If you run an AI-powered SaaS on dedicated GPU hosting, pricing your own product matters as much as infrastructure cost. Per-seat and per-GPU-capacity models have very different dynamics.
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Per-Seat
Charge $X per user per month. Simple, familiar to SaaS buyers, predictable revenue.
Downside: heavy power users subsidise light users. A user running 1000 AI queries/day costs you far more than the user running 5/day but pays the same. Profit margin is highly skewed.
Per-GPU Capacity
Sell dedicated GPU capacity to the customer: “1 dedicated 5080 instance” or “pooled 2 TFLOPs compute”. Unit economics are clear – each customer’s bill covers their infrastructure.
Downside: harder to sell. Customers have to think about GPUs. Often suits B2B developer tools more than end-user products.
Hybrid
Tiered seats with usage caps, overage charged at marginal cost. Standard seat: $20 with 500 queries/month. Power seat: $100 with 5,000 queries/month plus overage.
This is the most common modern pattern. Protects you from ruinous users while remaining seat-simple to sell.
Picking
| Situation | Best Model |
|---|---|
| B2C chatbot product | Tiered seats |
| B2B developer tool | Per-seat + usage |
| API for developers | Per-token or per-request |
| Agency / consulting | Per-GPU-month |
| Internal IT tool | Per-seat (simplest) |
Fixed Infrastructure for Flexible Pricing
Predictable UK dedicated GPU hosting costs regardless of your own pricing model.
Browse GPU ServersSee SaaS unit economics and pricing your AI API.
