Qwen-Image AI Image Generator

Qwen-Image has achieved major breakthroughs in three aspects: text rendering, image editing, and visual understanding. Precise Chinese-English text rendering capabilities, accurate object-level editing control, and deep visual understanding make it a new paradigm for multimodal visual generation.

Qwen-Image completely solves the 'text gibberish' problem in AI art, supports Chinese-English mixed, multi-line paragraphs, automatic layout and alignment, can generate 20+ text styles including handwriting, printing, neon, engraving, with text clarity improved by 5-7 dB.

Supports object-level editing (add/delete/modify/replace), style-level conversion (oil painting→realistic, anime→ink painting), structure-level adjustment (pose, perspective, depth of field), maintaining consistency of background, lighting, identity and other elements during editing.

Adopts three major innovative architectures: using Qwen2.5-VL as conditional encoder, video universal VAE + fine-tuned image decoder, dual-stream MMDiT + MS-RoPE, supporting arbitrary resolution input, achieving perfect decoupling of understanding and generation.

Native Chinese support, strong Chinese-English mixed understanding, complex descriptions accurately restored. Supports multi-line, paragraphs, mixed languages, automatic layout, line breaks, alignment, reducing prompt engineering requirements.

E-commerce main images/details, event posters/KV, social media covers/cards, brand inspiration boards, game/film concept art and storyboards, concept design, advertising creativity and other creative workflows requiring high consistency and efficiency.

Zero-shot completion of depth estimation, segmentation, super-resolution, novel view synthesis and other tasks using only editing interface, performance approaching specialized models. Shows the model's understanding of images has reached a very high level.

Qwen-Image has been deeply optimized for Chinese understanding, complex Chinese descriptions and Chinese-English mixed can be more accurately understood and restored. Native Chinese support reduces ambiguity issues when traditional models process Chinese.

Supports high-resolution generation (up to 1328px), excellent detail reconstruction, especially text detail reconstruction improved by 5-7 dB. Image quality reaches professional level, suitable for commercial applications.

Generated images support personal and commercial use. We adopt a zero-retention policy, do not save your prompts and generated images, ensuring privacy and security, please comply with relevant laws and platform regulations.

Use clear Chinese-English descriptions, specify text content, font style, layout requirements. Qwen-Image will automatically handle layout, alignment, line breaks and other details, generating professional-level text effects.

Through three levels of editing control: object-level, style-level, structure-level, combined with deep visual understanding capabilities, ensuring editing accuracy and consistency. Maintaining consistency of background, lighting, identity and other elements during editing.

Adopts seven-level data distillation pipeline, concentrating 5B original image-text pairs into 1.2B high-quality samples. Specially synthesized 80 million Chinese-English paragraphs for text rendering training, Chinese text rendering data accounts for 45% of total synthesis.

Supports high-quality image formats suitable for various application scenarios. Can export formats suitable for web, print or professional use, maintaining complete quality.

Free public nodes may queue or timeout during peak hours. Suggest retrying later, or reducing resolution/steps to improve speed; we are also continuously optimizing stability.

Qwen-Image's greatest value lies in demonstrating the new paradigm of 'generation is understanding'. By combining the advantages of language models and image models, it can better understand user intent and achieve precise editing control.

Suggest fixing core prompts and style elements (lighting, lens, material, etc.), and reusing successful cases as templates. Qwen-Image has better stable performance for style consistency.

Qwen-Image reserves architectural space for video generation, 3D modeling and other functions. Its modular design facilitates subsequent upgrades and maintenance, each module can be optimized separately.

Traditional language models find it difficult to explain a picture with thousands of words, while Qwen-Image can explain thousands of words with one picture. This capability is reflected at the technical level, and shows great value in practical applications.

Qwen-Image achieves SOTA (state-of-the-art) performance in multiple public benchmark tests, fully proving its strength as a powerful image generation foundation model, setting new standards for open source AI image generation.