moonvalley/text-to-image`
    * [GPT Image 1.5](/development/comfy-router/models/openai/gpt-image-1-5/code): `openai/gpt-image-1.5`
    * [GPT Image 1](/development/comfy-router/models/openai/gpt-image-1/code): `openai/gpt-image-1`
    * [GPT Image 2.5 Flare](/development/comfy-router/models/openai/gpt-image-2-5-flare/code): `openai/gpt-image-2.5-flare`
    * [GPT Image 2.5 Sunburst](/development/comfy-router/models/openai/gpt-image-2-5-sunburst/code): `openai/gpt-image-2.5-sunburst`
    * [GPT Image 2](/development/comfy-router/models/openai/gpt-image-2/code): `openai/gpt-image-2`
    * [Qwen Image 3.0 Pro](/development/comfy-router/models/qwen/qwen-image-3-0-pro/code): `qwen/qwen-image-3.0-pro`
    * [Qwen Image 3.0](/development/comfy-router/models/qwen/qwen-image-3-0/code): `qwen/qwen-image-3.0`
    * [Recraft V2](/development/comfy-router/models/recraft/recraftv2/code): `recraft/recraftv2`
    * [Recraft V3](/development/comfy-router/models/recraft/recraftv3/code): `recraft/recraftv3`
    * [Recraft V4.1 Pro Vector](/development/comfy-router/models/recraft/recraftv4-1-pro-vector/code): `recraft/recraftv4_1_pro_vector`
    * [Recraft V4.1 Pro](/development/comfy-router/models/recraft/recraftv4-1-pro/code): `recraft/recraftv4_1_pro`
    * [Recraft V4.1 Utility Pro Vector](/development/comfy-router/models/recraft/recraftv4-1-utility-pro-vector/code): `recraft/recraftv4_1_utility_pro_vector`
    * [Recraft V4.1 Utility Pro](/development/comfy-router/models/recraft/recraftv4-1-utility-pro/code): `recraft/recraftv4_1_utility_pro`
    * [Recraft V4.1 Utility Vector](/development/comfy-router/models/recraft/recraftv4-1-utility-vector/code): `recraft/recraftv4_1_utility_vector`
    * [Recraft V4.1 Utility](/development/comfy-router/models/recraft/recraftv4-1-utility/code): `recraft/recraftv4_1_utility`
    * [Recraft V4.1 Vector](/development/comfy-router/models/recraft/recraftv4-1-vector/code): `recraft/recraftv4_1_vector`
    * [Recraft V4.1](/development/comfy-router/models/recraft/recraftv4-1/code): `recraft/recraftv4_1`
    * [Recraft V4 Pro](/development/comfy-router/models/recraft/recraftv4-pro/code): `recraft/recraftv4_pro`
    * [Recraft V4 Styles Pro Vector](/development/comfy-router/models/recraft/recraftv4-styles-pro-vector/code): `recraft/recraftv4_styles_pro_vector`
    * [Recraft V4 Styles Pro](/development/comfy-router/models/recraft/recraftv4-styles-pro/code): `recraft/recraftv4_styles_pro`
    * [Recraft V4 Styles Vector](/development/comfy-router/models/recraft/recraftv4-styles-vector/code): `recraft/recraftv4_styles_vector`
    * [Recraft V4 Styles](/development/comfy-router/models/recraft/recraftv4-styles/code): `recraft/recraftv4_styles`
    * [Recraft V4](/development/comfy-router/models/recraft/recraftv4/code): `recraft/recraftv4`
    * [Gen 4 Image](/development/comfy-router/models/runway/gen4-image/code): `runway/gen4_image`
    * [Wan 2.5 I2I Preview](/development/comfy-router/models/wan/wan2-5-i2i-preview/code): `wan/wan2.5-i2i-preview`
    * [Wan 2.5 T2I Preview](/development/comfy-router/models/wan/wan2-5-t2i-preview/code): `wan/wan2.5-t2i-preview`
    * [Seedvr 2](/development/comfy-router/models/wavespeed/seedvr2/code): `wavespeed/seedvr2`
    * [Ultimate Image Upscaler](/development/comfy-router/models/wavespeed/ultimate-image-upscaler/code): `wavespeed/ultimate-image-upscaler`
    * [Grok Imagine Image 2.0](/development/comfy-router/models/xai/grok-imagine-image-2-0/code): `xai/grok-imagine-image-2.0`
    * [Grok Imagine Image Pro](/development/comfy-router/models/xai/grok-imagine-image-pro/code): `xai/grok-imagine-image-pro`
    * [Grok Imagine Image Quality](/development/comfy-router/models/xai/grok-imagine-image-quality/code): `xai/grok-imagine-image-quality`
    * [Grok Imagine Image](/development/comfy-router/models/xai/grok-imagine-image/code): `xai/grok-imagine-image`
  </Accordion>

  <Accordion title="Audio (35)">
    * [FLUX 3 Video](/development/comfy-router/models/black-forest-labs/flux-3-video/code): `bfl/flux-3-video`
    * [Dreamina Seedance 2.0 260128](/development/comfy-router/models/byteplus/dreamina-seedance-2-0-260128/code): `byteplus/dreamina-seedance-2-0-260128`
    * [Dreamina Seedance 2.0 Fast 260128](/development/comfy-router/models/byteplus/dreamina-seedance-2-0-fast-260128/code): `byteplus/dreamina-seedance-2-0-fast-260128`
    * [Dreamina Seedance 2.0 Mini](/development/comfy-router/models/byteplus/dreamina-seedance-2-0-mini/code): `byteplus/dreamina-seedance-2-0-mini`
    * [Dreamina Seedance 2.5 260628](/development/comfy-router/models/byteplus/dreamina-seedance-2-5-260628/code): `byteplus/dreamina-seedance-2-5-260628`
    * [Seed Audio 1.0 Multilingual](/development/comfy-router/models/byteplus/seed-audio-1-0-multilingual/code): `byteplus/seed-audio-1.0-multilingual`
    * [Seed Audio 1.0](/development/comfy-router/models/byteplus/seed-audio-1-0/code): `byteplus/seed-audio-1.0`
    * [Seedance 1.5 Pro 251215](/development/comfy-router/models/byteplus/seedance-1-5-pro-251215/code): `byteplus/seedance-1-5-pro-251215`
    * [Eleven Sfx V2](/development/comfy-router/models/elevenlabs/eleven-sfx-v2/code): `elevenlabs/eleven_sfx_v2`
    * [Eleven V3](/development/comfy-router/models/elevenlabs/eleven-v3/code): `elevenlabs/eleven_v3`
    * [Eleven V4 Turbo](/development/comfy-router/models/elevenlabs/eleven-v4-turbo/code): `elevenlabs/eleven_v4_turbo`
    * [Eleven V4](/development/comfy-router/models/elevenlabs/eleven-v4/code): `elevenlabs/eleven_v4`
    * [H3 Max Turbo](/development/comfy-router/models/fal/h3-max-turbo/code): `fal/h3-max-turbo`
    * [H3 Max](/development/comfy-router/models/fal/h3-max/code): `fal/h3-max`
    * [Gemini Omni 1.1 Flash](/development/comfy-router/models/gemini-interactions/gemini-omni-1-1-flash/code): `gemini-interactions/gemini-omni-1.1-flash`
    * [Gemini Omni Flash Preview](/development/comfy-router/models/gemini-interactions/gemini-omni-flash-preview/code): `gemini-interactions/gemini-omni-flash-preview`
    * [Starfish](/development/comfy-router/models/heygen/starfish/code): `heygen/starfish`
    * [Higgsfield Kling 3.4k](/development/comfy-router/models/higgsfield/higgsfield-kling-3-4k/code): `higgsfield/higgsfield-kling-3-4k`
    * [Higgsfield Kling 3 Pro](/development/comfy-router/models/higgsfield/higgsfield-kling-3-pro/code): `higgsfield/higgsfield-kling-3-pro`
    * [LTX 2.5 Fast](/development/comfy-router/models/ltx/ltx-2-5-fast/code): `ltx/ltx-2-5-fast`
    * [LTX 2.5 Pro](/development/comfy-router/models/ltx/ltx-2-5-pro/code): `ltx/ltx-2-5-pro`
    * [MiniMax H3](/development/comfy-router/models/minimax/minimax-h3/code): `minimax/minimax-h3`
    * [P Video 2](/development/comfy-router/models/pruna/p-video-2/code): `pruna/p-video-2`
    * [Veo 3.1 Fast Generate 001](/development/comfy-router/models/veo/veo-3-1-fast-generate-001/code): `veo/veo-3.1-fast-generate-001`
    * [Veo 3.1 Generate 001](/development/comfy-router/models/veo/veo-3-1-generate-001/code): `veo/veo-3.1-generate-001`
    * [Veo 3.1 Lite Generate 001](/development/comfy-router/models/veo/veo-3-1-lite-generate-001/code): `veo/veo-3.1-lite-generate-001`
    * [Wan 2.5 I2V Preview](/development/comfy-router/models/wan/wan2-5-i2v-preview/code): `wan/wan2.5-i2v-preview`
    * [Wan 2.5 T2V Preview](/development/comfy-router/models/wan/wan2-5-t2v-preview/code): `wan/wan2.5-t2v-preview`
    * [Wan 2.6 I2V](/development/comfy-router/models/wan/wan2-6-i2v/code): `wan/wan2.6-i2v`
    * [Wan 2.6 R2V](/development/comfy-router/models/wan/wan2-6-r2v/code): `wan/wan2.6-r2v`
    * [Wan 2.6 T2V](/development/comfy-router/models/wan/wan2-6-t2v/code): `wan/wan2.6-t2v`
    * [Wan 2.7 I2V](/development/comfy-router/models/wan/wan2-7-i2v/code): `wan/wan2.7-i2v`
    * [Wan 2.7 T2V](/development/comfy-router/models/wan/wan2-7-t2v/code): `wan/wan2.7-t2v`
    * [Wan 3.0 Video Prime](/development/comfy-router/models/wan/wan3-0-video-prime/code): `wan/wan3.0-video-prime`
    * [Wan 3.0 Video](/development/comfy-router/models/wan/wan3-0-video/code): `wan/wan3.0-video`
  </Accordion>

  <Accordion title="3D (11)">
    * [Animations](/development/comfy-router/models/meshy/animations/code): `meshy/animations`
    * [Meshy 5](/development/comfy-router/models/meshy/meshy-5/code): `meshy/meshy-5`
    * [Meshy 6](/development/comfy-router/models/meshy/meshy-6/code): `meshy/meshy-6`
    * [Meshy 7.1](/development/comfy-router/models/meshy/meshy-7-1/code): `meshy/meshy-7.1`
    * [Meshy 7](/development/comfy-router/models/meshy/meshy-7/code): `meshy/meshy-7`
    * [Remesh](/development/comfy-router/models/meshy/remesh/code): `meshy/remesh`
    * [Rigging](/development/comfy-router/models/meshy/rigging/code): `meshy/rigging`
    * [Hunyuan 3D Part](/development/comfy-router/models/tencent/hunyuan-3d-part/code): `tencent/hunyuan-3d-part`
    * [Hunyuan 3D Smart Topology](/development/comfy-router/models/tencent/hunyuan-3d-smart-topology/code): `tencent/hunyuan-3d-smart-topology`
    * [Hunyuan 3D Texture Edit](/development/comfy-router/models/tencent/hunyuan-3d-texture-edit/code): `tencent/hunyuan-3d-texture-edit`
    * [Hunyuan 3D Uv](/development/comfy-router/models/tencent/hunyuan-3d-uv/code): `tencent/hunyuan-3d-uv`
  </Accordion>

  <Accordion title="Text (46)">
    * [Claude Fable 5.1](/development/comfy-router/models/anthropic/claude-fable-5-1/code): `anthropic/claude-fable-5-1`
    * [Claude Fable 5](/development/comfy-router/models/anthropic/claude-fable-5/code): `anthropic/claude-fable-5`
    * [Claude Haiku 4.5 20251001](/development/comfy-router/models/anthropic/claude-haiku-4-5-20251001/code): `anthropic/claude-haiku-4-5-20251001`
    * [Claude Opus 4.6](/development/comfy-router/models/anthropic/claude-opus-4-6/code): `anthropic/claude-opus-4-6`
    * [Claude Opus 4.7](/development/comfy-router/models/anthropic/claude-opus-4-7/code): `anthropic/claude-opus-4-7`
    * [Claude Opus 4.8](/development/comfy-router/models/anthropic/claude-opus-4-8/code): `anthropic/claude-opus-4-8`
    * [Claude Opus 5.5](/development/comfy-router/models/anthropic/claude-opus-5-5/code): `anthropic/claude-opus-5-5`
    * [Claude Opus 5](/development/comfy-router/models/anthropic/claude-opus-5/code): `anthropic/claude-opus-5`
    * [Claude Sonnet 4.5 20250929](/development/comfy-router/models/anthropic/claude-sonnet-4-5-20250929/code): `anthropic/claude-sonnet-4-5-20250929`
    * [Claude Sonnet 4.6](/development/comfy-router/models/anthropic/claude-sonnet-4-6/code): `anthropic/claude-sonnet-4-6`
    * [Claude Sonnet 5.5](/development/comfy-router/models/anthropic/claude-sonnet-5-5/code): `anthropic/claude-sonnet-5-5`
    * [Claude Sonnet 5](/development/comfy-router/models/anthropic/claude-sonnet-5/code): `anthropic/claude-sonnet-5`
    * [Structured Instruction](/development/comfy-router/models/bria/structured-instruction/code): `bria/structured-instruction`
    * [Seed 2.0 Lite 260228](/development/comfy-router/models/byteplus/seed-2-0-lite-260228/code): `byteplus/seed-2-0-lite-260228`
    * [Seed 2.0 Mini 260215](/development/comfy-router/models/byteplus/seed-2-0-mini-260215/code): `byteplus/seed-2-0-mini-260215`
    * [Seed 2.0 Pro 260328](/development/comfy-router/models/byteplus/seed-2-0-pro-260328/code): `byteplus/seed-2-0-pro-260328`
    * [Gemini Omni 1.1 Flash](/development/comfy-router/models/gemini-interactions/gemini-omni-1-1-flash/code): `gemini-interactions/gemini-omni-1.1-flash`
    * [Gemini Omni Flash Preview](/development/comfy-router/models/gemini-interactions/gemini-omni-flash-preview/code): `gemini-interactions/gemini-omni-flash-preview`
    * [Gemini 2.5 Flash Image](/development/comfy-router/models/google/gemini-2-5-flash-image/code): `vertexai/gemini-2.5-flash-image`
    * [Gemini 3.1 Flash Lite](/development/comfy-router/models/google/gemini-3-1-flash-lite/code): `vertexai/gemini-3.1-flash-lite`
    * [Gemini 3.7 Flash](/development/comfy-router/models/google/gemini-3-7-flash/code): `vertexai/gemini-3.7-flash`
    * [Gemini 3.8 Flash](/development/comfy-router/models/google/gemini-3-8-flash/code): `vertexai/gemini-3.8-flash`
    * [Google Gemini](/development/comfy-router/models/google/gemini/code): `vertexai/gemini-3.1-pro-preview`
    * [Nano Banana 2 Lite](/development/comfy-router/models/google/nano-banana-2-lite/code): `vertexai/gemini-3.1-flash-lite-image`
    * [Nano Banana 2](/development/comfy-router/models/google/nano-banana-2/code): `vertexai/gemini-3.1-flash-image`
    * [Nano Banana Pro](/development/comfy-router/models/google/nano-banana-pro/code): `vertexai/gemini-3-pro-image`
    * [GPT 4.1 Mini](/development/comfy-router/models/openai/gpt-4-1-mini/code): `openai/gpt-4.1-mini`
    * [GPT 4.1 Nano](/development/comfy-router/models/openai/gpt-4-1-nano/code): `openai/gpt-4.1-nano`
    * [GPT 4.1](/development/comfy-router/models/openai/gpt-4-1/code): `openai/gpt-4.1`
    * [GPT 4o](/development/comfy-router/models/openai/gpt-4o/code): `openai/gpt-4o`
    * [GPT 5.5 Pro](/development/comfy-router/models/openai/gpt-5-5-pro/code): `openai/gpt-5.5-pro`
    * [GPT 5.5](/development/comfy-router/models/openai/gpt-5-5/code): `openai/gpt-5.5`
    * [GPT 5.6 Luna](/development/comfy-router/models/openai/gpt-5-6-luna/code): `openai/gpt-5.6-luna`
    * [GPT 5.6 Sol](/development/comfy-router/models/openai/gpt-5-6-sol/code): `openai/gpt-5.6-sol`
    * [GPT 5.6 Terra](/development/comfy-router/models/openai/gpt-5-6-terra/code): `openai/gpt-5.6-terra`
    * [GPT 5 Mini](/development/comfy-router/models/openai/gpt-5-mini/code): `openai/gpt-5-mini`
    * [GPT 5 Nano](/development/comfy-router/models/openai/gpt-5-nano/code): `openai/gpt-5-nano`
    * [GPT 5](/development/comfy-router/models/openai/gpt-5/code): `openai/gpt-5`
    * [GPT 6 Astra](/development/comfy-router/models/openai/gpt-6-astra/code): `openai/gpt-6-astra`
    * [GPT 6 Luna](/development/comfy-router/models/openai/gpt-6-luna/code): `openai/gpt-6-luna`
    * [GPT 6 Sol](/development/comfy-router/models/openai/gpt-6-sol/code): `openai/gpt-6-sol`
    * [o1-pro](/development/comfy-router/models/openai/o1-pro/code): `openai/o1-pro`
    * [o1](/development/comfy-router/models/openai/o1/code): `openai/o1`
    * [o3](/development/comfy-router/models/openai/o3/code): `openai/o3`
    * [o4-mini](/development/comfy-router/models/openai/o4-mini/code): `openai/o4-mini`
    * [Chat Completions](/development/comfy-router/models/openrouter/chat-completions/code): `openrouter/chat-completions`
  </Accordion>
</AccordionGroup>

## Anthropic

| Model | ID | Input | Output |
| - | - | - | - |
| [Claude Fable 5.1](/development/comfy-router/models/anthropic/claude-fable-5-1/code) | `anthropic/claude-fable-5-1` | Text, Image | Text |
| [Claude Fable 5](/development/comfy-router/models/anthropic/claude-fable-5/code) | `anthropic/claude-fable-5` | Text, Image | Text |
| [Claude Haiku 4.5 20251001](/development/comfy-router/models/anthropic/claude-haiku-4-5-20251001/code) | `anthropic/claude-haiku-4-5-20251001` | Text, Image | Text |
| [Claude Opus 4.6](/development/comfy-router/models/anthropic/claude-opus-4-6/code) | `anthropic/claude-opus-4-6` | Text, Image | Text |
| [Claude Opus 4.7](/development/comfy-router/models/anthropic/claude-opus-4-7/code) | `anthropic/claude-opus-4-7` | Text, Image | Text |
| [Claude Opus 4.8](/development/comfy-router/models/anthropic/claude-opus-4-8/code) | `anthropic/claude-opus-4-8` | Text, Image | Text |
| [Claude Opus 5.5](/development/comfy-router/models/anthropic/claude-opus-5-5/code) | `anthropic/claude-opus-5-5` | Text, Image | Text |
| [Claude Opus 5](/development/comfy-router/models/anthropic/claude-opus-5/code) | `anthropic/claude-opus-5` | Text, Image | Text |
| [Claude Sonnet 4.5 20250929](/development/comfy-router/models/anthropic/claude-sonnet-4-5-20250929/code) | `anthropic/claude-sonnet-4-5-20250929` | Text, Image | Text |
| [Claude Sonnet 4.6](/development/comfy-router/models/anthropic/claude-sonnet-4-6/code) | `anthropic/claude-sonnet-4-6` | Text, Image | Text |
| [Claude Sonnet 5.5](/development/comfy-router/models/anthropic/claude-sonnet-5-5/code) | `anthropic/claude-sonnet-5-5` | Text, Image | Text |
| [Claude Sonnet 5](/development/comfy-router/models/anthropic/claude-sonnet-5/code) | `anthropic/claude-sonnet-5` | Text, Image | Text |

## Beeble

| Model | ID | Input | Output |
| - | - | - | - |
| [SwitchX](/development/comfy-router/models/beeble/switchx/code) | `beeble/switchx` | Image, Video, Text | Image + Video |

## Black Forest Labs

| Model | ID | Input | Output |
| - | - | - | - |
| [Erase V1](/development/comfy-router/models/black-forest-labs/erase-v1/code) | `bfl/erase-v1` | Image | Image |
| [Flux 1.1 Pro Ultra Image](/development/comfy-router/models/black-forest-labs/flux-1-1-pro-ultra-image/code) | `bfl/flux-pro-1.1-ultra` | Text, Image | Image |
| [FLUX.1 Kontext](/development/comfy-router/models/black-forest-labs/flux-1-kontext/code) | `bfl/flux-kontext-pro` | Image, Text | Image |
| [FLUX 2 Max](/development/comfy-router/models/black-forest-labs/flux-2-max/code) | `bfl/flux-2-max` | Text, Image | Image |
| [FLUX 2 Pro](/development/comfy-router/models/black-forest-labs/flux-2-pro/code) | `bfl/flux-2-pro` | Text, Image | Image |
| [FLUX 3 Image](/development/comfy-router/models/black-forest-labs/flux-3-image/code) | `bfl/flux-3-image` | Text, Image | Image |
| [FLUX 3 Video](/development/comfy-router/models/black-forest-labs/flux-3-video/code) | `bfl/flux-3-video` | Text, Image | Video + Audio |
| [FLUX Pro 1.0 Expand](/development/comfy-router/models/black-forest-labs/flux-pro-1-0-expand/code) | `bfl/flux-pro-1.0-expand` | Image, Text | Image |
| [FLUX Pro 1.0 Fill](/development/comfy-router/models/black-forest-labs/flux-pro-1-0-fill/code) | `bfl/flux-pro-1.0-fill` | Image, Text | Image |
| [FLUX Video Upscale](/development/comfy-router/models/black-forest-labs/flux-video-upscale/code) | `bfl/video-upscale-v1` | Video | Video |
| [Video Edit V1](/development/comfy-router/models/black-forest-labs/video-edit-v1/code) | `bfl/video-edit-v1` | Video, Text | Video |
| [VTO V1](/development/comfy-router/models/black-forest-labs/vto-v1/code) | `bfl/vto-v1` | Image | Image |

## Bria

| Model | ID | Input | Output |
| - | - | - | - |
| [Fibo](/development/comfy-router/models/bria/fibo/code) | `bria/fibo` | Image, Text | Image |
| [Image Edit Add Object By Text](/development/comfy-router/models/bria/image-edit-add-object-by-text/code) | `bria/image-edit-add-object-by-text` | Image, Text | Image |
| [Image Edit Erase By Text](/development/comfy-router/models/bria/image-edit-erase-by-text/code) | `bria/image-edit-erase-by-text` | Image, Text | Image |
| [Image Edit Erase Foreground](/development/comfy-router/models/bria/image-edit-erase-foreground/code) | `bria/image-edit-erase-foreground` | Image | Image |
| [Image Edit Erase](/development/comfy-router/models/bria/image-edit-erase/code) | `bria/image-edit-erase` | Image | Image |
| [Image Edit Expand](/development/comfy-router/models/bria/image-edit-expand/code) | `bria/image-edit-expand` | Image, Text | Image |
| [Image Edit Gen Fill](/development/comfy-router/models/bria/image-edit-gen-fill/code) | `bria/image-edit-gen-fill` | Image, Text | Image |
| [Image Edit Increase Resolution](/development/comfy-router/models/bria/image-edit-increase-resolution/code) | `bria/image-edit-increase-resolution` | Image | Image |
| [Image Edit Relight](/development/comfy-router/models/bria/image-edit-relight/code) | `bria/image-edit-relight` | Image, Text | Image |
| [Image Edit Remove Background](/development/comfy-router/models/bria/image-edit-remove-background/code) | `bria/image-edit-remove-background` | Image | Image |
| [Image Edit Replace Background](/development/comfy-router/models/bria/image-edit-replace-background/code) | `bria/image-edit-replace-background` | Image, Text | Image |
| [Image Edit Replace Object By Text](/development/comfy-router/models/bria/image-edit-replace-object-by-text/code) | `bria/image-edit-replace-object-by-text` | Image, Text | Image |
| [Image Edit Reseason](/development/comfy-router/models/bria/image-edit-reseason/code) | `bria/image-edit-reseason` | Image, Text | Image |
| [Image Edit Restore](/development/comfy-router/models/bria/image-edit-restore/code) | `bria/image-edit-restore` | Image | Image |
| [Structured Instruction](/development/comfy-router/models/bria/structured-instruction/code) | `bria/structured-instruction` | Image, Text | Text |
| [Video Edit Erase](/development/comfy-router/models/bria/video-edit-erase/code) | `bria/video-edit-erase` | Video | Video |
| [Video Edit Green Screen](/development/comfy-router/models/bria/video-edit-green-screen/code) | `bria/video-edit-green-screen` | Video | Video |
| [Video Edit Remove Background](/development/comfy-router/models/bria/video-edit-remove-background/code) | `bria/video-edit-remove-background` | Video | Video |
| [Video Edit Replace Background](/development/comfy-router/models/bria/video-edit-replace-background/code) | `bria/video-edit-replace-background` | Video, Text | Video |

## BytePlus

| Model | ID | Input | Output |
| - | - | - | - |
| [Dreamina Seedance 2.0 260128](/development/comfy-router/models/byteplus/dreamina-seedance-2-0-260128/code) | `byteplus/dreamina-seedance-2-0-260128` | Text, Image, Video, Audio | Video + Audio |
| [Dreamina Seedance 2.0 Fast 260128](/development/comfy-router/models/byteplus/dreamina-seedance-2-0-fast-260128/code) | `byteplus/dreamina-seedance-2-0-fast-260128` | Text, Image, Video, Audio | Video + Audio |
| [Dreamina Seedance 2.0 Mini](/development/comfy-router/models/byteplus/dreamina-seedance-2-0-mini/code) | `byteplus/dreamina-seedance-2-0-mini` | Text, Image, Video, Audio | Video + Audio |
| [Dreamina Seedance 2.5 260628](/development/comfy-router/models/byteplus/dreamina-seedance-2-5-260628/code) | `byteplus/dreamina-seedance-2-5-260628` | Text, Image, Video, Audio | Video + Audio |
| [Seed 2.0 Lite 260228](/development/comfy-router/models/byteplus/seed-2-0-lite-260228/code) | `byteplus/seed-2-0-lite-260228` | Text, Image | Text |
| [Seed 2.0 Mini 260215](/development/comfy-router/models/byteplus/seed-2-0-mini-260215/code) | `byteplus/seed-2-0-mini-260215` | Text, Image | Text |
| [Seed 2.0 Pro 260328](/development/comfy-router/models/byteplus/seed-2-0-pro-260328/code) | `byteplus/seed-2-0-pro-260328` | Text, Image | Text |
| [Seed Audio 1.0 Multilingual](/development/comfy-router/models/byteplus/seed-audio-1-0-multilingual/code) | `byteplus/seed-audio-1.0-multilingual` | Text | Audio |
| [Seed Audio 1.0](/development/comfy-router/models/byteplus/seed-audio-1-0/code) | `byteplus/seed-audio-1.0` | Text | Audio |
| [Seedance 1.0 Pro 250528](/development/comfy-router/models/byteplus/seedance-1-0-pro-250528/code) | `byteplus/seedance-1-0-pro-250528` | Text, Image | Video |
| [Seedance 1.0 Pro Fast 251015](/development/comfy-router/models/byteplus/seedance-1-0-pro-fast-251015/code) | `byteplus/seedance-1-0-pro-fast-251015` | Text, Image | Video |
| [Seedance 1.5 Pro 251215](/development/comfy-router/models/byteplus/seedance-1-5-pro-251215/code) | `byteplus/seedance-1-5-pro-251215` | Text, Image | Video + Audio |
| [Seedream 4.0 250828](/development/comfy-router/models/byteplus/seedream-4-0-250828/code) | `byteplus/seedream-4-0-250828` | Text, Image | Image |
| [Seedream 4.5 251128](/development/comfy-router/models/byteplus/seedream-4-5-251128/code) | `byteplus/seedream-4-5-251128` | Text, Image | Image |
| [Seedream 5.0 260128](/development/comfy-router/models/byteplus/seedream-5-0-260128/code) | `byteplus/seedream-5-0-260128` | Text, Image | Image |
| [Seedream 5.0 Flash 260915](/development/comfy-router/models/byteplus/seedream-5-0-flash-260915/code) | `byteplus/seedream-5-0-flash-260915` | Text, Image | Image |
| [Seedream 5.0 Pro 260628](/development/comfy-router/models/byteplus/seedream-5-0-pro-260628/code) | `byteplus/seedream-5-0-pro-260628` | Text, Image | Image |

## Elevenlabs

| Model | ID | Input | Output |
| - | - | - | - |
| [Eleven Sfx V2](/development/comfy-router/models/elevenlabs/eleven-sfx-v2/code) | `elevenlabs/eleven_sfx_v2` | Text | Audio |
| [Eleven V3](/development/comfy-router/models/elevenlabs/eleven-v3/code) | `elevenlabs/eleven_v3` | Text | Audio |
| [Eleven V4 Turbo](/development/comfy-router/models/elevenlabs/eleven-v4-turbo/code) | `elevenlabs/eleven_v4_turbo` | Text | Audio |
| [Eleven V4](/development/comfy-router/models/elevenlabs/eleven-v4/code) | `elevenlabs/eleven_v4` | Text | Audio |

## fal

| Model | ID | Input | Output |
| - | - | - | - |
| [H3 Max Turbo](/development/comfy-router/models/fal/h3-max-turbo/code) | `fal/h3-max-turbo` | Text, Image | Video + Audio |
| [H3 Max](/development/comfy-router/models/fal/h3-max/code) | `fal/h3-max` | Text, Image, Video, Audio | Video + Audio |
| [Patina](/development/comfy-router/models/fal/patina/code) | `fal/patina` | Image | Image |

## Freepik

| Model | ID | Input | Output |
| - | - | - | - |
| [AI Image Upscaler Precision V2](/development/comfy-router/models/freepik/ai-image-upscaler-precision-v2/code) | `freepik/ai-image-upscaler-precision-v2` | Image | Image |
| [AI Skin Enhancer Creative](/development/comfy-router/models/freepik/ai-skin-enhancer-creative/code) | `freepik/ai-skin-enhancer-creative` | Image | Image |
| [AI Skin Enhancer Faithful](/development/comfy-router/models/freepik/ai-skin-enhancer-faithful/code) | `freepik/ai-skin-enhancer-faithful` | Image | Image |
| [AI Skin Enhancer Flexible](/development/comfy-router/models/freepik/ai-skin-enhancer-flexible/code) | `freepik/ai-skin-enhancer-flexible` | Image | Image |

## Gemini Interactions

| Model | ID | Input | Output |
| - | - | - | - |
| [Gemini Omni 1.1 Flash](/development/comfy-router/models/gemini-interactions/gemini-omni-1-1-flash/code) | `gemini-interactions/gemini-omni-1.1-flash` | Text, Image, Audio, Video | Text + Image + Audio |
| [Gemini Omni Flash Preview](/development/comfy-router/models/gemini-interactions/gemini-omni-flash-preview/code) | `gemini-interactions/gemini-omni-flash-preview` | Text, Image, Audio, Video | Text + Image + Audio |

## Google

| Model | ID | Input | Output |
| - | - | - | - |
| [Gemini 2.5 Flash Image](/development/comfy-router/models/google/gemini-2-5-flash-image/code) | `vertexai/gemini-2.5-flash-image` | Text, Image | Image + Text |
| [Gemini 3.1 Flash Lite](/development/comfy-router/models/google/gemini-3-1-flash-lite/code) | `vertexai/gemini-3.1-flash-lite` | Text, Image, Audio, Video | Text |
| [Gemini 3.7 Flash](/development/comfy-router/models/google/gemini-3-7-flash/code) | `vertexai/gemini-3.7-flash` | Text, Image, Audio, Video | Text |
| [Gemini 3.8 Flash](/development/comfy-router/models/google/gemini-3-8-flash/code) | `vertexai/gemini-3.8-flash` | Text, Image, Audio, Video | Text |
| [Google Gemini](/development/comfy-router/models/google/gemini/code) | `vertexai/gemini-3.1-pro-preview` | Text, Image, Audio, Video | Text |
| [Imagen 3.0 Fast Generate 001](/development/comfy-router/models/google/imagen-3-0-fast-generate-001/code) | `vertexai/imagen-3.0-fast-generate-001` | Text | Image |
| [Imagen 3.0 Generate 001](/development/comfy-router/models/google/imagen-3-0-generate-001/code) | `vertexai/imagen-3.0-generate-001` | Text | Image |
| [Imagen 3.0 Generate 002](/development/comfy-router/models/google/imagen-3-0-generate-002/code) | `vertexai/imagen-3.0-generate-002` | Text | Image |
| [Nano Banana 2 Lite](/development/comfy-router/models/google/nano-banana-2-lite/code) | `vertexai/gemini-3.1-flash-lite-image` | Text, Image, Video | Image + Text |
| [Nano Banana 2](/development/comfy-router/models/google/nano-banana-2/code) | `vertexai/gemini-3.1-flash-image` | Text, Image, Video | Image + Text |
| [Nano Banana Pro](/development/comfy-router/models/google/nano-banana-pro/code) | `vertexai/gemini-3-pro-image` | Text, Image | Image + Text |

## HeyGen

| Model | ID | Input | Output |
| - | - | - | - |
| [Starfish](/development/comfy-router/models/heygen/starfish/code) | `heygen/starfish` | Text | Audio |

## Higgsfield

| Model | ID | Input | Output |
| - | - | - | - |
| [Higgsfield Kling 3.4k](/development/comfy-router/models/higgsfield/higgsfield-kling-3-4k/code) | `higgsfield/higgsfield-kling-3-4k` | Text | Video + Audio |
| [Higgsfield Kling 3 Pro](/development/comfy-router/models/higgsfield/higgsfield-kling-3-pro/code) | `higgsfield/higgsfield-kling-3-pro` | Text | Video + Audio |

## Ideogram

| Model | ID | Input | Output |
| - | - | - | - |
| [Ideogram 4.5](/development/comfy-router/models/ideogram/ideogram-4-5/code) | `ideogram/ideogram-4-5` | Text, Image | Image |
| [Ideogram V3](/development/comfy-router/models/ideogram/ideogram-v3/code) | `ideogram/ideogram-v3` | Text | Image |
| [Ideogram 4.0](/development/comfy-router/models/ideogram/ideogram-v4/code) | `ideogram/ideogram-v4` | Text | Image |
| [P Image Ideogram](/development/comfy-router/models/ideogram/p-image-ideogram/code) | `ideogram/p-image-ideogram` | Text | Image |

## Kling

| Model | ID | Input | Output |
| - | - | - | - |
| [Kling 3.0 Turbo](/development/comfy-router/models/kling/kling-3-0-turbo/code) | `kling/kling-3.0-turbo` | Text | Video |
| [Kling Image O1](/development/comfy-router/models/kling/kling-image-o1/code) | `kling/kling-image-o1` | Text, Image | Image |
| [Kling V2.5 Turbo](/development/comfy-router/models/kling/kling-v2-5-turbo/code) | `kling/kling-v2-5-turbo` | Text | Video |
| [Kling V2.6](/development/comfy-router/models/kling/kling-v2-6/code) | `kling/kling-v2-6` | Text | Video |
| [Kling V3 Omni](/development/comfy-router/models/kling/kling-v3-omni/code) | `kling/kling-v3-omni` | Text, Image, Video | Video |
| [Kling V3](/development/comfy-router/models/kling/kling-v3/code) | `kling/kling-v3` | Text | Video |
| [Kling Video O1](/development/comfy-router/models/kling/kling-video-o1/code) | `kling/kling-video-o1` | Text, Image, Video | Video |
| [Videos Avatar Image 2video](/development/comfy-router/models/kling/videos-avatar-image2video/code) | `kling/videos-avatar-image2video` | Image, Audio | Video |
| [Videos Lip Sync](/development/comfy-router/models/kling/videos-lip-sync/code) | `kling/videos-lip-sync` | Video, Audio | Video |
| [Videos Video Extend](/development/comfy-router/models/kling/videos-video-extend/code) | `kling/videos-video-extend` | Video, Text | Video |

## Krea

| Model | ID | Input | Output |
| - | - | - | - |
| [Krea 2 Large](/development/comfy-router/models/krea/krea-2-large/code) | `krea/krea-2-large` | Text | Image |
| [Krea 2 Medium Turbo](/development/comfy-router/models/krea/krea-2-medium-turbo/code) | `krea/krea-2-medium-turbo` | Text | Image |
| [Krea 2 Medium](/development/comfy-router/models/krea/krea-2-medium/code) | `krea/krea-2-medium` | Text | Image |
| [Krea 2](/development/comfy-router/models/krea/krea-2/code) | `krea/krea-2` | Text | Image |

## LTX

| Model | ID | Input | Output |
| - | - | - | - |
| [LTX 2.5 Fast](/development/comfy-router/models/ltx/ltx-2-5-fast/code) | `ltx/ltx-2-5-fast` | Text | Video + Audio |
| [LTX 2.5 Pro](/development/comfy-router/models/ltx/ltx-2-5-pro/code) | `ltx/ltx-2-5-pro` | Text | Video + Audio |

## Luma

| Model | ID | Input | Output |
| - | - | - | - |
| [Photon 1](/development/comfy-router/models/luma/photon-1/code) | `luma/photon-1` | Text | Image |
| [Photon Flash 1](/development/comfy-router/models/luma/photon-flash-1/code) | `luma/photon-flash-1` | Text | Image |
| [Ray 2](/development/comfy-router/models/luma/ray-2/code) | `luma/ray-2` | Text, Image | Video |
| [Ray Flash 2](/development/comfy-router/models/luma/ray-flash-2/code) | `luma/ray-flash-2` | Text, Image | Video |

## Luma 2

| Model | ID | Input | Output |
| - | - | - | - |
| [Uni 1 Max](/development/comfy-router/models/luma_2/uni-1-max/code) | `luma_2/uni-1-max` | Text, Image | Image |
| [Uni 1](/development/comfy-router/models/luma_2/uni-1/code) | `luma_2/uni-1` | Text, Image | Image |

## Meshy

| Model | ID | Input | Output |
| - | - | - | - |
| [Animations](/development/comfy-router/models/meshy/animations/code) | `meshy/animations` | 3D | 3D |
| [Meshy 5](/development/comfy-router/models/meshy/meshy-5/code) | `meshy/meshy-5` | Text | 3D |
| [Meshy 6](/development/comfy-router/models/meshy/meshy-6/code) | `meshy/meshy-6` | Text | 3D |
| [Meshy 7.1](/development/comfy-router/models/meshy/meshy-7-1/code) | `meshy/meshy-7.1` | Text | 3D |
| [Meshy 7](/development/comfy-router/models/meshy/meshy-7/code) | `meshy/meshy-7` | Text | 3D |
| [Remesh](/development/comfy-router/models/meshy/remesh/code) | `meshy/remesh` | 3D | 3D |
| [Rigging](/development/comfy-router/models/meshy/rigging/code) | `meshy/rigging` | 3D | 3D |

## MiniMax

| Model | ID | Input | Output |
| - | - | - | - |
| [MiniMax H3](/development/comfy-router/models/minimax/minimax-h3/code) | `minimax/minimax-h3` | Text, Image | Video + Audio |

## Moonvalley

| Model | ID | Input | Output |
| - | - | - | - |
| [Image To Video](/development/comfy-router/models/moonvalley/image-to-video/code) | `moonvalley/image-to-video` | Image, Text | Video |
| [Text To Image](/development/comfy-router/models/moonvalley/text-to-image/code) | `moonvalley/text-to-image` | Text | Image |
| [Text To Video](/development/comfy-router/models/moonvalley/text-to-video/code) | `moonvalley/text-to-video` | Text | Video |
| [Video To Video Resize](/development/comfy-router/models/moonvalley/video-to-video-resize/code) | `moonvalley/video-to-video-resize` | Video | Video |
| [Video To Video](/development/comfy-router/models/moonvalley/video-to-video/code) | `moonvalley/video-to-video` | Video, Text | Video |

## OpenAI

| Model | ID | Input | Output |
| - | - | - | - |
| [GPT 4.1 Mini](/development/comfy-router/models/openai/gpt-4-1-mini/code) | `openai/gpt-4.1-mini` | Text, Image | Text |
| [GPT 4.1 Nano](/development/comfy-router/models/openai/gpt-4-1-nano/code) | `openai/gpt-4.1-nano` | Text, Image | Text |
| [GPT 4.1](/development/comfy-router/models/openai/gpt-4-1/code) | `openai/gpt-4.1` | Text, Image | Text |
| [GPT 4o](/development/comfy-router/models/openai/gpt-4o/code) | `openai/gpt-4o` | Text, Image | Text |
| [GPT 5.5 Pro](/development/comfy-router/models/openai/gpt-5-5-pro/code) | `openai/gpt-5.5-pro` | Text, Image | Text |
| [GPT 5.5](/development/comfy-router/models/openai/gpt-5-5/code) | `openai/gpt-5.5` | Text, Image | Text |
| [GPT 5.6 Luna](/development/comfy-router/models/openai/gpt-5-6-luna/code) | `openai/gpt-5.6-luna` | Text, Image | Text |
| [GPT 5.6 Sol](/development/comfy-router/models/openai/gpt-5-6-sol/code) | `openai/gpt-5.6-sol` | Text, Image | Text |
| [GPT 5.6 Terra](/development/comfy-router/models/openai/gpt-5-6-terra/code) | `openai/gpt-5.6-terra` | Text, Image | Text |
| [GPT 5 Mini](/development/comfy-router/models/openai/gpt-5-mini/code) | `openai/gpt-5-mini` | Text, Image | Text |
| [GPT 5 Nano](/development/comfy-router/models/openai/gpt-5-nano/code) | `openai/gpt-5-nano` | Text, Image | Text |
| [GPT 5](/development/comfy-router/models/openai/gpt-5/code) | `openai/gpt-5` | Text, Image | Text |
| [GPT 6 Astra](/development/comfy-router/models/openai/gpt-6-astra/code) | `openai/gpt-6-astra` | Text, Image | Text |
| [GPT 6 Luna](/development/comfy-router/models/openai/gpt-6-luna/code) | `openai/gpt-6-luna` | Text, Image | Text |
| [GPT 6 Sol](/development/comfy-router/models/openai/gpt-6-sol/code) | `openai/gpt-6-sol` | Text, Image | Text |
| [GPT Image 1.5](/development/comfy-router/models/openai/gpt-image-1-5/code) | `openai/gpt-image-1.5` | Text, Image | Image |
| [GPT Image 1](/development/comfy-router/models/openai/gpt-image-1/code) | `openai/gpt-image-1` | Text, Image | Image |
| [GPT Image 2.5 Flare](/development/comfy-router/models/openai/gpt-image-2-5-flare/code) | `openai/gpt-image-2.5-flare` | Text, Image | Image |
| [GPT Image 2.5 Sunburst](/development/comfy-router/models/openai/gpt-image-2-5-sunburst/code) | `openai/gpt-image-2.5-sunburst` | Text, Image | Image |
| [GPT Image 2](/development/comfy-router/models/openai/gpt-image-2/code) | `openai/gpt-image-2` | Text, Image | Image |
| [o1-pro](/development/comfy-router/models/openai/o1-pro/code) | `openai/o1-pro` | Text, Image | Text |
| [o1](/development/comfy-router/models/openai/o1/code) | `openai/o1` | Text, Image | Text |
| [o3](/development/comfy-router/models/openai/o3/code) | `openai/o3` | Text, Image | Text |
| [o4-mini](/development/comfy-router/models/openai/o4-mini/code) | `openai/o4-mini` | Text, Image | Text |

## Openrouter

| Model | ID | Input | Output |
| - | - | - | - |
| [Chat Completions](/development/comfy-router/models/openrouter/chat-completions/code) | `openrouter/chat-completions` | Text, Image | Text |

## Pruna

| Model | ID | Input | Output |
| - | - | - | - |
| [P Video 2](/development/comfy-router/models/pruna/p-video-2/code) | `pruna/p-video-2` | Text, Image, Audio | Video + Audio |

## Qwen

| Model | ID | Input | Output |
| - | - | - | - |
| [Qwen Image 3.0 Pro](/development/comfy-router/models/qwen/qwen-image-3-0-pro/code) | `qwen/qwen-image-3.0-pro` | Text, Image | Image |
| [Qwen Image 3.0](/development/comfy-router/models/qwen/qwen-image-3-0/code) | `qwen/qwen-image-3.0` | Text, Image | Image |

## Recraft

| Model | ID | Input | Output |
| - | - | - | - |
| [Recraft V2](/development/comfy-router/models/recraft/recraftv2/code) | `recraft/recraftv2` | Text | Image |
| [Recraft V3](/development/comfy-router/models/recraft/recraftv3/code) | `recraft/recraftv3` | Text | Image |
| [Recraft V4.1 Pro Vector](/development/comfy-router/models/recraft/recraftv4-1-pro-vector/code) | `recraft/recraftv4_1_pro_vector` | Text | Image |
| [Recraft V4.1 Pro](/development/comfy-router/models/recraft/recraftv4-1-pro/code) | `recraft/recraftv4_1_pro` | Text | Image |
| [Recraft V4.1 Utility Pro Vector](/development/comfy-router/models/recraft/recraftv4-1-utility-pro-vector/code) | `recraft/recraftv4_1_utility_pro_vector` | Text | Image |
| [Recraft V4.1 Utility Pro](/development/comfy-router/models/recraft/recraftv4-1-utility-pro/code) | `recraft/recraftv4_1_utility_pro` | Text | Image |
| [Recraft V4.1 Utility Vector](/development/comfy-router/models/recraft/recraftv4-1-utility-vector/code) | `recraft/recraftv4_1_utility_vector` | Text | Image |
| [Recraft V4.1 Utility](/development/comfy-router/models/recraft/recraftv4-1-utility/code) | `recraft/recraftv4_1_utility` | Text | Image |
| [Recraft V4.1 Vector](/development/comfy-router/models/recraft/recraftv4-1-vector/code) | `recraft/recraftv4_1_vector` | Text | Image |
| [Recraft V4.1](/development/comfy-router/models/recraft/recraftv4-1/code) | `recraft/recraftv4_1` | Text | Image |
| [Recraft V4 Pro](/development/comfy-router/models/recraft/recraftv4-pro/code) | `recraft/recraftv4_pro` | Text | Image |
| [Recraft V4 Styles Pro Vector](/development/comfy-router/models/recraft/recraftv4-styles-pro-vector/code) | `recraft/recraftv4_styles_pro_vector` | Text | Image |
| [Recraft V4 Styles Pro](/development/comfy-router/models/recraft/recraftv4-styles-pro/code) | `recraft/recraftv4_styles_pro` | Text | Image |
| [Recraft V4 Styles Vector](/development/comfy-router/models/recraft/recraftv4-styles-vector/code) | `recraft/recraftv4_styles_vector` | Text | Image |
| [Recraft V4 Styles](/development/comfy-router/models/recraft/recraftv4-styles/code) | `recraft/recraftv4_styles` | Text | Image |
| [Recraft V4](/development/comfy-router/models/recraft/recraftv4/code) | `recraft/recraftv4` | Text | Image |

## Runway

| Model | ID | Input | Output |
| - | - | - | - |
| [Aleph 2](/development/comfy-router/models/runway/aleph2/code) | `runway/aleph2` | Video, Text, Image | Video |
| [Gen 4 Image](/development/comfy-router/models/runway/gen4-image/code) | `runway/gen4_image` | Text, Image | Image |
| [Gen 4 Turbo](/development/comfy-router/models/runway/gen4-turbo/code) | `runway/gen4_turbo` | Image, Text | Video |

## Synclabs

| Model | ID | Input | Output |
| - | - | - | - |
| [Sync 3](/development/comfy-router/models/synclabs/sync-3/code) | `synclabs/sync-3` | Video, Image, Audio, Text | Video |

## Tencent

| Model | ID | Input | Output |
| - | - | - | - |
| [Hunyuan 3D Part](/development/comfy-router/models/tencent/hunyuan-3d-part/code) | `tencent/hunyuan-3d-part` | 3D | 3D |
| [Hunyuan 3D Smart Topology](/development/comfy-router/models/tencent/hunyuan-3d-smart-topology/code) | `tencent/hunyuan-3d-smart-topology` | 3D | 3D |
| [Hunyuan 3D Texture Edit](/development/comfy-router/models/tencent/hunyuan-3d-texture-edit/code) | `tencent/hunyuan-3d-texture-edit` | 3D, Text | 3D |
| [Hunyuan 3D Uv](/development/comfy-router/models/tencent/hunyuan-3d-uv/code) | `tencent/hunyuan-3d-uv` | 3D | 3D |

## Veo

| Model | ID | Input | Output |
| - | - | - | - |
| [Veo 3.1 Fast Generate 001](/development/comfy-router/models/veo/veo-3-1-fast-generate-001/code) | `veo/veo-3.1-fast-generate-001` | Text, Image, Video | Video + Audio |
| [Veo 3.1 Generate 001](/development/comfy-router/models/veo/veo-3-1-generate-001/code) | `veo/veo-3.1-generate-001` | Text, Image, Video | Video + Audio |
| [Veo 3.1 Lite Generate 001](/development/comfy-router/models/veo/veo-3-1-lite-generate-001/code) | `veo/veo-3.1-lite-generate-001` | Text, Image, Video | Video + Audio |

## Wan

| Model | ID | Input | Output |
| - | - | - | - |
| [HappyHorse 1.0 I2V](/development/comfy-router/models/wan/happyhorse-1-0-i2v/code) | `wan/happyhorse-1.0-i2v` | Image, Text | Video |
| [HappyHorse 1.0 R2V](/development/comfy-router/models/wan/happyhorse-1-0-r2v/code) | `wan/happyhorse-1.0-r2v` | Image, Text | Video |
| [HappyHorse 1.0 T2V](/development/comfy-router/models/wan/happyhorse-1-0-t2v/code) | `wan/happyhorse-1.0-t2v` | Text | Video |
| [HappyHorse 1.0 Video Edit](/development/comfy-router/models/wan/happyhorse-1-0-video-edit/code) | `wan/happyhorse-1.0-video-edit` | Video, Image, Text | Video |
| [HappyHorse 1.1 I2V](/development/comfy-router/models/wan/happyhorse-1-1-i2v/code) | `wan/happyhorse-1.1-i2v` | Image, Text | Video |
| [HappyHorse 1.1 R2V](/development/comfy-router/models/wan/happyhorse-1-1-r2v/code) | `wan/happyhorse-1.1-r2v` | Image, Text | Video |
| [HappyHorse 1.1 T2V](/development/comfy-router/models/wan/happyhorse-1-1-t2v/code) | `wan/happyhorse-1.1-t2v` | Text | Video |
| [Wan 2.5 I2I Preview](/development/comfy-router/models/wan/wan2-5-i2i-preview/code) | `wan/wan2.5-i2i-preview` | Image, Text | Image |
| [Wan 2.5 I2V Preview](/development/comfy-router/models/wan/wan2-5-i2v-preview/code) | `wan/wan2.5-i2v-preview` | Image, Audio, Text | Video + Audio |
| [Wan 2.5 T2I Preview](/development/comfy-router/models/wan/wan2-5-t2i-preview/code) | `wan/wan2.5-t2i-preview` | Text | Image |
| [Wan 2.5 T2V Preview](/development/comfy-router/models/wan/wan2-5-t2v-preview/code) | `wan/wan2.5-t2v-preview` | Audio, Text | Video + Audio |
| [Wan 2.6 I2V](/development/comfy-router/models/wan/wan2-6-i2v/code) | `wan/wan2.6-i2v` | Image, Audio, Text | Video + Audio |
| [Wan 2.6 R2V](/development/comfy-router/models/wan/wan2-6-r2v/code) | `wan/wan2.6-r2v` | Image, Video, Text | Video + Audio |
| [Wan 2.6 T2V](/development/comfy-router/models/wan/wan2-6-t2v/code) | `wan/wan2.6-t2v` | Audio, Text | Video + Audio |
| [Wan 2.7 I2V](/development/comfy-router/models/wan/wan2-7-i2v/code) | `wan/wan2.7-i2v` | Image, Video, Audio, Text | Video + Audio |
| [Wan 2.7 R2V](/development/comfy-router/models/wan/wan2-7-r2v/code) | `wan/wan2.7-r2v` | Image, Video, Text | Video |
| [Wan 2.7 T2V](/development/comfy-router/models/wan/wan2-7-t2v/code) | `wan/wan2.7-t2v` | Text | Video + Audio |
| [Wan 2.7 Video Edit](/development/comfy-router/models/wan/wan2-7-videoedit/code) | `wan/wan2.7-videoedit` | Video, Image, Text | Video |
| [Wan 3.0 Video Prime](/development/comfy-router/models/wan/wan3-0-video-prime/code) | `wan/wan3.0-video-prime` | Text, Image, Video, Audio | Video + Audio |
| [Wan 3.0 Video](/development/comfy-router/models/wan/wan3-0-video/code) | `wan/wan3.0-video` | Text, Image, Video, Audio | Video + Audio |

## WaveSpeed

| Model | ID | Input | Output |
| - | - | - | - |
| [Flashvsr](/development/comfy-router/models/wavespeed/flashvsr/code) | `wavespeed/flashvsr` | Video | Video |
| [Seedvr 2](/development/comfy-router/models/wavespeed/seedvr2/code) | `wavespeed/seedvr2` | Image | Image |
| [Ultimate Image Upscaler](/development/comfy-router/models/wavespeed/ultimate-image-upscaler/code) | `wavespeed/ultimate-image-upscaler` | Image | Image |

## xAI

| Model | ID | Input | Output |
| - | - | - | - |
| [Grok Imagine Image 2.0](/development/comfy-router/models/xai/grok-imagine-image-2-0/code) | `xai/grok-imagine-image-2.0` | Text | Image |
| [Grok Imagine Image Pro](/development/comfy-router/models/xai/grok-imagine-image-pro/code) | `xai/grok-imagine-image-pro` | Text | Image |
| [Grok Imagine Image Quality](/development/comfy-router/models/xai/grok-imagine-image-quality/code) | `xai/grok-imagine-image-quality` | Text | Image |
| [Grok Imagine Image](/development/comfy-router/models/xai/grok-imagine-image/code) | `xai/grok-imagine-image` | Text | Image |
| [Grok Imagine Video 1.5 Lite](/development/comfy-router/models/xai/grok-imagine-video-1-5-lite/code) | `xai/grok-imagine-video-1.5-lite` | Text, Image | Video |
| [Grok Imagine Video 1.5 Preview](/development/comfy-router/models/xai/grok-imagine-video-1-5-preview/code) | `xai/grok-imagine-video-1.5-preview` | Text, Image | Video |
| [Grok Imagine Video 1.5](/development/comfy-router/models/xai/grok-imagine-video-1-5/code) | `xai/grok-imagine-video-1.5` | Text, Image | Video |
| [Grok Imagine Video](/development/comfy-router/models/xai/grok-imagine-video/code) | `xai/grok-imagine-video` | Text, Image | Video |


# Use Claude Fable 5.1 with Comfy Router
Source: https://docs.comfy.org/development/comfy-router/models/anthropic/claude-fable-5-1/code

Call anthropic/claude-fable-5-1 through Comfy Router: endpoint, request shape and the response Router returns.

API Reference for `anthropic/claude-fable-5-1`, served by Comfy Router from Anthropic.

**Input:** Text, Image · **Output:** Text

## Quick start

Create a key in [your Comfy workspace](https://platform.comfy.org/profile/api-keys?onboarding=router) and export it as `COMFY_API_KEY`. The Python and TypeScript snippets use the Comfy SDKs (`pip install comfy-sdk` and `npm install @comfyorg/sdk`); the cURL snippet is the same call over raw HTTP.

**Model ID:** `anthropic/claude-fable-5-1`

**Endpoint:** `POST https://api.comfy.org/v2/models/anthropic/claude-fable-5-1`

<Tabs>
  <Tab title="Wait for the result">
    <CodeGroup>
      ```python Python theme={null}
      from comfy_sdk import Comfy

      # Reads COMFY_API_KEY from the environment.
      # The SDK automatically creates an idempotency key and reuses it for automatic retries.
      with Comfy() as client:
          result = client.models.run(
              "anthropic/claude-fable-5-1",
              {
                  "max_tokens": 16,
                  "messages": [
                      {
                          "content": "Reply with the single word: ok",
                          "role": "user",
                      },
                  ],
              },
          )

      print(result)
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // The SDK automatically creates an idempotency key and reuses it for automatic retries.
      const { data } = await comfy.models.run("anthropic/claude-fable-5-1", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });

      console.log(data);
      ```

      ```bash cURL theme={null}
      curl https://api.comfy.org/v2/models/anthropic/claude-fable-5-1 \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"
      ```
    </CodeGroup>
  </Tab>

  <Tab title="Queue and collect later">
    The same body, sent to `POST https://api.comfy.org/v2/models/anthropic/claude-fable-5-1/requests`. Router answers `201` with a `request_id` as soon as the run is admitted, and the result is collected once it is ready, from this process or another one. [Queued delivery](/development/comfy-router/queue) walks through status, cancellation and collection.

    <CodeGroup>
      ```python Python theme={null}
      import asyncio
      from comfy_sdk import AsyncComfy

      # Reads COMFY_API_KEY from the environment.
      # Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      async def main():
          async with AsyncComfy() as client:
              handle = await client.models.submit(
                  "anthropic/claude-fable-5-1",
                  {
                      "max_tokens": 16,
                      "messages": [
                          {
                              "content": "Reply with the single word: ok",
                              "role": "user",
                          },
                      ],
                  },
              )
              print("request_id:", handle.request_id)  # with the model ID, all another process needs

              # Poll until the request completes, waiting the Retry-After the server names.
              async for update in handle.iter_events():
                  print(update.status, update.queue_position)

              # The provider's own payload, the same value models.run() returns.
              # A request that failed or was cancelled raises the typed Router error here.
              result = await handle.get()

          print(result)

      asyncio.run(main())
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      const handle = await comfy.models.submit("anthropic/claude-fable-5-1", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });
      console.log("requestId:", handle.requestId); // with the model ID, all another process needs

      // Poll until the request completes, waiting the Retry-After the server names.
      for await (const update of handle.events()) {
        console.log(update.status, update.queuePosition);
      }

      // The same result models.run() returns. A request that failed or was cancelled rejects here.
      const result = await handle.get();

      console.log(result.data);
      ```

      ```bash cURL theme={null}
      # 1. Submit. Router answers 201 with request_id, status_url, response_url and cancel_url.
      curl https://api.comfy.org/v2/models/anthropic/claude-fable-5-1/requests \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"

      # 2. Poll until status is COMPLETED, waiting the Retry-After seconds each response names.
      REQUEST_ID="<request_id from the 201 body>"
      curl -i https://api.comfy.org/v2/models/anthropic/claude-fable-5-1/requests/$REQUEST_ID/status \
        -H "X-API-Key: $COMFY_API_KEY"

      # 3. Collect. 200 with the model's native output, 202 with the status body while it is still running.
      curl https://api.comfy.org/v2/models/anthropic/claude-fable-5-1/requests/$REQUEST_ID \
        -H "X-API-Key: $COMFY_API_KEY"
      ```
    </CodeGroup>
  </Tab>
</Tabs>

## Schema

### Input

<ParamField type="integer">
  Maximum number of tokens to generate before stopping.
</ParamField>

<ParamField type="object[]">
  Conversation turns. See Anthropic Messages API docs for the full content-block taxonomy.
</ParamField>

<ParamField type="object">
  Either a string shorthand or an array of content blocks (text, image, document, tool\_use, tool\_result, ...).
</ParamField>

<ParamField type="string">
  Possible values: `user`, `assistant`
</ParamField>

<ParamField type="string">
  Anthropic model identifier (e.g. `claude-sonnet-4-5`, `claude-opus-4-7`).
</ParamField>

<ParamField type="boolean">
  When true, the response is a `text/event-stream` of Anthropic message events instead of a single JSON body.
</ParamField>

<ParamField type="object">
  Top-level system prompt. Either a string or an array of content blocks; both reach Anthropic unchanged.
</ParamField>

Generated from the schema Router serves at `GET /v2/models/anthropic/claude-fable-5-1/openapi.json`, the same document it validates a call against before the request reaches the provider.

### Output

<ResponseField name="id" type="string" />

<ResponseField name="model" type="string" />

<ResponseField name="role" type="string" />

<ResponseField name="stop_reason" type="string" />

<ResponseField name="stop_sequence" type="string" />

<ResponseField name="type" type="string" />

<ResponseField name="usage" type="object">
  Token usage for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation" type="object">
  Per-TTL breakdown of cache-write input tokens for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation.ephemeral_1h_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation.ephemeral_5m_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation_input_tokens" type="integer" />

<ResponseField name="usage.cache_read_input_tokens" type="integer" />

<ResponseField name="usage.input_tokens" type="integer" />

<ResponseField name="usage.output_tokens" type="integer" />

<ResponseField name="content" type="object[]">
  The reply's content blocks, in order. Present on every completed message; empty when the turn produced nothing.
</ResponseField>

<ResponseField name="content[].text" type="string">
  The block's text. Present on `text` blocks and absent on every other kind.
</ResponseField>

<ResponseField name="content[].type" type="string">
  The block kind. `text` is the one that carries `text`; `thinking`, `redacted_thinking`, `tool_use`, `server_tool_use` and the tool-result blocks are the others Anthropic sends today, and the list is open.
</ResponseField>

## Examples

### Input

```json theme={null}
{
  "max_tokens": 16,
  "messages": [
    {
      "content": "Reply with the single word: ok",
      "role": "user"
    }
  ]
}
```

### Output

```json theme={null}
{
  "content": [
    {
      "text": "ok",
      "type": "text"
    }
  ],
  "id": "msg_01ExampleInvalidPlaceholder",
  "model": "claude-fable-5-1",
  "role": "assistant",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "type": "message",
  "usage": {
    "input_tokens": 16,
    "output_tokens": 3
  }
}
```

## Before you ship

The SDKs create an `Idempotency-Key` and reuse it for automatic retries. For manual retries, reuse the original key. Router can hold the connection for up to 10 minutes.

When a request fails, Router sends an `X-Comfy-Error-Type` response header explaining why. A `422` means Router rejected the input before calling the provider, and a `413` means the request body was larger than Router accepts. Download generated assets promptly because [result URLs can expire](/development/comfy-router/reference#result-assets).

Any size limit named in a field description above is the provider's own bound on that field, quoted from the provider's specification. Router applies a separate cap to the whole request body, which base64-encoded media counts against: see [request body size](/development/comfy-router/limitations#request-bodies-are-capped).

This page documents one partner model called through Comfy Router. The same `comfy-sdk` / `@comfyorg/sdk` package also ships a second client, for running a whole ComfyUI workflow graph on Comfy Cloud: `Comfy(api_key=...)` / `new Comfy({ apiKey })`, with `client.workflows`, `client.assets` and `client.jobs`. See [Comfy SDKs](/development/api-development/sdks).

<CardGroup>
  <Card title="Headers" icon="list" href="/development/comfy-router/headers">
    Authentication, idempotency, request IDs, error buckets, retry pacing, spend limits.
  </Card>

  <Card title="Using the Router API" icon="code" href="/development/comfy-router/api">
    Model discovery, validation errors, retries, and billing.
  </Card>

  <Card title="Limitations" icon="triangle-exclamation" href="/development/comfy-router/limitations">
    What Router does not do today, and what to use instead.
  </Card>
</CardGroup>


# Use Claude Fable 5 with Comfy Router
Source: https://docs.comfy.org/development/comfy-router/models/anthropic/claude-fable-5/code

Call anthropic/claude-fable-5 through Comfy Router: endpoint, request shape and the response Router returns.

API Reference for `anthropic/claude-fable-5`, served by Comfy Router from Anthropic.

**Input:** Text, Image · **Output:** Text

## Quick start

Create a key in [your Comfy workspace](https://platform.comfy.org/profile/api-keys?onboarding=router) and export it as `COMFY_API_KEY`. The Python and TypeScript snippets use the Comfy SDKs (`pip install comfy-sdk` and `npm install @comfyorg/sdk`); the cURL snippet is the same call over raw HTTP.

**Model ID:** `anthropic/claude-fable-5`

**Endpoint:** `POST https://api.comfy.org/v2/models/anthropic/claude-fable-5`

<Tabs>
  <Tab title="Wait for the result">
    <CodeGroup>
      ```python Python theme={null}
      from comfy_sdk import Comfy

      # Reads COMFY_API_KEY from the environment.
      # The SDK automatically creates an idempotency key and reuses it for automatic retries.
      with Comfy() as client:
          result = client.models.run(
              "anthropic/claude-fable-5",
              {
                  "max_tokens": 16,
                  "messages": [
                      {
                          "content": "Reply with the single word: ok",
                          "role": "user",
                      },
                  ],
              },
          )

      print(result)
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // The SDK automatically creates an idempotency key and reuses it for automatic retries.
      const { data } = await comfy.models.run("anthropic/claude-fable-5", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });

      console.log(data);
      ```

      ```bash cURL theme={null}
      curl https://api.comfy.org/v2/models/anthropic/claude-fable-5 \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"
      ```
    </CodeGroup>
  </Tab>

  <Tab title="Queue and collect later">
    The same body, sent to `POST https://api.comfy.org/v2/models/anthropic/claude-fable-5/requests`. Router answers `201` with a `request_id` as soon as the run is admitted, and the result is collected once it is ready, from this process or another one. [Queued delivery](/development/comfy-router/queue) walks through status, cancellation and collection.

    <CodeGroup>
      ```python Python theme={null}
      import asyncio
      from comfy_sdk import AsyncComfy

      # Reads COMFY_API_KEY from the environment.
      # Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      async def main():
          async with AsyncComfy() as client:
              handle = await client.models.submit(
                  "anthropic/claude-fable-5",
                  {
                      "max_tokens": 16,
                      "messages": [
                          {
                              "content": "Reply with the single word: ok",
                              "role": "user",
                          },
                      ],
                  },
              )
              print("request_id:", handle.request_id)  # with the model ID, all another process needs

              # Poll until the request completes, waiting the Retry-After the server names.
              async for update in handle.iter_events():
                  print(update.status, update.queue_position)

              # The provider's own payload, the same value models.run() returns.
              # A request that failed or was cancelled raises the typed Router error here.
              result = await handle.get()

          print(result)

      asyncio.run(main())
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      const handle = await comfy.models.submit("anthropic/claude-fable-5", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });
      console.log("requestId:", handle.requestId); // with the model ID, all another process needs

      // Poll until the request completes, waiting the Retry-After the server names.
      for await (const update of handle.events()) {
        console.log(update.status, update.queuePosition);
      }

      // The same result models.run() returns. A request that failed or was cancelled rejects here.
      const result = await handle.get();

      console.log(result.data);
      ```

      ```bash cURL theme={null}
      # 1. Submit. Router answers 201 with request_id, status_url, response_url and cancel_url.
      curl https://api.comfy.org/v2/models/anthropic/claude-fable-5/requests \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"

      # 2. Poll until status is COMPLETED, waiting the Retry-After seconds each response names.
      REQUEST_ID="<request_id from the 201 body>"
      curl -i https://api.comfy.org/v2/models/anthropic/claude-fable-5/requests/$REQUEST_ID/status \
        -H "X-API-Key: $COMFY_API_KEY"

      # 3. Collect. 200 with the model's native output, 202 with the status body while it is still running.
      curl https://api.comfy.org/v2/models/anthropic/claude-fable-5/requests/$REQUEST_ID \
        -H "X-API-Key: $COMFY_API_KEY"
      ```
    </CodeGroup>
  </Tab>
</Tabs>

## Schema

### Input

<ParamField type="integer">
  Maximum number of tokens to generate before stopping.
</ParamField>

<ParamField type="object[]">
  Conversation turns. See Anthropic Messages API docs for the full content-block taxonomy.
</ParamField>

<ParamField type="object">
  Either a string shorthand or an array of content blocks (text, image, document, tool\_use, tool\_result, ...).
</ParamField>

<ParamField type="string">
  Possible values: `user`, `assistant`
</ParamField>

<ParamField type="string">
  Anthropic model identifier (e.g. `claude-sonnet-4-5`, `claude-opus-4-7`).
</ParamField>

<ParamField type="boolean">
  When true, the response is a `text/event-stream` of Anthropic message events instead of a single JSON body.
</ParamField>

<ParamField type="object">
  Top-level system prompt. Either a string or an array of content blocks; both reach Anthropic unchanged.
</ParamField>

Generated from the schema Router serves at `GET /v2/models/anthropic/claude-fable-5/openapi.json`, the same document it validates a call against before the request reaches the provider.

### Output

<ResponseField name="id" type="string" />

<ResponseField name="model" type="string" />

<ResponseField name="role" type="string" />

<ResponseField name="stop_reason" type="string" />

<ResponseField name="stop_sequence" type="string" />

<ResponseField name="type" type="string" />

<ResponseField name="usage" type="object">
  Token usage for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation" type="object">
  Per-TTL breakdown of cache-write input tokens for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation.ephemeral_1h_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation.ephemeral_5m_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation_input_tokens" type="integer" />

<ResponseField name="usage.cache_read_input_tokens" type="integer" />

<ResponseField name="usage.input_tokens" type="integer" />

<ResponseField name="usage.output_tokens" type="integer" />

<ResponseField name="content" type="object[]">
  The reply's content blocks, in order. Present on every completed message; empty when the turn produced nothing.
</ResponseField>

<ResponseField name="content[].text" type="string">
  The block's text. Present on `text` blocks and absent on every other kind.
</ResponseField>

<ResponseField name="content[].type" type="string">
  The block kind. `text` is the one that carries `text`; `thinking`, `redacted_thinking`, `tool_use`, `server_tool_use` and the tool-result blocks are the others Anthropic sends today, and the list is open.
</ResponseField>

## Examples

### Input

```json theme={null}
{
  "max_tokens": 16,
  "messages": [
    {
      "content": "Reply with the single word: ok",
      "role": "user"
    }
  ]
}
```

### Output

```json theme={null}
{
  "content": [
    {
      "text": "ok",
      "type": "text"
    }
  ],
  "id": "msg_01ExampleInvalidPlaceholder",
  "model": "claude-fable-5",
  "role": "assistant",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "type": "message",
  "usage": {
    "input_tokens": 16,
    "output_tokens": 3
  }
}
```

## Before you ship

The SDKs create an `Idempotency-Key` and reuse it for automatic retries. For manual retries, reuse the original key. Router can hold the connection for up to 10 minutes.

When a request fails, Router sends an `X-Comfy-Error-Type` response header explaining why. A `422` means Router rejected the input before calling the provider, and a `413` means the request body was larger than Router accepts. Download generated assets promptly because [result URLs can expire](/development/comfy-router/reference#result-assets).

Any size limit named in a field description above is the provider's own bound on that field, quoted from the provider's specification. Router applies a separate cap to the whole request body, which base64-encoded media counts against: see [request body size](/development/comfy-router/limitations#request-bodies-are-capped).

This page documents one partner model called through Comfy Router. The same `comfy-sdk` / `@comfyorg/sdk` package also ships a second client, for running a whole ComfyUI workflow graph on Comfy Cloud: `Comfy(api_key=...)` / `new Comfy({ apiKey })`, with `client.workflows`, `client.assets` and `client.jobs`. See [Comfy SDKs](/development/api-development/sdks).

<CardGroup>
  <Card title="Headers" icon="list" href="/development/comfy-router/headers">
    Authentication, idempotency, request IDs, error buckets, retry pacing, spend limits.
  </Card>

  <Card title="Using the Router API" icon="code" href="/development/comfy-router/api">
    Model discovery, validation errors, retries, and billing.
  </Card>

  <Card title="Limitations" icon="triangle-exclamation" href="/development/comfy-router/limitations">
    What Router does not do today, and what to use instead.
  </Card>
</CardGroup>


# Use Claude Haiku 4.5 20251001 with Comfy Router
Source: https://docs.comfy.org/development/comfy-router/models/anthropic/claude-haiku-4-5-20251001/code

Call anthropic/claude-haiku-4-5-20251001 through Comfy Router: endpoint, request shape and the response Router returns.

API Reference for `anthropic/claude-haiku-4-5-20251001`, served by Comfy Router from Anthropic.

**Input:** Text, Image · **Output:** Text

## Quick start

Create a key in [your Comfy workspace](https://platform.comfy.org/profile/api-keys?onboarding=router) and export it as `COMFY_API_KEY`. The Python and TypeScript snippets use the Comfy SDKs (`pip install comfy-sdk` and `npm install @comfyorg/sdk`); the cURL snippet is the same call over raw HTTP.

**Model ID:** `anthropic/claude-haiku-4-5-20251001`

**Endpoint:** `POST https://api.comfy.org/v2/models/anthropic/claude-haiku-4-5-20251001`

<Tabs>
  <Tab title="Wait for the result">
    <CodeGroup>
      ```python Python theme={null}
      from comfy_sdk import Comfy

      # Reads COMFY_API_KEY from the environment.
      # The SDK automatically creates an idempotency key and reuses it for automatic retries.
      with Comfy() as client:
          result = client.models.run(
              "anthropic/claude-haiku-4-5-20251001",
              {
                  "max_tokens": 16,
                  "messages": [
                      {
                          "content": "Reply with the single word: ok",
                          "role": "user",
                      },
                  ],
              },
          )

      print(result)
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // The SDK automatically creates an idempotency key and reuses it for automatic retries.
      const { data } = await comfy.models.run("anthropic/claude-haiku-4-5-20251001", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });

      console.log(data);
      ```

      ```bash cURL theme={null}
      curl https://api.comfy.org/v2/models/anthropic/claude-haiku-4-5-20251001 \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"
      ```
    </CodeGroup>
  </Tab>

  <Tab title="Queue and collect later">
    The same body, sent to `POST https://api.comfy.org/v2/models/anthropic/claude-haiku-4-5-20251001/requests`. Router answers `201` with a `request_id` as soon as the run is admitted, and the result is collected once it is ready, from this process or another one. [Queued delivery](/development/comfy-router/queue) walks through status, cancellation and collection.

    <CodeGroup>
      ```python Python theme={null}
      import asyncio
      from comfy_sdk import AsyncComfy

      # Reads COMFY_API_KEY from the environment.
      # Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      async def main():
          async with AsyncComfy() as client:
              handle = await client.models.submit(
                  "anthropic/claude-haiku-4-5-20251001",
                  {
                      "max_tokens": 16,
                      "messages": [
                          {
                              "content": "Reply with the single word: ok",
                              "role": "user",
                          },
                      ],
                  },
              )
              print("request_id:", handle.request_id)  # with the model ID, all another process needs

              # Poll until the request completes, waiting the Retry-After the server names.
              async for update in handle.iter_events():
                  print(update.status, update.queue_position)

              # The provider's own payload, the same value models.run() returns.
              # A request that failed or was cancelled raises the typed Router error here.
              result = await handle.get()

          print(result)

      asyncio.run(main())
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      const handle = await comfy.models.submit("anthropic/claude-haiku-4-5-20251001", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });
      console.log("requestId:", handle.requestId); // with the model ID, all another process needs

      // Poll until the request completes, waiting the Retry-After the server names.
      for await (const update of handle.events()) {
        console.log(update.status, update.queuePosition);
      }

      // The same result models.run() returns. A request that failed or was cancelled rejects here.
      const result = await handle.get();

      console.log(result.data);
      ```

      ```bash cURL theme={null}
      # 1. Submit. Router answers 201 with request_id, status_url, response_url and cancel_url.
      curl https://api.comfy.org/v2/models/anthropic/claude-haiku-4-5-20251001/requests \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"

      # 2. Poll until status is COMPLETED, waiting the Retry-After seconds each response names.
      REQUEST_ID="<request_id from the 201 body>"
      curl -i https://api.comfy.org/v2/models/anthropic/claude-haiku-4-5-20251001/requests/$REQUEST_ID/status \
        -H "X-API-Key: $COMFY_API_KEY"

      # 3. Collect. 200 with the model's native output, 202 with the status body while it is still running.
      curl https://api.comfy.org/v2/models/anthropic/claude-haiku-4-5-20251001/requests/$REQUEST_ID \
        -H "X-API-Key: $COMFY_API_KEY"
      ```
    </CodeGroup>
  </Tab>
</Tabs>

## Schema

### Input

<ParamField type="integer">
  Maximum number of tokens to generate before stopping.
</ParamField>

<ParamField type="object[]">
  Conversation turns. See Anthropic Messages API docs for the full content-block taxonomy.
</ParamField>

<ParamField type="object">
  Either a string shorthand or an array of content blocks (text, image, document, tool\_use, tool\_result, ...).
</ParamField>

<ParamField type="string">
  Possible values: `user`, `assistant`
</ParamField>

<ParamField type="string">
  Anthropic model identifier (e.g. `claude-sonnet-4-5`, `claude-opus-4-7`).
</ParamField>

<ParamField type="boolean">
  When true, the response is a `text/event-stream` of Anthropic message events instead of a single JSON body.
</ParamField>

<ParamField type="object">
  Top-level system prompt. Either a string or an array of content blocks; both reach Anthropic unchanged.
</ParamField>

Generated from the schema Router serves at `GET /v2/models/anthropic/claude-haiku-4-5-20251001/openapi.json`, the same document it validates a call against before the request reaches the provider.

### Output

<ResponseField name="id" type="string" />

<ResponseField name="model" type="string" />

<ResponseField name="role" type="string" />

<ResponseField name="stop_reason" type="string" />

<ResponseField name="stop_sequence" type="string" />

<ResponseField name="type" type="string" />

<ResponseField name="usage" type="object">
  Token usage for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation" type="object">
  Per-TTL breakdown of cache-write input tokens for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation.ephemeral_1h_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation.ephemeral_5m_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation_input_tokens" type="integer" />

<ResponseField name="usage.cache_read_input_tokens" type="integer" />

<ResponseField name="usage.input_tokens" type="integer" />

<ResponseField name="usage.output_tokens" type="integer" />

<ResponseField name="content" type="object[]">
  The reply's content blocks, in order. Present on every completed message; empty when the turn produced nothing.
</ResponseField>

<ResponseField name="content[].text" type="string">
  The block's text. Present on `text` blocks and absent on every other kind.
</ResponseField>

<ResponseField name="content[].type" type="string">
  The block kind. `text` is the one that carries `text`; `thinking`, `redacted_thinking`, `tool_use`, `server_tool_use` and the tool-result blocks are the others Anthropic sends today, and the list is open.
</ResponseField>

## Examples

### Input

```json theme={null}
{
  "max_tokens": 16,
  "messages": [
    {
      "content": "Reply with the single word: ok",
      "role": "user"
    }
  ]
}
```

### Output

```json theme={null}
{
  "content": [
    {
      "text": "ok",
      "type": "text"
    }
  ],
  "id": "msg_01ExampleInvalidPlaceholder",
  "model": "claude-haiku-4-5-20251001",
  "role": "assistant",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "type": "message",
  "usage": {
    "input_tokens": 16,
    "output_tokens": 3
  }
}
```

## Before you ship

The SDKs create an `Idempotency-Key` and reuse it for automatic retries. For manual retries, reuse the original key. Router can hold the connection for up to 10 minutes.

When a request fails, Router sends an `X-Comfy-Error-Type` response header explaining why. A `422` means Router rejected the input before calling the provider, and a `413` means the request body was larger than Router accepts. Download generated assets promptly because [result URLs can expire](/development/comfy-router/reference#result-assets).

Any size limit named in a field description above is the provider's own bound on that field, quoted from the provider's specification. Router applies a separate cap to the whole request body, which base64-encoded media counts against: see [request body size](/development/comfy-router/limitations#request-bodies-are-capped).

This page documents one partner model called through Comfy Router. The same `comfy-sdk` / `@comfyorg/sdk` package also ships a second client, for running a whole ComfyUI workflow graph on Comfy Cloud: `Comfy(api_key=...)` / `new Comfy({ apiKey })`, with `client.workflows`, `client.assets` and `client.jobs`. See [Comfy SDKs](/development/api-development/sdks).

<CardGroup>
  <Card title="Headers" icon="list" href="/development/comfy-router/headers">
    Authentication, idempotency, request IDs, error buckets, retry pacing, spend limits.
  </Card>

  <Card title="Using the Router API" icon="code" href="/development/comfy-router/api">
    Model discovery, validation errors, retries, and billing.
  </Card>

  <Card title="Limitations" icon="triangle-exclamation" href="/development/comfy-router/limitations">
    What Router does not do today, and what to use instead.
  </Card>
</CardGroup>


# Use Claude Opus 4.6 with Comfy Router
Source: https://docs.comfy.org/development/comfy-router/models/anthropic/claude-opus-4-6/code

Call anthropic/claude-opus-4-6 through Comfy Router: endpoint, request shape and the response Router returns.

API Reference for `anthropic/claude-opus-4-6`, served by Comfy Router from Anthropic.

**Input:** Text, Image · **Output:** Text

## Quick start

Create a key in [your Comfy workspace](https://platform.comfy.org/profile/api-keys?onboarding=router) and export it as `COMFY_API_KEY`. The Python and TypeScript snippets use the Comfy SDKs (`pip install comfy-sdk` and `npm install @comfyorg/sdk`); the cURL snippet is the same call over raw HTTP.

**Model ID:** `anthropic/claude-opus-4-6`

**Endpoint:** `POST https://api.comfy.org/v2/models/anthropic/claude-opus-4-6`

<Tabs>
  <Tab title="Wait for the result">
    <CodeGroup>
      ```python Python theme={null}
      from comfy_sdk import Comfy

      # Reads COMFY_API_KEY from the environment.
      # The SDK automatically creates an idempotency key and reuses it for automatic retries.
      with Comfy() as client:
          result = client.models.run(
              "anthropic/claude-opus-4-6",
              {
                  "max_tokens": 16,
                  "messages": [
                      {
                          "content": "Reply with the single word: ok",
                          "role": "user",
                      },
                  ],
              },
          )

      print(result)
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // The SDK automatically creates an idempotency key and reuses it for automatic retries.
      const { data } = await comfy.models.run("anthropic/claude-opus-4-6", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });

      console.log(data);
      ```

      ```bash cURL theme={null}
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-4-6 \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"
      ```
    </CodeGroup>
  </Tab>

  <Tab title="Queue and collect later">
    The same body, sent to `POST https://api.comfy.org/v2/models/anthropic/claude-opus-4-6/requests`. Router answers `201` with a `request_id` as soon as the run is admitted, and the result is collected once it is ready, from this process or another one. [Queued delivery](/development/comfy-router/queue) walks through status, cancellation and collection.

    <CodeGroup>
      ```python Python theme={null}
      import asyncio
      from comfy_sdk import AsyncComfy

      # Reads COMFY_API_KEY from the environment.
      # Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      async def main():
          async with AsyncComfy() as client:
              handle = await client.models.submit(
                  "anthropic/claude-opus-4-6",
                  {
                      "max_tokens": 16,
                      "messages": [
                          {
                              "content": "Reply with the single word: ok",
                              "role": "user",
                          },
                      ],
                  },
              )
              print("request_id:", handle.request_id)  # with the model ID, all another process needs

              # Poll until the request completes, waiting the Retry-After the server names.
              async for update in handle.iter_events():
                  print(update.status, update.queue_position)

              # The provider's own payload, the same value models.run() returns.
              # A request that failed or was cancelled raises the typed Router error here.
              result = await handle.get()

          print(result)

      asyncio.run(main())
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      const handle = await comfy.models.submit("anthropic/claude-opus-4-6", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });
      console.log("requestId:", handle.requestId); // with the model ID, all another process needs

      // Poll until the request completes, waiting the Retry-After the server names.
      for await (const update of handle.events()) {
        console.log(update.status, update.queuePosition);
      }

      // The same result models.run() returns. A request that failed or was cancelled rejects here.
      const result = await handle.get();

      console.log(result.data);
      ```

      ```bash cURL theme={null}
      # 1. Submit. Router answers 201 with request_id, status_url, response_url and cancel_url.
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-4-6/requests \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"

      # 2. Poll until status is COMPLETED, waiting the Retry-After seconds each response names.
      REQUEST_ID="<request_id from the 201 body>"
      curl -i https://api.comfy.org/v2/models/anthropic/claude-opus-4-6/requests/$REQUEST_ID/status \
        -H "X-API-Key: $COMFY_API_KEY"

      # 3. Collect. 200 with the model's native output, 202 with the status body while it is still running.
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-4-6/requests/$REQUEST_ID \
        -H "X-API-Key: $COMFY_API_KEY"
      ```
    </CodeGroup>
  </Tab>
</Tabs>

## Schema

### Input

<ParamField type="integer">
  Maximum number of tokens to generate before stopping.
</ParamField>

<ParamField type="object[]">
  Conversation turns. See Anthropic Messages API docs for the full content-block taxonomy.
</ParamField>

<ParamField type="object">
  Either a string shorthand or an array of content blocks (text, image, document, tool\_use, tool\_result, ...).
</ParamField>

<ParamField type="string">
  Possible values: `user`, `assistant`
</ParamField>

<ParamField type="string">
  Anthropic model identifier (e.g. `claude-sonnet-4-5`, `claude-opus-4-7`).
</ParamField>

<ParamField type="boolean">
  When true, the response is a `text/event-stream` of Anthropic message events instead of a single JSON body.
</ParamField>

<ParamField type="object">
  Top-level system prompt. Either a string or an array of content blocks; both reach Anthropic unchanged.
</ParamField>

Generated from the schema Router serves at `GET /v2/models/anthropic/claude-opus-4-6/openapi.json`, the same document it validates a call against before the request reaches the provider.

### Output

<ResponseField name="id" type="string" />

<ResponseField name="model" type="string" />

<ResponseField name="role" type="string" />

<ResponseField name="stop_reason" type="string" />

<ResponseField name="stop_sequence" type="string" />

<ResponseField name="type" type="string" />

<ResponseField name="usage" type="object">
  Token usage for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation" type="object">
  Per-TTL breakdown of cache-write input tokens for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation.ephemeral_1h_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation.ephemeral_5m_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation_input_tokens" type="integer" />

<ResponseField name="usage.cache_read_input_tokens" type="integer" />

<ResponseField name="usage.input_tokens" type="integer" />

<ResponseField name="usage.output_tokens" type="integer" />

<ResponseField name="content" type="object[]">
  The reply's content blocks, in order. Present on every completed message; empty when the turn produced nothing.
</ResponseField>

<ResponseField name="content[].text" type="string">
  The block's text. Present on `text` blocks and absent on every other kind.
</ResponseField>

<ResponseField name="content[].type" type="string">
  The block kind. `text` is the one that carries `text`; `thinking`, `redacted_thinking`, `tool_use`, `server_tool_use` and the tool-result blocks are the others Anthropic sends today, and the list is open.
</ResponseField>

## Examples

### Input

```json theme={null}
{
  "max_tokens": 16,
  "messages": [
    {
      "content": "Reply with the single word: ok",
      "role": "user"
    }
  ]
}
```

### Output

```json theme={null}
{
  "content": [
    {
      "text": "ok",
      "type": "text"
    }
  ],
  "id": "msg_01ExampleInvalidPlaceholder",
  "model": "claude-opus-4-6",
  "role": "assistant",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "type": "message",
  "usage": {
    "input_tokens": 16,
    "output_tokens": 3
  }
}
```

## Before you ship

The SDKs create an `Idempotency-Key` and reuse it for automatic retries. For manual retries, reuse the original key. Router can hold the connection for up to 10 minutes.

When a request fails, Router sends an `X-Comfy-Error-Type` response header explaining why. A `422` means Router rejected the input before calling the provider, and a `413` means the request body was larger than Router accepts. Download generated assets promptly because [result URLs can expire](/development/comfy-router/reference#result-assets).

Any size limit named in a field description above is the provider's own bound on that field, quoted from the provider's specification. Router applies a separate cap to the whole request body, which base64-encoded media counts against: see [request body size](/development/comfy-router/limitations#request-bodies-are-capped).

This page documents one partner model called through Comfy Router. The same `comfy-sdk` / `@comfyorg/sdk` package also ships a second client, for running a whole ComfyUI workflow graph on Comfy Cloud: `Comfy(api_key=...)` / `new Comfy({ apiKey })`, with `client.workflows`, `client.assets` and `client.jobs`. See [Comfy SDKs](/development/api-development/sdks).

<CardGroup>
  <Card title="Headers" icon="list" href="/development/comfy-router/headers">
    Authentication, idempotency, request IDs, error buckets, retry pacing, spend limits.
  </Card>

  <Card title="Using the Router API" icon="code" href="/development/comfy-router/api">
    Model discovery, validation errors, retries, and billing.
  </Card>

  <Card title="Limitations" icon="triangle-exclamation" href="/development/comfy-router/limitations">
    What Router does not do today, and what to use instead.
  </Card>
</CardGroup>


# Use Claude Opus 4.7 with Comfy Router
Source: https://docs.comfy.org/development/comfy-router/models/anthropic/claude-opus-4-7/code

Call anthropic/claude-opus-4-7 through Comfy Router: endpoint, request shape and the response Router returns.

API Reference for `anthropic/claude-opus-4-7`, served by Comfy Router from Anthropic.

**Input:** Text, Image · **Output:** Text

## Quick start

Create a key in [your Comfy workspace](https://platform.comfy.org/profile/api-keys?onboarding=router) and export it as `COMFY_API_KEY`. The Python and TypeScript snippets use the Comfy SDKs (`pip install comfy-sdk` and `npm install @comfyorg/sdk`); the cURL snippet is the same call over raw HTTP.

**Model ID:** `anthropic/claude-opus-4-7`

**Endpoint:** `POST https://api.comfy.org/v2/models/anthropic/claude-opus-4-7`

<Tabs>
  <Tab title="Wait for the result">
    <CodeGroup>
      ```python Python theme={null}
      from comfy_sdk import Comfy

      # Reads COMFY_API_KEY from the environment.
      # The SDK automatically creates an idempotency key and reuses it for automatic retries.
      with Comfy() as client:
          result = client.models.run(
              "anthropic/claude-opus-4-7",
              {
                  "max_tokens": 16,
                  "messages": [
                      {
                          "content": "Reply with the single word: ok",
                          "role": "user",
                      },
                  ],
              },
          )

      print(result)
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // The SDK automatically creates an idempotency key and reuses it for automatic retries.
      const { data } = await comfy.models.run("anthropic/claude-opus-4-7", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });

      console.log(data);
      ```

      ```bash cURL theme={null}
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-4-7 \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"
      ```
    </CodeGroup>
  </Tab>

  <Tab title="Queue and collect later">
    The same body, sent to `POST https://api.comfy.org/v2/models/anthropic/claude-opus-4-7/requests`. Router answers `201` with a `request_id` as soon as the run is admitted, and the result is collected once it is ready, from this process or another one. [Queued delivery](/development/comfy-router/queue) walks through status, cancellation and collection.

    <CodeGroup>
      ```python Python theme={null}
      import asyncio
      from comfy_sdk import AsyncComfy

      # Reads COMFY_API_KEY from the environment.
      # Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      async def main():
          async with AsyncComfy() as client:
              handle = await client.models.submit(
                  "anthropic/claude-opus-4-7",
                  {
                      "max_tokens": 16,
                      "messages": [
                          {
                              "content": "Reply with the single word: ok",
                              "role": "user",
                          },
                      ],
                  },
              )
              print("request_id:", handle.request_id)  # with the model ID, all another process needs

              # Poll until the request completes, waiting the Retry-After the server names.
              async for update in handle.iter_events():
                  print(update.status, update.queue_position)

              # The provider's own payload, the same value models.run() returns.
              # A request that failed or was cancelled raises the typed Router error here.
              result = await handle.get()

          print(result)

      asyncio.run(main())
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      const handle = await comfy.models.submit("anthropic/claude-opus-4-7", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });
      console.log("requestId:", handle.requestId); // with the model ID, all another process needs

      // Poll until the request completes, waiting the Retry-After the server names.
      for await (const update of handle.events()) {
        console.log(update.status, update.queuePosition);
      }

      // The same result models.run() returns. A request that failed or was cancelled rejects here.
      const result = await handle.get();

      console.log(result.data);
      ```

      ```bash cURL theme={null}
      # 1. Submit. Router answers 201 with request_id, status_url, response_url and cancel_url.
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-4-7/requests \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"

      # 2. Poll until status is COMPLETED, waiting the Retry-After seconds each response names.
      REQUEST_ID="<request_id from the 201 body>"
      curl -i https://api.comfy.org/v2/models/anthropic/claude-opus-4-7/requests/$REQUEST_ID/status \
        -H "X-API-Key: $COMFY_API_KEY"

      # 3. Collect. 200 with the model's native output, 202 with the status body while it is still running.
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-4-7/requests/$REQUEST_ID \
        -H "X-API-Key: $COMFY_API_KEY"
      ```
    </CodeGroup>
  </Tab>
</Tabs>

## Schema

### Input

<ParamField type="integer">
  Maximum number of tokens to generate before stopping.
</ParamField>

<ParamField type="object[]">
  Conversation turns. See Anthropic Messages API docs for the full content-block taxonomy.
</ParamField>

<ParamField type="object">
  Either a string shorthand or an array of content blocks (text, image, document, tool\_use, tool\_result, ...).
</ParamField>

<ParamField type="string">
  Possible values: `user`, `assistant`
</ParamField>

<ParamField type="string">
  Anthropic model identifier (e.g. `claude-sonnet-4-5`, `claude-opus-4-7`).
</ParamField>

<ParamField type="boolean">
  When true, the response is a `text/event-stream` of Anthropic message events instead of a single JSON body.
</ParamField>

<ParamField type="object">
  Top-level system prompt. Either a string or an array of content blocks; both reach Anthropic unchanged.
</ParamField>

Generated from the schema Router serves at `GET /v2/models/anthropic/claude-opus-4-7/openapi.json`, the same document it validates a call against before the request reaches the provider.

### Output

<ResponseField name="id" type="string" />

<ResponseField name="model" type="string" />

<ResponseField name="role" type="string" />

<ResponseField name="stop_reason" type="string" />

<ResponseField name="stop_sequence" type="string" />

<ResponseField name="type" type="string" />

<ResponseField name="usage" type="object">
  Token usage for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation" type="object">
  Per-TTL breakdown of cache-write input tokens for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation.ephemeral_1h_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation.ephemeral_5m_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation_input_tokens" type="integer" />

<ResponseField name="usage.cache_read_input_tokens" type="integer" />

<ResponseField name="usage.input_tokens" type="integer" />

<ResponseField name="usage.output_tokens" type="integer" />

<ResponseField name="content" type="object[]">
  The reply's content blocks, in order. Present on every completed message; empty when the turn produced nothing.
</ResponseField>

<ResponseField name="content[].text" type="string">
  The block's text. Present on `text` blocks and absent on every other kind.
</ResponseField>

<ResponseField name="content[].type" type="string">
  The block kind. `text` is the one that carries `text`; `thinking`, `redacted_thinking`, `tool_use`, `server_tool_use` and the tool-result blocks are the others Anthropic sends today, and the list is open.
</ResponseField>

## Examples

### Input

```json theme={null}
{
  "max_tokens": 16,
  "messages": [
    {
      "content": "Reply with the single word: ok",
      "role": "user"
    }
  ]
}
```

### Output

```json theme={null}
{
  "content": [
    {
      "text": "ok",
      "type": "text"
    }
  ],
  "id": "msg_01ExampleInvalidPlaceholder",
  "model": "claude-opus-4-7",
  "role": "assistant",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "type": "message",
  "usage": {
    "input_tokens": 16,
    "output_tokens": 3
  }
}
```

## Before you ship

The SDKs create an `Idempotency-Key` and reuse it for automatic retries. For manual retries, reuse the original key. Router can hold the connection for up to 10 minutes.

When a request fails, Router sends an `X-Comfy-Error-Type` response header explaining why. A `422` means Router rejected the input before calling the provider, and a `413` means the request body was larger than Router accepts. Download generated assets promptly because [result URLs can expire](/development/comfy-router/reference#result-assets).

Any size limit named in a field description above is the provider's own bound on that field, quoted from the provider's specification. Router applies a separate cap to the whole request body, which base64-encoded media counts against: see [request body size](/development/comfy-router/limitations#request-bodies-are-capped).

This page documents one partner model called through Comfy Router. The same `comfy-sdk` / `@comfyorg/sdk` package also ships a second client, for running a whole ComfyUI workflow graph on Comfy Cloud: `Comfy(api_key=...)` / `new Comfy({ apiKey })`, with `client.workflows`, `client.assets` and `client.jobs`. See [Comfy SDKs](/development/api-development/sdks).

<CardGroup>
  <Card title="Headers" icon="list" href="/development/comfy-router/headers">
    Authentication, idempotency, request IDs, error buckets, retry pacing, spend limits.
  </Card>

  <Card title="Using the Router API" icon="code" href="/development/comfy-router/api">
    Model discovery, validation errors, retries, and billing.
  </Card>

  <Card title="Limitations" icon="triangle-exclamation" href="/development/comfy-router/limitations">
    What Router does not do today, and what to use instead.
  </Card>
</CardGroup>


# Use Claude Opus 4.8 with Comfy Router
Source: https://docs.comfy.org/development/comfy-router/models/anthropic/claude-opus-4-8/code

Call anthropic/claude-opus-4-8 through Comfy Router: endpoint, request shape and the response Router returns.

API Reference for `anthropic/claude-opus-4-8`, served by Comfy Router from Anthropic.

**Input:** Text, Image · **Output:** Text

## Quick start

Create a key in [your Comfy workspace](https://platform.comfy.org/profile/api-keys?onboarding=router) and export it as `COMFY_API_KEY`. The Python and TypeScript snippets use the Comfy SDKs (`pip install comfy-sdk` and `npm install @comfyorg/sdk`); the cURL snippet is the same call over raw HTTP.

**Model ID:** `anthropic/claude-opus-4-8`

**Endpoint:** `POST https://api.comfy.org/v2/models/anthropic/claude-opus-4-8`

<Tabs>
  <Tab title="Wait for the result">
    <CodeGroup>
      ```python Python theme={null}
      from comfy_sdk import Comfy

      # Reads COMFY_API_KEY from the environment.
      # The SDK automatically creates an idempotency key and reuses it for automatic retries.
      with Comfy() as client:
          result = client.models.run(
              "anthropic/claude-opus-4-8",
              {
                  "max_tokens": 16,
                  "messages": [
                      {
                          "content": "Reply with the single word: ok",
                          "role": "user",
                      },
                  ],
              },
          )

      print(result)
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // The SDK automatically creates an idempotency key and reuses it for automatic retries.
      const { data } = await comfy.models.run("anthropic/claude-opus-4-8", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });

      console.log(data);
      ```

      ```bash cURL theme={null}
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-4-8 \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"
      ```
    </CodeGroup>
  </Tab>

  <Tab title="Queue and collect later">
    The same body, sent to `POST https://api.comfy.org/v2/models/anthropic/claude-opus-4-8/requests`. Router answers `201` with a `request_id` as soon as the run is admitted, and the result is collected once it is ready, from this process or another one. [Queued delivery](/development/comfy-router/queue) walks through status, cancellation and collection.

    <CodeGroup>
      ```python Python theme={null}
      import asyncio
      from comfy_sdk import AsyncComfy

      # Reads COMFY_API_KEY from the environment.
      # Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      async def main():
          async with AsyncComfy() as client:
              handle = await client.models.submit(
                  "anthropic/claude-opus-4-8",
                  {
                      "max_tokens": 16,
                      "messages": [
                          {
                              "content": "Reply with the single word: ok",
                              "role": "user",
                          },
                      ],
                  },
              )
              print("request_id:", handle.request_id)  # with the model ID, all another process needs

              # Poll until the request completes, waiting the Retry-After the server names.
              async for update in handle.iter_events():
                  print(update.status, update.queue_position)

              # The provider's own payload, the same value models.run() returns.
              # A request that failed or was cancelled raises the typed Router error here.
              result = await handle.get()

          print(result)

      asyncio.run(main())
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      const handle = await comfy.models.submit("anthropic/claude-opus-4-8", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });
      console.log("requestId:", handle.requestId); // with the model ID, all another process needs

      // Poll until the request completes, waiting the Retry-After the server names.
      for await (const update of handle.events()) {
        console.log(update.status, update.queuePosition);
      }

      // The same result models.run() returns. A request that failed or was cancelled rejects here.
      const result = await handle.get();

      console.log(result.data);
      ```

      ```bash cURL theme={null}
      # 1. Submit. Router answers 201 with request_id, status_url, response_url and cancel_url.
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-4-8/requests \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"

      # 2. Poll until status is COMPLETED, waiting the Retry-After seconds each response names.
      REQUEST_ID="<request_id from the 201 body>"
      curl -i https://api.comfy.org/v2/models/anthropic/claude-opus-4-8/requests/$REQUEST_ID/status \
        -H "X-API-Key: $COMFY_API_KEY"

      # 3. Collect. 200 with the model's native output, 202 with the status body while it is still running.
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-4-8/requests/$REQUEST_ID \
        -H "X-API-Key: $COMFY_API_KEY"
      ```
    </CodeGroup>
  </Tab>
</Tabs>

## Schema

### Input

<ParamField type="integer">
  Maximum number of tokens to generate before stopping.
</ParamField>

<ParamField type="object[]">
  Conversation turns. See Anthropic Messages API docs for the full content-block taxonomy.
</ParamField>

<ParamField type="object">
  Either a string shorthand or an array of content blocks (text, image, document, tool\_use, tool\_result, ...).
</ParamField>

<ParamField type="string">
  Possible values: `user`, `assistant`
</ParamField>

<ParamField type="string">
  Anthropic model identifier (e.g. `claude-sonnet-4-5`, `claude-opus-4-7`).
</ParamField>

<ParamField type="boolean">
  When true, the response is a `text/event-stream` of Anthropic message events instead of a single JSON body.
</ParamField>

<ParamField type="object">
  Top-level system prompt. Either a string or an array of content blocks; both reach Anthropic unchanged.
</ParamField>

Generated from the schema Router serves at `GET /v2/models/anthropic/claude-opus-4-8/openapi.json`, the same document it validates a call against before the request reaches the provider.

### Output

<ResponseField name="id" type="string" />

<ResponseField name="model" type="string" />

<ResponseField name="role" type="string" />

<ResponseField name="stop_reason" type="string" />

<ResponseField name="stop_sequence" type="string" />

<ResponseField name="type" type="string" />

<ResponseField name="usage" type="object">
  Token usage for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation" type="object">
  Per-TTL breakdown of cache-write input tokens for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation.ephemeral_1h_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation.ephemeral_5m_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation_input_tokens" type="integer" />

<ResponseField name="usage.cache_read_input_tokens" type="integer" />

<ResponseField name="usage.input_tokens" type="integer" />

<ResponseField name="usage.output_tokens" type="integer" />

<ResponseField name="content" type="object[]">
  The reply's content blocks, in order. Present on every completed message; empty when the turn produced nothing.
</ResponseField>

<ResponseField name="content[].text" type="string">
  The block's text. Present on `text` blocks and absent on every other kind.
</ResponseField>

<ResponseField name="content[].type" type="string">
  The block kind. `text` is the one that carries `text`; `thinking`, `redacted_thinking`, `tool_use`, `server_tool_use` and the tool-result blocks are the others Anthropic sends today, and the list is open.
</ResponseField>

## Examples

### Input

```json theme={null}
{
  "max_tokens": 16,
  "messages": [
    {
      "content": "Reply with the single word: ok",
      "role": "user"
    }
  ]
}
```

### Output

```json theme={null}
{
  "content": [
    {
      "text": "ok",
      "type": "text"
    }
  ],
  "id": "msg_01ExampleInvalidPlaceholder",
  "model": "claude-opus-4-8",
  "role": "assistant",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "type": "message",
  "usage": {
    "input_tokens": 16,
    "output_tokens": 3
  }
}
```

## Before you ship

The SDKs create an `Idempotency-Key` and reuse it for automatic retries. For manual retries, reuse the original key. Router can hold the connection for up to 10 minutes.

When a request fails, Router sends an `X-Comfy-Error-Type` response header explaining why. A `422` means Router rejected the input before calling the provider, and a `413` means the request body was larger than Router accepts. Download generated assets promptly because [result URLs can expire](/development/comfy-router/reference#result-assets).

Any size limit named in a field description above is the provider's own bound on that field, quoted from the provider's specification. Router applies a separate cap to the whole request body, which base64-encoded media counts against: see [request body size](/development/comfy-router/limitations#request-bodies-are-capped).

This page documents one partner model called through Comfy Router. The same `comfy-sdk` / `@comfyorg/sdk` package also ships a second client, for running a whole ComfyUI workflow graph on Comfy Cloud: `Comfy(api_key=...)` / `new Comfy({ apiKey })`, with `client.workflows`, `client.assets` and `client.jobs`. See [Comfy SDKs](/development/api-development/sdks).

<CardGroup>
  <Card title="Headers" icon="list" href="/development/comfy-router/headers">
    Authentication, idempotency, request IDs, error buckets, retry pacing, spend limits.
  </Card>

  <Card title="Using the Router API" icon="code" href="/development/comfy-router/api">
    Model discovery, validation errors, retries, and billing.
  </Card>

  <Card title="Limitations" icon="triangle-exclamation" href="/development/comfy-router/limitations">
    What Router does not do today, and what to use instead.
  </Card>
</CardGroup>


# Use Claude Opus 5.5 with Comfy Router
Source: https://docs.comfy.org/development/comfy-router/models/anthropic/claude-opus-5-5/code

Call anthropic/claude-opus-5-5 through Comfy Router: endpoint, request shape and the response Router returns.

API Reference for `anthropic/claude-opus-5-5`, served by Comfy Router from Anthropic.

**Input:** Text, Image · **Output:** Text

## Quick start

Create a key in [your Comfy workspace](https://platform.comfy.org/profile/api-keys?onboarding=router) and export it as `COMFY_API_KEY`. The Python and TypeScript snippets use the Comfy SDKs (`pip install comfy-sdk` and `npm install @comfyorg/sdk`); the cURL snippet is the same call over raw HTTP.

**Model ID:** `anthropic/claude-opus-5-5`

**Endpoint:** `POST https://api.comfy.org/v2/models/anthropic/claude-opus-5-5`

<Tabs>
  <Tab title="Wait for the result">
    <CodeGroup>
      ```python Python theme={null}
      from comfy_sdk import Comfy

      # Reads COMFY_API_KEY from the environment.
      # The SDK automatically creates an idempotency key and reuses it for automatic retries.
      with Comfy() as client:
          result = client.models.run(
              "anthropic/claude-opus-5-5",
              {
                  "max_tokens": 16,
                  "messages": [
                      {
                          "content": "Reply with the single word: ok",
                          "role": "user",
                      },
                  ],
              },
          )

      print(result)
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // The SDK automatically creates an idempotency key and reuses it for automatic retries.
      const { data } = await comfy.models.run("anthropic/claude-opus-5-5", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });

      console.log(data);
      ```

      ```bash cURL theme={null}
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-5-5 \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"
      ```
    </CodeGroup>
  </Tab>

  <Tab title="Queue and collect later">
    The same body, sent to `POST https://api.comfy.org/v2/models/anthropic/claude-opus-5-5/requests`. Router answers `201` with a `request_id` as soon as the run is admitted, and the result is collected once it is ready, from this process or another one. [Queued delivery](/development/comfy-router/queue) walks through status, cancellation and collection.

    <CodeGroup>
      ```python Python theme={null}
      import asyncio
      from comfy_sdk import AsyncComfy

      # Reads COMFY_API_KEY from the environment.
      # Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      async def main():
          async with AsyncComfy() as client:
              handle = await client.models.submit(
                  "anthropic/claude-opus-5-5",
                  {
                      "max_tokens": 16,
                      "messages": [
                          {
                              "content": "Reply with the single word: ok",
                              "role": "user",
                          },
                      ],
                  },
              )
              print("request_id:", handle.request_id)  # with the model ID, all another process needs

              # Poll until the request completes, waiting the Retry-After the server names.
              async for update in handle.iter_events():
                  print(update.status, update.queue_position)

              # The provider's own payload, the same value models.run() returns.
              # A request that failed or was cancelled raises the typed Router error here.
              result = await handle.get()

          print(result)

      asyncio.run(main())
      ```

      ```typescript TypeScript theme={null}
      import { comfy } from "@comfyorg/sdk";

      // Reads COMFY_API_KEY from the environment.
      // Each submit() call mints its own Idempotency-Key and reuses it for automatic retries.
      const handle = await comfy.models.submit("anthropic/claude-opus-5-5", {
        max_tokens: 16,
        messages: [
          {
            content: "Reply with the single word: ok",
            role: "user",
          },
        ],
      });
      console.log("requestId:", handle.requestId); // with the model ID, all another process needs

      // Poll until the request completes, waiting the Retry-After the server names.
      for await (const update of handle.events()) {
        console.log(update.status, update.queuePosition);
      }

      // The same result models.run() returns. A request that failed or was cancelled rejects here.
      const result = await handle.get();

      console.log(result.data);
      ```

      ```bash cURL theme={null}
      # 1. Submit. Router answers 201 with request_id, status_url, response_url and cancel_url.
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-5-5/requests \
        -H "X-API-Key: $COMFY_API_KEY" \
        -H "Idempotency-Key: $(uuidgen)" \
        -H "Content-Type: application/json" \
        -d "{\"max_tokens\": 16, \"messages\": [{\"content\":\"Reply with the single word: ok\",\"role\":\"user\"}]}"

      # 2. Poll until status is COMPLETED, waiting the Retry-After seconds each response names.
      REQUEST_ID="<request_id from the 201 body>"
      curl -i https://api.comfy.org/v2/models/anthropic/claude-opus-5-5/requests/$REQUEST_ID/status \
        -H "X-API-Key: $COMFY_API_KEY"

      # 3. Collect. 200 with the model's native output, 202 with the status body while it is still running.
      curl https://api.comfy.org/v2/models/anthropic/claude-opus-5-5/requests/$REQUEST_ID \
        -H "X-API-Key: $COMFY_API_KEY"
      ```
    </CodeGroup>
  </Tab>
</Tabs>

## Schema

### Input

<ParamField type="integer">
  Maximum number of tokens to generate before stopping.
</ParamField>

<ParamField type="object[]">
  Conversation turns. See Anthropic Messages API docs for the full content-block taxonomy.
</ParamField>

<ParamField type="object">
  Either a string shorthand or an array of content blocks (text, image, document, tool\_use, tool\_result, ...).
</ParamField>

<ParamField type="string">
  Possible values: `user`, `assistant`
</ParamField>

<ParamField type="string">
  Anthropic model identifier (e.g. `claude-sonnet-4-5`, `claude-opus-4-7`).
</ParamField>

<ParamField type="boolean">
  When true, the response is a `text/event-stream` of Anthropic message events instead of a single JSON body.
</ParamField>

<ParamField type="object">
  Top-level system prompt. Either a string or an array of content blocks; both reach Anthropic unchanged.
</ParamField>

Generated from the schema Router serves at `GET /v2/models/anthropic/claude-opus-5-5/openapi.json`, the same document it validates a call against before the request reaches the provider.

### Output

<ResponseField name="id" type="string" />

<ResponseField name="model" type="string" />

<ResponseField name="role" type="string" />

<ResponseField name="stop_reason" type="string" />

<ResponseField name="stop_sequence" type="string" />

<ResponseField name="type" type="string" />

<ResponseField name="usage" type="object">
  Token usage for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation" type="object">
  Per-TTL breakdown of cache-write input tokens for an Anthropic Messages API call.
</ResponseField>

<ResponseField name="usage.cache_creation.ephemeral_1h_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation.ephemeral_5m_input_tokens" type="integer" />

<ResponseField name="usage.cache_creation_input_tokens" type="integer" />

<ResponseField name="usage.cache_read_input_tokens" type="integer" />

<ResponseField name="usage.input_tokens" type="integer" />

<ResponseField name="usage.output_tokens" type="integer" />

<ResponseField name="content" type="object[]">
  The reply's content blocks, in order. Present on every completed message; empty when the turn produced nothing.
</ResponseField>

<ResponseField name="content[].text" type="string">
  The block's text. Present on `text` blocks and absent on every other kind.
</ResponseField>

<ResponseField name="content[].type" type="string">
  The block kind. `text` is the one that carries `text`; `thinking`, `redacted_thinking`, `tool_use`, `server_tool_use` and the tool-result blocks are the others Anthropic sends today, and the list is open.
</ResponseField>

## Examples

### Input

```json theme={null}
{
  "max_tokens": 16,
  "messages": [
    {
      "content": "Reply with the single word: ok",
      "role": "user"
    }
  ]
}
```

### Output

```json theme={null}
{
  "content": [
    {
      "text": "ok",
      "type": "text"
    }
  ],
  "id": "msg_01ExampleInvalidPlaceholder",
  "model": "claude-opus-5-5",
  "role": "assistant",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "type": "message",
  "usage": {
    "input_tokens": 16,
    "output_tokens": 3
  }
}
```

## Before you ship

The SDKs create an `Idempotency-Key` and reuse it for automatic retries. For manual retries, reuse the original key. Router can hold the connection for up to 10 minutes.

When a request fails, Router sends an `X-Comfy-Error-Type` response header explaining why. A `422` means Router rejected the input before calling the provider, and a `413` means the request body was larger than Router accepts. Download generated assets promptly because [result URLs can expire](/development/comfy-router/reference#result-assets).

Any size limit named in a field description above is the provider's own