Figure shows the MAE(∆E) for different subset sizes and surrogates and Figure gives the average bb-RMSD between the closest reference and surrogate LM structures from which the ∆E were calculated. As could be expected, the B3LYP/6-31G(d,p) LM are best reproduced using the same method (B3LYP) but with the smaller (non-polarized) 6-31G basis set, with structures showing on average 0.2-0.4 Å bb-RMSD and ∼4 kcal/mol energy differences. While all other surrogates show similar differences in geometries that saturate at best around 0.3 Å bb-RMSD for DFTB3, the relative energies between methods are more variable. The PM6 semiempirical method appears to perform best with average energy deviations of 5 kcal/mol, followed by the GAFF(RESP) and AMOEBA force fields, as well as DFTB3, which all have energy differences of about 6 kcal/mol while these exceed 7 kcal/mol for the remaining surrogates. The worst approach is the GAFF force field with AM1-BCC charges, which were only used here to explicitly test the influence of the effective charge set but are indeed not recommended for common practice. Regarding the quality of the structural prediction, Figure gives an illustration of some bb-RMSD between reference and surrogate LM. In general, structures with a bb-RMSD of less than 0.5 Å are very similar and thus more likely to relax to their B3LYP/6-31G(d,p) counterpart upon re-optimization. As for the energetic performance, the closest reproduction of the reference geometries is found for the smaller basis set B3LYP variant but also all remaining surrogate methods perform relatively well in terms of geometric predictions, yielding LM geometries with a bb-RMSD around 0.5 Å from a subset size of 40, which is the population size of the GA chosen for GPGG. Therefore, we conclude that over a set of representative geometries encountered in a GA optimization, all non-DFT surrogates show a similar performance in terms of reproducing B3LYP/6-31G(d,p) structures. However, correct relative energies are more difficult to approximate and differ between methods, with PM6 slightly outperforming GAFF(RESP), AMOEBA and DFTB3 in terms of overall MAE. Apart from the fact that the surrogate method should be able to generate a diverse set of structures, we are particularly interested in the performance for the low-energy regime, whose members will drive GAs to the most optimal regions of the PES. The pool of low-energy LM at the surrogate level also represents the candidates that will be selected for a re-optimization with a higher level reference. For all cis, respectively trans isomers, Table presents the MAE of the relative energies of LM at less than 10 kcal/mol of the respective GM in the set. Again, the energies are compared between corresponding pairs of surrogate-reference geometries that exhibit the smallest bb-RMSD.