The current variance estimators for Jukes and Cantor's one-parameter model and Kimura's two-parameter model tend to underestimate the true variances when the true proportion of differences between the two sequences under study is not small. In this paper, we developed improved variance estimators, using a higher-order Taylor expansion and empirical methods. The new estimators outperform the conventional estimators and provide accurate estimates of the true variances.