Jev's calibration was measured. The LLMs won [D]

Jev Benchmarks, utilizing "Reinforcement Learning for Calibrated Decisions," measured the calibration of Jev against LLMs like Gemini 3.8 Flash 2.0 and DeepSeek V4.1 Flash 2.8. While Jev maintained 95% accuracy and handled 86% of yes/no decisions, its calibration gap was higher across all categories. For instance, in yes/no, Jev scored 5.0 compared to Gemini 3.8 Flash 2.0's 2.0, indicating that despite its accuracy, Jev was worse calibrated than the LLMs.

This report uniquely details Jev's calibration gap against LLMs like Gemini 3.8 Flash 2.0, showing it is worse calibrated despite higher accuracy, unlike other reports focusing solely on accuracy.