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The ability of the state-of-the-art Global and Regional Climate Models (GCMs and RCMs) to reproduce the mean and spatial characteristics of extreme precipitation indices over Africa is evaluated. In particular, the extent to which CORDEX (COordinated Regional Downscaling Experiment) adds useful details on the performance of CMIP5 (Coupled Model Intercomparison Project Phase 5) multimodel ensemble is investigated. Comparison of the present day simulation was performed with two precipitation observation datasets, the high-resolution TRMM (Tropical Rainfall Measuring Mission) and coarse resolution GPCP (Global Precipitation Climatology Project), to evaluate models strengths and weaknesses. Eight indices generated from absolute (1mm) and percentile (95th) based thresholds as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) are computed for seventeen CMIP5 GCMs and six CORDEX RCMs (for twelve downscaling experiments) for each year during the historical period (1975-2004). Our results suggest a good consistency between GPCP and TRMM in producing annual mean and frequency of extreme precipitation events over Africa despite few inconsistencies. However, their associated intensities largely differed from one another with GPCP data displaying drier bias. Overall, multimodel ensembles simulations overestimate the frequency of extreme precipitation events and underestimate their intensities. The results further show that CMIP5 exhibits wet bias of precipitation events and drier bias of precipitation intensity than CORDEX, and that CORDEX produces precipitation magnitude within the range of the observations and more in line with the higher-resolution TRMM data. This illustrates the added value achieved with the higher-resolution CORDEX multimodel ensemble for the simulation of such events, and points toward the use of these RCMs to study extreme precipitation for a better assessment of climate change over Africa.