Rabin has proposed a probabilistic algorithm for finding the closest pair of a set of points in Euclidean space. His algorithm is asymtomatically linear whereas the best of the known deterministic algorithms take order $n \log n$ time. We show that at least part of the speed up is due to the model rather than the probabilistic nature of the algorithm.