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Self-Hosted API and CLI Reference

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NVIDIA Run:ai is a platform for accelerating and managing AI workloads in shared computing environments. It enables teams to dynamically schedule, allocate, and monitor GPU resources across clusters.

The NVIDIA Run:ai control plane exposes a REST API for programmatic access and a CLI for interactive and scripted use, covering workload submission, resource management, and administrative operations.

REST API

About the REST API

Overview of the NVIDIA Run:ai REST API, structure, and core concepts

Authenticate to the API

Create and use access tokens to authorize API requests

Using the REST API

Make your first requests and learn common request, response, and pagination patterns

Command Line Interface (CLI)

Install and Configure the CLI

Install the NVIDIA Run:ai CLI and connect it to your cluster

CLI Command Reference

Browse the full list of runai commands, flags, and usage examples

Common Use Cases

Developers and administrators use the NVIDIA Run:ai API and CLI to:

  • Automate workload management - Submit, suspend/resume, and monitor AI training and inference jobs programmatically or from scripts.
  • Optimize resource utilization - Dynamically allocate GPU and CPU resources based on workload demand.
  • Integrate with existing systems - Connect NVIDIA Run:ai with CI/CD pipelines, data science platforms, or custom dashboards via the API.
  • Manage multi-tenant environments - Streamline access control, quotas, and user management across teams or projects.

Together, the API and CLI give you fine-grained control and scalability beyond the user interface, making it easier to embed NVIDIA Run:ai capabilities into your organization’s AI infrastructure.