This study aimed to quantitatively evaluate three GSMaP products including near-real-time (GSMaP-NRT), microwave-infrared reanalyzed (GSMaP-MVK), and gauge-adjusted (GSMaP-Gauge) data with a spatial resolution of 0.1° × 0.1° versus gauge-observed data (observation) at daily and monthly time scales over Iran. Different statistical metrics including correlation coefficient (R), percent bias (PBias), root mean square error (RMSE), probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) were used to evaluate the capability of the GSMaP products. The results indicated that all three products were generally capable of capturing the spatial pattern of precipitation. However, they all overestimated precipitation in general, and there was a considerable difference between the two satellite-only products GSMaP-MVK and GSMaP-NRT and the gauge-corrected product GSMaP-Gauge. GSMaP-Gauge performed better than the other products at both daily and monthly time scales. The evaluations demonstrated that all the GSMaP products provided better estimations of precipitation over Western than Eastern Iran. The strongest agreement between the products and the observed data was observed for the rainy months, while performance was poor for the dry months. The findings could help GSMaP product developers to better understand the characteristics of the involved errors.