TL;DR: Classifier-style "decision models" can replace LLM judges at 16 to 357 times lower cost, but they get things wrong in the same places the LLMs do.
Decision Models vs. LLMs as Rubric Judges: Cheaper, Faster, and Wrong in the Same Places
Key points
ใปโ๏ธ Compares Jev and Perplexity's Decider against 3 flash-tier LLM judges on 7 benchmarks, 9 panels, 5,003 items
ใป๐ธ LLM judges cost 16 to 357x more and take 5 to 350x longer
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Accuracy: significantly worse in at most 6 of 27 comparisons, and often stronger on binary panels
ใป๐ Weaker on ordinal scales, scoring lower than human raters
ใป๐ When Jev is confidently wrong, 96.0% of LLM verdicts repeat the error (50.3% expected by chance)
ใป๐ช Cascades gain at most +2.7 points, and just +1.7 even with higher-tier fallbacks
Swap them in to save cost; "defer to an LLM when unsure" is a weak accuracy safety net.
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