Model reference · open weights

Qwen-Image-Ed-2511

Qwen-Image-Ed-2511 is an open-weight image model from unsloth, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

Image unsloth 1 variants 260k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What Qwen-Image-Ed-2511 is

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. - Uses tooling from ComfyUI-GGUF by city96. - For more information on how to use and run the model in ComfyUI, read our guide. Samples 💜 <a href="https://chat.qwen.ai/"<bQwen 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/QwenImage.pdf"Tech Report</a &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qwenlm.github.io/blog/qwen-image-edit-2511/"Blog</a &nbsp&nbsp 🖥️ <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 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 The following contains a code snippet illustrating how to use Qwen-Image-Edit-2511: 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. Improved Multi-Person Consistency While Qwen-Image-Edit-2509 already improved cons

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

Makerunsloth
TypeImage models
Variants1
Based onQwen/Qwen-Image-Edit-2511
Released2025-12-20
Popularity260k downloads / month
Likes580
LicenceOpen weights

How it works

How image models work

Text promptwhat to makeText encoderunderstands itDiffusion stepsdenoise to pixelsImagePNG / JPEGA diffusion model starts from noise and denoises it, guided by your prompt, into a finished image.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
Qwen-Image-Edit-2511-GGUFGGUFWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys qwen-image-ed-2511 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qwen-image-ed-2511 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/images/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen-image-ed-2511","prompt":"a red bicycle","size":"1024x1024"}'

Details

Languages, data & research

Languages

en zh

Tags

gguf quantized unsloth qwen image-to-image en zh

Papers

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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