Jev calibration benchmark: LLMs beat humans yet know when they're right

Jev Benchmarks published calibration results: its training method is called Reinforcement Learning for Calibrated Decisions, yet its calibration gap trails Gemini 3.8 Flash, DeepSeek V4.1 Flash and GLM-5.3. Jev holds 95% accuracy and decides alone on 86% of yes/no items, more than those models, showing worse calibration but better awareness of when it is right.

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