OBJECTIVE While outcomes with cochlear implants (CIs) are generally good, performance can be fragile. The authors examined two factors that are crucial for good CI performance. First, while there is a clear benefit for adding residual acoustic hearing to CI stimulation (typically in low frequencies), it is unclear whether this contributes directly to phonetic categorization. Thus, the authors examined perception of voicing (which uses low-frequency acoustic cues) and fricative place of articulation (s/∫, which does not) in CI users with and without residual acoustic hearing. Second, in speech categorization experiments, CI users typically show shallower identification functions. These are typically interpreted as deriving from noisy encoding of the signal. However, psycholinguistic work suggests shallow slopes may also be a useful way to adapt to uncertainty. The authors thus employed an eye-tracking paradigm to examine this in CI users. METHODS Participants were 30 CI users (with a variety of configurations) and 22 age-matched normal hearing (NH) controls. Participants heard tokens from six b/p and six s/∫ continua (eight steps) spanning real words (e.g., beach/peach, sip/ship). Participants selected the picture corresponding to the word they heard from a screen containing four items (a b-, p-, s- and ∫-initial item). Eye movements to each object were monitored as a measure of how strongly they were considering each interpretation in the moments leading up to their final percept. RESULTS Mouse-click results (analogous to phoneme identification) for voicing showed a shallower slope for CI users than NH listeners, but no differences between CI users with and without residual acoustic hearing. For fricatives, CI users also showed a shallower slope, but unexpectedly, acoustic + electric listeners showed an even shallower slope. Eye movements showed a gradient response to fine-grained acoustic differences for all listeners. Even considering only trials in which a participant clicked "b" (for example), and accounting for variation in the category boundary, participants made more looks to the competitor ("p") as the voice onset time neared the boundary. CI users showed a similar pattern, but looked to the competitor more than NH listeners, and this was not different at different continuum steps. CONCLUSIONS Residual acoustic hearing did not improve voicing categorization suggesting it may not help identify these phonetic cues. The fact that acoustic + electric users showed poorer performance on fricatives was unexpected as they usually show a benefit in standardized perception measures, and as sibilants contain little energy in the low-frequency (acoustic) range. The authors hypothesize that these listeners may overweight acoustic input, and have problems when this is not available (in fricatives). Thus, the benefit (or cost) of acoustic hearing for phonetic categorization may be complex. Eye movements suggest that in both CI and NH listeners, phoneme categorization is not a process of mapping continuous cues to discrete categories. Rather listeners preserve gradiency as a way to deal with uncertainty. CI listeners appear to adapt to their implant (in part) by amplifying competitor activation to preserve their flexibility in the face of potential misperceptions.