BAGEL

What is BAGEL?

BAGEL is an open-source, natively multimodal AI model developed by ByteDance-Seed under the permissive Apache 2.0 license. Engineered for seamless integration of vision and language, BAGEL excels in understanding, generating, and manipulating both images and text within a single unified framework. With performance on par with leading closed models such as GPT-4o and Gemini 2.0, BAGEL enables photorealistic content creation, precise visual editing, and intelligent reasoning—fully customizable and deployable across any environment.

How to use BAGEL?

Leveraging its flexible multimodal interface, BAGEL allows users to input and receive mixed formats of text and images dynamically. Whether crafting detailed image generations from descriptive prompts, modifying existing visuals while preserving key features, or navigating simulated environments through timed commands, BAGEL supports rich, multi-turn interactions. By activating its thinking mode, users can refine outputs through step-by-step reasoning, making it ideal for creators, designers, and developers seeking high-fidelity, context-aware results.

Key Features From BAGEL

Unified Multimodal Architecture

Advanced Image and Text Comprehension

High-Fidelity Image and Video Frame Generation

Precision Image Editing with Identity Preservation

Creative Style Transfer Across Domains

Interactive Navigation in Simulated Worlds

Compositional Reasoning for Complex Queries

Thinking Mode for Enhanced Output Control

Initialization from Large Language Models

Mixture-of-Transformer-Experts (MoT) Design

FAQ from BAGEL

What is BAGEL?

How does BAGEL handle multimodal tasks?

What makes BAGEL stand out among open-source models?

When was BAGEL made publicly available?

• BAGEL Company

  BAGEL is developed by ByteDance-Seed, a research initiative under ByteDance.

• BAGEL Github

  Access the full repository and documentation at: https://github.com/bytedance-seed/BAGEL

FAQ from BAGEL

What is BAGEL?

BAGEL is an open-source unified multimodal AI model created by ByteDance-Seed. Built on a native multimodal architecture, it supports advanced capabilities in image and text understanding, generation, editing, and environmental navigation—all under the Apache 2.0 license for unrestricted use and deployment.

How does BAGEL handle multimodal tasks?

BAGEL processes and generates both visual and textual data within a single integrated pipeline. It accepts combined inputs (e.g., images with captions) and delivers mixed-format responses, enabling fluid interactions like conversational image editing, style transformation, and scene navigation through natural language or timed instructions.

What makes BAGEL stand out among open-source models?

BAGEL combines state-of-the-art performance with full openness. Its Mixture-of-Transformer-Experts (MoT) design, compositional reasoning, and built-in thinking mode allow it to outperform many existing open models on benchmark tasks, rivaling top proprietary systems in versatility and output quality.

When was BAGEL released?

BAGEL was officially released on May 20, 2025, marking a significant advancement in accessible, high-performance multimodal AI technology.