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Seven major technology companies, including Google, Nvidia, Microsoft and AMD, have entered into agreements to purchase an aggregate USD 26 billion of Anthropic's Class N common stock through a concurrent private placement alongside its proposed initial public offering (IPO), according to the company's roadshow presentation.
The other companies named in the agreements are Broadcom, Micron Technology and TSMC Partners. The disclosure highlights the participation of major technology players in Anthropic's fundraising as the artificial intelligence company prepares to enter the public markets. According to the offering summary, Anthropic is proposing to sell 825 million shares of Class A common stock in its IPO, comprising 97.1 per cent primary shares and 2.9 per cent secondary shares. The proposed price range is USD 70 to USD 78 per share, with the offering expected to be priced on November 18, 2026. The company plans to use the proceeds for general corporate purposes, including working capital, operating expenses and capital expenditure. Investments in computing and infrastructure are specifically listed among the intended uses. The proceeds will also cover tax withholding and remittance obligations linked to the settlement of certain outstanding restricted stock units. The roadshow presentation also outlines Anthropic's strategy to expand its computing capacity through multiple hardware suppliers. Its computing pool includes Amazon Web Services' Trainium chips, Google's tensor processing units (TPUs), and graphics processing units (GPUs) from Nvidia and AMD. Anthropic said the shared computing pool would allow resources to be directed towards frontier research, model development, customer demand and internal use of Claude, depending on workload requirements and price-performance considerations. The company also presented its enterprise strategy around APIs, software development kits and managed AI agents, allowing businesses to build applications with varying levels of control and autonomy. Its platform includes capabilities such as memory, tool use, web search and prompt caching. The presentation identifies autonomous software development, cybersecurity, drug discovery, advanced disease detection, financial and legal services, and supply chain automation among areas where AI systems could take on increasingly complex tasks. (ANI)
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