When we look at a face, we cannot help but ‘read’ it: beyond simply processing its identity, we also form robust impressions of both transient psychological states (e.g. surprise) and stable character traits (e.g. trustworthiness). But perhaps the most fundamental traits we extract from faces are their social demographics — e.g. race, age, and gender. How much exposure is required to extract such properties? Curiously, despite extensive work on the temporal efficiency of extracting both higher-level social properties (such as competence and dominance) and more basic characteristics (such as identity and familiarity), this question remains largely unexplored for demography. We correlated observers’ percepts of the race/age/gender of unfamiliar faces viewed at several brief durations (and then masked) with their judgments after unlimited exposure. Performance reached asymptote by 100 ms, was above chance by only 33.33 ms, and had a similar temporal profile to detecting faces in the first place. This was true even when the property to be reported wasn’t revealed until after the face had disappeared, and when the faces were matched for several lower-level visual properties. Collectively, these results demonstrate that the extraction of demographic features from faces is highly efficient, and can truly be done at a glance.