---
title: HunyuanVideo-I2V-gguf
canonical_url: "https://www.modelscope.cn/models/city96/HunyuanVideo-I2V-gguf"
md_url: "https://www.modelscope.cn/models/city96/HunyuanVideo-I2V-gguf.md"
repository: city96/HunyuanVideo-I2V-gguf
last_updated: 2025-03-11
license: other
pipeline_tag: image-to-video
tasks:
  - image-to-video
base_model:
  - tencent/HunyuanVideo-I2V
base_model_relation: quantized
library_name:
  - gguf
  - pytorch
frameworks:
  - pytorch
downloads: 1381
stars: 1
tags:
  - image-to-video
  - gguf
---

# HunyuanVideo-I2V-gguf

> HunyuanVideo-I2V-gguf - city96 在 ModelScope 开源的模型。This is a direct GGUF conversion of tencent/HunyuanVideo-I2V

city96/HunyuanVideo-I2V-gguf 是 ModelScope 魔搭社区上的image-to-video模型，采用 other 许可，基于 tencent/HunyuanVideo-I2V 构建。

- **Repository**: city96/HunyuanVideo-I2V-gguf
- **License**: other
- **Tasks**: image-to-video
- **Base model**: tencent/HunyuanVideo-I2V
- **Tags**: image-to-video, gguf
- **Downloads**: 1381
- **Stars**: 1
- **Last updated**: 2025-03-11

Source: https://www.modelscope.cn/models/city96/HunyuanVideo-I2V-gguf

---

This is a direct GGUF conversion of [tencent/HunyuanVideo-I2V](https://huggingface.co/tencent/tencent/HunyuanVideo-I2V)

NOTE: Hunyuan recently replaced the original model in the repo above with a **new and updated version** - the files in this repo have been reconverted and replaced. If you want to test against the original models, you can find them on [this branch](https://huggingface.co/city96/HunyuanVideo-I2V-gguf/tree/original)

**It is intended to be used with the native, built-in ComfyUI HunyuanVideo nodes**

As this is a quantized model not a finetune, all the same restrictions/original license terms still apply.

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 [this repository by Kijai](https://huggingface.co/Kijai/HunyuanVideo_comfy/blob/main/hunyuan_video_vae_bf16.safetensors)

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.