Cloud vs Local GPU Cost Calculator
Should you buy a GPU or rent cloud GPUs? This calculator compares the total cost of owning a local GPU (purchase + electricity, amortized over 36 months) against hourly cloud GPU rental on RunPod and Vast.ai.
Your usage pattern
The GPU you would buy if going local.
How long the GPU is actively loaded running inference. 24 hrs/day = always-on server.
How many days per month you actually use the GPU.
Your local electricity cost. Affects the local option only.
Spread the GPU purchase cost over this period. Longer = lower monthly cost but assumes the GPU holds value.
Local GPU
$78
per month
Cloud GPU
$39
per month
Break-even analysis
At this usage, the GPU pays for itself in 28 months vs pure cloud rental.
How the math works
Local GPU monthly cost
Local cost combines the amortized purchase price (spread over your chosen period) and monthly electricity. Electricity assumes 70% of the GPU's rated TDP during active use — real GPUs rarely hit 100% power draw during inference.
local_monthly = (gpu_price / amortize_months) + (tdp × 0.7 × hours × days × rate / 1000)
Cloud GPU monthly cost
Cloud cost is just hourly rate × monthly hours. No electricity, no hardware maintenance, no wear and tear — but also no asset at the end.
cloud_monthly = hourly_rate × hours × days
Break-even month
How many months of cloud rental would equal the GPU purchase price? This assumes electricity is a wash (roughly, it's added to cloud rental too via the provider's margin).
break_even = gpu_price / (cloud_monthly - electricity_monthly)
When cloud actually wins
- Occasional use — under 1-2 hours/day makes cloud cheaper until you hit 24+ months of ownership. Our RunPod vs Vast.ai comparison covers which provider fits which use case.
- Need large VRAM rarely — renting a 80GB H100 occasionally beats buying a 48GB A6000 you only use monthly
- Experimentation phase — not committed to local inference yet; cloud avoids the risk of buying the wrong card
- High electricity cost — at $0.35/kWh, local gets expensive fast with always-on inference
When local wins
- Heavy daily use — 4+ hours/day, 7 days/week — local almost always wins within a year. See our best used GPU for AI guide for the best buy-it-once options.
- Privacy-critical workloads — local keeps data off third-party servers
- Low electricity cost — under $0.15/kWh tilts the math toward local
- Development workflows — no cold-start latency, always-available for iteration
Electricity estimates use 70% of rated TDP, which is typical for sustained inference. Cloud rates are representative ranges (community/secure tiers vary by provider). GPU resale value at the end of the amortization period is assumed to be zero — real resale recovers 30-50% of purchase cost for NVIDIA cards in good condition, which tilts the math further toward local ownership. See our methodology.