Instructions to use nunchaku-ai/nunchaku-qwen-image-edit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nunchaku-ai/nunchaku-qwen-image-edit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nunchaku-ai/nunchaku-qwen-image-edit", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Model Card for nunchaku-qwen-image-edit
This repository contains Nunchaku-quantized versions of Qwen-Image-Edit, an image-editing model based on Qwen-Image, advances in complex text rendering. It is optimized for efficient inference while maintaining minimal loss in performance.
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Model Details
Model Description
- Developed by: Nunchaku Team
- Model type: image-to-image
- License: apache-2.0
- Quantized from model: 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 |
|
| r128 | svdq-int4_r128-qwen-image-edit.safetensors |
||
| NVFP4 | r32 | svdq-fp4_r32-qwen-image-edit.safetensors |
|
| r128 | 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 using LoRA strength = 1.0
| Data Type | Rank | Model Name | Comment |
|---|---|---|---|
| INT4 | r32 | svdq-int4_r32-qwen-image-edit-lightningv1.0-4steps.safetensors |
Fused with Qwen-Image-Edit-Lightning-4steps-V1.0 LoRA |
| r128 | svdq-int4_r128-qwen-image-edit-lightningv1.0-4steps.safetensors |
Fused with Qwen-Image-Edit-Lightning-4steps-V1.0 LoRA. Better quality, slower inference | |
| NVFP4 | r32 | svdq-fp4_r32-qwen-image-edit-lightningv1.0-4steps.safetensors |
Fused with Qwen-Image-Edit-Lightning-4steps-V1.0 LoRA |
| r128 | svdq-fp4_r128-qwen-image-edit-lightningv1.0-4steps.safetensors |
Fused with Qwen-Image-Edit-Lightning-4steps-V1.0 LoRA. Better quality, slower inference |
8-Step Distilled Models
8-step distilled models fused with Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA using LoRA strength = 1.0
| Data Type | Rank | Model Name | Comment |
|---|---|---|---|
| INT4 | r32 | svdq-int4_r32-qwen-image-edit-lightningv1.0-8steps.safetensors |
Fused with Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA |
| r128 | svdq-int4_r128-qwen-image-edit-lightningv1.0-8steps.safetensors |
Fused with Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA. Better quality, slower inference | |
| NVFP4 | r32 | svdq-fp4_r32-qwen-image-edit-lightningv1.0-8steps.safetensors |
Fused with Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA |
| r128 | svdq-fp4_r128-qwen-image-edit-lightningv1.0-8steps.safetensors |
Fused with Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA. Better quality, slower inference |
Model Sources
- Inference Engine: nunchaku
- Quantization Library: deepcompressor
- Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
- Demo: demo.nunchaku.tech
Usage
- Diffusers Usage: See qwen-image-edit.py and qwen-image-edit-lightning.py. Check this tutorial for more advanced usage.
- ComfyUI Usage: See nunchaku-qwen-image-edit.json.
Performance
Citation
@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}
}
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Model tree for nunchaku-ai/nunchaku-qwen-image-edit
Base model
Qwen/Qwen-Image-Edit