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Samsung HBM5 ilə HBM4E-ni ikiqatlayır: 4 TB/s hər stack və 4096-bit interfeys hədəfi

Samsung’s HBM5 Aims to Double HBM4E Bandwidth – Up to 4 TB/s per Stack and a Possible 4,096‑bit Interface

Samsung targets 2× the bandwidth of HBM4E and 20% better perf/W with HBM5, hinting at a much wider interface and massive bandwidth for future AI accelerators.

September 3, 20262 min read65 tags

HBM5 targets: 2× bandwidth, better perf/W

At its Memory Executive Summit, Samsung outlined its goals for next‑gen HBM5 memory:

  • 2× the performance of HBM4E per stack
  • Around 20% higher performance per watt

Samsung also confirmed that HBM5 stacks will integrate a heat path block (HPB), expected to cut thermal resistance by ~20%, simplifying cooling for dense HBM packages.

If per‑stack bandwidth is doubled, HBM5 would reach roughly 4 TB/s per stack in the 2028–2029 timeframe.

4,096‑bit interface on the table

Today, DRAM vendors and IP providers already ship HBM4/HBM4E PHYs and controllers capable of 16 GT/s, but the JEDEC official data rate for HBM4E is expected to be about 12 GT/s.

To get 2× HBM4E bandwidth, the HBM5 spec must do at least one of the following:

  • Double per‑pin data rate from 12 GT/s → 24 GT/s
  • Double interface width from 2,048 → 4,096 bits
  • Use a mix of wider bus + higher speed

A 4,096‑bit HBM interface has already been explored by KAIST and Marvell, but there is no semi‑official confirmation that JEDEC will adopt it.

From a performance‑per‑watt perspective, widening the interface is usually easier than pushing per‑pin speeds well beyond 20 GT/s, which demands faster drivers/receivers, tighter timing, stronger equalization, and a more complex PHY. However, going from 2,048 to 4,096 I/Os doubles TSVs, bumps, routing complexity, and makes the base die extremely challenging.

A compromise such as a 3,072‑bit bus with a moderate speed bump might be more practical, but for now all concrete HBM5 details remain speculative.

Meanwhile, TSMC expects AI accelerators to integrate 20–24 HBM5/HBM5E stacks per package by the end of the decade, yielding a staggering 80–96 TB/s of aggregate memory bandwidth.

The ambition to double HBM4E’s 2 TB/s per‑stack bandwidth in a single generation underlines how aggressively memory is scaling to keep up with AI workloads.


Source: Tom's Hardware