---
license: apache-2.0
library_name: gguf
base_model:
- Wan-AI/Wan2.1-VACE-14B
tags:
- video
- video-generation
pipeline_tag: text-to-video
---

[**Example workflow**](https://huggingface.co/QuantStack/Wan2.1-VACE-14B-GGUF/blob/main/vace_v2v_example_workflow.json) - based on the [Comfyui example workflow](https://docs.comfy.org/tutorials/video/wan/vace)

This is a direct GGUF conversion of [Wan-AI/Wan2.1-VACE-14B](https://huggingface.co/Wan-AI/Wan2.1-VACE-14B)

All quants are created from the FP32 base file, though I only uploaded the Q8_0 and less, if you want the F16 or BF16 one I would upload it per request. 

The model files can be used with the [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) custom node.

Place model files in `ComfyUI/models/unet` - see the GitHub readme for further install instructions.

The VAE can be downloaded from [here](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors?download=true)

Please refer to [this chart](https://github.com/ggerganov/llama.cpp/blob/master/examples/perplexity/README.md#llama-3-8b-scoreboard) for a basic overview of quantization types.

For conversion I used the conversion scripts from [city96](https://huggingface.co/city96)