Are OpenAI and Anthropic losing money on inference?

This whole article is built off using DeepSeek R1, which is a huge premise that I don't think is correct. DeepSeek is much more efficient and I don't think it's a valid way to estimate what OpenAI and Anthropic's costs are.

https://www.wheresyoured.at/deep-impact/

Basically, DeepSeek is _very_ efficient at inference, and that was the whole reason why it shook the industry when it was released.

Uhhh, I'm pretty sure DeepSeek shook the industry because of a 14x reduction in training cost, not inference cost.

We also don't know the per-token cost for OpenAI and Anthropic models, but I would be highly surprised if it was significantly more expensive than open models anyone can use and run themselves. It's not like they're also not investing in inference research.

Isn't training cost a function of inference cost? From what I gathered, they reduced both.

I remember seeing lots of videos at the time explaining the details, but basically it came down to the kind of hardware-aware programming that used to be very common. (Although they took it to the next level by using undocumented behavior to their advantage.)