Scaling from a dozen cells a decade ago to millions of cells today, single-cell measurement technologies are driving a revolution in the life sciences. Recent advances make it possible to measure multiple high-dimensional modalities (e.g. DNA accessibility, RNA, and proteins) simultaneously in the same cell. This data provides, for the first time, a direct and comprehensive view into the layers of gene regulation that drive biological diversity and disease. In this competition, we present three critical tasks on multimodal single-cell data using public datasets and a first-of-its-kind multi-omics benchmarking dataset. Teams will predict one modality from another and learn representations of multiple modalities measured in the same cells. Progress will elucidate how a common genetic blueprint gives rise to distinct cell types and processes, as a foundation for improving human health.