Assignment tests are increasingly applied in ecology and conservation, although empirical comparisons of methods are still rare or are restricted to few of the available approaches. Furthermore, the performance of assignment tests in cases with low population differentiation, violations of Hardy–Weinberg equilibrium and unbalanced sampling designs has not been verified. The release of adult hatchery steelhead to spawn in Forks Creek in 1996 and 1997 provided an opportunity to compare the power of different assignment methods to distinguish their offspring from those of sympatric wild steelhead. We compared standard assignment methods requiring baseline samples (frequency, distance and Bayesian) and clustering approaches with and without baseline information, using six freely available computer programs. Assignments were verified by parentage data obtained for a subset of returning offspring. All methods provided similar assignment success, despite low differentiation between wild and hatchery fish (FST = 0.02). Bayesian approaches with baseline data performed best, whereas the results of clustering methods were variable and depended on the samples included in the analysis and the availability of baseline information. Removal of a locus with null alleles and equalizing sample sizes had little effect on assignments. Our results demonstrate the robustness of most assignment tests to low differentiation and violations of assumptions, as well as their utility for ecological studies that require correct classification of different groups.