Choosing the Right Model for the Job
Frontier vs. fast vs. local — a decision guide that maps model choice to the actual shape of your task.
Choosing the Right Model for the Job
The best model is the cheapest one that clears your quality bar — and that changes per task.
Match the model to the work
- Hard reasoning, planning, ambiguous goals → a frontier model. This is where capability pays for itself.
- High-volume, well-defined steps (classify, extract, format) → a smaller, faster model. Often 80% of an agent's calls.
- Private or offline data → a local model, accepting a quality trade-off for control.
Mix models inside one agent
A common, money-saving pattern: a capable model plans and a fast model executes the routine sub-steps. You pay frontier prices only for frontier-shaped problems.
How to actually decide
Don't argue about it — run your golden eval set across two candidates and compare success, cost, and latency. The right answer is usually obvious within twenty examples.
Re-check quarterly
Model quality and pricing move fast. The choice you made six months ago deserves a fresh look — a routine that was too expensive last quarter may be trivial now.