BAAI Releases World Model Kairos, Leading Multiple Benchmarks

BAAI World Model Kairos Released: 4B Parameter Model Tops Four International Benchmarks

Recently, the Beijing Academy of Artificial Intelligence (BAAI) unveiled its world model series at the 2026 BAAI Conference, with the Kairos world model achieving first place in four authoritative international evaluations, drawing industry attention. Developed by BAAI-incubated company Daxiao Robotics, Kairos surpasses larger models across multiple dimensions with only 4 billion parameters, showcasing the potential of the world model technical route.

Technical Architecture: From Video Generation to Unified Prediction

Kairos adopts a native unified world model architecture, integrating multimodal understanding, video generation, and state prediction into a single model system, rather than post-training modifications based on video generation models. Its core includes a self-developed hybrid linear attention mechanism and a global state sharing mechanism, enabling the model to simultaneously perform understanding, generation, and prediction. This direction aligns with international mainstream models like NVIDIA Cosmos 3.0. For training data, Kairos uses over 100,000 hours of human-centric real-world scenes and millions of hours of internet video, combined with explicit imitation learning and latent space reinforcement learning to enhance understanding of physical laws and causal relationships.

Evaluation Performance: Four Firsts, Covering Manipulation, Generalization, and Physical Modeling

Kairos achieved first place in the following four evaluations:

RoboTwin 2.0: A dual-arm manipulation benchmark with 50 complex collaborative tasks. Kairos achieved an average success rate of 96.1% (96.9% in Clean scenes, 95.2% in Randomized scenes), surpassing G0.5 (93.2%) and starVLA (88.3%).
LIBERO-Plus: A scene generalization benchmark simulating real environments through seven variables including lighting, background, and noise. Kairos ranked first with 89.0 points, outperforming ACoT-VLA (88.0) and Pi 0.5 (85.7). It excelled in sub-items such as lighting (97.7), background (95.8), noise (96.8), and camera viewpoint (95.5).
WorldModelBench Robot: A physical modeling evaluation introduced by institutions including Berkeley and NVIDIA. Kairos-4B ranked first with a total score of 9.30, surpassing the 28B-parameter Lingbot (score undisclosed) and 16B Cosmos3. It led in sub-items such as instruction following (2.36, tied for first) and physical compliance (4.96).
DreamGen Bench: A generalization ability evaluation proposed by NVIDIA and others. Kairos ranked first in average physical compliance (AVG_PA: 0.538) and overall average score (AVG_Score: 0.618), leading in sub-items such as new behavior execution (PA: 0.489) and new environment adaptation (PA: 0.581).

Industry Impact and BAAI's Strategy

The release of Kairos marks the transition of world models from the lab to practical deployment. Its 4B parameter scale directly drives robot bodies on the edge, reducing intermediate conversion latency and improving response speed. At the conference, BAAI also released Wujie·Physis-v0.1 (a general world foundation model) and Wujie·RoboBrain Orca (an embodied brain), and systematically outlined four categories of world models: language-centric, pixel-centric, 3D structure-centric, and visual representation-centric. BAAI believes that a true world model should be able to perceive, understand, and reason about physical states, and possess active interaction capabilities.

Since its establishment in 2018, BAAI has open-sourced over 200 models, with global downloads exceeding 1 billion. Its Wujie·Emu3 was featured in Nature in January 2026, marking the first publication of a Chinese large model in Nature. The conference brought together international institutions such as Meta, NVIDIA, Harvard, and MIT, as well as domestic forces like Alibaba, Tencent, and Tsinghua, to discuss cutting-edge topics including world models, intelligent agents, and AI safety.