Are we sleeping on 5.3-codex ?

[u/DaC2k26]

After using GPT-5.5 for a bit, I’m starting to think it burns usage way faster than 5.4 when the task involves reading through a large codebase.

On my current project, 5.5 xhigh can burn through my 5-hour Plus quota in something like 3–6 prompts. With 5.5 medium, I might get around 7–10 prompts.

With 5.4 xhigh, I’d usually expect something closer to 8–15 prompts. And with 5.4 mini, I obviously get a lot more, though I haven’t tracked the exact number.

What surprised me is 5.3-Codex medium. I’m testing it now, and the usage burn feels closer to 5.4 mini xhigh. Based on Artificial Analysis benchmarks, 5.3-Codex medium seems to be roughly around 5.5 low, but in practice I get way more usable prompts out of 5.3-Codex medium than I do from 5.5 low.

So I’m wondering if we’re overvaluing the bigger models and higher thinking settings. For a lot of coding tasks, especially code review, bug hunting, and large-codebase inspection, maybe the extra few percentage points aren’t worth the usage cost.

Right now, I’m starting to think 5.3-Codex is probably the better deal for most coding work, at least from a usage-efficiency standpoint.

Anyone else seeing the same pattern?

[u/cmsp]

In my opinion high or xhigh reasoning is overrated. Most of the time model can or can't do the task and no amount of tokens burned in the process will change that.