Human faces are ecologically-salient stimuli. Face sex is particularly relevant for human interactions and face gender recognition is an extremely efficient cognitive process that is acquired early during childhood. To measure the minimum information required for correct gender classification, we have used a pixelation filter and reduced frontal pictures (28,672 pixels) of male and female faces to 7168, 1792, 448 and 112 pixels. We then addressed the following questions: Is gender recognition of male and female faces equally efficient? Are male and female subjects equally efficient at recognising face gender? We found a striking difference in categorisation of male and female faces. Categorisation of female faces reduced to 1792 pixels is at chance level whereas categorisation of male faces is above chance even for 112 pixel images. In addition, the same difference in the efficiency of categorisation of male and female faces was detected using a Gaussian noise filter. A clear sex difference in the efficiency of face gender categorisation was detected as well. Female subject were more efficient in recognising female faces. These results indicate that recognition of male and female faces are different cognitive processes and that in general females are more efficient in this cognitive task.