OpenAI is targeting $600 billion in computing spending through 2030 as it prepares for a potential IPO that could value the AI leader at up to $1 trillion.
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| Revenue has surpassed expectations, but soaring inference costs are squeezing margins as OpenAI embarks on one of the largest infrastructure expansions in tech history. Image: CH |
Tech Desk — February 21, 2026:
OpenAI is preparing for a scale of expansion that could redefine the economics of artificial intelligence. The ChatGPT maker is targeting approximately $600 billion in total computing expenditure through 2030, according to a source familiar with the matter, as it positions itself for a potential initial public offering that could value the company at up to $1 trillion.
The financial backdrop reflects both momentum and mounting strain. OpenAI reported $13 billion in revenue in 2025, exceeding its earlier $10 billion projection. Annual spending reached about $8 billion, slightly below its $9 billion target. The revenue outperformance signals surging demand across both consumer and enterprise segments, yet the scale of planned infrastructure investment underscores how capital-intensive advanced AI has become.
The company expects to generate more than $280 billion in cumulative revenue by 2030, split nearly evenly between consumer offerings and enterprise services. Its deep partnership with Microsoft remains central to that strategy, providing cloud infrastructure, enterprise distribution, and integration across widely used productivity platforms. For investors, the balance between consumer growth and enterprise stability may be critical to sustaining the lofty valuation targets being discussed.
At the same time, OpenAI’s economics reveal the challenges of operating at the frontier. Inference costs — the expenses associated with running AI models after they are trained — reportedly quadrupled in 2025. As a result, adjusted gross margins declined to 33 percent from 40 percent a year earlier. The figures highlight a structural tension: the more AI systems are used, the more computing power they require, placing direct pressure on profitability even amid rapid revenue expansion.
The infrastructure push is unfolding alongside a deepening financial alliance with Nvidia, which is reportedly nearing a $30 billion investment in OpenAI as part of a broader fundraising round exceeding $100 billion. That round could value the company at roughly $830 billion, potentially making it one of the largest private capital raises in history. For Nvidia, whose advanced chips power most large-scale AI systems, the investment would further cement its central role in the AI ecosystem. For OpenAI, it secures both capital and access to critical hardware supply at a time when global demand for high-performance semiconductors remains intense.
Chief Executive Sam Altman has previously outlined even more expansive ambitions, stating that the company is prepared to invest as much as $1.4 trillion to build 30 gigawatts of computing capacity, an amount of power comparable to that used by roughly 25 million U.S. homes. While the $600 billion target represents a nearer-term milestone, it reflects the same industrial-scale vision. Artificial intelligence, in this model, is no longer merely software; it is a vast network of data centers, energy infrastructure, and semiconductor supply chains.
The prospect of a $1 trillion IPO will ultimately depend on whether OpenAI can transform unprecedented capital spending into durable competitive advantage. Investors are likely to scrutinize whether efficiency gains in model design and hardware optimization can reverse margin compression, and whether enterprise contracts can deliver predictable long-term cash flow. The company’s ability to build a computing moat that competitors struggle to replicate may prove decisive.
OpenAI’s expansion signals that the race for AI dominance has evolved into a contest measured not only in algorithms, but in gigawatts and billions of dollars. The coming years will test whether such extraordinary infrastructure investment can deliver equally extraordinary returns — or whether the costs of scaling intelligence will reshape the financial logic of the technology industry itself.