Compare GPU cloud pricing across major providers. Estimate hourly, daily, monthly, and annual compute costs for H100, H200, A100, L40S, and RTX 4090 GPUs with on-demand and reserved pricing.
Hourly Cost
$6.88
$6.88/GPU
Daily Cost
$55.04
8 hrs
Monthly Cost
$1,210.88
22 days
Annual Cost
$14,530.56
12 months
CoreWeave
448
GPU-hours
Lambda
402
GPU-hours
RunPod
372
GPU-hours
Google Cloud
311
GPU-hours
Azure
217
GPU-hours
AWS
145
GPU-hours
GPU cloud pricing varies dramatically between providers and GPU models. Major cloud providers like AWS and Azure offer enterprise reliability and ecosystem integration, while specialized providers like Lambda, CoreWeave, and RunPod focus on GPU workloads with competitive pricing. The best choice depends on your scale, reliability requirements, and budget.
GPU cloud pricing changes frequently. Prices shown are approximate on-demand rates as of April 2026. Actual costs may vary based on region, availability, and specific instance configurations.
For large model training, the H100 and H200 are the current standard, offering the best performance for transformer workloads. The A100 remains a solid choice for smaller models and fine-tuning. For inference and smaller workloads, the L40S and RTX 4090 offer excellent price-to-performance ratios.
On-demand pricing lets you pay by the hour with no commitment — ideal for experimentation and burst workloads. Reserved instances (1-year or 3-year) offer 30-50% discounts but require upfront commitment. Choose reserved pricing when you have predictable, sustained compute needs.
Spot instances can save 60-90% over on-demand but can be interrupted with little notice. They work well for fault-tolerant workloads like hyperparameter sweeps, batch inference, and training with checkpointing. This calculator focuses on on-demand and reserved pricing for predictable budgeting.
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