Recognition of an item from a list is typically modeled by assuming that the representations of the items are activated in parallel and combined or summed into a single measure (sometimes termed 'familiarity' or 'degree-ofmatch') on which a recognition decision is based. The present research asks whether extra items (length), or extra repetitions (strength), increase this activation measure. Activation was assessed through examining hits and false alarms as the length or strength of word categories were varied. The use of a categorized list insured that response criteria were not changed across the length and strength manipulations. The results demon-strated that: 1) The activation does not change with an increase in the strength of presented items other than the test item; and 2) The activation is increased by an increase in the number of presented items in a category. The results provide important constraints for models of memory, because most models predict or assume either that activation grows with both length and strength, or grows with neither. In fact, the only extant model that can predict both the length and strength findings is the differentiation version of the SAM model (Shiffrin, Ratcliff, & Clark, 1990).