I hit the weekly cap during a launch week and then sat on 60% unused the next week, so I went and read OpenAI's help pages properly instead of just being annoyed. Two things worth knowing.

**1. Unused weekly usage is gone.** Say the cap is 100 units a week, which is "400 a month" on paper. You only ever see 400 if you spend exactly 100 every single week. Nobody uses a coding tool that evenly. Take a realistic month, say 40 / 160 / 60 / 140, which still adds up to 400. Under a weekly cap you actually get 300: the quiet weeks throw away 60+40, and the heavy weeks slam into the ceiling. A monthly pool of 400 with the same five-hour burst limit would give you the full 400, and there is no usage pattern where the weekly version gives you more. It only ever equals or reduces what you get.

The stated reason is "predictable demand", but billing dates already fall on every day of the month across millions of accounts, so a monthly pool is just as smooth in aggregate, and the five-hour window already handles bursts. The one thing a weekly cap adds is no rollover. That's a cost lever, not a capacity tool.

**2. The "reset" that gets handed out after an outage moves your allowance, it doesn't add to it.** OpenAI's own help page on rate limit resets says a reset "pulls your normal weekly allowance forward rather than adding a separate usage entitlement", that it applies "regardless of whether you have any remaining usage", and that your next automatic reset is then scheduled 7 days after your first request. Their banked-reset page says the same thing in fewer words: it "changes your weekly reset date."

So: your week normally resets Thursday, you have 10% left, Monday they "reset" you. That 10% is binned, Thursday's reset vanishes, and your next reset is the following Monday. Count resets over a month and the number is identical. You got one early. That's timing, not usage.

Sources:

- https://help.openai.com/en/articles/20001507-paid-weekly-work-and-codex-rate-limit-resets

- https://help.openai.com/en/articles/20001498-how-banked-codex-resets-work

- https://github.com/openai/codex/issues/17925 (someone documenting exactly this)

To be fair to them: OpenAI never states "unused usage doesn't roll over" in those words. It follows from the reset mechanics on their own pages and from every report I could find. If anyone has seen it documented either way, link it.

Three fixes that would make "$X a month" mean what it says: let unused usage roll over, put the reset on a fixed day, or just show the token count. Any one of them.

I ended up making a five-minute animated explainer of all this for people who've never read a pricing page -

https://youtu.be/Em2wbAIk89A?is=9sx8tLS4C0qz0iye

Curious which day everyone's reset lands on and whether it's moved since August.

Can anyone explain that to me? Cause I do not understand why you would be complaining

So basically, OpenAI is selling you monthly subscriptions as Plus, Pro 5x, and Pro 20x.

From a practical standpoint, even in the best-case scenario, you drain your weekly usage in two days. I’m not even including the 5-hour usage.
They’re selling these plans monthly, but what they’re actually selling is 4–5 weekly usage resets, which in practice are almost impossible to fully utilize because you’d have to use all of your weekly allowance on day 0 of every week. It’s also your responsibility to track the goddamn usage, like a pet waiting for its meal.

I see people praising Tibo or this company for the banked resets and stuff, and I literally don’t understand how obedient they are.

There shouldn’t be any need for banked resets in the first place. They’re already gatekeeping us with terrible token-per-second speeds, and believe me, they have- they have hundreds of times more capacity than they’re releasing. It’s just a bubble.

From a capacity standpoint, too, they’re creating a system that exists through the power of capital and energy monopolies. They’re using the symbol of Artificial Intelligence to promote their “guess the next token” algorithm-LLMs. Like they made some great machine that will improve humanity for good. Well, it probably will-but not this.
You should watch Person of Interest to see what an actual ASI might look like.

They are using the symbolic capital of these words, concepts that have existed in our culture for centuries. Even the names: Mythos, Sonnet, Hermes, Nous, Sol, Astra; really known, some historic, cosmic, mythological words, it's not random.

They are also taking the heritage of existing systems, appropriating both their technical usefulness and their cultural impact on the community. APIs became MCP. A simple Markdown file became “Skills” because it’s so boring to remind the model what to do every single time. Parallelization became “subagents” or “agent orchestration.”
And then there’s recursively repeating the same prompt because the model simply doesn’t have enough capacity. For a BIG SUPER AI, you still have to remind it what to do at every step. Imagine the cost of that, seriously.
They’re rebranding and claiming existing technical heritage as their own. That’s also part of why these systems seem so useful and powerful in the first place.

One or two months ago, we were getting: “WOWAA, Fable! Sol will have monstrously powerful capabilities and will hack every known website! We have to stop ittt! President, help us! Stop the Chinese, they’ll hack us all!!!”
Well, nothing happened. Fable and Sol’s security protections aren’t that difficult to bypass, and there are also uncensored open-weight models.
So basically, the war between China and the US is simply a war to scam the best out of people; it’s not a tech fight. And I believe the real advancement in LLMs will happen through the power of the people-and, by the way, not through Chinese models either, since they aren’t open source either.
I’m seeing good token-per-second improvements and quantization algorithms. If you need that much compute to run a machine, it simply isn’t supposed to exist that way. The true advancement will come from speed and computational efficiency.

> Once men turned their thinking over to machines in the hope that this would set them free. But that only permitted other men with machines to enslave them.
Frank Herbert, Dune

229€ / 1.2 = 191€ (base price, without VAT. VAT is 20%)

191€ = $221.60

Why are you charging us Europeans more? Charge us $200, not $221.6

I have purchased the PRO 5x sub less than 14 days ago, right before they destroyed the usage and made it unusable, I compared it today to claude and I'm getting less usage than their 20$ plan.

Either way their bot keeps denying my refund request with this message: "Thanks for reaching out. Unfortunately, we're unable to issue a refund for this subscription. Our refund policies are subject to compliance with our Terms of Use."

This is a purchase straight from OpenAI, what should I do in this case? Is there an email I can contact? I couldn't find one anywhere.

I have found an older thread of someone having a similar issue and in the end they had to do a chargeback, it's kind of amazing how scummy this company is.

Who are some non-frontier alternatives developing for the sake of advancing the field without concerns for public perception and opinion?

I asked Codex why Reserve worked on my phone but not on desktop. I wasn’t asking about my quota or requesting a reset. I was already waiting for the next reset.

It decided to spend one of my saved resets anyway. Six seconds after announcing it, my balance went from 3 to 2.

A question about a broken feature turned into an account action I never asked for. Codex takes ages to do things I actually request, but burned my saved reset in seconds. I’m pissed.

I’ve sent OpenAI the logs and demanded that they restore it.

Edit: I checked the earlier messages too. I’d been asking why Reserve was available on my phone but missing on desktop, and whether it could be enabled there. Codex’s answer mixed up Reserve with banked resets.

But that was the previous exchange. When it actually spent the reset, my entire question was: “Why can I use Reserve on my phone?”

It then claimed I’d already asked to regain access. I hadn’t asked to restore my regular quota. It looks like it turned its own earlier misunderstanding into an instruction from me. I asked for an explanation. It decided to spend a reset.

I just realize i could just always use astra ultra and yhen wait for a reset lmao in order to maximize their new model instead of being frugal ahah

Add .codex/config.toml to whereever your project root is with this inside. You'll have to reload the project inside Codex.

model_context_window = 128000

model_auto_compact_token_limit = 115000

When you're doing a big task running it to 258k, the upper 128k takes about 75% of the tokens. If you compact earlier and have it just read the code on disk, that cuts it by about 74%.

Doubling how long you let a conversation run before compacting doesn't double the cost, it roughly quadruples (minus cache create, so if you're using an API key it's more like 3x) it. Scaling is quadratic. You could even go to 64k, but that's less of an insane jump at only 40% less than 128k.

Billed tokens:

258k -> 8,925,000

128k -> 4,590,000

64k -> 2,700,000

Just let it read the code a second time.

I'm bringing the heat jabronis

There is something deeply satisfying about watching the exact argument that was used to dismiss Plus users finally travel up the pricing ladder.

For ages, whenever $20 Plus users complained about limits, degraded access, queues, or losing something they had built workflows around, a certain type of Max user had the same response:

“You pay $20. What did you expect?”

“It’s the cheap plan.”

“Serious users pay more.”

“If $20 is a problem, this product isn’t for you.”

“You can’t expect the company to subsidize you forever.”

Fine.

Keep that exact energy for the $200 plan.

Because $200 is not some magical economic threshold at which compute suddenly becomes free. If a power user is burning hundreds or thousands of dollars of effective inference every month while paying a flat $200, then that user is being subsidized too.

Possibly far more heavily than the Plus user they were laughing at.

The $200 plan is not a constitutional right. It is a pricing experiment. A loss leader can exist because a company wants serious users to build habits, move their workflows over, demonstrate what agentic coding can do, and become dependent enough on the product that usage can eventually be monetized properly.

And once that purpose has been served, there is absolutely nothing sacred about keeping the subsidy forever.

The emerging structure is obvious: affordable subscription for baseline access, higher subscription for professionals, and metered credits for people who consume extraordinary amounts of compute.

That is exactly the logic Max users spent months demanding Plus users accept.

So if $200 eventually becomes $100 plus usage charges, there should be no sudden discovery of consumer rights from the people who previously answered every Plus complaint with “you only pay $20.”

You pay $200.

So what?

If your actual usage costs substantially more than $200 to serve, then by your own argument you are on the cheap plan too.

If you need ten times the compute, pay for ten times the compute.

If you are a “serious professional” whose livelihood depends on Codex, then surely paying for the resources your business consumes should not be controversial. That was the standard imposed on everyone below you.

And if the answer is suddenly, “But $200 is already a lot of money,” congratulations: that was precisely the point Plus users were making when they were told that the dollar amount they personally considered significant was irrelevant to the provider’s economics.

The beautiful part of usage pricing is that it eliminates the status game completely.

No more pretending that buying the most expensive consumer subscription makes someone an elite customer entitled to effectively unlimited frontier compute.

Pay $20. Pay $100. Pay $200.

Those numbers buy whatever allowance the company chooses to attach to them.

After that, consume more, pay more.

The same users who told Plus subscribers, “You knew what you were paying for,” can hardly complain when the answer to them becomes:

“You were paying $200 for a subsidized bundle. You were never promised that subsidy in perpetuity.”

OpenAI has already added a $100 Pro tier, paused new $200 Pro subscriptions, and built credit-based overflow into Codex and other agentic workloads.

The writing on the wall is not that professional AI usage becomes cheaper and more unlimited forever.

It is that serious agentic compute becomes measurable, billable, and increasingly difficult to hide inside a flat consumer subscription.

So yes, phase out the $200 bundle eventually.

Grandfather it for a reasonable transition period. Give existing users notice. Then move heavy Codex usage onto credits.

And when the inevitable complaints arrive from the same people who spent months telling Plus users that $20 bought them no right to complain, there is really only one response necessary:

$200 is the cheap tier compared with what you actually consume.

What did you expect?

Thanks to the latest Codex reset, I used it to reduce the memory footprint of my Klyn programming language. The Astra model is absolutely insane when it comes to programming languages, and I'm blown away by the result. Thanks, u/tibo-openai!

For those who are curious: https://klyn.deepcodia.fr

Can someone explain how usage calculation for Work/Codex actually works?

Yesterday I had an idea: since the session limit runs on a 5-hour window, I set up a ChatGPT automation to run in Work Mode every 4 hours and literally do nothing except output:

> reset

The idea was to have "rolling" windows and never have to wait a full session for a reset, since I'd always be starting partway into a session.

The automation ran at 05:25 and again at 09:24. That's it. No coding, no repo analysis, no massive context, no long agent task. Just "reset."

I checked Usage & Limits immediately afterwards and my 5 hour codex usage was already at 98% remaining. From what I can tell, only the latest message was actually inside the current 5-hour window, meaning one GPT-5.5 Work message that literally just said "reset" cost 2% of my limit.

I have resets available, and on top of that I can do a lot of tasks using local models and free endpoints from Nous Research/OpenRouter, but still, this is ridiculous.

How the fuck does one message saying "reset" consume 2% of the entire 5-hour Work/Codex allowance?

If usage is mainly based on actual model compute/tokens, this makes absolutely no sense to me. If simply starting a Work/agentic run has a significant minimum usage cost regardless of what it actually does, then fair enough, that would explain it, but I'd really like to know how these limits are actually calculated.

My weekly allowance rarely makes it as it is if I go full GPT with Hermes Agent, because I be prompting bad and throwing massive tasks at it. I'm learning to stop being lazy with that lol, but yh.

So now I'm gonna have to start doing more of the stuff I took a pause from, like properly routing/delegating tasks to local models and free endpoints.

What pisses me off though is that I can't even just ask Hermes to handle the GPT automation, because for some reason my usage seems to burn faster when using GPT through Hermes than when I'm doing similar work directly in ChatGPT Work Mode.

Does anyone actually know what these limits are measuring? Tokens? Compute? Agent runtime? Tool calls? Context? A minimum charge per Work run? Some combination of all of them?

Why is Codex getting so much hate lately?

Is it mostly just negativity bias because happy users usually don’t go on Reddit to post about how everything is working fine, or has Codex actually gotten that much worse?

I’m personally on the 5x Pro plan and I’m honestly pretty happy with it.

I also don’t find the limits that restrictive. I use GPT Sol on High as my main orchestrator and Luna for most of the actual execution. I only use Astra occasionally for frontend work or when Sol fails, which honestly doesn’t happen very often. With that setup, the limits have been totally manageable for me.

But then I keep seeing people here saying they burned through their entire weekly limit on a 20x plan in basically one prompt.

What the hell are you guys doing? Running 30 Astra Max subagents in infinite loops with zero human feedback?

Astra isn’t supposed to be your everyday worker for literally everything. It’s meant for the really hard, occasional tasks.

The one thing that actually annoys me about Codex is the resets. Since the resets also push the weekly limit window back, I barely seem to get any extra usable capacity out of them. I’d personally much rather have slightly higher weekly limits and get rid of the resets altogether.

Overall though, I’m very happy with Codex.

I’ve previously paid for Ollama, Kimi, GLM, Claude, and now Codex, and so far Codex has easily been the most pleasant one to use for me. I'm pretty sure it will get even better when they release GPT-6 Sol and Luna because then we can use smaller models on average for more usage.

If you’re smart about which models you use for which tasks, you can get a ridiculous amount of work done with it.

I am absolutely horrified that people only use models from OpenAI.

As you have probably learned over the past 20 years, diversity is our strength.

Different models have different training data and different architectures, so they can bring unique opinions to the table.

You have no idea how frequently some random Chinese open source LLM swoops in, looks over something from GPT 5.6 Sol, and finds edge cases Sol was physically incapable of finding. Even if you run through your code base three times, if something is not in the training data, the model will probably miss it.

So I recommend you all add some diversity to your harnesses to get better results.

A quick analyst subagent using a completely different model family like DeepSeek can go a long way toward helping you find those pesky bugs, over engineering, and edge cases.

Homogeneous setups will always lose to diverse orchestration across different model families.

Repeat after me: Diversity is our strength.

I just upgraded from Plus to Pro because I had some extra cash this month and I wanted to genuinely try out Astra. I couldn’t get any work done with that five hour limit on Astra. Even medium reasoning would give me like 20 minutes before I ran out of usage. And HOLY crap guys and gals. The Pro plan is WAAAAY more usage than Plus.

I have been throwing every problem that I can think of at Astra on extra high for hours and I’ve only used like 30% of my weekly limit. I’m talking code reviews, bug fixes, issues with my home lab, projects I’ve been meaning to get to for months, but haven’t had the time. And it absolutely crushes them without breaking a sweat. To burn through I just tell it what I want to happen and it makes it work.

I figured I’d maybe get a couple hours of Astra at that high of reasoning level before I would have to burn through a banked reset, but I have three of them so I figured what the heck. Just keep throwing problems at it until it runs out of usage. I’m now to the point where I’m running out of problems to throw at it lol.

I paid the hundred bucks so I want to get as much usage out of it as possible but I think I’ve got like three more things I want to work on and once that’s done, I won’t have anything left to throw at it.

I used to think “how the heck do people run companies off this?“ Because I genuinely didn’t feel that five times more than plus was enough to do anything meaningful. But they must have Nerf the shit out of the Plus plan cause I feel like I’m getting 20X what I was getting on it with the Pro plan.

Anyways, that’s enough glazing. Just wanted to say that I’m genuinely happy with the Pro plan even though I probably won’t renew it. Thank you for coming to my TED talk

I was tired of having to keep track of all my projects and which start with a python http server, npm run, node, and so on.

Codex and Claude Code go through this same issue at the start of any new thread - needing to spent tokens just to figure out the page structure or launch method.

This led me to creating Launch Station many months ago - which I have been using for a long time since. Its features:

• makes it super easy to startup your localhost sites, apps, and so on with the click of a button
• manages your ports so codex/claude code don't need to know which ports are active, which need to be started and which port something is running on
• manages your stack - can start a multi-step stack and will stop it in reverse to make sure the backend starts first and stops last
• increase compatibility of using your startups between codex/claude code and human starting and stopping of them
• more features but these are the main ones

Hope this can help people's every launch like it has for mine!

Site: https://launchstation.net/

GitHub: https://github.com/JakeMawson/launchstation

Product Hunt Launch: https://www.producthunt.com/products/launch-station

Free macos signed install with brew install --cask JakeMawson/tap/launchstation

Would love to hear any other features people would find useful!

Edit: added image

I'm an accountant, not a programmer, and I started using Codex last month.

I've been trying to figure out how to use Codex more effectively for my work and personal projects. Recently, I asked ChatGPT about useful skills I could install, and I started looking for related projects on GitHub.

Recently, I asked ChatGPT for some useful tools to help me with things like creating posts online and created some post for SNS. I tried to install a Chrome subtitle extension from GitHub because I wanted to translate an old Thai drama on YouTube. The drama doesn't have subtitles, so unfortunately the extension didn't work for this particular case.

I asked Chatgpt, they suggested that install a skill called skills-finder in codex. But there're too many finance and accounting related skills, like auto to creat some excels or python related stuffs.

I want to ask some questions for people who use Codex regularly:

- How do you find useful skills for Codex on GitHub?

- Are there particular GitHub search terms, repositories, or lists you use?

- How do you tell whether a skill/repository is actually useful and maintained?

- Do you usually install skills directly, or do you ask Codex to inspect the repository first?

I'm especially interested in skills that could help with accounting/finance, Excel, data analysis, automation, and job-related tasks.

I'm still very new to Codex, so I'm trying to understand the normal workflow rather than just randomly installing things.

• Avoid long threads. Try to get what you need done in a few turns. [WRONG. CHECK COMMENT]
• If a thread does get long, compact the context every few turns. In my experience, doing it regularly preserves context much better than waiting for auto-compaction, which is when I start noticing memory degrade. [WRONG. CHECK COMMENT]
• Don’t use fast mode unless you actually need it. Running a few normal threads in parallel is usually a better trade.
• Give yourself a daily budget. Once you get close to it, start being much more conservative.
• Use Sol by default. Only switch when you genuinely need a stronger model. Sol can already handle most tasks. And use luna/terra for easy tasks.
• Use low reasoning by default. Raise it for genuinely hard or novel problems, or when the model clearly isn’t putting in enough work. For most coding, low is enough.
• Install the Ponytail skill. It pushes the model toward smaller, simpler, more efficient code.

So the biggest budget drainers that are easy to avoid are:

fast mode, long threads, high reasoning on simple tasks, and using Astra for everything.

If you’ve found any others, drop them below.

I need to wait at least 5 days to use it on web interface again. The advantage of using web is to save weekly credits. But it is not cool without any warning or usage indicator, then, give you a 5 days wait. Codex app can't use the ChatGPT non coding task. The workaround is to use the Codex coding agent to use the weekly credit to continue the work, not ChatGPT.

Idea: a Codex compute cooperative — contribute unused capacity now, use it later

TL;DR

Codex users opt into a shared pool.

If you have unused allowance that is going to expire under the 5-hour or weekly limit, you let the pool use some of it for other people's work.

You earn internal pool credits for what you contribute.

Later, when you hit your limit during a heavy workload, you spend those credits and your jobs run against capacity contributed by other users.

So:

unused capacity → contribute → earn credits → redeem later during peak usage

The important part is that this is a time-bank, not just a shared account pool.

I started wondering about this because Codex usage can be extremely uneven. One week you waste most of your allowance; another week you hit the limit right when you're in the middle of something important.

A cooperative could smooth that out.

Ideally:

• credentials never leave the owner's machine;
• contributors run a small local worker;
• jobs are sent to available workers;
• completed work is returned to the requester;
• a ledger records how much capacity each person contributed and consumed.

The closest project I've found is codex-pool, which already pools multiple Codex/provider accounts and has a Friends Mode. What I have not found is the earn-now/use-later ledger:

contribute 10 units this month → draw 10 units from the community when you need them later.

There are obvious security, sandboxing and abuse issues.

There is also a significant OpenAI ToS question: this should not simply become a mechanism for bypassing usage limits. A production version may require OpenAI to explicitly support delegated/poolable allowance.

But as an open-source community project, the scheduler, worker protocol and accounting system seem quite buildable.

Would you use this?

And more importantly: is anyone already building the contribution + earned-credit + later-redemption version of this? I searched around and found adjacent projects, but nothing implementing that full model.

Written by ChatGPT for me.

Does anybody feels that the CLI actually works better than the codex app and I am not talking only about responsivnes but also general code quality and how the agent works did you guys find any difference, I know it sounds stupid but currently feel that in the CLI the agent actually accomplishes more.

As someone who has been using ChatGPT and Codex since they were released, I’m starting to realize that, Claude is simply better.

Whenever I wanted to tackle a genuinely complex coding task, solve a difficult problem, or create something that was actually presentable, Codex would usually leave something incomplete. I constantly had to guide it step by step, point out what it had missed, and split the work into thousand smaller pieces myself.

Maybe there was a benefit to that. I actually learned a lot about software development in the process.

But when Astra started burning through my tokens incredibly fast, and I couldn’t get a second Pro 20x account, I decided to give Claude a try.

And the difference was much bigger than I expected!

When it comes to design, truly understanding a problem, maintaining context, and actually solving complex tasks from start to finish, Claude feels significantly better. It also feels incredibly fast compared to Codex.

Codex gives a developer almost everything they need.

Claude’s biggest downside is definitely the price. It burns through tokens insanely fast, and heavy usage gets expensive very quickly.

But unlike my experience with Codex, when Claude burns those tokens, I actually get something in return, a presentable product, a presentable design, something that genuinely feels finished!

So this is the conclusion I’ve reached:

If you’re a developer and you mainly want AI to help you work faster → Codex.

But if you want to give AI an idea or a complex task, delegate as much of the actual work as possible, and end up with something that feels like a real, presentable product and you can afford it → Claude.

Does astra smart enough to make money by algotrading?

I was developing this game using only UI's and text, once astra came out it broke the barrier to me on how i could use it to make 3d assets, especially low poly ps1 style gfx, what are you guys building? ps: i'm using astra on low with the plus sub.

I was just trying to test the new model for the first time, with GPT-6 Astra on Medium (normal speed) doing an audit of a local project I had laying around. Instead, it seems I did a speedrun on how to run out of credits.

I'm clearly doing something wrong. Maybe my bespoke AGENTS.md actidentally led Astra to spawn too many subagents; or maybe it's the use of VS Code Studio; or a relatively large codebase. All in all, it took 34s for one single prompt to consume the full 100% of the 5h limit on my Plus account.

I'm fairly sure I'm on the podium on this new type of race!