Abstract: Massive multiple-input multiple-output (MIMO) is a key enabling technology for future 5G-Advanced/5G mobile networks to effectively increase spectrum utilization by using large-scale antennas. It is expected that with the evolution to 6G massive MIMO will support more antennas and more complex algorithms, and thus baseband energy efficiency (EE) will be one of the crucial challenges to improve network energy efficiency. In such a system, base station (BS) computing architectures consist of dedicated (ASIC) and general-purpose (CPU) computing architectures. It is very difficult to choose the optimal computing architecture due to the lack of quantitative modeling of the computational requirements and EE of the baseband. Hence, it is necessary to study the power consumption model of different computing architectures related to combined logic units and processing cycles. Based on the proposed power consumption model, the closed forms of EE equations are derived with unit floating point operations per-second per-Watt. Numerical results show that the current EE of dedicated computing is 30 times and 200 times higher than that of the general-purpose computing (with hardware acceleration) and CPU general-purpose computing architecture respectively.