NVIDIA Expands Cosmos World-Model Platform With Training Tools and Blueprints
NVIDIA expanded its Cosmos platform with new training tools, simulation checkpoints and Cosmos Data Factory blueprints aimed at developers building world models for physical AI. The company said Data Factory now offers five cloud-native blueprints available through GitHub, Microsoft Azure, Nebius and CoreWeave, while new Cosmos 3 Nano variants support policy testing in repeatable multiview, multisensor simulations. NVIDIA also said updated Cosmos 3 NIM microservices deliver up to 2x faster inference in validated configurations, and it reported that the Cosmos platform ranks in the top five on six open-model leaderboards—a ranking not independently verified in the supplied material.
NVIDIA is pitching Cosmos as an open, modular stack spanning data curation, model training and NIM deployment for physical-AI world models, and says customers such as Porsche, which expects up to 90% fewer repeated test drives, and ANYbotics are already applying its Data Factory blueprints.
To help developers rapidly build world models, which help physical AI systems understand and simulate the real world, NVIDIA has expanded the Cosmos platform with new training tools, simulation checkpoints and Cosmos Data Factory blueprints.
Ranking top five on six different open models leaderboards, the NVIDIA Cosmos platform gives world model builders the frontier open models — as well as data, training and optimization tools and recipes — to scale training data, adapt models, test behavior and optimize for performance before deployment.
Build Better Training Data
Building world models begins with multimodal, multisensory data.
NVIDIA Cosmos Data Factory brings together the tools and skills for labeling, curating, augmenting and evaluating data at scale for training physical AI. Cosmos Curator, a GPU-accelerated solution for curating video training datasets, has now added support for multimodal multisensory inputs and processing blocks.
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