Core Insights - NVIDIA is fully committed to AI, marking its first appearance at CES in five years without showcasing gaming graphics cards [2] - The next-generation Rubin architecture GPU demonstrates significant performance improvements, with inference and training capabilities being 5 times and 3.5 times that of the Blackwell GB200, respectively [4][17] Group 1: New Product Launches - NVIDIA introduced five new product lines, emphasizing the importance of open-source training frameworks and multimodal datasets, including 100 trillion language training tokens and 100TB of vehicle sensor data [5][6] - The Vera Rubin NVL72 architecture was officially launched, featuring six core components designed to enhance AI data center capabilities [14][15] - The Rubin GPU achieves 50 PFLOPS in inference performance and 35 PFLOPS in training performance under NVFP4 data types, significantly surpassing previous models [17] Group 2: Technological Advancements - The NVLink 6 technology enhances inter-GPU bandwidth to 3.6 TB/s, with a total bandwidth of 260 TB/s across the entire architecture [21][20] - The Vera CPU integrates 88 custom Arm cores, allowing for high thread concurrency and improved memory bandwidth [22] - NVIDIA's new BlueField-4 DPU introduces a memory layer aimed at optimizing key-value cache operations, addressing performance bottlenecks in AI infrastructure [32][34] Group 3: AI Model Developments - The Alpamayo model series was launched for autonomous driving, featuring a 10 billion parameter open-source model capable of interpreting environmental data for decision-making [39][41] - The Nemotron model family expands into voice, retrieval-augmented generation (RAG), and safety applications, enhancing AI capabilities in various domains [49][51] - The Cosmos platform for robotics has been upgraded, providing new models for generating synthetic data that adheres to physical laws [54][58] Group 4: Healthcare and Life Sciences - NVIDIA Clara targets the healthcare sector, aiming to reduce costs and accelerate the implementation of treatment solutions [62] - The company offers a dataset of 455,000 synthetic protein structures to support research in drug discovery and personalized medicine [66][69]

来源丨 量子位（ID：QbitAI） 作者丨西风 闻乐 刚刚，英伟达CEO黄仁勋穿着鳄鱼皮夹克，在全球最大消费电子展 CES 2026 上发布AI新品。 这是五年来，英伟达首次来到CES却没有发游戏显卡，态度很明确：全力 搞AI。 全力搞出来的结果也让围观群众直呼：竞争对手如何追上英伟达？ 下一代Rubin架构GPU 推 理、训练性能分 别是 Blackwell GB 200的5倍和3.5倍 （NVFP4数据格 式）。 除此之外，老黄还带来了五大领域的全新发布，包括： 面向Agentic AI的 NVIDIA Nemotron 模型家族 面向物理AI的 NVIDIA Cosmos 平台 面向自动驾驶开发的全新 NVIDIA Alpamayo 模型家族 同时，英伟达宣布持续向社区 开 源训 练框架 以 及 多模 态数据 集 。其中数据集包括10万亿语言 训练token、50万条机器人轨迹数据、45.5万个蛋白质结构、100TB车辆传感器数据。 这次的核心主题，直指 物理AI 。 用网友的话来说： 这是英伟达将护城河从芯片层进一步拓展到全栈平台层（模型+数据+工具）的体现，通过这种方式可 以持续拉动更多GPU与基 ...