The purpose of this article is to report on a comparison of several alternative numerical solution techniques for nonlinear rational-expectations models. The comparison was made by asking individual researchers to apply their different solution techniques to a simple representative-agent, optimal, stochastic growth model. Decision rules as well as simulated time series are compared. The differences among the methods turned out to be quite substantial for certain aspects of the growth model. Therefore, researchers might want to be careful not to rely blindly on the results of any chosen numerical solution method in applied work.