BAGEL
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Introduction
BAGEL is an open-source unified multimodal model for generation and understanding, fine-tunable and deployable anywhere.
Listed on
July 23, 2026
What is BAGEL?
BAGEL is an open-source unified multimodal model that handles both image and text inputs and outputs in a mixed format. It is pre-trained on large-scale interleaved video and web data, providing capabilities for reasoning, conversation, image generation, editing, style transfer, navigation, and composition. It offers functionality comparable to proprietary systems like GPT-4o and Gemini 2.0 in an open form.
How to use BAGEL?
- BAGEL can be fine-tuned, distilled, and deployed anywhere. Users can access the model via GitHub, HuggingFace, and a demo showcase. The model supports chat, generation, editing, style transfer, navigation, and composition tasks through a unified interface.
Core features of BAGEL
- Unified multimodal generation and understanding
- Image and text mixed input/output
- High-fidelity photorealistic image and video generation
- Image editing with visual identity preservation
- Style transfer across different visual styles
- Navigation knowledge from real-world video
- Compositional reasoning and multi-turn conversation
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