By using the precipitation data of the US Global Precipitation Climate Center (GPCC) and the outputs of six Chinese climate models ［BCC_CSM1.1, BCC_CSM1.1(m), BNU-ESM model, FGOALS-s2, FGOALS-g2 and FIO-ESM］ participating in the historical simulations of Coupled Model Intercomparison Project Phase 5 (CMIP5) as well as the methods featuring the relative and absolute magnitudes of precipitation variability, this paper evaluated the capabilities of the six models quantitatively to capture the interannual and interdecadal variations of global precipitation. The research results showed that the interannual variance of observational precipitation generally accounts for 65%-80% of the total variance, and the interdecadal variance accounts for 10%-35% of the total variance. In the CMIP5 simulations, the interannual variance of the ensemble mean precipitation of the six models is generally stronger than observation, accounting for over 70% of the total variance, while the variance of the interdecadal component contributes less to the total variance (about 10%-20%). Compared with observation, the variability of the globally averaged total, interannual and interdecadal precipitations were underestimated, the contribution of interannual precipitation to total precipitation was overestimated, and the contribution of interdecadal precipitation to total precipitation was underestimated by the models. The interdecadal precipitation in East Asia and Australia was well simulated by the six models, and the ratio between simulated and observed interdecadal precipitation variance is about 1. For Africa, South America and Maritime Continent areas, the simulated interdecadal precipitation variability of BCC_CSM1.1 model is the closest to observation, and for Eurasia and North America, the simulated interdecadal precipitation variability of BNU-ESM model is also close to observation. In Eurasia, the ratio between interannual and interdecadal precipitation variances simulated by BCC_CSM1.1 model is the closest to observation, so did the FGOALS-s2 model in Africa and America. The results of this study would help to understand the current simulation ability of the six Chinese climate models and to improve the models in the future.