全球科技盛会2026年国际消费电子展（CES 2026）于当地时间1月6日开幕，芯片巨头掌门人——英伟 达CEO黄仁勋、英特尔CEO陈立武、AMD CEO苏姿丰、高通CEO安蒙相继登场。值得注意的是，这四 家芯片巨头既有合作也有竞争，却鲜少出现在同一舞台。 他们正指向AI时代一个更为宏大的发展目标：数百倍的算力增长需求和背后从云到端全面的AI应用拓 展空间。 而中国厂商正在CES上扮演越来越重要的角色。无论是AI眼镜、各形态机器人，中国厂商的积极参展， 也在海外引发高度关注，甚至让现场展台"水泄不通"。 例如，宇树科技把"传统艺能"拳击赛带到现场，21世纪经济报道记者发现，观赛人员围了里三层外三 层，纷纷高举手机拍摄G1机器人灵活的动作表现。 一众中国原生AI硬件厂商备受关注的背后，是中国企业全球角色的进阶：凭借供应链与研发能力的长 期沉淀，中国已升级为全球科技创新的关键力量。 AI大模型加速发展背后，是底层算力基础设施的快速演进支撑。在CES现场，芯片巨头掌门人们都强调 了算力的飞速增长态势，以及由此引发的应用新机会。 英伟达创始人兼CEO黄仁勋指出，物理AI的"ChatGPT时刻"已然到来。机器开始具备理 ...

记者丨孔海丽 骆轶琪 编辑丨包芳鸣 图片来源：孔海丽 摄 全球科技盛会2026年国际消费电子展（CES 2026）于当地时间1月6日开幕，芯片巨头掌门人 —— 英伟达CEO黄仁勋、英特尔CEO陈立武、AMD CEO苏姿丰、高通CEO安蒙相继登场。 值得注意的是， 这四家芯片巨头既有合作也有竞争，却鲜少出现在同一舞台。 他们正指向AI时代一个更为宏大的发展目标：数百倍的算力增长需求和背后从云到端全面的 AI应用拓展空间。 而中国厂商正在CES上扮演越来越重要的角色。无论是AI眼镜、各形态机器人，中国厂商的积 极参展，也在海外引发高度关注，甚至让现场展台"水泄不通"。 例如，宇树科技把"传统艺能"拳击赛带到现场，21世纪经济报道记者发现，观赛人员围了里三 层外三层，纷纷高举手机拍摄G1机器人灵活的动作表现。 一众中国原生AI硬件厂商备受关注的背后，是中国企业全球角色的进阶：凭借供应链与研发能 力的长期沉淀， 中国已升级为全球科技创新的关键力量。 AI大模型加速发展背后，是底层算力基础设施的快速演进支撑。在CES现场，芯片巨头掌门人 们都强调了算力的飞速增长态势，以及由此引发的应用新机会。 英伟达创始人兼CEO黄仁 ...

Core Insights - The competition among major chip manufacturers is intensifying around the foundational computing power for AI, with native AI hardware accelerating its large-scale implementation, transitioning from laboratory settings to consumer and industrial applications [1][2] - Chinese manufacturers are playing an increasingly significant role at global tech events, showcasing their advancements in AI hardware and capabilities, which are supported by their supply chain and R&D strengths [2][11] Group 1: Computing Power and AI Development - The rapid evolution of underlying computing infrastructure is crucial for the accelerated development of AI large models, with chip leaders emphasizing the exponential growth of computing power and the new application opportunities it creates [3][4] - NVIDIA's CEO highlighted the arrival of the "ChatGPT moment" for physical AI, indicating that machines are beginning to understand and act in the real world, with autonomous taxis being one of the first applications to benefit [3] - AMD's CEO noted that the floating-point computing power for training AI models is growing fourfold annually, with inference token consumption increasing by 100 times over the past two years, necessitating new product offerings to meet Yotta-scale infrastructure demands [4] Group 2: Emerging AI Applications - The potential of edge AI is significant, with advancements in smart wearable devices being highlighted as a new category of mobile terminals that will coexist with smartphones [5][6] - Qualcomm's CEO projected that the market for personal AI devices could reach 100 million units in the coming years, emphasizing the importance of edge data for providing highly relevant user services [6] Group 3: Robotics and Physical AI - The maturity of physical AI was showcased at CES, with Chinese manufacturers presenting advanced robots that demonstrate improved capabilities compared to previous years [7][8] - The introduction of humanoid robots and their increasing commercial viability was noted, with companies achieving substantial progress in motion control and operational precision [9][10] - The integration of hardware, sensors, and environmental perception into scalable systems is seen as essential for advancing physical AI applications across various industries [10] Group 4: Chinese Manufacturers' Competitive Edge - Chinese companies are leveraging their supply chain efficiencies and R&D capabilities to drive rapid iterations and cost optimization in the robotics sector, significantly outpacing European competitors in product development cycles [11][12] - The shift from simple manufacturing to innovative solutions reflects a broader transformation in the perception of "Made in China" to "Created in China," highlighting the technological advancements and better solutions being offered [12]

在2026年国际消费电子展期间，高通公司总裁兼首席执行官克里斯蒂亚诺·安蒙在联想创新科技大会上发表演讲。他表示，智能可穿戴设备为代表的个人AI 终端市场潜力巨大，未来市场规模有望达到数十亿台级别。 在技术层面，安蒙称，尽管这类设备体积小巧，但仍需出色的能效、强劲的算力、稳定的连接和本地运行AI模型的能力。他表示，高通的骁龙芯片已具备 在小型可穿戴设备上运行数十亿参数模型的能力，并在连接技术方面实现了创新，例如在蓝牙功耗级别下运行Wi-Fi，以保持设备与智能体的持续连接。 市场有风险，投资需谨慎。本文为AI基于第三方数据生成，仅供参考，不构成个人投资建议。 来源：市场资讯 安蒙指出，下一代个人AI设备将依托端侧AI、情境感知能力和用户数据，实现对用户环境与意图的实时理解，融合物理世界和数字世界。他认为，这类设 备将成为用户真正的个人AI伙伴，在获得授权的前提下获取相关数据，并做出实时响应。 根据高通的预计，未来几年内，这类智能可穿戴设备的出货量就能达到千万至一亿台。安蒙表示，市场规模达到数十亿台的预测并非不切实际。他强调，这 类设备是一种全新的移动终端品类，将与手机并存，其形态将涵盖智能眼镜、首饰、吊坠、戒指、 ...

Core Viewpoint - The evolution of AI applications can be categorized into four stages: Perception AI, Generative AI, Agent AI, and Physical AI [9]. Group 1: Stages of AI Evolution - The first stage, Perception AI, includes traditional technologies such as natural language processing, speech noise reduction, and image recognition, which have been commercialized in many terminal devices for years [13][14]. - The second stage, Generative AI, emerged with the rise of ChatGPT, focusing on pre-training with large datasets and completing specific tasks under human supervision, including text-to-image generation and chatbots [14][19]. - The third stage, Agent AI, allows for autonomous actions, predictions, intent understanding, and task orchestration with minimal human intervention [18][19]. - The fourth stage, Physical AI, is still in the research phase, where AI can understand the physical world and respond according to real physical laws [21][22]. Group 2: Current Industry Trends - The industry is currently transitioning from Generative AI to Agent AI, with a focus on enhancing terminal capabilities from single text modalities to multi-modal interactions [4][19]. - The deployment of large models on terminal devices faces challenges such as memory limitations, bandwidth constraints, and power consumption [6][30][34]. Group 3: Advantages and Challenges of Edge AI - The primary advantage of running large models on terminal devices is personalization, as data generation occurs close to the source, enhancing privacy and security [31]. - Edge AI also offers the benefits of being free and not requiring internet connectivity [32]. - Challenges include memory limitations that restrict model size, bandwidth limitations affecting inference speed, and the need for efficient power management in high-integration devices [34][35][36]. Group 4: Technological Innovations - Qualcomm has developed several technological innovations to address these challenges, including quantization and compression techniques to reduce memory usage, parallel decoding to enhance token generation speed, and advanced NPU architectures for improved performance [37][39][40]. - The parallel decoding technique allows for the generation of multiple tokens simultaneously, improving efficiency and user experience [41][42]. Group 5: Future of AI Experience - The future AI experience is expected to evolve towards a hybrid AI model, where efficient models run on the edge provide personalized services, while larger models in the cloud offer more powerful capabilities [55][57]. - Qualcomm aims to ensure seamless collaboration between edge and cloud environments through low-latency, high-speed, and secure connectivity [58].

Core Insights - Qualcomm is excited about entering the data center market, viewing it as a "new chapter" in its diversification strategy, with a focus on energy efficiency as its core competitive advantage [1][2][3] - The company is developing a highly competitive energy-efficient CPU for AI clusters and a new architecture specifically designed for AI inference, with the AI 200 and AI 250 chips and accelerator card solutions being key developments [1][2][3] - Qualcomm has engaged in discussions with a "hyperscale" customer and is satisfied with the outcomes, with more details to be shared in future data center roadmap updates [1][3] Data Center Strategy - The company aims to achieve the highest computational density with the lowest cost and energy consumption, differentiating its approach from traditional GPU and HBM memory combinations [8] - Qualcomm anticipates significant revenue growth in the data center business starting from fiscal year 2027, accelerated by partnerships and advancements in AI accelerators [4][12] - The company is receiving widespread market interest due to the current limitations in power consumption and computational density in data centers [4] Customer Relationships - Qualcomm maintains a strong relationship with its major Android customer, Samsung, with a target market share of 75%, despite fluctuations in share [3][5] - The company expects to see continued growth in its mobile business driven by high-end Android devices, with a projected revenue increase of approximately 11%-13% quarter-over-quarter [6][10] Financial Performance - Qualcomm's QCT division reported a 5% year-over-year revenue growth, although profit margins declined by over 100 basis points due to increased investments in the data center sector [12] - The company is focusing on shifting operational expenditures from mature businesses to high-growth areas, impacting current profit margins [12] Market Trends - The high-end Android smartphone market is expanding, contributing to healthy growth for Qualcomm's Snapdragon platform, with a notable increase in average selling prices (ASP) driven by consumer demand for more powerful devices [9][10] - The company observes a long-term trend of consumers opting for higher-end devices, which is expected to continue driving revenue growth [9]

Core Viewpoint - Qualcomm's stock price drop of 4% post-earnings release is unjustified as analysts find no fundamental factors supporting such a reaction [1][25][38] Financial Performance - Qualcomm reported revenues of $9.82 billion for Q4FY25, a 13% year-over-year increase, with mobile device revenue at $6.96 billion (up 14%), automotive revenue at $1.05 billion (up 17%), and IoT revenue at $1.81 billion (up 7%) [8][9] - The company’s non-GAAP earnings per share (EPS) for Q4FY25 was $3.00, a 12% increase from $2.69 in Q4FY24 [9] - The QCT segment, which drives over 80% of revenue, showed strong performance with a 13% revenue increase [5][9] Market Perception - The market has mischaracterized Qualcomm as merely another "AI stock," leading to a perception that its valuation needs to revert to a more reasonable level [2] - Qualcomm's current P/E ratio is around 16-17, which is considered reasonable compared to much higher valuations in the tech sector [2][30] Growth Drivers - Qualcomm's non-Apple business is expected to grow at a compound annual growth rate (CAGR) of 15% over the next five years, with the last two years showing a CAGR of 17-18% [11] - The automotive and IoT segments are also projected to grow significantly, with automotive expected to grow at a CAGR of 27% over the next year [13] Tax and Cash Flow - The recent stock price decline was influenced by a $5.7 billion tax expense, which is a non-cash accounting adjustment related to new U.S. tax laws, not affecting actual cash flow [18][25] - Qualcomm's tax rate is expected to stabilize between 13-14%, with actual cash tax payments anticipated to be lower than expected [18] Competitive Position - Qualcomm is focusing on edge-to-cloud AI solutions, differentiating itself from competitors like NVIDIA by emphasizing cost-effective inference rather than model training [20] - The company has partnered with HUMAIN in Saudi Arabia to launch a hybrid edge-cloud AI inference service, indicating its commitment to AI development [20] Valuation and Future Outlook - Analysts believe Qualcomm's current valuation is significantly discounted compared to industry peers, with a target P/E ratio of 18 being more appropriate [30][36] - The company’s ability to maintain a stable profit margin in the QCT segment and continued growth in mobile devices and automotive sectors are critical for achieving this valuation [37]

Core Insights - Qualcomm has participated in the China International Import Expo for eight consecutive years, showcasing its commitment to global trade cooperation [1] - The company is recognized as a core technology supplier in the connectivity and computing sectors, with over 3 billion devices powered by Snapdragon chips globally [1] - Qualcomm's business extends beyond mobile phones, with significant investments in 5G, IoT, and automotive electronics, contributing to the global digital economy [1] Qualcomm's Strategic Focus - Qualcomm emphasizes the importance of the Import Expo as a platform for collaboration and innovation with Chinese partners, expanding its product offerings from smartphones to PCs, smart connected vehicles, and IoT [2] - The company has been a key player in China's telecommunications evolution, from 2G to 5G, and aims to ensure Chinese brands are among the first to launch 5G products globally [3] Emerging Technologies and Market Potential - Qualcomm identifies robotics and smart wearable devices, including AR, VR, and AI glasses, as two sectors that could rival or surpass the smartphone market in the future [3] - The company has launched the "Qualcomm Leap" brand to focus on industrial IoT and connectivity solutions, showcasing various IoT applications at the Import Expo [4] AI and XR Integration - The integration of AI and XR technologies is expected to revolutionize user experiences, with China leading in the development of innovative terminal products [4] - Qualcomm's AI initiatives are projected to significantly impact various sectors, with McKinsey estimating AI could contribute an additional $13 trillion to global GDP by 2030 [5][6] Automotive Industry Transformation - The automotive sector is becoming a key area for innovation, with Qualcomm's Snapdragon Digital Chassis supporting over 210 vehicle models from various Chinese brands [7] - The company aims to collaborate with China's automotive industry to accelerate the adoption of advanced technologies and drive deeper smart transformation [7] Future Outlook on 6G - Qualcomm is preparing for the transition from 5G to 6G, emphasizing the integration of AI in future communication technologies [8] - The company envisions 6G as a collaborative innovation platform that will enhance AI applications and connectivity, with commercial terminals expected as early as 2028 [9]

Core Insights - Qualcomm has participated in the China International Import Expo for eight consecutive years, showcasing its commitment to global trade cooperation and innovation in various technology sectors [1][2][5] - The company emphasizes its extensive involvement in mobile technology, particularly through its Snapdragon chips, which have been integrated into over 3 billion devices globally [1] - Qualcomm is expanding its focus beyond smartphones to include sectors such as 5G, IoT, automotive electronics, and AI, highlighting its role in driving the global digital economy [1][8] Qualcomm's Participation in the Expo - The expo serves as a platform for Qualcomm to demonstrate its collaboration with Chinese partners and showcase innovations across multiple fields, including smartphones, automotive, IoT, and edge AI [1][2] - The company has seen a diversification of its product offerings at the expo, moving from smartphones to include PCs, smart connected vehicles, and XR technologies [2] Technological Advancements and Market Trends - Qualcomm has been a key player in the evolution of mobile communication technologies, from CDMA to 5G, and is now preparing for the transition to 6G [5][15] - The company anticipates significant growth in the robotics and smart wearable device markets, which may rival or surpass the smartphone market in the future [7][8] - AI integration is expected to redefine product design and user interaction across various sectors, with Qualcomm positioning itself at the intersection of connectivity, computing, and AI [9][10] AI and IoT Developments - The company is actively developing AI solutions for a wide range of devices, including smartphones, PCs, and IoT terminals, to enhance user experiences and create new business models [10][11] - Qualcomm's new brand "Qualcomm Leap" focuses on industrial IoT and cellular infrastructure, complementing its consumer-oriented Snapdragon brand [8] Automotive Sector Innovations - The automotive industry is emerging as a significant area for innovation, with Qualcomm's Snapdragon Digital Chassis supporting over 210 vehicle models from various Chinese brands [12][13] - The company aims to leverage China's robust automotive ecosystem to accelerate the adoption of advanced technologies in smart vehicles [13] Future Outlook on 6G - Qualcomm is preparing for the 6G era, emphasizing the integration of AI and communication technologies as a key direction for future development [15][16] - The company envisions 6G as a collaborative innovation platform that will enhance AI applications and connectivity, with commercial deployment expected as early as 2028 [15][16]

Core Insights - Qualcomm has announced its entry into the AI data center chip market with the AI200 and AI250, directly competing with Nvidia [1][4] - The move is driven by the rising costs of GPUs and the need for more efficient energy use in AI applications [2][3] - Qualcomm aims to leverage its expertise in energy efficiency from mobile chips to address the challenges of power consumption in AI [5][6] Group 1: Market Dynamics - The GPU market is currently dominated by Nvidia, with prices for high-end models like the H100 reaching $30,000, leading to a bottleneck in AI access [2][12] - The global data center energy consumption is projected to exceed 460 TWh in 2024, with 20% attributed to AI training and inference, highlighting the urgent need for more efficient solutions [2][7] - Qualcomm's strategy reflects a shift in focus from traditional mobile markets to the burgeoning AI sector, as its mobile chip revenue has declined over 20% in 2023 [5][6] Group 2: Strategic Partnerships - Qualcomm's first customer for its AI chips is Saudi Arabia's HumAiN, which is part of the Vision 2030 initiative aimed at building an AI city in the desert [6][7] - The deal involves a significant order of 200 MW, equivalent to the annual power consumption of a medium-sized city, indicating a major investment in AI infrastructure [7][8] - This partnership signifies a shift in Saudi Arabia's energy strategy from oil exportation to investing in AI capabilities, marking a geographical and strategic transformation [8][9] Group 3: Competitive Landscape - Nvidia currently holds a dominant market share in the GPU sector, with projections indicating its data center GPU market size could reach $120 billion by 2025 [12][13] - The high profit margins of Nvidia's data center business, at 78%, position it as a critical player in the AI ecosystem, creating a dependency among various stakeholders [13][14] - As competition intensifies, other tech giants like Google, Amazon, and Microsoft are developing their own AI chips to reduce reliance on Nvidia, indicating a potential shift in the power dynamics of the industry [26][27] Group 4: Future Trends - The industry is witnessing a transition from centralized AI processing to decentralized models, with a focus on energy efficiency and cost reduction [20][21] - Qualcomm's AI200 and AI250 chips are designed to enhance performance per watt, aiming to become the "energy plants" of the AI world [22][23] - The evolution of AI technology is expected to democratize access, moving from a "noble configuration" to a "public utility," allowing broader participation in AI development [23][24]