Cosmos 3 combines reasoning, world generation, and robot action

The hard part of physical AI is not only language reasoning; it is predicting, simulating, and acting in a changing world. NVIDIA’s June 1 post positions Cosmos 3 as a frontier model for that problem, combining vision reasoning with world and action generation.

The concrete release detail is the two-model split: Super and Nano. NVIDIA’s technical blog says Cosmos 3 Nano and Cosmos 3 Super checkpoints are on Hugging Face, with post-training scripts on GitHub for adapting the models to new domains. Public release material describes Nano as an 8B reasoner plus 8B generator setup, while Super pairs 32B reasoning and 32B generation towers. The source tweet calls Cosmos 3 a fully open omnimodel for Physical AI.

The architecture is the part to watch. Cosmos 3 uses a Mixture-of-Transformers design: an autoregressive tower handles language and discrete understanding, while a diffusion-based tower handles image, video, audio, and action trajectory generation. NVIDIA says Cosmos 3 has been evaluated across VANTAGE-Bench, Physics-IQ, PAI-Bench, R-Bench, RoboLab, and related public leaderboards for physical reasoning, generation, and policy tasks. The release also includes six synthetic data generation datasets covering robotics, physics simulation, spatial reasoning, human motion, driving, and warehouse environments.

The next question is practical openness. Checkpoints, recipes, and code make the release more useful than a demo, but hardware cost, license terms, and deployment paths through NIM will determine how many robotics and autonomous-systems teams can actually adapt it. The real benchmark is whether Cosmos 3 reduces the number of expensive real-world trials needed to train useful physical AI systems.