OpenAI revenue run rate tops $40 billion ahead of $1 trillion IPO push
OpenAI's annualized revenue run rate has exceeded $40 billion, marking a significant increase from $24 billion in late March. This growth is driven by coding software, subscriptions, and advertising, despite falling AI model prices due to competition from Chinese rivals like DeepSeek. The company aims for a $1 trillion IPO valuation, supported by usage surges that offset price cuts, though it faces massive compute costs totaling $600 billion through 2030.

*this image is generated using AI for illustrative purposes only.
OpenAI’s annualized revenue run rate has surpassed $40 billion as the company advances preparations for its initial public offering. The disclosure highlights the firm’s substantial top-line growth trajectory leading up to its planned market debut, with President Greg Brockman stating the run rate jumped more than 20% in July alone.
The $40 billion figure represents roughly double the company's revenue level at the end of 2025. This acceleration implies the run rate has grown at least 67% since late March, when OpenAI reported generating $2 billion per month, or roughly $24 billion annualized. At that time, the company had more than 900 million weekly ChatGPT users and over 50 million paying subscribers, with enterprise customers accounting for more than 40% of revenue.
Revenue Drivers and Price Dynamics
The recent acceleration has been driven partly by OpenAI’s coding software, subscription sales and emerging advertising business, while demand for agents including Codex and ChatGPT Work has also jumped. This growth occurs even as the price of AI falls; prices for leading U.S. models have dropped by almost a quarter since mid-July, according to Silicon Data’s token price index.
Intensifying competition from cheaper Chinese rivals such as DeepSeek and Moonshot has pressured pricing. Companies including DoorDash (NASDAQ: DASH) and Airbnb (NASDAQ: ABNB) have started using Chinese-made models to rein in their AI bills. In response, OpenAI cut the price of GPT-5.6 Luna by 80% and Terra by 20%, while leaving its flagship Sol unchanged. Competitor Anthropic scrapped a planned September price increase for Sonnet 5 and launched Opus 5 at half the price of its top model, Fable 5.
What the Numbers Show
The central test of OpenAI’s reported push toward a $1 trillion initial public offering is whether explosive growth in usage can outrun falling prices and heavy compute costs. OpenAI states that improvements to its inference systems have reduced the end-to-end cost of serving GPT-5.6 by 20% and lifted token-generation efficiency by more than 15%.
Early data suggests price cuts are stimulating additional usage. TD Cowen, analyzing OpenRouter data after the July 30 cuts, found Luna consumption jumped roughly 14-fold while Terra usage rose about fivefold. The analysts estimated OpenRouter revenue climbed 34% for Luna and 45% for Terra versus the preceding seven days. This indicates that volume growth is currently offsetting lower per-token prices.
Valuation and Market Outlook
The Microsoft (NASDAQ: MSFT)-backed startup reportedly reached an $852 billion valuation in March. A $1 trillion listing would value the company at roughly 25 times its current annualized revenue run rate. The stakes are heightened by OpenAI’s enormous infrastructure bill: the company is targeting roughly $600 billion in compute spending through 2030.
Market sentiment reflects uncertainty regarding the timeline and scale of the offering. Traders on Polymarket currently see a 17% chance that OpenAI completes an IPO this year, with $2.7 million in volume traded. A separate market puts the chance that OpenAI’s valuation reaches $1 trillion by year-end at 65%, while traders see roughly a 30% chance of $1.5 trillion.
How will OpenAI's $600 billion compute spending plan through 2030 impact its path to profitability and free cash flow ahead of the IPO?
To what extent will the aggressive price cuts by competitors like Anthropic and Chinese firms erode OpenAI's pricing power and margins in the enterprise sector?
Will the 40% revenue contribution from enterprise customers be sufficient to stabilize growth if consumer subscription churn increases due to cheaper alternative models?

































