OpenAI and Anthropic Post Soaring Revenue and Deepening Losses

OpenAI lost USD 10.9 billion on an adjusted operating basis in the third quarter of this year, even as revenue climbed roughly 50% quarter over quarter to USD 10 billion. Anthropic swung from a USD 974 million operating profit to a USD 567 million operating loss in the same period, according to an amended registration statement filed with the U.S. Securities and Exchange Commission. The two figures, reported by Bloomberg and other foreign media on November 12, frame the central dilemma of the artificial intelligence industry in 2026: revenue is compounding faster than almost any business in history, and profitability is moving in the opposite direction.

The losses are not a sign of weak demand. They are the price of a competitive structure that forces every major player to keep spending on computing infrastructure and to keep cutting prices, regardless of the financial consequences. Industry observers quoted in the coverage compare the dynamic to the "game of chicken" that consolidated the memory semiconductor market into a three-company oligopoly after two rounds of ruinous competition between 2007 and 2012.

How fast is revenue actually growing?

Fast enough to mask the deterioration, for now.

OpenAI's third-quarter revenue of USD 10 billion compared with USD 6.7 billion in the second quarter, a gain of approximately 50%, and stood at about 2.6 times the year-earlier figure. The company attributed growth to increased demand for its latest AI models, including GPT-5.6 and Astra, and the resulting expansion in application programming interface revenue. Enterprise AI services and advertising also contributed. OpenAI said its enterprise business doubled in size during the quarter and accounted for more than half of total revenue.

Anthropic's numbers are larger and its deceleration is visible. According to the amended IPO registration statement, third-quarter revenue reached USD 16.96 billion, up approximately 47% from USD 11.6 billion in the previous quarter. Quarterly growth slowed from 144% in the second quarter to 47% in the third. Increased usage of the AI coding tool Claude Code and of enterprise API services indicates, in the filing's framing, that the revenue growth trajectory remains intact.

Where are the losses coming from?

Two forces are eroding margins at once: computing costs and price competition.

OpenAI's adjusted operating loss widened by approximately 8%, from USD 10.1 billion in the second quarter to USD 10.9 billion in the third. Its adjusted operating margin improved from -150% to -109%, which means losses still exceeded revenue. Anthropic's swing to a USD 567 million operating loss came despite the near-USD 17 billion top line.

The cost side is stark. Anthropic procured USD 5 billion worth of computing resources in the third quarter alone through relatively expensive short-term contracts. Its cumulative computing and infrastructure costs for January through September surged 329% year on year to USD 18.808 billion.

The pricing side is equally aggressive. A push by Chinese companies offering low-cost models, combined with intensified competition among global AI developers for enterprise customers, has accelerated fee reductions across the market:

• In July, OpenAI cut API pricing for GPT-5.6 Luna by 80% and for GPT-5.6 Terra by 20%.
• In August, OpenAI lowered pricing for GPT-5.6 Sol by more than 20%.
• Anthropic disclosed in its amended registration statement that price cuts for new models and contract discounts for enterprise customers offset USD 600 million of its revenue increase from the second to the third quarter.
• Fable 5.1, released by Anthropic in September, reduced the cost of typical tasks by approximately 25% and of complex coding tasks by up to 45% compared with its predecessor.
• Opus 5.5, unveiled the same month, cut costs per task by approximately 40%.

Anthropic is, in effect, discounting its way through its own growth.

Why can't anyone stop investing?

The structural characteristics of the AI industry explain the recklessness. Companies must continually secure large-scale computing resources and data center infrastructure to develop high-performance models and expand services. Financial strength determines technological competitiveness and market position.

As model performance has improved rapidly and product release cycles have shortened, established leaders must invest again immediately whenever a competitor narrows the technology gap. That is why companies prioritize market share and customer acquisition over short-term profitability.

Market observers liken the dynamic to a prisoner's dilemma. All players could ease their financial burdens by jointly moderating investment. But any single company that cuts spending while rivals continue faces a substantial risk of losing its technological competitiveness and its customer base.

One market expert, quoted in the report, put it directly: "AI companies are engaged in a game of chicken, continuing to invest while accepting enormous losses until the other side gives up first." The expert added: "With the AI market's technical standards and long-term competitive hierarchy still undecided, companies appear more concerned about being left behind in the future market than about immediate returns on investment."

Is Big Tech feeling the same strain?

Yes, and the numbers are larger.

Microsoft, Alphabet, Amazon and Meta together spent USD 201.9 billion in capital expenditure in the third quarter of this year, more than double the year-earlier figure. That sum exceeded the USD 175.5 billion in cash the four companies generated from operating activities during the same period. The gap is the strain, made visible.

Individual balance sheets show where the pressure concentrates:

• Alphabet posted negative free cash flow of USD 9.1 billion in the third quarter.
• Meta recorded a cash outflow of USD 1.2 billion.
• Amazon's free cash flow over the latest 12 months swung to a deficit of USD 42.4 billion from a surplus of USD 14.8 billion in the corresponding year-earlier period.
• Only Microsoft held a relatively stable position, generating USD 18.6 billion in free cash flow in the quarter.

Does the memory-chip precedent predict the outcome?

The closest historical analogue, according to the observers cited, is the DRAM industry.

In 2007, expanded production by Taiwanese semiconductor companies triggered oversupply and a price collapse in the DRAM market. The global financial crisis the following year compounded the damage and sharply eroded profitability across the industry. Germany's Qimonda went bankrupt in 2009. Taiwanese companies absorbed massive losses.

In 2010, increased production by Japanese and Taiwanese companies sparked a second game of chicken. Elpida, which had survived on public funding from the Japanese government, went bankrupt in 2012 and was acquired by U.S.-based Micron.

The consolidation that followed reshaped the market. The global DRAM business, once contested by about 20 companies, came to be dominated by three players: Samsung Electronics, SK Hynix and Micron. Samsung Electronics' share of the global DRAM market rose from approximately 27% in 2007 to around 45% in 2015. The top three companies' combined share reached approximately 95% as of 2015. As competitors exited, oversupply eased, and the surviving companies regained pricing power and profitability.

The implication for AI is uncomfortable and concrete. If the pattern repeats, today's field of well-funded competitors will narrow to a small oligopoly, and the companies with the deepest balance sheets and strongest technology will be the ones still standing when the spending war ends. Every quarter of record losses is, on that reading, a move in a longer game whose winners have not yet been decided.