GPU compute is the single largest line item for most AI projects. With a few disciplined habits you can cut that bill dramatically without slowing your models down.
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Right-size your VRAM
The most common mistake is renting a card far larger than the model needs. Quantized 7B–13B models run comfortably on 16–24GB of VRAM, so paying for an 80GB data-center card wastes money on idle capacity.
Use spot and reserved pricing
Interruptible spot instances can be 60–70% cheaper for fault-tolerant batch jobs. For steady production traffic, reserved plans beat on-demand rates once utilization passes roughly 40%.
Measure before you optimize
Track cost-per-token, not cost-per-hour, and use our VPS cost calculator to model different providers side by side before committing to any long-term plan.
