Minimizing wake losses in wind or marine hydrokinetic (MHK) turbine arrays is a crucial design consideration, as it has a large impact on overall energy production. To understand and mitigate these losses, interactions between turbine wakes must be accurately predicted, with near-wakes being especially important for cross-flow (or vertical-axis) turbines, given their affinity for close-spaced operation. As numerical models become more accurate, validation efforts will need to take into account scale discrepancies between the numerical and physical models and their real-world applications. One such important scaling parameter is the Reynolds number, and it remains unclear what level of confidence can be placed in models validated away from full-scale Reynolds numbers. In other words, what is the minimum acceptable scale mismatch for experimental validation at which models can be said to be “accurate enough?” To address this uncertainty, we investigated—experimentally and numerically—the effects of Reynolds number on the performance and near-wake characteristics of a 3-bladed cross-flow turbine. Mechanical power output and overall streamwise drag were measured in a towing tank at turbine diameter Reynolds numbers ReD = U•D/n = 0.3–1.3⇥106, with performance becoming essentially Reynolds number independent at ReD = 0.8⇥106, corresponding to an average blade chord Reynolds number Rec ⌘ lU•c/n ⇡ 2.1⇥105. Detailed measurements of the near-wake one turbine diameter downstream were acquired via acoustic Doppler velocimetry for each Reynolds number case, showing very slight differences in the mean velocity, turbulence intensity, and Reynolds stress at the turbine mid-height plane, i.e., the near-wake statistics were less Reynolds number dependent than the turbine performance. The wake was also simulated using a 2-D Reynolds-averaged Navier–Stokes (RANS) model. The performance results show poor agreement with the experimental data, due to 2-D blockage and the neglecting of blade end effects, however, an increase in performance with Re is predicted. The CFD predictions for wake characteristics are reasonably accurate on the side of the turbine where blades are turning back into the direction of the flow, or where dynamic stall is occurring, but Reynolds number dependence is much more exaggerated compared with the experimental data.