热点丨CES2026双雄算力升级，英伟达 Rubin 对决 AMD Helios

Ofweek维科网01-12

前言：CES2026的核心叙事早已超越单一产品的功能展示，而是围绕两大主题展开：物理AI让智能走出屏幕，个人AI让技术融入生活。英伟达CEO黄仁勋带着Rubin平台与物理AI生态强势领跑，AMD董事长苏姿丰则以Helios机架和全栈战略强势突围。图片来源|网络英伟达：从Blackwell到Rubin的跃迁在黄仁勋标志性的皮衣加持下，英伟达的CES2026发布会堪称一场[全栈AI秀]。从Rubin...

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duo computing power upgrade, Nvidia Rubin vs. AMD Helios","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"NVDS":0.6,"NVDD":0.6,"2NVD.UK":0.6,"AMD":1.96,"3NVD.UK":0.6,"NVDS.UK":0.6,"NVD3.UK":0.6,"NVDY":0.6,"NVDU":0.6,"SNVD.UK":0.6,"NVDX":0.6,"NVD":0.6,"NVDA":1.98,"NVIW.SI":0.6,"NVD2.UK":0.6},"content_text":"前言：CES2026的核心叙事早已超越单一产品的功能展示，而是围绕两大主题展开：物理AI让智能走出屏幕，个人AI让技术融入生活。英伟达CEO黄仁勋带着Rubin平台与物理AI生态强势领跑，AMD董事长苏姿丰则以Helios机架和全栈战略强势突围。图片来源|网 络英伟达：从Blackwell到Rubin的跃迁在黄仁勋标志性的皮衣加持下，英伟达的CES2026发布会堪称一场[全栈AI秀]。从Rubin超级计算平台到Alpamayo自动驾驶模型，从Cosmos物理AI框架到GR00T机器人生态，英伟达不仅定义了物理AI的技术标准，更通过开源策略构建起难以逾越的生态壁垒。作为本次发布会的重磅核心，Rubin平台的亮相标志着AI算力进入[机架级协同]时代。这套以天文学家Vera Rubin命名的超级计算系统，由六款芯片深度协同设计。VeraCPU、RubinGPU、NVLink 6交换机、ConnectX-9网卡、BlueField-4 DPU和Spectrum-6以太网交换机，通过极致协同实现性能的跨越式提升。Rubin GPU的性能参数堪称震撼，NVFP4推理性能达50 PFLOPS（是Blackwell的5倍），训练性能35 PFLOPS（3.5倍），HBM4内存带宽22 TB/s（2.8倍），单GPU NVLink互连带宽翻倍至3.6 TB/s。这些提升让单个GPU能处理更多推理任务与更长上下文，从根本上降低对GPU数量的依赖。而Vera CPU采用88个自研Olympus核心，配备1.5 TB系统内存，通过1.8 TB/s的NVLink-C2C技术实现CPU与GPU的一致性内存访问，成为AI推理的高效协调者。针对AI推理的核心瓶颈，上下文存储，英伟达推出推理上下文内存存储平台。该平台由BlueField-4驱动，在GPU内存与传统存储间构建[第三层记忆层]，让上下文数据能在多个节点、多个AI智能体间快速共享，特定场景下每秒处理token数提升最高达5倍。配合NVLink 6的3.6 TB/s带宽和网络内计算能力，72个GPU能像一个超级GPU协同工作，彻底解决了推理成本高、上下文难以持续的痛点。新一代DGX SuperPOD则将Rubin的能力扩展至数据中心级别，由8个Vera Rubin NVL72机架组成，576个GPU通过NVLink 6和Spectrum-X以太网实现无缝协同。搭配推理上下文内存存储平台和Mission Control管理软件，成为[开箱即用]的大规模AI基础设施。而Spectrum-6交换机引入的共封装光学（CPO）技术，将光模块直接封装在交换芯片旁，显著降低功耗与延迟，为超大规模部署提供支撑。本次CES上，英伟达扩展Open Model Universe开源模型生态，覆盖生物医学AI、AI物理模拟、Agentic AI、物理AI、机器人和自动驾驶六大领域。Alpamayo作为全球首个面向自动驾驶的开源推理VLA模型，其采用100亿参数架构，通过视频输入生成行驶轨迹及推理痕迹，能解释决策背后的逻辑。在机器人领域发布Isaac GR00T N1.6开源VLA模型，专为人形机器人设计，可实现全身控制并具备推理能力。波士顿动力、LG电子、智元机器人等企业已基于Jetson Thor硬件平台集成相关模型，推动机器人技术规模化落地。通过开放生态将200万机器人开发者与Hugging Face的1300万AI构建者连接起来，形成全球协作的创新网络。AMD：开放架构的yotta-scale蓝图在黄仁勋演讲结束仅4小时后，苏姿丰带着AMD的[AI全家桶]登台，以[AI Everywhere, for Everyone]为核心，展示了从数据中心到终端设备的全栈布局。与英伟达聚焦物理AI不同，AMD选择了[系统工程+生态协同]的差异化路线，试图以Helios机架、Ryzen AI平台和开放软件栈，从英伟达手中抢夺市场份额。AMD的反击从最顶层的算力基础设施开始，专为Yotta级计算时代设计的Helios机架，堪称[算力核弹]。基于OCP开放式机架标准，重量接近7000磅（超过两辆小型轿车），搭载72颗MI455X GPU和18颗Venice CPU，单机架可提供高达2.9 ExaFLOPS的FP8算力。MI455X GPU是Helios的核心动力，采用2nm和3nm工艺，集成3200亿晶体管（比MI355X多70%），配备432GB HBM4显存，性能较MI355X提升10倍。其核心优势在于通过大容量HBM内存，实现显存、带宽和算力的三维扩展，打破AI推理的[内存墙]限制。更强的扩展能力可容纳巨型模型，更高带宽提升token输出速度，极高的QPS则能同时响应更多用户请求。Venice CPU则为系统提供坚实支撑，采用2nm工艺和Zen 6架构，核心数高达256核。通过Pensando的800 Gb/秒以太网芯片[Vulcano]和[Salina]，实现与MI455X的高速协同，内存和GPU带宽较上一代翻倍，确保数据传输无瓶颈。每个液冷托架包含4颗MI455X GPU、1颗Venice CPU及网络芯片，数万个机架可扩展至整个数据中心，形成规模化算力集群。苏姿丰公布的GPU路线图显示，2027年将推出基于2nm工艺、搭载HBM4e内存的MI500系列，性能预计较MI455X再提升30倍，四年内实现AI性能1000倍的跨越。而新增的MI440X GPU专为8路UBB机箱设计，可直接替代MI300/350系列，满足企业级部署的现实需求，形成[高端突破+中端普及]的产品矩阵。在数据中心之外，AMD将重点放在了AI PC的规模化普及上。全新发布的Ryzen AI 400系列处理器，采用Zen 5 CPU架构与RDNA 3.5 GPU，集成最高60 TOPS的NPU算力，全面支持Windows Copilot+生态。Ryzen AI Max平台则针对高性能开发者和创作者，最高配备16核/32线程Zen 5架构CPU、40个RDNA 3.5计算单元GPU，NPU算力达50 TOPS，配备128GB统一内存。而Ryzen AI Halo更是引发关注，作为[世界上最小的AI开发系统]，其基于Ryzen AI Max打造，预装GPT-OSS、FLUX.2等主流开源模型，开发者无需复杂配置即可在本地运行2000亿参数大模型，极大降低了本地AI开发门槛。AMD的端侧战略核心在于[算力下沉]，苏姿丰认为，AI PC并非云端AI的替代品，而是下一代个人计算的基础设施。AI从技术竞赛到生态博弈CES2026上的双雄对决，本质上是AI行业发展阶段的缩影。随着技术从爆发期进入工程化深水区，竞争已从单一芯片性能比拼，转向[技术架构+生态协同]的综合实力较量，行业正在发生三大深刻变革。无论是英伟达的Rubin平台还是AMD的Helios机架，都标志着算力竞争已从单卡层面升级至系统级。两家企业均通过CPU、GPU、NPU、网络芯片的协同设计，解决了大规模AI部署中的带宽、延迟、存储等瓶颈。这种[全栈优化]的思路，让算力提升不再依赖单一组件的性能跃迁，而是通过系统架构创新实现整体效率的突破。更重要的是，两家企业都将目光投向了Yotta级计算时代。苏姿丰预判，未来五年全球需将AI计算能力提升至10 Yottaflops（是2022年的10000倍）。黄仁勋则通过Rubin平台的机密计算、温水冷却、电力平滑等技术，为超大规模部署提供了可行性。这种[面向未来的系统设计]，将决定企业在下一代AI基础设施市场的话语权。开源成为生态扩张的关键英伟达与AMD都意识到，AI的普及离不开开源生态的推动。英伟达开放Alpamayo、GR00T等核心模型，提供从数据到工具的全栈资源；AMD则通过ROCm软件栈的持续升级，提升与主流大模型框架的兼容性，吸引开发者参与。开源不仅降低了AI开发门槛，更让企业的技术标准成为行业共识，形成[技术开源—生态壮大—商业反哺]的良性循环。开源生态的竞争也体现了两家企业的战略差异，英伟达聚焦物理AI核心场景，通过自动驾驶、机器人等领域的开源模型，巩固其在垂直领域的优势。AMD则更注重全场景覆盖，从数据中心的Helios到端侧的Ryzen AI，通过开源工具链打通不同场景的开发链路，吸引更广泛的开发者群体。随着AI模型从千亿参数跃升至万亿参数，全球计算容量预计从当前的100 zettaflops激增至10+yottaflops，这场对决的背后，是对未来AI工厂主导权的争夺。结尾硬件竞争会随着软件支持、开发者生态和行业适配逐渐进入[二线]，而软件生态能否形成规模效应将成为最终赢家决定性因素。未来AI架构不再是简单堆叠芯片，而是需要CPU、GPU、DPU、网络与存储在系统层实现协同优化。AMD的开放性策略和英伟达的闭环平台或共同推动一套新的AI基础设施标准诞生，类似当年x86与ARM争夺移动设备主导权的情形。随着Rubin的量产部署与Helios的生态落地，未来全球AI计算图谱将被重新绘制。部分资料参考：腾讯科技：《MI455X芯片+72卡机架，2027年冲2nm，苏姿丰：4年算力涨1000倍》，甲子光年：《直击CES：黄仁勋演讲后4个小时，苏姿丰带着她的[复仇者联盟]上台了》，腾讯科技：《黄仁勋CES2026最新演讲：三个关键话题，一台[芯片怪兽]》，DoNews：《CES 2026，AMD居然[如此激进]？》，极客公园：《黄仁勋：物理AI 的 ChatGPT 时刻，快到了》原文标题 : 热点丨CES2026双雄算力升级，英伟达 Rubin 对决 AMD 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