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 — this GPU cost calculator exists because 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. Pick a GPU model and provider, set your usage pattern, and see hourly, daily, monthly, and annual costs, while comparing every other provider offering that same GPU so you can spot the cheapest option immediately.
It multiplies a chosen GPU/provider's on-demand hourly rate by your GPU count and total usage hours to project cost, then re-runs that same math against every other listed provider offering the identical GPU model — surfacing the cheapest alternative for an apples-to-apples comparison rather than a single isolated quote.
ML engineers scoping a training run, startup founders budgeting inference infrastructure, researchers comparing cloud GPU vendors before a grant-funded project, and DevOps/platform teams deciding between a hyperscaler and a GPU-specialized cloud all benefit from seeing the true monthly cost side by side before committing a budget line.
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.
How this GPU cost calculator turns an hourly rate and usage pattern into a monthly projection
Annualizing by 365 ÷ days-per-month (rather than a flat ×12) correctly scales a partial-month figure — say, a 10-day sprint — up to a realistic full-year run rate instead of understating it.
On-demand pricing guarantees availability at a fixed hourly rate. Spot/preemptible instances offer 30-70% discounts but can be reclaimed 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. Running a model that needs 60GB on a 24GB card simply isn't possible — check the VRAM Calculator first.
From picking a GPU to spotting the cheapest provider
Select a GPU model and provider combination from the dropdown — NVIDIA H100 80GB, A100 80GB, A100 40GB, L40S, RTX 4090, or T4 across AWS, GCP, Azure, Lambda Labs, RunPod, CoreWeave, or Vast.ai — each option shows its on-demand hourly rate.
Set how many GPUs of that type you need running in parallel, from a single card up to a large multi-node cluster.
Enter how many hours per day the GPUs will actually run — continuous 24 hours for training, or fewer hours for intermittent or business-hours-only inference workloads.
Enter how many days per month you expect to run the workload so partial-month or seasonal usage is reflected in the projection.
Click "Calculate GPU Cost" to see hourly, daily, monthly, and annual totals, plus a side-by-side comparison chart of every other provider offering the same GPU model, with the cheapest option highlighted.
Using the calculator's own default scenario — 1× H100 80GB on RunPod, 24 hrs/day, 30 days
Suppose you rent a single NVIDIA H100 80GB on RunPod ($2.79/hr), running continuously (24 hrs/day) for a 30-day month.
Explanation: At this usage level, choosing RunPod over AWS for the identical H100 80GB card saves roughly $6,840 per month — over $82,000 per year. That gap is exactly what this calculator is built to surface: hardware-identical comparisons across the on-demand market so a provider choice is a deliberate decision, not a default.
What your projected monthly GPU spend generally implies
| Monthly Cost Range | What It Generally Means | Recommended Next Step |
|---|---|---|
| Under $500 | Hobbyist or small experiment scale | A single consumer GPU (RTX 4090) or community-cloud rental fits comfortably |
| $500 – $3,000 | Serious side project or small production workload | Compare GPU-specialized clouds against hyperscalers before committing |
| $3,000 – $15,000 | Meaningful production training or inference spend | Evaluate reserved/committed-use pricing and spot for fault-tolerant jobs |
| $15,000 – $50,000 | Scaled multi-GPU workload | Negotiate volume pricing directly with your chosen provider |
| Over $50,000 | Large-scale training or fleet-wide inference | Consider a dedicated enterprise agreement or owning hardware outright |
If the cheapest provider differs from your selection: the "Cheapest Provider" result shows exactly how much switching would save for identical hardware — but factor in migration effort, data residency requirements, and support needs before moving a live workload.
If your annual cost looks unexpectedly large: check the "Days Per Month" field — a low value (say, a 10-day sprint) gets annualized up to a full-year run rate, which is intentional but can surprise users expecting a simple ×12.
These are on-demand list-price estimates, not a live quote. Always confirm current rates on the provider's own pricing page before finalizing a budget.
This calculator provides planning estimates only. Actual charges depend on your provider's live pricing, region, committed-use discounts, and any negotiated enterprise rate on your account.
Where comparing GPU rental cost up front genuinely helps
Estimate the total cost of a multi-day or multi-week fine-tuning job before starting it.
Project the monthly GPU line item for a live inference endpoint under continuous load.
Compare on-demand cost against a discounted spot/community rate to decide if the risk is worth it.
Budget a grant-funded or academic training run across multiple candidate providers.
Run the same hardware and usage pattern across AWS, GCP, Azure, RunPod, and Lambda Labs side by side.
Weigh a hyperscaler's SLA and compliance certifications against a GPU cloud's lower hourly rate.
Test a small GPU configuration's cost before committing to a larger multi-node cluster.
Fold projected GPU spend into a startup's monthly infrastructure burn-rate model.
Use the monthly and annual figures as the "rent" side of a buy-vs-rent hardware comparison.
Check whether GPU pricing differs meaningfully by provider region before choosing a deployment zone.
Estimate cost for intermittent batch training jobs that don't need 24/7 GPU allocation.
Re-run the numbers whenever a provider publishes a new on-demand rate.
What this GPU cost calculator does well, and where it can't replace a live quote
Approximate 2026 on-demand hourly rates by GPU class
| GPU Class | VRAM | Cheapest Provider | Hyperscaler Rate |
|---|---|---|---|
| H100 80GB | 80GB | RunPod — $2.79/hr | AWS — $12.29/hr |
| A100 80GB | 80GB | RunPod — $1.64/hr | AWS — $5.12/hr |
| A100 40GB | 40GB | Lambda Labs — $1.29/hr | AWS — $2.74/hr |
| L40S | 48GB | RunPod — $0.86/hr | Lambda Labs — $1.09/hr |
| RTX 4090 | 24GB | Vast.ai — $0.35/hr | RunPod — $0.44/hr |
| T4 | 16GB | GCP — $0.35/hr | AWS — $0.526/hr |
Summary: This GPU cost calculator gives you an instant, free comparison of cloud GPU rental pricing across 7 major providers and 6 GPU classes, automatically surfacing the cheapest option for identical hardware. Pair it with the VRAM Requirement Calculator and Cloud Cost Calculator for a complete AI infrastructure budgeting workflow.
Common questions about GPU cost calculator estimates
Official documentation to complement this calculator — always verify live rates before finalizing a budget
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