This study aimed to investigate performance of ARM-based computer clusters using two-phase immersion cooling approach, and demonstrate its potential benefits over the air-based natural and forced convection approaches. ARM-based clusters were created using Raspberry Pi model 2 and 3, a commodity-level, single-board computer. Immersion cooling mode utilized two types of dielectric liquids, HFE-7000 and HFE-7100. Experiments involved running benchmarking tests Sysbench high performance linpack (HPL), and the combination of both in order to quantify the key parameters of device junction temperature, frequency, execution time, computing performance, and energy consumption. Results indicated that the device core temperature has direct effects on the computing performance and energy consumption. In the reference, natural convection cooling mode, as the temperature raised, the cluster started to decease its operating frequency to save the internal cores from damage. This resulted in decline of computing performance and increase of execution time, further leading to increase of energy consumption. In more extreme cases, performance of the cluster dropped by 4X, while the energy consumption increased by 220%. This study therefore demonstrated that two-phase immersion cooling method with its near-isothermal, high heat transfer capability would enable fast, energy efficient, and reliable operation, particularly benefiting high performance computing applications where conventional air-based cooling methods would fail.