> 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.

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.

I’m not saying charging above marginal cost to fund R&D is weird. That’s how every R&D company works.

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Training frontier models takes months, costs billions, and the model is outdated in six months.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.