GigaBrain-0 - Open source embodied base model driven by world model generation data

What is GigaBrain-0

GigaBrain-0 isChina's First End-to-End Vision-Language-Action (VLA) Embodied Base Model Using World Model Generation Data for Real Machine Generalization, jointly released as open source by Excellent Vision and Hubei Humanoid Robot Innovation Center.Adopting a hybrid Transformer architecture, it fuses a pre-trained Visual Language Model (VL-M) with a Diffusion in Motion Transformer (DIT) to support RGB-D inputs and enhance 3D spatial perception.Introducing the Embodied CoT mechanism to generate intermediate reasoning steps (e.g., trajectories, subgoal languages) to improve long-duration task planning.The data engine is built with the "world model" as the core, and through simulation generation, style migration, perspective change and other techniques, diverse training data are generated to reduce the dependence on real-world data.The data covers multiple scenarios such as industrial, commercial, office, and home to enhance the model generalization capability.

Functional Features of GigaBrain-0

• Data Efficiency: Generate diverse data with the help of world models to reduce the dependence on real robot data and improve generalization capabilities.
• Spatial perception: Enhanced accuracy in perceiving 3D position and spatial layout of objects via RGB-D input.
• Reasoning Strengthening: Generate intermediate reasoning steps to simulate human thought processes and enhance reasoning for complex tasks.
• Capacity for task generalization: Demonstrates excellent generalization performance in scenarios such as appearance, object placement, and camera viewpoint changes.
• Lightweight Deployment: Introducing the GigaBrain-0-Small version, designed for edge platforms to enable efficient inference and deployment.

Core Benefits of GigaBrain-0

• Efficient data utilization: Generating diverse data through world models dramatically reduces the reliance on expensive and time-consuming real robot data, and significantly improves the model's generalization ability and learning efficiency.
• Enhanced spatial awareness: Modeling with RGB-D inputs enables the model to more accurately perceive the 3D position and spatial layout of objects, leading to more precise manipulation in complex scenes.
• Reinforcement of reasoning skills: Introducing embodied thought chain supervision, the model is able to generate intermediate reasoning steps while performing tasks, simulating the human thought process and enhancing the reasoning ability for long duration tasks and complex operations.
• Excellent generalization performance: Demonstrates excellent generalization ability in a wide range of scenarios such as appearance, object placement and camera viewpoint changes, and is able to adapt to task requirements under different conditions.
• Lightweight and efficient deployment: Introducing the lightweight version of GigaBrain-0-Small, designed for edge platforms to enable efficient inference on resource-constrained devices and meet deployment requirements in real-world applications.

What is the official website for GigaBrain-0?

• Project website:: https://gigabrain0.github.io/
• Github repository:: https://github.com/open-gigaai/giga-brain-0
• HuggingFace Model Library:: https://huggingface.co/open-gigaai
• arXiv Technical Paper:: https://arxiv.org/pdf/2510.19430

People for GigaBrain-0

• Robotics researchers: GigaBrain-0 provides new tools for studying the fusion of vision, language and action in robots, helping to explore more efficient data utilization and stronger generalization capabilities.
• Artificial Intelligence Developers: The model provides a powerful basis for developing robotics applications for complex tasks in scenarios that require high-precision manipulation and long-duration task planning.
• Industrial Automation Engineer: In industrial environments, GigaBrain-0 can be used to develop and deploy robotic systems that increase productivity and flexibility, especially in tasks that require fine manipulation and mobile operation.
• Edge computing device developers: The GigaBrain-0-Small version opens up the possibility of deploying robotic applications on resource-constrained edge devices for developers who need to achieve efficient inference on miniaturized devices.
• Universities and Research Institutions: It provides a platform for students and researchers of related majors to practice and research, and helps to promote the application and development of robotics in education and research.