Are You Using More Tokens Than Your Prompt Needs?

AI model optimization is the practice of matching each prompt to a model with capability proportional to the task, rather than sending every request to the same default model regardless of complexity. A simple extraction or summarization task often doesn't need the same model a complex reasoning or coding task requires, yet many organizations route both through one model by default. The gap between the cheapest usable model and the most capable frontier model runs to roughly 100x in per-token price, and organizations that implement tuned model routing report bill reductions in the 40-85% range without a corresponding drop in output quality, because most everyday prompts never needed frontier-level capability in the first place. LangProtect Optimizer analyzes prompts and their token consumption to identify where the current model may exceed what a task requires and recommends a more efficient alternative.