The SARS-CoV-2 Omicron variant evades most neutralizing vaccine-induced antibodies and is associated with lower antibody titers upon breakthrough infections than previous variants. However, the mechanism remains unclear. Here, we find using a geometric deep-learning model that Omicron’s extensively mutated receptor binding site (RBS) features reduced antigenicity compared with previous variants. Mice immunization experiments with different recombinant receptor binding domain (RBD) variants confirm that the serological response to Omicron is drastically attenuated and less potent. Analyses of serum cross-reactivity and competitive ELISA reveal a reduction in antibody response across both variable and conserved RBD epitopes. Computational modeling confirms that the RBS has a potential for further antigenicity reduction while retaining efficient receptor binding. Finally, we find a similar trend of antigenicity reduction over decades for hCoV229E, a common cold coronavirus. Thus, our study explains the reduced antibody titers associated with Omicron infection and reveals a possible trajectory of future viral evolution. Display omitted •Omicron breakthrough infection elicits lower antibody response than prior variants•Deep-learning model predicts reduced antigenicity of the Omicron RBD•Mice immunization experiments show reduced B cell immunogenicity of Omicron spike RBD•Additional mutations could reduce antigenicity while maintaining receptor binding SARS-CoV-2 Omicron variant evades most neutralizing vaccine-induced antibodies and is associated with lower antibody titers upon breakthrough infections than previous variants. Tubiana et al. investigate the underlying mechanism using geometric deep learning, mice immunization experiments, and biochemical assays. Mutations reduce antigenicity of the receptor binding site, leading to lower antibody response.