Anthropic has rocketed to a massive valuation in just a few years, even as its chief executive unveils the economics of scaling frontier AI models, creating a paradox of rising costs and hidden profits.
In a new blog post, Anthropic reveals that it closed a $13 billion Series F round led by ICONIQ, Fidelity and Lightspeed Venture Partners, valuing the AI startup at $183 billion in less than three years since launching its Claude model.
The round also drew heavyweight backers including BlackRock, Blackstone, Goldman Sachs, Jane Street, Qatar’s sovereign wealth fund and Ontario Teachers’ Pension Plan.
The financing cements Anthropic’s status as one of the fastest-growing technology companies in history, with run-rate revenue climbing from roughly $1 billion at the start of 2025 to more than $5 billion by August.
But even as investors pour billions into the company, CEO Dario Amodei is warning that the economics of frontier AI carry a paradox that distorts traditional financial statements.
In an interview with the A Cheeky Pint YouTube channel, Amodei explains why a big AI firm’s balance sheet may look like it is losing money at a staggering pace, training models and investing in infrastructure, when in reality, each generation of models is highly profitable
“So let’s say in 2023, you train a model that costs $100 million. And then you deploy it in 2024. And it makes $200 million in revenue. Meanwhile, because of the scaling laws in 2024, you also train a model that costs a billion dollars. And then in 2025, you get $2 billion of revenue from that $1 billion, and you’ve spent $10 billion to train the model. So if you look in a conventional way at the profit and loss of the company, you’ve lost $100 million the first year, you’ve lost $800 million the second year, and you’ve lost $8 billion in the third year.”
Amodei notes the apparent losses come from plowing each generation’s revenue into an even larger training run, a treadmill that obscures the underlying profitability.
“So it looks like it’s getting worse and worse. If you consider each model to be a company, the model that was trained in 2023 was profitable. You paid $100 million and then it made $200 million in revenue… But let’s just assume in this cartoonish cartoon example that even if you add those two up, you’re in a good state.
So if every model was a company, the model is actually profitable. What’s going on is that at the same time as you’re reaping the benefits from one company, you’re founding another company that’s like much more expensive and requires much more upfront R&D investment. And so the way that it’s going to shake out is this will keep going up until the numbers go very large and the models can’t get larger. And then it’ll be a large, very profitable business.”
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