MVBench is a comprehensive Multi-modal Video understanding Benchmark. It was introduced to evaluate the comprehension capabilities of Multi-modal Large Language Models (MLLMs), particularly their temporal understanding in dynamic video tasks. MVBench covers 20 challenging video tasks that cannot be effectively solved with a single frame. It introduces a novel static-to-dynamic method to define these temporal-related tasks. By transforming various static tasks into dynamic ones, it enables the systematic generation of video tasks that require a broad spectrum of temporal skills, ranging from perception to cognition.