Bagel
Why Choose Bagel?
Go for this if you want a powerful open-source multimodal AI that handles image and text understanding, generation, and editing with high precision. It’s ideal for those who want advanced features like photorealistic outputs and style transfer, plus the freedom to fine-tune and deploy anywhere.
Open-source unified multimodal AI for understanding, generation, editing.
Bagel Introduction
What is Bagel?
BAGEL by ByteDance-Seed is an Apache 2.0 open-source unified multimodal model designed for advanced image/text understanding, generation, editing, and navigation. It offers capabilities comparable to proprietary systems like GPT-4o and Gemini 2.0. BAGEL can be fine-tuned, distilled, and deployed anywhere, providing precise, accurate, and photorealistic outputs through its natively multimodal architecture.
How to use Bagel?
BAGEL can be used through its unified multimodal interface, accepting both image and text inputs and outputs in a mixed format. Users can engage in multi-turn conversations, generate high-fidelity images and video frames, perform image editing, apply style transfers, navigate virtual environments, and leverage its compositional and thinking modes by providing prompts and interacting with the model.
Why Choose Bagel?
Go for this if you want a powerful open-source multimodal AI that handles image and text understanding, generation, and editing with high precision. It’s ideal for those who want advanced features like photorealistic outputs and style transfer, plus the freedom to fine-tune and deploy anywhere.
Bagel Features
AI Image Generator
- ✓Unified Multimodal Model
- ✓Image/Text Understanding
- ✓Image/Text Generation (photorealistic images, video frames)
- ✓Image Editing (preserves visual identities and details)
- ✓Style Transfer
- ✓Navigation (in diverse environments)
- ✓Compositional Abilities (multi-turn conversations)
- ✓Thinking Mode (enhances generation and editing through reasoning)
- ✓Pre-training initialized from large language models
- ✓Mixture-of-Transformer-Experts (MoT) architecture
FAQ?
Pricing
Pricing information not available