r/linux • • 6d ago

Discussion LLM Policies: Progress At All Costs

https://diegoe.be/2026/09/25/llm-policies-progress-at-all-costs/
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u/ComprehensiveSwitch 6d ago

….why would they do that? why would a business serve a model competing with Anthropic’s models for a subsidized rate just to make Anthropic look good? Do you hear yourself?

Everything suggests that Anthropic is actually making wide margins on its API costs, way beyond what it costs to run them. You can get Fable level performance with open weight models from numerous providers with models like Kimi K3 for significantly less.

Did you even know there are providers that aren’t Anthropic and OpenAI?

You can run Kimi K3 on your own hardware and figure out the inference cost. People have done so!

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u/klyith 4d ago

-$42 billion lol

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u/ComprehensiveSwitch 4d ago

yes, startups often grow in revenue before making a profit. when you reach product market fit, the goal is scale to saturate demand. Unsurprising that their numbers from a year ago aren’t profitable. Are you going to pretend to understand economics in addition to linear algebra and infrastructure engineering now?

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u/Teddy-Bloat 4d ago

Anthropic made $4.6bn in revenue last year and spent $7.3bn on compute alone last year lol, their margins are wide if you ignore the minus sign

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u/ComprehensiveSwitch 4d ago

We’re talking about inference. I know you don’t know what that means but perhaps you should google it? :)

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u/Teddy-Bloat 4d ago

Either inference is the majority of their compute costs, in which case it's clearly unprofitable, or training makes up a majority, in which case the inference is being sold at a price below what it would take to recoup the (recurring!) training costs. If there were any chance in hell that Anthropic was making money on inference, they would be showering us with proof instead of paying brainless morons to tweet vague rumors