Interestingly, there is seen little difference between increasing the basis set size from 6-31++G(d,p) to aug-cc-pVTZ for ωB97X-D3BJ. Based on the large aug-cc-pVTZ basis set it is seen that PW91 is performing significantly worse than the ωB97X-D3BJ functionals with only 66% of the clusters being assigned to the correct minimum. This is consistent with numerous previous benchmarks of the binding energies of atmospheric molecular clusters. The semi-empirical methods PM6 and PM7 find less than 40% of the clusters to be the same minimum. GFN1-xTB and GFN2-xTB are performing slightly better, but only finds the presumed correct minimum 56% and 57% of the time, respectively. This illustrates that these methods cannot reliable identify the correct configurations and should only be used as pre-screening tools in configurational sampling and not for the final geometries. This is consistent with the previous work by Kurfman et al. for (SA) 3 cluster configurations and the work by Wu et al. on large (SA) n (AM/DMA) n clusters, with n = 1 -20. The newly parameterized AMC-xTB method is performing significantly better than the other semiempirical methods. Hence, AMC-xTB should be the best method to use for pre-optimization of atmospheric molecular clusters during cluster configurational sampling. It should be noted that AMC-xTB was parameterized on the full clusteromics I-V data sets and thereby the improved performance is not surprising.