Reports dated October 9, 2026, said OpenAI was negotiating to raise at least $30 billion in new funding. Revenue annualized from its results at the end of September was about $50 billion, and the company is said to be targeting at least $70 billion by year-end, driven by expansion of its enterprise business.
How to Interpret the Difference Between $50 Billion and $70 Billion
The first thing to note about these figures is that annualized revenue is not the same as revenue actually earned over a full year. Annualized revenue is a measure of business scale based on the assumption that current monthly revenue will continue for 12 months. The figure of about $50 billion is not revenue confirmed in annual financial results.
There is another caveat with the initially reported figure of about $70 billion. It is said to have been adjusted for revenue-recognition methods to make it easier to compare with rival Anthropic. It does not mean that actual annualized revenue at the end of September was about $70 billion.
The difference arises in sales made through cloud providers and similar companies. Anthropic records the full amount paid by customers as revenue and treats the cloud providers’ share as an expense. OpenAI, by contrast, records only its own share as revenue in some partner transactions. Both approaches are said to comply with U.S. accounting standards, with the treatment depending on which party is responsible for customer relations and service delivery in a given transaction.
In other words, simply placing the revenue figures side by side does not provide a like-for-like comparison of business scale. The goal of reaching at least $70 billion by year-end also needs to be considered separately from the historical figure adjusted for comparison.
Enterprise Business Drives Growth
Reports say overall annualized revenue rose 77% in the third quarter, while enterprise revenue increased 107%. The materials provided do not specify the comparison period, so the figures cannot definitively be described as year-over-year growth, but enterprise growth outpaced the overall figure.
The usage figures OpenAI reportedly shared at a developer event are also substantial: ChatGPT has more than 1.2 billion weekly users; ChatGPT Work and the coding assistant Codex have a combined total of more than 35 million weekly users; and 2.5 million companies use the company’s products.
However, user numbers and revenue are not the same metric. Separating broad adoption, including free users, from the payments businesses make for work purposes helps clarify the focus of this growth. Reports say that expanding business with companies that integrate AI into their work and continue paying for it is driving revenue higher.
A $30 Billion Fundraising Round and Caution Over an IPO
In the new funding talks, OpenAI is said to be targeting a valuation of $1.4 trillion before the investment. The targeted fundraising amount of at least $30 billion and the valuation assigned to the company as a whole are separate figures.
In March 2026, OpenAI was reported to have raised up to $122 billion at a post-money valuation of $852 billion. The current target is higher, but pre-money and post-money valuations are calculated on different terms and cannot be compared on a straightforward like-for-like basis. The materials provided do not identify the investors in the new talks or their final terms.
Meanwhile, the initial public offering is said to have been postponed until the following year. CEO Sam Altman reportedly cited safety risks, but there are also accounts that discussions about the delay were underway before the recent cybersecurity issue. It cannot be concluded that safety was the sole reason for the postponement.
Investment Returns Cannot Be Measured by Revenue Growth Alone
Reports say technology stocks came under selling pressure after annualized revenue of about $50 billion was reported, with semiconductor stocks falling by several percentage points. However, share prices move for multiple reasons, so it cannot be concluded that this report alone caused the decline.
When assessing the growth of AI companies, revenue growth needs to be considered alongside the spending required to generate that revenue. Increased usage creates more revenue opportunities, but training AI models and generating responses require computing infrastructure. For companies facing massive data-center-related spending, higher revenue does not automatically mean higher profits.
From a business customer’s perspective, the reason to keep paying is whether the company can verify shorter work times or improved outcomes. The materials show growth in enterprise revenue, but do not provide specific figures for productivity gains achieved by customers or the returns after deducting OpenAI’s spending on computing infrastructure.
Comments