The present work focuses on the comparison between the (EGM2008) that was recently released by the NGA (National Geospatial-Intelligence Agency, U.S)/EGM-development teamand supplied to a new Joint Working Group established between IGFS and the IAG commission 2 for validation, with land gravity anomalies supplied by the B.G.I. and a pre-processed 5’x 5’ grid of the free air anomalies covering the area bounded by the limits 16° ≤ φ ≥ 40° and -10° ≤ λ ≥ 14° provided us by GETECH, some of the precise GPS data collected from the international TYRGEONET (TYRhenian GEOdynamical NETwork), ALGEONET (ALGerian GEOdynamical NETwork) projects with baseline length ranging fromabout 1 to 1000 km and Algerian gravimeric geoid model based on OSU91A geopotential model in order to assess its quality in Algeria region. Additional comparisons of the terrestrial point data (such as the gravity data and the GPS-based geoid heights used in this study) with the corresponding values obtained from other geopotential models were made. Six global geopotential models were used in this comparison: The new GRACE satellite-only and combined models EIGEN-GRACE02S and GGM02C, the combined CHAMP and GRACE model EIGEN-CG01C, combined CHAMP and LAGEOS model EIGEN-GL04C, OSU91A and EGM96. The comparisons were made at all gravity and GPS levelled data by computation of the residual data (i. e. observed data minus model). The geopotential model that provides the closest statistical fit to these data can be assumed to be the most suitable model to adopt for the determination of the new Algerian gravimetric geoid. The study shows that all tested models are an improvement over OSU91A geopotential model used in all previous Algeriangeoid computations and that new released combined model (EGM2008) is relatively superior to other models in the Algerian region. According to our numerical results, the EGM2008 model fits best the observed values used in this investigation. Its standard deviation fit with GPS/levelling data is 21.2cm and 19.6cm before and after the bias and tilts fitting using four parametric transformation model.