Jev + Opus: Frontier-Accuracy LLM Judging at 4x Lower Cost
Hightouch's test: a Jev plus Opus hybrid judge matched frontier accuracy at over 4x lower cost.
About Jev + Opus: Frontier-Accuracy LLM Judging at 4x Lower Cost
Hightouch tested whether decision models, Jev and Luna, could grade identity resolution: deciding which customer records belong to the same real person. Out of the box they scored 88.8 to 97.3% accuracy. They were up to 90 times cheaper and more than 10 times faster than a frontier model, at $0.05 to $0.10 per 1,000 identities and about 0.15 seconds per answer, but trailed Opus by about 6 percentage points on harder benchmarks.
Why it is worth reading: the useful finding is about calibration. Most of Jev's mistakes came with low confidence, while most of Luna's came with high confidence. That makes Jev the better first pass in a hybrid that sends low-confidence calls to Opus. If you run an LLM judge on volume, the routing pattern transfers to your own task.
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- November 9, 2026
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