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Are OpenAI and Anthropic losing money on inference?

(martinalderson.com)
507 points martinald | 2 comments | 28 Aug 25 10:15 UTC | HN request time: 0.034s | source
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sc68cal ◴[28 Aug 25 15:12 UTC] No.45053212[source]▶
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.

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CjHuber ◴[28 Aug 25 15:26 UTC] No.45053401[source]▶
The reason it shook the market at least was because of the claim that its training cost was 5 million.
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hirako2000 ◴[28 Aug 25 15:33 UTC] No.45053502[source]▶
That' what the buzz focused on, strange as we don't actually know what it cost them. While inference optimization is a fact and is even more impactful since training costs benefit from economics of scale.
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1. CjHuber ◴[28 Aug 25 17:49 UTC] No.45054957{3}[source]▶
I don't think that's strange at all, it's a much more palatable narrative for the mass who doesn't know what inference and training is and who think having conversations=training
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2. hirako2000 ◴[29 Aug 25 15:20 UTC] No.45065298[source]▶
I agree nothing surprising in that, also back then inference wasn't as much questioned as today with regards to being sold at a loss.