When using covariates, you are not estimating the groups separately. Rather you are simply informing the upper (population) model that there are two subgroups (male and female). All the respondents are still estimating together, and they are still using HB's power to strengthen each other. If you estimate the subgroups separately, you do not get the influence from the other subgroups.
"Which way is better" is a subjective question. If you believe that male preferences are not entirely disconnected from female preferences, you may decide to run the analysis with covariates. If you believe they are separate entities, you may want to run them separately.
We have discovered that when using covariates, you should be cautious about what covariates are chosen. Gender may not be a significant predictor of choice, and so using it as a covariate will not be helpful and possibly harmful. You should choose covariates that have significance in terms of choice prediciton.