Anthropic, the artificial intelligence company behind the Claude large language models, has initiated early-stage development of its own custom AI semiconductors and held preliminary talks with South Korea’s Samsung Electronics Co. as a potential manufacturing partner. The strategic move, first reported by The Information, represents a major step in the startup’s broader effort to diversify its hardware supply chains and reduce its heavy operational dependence on market leader Nvidia Corporation. If the negotiations proceed to a formal contract, the partnership would severely alter the balance of power in the global semiconductor market, placing immense competitive pressure on Nvidia, which currently holds an estimated 74% share of the highly lucrative AI processor sector.
The proposed custom chip project focuses heavily on utilizing Samsung’s state-of-the-art 2-nanometer (2nm) gate-all-around (GAA) contract manufacturing process and the South Korean conglomerate’s advanced packaging facilities. While the project remains in its nascent, conceptual stages—with no physical designs finalized or manufacturing contracts signed—the company is systematically building out its internal engineering capability. Anthropic recently made a major hiring move, recruiting Clive Chan, an experienced hardware engineer who was an early member of rival OpenAI’s own custom chip development team. By building up its in-house chip design talent, Anthropic is preparing to join a high-stakes, industry-wide shift toward proprietary custom silicon.
The Financial Powerhouse: Anthropic’s $965 Billion Valuation
To understand how a five-year-old software startup has the financial resources to design and manufacture custom microchips from scratch, one must examine Anthropic’s extraordinary capitalization. In late May, the San Francisco-based AI developer closed a massive, record-shattering $65 billion Series H funding round. The investment round propelled Anthropic’s market valuation to a staggering $965 billion, making it the most valuable independent artificial intelligence company in the world and placing it comfortably ahead of rival OpenAI’s last-reported valuations of $730 billion and $852 billion.
This massive $65 billion funding round was notable not just for its scale, but for the strategic nature of the investors who backed it. The round drew heavy capital participation from the world’s top three memory and semiconductor storage suppliers: Samsung Electronics, SK Hynix, and Micron Technology. This structural alignment with the global hardware giants was a calculated move. Anthropic’s management openly stated that these partnerships would help the company secure stable, high-volume computing capacity and memory components in an increasingly supply-constrained market.
Among these three strategic investors, Samsung Electronics stands out for one unique reason: it is the only conglomerate in the world that operates both a world-class memory business and a leading-edge, logic semiconductor contract manufacturing foundry business. This dual capability makes Samsung the most logical, integration-ready candidate to produce custom AI silicon for Anthropic, giving the startup a direct pathway to turn its software expertise into physical, high-performance hardware.
The Strategic Shift to Custom Silicon for Large Language Models
By initiating the development of its own custom chips, sometimes referred to as application-specific integrated circuits (ASICs), Anthropic is following a well-worn playbook established by other global technology giants. During the initial phase of the generative AI boom, software companies had little choice but to purchase off-the-shelf graphics processing units (GPUs) from Nvidia to train and run their models. However, as these AI systems scale toward trillions of parameters, general-purpose GPUs have become a major source of cost and efficiency bottlenecks.
Custom silicon allows AI companies to optimize their hardware architecture specifically for their own software algorithms, such as Anthropic’s Claude model series. By tailoring the memory bandwidth, core processing units, and high-speed interconnects to match the exact mathematical properties of their model training and inference workloads, developers can achieve significant performance gains while cutting energy consumption and operational costs by several orders of magnitude.
Several major tech firms have already proven the economic viability of this strategy:
- Google’s TPU Program: Google pioneered the custom silicon shift years ago with its Tensor Processing Units (TPUs), which have successfully allowed the search giant to train its most advanced models without relying entirely on third-party GPU suppliers.
- OpenAI’s Jalapeño Chip: In late 2024, OpenAI tapped U.S. chip design firm Broadcom to design its own custom silicon, resulting in the successful launch of its first-ever custom inference chip, codenamed Jalapeño, designed to run large language models far more efficiently.
- Hyperscaler Efforts: Amazon (Trainium and Inferentia), Meta (MTIA), and Microsoft (Maia) are all designing custom silicon to lower their data center operating costs.
For Anthropic, entering the custom silicon race is an essential defensive hedge. By designing its own processors, the company can protect its future profit margins from Nvidia’s high hardware markups, ensuring that it can deliver fast, affordable, and highly competitive AI services to its enterprise customers over the long term.
The Technical Specs of the Proposed 2nm Partnership
The potential collaboration between Anthropic and Samsung would center on two highly critical semiconductor technologies: the 2-nanometer manufacturing process and advanced packaging. The 2nm process represents the next major milestone in semiconductor fabrication, promising to pack more transistors into a smaller physical space to deliver up to 50% more performance and significantly better energy efficiency than existing 3-nanometer and 4-nanometer nodes.
Samsung’s 2nm process utilizes an advanced Nanosheet gate-all-around (GAA) transistor architecture. Unlike traditional FinFET transistors, which are limited by three-sided physical gates, GAA transistors surround the channel on all four sides, minimizing current leakage and allowing for precise electrical control at microscopic scales. This technology is highly critical for AI chips, which generate extreme heat and consume massive amounts of power during continuous, high-density computing workloads.
However, fabricating the silicon wafer is only half the battle. High-performance AI chips require advanced packaging to integrate the main computing core with high-speed High-Bandwidth Memory (HBM) modules on a single, unified substrate. By leveraging Samsung’s domestic advanced packaging facilities, Anthropic can ensure that its custom chips are assembled with the shortest possible data pathways, minimizing signal latency and maximizing the memory bandwidth required to run next-generation models smoothly.
Google’s Icefish Project and the Split-Manufacturing Trend
The strategic importance of Samsung’s 2nm process is further demonstrated by its growing role in Google’s next-generation hardware development. Google is currently designing its 10th-generation Tensor Processing Unit, codenamed Icefish, which is slated for mass production as early as 2028.
To avoid potential production bottlenecks and optimize costs, Google is adopting a split-manufacturing strategy for the Icefish project:
- TSMC Computing Core: Google plans to have Taiwan Semiconductor Manufacturing Company (TSMC) fabricate the primary computing core of the Icefish processor, utilizing TSMC’s cutting-edge 1.4-nanometer process.
- Samsung 2nm I/O Die: Google plans to outsource the manufacturing of the critical memory input/output (I/O) die—the specialized component that connects the main processor to its HBM memory stack—to Samsung’s 2nm foundry process.
- Advanced Packaging integration: Industry observers believe Google may also entrust Samsung with the final advanced packaging of the Icefish chip, shipping the core processors fabricated at TSMC to South Korea to be integrated with Samsung’s own HBM and I/O dies.
This split-manufacturing model highlights how major technology firms are increasingly using a mix of TSMC and Samsung foundry services to diversify their supply chains, reduce concentration risks, and leverage the unique technical strengths of both manufacturers.
The Long-Awaited Profit Turnaround for Samsung Foundry
If Samsung successfully secures the contract to manufacture custom AI chips for a marquee client like Anthropic, it would represent a massive commercial victory and a long-awaited profit turnaround for its contract manufacturing foundry division. While Samsung’s memory business has generated exceptional profits during the AI boom, its foundry business has historically struggled to achieve profitability, burdened by low manufacturing yields on its early-stage GAA nodes.
However, recent indicators suggest that Samsung’s foundry division is approaching a major recovery. The company’s 2nm manufacturing yields have steadily improved to a highly viable 55% to 60%, and its order book is expanding rapidly. The business showed its first signs of recovery after securing a massive 23 trillion Korean won (approximately $16.5 billion) contract to produce next-generation AI chips for Tesla in July 2025. By following this up with potential 2nm partnerships with Google, AMD, Qualcomm, and Anthropic, Samsung is rapidly transforming its foundry into a premier global manufacturing destination.
Challenging TSMC’s Absolute Foundry Dominance
The potential partnership between Anthropic and Samsung represents a direct challenge to the near-absolute market dominance of Taiwan Semiconductor Manufacturing Company (TSMC). Currently, TSMC is the undisputed king of advanced semiconductor contract manufacturing, producing more than 90% of the world’s high-end AI processors, including virtually all of Nvidia’s flagship GPU lines.
This extreme geographic and corporate concentration has become a major source of anxiety for global technology companies and national security policymakers. Any geopolitical crisis, maritime shipping blockade, or major seismic event in the Taiwan Strait could instantly paralyze the global technology industry, cutting off the supply of the advanced chips that power everything from smartphones to defense systems. By establishing a viable, high-volume alternative manufacturing hub with Samsung in South Korea, Anthropic is helping to build a more resilient, diversified global hardware ecosystem that is less vulnerable to single-point failures.
Navigating the Multi-Cloud and Custom Hardware Matrix
While the potential partnership with Samsung represents a major step forward, Anthropic is keeping its strategic options open by building a highly flexible, multi-cloud infrastructure strategy. The company recognizes that developing a custom chip is a multi-year process, and it must continue to secure high-performance computing power from multiple sources in the short term to support the rapid growth of its Claude model series.
As part of this diversified approach, Anthropic is continuing to expand its hardware alliances across several fronts:
- Microsoft Maia Chips: The company has reportedly engaged in active discussions with Microsoft to run its models on Microsoft’s custom-designed Maia AI chips within the Azure cloud ecosystem.
- Fractile Fusion Technology: Anthropic has held early-stage discussions with UK-based hardware startup Fractile to evaluate its innovative Memory Compute Fusion Architecture, which promises to run AI inference tasks 100 times faster and at one-tenth the cost of traditional processors by eliminating off-chip memory bottlenecks.
- Nvidia Baseline: Despite its custom silicon efforts, Anthropic continues to purchase and rent thousands of standard Nvidia GPUs, ensuring that its core model training operations are supported by the most powerful hardware currently available.
This multi-pronged strategy—combining custom silicon development with Samsung, cloud hosting agreements with Microsoft and Google, and strategic partnerships with emerging hardware startups—helps Anthropic build a resilient, cost-effective infrastructure that can support its global AI ambitions for years to come.
Conclusion
Anthropic’s early-stage efforts to develop its own custom AI semiconductors and its preliminary discussions with Samsung Electronics represent a significant milestone in the rapidly consolidating artificial intelligence market. Backed by a historic $65 billion Series H funding round that valued the startup at a record $965 billion, the company possesses the immense financial resources and strategic partnerships necessary to take control of its own hardware destiny. By exploring Samsung’s state-of-the-art 2nm GAA manufacturing process and advanced packaging facilities, Anthropic is following a highly successful, industry-wide playbook designed to bypass Nvidia’s high hardware markups and build a more cost-effective, custom-optimized software-hardware ecosystem.
While the custom chip project remains in its nascent stages and will require years of engineering coordination before reaching mass production, the strategic implications of the potential partnership are clear. For Samsung, securing a marquee AI client like Anthropic would represent a massive victory for its foundry division, validating its advanced 2nm manufacturing capabilities and accelerating its profit recovery. For the global technology sector, the creation of a viable, high-volume alternative manufacturing hub in South Korea would help reduce the extreme concentration risks associated with relying entirely on TSMC and Taiwan, building a more resilient, diversified, and stable foundation to power the next generation of global innovation.
