GPU cost rising

GPU cost rises quickly when workloads scale faster than efficiency improvements. The hardware may be doing exactly what it is supposed to do, but the economics become uncomfortable if utilization is low or inference demand keeps growing.

Some of the cost increase comes from using heavy models where lighter ones would work well enough. Other times the issue is poor batching, low utilization, or too much idle capacity being left on the table.

The best response is to look at utilization patterns, model routing, and workload shape. Cost control gets much easier when the team understands where compute is actually being spent.