Summary. We compare two flexible estimators of technical efficiency in a cross-sectional setting: the non-parametric kernel stochastic frontier analysis estimator of Fan, Li and Weersink with the non-parametric bias-corrected data envelopment analysis estimator of Kneip, Simar and Wilson. We assess the finite sample performance of each estimator via Monte Carlo simulations and empirical examples. We find that the reliability of efficiency scores critically hinges on the ratio of the variation in efficiency to the variation in noise. These results should be a valuable resource to both academic researchers and practitioners.