Anthropic is in early-stage discussions with Samsung Electronics about designing and manufacturing a custom AI chip, with conversations centering on Samsung’s 2nm foundry process and its advanced packaging facilities, according to people familiar with the matter. The chip’s purpose, power requirements, and server configuration have not been finalized. Anthropic could abandon the effort. When asked for comment, Anthropic told TechCrunch that a diversified hardware stack including chips from Google, Amazon, and Nvidia will remain central to its compute strategy, and said it had nothing further to add on the Samsung discussions. What the company did not say is that the Samsung conversations are not happening – which is itself a deliberate kind of answer. The effort represents Anthropic’s first known attempt to develop proprietary silicon, and it arrives in the week after OpenAI unveiled its first custom inference chip, code-named Jalapeño, built with Broadcom.
Anthropic hired Clive Chan to lead the initiative. Chan previously worked on OpenAI’s custom silicon program before joining Anthropic, making him the specific engineering credential Anthropic needed to credibly begin this work. The hire preceded the Samsung discussions by enough time to suggest that the chip program is not reactive to OpenAI’s Jalapeño announcement but represents a parallel strategic development running on its own timeline. Samsung’s involvement in Anthropic’s $65 billion Series H round in May 2026, as a strategic infrastructure partner alongside SK Hynix and Micron, created the commercial relationship that makes a foundry conversation natural – Samsung is the only one of those three memory investors that also operates a chip foundry capable of producing logic chips at advanced nodes. That specific structural advantage is what NewsTrackerToday picks up as the reason Samsung is the interlocutor rather than a general talent or capital relationship.
Liam Anderson reads the economics of the custom silicon bet: “Anthropic’s annualized revenue run rate crossed $30 billion earlier this year, roughly tripling from $9 billion at end of 2025. At $30 billion in revenue with inference costs as the primary cost-of-goods driver, the economics of a custom chip optimized for Claude’s inference workload start to look compelling in the same way they do for Google’s TPUs and Amazon’s Trainium. You need scale before custom silicon is worth the engineering investment. Anthropic is approaching that scale.” The target is inference rather than training. Training requires enormous compute clusters running for months. Inference happens billions of times per day as users query Claude. A chip optimized for Claude’s specific inference pattern – optimized for its architecture, its attention mechanism, its token generation profile – could reduce inference cost per token materially while improving latency, and at Anthropic’s query volume, even a modest per-token cost reduction compounds significantly.
Isabella Moretti examines the deal mechanics: “Samsung participated in Anthropic’s Series H round. Now Anthropic is discussing manufacturing at Samsung Foundry. That sequence describes a pattern where strategic investors gain access to commercial relationships beyond the capital itself. Samsung’s SF2 process, its 2nm node using Gate-All-Around transistors, is competitive with TSMC’s 2nm offering in principle but unproven at high volume. Samsung’s reported yield rate of near 70% on SF2 is meaningful progress but introduces supply reliability risk that Anthropic’s inference requirements do not tolerate well. The design-and-manufacturing relationship with Samsung is also a competitive signal for TSMC: if Anthropic moves forward, TSMC faces another major AI company diversifying away from its dominant position.” The Jalapeño mirror is what NewsTrackerToday traces as the competitive logic: OpenAI’s custom chip with Broadcom, Google’s TPUs, Amazon’s Trainium, Meta’s MTIA, and now Anthropic with Samsung each represent a lab trying to reduce dependence on Nvidia, which still holds approximately 74% of AI chip market share.
The discussions with Samsung are not exclusive. Anthropic has also been in conversations with Microsoft and UK startup Fractile as potential hardware alternatives. That multi-party engagement suggests Anthropic is in the early stages of mapping the hardware partnership landscape rather than committed to a single solution. Samsung’s advantage over Fractile is obvious: scale, manufacturing capacity, and the existing financial relationship. Samsung’s disadvantage relative to TSMC, where most of Anthropic’s current chips come from through Nvidia, is yield reliability and ecosystem maturity. The specific design and manufacturing challenges of a 2nm chip optimized for transformer inference at Claude’s scale are what News Tracker Today holds as the TSMC challenge Samsung has to prove it can match before Anthropic commits manufacturing volume.
Three things to watch as Anthropic’s chip program develops: whether Anthropic moves from exploratory discussions to a signed design agreement with Samsung, which would make the program real enough to include in IPO disclosures; whether OpenAI’s Jalapeño chip achieves the performance-per-watt benchmarks that OpenAI claimed at announcement, since that data would inform Anthropic’s own inference chip specifications; and whether Samsung’s SF2 yield rates improve sufficiently over the second half of 2026 to make it a credible high-volume manufacturer for a chip that Anthropic’s inference operations would require at significant scale. The hire of Clive Chan is the firm commitment signal so far. The Samsung conversations are the direction-of-travel indicator. The chip’s actual specification, which Anthropic has not yet determined, is what NewsTrackerToday names as the foundational decision that turns an initiative into an engineering program.
