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ABSTRACTChanging temperature and precipitation are the prominent candle bearers of climate change. Global Climate Models (GCM) simulate and predict historical, present, and future climate scenarios. This study focused on selecting the best performing GCM under High-resolution Model Intercomparison Project (HighResMIP) suitable for the Indian subcontinent for predicting daily maximum (Tasmax) and minimum (Tasmin) temperature. Entropy-TOPSIS Multicriteria Decision-Making (MCDM) approach was employed for the relative ranking of GCM models. This study compared 64 years (1951–2014) historical data of 11 high-resolution GCMs under three different nominal resolutions viz., 25 km, 50 km, and 100 km. India Meteorological Department (IMD) gridded data was used as observed data for the performance measure. The data were evaluated using three factors, i.e. Intra- and inter-annual variation of temperature, tempo-spatial extreme events study, and using selected performance indicators. The predictive ability of the GCM models spatially in different Koppen climate zones of India is also reported in this study. This study highlighted Hadgem3-Gc31 and ECMWF-IFS models for Tasmax; NICAM16-8S and MPI-ESM1-2 models for Tasmin are suitable for simulating Indian temperature. The outcome of this study will be helpful to the climate researchers and decision-makers to choose the best suitable CMIP6 GCM model at a regional level.