The same extrapolation applied to the generation of one million structures using feature fingerprint selection results in 127 hours without augmentations and 138 hours with augmentations. The user could split up the input SMILES lists here, too, and initialise the MaxMin picking mechanism with different seeds on every instance in a computing cluster to ensure different sets of parameters are picked. Nevertheless, the creation of datasets from fingerprints is significantly slower than the generation with random parameter sampling. Depending on the desired dataset size, the user can decide whether to use depiction feature fingerprints. The feature fingerprint picking functionality is highly recommended for the generation of smaller test and benchmark sets as it ensures a diverse selection of features.