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The Decoder· Matthias Bastian·· 3 小时前精选AI 评分81

Anthropic Q3 收入达 $16.8B 但增速放缓,11 月 IPO 估值预期或下调

Anthropic's Q3 revenue hits $16.8B but growth slows ahead of planned November IPO

AI 导读

Anthropic 在面向潜在投资者的会议上披露 Q3 收入达 $16.8B,环比增长约 45%,远低于 Q2 超 140% 的环比增速。据 The Information 与 Financial Times,公司前三季度调整后营业利润率为 11%,连续两季调整后盈利,Q3 每支出 1 美元算力产生 $1.70 收入。

推荐理由

文章汇总了 Anthropic 三季度收入、利润率与 IPO 估值预期变化,读者可据此了解其增长放缓与市场反应。

正文 · 原文

Slowing growth and a tough market are hurting Anthropic's valuation ahead of its planned November IPO.

Anthropic shared its quarterly numbers with potential investors at a private meeting in San Francisco, according to multiple US media reports. Third-quarter revenue hit $16.8 billion. That marks a roughly 45 percent jump from the second quarter and is more than 3.6 times the company's total annual revenue for 2025.

Growth has slowed, though. In the second quarter, surging demand for the developer tool Claude Code had pushed revenue up by more than 140 percent compared to Q1. Anthropic is far from that pace now, though a summer slowdown is one likely factor since people typically work less during those months and burn through fewer tokens. OpenAI also launched a strong competitor with Astra in September, which Anthropic only successfully countered in late September with Opus 5.5.

Profitable inference shows AI models can make money

According to The Information, Anthropic reported an adjusted operating margin of 11 percent for the year through Q3. That number leaves out major costs like stock-based compensation, but it shows the company is moving toward profitability.

The Financial Times reports this was the second straight quarter of adjusted profitability for the AI lab. The company is cash-flow positive, too. During the third quarter, Anthropic generated $1.70 in revenue for every dollar it spent on compute.

This is good news for the AI industry because it shows trained models can turn a profit despite months of price wars. Plenty of caveats remain, though, including steep training and staff costs and the risk that open-weight alternatives start replacing proprietary models like Claude.

Blocking model theft will hurt Anthropic's short-term revenue

Anthropic also estimates that 5 to 7 percent of its revenue comes from distillation. In this process, other companies use Anthropic's AI to extract data about how it works and train their own models.

Anthropic has repeatedly accused Chinese AI labs of copying its models this way. Still, the company recently rolled out effective countermeasures, raising questions about why Anthropic spent so much time lobbying against distillation if it had the tools to stop the practice all along.

That said, distillation revenue will likely drop now and weigh on the current quarter's numbers, Anthropic told investors. Over the long run, blocking distillation should pay off by making it harder for rival model makers to match Claude's quality.

Investor skepticism could force a lower IPO price

The planned IPO, which The Information says is set for November before Thanksgiving, will be the biggest test yet of investor appetite for the AI boom. Anthropic's private valuation jumped to $965 billion in May, up from under $20 billion just two years earlier. Some bankers even floated a $2 trillion IPO.

But the now presented revenue numbers reportedly disappointed some potential investors. Several now expect Anthropic's banking advisors to lower valuation expectations to possibly under $1.5 trillion, especially since the company did not discuss its September annualized revenue rate or a full-year outlook. In July, that rate was reportedly $65 billion.

The timing for an IPO is hardly ideal. Inflation stays high, borrowing costs are rising, public sentiment toward AI remains more negative than positive, and unsolved cybersecurity risks pose a real operational threat. Moreover, OpenAI, Anthropic, Google, and others have been locked in a brutal price war for months while open models keep closing the performance gap. Still, people will almost certainly use more AI in the future rather than less as improving model capabilities work their way into more everyday office jobs.

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来源:The Decoder · the-decoder.com