Anthropic, the AI safety company behind the Claude family of models, is in early discussions with Samsung Electronics to develop a custom artificial intelligence chip built on Samsung’s advanced 2-nanometer process, according to a report from The Information corroborated by Bloomberg and TechCrunch.
What Happened
The talks represent Anthropic’s first serious move into custom silicon after years of relying on Nvidia GPUs and third-party cloud providers for its computational needs. According to sources familiar with the matter, Anthropic has been quietly building an internal chip team, recently hiring Clive Chan — an early member of OpenAI’s chip program — as part of a deliberate engineering buildout. While specific design details remain unresolved, the company is considering Samsung’s state-of-the-art 2nm fabrication process as well as the Korean manufacturer’s advanced packaging facilities.
The project is still in its earliest stages. No silicon design work has begun, no architecture has been finalized, and Anthropic has not yet determined how the chip would integrate into server infrastructure. Crucially, the company may ultimately decide not to proceed at all — a caveat that multiple sources emphasized when speaking to reporters.
Why It Matters
Custom AI silicon has become a strategic priority across the AI industry, as companies seek to reduce their dependence on Nvidia’s dominant GPU architecture — and the costs that come with it. OpenAI and Broadcom recently unveiled Jalapeño, their jointly developed custom AI chip, signaling that the era of AI labs building proprietary hardware is now fully underway. A successful Anthropic-Samsung partnership would give the company direct control over the performance and cost characteristics of its inference infrastructure — a critical competitive advantage as Claude scales across millions of enterprise users.
The timing is notable. Samsung, SK Hynix, and Micron all participated in Anthropic’s $65 billion Series H fundraising round in May 2026, creating a web of financial relationships between the AI company and its potential manufacturing partners. Samsung in particular has been aggressively expanding its foundry business to compete with TSMC, and winning Anthropic as a 2nm customer would be a significant validation of its process technology.
Background and Context
Anthropic’s interest in custom chips is being driven by the same economics facing every frontier AI company: inference at scale is extraordinarily expensive, and GPUs — while versatile — are not optimized for the specific operations that large language models require. A purpose-built chip tuned to Claude’s architecture could dramatically reduce the cost per token, allowing Anthropic to serve more users at higher margins. Samsung posted a record $58 billion profit in Q2 2026, largely on the back of AI chip demand, underscoring how central semiconductor partnerships have become to the AI industry’s infrastructure story.
The 2nm node is currently the most advanced commercially available manufacturing process in the world. Samsung is one of only two foundries — alongside TSMC — capable of producing chips at this density. The choice of 2nm would put any Anthropic chip among the fastest and most power-efficient AI processors ever designed, potentially rivaling Google’s TPUs and Amazon’s Trainium accelerators.
Anthropic is considering Samsung’s 2-nanometer manufacturing process and the Korean conglomerate’s advanced packaging facilities.
The Information
What Comes Next
Even if the Samsung discussions advance, timelines for custom AI silicon are long. Designing, taping out, and qualifying a new chip typically takes two to three years — meaning any Anthropic-branded processor would not reach production until 2028 at the earliest. In the interim, the company is reportedly in parallel discussions with Microsoft and UK-based startup Fractile for chip supply, reinforcing a multi-vendor strategy rather than a single-provider bet.
For critics, the move raises questions about resource allocation. Anthropic’s core mission is AI safety research, and diverting engineering talent and capital toward silicon development could be seen as a distraction. However, the company’s leadership appears to view control over its own hardware as essential to the long-term reliability and safety guarantees it wants to offer enterprise customers. Anthropic has been expanding rapidly into new enterprise verticals, including drug discovery, where inference latency and cost are direct barriers to adoption. The broader semiconductor competition between AI labs is accelerating fast, and if Anthropic’s Samsung talks lead to a formal partnership, it would mark another significant step in the decoupling of AI infrastructure from Nvidia’s near-monopoly.
