OpenAI in Talks for Huge Investment Round Valuing It Up to $300 Billion
SoftBank would lead $40 billion round for ChatGPT maker, some of which would go to Stargate AI infrastructure venture
2 min
OpenAI is in early talks to raise up to $40 billion in a funding round that would value the ChatGPT maker as high as $300 billion, according to people familiar with the matter.
SoftBank would lead the round and is in discussions to invest between $15 billion and $25 billion. The remaining amount would come from other investors.
The two companies were recently in talks to value OpenAI as high as $340 billion, one of the people familiar with the matter said. After The Wall Street Journal published that figure in an earlier version of this story, the person said newer negotiations lowered the proposed valuation to as much as $300 billion.
The Japanese company is helping assemble investors for the rest of the round, one of the people said. The discussions are still in flux and could fall apart, the person said.
The $300 billion valuation would include the cash OpenAI raises in the round.
OpenAI was last valued at $157 billion in October, when it raised $6.6 billion . Roughly doubling its value in just a few months would be extraordinary even by the standards of Silicon Valley’s current AI boom.
The funding will be used in part to help OpenAI fulfill its roughly $18 billion commitment to Stargate , a joint venture with SoftBank and others to finance the construction of new data centers in the U.S. powering OpenAI’s technology. The startup also expects to use the cash to fund its money-losing business operations.
At $300 billion, OpenAI would be the second-most valuable startup in the world, behind only Elon Musk’s SpaceX, according to the data provider CB Insights. A funding round of this size would be the largest in Silicon Valley history, according to PitchBook, and blow past OpenAI’s previous fundraising record achieved in 2023, when it raised $10 billion from Microsoft .
OpenAI is attempting to raise the cash after AI models released by the Chinese firm DeepSeek led to a selloff in big tech stocks , including Nvidia , earlier this week. DeepSeek’s success with cheaply made and free-to-use AI technology has led many investors and executives to question the big-spending strategies of OpenAI and other U.S. developers.
OpenAI expected to lose around $5 billion last year on revenue of $3.7 billion, The Wall Street Journal reported in October . At the time, it projected its revenue would grow to $11.6 billion this year.
The funding talks mark a quickly deepening relationship between OpenAI chief executive Sam Altman and SoftBank CEO Masayoshi Son , who appears to have picked the ChatGPT maker as his vehicle to bet big on the AI industry.
SoftBank has separately committed to contribute some $18 billion to Stargate, which Son announced at the White House earlier this month, alongside Altman and Oracle executive chairman Larry Ellison . The project’s partners have committed to invest $100 billion in U.S. data center projects for OpenAI and plan to invest up to $500 billion over four years.
In October, SoftBank contributed $500 million to a $6.6 billion funding round for OpenAI. The following month, it launched a $1.5 billion tender offer to purchase existing shares from employees.
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
The debt behind the AI build-out
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
Inflation changes the calculation
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
China adds another source of pressure
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
A reset rather than the end of the boom
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Fact box
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
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