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

Self-Service GPU-as-a-Service Solutions for AI Workloads

There are two categories worth considering: consumer-ready GPU clouds (rent capacity directly, no infrastructure setup) and platform software (for building/operating your own GPUaaS offering, e.g., if you're a neocloud or enterprise IT team).

Ready-to-Use GPU Clouds (rent GPU capacity directly)

1. Runpod —
Offers three primary infrastructure products: Serverless (autoscaling GPU endpoints that scale to zero when idle), Pods (GPU instances for persistent compute and development – available as Reserved or Spot), and Clusters (multi-GPU distributed compute for training and large-batch inference)
.
You can spin up a fully-loaded, GPU-enabled environment in under a minute, with support for over 30 GPU SKUs
. (runpod.io)

2. Vast.ai —
Provides on-demand instances across 40+ data centers and 20,000+ GPUs, with deployment in seconds via CLI, SDK, or API
. It also offers
a Serverless option to deploy models as endpoints with automatic benchmarking, autoscaling to zero, paying only for compute time
. (vast.ai)

3. GMI Cloud — Features
instant on-demand provisioning with no quota application, no approval workflow, and no waitlist — you select the GPU tier or inference model you need, and it's available
.
Runs on NVIDIA H100 and H200 GPUs, supports bare-metal instances and a pre-deployed model library of 100+ models
. (gmicloud.ai)

4. Together AI Instant Clusters —
Designed to emulate the user experience of conventional cloud infrastructure while handling the specific demands of AI workloads
, with
optimization for use with Kubernetes, Slurm and other orchestration tools
. (siliconangle.com)

5. Gcore GPU Cloud —
Gives full access to NVIDIA GPUs with no virtualization overhead, and full API and Terraform integration for automated provisioning
. (gcore.com)

Platform Software (build your own GPUaaS)

If you're a service provider or enterprise wanting to offer self-service GPU access internally/externally, NorthWind's GPU PaaS
delivers on-demand access to GPU compute through APIs or self-service portals, letting users instantly launch GPU-backed environments with built-in governance, isolation, and usage tracking
, and Red Hat OpenShift AI
is a Kubernetes-based platform that can be used to implement a multi-user GPUaaS solution
.