Neural responses to identical sensory stimuli can be highly variable across trials, even in primary sensory areas of the cortex. This raises the question of how such areas reliably transmits sensory-evoked responses to guide appropriate behavior. Internally-generated, spontaneous activity, which is ubiquitous in the cortex, is a leading candidate for causing much of the observed response variability. Recent theoretical analyses suggested that chaotic spontaneous activity generated by a recurrent network model can be strongly suppressed by external input in a stimulus-dependent manner. A hallmark feature of this result is a non-monotonic temporal frequency – dependence, which implies that there is an optimal stimulus frequency for suppression of internally generated noise. To test the prediction that cortical areas operate similar to such models, we investigated spontaneous and visually-evoked extracellular neural activity from 57 mostly multi-units (MUs) in the primary visual cortex (V1) of 6 rats. We recorded from the rats under five conditions: while fully awake and while under 4 different levels of isoflurane anesthesia. The anesthetized conditions were included to investigate the responses of the neural circuitry as its dynamic behavior is gradually modified. Anesthesia ranged from very light to deep, and stable levels were verified by various physiological parameters such as breathing rate, reflex response, and local field potential structure. Rats were head-fixed in a sound- and light- attenuating box while passively viewing flashing stimuli on a monitor 6 inches away from the retina. Five different stimulus conditions were used for all rats in all states. Full-field flashing visual stimuli were presented at four frequencies, ranging from 1 Hz to 7.5 Hz, and spontaneous neural activity was also recorded during periods of complete darkness. Stimulus appearance was interleaved and randomized. Variability was assessed by computing Fano-factors over a range of spike-counting intervals. We found that variability in spontaneous neural firing is actively and selectively suppressed by visual stimulation both in awake and anesthetized conditions. However, the pattern of suppression was different: in the awake case, it followed the theoretical prediction showing a significant dip in the Fano-factor across the different temporal frequencies of the stimuli. This frequency-dependency vanished with increased anesthesia. In addition, we found that the lowest level of noise and the largest amount of suppression compared to the spontaneous condition across all evoked conditions occurred in the awake state. Importantly, power spectrum analysis showed that this patterns of frequency-dependent noise suppression could not be explained by differences in intrinsic neural oscillations. These results suggest the existence of an active noise-suppression mechanism in the primary visual cortex of the awake animal that is tuned to operated maximally in the awake state for stimuli modulated at behaviorally relevant frequencies.