Comment by Razengan
16 hours ago
on Codex I ran into limits maybe like 2 times in 3 months, after doing several "upgrade this experimental game to my latest shared framework" passes on 5.5 Extra High
16 hours ago
on Codex I ran into limits maybe like 2 times in 3 months, after doing several "upgrade this experimental game to my latest shared framework" passes on 5.5 Extra High
On which plan?
I can go through a 5-hour limit with a $20/mo Plus subscription in a few minutes with 5.5 Extra High. This causes me to reserve the latest/best rev for the harder problems.
5.5 really does seem to be very superior to 5.4, but it's also very expensive to run: The gas gauge moves fast. It's not very clearly defined whether 5.5 will cost less to get a problem solved quickly, or if a bunch of automatic iterations of 5.4 will solve it less-expensively. Both are often frustrating to me on the $20 plan.
(Also: Are you sure you're seeing it right? 5.5 has been in the wild for less than a month, so far. https://openai.com/index/introducing-gpt-5-5/ )
The standard $20 plan, on my existing Godot code: https://github.com/InvadingOctopus/comedot
Most of those commits since the last few months are thanks to Codex reviews (but the code is not AI generated): 5.5 since it came out, and 5.4 etc before that, almost always on Extra High because it's for a framework that underlies the other stuff I do so I want make to sure everything's correct.
Sometimes I have to run multiple passes on the same task: I rarely continue any session beyond 4-5 prompts to avoid "bloat" or accumulate "stale context", so sometimes Codex finds different stuff in subsequent reviews of the same file/subsystem.
The project is modular enough where each file can be considered standalone with only 1-2 dependencies, and I already used to write a lot of comments everywhere (something some people laughed at), so maybe that helps the AI along?
Thanks. That's good data.
I'm taking this, along with my own experience, to mean that the GPTs are cheaper to use for refactors of an existing body of work than they are for creating a new one.
(And perhaps part of that is in the name? These "LLM" contraptions are very good at translation, after all. And tokens seem to relate more to concepts than to specific phrases or words.)