Compare cloud GPU rental costs across AWS, GCP, Azure, Lambda Labs, RunPod, CoreWeave, and Vast.ai. Estimate hourly, daily, and monthly spend for H100, A100, L40S, RTX 4090, and T4 GPUs, and instantly spot the cheapest provider.
Enter your details and click Calculate to see results
Renting GPUs in the cloud is the backbone of most AI training and inference budgets, but pricing varies enormously depending on where you rent from. The same NVIDIA H100 80GB card can cost $12.29/hr on AWS or as little as $2.79/hr on RunPod — more than a 4x difference for identical hardware. This GPU cost calculator lets you pick a GPU model and provider, set your usage pattern, and see hourly, daily, monthly, and annual costs, while also comparing every other provider offering that same GPU so you can spot the cheapest option immediately.
Select a GPU type and provider combination from the dropdown — covering NVIDIA H100 80GB, A100 80GB/40GB, L40S, RTX 4090 (community cloud), and T4 across AWS, GCP, Azure, Lambda Labs, RunPod, CoreWeave, and Vast.ai — then enter how many GPUs you need, how many hours per day they'll run, and how many days per month. The calculator multiplies the per-GPU hourly rate by GPU count and total hours to produce your cost estimate, and simultaneously recalculates the same workload against every other provider that offers the same GPU model so you can see exactly how much you'd save (or lose) by switching providers.
GPU compute is often the single largest line item in an AI infrastructure budget, whether you're fine-tuning a model, running batch inference, or serving a production LLM endpoint. Hyperscalers (AWS, GCP, Azure) charge a premium for enterprise SLAs, compliance certifications, and integrated networking, while GPU-specialized clouds (RunPod, Lambda Labs, Vast.ai, CoreWeave) often undercut them significantly for raw compute. Knowing the true monthly cost — and the cheapest alternative — before committing to a provider can save thousands of dollars a month at scale.
On-demand pricing guarantees availability at a fixed hourly rate. Spot/preemptible instances offer 30-70% discounts but can be reclaimed by the provider with little notice — better suited to fault-tolerant training jobs than production inference.
AWS, GCP, and Azure bundle GPU instances with enterprise networking, compliance, and support — at a premium. Specialized clouds like RunPod, Lambda Labs, and CoreWeave focus purely on GPU compute and typically cost less per hour.
GPU choice should match your model's VRAM requirement, not just price. An H100 80GB costs more per hour than an RTX 4090, but running a model that needs 60GB of VRAM on a 24GB card simply isn't possible — check our VRAM Calculator first.
Common questions about GPU cloud cost calculations
Explore other AI & infrastructure tools