> ## 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.

# VAELoader - ComfyUI Built-in Node Documentation

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

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      | Comfy dtype     | Description                                                                                                                                                                      |
| ---------- | --------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `vae_name` | `COMBO[STRING]` | 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'. |

## Outputs

| Field | Data Type | Description                                                                                                                                                   |
| ----- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `vae` | `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. |