A 14 percent reduction in LLM training energy is possible by adjusting GPU clock frequencies during computation. Researchers at the University of Twente achieved these savings without sacrificing processing speed. This method targets computational waste in frontier models. It offers a concrete path to lower the massive power overhead of large-scale training.