The Matbench test suite v0.1 contains 13 supervised ML tasks from 10 datasets. Matbench’s data are sourced from various subdisciplines of materials science, such as experimental mechanical properties (alloy strength), computed elastic properties, computed and experimental electronic properties, optical and phonon properties, and thermodynamic stabilities for crystals, 2D materials, and disordered metals. The number of samples in each task ranges from 312 to 132,752, representing both relatively scarce experimental materials properties and comparatively abundant properties such as DFT-GGA formation energies. Each task is a self-contained dataset containing a single material primitive as input (either composition or composition plus crystal structure) and target property as output for each sample.