A systematic procedure for modeling and optimal control of a multivariable 6-DOF (degree-of-freedom) magnetically levitated (maglev) stage has been described in this paper. In our previous publications, we have presented the design, SISO (single-input single-output) control, and testing of the maglev stage with nanometer-precision positioning capability and several-hundred-micrometer travel range. In the present work, we extended the current model to a more rigorous LQR (linear quadratic regulation) controller for the lateral control to reduce the coupling between axes. Independent lead-lag controllers have been used for the vertical control. The system equations have been derived using the Euler angle methodology and linearized about an operating point. The performance of this multivariable control has been analyzed and compared with all the six decoupled SISO controllers. The effect of adding the integrators to eliminate the steady-state error has also been discussed and the performance of the LQR controller with different weight matrices has been compared. In this paper, we also address the issues related to the stochastic modeling of the stage to analyze the coupling between different axes and transfer function identification.