Anthropic raises $30 billion in Series G at a $380 billion post-money valuation

Original: Anthropic raises $30 billion in Series G funding at $380 billion post-money valuation View original →

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AI Mar 23, 2026 By Insights AI 1 min read 1 views Source

Anthropic said on February 12, 2026 that it raised $30 billion in Series G funding at a $380 billion post-money valuation. The round was led by GIC and Coatue, with D. E. Shaw Ventures, Dragoneer, Founders Fund, ICONIQ, and MGX listed as co-leads. Anthropic says the capital will be used to accelerate frontier research, product development, and infrastructure expansion.

The announcement was also a business performance update. Anthropic said its run-rate revenue has reached $14 billion and has grown more than 10x annually in each of the last three years. The company said the number of customers spending more than $100,000 annually on Claude has grown 7x over the last year, and the number of customers spending more than $1 million annually now exceeds 500. Anthropic also said eight of the Fortune 10 are Claude customers.

  • Series G size: $30 billion
  • Post-money valuation: $380 billion
  • Claude Code run-rate revenue: more than $2.5 billion
  • Claude is available across AWS Bedrock, Google Cloud Vertex AI, and Microsoft Foundry

The significance of the raise is that Anthropic is pitching itself not just as a model maker, but as an enterprise AI platform company. In the same announcement, it tied Claude Code, Claude for Work, API adoption, healthcare expansion, and multi-cloud availability into one operating story. Anthropic also emphasized a diversified hardware stack built on AWS Trainium, Google TPUs, and NVIDIA GPUs.

Most of the growth and customer metrics in the announcement are company-reported and should be read that way. Even so, the raise is a strong signal of how capital-intensive the 2026 AI market has become, especially for labs competing on enterprise distribution, coding agents, and infrastructure footprint. The next question is how quickly Anthropic converts that capital into stronger models, broader deployment, and durable share in production AI workflows.

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