Compare GPU Cloud Providers
Side-by-side pricing, specs, regions, and billing models for every major GPU cloud.
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Select any two providers to compare live GPU pricing, regions, billing models, and platform features.
How to Compare GPU Cloud Providers
What this comparison covers
This page compares live on-demand GPU hourly rates, spot pricing, available GPU models, regions, billing models, minimum commitments, and support tiers between two providers.
Hyperscalers vs specialists
Hyperscalers (AWS, Google Cloud, Azure) offer the widest region coverage and enterprise compliance, but typically charge a premium over specialist GPU clouds. Specialists like Lambda Labs, CoreWeave, and RunPod often offer lower per-GPU rates with less overhead.
Spot vs on-demand pricing
Spot instances can be 60–80% cheaper than on-demand but may be interrupted. On-demand rates are guaranteed but cost more. Check both columns when comparing total workload cost.
Hidden costs to watch
Egress fees, storage costs, and minimum runtime commitments can significantly affect the real cost of a workload. Always check the provider's full pricing page before committing.
Billing model differences
Providers bill per-second, per-minute, or per-hour. A per-hour minimum on a 10-minute job costs 6× more than a per-minute billing provider. Confirm the billing unit before comparing listed rates.
Training workloads
Long-running training jobs benefit most from reserved or committed-use pricing. Compare 1-year and 3-year reserved rates if you expect sustained GPU usage.
Inference workloads
Inference workloads are often bursty and benefit from on-demand or spot pricing. Look for providers with fast provisioning and low minimum commitments.
Budget workloads
For cost-sensitive workloads, marketplace providers like RunPod and Vast.ai often offer the lowest rates. Verify host reliability and SLA terms before running production workloads.