Samsung plans to begin manufacturing its next-generation HBM4 memory chips as early as next month and aims to supply Nvidia for AI accelerators, with the qualification process reaching the final stage after initial samples were provided to Nvidia in September.

Investors reacted to the news, sending Samsung’s shares up as much as 3.2% in Seoul before trimming gains, while SK Hynix fell about the same amount.

The memory design passed verification without redesign even after customers requested performance improvements, underscoring the technology’s readiness.

Industry notes show AI customers are prioritizing raw performance over tighter thermal margins, raising speed requirements as custom accelerators like Google’s TPUs influence demand.

This development sits within broader trends of AI infra spending, collaboration on AI factories, and ongoing competition for high-bandwidth memory contracts.

Market dynamics remain favorable for all suppliers due to strong AI memory demand, creating a seller’s market with limited shifts in market share among Samsung, SK Hynix, and Micron.

Technical details include a 6th-generation 10nm-class DRAM, a 4nm logic base die, and memory speeds surpassing 11 Gbps to support broad AI infrastructure needs.

Micron kicked off 2026 strong with new highs, aided by better-than-expected earnings, highlighting the competitive landscape among memory makers.

Strategic timing aligns with rising AI infrastructure spending in cloud data centers, sovereign AI projects, and enterprise and defense sectors, signaling sustained demand for HBM.

The development could reshape the AI memory supply chain by reducing Nvidia’s single-supplier risk and tightening pricing leverage across the ecosystem.

Investors view the move as potentially elevating Samsung’s high-margin AI memory business and improving sentiment around its foundry and memory strategy while reducing reliance on commoditized DRAM pricing cycles.

India operations feature a large AI-focused engineering workforce, with thousands of semiconductor engineers supporting AI-centric development.