The computational and time cost of calculating G4MP2 energies can also become quite significant and the utility of doing so can become considerable and less costeffective for larger systems. Our study uses data from QM9, which conveniently contains a comprehensive set of enumerated isomers with available calculated G4MP2 energies. After recalculating E min using the B3LYP-calculated energies from the QM9 dataset, we do not find a significant drop in synthesizability prediction accuracy. While the overall accuracies do not drop much compared to G4MP2-calculated E min , it is possible that individual predictions have changed; thus, follow up work is required to evaluate the finer differences between B3LYP-calculated and G4MP2-calculated E min values. If energies from B3LYP energies lack problematic biases, it may be possible to use even faster methods (e.g., forcefields, tight-binding); these methods are briefly investigated in the following section. An alternative approach could be to use faster methods to approximate E min and recalculate E min with more accurate energies for a smaller set of molecules of interest. ML models can also predict accurate energies for molecules and have even been used for molecules with sizes beyond those found in the training set. These ML models provide additional avenues for quickly determining molecular energies. W