> $2.08 for every $1 of compute.

sounds pretty good. if I made 2.08 for every dollar of my spend I would make more money. Plenty of businesses operate on much much thinner margins, and thats not utility-like at all.

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drillsteps5 4 hours ago | parent | next [-]

I could only find these numbers in articles on something called crypto briefing dot com, not sure how the author got this number from the S-1.

When using traditional business metrics, such as operational net income, we'll see that Anthropic has been in the red for the entirety of its history, at times to the tune of $3B per quarter, except in Q2 2026.

When looking at amended S-1 (with Q3 numbers), page 23, "Consolidated Statements of Operational Data", we can see that for 2026 YTD (Q1 - Q3) net loss was $103B; operating loss was $1,260B.

Anthropic also disclosed up to $895B (multiyear) commitments for infrastructure build-up.

Basically, the company's financial results do not allow for any reasonable valuation (which would be more than 0), leave alone $2T or even $1T. If this is not an indication of a bubble I don't know what is.

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3 hours ago | parent | prev | next [-]

[deleted]

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sanp 8 hours ago | parent | prev | next [-]

That’s 52% gross margin. Not much higher than the overall S&P 500. If you break it down by sector, Real Estate, Health are, Financials (and of course Tech overall) have higher gross margins at the sector level.

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gonzalohm 8 hours ago | parent | prev [-]

That $1 of compute is not taking into account R&D spending, infrastructure, etc.

And that's their only revenue stream

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sigmar 7 hours ago | parent [-]

>That $1 of compute is not taking into account R&D spending, infrastructure, etc

People assume this, but it is wrong. Check the S-1 for Q2, the $2.08 in revenue is for every $1.00 spent on "compute and infrastructure expenses" which also include R&D compute. (Chart is on page 137)

"Compute and infrastructure expenses primarily consist of costs attributable to operating our technology infrastructure, which supports the full range of workloads for our models, including research, model development, serving customers, and internal usage of Claude." page 146 in the S-1/A-1

	▲	drillsteps5 4 hours ago \| parent [-]
		It is not really clear. In the graph on page 137 does the "dollar of compute" includes only compute required for inference to provide the answer? Or does this include training as well? It would be logical to assume that they show expense of compute required to run inference. Leaving training compute (which is huge expense) out.