Cosmos 3 is Here 🚀
Today, we're excited to release Cosmos 3 — NVIDIA's next-generation family of open omnimodal world foundation models for Physical AI.
Cosmos 3 unifies language, images, video, audio, and actions within a single architecture, enabling developers to build agents that can understand, reason about, simulate, and act in the physical world. From world generation and simulation to robotics and embodied AI, Cosmos 3 serves as a general-purpose foundation model for Physical AI.
What's new:
- 🌍 Unified omnimodal world model supporting text, image, video, audio, and action modalities
- 🧠 Integrated Reasoner + Generator architecture for world understanding and world generation
- 🎬 Flexible generation across Text-to-Image, Image-to-Video, Video-to-World, and multimodal simulation tasks
- 🤖 Native support for robot action generation and policy learning through Cosmos3-Policy models
- 📈 State-of-the-art open model performance across world understanding, generation, and robotics benchmarks
- 🔓 Open release of models, code, datasets, evaluation benchmarks, and inference tooling for the Physical AI community
📖 Read the Paper | 👉 Download the Models | 🧑🍳 Explore the Cosmos Cookbook
The Cosmos 3 release includes:
- Cosmos3-Nano (16B) – Compact omnimodal world foundation model optimized for efficient deployment and development.
- Cosmos3-Super (64B) – High-capacity world model for advanced reasoning, generation, simulation, and Physical AI applications.
- Cosmos3-Super-Text2Image – State-of-the-art text-to-image generation model built on Cosmos 3.
- Cosmos3-Super-Image2Video – High-fidelity image-to-video generation model with strong temporal consistency and controllability.
- Cosmos3-Nano-Policy-DROID – Open robot foundation model for learning manipulation and control policies directly from demonstrations.
Cosmos 3 represents a major step toward general-purpose world models that can perceive, reason, simulate, and act—bringing us closer to a future where Physical AI can learn from both the real world and generated worlds at scale.