Somewhere in most AI infrastructure conversations, someone suggests self-hosting the model on dedicated GPUs instead of paying per-token API costs. It's an appealing idea — fixed cost instead of variable, no rate limits, full control — and it's frequently the wrong call, because the comparison people run in their heads ignores utilization, ops burden, and the fact that GPU capacity sitting idle overnight is a cost, not a saving.
The costs that don't show up in the naive comparison
- Utilization — a GPU instance costs the same whether it's serving requests or sitting idle. Unless your traffic is steady and high enough to keep it busy most hours, the effective per-request cost is far higher than the sticker price suggests.
- Operational burden — someone now owns model updates, scaling policy, failover, and security patching for infrastructure that used to be someone else's problem entirely.
- Latency and reliability engineering — a hosted API comes with someone else's SRE team behind it. Self-hosting means you're building that reliability yourself, from the first outage.
Where self-hosting genuinely wins
At sustained high volume with predictable, steady traffic, where utilization stays high around the clock. When data sensitivity rules out sending requests to a third party regardless of cost. Or when a smaller, fine-tuned open-weight model can match a much larger API model's accuracy on your narrow task — trading model size for cost efficiency deliberately, not by default.
Run the actual crossover calculation before deciding: your expected volume, your traffic shape (steady versus spiky), your team's capacity to own new infrastructure, and your data sensitivity requirements. The answer is a number, not an instinct about which option sounds more serious.
The pragmatic default
Start on a hosted API. It's faster to ship, someone else owns the reliability, and you'll have real production volume data before you need to guess. Move to self-hosted only when the data says the crossover point has actually been reached — not when it feels like the more sophisticated architecture.