OpenAI is “in discussions” to raise up to $100 billion at a potential $830 billion valuation, reports the Wall Street Journal, confirming earlier signals by The Information. If and when closed, it would be one of the largest private financings in history and a bet on the strength of ChatGPT. It would fortify the company as it races to scale infrastructure, launch more competent models, and keep its enterprise footing.
Why this raise and why now for OpenAI’s expansion
The capital requirements are clear: compute at never-before-seen scale, secure access to power and data center capacity, and the growing inference bill as usage rises. Inference charges, unlike training costs, will add up every time a model provides a response to a query. SemiAnalysis states that inference can become the largest part of companies’ AI spend at scale, a fact that is forcing leaders to secure cash by moving off running usage on cloud credits.
OpenAI has signaled ambition beyond model training to upstream planned industrial capability, including chips and energy. Executives have mentioned global relationships and long-term supply contracts to ensure their anticipated numbers of semiconductor and electric units keep latency low and availability high. Such a raise would back multi-year contracts across GPUs, memory, networking, and electricity procurement.
Who might fund it, and what strategic investors could do
OpenAI could go to the sovereign wealth funds for the round, according to the Wall Street Journal. Its backers are not named, but investors such as the Public Investment Fund (PIF), Mubadala, Qatar Investment Authority (QIA), GIC, and Temasek have been active in late-stage technology financing. Strategic investors might also get involved if the deal structure locks in capital to buy compute, chips, or cloud distribution.
Media reports have also floated an unrelated investment from Amazon that could include access to the company’s in-development AI silicon. Any new money would be in addition to OpenAI’s longstanding partnership with Microsoft, which has supplied capital and Azure compute resources. In private markets, PitchBook data show that OpenAI now has over $64 billion in cash and was valued at roughly $500 billion in a prior secondary.
Valuation math and business trajectory for OpenAI
At an $830 billion valuation, on an annualized revenue run rate of nearly $20 billion, as multiple outlets have reported, that would make the sales multiple well north of 40x. Bulls contend that frontier model providers deserve premium multiples for network effects in data, tooling, and developer ecosystems — plus the option value of new product lines (from assistants to enterprise platforms).
Skeptics argue that unit economics are still unstable at larger model sizes, and that inference costs, customer churn, and price compression might weigh on margins.
OpenAI’s unusual governance and capped-profit structure introduces another twist: investor returns are capped beyond certain thresholds. That framework can impact how rounds are designed, the distribution between primary and secondary elements, and how late-stage capital is priced. That said, there has still been fierce demand for exposure to core AI assets from late-stage investors in search of rarefied but substantial growth stories.
Constraints on chips, energy supply, and market sentiment
Hardware remains the chokepoint. High bandwidth memory supply and advanced packaging capacity have limited GPU availability, according to TrendForce and other supply chain monitors. Memory vendors and some foundries are adding capacity, but delivery schedules and yields remain a planning risk. Power is another chokehold: dense AI clusters demand steady power and cooling, forcing operators to commit to long-term energy contracts or tap unconventional types of generation.
Investor sentiment on AI is constructive for the long term, but the level has become more discerning. It also has questions over whether hyperscalers’ and model labs’ capex driven by debt can increase as fast as demand. Enterprise usage is climbing — but uneven across verticals — and CIOs are evaluating ROI, data privacy, and integration costs. Analysts at firms such as Gartner and IDC are still forecasting tens of billions in AI infrastructure spend over the next few years; however, the pace and mix of that spend is changing.
What a $100 billion deal would signal about the market
An effective $100 billion raise could herald the next era in frontier AI: the centralization of capital and capacity in a handful of platforms that can fund the full stack, from chips and data centers to software and distribution. For customers, that might result in faster release cycles, bigger windows for context, better reliability, and tighter integrations with productivity suites and developer tools.
For the broader economy, the stakes are more than valuation optics. Generative AI, McKinsey has estimated, could add trillions in annual value in areas from customer support and coding to content creation. Realizing the promise of that potential does, however, demand industrial-scale infrastructure, disciplined product packaging, and consistent progress on safety and governance. This prospective raise is a wager that OpenAI can perform on all three — globally and urgently.
