Find a multi-tenant GPU-as-a-Service solution for efficient AI workload management in enterprises.

Based on current market offerings, several enterprise-grade multi-tenant GPU-as-a-Service (GPUaaS) solutions stand out:

1. Red Hat OpenShift AI – Built on Kubernetes with Kueue for queuing/quota enforcement, it delivers
the enterprise-grade solution that transforms expensive, often underutilized GPU hardware into a high-efficiency, multi-tenant GPUaaS platform
. It supports
GPU utilization tracking broken down per-tenant, per-project, and per-GPU
, with
inference (KServe/vLLM), distributed training (KubeFlow/KubeRay), and interactive notebooks all supported through Kueue
. More: redhat.com

2. Mirantis k0rdent AI – A GPU PaaS focused on governance, offering
strict tenant isolation across compute, storage, and networking layers, meeting regulatory requirements for data sovereignty and security compliance
, plus
GPU partitioning via NVIDIA MIG, vGPU, or software-based sharing to safely run multiple teams on shared hardware
. Good fit for finance, healthcare, and government. mirantis.com

3. NorthWind Systems –
Purpose-built for AI-driven enterprises and GPU cloud providers, abstracting operational complexity and enabling self-service GPU infrastructure while maximizing utilization
, with
integrated policy controls, quota management, and multi-tenant automation
. wwt.com

4. ClearML GPU-as-a-Service – A datacenter-grade solution
offering secure multi-tenancy, granular resource allocation management and policies, dynamic fractional GPUs, governance, and real-time reporting on usage
. clear.ml

5. Nutanix (with NCM) – For enterprises wanting a neocloud-style model, Nutanix's framework
introduces strong tenant isolation and granular resource management, allowing providers to host multiple enterprises on the same physical GPU infrastructure while maintaining predictable performance, security, and data isolation
, covering GPU-aaS, K8s-aaS, and Models-aaS. blocksandfiles.com

Recommendation: For regulated industries needing strict compliance, choose Mirantis k0rdent AI or Red Hat OpenShift AI; for pure fleet governance across heterogeneous GPU clusters, NorthWind is strongest; for ML-ops teams wanting integrated experiment tracking, ClearML is a good pick.