Open medical LLMs achieve competitive exam scores but lack reliable confidence signals, sound clinical reasoning for many correct answers, and don't actually use medical images—critical gaps for real healthcare deployment beyond raw accuracy metrics.
This study evaluates four open-source language models (8-27B parameters) on the Spanish MIR medical residency exam, examining not just accuracy but also confidence calibration, reasoning quality, and image use.