// AI news · 2026-11-03 · Google AI Changelog
Cheap classifiers route decisions across Gemini models
Google introduces lightweight classifiers to route coding agent tasks efficiently, avoiding unnecessary high-cost reasoning.
Published 2026-11-03 08:00 (Beijing time)Source Google AI ChangelogAuto-summarised, fact-checked against source
01Summary
A test with Jev classifier shows atomic decision-making outperforms broad routing or heuristic rules on unseen tasks. Local heuristics degrade significantly under real-world conditions, while Jev maintains 100% accuracy. Setting maxOutputTokens does not reduce token costs for simple tasks, as outputs rarely reach the limit.
Summarised from the original article by an open-source model, then checked automatically: every number and English name must appear in the source. The original article is authoritative.
02Key points
- Jev uses structured primitives to route tasks efficiently without expensive reasoning.
- Atomic checks outperform broad routing on unseen coding tasks.
- Local heuristics fail under real-world traffic, dropping from 93.8% to 70.6%.
- maxOutputTokens has no effect on thinking token cost for simple tasks.
03Source
Cost per task: Using cheap classifiers to route across Gemini models and thinking levels
Google AI Changelog · published 2026-11-03 08:00 Beijing time
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