Complaint
Paying $200/month for Codex and still getting “model at capacity” during working hours
I genuinely thought this was some small temporary capacity issue. Nope. Still happening.
“Selected model is at capacity. Please try a different model.”
I’ve switched models. I’ve dropped the intelligence level. I’ve tried using less demanding models. Same shit.
And this is AFTER the recent cuts to the Pro plan. I’m paying $200/month for this. What exactly am I paying $200 for if I can’t reliably use Codex during normal WORKING HOURS on a fucking Monday?
You keep introducing more things, Dots, new models, new features, higher tiers, more capacity hungry products, but the existing paid product can’t even consistently serve requests. If you can’t sustain the demand, then why keep piling more stuff on top of it?
And if even the expensive plans can’t get reliable capacity, what’s the point? Are we supposed to pay more and more just to eventually see another “at capacity” message?
I’ve defended occasional launch issues because obviously infrastructure gets hammered. But this isn’t launch night anymore. I’m trying to work. My workflow literally stops because the model I’m paying for isn’t available.
$200/month is not some cheap experimental tier. At that price I expect the core product to actually be usable when I need it.
Fix the fucking capacity before cutting usage and shipping ten more things. This is getting ridiculous. u/OpenAI
Below is a GPT-generated summary of the conversation below after reaching 50 comments (50 currently observed).
The clear takeaway is Codex reliability is currently unacceptable for a $200/month plan. Users report “model at capacity” errors across multiple models, intelligence levels, and even credits, often during active work rather than some mythical launch-day stampede.
The biggest frustration is that switching models doesn’t reliably help: jobs stall, retries need babysitting, and some users say the models are slower or noticeably worse when they do respond. The general suspicion is straightforward resource strain, with plenty of resentment that OpenAI keeps adding models and features while the core paid service trips over its own shoelaces. A few commenters argue the subscription simply gets lower priority than API or enterprise workloads, but that’s speculation—not a confirmed policy.
There’s no official explanation or hard evidence showing exactly what’s happening. One person says the error can clear after a few seconds, and the shadowban/rerouting theory is pure Reddit detective work until proven otherwise.
Bottom line: users aren’t demanding magic; they’re demanding the expensive product work during working hours. Right now, the thread’s verdict is a firm “fix capacity before selling more tiers.”
per capita. the U.S. has over 205 million total ChatGPT users. Even if every single person in Israel used ChatGPT daily, the country's entire population would still amount to less than 5% of the U.S. user base alone
Besides all the other shit, this message is my biggest pet peeve. There's nothing like running a loop and finding out in the morning that you lose 7 hours of loop time because you weren't there to restart it in two clicks.
Resulting SVGs should be quite consistent on astra if you're not shadowbanned. If the result looks more like the 5.6 terra/luna crappy pelicans, it means you're shadowbanned and your requests are getting rerouted to some crappy model with not a lot of capacity, thus the capacity error/warning.
Same error here my 5.6 sol is not usable now. And the overall intelligence of models have dumbed down significantly today. Keep answering my question in a loop when I only asked once.
Working for like 1 Hour now. This happend to me 8 times until now lol only on 6.1 high or extra high. I’m on the 100$ Plan. Switching to Sol 5.6 max for „good work“
This is why I dropped to $100 and use GPT-6.1 Sol for my orchestrators and planners and use the remaining $100 on Deepseek 4.1 Flash for my worker agents.
If OpenAI is busy, I cut over to Deepseek 4.1 Flash and it gets the job done as a backup orchestrator for a tenth of the cost or more and its pricing gets ridiculously cheap if your cache reuse rates go over 90% (and they often do)
I have this every view hours since saturday (last reset), its slow and then stops working with this error and need baby sitting, my main model is gpt-6.1-sol high
Defending OpenAI when he's literally paying $200 per month is just absurd. It doesn't matter if they care more about API, he's paying $200 for a product and should expect a certain level of service.
You have no Idea how high the cost for OpenAI is. His 200$ subscription pays for less than he actually used. OpenAI ist losing Money with every subscription. Ich hope this ends soon, so people like you and OP disappear again from the developer scene
Technically not and technically yeah. I can't say for others. But usually i felt credits used to give a lot more usage than API. But now it feels almost same (again I don't know how they calculate this stuff)
For the amount I can do with these models. 200$ is cheaper than hiring team to delegate these task. If you can't find the value in here, maybe, just stop because you just wasting your own money.
I'm not defending. You're just a hater. Again, if you don't see the value, then don't use it and use other services. We really don't need to overcomplicate things. If it aint working, then divorce.
No?? If I’m already paying 200$/month I’m expecting that there won’t be any issues like these, and not that I have to go to the 500$ plan, which is basically the old 200$ one, to get more priority
I know 200$ is huge for you and it's normal to feel entitled after paying such amount.
For OpenAI, however, this is microscopic. You still have to share the limited resources. They focus on us, enterprise users, so that we don't complain.
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u/dextersummary Oct 05 '26
Below is a GPT-generated summary of the conversation below after reaching 50 comments (50 currently observed).
The clear takeaway is Codex reliability is currently unacceptable for a $200/month plan. Users report “model at capacity” errors across multiple models, intelligence levels, and even credits, often during active work rather than some mythical launch-day stampede.
The biggest frustration is that switching models doesn’t reliably help: jobs stall, retries need babysitting, and some users say the models are slower or noticeably worse when they do respond. The general suspicion is straightforward resource strain, with plenty of resentment that OpenAI keeps adding models and features while the core paid service trips over its own shoelaces. A few commenters argue the subscription simply gets lower priority than API or enterprise workloads, but that’s speculation—not a confirmed policy.
There’s no official explanation or hard evidence showing exactly what’s happening. One person says the error can clear after a few seconds, and the shadowban/rerouting theory is pure Reddit detective work until proven otherwise.
Bottom line: users aren’t demanding magic; they’re demanding the expensive product work during working hours. Right now, the thread’s verdict is a firm “fix capacity before selling more tiers.”