Background: HBM4 and AI Memory Chips
Samsung and SK Hynix, two of South Korea’s semiconductor giants, are reportedly preparing to mass-produce their sixth-generation high-bandwidth memory (HBM) chips, HBM4, starting in 2026. These chips are specifically designed for artificial intelligence (AI) workloads, offering significantly higher performance and better power efficiency compared to previous generations.
High-bandwidth memory is essential for AI applications because it allows rapid data transfer between processors and memory, supporting computationally intensive tasks like machine learning training, AI inference, and deep neural network processing. With HBM4, Samsung and SK Hynix aim to provide cutting-edge solutions for the next wave of AI accelerators.
Samsung and SK Hynix Production Timeline
According to South Korean media outlet SEDaily, Samsung is expected to begin HBM4 production in February 2026, making it the first company to start manufacturing these next-generation AI memory chips. SK Hynix is reportedly scheduled to complete its production cycle by September 2026. Both companies have exclusive deals with Nvidia to supply HBM4 chips for its Vera Rubin AI accelerator system.
Interestingly, other industry players like Micron are not expected to manufacture HBM4 chips in 2026, giving Samsung and SK Hynix a competitive advantage in the high-performance AI memory market. Early production is expected to help Samsung create a market lead, while SK Hynix focuses on refining its 12nm logic process for the base die, as opposed to Samsung’s 10nm process.
Technical Advantages of HBM4
HBM4 is not only faster but also significantly more power-efficient than previous generations. Key benefits include:
- Twice the Bandwidth: Allows AI models to access data faster, reducing latency in computations.
- Power Efficiency: Nearly 40% improvement, which is critical for large-scale AI deployments.
- Customizability: Optimized for both AI and non-AI applications, offering flexibility for various hardware integrations.
- Advanced Manufacturing: Samsung uses a 10nm logic process while SK Hynix uses 12nm for the base die, ensuring high-speed and reliable performance.
The increased bandwidth and efficiency are crucial for AI accelerators such as Nvidia’s Vera Rubin platform, which relies on rapid memory access to run large-scale neural network models efficiently. These improvements are expected to set a new benchmark for AI memory performance in 2026.
Integration with Nvidia’s Vera Rubin Platform
Most of the HBM4 chips produced by Samsung and SK Hynix will reportedly be dedicated to Nvidia’s Vera Rubin AI accelerator system. The Vera Rubin platform is designed to handle intensive AI workloads such as large language model training, deep learning inference, and AI-driven simulations. By pairing high-bandwidth memory with AI accelerators, Nvidia aims to reduce bottlenecks and improve overall computational efficiency.
Samsung recently passed Nvidia’s quality tests, validating its HBM4 chips for integration into Vera Rubin. This collaboration ensures that Nvidia’s AI solutions benefit from the cutting-edge memory performance and power efficiency offered by HBM4.
Production Volumes and Market Impact
Production volume data indicates Samsung will lead SK Hynix in HBM4 output. Monthly DRAM production for Samsung is projected at 650,000 units, compared to SK Hynix’s 550,000 units. For HBM4 chips, Samsung will produce approximately 170,000 units per month, outpacing SK Hynix’s 160,000 units.
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This early dominance in HBM4 production could help Samsung capture a larger share of the AI memory market. With competitors like Micron not expected to start production in 2026, the gap between Samsung, SK Hynix, and other players may widen. Consequently, HBM4 could set a new standard for AI memory performance and reliability.
Consumer Market Implications and RAM Shortage
Despite the mass production of HBM4, the consumer market is unlikely to benefit immediately. Both Samsung and SK Hynix have reportedly booked their HBM4 production entirely for AI companies and large-scale data centers. As a result, the ongoing RAM shortage affecting consumer PCs and gaming rigs may persist throughout 2026.
Industry analysts note that this scarcity could influence pricing and availability of traditional DRAM modules. Consumers might experience higher costs and limited supply for conventional memory products, even as cutting-edge AI memory continues to advance in parallel.
Conclusion and Future Outlook
The launch of HBM4 by Samsung and SK Hynix marks a significant milestone in AI memory development. These next-generation chips promise superior bandwidth, improved power efficiency, and enhanced integration capabilities, which will be critical for AI accelerators like Nvidia’s Vera Rubin platform.
While consumers may not immediately see the benefits due to prioritization of AI workloads, HBM4 production underscores the growing demand for specialized memory solutions in AI-driven computing. As Samsung begins production in February 2026 and SK Hynix follows in September, the landscape of AI memory is set to shift dramatically, shaping the future of high-performance computing.
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By The News Update — Updated 29 December 2025
