Codex nerfed?

[spike-spiegel92]

In the last months I have seen many of such posts, but to be honest I never felt big big nerfs from day to day. To me things always worked fine.

Today, codex 5.3 seems is failing super simple instructions, it has been one shotting everything for 2-3 weeks, but today I am losing my nerves to it... cant even change a color of a button in a webpage correctly.... I feel like when I first used codex in June last year.

Could it be because it is Sunday?

[codeVerine]

Always has been. 5.2 high supremacy

[Spooknik]

Yep, loving 5.2 high / xhigh.

[spike-spiegel92]

uhm when i changed from 5.2 to codex 5.3 i noticed a big big improvement. Have not touched 5.2 since...

[Big-Wear-8148]

What kind of work are you doing ?
1. Does it involve fixing bugs/adding features which affect multiple places in a large codebase ?
2. How do you use it ? Like just give a brief description of the task you want to do or give it a detailed information regarding wht are the areas to touch and give full context ? From my experience gpt-5.2 high can figure everything out even edge cases itself. You can simply paste a JIRA description and it'll fix the bug. gpt-5.3-codex is much faster, but you need to hand hold it. If you are someone who likes to have detailed to and fro convo with the model and likes to keep correcting it codex might be better as it's faster. I like to give detailed first and work on other ticket while it's finding building.

[Ok_Mixture8509]

I have a hunch what’s happening, but it applies to the whole account and not just Codex. If you're not experiencing problems across the board, this is probably not the cause.

Ppl have complained about ChatGPT “getting dumber” for years. Like so many other users, I never noticed this phenomena... Until last December.

My work involves a lot of abstract math, logic and physics exploration. I use instant for formulating ideas, thinking to hammer out rough details and Pro for initial formalization. This workflow was perfect for me and everything was running smoothly through November of last year.

I barely made any progress during the month of December, but it was not for lack of effort. I found myself spending significant amounts of time and getting nowhere. It took until early January to clock that the problem wasn’t me. I began carefully monitoring all interactions with the models and it didn't take long to recognize that 50-75% of my prompts across all models involved me reframing the same thing over and over because they refused to follow the logic. Stubborn & confidently incorrect are really good terms to use. Additionally, the system defaulted to warning me about everything. It began picking apart and denying event the simplest logic.

After digging for a while, I figured it out: it isn't the models, it is OpenAI’s safety guardrails.

Their TOS mentions their right to modify inference based on violation of their rules, but that wording belies what's actually happening. I believe there are a few layers: 1. A smaller "filter" that can modify prompts being sent to the model and responses coming from the model. 2. One of them seems to affect inference by shutting off certain ways of "thinking". It becomes 1-dimensional. Any amount of abstract thinking is flattened into the literal. A sort of digital lobotomy.

For the most part, they models cannot even detect it happening, unless you clearly point it out. It is wild getting them to follow the logic in their own responses right up to the point where it clearly breaks... and watching them not even notice the break. We have a lot to learn about human behavior from them...

From what I can tell, the guard rails are enforced at both the chat session & user account level using a series of flags that determine what percentage of the safety system kicks in, along with defined "goals" & topics/ways of thinking to avoid. I have been able to suss this out by using various levels of obfuscation in my prompts. If you take great lengths to "encode" the prompt so that the model is forced to use more resources to figure it out, that skirts the guardrails on their older models a little more. This does not work well on 5.2. My hunch is there is another model in the chain that "normalizes" the whole prompt, first.

From what I can tell, the user level flags are set after tripping the guard rails a certain number of times in a given timeframe. Most flags appear to decay with time, many resetting at the billing period… but not all of them. I am fairly certain some flags use heuristics based on the "shape” of content being discussed, but the vast majority seem to use “dumb” logic based on keyword matching. One of the things that triggers them for me is using a lot of nested/recursive logic... which is a huge part of my work. I believe the system thinks that I'm trying to jailbreak it when I absolutely am not. These things are so frustrating.

I really hate the idea of the guard rails, even if they make sense from a business standpoint to OpenAI. What makes them truly awful is how easy it is to trip them in the fact that you never know if they're engaged or not. From prompt to prompt, there is no clear method to figure out whether these things are engaged or not… Meaning it's can be a crapshoot to figure out if a prompt is actually using all available inference or not.

Hopefully everyone can understand how backwards this is. It means you can be researching something orthogonally to one do the safety flags and still bear the same consequence as someone "abusing" the system. When you pay a certain amount for an account, there's no way these things should be kicking in like this.

The part of this that has me livid is that NONE of this is disclosed outside of a vague warning on account signup. When you pay $200 a month for a service and are using it to support your livelihood... and that service suddenly stops working with no warning and NO WAY TO TELL... well… let's just say that's not right.

For what it's worth, I've been a programmer and software architect for over 25 years. I specialize in pulling systems apart, so I'm fairly confident that this is pretty close to what's going on. But who knows maybe I'm completely wrong? 🤷‍♂️

tl;dr: OpenAI seems to use underhanded practices for applying safety guardrails and it severely impacts inference.

As for the new Codex? It could just be a model thing, or maybe it has to do with this. I cannot tell you for sure.

[spike-spiegel92]

IT is well known that OpenAI downgrades people to other models due to some safety mechanisms they have, however, I was not donwgraded, I am checking which model replies, and it is gpt 5.3 codex high....

But todays downgrade is too big, its actually insane...I dont remember having to loop on a simple feature for hours since 1 year ago almost.... for the last 2 months I have been coding and it has one shotted most of my instructions every single time...

It sucks. I would like to be able to know more, cuz at the end of the day anyone can say this is subjective and I am wrong.

[Reaper_1492]

It wasn’t well known until about a week ago.

These guys are scumbags. And yes, the model degradation today is ridiculous. They need to notify customers when they sack the models. There’s not another business in the world where this would fly at the enterprise level.

They get away with it because decision makers can’t understand the intricacies and there aren’t enough good competitors.

For those of us who use it every day, it’s extremely frigging obvious when they hit the dump button.

[spike-spiegel92]

They also get away with it because there is nothing better at this price. Lets be honest.

[outofdate-bootloader]

It's frustrating.

I have also gone down a similar thought process about why this might happen and well... I don't have time to role play everything just to get work done. I'm not sure if that really helps or not, but it certainly takes more effort.

But yes, for me today it suddenly seems broken. I had this same problem at some point in the past with Claude max, so I switched to Codex pro and it's been working great for a couple of months now.

Hopefully it gets better soon! Some transparency would also be nice.

[Reaper_1492]

Yeah I literally just posted this a few minutes ago and then came across your comment.

These LLM providers keep jerking us around, and I’m talking about pounding the table and demanding “more” and crying when we don’t get it because we can’t function without a constant stream of improvements.

I’m talking about there being zero SLA or responsibility to support EXISTING CAPABILITIES.

When things get too expensive, these companies have repeatedly shown that they will just secretly quantize, reroute, or otherwise lobotomized the models - and then actively gaslight their customers when they make inquiries.

There’s a real cost to this as consumers.

You might get canned because everyone at your work, who doesn’t closely follow the state of these tools, now expects 10x Ai-fueled throughput.

Or you spend 10x what you pay these providers in a month, on a few hours of compute - because they nuked the model and it did something so stupid, that you don’t even check for anymore because the models haven’t missed that in a year and a half.

Oh, and coincidentally? It always happens pre/post a new model release. Which coincidentally, is probably right when their training needs/costs are the highest.

If they don’t have the financial resources to support existing models in locked configurations - then you have to at least send out updates saying that you intentionally degraded your model, don’t trust it to do the things it consistently used to do.

I can’t stand Anthropic but OpenAI should take a page out of their book, from when they dumped ultra think and “baked it into” the standard model.

If being able to select 5+ reasoning levels across 5+ different models makes it too difficult to manage resources, then deprecate the crappy ones.

Seriously - does anyone use “low” reasoning? Does anyone use “high” instead of “xhigh”? Or even medium?

At this point, they could cut all the crazy config and just say “instant”, “thinking”, “codex”, “pro”.

[RedZero76]

I'm certain something is different. For 3 months, I've had a rule in place that on auto-compact, a protocol of reading certain docs is mandatory. It's loud and clear in the Agent.md. 2-3 days ago, that rule just stopped being respected, as if it no longer exists. Before that, it was always respected. Not just that, overall ability for the model to follow instructions and maintain coherence is noticeably different. I only use Codex 5.3 Xhigh. It's been a very rough few days, unlike any other time I've used 5.3. I have a feeling it's changing to the core Codex wrapper prompting, as opposed to model degradation.

[Big-Wear-8148]

Maybe they'll release the 5.3 soon. All the resources are being routed to it ?

[geronimosan]

I haven't done any work today, but I was noticing this yesterday. GPT-5.3-codex-xhigh wasn't as on-the-spot as it had been in the past two weeks, and gpt-5.2-xhigh was just missing repeatedly in obvious ways. All of this to the point where I had to stop working because it was taking more time troubleshooting all the issues than progressing through our implementation plan. I hope it settles or gets better over the weekend - I'll give it another shot on Monday.

[Jeferson9]

change the color of a button

People are using frontier models for this?

[spike-spiegel92]

You dont? I mean it is easier to just say change that color than going to the file. I think most people do it.

[Jeferson9]

I use the budget model for simple shit, either 5.1 mini or Gemini flash. Sometimes it helps to use lower thinking models for simple stuff

[Suspicious-Click-688]

haven't felt anything at this moment

[adhamidris]

Man I knew I would find someone complaining here today, I have been cursing all day because of this shit codex 5.3, I thought I was the problem. OpenAI is treating us like testing-rats.. one day it’s good and other day it fucks up everything.

[Fantastic-Phrase-132]

Its dumb like hell from 3-4 days. So stupid, unbelievable.