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SK Group and Nvidia Deepen AI Alliance as HBM4 Competition Intensifies Under U.S. Tech Sovereignty

Summarized by NextFin AI
  • SK Group Chairman Chey Tae-won met Nvidia CEO Jensen Huang to discuss the supply of sixth-generation High Bandwidth Memory (HBM4) for Nvidia's upcoming AI architecture, indicating a strategic partnership.
  • SK Hynix currently holds about 70% of the HBM3E market, but Samsung's new HBM4 production could challenge this dominance, highlighting a competitive landscape in AI memory supply.
  • The partnership aims to transition SK Group from a component supplier to a full-stack AI infrastructure provider, with a commitment of $10 billion towards AI solutions, aligning with Nvidia's expansion into autonomous systems.
  • The shift to HBM4 represents a fundamental change in chip architecture, requiring deep collaboration between memory providers and GPU designers, which could lock in SK's market share if successful.

NextFin News - In a move that underscores the critical interdependence of the global artificial intelligence supply chain, SK Group Chairman Chey Tae-won met with Nvidia CEO Jensen Huang in Santa Clara, California, on February 5, 2026. The meeting, held at a local Korean restaurant, served as a high-stakes strategy session disguised as a casual "chimaek" (chicken and beer) dinner. According to BusinessKorea, the discussions focused on the supply of sixth-generation High Bandwidth Memory (HBM4) for Nvidia’s upcoming "Vera Rubin" AI architecture, scheduled for release in the second half of 2026.

The timing of this meeting is pivotal. SK Hynix, the semiconductor arm of SK Group, currently commands approximately 70% of the market for HBM3E chips used in Nvidia’s Blackwell GPUs. However, the landscape is shifting rapidly. Samsung Electronics recently announced it would begin mass production of HBM4 in the third week of February 2026, aiming to challenge SK’s dominance. By meeting Huang in person, Chey sought to solidify SK’s position as the primary partner for Nvidia’s next-generation accelerators, with reports suggesting SK has already secured over 60% of the initial HBM4 orders for the Vera Rubin line.

Beyond immediate hardware procurement, the dialogue delved into the broader AI ecosystem. The presence of the leaders' daughters—Choi Min-jung, CEO of Integral Health, and Madison Huang, a senior director at Nvidia’s Robotics Division—indicates a long-term vision for cross-generational collaboration in robotics and AI-driven healthcare. Furthermore, SK Group’s recent decision to rename its U.S. NAND subsidiary Solidigm to "AI Company" and commit $10 billion to AI solutions suggests a transition from a component supplier to a full-stack AI infrastructure provider. This aligns with Nvidia’s expansion into autonomous systems and digital twins, where high-speed memory and specialized NAND flash are increasingly vital.

From a geopolitical perspective, this alliance is navigating a complex regulatory environment. U.S. President Trump, inaugurated in January 2025, has maintained a rigorous "America First" stance on technology, emphasizing the reshoring of semiconductor manufacturing and the security of AI supply chains. For SK Group, maintaining a "special relationship" with Nvidia is not just a commercial necessity but a strategic buffer against potential trade volatility. By deepening ties with the most valuable U.S. chip designer, SK positions itself as an indispensable partner in the U.S.-led AI bloc, potentially mitigating risks associated with tariffs or export controls.

The technical shift to HBM4 represents a fundamental change in chip architecture. Unlike previous generations, HBM4 will utilize a logic base die manufactured on advanced foundry processes—specifically the 3nm node. SK Hynix has partnered with TSMC for this transition, creating a powerful "triangular alliance" between the world’s top memory maker, the leading foundry, and the dominant AI chip designer. This integration makes it increasingly difficult for competitors to break into the ecosystem, as the customization required for HBM4 necessitates deep, early-stage collaboration between the memory provider and the GPU architect.

Looking ahead, the success of the SK-Nvidia partnership will likely depend on their ability to scale "Custom HBM" (cHBM). As AI models grow in complexity, generic memory solutions are reaching their thermal and bandwidth limits. The industry is moving toward a model where memory is co-designed with the processor. If SK can successfully integrate its memory directly onto Nvidia’s logic dies, it will effectively lock in its market share for the remainder of the decade. However, with Samsung doubling down on its own HBM4 capacity and U.S.-based Micron receiving significant federal support under the current administration, the race for AI memory supremacy is far from over. The Santa Clara meeting confirms that in the 2026 AI economy, personal diplomacy at the CEO level remains as critical as engineering breakthroughs.

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Insights

What concepts underpin the high bandwidth memory (HBM) technology?

What historical events led to the formation of the current AI supply chain?

What are the latest trends in the global chip market regarding HBM4?

What feedback have users provided about HBM3E chips in Nvidia GPUs?

What recent developments have occurred in the SK Group and Nvidia partnership?

What policy changes have impacted the semiconductor industry under the Trump administration?

How might the HBM4 technology evolve in the next five years?

What long-term impacts could the SK-Nvidia alliance have on the AI industry?

What challenges does SK Group face in maintaining its market dominance?

What controversies surround the U.S. tech sovereignty initiatives?

How do SK Group and Nvidia compare with their competitors in AI memory solutions?

What historical cases illustrate the evolution of AI memory technologies?

What similarities exist between HBM4 and previous generations of memory technology?

What competitive strategies are being employed by Samsung in the HBM market?

What role does personal diplomacy play in the tech industry, as seen in SK-Nvidia meetings?

How does the integration of memory and processor affect chip architecture?

What potential barriers exist for new entrants in the HBM market?

How does the current geopolitical climate influence semiconductor collaborations?

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