OpenAI is negotiating a new round of funding with investors, targeting a valuation as high as $1.2 trillion, a significant increase from $852 billion in March this year.Article author, source: AIBase
Recently, OpenAI, a leader in the field of artificial intelligence, is engaged in new private funding discussions with investors, targeting a valuation as high as $1.2 trillion. This proposed valuation represents a significant increase from the $852 billion post-money valuation established during its March funding round of $122 billion, and would further solidify OpenAI’s position as the highest-valued private technology company. However, this sky-high valuation hinges on the assumption that its initial public offering (IPO) in 2027 will achieve a comparable valuation. Initially, the advisory team explored the possibility of going public as early as this quarter at a lower valuation, but after comprehensive evaluation, the company has opted to delay the offering until 2027, with CEO Sam Altman explicitly setting $1 trillion as the minimum threshold for going public.
On the capital side, the interests of existing investors are deeply aligned. As the largest single institutional shareholder, Microsoft has invested over $13 billion to hold approximately 27% of the equity; NVIDIA has contributed approximately $30 billion in compute credits. Additionally, SoftBank anchored its March funding round with a $40 billion bridge loan, and Amazon’s $50 billion anchored investment is closely tied to either an IPO or a general artificial intelligence milestone. It should be noted that the $122 billion figure includes significant conditional, deferred, or vendor-linked权益—for example, NVIDIA’s $30 billion primarily consists of compute credits offsetting GPU infrastructure expenses rather than pure cash.
From a financial fundamentals perspective, OpenAI's revenue demonstrates strong growth momentum. As of February 2026, its annualized revenue reached approximately $25 billion, representing about a 92% increase over the past 12 months. First-quarter revenue amounted to $5.7 billion, with the full-year target of $30 billion on track, and some estimates suggest it may have approached $40 billion by mid-2026. Enterprise business has become the core growth driver, accounting for over 40% of revenue and is expected to match consumer business revenue by year-end.
However, accompanied by high growth is a continuously expanding loss. The operating loss in the first quarter of 2026 was approximately $9.3 billion, further widening to about $12.3 billion in the second quarter, with full-year operating losses projected between $27 billion and $33 billion. As inference costs rose to $14.1 billion in 2026, coupled with the company’s strategic plan to achieve 30 gigawatts of computing capacity by 2030, expenditures on computing power and talent have grown in tandem with revenue. Although the gross margin improved from approximately 33% a year ago to about 39% in the first quarter of 2026, every gain in efficiency has been swiftly reinvested into the next round of capacity and research, leading to escalating operating losses. Based on current revenue and a $1.2 trillion valuation, its price-to-sales ratio stands at around 40x, prompting market scrutiny over its high multiple valuation in the absence of a credible path to profitability.
In terms of user base and market competition, OpenAI still holds a dominant position. As of February 2026, ChatGPT reached 900 million weekly active users and surpassed 1 billion monthly active users in May, with over 50 million individual subscribers and 9 million paid enterprise users, and 92% of Fortune 500 companies are using the service. However, its market share faces serious challenges: according to Sensor Tower data, its share of the global AI assistant market dropped below 50% in May to approximately 46%. Meanwhile, competitor Anthropic has surpassed OpenAI in enterprise API spending, with its annualized revenue reaching $30 billion in April 2026 and overtaking OpenAI. Intense market competition has prompted OpenAI to revise its product roadmap twice within six months and adjust the rollout plans for certain features.
Regarding the nature of the losses, the market’s core divergence lies in whether they represent cyclical expansion costs or structural characteristics that cannot self-correct. Analysis indicates that OpenAI’s losses exhibit strong structural traits: on one hand, inference costs rise rigidly with usage scale; on the other, the company has locked in a fixed cost base of 30 gigawatts, obligating it to fulfill these expenses regardless of demand. This model, driven by continuous compute consumption and massive infrastructure expenditures, implies that the substantial losses are not a short-term phenomenon.
Supporters argue that each major technological platform transition has produced dominant giants whose value far exceeded expectations; ChatGPT’s massive user base and enterprise penetration are clear signs of infrastructure-level adoption. Conversely, critics worry that as model capabilities converge and competition intensifies, the high cost base may expose the company to price wars. Overall, the $1.2 trillion valuation reflects not only a bet on OpenAI’s own revenue growth, but also a pricing-in of sustained expansion across the entire AI capital expenditure cycle. The key going forward lies in whether gross margins can further improve, enterprise revenue can continue to catch up, and the loss trajectory can achieve meaningful narrowing.