Current theories and supporting simulations of similaritybased retrieval disagree in their process model of semantic similarity decisions. We compare two current computational simulations of similarity-based retrieval, MAC/FA C and ARCS, with particular attention to the semantic similarity models used in each. Four experiments are presented comparing the performance of these simulations on a common set of representations. The results suggest that MAC/FAC, with its identicality-based ccmstraint on semantic similarity, provides a better account of retrieval than ARCS, with its similarity-table based model.