In this study, we employed Furhat to investigate how people attribute gender to a robot and whether the attribution of gender might elicit stereotypes already at a first impression. We involved 223 participants in an online study and asked them to rate 15 of Furhat's predefined faces in terms of femininity, masculinity, communion, and agency, and identify which facial cues they based their attribution of gender upon. Our results show that Furhat's predefined faces are attributed the same gender predicted by their names, except for one face which was perceived as androgynous. They disclose that feminine robots are perceived as less agentic than masculine robots already at a first impression, and reveal that vocal cues have higher relevance than facial cues in determining the gender attributed to a robot. Besides providing a complete account of the genderedness of Furhat's predefined faces, the present study also raises awareness of the importance of gender in the design of robots and provides a starting point to design more inclusive robotic technologies.