Unsteady separation is a phenomenon that occurs in many flows due to time-varying adverse pressure gradients and results in increased drag, decreased lift, and loss of efficiency or failure in flow devices. Therefore, it is important to predict and analyze unsteady separation. Turbulence models for the RANS equations are commonly used in the industrial design process due to their low computational cost; however, their performance in predicting steady separations is unsatisfactory, and very few studies investigate unsteady separation. Our goal is to use high-fidelity Large-Eddy Simulation results to evaluate the accuracy of the K − ω, K − ε, and Spalart Almaras turbulence models in unsteady separation. By using an identical grid, numerical scheme and consistent boundary conditions to the LES calculations we are able to isolate modelling errors. All three turbulence models capture the general features of this complex unsteady flow correctly, with only small discrepancies from the LES. Memory effects due to the periodic nature of the unsteadiness have been found to contribute to the model's success.