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base_model: Qwen/Qwen-Image-Edit-2509
base_model_relation: quantized
datasets:
- mit-han-lab/svdquant-datasets
language:
- en
library_name: diffusers
license: apache-2.0
pipeline_tag: text-to-image
tags:
- image-editing
- SVDQuant
- Qwen-Image-Edit-2509
- Diffusion
- Quantization
- ICLR2025
---
<p align="center" style="border-radius: 10px">
<img src="https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/nunchaku/assets/nunchaku.svg" 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-2509
This repository contains Nunchaku-quantized versions of [Qwen-Image-Edit-2509](https://huggingface.co/Qwen/Qwen-Image-Edit-2509), 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.
## News
- [2025-09-25] 🔥 Release **4-bit [4/8-step lightning Qwen-Image-Edit](https://huggingface.co/lightx2v/Qwen-Image-Lightning)**!
- [2025-09-24] 🚀 Release 4-bit SVDQuant quantized Qwen-Image-Edit-2509 model with rank 32 and 128!
## Model Details
### Model Description
- **Developed by:** Nunchaku Team
- **Model type:** image-to-image
- **License:** apache-2.0
- **Quantized from model:** [Qwen-Image-Edit-2509](https://huggingface.co/Qwen/Qwen-Image-Edit-2509)
### Model Files
- [`svdq-int4_r32-qwen-image-edit-2509.safetensors`](./svdq-int4_r32-qwen-image-edit-2509.safetensors): SVDQuant INT4 (rank 32) Qwen-Image-Edit-2509 model. For users with non-Blackwell GPUs (pre-50-series).
- [`svdq-int4_r128-qwen-image-edit-2509.safetensors`](./svdq-int4_r128-qwen-image-edit-2509.safetensors): SVDQuant INT4 (rank 128) Qwen-Image-Edit-2509 model. For users with non-Blackwell GPUs (pre-50-series). It offers better quality than the rank 32 model, but it is slower.
- [`svdq-int4_r32-qwen-image-edit-2509-lightningv2.0-4steps.safetensors`](./svdq-int4_r32-qwen-image-edit-2509-lightningv2.0-4steps.safetensors): SVDQuant INT4 (rank 32) 4-step Qwen-Image-Edit-2509 model by fusing [Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors) using LoRA strength = 1.0. For users with non-Blackwell GPUs (pre-50-series).
- [`svdq-int4_r128-qwen-image-edit-2509-lightning`](./svdq-int4_r128-qwen-image-edit-2509-lightning): SVDQuant INT4 (rank 128) 4-step Qwen-Image-Edit-2509 model by fusing [Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors) using LoRA strength = 1.0. For users with non-Blackwell GPUs (pre-50-series).
- [`svdq-int4_r32-qwen-image-edit-2509-lightningv2.0-8steps.safetensors`](./svdq-int4_r32-qwen-image-edit-2509-lightningv2.0-8steps.safetensors): SVDQuant INT4 (rank 32) 8-step Qwen-Image-Edit-2509 model by fusing [Qwen-Image-Lightning-8steps-V2.0-bf16.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-8steps-V2.0-bf16.safetensors) using LoRA strength = 1.0. For users with non-Blackwell GPUs (pre-50-series).
- [`svdq-int4_r128-qwen-image-edit-2509-lightningv2.0-8steps.safetensors`](./svdq-int4_r128-qwen-image-edit-2509-lightningv2.0-8steps.safetensors): SVDQuant INT4 (rank 128) 8-step Qwen-Image-Edit-2509 model by fusing [Qwen-Image-Lightning-8steps-V2.0-bf16.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-8steps-V2.0-bf16.safetensors) using LoRA strength = 1.0. For users with non-Blackwell GPUs (pre-50-series).
- [`svdq-fp4_r32-qwen-image-edit-2509.safetensors`](./svdq-fp4_r32-qwen-image-edit-2509.safetensors): SVDQuant NVFP4 (rank 32) Qwen-Image-Edit-2509 model. For users with Blackwell GPUs (50-series).
- [`svdq-fp4_r128-qwen-image-edit-2509.safetensors`](./svdq-fp4_r128-qwen-image-edit-2509.safetensors): SVDQuant NVFP4 (rank 128) Qwen-Image-Edit-2509 model. For users with Blackwell GPUs (50-series). It offers better quality than the rank 32 model, but it is slower.
- [`svdq-fp4_r32-qwen-image-edit-2509-lightningv2.0-4steps.safetensors`](./svdq-fp4_r32-qwen-image-edit-2509-lightningv2.0-4steps.safetensors): SVDQuant NVFP4 (rank 32) 4-step Qwen-Image-Edit-2509 model by fusing [Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors) using LoRA strength = 1.0. For users with Blackwell GPUs (50-series).
- [`svdq-fp4_r128-qwen-image-edit-2509-lightningv2.0-4steps.safetensors`](./svdq-fp4_r128-qwen-image-edit-2509-lightningv2.0-4steps.safetensors): SVDQuant NVFP4 (rank 128) 4-step Qwen-Image-Edit-2509 model by fusing [Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors) using LoRA strength = 1.0. For users with Blackwell GPUs (50-series).
- [`svdq-fp4_r32-qwen-image-edit-2509-lightningv2.0-8steps.safetensors`](./svdq-fp4_r32-qwen-image-edit-2509-lightningv2.0-8steps.safetensors): SVDQuant NVFP4 (rank 32) 8-step Qwen-Image-Edit-2509 model by fusing [Qwen-Image-Lightning-8steps-V2.0-bf16.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-8steps-V2.0-bf16.safetensors) using LoRA strength = 1.0. For users with Blackwell GPUs (50-series).
- [`svdq-fp4_r128-qwen-image-edit-2509-lightningv2.0-8steps.safetensors`](./svdq-fp4_r128-qwen-image-edit-2509-lightningv2.0-8steps.safetensors): SVDQuant NVFP4 (rank 128) 8-step Qwen-Image-Edit-2509 model by fusing [Qwen-Image-Lightning-8steps-V2.0-bf16.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-8steps-V2.0-bf16.safetensors) using LoRA strength = 1.0. For users with Blackwell GPUs (50-series).
### 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:** [svdquant.mit.edu](https://svdquant.mit.edu)
## Usage
- Diffusers Usage: See [qwen-image-edit-2509.py](https://github.com/nunchaku-tech/nunchaku/blob/main/examples/v1/qwen-image-edit-2509.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-2509.json](https://nunchaku.tech/docs/ComfyUI-nunchaku/workflows/qwenimage.html#nunchaku-qwen-image-edit-2509-json).
## Performance
## 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}
}
``` |