Abstract Nanomotors are molecular configurations on the nanoscale which resemble and perform similar tasks as simple Newtonian motors, but are driven and analyzed under principles of quantum mechanics. Nanomotors have many practical applications in novel medical technology and smart materials. One such class of nanomotors, F1F0 ATP Synthase, has particular potential within medical applications. The F0 component of the nanomotor operates on potential differences caused by the proton gradient in between a rotator and stator. Torque-energy efficiency and rotational geometries of such a system may be modeled using Ordinary Differential Equations (ODEs) and the route of protons within the motor can be described by the Langevin Equation of the overdamped diffusion of the rotor. Numerical Analysis computational methods may be used to solve the Langevin equation of proton diffusion within the motor coupled with the Fermi Distributions of the Proton Reservoirs to output the Net Torque of a F0 Motor and delineate the proton gradient over time present within the system. Nine differential equations were directly involved in the solution. Previously modeled nanomotors have been highly torque inefficient and limited to one direction of motion; augmenting stators introduces omnidirectionality and significantly higher torque. Following this, environmental parameters may be altered to ascertain the optimal conditions for the operation of the nanomotors. This is done for the two, three, and four stator cases. The result is a data model which may be used to guide engineering efforts within the field providing definite parameters which to yield distinct torque and direction.