Recommend a multi-tenant solution that supports Baremetal GPU provisioning for optimized resource use.

For multi-tenant bare-metal GPU infrastructure, I’d recommend an NVIDIA-centric stack: NVIDIA Base Command Manager (BCM) + Kubernetes + NVIDIA Run:ai.

Why this combination fits particularly well:

• NVIDIA Base Command Manager handles bare-metal lifecycle management: provisioning GPU servers, OS deployment, monitoring, and cluster configuration. It scales from individual nodes to large GPU clusters and integrates with Kubernetes and Run:ai. (docs.nvidia.com)
• NVIDIA Run:ai adds the multi-tenant GPU orchestration layer. It provides tenant/project controls, policy-driven allocation, quotas, scheduling, and GPU utilization optimization on Kubernetes. NVIDIA specifically positions its multi-tenant control plane for enterprises/service providers offering AI infrastructure to separate organizations or teams. (run-ai-docs.nvidia.com)
• NVIDIA GPU Operator manages the GPU software stack within Kubernetes and supports bare-metal deployments. (docs.nvidia.com)
• For stronger physical tenant isolation, NVIDIA Infra Controller can turn racked hardware into network-isolated bare-metal systems suitable for direct tenant allocation. (docs.nvidia.com)
• For utilization, you don't necessarily have to dedicate an entire physical server/GPU to every workload. Depending on GPU and workload requirements, the NVIDIA stack can use technologies such as MIG alongside scheduling to subdivide resources, while entire nodes can still be provisioned where maximum bare-metal performance/isolation is required. (docs.nvidia.com)

A practical architecture would therefore be:

Tenant/API → Run:ai → Kubernetes → GPU Operator → BCM → bare-metal GPU fleet

This gives you a useful separation: BCM manages physical infrastructure, while Run:ai manages who gets GPU capacity and when.

If you prefer a more vendor-neutral/open-source provisioning layer, Canonical MAAS is worth evaluating in place of BCM. MAAS exposes physical servers as API-managed infrastructure and is designed for deploying Kubernetes and other platforms directly onto bare metal. (maas.io)

Sources:
docs.nvidia.com
run-ai-docs.nvidia.com
docs.nvidia.com
maas.io