Cosmos 3 - NVIDIA's open-source, multimodal physics AI foundational model

What is Cosmos 3?

Cosmos 3 is NVIDIA's first fully open-source, multimodal physics AI foundational model, employing a hybrid Transformer architecture that integrates visual inference, world generation, and motion prediction capabilities. The model can natively understand and generate text, images, videos, sound effects, and motion content, achieving industry-leading accuracy in physics simulation. NVIDIA has also launched the Cosmos Coalition, whose members include Runway and Black Forest Labs, to jointly drive the development of next-generation world models. Cosmos 3 Super and Nano versions are now available, with the Edge version coming soon.

Main features of Cosmos 3

• Full-modal native understanding and generationIt unifies the processing of text, images, videos, ambient sound effects, and motion trajectories, eliminating the need for separate modules to be pieced together.
• Physical World SimulationAs a world model, it simulates the physical environment, predicts the future state of the scene, and supports model training and evaluation.
• Action strategy generation: Assisting in the training of robots and autonomous driving systems to complete specific tasks through motion trajectory planning.
• Multimodal visual reasoningCross-modal understanding of object interactions, motion patterns, and spatiotemporal relationships.
• Synthetic data generationGenerate high-quality training data based on physical precision, reducing the cost of real data collection.

Cosmos 3 Technical Principles

• Hybrid Transformer architectureCosmos 3 combines an inference Transformer with a specialized generative Transformer. The model first analyzes object interactions, motion patterns, and spatiotemporal relationships to understand the underlying logic of the physical world, and then uses this understanding to generate videos and predict motion trajectories. This architectural design creates a closed loop between inference and generation, ensuring that the output conforms to physical laws.
• Training on massive multimodal physics AI datasetsThe model is trained on billions of samples covering text, images, videos, sound effects, and motion trajectories to build a deep understanding of the physical world, enabling developers to build physical AI systems with less data and lower costs.

How to use Cosmos 3

• Access PlatformVisit https://www.nvidia.com/en-us/ai/cosmos/ to experience Cosmos 3 features.
• Get the modelDownload open-source model weights from Hugging Face.
• Custom developmentCustomize models and generate synthetic data using Hugging Face Diffusers and GitHub resources.
• Deployment reasoningAccelerate inference by deploying the model via NVIDIA NIM microservices or by choosing cloud partners such as Baseten, CoreWeave, and Microsoft Azure.

Cosmos 3's core advantages

• Fully open sourceThe model weights and architecture are completely open, allowing for free customization and secondary training.
• Leading in physical precisionThe open-source model ranks first in world generative benchmarks such as Artificial Analysis, Physics-IQ, PAI-Bench, and R-Bench.
• Improved training efficiencyThis reduces the training and evaluation cycle for physical AI from months to days.
• Three-in-one abilityIt simultaneously possesses the three roles of a visual language model, a world model, and a world action model backbone network.
• Industry alliance supportCosmos Coalition brings together top AI labs and robotics companies from around the world to build an ecosystem.

Cosmos 3 project address

• Project official websitehttps://www.nvidia.com/en-us/ai/cosmos/
• HuggingFace model libraryhttps://huggingface.co/collections/nvidia/cosmos3

Cosmos 3 Comparison with Similar Products

Application scenarios of Cosmos 3

• Robot TrainingIt provides world model simulation and motion strategy pre-training for industrial robots and humanoid robots.
• Autonomous driving developmentSimulate complex traffic scenarios, generate corner case training data, and accelerate AV model iteration.
• Visual AI intelligent agentIt enables a closed loop of perception, reasoning, and decision-making in scenarios such as industrial inspection, intelligent security, and warehouse management.
• Synthetic Data FactoryIt replaces expensive real-world data collection, generating batches of physically consistent training samples.
• Physical World ResearchTo provide open foundational models for academic institutions and promote theoretical research on embodied intelligence and world models.