Physical AI
NVIDIA Cosmos
Develop world foundation models to advance physical AI.
Overview
What is NVIDIA Cosmos?
NVIDIA Cosmos™ is a platform of state-of-the-art generative world foundation models (WFMs), advanced tokenizers, guardrails, and an accelerated data processing and curation pipeline. It is built to power world model training and accelerate physical AI development for autonomous vehicles (AVs) and robots.
Benefits
Accelerate World Generation for Physical AI
Cosmos provides developers easy access to high-performance world foundation models, data pipelines, and tools to post-train these models for robotics and autonomous driving tasks.
Physics First Data
World foundation models are pre-trained on 20 million hours of robotics and driving data to generate world states grounded in physics.
Open
Cosmos WFMs, guardrails, and tokenizers are licensed under the NVIDIA Open Model License, allowing access to all physical AI developers.
Models
Cosmos World Foundation Models
A family of pretrained multimodal models that developers can use out-of-the-box for world generation and reasoning, or post-train to develop specialized physical AI models.
Predict
Generalist model for world generation and motion prediction from multimodal input. Trained on 9,000T tokens of robotics and driving data and purpose-built for post-training.
Available as Cosmos NIM for accelerated inference anywhere.
Transfer
Physics-aware world generation conditioned on ground-truth and 3D inputs. Input includes segmentation maps, depth signals, LiDAR scans, key points, trajectories, HD maps, and ground-truth simulation from NVIDIA Omniverse™ for controllable synthetic data generation.
Reason
Fully customizable, multimodal reasoning model for planning response based on spatial and temporal understanding.
Trained using visual-language model fine-tuning and reinforcement learning for chain-of-thoughts reasoning.
Guardrails
Develop responsible models using Cosmos WFM with pre-guard for filtering unsafe input and post-guard for consistent and safe outputs.
Tools
Post-train Cosmos World Foundation Models
Cosmos provides developers with open and highly performant data curation pipelines, tokenizers, training framework and post-training scripts to quickly and easily build specialized world models like policy models and visual language action (VLA) models for embodied AI.
Use Cases
How Developers Use NVIDIA Cosmos
Developers post-train Cosmos WFMs or couple with NVIDIA Omniverse to drive downstream physical AI use cases.
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Synthetic Data Generation (SDG)
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Policy Model Initialization
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Policy Model Evaluation
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Multiverse Engine
Synthetic Data Generation (SDG)
Cosmos accelerates synthetic data generation to train perception AI models.
Omniverse provides generative APIs, tools, and NVIDIA RTX™ rendering to create physically accurate ground-truth 3D scenes for Cosmos WFM. Using these visuals as inputs, Cosmos Transfer WFM generates photorealistic outputs—simulating diverse weather, environments, and lighting—while predicting world states with physical accuracy, based on text prompts.
Developers can use generalist Cosmos WFMs out of the box or customize them with their own data for greater precision in downstream SDG.
Our Commitment
Democratizing Trustworthy AI for Physical AI Community
Cosmos models, guardrails, and tokenizers are available on Hugging Face and GitHub, with resources to tackle data scarcity in training physical AI models. We are committed to driving Cosmos forward— transparent, open, and built for all.
Ecosystem
Adopted by Leading Physical AI Innovators
Model developers from robotics, autonomous vehicles, and vision AI industries are using Cosmos to accelerate physical AI development.