---
title: Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF
canonical_url: "https://www.modelscope.cn/models/AI-ModelScope/Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF"
md_url: "https://www.modelscope.cn/models/AI-ModelScope/Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF.md"
repository: AI-ModelScope/Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF
last_updated: 2025-06-17
license: apache-2.0
pipeline_tag: image-to-video
tasks:
  - image-to-video
base_model:
  - lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill
base_model_relation: quantized
library_name:
  - gguf
  - pytorch
frameworks:
  - pytorch
language:
  - en
downloads: 453
stars: 0
tags:
  - text-to-video
  - image-to-video
  - video-to-video
  - quantized
  - gguf
---

# Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF

> Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF - AI-ModelScope 在 ModelScope 开源的模型。This is a GGUF conversion of an addon of lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill and Wan-AI/Wan2.1-VACE-14B scopes.

AI-ModelScope/Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF 是 ModelScope 魔搭社区上的image-to-video模型，采用 apache-2.0 许可，基于 lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill 构建。

- **Repository**: AI-ModelScope/Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF
- **License**: apache-2.0
- **Tasks**: image-to-video
- **Base model**: lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill
- **Tags**: text-to-video, image-to-video, video-to-video, quantized, gguf
- **Downloads**: 453
- **Stars**: 0
- **Last updated**: 2025-06-17

Source: https://www.modelscope.cn/models/AI-ModelScope/Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF

---

This is a GGUF conversion of an addon of [lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill](https://huggingface.co/lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill) and [Wan-AI/Wan2.1-VACE-14B](https://huggingface.co/Wan-AI/Wan2.1-VACE-14B) scopes. 

The process involved extracting VACE scopes and injecting into the target models, using scripts provided by [wsbagnsv1](https://huggingface.co/wsbagnsv1). 

All quantized versions were created from the FP16 model using the conversion scripts provided by city96, available at the [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF/tree/main/tools) GitHub repository. 


## Usage

The model files can be used in [ComfyUI](https://github.com/comfyanonymous/ComfyUI/) with the [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) custom node. Place the required model(s) in the following folders:

| Type         | Name                                               | Location                       | Download         |
| ------------ | -------------------------------------------------- | ------------------------------ | ---------------- |
| Main Model   | Wan2.1_T2V_14B_LightX2V_Step_Cfg_Distill_VACE-GGUF | `ComfyUI/models/unet`          | GGUF (this repo) |
| Text Encoder | umt5-xxl-encoder                                   | `ComfyUI/models/text_encoders` | [Safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/text_encoders) / [GGUF](https://huggingface.co/city96/umt5-xxl-encoder-gguf/tree/main) |
| VAE          | Wan2_1_VAE_bf16                                    | `ComfyUI/models/vae`           | [Safetensors](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Wan2_1_VAE_bf16.safetensors) |

[**ComfyUI example workflow**](https://docs.comfy.org/tutorials/video/wan/vace)

### Notes

*All original licenses and restrictions from the base models still apply.*

 ## Reference

- For an overview of quantization types, please see the [GGUF quantization types](https://huggingface.co/docs/hub/gguf#quantization-types).