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We present new findings that distinguish drift diffusion models (DDMs)from the linear ballistic accumulator (LBA) model as descriptions ofhuman behavior in a two-alternative forced-choice reward maximization(Rmax) task. Previous comparisons have not considered Rmax tasks, anddifferences identified between the models' predictions have centeredon practice effects. Unlike the parameter-free optimal performancecurves of the pure DDM, the extended DDM and LBA predict families ofcurves depending on their additional parameters, and those of the LBAshow significant differences from the DDMs, especially for poorlydiscriminable stimuli that incur high error rates. Moreover, fits tobehavior reveal that the LBA and DDM provide different interpretationsof behavior as stimulus discriminability increases. Trends forthreshold setting (caution) in the DDMs are consistent between fits,while in the corresponding LBA fits, thresholds interact withdistributions of starting points in a complex manner that depends uponparameter constraints. Our results suggest that reinterpretation ofLBA parameters may be necessary in modeling the Rmax paradigm.