---
title: nunchaku-qwen-image-edit
canonical_url: "https://www.modelscope.cn/models/nunchaku-tech/nunchaku-qwen-image-edit"
md_url: "https://www.modelscope.cn/models/nunchaku-tech/nunchaku-qwen-image-edit.md"
repository: nunchaku-tech/nunchaku-qwen-image-edit
last_updated: 2026-01-10
license: "Apache License 2.0"
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
base_model:
  - Qwen/Qwen-Image-Edit
base_model_relation: quantized
parameters: 106.9B
tensor_type:
  - I32
  - BF16
  - I8
  - F8_E4M3
library_name:
  - safetensors
  - pytorch
frameworks:
  - PyTorch
language:
  - en
downloads: 5472
stars: 18
tags:
  - image-editing
  - SVDQuant
  - Qwen-Image-Edit
  - Diffusion
  - Quantization
  - ICLR2025
---

# nunchaku-qwen-image-edit

> nunchaku-qwen-image-edit - nunchaku-tech 在 ModelScope 开源的模型。Model Card for nunchaku-qwen-image-edit

nunchaku-tech/nunchaku-qwen-image-edit 是 ModelScope 魔搭社区上的 106.9B 参数text-to-image-synthesis模型，采用 Apache License 2.0 许可，基于 Qwen/Qwen-Image-Edit 构建。

- **Repository**: nunchaku-tech/nunchaku-qwen-image-edit
- **License**: Apache License 2.0
- **Tasks**: text-to-image-synthesis
- **Parameters**: 106.9B
- **Base model**: Qwen/Qwen-Image-Edit
- **Tags**: image-editing, SVDQuant, Qwen-Image-Edit, Diffusion, Quantization, ICLR2025
- **Downloads**: 5472
- **Stars**: 18
- **Last updated**: 2026-01-10

Source: https://www.modelscope.cn/models/nunchaku-tech/nunchaku-qwen-image-edit

---

<p align="center" style="border-radius: 10px">
  <img src="https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/nunchaku/assets/nunchaku_v2.png" width="30%" alt="Nunchaku Logo"/>
</p>

<div align="center">
  <a href=https://discord.gg/Wk6PnwX9Sm target="_blank"><img src=https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Finvites%2FWk6PnwX9Sm%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&logo=discord&logoColor=white&label=Discord&color=green&suffix=%20total height=22px></a>
  <a href=https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/nunchaku/assets/wechat.jpg target="_blank"><img src=https://img.shields.io/badge/WeChat-07C160?logo=wechat&logoColor=white height=22px></a>
</div>

# Model Card for nunchaku-qwen-image-edit

![comfyui](https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/ComfyUI-nunchaku/workflows/nunchaku-qwen-image-edit.png)
This repository contains Nunchaku-quantized versions of [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit), an image-editing model based on [Qwen-Image](https://huggingface.co/Qwen/Qwen-Image), advances in complex text rendering. It is optimized for efficient inference while maintaining minimal loss in performance.



No recent news. Stay tuned for updates!

## Model Details

### Model Description

- **Developed by:** Nunchaku Team
- **Model type:** image-to-image
- **License:** apache-2.0
- **Quantized from model:** [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit)

### Model Files

**Data Type**: `INT4` for non-Blackwell GPUs (pre-50-series), `NVFP4` for Blackwell GPUs (50-series).
**Rank**: `r32` for faster inference, `r128` for better quality but slower inference.





### Base Models

Standard inference speed models for general use


| Data Type | Rank | Model Name | Comment |
|-----------|------|----------|---------|
| INT4 | r32 | [`svdq-int4_r32-qwen-image-edit.safetensors`](./svdq-int4_r32-qwen-image-edit.safetensors) |  |
|  | r128 | [`svdq-int4_r128-qwen-image-edit.safetensors`](./svdq-int4_r128-qwen-image-edit.safetensors) |  |
| NVFP4 | r32 | [`svdq-fp4_r32-qwen-image-edit.safetensors`](./svdq-fp4_r32-qwen-image-edit.safetensors) |  |
|  | r128 | [`svdq-fp4_r128-qwen-image-edit.safetensors`](./svdq-fp4_r128-qwen-image-edit.safetensors) |  |





### 4-Step Distilled Models

4-step distilled models fused with [Qwen-Image-Edit-Lightning-4steps-V1.0 LoRA](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-4steps-V1.0-bf16.safetensors) using LoRA strength = 1.0


| Data Type | Rank | Model Name | Comment |
|-----------|------|----------|---------|
| INT4 | r32 | [`svdq-int4_r32-qwen-image-edit-lightningv1.0-4steps.safetensors`](./svdq-int4_r32-qwen-image-edit-lightningv1.0-4steps.safetensors) | Fused with [Qwen-Image-Edit-Lightning-4steps-V1.0 LoRA](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-4steps-V1.0-bf16.safetensors) |
|  | r128 | [`svdq-int4_r128-qwen-image-edit-lightningv1.0-4steps.safetensors`](./svdq-int4_r128-qwen-image-edit-lightningv1.0-4steps.safetensors) | Fused with [Qwen-Image-Edit-Lightning-4steps-V1.0 LoRA](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-4steps-V1.0-bf16.safetensors). Better quality, slower inference |
| NVFP4 | r32 | [`svdq-fp4_r32-qwen-image-edit-lightningv1.0-4steps.safetensors`](./svdq-fp4_r32-qwen-image-edit-lightningv1.0-4steps.safetensors) | Fused with [Qwen-Image-Edit-Lightning-4steps-V1.0 LoRA](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-4steps-V1.0-bf16.safetensors) |
|  | r128 | [`svdq-fp4_r128-qwen-image-edit-lightningv1.0-4steps.safetensors`](./svdq-fp4_r128-qwen-image-edit-lightningv1.0-4steps.safetensors) | Fused with [Qwen-Image-Edit-Lightning-4steps-V1.0 LoRA](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-4steps-V1.0-bf16.safetensors). Better quality, slower inference |





### 8-Step Distilled Models

8-step distilled models fused with [Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-8steps-V1.0-bf16.safetensors) using LoRA strength = 1.0


| Data Type | Rank | Model Name | Comment |
|-----------|------|----------|---------|
| INT4 | r32 | [`svdq-int4_r32-qwen-image-edit-lightningv1.0-8steps.safetensors`](./svdq-int4_r32-qwen-image-edit-lightningv1.0-8steps.safetensors) | Fused with [Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-8steps-V1.0-bf16.safetensors) |
|  | r128 | [`svdq-int4_r128-qwen-image-edit-lightningv1.0-8steps.safetensors`](./svdq-int4_r128-qwen-image-edit-lightningv1.0-8steps.safetensors) | Fused with [Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-8steps-V1.0-bf16.safetensors). Better quality, slower inference |
| NVFP4 | r32 | [`svdq-fp4_r32-qwen-image-edit-lightningv1.0-8steps.safetensors`](./svdq-fp4_r32-qwen-image-edit-lightningv1.0-8steps.safetensors) | Fused with [Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-8steps-V1.0-bf16.safetensors) |
|  | r128 | [`svdq-fp4_r128-qwen-image-edit-lightningv1.0-8steps.safetensors`](./svdq-fp4_r128-qwen-image-edit-lightningv1.0-8steps.safetensors) | Fused with [Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Edit-Lightning-8steps-V1.0-bf16.safetensors). Better quality, slower inference |





### Model Sources

- **Inference Engine:** [nunchaku](https://github.com/nunchaku-tech/nunchaku)
- **Quantization Library:** [deepcompressor](https://github.com/nunchaku-tech/deepcompressor)
- **Paper:** [SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models](http://arxiv.org/abs/2411.05007)
- **Demo:** [demo.nunchaku.tech](https://demo.nunchaku.tech)

## Usage

- Diffusers Usage: See [qwen-image-edit.py](https://github.com/nunchaku-tech/nunchaku/blob/main/examples/v1/qwen-image-edit.py) and [qwen-image-edit-lightning.py](https://github.com/nunchaku-tech/nunchaku/blob/main/examples/v1/qwen-image-edit-lightning.py). Check this [tutorial](https://nunchaku.tech/docs/nunchaku/usage/qwen-image-edit.html) for more advanced usage.
- ComfyUI Usage: See [nunchaku-qwen-image-edit.json](https://nunchaku.tech/docs/ComfyUI-nunchaku/workflows/qwenimage.html#nunchaku-qwen-image-edit-json).

## Performance

![performance](https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/nunchaku/assets/efficiency.jpg)

## Citation

```bibtex
@inproceedings{
  li2024svdquant,
  title={SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models},
  author={Li*, Muyang and Lin*, Yujun and Zhang*, Zhekai and Cai, Tianle and Li, Xiuyu and Guo, Junxian and Xie, Enze and Meng, Chenlin and Zhu, Jun-Yan and Han, Song},
  booktitle={The Thirteenth International Conference on Learning Representations},
  year={2025}
}
```
