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終端人工智慧晶片市場報告：趨勢、預測和競爭分析（至2035年）

Terminal AI Chip Market Report: Trends, Forecast and Competitive Analysis to 2035
出版日期: | 出版商: Lucintel | 英文 150 Pages | 商品交期: 3個工作天內

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面向裝置的AI晶片市場

受行動電話、安防攝影機、汽車電子、智慧家居設備和醫療保健服務等市場機會的推動，全球設備用人工智慧晶片市場前景光明。預計到2035年，全球設備用人工智慧晶片市場規模將達到139億美元，高於2027年的25億美元，2027年至2035年的複合年成長率（CAGR）為24.3%。推動該市場成長的關鍵因素包括邊緣運算需求的不斷成長以及這些晶片在自動駕駛汽車和機器人等領域的日益廣泛的應用。

  • 根據 Lucintel 的預測，由於 ASIC 晶片具有更專業的 AI 功能和更高的能源效率，預計在預測期內其成長率將最高。
  • 按應用領域分類，鑑於智慧型手機設備內人工智慧處理能力的不斷增強，預計行動電話產業在整個預測期內將呈現最高的成長率。
  • 從區域來看，亞太地區預計將在整個預測期內呈現最高的成長率，這主要得益於其龐大的智慧型手機製造地和人工智慧的持續普及。

以設備為導向的AI晶片市場新趨勢

2025年至2027年間，人工智慧晶片在設備上的部署預計將從邊緣實驗階段轉向智慧型手機、汽車、相機、工業設備和企業設備的大規模部署。 Lucintel預測，隨著客戶部署的推理模型更靠近用戶，買家不僅會考慮運算速度（TOPS），還會考慮記憶體消耗、軟體分區、散熱限制、安全性和推理成本。

  • 節能推理：由於散熱、熱管理和電池容量的限制，多功能晶片的普及受到限制，未來幾年，能源效率將成為設備AI晶片市場的主導因素。高通驍龍X2平台於2025年9月發布，旨在滿足筆記型電腦在各種功耗預算下的高效AI推理需求。
  • 異質架構：蘋果的 M 系列、AMD 的 Ryzen AI 300 系列和英特爾酷睿 Ultra 處理器都融合了多種 CPU、GPU 和 NPU 資源。英特爾正在生產搭載 2024 代 CPU 的 PC 晶片，其 NPU 算力最高可達 48 TOPS。未來五年，邊緣運算整合度的提高將顯著降低延遲，並減少工作負載對雲端的依賴。
  • 汽車邊緣智慧：NVIDIA DRIVE Thor 擁有每秒 2,000 兆次浮點運算 (FP8) 的處理能力，使其成為汽車系統中集中式運算的高效平台。 NVIDIA 目前正準備在 2025 年實現 DRIVE Thor 的量產，其他公司也正在為量產搭載 NVIDIA DRIVE Thor 的車輛做準備。
  • 開放軟體生態系統：高通、聯發科和Google採用 ONNX 和 TensorFlow Lite 生態系統，標誌著封閉式工具鏈的時代正在終結。更廣泛的 AI 運算生態系統預計將影響晶片採購，因為開發者將能夠在晶片系列之間遷移模型，而無需進行大量修改。
  • 區域供應鏈多元化：隨著客戶對半導體產能多元化的需求日益成長，台積電在日本和美國的擴張，以及英特爾晶圓代工服務在美國的本土化生產，都體現了區域供應鏈多元化策略。儘管尖端封裝技術仍存在局限性，但《晶片法案》（CHIPS Act）提供的超過500億美元的額外獎勵將推動區域採購。

終端用戶人工智慧晶片市場正進入實際擴張階段。耗電量、軟體可攜性、汽車安全性和供電可靠性與整體效能同等重要。擁有完整開發生態系統的大型供應商將佔據更大的市場佔有率。小規模、更專業的公司也將有機會在這個市場中運作。到2027年，決定出貨量的最大因素將是製造能力和型號最佳化。

終端人工智慧晶片市場的最新趨勢

邊緣人工智慧晶片市場預計將在2025年至2027年間達到高峰。隨著製造商將推理處理從雲端轉移到嵌入式設備，這一趨勢正在持續發展。 Lucintel預測，製造商將採購邊緣人工智慧晶片以提升邊緣處理能力、減少資料傳輸量並降低功耗。此外，製造商還將專注於軟邊緣架構以推動市場普及。

  • 邊緣加速器：隨著英偉達宣布將於 2025 年 3 月推出「Jetson Thor」（FP4 運算速度達 2,070 兆次浮點運算），終端設備系統的效能預期有望提升。此外，緊湊型、易於取得的平台的發展預計也將增加對邊緣加速器的需求。
  • AI PC 的發展：2025 年 1 月，AMD 發布了 Ryzen AI Max+ 395，其 NPU 效能高達 50 TOPS。隨著本地推理能力的提升，筆記型電腦和工作站製造商可能會轉向設計支援本地生成式 AI 的產品，而不是基於雲端的 AI。
  • 進軍汽車領域：今年3月，NVIDIA公佈其2025會計年度汽車設計採用專案儲備金額超過50億美元。隨著汽車軟體日益複雜，每輛車所需的晶片數量將會增加，這將推高設備AI晶片的價格，並有助於NVIDIA與製造商簽訂長期合約。
  • 以記憶體為中心的架構：2025年2月，美光開始出貨12棧HBM3E顯存，單棧容量高達36GB。雖然這種容量趨勢主要面向加速器，但隨著開發者對具有更快記憶體存取速度的本地邊緣晶片的需求不斷成長，它也將影響終端設備晶片。
  • 對國家半導體公司的投資：歐盟委員會已向德國ESMC公司撥款9.2億歐元，用於建造先進半導體工廠。該廠預計將於2027年投產。這座先進半導體製造廠將有助於提升區域供應鏈的韌性，因為先進特種半導體的供不應求將成為人工智慧晶片終端供應商的阻礙因素。

人工智慧晶片的終端用戶市場正從單一加速器的銷售階段轉向整合完整的運算平台。本地推理、記憶體最佳化、軟體棧和供貨可靠性是供應商贏得市場認可的關鍵因素。儘管汽車、工業、成像和消費市場預計將持續採用人工智慧晶片，但由於工作負載模型尚不明確，價格波動在所難免。長期的成功並非取決於名義上的TOPS數據，而是取決於執行的成敗。

目錄

第1章執行摘要

第2章 市場概覽

  • 背景與分類
  • 供應鏈

第3章 市場趨勢與預測分析

  • 產業促進因素與挑戰
  • PESTLE分析
  • 專利分析
  • 法規環境

第4章：全球人工智慧晶片市場（按設備類型分類）

  • 吸引力分析：按類型
  • ASIC
  • FPGA
  • GPU
  • 其他

第5章 全球人工智慧晶片市場（面向設備）：按應用領域分類

  • 吸引力分析：依目的
  • 行動電話
  • 監視器
  • 汽車電子
  • 智慧家庭設備
  • 醫療服務
  • 其他

第6章 區域分析

第7章：北美設備用人工智慧晶片市場

  • 北美設備用人工智慧晶片市場：按類型分類
  • 北美設備用人工智慧晶片市場：按應用領域分類
  • 美國市場對設備用人工智慧晶片的需求
  • 墨西哥市場對設備用人工智慧晶片的需求
  • 加拿大市場對設備用人工智慧晶片的需求

第8章：歐洲終端人工智慧晶片市場

  • 歐洲設備用人工智慧晶片市場：按類型分類
  • 歐洲設備用人工智慧晶片市場：按應用領域分類
  • 德國市場對設備用人工智慧晶片的需求
  • 法國市場對設備用人工智慧晶片的需求日益成長。
  • 西班牙設備用人工智慧晶片市場
  • 義大利市場對設備用人工智慧晶片的需求
  • 英國設備用人工智慧晶片市場

第9章：亞太地區終端人工智慧晶片市場

  • 亞太地區終端人工智慧晶片市場：按類型分類
  • 亞太地區人工智慧晶片市場（按應用領域分類）
  • 日本設備用人工智慧晶片市場
  • 印度設備用人工智慧晶片市場
  • 中國設備用人工智慧晶片市場
  • 韓國設備用人工智慧晶片市場
  • 印尼設備用人工智慧晶片市場

第10章：面向世界其他地區（Royal-of-Work）終端的AI晶片市場

  • 其他地區人工智慧晶片市場：按類型分類
  • 其他地區人工智慧晶片市場：按應用領域分類
  • 中東市場對設備用人工智慧晶片的需求
  • 南美洲設備用人工智慧晶片市場
  • 非洲市場對設備用人工智慧晶片的需求

第11章 競爭分析

  • 產品系列分析
  • 業務整合
  • 波特五力分析
  • 市佔率分析

第12章 機會與策略分析

  • 價值鏈分析
  • 成長機會分析
  • 新趨勢：全球設備用人工智慧晶片市場
  • 戰略分析

第13章：價值鏈中關鍵企業的公司概況

  • Competitive Analysis
  • Intel
  • Qualcomm
  • Advanced Micro Devices
  • Synopsys
  • Huawei
  • Google
  • Amazon

第14章附錄

Terminal AI Chip Market

The future of the global terminal ai chip market looks promising with opportunities in the mobile phone, security camera, automotive electronics, smart home device, and medical service markets. The global terminal ai chip market is expected to reach an estimated $13.9 billion by 2035 from $2.5 billion in 2027 with a CAGR of 24.3% from 2027 to 2035. The major drivers for this market are the rising demand for edge computing and the growing application of this chip in autonomous vehicles and robotics.

  • Lucintel forecasts that, within the type category, asic is expected to witness the highest growth over the forecast period due to more dedicated AI performance and power efficiency.
  • Within this application category, mobile phone is expected to witness the highest growth over the forecast period due to increased the trend of on-device AI processing in smartphones.
  • In terms of regions, APAC is expected to witness the highest growth over the forecast period due to a larger smartphone manufacturing base coupled with increased AI adoption.

Emerging Trends in Terminal AI Chip Market

From 2025 to 2027, we expect terminal AI chip deployments to move from edge experimentation to mass deployment in smartphones, vehicles, cameras, industrial equipment, and enterprise devices. Lucintel expects buyers will consider more than just TOPS, and will consider memory consumption, software partitioning, thermal limits, security, and inference costs as customers will deploy models that run inference closer to the user.

  • Energy-efficient Inference: Efficiency will dominate the terminal AI chip landscape over the next few years as cooling, thermal and battery limitations constrain the deployment of multi-purpose chips. Qualcomm's September 2025 announcement of their Snapdragon X2 platform aims to perform AI inference efficiently within a range of laptop power budgets.
  • Heterogeneous Architectures: Apple's M-series, AMD Ryzen AI 300 series, and Intel Core Ultra place a variety of CPU, GPU, and NPU resources; Intel manufacturers PC chips with 2024-generation CPUs with up to 48 TOPS NPUs. Throughout the next five years, latter-edge integration will significantly reduce latency and lessen reliance on the cloud for workloads.
  • Automotive Edge Intelligence: NVIDIA DRIVE Thor is capable of 2,000 FP8 tera operations per second, making it an efficient platform for centralized computing in vehicles. NVIDIA is currently preparing to mass produce DRIVE Thor in 2025, while other companies are preparing to mass produce vehicles outfitted with NVIDIA's DRIVE Thor.
  • Open Software Ecosystems: Qualcomm, Mediatek, and Google's adoption of the ONNX and TensorFlow Lite ecosystems signals a departure from closed toolchains. Broader AI computing ecosystems will influence chip purchases as developers will have to move models across chip families without significant rework.
  • Regional Supply-chain Diversification: As customers demand advanced diversification of semiconductor capacity, TSMC's Japan and US expansions, along with Intel Foundry Services' manufacturing on US soil, demonstrate regional supply-chain diversification strategies. Regional sourcing will occur with the additional CHIPS Act incentives exceeding $50 billion, even with the constraint of leading-edge packaging.

The terminal ai chip market is starting to enter the practical scaling phase. Energy use, software portability, automotive safety, and supply assurance will be as important as overall performance. With complete development ecosystems, prime vendors will capture more market share. Smaller and more specialized companies will have a chance operate in the market too. Manufacturing capacity and model optimization will be the largest determining factors of shipping capability through 2027.

Recent Developments in the Terminal AI Chip Market

The terminal ai chip market will reach its peak between 2025 and 2027. This happening now as manufacturers move inference from the cloud to embedded devices. Lucintel expects manufacturers will buy terminal AI chips as they improve their edge processing, reduce data transfer, and consume low energy; additionally, manufacturers will focus on soft edge architectures for market adoption.

  • Edge Accelerators: With NVIDIA's announcement of the Jetson Thor in March 2025 (2,070 FP4 teraflops), performance expectations for terminal systems will increase. Additionally, the development of compact and ready-to-use platforms will increase the demand for edge accelerators.
  • Expanding AI PC's: In January 2025, AMD announced the Ryzen AI Max+ 395 with their 50 TOPS NPU. As local inference capacities increase, it will push manufactures of notebooks and workstations to design their products to support local based generative AI compared to cloud based AI.
  • Automotive Deployment: For their fiscal year of 2025, NVIDIA reported in March that their automotive design win pipeline was over $5 billion. As the software becomes more complex in automobiles, it will increase the chip content in a vehicle which will support terminal AI chip pricing and lengthy contracts from manufacturers for that chip.
  • Memory Centric Architectures: In February 2025, Micron began shipping 12-high HBM3E and reached 36GB per stack. Although designed mainly for accelerators, this capacity trend will influence terminal chips as developers demand local edge models with even faster memory access.
  • National Semiconductor Investment: The European Commission earmarked €920 million for Germany's ESMC advanced semiconductor plant. Production is expected to commence in 2027. The advanced semiconductor manufacturing plant will help increase regional supply chain resilience, although advanced specialty semiconductors will be a constraint for terminal AI chip suppliers.

The AI chip terminal market is progressing past the selling of individual accelerators, toward the integration of complete computing platforms. Local inference, memory optimization, software stack, and supply assurances will help vendors receive design wins. Ramping diffusion across the automotive, industrial, imaging, and consumer markets will also occur, while pricing may be volatile due to unclear workload models. Long-term success will be determined not by the number of claimed TOPS, but rather by successful execution.

Strategic Growth Opportunities in the Terminal AI Chip Market

The terminal ai chip market will move away from isolated inference to a more distributed approach across phones, personal computers, automobiles, cameras, and industrial equipment. Decreases in power budgets, tighter data regulations, and the requirement for more instantaneous responses will create market opportunities in 2024 to 2026. Lucintel also reveals a market trend of design specialization as opposed to mass acceleration.

  • Edge Vision Systems: Systems such as retail and logistics security, factory inspections, etc., require local image processing with minimal, if any, tolerance for latency or connectivity. Hailo launched the Hailo-10H which is rated at 40 TOPS, in May 2025. There will be increased demand for vision processing modules as enterprises focus on reducing bandwidth and latency, and increasing the speed of operational decisions within the next 3 to 5 years.
  • Automotive Cockpit Intelligence: Automakers are integrating generative AI into the cockpit infotainment and driver monitoring systems thereby creating a market demand for terminal AI chips. NVIDIA announced the DRIVE Thor with 2,000 TOPS in March 2025. Increasing software defined vehicles will support high margins and loyalty focused business models.
  • Private Enterprise Devices: Banking, healthcare, legal and any other privacy conscious profession will require embedded and secure AI processing units. As a part of the 2025 Copilot+ PC initiative, Microsoft is looking for at least 40 TOPS through its NPU. Increased privacy regulations will create a market for terminal processors with secure and privately controlled AI in enterprise computing.
  • AI Chips for Consumers: Smartphone and PC buyers want translation, search, and content apps available for use with minimal or no internet access. Qualcomm's Snapdragon X2 Elite plans for up to 80 TOPS NPU performance. Premium terminal AI chips hinge on performance and energy consumption. Better performance per watt will spur replacement and will drive the demand for higher tiers of AI chips for end devices.
  • Custom AI Chips: Application-specific inference boards are a better solution for low volume clients, as customized general purpose boards will be prohibitively expensive. NVIDIA's Jetson Thor Project, announced in March 2025, is designed for the robotics market, with up to 2,000 TOPS. Implementation of customized modules for robots, cameras, or machines will result in faster deployment, as demand will extend beyond large technology customers.

In the next five years, the market will shift toward application specific silicon, with a focus on tools and software, and support contracts to be dominated by long term commitments. Security will play a major role in providing hardware and components to highly regulated industries. The automotive and industrial industries will use the most chip-centric systems, while consumer devices will provide the most volume. In a fragmented market, focused specialization will be the major factor for survival.

Terminal AI Chip Market Drivers and Challenges

Growth of terminal AI chips is influenced by multiple factors, including technology, customer needs, economy, sustainability, and regulations. Lucintel indicates that the terminal ai chip market is characterized by trends of growing edge intelligence and offering more advanced products, as well as challenges of supply chain, high costs of innovation and energy, and increasing regulations.

The factors responsible for driving this market include:

  • Growing Demand for Edge AI: Rising adoption of AI in consumer devices like smartphones and PCs, automobiles, cameras, and other equipment used in industry will result in manufacturers putting local processing units in their products. NVIDIA introduced Blackwell architecture at CES 2025 with RTX 50 series consisting of chips that have up to 92 billion transistors. Local processing gives devices fast and independent computation, enhanced privacy, and reduces the need for a constant connection. It is expected in the next few years that edge AI will be deployed in consumers, automobiles, healthcare, and industrial devices.
  • Advanced Semiconductor Architectures: The design of chiplets, cutting edge 3D packaging, and specialized neural processing units (NPU) is improving terminal performance and consuming less power. In January 2025, NVIDIA announced that their GB202 processor in the RTX 5090 had roughly 92 billion transistors, illustrating continuing integration growth. These advancements will help terminals run bigger language models, computer vision, and multimodal workloads locally. In the next three to five years, architectural improvements will allow manufacturers to make smaller devices more capable and encourage them to differentiate their AI processing devices in the marketplace with more speed and efficiency.
  • Product Innovation and Ecosystem Expansion: The market for AI-enabled computers, smartphones, vehicles, robots, and embedded systems is growing along with chipmaker and device manufacturer innovations. Microsoft's Copilot+ PC initiative launched in June 2024, made a 40 trillion operations-per-second NPU performance, laying the foundation for more product innovation in 2025. Terminal AI features are becoming easier to use with standardized software frameworks and developer tools. The next three to five years will see rapid device and consumer adoption of easier ways to integrate AI in small computing devices throughout the enterprise.
  • Energy Efficiency and Data Privacy: On-device AI lowers data transmission, promotes real-time decisions, and can decrease back-end workload. In August 2025, several provisions of the EU AI Act are scheduled to go into effect. This creates further emphasis on governance, transparency, and responsible data management. Optimized terminal chips are able to analyze locally cached data and are able to limit data transmissions and energy consumption. Within the next three to five years, pursuit of privacy and sustainability will incentivize companies to shift distributed job assignments from centralized data processing facilities to optimized, secure terminal devices.
  • Manufacturing Scale and Cost Advantages: The combination of more ample capacity for semiconductor manufacturing, reusable IP blocks, low-cost packaging, competition in chip design, and an improving supply environment decreases the cost of units. TSMC reported for the first quarter of 2025 unit revenue of approximately NT$839.3 billion, indicating robust market demand for advanced semiconductors. With increased production, AI solutions propagate from premium devices to the mass market. Moore's law will be even more pronounced during the next three to five years as cost decreases paired with increased competition ensure further favored adoption of terminal devices and systems.

The challenges facing this market include:

  • High Developments and Component Costs: Manufacturing premium chips involves significant costs for architecture, software, verification, fabrication, and packaging. Additionally, leading-edge manufacturing includes costs for high masks, wafers, and tests while memory components can increase the bill of materials. In January 2025, DeepSeek reported a training cost of approximately 5.6 million USD and sparked industry discussions on AI efficiency, but the terminal manufacturers are also facing huge costs for hardware development. In the next 3-5 years, it is likely that costs will drive smaller vendors away from market and limit most advanced terminal AI capabilities to premium market segments.
  • Supply Chain and Manufacturing Restrictions: Manufacturing terminal AI chips requires leading-edge foundries, high bandwidth memory, special substrates, and integrated Manufacturing. Export controls and geopolitical issues can create supply chain planning challenges by restricting access to necessary technologies. The U.S. semiconductor-related export controls to China in January 2025, shows the ongoing advanced chips policy risk. Within the next 3-5 years, it is likely that chip shortages, regional concentrations, and protectionist trade policies will increase lead times, costs, and motivate vendors to use more diverse suppliers and to expand manufacturing to more geographically dispersed locations.
  • Power, Thermal, and Software Limitations: As models become more capable, there are problems of heating and battery drain; memory bandwidth and cooling become problems, especially in compact terminals. In addition, software fragmentation increases challenges in optimizing different processors, operating systems, model formats, and developer environments. Microsoft pegged the performance bar for modern local AI features when it set a 40-trillion-operations-per-second NPU target for Copilot+ PCs by June 2024. To make advanced AI features more convenient and less of a burden on the performance of the device, it is necessary to develop better cooling technologies, software, and standards.

Compared to devices used for communicating and computing, terminals for military and defense are less capable, but have increased connectivity and automation. There are opportunities for product differentiation and growth driven by customer needs and hardware-software ecosystems. Challenges due to leading participants having higher R&D costs, flexible supply chains, hardware power limits, fragmentation of software, and regulatory pressures are expected. Software and hardware security will influence the design of devices. In the next three to five years, the most successful firms will integrate all these elements along with strategic partnerships across semiconductor, device, cloud, and regulatory spheres.

List of Terminal AI Chip Market Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies terminal ai chip market companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the terminal ai chip market companies profiled in this report include-

  • Intel
  • Qualcomm
  • Advanced Micro Devices
  • Synopsys
  • Huawei
  • Google
  • Amazon

Terminal AI Chip Market by Segment

The study includes a forecast for the global terminal ai chip market by type, application, and region.

Terminal AI Chip Market by Type [Value ($B) from 2019 to 2035]:

  • ASIC
  • FPGA
  • GPU
  • Others

Terminal AI Chip Market by Application [Value ($B) from 2019 to 2035]:

  • Mobile Phone
  • Security Camera
  • Automotive Electronics
  • Smart Home Device
  • Medical Service
  • Others

Terminal AI Chip Market by Region [Value ($B) from 2019 to 2035]:

  • North America
  • Europe
  • Asia Pacific
  • The Rest of the World

Country Wise Outlook for the Terminal AI Chip Market

The terminal ai chip market is already being affected by sovereign chip programs, building data centers, and more control over technology. concise $number$ billion ($number$). The years 2025 to 2027 will see leading economies funding projects and establishing domestic manufacturing with advanced packaging. These projects are expected to influence chip supplier markets and customer purchasing preferences, according to Lucintel.

  • United States: Capacity investment continues (NVIDIA launched the Vera Rubin platform in March 2025). The platform will provide better access to advanced processors and packaging to support terminal AI deployment through 2030 and beyond.
  • China: With an emphasis on domestic substitution, Huawei began selling its first domestically built Ascend 910C chip (March 2025) - built with two Ascend 910B dies - as export controls blocked access to top foreign accelerators. This will speed up the availability of terminal AI hardware in China's cloud, telecommunication, and industrial industries.
  • Germany: TSMC is one of the key investors in the European Semiconductor Manufacturing Company, which plans to build a €10 billion advanced chip fabrication plant in Dresden (August 2024). This will improve the supply of advanced chips designed for automotive and industrial applications throughout Europe.
  • India: Construction of a number of semiconductor manufacturing facilities will begin (February 2024). This includes the 50,000 wafer per month fabrication and assembly facility by Tata Electronics. This will provide the necessary domestic manufacturing and packaging capacity to support the deployment of AI within India's infrastructure and devices.
  • Japan: Japan has reached another level in technology: Rapidus has begun running its 2-nanometer pilot manufacturing line at IIM-1 in Hokkaido in April 2025. The company aims for mass production by 2027. The supply chain program will allow Japanese technology companies to produce advanced AI processors domestically, and at the same time, improve Japan's national defense supply chain.

Features of the Global Terminal AI Chip Market

  • Market Size Estimates: terminal ai chip market size estimation in terms of value ($B).
  • Trend and Forecast Analysis: Market trends (2019 to 2026) and forecast (2027 to 2035) by various segments and regions.
  • Segmentation Analysis: terminal ai chip market size by type, application, and region in terms of value ($B).
  • Regional Analysis: terminal ai chip market breakdown by North America, Europe, Asia Pacific, and Rest of the World.
  • Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the terminal ai chip market.
  • Strategic Analysis: This includes M&A, new product development, and competitive landscape of the terminal ai chip market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

If you are looking to expand your business in this or adjacent markets, then contact us. We have done hundreds of strategic consulting projects in market entry, opportunity screening, due diligence, supply chain analysis, M & A, and more.

This report answers following 11 key questions:

  • Q.1. What are some of the most promising, high-growth opportunities for the terminal ai chip market by type (asic, FPGA, GPU, and others), application (mobile phone, security camera, automotive electronics, smart home device, medical service, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
  • Q.2. Which segments will grow at a faster pace and why?
  • Q.3. Which region will grow at a faster pace and why?
  • Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
  • Q.5. What are the business risks and competitive threats in this market?
  • Q.6. What are the emerging trends in this market and the reasons behind them?
  • Q.7. What are some of the changing demands of customers in the market?
  • Q.8. What are the new developments in the market? Which companies are leading these developments?
  • Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
  • Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
  • Q.11. What M&A activity has occurred in the last 8 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Market Overview

  • 2.1 Background and Classifications
  • 2.2 Supply Chain

3. Market Trends & Forecast Analysis

  • 3.2 Industry Drivers and Challenges
  • 3.3 PESTLE Analysis
  • 3.4 Patent Analysis
  • 3.5 Regulatory Environment

4. Global Terminal AI Chip Market by Type

  • 4.1 Overview
  • 4.2 Attractiveness Analysis by Type
  • 4.3 ASIC: Trends and Forecast (2019-2035)
  • 4.4 FPGA: Trends and Forecast (2019-2035)
  • 4.5 GPU: Trends and Forecast (2019-2035)
  • 4.6 Others: Trends and Forecast (2019-2035)

5. Global Terminal AI Chip Market by Application

  • 5.1 Overview
  • 5.2 Attractiveness Analysis by Application
  • 5.3 Mobile Phone: Trends and Forecast (2019-2035)
  • 5.4 Security Camera: Trends and Forecast (2019-2035)
  • 5.5 Automotive Electronics: Trends and Forecast (2019-2035)
  • 5.6 Smart Home Device: Trends and Forecast (2019-2035)
  • 5.7 Medical Service: Trends and Forecast (2019-2035)
  • 5.8 Others: Trends and Forecast (2019-2035)

6. Regional Analysis

  • 6.1 Overview
  • 6.2 Global Terminal AI Chip Market by Region

7. North American Terminal AI Chip Market

  • 7.1 Overview
  • 7.2 North American Terminal AI Chip Market by Type
  • 7.3 North American Terminal AI Chip Market by Application
  • 7.4 United States Terminal AI Chip Market
  • 7.5 Mexican Terminal AI Chip Market
  • 7.6 Canadian Terminal AI Chip Market

8. European Terminal AI Chip Market

  • 8.1 Overview
  • 8.2 European Terminal AI Chip Market by Type
  • 8.3 European Terminal AI Chip Market by Application
  • 8.4 German Terminal AI Chip Market
  • 8.5 French Terminal AI Chip Market
  • 8.6 Spanish Terminal AI Chip Market
  • 8.7 Italian Terminal AI Chip Market
  • 8.8 United Kingdom Terminal AI Chip Market

9. APAC Terminal AI Chip Market

  • 9.1 Overview
  • 9.2 APAC Terminal AI Chip Market by Type
  • 9.3 APAC Terminal AI Chip Market by Application
  • 9.4 Japanese Terminal AI Chip Market
  • 9.5 Indian Terminal AI Chip Market
  • 9.6 Chinese Terminal AI Chip Market
  • 9.7 South Korean Terminal AI Chip Market
  • 9.8 Indonesian Terminal AI Chip Market

10. ROW Terminal AI Chip Market

  • 10.1 Overview
  • 10.2 ROW Terminal AI Chip Market by Type
  • 10.3 ROW Terminal AI Chip Market by Application
  • 10.4 Middle Eastern Terminal AI Chip Market
  • 10.5 South American Terminal AI Chip Market
  • 10.6 African Terminal AI Chip Market

11. Competitor Analysis

  • 11.1 Product Portfolio Analysis
  • 11.2 Operational Integration
  • 11.3 Porter's Five Forces Analysis
    • Competitive Rivalry
    • Bargaining Power of Buyers
    • Bargaining Power of Suppliers
    • Threat of Substitutes
    • Threat of New Entrants
  • 11.4 Market Share Analysis

12. Opportunities & Strategic Analysis

  • 12.1 Value Chain Analysis
  • 12.2 Growth Opportunity Analysis
    • 12.2.1 Growth Opportunities by Type
    • 12.2.2 Growth Opportunities by Application
  • 12.3 Emerging Trends in the Global Terminal AI Chip Market
  • 12.4 Strategic Analysis
    • 12.4.1 New Product Development
    • 12.4.2 Certification and Licensing
    • 12.4.3 Mergers, Acquisitions, Agreements, Collaborations, and Joint Ventures

13. Company Profiles of the Leading Players Across the Value Chain

  • 13.1 Competitive Analysis
  • 13.2 Intel
    • Company Overview
    • Terminal AI Chip Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.3 Qualcomm
    • Company Overview
    • Terminal AI Chip Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.4 Advanced Micro Devices
    • Company Overview
    • Terminal AI Chip Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.5 Synopsys
    • Company Overview
    • Terminal AI Chip Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.6 Huawei
    • Company Overview
    • Terminal AI Chip Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.7 Google
    • Company Overview
    • Terminal AI Chip Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing
  • 13.8 Amazon
    • Company Overview
    • Terminal AI Chip Business Overview
    • New Product Development
    • Merger, Acquisition, and Collaboration
    • Certification and Licensing

14. Appendix

  • 14.1 List of Figures
  • 14.2 List of Tables
  • 14.3 Research Methodology
  • 14.4 Disclaimer
  • 14.5 Copyright
  • 14.6 Abbreviations and Technical Units
  • 14.7 About Us
  • 14.8 Contact Us

List of Figures

  • Figure 1.1: Trends and Forecast for the Global Terminal AI Chip Market
  • Figure 2.1: Usage of Terminal AI Chip Market
  • Figure 2.2: Classification of the Global Terminal AI Chip Market
  • Figure 2.3: Supply Chain of the Global Terminal AI Chip Market
  • Figure 3.1: Driver and Challenges of the Terminal AI Chip Market
  • Figure 3.2: PESTLE Analysis
  • Figure 3.3: Patent Analysis
  • Figure 3.4: Regulatory Environment
  • Figure 4.1: Global Terminal AI Chip Market by Type in 2019, 2026, and 2035
  • Figure 4.2: Trends of the Global Terminal AI Chip Market ($B) by Type
  • Figure 4.3: Forecast for the Global Terminal AI Chip Market ($B) by Type
  • Figure 4.4: Trends and Forecast for ASIC in the Global Terminal AI Chip Market (2019-2035)
  • Figure 4.5: Trends and Forecast for FPGA in the Global Terminal AI Chip Market (2019-2035)
  • Figure 4.6: Trends and Forecast for GPU in the Global Terminal AI Chip Market (2019-2035)
  • Figure 4.7: Trends and Forecast for Others in the Global Terminal AI Chip Market (2019-2035)
  • Figure 5.1: Global Terminal AI Chip Market by Application in 2019, 2026, and 2035
  • Figure 5.2: Trends of the Global Terminal AI Chip Market ($B) by Application
  • Figure 5.3: Forecast for the Global Terminal AI Chip Market ($B) by Application
  • Figure 5.4: Trends and Forecast for Mobile Phone in the Global Terminal AI Chip Market (2019-2035)
  • Figure 5.5: Trends and Forecast for Security Camera in the Global Terminal AI Chip Market (2019-2035)
  • Figure 5.6: Trends and Forecast for Automotive Electronics in the Global Terminal AI Chip Market (2019-2035)
  • Figure 5.7: Trends and Forecast for Smart Home Device in the Global Terminal AI Chip Market (2019-2035)
  • Figure 5.8: Trends and Forecast for Medical Service in the Global Terminal AI Chip Market (2019-2035)
  • Figure 5.9: Trends and Forecast for Others in the Global Terminal AI Chip Market (2019-2035)
  • Figure 6.1: Trends of the Global Terminal AI Chip Market ($B) by Region (2019-2026)
  • Figure 6.2: Forecast for the Global Terminal AI Chip Market ($B) by Region (2027-2035)
  • Figure 7.1: North American Terminal AI Chip Market by Type in 2019, 2026, and 2035
  • Figure 7.2: Trends of the North American Terminal AI Chip Market ($B) by Type (2019-2026)
  • Figure 7.3: Forecast for the North American Terminal AI Chip Market ($B) by Type (2027-2035)
  • Figure 7.4: North American Terminal AI Chip Market by Application in 2019, 2026, and 2035
  • Figure 7.5: Trends of the North American Terminal AI Chip Market ($B) by Application (2019-2026)
  • Figure 7.6: Forecast for the North American Terminal AI Chip Market ($B) by Application (2027-2035)
  • Figure 7.7: Trends and Forecast for the United States Terminal AI Chip Market ($B) (2019-2035)
  • Figure 7.8: Trends and Forecast for the Mexican Terminal AI Chip Market ($B) (2019-2035)
  • Figure 7.9: Trends and Forecast for the Canadian Terminal AI Chip Market ($B) (2019-2035)
  • Figure 8.1: European Terminal AI Chip Market by Type in 2019, 2026, and 2035
  • Figure 8.2: Trends of the European Terminal AI Chip Market ($B) by Type (2019-2026)
  • Figure 8.3: Forecast for the European Terminal AI Chip Market ($B) by Type (2027-2035)
  • Figure 8.4: European Terminal AI Chip Market by Application in 2019, 2026, and 2035
  • Figure 8.5: Trends of the European Terminal AI Chip Market ($B) by Application (2019-2026)
  • Figure 8.6: Forecast for the European Terminal AI Chip Market ($B) by Application (2027-2035)
  • Figure 8.7: Trends and Forecast for the German Terminal AI Chip Market ($B) (2019-2035)
  • Figure 8.8: Trends and Forecast for the French Terminal AI Chip Market ($B) (2019-2035)
  • Figure 8.9: Trends and Forecast for the Spanish Terminal AI Chip Market ($B) (2019-2035)
  • Figure 8.10: Trends and Forecast for the Italian Terminal AI Chip Market ($B) (2019-2035)
  • Figure 8.11: Trends and Forecast for the United Kingdom Terminal AI Chip Market ($B) (2019-2035)
  • Figure 9.1: APAC Terminal AI Chip Market by Type in 2019, 2026, and 2035
  • Figure 9.2: Trends of the APAC Terminal AI Chip Market ($B) by Type (2019-2026)
  • Figure 9.3: Forecast for the APAC Terminal AI Chip Market ($B) by Type (2027-2035)
  • Figure 9.4: APAC Terminal AI Chip Market by Application in 2019, 2026, and 2035
  • Figure 9.5: Trends of the APAC Terminal AI Chip Market ($B) by Application (2019-2026)
  • Figure 9.6: Forecast for the APAC Terminal AI Chip Market ($B) by Application (2027-2035)
  • Figure 9.7: Trends and Forecast for the Japanese Terminal AI Chip Market ($B) (2019-2035)
  • Figure 9.8: Trends and Forecast for the Indian Terminal AI Chip Market ($B) (2019-2035)
  • Figure 9.9: Trends and Forecast for the Chinese Terminal AI Chip Market ($B) (2019-2035)
  • Figure 9.10: Trends and Forecast for the South Korean Terminal AI Chip Market ($B) (2019-2035)
  • Figure 9.11: Trends and Forecast for the Indonesian Terminal AI Chip Market ($B) (2019-2035)
  • Figure 10.1: ROW Terminal AI Chip Market by Type in 2019, 2026, and 2035
  • Figure 10.2: Trends of the ROW Terminal AI Chip Market ($B) by Type (2019-2026)
  • Figure 10.3: Forecast for the ROW Terminal AI Chip Market ($B) by Type (2027-2035)
  • Figure 10.4: ROW Terminal AI Chip Market by Application in 2019, 2026, and 2035
  • Figure 10.5: Trends of the ROW Terminal AI Chip Market ($B) by Application (2019-2026)
  • Figure 10.6: Forecast for the ROW Terminal AI Chip Market ($B) by Application (2027-2035)
  • Figure 10.7: Trends and Forecast for the Middle Eastern Terminal AI Chip Market ($B) (2019-2035)
  • Figure 10.8: Trends and Forecast for the South American Terminal AI Chip Market ($B) (2019-2035)
  • Figure 10.9: Trends and Forecast for the African Terminal AI Chip Market ($B) (2019-2035)
  • Figure 11.1: Porter's Five Forces Analysis of the Global Terminal AI Chip Market
  • Figure 11.2: Market Share (%) of Top Players in the Global Terminal AI Chip Market (2026)
  • Figure 12.1: Growth Opportunities for the Global Terminal AI Chip Market by Type
  • Figure 12.2: Growth Opportunities for the Global Terminal AI Chip Market by Application
  • Figure 12.3: Growth Opportunities for the Global Terminal AI Chip Market by Region
  • Figure 12.4: Emerging Trends in the Global Terminal AI Chip Market

List of Tables

  • Table 1.1: Growth Rate (%, 2025-2026) and CAGR (%, 2027-2035) of the Terminal AI Chip Market by Type and Application
  • Table 1.2: Attractiveness Analysis for the Terminal AI Chip Market by Region
  • Table 1.3: Global Terminal AI Chip Market Parameters and Attributes
  • Table 3.1: Trends of the Global Terminal AI Chip Market (2019-2026)
  • Table 3.2: Forecast for the Global Terminal AI Chip Market (2027-2035)
  • Table 4.1: Attractiveness Analysis for the Global Terminal AI Chip Market by Type
  • Table 4.2: Market Size and CAGR of Various Type in the Global Terminal AI Chip Market (2019-2026)
  • Table 4.3: Market Size and CAGR of Various Type in the Global Terminal AI Chip Market (2027-2035)
  • Table 4.4: Trends of ASIC in the Global Terminal AI Chip Market (2019-2026)
  • Table 4.5: Forecast for ASIC in the Global Terminal AI Chip Market (2027-2035)
  • Table 4.6: Trends of FPGA in the Global Terminal AI Chip Market (2019-2026)
  • Table 4.7: Forecast for FPGA in the Global Terminal AI Chip Market (2027-2035)
  • Table 4.8: Trends of GPU in the Global Terminal AI Chip Market (2019-2026)
  • Table 4.9: Forecast for GPU in the Global Terminal AI Chip Market (2027-2035)
  • Table 4.10: Trends of Others in the Global Terminal AI Chip Market (2019-2026)
  • Table 4.11: Forecast for Others in the Global Terminal AI Chip Market (2027-2035)
  • Table 5.1: Attractiveness Analysis for the Global Terminal AI Chip Market by Application
  • Table 5.2: Market Size and CAGR of Various Application in the Global Terminal AI Chip Market (2019-2026)
  • Table 5.3: Market Size and CAGR of Various Application in the Global Terminal AI Chip Market (2027-2035)
  • Table 5.4: Trends of Mobile Phone in the Global Terminal AI Chip Market (2019-2026)
  • Table 5.5: Forecast for Mobile Phone in the Global Terminal AI Chip Market (2027-2035)
  • Table 5.6: Trends of Security Camera in the Global Terminal AI Chip Market (2019-2026)
  • Table 5.7: Forecast for Security Camera in the Global Terminal AI Chip Market (2027-2035)
  • Table 5.8: Trends of Automotive Electronics in the Global Terminal AI Chip Market (2019-2026)
  • Table 5.9: Forecast for Automotive Electronics in the Global Terminal AI Chip Market (2027-2035)
  • Table 5.10: Trends of Smart Home Device in the Global Terminal AI Chip Market (2019-2026)
  • Table 5.11: Forecast for Smart Home Device in the Global Terminal AI Chip Market (2027-2035)
  • Table 5.12: Trends of Medical Service in the Global Terminal AI Chip Market (2019-2026)
  • Table 5.13: Forecast for Medical Service in the Global Terminal AI Chip Market (2027-2035)
  • Table 5.14: Trends of Others in the Global Terminal AI Chip Market (2019-2026)
  • Table 5.15: Forecast for Others in the Global Terminal AI Chip Market (2027-2035)
  • Table 6.1: Market Size and CAGR of Various Regions in the Global Terminal AI Chip Market (2019-2026)
  • Table 6.2: Market Size and CAGR of Various Regions in the Global Terminal AI Chip Market (2027-2035)
  • Table 7.1: Trends of the North American Terminal AI Chip Market (2019-2026)
  • Table 7.2: Forecast for the North American Terminal AI Chip Market (2027-2035)
  • Table 7.3: Market Size and CAGR of Various Type in the North American Terminal AI Chip Market (2019-2026)
  • Table 7.4: Market Size and CAGR of Various Type in the North American Terminal AI Chip Market (2027-2035)
  • Table 7.5: Market Size and CAGR of Various Application in the North American Terminal AI Chip Market (2019-2026)
  • Table 7.6: Market Size and CAGR of Various Application in the North American Terminal AI Chip Market (2027-2035)
  • Table 7.7: Trends and Forecast for the United States Terminal AI Chip Market (2019-2035)
  • Table 7.8: Trends and Forecast for the Mexican Terminal AI Chip Market (2019-2035)
  • Table 7.9: Trends and Forecast for the Canadian Terminal AI Chip Market (2019-2035)
  • Table 8.1: Trends of the European Terminal AI Chip Market (2019-2026)
  • Table 8.2: Forecast for the European Terminal AI Chip Market (2027-2035)
  • Table 8.3: Market Size and CAGR of Various Type in the European Terminal AI Chip Market (2019-2026)
  • Table 8.4: Market Size and CAGR of Various Type in the European Terminal AI Chip Market (2027-2035)
  • Table 8.5: Market Size and CAGR of Various Application in the European Terminal AI Chip Market (2019-2026)
  • Table 8.6: Market Size and CAGR of Various Application in the European Terminal AI Chip Market (2027-2035)
  • Table 8.7: Trends and Forecast for the German Terminal AI Chip Market (2019-2035)
  • Table 8.8: Trends and Forecast for the French Terminal AI Chip Market (2019-2035)
  • Table 8.9: Trends and Forecast for the Spanish Terminal AI Chip Market (2019-2035)
  • Table 8.10: Trends and Forecast for the Italian Terminal AI Chip Market (2019-2035)
  • Table 8.11: Trends and Forecast for the United Kingdom Terminal AI Chip Market (2019-2035)
  • Table 9.1: Trends of the APAC Terminal AI Chip Market (2019-2026)
  • Table 9.2: Forecast for the APAC Terminal AI Chip Market (2027-2035)
  • Table 9.3: Market Size and CAGR of Various Type in the APAC Terminal AI Chip Market (2019-2026)
  • Table 9.4: Market Size and CAGR of Various Type in the APAC Terminal AI Chip Market (2027-2035)
  • Table 9.5: Market Size and CAGR of Various Application in the APAC Terminal AI Chip Market (2019-2026)
  • Table 9.6: Market Size and CAGR of Various Application in the APAC Terminal AI Chip Market (2027-2035)
  • Table 9.7: Trends and Forecast for the Japanese Terminal AI Chip Market (2019-2035)
  • Table 9.8: Trends and Forecast for the Indian Terminal AI Chip Market (2019-2035)
  • Table 9.9: Trends and Forecast for the Chinese Terminal AI Chip Market (2019-2035)
  • Table 9.10: Trends and Forecast for the South Korean Terminal AI Chip Market (2019-2035)
  • Table 9.11: Trends and Forecast for the Indonesian Terminal AI Chip Market (2019-2035)
  • Table 10.1: Trends of the ROW Terminal AI Chip Market (2019-2026)
  • Table 10.2: Forecast for the ROW Terminal AI Chip Market (2027-2035)
  • Table 10.3: Market Size and CAGR of Various Type in the ROW Terminal AI Chip Market (2019-2026)
  • Table 10.4: Market Size and CAGR of Various Type in the ROW Terminal AI Chip Market (2027-2035)
  • Table 10.5: Market Size and CAGR of Various Application in the ROW Terminal AI Chip Market (2019-2026)
  • Table 10.6: Market Size and CAGR of Various Application in the ROW Terminal AI Chip Market (2027-2035)
  • Table 10.7: Trends and Forecast for the Middle Eastern Terminal AI Chip Market (2019-2035)
  • Table 10.8: Trends and Forecast for the South American Terminal AI Chip Market (2019-2035)
  • Table 10.9: Trends and Forecast for the African Terminal AI Chip Market (2019-2035)
  • Table 11.1: Product Mapping of Terminal AI Chip Suppliers Based on Segments
  • Table 11.2: Operational Integration of Terminal AI Chip Manufacturers
  • Table 11.3: Rankings of Suppliers Based on Terminal AI Chip Revenue
  • Table 12.1: New Product Launches by Major Terminal AI Chip Producers (2019-2026)
  • Table 12.2: Certification Acquired by Major Competitor in the Global Terminal AI Chip Market