Alzheimer's disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in ¹⁸F-flortaucipir vs. ¹⁸F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (N_M) in 289 symptomatic patients from the Alzheimer's Disease Neuroimaging Initiative. We identified six T/N_M clusters with differing limbic and cortical patterns. The canonical group was defined as the T/N_M pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/N_M mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD.