Including in the training-set and in the score, in a second test, the density and static dielectric constant of liquid water, was then seen to provide considerable improvements. The obtained model showed a remarkable improvement in reproducing macroscopic properties, especially with respect to self-diffusion coefficient and enthalpy of vaporization. This also suggests that these properties -density and dielectric constant -are not strongly dependent on the g(r) of water. Overall, we found that our optimized water model (called OPTI-3T herein) exhibits a comparable level of accuracy as two models, OPC3 and TIP3P-FB, which were also obtained through automatic optimization approaches and are considered state-ofthe-art models in the realm of three-site rigid water models. Nonetheless, it is worth noting how, in our case, combining microscopic and macroscopic target properties allows achieving such a level of accuracy in an efficient way, and with a relatively reduced computational time (e.g., TIP3P-FB is trained on a large amount of thermodynamic properties at various temperatures in a computationally intensive process). At the same time, our tests show that there is little room for further improvement in these models by, e.g., adding more experimen-tal observables in the training-set, etc., which suggested that all these models are somewhat very similar and possibly nearly consistent with each other, considered the precision that it is reasonable to expect from them.