In this paper we employ the Clusteromics I-V datasets to massively assess the geometries of atmospheric molecular clusters. We initially optimized the geometry of 45 dimer clusters at the DF-CCSD(T)-F12b/cc-pVDZ-F12 level of theory to probe how well cheaper wave function theory (MP2) can reproduce the cluster geometries. Based on the results we utilize DF-MP2/aug-cc-pVQZ to optimize the geometry of a subset of the Clusteromics I-V datasets. We optimized the geometry of the five lowest configurations of each cluster composition, yielding a total of 1283 cluster structures. Finally, we compare several faster and more approximate methods to this DF-MP2/aug-cc-pVQZ geometry dataset and apply detailed statistics to compare the geometries.