Bagel

Bagel is an open-source multimodal AI model that processes and generates both visual and textual content through a unified interface. It can handle image and text inputs to produce coherent responses, generate photorealistic images from descriptions, edit existing images based on natural language commands, and transform images between different artistic styles. The model uses a Mixture-of-Transformer-Experts architecture trained on trillions of multimodal tokens spanning language, image, video, and web data.

What sets Bagel apart is its native multimodal architecture that doesn't require separate models for different tasks. It features a 'thinking mode' where the model reasons through prompts before generating outputs, resulting in more detailed and coherent results. The model demonstrates advanced capabilities like free-form image editing, future frame prediction, 3D manipulation, and sequential reasoning—all through a single unified interface rather than specialized tools.

Bagel is particularly valuable for AI researchers and developers who want to experiment with multimodal AI without relying on proprietary APIs. Content creators can use it for generating consistent visual content, editing images with precise instructions, or transforming artwork between styles. The open-source nature means it can be fine-tuned, distilled, and deployed anywhere, making it accessible for both research and practical applications.