The speed at which individuals interact, in particular prey and predators, affects ecological processes at all scales, including how fast matter and energy flow through ecosystems, and how stable communities are. Environmental heterogeneity and individual variabilities are generally believed to be the main factors underlying the variation of consumption rates of prey by predators. We challenge this view by comparing predicted variability from a stochastic model to experimental data. We first analyze a stochastic model of a simple random walk with elementary ecological processes involved in prey consumption, including prey depletion, predator movements and prey handling. We provide sharp approximations of the distribution of the consumption rate and a quantitative prediction of the coefficient of variation when stochastic foraging is the only source of variability. Predictions are then compared to the coefficients of variation estimated from data from dozens of various species and experimental contexts. We show that the predictions only accounting for intrinsic stochasticity in foraging are compatible with the range of observed values, in particular in 1 or 2 dimensional space. After evaluating the robustness of our model’s predictions through stochastic computer simulations, we conclude that the main driver of the variation of the consumption rate is the foraging process itself rather than environmental or between-individual variabilities. Our approach lays the foundations for unifying foraging theory and population ecology, and as such has many empirical and theoretical implications for both fields.