Accelerated life tests (ALTs) and accelerated degradation tests (ADTs) are widely used for the reliability assessment of components or materials. In an ALT, failure times of test units are observed while in an ADT the failure-causing performance characteristic is measured. This article develops optimal ALT and ADT plans for estimating the gth quantile of the lifetime distribution at the use condition, the latter being an extension of Park and Yum. Then, the two test plans are compared in terms of the asymptotic efficiency in estimating the qth quantile and of the robustness to the mis-specifications of failure probabilities. Computational results show that the ADT provides a more precise estimator than the corresponding ALT, especially when the failure probabilities are small. Concerning the robustness of a test plan to the departures of the guessed failure probabilities from their true values, neither plan completely dominates the other.