Local vs. cloud models: Local vs. cloud models: quality, data protection, costs, latency, operation.
Local and external language models: where local models suffice, where external ones help, and why the answer is usually both, depending on the task.
In short: Local models protect data and cost money to operate; external models offer reach and cost money per use. The right strategy is rarely one or the other. It is routing per task – exactly what Swiss AI Factory does.
Not “either – or”, but “which one for what”.
Local models can be sufficient for classification, extraction, knowledge search and summarisation. With a suitably configured operating model, data can be processed locally. For broad research on public data or demanding wording, an external model may be better.
A decoupled application layer can connect local and external models and make switching easier. Testing, interfaces and contracts still need to be checked.
Local vs. external.
| Criterion | Local | External |
|---|---|---|
| Privacy policy | local processing as configured | check processor arrangements, contract and location |
| Quality | sufficient for standard tasks | often higher for broad, creative tasks |
| Cost | Hardware + operation, no usage fee | usage-based, scales with volume |
| Latency | depends on your own hardware | depends on network and provider |
| Operation | your own IT or a partner | Provider |
| Dependency | low | high if the application is tied to the model |
Decision path
- Define data classes: what may go where?
- Assign tasks: classify, extract, search → local; public research → external.
- Calculate costs per task, not as a flat rate.
- Decouple the application layer so the assignment can still be changed.
What this article is based on.
- Own project evaluations at Swiss AI Labs on model assignment; no external study
Products, Labs and case studies.
Frequently asked questions: local vs. cloud models
Are local models worse?
For many business tasks, no. We measure per task instead of making sweeping judgements.
Can you switch later?
A decoupled application can make switching easier. Configuration, testing and possible adjustments are still needed.
Have a specific process assessed.
The AI potential assessment examines the benefits, prerequisites and risks of the process.