What is the advantage of running generalized mixed effect linear regression model with bayesian with non-informative prior vs frequentist approach?

Question

I am curious as to whether the bayesian approach with non-informative prior (flat prior) is more suitable for generalized mixed effects linear model than frequentist approach and what the reasons may be?