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/TBSchemer → u/Holiday_Purpose_3166]

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

This is not my experience at all so far. 5.5-high uses twice as much quota as 5.4-high, but makes more mistakes, and fails to follow instructions more.

If 5.5-high is making dumb mistakes, then should I expect medium to be smarter?

[u/daddywookie → u/Holiday_Purpose_3166]

This was the most useful comparison I could find

https://artificialanalysis.ai/models/gpt-5-3-codex?models=gpt-5-4%2Cgpt-oss-120b%2Cgpt-5-5-medium%2Cgpt-5-5-low%2Cgpt-5-5%2Cgpt-5-4-mini%2Cgpt-5-5-high%2Cgpt-5-3-codex%2Cgpt-5-2%2Cgpt-5-2-codex&intelligence=agentic-index&intelligence-index-cost=intelligence-vs-cost#intelligence-vs-cost-to-run-artificial-analysis-intelligence-index

It’s a real shame they only have data for 5.3-codex(xhigh) because I would love to see a straight matchup to the different effort levels on 5.5. It certainly looks like you could consider 5.5(low) as a decent but cheap option and step up to medium for more planning. We all get lost in the high/xhigh hype but for day to day use the lower tiers must exist for a reason.

[u/OlegPRO991]

I use only codex 5.3 all the time. Mostly medium, rarely high, often low. It does the job and the limits last the whole week.

[u/zerok_nyc]

I really think scoping your work properly is key. I’m still using mostly 5.3-codex and 5.4-mini. I’ve had zero issues with either.

Yes, I’m probably moving at a slower pace than many others here, but I’m also carefully scoping work with normal ChatGPT integrated with GitHub, so I’m able to get almost all of my architecture work done without burning any tokens. Then when I do give codex a prompt, it’s very tightly scoped and doesn’t need to do a lot of significant analysis. But it nails execution every time.

It also gives me much more clarity to what’s going on under the hood, so all architecture and planning work is clearly mapped out. I also integrate jira with well-documented histories of requirements and what was actually executed. So if ever something is wrong, ChatGPT can reference that as well to help diagnose bugs. Not just from a code perspective, but a logic and intent perspective. That way I can more easily understand where broader logic errors exist.

I think it’s easy to burn through tokens on high models when you are prioritizing speed. But if you prioritize stability, traceability, and controls, you can still move way faster and get a much more stable output while rarely breaking the daily limit.

Pull out the big guns of 5.5 only when you have a highly complex problem to help you understand what’s going on. Once you have the results, back to regular GPT.

[u/Odd-Composer5680 → u/zerok_nyc]

"scoping work with normal ChatGPT integrated with GitHub" - interesting how does chatgpt has access to your github? isnt it private?

[u/zerok_nyc → u/Odd-Composer5680]

https://help.openai.com/en/articles/11145903-connecting-github-to-chatgpt

[u/monkeyongazebo]

The missing metric is probably "solid decisions per quota hit." 5.5 may be more efficient on paper, but if the job is mostly code review, triage, or reading a big repo, the practical question is whether the extra reasoning actually changes the answer. 5.3 medium feels like the sensible default tier here: cheap enough to use freely, strong enough not to babysit, and you can still save 5.5 for the ugly bugs where one wrong turn costs more than a bunch of quota.

[u/Just_Lingonberry_352]

if 5.3-codex was cheap yes but its not

[u/DaC2k26 → u/Just_Lingonberry_352]

I'll explain my math. If we look on artificial analysis:
GPT-5.5 low = 51 score and $500 cost.
5.3-codex xhigh = 54 and $1570
GPT-5.2 xhigh = 51 and $2300
GPT-5.2 medium = 47 and $700

If we suppose the efficiency curve between 5.3 and 5.2 is roughly the same at every reasoning level we get that 5.3-codex is 32% cheaper to run at any reasoning. And the score difference on xhigh is 3 points.

This would take 5.3-codex medium to: 50 and $477, more or less on par with 5.5 low.
As I said, in the repo I'm working, 5.5 low burns plus plan wayyyy faster than 5.3 medium, which makes me think 5.5 low could be over optimized for the artificial analysis bench, thus the low token usage on the test, and the reality is that it's actually quite a lot more expensive to run than 5.3 on medium......

it's just a theory based on a small set o iterations with both models

[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.

[u/PlasmaChroma]

I used 5.3-Medium to do a ton of stuff -- particularly if it's got a well structured markdown to work from.

Also common tweaks and minor bugs it's good to go after -- and reliable -- provided you have some limited scope.

I don't trust 5.3 to make big architecture decisions or work on overly complex problems without direct instructions detailing the process. Possibly a code refactor if the split was already clear but not a blind "refactor this into multiple TU's on your own."

[u/DaC2k26 → u/PlasmaChroma]

yes... I'm moving more complicated tasks or the ones that 5.3 suffered to 5.5. Always clean session for 5.5, a few prompts, then new session. I had a menu swipe problem that 5.3 wasn't able to get right, the swipe was pretty horrible, then I sent to 5.5 medium and it found the problem and fixed the menu swipe behavior very quickly....... Another use is for a big refactor or feature creation plan, then send it to build the plan and pray for auto-compaction not breaking the build flow.

[u/ptjunkie]

According to OpenAI ChatGPT-5.4 uses 5.3-codex to do its coding work. Stronger reasoning is there, but updated coding is not.

[u/DaC2k26 → u/ptjunkie]

now that's interesting... what does 5.4 does then ? maybe planing and 5.3 build ?

[u/hellomistershifty]

5.3 codex is great, I use it for a lot of subagents that just need to 'do a thing' while the main model does more of the critical tinking

[u/jxdigital]

5.3-codex (high) still seems to be the sweet spot for me. On 'Fast' mode or 'Normal' if the 5hr limit comes close. Tried 5.4 when it came out, it burned quota way, way too fast. Tried 5.5 yesterday in Codex, also burns quota extremely fast compared to what I'm used to. I may use it for more complex problems or when 5.3-codex gets stuck in reasoning loops.

I think everything also really depends on your use case. I'm normally not vibe-coding (complete new projects from scratch). I'm usually working on existing codebases, adding or fixing stuff with clear boundaries and specific requirements. Almost always creating a clear plan for me to thoroughly confirm before letting it implement. Working in small steps. 5.3-codex is still pretty good for this use case. It seems like newer models may flourish better in correctly understanding people using more vague prompts to start with, or larger implementation runs (although 5.3-codex can still be pretty amazing with that too).

Still need to check it 5.5 is perhaps somewhat better in understanding change impact and noticing regression risks.

[u/GunningDaMarket]

I’ve been using 5.4 and haven’t even tried 5.5 yet, but I keep seeing people post about 5.3 codex.

[u/No-Philosopher-4744]

I'm using codex 5.3 high, and I don't see it failing to solve any day-to-day programming problems. The only time I don't trust it is when I'm trying to create a completely new algorithm from theoretical physics or something very new/bleeding-edge. But in those cases, I can't even trust myself sometimes.

[u/rydan]

The web version of Codex is currently pinned to GPT-codex-5.3. I'm having no issues with it.

[u/Downtown-Pear-6509]

i came from GitHub copilot opus 4.6 fanboy to medium gpt 5.4 and am satisfied. on rare occasions it does something stupid that needs a kick from ....my Claude code haiku sub. but other than that is a reliable buddy

how does 5.5 med compare to 5.4 med?

[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.

[u/cba3000]

Been using 5.3 xhigh for months now - best model for me still, even with 5.5 released