In each case, the speedup is greater than a factor of 2. Training for single models on moderately sized datasets can be carried out reasonably even on a laptop. For large datasets, hyperparameter optimization, and model structures involving many submodels, training on cluster resources or using a GPU is recommended. Inference times in the 10,000 and 100,000 dataset sizes are also improved when moving from laptop to cluster CPU to cluster GPU, but the progressive improvement is smaller than for training. Inference using any of the system levels tested is relatively fast for these dataset sizes. Table : Inference times in hours:minutes:seconds for subsets of the QM9 dataset.