BAGEL is an open-source unified multimodal model that can be fine-tuned, distilled, and deployed anywhere. It offers functionality comparable to proprietary systems like GPT-4o and Gemini 2.0, with capabilities for precise, accurate, and photorealistic image generation through a natively multimodal architecture.
Free
How to use BAGEL?
BAGEL can be used for a variety of tasks including chat, generation, editing, style transfer, navigation, composition, and thinking. It handles both image and text inputs and outputs, making it versatile for developers and researchers looking to integrate advanced AI capabilities into their projects.
BAGEL 's Core Features
Unified generation and understanding model
Handles both image and text inputs and outputs
High-fidelity, photorealistic image generation
Advanced image editing capabilities
Style transfer across different visual worlds
Navigation knowledge distilled from real-world video
Compositional abilities for multi-turn conversations
BAGEL 's Use Cases
Developers can integrate BAGEL into applications requiring advanced AI interactions with complex systems.
Researchers can use BAGEL for experiments in multimodal AI, leveraging its open-source nature for customization.
Content creators can utilize BAGEL for generating photorealistic images and videos, enhancing creative projects.
Educators can employ BAGEL as a teaching tool for AI and multimodal technologies.
Businesses can deploy BAGEL for customer service chatbots that understand and generate both text and images.
