Previous studies considering explicit NQEs in water, have identified the hybrid revPBE0-D3, and the rung-5 RPA (EXX+RPA, RPA@PBE) with the help of machine learning potentials, as the only two approximations that agree closely with experiments so far. This therefore encourages the investigation of the performance of M06-2X(-D3) functionals with NQEs via path integral approaches. Although it is unfortunate that this involves drastic computational overheads, our work provides further evidence that both exact exchange and appropriate (non-local) correlation are essential for accurately describing water interactions. This, in turn, suggests that well-balanced XC functionals from higher rungs of the Jacob's ladder are required for simulating complex biological systems in water with predictive accuracy. In this regard, determining whether M06-2X(-D3) are indeed one of the best functionals would avoid the resort to the significantly more expensive fifth rung of the Jacob's ladder.