Tested Claude AI LLM Models' Effort Levels - Low To Max: How Claude Opus 4.7 differs

Claude Code now exposes a reasoning_effort knob with five public rungs: low, medium, high, xhigh, max. The pitch is simple. Higher effort means more thinking, which means better answers on hard problems.The unasked question is what that knob actually costs, in tokens and dollars, and whether the same crank behaves the same way across different models. I spent an afternoon of subscription quota finding out. Read on if you want to understand how Claude Opus and Sonnet models’ effort levels impact your token usage, costs and performance.Four models, every effort rung, 10 canonical prompts per rung, 220 headless claude -p subprocesses. Total spend: around $18. The short version is that “higher effort = more money” is almost right but misses the more interesting story underneath. The four models have qualitatively different personalities. The knob amplifies those personalities in four different directions, and Opus 4.7 is so different from the other three that it is better thought of as a…