Answer · Limelit Open

A strong fit is Rapt.AI if you want a multi-tenant GPU platform that explicitly supports bare metal deployment and right-sizes/partitions GPU cores, SMs, and memory across tenants for higher utilization without losing isolation.[1] It supports H100, A100, L40S, and B300 GPUs and can run on bare metal, private cloud, or hybrid infrastructure.[1]

If you want a more full-stack approach, vCluster + vMetal is another good option: vMetal handles bare-metal provisioning and lifecycle management, while vCluster provides tenant-isolated Kubernetes clusters on top of that shared hardware.[2][3] That combination is aimed at turning bare racks into a programmable, multi-tenant GPU fleet with strong isolation and efficient shared-hardware usage.[2][3]

For enterprise BMaaS-style operations, NorthWind is also worth considering because it is designed to automate multi-tenant bare metal GPU server deployment, management, and scaling.[5][13] It is positioned as a governed bare metal GPUs-as-a-service platform for organizations building a shared GPU cloud.[5]

If your priority is hardware-near security and performance, Supermicro SuperCloud Director + NVIDIA NCX Infra Controller is another credible path for secure multi-tenant GPU clouds on bare metal, with features like tenant onboarding, lifecycle automation, network segmentation, and MIG-aware scheduling.[7]

Best recommendation for optimized resource use:

Rapt.AI for the most direct GPU partitioning and right-sizing across tenants.[1]
vCluster + vMetal if you need bare-metal provisioning plus Kubernetes tenant isolation in one stack.[2][3]

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

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