This article estimated the precision of the precipitation simulated by 15 IPCC AR5 (the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC AR5) GCMs (Global Climate Models) and the multi-model ensemble (MME), based on the observed precipitation from 660 stations in China during 1996 to 2005. We firstly extracted the model simulation value at the corresponding position of the meteorological station, using the bilinear interpolation method, and took the average value of different models at the same station as the multi-model ensemble simulation value, then estimated the precision of the precipitation simulated by 15 IPCC AR5 GCMs and MME based on the observation of meteorological station. There were four evaluation parameters, including Corr (correlation coefficient), Bias, MRE (Mean Relative Error), and RMSE (Root Mean Square Error). Results show that the biases of the average daily precipitations simulated by IPCC AR5 GCMs present a gradually downward trend from northwest to southeast, and the RMSEs show a gradually increasing trend from northwest to southeast, while MREs in the east are less than those in the west. 82.3% of the average daily precipitations simulated by MRI-CGCM3 have relatively small biases, ranging from -0.5 to 0.5. The precisions of average daily precipitations simulated by BNU and MIROC-ESM are lower than that of others. Compared with other models, the MME simulation has the largest percentages of which the correlation coefficients are more than 0.5, MREs are less than 0.5, and RMSEs are less than 4mm, which accounted for 64.8%, 25.8% and 86.4% respectively. And the percentage of the biases ranging from -0.5 to 0.5 is relatively large, which is 56.7%, indicating that the simulation precision of MME is better than that of any other GCMs, and the MME can reduce the uncertainty of a single GCM simulation in future scenarios. Therefore, it is more scientific and reasonable to select the precipitation simulated by MME as the climate change condition, while studying subjects related to climate change.