Gridded climate products (GCPs) provide a potential source for representing weather in remote, poor quality or short-term observation regions. The accuracy of three long-term GCPs (Asian Precipitation-Highly-Resolved Observational Data Integration towards Evaluation of Water Resources: APHRODITE, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Record: PERSIANN-CDR and National Centers for Environmental Prediction Climate Forecast System Reanalysis: NCEP-CFSR) was analyzed for the Kelantan River Basin (KRB) and Johor River Basin (JRB) in Malaysia from 1983 to 2007. Then, these GCPs were used as inputs into calibrated Soil and Water Assessment Tool (SWAT) models, to assess their capability in simulating streamflow. The results show that the APHRODITE data performed the best in precipitation estimation, followed by the PERSIANN-CDR and NCEP-CFSR datasets. The NCEP-CFSR daily maximum temperature data exhibited a better correlation than the minimum temperature data. For streamflow simulations, the APHRODITE data resulted in strong results for both basins, while the NCEP-CFSR data showed unsatisfactory performance. In contrast, the PERSIANN-CDR data showed acceptable representation of observed streamflow in the KRB, but failed to track the JRB observed streamflow. The combination of the APHRODITE precipitation and NCEP-CFSR temperature data resulted in accurate streamflow simulations. The APHRODITE and PERSIANN-CDR data often underestimated the extreme precipitation and streamflow, while the NCEP-CFSR data produced dramatic overestimations. Therefore, a direct application of NCEP-CFSR data should be avoided in this region. We recommend the use of APHRODITE precipitation and NCEP-CFSR temperature data in modeling of Malaysian water resources.