HBF記憶體評測：SK hynix新標準解AI推論瓶頸 | HBF Memory Review: SK hynix's New AI Bottleneck Fix

By Kit 小克 | AI Tool Observer | 2026-08-06

🇹🇼 HBF記憶體評測：SK hynix新標準解AI推論瓶頸

HBF（High Bandwidth Flash）是SK hynix和SanDisk在2026年8月的Flash Memory Summit上共同發表的全新記憶體標準，鎖定AI推論（inference）最頭痛的「頻寬 vs 容量」兩難。過去AI晶片得在「快但貴又小」的HBM和「大但慢」的SSD之間妥協，HBF想當一個折衷的中間層，一次解決兩邊都想要的東西。

HBF是什麼？跟HBM有什麼不同？

HBF是一種疊在AI加速器旁邊的NAND快閃記憶體，設計概念是「用HBM的堆疊方式，塞進SSD等級的容量」。根據OCP（Open Compute Project）公布的第一版技術規格，HBF最高支援512GB容量（採8層或16層NAND堆疊），頻寬則依等級分成三種，從約0.4 TB/s到3.0 TB/s不等——比一般SSD快上好幾個量級，但容量又遠勝HBM動輒只有幾十GB的天花板。

為什麼AI公司需要HBF？

大型語言模型的推論瓶頸，很多時候卡在「記憶體不夠大，模型參數塞不進去」或「記憶體不夠快，資料搬不動」。HBF的定位就是專門解決這個AI推論瓶頸：讓模型能在單一晶片旁掛更大容量的記憶體，同時維持接近HBM的存取速度，減少對外部儲存裝置的依賴。

誰在推動HBF標準？

SK hynix：負責HBF的堆疊封裝技術，是HBM市場的領導廠商之一
SanDisk：提供NAND快閃記憶體技術基礎
Google：已加入聯盟，代表雲端AI基礎設施端的需求
Tenstorrent：AI晶片新創，代表硬體設計端的採用意願

整份規格已透過OCP架構公開釋出，意味著其他晶片廠商也能參考這套標準來設計相容產品，而不是被單一供應商鎖死。

HBF什麼時候能用？值得關注嗎？

目前公布的只是第一版技術規格，距離量產出貨還有一段距離，實際效能與良率都還要等真正的晶片問世才能驗證。但這代表記憶體廠商已經正式承認：AI推論的瓶頸不只在算力，記憶體架構本身也需要一次典範轉移。對關注AI基礎設施的人來說，HBF是接下來一兩年值得追蹤的硬體規格之一。

好不好用，試了才知道。

🇺🇸 HBF Memory Review: SK hynix's New AI Bottleneck Fix

HBF (High Bandwidth Flash) is a new memory standard unveiled by SK hynix and SanDisk at Flash Memory Summit 2026, aimed squarely at AI inference's toughest trade-off: bandwidth versus capacity. Until now, AI chips had to choose between HBM (fast but small and expensive) and SSDs (huge but slow). HBF is pitched as the middle layer that gives you both.

What Is HBF and How Does It Differ from HBM?

HBF is NAND flash memory stacked next to an AI accelerator, essentially borrowing HBM's stacking architecture and filling it with SSD-class capacity. Per the first OCP (Open Compute Project) technical specification, HBF supports up to 512GB using 8-high or 16-high NAND die stacks, with bandwidth ranging across three tiers from roughly 0.4 TB/s to 3.0 TB/s — orders of magnitude faster than a typical SSD, while dwarfing HBM's usual tens-of-gigabytes ceiling.

Why Does the AI Industry Need HBF?

Large model inference bottlenecks often boil down to two problems: memory too small to hold the model, or memory too slow to move data fast enough. HBF is designed to fix exactly this AI inference bottleneck — letting accelerators pair with much larger memory pools while staying close to HBM-level access speeds, cutting reliance on external storage round-trips.

Who's Backing the HBF Standard?

SK hynix — brings its HBM stacking and packaging expertise, one of the dominant HBM suppliers today
SanDisk — contributes the underlying NAND flash technology
Google — represents cloud AI infrastructure demand
Tenstorrent — an AI chip startup signaling hardware-design-side buy-in

The full spec was released through the OCP framework, meaning it's openly published rather than locked to one vendor — other chipmakers can design HBF-compatible products against the same standard.

Is HBF Ready to Use Yet?

This is only the first technical specification, not shipping silicon — real-world performance and manufacturing yield still need to be proven once actual chips arrive. But the move signals something notable: memory makers are now openly acknowledging that AI inference bottlenecks aren't just about compute, they're about memory architecture too. If you track AI infrastructure, HBF is worth watching over the next year or two.

Good or not, you won't know until you try it.

Sources / 資料來源

常見問題 FAQ

HBF是什麼？

HBF（High Bandwidth Flash）是SK hynix與SanDisk共同制定的新記憶體標準，定位在HBM與SSD之間，目標是同時提供高頻寬與大容量，解決AI推論的記憶體瓶頸。

HBF和HBM有什麼差別？

HBM頻寬高但容量小、成本高；HBF用類似的堆疊技術搭配NAND快閃，最高可支援512GB容量，頻寬則落在0.4到3.0 TB/s之間，是容量與速度的折衷方案。

HBF目前有哪些廠商支持？

目前公開加入的有SK hynix、SanDisk、Google與Tenstorrent，規格透過OCP（Open Compute Project）公開釋出，其他廠商也能參考設計相容產品。

HBF什麼時候能商用？

目前只公布第一版技術規格，尚未有實際量產晶片問世，實際效能與良率都要等真正產品出來才能驗證。

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