The global race to dominate artificial intelligence hardware is accelerating, and memory technology sits at the heart of this competition. According to recent reports, Samsung Electronics and SK Hynix are preparing to enter mass production of their sixth-generation high-bandwidth memory (HBM4) chips in 2026. Designed specifically for advanced AI workloads, HBM4 is expected to deliver major gains in bandwidth, efficiency, and system-level customisation.

Among the two South Korean giants, Samsung is reportedly set to start production earlier, giving it a potential edge in the rapidly expanding AI accelerator market.

HBM4: Memory Built for the AI Era

High-bandwidth memory has become a critical component in modern AI systems, particularly for training and running large-scale models. The upcoming HBM4 standard is purpose-built for next-generation AI accelerators and data-center workloads, where massive data throughput and energy efficiency are essential.

Compared to its predecessor, HBM4 is expected to offer:

Nearly double the memory bandwidth

Up to 40 percent improvements in power efficiency

Enhanced customisation for both AI-focused and non-AI chipsets

Better integration with advanced processors and accelerators

These improvements make HBM4 a key enabler for future AI platforms.

Samsung and SK Hynix Lead the HBM4 Production Timeline

According to a report by South Korean publication SEDaily, both Samsung and SK Hynix are planning to begin mass manufacturing HBM4 chips in 2026. However, their timelines differ:

Samsung is reportedly targeting February 2026 to kick off production

SK Hynix is expected to complete manufacturing readiness by September 2026

This early start could allow Samsung to widen the gap with competitors, especially as other memory makers, including Micron, are not expected to begin HBM4 fabrication in the same year.

Strong Ties With Nvidia’s Next-Gen AI Platform

Most of the HBM4 output from Samsung and SK Hynix is reportedly earmarked for Nvidia’s upcoming “Vera Rubin” AI accelerator system. These accelerators are expected to power future generations of AI data centers and supercomputing infrastructure.

Recent reports suggest that Samsung has already passed Nvidia’s quality and validation tests, making it eligible to supply HBM4 chips for Nvidia’s AI platforms. This development is significant, as Nvidia’s approval is often considered a major milestone in the AI hardware supply chain.

Different Manufacturing Approaches, Same AI Goal

While both companies are racing toward the same market, their manufacturing strategies show notable differences:

SK Hynix is reportedly working with TSMC and plans to use a 12nm logic process for the base die, which acts as the control logic or “brain” of the HBM4 stack.

Samsung, on the other hand, is said to be using its own 10nm logic process for the same component.

Despite these differences, both approaches aim to deliver higher performance, lower power consumption, and tighter integration with AI accelerators.

Production Volume Advantage for Samsung

In terms of scale, Samsung appears to have a production edge. Reports indicate that:

Samsung’s monthly DRAM output stands at around 6.5 lakh units, compared to SK Hynix’s 5.5 lakh units

In HBM production specifically, Samsung is said to lead by approximately 10,000 units per month, producing around 1.7 lakh units versus SK Hynix’s 1.6 lakh units

This manufacturing advantage could translate into better supply reliability for major AI customers.

No Immediate Relief for the Consumer Market

Despite the massive investment in next-generation memory, consumer markets are unlikely to benefit in the near term. Reports suggest that nearly all HBM4 production capacity for 2026 has already been reserved by AI companies.

As a result:

AI and data-center customers will receive priority

The ongoing RAM and memory supply tightness is expected to continue through 2026

Consumer-grade memory prices may remain under pressure due to limited availability

What This Means for the AI and Semiconductor Industry

The early move toward HBM4 production highlights how central memory technology has become to AI innovation. With Samsung and SK Hynix leading the charge, the competitive gap in the AI memory market could widen significantly over the next two years.

For Samsung, an earlier production start combined with higher output volumes strengthens its position as a key supplier for AI infrastructure. For SK Hynix, close collaboration with TSMC and strong ties with Nvidia ensure it remains a critical player in the high-bandwidth memory ecosystem.

Conclusion

Samsung’s reported plan to begin HBM4 manufacturing in early 2026 signals a major milestone in AI-focused semiconductor development. Alongside SK Hynix, the company is helping define the future of high-performance memory—one where bandwidth, efficiency, and customisation are paramount.

As AI workloads continue to grow in scale and complexity, HBM4 is poised to become a foundational technology, powering the next generation of accelerators, data centers, and intelligent systems worldwide.

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