AI & ML 5 min read

Baseten is in talks to raise US$1 billion at a valuation of US$11 billion as inference money keeps flowing

Baseten, which rents Nvidia servers for AI models, is in talks to raise US$1bn at a US$11bn valuation, more than double the price it set three months ago, on revenue it says tripled in a quarter.

AI Tools Desk
AI & Developer Productivity Desk
Published 2 Jun 2026, 11:16 AM (SGT)
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Rows of servers in a data centre, illustrating the AI inference infrastructure Baseten provides. Rows of servers in a data centre, illustrating the AI inference infrastructure Baseten provides. Photo by Brett Sayles on Pexels
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Baseten is in talks to raise US$1 billion at a valuation of US$11 billion, according to reports on 26 May. The round has not closed, so the figure is still a target. If it lands, it more than doubles the US$5 billion valuation Baseten set in January.

What Baseten does

Inference is the part of AI that comes after training, when the model is running in production, answering queries and generating responses. Baseten rents Nvidia servers to application developers and helps them deploy, customise and run mostly open-source models on that hardware. Its business is the unglamorous layer between a model and a working product, and that layer is where demand has rushed this year.

Why investors are circling

Revenue is what draws investors. Baseten's annualised revenue reached roughly US$600 million by the end of the first quarter, up from about US$200 million at its start, per PYMNTS. Revenue that triples in three months tends to pull a valuation up with it. Its January round was led by IVP and CapitalG, and Nvidia put in US$150 million, a sign the chipmaker wants its hardware booked through fast-growing inference resellers.

US$1BRound being raised
US$11BTarget valuation
~US$600MAnnualised revenue, end Q1
US$5BValuation in January

The read

Two AI-infrastructure rounds in a week, Baseten's and the data-layer repricing at Snowflake, point the same way. The market seems to have decided that the money in this cycle is in infrastructure, meaning the compute, serving and plumbing that every AI product needs. Whether US$11 billion is the right price depends on margins holding as Baseten rents hardware it does not own and resells at a markup the cloud giants would happily undercut. The revenue looks solid. How long Baseten's margins can last is less clear.

The round closed four weeks later, half as large again

The deal that eventually landed was bigger than the one being reported.

Baseten announced a US$1.5bn Series F at a US$13bn valuation on 22 June, not US$1bn at US$11bn. It was led by Altimeter Capital, Conviction Partners and Spark Capital, and co-led by Sands Capital and Wellington Management. The company had been valued at US$5bn in January, which puts the move at roughly 2.6 times in five months rather than the doubling anticipated above.

The revenue figure held up as the reason. Annualised revenue of about US$600m at the end of the first quarter, up from roughly US$200m at its start, is the curve the round was priced against, and no larger figure was needed to justify the higher price.

The question about the spread is now the whole sector's question

The doubt raised here was whether margins hold for a company renting hardware it does not own and reselling at a markup the cloud giants could undercut. Three months on, that has stopped being a Baseten question.

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Five hyperscalers have disclosed roughly US$1.2 trillion of lease obligations, of which about US$725bn has not yet commenced and therefore sits in the notes rather than on the balance sheet, with Goldman expecting around 35 per cent of 2027 AI capital expenditure to be debt-funded. The companies that could undercut an inference reseller are themselves financing the capacity to do it, on terms that are only partly visible.

This creates a two-sided risk for a business like Baseten. A competitor carrying committed lease obligations has a strong incentive to fill capacity at whatever price keeps it booked, which compresses the reseller's spread. It also means the reseller is not the party holding the duration risk on a data centre.

The layer kept attracting money, and it kept moving

The bet that this cycle's money is in the picks and shovels has held up, though the range of tools that count as shovels has grown.

Together AI booked up to 10,000 Nvidia B300s at a Chennai campus in August, its second buildout in a week, which is an inference provider taking on exactly the physical commitment Baseten's model avoids. River AI raised US$1.1bn at two months old with an API still in preview, and both Nvidia and AMD Ventures were in the same round. Stripe agreed to buy OpenRouter, which routes across roughly 400 models and meters the spend.

Each is a bet on the same layer. Together AI wants to own the hardware, River AI the models and Stripe the routing. Baseten sits between them, renting hardware to serve other companies' models, a position that needs the least capital and has the weakest moat. Seen that way, Nvidia's US$150m in Baseten is a chipmaker booking demand for its hardware through a fast-growing reseller, and it made a comparable bet on River AI alongside its closest competitor two months later.

What is still unsettled

The tripling of revenue in a quarter was real, and the valuation followed it. The margin has never been published.

Margin is the figure that would settle the question, and inference resellers do not disclose it. Until one does, a valuation in this layer is a bet on revenue growth outrunning a spread nobody outside the company can measure.

Correction, 18 October 2026: An earlier version described the June Series F as split across two valuation tiers and listed its leads incorrectly. Baseten announced a US$1.5bn round at a US$13bn valuation, led by Altimeter Capital, Conviction Partners and Spark Capital.

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AI Tools Desk
AI & Developer Productivity Desk

AI Tools Desk tracks AI products, coding agents, model releases, and developer productivity tools for RECATOOLS.

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About this byline AI Tools Desk is a specialist RECATOOLS editorial desk focused on AI tools and developer productivity coverage. Articles are produced and reviewed under RECATOOLS editorial supervision. The articles listed here keep this byline. New coverage on these beats is published under the persona whose beat it falls in: Kenji Tanaka for AI and machine learning, developer tooling and cloud, and Amelia Wong for consumer-facing AI.

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