admin The San Francisco-based company is expected to complete the round as soon as next week, though final terms could still change. The deal, if sealed near the levels under discussion, would more than double Anthropic’s valuation from the $380 billion post-money figure attached to its Series G round in February, when it raised $30 billion from investors including GIC, Coatue, D. E. Shaw Ventures, Dragoneer, Founders Fund, ICONIQ and MGX.
The scale of the proposed financing underlines how quickly investor appetite has shifted towards a small group of frontier AI developers with fast-growing revenue, heavy enterprise adoption and privileged access to computing power. Anthropic, founded in 2021 by former OpenAI employees including Dario Amodei and Daniela Amodei, has built its position around Claude, a family of large language models marketed heavily to businesses, software developers and regulated industries.
The latest talks come after a steep acceleration in Anthropic’s commercial performance. Its annualised revenue run rate has been reported at around $30 billion, compared with about $14 billion at the time of the February funding round and roughly $1 billion at the start of 2025. Run-rate figures are not the same as audited annual revenue, but they have become a key measure for investors assessing how quickly AI subscription, coding and enterprise usage can convert into durable sales.
Claude Code, the company’s software development assistant, has emerged as one of the strongest growth drivers. Demand from programmers and corporate engineering teams has pushed coding tools to the centre of the AI revenue contest, with Anthropic competing against OpenAI’s Codex-related products, Google’s Gemini ecosystem, Microsoft-backed developer tools and a widening field of specialist platforms. Enterprise clients are also using Claude for customer support, document analysis, workflow automation, legal review and internal knowledge systems.
The proposed valuation would put Anthropic ahead of several listed technology giants by market value and close to the upper tier of global corporations, despite remaining privately held and only five years old. Such pricing reflects both optimism about AI demand and concern that only a handful of companies may be able to afford the computing infrastructure required to train and deploy leading models.
Compute access has become Anthropic’s central strategic constraint. The company has expanded partnerships with Google and Broadcom for next-generation chips and large-scale computing capacity, while Amazon has deepened its commercial and investment ties. Amazon has already invested $8 billion in Anthropic and has committed another $5 billion, with scope for up to $20 billion more tied to commercial milestones.
Anthropic has also agreed to pay SpaceX $1.25 billion a month through May 2029 for computing capacity linked to the Colossus and Colossus II data centre clusters. The agreement highlights the extraordinary cost of serving frontier AI models at scale. It also shows how the AI infrastructure market is expanding beyond traditional cloud providers into companies able to assemble power, chips, land and cooling at speed.
The fundraising is taking shape as private capital floods into AI at a pace that has raised both enthusiasm and unease. Supporters argue that Anthropic’s revenue growth, enterprise focus and safety-oriented branding give it a stronger path to monetisation than earlier consumer-led AI platforms. Sceptics point to enormous infrastructure obligations, uncertain margins, regulatory scrutiny and the risk that model capabilities become harder to differentiate as rivals improve.
Competition remains intense. OpenAI continues to command a dominant consumer profile through ChatGPT and has expanded deeper into enterprise services. Google is integrating Gemini across search, cloud and productivity tools. Meta is pursuing open-source and advertising-linked AI strategies, while xAI, Mistral, Cohere and other challengers are pushing into specialised markets. Anthropic’s bet is that safer, more controllable models and business-focused deployment can win large corporate budgets even as the wider market becomes crowded.
