Choosing AI models

Model choice is an engineering decision, not a fandom. Here is the framework we use before writing a single line of code.

Start with the task, not the model

Write down what success looks like: acceptable latency, output format, cost ceiling. A model that "wins benchmarks" but blows your latency budget is the wrong model.

Test with your own data

Public leaderboards measure someone else’s data. Run 20–50 of your real inputs through 2–3 candidate models and compare outputs blind. The winner often is not the loudest name.

Frequently asked questions