Run your own language model or use an API?
Updated: 2026-09
A provider API is immediately available, always current and free of operational burden, but hands data outside. A self-hosted model keeps data in house but demands infrastructure, expertise and ongoing upkeep. For most, the API wins — provided the data location fits.
As soon as a company wants to deploy AI in production this question arises, usually driven by concern about data leaving. The concern is legitimate but often leads to a decision whose follow-on costs are underestimated.
Running a model yourself is technically well within reach today. The effort lies not in getting it running but in what comes after: operations, scaling, updating, and the gap to the strongest available models, which widens over time.
Head to head
| Criterion | Self-hosted model | Provider API |
|---|---|---|
| Data sovereignty | Data stays entirely in house | Depends on provider and location — verify |
| Availability | Setup takes time, operations are yours | Usable immediately |
| Running cost | Infrastructure runs regardless of use | Billed by usage |
| Model quality | Limited to models you can operate | Access to the strongest models available |
| Currency | Updating is your job | Provider updates continuously |
| Expertise required | Operations and ML competence needed | Application knowledge suffices |
When Self-hosted model wins
- —Regulation or contracts require that data does not leave the house.
- —Load is high and even, so your own infrastructure is well utilised.
- —You have, or want, the operational and specialist competence in house permanently.
When Provider API wins
- —You want to start quickly and prove the value first.
- —Load fluctuates or is too low for your own infrastructure.
- —A provider with EU or Swiss processing meets your requirements.
Our take
Our view: for most companies the API is the right route — not out of convenience but because the gap between self-operable and the strongest available models is real and operational competence is tied up permanently. What is decisive is verifying the processing location and the contractual commitments on further use.
Self-hosting remains right where regulation or contracts leave no choice, or where load is so high and even that own infrastructure pays. A mixed route is often sensible: uncritical cases via an API, sensitive cases in house.
Parent service: Digital Transformation
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FAQ
Is an API automatically a data protection problem?
No. What matters is the processing location, contractual commitments not to use data for training, and the processing agreement. Providers with EU processing are unproblematic for many use cases.
Does self-hosting get cheaper at high usage?
Possibly — but the calculation must include infrastructure, operations, staff and updating, not only compute. Those items are regularly left out.
What about the gap in model quality?
It is real and shifts continuously. Choosing to self-host is choosing deliberately not always to use the strongest available model — for many tasks that is unproblematic.