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mirzap | 11 days ago
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 screwing developers is not a good strategy.
They are not 10× better than Codex; on the contrary, in my opinion Codex produces much better code. Even Kimi K2.5 is a very capable model I find on par with Sonnet at least, very close to Opus. Forcing people to use ONLY a broken Claude Code UX with a subscription only ensures they loose advantage they had.
rjh29|11 days ago
Google AI Pro is like $15/month for practically unlimited Pro requests, each of which take million tokens of context (and then also perform thinking, free Google search for grounding, inline image generation if needed). This includes Gemini CLI, Gemini Code Assist (VS Code), the main chatbot, and a bunch of other vibe-coding projects which have their own rate limits or no rate limits at all.
It's crazy to think this is sustainable. It'll be like Xbox Game Pass - start at £5/month to hook people in and before you know it it's £20/month and has nowhere near as many games.
harrall|11 days ago
Google has made custom AI chips for 11 years — since 2015 — and inference costs them 2-5x less than it does for every other competitor.
The landmark paper that invented the techniques behind ChatGPT, Claude and modern AI was also published by Google scientists 9 years ago.
That’s probably how they can afford it.
touristtam|10 days ago
gbear605|11 days ago
trymas|11 days ago
5h allowance is somewhere between 50M-100M tokens from what I can tell.
On 200$ claude code plan you should be burning hundreds of millions of token per day to make anthropic hurt.
IMHO subscription plans are totally banking on many users underusing them. Also LLM providers dont like to say exact numbers (how much you get , etc)
dcre|10 days ago
dgellow|10 days ago
MikeNotThePope|11 days ago
thunfischtoast|11 days ago
But this is how every subscription works. Most people lose money on their gym subscription, but the convenience takes us.
bildung|11 days ago
The interesting question is: In what scenario do you see any of the players as being able to stop spending ungodly amounts for R&D and hardware without losing out to the competitors?
stavros|10 days ago
KingMob|11 days ago
You've described every R&D company ever.
"Synthesizing drugs is cheap - just a few dollars per million pills. They're trying to bundle pharmaceutical research costs... etc."
There's plenty of legit criticisms of this business model and Anthropic, but pointing out that R&D companies sink money into research and then charge more than the marginal cost for the final product, isn't one of them.
mirzap|11 days ago
My point was simpler: they’re almost certainly not losing money on subscriptions because of inference. Inference is relatively cheap. And of course the big cost is training and ongoing R&D.
The real issue is the market they’re in. They’re competing with companies like Kimi and DeepSeek that also spend heavily on R&D but release strong models openly. That means anyone can run inference and customers can use it without paying for bundled research costs.
Training frontier models takes months, costs billions, and the model is outdated in six months. I just don’t see how a closed, subscription-only model reliably covers that in the long run, especially if you’re tightening ecosystem access at the same time.
maplethorpe|11 days ago
Why do people keep saying inference is cheap if they're losing so much money from it?
mirzap|11 days ago
hhh|11 days ago
mirzap|11 days ago
andersmurphy|11 days ago
phyrex|11 days ago
mvdtnz|11 days ago
carderne|11 days ago