The Usual Closed Loop Output Error (CLOE) method for dynamic parameters identification of robots has several drawbacks: slow convergence, sensitivity to initial conditions and the calculation of significant parameters is not easy-to-run. Recently a new CLOE method called as DIDIM for Direct and Inverse Identification Model needing only actual forces/torques data was validated on rigid robots. This method avoids the drawbacks of the usual CLOE method. With the DIDIM method, the optimal parameters minimize the 2-norm of the error between the actual forces/torques and the simulated ones. It is based on a closed-loop simulation of the robot using the direct dynamic model, the same structure of control-law and the same reference trajectory for both the actual robot and the simulated one. The DIDIM method simplifies dramatically the non-linear Least Squares problem by using the Inverse Dynamic Model in order to obtain an analytical expression of the simulated forces/torques which are linear in the parameters. This explains why the DIDIM method has a fast convergence. In this paper, the DIDIM method is compared with the usual CLOE method which uses the actual positions as output. Experiments are performed on a 6 degrees of freedom robot Stäubli TX40.