This study presents the evaluation of the historical reference simulations (1961–1990) of the NUKLEUS ensemble, the first kilometer-scale convection-permitting multi-model climate ensemble for Germany. The main goal is to examine to what extent these high-resolution simulations can provide high-quality and actionable information for climate adaptation measures in Germany. The NUKLEUS ensemble comprises nine members, generated by dynamically downscaling three global climate models from the Coupled Model Intercomparison Project phase 6 (CMIP6) with three regional climate models to a 3 km grid over a Central European domain. The evaluation focuses on the spatio-temporal and statistical representation of basic meteorological variables (temperature, wind speed, and precipitation) and derived application-relevant climate indices compared to reanalyses and observation-based data sets. The analyses are performed for Germany and six pilot regions representing diverse climatic and physiographic settings. The results reveal that the ensemble overall exhibits moderate biases with temperature and precipitation generally showing high distributional skill. Only few simulations exhibit strong warm biases, particularly during summer, while all simulations exhibit a wet bias throughout the year, except local dry biases during summer in individual members. Wind biases are more heterogeneous, particularly due to reference data constraints over complex terrain. Percentile-based climate indices are well reproduced, while fixed-threshold indices show systematic deviations. A comparison with previous regional climate model ensembles highlights the added value of the here-chosen multi-model approach. With regard to downstream applications, a quantile (delta) mapping bias correction is applied to daily precipitation totals and daily mean, minimum, and maximum temperature, which removes climatological biases and markedly improves threshold-based indices. The paper also demonstrates important limitations of this bias correction approach for event-based applications, showing that it may disrupt spatial coherence and introduce spurious spatial gradients in precipitation fields, which can affect the characterization of extreme precipitation events. Overall, the presented analyses support the use of the NUKLEUS ensemble as a high-resolution basis for regional climate and impact studies, while underlining that application-oriented post-processing and validation should be tailored to the target variable and use case.