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Description: Previous research suggests that the MINERVA2 model can capture basic Deese/Roediger/McDermott (DRM) false recognition findings with either randomized representations or distributional semantic representations. In the current paper, we further extended this line of research by showing that MINERVA2 can accommodate not only the basic DRM recognition findings but also the effects of various manipulations on true and false recognition. Importantly, we incorporated two assumptions of fuzzy-trace theory into MINERVA2: the verbatim-gist distinction and hierarchies of gist. For the former, we represented gist traces with distributional semantic vectors and verbatim traces with holographic word-form vectors. With separate representations incorporated into the MINERVA2 model, we successfully simulated both semantic and phonological versions of the DRM illusion as well as several phenomenological findings (remember/know and source judgments). For the latter, we added an assumption to MINERVA2 that an item’s storage quality depends on its similarity to the preceding item. This helped accommodate the effect of global gist beyond that of local gist and solve a general issue of storage independence in multi-trace models of episodic memory. Our findings provided extensive evidence that MINERVA2 is a viable candidate for scalable modeling of the DRM illusion and strengthened the connection between computational modeling and substantive theories of false memory.