The comparisons in Figure show the clear benefits of the ARGP model, whose cost and accuracy are determined by the training set sizes at the lower and higher levels. Figure (and Tables S3-S5 in SI) compares the prediction errors from, and relative computation costs of, ARGP models for oxalic acid with differing sized training sets for PBE and PBE0. Analagous plots and tables are provided for maleic hydrazide and urazole in the SI. Costs are defined relative to the expense of obtaining the lattice energies of 1% of structures using PBE0. Thus, from the average timings (see Table ), the cost of obtaining PBE evaluations for 1% of oxalic acid structures is 4.56 * 10 -3 . The computational costs of force field calculations and statistical modelling are negligible. As an The typical energy differences seen between predicted crystal structures, and between observed polymorphs, set target criteria for acceptable errors, which can inform the choice the training fractions. Over 50% of observed polymorphs of organic molecules are separated in lattice energy by less than 2 kJ mol -1 , making this an upper bound for acceptable errors. The orange contour in Figure separates models that provide errors above and below 2 kJ mol -1 (CRPS), with red and black contours showing stricter 1 and 0.5 kJ mol -1 thresholds, respectively. These contours are nearly vertical, showing that the target errors can be met by increasing the lower-level, PBE, training fraction without the expense of increasing the fraction of PBE0 calculations. Due to the large cost ratio between PBE0 and PBE, the lowest cost model meeting the target error involves the smallest PBE0 training fraction: only 10% of the lower level training set. To meet a smaller target error of 0.5 kJ/mol requires 20% PBE0 for oxalic acid and is not achieved at all for maleic hydrazide and urazole. Although small numbers of PBE0 calculations are required, these are necessary for achieving the required accuracy; pure PBE-based models yield significantly larger errors (see Table ).