---
title: "Route Reasoning Effort by Task Difficulty"
description: "Build a simple difficulty router with escalation based on confidence and verification rather than one expensive default."
language: en
canonical: https://navinresearch.com/blog/reasoning/reasoning-effort-routing.md
topics: ["reasoning effort routing", "adaptive inference", "LLM cost optimization"]
---

# Route Reasoning Effort by Task Difficulty

Build a simple difficulty router with escalation based on confidence and verification rather than one expensive default.

**Short answer:** Start low and escalate when a deterministic verifier fails, required evidence is absent, or the task belongs to a benchmarked hard class. The router should use observable features and never treat self-reported confidence as proof.

## Implementation steps

1. Extract routing features such as tool count, constraint count, input length, and verifier availability.
2. Choose effort tiers from measured task performance.
3. Run the cheapest tier first when verification is inexpensive.
4. Escalate with the original evidence and failure reason, not an ever-growing transcript.

## Validation checklist

- Measure false escalations and missed hard tasks.
- Cap attempts and total spend.
- Log router version so regressions can be attributed.

## Common mistakes

- Routing from prompt length alone.
- Trusting a confidence sentence generated by the same model.
- Retrying identical inputs without new information or changed settings.

## Practical decision

Ship the smallest design that passes the checks above. Record the model, prompt, tool, dataset, and runtime versions used in testing so later changes can be compared rather than guessed. Recheck the linked documentation before relying on provider-specific limits, model names, prices, or preview features; those details change more quickly than the engineering principles in this note.

## Official sources

- [OpenAI, Evaluations guide](https://platform.openai.com/docs/guides/evals)
- [Anthropic, Extended thinking guide](https://docs.anthropic.com/en/docs/build-with-claude/extended-thinking)

---

Reviewed: 2026-08-24. This concise engineering note is educational, not a claim that Navin Research created or independently verified the cited provider technology.