Friedrich et al. have reported benchmarking of numerous conformer generation algorithms using PLATINUM diverse dataset (for ~2859 molecules) and observed mean RMSD of 0.79 Å for RDKit using MMFF94 and 0.82 using UFF when maximum ensemble size is set to 50. These results are in perfect agreement with our predictions of 0.78 Å and 0.82 Å (in the ensemble sizes of 20), respectively, for RDKit using MMFF94 and UFF for prediction of QM optimized model structures starting from QM optimized ideal structures. In the same study, the best performance among 22 different algorithms (of ConfGenX by Schrodinger) were found to have the mean (of the closest structures) RMSD of 0.63 Å and 0.54 Å for maximum cluster sizes of 50 and 250, respectively. In another study , they have also reported that RDKit gives the performance of 0.98 Å when the cluster size is 10, which is also in perfect agreement with our finding, which is 0.93-0.95 Å for the top 10 structure evaluation. The lowest value they could get was 0.59 Å when they generated up to 500 conformers using the same method. One of the most recent studies by Seidel et al. reported that RDKit utilized with ETKDGv3 in the same force fields (MMFF94 and UFF) has a performance of mean RMSD of 0.74 Å and 0.71 Å for a maximum ensemble size of 50. Their introduced method, so-called "CONFORGE", yielded 0.67 Å for the same value. As a conclusion, to the best of our knowledge none of the studies could bring this value below 0.5 Å no matter what maximum ensemble size is used.