Physical AI systems must understand the real world before they can act within it. Robots, autonomous vehicles, and smart spaces need to understand what’s happening in their world, predict what’s likely to happen next, and generate actions for specific environments, embodiments, and tasks. NVIDIA Cosmos 3 is a frontier foundation model for physical AI that combines physical reasoning, world generation, and action generation within a single open model. NVIDIA is open sourcing Cosmos 3 models, training scripts, deployment tools, and datasets to make physical AI development more open and reproducible. This blog post covers the fundamentals of Cosmos 3, highlights key concepts from the technical report, guides through technical workflows and shows how teamsrobotic manipulation systems, autonomous vehicles, and warehouse monitoring solutions can get started. Key highlights of this release include: - NVIDIA Cosmos 3 Nano and NVIDIA Cosmos 3 Super model checkpoints on Hugging Face with code on GitHub. - Open datasets for physical AI applications like robotics and autonomous driving. - Open post-training scripts for adapting Cosmos 3 to your domain. - Cosmos NIM microservices for easy, optimized deployment on NVIDIA GPUs. What’s new in Cosmos 3 Previous Cosmos releases separated world generation, physical understanding, and controlled scene generation into different models and workflows. This release unifies those capabilities with a Mixture-of-Transformers (MoT) architecture built around two towers. - Reasoner tower: A vision-language model (VLM) that interprets multimodal observations like images, videos, and text. This tower uses an autoregressive architecture to interpret the input and understand motion, object interactions, and other physical context. This serves as the ‘brain’ that reasons about the world before any generation happens. - Generator tower: Generates future observations and action sequences. This tower uses a diffusion-based process to generate physics-aware video and action outputs that are conditioned on the reasoner tower’s understanding. The