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It sure looks like that. Anthropic might not be evil in the actively-building-the-torment-nexus way, but from reading the comments on github they are either saving compute or intentionally sabotaging existing models so that their users will upgrade when the next model comes out, both of which are things one would avoid in companies one does business with.
The obvious solution would be to separate the development and the hosting of the models. So you would pay Anthropic for the license to run the model and Nvidia (or whomever) for the inference, with the idea that the computation provider has no incentive to care whether you prefer this or that model, and will thus simply run it without cutting any corners. Just like Intel does not really care if I run Linux or Windows or whatever on my CPU.
One of the problems would be that the data center would obviously need the node weights (which are probably worth billions to China in a way the binaries of Windows are not), but there are already solutions for that for using LLMs for classified government data. You would not need hundreds of compute vendors which have access to Claude's weights, but perhaps three or four. And of course LLM vendors might whine about having to fix jailbreaks of their models so that they can't be used for bioweapons research (or whatever the scary thing of the day is), but at least people would be notified that their model got mandatory updates, rather than "as of March 8".
I imagine that a LLM company is always living on borrowed time. A business decision which will make you appear as a trustworthy partner, but also decrease the hype for your product and thus give you a few tens of billions less of money to burn might result in you losing your lead and getting sidelined. So instead you hype-maxx, whatever that takes, and if it takes selling tokens below cost to establish that your LLM is the best in a domain, and then later pulling the rug from under your customer base then you simply do that.
This also makes me slightly more pessimistic about ASI alignment. Charitably, it could be "Anthropic cares so much about ASI alignment that they are beyond any lesser concerns than winning the AI race." But realistically, if one side in a civil war decides that their victory is more important than anything and every crime they commit will be worth it a hundredfold once they have won and established their utopia, at least nine times out of ten their envisioned utopia will be some sort of hellscape. Empirically, there seems to be a limit to instrumental convergence in humans, and you can learn a lot about the character of your date by observing how they treat the waiter, or a general by what lines they will cross.
In the modern internet, servers are nicely scalable. Get more customers? Spin up a few more virtual AWS boxes, so to speak. However, AI compute is not like this. Claude has only so much, some of which needs to be reserved for new models to keep R&D going (and the AI sector is so rivalrous that you cannot even buy compute from a rival even if the economics would theoretically work out for both parties)... and all of the sudden a few months back they got a giant wave of sign-ups. A perfect storm of "hey Claude's actually pretty good compared to ChatGPT", Claude Code positive PR, OpenAI's ad foray, favorable PR from the Defense Department feud, etc.
So of course limits need to go down, even for paying users. Supply and Demand 101. But most users aren't used to internet-era resources being subject to supply and demand (as I mentioned server compute is usually supremely elastic for the last 15 years or so) so they see Anthropic as acting "nefarious". This is not true. They are definitely not sabotaging models just to sell the next model because they are literally incapable of accepting more customers without hurting existing ones. No company is going to outright say "sorry we don't want your money" so of course they don't, but that's the reality. They've looked at 2-year projections and feel OK about it, so for the moment they will just circle the wagons and deliver 70% of the value most customers expect, just enough not to lose too many and keep people hungry for more in a few months when (I assume) more compute comes online. No conspiracy, and really no intent to harm either I don't think.
You're correct that at least in theory there are ways around this like farming out the inference in a more traditional manner. But 1) I don't think the economics actually work out very well for this and 2) the proprietary sauce of how inference is delivered to end-users at scale is actually very valuable, any outsourcing thus endangers the golden goose there too - on top of the weights issue point you bring up. Also, inference at scale requires certain hardware, and most of the existing flexible-type compute is more CPU-bound (to oversimplify massively). You absolutely can serve inference in a more fragmented (and thus flexible) way on worse hardware but costs spike pretty substantially, from what I understand (various caching optimizations and energy usage and also all sorts of latency issues crop up).
I think reputational damage is overblown for Anthropic; it's really not so bad to have a product so good they can't make enough of it. Compared to OpenAI they are sitting pretty. They can still cannibalize other AI providers too for more headroom, they aren't maxxed out in terms of customer base like OpenAI arguably is. Their relative success at B2B sales and integration only magnifies this.
More to the "evil" point - Dario Amodei is the nerd who left OpenAI because he was the type to whine that a new model hadn't done safety testing yet before being deployed. We even see this crop up in that one Sam Altman article. And he's in charge. Business pressures are strong of course, but Amodei I'm pretty sure is one of the rare diehard true believers in alignment, so while he might be insane in a different way, it won't be an alignment issue, my sense is that it would take another order of magnitude more investor pressure for that to be a notable threat.
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Unfortunately wouldn't work. Provider has every incentive to have you use less compute, and thus could attempt to quantize or mini-fy models it is serving you
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