The dense ensemble is the highest performing CNN model for both redocking and crossdocking, but it is also the most computationally demanding (Figure ) so distilling the dense ensemble's knowledge would be the most useful for accurate high-throughput docking. Figure shows the dense ensemble distilled into a Dense architecture has about the same crossdocking performance as the non-KD trained dense single models while demonstrating improved performance on redocking over the non-KD trained dense single models.