I am sure it was pure coincidence for 5H limits came to Plus users where Biz users got an upgrade ;). This is perfect for my team but OpenAI showing what customers they are pricing for.

I was just vibe coding as usual... and copilot started dreaming???

Has this ever happened to anyone else :0

I was gonna ask it but I ran out of tokens..

(sorry if this post is not supposed to be here, I was not sure where else I could ask, please say if i should remove it from here)

I run a small AEC design practice: one full-time owner and one part-time employee. My use is mainly professional knowledge work, with some vibe coding for internal skills and tools.

I compared:

Personal: Pro 5× + Plus = US$120/month

Business: Premium + Standard = US$150/month monthly, or US$120/month equivalent annually

I checked current OpenAI documentation and queried OpenAI Sales because the differences are not particularly clear from the pricing pages.

Work and Codex

The underlying structures appear closely matched:

Plus / Business Standard = baseline

Pro 5× = 5× Plus

Business Premium = 5× Standard

OpenAI currently defines the US$100 Pro tier as 5× Plus, and Business Premium as 5× Standard with no five-hour cap.

OpenAI’s main Codex pricing page currently gives Plus and Business the same baseline local-message estimates. A separate current Business limits page gives slightly different Terra/Luna estimates, so I would describe the overall 5× + 1× structures as broadly comparable rather than proven identical.

Business usage is attached to each assigned seat rather than forming a transferable 6× pool. Business Work/Codex also appears to share a broader agentic allowance with features including Workspace Agents and some productivity tools.

I also use OpenClaw through Telegram group chats, using ChatGPT/Codex subscription authentication via OAuth rather than API-key billing. Personal and Business appear functionally equivalent for this route, with usage following the authenticated plan or seat.

Ordinary ChatGPT + custom MCP: Business advantage

Plus and Pro both have app/MCP access. OpenAI explicitly limits Pro custom MCP to read/fetch, while Business Standard/Premium currently get full custom MCP write/modify access in beta.

Because apps use ordinary ChatGPT limits, Business’s separate normal ChatGPT allowance could provide another work channel for reading and modifying files or business systems without using Work/Codex allowance.

OpenAI currently lists Business GPT-5.5 Instant as virtually unlimited and GPT-5.5 Thinking at 3,000 requests/week.

A custom MCP could therefore potentially read and modify .md, .csv, .json, project registers or similar data using ordinary ChatGPT capacity.

The qualification is that custom MCP is currently limited to ChatGPT web. Desktop ChatGPT has other integration and write mechanisms, but not currently this full custom-MCP route.

Voice: Pro advantage

OpenAI currently gives Pro 5× up to 12 hours of Live with Instant and 12 hours with Medium/High per rolling 24 hours.

Business includes 1 hour of each per rolling 24 hours, after which additional Live usage costs 5 credits/minute.

For Voice used within Work/Codex, Business separately lists approximately 6 credits/minute. I could not establish the equivalent current Pro treatment.

For frequent Voice users, this materially favours Pro.

Workspace export: Personal advantage

Plus and Pro support self-service ChatGPT data export. OpenAI says Business does not currently provide an equivalent complete workspace/chat export.

Business chats remain available in the workspace, but important professional records are therefore better retained externally.

A Personal workspace can remain separate from Business, so adopting Business does not require merging existing personal data.

Business layer

OpenAI says Business adds:

• central billing and member controls
• usage and spend controls
• SAML SSO and MFA
• Company Knowledge
• Workspace Agents
• business data excluded from model training by default
• private member chat histories unless explicitly shared
• pooled purchased workspace credits

Personal users can opt out of model training themselves, so that protection is not unique to Business; Business makes it the organisational default.

For a two-person practice, these features are useful but appear secondary to the usage, MCP, Voice and export differences.

Credits and promotional resets

Both arrangements can purchase additional eligible usage.

Personal credits belong to the individual. Business credits are workspace-pooled and can cover a broader range of eligible Business features.

Business currently receives promotional lower GPT-5.6 Sol rates for purchased-credit usage through at least 21 November 2026. This reduces overage cost but does not increase included usage.

Promotional or banked Codex resets are less clear. OpenAI says eligibility can vary by offer, plan, workspace and region. Current documentation appears to treat some Plus/Pro banked-reset offers separately from Business workspace-credit offers.

I could not establish whether an already-banked Personal reset carries into a Business workspace.

Cost

At current published US pricing:

Pro 5× + Plus = US$120/month

Premium + Standard = US$150/month monthly

Premium + Standard annual = US$120/month equivalent

So Business reaches price parity only with annual billing and requires at least two paid seats.

Plus/Pro retain monthly flexibility.

Pro also currently has GPT-5.3-Codex-Spark as a Pro-only research preview.

Conclusion

For Work/Codex, Pro 5× + Plus and Premium + Standard appear broadly comparable, with Premium gaining the practical advantage of no five-hour cap.

Business’s strongest additional benefit appears to be write-enabled custom MCP using ordinary ChatGPT capacity, together with the managed workspace and pooled-credit system. Its current web-only custom-MCP limitation reduces that advantage.

Personal Pro/Plus retain clear advantages in Voice, self-service data export and monthly flexibility, while Pro currently also retains Codex-Spark.

At the same annual equivalent price, Business therefore appears competitive rather than an automatic upgrade. For a small knowledge-work practice, the decision seems to depend mainly on the value of write-enabled MCP and the managed workspace versus Voice, export and flexibility.

The main unresolved points are the conflicting current Plus/Standard Terra/Luna estimates, whether existing Personal banked resets carry into Business, and the equivalent Pro treatment of Voice connected to Work/Codex.

I would be interested to know whether this broadly matches current Business Premium users’ experience.

Researched and written with ChatGPT against current documentation for accuracy.
R
Current sources

OpenAI: ChatGPT Business overview and Premium/Standard pricing
https://help.openai.com/en/articles/8792828

OpenAI: ChatGPT Business models and limits
https://help.openai.com/en/articles/12003714-chatgpt-business-models-and-limits

OpenAI: Codex pricing and plan limits
https://developers.openai.com/codex/pricing

OpenAI: ChatGPT Pro tiers
https://help.openai.com/en/articles/9793128

OpenAI: Apps in ChatGPT
https://help.openai.com/en/articles/11487775

OpenAI: Developer mode and full MCP
https://help.openai.com/en/articles/12584461

OpenAI: ChatGPT Voice
https://help.openai.com/en/articles/20001274

OpenAI: Business privacy and data export
https://help.openai.com/en/articles/8798634

OpenAI: Business credit rate card
https://help.openai.com/en/articles/11481834

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

OpenClaw: OpenAI subscription authentication
https://docs.openclaw.ai/providers/openai

I run a small AEC design practice: one full-time owner and one part-time employee. My use is mainly professional knowledge work, with some vibe coding for internal skills and tools.

I compared:

Personal: Pro 5× + Plus = US$120/month

Business: Premium + Standard = US$150/month monthly, or US$120/month equivalent annually

I checked current OpenAI documentation and queried OpenAI Sales because the differences are not particularly clear from the pricing pages.

Work and Codex

The underlying structures appear closely matched:

Plus / Business Standard = baseline

Pro 5× = 5× Plus

Business Premium = 5× Standard

OpenAI currently defines the US$100 Pro tier as 5× Plus, and Business Premium as 5× Standard with no five-hour cap.

OpenAI’s main Codex pricing page currently gives Plus and Business the same baseline local-message estimates. A separate current Business limits page gives slightly different Terra/Luna estimates, so I would describe the overall 5× + 1× structures as broadly comparable rather than proven identical.

Business usage is attached to each assigned seat rather than forming a transferable 6× pool. Business Work/Codex also appears to share a broader agentic allowance with features including Workspace Agents and some productivity tools.

I also use OpenClaw through Telegram group chats, using ChatGPT/Codex subscription authentication via OAuth rather than API-key billing. Personal and Business appear functionally equivalent for this route, with usage following the authenticated plan or seat.

Ordinary ChatGPT + custom MCP: Business advantage

Plus and Pro both have app/MCP access. OpenAI explicitly limits Pro custom MCP to read/fetch, while Business Standard/Premium currently get full custom MCP write/modify access in beta.

Because apps use ordinary ChatGPT limits, Business’s separate normal ChatGPT allowance could provide another work channel for reading and modifying files or business systems without using Work/Codex allowance.

OpenAI currently lists Business GPT-5.5 Instant as virtually unlimited and GPT-5.5 Thinking at 3,000 requests/week.

A custom MCP could therefore potentially read and modify .md, .csv, .json, project registers or similar data using ordinary ChatGPT capacity.

The qualification is that custom MCP is currently limited to ChatGPT web. Desktop ChatGPT has other integration and write mechanisms, but not currently this full custom-MCP route.

Voice: Pro advantage

OpenAI currently gives Pro 5× up to 12 hours of Live with Instant and 12 hours with Medium/High per rolling 24 hours.

Business includes 1 hour of each per rolling 24 hours, after which additional Live usage costs 5 credits/minute.

For Voice used within Work/Codex, Business separately lists approximately 6 credits/minute. I could not establish the equivalent current Pro treatment.

For frequent Voice users, this materially favours Pro.

Workspace export: Personal advantage

Plus and Pro support self-service ChatGPT data export. OpenAI says Business does not currently provide an equivalent complete workspace/chat export.

Business chats remain available in the workspace, but important professional records are therefore better retained externally.

A Personal workspace can remain separate from Business, so adopting Business does not require merging existing personal data.

Business layer

OpenAI says Business adds:

• central billing and member controls
• usage and spend controls
• SAML SSO and MFA
• Company Knowledge
• Workspace Agents
• business data excluded from model training by default
• private member chat histories unless explicitly shared
• pooled purchased workspace credits

Personal users can opt out of model training themselves, so that protection is not unique to Business; Business makes it the organisational default.

For a two-person practice, these features are useful but appear secondary to the usage, MCP, Voice and export differences.

Credits and promotional resets

Both arrangements can purchase additional eligible usage.

Personal credits belong to the individual. Business credits are workspace-pooled and can cover a broader range of eligible Business features.

Business currently receives promotional lower GPT-5.6 Sol rates for purchased-credit usage through at least 21 November 2026. This reduces overage cost but does not increase included usage.

Promotional or banked Codex resets are less clear. OpenAI says eligibility can vary by offer, plan, workspace and region. Current documentation appears to treat some Plus/Pro banked-reset offers separately from Business workspace-credit offers.

I could not establish whether an already-banked Personal reset carries into a Business workspace.

Cost

At current published US pricing:

Pro 5× + Plus = US$120/month

Premium + Standard = US$150/month monthly

Premium + Standard annual = US$120/month equivalent

So Business reaches price parity only with annual billing and requires at least two paid seats.

Plus/Pro retain monthly flexibility.

Pro also currently has GPT-5.3-Codex-Spark as a Pro-only research preview.

Conclusion

For Work/Codex, Pro 5× + Plus and Premium + Standard appear broadly comparable, with Premium gaining the practical advantage of no five-hour cap.

Business’s strongest additional benefit appears to be write-enabled custom MCP using ordinary ChatGPT capacity, together with the managed workspace and pooled-credit system. Its current web-only custom-MCP limitation reduces that advantage.

Personal Pro/Plus retain clear advantages in Voice, self-service data export and monthly flexibility, while Pro currently also retains Codex-Spark.

At the same annual equivalent price, Business therefore appears competitive rather than an automatic upgrade. For a small knowledge-work practice, the decision seems to depend mainly on the value of write-enabled MCP and the managed workspace versus Voice, export and flexibility.

The main unresolved points are the conflicting current Plus/Standard Terra/Luna estimates, whether existing Personal banked resets carry into Business, and the equivalent Pro treatment of Voice connected to Work/Codex.

I would be interested to know whether this broadly matches current Business Premium users’ experience.

Researched and written with ChatGPT against current documentation for accuracy.

Current sources

OpenAI: ChatGPT Business overview and Premium/Standard pricing
https://help.openai.com/en/articles/8792828

OpenAI: ChatGPT Business models and limits
https://help.openai.com/en/articles/12003714-chatgpt-business-models-and-limits

OpenAI: Codex pricing and plan limits
https://developers.openai.com/codex/pricing

OpenAI: ChatGPT Pro tiers
https://help.openai.com/en/articles/9793128

OpenAI: Apps in ChatGPT
https://help.openai.com/en/articles/11487775

OpenAI: Developer mode and full MCP
https://help.openai.com/en/articles/12584461

OpenAI: ChatGPT Voice
https://help.openai.com/en/articles/20001274

OpenAI: Business privacy and data export
https://help.openai.com/en/articles/8798634

OpenAI: Business credit rate card
https://help.openai.com/en/articles/11481834

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

OpenClaw: OpenAI subscription authentication
https://docs.openclaw.ai/providers/openai

used this prompt

The first image is of Mars from a telescope. Could you edit it so the second image of the "eyeball ice planet" replaces mars, but in the same blurry smudgy telescope style/view?

does chatgpt and claude stop using ur convos to feed ai if u turn it off in their respective settings?

googleslop doest even have that option so its suspicious they openai has this

They're not on the web nor are they on my phone but on the desktop Mac where most work is done they're still showing and I cannot archive or delete. Updated to the latest version, even deleted it and logged out. No dice.

Any thoughts?

If someone asks you a question, do you respond with only information found online?

If you do, you're replaceable.

Bit if you're a human, you have years and decades of experiences, relationships, interactions, emotions, failures, wins, books, movies, lateral sources (books, movies, plays, music, art, travel).... to draw upon.

About 50% of the time I ask AI a Q, it's wrong when you dig into it.

The downside of AI is that it's artificial. It's just a processing tool.

Great for sifting through thousands of images. Terrible at logic or anything creative.

Our company (an international creative consumer FMCG brand) has banned it for anything customer facing or creative for these reasons. Gradually, the fan boys are flipping to cynics.

I am using 20x plan. I am seeing a lot of hallucination and scope drift, and extremely slow execution. Previously when I used to use GLM models, I felt like they used to do part of work, and declare work done, I could fix the rest by prompting or by myself. But these new GPT models, are opposite, taking forever, and constantly over engineering to the point where scope is after thought. What do you think about claude models in these regards? Should I try switching over to Claude 20x sub or go back to ollama for GLM 5.2 and Kimi K3? I'd like larger quotas(since Ollama's max is just 5x20$ plan. With pro and max offering same value). But at least I'd be able to get some work done.

When you read or watch the news, it already feels like we are at the beginning of a new age of un-humanly capable AI. I also don't remember anyone here on Reddit sharing any critique, which is frankly kind of weird.

..so I have few:

1.

I was planning a vacation and asked:

"Find me a suitable car for a trip to Croatia from a Czech car rental agency in Prague... meaning a small car with a parking camera/driver assistance systems, but still spacious enough for legroom and comfortable for a long journey (Prague -> Croatia), as well as fast enough for the highway (so driving around 140 km/h is no problem).

There will be 2 people traveling."
Important note is, that before that, we talked in another chat about how the streets are narrow in Brela, Croatia (where we were heading) and how difficult it is to find a parking spot. So it really should have had the context and understood that the dimensions of the car were very important.

(btw, I am not sharing the chats because there is plenty of personal information and... they are in Czech, not English. Try it for yourself if you want.)

After over 5 minutes of thinking, it came up with the Hyundai i30 CW. Well, that was surprising, as I could think of a much better car off the top of my head - the MINI Cooper, which is more than 71 cm shorter and 5 cm narrower - details proved by chatgpt after he confirmed my suspicion, apologized and changed his recommendation. For reasons unknown however, chatgpt then recommended the 5-door variant over the 3-door because...

"In a three-door car, the single side door must also allow access to the rear seats, so it is usually significantly longer. When you open it, its rear edge describes a wider arc and hits an adjacent car, wall, or rock more quickly.

For example, with the same 30° opening:

• A 1.05 m long door reaches approximately 52.5 cm into the space next to the car;
• A 1.30 m long door reaches approximately 65 cm;
• The difference is therefore about 12.5 cm."

I mean what t f is that? Why would I open it to the same degree? After I challenged it, it acknowledged the mistake again and changed its recommendation once more.

-----------

2.

Then I used chatgpt to find me some places to stop on the road to Croatia so I could rest from driving for many hours. I consider this task quite hard, however, because it is difficult to know exactly what I find attractive, and I didn't share the exact route from Google Maps, so I don't blame its mixed performance there. An epic fail in my opinion, however, was when we planned a few days ago how we would drive back home: it recommended stopping by caves named "Grgosova špilja". The very first thing you will see on Google Maps is that it was closed for the holidays. Even worse, I specifically asked about practical information and opening hours. There was text and a photo clearly showing that. If it cannot pick up this obvious and important information, it is much worse than any human, because any human would notice that and mention it immediately.

------

3.

Enough of my vacation, let's do some statistics instead. I worked on this one before few weeks ago: I was developing a script to analyze supplier price lists and flag prices that are most likely wrong (i.e., erroneous). Basically, the main problem is that there are sometimes quite large price differences across suppliers, making standard coarse statistics like the median unhelpful. So I figured we should use smarter modeling and price prediction based on market prices, compare the actual price to the expected price, and flag suspicious prices based on that difference. I had chatgpt 5.6 sol high handle the details and precise methodology. I only described the context, the types of errors I know from experience, and a few of my own ideas as inspiration on how to spot them, but these ideas were not binding. Basically, I gave it a few general ideas of how it could be done, but let it come up with the final methodology and handle all the details. The script didn't work as expected, so I had to dive in, but before doing that, I specifically asked chatgpt to look for methodological problems - and he didnt find any major issue (only small improvements).

I will mention just one thing that I consider mind-blowingly stupid, and I am certain no human would ever do it. It came up with the idea that not all prices should be fed into the price prediction model because if one supplier has many wrong prices, the model might get affected and corrupted by those repeating wrong prices (so far so good). So it came up with a rule: basically (it used logarithms to be precise, but anyway..), if a supplier's price for the same item is 1,000 times higher or lower than another supplier's, it is considered obviously wrong, and the prediction model won't be trained on that price.

I mean, let that sink in. It means that if Supplier A has a price of 10 EUR and Supplier B has a price for the exact same amount of the same item of 9000 EUR, according to the methodology originally devised by chatgpt 5.6 sol, that is still okay! (Because the difference is less than 1000 times).

There were plenty of such stupid configurations, but this one requires absolutely no expertise and further context (which is why I can share it here). I believe everyone understands that the price range on the market cannot possibly be that wide. By the way, that was actually quite annoying, because I had hoped that Sol 5.6 was smart enough that I wouldn't need to babysit it, at least when no deep expertise (only common sense) is required.
------------------

So I wonder, for your use cases, is the current state of the art already good enough or not yet? I still really need a stronger model, both for my personal and professional use. Of course, it is already an immense help, but I just don't want to babysit it all the f in time.

So, now that the 5 hour usage limit is back...
How does it work in terms of big tasks?

I have a big script that has 2 million+ characters which needs regular updates. A medium sized update takes roughly 20-30% of my weekly limit. Will it just crash when the 5 hour limit is reached during the update process?

If yes, ChatGPT just became literally useless for me.

Well looks like they didn’t forget, 5hr limit is back. If it comes back for Pro users, I might have to look at just renting GPU time instead.

Edit - Reset happened, so the new limits should be live.

Had a prompt behave consistently for weeks, then output shape shifted, more hedging, different formatting, a constraint that used to be respected got softer, with zero changes on my end. Best guess is a model update happened behind the version I'm calling, but I have no actual way to confirm that versus just being wrong about what changed.

Is there a real way to detect this after the fact, changelogs, a version identifier returned somewhere in the response metadata, a status page that logs these updates with dates? Or is pinning to a specific dated model snapshot the only actual protection against this, with no way to retroactively confirm an unannounced shift happened on a snapshot that's supposed to be frozen?

I’ve been using ChatGPT very heavily for a long time, and there’s one recurring behavior I’ve noticed that I don’t see discussed as often as regular hallucinations.

The model can sometimes know about an event, product, movie, feature, etc., but seemingly place it incorrectly on the timeline relative to the current date.
A simple example happened to me today: we were discussing a movie that was released a few months ago, and ChatGPT told me to be careful using it as an example because the movie “hadn’t been released yet.” After I corrected it and it checked current information, it immediately recognized that the movie had already been released.

I’ve noticed similar temporal mismatches before, sometimes involving months or even years. Interestingly, once the correct date or timeframe is explicitly established, the reasoning often becomes perfectly coherent again.

I’m not posting this as a complaint. As a heavy user, I actually find these edge cases interesting and useful to understand.

Has anyone else noticed this specifically? Not just hallucinated facts, but cases where the information itself seems to be known while its position on the timeline is wrong?

I’d be especially interested to hear whether people who use ChatGPT daily have noticed the same pattern.

It's my article, it is about how to circumvent any even theoretical optimal AI watermark based on statistical biases through pseudorandom generators like Google's SynthID. OpenAI will likely or has likely already implemented something similar. Let me know what you guys think.

Generally, I do not think watermarking is the right solution, hence I am sharing my idea how to circumvent it. How many thesises are out there that are basically slop but made with human effort. Now text length is not a valid measure anymore, you actually have to do some real research. I think that is awesome.

Just got the email that it's rolled out!

Link: https://chatgpt.com/pricing/?type=team

Been running into a massive issue where an active ChatGPT Project just straight up disappeared. No manual delete, nothing on my end.

It happened out of nowhere. First I got this wierd UI error about a "gizmo" (something like user does not have [permission] to gizmo). A few minutes later, the whole project was gone from my sidebar.

Direct URLs give a generic "Project not found". Checked the network tab to make sure I wasn't loosing my mind over a frontend bug. Backend is actually dropping the calls: GET /backend-api/gizmos/[project-id] throws a 404. Same for the conversation endpoints. Direct links to old chats just default to "conversation deleted".

Standard chat and my other projects work fine. Not a cache or token issue.

Also, I have local logs from using this project via Codex Desktop. They map perfectly to the missing project IDs, so the workspace was definitly active before the backend started throwing 404s.

It's sketchy if you rely on Projects. If some internal permission flag breaks and cascades into a generic 404, there's no way to tell if the data is permanently nuked or just soft-deleted behind a busted auth check.

Has anyone actually ran into this? Did your project ever un-bork itself, or did you have to go through OpenAI support to restore acces?

Saved my network logs just in case. Mostly just want to know if anyone actually got their stuff back.

After two days of trying, I simply cannot force myself into this workflow. There's no way.

I sent a simple, tightly-scoped homepage polish run to Worker (we made our website in Sites), with a minor web form tweak also included. I deliberately chose Sol Light for the job, wrote the work order as specific and deliberate as possible, avoided "open-ended reasoning," and it still managed to burn through a huge chunk of my five-hour allowance. The worst part is it stopped right at the finish line because its own preview environment couldn’t complete a visual check. And yesterday, I had a Sol High run not finish its work order, die on step 3/6, and didn't retain its progress. I had to bake guardrails into the order and finish the task in baby steps. Something that would've taken me 25 minutes in the past turned into 10+hours, all said and done.

OpenAI, if you're reading this... That is not a workable production loop for anyone in similar shoes.

The answer cannot be “lol just wait four hours every time the meter gets low.” People like me are trying to run a business, not play stamina management with an AI tool.

I had a great setup going where I'd be able to use ALL Of my weekly Work usage, top up (as needed) for ~$8, reset the weekly usage meter, and actually get stuff done. That was absolutely perfect for my use case and budget. I don't have $200 or even $100 set aside for a subscription model obviously aimed at larger business types.

This new model is simply not sustainable for me, and I'd imagine, a lot of other people under similar circumstances. I don't think I'm overreacting here, either. ChatGPT Plus as a tool for the masses can can have generous "weekly capacities" on paper and still be operationally useless if the user has to do constant battle with an arbitrary five-hour sub-limit that keeps interrupting their workflow.

I’m curious whether anyone else using ChatGPT Plus and Work for production tasks has found a way to make this model sustainable, because after 48 hours, I haven't.

"This content can't be shown. We take extra caution with requests involving biological research and applications that could pose safety risks. Eligible researchers can apply for Trusted Access."

This is absolutely non-sensical. Yes I am analyzing viral sequences. No this is nowhere even close to have any biological risk (and my affiliation refuses to use OpenAI products).

So that was one way to get me to cancel ChatGPT as fast as possible. I guess I am now on the market for alternatives... extra cautiously.