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NVIDIA posts four Cosmos 3 Nano open models for world simulation
NVIDIA said Nov. 5 it released four open-weight Cosmos 3 Nano checkpoints on Hugging Face for driving and robot world simulation, each with 16 billion trainable parameters.
NVIDIA posted four open-weight Cosmos 3 Nano checkpoints on Hugging Face on Nov. 5 for interactive world simulation, including multi-view driving scenes and robot action video1.
The company said all four models are post-trained examples of Cosmos 3 Nano with 16 billion trainable parameters and are offered under OpenMDW1.1, which it said permits commercial and non-commercial use under that license's terms1.
Cosmos3-Nano-Transfer-Auto is described as a bidirectional model for offline synthetic driving data, generating synchronized video across up to 11 camera views, including fisheyes, with optional joint RGB and LiDAR output1.
Cosmos3-Nano-Sim-Auto is presented as a causally distilled streaming version of Transfer-Auto that generates successive chunks of camera video and LiDAR in a few denoising steps1.
Cosmos3-Nano-Sim-Transfer is said to turn simulator controls and a text prompt into photorealistic video, and Cosmos3-Nano-Sim-Bimanual is said to predict video from robot or camera actions, including two-arm simulation for YAM and AgiBot embodiments1.
NVIDIA said post-training recipes start from Cosmos3-Nano or compatible base weights and that checkpoints are available on Hugging Face, with a technical report and demo page linked from the post1.
Independent benchmarks of the models' fidelity for policy learning were not included in the Hugging Face post, which said measuring where the models support evaluation and where they fall short remains work ahead1.
