No Free Tokens: The New Economics of LLM Inference
Opening — Why this matters now For the last few years, AI strategy has been narrated as a model-quality story: bigger models, better benchmarks, longer context windows, more agents, more demos, more adjectives. That story was useful. It was also incomplete. The less glamorous reality is now arriving with the invoice attached. LLM systems are not merely models. They are production services that consume GPU memory, scheduling capacity, engineering attention, and operational patience. Once a business moves from a prototype to repeated daily use, the question changes from “Can the model answer?” to “Can the system answer reliably, cheaply, and repeatedly when real users arrive at inconvenient times?” ...