Qwen Image Edit

Edit images with text prompts. Supports precise text editing and semantic/appearance modifications.

Model Overview

A powerful image editing model that leverages Qwen-Image's text rendering capabilities and integrates visual semantic and appearance control for precise image modifications.

Best At

• Precise text editing within images (bilingual support).
• Semantic editing: Modifying image content while maintaining visual semantics (e.g., object rotation, style transfer, IP creation).
• Appearance editing: Adding, removing, or modifying specific elements while keeping other regions unchanged (e.g., adding objects, reflections, changing backgrounds or clothing).
• Transforming images into different artistic styles.

Limitations / Not Good At

• While it excels at precise edits, complex or highly abstract editing requests might require iterative refinement.
• The model's performance on extremely low-resolution or heavily artifacted input images may vary.

Ideal Use Cases

• Adding or modifying text on product mockups, posters, or merchandise.
• Creating custom illustrations for blog posts or social media by altering existing images.
• Generating variations of existing artwork or photos with different styles or elements.
• Virtual avatar creation and character design.
• Rapid prototyping of visual content requiring specific text overlays.

Input & Output Format

• Input: Image file (JPEG, PNG, GIF, WEBP) and a text prompt describing the desired edits. Optional parameters include aspect ratio, speed optimization, seed, output format, output quality, and safety checker disabling.
• Output: An array of URIs pointing to the edited image files.

Performance Notes

• The go_fast parameter allows for faster predictions with additional optimizations.
• output_quality influences the quality of non-PNG outputs (0-100).