Right-Sizing GPU Capacity Cost Without Overprovisioning

Right-sizing GPU capacity cost means matching the commitment to the utilization floor — the capacity that is always used — and buying the variance flexibly, so the fixed cost is never wasted on idle GPUs. For the capacity sizing method, see how to size AI infrastructure capacity. For the cost framework, see GPU cost per hour vs TCO.

The Right-Sizing Method

Find the utilization floor: the minimum GPU-hours used each month, not the average or peak. This is the commitment — the capacity that is never wasted because it is always used. Commit to the floor at a reserved or dedicated rate for the lowest unit cost on the steady-state baseline. Buy the variance flexibly: the capacity above the floor — the gap between minimum and peak — is purchased on-demand or spot, paying a premium only for the capacity actually used during spikes. Monitor and adjust: as workloads evolve, the floor shifts. Review quarterly: is the floor higher (increase commitment for lower rate on larger baseline) or lower (decrease commitment to avoid paying for idle capacity)? For the monitoring method, see stabilize AI infrastructure cost.

FAQ

How do I avoid overprovisioning GPU capacity?

Commit to the utilization floor — the minimum always-used capacity — at a reserved rate. Buy the variance above the floor flexibly. Review quarterly to adjust the commitment as workloads evolve. Overprovisioning is committing to the peak; right-sizing is committing to the floor. See the method above.

Summary

Right-size GPU capacity by committing to the floor and buying variance flexibly. For the full framework, see how to size AI infrastructure capacity.