A 14 percent energy reduction in LLM training 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 computing waste in frontier models like GPT-4. Practitioners can now lower power overhead without extending training timelines.