271–280 of 827 posts
AI is the new high-end gym membership. They want you to pay the big fee and then not use what you paid for. We'll see more and more roadblocks to usage as time goes on.
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A $200/m max subscriber using OpenCode and not wanting to use API keys with pay-per-token pricing is very clearly trying to get around paying for tokens.
Is there any limits to that users 200/month? Why should they not be able to use the limits to the extent from other tools? If openclaw chews my 200/month up in 15 days... I don't get more requests for free
Once again: you can use API keys and pricing to get UNLIMITED usage whenever you want. If you are choosing to pay for a subscription instead, it is because Anthropic is offering those subscriptions at a much better value-per-token. They are not offering such a subscription out of the goodness of their heart.
Opus has gone down the hill continously in the last week (and before you start flooding with replies, I've been testing opus/codex in parallel for the last week, I've plenty of examples of Claude going off track, then apologising, then saying "now it's all fixed!" and then only fixing part of it, when codex nailed at the first shot).
I can accept specific model limits, not an up/down in terms of reliability. And don't even let me get started on how bad Claude client has become. Others are finally catching up and gpt-5.3-codex is definitely better than opus-4.6
Everyone else (Codex CLI, Copilot CLI etc...) is going opensource, they are going closed. Others (OpenAI, Copilot etc...) explicitly allow using OpenCode, they explicitly forbid it.
This hostile behaviour is just the last drop.
I don't think it's a secret that AI companies are losing a ton of money on subscription plans. Hence the stricter rate limits, new $200+ plans, push towards advertising etc. The real money is in per-token billing via the API (and large companies having enough AI FOMO that they blindly pay the enormous invoices every month).
Why do you think they're losing money on subscriptions?
If the answer is not yes, then they are making money on inference. If the answer is no, the market is going to have a bad time.
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The question I have: how much are they _also_ losing on per-token billing?
From what I understand, they make money per-token billing. Not enough for how much it costs to train, not accounting for marketing, subscription services, and research for new models, but if they are used, they lose less money. Finance 101 tldr explanation: The contribution margin (= price per token -variable cost per token ) this is positive Profit (= contribution margin x cuantity- fix cost)
I think what they want to achieve here is less "kill openclaw" or similar and more "keep our losses under control in general". And now they have a clear criteria to refer when they take action and a good bisection on whom to act on.
In case your usage is high they would block / take action. Because if you have your max subscription and not really losing them money, why should they push you (the monopoly incentive sounds wrong with the current market).
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They'll all do this eventually. We're in the part of the market cycle where everyone fights for marketshare by selling dollar bills for 50 cents. When a winner emerges they'll pull the rug out from under you and try to wall off their garden. Anthropic just forgot that we're still in the "functioning market competition" phase of AI and not yet in the "unstoppable monopoly" phase.
Unstoppable monopoly will be extremely hard to pull off given the number of quality open (weights) alternatives. I only use LLMs through OpenRouter and switch somewhat randomly between frontier models; they each have some amount of personality but I wouldn't mind much if half of them disappeared overnight, as long as the other half remained available.
Software always gets monopoly simply by usage. Every time a model gets used by esoteric use cases, it gets more training data (that a decentralized open weight model doesn't get) and it starts developing its moat.
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Unstoppable monopoly will be extremely hard to pull off given the number of quality open (weights) alternatives. I only use LLMs through OpenRouter and switch somewhat randomly between frontier models; they each have some amount of personality but I wouldn't mind much if half of them disappeared overnight, as long as the other half remained available.
I'm old, so I remember saying the same thing about Google and search. I hope you're right!
I can get a ridiculous amount of tokens in and out of something like gpt-5.2 via the API for $100.
Is this primarily about gas town and friends?
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They are not losing money on subscription plans. Inference is very cheap - just a few dollars per million tokens. What they’re trying to do is bundle R&D costs with inference so they can fund the training of the next generation of models. Banning third-party tools has nothing to do with rate limits. They’re trying to position themselves as the Apple of AI companies -a walled garden. They may soon discover that screwi…
Except all those GPUs running inference need to be replaced every 2 years.