Defluffer: Cutting Prompt Token Waste by Nearly Half

Defluffer demonstrates a practical approach to AI efficiency: removing unnecessary text from prompts can reduce token consumption by up to 45% without additional computational cost. This matters because every token saved in a prompt multiplies across entire conversations, as LLM context is reloaded at each step. At global scale—if adopted widely by developers—this principle could reduce AI-related energy consumption by billions of watts annually, creating measurable environmental and financial benefits.