Anthropic Raises $30B, Reaches $380B Valuation
AI research company Anthropic has closed a $30 billion funding round, bringing its valuation to $380 billion. The mega-round underscores continued investor appetite for leading foundation model developers. The company's rapid rise highlights the intense capital concentration in the AI sector.
- This Series G round was led by Singapore's sovereign wealth fund GIC and private equity firm Coatue, with notable participation from D.E. Shaw Ventures, ICONIQ, Microsoft, and Nvidia. The company has now raised a total of approximately $67.3 billion over 17 funding rounds since its founding in 2021 by former OpenAI executives. - Anthropic's growth is heavily enterprise-focused, with roughly 80% of its revenue coming from business clients. It reports a $14 billion revenue run rate and has seen a seven-fold increase in customers spending over $100,000 annually. - A key driver of its enterprise success is Claude Code, which has captured an estimated 54% of the coding automation market, helping Anthropic overtake OpenAI in enterprise LLM spending share in 2025 (40% vs. 27%). - To power its models, the company is making massive infrastructure investments, including a $50 billion plan to build custom data centers in the U.S. with partner Fluidstack. This move aims to increase compute independence and optimize performance for its specific AI workloads. - The company also maintains a deep partnership with Amazon, which has invested $8 billion and is Anthropic's primary cloud provider. AWS built an $11 billion data center in Indiana running on its custom Trainium2 AI training chips specifically for Anthropic's use. - This close collaboration with AWS on hardware is converging toward a custom-silicon program, allowing Anthropic to benefit from tight hardware-software co-design, similar to Google's advantage with its TPUs. - Beyond its core models, Anthropic is developing an ecosystem strategy through the Model Context Protocol (MCP), an open-source standard it donated to the Linux Foundation to help AI applications connect with external systems and data sources.