GPU Cost Calculator
Estimate the cost of renting cloud GPUs for training or self-hosted inference.
Cluster
Estimated cost
$1,936.80/month
Per hour (1× GPU)
$2.69
Per day
$64.56
Rate shown for H100 SXM 80GB on RunPod: $2.69/GPU-hour on-demand. Spot, reserved, or marketplace pricing can run substantially lower — this estimate uses on-demand list rates.
How this is calculated
cost = GPU count × price per GPU-hour × hours per day × days per month. Rates are representative on-demand list prices gathered from provider pricing pages and GPU rental trackers.
Pricing is verified against provider pricing pages as of 2026-09-01. AI and cloud pricing changes frequently — confirm the current rate on the provider's own pricing page before budgeting.
Frequently asked questions
Why do GPU prices vary so much between providers?
Hyperscalers (AWS, Azure, GCP) charge a premium for integrated tooling, SLAs, and enterprise support; specialized GPU clouds (RunPod, Lambda, CoreWeave) and spot marketplaces (Vast.ai) undercut them significantly by focusing purely on compute.
Should I rent on-demand or reserve capacity?
On-demand is simplest for short or bursty workloads. For sustained, predictable usage over months, reserved or committed-use pricing (often 30-50% cheaper) is usually worth the commitment — check each provider's reserved pricing separately.
Is it cheaper to rent a GPU or use a hosted API?
For most application workloads, a hosted LLM API (billed per token) is cheaper and far simpler than renting and managing GPUs yourself. Renting GPUs directly makes sense mainly for training, fine-tuning, or workloads with very high, sustained inference volume.
Does this include storage, networking, or data transfer costs?
No — this estimates GPU compute time only. Storage, egress bandwidth, and orchestration costs are billed separately and vary by provider.