---
格式版本: 2
标题: "SK Hynix, Sandisk unveil first standard for high-bandwidth flash"
原文链接: "https://www.sdxcentral.com/news/sk-hynix-sandisk-unveil-first-standard-for-high-bandwidth-flash/"
发布日期: "2026-08-04"
发布时间校准状态: "found"
发布时间需复核: "否"
发布时间来源: "llm:local:strict_original_body"
发布时间证据: "August 04, 2026 ByBen WodeckiHave your say"
发布时间校准原因: "标题附近明确标注发布时间为2026年8月4日，且该日期为页面正文中的发布信息。"
发布时间校准置信度: "1"
发布时间候选数量: 40
发布时间严格候选数量: 14
发布时间原页读取状态: "source template page reused from URL open"
发布时间未找到原因: ""
发布时间校准时间: "2026-08-28T16:23:53+08:00"
发布时间仲裁状态: "confirmed"
发布时间仲裁尝试次数: 1
发布时间仲裁耗时毫秒: 16109
发现时间: "2026-08-28T16:22:27+08:00"
入库时间: "2026-08-28T08:24:59.674Z"
来源平台: "SDxCentral 搜索"
搜索渠道: "source_template"
搜索词: "site:sdxcentral.com HBM"
匹配关键词:
  - "HBM"
  - "latency"
  - "bandwidth"
  - "AI"
  - "performance"
相关厂家:
  - "Meta"
  - "Google"
相关专家:
  []
内容类型: "网页"
抓取工具: "Jina Reader"
清洗工具: "Jina Reader Markdown + Defuddle/Readability 正文提取"
原始附件:
  []
AI优质: "是"
AI打分: 78
AI分档: "高置信优质"
AI质检状态: "通过"
AI打分理由: "正文主线是SK海力士与闪迪面向AI推理基础设施发布首套HBF标准规格，属于关键内存/存储架构。SDxCentral为专业技术媒体，虽非OCP或厂商标准原文，但报道完整且引用厂商与此前采访。固定知识库未显示该标准规格已被完整披露；本文新增可核验信息包括最高512GB、两种堆叠配置、400Mb/s至3Tb/s三档带宽、采用UCIe连接GPU/CPU，以及首批设备预计2027年初送样。技术参数较具体，但尚无量产、具名客户采用或部署数据。命中正式标准/路线图通道，当前页面可作为标准发布及样品时间表的专业报道来源。"
AI质检模型: "gpt-5.6-sol"
AI质检时间: "2026-08-28T16:25:12+08:00"
AI主题相关性: 16
AI来源权威性: 12
AI新颖性: 19
AI技术细节: 15
AI商业部署信号: 7
AI完整性: 9
AI评分提示词版本: "v17-精简生产版"
AI评分提示词SHA256: "48fb9777f386026761b4873eaff30807694fb11e9b352d7c69bf2dfde750cc7d"
AI评分知识库版本: "knowledge_base_v1-20260819+runtime.16"
AI评分知识库SHA256: "40a80af8608138e357722148252278b4dd8d0d4a304d568c70eb0f9a35cf8b77"
AI评分知识库检索词: "[\"HBM\",\"latency\",\"bandwidth\",\"site:sdxcentral.com HBM\",\"RAS\",\"GPU\",\"Google\",\"Meta\",\"SK\",\"URL\",\"SDxCentral\",\"LDN\"]"
AI评分知识库命中: "[{\"id\":\"runtime-5095d81c147567ab9111181d\",\"title\":\"Meta’s custom transport protocol embraces packet chaos to boost AI throughput\",\"sourceType\":\"ai_excellent_article\",\"time\":\"\",\"matchedTerms\":[\"latency\",\"bandwidth\",\"RAS\",\"GPU\",\"Meta\",\"URL\",\"SDxCentral\",\"LDN\"],\"rank\":-19.61801902814916},{\"id\":\"july-correct-0016\",\"title\":\"AMD launches Instinct MI400 Series GPUs for AI workloads\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"HBM\",\"latency\",\"bandwidth\",\"RAS\",\"GPU\",\"URL\",\"SDxCentral\"],\"rank\":-15.90631059814967},{\"id\":\"july-correct-0017\",\"title\":\"AMD challenges Nvidia’s networking dominance with Helios racks boasting 50% higher bandwidth\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"HBM\",\"latency\",\"bandwidth\",\"RAS\",\"GPU\",\"SK\",\"URL\",\"SDxCentral\"],\"rank\":-15.344612290712476},{\"id\":\"july-correct-0071\",\"title\":\"SK Group and NVIDIA Expand Strategic Partnership Across AI Factories and Next-Generation Memory\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"HBM\",\"RAS\",\"SK\",\"URL\"],\"rank\":-14.305324176520182},{\"id\":\"runtime-5b8a3335997f3b1b31558541\",\"title\":\"STORE You Probably Forget How Cheap Memory Used To Be – And Is Not So Now\",\"sourceType\":\"ai_excellent_article\",\"time\":\"2026-08-25\",\"matchedTerms\":[\"HBM\",\"bandwidth\",\"RAS\",\"GPU\",\"Google\",\"Meta\",\"SK\"],\"rank\":-13.628849044749042}]"
AI摘要: "SK海力士与闪迪联合发布首个高带宽闪存（HBF）标准规范，作为高带宽内存（HBM）的替代方案，面向AI推理基础设施。该规范支持最高512GB容量，带宽覆盖400Mb/s至3Tb/s，首批HBF推理设备预计2027年初出样。"
AI摘要模型: "ali-deepseek-v4-flash"
AI摘要时间: "2026-09-07T02:08:37.633Z"
采集批次: "2026年8月28日16点22分01秒"
采集批次ID: "20260828-162201-542"
去重键: "https://www.sdxcentral.com/news/sk-hynix-sandisk-unveil-first-standard-for-high-bandwidth-flash"
---

Title: SK Hynix, Sandisk unveil first standard for high-bandwidth flash

URL Source: https://www.sdxcentral.com/news/sk-hynix-sandisk-unveil-first-standard-for-high-bandwidth-flash/

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# SK Hynix, Sandisk unveil first standard for high-bandwidth flash

NAND flash alternative to HBM redefine low latency for AI inference infrastructure

August 04, 2026 By[Ben Wodecki](https://www.sdxcentral.com/profile/ben-wodecki/)[Have your say](https://www.sdxcentral.com/news/sk-hynix-sandisk-unveil-first-standard-for-high-bandwidth-flash/#comments)

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![Image 3: High bandwidth flash graphic](./assets/img-f23a1c7e.jpg)

– SK hynix

SK Hynix and Sandisk unveiled the first standard specifications for high-bandwidth flash (HBF), the next-generation alternative to supply chain-constrained high-bandwidth memory (HBM).

The specification was hinted at earlier this year through a consortium to standardize the nascent HBF technology via the Open Compute Project (OCP). The capacity specs cover up to 512 gigabytes across two stack configurations and with bandwidth levels measured across three grades, outlining performance capabilities ranging from 400 Mb/s to 3 Tb/s.

It also makes use of the universal chiplet interconnect express (UCIe) open high-speed interconnection to interlink the memory hardware with accelerators including graphics processing units (GPUs) and central processing units (CPUs).

“With the rapid spread of AI applications, we are at a point where overall data processing structures must be redesigned,” SK Hynix EVP and head of solution development Kim Chun-sung noted. “Through HBF, SK Hynix will expand the boundaries between memory and storage and contribute to building new architectures that enhance overall system efficiency.”

HBF was teased back in February 2025, with Sandisk contending that traditional HBM, which uses dynamic random-access memory (DRAM) at its core, cannot scale physically or economically. Instead, it argued that taking vertical stacking and packaging concepts used for HBM and pairing them with non-volatile (NAND) flash allows for more memory capacity while providing comparable levels of bandwidth – all while maintaining a similar price point.

![Image 4: High bandwidth flash graphic](./assets/img-0db091d1.png)

11 May 2026

# [Beyond HBM: The flash memory technology that could reshape AI infrastructure](https://www.sdxcentral.com/analysis/beyond-hbm-the-flash-memory-technology-that-could-reshape-ai-infrastructure/)

Sandisk thinks a NAND-based architecture can smash the memory wall

Sandisk’s Cynthia Hsu in a [conversation with _SDxCentral_](https://www.sdxcentral.com/analysis/beyond-hbm-the-flash-memory-technology-that-could-reshape-ai-infrastructure/) earlier this year said HBF was purpose-built for AI inference workloads, while also offering means to significantly reduce energy consumption for memory-intensive workloads.

HBF development efforts were given a lift when Google engineers [lauded it](https://www.sdxcentral.com/news/ai-inference-crisis-google-engineers-on-why-network-latency-and-memory-trump-compute/) for potentially providing 10-times the memory capacity per node for inference workloads. Google was listed as a participant in the HBF consortium per SK Hynix’s announcement, with Jeff Bezos and Samsung-backed AI chip firm Tenstorrent also on board.

Following the launch of the first HBF standard, the memory chip makers said the consortium will work to further expand technical maturity and market acceptance “based on open collaboration.”

“As agentic AI rapidly commercializes, the volume of data to process is surging alongside growing demands for higher speed and efficiency,” the announcement reads. “Recognizing that a single memory type cannot address these complex challenges, both speakers will present the necessity and future direction of a next-generation architecture based on tiered memory, a framework that connects and optimizes diverse memory types into a unified system.”

The first HBF-powered inference devices are expected to sample in early 2027, Hsu outlined back in May, with the OCP collaboration allowing the pair to “move a little bit faster.”

“You don't want to do this in a silo. And we're moving quite fast under OCP," Hsu told _SDxCentral_. “You won't have to wait too long.”

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