This article is linked to the previous article, “Categorical color mapping using color-categorical weighting method Part I: Theory” (Ref. 1) and shows its performance for gamut mapping through psychophysical experimentation. This method maps an original color to a reproduced color by weighting constraints mapping so as to match their color names between the original color and the reproduced color. A degree of the weighting is derived from a categorical color naming experimentation. Therefore, categorical color mapping incorporates an observer's response in calculating an optimal mapping point. The algorithm of categorical color mapping has seventeen constraints. Nine of them are given as the geometrical centers of gravity of the color categories. The others are positioned on the gamut surface. In the former case there was colorimetric matching pair-wise between a source space, and a destination space and the latter was given by categorical lightness mapping with constant hue. Categorical color mapping was evaluated as the superior method among tested methods in paired-comparison experiments. GCUSP and clipping method were applied as conventional techniques to compare to categorical color mapping. From the viewpoint of categorical color mapping, performance of GCUSP can be explained. In comparison with these conventional methods, hue linearity correction in CIELAB space by categorical color mapping was confirmed.