The fundamental unit of visual working memory (WM) has been debated for decades. WM could be object-based, such that capacity is set by the number of individuated objects, or feature-based, such that capacity is determined by the total number of feature values stored. The present work examined whether object- or feature-based models would best explain how multifeature objects (i.e., color/orientation or color/shape) are encoded into visual WM. If maximum capacity is limited by the number of individuated objects, then above-chance performance should be restricted to the same number of items as in a single-feature condition. By contrast, if the capacity is determined by independent storage resources for distinct features-without respect to the objects that contain those features-then successful storage of feature values could be distributed across a larger number of objects than when only a single feature is relevant. We conducted four experiments using a whole-report task in which subjects reported both features from every item in a six-item array. The crucial finding was that above-chance recall-for both single- and multifeatured objects-was restricted to the first three or four responses, while the later responses were best modeled as guesses. Thus, whole-report with multifeature objects reveals a distribution of recalled features that indicates an object-based limit on WM capacity. (PsycInfo Database Record (c) 2023 APA, all rights reserved).