Cost at different volumes
Cloud scales with usage; self-hosting is flat until you need more GPUs.
| Tokens / mo | Cloud API | Self-hosted | Cheaper |
|---|
Fixed cost vs per-token cost
The whole decision comes down to one shape. A cloud API is a straight line through the origin: zero tokens, zero cost; double the tokens, double the bill. A self-hosted GPU is a flat line: you pay the same rental whether it serves one request or a million, until you saturate it and rent another. At low volume the API is obviously cheaper — you'd be paying for an idle GPU. Somewhere up the curve the lines cross, and beyond that break-even volume your own hardware wins. This tool finds that crossover for your numbers.
Utilization is the hidden killer
The mistake people make is comparing a 24/7 GPU rental against an API at peak traffic. But traffic isn't flat — it's spiky. If your GPU is only busy 40% of the time, you're paying full rental for less than half the work, so your real cost per token is more than double the napkin math. Self-hosting only pays off when the GPU stays genuinely busy: steady traffic, request batching, and a queue that smooths spikes. Below the break-even line, the convenience and zero-idle billing of an API almost always wins.
Decide with the full picture
Even above break-even, the GPU bill isn't the whole story — budget for the engineering to deploy and babysit the model, monitoring, and scaling for spikes. Many teams run a hybrid: self-host the steady baseline load and burst to an API for peaks. Model the API side precisely with the AI cost calculator and the AI app cost estimator, and if you're deciding between providers first, compare them on the AI API guides.
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