What is LongCat-Image
LongCat-Image is Meituan's open-source high-performanceimage generationmodel. With only 6B parameters, it reaches the top open-source level in text-to-image generation and image editing. The model adopts an innovative architecture and training strategy, supports high-quality Chinese text rendering, covers 8,105 Chinese characters, and is suitable for poster, advertising, and other design scenarios. Through multi-task learning and adversarial training, the model improves image realism and texture details, and provides a complete toolchain from pre-training to fine-tuning, helping developers explore more possibilities in visual generation with a low barrier to entry.
Main Features of LongCat-Image
-
Text-to-Image：Generates high-quality images based on text descriptions entered by users, supports multiple styles and scenarios, and is suitable for creative design, social media content creation, and more.
-
Image Editing：Provides powerful image editing capabilities, supports style transfer, attribute editing, composition adjustment, and more. It can precisely modify image content according to user instructions, and is suitable for design, advertising, film and television post-production, and other fields.
-
Chinese Text Rendering：Specially optimizes Chinese text generation capability, covers the 8,105 Chinese characters in the Table of General Standard Chinese Characters, supports rendering of complex strokes and rare characters, and is suitable for scenarios such as poster design, signboard production, and illustrations for classical poetry.
-
Improved Realism and Texture Details：Through systematic data filtering and adversarial training, the generated images have higher realism and texture details, avoiding a "plastic" texture.
-
Low-Barrier Development and Application：Provides a complete toolchain from pre-trained models to fine-tuning code, supports advanced development features such as SFT and LoRA, and facilitates secondary development and customization by developers.
Technical Principles of LongCat-Image
- Architecture Design：Adopts an architecture design in which text-to-image generation and image editing share the same source, achieving efficient collaborative improvement through a compact 6B parameter scale, while balancing instruction-following accuracy, image generation quality, and text rendering capability.
- Progressive Learning Strategy：In the pre-training stage, multi-source data and instruction rewriting strategies are used to improve the model's ability to understand diverse instructions.In the SFT stage, manually finely labeled data is introduced to further improve instruction-following accuracy and generalization. In the RL stage, dual reward models for OCR and aesthetics are incorporated to optimize text accuracy and the naturalness of background integration.
- Data Engineering and Training Paradigm：Through strict pre-training data filtering, avoid the "plastic" texture of generated images.In the SFT stage, manually carefully screened data is used to align with public aesthetics and improve the realism and beauty of generated images.Innovatively introduces an AIGC content detector as a reward model, using adversarial signals to guide the model in learning real-world physical textures and lighting effects.
- Chinese Text Generation Optimization: Uses a curriculum learning strategy. In the pre-training stage, it learns glyphs, covering the 8,105 Chinese characters in the Table of General Standard Chinese Characters. In the SFT stage, real-world text image data is introduced to improve the generalization ability of fonts and layout. In the RL stage, text accuracy and the naturalness of background integration are further improved.
Project Address of LongCat-Image
- GitHub Repository：https://github.com/meituan-longcat/LongCat-Image
- HuggingFace Model Library：https://huggingface.co/meituan-longcat/LongCat-Image
- Technical Paper：https://github.com/meituan-longcat/LongCat-Image/blob/main/assets/LongCat_Image_Technical_Report.pdf
Application Scenarios of LongCat-Image
- Poster Design: Quickly generate high-quality posters based on creative copy, supporting text rendering and style customization to meet the needs of advertising, event promotion, and more.
- Advertising Material Production: Generate attractive advertising images for brands, supporting different scenarios and styles, reducing advertising production costs.
- Film and Television Concept Art: Generate movie posters, concept art, and scene design drawings for film and television production, assisting script creation and visual effect design.
-
Teaching Assistance: The model can generate images related to teaching content, such as historical scenes, scientific experiment illustrations, etc., helping students better understand and remember knowledge.
-
Style Transfer and Beautification: Perform style transfer, background replacement, portrait beautification, and other edits on personal photos to meet personalized needs.