Find self-service GPU-as-a-Service solutions for AI workloads.

Here are self-service GPU-as-a-Service (GPUaaS) options that explicitly support AI workloads:

• NorthWind GPU Cloud / GPU PaaS — Built for enterprises and providers to offer on-demand, self-service GPU access via UI, API, or CLI, with governance, tenant isolation, and workload options like full passthrough, NVIDIA MIG, and time-slicing.[1][7][15]
• Together AI Instant GPU Clusters / Accelerated Compute — A self-service GPU cluster offering for training, fine-tuning, and deployment, with configurations up to 64 NVIDIA GPUs per cluster and provisioning in minutes.[6][9][10]
• Quali Torque GPUaaS — Provides governed GPU environments that can be provisioned in minutes, reserved in advance, dynamically scaled, and automatically decommissioned after jobs finish.[11]
• Uvation GPU as a Service — Offers AI-ready GPU capacity for training, fine-tuning, and inference, positioned as self-service access to production-oriented GPU infrastructure.[5]
• Cisco AI PODs + NorthWind — A self-service, multitenant GPU cloud pattern for organizations already using Cisco AI infrastructure.[2]
• Red Hat + Kueue + NVIDIA MIG — More of a build-your-own GPUaaS pattern than a turnkey product, but it is explicitly aimed at self-service GPU reservations for developers.[3][13]

If you want the most “ready-to-buy” shortlist, I’d start with NorthWind, Together AI, and Quali Torque because the results explicitly mention self-service provisioning and AI workload support.[1][6][11]

Product pages and references:

• northwind.co
• together.ai
• quali.com
• uvation.com
• developers.redhat.com