In the ongoing effort to improve Earth orientation parameter (EOP) prediction accuracy, the effect of various atmospheric models on EOP forecasts is explored. The first derivative of UT1-UTC, or length of day (LOD), is proportional to the axial component of the dimensionless effective atmospheric angular momentum (AAM) functions, given conservation of angular momentum in the Earth-atmosphere system. Previous work showed that using a robust multiple regression algorithm to pre-process AAM data improves 0 and 7-day predictions of UT1-UTC by 47% and 20%, respectively, even when significant outliers are present in other UT1 or LOD measurement sources during combination. AAM data are produced by various atmospheric modeling centers, and previous work used inputs from multiple AAM models weighted by their regression fit alone after applying effects from estimated systematic errors. This present work compares different AAM models to the derived geodetic AAM excitation functions to better characterize the systematic effects of the individual models. Various techniques to compare model accuracies are explored, and the effects of different AAM models on UT1-UTC forecasts are estimated