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Qwen-Image is a powerful 20-billion parameter foundation model designed for advanced image generation and precise editing, with a particular strength in complex text rendering across diverse languages, especially Chinese. Built on the MMDiT architecture, it achieves remarkable fidelity in integrating text seamlessly into images while preserving typographic details and layout coherence. The model excels not only in text rendering but also in a wide range of artistic styles, including photorealistic, impressionist, anime, and minimalist aesthetics. Qwen-Image supports sophisticated editing tasks such as style transfer, object insertion and removal, detail enhancement, and even human pose manipulation, making it suitable for both professional and casual users. It also includes advanced image understanding capabilities like object detection, semantic segmentation, depth and edge estimation, and novel view synthesis.
Features
- Strong text rendering capabilities — particularly good with complex text layout, multilingual prompts, and preserving font/style in generated images
- Image editing pipelines: single-image editing as well as a newer version “Edit-2509” with multi-image editing support
- Native support for control inputs such as depth maps, edge maps, keypoint maps (ControlNet-style conditioning) to guide generation or editing
- Improved consistency in identity and style: better preservation of facial identity, product identity, font colors/types/materials, etc.
- Flexible deployment via Hugging Face Diffusers, ModelScope, with support for multi-GPU servers, prompt enhancement tools, and different aspect ratios
- Licensed under Apache-2.0, with technical reports, active demo/benchmark support (e.g. “AI Arena”) and frequent updates (e.g. Edit-2509)
Project Samples
License
Apache License V2.0Follow Qwen-Image
User Reviews
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Amazing open source image generation AI model