Self-hosted AI vs a per-token API: which is cheaper?
Whether running your own AI is cheaper than a public API comes down to how much you use it. A per-token API costs almost nothing to start but grows with every user and every message. Self-hosted AI is a large fixed cost up front that stays flat no matter how much you run it. The right choice depends on your volume, your user count, and how sensitive your data is.
Two ways to pay for AI
There are two cost models to compare.
- Per-token API. You call an external model (ChatGPT, Claude and similar) and pay for every unit of text going in and coming out. The starting cost is near zero, but the bill rises with each user, each conversation, and each long document you process.
- Self-hosted. You buy GPU hardware once, pay a one-time setup, and optionally a managed plan. The cost is flat: one heavy user or fifty cost the same, because the machine is already paid for.
When a public API is cheaper
For low or occasional use, the API almost always wins. If a handful of people run a few queries a day, or your AI feature is still an experiment, you would pay years of token bills before you matched the price of a GPU. Pay-per-use also means no capital outlay and nothing to maintain.
When self-hosting wins
Owning the hardware pays off in three situations:
- Many users. Dozens of people using AI daily turn a small per-message fee into a large monthly bill.
- High message volume. Bulk jobs, long documents, and automated pipelines burn tokens fast.
- Sensitive data. Legal, medical, or client records that must stay in-house. With a private model, prompts and data never leave your machine, which matters for GDPR and NIS2.
A simple break-even example
Say a team of twenty uses AI heavily every working day for drafting, support replies, and document analysis. On a per-token API that traffic can run into a serious monthly bill that only climbs as adoption grows. A private appliance is a one-time hardware purchase plus setup, and the team can pass its cost within a year or two of heavy use. After that point extra usage is effectively free, while the API bill keeps rising every month. Flip the numbers around: a five-person team with light, occasional use may never reach that break-even, and the API stays the smarter choice.
Exact figures depend on the models you run and how you use them, so we quote each case rather than publish one price.
Which fits your business
If you have the volume or the privacy need, a private model on our GPU hardware in Riga gives you flat, predictable cost and full control over your data. Our AI servers are ready appliances (128 GB VRAM, enough to run Llama 3.3 70B for 10 to 20 users) or standalone GPU cards, a one-time purchase quoted per case with an optional managed plan from 500 EUR per month. For lighter, low-volume needs there is a cheaper middle path: an AI agent on a normal VPS that calls an external model API from 9.35 EUR per month, with no GPU to buy. Tell us your user count and workload and we will size the right option.