Codex vs OMP harness
A user on Reddit's dev_community is questioning the performance of OMP (Oh My Pi) when compared to Codex. They note that OMP's usage limits are unexpectedly difficult to reach, even with 10 subagents and reasoning set to maximum. This has led them to wonder if they are fully utilizing the model's capabilities through OMP or if some functionality is being lost compared to using Codex, despite acknowledging that lower usage doesn't always imply poorer results.
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PublishedOffset at this time: UTC+0Sep 9, 2026, 21:01 UTC
IngestedOffset at this time: UTC+0Sep 10, 2026, 00:00 UTC
- Published
- Sep 9, 2026, 21:01
- Ingested
- Sep 10, 2026, 00:00
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- Dev community
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Hi everyone,
You might find this funny, but I actually have the opposite problem to y’all. My usage allowance with Astra Max feels so generous that I’m starting to wonder if the model is running at half power or something, lol.
I’ve been using OMP (Oh My Pi), and the usage limits are surprisingly hard to hit, even with 10 subagents running and reasoning set to max for all of them. That got me thinking: “Wait, is everything actually working as intended? Am I getting the full capabilities of the model through OMP, or is something getting lost compared to using Codex?”
So now I’m considering trying Codex to see whether there’s a noticeable difference.
For those who’ve used both, how does OMP compare to Codex in terms of output quality when using the same OpenAI model? Does the official Codex harness actually get better results, or is the difference mostly in workflow and tooling?
I know lower usage doesn’t necessarily mean worse results, but it’s generous enough that it made me suspicious, lol.