> ## 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.

# WanVaceToVideo - ComfyUI Built-in Node Documentation

> 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`


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.