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The Anthropic chip would use Samsung’s advanced 2nm process
In sum – what we know:
- Still exploratory – No chip design has been finalized and no tape-out has occurred, with Anthropic reportedly consulting multiple chip design firms.
- Samsung’s 2nm process – The chip would be built on Samsung Foundry’s 2nm node, and the talks extend to Samsung’s advanced packaging tech.
- Likely an inference chip – It would probably handle inference rather than training, deployed alongside Anthropic’s existing Trainium, TPU, and GPU hardware rather than replacing it.
Anthropic is in exploratory talks with Samsung Electronics about manufacturing a custom AI processor, according to reporting from The Information. The project is still nascent — no detailed chip design has been finalized, no tape-out has occurred, and Anthropic is reportedly consulting with multiple chip design firms, suggesting it may outsource at least part of the architecture and implementation rather than doing everything in-house. The company also recently hired Clive Chan, described as an early member of the OpenAI custom chip team behind the “Jalapeño” accelerator co-developed with Broadcom, a hire that signals Anthropic is building serious silicon expertise even if a first chip remains years away.
The strategic logic mirrors what OpenAI has already done with Broadcom. Bespoke silicon gives an AI lab a path to reducing its long-term dependency on Nvidia and others, while optimizing performance and cost for its own workloads — Claude inference at scale being the obvious candidate. It also secures more predictable access to compute capacity at a time when GPU demand and prices keep climbing.
To be clear, Anthropic isn’t walking away from its existing suppliers. The company has emphasized it will continue relying heavily on Amazon’s Trainium, Google’s TPUs, and its current GPU providers, positioning any custom chip as additive rather than a replacement. That said, it makes long-term sense for all of the major AI labs to own their entire stack.
An advanced chip
The chip would be built on Samsung Foundry’s 2-nanometer process, which promises higher transistor density and better power efficiency than the 3nm and 4nm nodes powering most current-generation accelerators. The partnership talks reportedly extend to Samsung’s advanced packaging technology as well — a critical piece, since high-bandwidth connections between logic and memory are where much of an AI accelerator’s real-world performance is won or lost.
What the chip would actually do remains undecided. Anthropic hasn’t confirmed whether it would handle model training, inference, or some mix of both. It’s perhaps more likely it would be an inference chip rather than a training one — training remains tightly optimized for Nvidia hardware and other established accelerators, while custom inference silicon can be tailored to specific workloads and deployed alongside existing GPUs rather than displacing them. That’s the same calculus that shaped OpenAI’s Jalapeño effort and Amazon’s Inferentia line.
For Samsung, landing Anthropic would be a genuine coup. Samsung Foundry has lagged TSMC in winning leading-edge contracts for high-performance computing, and a flagship AI logic customer would go a long way toward validating its 2nm capabilities and narrowing the perceived gap with TSMC.
A deeper partnership
The chip talks don’t exist in a vacuum. Anthropic recently closed a Series H funding round reported at about $65 billion, valuing the company at roughly $965 billion, and the investor list included Samsung, SK hynix, and Micron — explicitly labeled as “strategic infrastructure partners.” It’s highly unusual for all three of the world’s largest memory manufacturers to simultaneously invest in a single AI lab, and the arrangement is being read as closing a “chip-to-model pipeline,” giving hardware vendors direct influence over a major model developer’s roadmap.
Among those three, Samsung stands out. SK hynix and Micron can supply memory and storage — and all three investors will likely secure long-term supply relationships within Anthropic’s data centers — but Samsung is the only one with advanced logic foundry capabilities. It can fabricate the accelerator itself, not just feed it DRAM. That makes it the natural candidate for the custom chip work, and the timing matters, too. Samsung’s preliminary custom SoC work for OpenAI has reportedly slowed, raising the strategic importance of Anthropic as an alternative logic customer.
Google, Amazon, Meta, and Microsoft have all pursued greater control over their compute stacks rather than relying entirely on generic cloud compute and merchant silicon, and Anthropic joining that club was arguably a matter of when, not if.
Unknowns
For all the strategic significance, this remains a set of talks, not a deal. The list of open questions is long. Neither company has announced specific design parameters, volume commitments, or a timeline for a first-generation tape-out. The deployment model is equally murky — whether Anthropic would use the chips purely internally, offer them through cloud partners, or license them remains unknown. And there’s no indication yet of how the silicon’s performance goals, from FLOPs to memory bandwidth to energy efficiency, would stack up against Nvidia’s flagship accelerators.
What is clear is that the world’s most valuable private AI startup is laying the groundwork to control more of its own hardware destiny, and that Samsung is positioning itself to be the foundry that makes it happen. Whether that groundwork becomes an actual chip is a question neither company is ready to answer.
