Open or closed, hosted or private, fine-tuned or prompted? A practical framework for choosing the right LLM for an enterprise use case — without locking yourself in.
Start with the use case, not the model
The 'best' model depends on the job: latency, accuracy, privacy and cost pull in different directions. Pin those requirements down before you compare leaderboards.
The real trade-offs
Frontier hosted models lead on capability; open models win on control, privacy and unit economics at scale. Most enterprises end up with a portfolio, routing each task to the cheapest model that clears the quality bar.
Avoid lock-in
Abstract the model behind your own interface, keep your evals provider-agnostic, and treat the model as a swappable component. The field moves monthly; your architecture should let you move with it.
Prove it with evals
Don't choose on vibes or vendor demos. Build a small, representative eval set from your own data and let the numbers decide — it's the cheapest insurance you can buy.