In this paper, the desired speed is figured out as an important parameter for ordinary differential equation (ODE) based pedestrian simulation models. However, there lacks a thorough study on the optimal way of assigning the desired speed for ODE based pedestrian simulation models to achieve reliable performance. To gain a deep understanding of the role of the desired speed and its influence on the performances of the ODE based pedestrian simulation models, a total of nine assigning strategies of the desired speed are conducted a comparison study. Specifically, the performances of the ODE based models equipped with such desired speed assigning strategies are compared with regard to reference data from both the uni- and bi-directional pedestrian flow scenarios using a fair model comparison framework. Then, the performances are compared across several dimensions, including different assigning strategies of the desired speed, the different pedestrian simulation models, different experiments for the same motion base, and different motion base scenarios. Based on these results, four findings are summarized. Firstly, the desired speed is quantitatively verified to be an important role in the performance of ODE based pedestrian simulation models. Secondly, pedestrian density level is verified to be an effective indicator for the complexity of pedestrian crowd dynamics. Thirdly, the performance of the ODE based models is dependent on the extent to which the heterogeneity of desired speed is considered. Lastly, the performance of the social force model (SF) is suggested to be more predictable than optimal reciprocal collision avoidance model (ORCA) regarding the stability and optimality. Finally, based on the above findings, recommendations on assigning the desired speed for ODE based pedestrian simulation models are given.