Anthropic Reportedly Pays $6 Billion to Acquire Decart, Making History’s Largest AI Infrastructure Deal

Bloomberg reported, citing sources, that Anthropic is negotiating the acquisition of peer AI startup Decart, with the deal valued at around $6 billion. If finalized, this would become Anthropic’s largest acquisition to date, coming just ahead of its highly anticipated initial public offering.

Historically cautious about large-scale mergers and acquisitions, Anthropic has nonetheless been investing heavily in computing power in recent years to develop new products and serve customers.

Sources said Decart’s software enables chips to operate more efficiently, thereby reducing the cost of training artificial intelligence models. This technology will help Anthropic’s existing infrastructure handle greater demand. After the acquisition closes, Decart’s team will join Anthropic’s inference and performance division.

Decart also focuses on generative video technology, using so-called 'world models' to modify live video streams in real time. Sources indicated this capability reflects Decart’s possession of top-tier infrastructure engineering talent.

Representatives from both Anthropic and Decart declined to comment.

In May, Decart announced it had raised $300 million in a funding round led by Radical Ventures. Investors included NVIDIA (NVDA-US), Atreides Management, Valor Equity Partners, and Adobe Ventures. Existing investors Sequoia Capital, Benchmark, and Zeev Ventures also participated in this round.

According to The Wall Street Journal, the funding round valued the startup at nearly $4 billion, up from $3.1 billion in August 2025.

Founded in 2023, Decart was co-founded by three Israeli engineers: brothers Dean Leitersdorf and Orian Leitersdorf, along with Moshe Shalev.

Both OpenAI and Anthropic have committed to spending tens or even hundreds of billions of dollars building data centers equipped with expensive chips. As computational demand surges, both companies are increasingly relying on hardware from multiple suppliers to meet massive computing needs.

As these two AI startups prepare for their Wall Street debut in the coming months, the enormous expenditures deemed essential by leadership to build and support cutting-edge AI models could also pose financial pressures.