A global comparison of the training set performance is not straightforward, because the submitted methods differ widely in their system coverage. However, the group of methods which achieve a test set RMSD better than 15 cm -1 (PH5, AC2, LS3, LS4) overlaps well with the methods achieving a training performance better than 15 cm -1 (PH5, LS3, LS4). AC2, the only outlier in this correspondence, is unusual because it actually shows a 25% better performance for the (blind) test set than for the (known) training set. The other three methods perform better for the training set, which is expected for learning methods and for a purely harmonic approach (PH5) which has been manually tuned to achieve a good agreement with the training data.