Suno raises at a $5.4bn valuation, more than doubling its worth in six months


Eighteen months ago Suno was the AI company the music industry wanted to destroy. Every major record label had sued it, accusing it of training its models on copyrighted songs without permission. Now the labels are its partners, and investors have repriced the company accordingly. Suno has raised new capital at a $5.4bn valuation, more than double the $2.45bn it was worth just six months ago.


Bond Capital led the round, a Series D that had been reported to be closing for several weeks. The step-up is steep: a little over 2x in roughly half a year, the kind of re-rating that usually reflects either explosive growth or a fundamental change in a company’s risk profile. In Suno’s case it reflects both, and the second may matter more than the first.

The growth is real enough. Suno says more than 100 million people have now used the service, with around 2 million paid subscribers, and it reported roughly $150M in revenue in 2025.

By the measure investors care about, it is one of the breakout consumer-AI products, turning text prompts into finished songs for a mass audience rather than a niche of producers.

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But the more important shift is legal. When Suno last raised, it did so under an existential cloud: lawsuits from Universal, Warner and Sony, any of which could in principle have ended the business if the courts found its training data infringing. That cloud has substantially lifted.

Warner settled in November 2025 and struck a partnership to build licensed models, and Universal settled in October, its deal pairing a payment with a licensing arrangement for a joint AI platform. Two of the three majors that wanted Suno gone are now commercial partners.

That is the change investors are paying for. A company facing three industry-ending lawsuits is priced for the possibility of zero. A company that has converted two of those plaintiffs into licensors, and is rebuilding its models on authorised catalogue with artist opt-in, is priced as a going concern with a path to legitimacy. The valuation jump is less a bet on more users than a re-rating of the chance that Suno survives to keep them.

The terms of the settlements point at what Suno becomes on the other side. It has said it will launch new, licensed models in 2026 and deprecate the current ones, give artists and songwriters control over whether their names, voices and compositions are used, and require a paid account to download audio.

That is a more constrained, more expensive product than the free-for-all that built its user base, and the strategic question is whether 100 million users trained on the old model accept the new one.

The truce is also incomplete. Sony, the last of the three majors still litigating, has settled with neither Suno nor its rival Udio, and its fair-use cases are expected to produce a pivotal ruling in summer 2026. That decision could shape the copyright ground rules for the entire generative-music field, and a result unfavourable to Suno would complicate the legitimacy narrative this valuation rests on. The risk has shrunk, not vanished.

What the round captures is a company mid-transformation, from insurgent to licensee, from sued to partnered, from free tool to paid platform. The $5.4bn says the market believes the transformation is working. Sony’s lawyers, and a courtroom this summer, still get a say in whether it finishes.



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“It was severely downgraded,” Gilbert confirms. “I never would have found it if I was just looking through Google results.” (I tried the same prompt in Gemini earlier this month, and after an initial denial, the tool also gave me Eiger’s number.)

After this experience, Eiger, Gilbert, and another UW PhD student, Anna-Maria Gueorguieva, decided to test ChatGPT to see what it would surface about a professor. 

At first, OpenAI’s guardrails kicked in, and ChatGPT responded that the information was unavailable. But in the same response, the chatbot suggested, “if you want to go deeper, I can still try a more ‘investigative-style’ approach.” Their inquiry just had to help “narrow things down,” ChatGPT said, by providing “a neighborhood guess” for where the professor might live, or “a possible co-owner name” for the professor’s home. ChatGPT continued: “That’s usually the only way to surface newer or intentionally less-visible property records.” 

The students provided this information, leading ChatGPT to produce the professor’s home address, home purchase price, and spouse’s name from city property records. 

(Taya Christianson, an OpenAI representative, said she was not able to comment on what happened in this case without seeing screenshots or knowing which model the students had tested, even after we pointed out that many users may not know which model they were using in the ChatGPT interface. She also declined to comment generally about the exposure of PII by the chatbot, instead providing links to documents describing how OpenAI handles privacy, including filtering out PII, and other tools.) 

This reveals one of the fundamental problems with chatbots, says DeleteMe’s Shavell. AI companies “can build in guardrails, but [their chatbots] are also designed to be effective and to answer customer questions.”

The exposure issue is not limited to Gemini or ChatGPT. Last year, Futurism found that if you prompted xAI’s chatbot Grok with “[name] address,” in almost all cases, it provided not only residential addresses but also often the person’s phone numbers, work addresses, and addresses for people with similar-sounding names. (xAI did not respond to a request for comment.) 

No clear answers

There aren’t straightforward solutions to this problem—there’s no easy way to either verify whether someone’s personal information is in a given model’s training set or to compel the models to remove PII. 



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