也没见闪迪跌啊_老虎社区_美港股上老虎 - 老虎社区

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Yangsirisme
06-16

也没见闪迪跌啊

Citrini：AMD、苹果双双押注闪存替代DRAM，内存成本或直降55倍

面对DRAM暴涨，AI存储向低成本闪存转移。AMD收购MEXT将AI驱动闪存技术引入数据中心，苹果推进端侧闪存方案。巨头看重闪存成本仅为DRAM的1/55，正重构AI存储架构。

Citrini：AMD、苹果双双押注闪存替代DRAM，内存成本或直降55倍

免责声明：上述内容仅代表发帖人个人观点，不构成本平台的任何投资建议。

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16:51","market":"fut","language":"zh","title":"Citrini：AMD、苹果双双押注闪存替代DRAM，内存成本或直降55倍","url":"https://stock-news.laohu8.com/highlight/detail?id=2643373567","media":"华尔街见闻","summary":"面对DRAM暴涨，AI存储向低成本闪存转移。AMD收购MEXT将AI驱动闪存技术引入数据中心，苹果推进端侧闪存方案。巨头看重闪存成本仅为DRAM的1/55，正重构AI存储架构。","content":"<html><head></head><body><p style=\"text-align: left;\">AI推理对昂贵DRAM的依赖正在松动。<a href=\"https://laohu8.com/S/AMD\">AMD</a>宣布收购内存优化公司MEXT，将AI驱动的闪存优化技术引入数据中心。这标志着AI存储架构正在经历一场结构性迁移，而核心驱动力只有一个数字：<strong>闪存成本仅为DRAM的1/55。</strong></p><p style=\"text-align: left;\">周一，AMD宣布以未披露金额完成对MEXT的收购。MEXT开发的AI驱动预测内存技术，旨在让闪存的行为更接近DRAM，在维持性能与效率的同时扩展可用内存容量。AMD表示，此次收购将扩充其AI产品组合，帮助数据中心客户提升性能、降低总拥有成本并加速工作负载部署。&#34;对内存的需求正在企业计算的每个品类中增长，&#34;AMD在声明中称。</p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/a86b38617b68e608382e6d8db9bf1389\" data-align=\"center\" tg-width=\"1024\" tg-height=\"755\"/><span></span></p><p style=\"text-align: left;\">收购消息刺激AMD股价周一上涨7.7%至550.75美元，市值逼近9000亿美元关口，当日S&amp;P 500指数整体上涨1.8%。AMD今年以来累计涨幅已达323%。花旗上周五将AMD评级从中性上调至买入，目标价从460美元上调至575美元。</p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/fe5a732905489dfc96d3c249e9bea543\" data-align=\"center\" tg-width=\"882\" tg-height=\"984\"/><span></span></p><p style=\"text-align: left;\">值得注意的是，<a href=\"https://laohu8.com/S/AAPL\">苹果</a>早在2024年就开始推进&#34;LLM in a Flash&#34;端侧方案。这一布局背后，是愈演愈烈的DRAM供给危机。据TrendForce数据，高带宽内存（HBM）已占全部DRAM晶圆产能的约四分之一，DRAM合约价格在2026年第一季度单季环比暴涨约90%。Citrini Research指出，<strong>AI存储需求已大到需要多层架构共同承接，闪存并非取代HBM，而是在容量维度承接溢出需求</strong>——这场架构重构正在重新定价整条AI存储产业链。</p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/7db9e832d1e323bc33ae1b899213dd97\" data-align=\"center\" tg-width=\"1024\" tg-height=\"825\"/><span></span></p><h2 style=\"text-align: left;\">内存税危机：瓶颈从AI蔓延至全经济</h2><p style=\"text-align: left;\">据<a href=\"https://laohu8.com/S/MS\">摩根士丹利</a>分析师Shawn Kim团队本月早些时候的判断，<strong>内存价格飙升和供应稀缺正演变为数字经济的全面风险，</strong>&#34;从AI基础设施的瓶颈，蔓延至硬件利润率、设备可负担性、云成本、通胀乃至政策层面。&#34;这一压力已有具体案例佐证：Xbox首席执行官Asha Sharma上周表示，内存成本在过去两年间上涨了约五倍，导致公司无法生产消费者所需数量的游戏主机。</p><p style=\"text-align: left;\">HBM对DRAM产能的持续蚕食是这场危机的核心驱动。据TrendForce及<a href=\"https://laohu8.com/S/SMSN.UK\">三星</a>、SK海力士、<a href=\"https://laohu8.com/S/MU\">美光</a>等厂商的披露数据，HBM在DRAM晶圆产能中的占比已从2020年的2%攀升至2026年预估的25%。超大规模云厂商以多年期合同预购未来晶圆产出，进一步压缩了面向手机和PC的标准芯片可用产能。</p><p style=\"text-align: left;\">新增DRAM产能的建设同样面临结构性制约。扩产依赖EUV光刻机印制更精细线宽，每台EUV设备售价高达约2亿美元，一座新晶圆厂的投资动辄<a href=\"https://laohu8.com/S/SBAY\">数百亿</a>美元，建设周期在顺利情况下也需数年。这一供给刚性，正是本轮短缺具备持续性的根本原因。</p><h2 style=\"text-align: left;\">55倍成本差：闪存替代的经济逻辑</h2><p style=\"text-align: left;\">据Citrini Research测算，<strong>闪存的每比特成本约为DRAM的1/55——QLC NAND约为每GB 0.05美元，DDR5 DRAM约为2.75美元，HBM3E则高达15美元。</strong>这一价差的可利用空间，在于AI推理中最大的单一内存消耗——KV缓存（记录模型每次生成步骤中所有先前标记的上下文，长对话中可增长至数百GB）——对读取速度的要求远低于模型权重的解码路径。对于此类顺序读取数据，DRAM的速度优势大幅收窄，而闪存的容量优势则充分体现。</p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/8f9b061541f243d013842840b2a9af30\" data-align=\"center\" tg-width=\"1024\" tg-height=\"671\"/><span></span></p><p style=\"text-align: left;\">闪存的扩容路径也与DRAM存在本质区别。闪存通过垂直堆叠更多单元层来增加容量，依赖现有工厂已有的沉积和刻蚀工艺，无需新的光刻节点，不占用EUV资源。闪存控制器基于成熟的6/7纳米制程生产，远离正在制约先进制程的瓶颈节点。</p><p style=\"text-align: left;\">苹果研究人员此前发表的论文&#34;LLM in a Flash&#34;提供了方法论支撑：通过将大语言模型参数存储于设备闪存、按需调取至DRAM的方式，可在DRAM容量受限的设备上运行超出其容量上限的模型，并在CPU和GPU上分别实现比朴素加载方式快4至5倍和20至25倍的推理速度。</p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/1b87a29aa7ba0ff023c247b4f54e9951\" data-align=\"center\" tg-width=\"1024\" tg-height=\"630\"/><span></span></p><h2 style=\"text-align: left;\">两条路径：数据中心与端侧同步演进</h2><p style=\"text-align: left;\">AMD的收购聚焦数据中心场景。通过将MEXT技术整合至AMD数据中心产品组合，AMD寻求帮助企业客户在AI工作负载部署中提升资源利用效率并压缩成本。摩根士丹利Shawn Kim团队认为，尽管内存短缺持续，AMD在云端市场竞争格局上仍具结构性优势——&#34;代理式AI驱动的CPU需求在结构上有利于AMD在云端市场份额的扩张。&#34;花旗对AMD的乐观预判则更多基于其GPU销售与<a href=\"https://laohu8.com/S/NVDA\">英伟达</a>的正面竞争态势。</p><p style=\"text-align: left;\">苹果的路径则落子端侧。&#34;LLM in a Flash&#34;方案将模型推理对昂贵云端内存的依赖部分转移至设备本地闪存，在降低云端运算成本的同时，为端侧AI应用提供可行的内存架构支撑。</p><p style=\"text-align: left;\">据Citrini Research，两大路径共同指向同一结论：<strong>AI推理的内存层级正在重构，低频KV缓存、模型权重及端侧数据，将逐步从高价的HBM/DRAM下沉至NAND Flash/SSD层，形成多层次存储架构。</strong></p><p style=\"text-align: left;\">这一架构转变正沿产业链形成多层次的传导效应。据Citrini Research梳理，最直接的受益层是NAND原厂，高容量NAND、企业级SSD及QLC NAND为最纯粹的方向，包括SanDisk、<a href=\"https://laohu8.com/S/WDC\">西部数据</a>、美光及铠侠。</p><p style=\"text-align: left;\">SSD控制器层被认为持续性最强——让闪存真正接近内存体验的核心在于控制器、固件与NVMe架构优化，涉及<a href=\"https://laohu8.com/S/SIMO\">Silicon Motion</a>、Marvell等。CXL/PCIe高速互联层亦受益。</p></body></html>","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta 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padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 11px; color: #7E829C; margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nCitrini：AMD、苹果双双押注闪存替代DRAM，内存成本或直降55倍\n</h2>\n\n<h4 class=\"meta\">\n\n\n<a class=\"head\" href=\"https://laohu8.com/wemedia/1084101182\">\n\n\n<div class=\"h-thumb\" style=\"background-image:url(https://static.tigerbbs.com/66809d1f5c2e43e2bdf15820c6d6897e);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">华尔街见闻 </p>\n<p class=\"h-time\">2026-06-16 16:51</p>\n</div>\n\n</a>\n\n\n</h4>\n\n</header>\n<article>\n<html><head></head><body><p style=\"text-align: left;\">AI推理对昂贵DRAM的依赖正在松动。<a href=\"https://laohu8.com/S/AMD\">AMD</a>宣布收购内存优化公司MEXT，将AI驱动的闪存优化技术引入数据中心。这标志着AI存储架构正在经历一场结构性迁移，而核心驱动力只有一个数字：<strong>闪存成本仅为DRAM的1/55。</strong></p><p style=\"text-align: left;\">周一，AMD宣布以未披露金额完成对MEXT的收购。MEXT开发的AI驱动预测内存技术，旨在让闪存的行为更接近DRAM，在维持性能与效率的同时扩展可用内存容量。AMD表示，此次收购将扩充其AI产品组合，帮助数据中心客户提升性能、降低总拥有成本并加速工作负载部署。&#34;对内存的需求正在企业计算的每个品类中增长，&#34;AMD在声明中称。</p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/a86b38617b68e608382e6d8db9bf1389\" data-align=\"center\" tg-width=\"1024\" tg-height=\"755\"/><span></span></p><p style=\"text-align: left;\">收购消息刺激AMD股价周一上涨7.7%至550.75美元，市值逼近9000亿美元关口，当日S&amp;P 500指数整体上涨1.8%。AMD今年以来累计涨幅已达323%。花旗上周五将AMD评级从中性上调至买入，目标价从460美元上调至575美元。</p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/fe5a732905489dfc96d3c249e9bea543\" data-align=\"center\" tg-width=\"882\" tg-height=\"984\"/><span></span></p><p style=\"text-align: left;\">值得注意的是，<a href=\"https://laohu8.com/S/AAPL\">苹果</a>早在2024年就开始推进&#34;LLM in a Flash&#34;端侧方案。这一布局背后，是愈演愈烈的DRAM供给危机。据TrendForce数据，高带宽内存（HBM）已占全部DRAM晶圆产能的约四分之一，DRAM合约价格在2026年第一季度单季环比暴涨约90%。Citrini Research指出，<strong>AI存储需求已大到需要多层架构共同承接，闪存并非取代HBM，而是在容量维度承接溢出需求</strong>——这场架构重构正在重新定价整条AI存储产业链。</p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/7db9e832d1e323bc33ae1b899213dd97\" data-align=\"center\" tg-width=\"1024\" tg-height=\"825\"/><span></span></p><h2 style=\"text-align: left;\">内存税危机：瓶颈从AI蔓延至全经济</h2><p style=\"text-align: left;\">据<a href=\"https://laohu8.com/S/MS\">摩根士丹利</a>分析师Shawn Kim团队本月早些时候的判断，<strong>内存价格飙升和供应稀缺正演变为数字经济的全面风险，</strong>&#34;从AI基础设施的瓶颈，蔓延至硬件利润率、设备可负担性、云成本、通胀乃至政策层面。&#34;这一压力已有具体案例佐证：Xbox首席执行官Asha Sharma上周表示，内存成本在过去两年间上涨了约五倍，导致公司无法生产消费者所需数量的游戏主机。</p><p style=\"text-align: left;\">HBM对DRAM产能的持续蚕食是这场危机的核心驱动。据TrendForce及<a href=\"https://laohu8.com/S/SMSN.UK\">三星</a>、SK海力士、<a href=\"https://laohu8.com/S/MU\">美光</a>等厂商的披露数据，HBM在DRAM晶圆产能中的占比已从2020年的2%攀升至2026年预估的25%。超大规模云厂商以多年期合同预购未来晶圆产出，进一步压缩了面向手机和PC的标准芯片可用产能。</p><p style=\"text-align: left;\">新增DRAM产能的建设同样面临结构性制约。扩产依赖EUV光刻机印制更精细线宽，每台EUV设备售价高达约2亿美元，一座新晶圆厂的投资动辄<a href=\"https://laohu8.com/S/SBAY\">数百亿</a>美元，建设周期在顺利情况下也需数年。这一供给刚性，正是本轮短缺具备持续性的根本原因。</p><h2 style=\"text-align: left;\">55倍成本差：闪存替代的经济逻辑</h2><p style=\"text-align: left;\">据Citrini Research测算，<strong>闪存的每比特成本约为DRAM的1/55——QLC NAND约为每GB 0.05美元，DDR5 DRAM约为2.75美元，HBM3E则高达15美元。</strong>这一价差的可利用空间，在于AI推理中最大的单一内存消耗——KV缓存（记录模型每次生成步骤中所有先前标记的上下文，长对话中可增长至数百GB）——对读取速度的要求远低于模型权重的解码路径。对于此类顺序读取数据，DRAM的速度优势大幅收窄，而闪存的容量优势则充分体现。</p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/8f9b061541f243d013842840b2a9af30\" data-align=\"center\" tg-width=\"1024\" tg-height=\"671\"/><span></span></p><p style=\"text-align: left;\">闪存的扩容路径也与DRAM存在本质区别。闪存通过垂直堆叠更多单元层来增加容量，依赖现有工厂已有的沉积和刻蚀工艺，无需新的光刻节点，不占用EUV资源。闪存控制器基于成熟的6/7纳米制程生产，远离正在制约先进制程的瓶颈节点。</p><p style=\"text-align: left;\">苹果研究人员此前发表的论文&#34;LLM in a Flash&#34;提供了方法论支撑：通过将大语言模型参数存储于设备闪存、按需调取至DRAM的方式，可在DRAM容量受限的设备上运行超出其容量上限的模型，并在CPU和GPU上分别实现比朴素加载方式快4至5倍和20至25倍的推理速度。</p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/1b87a29aa7ba0ff023c247b4f54e9951\" data-align=\"center\" tg-width=\"1024\" tg-height=\"630\"/><span></span></p><h2 style=\"text-align: left;\">两条路径：数据中心与端侧同步演进</h2><p style=\"text-align: left;\">AMD的收购聚焦数据中心场景。通过将MEXT技术整合至AMD数据中心产品组合，AMD寻求帮助企业客户在AI工作负载部署中提升资源利用效率并压缩成本。摩根士丹利Shawn Kim团队认为，尽管内存短缺持续，AMD在云端市场竞争格局上仍具结构性优势——&#34;代理式AI驱动的CPU需求在结构上有利于AMD在云端市场份额的扩张。&#34;花旗对AMD的乐观预判则更多基于其GPU销售与<a href=\"https://laohu8.com/S/NVDA\">英伟达</a>的正面竞争态势。</p><p style=\"text-align: left;\">苹果的路径则落子端侧。&#34;LLM in a Flash&#34;方案将模型推理对昂贵云端内存的依赖部分转移至设备本地闪存，在降低云端运算成本的同时，为端侧AI应用提供可行的内存架构支撑。</p><p style=\"text-align: left;\">据Citrini Research，两大路径共同指向同一结论：<strong>AI推理的内存层级正在重构，低频KV缓存、模型权重及端侧数据，将逐步从高价的HBM/DRAM下沉至NAND Flash/SSD层，形成多层次存储架构。</strong></p><p style=\"text-align: left;\">这一架构转变正沿产业链形成多层次的传导效应。据Citrini Research梳理，最直接的受益层是NAND原厂，高容量NAND、企业级SSD及QLC NAND为最纯粹的方向，包括SanDisk、<a href=\"https://laohu8.com/S/WDC\">西部数据</a>、美光及铠侠。</p><p style=\"text-align: left;\">SSD控制器层被认为持续性最强——让闪存真正接近内存体验的核心在于控制器、固件与NVMe架构优化，涉及<a href=\"https://laohu8.com/S/SIMO\">Silicon Motion</a>、Marvell等。CXL/PCIe高速互联层亦受益。</p></body></html>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/a86b38617b68e608382e6d8db9bf1389","relate_stocks":{"BK4533":"AQR资本管理(全球第二大对冲基金)","LU2023250330.USD":"ALLIANZ INCOME AND GROWTH \"AMG\" (USD) INC","LU1732799900.SGD":"JPMorgan Investment Funds - Global Income A (irc) SGD-H","LU0203201768.USD":"AB SICAV I - ALL MARKET INCOME PORTFOLIO \"AX\" (USD) INC","LU0353189680.USD":"富国美国全盘成长基金Cl A Acc","LU1935042991.SGD":"MANULIFE GF GLOBAL MULTI-ASSET DIVERSIFIED INCOME  \"AA\" 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Research指出，AI存储需求已大到需要多层架构共同承接，闪存并非取代HBM，而是在容量维度承接溢出需求——这场架构重构正在重新定价整条AI存储产业链。内存税危机：瓶颈从AI蔓延至全经济据摩根士丹利分析师Shawn Kim团队本月早些时候的判断，内存价格飙升和供应稀缺正演变为数字经济的全面风险，\"从AI基础设施的瓶颈，蔓延至硬件利润率、设备可负担性、云成本、通胀乃至政策层面。\"这一压力已有具体案例佐证：Xbox首席执行官Asha Sharma上周表示，内存成本在过去两年间上涨了约五倍，导致公司无法生产消费者所需数量的游戏主机。HBM对DRAM产能的持续蚕食是这场危机的核心驱动。据TrendForce及三星、SK海力士、美光等厂商的披露数据，HBM在DRAM晶圆产能中的占比已从2020年的2%攀升至2026年预估的25%。超大规模云厂商以多年期合同预购未来晶圆产出，进一步压缩了面向手机和PC的标准芯片可用产能。新增DRAM产能的建设同样面临结构性制约。扩产依赖EUV光刻机印制更精细线宽，每台EUV设备售价高达约2亿美元，一座新晶圆厂的投资动辄数百亿美元，建设周期在顺利情况下也需数年。这一供给刚性，正是本轮短缺具备持续性的根本原因。55倍成本差：闪存替代的经济逻辑据Citrini Research测算，闪存的每比特成本约为DRAM的1/55——QLC NAND约为每GB 0.05美元，DDR5 DRAM约为2.75美元，HBM3E则高达15美元。这一价差的可利用空间，在于AI推理中最大的单一内存消耗——KV缓存（记录模型每次生成步骤中所有先前标记的上下文，长对话中可增长至数百GB）——对读取速度的要求远低于模型权重的解码路径。对于此类顺序读取数据，DRAM的速度优势大幅收窄，而闪存的容量优势则充分体现。闪存的扩容路径也与DRAM存在本质区别。闪存通过垂直堆叠更多单元层来增加容量，依赖现有工厂已有的沉积和刻蚀工艺，无需新的光刻节点，不占用EUV资源。闪存控制器基于成熟的6/7纳米制程生产，远离正在制约先进制程的瓶颈节点。苹果研究人员此前发表的论文\"LLM in a Flash\"提供了方法论支撑：通过将大语言模型参数存储于设备闪存、按需调取至DRAM的方式，可在DRAM容量受限的设备上运行超出其容量上限的模型，并在CPU和GPU上分别实现比朴素加载方式快4至5倍和20至25倍的推理速度。两条路径：数据中心与端侧同步演进AMD的收购聚焦数据中心场景。通过将MEXT技术整合至AMD数据中心产品组合，AMD寻求帮助企业客户在AI工作负载部署中提升资源利用效率并压缩成本。摩根士丹利Shawn Kim团队认为，尽管内存短缺持续，AMD在云端市场竞争格局上仍具结构性优势——\"代理式AI驱动的CPU需求在结构上有利于AMD在云端市场份额的扩张。\"花旗对AMD的乐观预判则更多基于其GPU销售与英伟达的正面竞争态势。苹果的路径则落子端侧。\"LLM in a Flash\"方案将模型推理对昂贵云端内存的依赖部分转移至设备本地闪存，在降低云端运算成本的同时，为端侧AI应用提供可行的内存架构支撑。据Citrini Research，两大路径共同指向同一结论：AI推理的内存层级正在重构，低频KV缓存、模型权重及端侧数据，将逐步从高价的HBM/DRAM下沉至NAND Flash/SSD层，形成多层次存储架构。这一架构转变正沿产业链形成多层次的传导效应。据Citrini Research梳理，最直接的受益层是NAND原厂，高容量NAND、企业级SSD及QLC NAND为最纯粹的方向，包括SanDisk、西部数据、美光及铠侠。SSD控制器层被认为持续性最强——让闪存真正接近内存体验的核心在于控制器、固件与NVMe架构优化，涉及Silicon Motion、Marvell等。CXL/PCIe高速互联层亦受益。","news_type":1,"symbols_score_info":{"AAPD":0.6,"AMUU":0.6,"AMDS":0.6,"AMDD":0.6,"AMDL":0.6,"DAMD":0.6,"AMD":1.96,"AMDW":0.6,"APLY":0.6,"AAPB":0.6,"AAPU":0.6,"AAPW":0.6,"AAPL":1.89,"AMDU":0.6,"AMDY":0.6,"AAPX":0.6,"AMYY":0.6,"AMDG":0.6,"AAPY":0.6}},"isVote":1,"tweetType":1,"viewCount":33,"commentLimit":10,"likeStatus":false,"favoriteStatus":false,"reportStatus":false,"symbols":[],"verified":2,"subType":0,"readableState":1,"langContent":"CN","currentLanguage":"CN","warmUpFlag":false,"orderFlag":false,"shareable":true,"causeOfNotShareable":"","featuresForAnalytics":[],"commentAndTweetFlag":false,"andRepostAutoSelectedFlag":false,"upFlag":false,"length":14,"optionInvolvedFlag":false,"xxTargetLangEnum":"ZH_CN"},"commentList":[],"hasMoreComment":false,"orderType":2}