Another way to assess the quality of latent space concerns their application as variables in machine-learning models linking chemical or biological properties with molecular structure. Here, the VQGAE latent and feature vectors and previously described molecular descriptors were benchmarked in classification models obtained with the random forest method on 532 datasets corresponding to different biological activities extracted from ChEMBL.