SK Hynix Ships 12-Layer HBM4E AI Memory Samples With 16Gbps Speed and 48GB Capacity

SK Hynix announced on Thursday that it has shipped 12-layer HBM4E samples to major customers — the next generation of high-bandwidth memory designed for AI training and inference workloads. The announcement, made via the company's official newsroom, confirms SK Hynix remains ahead in the HBM production race: Samsung shipped its own HBM4E samples in late May, but SK Hynix's 12-stack version delivers higher capacity and speed specifications.

The 12-layer HBM4E achieves 48 gigabytes of capacity per stack and a maximum data transfer speed of 16 gigabits per second per pin. Power efficiency is improved by more than 20 percent compared to the previous HBM4 generation. These are not incremental gains: in AI training clusters where dozens or hundreds of accelerators run simultaneously, memory bandwidth and power efficiency directly affect both throughput and operational cost.

What HBM4E Improves Over HBM4

SK Hynix uses its Advanced MR-MUF (Mass Reflow Molded Underfill) packaging process to stack 12 chips while maintaining structural stability — a manufacturing challenge that grows significantly harder as layer counts increase. The new generation also reduces heat resistance by 17 percent compared to HBM4, addressing one of the primary reliability concerns at high layer counts where thermal management between tightly packed chips becomes critical.

Latency has also been reduced through interface and design optimization, which matters particularly for inference workloads where memory access patterns are less predictable than in training. The net result is memory that runs faster, cooler, and more efficiently than its predecessor — all three improvements being relevant to the AI accelerator customers SK Hynix is targeting.

The Competitive Landscape

HBM has become the decisive battlefield in AI hardware. Nvidia's H100 and H200 GPUs use HBM3E, and the company's upcoming Rubin Ultra platform is designed around HBM4E — making this generation of memory critical to Nvidia's next product cycle. SK Hynix has been Nvidia's primary HBM supplier; maintaining that relationship through HBM4E matters enormously for both companies.

Samsung's HBM4E samples, shipped in late May, were 10-layer rather than 12-layer — giving SK Hynix a capacity advantage at the same generation. Micron, the third major HBM supplier, has not announced HBM4E timelines publicly. SK Hynix's position is that its early 12-layer samples give customers more time for qualification before the Rubin Ultra ramp begins.

The current shipments are qualification samples, not mass production. SK Hynix said it is working closely with partners to establish mass production timing but has not committed to a specific date. Given the typical 6-to-12-month qualification cycle for AI memory, volume HBM4E production likely begins in late 2026 or early 2027.