OpenAI eyes more funding to meet AI compute demand

OpenAI may raise more capital after a recent private fundraising round as it tries to secure enough computing power for rising AI demand, said Sarah Friar, CFO, in a Bloomberg TV interview.

Any new fundraising would depend on demand, revenue, cash flow, and the gap between the computing capacity OpenAI needs and what it can afford.

Public markets could become an option over time because they are larger than private ones, Friar said.

ChatGPT has more than 900 million weekly active users and Codex has over 4 million users, she said.

Friar declined to comment on possible litigation linked to OpenAI’s partnership with Apple.

🔗 Source: Bloomberg

🧠 Food for thought

Implications, context, and why it matters.

OpenAI’s recent fundraising may be more complicated than it looks

The recent private round was described as a US$122 billion deal at an US$852 billion post-money valuation. Some commentators say the setup is more layered than a standard cash raise 1.
One analysis puts immediate cash at about US$37 billion. The rest may depend on conditions, later tranches, or non-cash support such as guaranteed computing access 2.
That same analysis says Amazon’s US$50 billion commitment sits alongside a separate deal for OpenAI to spend US$100 billion on Amazon Web Services (AWS), Amazon’s cloud computing division, over eight years. It also says Nvidia’s US$30 billion is mostly computing capacity, not liquid capital 2.
Another estimate puts OpenAI’s losses at US$14–17 billion in 2026. If that holds, the cash runway may be shorter than the headline number suggests, which could help explain a need for more funding 2.

Distribution deals can cut both ways for AI leaders

Friar declined to comment on the Apple partnership. That stands out while reports say the relationship is under strain and OpenAI has weighed legal options internally 3.
OpenAI has been frustrated that the partnership has not brought the subscription growth or deeper product integration it expected 4.
Apple is also testing links with several AI providers, including Google’s Gemini and Anthropic’s Claude. The work fits a broader push to support multiple models in Apple Intelligence, Apple’s AI feature set 3.
When large AI models are treated as interchangeable by big distribution partners, AI companies may need to spend more to win users directly. That can deepen their dependence on fresh funding.