ZeroBench is a benchmark specifically designed to evaluate the visual understanding capabilities of large multimodal models (LMMs). It challenges the limits of current models through 100 meticulously crafted and rigorously vetted complex questions, along with 334 sub-questions. This benchmark aims to address the shortcomings of existing visual benchmarks by offering a more challenging and high-quality evaluation tool. ZeroBench's primary strengths are its high difficulty, lightweight design, diversity, and high quality, enabling it to effectively differentiate model performance. Additionally, it provides detailed sub-question evaluation, helping researchers better understand the reasoning abilities of the models.