A new generalized embedded-atom method (GEAM) model driver with various parameterizations is now available in OpenKIM (DOI: 10.25950/835fca74). The driver was adapted by Chloe Zeller and Woo Kyun Kim from a LAMMPS implementation of GEAM by Amit Samanta and coworkers at LLNL. This Driver is compatible with all simulators compatible with the KIM API. Currently (30-Jan-2026), there are seven parameterizations (KIM Models) available for this Driver for a variety of metallic material systems. GEAM is a data-driven interatomic potential aimed at modeling primarily BCC metals with accuracy comparable to machine learning potentials. It includes contributions from embedding energy, two- and three-body interactions, and nonlocal many-body interaction terms. The use of basis functions provides sufficient flexibility to model diverse atomic environments and simplifies the optimization of free parameters.