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Computer Science & Data / AI Infrastructure & LLM Economics

AI Infrastructure Total Cost of Ownership (On-Prem vs Cloud GPU) Calculator

Compare on-prem and cloud GPU costs using user-provided assumptions. Defaults are examples only.

Compare the true monthly and multi-year cost of running AI workloads on your own GPUs versus renting from cloud GPU providers.

Formula

C_capex = N * C_hw * (1 + o); C_amort_month = C_capex / (Y * 12); kWh_gpu = P * hours_month * PUE; kWh_total = N * kWh_gpu; C_power_month = kWh_total * p_e; C_onprem_month = C_amort_month + C_power_month + C_dc; C_cloud_month = N * hours_month * p_cloud; if C_cloud_month > C_onprem_month then months_breakeven = C_capex / (C_cloud_month - C_onprem_month).

Worked Example

numGpus8
hardwareCostPerGpu35000
infraOverheadFactor0.4
amortizationYears4
gpuPowerKw0.7
pue1.4
electricityPricePerKwh0.12
hoursPerMonth400
datacenterMonthlyCost3000
cloudPricePerGpuHour4.5
Result: onPremMonthlyCost: 16800; cloudMonthlyCost: 14400; onPremCostPerGpuHour: 5.25; cloudCostPerGpuHour: 4.5; breakevenMonths: nullWith these assumptions, cloud remains slightly cheaper per month; the on-prem cluster never beats cloud within the 4-year amortization window, so no clear break-even point appears.

Frequently Asked Questions

How should I estimate realistic GPU utilization hours?

Use measured scheduler logs or production monitoring to estimate average monthly utilization hours per GPU under your expected workload mix.

Can I include staff costs and cooling separately?

Yes. Enter recurring costs in the datacenter monthly cost field if you want those costs reflected in on-prem TCO.

Do tax benefits (depreciation) affect the calculation?

This calculator is a direct cost model; tax treatment and depreciation schedules should be evaluated separately in your finance process.