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 high-power training runs like those used for GPT-4. It offers a direct efficiency gain for hardware operators.