Why Anthropic Wants Decart In A Potential $6 Bn AI Deal

Anthropic is in talks to acquire artificial intelligence startup Decart AI for about $6 billion, according to a Bloomberg report. The deal has not been finalised and the talks could still fall through.

If completed, the acquisition would be Anthropic’s largest known deal and would come as the AI company prepares for a potential initial public offering (IPO). Anthropic has generally been cautious about large acquisitions but has been spending heavily on computing capacity to develop AI products and handle growing customer demand.

Decart’s Technology Could Help Cut AI Costs

Decart develops software designed to make AI chips work more efficiently, potentially helping Anthropic get more output from its existing computing infrastructure, according to the news agency. Decart’s team is expected to join Anthropic’s inference and performance organisation, one of the people said.

The startup also works on generative video and has developed so-called world models that can modify live video feeds instantly. Bloomberg reported that this work highlights the startup’s infrastructure and AI engineering capabilities.

Decart was founded in 2023 by Israeli engineers Dean and Orian Leitersdorf and Moshe Shalev. In May, it raised $300 million in a funding round led by Radical Ventures, with Nvidia, Atreides Management, Valor Equity Partners and Adobe Ventures among the other participants. Earlier investors including Sequoia Capital, Benchmark and Zeev Ventures also joined the round.

AI Compute Race Drives Spending

The funding round valued Decart at nearly $4 billion, according to the Wall Street Journal, up from $3.1 billion in August 2025. A potential $6 billion acquisition would therefore represent a significant premium over its latest reported valuation.

The talks also highlight the growing pressure on AI companies to secure computing power. Anthropic and rival OpenAI have each committed to spending tens, and potentially hundreds, of billions of dollars on data centres and expensive AI chips.

Both companies are increasingly using hardware from multiple providers as demand for computing capacity rises. While the spending is aimed at supporting increasingly powerful AI models, the heavy costs could also become a major factor for the companies as they prepare for potential listings on Wall Street.