TLDR: The experiment worked but using Luna actually ended up costing more tokens due to orchestration and then fixing its bugs. I ran a 10 hour experiment to test if I could substantially reduce my Claude Code token usage by using the cheaper Luna (via Codex CLI) as the builder model… the results were surprising to say the least. For context - on July 30th OpenAI dropped the price of their Luna model by 80% and released compelling benchmark results indicating GPT-5.6 Luna with max effort exceeds Claude Sonnet 5 at high effort at ~1/8 of the cost. So… my hypothesis was Luna could be used as an effective “builder” model within a multi agent workflow to significantly save on token usage. I tested this by pinning multiple harness configurations against each other in a task to migrate the front end of a web app from vanilla JavaScript to React. The results were counterintuitive to say the least - using Luna was consistently more expensive! Why? The orchestration tax of having multiple agents work together (including larger reviewer agents fixing issues with Luna’s code) outweighed simply asking Claude Opus5 to complete the build on its own. This is just one experiment on one task, with it’s limitations, but alot of learnings. Full writeup here (free): https://fresh-worktree.ghost.io/is-luna-on-max-effort-the-solution-to-coding-cost/ submitted by /u/turtleninja99
Originally posted by u/turtleninja99 on r/ClaudeCode