Deep Learning models are designed to get max throughput on GPUs, which ends up being batched workloads.

You'll never get proper price competitive utilization on personal hardware vs a cloud inference provider that can batch and pipeline requests optimally to maximize utilization, unless you yourself start running batch jobs.

Even once local hardware and models catch up to todays frontiers, by that time there will be 10x better cluster sized models available at a similar discount.