Additionally, we confirmed that these models could give predictions exponentially faster (ca. 10 5 for 2D models and ca. 10 4 for 3D models) than collecting descriptors through the DFT workflow. As an illustrative example, for the library of 8528 carboxylic acids, DFT calculations to build the library (not including conformer generation or property extraction) required over 1,000,000 CPU hours to complete. By contrast, predicting all descriptors for entire libraries of compounds is possible on a modern personal computer in approximately a single day; the library of carboxylic acid descriptors was predicted for all 8528 compounds from SMILES strings in 2 hours using the 2D models or in 13 hours using the 3D models with a single CPU.