Key Highlights
- A long-term technology alliance between NVIDIA and SK hynix targets advanced memory solutions for global AI data centers.
- The South Korean memory maker will jointly engineer chips for NVIDIA’s Vera Rubin supercomputers, Vera CPUs, RTX Spark consumer systems, and Jetson Thor robotics modules.
- Both firms plan to leverage artificial intelligence to streamline chip architecture development and production pipelines.
- SK hynix is constructing virtual manufacturing replicas with NVIDIA Omniverse and cuOpt, aiming for self-operating fabrication facilities.
- This collaboration positions SK hynix in emerging sectors orchestrated by NVIDIA, such as consumer-level AI computing and embodied intelligence.
NVIDIA and SK hynix have unveiled a comprehensive, multi-year alliance centered on engineering cutting-edge memory solutions for artificial intelligence manufacturing complexes across the globe.
The partnership was formally disclosed on June 7, 2026, encompassing memory provisioning, chip architecture, and production processes—integrating SK hynix firmly into NVIDIA’s strategic AI hardware timeline.
Shares of SK hynix (KRX: 000660) were hovering near ₩238,000 in the trading sessions preceding the official announcement.
The collaboration addresses the extended timelines and substantial investment demands inherent in cutting-edge memory production at industrial scale.
As global AI infrastructure expands rapidly, NVIDIA requires memory suppliers capable of matching its pace. This agreement is architected to deliver that capability.
SK hynix will jointly engineer memory products for multiple NVIDIA ecosystems—spanning Vera Rubin AI supercomputing clusters, Vera central processing units, RTX Spark-enabled consumer desktops, and the Jetson Thor robotics computation module.
The robotics component deserves particular emphasis. It positions SK hynix across three separate NVIDIA-dominated verticals: enterprise AI infrastructure, consumer-grade AI computing, and embodied artificial intelligence.
Artificial Intelligence Transforms Semiconductor Engineering
Beyond hardware supply chains, both organizations are deploying AI methodologies directly into semiconductor development processes.
SK hynix is implementing NVIDIA’s CUDA-X software libraries alongside the PhysicsNeMo computational framework to accelerate chip simulation tasks—encompassing technology computer-aided design and lithography modeling workflows.
The partnership also facilitates trilateral cooperation involving semiconductor manufacturers, NVIDIA, and electronic design automation platform providers.
This represents a strategic ecosystem expansion rather than a simple two-party supply arrangement.
Virtual Manufacturing and Self-Governing Production Facilities
SK hynix is engineering digital replicas of its production facilities—three-dimensional virtual representations of its fabrication operations—utilizing NVIDIA Omniverse technology and OpenUSD pipelines.
These virtual environments are designed to model and enhance intricate manufacturing ecosystems, including autonomous mobile robot navigation within cleanroom facilities.
The open-source NVIDIA cuOpt optimization engine and the NVIDIA Metropolis framework enable operational refinement within these simulated settings.
Both companies are additionally integrating these digital twins with established legacy systems and agentic AI operational flows—enabling AI systems to analyze fabrication data and autonomously execute manufacturing protocols.
Jensen Huang, chief executive of NVIDIA, characterized advanced memory as “essential” to AI factory capabilities and recognized SK hynix as having performed a “central role” in supplying memory for NVIDIA’s hardware platforms.
SK Group Chairman Chey Tae-won stated the alliance “reflects the depth” of sustained collaboration between the firms and noted both organizations are now deploying AI throughout semiconductor design and manufacturing operations.
In a concurrent announcement on the same date, NVIDIA revealed that South Korea’s Naver corporation will adopt its DSX infrastructure to architect and deploy comprehensive AI platforms for corporate and governmental applications.
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