东方证券发布研报称，英伟达(NVDA.US)在CES 2026展会上发布面向自动驾驶的开源AI模型平台 Alpamayo，与传统VLA模型不同，作为推理VLA模型的Alpamayo具备逐步解决复杂问题并生成类似于 人类思维过程推理痕迹的能力。随着英伟达自动驾驶生态持续拓展、高级别自动驾驶及Robotaxi渗透率 逐步提升，预计智驾芯片、激光雷达、域控制器、线控制动/转向等高级别自动驾驶相关零部件需求将 迎来快速增长，自动驾驶软硬件供应商将持续迎来发展机遇。 黄仁勋在演讲中展示了英伟达构建的全球L4级自动驾驶与Robotaxi生态系统，其中包括德赛西威 （002920）、禾赛、Momenta、文远知行、小马智行、元戎启行等一系列Robotaxi运营商及自动驾驶软 硬件供应商。随着英伟达自动驾驶生态持续拓展、高级别自动驾驶及Robotaxi渗透率逐步提升，预计智 驾芯片、激光雷达、域控制器、线控制动/转向等高级别自动驾驶相关零部件需求将迎来快速增长，自 动驾驶软硬件供应商将持续迎来发展机遇。 投资建议与投资标的 英伟达发布开源自动驾驶模型Alpamayo，有望推动高级别自动驾驶及Robo-X渗透率提升，预计自动驾 ...

智通财经APP获悉，东方证券发布研报称，英伟达(NVDA.US)在CES 2026展会上发布面向自动驾驶的开 源AI模型平台Alpamayo，与传统VLA模型不同，作为推理VLA模型的Alpamayo具备逐步解决复杂问题 并生成类似于人类思维过程推理痕迹的能力。随着英伟达自动驾驶生态持续拓展、高级别自动驾驶及 Robotaxi渗透率逐步提升，预计智驾芯片、激光雷达、域控制器、线控制动/转向等高级别自动驾驶相关 零部件需求将迎来快速增长，自动驾驶软硬件供应商将持续迎来发展机遇。 东方证券主要观点如下： 英伟达发布自动驾驶开源模型Alpamayo，将有望促进高级别自动驾驶及Robo-X渗透率提升 英伟达CEO黄仁勋在CES 2026发布自动驾驶的开源VLA(视觉-语言-动作)大模型平台Alpamayo，同时配 套发布仿真工具AlpaSim以及包含1700多小时驾驶数据的开放数据集，构建完整的自动驾驶生态平台。 黄仁勋表示，英伟达NVIDIA DRIVE AV智驾系统将率先搭载于奔驰CLA，预计年底在美国上市，2027 年英伟达将测试无人驾驶出租车服务。 与传统VLA模型不同，作为推理VLA模型的Alpamayo具 ...

Group 1: Automotive Industry - Nvidia launched the Alpamayo inference driving model at CES 2026, featuring a 100 billion parameter end-to-end VLA (Vision-Language-Action) model, which enhances the reasoning capabilities for novel scenarios and provides interpretability for driving decisions [5][10] - The introduction of simulation tools like AlpaSim and a 1700-hour physical AI open dataset supports autonomous driving training and testing, aiming to create a comprehensive autonomous driving solution [10][11] - The demand for autonomous driving features is increasing, becoming essential for consumers when choosing vehicles, with expectations for L2++ and L4 Robotaxi technologies to proliferate globally [12][11] Group 2: Electronics Industry - The consumer electronics and components sector showed significant performance improvement in 2025, with the PCB industry leading in growth due to rapid iterations and shipments of AI products [6][15] - Traditional categories like smartphones and PCs maintained stable growth, while AI glasses and AI servers exhibited rapid growth trends [16][19] - Investment strategies for 2026 focus on key players in the Apple, Huawei HarmonyOS, AI glasses, and OpenAI hardware sectors, indicating a new cycle of innovation in consumer electronics [17][20] Group 3: Chemical Industry - Salt Lake Co. reported an expected net profit of 82.9-88.9 billion yuan for 2025, a year-on-year increase of 77.78%-90.65%, driven by the recovery in potassium and lithium prices [22][24] - The company plans to acquire a 51% stake in Minmetals Salt Lake to expand its potassium and lithium resources, with projected net profits for 2025-2027 revised upwards [23][24] - The production of potassium chloride is expected to be approximately 4.9 million tons in 2025, while lithium carbonate production is projected at 46,500 tons, reflecting a strategic focus on resource control and high-quality development [24][22] Group 4: Investment Recommendations - The automotive sector is advised to focus on companies like Desay SV, Huayang Group, and XPeng Motors, which are expected to benefit from advancements in autonomous driving technology [13] - In the electronics sector, companies such as Industrial Fulian, Luxshare Precision, and GoerTek are highlighted as beneficiaries of the AI computing and terminal resonance [20][19] - Salt Lake Co. is recommended for investment due to its strong market position in potassium and lithium resources and the anticipated growth from the acquisition of Minmetals Salt Lake [23][22]

Investment Rating - The industry investment rating is Neutral (maintained) [5] Core Insights - NVIDIA has launched an open-source autonomous driving model, Alpamayo, which is expected to enhance the penetration rates of high-level autonomous driving and Robo-X. This development is anticipated to benefit related vehicle manufacturers, component suppliers, and mobility service providers [3][9] - The Robo-X scale is expected to accelerate, with leading companies like LoBot and Pony.ai achieving or nearing single-vehicle breakeven points for their Robotaxi services. The deployment of Robovans is also increasing, with significant cost reductions in unmanned logistics vehicles [8] - NVIDIA is building a comprehensive autonomous driving ecosystem, which is likely to create growth opportunities for suppliers of autonomous driving hardware and software as demand for advanced components rises [8] Summary by Sections Investment Recommendations and Targets - Recommended stocks in the component sector include: - Jingwei Hirain (688326, Buy) - Bertel (603596, Buy) - Desay SV (002920, Buy) - Huayang Group (002906, Buy) - Coboda (603786, Buy) - Horizon Robotics (09660, Not Rated) - Hesai (02525, Not Rated) - Nexperia (01316, Not Rated) - Recommended stocks in the vehicle and mobility service sector include: - Xpeng Motors (09868, Not Rated) - Seres (601127, Not Rated) - Pony.ai (02026, Not Rated) [3][9]

在新发布的这一模型平台中，Alpamayo可基于视频输入生成行驶轨迹并输出对应推理过程，用于 研究、模型蒸馏及开发辅助工具；AlpaSim则是一套完全开源的端到端辅助驾驶仿真框架，已在GitHub 发布，支持高保真传感器建模和闭环测试；物理AI开放数据集，包含超过1700小时的真实道路驾驶数 据，覆盖不同区域和环境条件，并包含一定比例的复杂和罕见场景。 目前，Alpamayo主要作为自动驾驶的训练模型和开发基础使用。同时，英伟达允许开发者利用其 丰富的相关工具和模型库，包括NVIDIA Cosmos™和NVIDIA Omniverse™平台。开发者能够基于专有 车队数据对模型版本进行优化升级，将其集成至NVIDIA DRIVE AGX Thor™加速计算构建的NVIDIA DRIVE Hyperion™架构中，并在商业部署前通过仿真验证其性能表现。 1月6日，据报道，英伟达在CES 2026举行的吹风会上，面向推理型辅助驾驶与自动驾驶系统研 发，发布Alpamayo系列开源AI自动驾驶模型、仿真工具及数据集。该系列主要用于训练、评估和验证 辅助驾驶及自动驾驶系统在复杂及罕见驾驶场景下的决策能力，还可以利用这一 ...

英伟达在CES 2026展会上推出名为Alpamayo的开源自动驾驶AI模型，CEO黄仁勋称其为"世界上首款能思考、能推理的自动驾驶汽车AI"，直接 挑战特斯拉的FSD系统。 1月6日，电动汽车分析师Sawyer Merritt在X平台发帖称，英伟达宣布将于今年晚些时候在美国道路上推出Alpamayo。马斯克对此回应称："好吧， 这正是特斯拉在做的。他们会发现，达到99%很容易，但要解决分布的长尾问题却非常困难。" 当有网友表示担心Alpamayo成为FSD的首个真正竞争对手，并指出英伟达可以在没有任何车队的情况下达到接近99%的水平，证明大规模车队数 据已不再重要时，马斯克再次回应："我才不会因为这个失眠呢。我真心希望他们能成功。" 英伟达正通过全面的开源策略切入自动驾驶领域，其最新发布的Alpamayo 1模型权重已在Hugging Face平台开放获取，同步推出的还包括端到端 仿真框架AlpaSim以及涵盖1700小时复杂驾驶场景的物理AI开放数据集。 此举标志着英伟达正以"自动驾驶领域的安卓系统"为定位，构建开放生态，与特斯拉完全封闭的FSD系统形成差异化竞争路径。英伟达同时宣 布，该项技术将自今年第 ...

太平洋时间 2026 年 1 月 5 日 ——NVIDIA 发布 NVIDIA Alpamayo 系列开源 AI 模型、仿真工具及数据 集，旨在推动安全可靠的推理型辅助驾驶汽车开发。 智能汽车必须在复杂多变的驾驶条件下安全运行。被称为"长尾"的罕见、复杂场景始终是辅助驾驶系统 需要攻克的最大难题之一。传统辅助驾驶架构将感知与规划分离开来，这在面临突发或异常状况时，往 往会限制其系统扩展性。尽管端到端学习的最新进展已取得显著突破，但要解决这些长尾极端事件，仍 需具备安全推理因果关系能力的模型，特别是在遇到的场景超出模型训练经验的情况下。 Alpamayo 系列引入基于思维链的 VLA 推理模型，为辅助驾驶决策注入类人的思维能力。这些系统能够 逐步推演罕见或全新场景，提升驾驶能力和可解释性，这对构建智能汽车的安全信任体系至关重要，其 核心技术由 NVIDIA Halos 安全系统提供支撑。 NVIDIA 创始人兼首席执行官黄仁勋表示："物理 AI 的 ChatGPT 时刻已然到来，机器开始具备理解真 实世界、推理并付诸行动的能力。无人驾驶出租车将是最早受益的应用之一。Alpamayo 为智能汽车注 入推理能力，使 ...

Core Viewpoint - The article discusses NVIDIA's advancements in the autonomous driving sector, particularly the launch of the open-source VLA model Alpamayo, which aims to enhance the capabilities of self-driving vehicles and compete in the market against local Chinese manufacturers [3][4][9]. Group 1: NVIDIA's Innovations - NVIDIA's CEO Jensen Huang announced at CES 2026 that the future will see 1 billion vehicles achieving high or full automation, with autonomous taxis being one of the first beneficiaries [3]. - The Alpamayo model, featuring a 10 billion parameter architecture, is designed to support Level 4 autonomous driving and is the first open-source AI system capable of reasoning and decision-making for self-driving vehicles [4][5]. - The Alpamayo series includes simulation tools and an open dataset with over 1,700 hours of driving data, providing a comprehensive foundation for developers [4]. Group 2: Competitive Landscape - Despite NVIDIA's advancements, local Chinese companies like Li Auto, Xpeng, NIO, and Huawei have already developed similar models, indicating a competitive landscape where NVIDIA is not the frontrunner [4][5]. - NVIDIA faces immediate challenges in the Level 2 assisted driving market, where it has announced a partnership with Mercedes-Benz to deploy its full-stack assisted driving solution in the 2025 model of the CLA [5][7]. - The collaboration with Mercedes-Benz involves a dual-system approach, combining an end-to-end AI system with a traditional safety-certified system to ensure reliability in complex driving scenarios [7]. Group 3: Market Opportunities and Challenges - NVIDIA's strategy includes targeting overseas markets, where the penetration of assisted driving solutions is still low compared to China, presenting significant opportunities for growth [9]. - The company is working to improve its autonomous driving solutions, with plans for quarterly software updates to enhance user experience following previous setbacks in the Chinese market [8][9]. - Despite being behind local competitors in China, NVIDIA aims to regain its influence in the autonomous driving sector through strategic partnerships and technological advancements [9].

Core Viewpoint - NVIDIA has launched Alpamayo, a series of open-source inference models aimed at guiding autonomous vehicles through complex driving situations, with Alpamayo 1 being the centerpiece featuring 10 billion parameters [1] Group 1: Product Launch - The core of the launch is Alpamayo 1, a logical reasoning system designed to mimic human driving behavior [1] - The model works by breaking down unexpected driving situations into smaller problems to find the safest driving path, providing explanations for its reasoning process at each step [1] Group 2: Related Technologies - A sister model named AlpaSim allows developers to conduct closed-loop training for rare driving scenarios encountered in real life [1] - The 2025 Mercedes-Benz CLA will be the first vehicle to feature NVIDIA's complete autonomous driving technology stack, including Alpamayo [1]

Core Viewpoint - Nvidia has announced the open-source release of its first inference VLA (Vision-Language-Action) model, Alpamayo 1, aimed at enhancing autonomous vehicle capabilities to "think" and solve problems in unexpected situations, utilizing a 10 billion parameter architecture [1][3][4]. Group 1: Model and Technology Overview - The Alpamayo model is designed to process complex driving scenarios using human-like reasoning, providing new pathways to address long-tail issues in autonomous driving [1][3]. - The model integrates three foundational pillars: open-source models, simulation frameworks, and datasets, creating a comprehensive open ecosystem for automotive developers and research teams [4]. - The model is now available on the Hugging Face platform and allows developers to adapt it for smaller runtime models or as a foundational tool for autonomous driving development [4][10]. Group 2: Industry Support and Collaboration - Major companies in the mobility sector, including Jaguar Land Rover, Lucid, and Uber, have expressed strong interest in utilizing the Alpamayo model to develop inference-based autonomous driving technology stacks [3][11]. - Nvidia's CEO highlighted the importance of the Alpamayo model in enabling autonomous vehicles to navigate rare scenarios safely and explain their driving decisions, which is crucial for scalable autonomous driving [6][11]. Group 3: Simulation and Data Resources - Alongside the Alpamayo model, Nvidia has released AlpaSim, a fully open-source end-to-end simulation framework for high-fidelity autonomous driving development, available on GitHub [9][10]. - Nvidia provides a large-scale open dataset containing over 1,700 hours of driving data, covering a wide range of geographical locations and conditions, essential for advancing inference architectures [9][10]. Group 4: Broader AI Model Releases - Nvidia has also launched several new open-source models, data, and tools across various industries, including the Nemotron family for agent AI, the Cosmos platform for physical AI, and the Isaac GR00T for robotics [12][14]. - These models include extensive datasets, such as 100 trillion language training tokens and 100TB of vehicle sensor data, aimed at accelerating AI development across sectors [14][15].