Anthropic Wants Its Own Silicon — and Samsung Is the Unlikely Partner

Anthropic is in early-stage talks with Samsung Electronics to manufacture a custom AI chip using its 2-nanometer process, according to The Information. The discussions are preliminary — no design exists, no production timeline has been set — but the strategic signal is unmistakable: the Claude maker wants to stop being entirely dependent on Nvidia GPUs.

The move comes exactly one week after OpenAI announced its own custom chip, Jalapeño, built with Broadcom. Google has its TPU line. Amazon has Trainium. Now Anthropic is the latest AI lab to conclude that renting compute from a single vendor is a strategic vulnerability.

🔍 THE BOTTOM LINE

Anthropic is designing its own silicon. The talks with Samsung are early, but the intent is serious: a dedicated chip for Claude-scale inference, built on 2nm process technology that TSMC doesn’t yet offer to non-Apple customers. If this deal closes, Samsung becomes a credible foundry alternative to TSMC for frontier AI chips — and Anthropic joins the ranks of AI labs verticalizing into hardware.

Why Samsung, and Why Now

Samsung is the only company that both invested in Anthropic’s $65 billion Series H round in May AND operates a leading-edge foundry. SK Hynix and Micron also participated, but neither manufactures logic chips. Samsung does. That dual relationship — financial backer and potential manufacturing partner — creates a natural bridge.

Blockonomi reports that discussions have focused on Samsung’s 2nm production node and its advanced packaging capabilities. Samsung has struggled with yields at leading-edge nodes compared to TSMC, which is why it’s been losing foundry market share for years. An Anthropic contract would be a significant commercial win — proof that Samsung’s 2nm process is viable for serious AI workloads.

Anthropic has also hired Clive Chan, previously a chip engineer at OpenAI working on that company’s semiconductor initiatives. That hire, first reported by Bloomberg, signals the company is building internal silicon expertise rather than outsourcing the design entirely.

The Pattern: Every Major AI Lab Is Building Chips

The custom-chip trend is now industry-wide:

Google — TPU architecture, now in its sixth generation, manufactured by TSMC but designed in-house
Amazon — Trainium and Inferentia, built for AWS-scale inference workloads
OpenAI — Jalapeño, a Broadcom collaboration announced in late June 2026
Meta — MTIA inference chips, already deployed in production
Anthropic — now in early talks with Samsung

The logic is straightforward: Nvidia controls roughly 74% of the AI semiconductor market, and GPU pricing reflects that dominance. A custom ASIC — designed for a specific model architecture — can deliver 3-5x better performance per watt for inference compared to a general-purpose GPU. At Anthropic’s scale, serving Claude to millions of users daily, the economics justify the enormous upfront design cost.

Not Abandoning Nvidia — Yet

Anthropic has been careful to signal that custom chip exploration doesn’t mean cutting ties with current suppliers. Company representatives told The Information that AWS Trainium, Google TPUs, and Nvidia GPUs will continue serving as foundational compute infrastructure. The company is also evaluating processors from Microsoft and UK-based Fractile.

This is a diversification play, not a replacement strategy. The AI compute stack is fragmenting: training remains dominated by Nvidia’s H100 and Blackwell GPUs, but inference — where the recurring cost sits — is where custom silicon pays off. Anthropic’s existing compute partnerships with SpaceX and its deep AWS integration aren’t going away. The Samsung chip would slot in as a specialized inference accelerator, not a wholesale platform change.

Samsung’s $518 Billion Bet

The Anthropic talks arrive alongside Samsung Group and SK Group’s joint $518 billion investment to build four memory chip manufacturing facilities in South Korea over the next decade. Samsung is pouring capital into semiconductor manufacturing capacity at a moment when TSMC’s lead looks increasingly vulnerable to geopolitical disruption.

If Samsung lands the Anthropic contract, it validates the company’s 2nm process for frontier AI applications — a credibility signal that could attract Google (already evaluating Samsung for future TPU iterations) and other AI labs looking for foundry diversity.

NZ Angle

New Zealand’s sovereign AI conversation, recently energized by the NZ Super Fund’s infrastructure push, has focused on data centers and energy. But the chip layer matters too. If the global AI compute market fragments across multiple foundry ecosystems — TSMC, Samsung, Intel — the cost of accessing specialized AI silicon drops. That benefits smaller nations that can’t build their own chips but need to rent compute. A more competitive foundry market means better pricing for everyone, including NZ research institutions and startups.

❓ FAQ

Is Anthropic abandoning Nvidia? No. The company has explicitly stated that Nvidia GPUs, AWS Trainium, and Google TPUs remain core infrastructure. The Samsung chip would be an addition, not a replacement — likely focused on inference optimization for Claude.

Why 2nm? What’s wrong with current process nodes? Smaller transistors mean better power efficiency and higher density. Samsung’s 2nm node is its most advanced offering. For inference workloads where you’re running models 24/7, even a 20% improvement in performance-per-watt translates to massive cost savings at scale.

Does Samsung have the manufacturing capability to pull this off? That’s the open question. Samsung’s foundry has historically struggled with yields at leading-edge nodes compared to TSMC. The company wouldn’t be in these talks if it didn’t believe it could deliver, but the risk is real — and Anthropic is reportedly still in the “deciding what the processor should do” phase.

How does this compare to OpenAI’s Jalapeño chip? OpenAI partnered with Broadcom for chip design and is further along. Anthropic’s effort is earlier-stage and uses a different manufacturing partner. Both reflect the same trend: AI labs verticalizing into hardware to reduce GPU dependency.

🔍 THE BOTTOM LINE

The AI chip independence race just added its third major player in a month. OpenAI has Jalapeño, Google has TPU, Amazon has Trainium — and now Anthropic is quietly designing its own silicon with Samsung as the foundry partner. The talks are early, Samsung’s 2nm yields remain unproven, and the project could be abandoned. But the direction is clear: every frontier AI lab is concluding that Nvidia-only infrastructure is a strategic liability. The next two years will determine whether Samsung can challenge TSMC’s foundry dominance — and whether Anthropic can build silicon that actually beats the GPUs it’s trying to replace.