GPU & Cost Calculator
How many GPUs do you
actually need?
Enter your traffic and model requirements. We’ll calculate the exact GPU count and VRAM needed to handle your load without crashing — then compare costs across every major cloud.
Your workload
Models to serve
20
150
Avg model size
8 GB
1 GB80 GB
Requests / hour per gateway
8,000
100100,000
Hours / month
Avg tokens / response
Traffic pattern
What you need to handle this load
Peak concurrent requests
9
8,000 req/hr ÷ 3600 × 3.8s avg response
Without VRAM AI — dedicated endpoints
160 GB
20 GPUs · 1 dedicated GPU per model (cloud default)
With VRAM AI — VRAM needed
72 GB
9 active in VRAM · 11 in RAM/disk
Why VRAM AI needs fewer GPUs: At 8,000 req/hr through the gateway you have 9 concurrent requests at peak. VRAM AI keeps only the 9 hot models resident — the other 11 models stay in RAM/disk and swap in on demand. Traditional pays for all 20 models in VRAM 24/7.Break-even: VRAM AI saves GPU cost while the hot set stays below your 20 models — i.e. gateway traffic under 9,600 req/hr (with 150-token responses). You are at 8,000 — safely under.
Cloud cost comparison — traditional vs VRAM AIswipe →
| Provider | GPU | $/hr / GPU | GPUs (Traditional) | Cost / mo (Traditional) | GPUs (VRAM AI) | Cost / mo (VRAM AI) | Monthly savings |
|---|---|---|---|---|---|---|---|
GCP | T4 16G | $0.35 | 20 GPUs $7/hr 1 dedicated GPU × 20 models | $5,110 | 5 GPUs $2/hr 9 active in VRAM · 11 in RAM/disk | $1,278 | OLD NEW Save $3,833 75% less |
Azure | T4 16G | $0.53 | 20 GPUs $11/hr 1 dedicated GPU × 20 models | $7,738 | 5 GPUs $3/hr 9 active in VRAM · 11 in RAM/disk | $1,935 | OLD NEW Save $5,804 75% less |
AWS | T4 16G | $0.53 | 20 GPUs $11/hr 1 dedicated GPU × 20 models | $7,738 | 5 GPUs $3/hr 9 active in VRAM · 11 in RAM/disk | $1,935 | OLD NEW Save $5,804 75% less |
Your best monthly saving
Best savings on Azure using T4 16G — $7,738 traditionally vs $1,935 with VRAM AI.
Per month
$5,804
$7,738 → $1,935 per month
GPU prices are on-demand estimates as of June 2026 · AWS per-GPU rates from multi-GPU instance pricing
Concurrency model: Little’s Law — concurrent = (req/hr ÷ 3600) × avg_response_seconds
Avg response time estimated from token count at 40 tok/s (A100-class GPU)