However, another way to compare the models is to consider recall per runtime: When using a single Chemprop per GPU, the 0.1% docking fraction model can run for five iterations in slightly more than 7 days. This, in our setting, was faster than ten iterations of the 0.01% docking fraction model (runtime approx. 8 days). Importantly, for SurA, the larger docking fraction recalls 92%, 84%, and 78% of the top-scoring 100, 1000, and 10 000 virtual hits in five iterations. Thus, the large model is faster and its recall is 12%-16% higher than with ten iterations of the smaller docking fraction model (see Figure and Table ).