AI News
OpenAI Races to Raise $30 Billion at a $1.4 Trillion Valuation Before Anthropic's IPO
OpenAI is racing to secure investor commitments for a funding round of about $30 billion before Anthropic's expected stock market debut in mid-November, Reuters reported on October 19, citing two people familiar with the matter. The round would value the ChatGPT maker at more than $1.4 trillion — over 60% above the $852 billion valuation set in March, when OpenAI raised $122 billion in the largest private round in history. The compressed timetable is the story: fundraisings of this size normally take months, and OpenAI is trying to close in weeks.
Why the hurry
The two frontier labs are increasingly fishing in the same pool. The same sovereign wealth funds and long-only institutional investors that Anthropic is courting for its IPO are the ones OpenAI wants commitments from first, and money committed to one offering is money unavailable for the other. The sequencing last week was pointed: OpenAI held meetings with long-only and sovereign wealth funds during the same days Anthropic was hosting its own investor day. Some investors read the push as an effort to lock in capital before Anthropic's listing publishes its financials and the two companies' numbers can be compared side by side.
Existing backers are expected to anchor the round. SoftBank Group and Abu Dhabi-based MGX are in talks to participate, according to one of the people Reuters cited. OpenAI and SoftBank declined to comment on the report.
The pitch and the need
OpenAI is selling growth. The company has told investors that revenue has steepened since the launch of its GPT-6 Astra model; according to the reporting, its annualized revenue run rate stands at about $50 billion and is expected to reach $70 billion by the end of the year. Those figures are the company's own, shared in investor meetings, and have not been independently audited.
The need is as large as the pitch. OpenAI has committed to infrastructure spending on a scale that dwarfs its revenue, and the new capital would fund those commitments and strengthen its balance sheet. There is also a defensive reason: if technology markets deteriorate further, OpenAI's own planned listing in 2027 could slip — and a company that has already raised at $1.4 trillion can afford to wait, while one that has not cannot. Rising interest rates, volatile tech stocks and growing scrutiny of AI valuations form the backdrop; both labs are pursuing trillion-dollar price tags into a market that is asking harder questions than it did a year ago.
What happens next
The comparison Anthropic's listing will force is not obviously unflattering to Anthropic. Its draft prospectus, reviewed by the Wall Street Journal, showed quarterly revenue of $16.8 billion in the third quarter, up from $11.6 billion in the second, with annualized revenue reported around $65 billion by July — ahead of the run rate OpenAI is pitching. The same filing showed a net loss of $80.7 billion for the first half of the year, though much of it stemmed from accounting adjustments tied to the financial instruments used to raise capital rather than from operations alone. In other words, the public numbers will show a company growing at least as fast as its rival while spending at a similar, extraordinary scale.
If OpenAI closes on schedule, the two rivals will have raised or listed within days of each other, and investors will effectively be asked to price both companies at once. Anthropic's IPO, which some estimates value as high as $2 trillion, will put audited numbers on one side of that comparison — something the private market has never had for either lab. OpenAI's round, if it lands at $1.4 trillion, sets the mark the public market will be measured against.
The takeaway
This is no longer a story about who has the better model. It is a story about who controls the calendar. OpenAI is spending speed — closing a $30 billion round at unusual pace — to buy position before Anthropic's numbers become public. Whether investors reward the urgency or discount it will say a great deal about how much of the AI boom still runs on momentum, and how much now runs on evidence.