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Advanced Image-to-Image Editing

Tell it what to change in plain words — "put her in a blue blazer", "merge these two people into one group photo" — and it edits the picture without turning your subject into a stranger. The stubborn problem with AI editing is drift: touch one thing and the face or scene quietly shifts too. This release is tuned to hold identity steady across edits, even when fusing multiple people. Built by the Qwen team at Alibaba as an enhanced version of Qwen-Image-Edit-2509..

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What it does

Qwen-Image-Edit-2511 is an image editing model developed by Qwen (Alibaba), and is an enhanced version of Qwen-Image-Edit-2509. It takes one or more reference images alongside a natural language instruction and produces a high-fidelity edited output. The model is particularly strong at preserving subject identity across edits, compositing multiple subjects into coherent scenes, and handling practical design and engineering scenarios. It supports the QwenImageEditPlusPipeline via Hugging Face Diffusers and is deployable on CUDA-compatible hardware.

Problem it solves

• Image drift & consistency – Mitigates drift between input and output, keeping edits faithful to the source subject's identity and visual characteristics
• Multi-person consistency – Enables high-fidelity fusion of two separate person images into a coherent group scene
• LoRA integration – Selected community-created LoRAs (e.g., lighting enhancement, novel viewpoint generation) are baked directly into the base model, removing the need for extra tuning steps
• Industrial design – Supports batch product design generation and material replacement for engineering and manufacturing workflows
• Geometric reasoning – Can generate auxiliary construction lines and annotations directly within edited images, useful for design and technical applications
• Creative workflows – Suitable for portrait editing, character storytelling, style transfer, and multi-subject scene composition

Input/Output

• Input: Images and text instructions

  • Required:
    • Image: RGB image to edit (the main image being modified)
    • Prompt: Natural language text describing desired edits
  • Optional:
    • Reference Image: Additional image used as style/content reference for edits
  • Diffusion Steps: 5-40 (higher = better quality, slower)
  • Random Seed: Enter a number for reproducibility, or use -1 to randomly generate.
  • Output Image Size - Width x Height: 512 ~ 1600

  

• Output: High-quality RGB image with edits applied

  • If reference image provided: Uses reference as guidance (e.g., copy specific details from reference)
  • If no reference image: Generates based on text prompt alone (e.g., creates random variation)

Accuracy & Speed

• Key Enhancements over Qwen-Image-Edit-2509

  Feature	Improvement
  Image Drift	Mitigated — edits stay closer to source identity
  Character Consistency	Significantly improved for single-subject edits
  Multi-Person Consistency	New — fuses two separate portraits into coherent group photos
  LoRA Support	Community LoRAs integrated natively (lighting, viewpoints, etc.)
  Industrial Design	Enhanced batch product design & material replacement
  Geometric Reasoning	New — generates construction lines and design annotations

Technical Details

Compliance & Provenance