The poster believes that GPT-5.6 Luna, at medium thinking, is close to GPT-5.4 mini in speed and capability, and can approach GPT-5.5 medium at high effort. In the comments, one user set Luna Max as the default model, while others considered Luna's quality and price advantages significant. Opinions on speed, context, and task-completion reliability were not consistent.
Luna can be the first choice for tasks such as brainstorming and routine implementation; switch to Sol high for plan reviews and final verification.
One commenter shared a simple Codex routing configuration: subagents use gpt-5.6-luna-xhigh, ordinary tasks use gpt-5.6-luna-max, and the review and final models use gpt-5.6-sol-high.
The community explicitly cautioned that benchmarks should be treated only as a guide and that real projects should be tested independently.
Negative feedback included the possibility that Luna Max is slow, that lower-tier models may falsely report Git operations as complete, and that model preferences vary substantially across tasks.
These are early community experiences, not a controlled benchmark. They support the direction that “Luna is suitable for high-frequency, cost-sensitive coding-agent tasks,” but they do not prove that Luna outperforms Sol or Terra in every workflow.
The following is the original post text and the comments directly related to model selection, extracted through the Tabbit international edition; Reddit navigation, ads, and the community footer have been omitted.
GPT-5.6 Luna is really underrated
It's basically as fast as 5.4 mini if you use medium thinking and reasons really well like above 5.4 level, even around 5.5 medium if you use high effort I'd say.
But terra is kind of useless sadly, you're better off using sol on a lower setting and you'd get a better output for a lower price, it's like the worst of both worlds between sol and luna. This is really promising though since apparently luna was trained by sol which means sol did the model better than the engineers could do terra. Excited to see how GPT-6 turns out
It's only underrated in the sense that some want to only use the best model for anything and everything. Whatever floats their boat, but yes, Luna (max) is my new default.
I first tried to use sol high as default, but now I changed to luna max as default. One thing I overlooked before is, on paper sol high is cost effective only because it can finish job with fewer token, but in stage like brain storming, tokens are supposed to be used extensively. And I found using luna max as the default is better for this reason.
I use a fork of superpower (a much lighter fork), and I keep the plan review in sol-high, planning / brainstorming in luna max.
The best thing about my fork is, it combine all the review steps, and it parallelize all the implementation to multiple agents, so if your PR involve a lot of file changes, it just do it all at the same time.
One of the problem of this fork is, right now in the latest sol model, codex internal cap num of active agent to 4, I have a forked codex version to bypass it.
use_subagent = true subagent_model = "gpt-5.6-luna-xhigh" review_model = "gpt-5.6-sol-high" best_model = "gpt-5.6-sol-high" normal_model = "gpt-5.6-luna-max" fast_model = "gpt-5.3-codex-spark-xhigh"
I'm not going to lie, luna max quality has really impressed me, but the load times are so extreme compared to using sol.
The crazy part is Luna has solved things that not even 5.5 xhigh could do, despite it being a “weaker” model. I just don't get it, can't really trust any benchmark and just have to try everything lol
You do have to try everything and benchmarks are basically a guideline.
I use Luna medium as my default, only changing if it can't solve my problem. I don't think I've had to change it to a bigger model (or even thinking level) yet. But I'm also just using normal, well-known tech stacks so nothing crazy.
As fast as 5.4 mini, with intelligence on-par with 5.5 medium and about as cheap as 5.5 medium.
That's weird I've always had the opposite experience. Terra was usually taking as much usage as sol without really being better than it so I just decided to use sol and it solved the problem better, and luna handled the same problem pretty well as well as I switched between them. I guess it just depends.
In my testing. Luna Max has been the kindest to me for UI design out of the new line up.
GPT-5.6 Luna
