NVIDIA open-sources OSMO to unify physical AI training, simulation, and testing
NVIDIA has released OSMO, an open-source, Kubernetes-native workflow orchestrator designed to streamline the development of physical AI. The tool addresses the fragmentation in robotics development by allowing engineers to define complex pipelines—spanning data-center training, workstation simulation, and edge-device testing—in a single YAML file. This eliminates the need for custom glue scripts…
Key points
- OSMO unifies training, simulation, and edge testing into a single YAML workflow across heterogeneous Kubernetes clusters.
- The Apache-2.0 licensed tool supports GB200, RTX, and Jetson hardware, with NVLink-aware scheduling and enhanced security features.
- NVIDIA claims OSMO’s content-addressable datasets can cut storage costs by 10 to 100x while integrating with AI coding agents.
OSMO routes tasks to specific hardware pools, such as GB200 clusters for training, RTX GPUs for Isaac Sim, and Jetson AGX Thor for hardware-in-the-loop validation. The latest release, version 6.3.1, includes enhanced security features like RBAC and OAuth2, as well as NVLink-aware scheduling. NVIDIA claims the system’s content-addressable datasets can reduce storage requirements by up to 100x. The project is Apache-2.0 licensed and integrates with major coding agents like Claude Code and Cursor, aiming to make physical AI development more accessible and efficient.
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NVIDIA Open-Sources OSMO: One YAML Orchestrates Physical AI Training, Simulation, and Robot Testing
MarkTechPost · 14 September 2026
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