> ## Documentation Index
> Fetch the complete documentation index at: https://docs.comfy.org/llms.txt
> Use this file to discover all available pages before exploring further.

# ModelSamplingContinuousV - ComfyUI Built-in Node Documentation

> Complete documentation for the ModelSamplingContinuousV node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have 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)

The ModelSamplingContinuousV node modifies a model's sampling behavior by applying continuous V-prediction sampling parameters. It creates a clone of the input model and configures it with custom sigma range settings for advanced sampling control. This allows users to fine-tune the sampling process with specific minimum and maximum sigma values.

## Inputs

| Parameter   | Data Type | Required | Range           | Description                                                             |
| ----------- | --------- | -------- | --------------- | ----------------------------------------------------------------------- |
| `model`     | MODEL     | Yes      | -               | The input model to be modified with continuous V-prediction sampling    |
| `sampling`  | STRING    | Yes      | "v\_prediction" | The sampling method to apply (currently only V-prediction is supported) |
| `sigma_max` | FLOAT     | Yes      | 0.0 - 1000.0    | The maximum sigma value for sampling (default: 500.0)                   |
| `sigma_min` | FLOAT     | Yes      | 0.0 - 1000.0    | The minimum sigma value for sampling (default: 0.03)                    |

## Outputs

| Output Name | Data Type | Description                                                      |
| ----------- | --------- | ---------------------------------------------------------------- |
| `model`     | MODEL     | The modified model with continuous V-prediction sampling applied |