My chatgpt pro account gave me 62k of their "credits" which they try to sell you at extortionate rates when your subscription runs out. I spent two days hammering it and used about 4k of those.
This is clear manipulation to prevent me from complaining about lower limits until it's out of the news cycle, but I don't care. As soon as those are gone, if my $200 account doesn't give me the value it used to, I'm out.
The random resets are also clear manipulation in this regard as well. Rather than just give me a fixed weekly limit which I could then get a sense of and know if it's getting reduced, they throw out a ~0-3 resets a week at random, unexpected intervals so that I'll never know.
I would pivot to a Chinese provider via open router so fast... Most months on glm or DeepSeek it would be a challenge to spend $100. But now I mostly use local models... Sounds obnoxious bouncing between 2 companies who rug pull their customers every 4 months and degrade service as a form of advertising...
Do you have beefy hardware? i dream of using a local LLM, but neither my 24GB RAM M4 Air nor my PC with a RTX3080 and 16GB of RAM seem usable (yet).
i could label them usable if "prompt it and then wait for 6 minutes for it to change a single line" is deemed usable, which i don't.
spent the last weekend in a rabbit-hole of which models to use in what kind of setup, but i think with my hardware i'm just out of luck for now.
for private matters I can use Cloud AIs, but not allowed to use it for work-related matters, which is where i could use it the most. they do provide us an isolated AI environment where we can use Claude etc. for work stuff, but heavily rated (about 20 prompts per week per Claude model).
> subscription gross margins are way lower than API and meaningfully reduce revenue per MW for both OpenAI and Anthropic
I don't know about everyone else, but there is no way in hell I would pay even $200 for API-priced tokens for personal use. So at least for my sample size of one, Anthropic's revenue would not be higher if they dropped their subscription plan (they would get $0 from me instead of $200 per month).
I’m not everyone else but I am SOMEBODY else and you’re absolutely right. I was paying for Claude since they first offered subscriptions, right up until this summer.
I respect Anthropic (and OpenAI to a lesser extent) but I’m not going to play these games.
Local ai can be about as capable as anything you get a subscription for. The benefit to local beyond a lot of other things is, no model degradation, and stationary costs. Actually, you get effectively free model upgrades.
For 2-4k you can have opus 4.8 at home running faster than anthropic. In 8-20 months you have broke more than even.
I think for almost anyone it's worth trying. Especially if you already have hardware.
$4k doesn’t even buy you a DGX spark these days. You can get a Ryzen AI max 128GB machine for a bit less than $4k but the models you can run on there aren’t even close to Opus 4.8.
I exclusively pay for API tokens. This is the primary way I consume these models.
The flat monthly subscriptions seem too tempting for the providers to screw with. I prefer to paygo and to be responsible with my consumption. I also want the ability to scale substantially beyond what a typical consumer plan may offer on occasion.
My monthly usage ranges from $10-$1000. I don't have to worry about quotas or anything. If I need to use several thousand dollars worth of tokens, I can just pull out the Amex and everything works. It's constant performance all day every day. I have long since maxed out my org level with OAI, so it would be very difficult to exceed any realistic limits.
Spending 5/10 months equiv of subscription cost that have significantly lower revenue for X company (or even costs money) when 1 week of $200 subscription gets you $800~$1200 sure is something.
> Token efficiency is also an extremely relevant factor, but the industry unfortunately lacks reliable data here. Many people like to cite this chart from Artificial Analysis, but we do not believe the benchmark tasks in the AA Intelligence Index are at all representative of real work people do with LLMs.
Right, so they just ignore the fact that different models use very different number of tokens to achieve the same thing. Ignoring that means they can't say anything about "value". This is like comparing numbers with different units. They're Atokens and Otokens.
Hmm I'm not sure this is really the case I have the pro level of each, and GPT 6.1 Sol feels virtually unlimited to me atm, doesnt feel the same with opus and its probably only a few percentage points better and not in all situations.
The title is misleading: by token count, it’s only 3× more valuable.
And there’s also a major error in the calculation: it doesn’t account for the “generous” resets that are mentioned at the beginning of the article!
Taking the 1 to 2 weekly resets into account and comparing tokens, the ChatGPT Pro 200 plan works out to be between 1.2× and 1.7× more cost-effective per token than Claude’s for Astra/Fable, while for Sol/Opus it’s more like 0.7× to 1.04× as valuable.
However, this also doesn’t take into account the fact that, as another commenter pointed out, GPT-6.1 Sol currently uses fewer tokens to perform the same task (according to that comment, 5× fewer tokens, but I haven’t verified those numbers).
My figures are very rough, but the conclusion in the title is clearly false and clickbait. I get the impression that OpenAI offers better value for now, even if that means we’re relying on those “generous” resets continuing to happen.
I’d agree if Claude’s limits weren’t changing and getting lower month after month. For now, neither one is profitable for their lab, and I don’t find their plans very predictable.
> I want a predictable LLM inference subscription, not a gacha game.
The only way we get to predictability is by paying what subscriptions are actually worth, and this entire game hinges on the fast that AI companies are not convinced that most people are willing to pay the 3-5x (or however much it is) multiple on what these accounts actually cost to run.
It's an advertisement. Just like 90% of the AI posts on here and all of social media. I bet it's less than 3x in reality too. Especially once anthropic needs to become profitable for their IPO...
I have both, 6.1 sol is no where near 5x more efficient then opus in day2day. Without numbers i would not even entertain that though and with numbers i would look closly if its the same code. I put it to work on the same repo so i have somewhat of a comparison. Not to mention that opus 5.5 is way better in most of the tasks. Currently openai gives you less for worse idk how did they think that could work.
One of their three identical accounts had ~20% lower limits and the explanation was an "extremely tiny" A/B test. Makes the "5x" kind of a joke. I'd honestly take a slightly worse plan if it just published the actual token limits.
They would never do this because it would allow customers to see how often and to what degree they're shifting account limits. Token transparency costs extra, full API price to be exact.
Somewhat tuning out these "X is better than Y" news and articles, as things are still moving quite fast. In a few weeks, OpenAI offers more value for money and the cycle repeats again.
As a Claude subscriber, I am quite enjoying the value I get from Anthropic. But I am not forgetting that this is their loss leader, and API access is still their main driver. So strike while things are good, but expect some pullback in the future.
My theory is that for a large amount of people, “work are paying anyway so what do I care?”.
I lost my job recently, so gave myself an AI budget of $100 to help with search and applications.
If I put that in OpenAI or Anthropic, I’d hit limits quickly and lose whatever I didn’t use.
Or… I could put the same money in OpenRouter, use open models at 1/25th the price, and only need to pay more when I’ve spent what I put in.
Back in January when Claude Cowork was new and Claude Code was one of the only performant harnesses, it would have been a tougher decision.
But Hermes, dsh, agy, codex, opencode, pi… they make it so easy to achieve so much with such a low budget.
I know it’s a cliche nowadays to say “just use cheaper models” but the value they offer is SO much greater. And i can switch to GPT6, or Opus 5.5 in two clicks for tasks anyway.
My point is this: OpenAI and Anthropic are pulling stunts like this because they don’t care about you and your subscription. So stop caring about them.
> My point is this: OpenAI and Anthropic are pulling stunts like this because they don’t care about you and your subscription. So stop caring about them.
Exactly where I landed, I had a personal subscription last year that shifted between OpenAI and Anthropic depending on who had the better model for that month.
This year? I don't need that, I can do the same as you: budget and pre-pay for some tokens in OpenRouter, and use very cheap models for absolutely anything I need on my personal projects. I can use open source harnesses that give me similar results, my projects do not need the absolute most-expensive frontier model at all, that's just a waste.
And if absolutely needed to use some frontier capability I can pay the tokens for that instead of committing to US$ 200-500 for a subscription that they can just pull the rug from me at any point.
I still have my job where they give me access to all the shiny expensive models with their enterprise agreements about data retention, the legal stuff that a company cares about and my personal projects don't, if I keep my usage under the newly implement monthly budget no one will bother me about it and so I just use what I'm told to.
How do we know 100% subscriptions are subsidized, it’s a possibility that they are actually ok (ie some people over use, majority under use and on net profitable) and the API pricing is actually just super expensive. Subscription is a buffet and API is a private chef :)
I have subscriptions to both, one for personal and one for work use, and I haven't really come close to hitting the limits since the release of Opus 5.5 and GPT-Sol 6.1, and I'm no longer hitting any of the capability limits I used to experience when using the "mid" tier models, so I don't miss using Astra. It feels like limits at pretty much a solved problem right now, for my level of use.
I'm absolutely hitting the limits with 6.1. I'd say maybe a bit slower than before, but only because the model is dog slow, not because it's more efficient.
I wonder how subscription breakage (people who pay, but don't use a fraction of their subscribe-for-paid-token-count) plays into the frontier labs gross margins. A number we will likely understand if/when they go public and something users can track locally if they choose.
if anyone wants a lifehack just get $100 sub from anthropic, get $80 sub from z.ai, download omp.sh, set task/advisor to glm 5.3 flash with max thinking, default opus 5.5 with medium thinking, slow set to xhigh thinking and design set to xhigh/max - max will produce significantly more complete designs.
day2day performance difference is negligible, there's less refusals and you always have glm 5.3 for whenever opus 5.5 arbitrarily decides to terminate your conversation.
This is enough to run 2 concurrent sessions 16 hours a day.
But back in February the OpenAI offer was better. Have both of them. Nowadays Anthropic really is the best again. But only after DeepSeek raised its prizes.
What’s news to me is that Anthropic reports that it has 88% gross margin. I find that extremely hard to believe with the capex required to build and run the models.
Accounting 101: CapEx doesn’t directly affect either gross or net margin (when the expenditure occurs). It is capitalized on the balance sheet and affects profitability over time (through depreciation or amortization).
This says “Anthropic gives you 5× more API-priced model usage”, which is not equivalent to “Anthropic is 5x as much value”. This does not take into account model/harness efficiency. I tried looking up some benchmarks and Claude seemingly uses roughly 5x as many tokens while taking its sweet time to complete a task. No such thing as a coincidence.
My chatgpt pro account gave me 62k of their "credits" which they try to sell you at extortionate rates when your subscription runs out. I spent two days hammering it and used about 4k of those.
This is clear manipulation to prevent me from complaining about lower limits until it's out of the news cycle, but I don't care. As soon as those are gone, if my $200 account doesn't give me the value it used to, I'm out.
The random resets are also clear manipulation in this regard as well. Rather than just give me a fixed weekly limit which I could then get a sense of and know if it's getting reduced, they throw out a ~0-3 resets a week at random, unexpected intervals so that I'll never know.
Do you need the $200 sub to use the credits?
As soon as I received them and realized they expire this year, I switched to a $20 membership (billing cycle starts tomorrow), assuming you don't.
After consuming them, I will decide to whom subscribe next.
I would pivot to a Chinese provider via open router so fast... Most months on glm or DeepSeek it would be a challenge to spend $100. But now I mostly use local models... Sounds obnoxious bouncing between 2 companies who rug pull their customers every 4 months and degrade service as a form of advertising...
> But now I mostly use local models
Do you have beefy hardware? i dream of using a local LLM, but neither my 24GB RAM M4 Air nor my PC with a RTX3080 and 16GB of RAM seem usable (yet).
i could label them usable if "prompt it and then wait for 6 minutes for it to change a single line" is deemed usable, which i don't.
spent the last weekend in a rabbit-hole of which models to use in what kind of setup, but i think with my hardware i'm just out of luck for now.
for private matters I can use Cloud AIs, but not allowed to use it for work-related matters, which is where i could use it the most. they do provide us an isolated AI environment where we can use Claude etc. for work stuff, but heavily rated (about 20 prompts per week per Claude model).
They also carefully sequence the resets so they bunch up all at once, including with the regular weekly reset.
Last week I've have about 4 resets in 48 hours:
- reset done by OpenAI around Friday
- banked reset expiring on Saturday
- banked reset expiring on Sunday
- regular weekly reset expiring on Sunday
So basically I was unable to use them, given weekend and all at once, unless you have the software factory ready to spin up...
I'm not complaining, they are free after all, but it's clear they are not randomly distributed.
> subscription gross margins are way lower than API and meaningfully reduce revenue per MW for both OpenAI and Anthropic
I don't know about everyone else, but there is no way in hell I would pay even $200 for API-priced tokens for personal use. So at least for my sample size of one, Anthropic's revenue would not be higher if they dropped their subscription plan (they would get $0 from me instead of $200 per month).
I’m not everyone else but I am SOMEBODY else and you’re absolutely right. I was paying for Claude since they first offered subscriptions, right up until this summer.
I respect Anthropic (and OpenAI to a lesser extent) but I’m not going to play these games.
$200/mo for hiring some very capable interns, that's not very expensive.
And a local AI solution is less capable and also quite expensive, but for some worth trying.
Local ai can be about as capable as anything you get a subscription for. The benefit to local beyond a lot of other things is, no model degradation, and stationary costs. Actually, you get effectively free model upgrades.
For 2-4k you can have opus 4.8 at home running faster than anthropic. In 8-20 months you have broke more than even.
I think for almost anyone it's worth trying. Especially if you already have hardware.
$4k doesn’t even buy you a DGX spark these days. You can get a Ryzen AI max 128GB machine for a bit less than $4k but the models you can run on there aren’t even close to Opus 4.8.
It's not "about as" capable. It might be capable enough, depending on use case however.
I exclusively pay for API tokens. This is the primary way I consume these models.
The flat monthly subscriptions seem too tempting for the providers to screw with. I prefer to paygo and to be responsible with my consumption. I also want the ability to scale substantially beyond what a typical consumer plan may offer on occasion.
My monthly usage ranges from $10-$1000. I don't have to worry about quotas or anything. If I need to use several thousand dollars worth of tokens, I can just pull out the Amex and everything works. It's constant performance all day every day. I have long since maxed out my org level with OAI, so it would be very difficult to exceed any realistic limits.
Spending 5/10 months equiv of subscription cost that have significantly lower revenue for X company (or even costs money) when 1 week of $200 subscription gets you $800~$1200 sure is something.
What's stopping you from using the subscription plan and then topping up with API if you need?
This is a joke.
> Token efficiency is also an extremely relevant factor, but the industry unfortunately lacks reliable data here. Many people like to cite this chart from Artificial Analysis, but we do not believe the benchmark tasks in the AA Intelligence Index are at all representative of real work people do with LLMs.
Right, so they just ignore the fact that different models use very different number of tokens to achieve the same thing. Ignoring that means they can't say anything about "value". This is like comparing numbers with different units. They're Atokens and Otokens.
Hmm I'm not sure this is really the case I have the pro level of each, and GPT 6.1 Sol feels virtually unlimited to me atm, doesnt feel the same with opus and its probably only a few percentage points better and not in all situations.
The title is misleading: by token count, it’s only 3× more valuable.
And there’s also a major error in the calculation: it doesn’t account for the “generous” resets that are mentioned at the beginning of the article!
Taking the 1 to 2 weekly resets into account and comparing tokens, the ChatGPT Pro 200 plan works out to be between 1.2× and 1.7× more cost-effective per token than Claude’s for Astra/Fable, while for Sol/Opus it’s more like 0.7× to 1.04× as valuable.
However, this also doesn’t take into account the fact that, as another commenter pointed out, GPT-6.1 Sol currently uses fewer tokens to perform the same task (according to that comment, 5× fewer tokens, but I haven’t verified those numbers).
My figures are very rough, but the conclusion in the title is clearly false and clickbait. I get the impression that OpenAI offers better value for now, even if that means we’re relying on those “generous” resets continuing to happen.
No serious analysis can consider the completely discretionary resets. I want a predictable LLM inference subscription, not a gacha game.
I’d agree if Claude’s limits weren’t changing and getting lower month after month. For now, neither one is profitable for their lab, and I don’t find their plans very predictable.
We should take advantage of it while it lasts.
> I want a predictable LLM inference subscription, not a gacha game.
The only way we get to predictability is by paying what subscriptions are actually worth, and this entire game hinges on the fast that AI companies are not convinced that most people are willing to pay the 3-5x (or however much it is) multiple on what these accounts actually cost to run.
It's an advertisement. Just like 90% of the AI posts on here and all of social media. I bet it's less than 3x in reality too. Especially once anthropic needs to become profitable for their IPO...
> It's an advertisement.
Evidence?
I have both, 6.1 sol is no where near 5x more efficient then opus in day2day. Without numbers i would not even entertain that though and with numbers i would look closly if its the same code. I put it to work on the same repo so i have somewhat of a comparison. Not to mention that opus 5.5 is way better in most of the tasks. Currently openai gives you less for worse idk how did they think that could work.
One of their three identical accounts had ~20% lower limits and the explanation was an "extremely tiny" A/B test. Makes the "5x" kind of a joke. I'd honestly take a slightly worse plan if it just published the actual token limits.
Grab a plan from one of the Chinese companies, they give you explicit ranges token that you can expect to get.
They would never do this because it would allow customers to see how often and to what degree they're shifting account limits. Token transparency costs extra, full API price to be exact.
Somewhat tuning out these "X is better than Y" news and articles, as things are still moving quite fast. In a few weeks, OpenAI offers more value for money and the cycle repeats again.
As a Claude subscriber, I am quite enjoying the value I get from Anthropic. But I am not forgetting that this is their loss leader, and API access is still their main driver. So strike while things are good, but expect some pullback in the future.
My theory is that for a large amount of people, “work are paying anyway so what do I care?”.
I lost my job recently, so gave myself an AI budget of $100 to help with search and applications.
If I put that in OpenAI or Anthropic, I’d hit limits quickly and lose whatever I didn’t use.
Or… I could put the same money in OpenRouter, use open models at 1/25th the price, and only need to pay more when I’ve spent what I put in.
Back in January when Claude Cowork was new and Claude Code was one of the only performant harnesses, it would have been a tougher decision.
But Hermes, dsh, agy, codex, opencode, pi… they make it so easy to achieve so much with such a low budget.
I know it’s a cliche nowadays to say “just use cheaper models” but the value they offer is SO much greater. And i can switch to GPT6, or Opus 5.5 in two clicks for tasks anyway.
My point is this: OpenAI and Anthropic are pulling stunts like this because they don’t care about you and your subscription. So stop caring about them.
> My point is this: OpenAI and Anthropic are pulling stunts like this because they don’t care about you and your subscription. So stop caring about them.
Exactly where I landed, I had a personal subscription last year that shifted between OpenAI and Anthropic depending on who had the better model for that month.
This year? I don't need that, I can do the same as you: budget and pre-pay for some tokens in OpenRouter, and use very cheap models for absolutely anything I need on my personal projects. I can use open source harnesses that give me similar results, my projects do not need the absolute most-expensive frontier model at all, that's just a waste.
And if absolutely needed to use some frontier capability I can pay the tokens for that instead of committing to US$ 200-500 for a subscription that they can just pull the rug from me at any point.
I still have my job where they give me access to all the shiny expensive models with their enterprise agreements about data retention, the legal stuff that a company cares about and my personal projects don't, if I keep my usage under the newly implement monthly budget no one will bother me about it and so I just use what I'm told to.
i am partial to qwencloud
How do we know 100% subscriptions are subsidized, it’s a possibility that they are actually ok (ie some people over use, majority under use and on net profitable) and the API pricing is actually just super expensive. Subscription is a buffet and API is a private chef :)
I have subscriptions to both, one for personal and one for work use, and I haven't really come close to hitting the limits since the release of Opus 5.5 and GPT-Sol 6.1, and I'm no longer hitting any of the capability limits I used to experience when using the "mid" tier models, so I don't miss using Astra. It feels like limits at pretty much a solved problem right now, for my level of use.
I'm absolutely hitting the limits with 6.1. I'd say maybe a bit slower than before, but only because the model is dog slow, not because it's more efficient.
> but the gap is still massive even if you switch to comparing the number of tokens.
Token doesn't have the same meaning at OpenAI vs Anthropics, they use different tokenizer. How can this be used for comparison?
I wonder how subscription breakage (people who pay, but don't use a fraction of their subscribe-for-paid-token-count) plays into the frontier labs gross margins. A number we will likely understand if/when they go public and something users can track locally if they choose.
if anyone wants a lifehack just get $100 sub from anthropic, get $80 sub from z.ai, download omp.sh, set task/advisor to glm 5.3 flash with max thinking, default opus 5.5 with medium thinking, slow set to xhigh thinking and design set to xhigh/max - max will produce significantly more complete designs.
day2day performance difference is negligible, there's less refusals and you always have glm 5.3 for whenever opus 5.5 arbitrarily decides to terminate your conversation.
This is enough to run 2 concurrent sessions 16 hours a day.
These prices are getting ridiculous, we’re talking about 180$ / month here.
Is anthropic allowing 3rd party harnesses like that?
But back in February the OpenAI offer was better. Have both of them. Nowadays Anthropic really is the best again. But only after DeepSeek raised its prizes.
What’s news to me is that Anthropic reports that it has 88% gross margin. I find that extremely hard to believe with the capex required to build and run the models.
Accounting 101: CapEx doesn’t directly affect either gross or net margin (when the expenditure occurs). It is capitalized on the balance sheet and affects profitability over time (through depreciation or amortization).
[1] https://en.wikipedia.org/wiki/Capital_expenditure
There's a simple explanation here.
Anthropic has way more inflated api token priced than OpenAI what is plainly visible on cost charts.
This says “Anthropic gives you 5× more API-priced model usage”, which is not equivalent to “Anthropic is 5x as much value”. This does not take into account model/harness efficiency. I tried looking up some benchmarks and Claude seemingly uses roughly 5x as many tokens while taking its sweet time to complete a task. No such thing as a coincidence.
Also how tokenization works. There was a post the other day saying 150k OpenAI tokens is equivalent to 250k Anthropic tokens.
Can't find the link now it was a the pi harness author saying you could load the entire harness into context with those budgets IIRC.
Let's hope they don't nerf Opus 5.5
im legit praying this doesn't happen
Submarine ?
but ai credit runs out really really fast