Anthropic to develop its own AI chip with Samsung

Following a massive wave of custom silicon announcements across Silicon Valley, Anthropic has entered early-stage discussions with Samsung Electronics to manufacture its first in-house, bespoke AI accelerator chip.

The disclosure, first reported by The Information, reveals that the developer behind the Claude model series is moving aggressively to vertically integrate its hardware stack. The development comes just over a week after primary rival OpenAI unveiled “Jalapeño,” its own first-generation custom inference processor built in collaboration with Broadcom.

1. The Engineering Strategy: Poaching and 2nm Ambitions

While Anthropic has publicly maintained that its hardware plans remain deeply diversified, internal movements show the startup is accelerating its timeline to establish silicon independence from NVIDIA’s supply-chain monopoly:

• The Key Hire: To spearhead the effort, Anthropic recently hired Clive Chan, a high-profile hardware engineer who previously worked directly on OpenAI’s proprietary custom chip program.
• The 2-Nanometer Target: Industry sources indicate that the discussions with Samsung center on the South Korean giant’s upcoming 2-nanometer (SF2P) foundry process and advanced packaging facilities. The SF2P node uses a next-generation gate-all-around (GAA) transistor architecture, which drastically mitigates power leakage—a critical requirement for power-hungry data center operations.
• A “Blank Canvas” Architecture: Because talks are in the initial phase, Anthropic has not yet locked in the precise technical layout. It remains undecided whether the chip will be a single-purpose inference engine (similar to OpenAI’s Jalapeño) or a broader, dual-purpose chip capable of handling heavy model training.

2. Samsung’s Crucial Foundry Breakthrough

For Samsung, securing Anthropic would serve as a massive, marquee validation of its struggling foundry business, which has historically spent years trying to narrow a massive market-share gap with TSMC.

 [ THE 2026 FRONTIER LAB CHIP LANDSCAPE ]
 
  ├── Google:     Tensor Processing Units (TPUs) ──► Custom Built with Broadcom / TSMC
  ├── OpenAI:     "Jalapeño" Inference Processor ──► Custom Built with Broadcom / TSMC
  └── Anthropic:  Bespoke AI Accelerator         ──► In-Discussion with Samsung (2nm GAA Node)

Samsung possesses a unique structural advantage over other standalone chip foundries: it is a fully integrated device manufacturer. Unlike TSMC, which must source components externally, Samsung can manufacture the advanced High Bandwidth Memory (HBM) internally alongside the primary logic processor, offering Anthropic a streamlined, single-vendor assembly pipeline.

3. Balancing the Cloud Alliance Trillionaires

The decision to explore private silicon introduces a delicate political balancing act for Anthropic. The company’s entire computing infrastructure is currently anchored by multi-billion-dollar investments from two primary cloud hyper-scalers: Amazon Web Services (AWS) and Google.

Compute Platform Component	Baseline Infrastructure Role	Future Custom Chip Positioning
AWS Alliance	Anthropic uses specialized AWS Trainium and Inferentia chips to run core workloads.	Serving as a long-term hedge to ensure Anthropic isn’t completely locked into Amazon’s proprietary ecosystem.
Google Cloud Alliance	Deep dependency on Google’s specialized Tensor Processing Units (TPUs).	Reduces reliance on Google’s specialized developer environments while driving down per-token operational margins.
NVIDIA Fleet	Standard foundation for massive multi-modal pre-training.	Limits exposure to hardware supply shortages and expensive markup fees.

Anthropic was quick to issue a cautious buffer statement following the leak, emphasizing that its existing partnerships with AWS, Google, and NVIDIA remain “pivotal” to its long-term scaling strategy.

However, by following OpenAI into the custom silicon race, Anthropic is signaling to the market that relying entirely on third-party cloud architectures is no longer sustainable. If a frontier lab wants to keep slashing the cost-per-token of its models to stay price-competitive, owning the underlying intellectual property of the physical factory silicon is rapidly becoming the ultimate cost-cutting variable.