NVIDIA Open-Sources Its Full Run:ai GPU Orchestration Platform

NVIDIA made the full NVIDIA Run:ai platform open source on October 13, 2026, as part of its NVIDIA DSX AI Factory Platform.

What Run:ai does

Run:ai is NVIDIA’s software for orchestrating AI workloads and GPUs on Kubernetes. It allocates GPU resources dynamically and manages workloads across their lifecycle, from data processing and training to inference. NVIDIA says opening it up lets partners and AI clouds increase workload throughput, improve GPU utilization and run shared AI infrastructure more efficiently.

NVIDIA first announced its agreement to acquire Run:ai, an Israeli Kubernetes orchestration startup, in April 2024.

What’s in the release

The complete source code lives in the Run:ai repository in the NVIDIA DSX AI Factory GitHub organization, and the platform is also on NVIDIA NGC as a Community Product with a Helm chart. Four components can be adopted independently:

• KAI Scheduler, the Kubernetes-native scheduler behind Run:ai, already released under Apache 2.0 and contributed to the CNCF as a Sandbox project.
• GPU Fractioning Operator, which brings CUDA 13.4-native GPU fractioning to Kubernetes so several workloads can share one GPU with hard memory limits. NVIDIA says it has retired its proprietary fractioning implementation in favor of this native capability.
• KAI Resource Management, the layer for projects, departments, quotas and node pools that decides which teams get which share of the cluster.
• Workload Map, a Go library that gives tools one consistent way to describe and manage AI workload types such as PyTorchJob, RayCluster or KServe services.

Who is using it

Eight NVIDIA DSX ecosystem partners are integrating the open source platform: Crusoe, Mirantis, Nebius, OpenNebula Systems, Rafay, Saturn Cloud, Spectro Cloud and vCluster. Nebius, for example, is offering it as a one-click deployment in Nebius AI Cloud.

What it costs

No paid Run:ai subscription or NVIDIA support entitlement is required for the Community Product, though NVIDIA enterprise support is not included and downloading it from NGC requires accepting NVIDIA’s license terms. Run:ai remains available as a supported commercial product, including through NVIDIA Mission Control and NVIDIA AI Enterprise.

Why it matters

GPU time is one of the biggest costs in AI, and scheduling software decides how much of it gets wasted. With Run:ai open, cloud providers can package and modify it themselves instead of only reselling a license.