JevBench evaluator: most models lose to fixable settings and calibration
airesearch12 · x · 2026-09-27
After running evals on dozens of Jev-class models, the evaluator keeps seeing the same easy wins authors miss: settings, option handling, calibration, and speed/cost trade-offs that would move models up the board. Since 1:1 feedback doesn't scale, authors who book a dedicated eval on JevBench / ImageJevBench get his notes on what he noticed and would change. He stresses this is purely technical advice — evaluation stays fair and independent, rankings cannot be bought, and bribery attempts get a leaderboard ban.
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