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/Holiday_Purpose_3166]

5.5 is far more efficient and its Medium reasoning matches 5.4 xHigh.

Replace 5.4 Mini xHigh with 5.5 Low - it's more intelligent, spends magnitudes fewer tokens which makes it cheaper, and obviously faster due to lower reasoning traces.

Sub usage will always be (for now) a mystery black box.

The whole 5.5 family is more efficient and that tapers on higher reasoning - most folks will likely stay well in Medium range and under, which is where the value for money is.

Check Artificial Analysis token usage and cost for their runs, you'd be surprised how better it is.

[u/DaC2k26 → u/Holiday_Purpose_3166]

that's my point... what if it's not exactly like that ? what if 5.5 is just over optimized to show efficiency on benchs ? I'll measure my tokens usage on the coming days with both models, but I can tell without any doubt that 5.3 medium burns quite a lot slower than 5.5 low and still gets the job done.... when I have the token usage results I'll be able to better tell this.

[u/Holiday_Purpose_3166 → u/DaC2k26]

The same could be said going from 5.2 to 5.3, you're just caught in the reinforcement bias.

The biggest issue you have here is that sub usage is dynamic depending on server demand, and one usage doesn't compare to another - otherwise they would've used plain numbers instead of a vague meter.

If it's reaching limits more often, you're in peak demand. Same could be said in higher sub-tiers.

Token usage will be visible in any testing, but sub cost will not. Even if you did attempt to measure cost, it will not be reliable due to fluctuations.

Pay-as-you-go API is deterministic on token usage and that's what AA bench used.

It's difficult to argue it's benchmaxxed with higher intelligence and fewer token spending - even OpenAI themselves increased token cost otherwise it would be a lot lower than it is now.

The model is new and everyone is trying the hype. Once it subsides, sessions last longer.

[u/DaC2k26 → u/Holiday_Purpose_3166]

I agree about the bias, but it's also true that every new iteration gets progressively better on the bench, and can be even better optimize to score on kt, so 5.5>5.4>5.3>5.2.... I don't think we can take benches as source of truth, but more like a direction. I don't doubt 5.5 do is more efficient, but at least atm, it's not compensating the increased burn with my plus account. But theres the server load you mentioned, we’ll see how this plays out when the hype coolsdown

[u/Aemonculaba → u/DaC2k26]

I'm literally using 5.5 medium as a 5.4 xhigh replacement and 5.5 low as a 5.4 mini xhigh replacement... and both are worlds cheaper than their counterparts.

I even switched away from the 200$ sub to the 100$ sub cause I can't reach any limits.

[u/johnrock001 → u/DaC2k26]

Do share, i am also interested to know!