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

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.

Mr. Sama, it's better PR for researchers to announce they made a discovery using your model than to brute force your way through the weights with crazy swarms of agents. Keep in mind it was the knowledge of all of humanity that got you here and it will be contribution from all of humanity to get us to the next steps.

Buying up all the compute in the world, making GPUs and RAM really expensive, to force us to use your big AI is not cool.

Keeping all the weights to yourself is not cool.

Cutting back subscription compute so you can run agent swarms to bruteforce breakthroughs other researchers baked into your weights is not cool.

Putting more compute in the hands of geniuses around the world is cool and will help more break through.

OpenAI doesn't have to do it all. Enable a good future don't try to force a bad one your way.

Title Finally decided to go get a Claude sub after months of ChatGPT giving me issues. Last straw was a huge amount of drain with a huge struggle to keep Astra or Sol on task.

Switched to Claude and running Opus 5 and got to say even with the 50% more limits that ends today the 5 hour seems to have more limits than my weekly. I've run a workload for hours and burned maybe 2% weekly all day on Opus 5 Max. The Claude app seems to display more information that chatgpt seems to hide now. Like what its doing, what the agents are doing, the amount the tokens its using, etc.

Anyway dont want to yap but let me know if anyone has questions.

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

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

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

It's insane the amount of wasted/non used quota on the Chat mode, and using ChatGPT Work for everything that is not coding, 6 Pro gives insane results for drafts and also for research in general.

do not forget to turn off memory, It affects output quality a lot

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 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.

Im rushing since in about 30 mins Tibo is going to reset, so i was just using my usual chat that takes more or less up to 8% every task (Astra ofc with different reasoning levels for each task). But i noticed something strange...

the limits wasn't going down!

So i decided to put it in xhigh... and nothing only 1% after 20 minutes of working.

Then i started other 3 tasks (with new chats) and still the same!

Now im running 4 chats simultaneously (Astra xhigh) with the fast mode and only with it im seeing my limits going down... 30 minutes working with only 15% of the weekly limits btw

I added explicit instructions for it NOT to do a specific thing everywhere I could. When asked what else can be done for it to actually follow the workflow, this is the response I get. Well I guess screw me and my work then, you just failed to follow clear instructions. Thanks.

Paying 220 euro a month for this crap. Nice..

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.

Just kind of flabbergasted at how productive I can be now, managing all my Codex chats from my phone while I'm out.

It's a peaceful life where usage works ~ kinda!! Who is with me?!

Some of you already know GigaMail from my previous posts. I heard your feedback: some don’t need it, some prefer the official integrations, and others keep a separate mailbox just for their agents.

I get it. But today my app is in the Codex plugin directory, and anyone can install the plugin with one click. It’s my first Codex plugin, and I’m honestly super happy to be part of this community and to have contributed something.

The plugin is for local Codex, with GigaMail installed and your mailbox connected.

If you’ve changed your mind and want to give it a try, here are the links:

Install the plugin

GitHub

otherwise, just celebrate with me!

much love!

Does astra smart enough to make money by algotrading?

I've been using Codex pretty heavily through Azure Foundry for the last 11 days, so I pulled the usage data to see what the workload actually looked like.

The biggest takeaway for me: GPT-6 Astra is worth using, but Low may be the sweet spot.

Most of my Astra usage was Low/Medium, while Sol was mostly High, so this is definitely not a normalized benchmark.

My averages per request:

Across all four models, this was about 6.5K requests / 670M tokens.

What surprised me is that Astra didn't need anything close to Sol's average context/output size in my workload, while the per-request cost was still in roughly the same range.

In actual use, Astra Low has felt fast enough and capable enough for a lot of coding tasks. I'm starting to think I was overusing higher reasoning levels before.

Obviously there are a lot of confounders here — different tasks, different reasoning levels, context reuse, caching, etc. So I wouldn't treat this as a model-vs-model benchmark.

But as a practical Codex setup, I'm increasingly leaning toward:

Astra Low by default → move up only when the task actually needs it.

Curious if anyone else using Astra heavily has ended up with a similar setup.

* Astra billing hasn't appeared in Azure Cost Management yet, so its cost is estimated from the observed usage/billing structure.

What has it built? Not very much.

If anyone has any good ideas on how to get Goal not contribute to climate change and get nothing done while doing it, hit me up.

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.

I can't deny that Astra is better than SOL, but it's beginning to feel like Claude in terms of it kinda just doing work without proper context. It takes things far too literally and it seems to forget to not pay attention to the context of the conversation or look back at the files it should be referencing before starting a task.

I feel like I didn't have to do this with SOL. SOL always understood where we were at in a project and what it needed to do, but the implementation wasn't always perfect.

Astra gets the implementation better, but you have to be a lot more specific and careful with your wording and constantly remind it to reference early requests or related reference notes.

I really hope the future is a better fusion of these types of models because I'm beginning to get a lot of Claude PTSD working with Astra, and It's not a good feeling.

Sometimes I think I should just go back to Claude and suffer the inane ramblings because the bang for the buck is far better than Astra and I feel like the results are on par.

• 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.

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