Timing. One final consideration in the choice of water model is the computational efficiency. The average timing for each water model type, reported in ns/day, when run on a single 48-CPU node (comprising two 24-core Intel Xeon Scalable 'Cascade Lake' processors) of the Australian National Computational Infrastructure supercomputer Gadi is listed in Table . In terms of computational efficiency, 3-point models were significantly faster to run than 4-point, 5point, or polarizable models. The additional force constants and cross-terms in the flexible and Class II models only slightly decreased their efficiency, as the most time-consuming step is the calculation of non-bonded interactions. For the 4-point models there was little difference, on average, between running them as explicit 4-point models or as 3-point models with an internal calculation for the offset partial charge on oxygen (implicit 4-point model). While all of the models in this study were run with a 1 fs timestep, for the rigid non-polarizable models it is possible to run with a 2 fs timestep, effectively doubling the computational efficiency reported here. The purpose of this study was to run all models under the same conditions, but presumably improvements in efficiency can be gained by fine-tuning the non-bond settings, utilizing GPUs, or other methods.