++   ⭐️ Project   |   ⭐️ Github   |   🤖 ModelScope   |   📑 Technical Report   |   💬 WeChat +
++   🎯 RoboOS: An Efficient Open-Source Multi-Robot Coordination System for RoboBrain. +
++  🌍 RoboBrain 1.0: A Unified Brain Model for Robotic Manipulation from Abstract to Concrete. +
+ +## 🗞️ News +- **`2025-07-23`**: 🤗 **[RoboBrain 2.0-3B](https://huggingface.co/BAAI/RoboBrain2.0-3B) model checkpoint has been released in Huggingface.** +- **`2025-07-03`**: 🤗 [RoboBrain 2.0-32B](https://huggingface.co/BAAI/RoboBrain2.0-32B) model checkpoint has been released in Huggingface. +- **`2025-06-07`**: 🎉 We highlight the training framework ([FlagScale](https://github.com/FlagOpen/FlagScale)) developed by *BAAI Framework R&D team*, and the evaluation framework ([FlagEvalMM](https://github.com/flageval-baai/FlagEvalMM)) by *BAAI FlagEval team*. Both are used for RoboBrain 2.0. +- **`2025-06-06`**: 🤗 [RoboBrain 2.0-7B](https://huggingface.co/BAAI/RoboBrain2.0-7B) model checkpoint has been released in Huggingface.. +- **`2025-06-06`**: 🔥 We're excited to announce the release of our more powerful [RoboBrain 2.0](https://superrobobrain.github.io/). +- **`2025-04-11`**: 🎉 [RoboBrain 1.0](https://github.com/FlagOpen/RoboBrain/) was selected for CVPR 2025's official [Embodied AI Trends Commentary](https://cvpr.thecvf.com/Conferences/2025/News/AI_Enhanced_Robotics). +- **`2025-02-27`**: 🌍 [RoboBrain 1.0](http://arxiv.org/abs/2502.21257/) was accepted to CVPR2025. + +## 🔥 Overview +We are thrilled to announce the launch of **RoboBrain 2.0**, the most powerful open-source embodied brain model to date. Compared to its predecessor, RoboBrain 1.0, the new version is designed to unify perception, reasoning, and planning for complex embodied tasks in physical environments. RoboBrain 2.0 comes in three variants: an ultra-lightweight 3B model, a lightweight 7B model, and a full-scale 32B model, all featuring a heterogeneous architecture with a vision encoder and a language model. +Despite its compact size, RoboBrain 2.0 delivers exceptional performance across a wide range of embodied reasoning tasks. The newly released 3B model is optimized for resource-constrained scenarios, being extremely lightweight and easy to deploy, with spatial understanding capabilities comparable to the 7B model, making it ideal for edge devices and real-time applications. The 7B model strikes a balance between performance and computational requirements, suitable for diverse scenarios, while the 32B model achieves leading results in most spatial and temporal benchmarks, surpassing prior open-source and proprietary models. RoboBrain 2.0 supports critical real-world embodied intelligence capabilities, including spatial understanding (e.g., affordance prediction, spatial referring, trajectory forecasting) and temporal decision-making (e.g., closed-loop interaction, multi-agent long-horizon planning, and real-time scene memory). +This report details the model architecture, data construction, multi-stage training strategies, infrastructure, and practical applications. We hope RoboBrain 2.0 advances embodied AI research and serves as a practical step toward building generalist embodied agents. +
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