Serving and fine-tuning AI models is now the fastest-growing reason to rent a server. We benchmarked on-demand GPU clouds on the metric that actually matters for your budget: real price-per-token, not sticker price-per-hour.
Why price-per-hour lies
A cheaper hourly GPU can cost you more if it has slow cold starts, limited VRAM, or throttled bandwidth. We measured end-to-end throughput on a Llama-class model and divided by the hourly rate to get a true cost-per-token figure.
The results reshuffled the rankings entirely — a mid-priced RTX 4090 instance beat several "cheaper" cards once real throughput was accounted for.
Matching the GPU to the job
For inference on 7B–13B models, 16–24GB of VRAM is the sweet spot and keeps hourly costs low. Fine-tuning and image generation reward larger cards and faster interconnects, where data-center GPUs pull ahead despite the higher rate.
Our recommendation
Start on an hourly RTX instance with a new-user credit to prototype cheaply, then move sustained production workloads to a reserved plan. Use our VPS cost calculator to project your monthly spend before you commit.
