AI EVALUATION, IN CONTEXT.BY EQUALITY MACHINE

LLM Stats

PathMCQA

PathMMU is a massive multimodal expert-level benchmark for understanding and reasoning in pathology, containing 33,428 multimodal multi-choice questions and 24,067 images validated by seven pathologists. It evaluates Large Multimodal Models (LMMs) performance on pathology tasks, with the top-performing model GPT-4V achieving only 49.8% zero-shot performance compared to 71.8% for human pathologists.

Evaluation context and evidence

Source
LLM Stats
Publisher
Not recorded
Benchmark release
Not recorded
Collected
2026-08-17
Modality
multimodal

These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.

Original sources

Reported results 1

Shown in source observation order, not ranked. Dates retain the precision provided by the source.

ModelValueUnitProtocolReported date and basisSource
MedGemma 4B IT0.698Not recordedNot recorded2025-05-20 · model_announcementLLM Stats