Qwen Image Edit 2511 GGUF

Providerunsloth
Categoryimage-to-image
Licenseapache-2.0
Downloads18.6K
Stars66

Overview

Qwen Image Edit 2511 GGUF is a specialized image-to-image model optimized for local deployment via the GGUF format. Unlike general-purpose diffusion models, this version focuses on precise image manipulation and editing tasks, allowing developers to modify visual content based on textual instructions while maintaining structural consistency. By leveraging GGUF quantization, it significantly lowers the VRAM barrier, making it viable for integration into edge applications or developer workstations without requiring enterprise-grade GPUs. It is particularly useful for building automated design tools, iterative asset refinement pipelines, and AI-driven photo editing software where low latency and local privacy are priorities.

Highlights

  • GGUF quantization for efficient local hardware deployment
  • Precise image-to-image editing with textual control
  • Low VRAM overhead compared to full-precision models
  • Apache-2.0 license for flexible commercial integration
  • Optimized for fast inference in local pipelines

Usage

Install
# Install Hugging Face transformers
pip install transformers torch
SDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("unsloth/Qwen-Image-Edit-2511-GGUF")
tokenizer = AutoTokenizer.from_pretrained("unsloth/Qwen-Image-Edit-2511-GGUF")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance:Before downloading, install huggingface_hub with:

Guidance
pip install -U huggingface_hub

CLI Download

Download the full repository

Download the full repository
huggingface-cli download unsloth/Qwen-Image-Edit-2511-GGUF

Download a single file to a local folder (e.g. config.json into ./dir)

Download a single file to a local folder (e.g. config.json into ./dir)
huggingface-cli download unsloth/Qwen-Image-Edit-2511-GGUF config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

SDK Download
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('unsloth/Qwen-Image-Edit-2511-GGUF')

Git Download

Make sure git-lfs is installed first

Git Download
git lfs install
git clone https://huggingface.co/unsloth/Qwen-Image-Edit-2511-GGUF

To skip LFS large-file downloads, use:

Skip LFS
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/unsloth/Qwen-Image-Edit-2511-GGUF

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

Install Transformers
pip install -U transformers torch

Load the model and run inference

Load the model and run inference
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('unsloth/Qwen-Image-Edit-2511-GGUF')
tokenizer = AutoTokenizer.from_pretrained('unsloth/Qwen-Image-Edit-2511-GGUF')

Model Download

We recommend downloading the model via the ModelScope CLI or SDK.

Guidance:Before downloading, install ModelScope with:

Guidance
pip install modelscope

CLI Download

Download the full repository

Download the full repository
modelscope download --model unsloth/Qwen-Image-Edit-2511-GGUF

Download a single file to a local folder (e.g. README.md into ./dir)

Download a single file to a local folder (e.g. README.md into ./dir)
modelscope download --model unsloth/Qwen-Image-Edit-2511-GGUF README.md --local_dir ./dir

See the docs for more CLI options

SDK Download

SDK Download
# 模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('unsloth/Qwen-Image-Edit-2511-GGUF')

Git Download

Make sure git-lfs is installed first

Git Download
git lfs install
git clone https://www.modelscope.cn/unsloth/Qwen-Image-Edit-2511-GGUF.git

To skip LFS large-file downloads, use:

Skip LFS
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/unsloth/Qwen-Image-Edit-2511-GGUF.git

ModelScope 模型页直接下载模型文件;无需将模型文件放在本站服务器。

Notebook Quickstart

Install the ModelScope library

Install the ModelScope library
pip install "modelscope[audio,cv,nlp,multi-modal,science]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html

Load the model and run inference

Load the model and run inference
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks

p = pipeline('text-generation', 'unsloth/Qwen-Image-Edit-2511-GGUF')

Full Documentation

来源: HuggingFace

---
base_model: Qwen/Qwen-Image-Edit-2511
language:

  • en

  • zh

license: apache-2.0
pipeline_tag: image-to-image
tags:
  • gguf

  • quantized

  • unsloth

  • qwen

widget:
  • text: cartoon sloth

output:
url: assets/sloth_cart.png
---

Read our How to Run Qwen-Image Guide! 💜

This is a GGUF quantized version of Qwen-Image-Edit-2511. <br>
unsloth/Qwen-Image-Edit-2511-GGUF uses Unsloth Dynamic 2.0 methodology for SOTA performance.

  • Important layers are upcasted to higher precision.
  • For more information on how to use and run the model in ComfyUI, read our guide.

<div>
<div style="display: flex; gap: 5px; align-items: center; ">
<a href="https://github.com/unslothai/unsloth/">
<img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133">
</a>
<a href="https://discord.gg/unsloth">
<img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173">
</a>
<a href="https://docs.unsloth.ai"/>
<img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143">
</a>
</div>
</div>

Samples

<table>
<tr>
<td><img src="assets/sloth_cur.png" width="200"></td>
</tr>
<tr>
<td><img src="assets/sloth_sketch.png" width="200"></td>
<td><img src="assets/sloth_excited.png" width="200"></td>
</tr>
<tr>
<td><img src="assets/sloth_cart.png" width="200"></td>
<td><img src="assets/sloth_starry.png" width="200"></td>
</tr>
</table>

---

<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/qwen_image_edit_logo.png" width="400"/>
<p>
<p align="center">
💜 <a href="https://chat.qwen.ai/"><b>Qwen Chat</b></a>&nbsp&nbsp | &nbsp&nbsp🤗 <a href="https://huggingface.co/Qwen/Qwen-Image-Edit-2511">Hugging Face</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/models/Qwen/Qwen-Image-Edit-2511">ModelScope</a>&nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/Qwen_Image.pdf">Tech Report</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qwenlm.github.io/blog/qwen-image-edit-2511/">Blog</a> &nbsp&nbsp
<br>
🖥️ <a href="https://huggingface.co/spaces/Qwen/Qwen-Image-Edit-2511">Demo</a>&nbsp&nbsp | &nbsp&nbsp💬 <a href="https://github.com/QwenLM/Qwen-Image/blob/main/assets/wechat.png">WeChat (微信)</a>&nbsp&nbsp | &nbsp&nbsp🫨 <a href="https://discord.gg/CV4E9rpNSD">Discord</a>&nbsp&nbsp| &nbsp&nbsp <a href="https://github.com/QwenLM/Qwen-Image">Github</a>&nbsp&nbsp
</p>

<p align="center">
<img src="https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/Qwen-Image/edit2511/edit2511big.JPG#center" width="1600"/>
<p>

Introduction

We are excited to introduce Qwen-Image-Edit-2511, an enhanced version over Qwen-Image-Edit-2509, featuring multiple improvements—including notably better consistency. To try out the latest model, please visit Qwen Chat and select the Image Editing feature.

Key enhancements in Qwen-Image-Edit-2511 include: mitigate image drift, improved character consistency,integrated LoRA capabilities, enhanced industrial design generation, and strengthened geometric reasoning ability.

Quick Start

Install the latest version of diffusers

code
pip install git+https://github.com/huggingface/diffusers

The following contains a code snippet illustrating how to use Qwen-Image-Edit-2511:

python
import os
import torch
from PIL import Image
from diffusers import QwenImageEditPlusPipeline

pipeline = QwenImageEditPlusPipeline.from_pretrained("Qwen/Qwen-Image-Edit-2511", torch_dtype=torch.bfloat16)
print("pipeline loaded")

pipeline.to('cuda')
pipeline.set_progress_bar_config(disable=None)
image1 = Image.open("input1.png")
image2 = Image.open("input2.png")
prompt = "The magician bear is on the left, the alchemist bear is on the right, facing each other in the central park square."
inputs = {
"image": [image1, image2],
"prompt": prompt,
"generator": torch.manual_seed(0),
"true_cfg_scale": 4.0,
"negative_prompt": " ",
"num_inference_steps": 40,
"guidance_scale": 1.0,
"num_images_per_prompt": 1,
}
with torch.inference_mode():
output = pipeline(inputs)
output_image = output.images[0]
output_image.save("output_image_edit_2511.png")
print("image saved at", os.path.abspath("output_image_edit_2511.png"))

Showcase

Qwen-Image-Edit-2511 Enhances Character Consistency
In Qwen-Image-Edit-2511, character consistency has been significantly improved. The model can perform imaginative edits based on an input portrait while preserving the identity and visual characteristics of the subject.

![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片1.JPG#center)
![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片2.JPG#center)
![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片3.JPG#center)
![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片4.JPG#center)

Improved Multi-Person Consistency
While Qwen-Image-Edit-2509 already improved consistency for single-subject editing, Qwen-Image-Edit-2511 further enhances consistency in multi-person group photos—enabling high-fidelity fusion of two separate person images into a coherent group shot:
![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片5.JPG#center)
![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片6.JPG#center)

Built-in Support for Community-Created LoRAs
Since Qwen-Image-Edit’s release, the community has developed many creative and high-quality LoRAs—greatly expanding its expressive potential. Qwen-Image-Edit-2511 integrates selected popular LoRAs directly into the base model, unlocking their effects without extra tuning.

For example, Lighting Enhancement LoRA
Realistic lighting control is now achievable out-of-the-box:
![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片7.JPG#center)

![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片8.JPG#center)

Another example, generating new viewpoints can now be done directly with the base model:

![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片9.JPG#center)

![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片10.JPG#center)

Industrial Design Applications

We’ve paid special attention to practical engineering scenarios—for instance, batch industrial product design:

![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片11.JPG#center)

![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片12.JPG#center)

…and material replacement for industrial components:
![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片13.JPG#center)

![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片14.JPG#center)

Enhanced Geometric Reasoning**
Qwen-Image-Edit-2511 introduces stronger geometric reasoning capability—e.g., directly generating auxiliary construction lines for design or annotation purposes:

![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片15.JPG#center)

![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/edit2511/幻灯片16.JPG#center)

That wraps up the major updates in Qwen-Image-Edit-2511.
Enjoy exploring the new capabilities! 🎉

License Agreement

Qwen-Image is licensed under Apache 2.0.

Citation

We kindly encourage citation of our work if you find it useful.

```bibtex
@misc{wu2025qwenimagetechnicalreport,
title={Qw

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