School Logo Light School Logo Dark Company Logo
Auto

RynnBrain: Open Embodied Foundation Models

Ronghao Dang*,†,‡ Jiayan Guo*,† Bohan Hou* Sicong Leng* Kehan Li*,† Xin Li*,† Jiangping Liu* Yunxuan Mao* Zhikai Wang* Yuqian Yuan* Minghao Zhu*
Xiao Lin Yang Bai Qian Jiang Yaxi Zhao Minghua Zeng Junlong Gao Yuming Jiang Jun Cen Siteng Huang Liuyi Wang Wenqiao Zhang Chengju Liu Jianfei Yang Shijian Lu Deli Zhao
* Core contributors (alphabetical order) Project lead Correspondence

Abstract

We present RynnBrain, an embodied foundation model grounded in physical reality. Moving beyond passive observation, RynnBrain anchors its understanding in the physical world through comprehensive egocentric cognition, precise spatiotemporal grounding, and real task planning. This systematic upgrade enables active, physics-aware reasoning and complex task execution.

We release RynnBrain in dense (2B, 8B) and MoE (30B) variants, alongside three specialized models: RynnBrain‑Plan (manipulation planning), RynnBrain‑Nav (navigation), and RynnBrain‑CoP (spatial reasoning).

🌟 Key Highlights

  • Comprehensive Egocentric Understanding:
    Excels in fine-grained video understanding and egocentric cognition, covering diverse tasks such as embodied QA, counting, and OCR.
  • Diverse Spatiotemporal Localization:
    Possesses powerful localization capabilities across episodic memory, enabling precise identification of objects, target areas, and motion trajectories.
  • Physical-Space Reasoning:
    Interleaves textual and spatial grounding to anchor reasoning firmly in physical reality.
  • Physics-Aware Planning:
    Integrates localized affordances and object info into planning, enabling downstream VLA models to execute intricate tasks.

Overview

Overview

Results

Click on the image to view a larger version.

2B & 8B results
2B & 8B Results
30B results
30B-A3B Results
Planning Results
Planning Results
Navigation Results
Navigation Results

Skill Demonstration

Showcasing specific capabilities.

Real-Robot Demos

Click on the video to view a larger version.

Navigation Demos

Click on the video to view a larger version.

Model Architecture

Architecture

RynnBrain Bench

RynnBench

BibTeX

@article{rynnbrain2026,
  title   = {RynnBrain: Open Embodied Foundation Models},
  author  = {Ronghao Dang and Jiayan Guo and Bohan Hou and Sicong Leng and Kehan Li and Xin Li and Jiangping Liu and Yunxuan Mao and Zhikai Wang and Yuqian Yuan and Minghao Zhu and Xiao Lin and Yang Bai and Qian Jiang and Yaxi Zhao and Minghua Zeng and Junlong Gao and Yuming Jiang and Jun Cen and Siteng Huang and Liuyi Wang and Wenqiao Zhang and Chengju Liu and Jianfei Yang and Shijian Lu and Deli Zhao},
  year    = {2026}
}