Description
NVIDIA OSMO is an open-source orchestration platform tailored for physical AI development. It enables developers to build, run, and scale multi-stage workflows, including data generation, training, simulation, evaluation, and hardware-in-the-loop testing across heterogeneous compute environments. The platform unifies training clusters, simulation, and edge environments into a single YAML-defined engine, managing datasets, dependencies, and compute scheduling across cloud or on-prem infrastructure. Delivered as a CLI with agent context files, OSMO provides full situational awareness over the development environment, allowing coding agents to reason about pipelines, query workflows, inspect GPU capacity, and monitor platform activity in real time.
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OSMO lowers the barrier to robotics development by offering end-to-end orchestration through a no-code YAML workflow. It supports multistage runs without requiring Kubernetes experience, enabling centralized control over workloads on Kubernetes clusters with x86, Arm, and NVIDIA GPUs. The platform is secure with open standards, utilizing OIDC for authentication and other security measures.
While OSMO orchestrates various components like NVIDIA Isaac Sim, PyTorch-based training jobs, and reinforcement learning frameworks, it does not replace them. It prepares trained policies, datasets, and artifacts for integration with preferred deployment runtimes or robotics stacks. OSMO is not an MLOps platform; it focuses on workflow execution, dataset versioning, data lineage, and compute orchestration. It supports on-prem clusters, major cloud providers, and mixed compute setups, abstracting the underlying infrastructure to simplify AI workload management.
- CategoryMachine Learning Platforms
- Pricing ModelOpen source
- DeploymentCloud, On-prem
- Platformsx86, Arm, NVIDIA GPUs
NVIDIA OSMO Platform's Core Features
Cloud-native orchestration
Multi-stage workflow management
YAML-defined engine
Real-time situational awareness
End-to-end orchestration
Centralized control plane
Secure with open standards
Supports heterogeneous compute environments
How to use NVIDIA OSMO Platform?
Configure: Define YAML workflows
Use: Orchestrate multi-stage workloads
Monitor: Inspect GPU capacity and workflows
Optimize: Manage datasets and dependencies
NVIDIA OSMO Platform's Use Cases
- Robotics Workflows
- AI Development
- Simulation Integration
- Dataset Management
- Multi-cloud Support
