Rent a GPU or pay per token β see which wins at your volume, and where they cross.
Self-hosting wins only when you keep the GPU busy enough to beat the per-token rate. Model the raw GPU bill on the GPU cloud cost calculator and the true per-token rate you would hit on the GPU inference cost calculator.
The Self-Host vs API Cost Calculator computes two monthly figures side by side: what you would pay a provider at a per-token API rate, and what it would cost to rent a GPU and run an open model yourself. The API side is simple β your tokens per month multiplied by the API price per 1M tokens. The self-host side is driven by the GPU hourly rate, the model's throughput in tokens per second, and your realistic utilisation, which together set an effective cost per token. The tool then finds the monthly volume where self-hosting becomes cheaper than paying per token.
The number to watch most closely is utilisation. A rented GPU bills every hour whether it is busy or idle, so a card running at 20% of capacity effectively costs five times more per token than one kept saturated. Self-hosting tends to win only at high, steady volume; below the breakeven point, API pricing is usually cheaper and carries no fixed commitment. Before switching, confirm your real traffic can keep the hardware genuinely busy β an optimistic throughput or utilisation estimate can make self-hosting look far better than it performs in practice.
Only at high, steady volume. A rented GPU is a fixed 24/7 cost, so it pays off once your token throughput fills it. Below the break-even volume the per-token API is cheaper because you pay only for what you use; above it, a well-utilised GPU beats the metered price.
Utilisation is the big one β a GPU billed around the clock but used 30% of the time triples your effective cost per token. On top of that come engineering time, autoscaling for spikes, model quality gaps versus frontier APIs, and reliability. Factor those before switching for the sticker saving.