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

For self-service GPU-as-a-Service (GPUaaS) aimed at AI/ML, I’d shortlist these options as of August 2026:

• Runpod — One of the easiest developer-first options. Offers self-service GPU “Pods,” serverless GPU inference, and multi-node clusters. Supports GPUs ranging from RTX-class cards through H100/H200-class accelerators. Good for experimentation, fine-tuning, inference, and teams that want minimal cloud-ops overhead. (runpod.io)
• Lambda Cloud — Strong AI-focused alternative with self-serve NVIDIA B200, H100, A100, and GH200 instances. Lambda explicitly offers first-come self-service deployment without the complexity of a hyperscaler. Particularly attractive for training and dedicated GPU VMs. (lambda.ai)
• Nebius AI Cloud — More infrastructure-oriented while remaining self-service. Its NVIDIA HGX H100 instances can explicitly be provisioned without talking to sales; its broader platform supports large AI clusters and newer NVIDIA accelerators. Good fit when scaling beyond individual GPU VMs. (nebius.com)
• Hyperstack — Straightforward on-demand GPU cloud oriented specifically around AI/ML. Its current catalog includes H100 SXM and other NVIDIA GPUs, with hourly deployment and comparatively simple pricing. (hyperstack.cloud)
• Vast.ai — Marketplace approach rather than a conventional cloud: users self-service GPUs supplied by third-party hosts. Pricing is market-driven, which can make it particularly inexpensive, but infrastructure consistency and enterprise assurances differ from dedicated-cloud providers. (docs.vast.ai)
• AWS EC2 — More complicated, but fully self-service and much broader in infrastructure/services. Current GPU choices include single-H100 P5.4xlarge and 8× H100 P5.48xlarge, plus H200 and Blackwell families. Best when integration with the AWS ecosystem, security controls, and production infrastructure matter more than simplicity. (aws.amazon.com)

For most buyers, I’d evaluate Runpod and Lambda first for easy self-service, Nebius for scalable AI infrastructure, Vast.ai for price-sensitive workloads, and AWS for enterprise integration.

Useful product pages:
runpod.io
lambda.ai
nebius.com
hyperstack.cloud
vast.ai