Qwen Image Edit LoRA

Qwen Image Edit LoRA

Playground

Qwen-Image-Edit — a 20B MMDiT model for next-gen image edit generation. Built on 20B Qwen-Image, it brings precise bilingual text editing (Chinese & English) while preserving style, and supports both semantic and appearance-level editing.

Features

Qwen-Image-Edit-LoRA

Qwen-Image-Edit with LoRA is a 20B MMDiT-based next-gen image editing model, Built on 20B Qwen-Image, it brings precise bilingual text editing (Chinese & English) while preserving style, and supports both semantic and appearance-level editing.

Key Features

• Precise bilingual text editing: Directly add, delete, or modify text in Chinese or English, while preserving font, size, kerning, and style.

• LoRA integration: Import up to 3 external LoRA weights (.safetensors), each with its own blending scale, for tailored effects.

• Style preservation: Maintains palette, lighting, and overall artistic intent even under substantial edits.

• SOTA benchmark results: Achieves state-of-the-art performance across multiple public image editing benchmarks.

Limits and Performance

• Max resolution per job: up to 1536 × 1536 pixels
• Max LoRAs: 3 per job (with individual scaling controls)
• Output formats: JPEG / PNG / WEBP
• Processing speed: ~6–12 seconds per image
• Input: Requires image + prompt (can include editing instructions and/or text edits)

Pricing

• $0.025 per image
• Each generated image is billed individually.

How to Use

1. Upload or paste a link to your source image.

2. Write a prompt describing desired edits (appearance or semantic).

3. (Optional) Add up to 3 LoRAs:

   • Provide LoRA path/URL.
   • Adjust scale for each (0.1–1.0 recommended).

4. Adjust size (width & height, up to 1536×1536).

5. (Optional) Add a seed for reproducibility.

6. Run the job → preview results → refine with prompt or LoRA scaling.

Pro tips for best results

• Use appearance editing for clean local changes (e.g., shirt color).
• Use semantic editing for creative/global changes (e.g., pose, style transfer).
• For text edits, clearly specify text content + style in the prompt.
• Combine LoRAs for hybrid results, but keep scale balanced (too high may distort).
• Lock the seed when testing multiple LoRAs to compare effects consistently.

Note

• If you did not upload the image locally, please ensure that the image URL is accessible! A successfully accessible image will display a preview in the interface.

# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/qwen-image/edit-lora" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "loras": [],
    "seed": -1,
    "output_format": "jpeg",
    "enable_base64_output": false,
    "enable_sync_mode": false
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"