The reliability of myoelectric control is important to ensure the performance of prostheses during daily use. Recently, we proposed a multi-user neural-machine interface based on a generic musculoskeletal model to simultaneously and continuously estimate flexion/extension movements at the metacarpophalangeal (MCP) and wrist joints from surface electromyography (EMG) signals. Our previous results demonstrated that the multi-user EMG interface was reliable against upper limb posture changes. However, the reliability of the interface against different loading weights, which is an important factor that would decrease the performance of myoelectric control and be tested during the occupational therapy for myoelectric prosthesis users, is still unclear. In this study, we aimed to evaluate the reliability of the generic model over different loading weights. Four able-bodied subjects were tested in this study. Subjects performed a virtual hand/wrist posture matching task with three different loading weights (no weight, 1.25 Lbs, and 2.5 Lbs). All subjects accomplished all the assigned virtual tasks. The on-line experimental results showed that performance with different loading weights was very close. The results demonstrated that the multi-user EMG interface was reliable against the different loading weights, indicating it has potential to promote the myoelectric control into clinical applications.