Herein, our primary objective was the investigation and benchmarking of HASTEN for the speed-up of screening efforts on the giga-scale. While all tools that utilize ML for faster virtual screening were ultimately developed to be able to process modern giga-scale screening libraries, to the best of our knowledge, so far no tool has been benchmarked against a billion-scale docking ground truth. Our work thus makes HASTEN the first application that underwent a benchmarking effort on the intended use-scale.