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

Here are self-service GPU-as-a-Service (GPUaaS) platforms suitable for AI training, fine‑tuning, and inference in 2026. These let you spin up GPUs on demand without enterprise sales contracts.

1) RunPod (On‑Demand + Serverless GPUs)

Best for: Startups, fine‑tuning, inference endpoints

• On-demand & serverless GPU pods (H100, H200, A100, RTX 4090/5090)
• Pay‑as‑you‑go; persistent storage options
• Easy API + templates for PyTorch, HF, etc.

runpod.io

2) Vast.ai (GPU Marketplace – Lowest Cost)

Best for: Cost-sensitive experimentation

• Marketplace of global GPU providers
• H100 pricing can be significantly below hyperscalers
• Spot-style pricing; variable availability

vast.ai

3) Lambda Cloud

Best for: Stable, production-grade GPU workloads

• On-demand & reserved NVIDIA H100, H200, A100
• Jupyter, SSH, Kubernetes support
• Strong AI ecosystem integration

lambdalabs.com

4) CoreWeave

Best for: Scalable enterprise AI training

• Specialized AI cloud (NVIDIA partner)
• H100/H200 clusters, Kubernetes-native
• Used for large-scale LLM training

coreweave.com

5) Google Cloud Vertex AI (Serverless + Dedicated GPUs)

Best for: Managed ML pipelines

• Serverless training + dedicated GPU clusters
• Integrated MLOps, model registry, endpoints
• HIPAA & enterprise security options

cloud.google.com

6) NVIDIA DGX Cloud

Best for: Full-stack NVIDIA-optimized AI training

• Managed DGX clusters (H100/H200 class systems)
• Includes NVIDIA AI software stack

nvidia.com

7) Thunder Compute (Low-Cost Alternative Cloud)

Best for: Budget-conscious teams wanting AWS-like UX

• Claims significantly lower pricing vs hyperscalers
• Multi-GPU instances available

thundercompute.com

Quick Comparison

| Platform | Serverless | Dedicated Nodes | Best For |
|---------------|------------|----------------|----------|
| RunPod | ✅ Yes | ✅ Yes | Startups, inference |
| Vast.ai | ❌ (VM-style) | ✅ Yes | Cheapest training |
| Lambda Cloud | ❌ | ✅ Yes | Stable production |
| CoreWeave | ❌ | ✅ Yes | Large-scale training |
| Vertex AI | ✅ Yes | ✅ Yes | Managed ML |
| DGX Cloud | ❌ | ✅ Yes | Enterprise LLM training |

If you tell me:

• Training vs inference?
• Model size (e.g., 7B vs 70B)?
• Budget range?
• Need for HIPAA/SOC2?

I can narrow this to 2–3 best-fit options.