Equivalence and interval tests for Lehmann's alternative that extend the well-known Savage test for one-sided hypotheses are proposed. The proposed tests are shown to be unbiased with a strictly unimodal power function, provided the sample sizes in both treatment groups are equal. By means of a numerical investigation of the bias in the case of unequal sample sizes that are not too far apart, the suggested tests still turn out to provide practicable solutions. Because the computational effort to perform the suggested tests is considerable, tables containing the critical values are displayed to perform these tests easily. A numerical analysis of the power function of the interval test establishes this procedure as a powerful tool for detection of a significantly relevant difference in the small-sample case. In contrast to the case of interval testing, the fact arises that the performance of a powerful equivalence study under Lehmann's alternative requires an extensive amount of data. Because the proposed tests are based on the locally optimal scores under Lehmann's alternative, we cannot improve the suggested equivalence test essentially. Therefore, we also provide the asymptotic version of this test and display tables containing the required numerical values.