ACE ROBOTICS Unveils Kairos 3.0-4B: The First Real-Time Generative World Model for Embodied Intelligence
SHANGHAI, CHINA – March 13, 2026 – ACE ROBOTICS has announced the open-source release of Kairos 3.0-4B, marking a significant advancement in the field of embodied intelligence. This model is the first of its kind to integrate a unified architecture for multi-modal understanding, generation, and prediction, designed specifically for real-world robotic operations.
Revolutionary Design for Embodied Intelligence
Kairos 3.0-4B is a native world model that provides a physics-consistent deep understanding of environments, enabling a single “brain” to control robots of various forms. This model is built from the ground up, incorporating physical laws, human behaviors, and actual robotic actions. By doing so, it achieves a level of understanding that goes beyond mere behavioral imitation, allowing robots to comprehend not just what actions to take, but also the reasoning behind those actions.
The model’s architecture is distinct from traditional approaches that often retrofit general-purpose models with motion capabilities. Instead, Kairos 3.0-4B is constructed around the fundamental physical and causal laws governing real-world environments. This innovative design allows for cross-embodiment generalization, breaking down barriers between different types of data sources, including real robot interaction data, structured human behavioral data, and chain-of-thought reasoning data.
Industry-Leading Performance Metrics
Kairos 3.0-4B leverages a multi-modal understanding-generation-prediction architecture, enabling it to perform long-horizon dynamic interactions and precise action control. The model is capable of generating coherent interaction videos lasting up to seven minutes, setting a new benchmark in the industry.
As a lightweight model with only 4 billion parameters, Kairos 3.0-4B outperforms many mainstream embodied world models while achieving exceptional inference efficiency. It demonstrates real-time edge generation capabilities on the NVIDIA THOR platform, achieving a generation time to video duration ratio of 1:1.5. This performance is notable across both cloud and edge environments.
In terms of speed, Kairos 3.0-4B’s inference capabilities are 72 times faster than those of the previous Cosmos 2.5 model, establishing a new global performance record for embodied world models.
Real-Time Edge Deployment Capabilities
A significant achievement of Kairos 3.0-4B is its real-time edge deployment capability. Deployed on the NVIDIA Jetson Thor T5000 platform, the model operates at 517 TFLOPs, making it the first embodied world model capable of real-time generation on edge hardware. This allows for direct control of physical robot bodies, facilitating real-world task execution without the need for intermediate control layers. The model can issue full-body control commands across various robotic configurations, enhancing operational efficiency.
Breakthroughs in Long-Horizon Interaction
Kairos 3.0-4B also excels in long-horizon interaction capabilities. By integrating Agent-based hierarchical planning with a self-reflective iterative optimization mechanism, the model can generate coherent future-state predictions while maintaining scene coherence and physical fidelity. This innovation sets a new standard for long-horizon embodied interaction, paving the way for advancements in embodied intelligence training and deployment.
The model has achieved top rankings across several authoritative benchmarks, including PAI-Bench-robot, co-developed by Georgia Tech and Carnegie Mellon University, WorldModelBench-robot TI2V, introduced at CVPR 2025, and NVIDIA GEAR Lab’s DreamGen Bench. It outperforms all evaluated models in terms of physical consistency and instruction-following metrics.
Compatibility and Accessibility
Kairos 3.0-4B supports seamless deployment across various robotic configurations, including single-arm, dual-arm, and dexterous hand setups, without requiring additional training for each embodiment. It is compatible with major hardware platforms such as Agilex PIPER, Unitree G1, and Galaxy G1.
The model is now available for public access on GitHub and Hugging Face, allowing developers and researchers to leverage its capabilities in their own projects.
As reported by www.zawya.com.
About ACE ROBOTICS
ACE ROBOTICS is a pioneering company in the field of embodied intelligence, founded by Wang Xiaogang, a co-founder of SenseTime. The company has assembled a team of leading AI scientists and industry experts to focus on advancing embodied intelligence technologies. ACE ROBOTICS aims to empower robots with the ability to autonomously understand and navigate the physical world, facilitating their commercial implementation.
The company has developed the ACE R&D paradigm, which includes a vision-based environmental data engine and a technology chain for real-world cognition and embodied interaction generalization. By addressing core industry challenges such as data scarcity and limited versatility, ACE ROBOTICS is positioned to accelerate the large-scale deployment of embodied intelligence across various applications.
