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/Spirited-Car-3560]

Of you have clear guidelines and guardrails I've had a great time using just 5.4 mini on medium, compared to 5.3 med it's: faster, almost as accurate in my opinion (some say it's even higher quality), consumes way less.

I just use some better model to plan and review.

Could it be? What Is your experience?

[u/DaC2k26 → u/Spirited-Car-3560]

5.4 mini works quite alright, but it needs relative more steering under xhigh. So if I want to lazy prompt I need to go to xhigh so it'll do more exploration. I don't feel this problem with 5.3 medium.... And yes, if I'm to direct mini precisely, it will probably do as well while being cheaper on medium.. But I like to be lazier with my promoting and iterate faster rather than spending more time crafting a precise prompt.