Model reduction has become a must in realistic multi-query and/or realtime situations. Huge progress has been made in the last decade both in the analysis of such methods and their application also in industrial frameworks. However, from a mathematical point of view most results are for elliptic and parabolic linear PDEs where the solution depends smoothly on the parameter. Most model reduction techniques rely on linear approximation schemes and this fact clearly limits their scope. In this talk, we report on both success stories and recent limitations and challenges for model reduction.