codex 里的 agent 之前全跑 Astra/high，用量烧得很快。GPT-6 的 Sol 和 Luna 出来以后， 我拿七种模型和 effort 组合在真实 repo 上跑了三轮：自己的 monorepo、工作上三个 repo 的跨项目题、 还有盲测复现历史 PR。代码能写对的比想象中多，但在 agent 自己的集成 runner 里把真实调用路径也跑通的少很多， 好几份自测全绿的提交其实没修好。文末是最后定下来的分工表和几个派活规则。

opus 5.5 出来当天，我拿自己 11 个 repo 里的 22 个真实提交做了一轮 medium 对 high 的配对测试： 两档完成度一样，high 慢三分之一、多花三成多 token，但盲评里多抓出几个测试查不出来的真 bug。 再对一下 Artificial Analysis 的 Intelligence Index 数据，最后把默认档定成了 high。 文末按不同用法给了推荐。

Every Codex agent I ran was on Astra/high, and usage burned fast. When GPT-6 Sol and Luna landed, I had seven model and effort combinations run through three rounds on real repos: my own monorepo, cross-project tasks in three work repos, and blind replays of historical PRs. More routes wrote correct code than I expected; far fewer also got the real caller path passing in their own integration runner, and several submissions with green self-tests weren't actually fixed. The final routing table and delegation rules are at the end.

On launch day I replayed 22 real commits from 11 of my own repos, running Opus 5.5 at medium and high effort side by side. Both finished every task; high took about a third longer and 35% more tokens, but blind judges credited it with catching several bugs the tests couldn't see. Cross-checked against the Artificial Analysis Intelligence Index, I made high my default. Recommendations by usage profile at the end.