Overview
NVIDIA formally released Cosmos 3 at Computex 2026 (May 31 Beijing time), with a follow-up NVIDIA Blog post on August 6 titled *Open World Models Power the Next Frontier of Physical AI*. The release reframes the Cosmos line: rather than a video generator, Cosmos 3 is positioned as a multimodal foundation for physical AI, unifying vision, action, text, and sensor reasoning within a single set of weights.
Three Model Sizes
Cosmos 3 ships as a family of three checkpoints:
- Cosmos-3 Super (64B) — flagship for physics simulation, robot policy learning, and autonomous-driving scene generation.
- Cosmos-3 Nano (16B) — tuned for edge and embedded deployment with latency-sensitive use cases.
- Cosmos-3 Edge (4B) — targets board-level and GPU-less devices such as robot onboard controllers and in-vehicle units.
- Vision: ~85 million hours of simulation video plus real-world driving and robot teleoperation clips
- Action: ~450 million sequences (robot joint trajectories, driving trajectories, dexterous-hand actions)
- Text / annotations: ~280 million entries (task descriptions, scene labels)
- Sensors: ~120 million entries (IMU, torque, depth)
- No use for military or weapons systems
- No generation of synthetic media that violates NVIDIA's Acceptable Use Policy (e.g., deepfakes)
- Derivative models must retain the OpenMDW license
- Cosmos 1 (Jan 2025): established that diffusion models can generate physics-plausible video.
- Cosmos 2 (mid-2025): added conditional control over language, action, and sensors.
- Cosmos 3 (2026): unifies vision, action, and text within one model — eliminating the need for separate video, policy, and control stacks.
- GR00T (humanoid robot foundation model): Cosmos 3 serves as its "vision brain" for scene understanding and prediction.
- Isaac Sim / Isaac Lab: primary source of synthetic training data and the RL fine-tuning platform.
- Omniverse: not where Cosmos 3 runs, but used as a debugging tool for inspecting generated scenes.
- Training compute, total tokens, and per-tower parameter counts are undisclosed.
- The "data point" definition (frame, segment, or token) is not clarified.
- Public lists of the founding coalition and early adopters are incomplete; marquee names such as Boston Dynamics should be independently verified given NVIDIA's marketing tendencies.
- No official benchmarks compare Cosmos 3 against Cosmos 1/2 or against Genie 3, Veo 3, and Sora 2.
- Legal review of OpenMDW 1.1's clauses on training-data provenance and derivative-model weights is advised.
- NVIDIA Blog (2026-08-06): https://blogs.nvidia.com/blog/open-world-models-physical-ai
- Cosmos repository: https://github.com/NVIDIA/Cosmos
- NVIDIA OpenMDW 1.1 license: https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
- Reuters / CNBC (2026-08-06): https://www.reuters.com/technology/nvidia-cosmos-3-physical-ai-2026-08-06/
- VentureBeat: https://venturebeat.com/ai/nvidia-cosmos-3-physical-ai-gpt-moment/
- The Decoder: https://the-decoder.com/nvidia-cosmos-3-world-foundation-model/
- Cosmos 3 is a three-size model family (64B / 16B / 4B) sharing a Mixture-of-Transformers dual-tower architecture.
- Training data totals ~1.3B points across video, action, text, and sensors; compute and token totals remain undisclosed.
- Released under OpenMDW 1.1, enabling commercial derivatives while excluding military and deepfake use.
- Integrates with GR00T, Isaac Sim/Lab, and Omniverse as a unified physical-AI foundation.
- Differentiates from Genie 3, Veo 3, and Sora 2 by making action a first-class output, not just video.
Architecture: Mixture-of-Transformers Dual Tower
Cosmos 3 uses a Mixture of Transformers (MoT) dual-tower design. One tower handles video and image tokens; the other handles text, action, and sensor signals. The two branches exchange information via cross-attention at intermediate layers. This differs from Cosmos 1 (single Transformer) and Cosmos 2 (late-fusion).
Training Data
The training corpus totals roughly 1.3 billion data points (not tokens), distributed approximately as:
NVIDIA did not disclose parameter counts beyond the size tiers, total training tokens, or GPU-hours — consistent with the company's long-standing policy of releasing model weights while keeping training-cost figures opaque.
Licensing
Cosmos 3 is released under the NVIDIA Open Model License (W) v1.1 (OpenMDW). Commercial use, modification, derivative work, and redistribution are permitted, subject to:
This is a relaxation from the non-commercial terms attached to Cosmos 1 and 2, allowing third parties to build products directly on Cosmos 3.
Reported early adopters include 1X, Boston Dynamics (partial research collaboration), Figure AI, Skydio, an Uber ATG spinoff team, Tsinghua X-Lab, UC Berkeley BAIR, and the Stanford Fei-Fei Li group.
Lineage and Positioning
Relationship to the NVIDIA Stack
Competitive Landscape
Compared with Google DeepMind's Genie 3, Google's Veo 3, and OpenAI's Sora 2, Cosmos 3's distinguishing feature is treating action tokens as first-class citizens. The other three models treat video as the primary output; Cosmos 3 outputs action and video on equal footing. The shift aligns with the broader industry reading that world models are moving from "generator" to "reason-then-render."