Samsung AI Investment Strategy, September 2026: From Euclyd's $231M Inference Bet to the OpenAI Foundry

Samsung co-led Dutch startup Euclyd's $231 million Series A to develop lower-cost AI inference accelerators competing with Nvidia, the latest in a concurrent capital campaign that also includes leading Mistral AI's €3 billion Series D and securing a custom-chip foundry role with OpenAI.

Samsung's September investment in Euclyd, a Dutch AI chip startup, marks the clearest signal yet that the Korean conglomerate intends to shape the inference layer of the AI stack rather than simply supply memory and logic silicon to whoever wins it. The round — $231 million at Series A, co-led by Samsung and Somerset Capital — will fund development of accelerators designed to undercut Nvidia on inference cost. The appointment of Peter Wennink, the former ASML chief executive, as Euclyd's chairman adds industry credibility that is rarely assembled at this stage; it also connects two relationships Samsung has been cultivating in parallel, having deepened its strategic alignment with ASML to secure capacity on the latest extreme-ultraviolet tools alongside TSMC and Intel.

The Euclyd commitment sits inside a broader, rapidly accumulating portfolio. Reporting confirmed Samsung led the €3 billion Series D for Mistral AI, lifting the French developer's valuation above €21 billion in one of the largest sovereign-backed AI funding rounds Europe has seen. Separately, OpenAI has confirmed plans to double-source its next-generation custom processors between Samsung and TSMC, even as reports suggest the Korean Stargate build-out has made limited on-the-ground progress so far. Together, the three moves sketch a working hypothesis: whether the inference stack consolidates around Nvidia-compatible silicon or fragments toward lower-cost alternatives, Samsung has positioned itself to capture value in either scenario.

The memory business remains the financial engine behind this ambition — and its competitive position is in motion. SK Hynix is already shipping 16-layer HBM4 modules for Nvidia's Rubin GPU architecture, giving it a timing lead in the next-generation high-bandwidth memory transition. Samsung has been narrowing that gap, according to Businesskorea, while simultaneously teasing HBM5 specifications targeting 4 TB/s of bandwidth per stack — roughly double HBM4E performance — potentially over a 4,096-bit interface. With SK Hynix, Samsung, and Micron all reportedly sold out of 2026 HBM4 capacity, competition has shifted to yield, qualification timelines, and the HBM4E validation race in which accelerator design firm Astra is reportedly a pivotal customer.

The risks are material. A South Korean court ruled that Chinese memory maker CXMT had systematically copied Samsung's DRAM manufacturing process — a 620-step recipe allegedly transferred via a written document trail codenamed Project Hefei. Reporting now shows CXMT's profit margins have overtaken both Samsung's and SK Hynix's, suggesting the technology transfer has produced commercial results regardless of the legal outcome. Separately, both Samsung and SK Hynix reportedly face escalating US and Chinese export controls that threaten cross-border supply relationships. On the foundry side, a significant pricing dispute has emerged with Qualcomm over an AI chip deal. And DeepSeek's claims about efficient high-bandwidth memory use — however ultimately substantiated — have already introduced uncertainty into HBM demand forecasts, with reporting noting they have weighed on Samsung Electronics and SK Hynix valuations.

Three signals will define how Samsung's multi-front strategy resolves over the next several quarters. First, whether Samsung Foundry can demonstrate competitive yield for the OpenAI custom chip program — any sustained shortfall against TSMC would diminish the partnership's strategic weight. Second, the trajectory of Euclyd's inference accelerator relative to the broader field: d-Matrix, another inference startup backed early by Samsung and SK, has already pivoted to join Nvidia's ecosystem rather than compete with it, a reminder that positioning against Nvidia in accelerated compute is easier to fund than to execute. Third, the resolution of the CXMT intellectual-property dispute and its export-control backdrop, which will largely determine whether Samsung can sustain the pricing power in DRAM that its memory roadmap assumes. At ₩248,500, down 0.2% at last close, Samsung trades as what it is: a company indispensable to AI infrastructure, and exposed to nearly every fault line running through it.