The capability of Coupled Model Inter-comparison Project Phase-6 (CMIP6) is analysed in simulating the seasonal variability of Sea Surface Temperature (SST) and Sea Surface Salinity (SSS) over the Arabian Sea in this study. The historical simulations of 11 CMIP6 models, which come from various source are validated with the observational data (HadISST for SST and SODA for SSS). This study covers the Arabian Sea, spanning 5°S to 32°N and 33°E to 80°E from 1985 to 2014 (30 years). Seasonal mean climatology and annual cycle of SST and SSS are estimated over the Arabian Sea. The deviation of coupled model-simulated SST and SSS from the observation is quantified by determining the biases during all the seasons. Four distinct model evaluation measures are used to access the performance of CMIP6 models: root mean square error (RMSE), standard deviation (STD), correlation coefficient (CC) and interannual variability skill score (IVS). CMCC-CM2-SR5, NESM3 and IITM-ESM models for SST yield CC/RMSE values of 0.988/0.174, 0.983/0.204 and 0.963/0.299, respectively. CMCC-CM2-SR5, IPSL-CM6A-LR and CanESM5 models for SSS yield CC/RMSE values of 0.956/0.035, 0.937/0.042 and 0.820/0.069, respectively. Thus, these models having higher CC and lower RMSE among all models, give better performance. The present study is important as the future scenarios can be predicted using the best models.