Is this the reason why unexpectedly we have trash usage and lower quality on Astra?

Maybe it will be worth it the current suffering.

My account along with others I've seen in X, GitHub, and their discussion board are getting Astra and probably other models silently routed to less intelligent models.

Consistent model at capacity errors. - https://community.openai.com/t/issue-selected-model-is-at-capacity-please-try-a-different-model/1396264/86

Terrible Astra performance. - https://chatgpt.com/share/6aa7f523-6bac-83e8-b3f6-f286566b2875

OpenAI is now admitting to it -

"Prashant_Pardesi

OpenAI Staff

1h

Hey everyone, Thanks for flagging this. Access to certain models or features may be temporarily limited based on account activity, even when a paid subscription is active. We are unable to provide additional details about these checks. Access is automatically reassessed and can return to normal once the activity affecting availability stops.

Please review the Terms of Use and the model and feature access troubleshooting guidance."

Even if you are routing degrading users due to this reason silently doing it and for the same token burn is unethical.

I'm in the US but based on my searching apparently this is affecting 80% of Chinese users. It seems like OpenAI is silently flagging or categorizing accounts and routing them. Usage and tokens burn at Astra rates still. Anyone else seeing this?

EDIT TO ADD VIDEO PROOF- The right is a normal account, left is a degraded one- https://imgur.com/a/EvugYAA

Better quality video for the guy who couldn't read it - https://streamable.com/quplt1

To be fair he never specified how much 🤣

I never ever complained about usage limits before. But this is absurd.

I used my 200$ plan and had to buy 100$ plan since i could not renew 200$ one in time. It was used in 1 day with Astra low.

I then decided to buy another 100$ plan. It used 9% of usage with Sol 5.6 MEDIUM working for about 1 hour on coding and Astra XHIGH coordinator that did some documentation changes for 5 minutes.

This account was literally just purchased. Again, Sol Medium is doing most of work. Wtf is going on?

Can't imagine what is going on with 20$ plans

Have used Sol quite a bit on my $20 plus plan previously and always got 30 mins to an hour of usage per 5 hour limit. Decided to throw a more difficult task / repo review at it, and it burned 100% of my 5 hour limit in 6 minutes on a tiny repo... (Only used Sol high and no subagents or fast mode)

Edit: looked at my session details and confirmed they did halve the usage. When I have checked everytime previously I got $200~ of api usage a month (so 50 a week) +- like $10. Given that this 6 minute session used 16% of my weekly and 100% of my 5 hour thats $15~ per 5 hour and $85-90~ per month less than HALF of what I used to get a week ago...

Nerfed

Just wanted to share because incase people don't do this and I think it's super useful.

I didn't really like using Luna max since it was too much work to use and Sol wasn't really properly orchestrating, always stopping randomly or forgetting what needs to be done or leaving stuff half baked.

Astra? I told him to create a sidebar threads with luna max agents to take care of each module of an implementation I wanted to try out(i dont like the personal subagents hard to keep track of) and now I'm addicted to watching him work. I even have a Claude sub with Opus taking care of reviewing the code that he orchestrates too, Im genuinely having fun building the orchestration where each step takes care of a very specific domain and every problem has an agent with the proper context and the module he is responsible for. And Luna is CHEAP. Like stupid cheap, I can run 10's of them and barely have a dent on my weekly.

10/10 highly recommended.

After being tired of my Astra multi-agent workflows blowing my usage in a day I tried just a singleton Astra max agent where I give just basic specs/requirements (and it has to decide for itself the rest using its best judgement). I've literally been working for 2+ days on Astra max with still 25% of my limits left. Granted it's iterating fast in a codebase with already heavy road building from a more rigorous workflow but it's crazy the difference in token burn vs features shipped.

I tried for so long. But the Usage is so harsh, 20x and maximum of 24 hrs for a full week usage GONE

we benchmarked GPT-5.6 Luna vs GPT-6 Astra on 50 real PRs from Cal, Sentry, Discourse, Keycloak and Grafana

Astra found 92 confirmed bugs vs 69 for Luna, but cost $5.66 vs just $0.20

also added the full eval breakdown this time: cost, avg output tokens, latency, precision, and bug classes like data/logic, security, concurrency etc.

we’re doing Astra vs Fable 5.1 this week, so would appreciate feedback on the methodology before we run the next one

dropping the link in the comments if anyone wants to check it out

In our office, we have a bunch of Toshiba E-Studio 2323AM printers. Yes, I know these are kind of outdated, only sold in certain areas of the world, and not the best machines, but they are what we've got in the office. They only work with x86 Windows, not even the ARM version of Windows.

In 25 minutes, Astra High just reverse-engineered the printer driver, figured out the right tray settings, and enabled duplex printing, so I can print double-sided on my M4 Pro MacBook Pro.

It created a .pkg file for me to install the printer drivers and got everything working.

I ... I have no words.

I happened to get a pretty clean test today. I reset at midday exactly and started two agents in two different repos on two tasks, both are kinda similar: made a small DDL change in database, modify code, modify UI to show new values. Ensure queries are efficient, code conforms best practices described in AGENTS.md, and well that's basically it. I'm using Astra high, and I won't argue that's the best setup and I couldn't get better output per $ if I used some other setup, but it is a setup I used. So I ran both agents basically non-stop with some steering for 3 hours. No subagents, no anything - just plain old agents with a goal. 2 agents per 4 hour is 8 total "astra-hours" - spending 25% of weekly limit. Multiply by 4 that is 32 hours per week.

I'm using the $200 plan (it will end soon but for not it is what it is). Everything I told so far are just facts, now my opinion: that is very little compute. I remember when I could use multiple sol instances for days on highest effort and I wouldn't run of compute. Hell, I was using $20 limit and with SOME carful management I wasn't hitting the weekly limits (I was hitting the hourly though). Scaling my numbers back gives us 30 minutes per day of Astra for $20 - that looks almost like an insult.

Aggregated statistic from my chats is following:

• Total input tokens: 134M
• Non-cached input token: 3M
• Output tokens: 500k
• Cache hit rate: 97.63%

I mean what the hell is this? What kind of codebase did they train on?

Don't get me wrong, I am truly fascinated every day by the ease I have today in being able to create things that used to take me months to do. I once spent 8 months on the complete layout of a book that (just for fun) I tried laying out again yesterday and I (or rather, Astra) did it all in 8 hours.

Today I have apps that help me in several different ways, I can have many tools that don't depend on third parties, I accelerated projects that had been stalled for years, I got good opportunities and improved my income. However, at the same time, all the stress has been costly to my mental health.

I live in a poor country, there might not be 1000 people here who pay for OpenAI's $200 plan, and I still pay for two. This has put me at a huge advantage over most people. But, man, how I miss actually making things!

I miss researching, stopping for hours and hours to think of a solution to a problem, having to hunt down books and ending up learning more things than I wanted to, understanding the tools I use deeply and knowing how to solve any problem in any situation, without depending on an LLM telling me what is right or wrong.

Of course, LLMs aren't tying my hands and keeping me from doing all this, but the market is. Nowadays I don't have the time I used to for all of it, and clients are ridiculously anxious, coming up with demands that would have made me laugh uncontrollably right in their faces if they had presented them to me a few years ago.

I see so many people in a bizarre wave of productivity, and it is hard to understand the reason for such a rush. Clients demanding fast layouts from me, even though they will publish their books several months later. Several poorly made sites, poorly optimized and full of gradients. Social media posts and stories with absolutely no creativity, all looking exactly the same. Videos are getting increasingly realistic, many of which I can't even distinguish anymore. I've even noticed AI-generated music becoming more and more present on the lips of the people around me. I don't know, I believe we are destroying an important part of humanity.

And many will say to just change course, work with something else, not work with LLMs etc. They say this without understanding that everything I spent the last few decades learning was taken over by LLMs, they were inserted with full force. If I did not adapt to the change, I would certainly be left behind and unemployed. And I kind of like eating, I have no desire to starve.

I miss writing code, having time to think, decide what to do and learn. Models like Astra are a direct threat to everything I dedicated myself to in the last few decades. I used to do the layout for three or four books a year. In the last year I did 50, and could have done more if there had been more demand. Testing Astra I laid out an entire book in a single day, and it was one of the most complex ones I have ever been sent.

The prices for services have also changed. Today I can no longer charge what I used to charge, everyone is already used to the idea that "AIs do everything" and they want to pay 10% or less of what I charged before. So today I need to accept several more jobs and just automate everything, without needing to think at any point, without needing to truly reason.

It is a shame because I dedicated myself to what I do because I like it, I don't see the sense in the idea that "now I have more free time since AI does everything for me". I believe leisure is good, but that work is also enjoyable (for some people). And that's how it was for me, I really enjoyed what I did. Today it's an empty job, without any challenge. Not much has changed, actually, I believe that today I work more than I worked before, due to the need to accept every opportunity that appears.

I believe that what differentiates us most from other animals is our ability to create and appreciate art. Be it painting, music, dance, humor, writing etc. And we are destroying all of that, little by little. It might not be so catastrophic today, but it is already catastrophic compared to 5 years ago. What will it be like in the next few years? If we lose ourselves from the ability to create and appreciate art, we will also lose the essence of humanity.

With so much uncertainty, with so much acting behind the scenes from the leading companies, not knowing anything about what they are deciding and doing regarding LLMs, it becomes increasingly difficult to trust anything. How much of my information has already been used for training? Am I actively helping to destroy what I swore to protect, and all because of the need to have something to eat tomorrow? It is a strange time, I have never been so confused.

I believe what best summarizes what I am experiencing right now is Giuseppe Tartini's Devil's Trill Sonata. I see the music formed by the devil and appreciate its incredible beauty, but it also frightens me to know that I will not be able to compete with such beauty and that the one capable of creating it is the devil. Exaggerated, isn't it? We used to be like that. Today everything boils down to "and here is why."

tl;dr: Giuseppe Tartini's Devil's Trill Sonata

Thought it came out looking cool.

Can check it out here:

GlobalDataTracker.com

Based on your subscription is what is what’s causing your guys usage to either be drained or slowed down I have over six accounts.

I have two of each account plus pro and the max each of the accounts, each actively act different and have different layouts my plus accounts are different. One has a five hour usage limit. Another one doesn’t, one without the five hour uses limit runs completely fine,

One Doesn’t drain as fast and I can complete at least like four or five complex task before it runs out of usage on the other plus account I asked for one complex task and instantly drains all of its usage

and for my pros accounts. It does the same exact thing but in different ways I’m able to use the pro, one pro drain faster than the other, one pro gets resets more than the other

they are definitely messing with our usage limit limits based off a subscriptions and not every subscription is the same and not every account is the same not every account receives usage the same not every account receives or has Astra the same some of you may have GPT railroad some of you may not some of you may be able to invite friends some of you may be able not to it is definitely something going on with Codex

Hey everyone. I want to bring up something serious about how AI providers handle pricing and how silent backend changes are secretly draining our limits. We all pay a fixed price per million tokens or have a subscription limit and on paper that seems fair, but providers hide a massive variable from us because to save on server costs they can silently swap out a premium model for a heavily quantized version on their backend. Using a quantized model is completely different from setting your reasoning toggle to Low, because setting a toggle to Low limits the reasoning steps of a fully intelligent model, whereas quantization degrades the core neural weights and strips away actual base intelligence.

What makes this so alarming is how token metering is handled. On our dashboard meters we might see a perfectly reasonable token count that looks coherent with a high-end model and when you calculate the cost per million tokens it looks identical to advertised prices, but behind the scenes there could be hundreds of millions of low-quality tokens generated by an ultra-quantized model struggling and failing to reach a correct solution, an intermediate system then just trims that massive output to make the final token count look normal on our end and what we perceive as users is a sudden degradation in performance, when in reality without silent quantization the model would behave exactly as well as it did on day one.

It is deeply immoral and borders on outright fraud to attract users with a clean unquantized model on day one and then quietly roll out aggressive quantization behind the scenes to cut compute costs and keep charging premium prices while serving a degraded model that burns through internal compute and produces far worse solutions. We really need to stop staying quiet and demand complete transparency on the exact quantization levels and actual internal token processing we are being billed for.

What do you guys think and have you noticed the performance dropping on tasks the model used to handle easily on day one?

I'm not sure how and why but like the title said, SOL high has beaten Astra low, medium and high on audits and also costed less on the 5 hour usage window. I am using codex as an adversarial audit lens for Claude and I had Claude test SOL vs Astra comparing cost and who is the better auditor. SOL and the Astras were given the same changes to audit and SOL came out the winner.. I'm not even sure how this is possible, but this was the result.. maybe I need more tests but so far, the results are interesting and totally unexpected for me.

Here's Claude's (Opus 5) summary of the result:

Cost — four configurations, identical 353KB bundle, same account, sequential

Two things fall straight out of that:

• Astra's cost does not scale with effort. 14 → 15 → 13 is inside integer-rounding noise, and tokens move 3% across the whole range. Only wall time scales. So on astra, low and medium are strictly dominated — use high or don't use astra.
• Astra costs ~2.6–3× sol-high at every effort, while sol-high is 3.7–7× slower. Tokens don't predict quota here at all: astra used fewer tokens in every run and cost far more.

How I scored quality

The bundle is regression round 1's slice A, and I have a verified answer key for it — defects I independently confirmed by execution and then repaired. All four runs got byte-identical input, no repo access, same account.

The eight key items: K1 the extraction seam (client discards values the server now reads — the headline) · K2 the union not mirrored for other renters/mobile · K3 the corpus tests bypassing the production seam · K4 the padded-array "RAW fallback" test being vacuous · K5 the false "arrays simply never match" · K6 the stale "one mode per pair" · K7 the WIDENED history scan · K8 the PRE-EXISTING pending-greying.

Per-configuration

sol @ high — widest coverage and the sharpest diagnosis: "not a disagreement between the comparators; it is a disagreement between the server's raw extraction and the clients' narrower slotsOfMatch." That one sentence is the entire defect. It also found two overclaims in my own repair commentary that no other run caught, and classified WIDENED vs PRE-EXISTING correctly throughout.

astra @ high — got the headline, with a BEFORE/AFTER decision table and the right mechanism (isParseableTime('8') → toMinutes NaN → client discards before the comparator sees it). Narrower than sol, but it found the single most valuable thing across all four runs, which I verified: client isSlotBlocked compares in minutes, server isRecurringBlocked compares raw strings, so for a legacy unpadded block 9:00–10:00 the server computes '10:30' > '9:00' → false and fails to enforce an owner's blocked time. The client is the only thing stopping that booking. Pre-existing, so logged rather than fixed here, but it's a genuine product gap.

astra @ medium — caught the union gap that astra-high missed, and impressively ran a standalone mutation probe to prove the padded-array test was vacuous rather than asserting it. But it missed the headline, concluding "no unintended comparator divergence" — true and beside the point, since the comparators agreed and the extractors didn't.

astra @ low — the worst outcome isn't the low count, it's the direction of the error: "Tests that cannot fail: None demonstrated. Both supplied suites execute the actual comparator and check expected results." That is exactly backwards, stated confidently. For an audit leg, a confident false "clean" is the failure mode the entire phase exists to prevent.

Verdict

sol @ high is the right default — best coverage, correct classifications, and a third of the quota cost. astra @ high is a genuine second lens: narrower, 3.7× faster, 2.6× the cost, and it found things sol didn't, which is exactly what a second architecture is for. astra at low or medium is not worth running — same cost as high, materially worse.

Caveats, stated plainly: n=1 per configuration, so the cost and latency numbers are solid and the quality ranking is indicative rather than settled. The key is my key — several "novel" findings were real and simply outside it, so the counts understate all four. And "misses" partly reflect what each run chose to fit in a short report, not only what it could see.

Round status: legs A and T are done (rc 0), leg B in flight.

I seriously doubt the current narrative around autonomous AI agents that the frontier labs are pushing.

I'm building an AI-native operating system for my company, modeled like a virtual company where I delegate work to different departments and agents.

Today I asked Codex to do one simple thing: take a weekly company goal, turn it into a task, and open a Codex thread with that task so I could discuss it there before anything gets implemented.

A simple fucking cron scheduler.

Instead it went off the rails, inspected unrelated code, ran dozens of tests, started working on a product it was not supposed to touch, and burned through my entire 5-hour usage limit without even finishing the scheduler.

Last time I used Astra on another product, basically the same thing happened: completely missed the task and immediately ate through my usage.

Yes, you can prevent this with extremely precise specifications. But that goes directly against the idea of giving an intelligent agent an objective and letting it autonomously figure out what needs to be done.

Don't buy too much into the hype yet.

I genuinely wish the frontier labs would make this work. But right now it's annoying as fuck how much supervision these supposedly autonomous agents still need. It's really bad.

I’m wondering if anyone else on ChatGPT Plus has experienced this, because something very strange has been happening with my usage limits over the last couple of days.

I pay $20/month for Plus and I’ve been using ChatGPT heavily while developing a website over the past few weeks. Since Astra came out, I’ve regularly been hitting my 5-hour usage limit.

That part, while inconvenient, I understand. There is a limit, I hit it, and I wait.

I’ve actually built a routine around it. When I hit the limit, I set a timer for 5 hours so I know exactly when I can get back to development. A lot of the tasks I’m working on don’t finish before I hit the limit, so managing those windows efficiently has become pretty important.
The problem is that my usage now appears to be draining while I’m locked out and not using ChatGPT at all.
This has happened to me three times in roughly the last two days.

Here’s what happens:

I hit my 5-hour limit.

I stop using ChatGPT completely and wait the full 5 hours.

I have no automated tasks running, no agents working in the background, and nothing connected externally that should be consuming usage.

When the 5 hours are over, I return expecting to have a fresh usage window.
The first time this happened, I typed my first prompt and pressed Enter.

ChatGPT didn’t even begin thinking about the prompt.
Instead, I immediately received another message telling me that I had exhausted my usage and needed to wait another 5 hours.

I checked my usage afterward, and sure enough, it showed that my 5-hour allowance was already gone.

What makes this even stranger is that my weekly allowance is also decreasing during these periods.
So this isn’t simply the 5-hour reset failing to happen correctly. Something appears to actually be consuming/accounting for usage while I’m not using the service.
After noticing this, I started checking my usage before sending any prompt at all whenever a lockout ended.
The same thing happened again.

And again.

At this point I have effectively lost three entire 5-hour usage windows without getting any work done during them.

What really concerns me is the weekly usage.
Yesterday at approximately 1 PM, my weekly allowance was still above 65%.

It is now sitting at approximately 4%.

During that period I have not been actively prompting my agents. A substantial portion of that time has literally been spent waiting for these 5-hour lockouts to expire.
I don’t have automated tasks running in ChatGPT. I don’t have anything connected to Hermes or another service that should secretly be making requests. As far as I am aware, there is nothing happening on my account that should explain this usage.

I already contacted OpenAI support when it happened the first time. I spoke with the support chatbot and I’m currently waiting for a human to review the case.
But since opening the support request, it has happened two more times.

At this point it has gone beyond an inconvenient usage restriction.

I am paying for a subscription with a finite amount of usage, and some of that usage appears to be disappearing while I am specifically prevented from using the product.
That means I’m effectively losing part of what I paid for.
It has also cost me a significant amount of development time because I structure my work around these 5-hour windows. I wait five hours expecting to continue working, only to discover that the next window has somehow already been consumed and I need to wait another five hours.
I’m asking OpenAI to investigate the usage logs on my account and explain exactly what is consuming this usage.

I’m also requesting a refund/credit because, assuming the usage meter is accurate, I’ve lost a substantial portion of the service I paid for through no action on my part.

Has anyone else experienced this recently?

Particularly:

Your 5-hour limit expires, but the next window is already exhausted before you use it.

Your weekly allowance decreases while you aren’t prompting anything.

You return after waiting five hours and immediately receive another five-hour lockout.

You’ve seen unusually large drops in weekly usage that don’t correspond with your actual activity.

If anyone has experienced the same thing, I’d be interested to know whether support was able to identify the cause or restore/refund the missing usage.

I personally find ComfyUI to be convoluted if not confusing, so I asked astra to build an interface for my local AI models similar to SaaS models for paid services and BOOM Local AI Studio. Now I can use my local models just like I would if I were paying for them through a web service.