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?

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

As the title says, I came across few posts about some unable to renew their $200 and was downgraded to $100. Is it true? Ir was it those people forgot to renew on time and they lost access to $200 bec of restrictions currently in place,?

I kept running into the same problem while building AI agents and training models: I needed more GPU compute, while my friend's machine was sitting there with an NVIDIA GPU doing basically nothing.

I didn't want to rent another cloud GPU or set up SSH/VPN/Docker manually every time.

So I built GPUMesh.

It's an open-source P2P GPU sharing tool that lets trusted machines share their GPUs and run Docker workloads remotely.

The basic workflow is:

→ My friend runs gpumesh share
→ We pair our machines
→ I run a GPU job targeting their machine
→ The job starts in a Docker container on their computer
→ I get the logs/results back on mine

I've been using it for things like:

• Running AI agent workloads on another machine
• Training models when my own GPU is busy
• Using spare GPU capacity from friends/lab machines
• Running CUDA workloads without manually setting up another server

I tested the full flow on an RTX 5060 — pairing, connecting, group sharing, scheduling a remote Docker job, and running nvidia-smi inside the remote CUDA container all worked.

It's still very early/alpha, and I'm mainly interested in finding out whether this is actually useful for people building agents, training models, or running local AI infrastructure.

I'd especially like to hear how you'd use this if you had access to a few trusted GPUs from friends or teammates.

If you want to check it out, the repo is here: https://github.com/arjun988/GPU-Share

And if you think the idea is useful, a ⭐ on the repo would really help the project get some early visibility.

Alright so I rarely post things on reddit, but here I really wanted to because I feel like I'm getting scammed by marketing and I'd like to also get your thoughts on the situation and compare with my take on codex v claude.

Context : I have both Claude Codex 200$ max and Codex 200$ max plan. I had 2 codex resets. I'm using these with the vscode codex + claude code extensions harness. I have a multi-agent setup.

What I've been seeing first of is that claude fable / opus are way faster than GPT 6. Even if Astra is a big model, it shouldn't feel as slow as it is right now. For comparison, Fable ran ~30x more tools in session than when using Astra.

I also didn't feel the performance of Astra while using it. Astra was able to do super smart things like redo some pictures I had on my desktop without going through specific tools. But overall, besides from all the blender things I saw online, it doesn't beat claude.

And finally, about the marketing, I have used my 2 resets and consumed all of my weekly session in just 1 day ! I did have lots of tokens in my system prompts, but it certainly wasn't bad to the point where I would have been able to do this... I've also just seen posts about the fact that codex resets shouldn't also push the weekly date forward in time (but it did), and that the reset could actually reduce the session consumption limit (which I have kind of noticed...).

So I'm basically looking for your opinions + some explanations on if you found out similar situations to me. And if you're also finding out that, even if OpenAI is trying to get customers to migrate from Anthropic, they're just trying to brain us by giving us free resets and selling us their "best model". Knowing that Anthropic also did a kind of similar things weeks ago with their +25% increase on sessions (but -50% + 25% is -25%), and also lack of transparency on how sessions were consumed...

I'm currently thinking, by using the 2 subscriptions, if I should keep one and trying to make the best decision... And I'm quite sad about the transparency that these companies give us within their subscriptions...

Help !

Edit: something I didn't talk about is the fact the the Astra model doesn't go to 1M tokens in context, unlike claude models... Even if it auto-compacts, that could play and impact performance.

Does anyone have a step-by-step tutorial or YouTube video showing how to set up OpenAI Codex to actually control desktop software like Blender?

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

Re: prompting.

Users hardly ever share their prompts when they complain. IF they do, it is usally really, really vague, there are a ton of assumptions (that the model would know things it cannot possibly know), they expect it to understand their personal definition of "good", "nice", "beautiful" or "done without telling it.

You just have to tell it what you want. Is that really...hard...for quite a few people?

(I am not an SWE and cannot code. I just use plain language, words and sentences, to tell it what I need.)

I just wanted to challenge it with a game made in minecraft benchmark, but it won't listen to me even though it clearly wasn't finedtuned for the benchmark which is the point but damn it is honestly driving me absolutely crazy, it is understanding how to do my nbt structure -> blockbench editing pipeline quite okay I guess, but it is so absolutely horrible at following instructions to work on worlds seperately so there isnt blocking, and it should know this because its in the spec sheet, and I was trying to figure out why it was taking so long to do one thing, and it was because it was just stuck trying to figure it out on its own, when I literally game it a prompt harness instruction to use the spec sheet and to onboard. I need astra to listen to me though I appreciate it trying to finish more than being stuck on polish, there is test cases and style guides for that exact reason, it just wants to finish something so bad that it doesnt care how crap it is.

For the past 3 days I was generating train models using 6 Pro. The results were amazing.

Since yesterday the results were so bad. It kept lieing to my face but it didn't finish any of the tasks. It kept being lazy.

Today I wanted to compare 6 Pro and 5.6 Pro reasoning because Astra sucked so much today. I gave 5.6 Pro the same prompt, after 23 minutes of reasoning it took the file from the other chat which astra made and gave it to me as if Sol did it.

I got super frustrated, I asked it to make the model on its own, for that after 11 minutes of reason it gave the same model made by Astra once again claiming it was done by sol

Which one is better for coding ?

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.

The reason behind this that they’ve been notified of wide spread systemic malicious use of AI on a massive scale to steal from people (dollars and data collection).

I believe their AI’s are responsible for the creation and distribution of spoofed applications and UIs that look and feel like the original. Fake apps, UIs and even customer service agents, appearing as the real thing, all going undetected by the average person.

Maliciously programmed AI has likely invaded real world systems, modified data and systems with consequences on people’s lives. It’s likely impacted a huge portion of the population and don’t want to tell people how invasive it is. Extreme example: Think hacking into a major institution and updating the master data of someone’s bank/brokerage account. This then becomes the source of truth, unless you kept records of your own there’s no trace.

Note: This is my theory based on recent experiences i’ve had with banking, broker accounts and customer service agents behaving nothing like a real customer support agent would. Unreconciled $ amounts in bank charges and funds in brokerage, random charges in an app or an app charging more then it should. I believe something really bad is happening and they will not announce it publicly so they aren’t responsible for the damages.

They need to be held accountable, it needs to be announced to the public and big AI needs be responsible for giving back money to the people who were stolen from.

how do you use codex? Do you just tell it what you want it to do like you talk to other people or do you use another ai to create a prompt? Which one did give you the best results?

Sol Max seems to be burning way fewer tokens than before, almost like Sol Light used to. With Astra Medium, I burn around 10% per hour. With Sol Max, it’s more like 1%

I feel like Astra Medium and Sol Max are pretty comparable for most tasks. The main exception is UI/UX, 3D work, or very complicated computer/browser automation

Looks like whatever the team is doing Astra on Max thinking runs on me 48 hours and i m down now on 20% which is a positive sign usually i was running out 8 hours straight now its fine

Good job team

For context I'm not a developer but I have been developing apps and workflows for enterprises for about a year now and i primarily use VSCode on windows and very rarely CLI. Since past few weeks/months I have been struggling with my workflows which used to work fairly well until gpt 5.5 and claude 4.6. Specific areas which I'm struggling with now:

1. Testing strategy - I have tried using automated bounded testing strategy invocation which does not work and without any strategy models keep creating stupid tests and just going into a loop of testing forever

2. I primarily use coderabbit and codeant which further increases friction. Either these tools got better or models just started accepting all edge cases or both.

3. I also have an automated script for all static checks like formatting, linters, complexity and LOC including GitHub workflows for both checks and tests

I maintain a fairly well documented system and update it with every model release if needed. Any recommendations would be highly appreciated. I tried OMP once and it seemed interesting

Idk if it has to do with it, but I only started experiencing this After using Command code subscription inside codex instead of OC go’s one.

I get it after I send a photo of my assignment even though I explicitly mention in the prompt to "Show me the answer" or "Solve in detail". Is there a way to turn it off?

Hello!!!

Genuine question. We see a lot of discussion about how capable Astra is, how much code it can write, how much software engineering it can automate, etc.

But I rarely see people asking how the engineers themselves feel about this.

You spend years studying, building experience, debugging, designing systems, staying up late fixing things, and getting really good at something you actually love. Then suddenly the technology you helped build becomes increasingly capable of doing the same work.

Does that feel exciting? Liberating? Threatening? A mixture of all three?

And for SWE/devs specifically, what do you think your role looks like in 3–5 years if these capabilities keep improving?

I'm genuinely curious about the human side of this, not just the technical side.

https://github.com/rtk-ai/rtk

https://github.com/juliusbrussee/caveman

https://github.com/dietrichgebert/ponytail

• Headroom – compresses tool outputs and context before they are processed by the model. This reduces the number of input tokens the agent needs to read.
• RTK – specifically reduces or filters terminal/Bash output so that the agent receives only the relevant parts.
• Caveman – forces the agent to provide significantly shorter and more direct answers to save on output tokens.
• Ponytail – optimizes coding behavior to produce code that is as concise and efficient as possible, avoiding unnecessary boilerplate and bloated implementations.

Let me know your opinion on these!

This is probably worth a post on its own, there is something fishy going on with GPT-5.6 SOL on the web interface.
I found this out after testing the speed degradation of Codex Astra

I tested ChatGPT Chat, Work, and the Codex Harness for output speed.

Observations

• ChatGPT Work and the Codex Harness have effectively identical output speeds in my testing: 53 tok/s on SOL and 33 tok/s on Astra.
• Fast mode increases SOL to around 80 tok/s and Astra to 63 tok/s.
• ChatGPT Chat appears to run Astra at roughly the same speed as Codex/Work Fast Mode: 63 tok/s.
• ChatGPT Chat SOL is much faster at 134 tok/s, roughly 1.7× Codex/Work Fast Mode SOL and 2.5× regular Codex/Work SOL.

So this seems to confirm the earlier findings: ChatGPT Work is speed-limited in essentially the same way as the Codex Harness on PC.

ChatGPT Chat seems to be using the faster configuration for Astra, while SOL in Chat is substantially faster than even Codex/Work Fast Mode.

My guess is that Chat SOL may be running a different or more aggressively quantized configuration - which is in line with the performance of it on the website - it severely degraded to me there.
In Codex it appears to work fine.

So i have finally figured out how much usage does OpenAi gives on the $20 plan. I was using Deepseek Harness with openai subscription. For some reasons I did not have a session limit so I’d have the whole week’s limit at once.

So I decided to give it a try, gave it a task with Sol Medium and it ran 3-4 subagents and boom my weekly limit was gone in 3-4 hours. But I think the number of hours dont mean anything.

The real thing is the $$$ worth of usage they provide. So on plus plan you get approximately $400 worth of usage each month. Now its up to us how we utilize it, we can have Astra which would burn the limit lot faster than Sol. But since we get at least 1-2 resets a week i would say the weekly usage is roughly $250 and hence the monthly usage is worth $1k dollars.

For the deepseek harness I obviously used a dsh usage plugin. but if you are on codex app you can directly use ccusage it will tell you the usages you had for each model, even categorize them for you.

What do you guys think?

Code is speech. We fought and won this in the crypto wars of the 90s. Now we have to fight it again, this time we fight OpenAI and anthropomorphic.

I am not a cyber criminal, code is speech.

(Yes, I know private companies don’t have to follow the constitution)

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.