perception-bench

PerceptionBench is a benchmark designed to evaluate atomic visual perception capabilities of Multimodal Large Language Models (MLLMs), using a bottom-up taxonomy of ten atomic perceptual capabilities. Results across 16 frontier MLLMs show no model reaches 60% accuracy, indicating visual perception remains largely unsolved.