Router Lab
Live published free itemAI Token Coach Router Lab: When to Use a Fast Model vs a Deep One
A free decision rule for routing: use a fast model for classification, drafts, and clear narrow tasks; reserve a deep model for ambiguous reasoning, high-stakes judgement, and hard synthesis. Wrong default burns capacity or quality.
What changed
Many teams default everything to the strongest model, or everything to the cheapest. Both waste capacity or quality. Router Lab starts with a simple fast-vs-deep rule of thumb.
Why it matters
Routing is a primary burn and performance lever once prompts are clear. Free orientation now; deeper playbooks later as paid.
Take
A free decision rule for routing: use a fast model for classification, drafts, and clear narrow tasks; reserve a deep model for ambiguous reasoning, high-stakes judgement, and hard synthesis. Wrong default burns capacity or quality.
What to do
Label the next 20 tasks fast or deep before you send. Deep only if ambiguity, stakes, or multi-step reasoning are real. Review misses (fast failed; deep was overkill) at week end.
Evidence
No public sources are linked yet.