Stepped-wedge cluster randomized trials (CRTs) are characterized by the sequential transition of clusters from control to intervention. Most studies that explored the statistical properties of such trials relied on asymptotic theory and/or assumed equal cluster sizes. In practice, sample size is often limited and cluster sizes are subject to variation. The impact of unequal cluster sizes has been studied in the context of parallel-arm CRTs, but it is unclear whether these results are generalizable to stepped-wedge trials, as they involve fundamentally distinct designs. We conducted simulations for continuous and binary outcomes to evaluate the performance of various analysis approaches for stepped-wedge trials with small numbers of clusters and unequal cluster sizes. Type I error was generally inflated with the Wald test, the F-test with Satterthwaite’s approximation, and bootstrap procedures, but overly conservative with Kenward-Roger's approximation.