The choice of C/C++ compiler significantly impacts the performance and energy consumption of multithreaded numerical algorithms related to linear algebra. This study investigates the effects of the C/C++ compiler choice and processor frequency scaling (using dynamic voltage frequency scaling) on the performance and energy consumption of the multithreaded WZ factorization on three different computing platforms, two featuring Intel Xeon processors and one featuring AMD EPYC processor. The factorization is implemented both without optimization techniques and with strip-mining. Based on time and energy tests, we have demonstrated that, for the WZ factorization (in both implementations), each compiler reacts somewhat differently to frequency changes, thus affecting overall performance and energy consumption. The Intel compilers achieved the best performance and energy savings in a multithreaded environment compared to the other compilers on each of the tested computing platforms.