GPU Procurement Intelligence
for Enterprise Teams
Normalize cloud GPU pricing across providers, model your deployment scenario, and build a defensible business case — without needing a dedicated infrastructure analyst.
Book a Free Discovery Call →15 providers, per-GPU pricing, apples-to-apples. On-demand, spot, and 1-year reserved, all on the same scale.
Input your workload — request volume, cluster size, training run, inference throughput — and get a cost and ROI output specific to your situation, not a generic benchmark.
Generate a shareable business case that compares on-prem vs cloud, hyperscaler vs specialist cloud, and reserved vs on-demand — with the numbers to back the recommendation.
Model the full 3-year cost of owning vs renting GPU capacity before committing budget. Factor in hardware depreciation, power, staffing, and cloud equivalent rates.
Run TCO Calculator →Compare GPU cloud providers on normalized per-GPU pricing and minimum commitment — side by side in a single table.
Open Pricing Table →At your expected utilization rate and workload duration, does a 1-year reservation pay off vs paying on-demand? Get the exact crossover point.
Run Breakeven Analysis →Monthly bill & cost per 1M tokens at your request volume
Model
Requests/day — 10,000
Tokens/request — 500
GPU Utilization — 70%
RTX 4090 is cheapest at this scale — saves $5,884/mo ($70,606/yr) vs the most expensive option.
* NVIDIA/AMD: vLLM FP16 throughput. Google TPU: JAX/JetStream benchmarks (not directly comparable). 730 hrs/month on-demand pricing. H300: estimated specs.
Walk through your procurement scenario with us — free 30-min call, no pitch.