D-NoCs have been the mainstream approach used to interconnect multi-core systems. 3D-NoCs have emerged to compensate for deficiencies of 2D-NoCs such as long latency and power overhead. A low-latency routing algorithm for 3D-NoC is designed to accommodate high-speed communication between cores. Both simulation and analytical models are applied to estimate the communication latency of NoCs. Generally, simulations are time-consuming and slow down the design process. Analytical models provide, within a fraction of the time, nearly accurate results which can be used by simulation to fine-tune the design. In this paper, a high performance and adaptive routing algorithm has been proposed for partially connected 3D-NoCs. Latency of the routing algorithm under different traffic patterns, different number of elevators and different elevator assignment mechanisms are reported. An analytical model, tailored to the adaptivity of the algorithm and under low traffic scenarios, has been developed and the results have been verified by simulation. According to the results, simulation and analytical results are consistent within a 10% margin. D-NoCs have been the mainstream approach used to interconnect multi-core systems. 3D-NoCs have emerged to compensate for deficiencies of 2D-NoCs such as long latency and power overhead. A low-latency routing algorithm for 3D-NoC is designed to accommodate high-speed communication between cores. Both simulation and analytical models are applied to estimate the communication latency of NoCs. Generally, simulations are time-consuming and slow down the design process. Analytical models provide, within a fraction of the time, nearly accurate results which can be used by simulation to fine-tune the design. In this paper, a high performance and adaptive routing algorithm has been proposed for partially connected 3D-NoCs. Latency of the routing algorithm under different traffic patterns, different number of elevators and different elevator assignment mechanisms are reported. An analytical model, tailored to the adaptivity of the algorithm and under low traffic scenarios, has been developed and the results have been verified by simulation. According to the results, simulation and analytical results are consistent within a 10% margin. 2