GPU vs API Break-Even Calculator
Compare the real monthly cost of self-hosted GPU inference vs. hosted API tokens. Find the exact break-even volume where self-hosting becomes cheaper.
Configure Your Workload
GPU Hardware
$1.006/hr × 730 h = $734/mo on-demand
Model to Self-Host
Fits: 14 GB needed, 24 GB available (1× A10G 24 GB)
API to Compare Against
Token Volume & Utilization
Configure workload and click Calculate Break-Even
Monthly costs, break-even volume, and recommendation will appear here
GPU vs API Decision Guide
- The 60% utilization rule: Self-hosted GPU costs are mostly fixed. If your workload can't sustain >60% utilization, the API almost always wins on cost-per-token.
- Ops overhead is real. Add 15–30% on top of GPU cost for monitoring, storage, networking, inference framework tuning, and on-call engineering time.
- int4 quantization halves your VRAM requirement with ~5–10% quality loss on most tasks. It lets you run 70B on 2× A100 40 GB instead of needing 80 GB cards.
- Cloud on-demand GPUs rarely make sense for long-running inference. Spot or reserved instances can cut GPU cost 60–70%. Bare metal colocation is cheapest for sustained high-volume loads.
- APIs win for bursty, low-volume, or latency-sensitive workloads. No cold-start, no provisioning, no idle cost. Self-hosting wins at consistent high volume with data privacy needs.