Background: Empirical estimates of the female-to-male ratio of infections in generalized HIV epidemics in sub-Saharan Africa range from 1.31 in Zambia to 2.21 in Ivory Coast. Inequalities in the gender ratio of infections can arise because of differences in exposure (to HIV-positive partners), susceptibility (given exposure), and survival (once infected). Differences in susceptibility have to date received most attention, but neither the relatively high gender ratio of infections nor the heterogeneity in empirical estimates is fully understood. Objective: Demonstrate the relevance of partnership network attributes and sexual mixing patterns to gender differences in the exposure to HIV-positive partners and the gender ratio of infections. Methods: Agent-based simulation model built in NetLogo. Results: The female-to-male ratio of infections predicted by our model ranges from 1.13 to 1.75. Gender-asymmetric partnership concurrency, rapid partnership turnover, elevated partnership dissolution in female-positive serodiscordant couples, and lower partnership re-entry rates among HIV-positive women can produce (substantial) differences in the gender ratio of infections. Coital dilution and serosorting have modest moderating effects. Conclusions: Partnership network attributes and sexual mixing patterns can have a considerable effect on the gender ratio of HIV infections. We need to look beyond individual behavior and gender differences in biological susceptibility if we are to fully understand, and remedy, gender inequalities in HIV infection in generalized epidemics.