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1851110

圖形處理器（GPU）：市場佔有率分析、行業趨勢、統計數據和成長預測（2025-2030 年）

Graphics Processing Unit (GPU) - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3個工作天內

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簡介目錄

預計到 2025 年，圖形處理器市場規模將達到 826.8 億美元，到 2030 年將達到 3,525.5 億美元，年複合成長率為 33.65%。

圖形處理器 (GPU) - 市場 - IMG1

這一激增反映了產業從純圖形工作負載向以人工智慧為中心的運算的轉變，GPU 成為驅動生成式人工智慧訓練、超大規模推理、雲端遊戲和異質邊緣系統的核心力量。自主人工智慧舉措的加速推進、企業對特定領域模型的投資以及 8K 和光線追蹤遊戲技術的快速成熟，持續推動對高頻寬設備的需求。先進節點產能緊張，加上複雜的出口管制，促使訂單轉向多代工廠供應策略。同時，基於晶片組的設計和開放指令集正在引入新的競爭因素，但並未打破該行業目前的集中度。

全球圖形處理器 (GPU) 市場趨勢與洞察

利用GPU密集型訓練生成式AI模型

大參數變換模型通常超過 1000 億個參數，迫使企業在長達數月的訓練運行中並行運行數萬個 GPU，從而將張量吞吐量推至超越傳統圖形指標的水平。高頻寬記憶體、無損互連和液冷機架已成為標準的採購標準。醫療保健、金融和製造企業現在效仿超大規模資料中心營運商，部署專用於領域模型的叢集，這種模式正在擴大圖形處理器市場的終端用戶群。隨著工作流程編配異質 GPU 池以處理特定上下文的分片，專用混合架構進一步加劇了需求。傳統資料中心的功率密度限制進一步加速了向專用 AI 群集的遷移。

建構「主權人工智慧」資料中心

世界各國政府將國內人工智慧運算視為戰略資產，如同能源或通訊骨幹網路。加拿大已撥款20億美元用於其國家人工智慧運算策略，專注於發展GPU驅動的超級電腦。印度的「印度人工智慧計畫」（IndiaAI Mission）計畫購置超過1萬塊GPU用於本土語言模式。韓國也儲備了類似數量的GPU，以確保研究水準的平等。這些計劃將公共預算轉化為多年採購計劃，從而穩定了整個圖形處理器市場的基準需求。從歐盟的工業自動化到墨西哥灣沿岸的能源分析，區域模型訓練將架構需求從資料中心SKU擴展到強大的邊緣加速器。

對7奈米以下GPU銷售的出口管制限制

英偉累計了45億美元的費用，用於支付受限的H2O加速器相關費用，這顯示其收入對授權變化十分敏感。中國企業則加速了國內GPU計劃的研發，可能會削弱未來對美國智慧財產權的需求。供應鏈中斷迫使供應商維護多種晶片版本，這增加了營運成本，並使整個圖形處理器市場的庫存規劃變得更加複雜。

細分市場分析

到2024年，獨立顯示卡將佔據圖形處理器（GPU）市場62.7%的佔有率，成為當年GPU市場規模最大的組成部分。市場需求集中在高頻寬記憶體、專用張量核心和可擴展互連技術上，這些特性尤其適用於人工智慧叢集。企業傾向於採用模組化設計，這種設計允許在不更換主機板的情況下逐步升級機架。由於整合GPU無法支援射線追蹤和8K素材，遊戲領域對高階GPU的需求持續檢驗。

晶片組的採用降低了單位性能成本，並透過拼接更小的晶粒提高了產量比率。 AMD 的多晶片組佈局和 NVIDIA 的 NVLink Fusion 都擴大了獨立顯示卡在半客製化伺服器設計的應用範圍。同時，整合式顯示卡對於行動裝置和入門級桌上型電腦仍然至關重要，因為散熱預算決定了其選擇。因此，圖形處理器產業的細分不再僅僅基於成本，而是沿著移動性和吞吐量之間的頻譜展開。

伺服器和資料中心加速器預計到2030年將以37.6%的複合年成長率快速成長，從而推動圖形處理器市場的擴張。超大規模營運商正在提供完整的AI工廠，其中包含數萬塊通過光纖NVLink或PCIe 6.0互連的電路板。來自雲端服務提供者、公共研究聯盟和製藥公司持續簽訂的採購契約，支撐著未來多年的市場需求。

遊戲系統仍然是裝置量最大的單一類別，但其成長速度慢於雲端運算和企業級人工智慧。汽車、工業機器人和醫療影像處理雖然規模較小，但由於對功能安全性和長期支援的要求較高，因此利潤率很高。這些邊緣產品類別共同作用，使圖形處理器產業的收入擺脫了對週期性消費的依賴。

圖形處理器 (GPU) 市場按 GPU 類型（獨立 GPU、整合 GPU 及其他）、裝置應用（行動裝置和平板電腦、PC 和工作站及其他）、部署模式（本地部署和雲端部署）、指令集架構（x86-64、Arm 及其他）和地區進行細分。市場預測以美元計價。

區域分析

到2024年，北美將佔據43.7%的圖形處理器（GPU）市場佔有率，這主要得益於矽谷的晶片設計、超大規模雲園區以及豐富的創業投資資金。該地區受益於半導體智慧財產權所有者與人工智慧軟體新興企業之間的緊密合作，從而加速了下一代電路板的量產。出口管制制度雖然增加了合規成本，但也促使國內補貼轉向先進節點製造和封裝生產線。

亞太地區是成長最快的地區，預計到2030年將以37.4%的複合年成長率成長。中國正根據其技術主權指令加速推動自主GPU計劃，印度的「印度人工智慧計劃」（IndiaAI Mission）正在資助建造國家級GPU設施和全邦語言模型。韓國擁有1萬個GPU的國家運算中心和日本的人工智慧災害應變計畫將推動該地區對超級運算的需求從商業雲端運算轉向公共部門超級運算。

在歐洲，嚴格的人工智慧管治正在平衡工業現代化目標。德國正與英偉達合作建造一個面向車輛和機械數位孿生的工業人工智慧雲端平台。法國、義大利和英國優先發展多語言學習模型和金融科技風險分析，並推廣部署在高效率、區域性冷卻資料中心的區域專屬GPU叢集。以沙烏地阿拉伯和阿拉伯聯合大公國為首的中東地區正大力投資人工智慧工廠，以實現經濟多元化，進一步擴大全部區域圖形處理器的市場。

其他福利：

  • Excel格式的市場預測（ME）表
  • 3個月的分析師支持

目錄

第1章 引言

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章 市場情勢

  • 市場概覽
  • 市場促進因素
    • AAA 遊戲畫面真實感的演變
    • 對擴增實境/虛擬實境和人工智慧主導的異質運算的需求
    • 雲端遊戲服務開發
    • 用於訓練生成式人工智慧模型的GPU強度
    • 主權人工智慧資料中心建設
    • 基於晶片組的客製化GPU SKU
  • 市場限制
    • 前期投資和零件成本較高
    • 先進節點長期供應受限
    • 對7nm及以上GPU的銷售實施出口管制限制
    • 超大規模資料中心的冷卻和功率密度限制
  • 供應鏈分析
  • 監管環境
  • 技術展望
  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭對手之間的競爭
  • 評估市場的宏觀經濟因素

第5章 市場規模與成長預測

  • 按GPU類型
    • 獨立顯示卡
    • 整合顯示卡
    • 其他
  • 按設備使用狀況
    • 行動裝置和平板電腦
    • 個人電腦和工作站
    • 伺服器和資料中心加速器
    • 遊戲主機和掌上型遊戲機
    • 汽車/ADAS
    • 其他嵌入式和邊緣設備
  • 按部署模式
    • 本地部署
    • 雲
  • 依指令集架構
    • x86-64
    • Arm
    • RISC-V 和 OpenGPU
    • 其他（功耗、MIPS）
  • 按地區
    • 北美洲
      • 美國
      • 加拿大
      • 墨西哥
    • 南美洲
      • 巴西
      • 阿根廷
      • 其他南美洲
    • 歐洲
      • 德國
      • 英國
      • 法國
      • 義大利
      • 其他歐洲地區
    • 亞太地區
      • 中國
      • 日本
      • 印度
      • 韓國
      • 東南亞
      • 亞太其他地區
    • 中東和非洲
      • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 土耳其
      • 其他中東地區
      • 非洲
      • 南非
      • 埃及
      • 奈及利亞
      • 其他非洲地區

第6章 競爭情勢

  • 市場集中度
  • 策略趨勢
  • 市佔率分析
  • 公司簡介
    • NVIDIA Corporation
    • Advanced Micro Devices Inc.
    • Intel Corporation
    • Apple Inc.
    • Samsung Electronics Co. Ltd.
    • Qualcomm Technologies Inc.
    • Arm Ltd.
    • Imagination Technologies Group
    • EVGA Corp.
    • Sapphire Technology Ltd.
    • ASUStek Computer Inc.
    • Micro-Star International（MSI）
    • Gigabyte Technology Co. Ltd.
    • Zotac Technology Ltd.
    • Palit Microsystems Ltd.
    • Leadtek Research Inc.
    • Colorful Technology Co. Ltd.
    • Amazon Web Services（Elastic GPUs）
    • Google LLC（Cloud TPU/GPU）
    • Huawei HiSilicon
    • Graphcore Ltd.

第7章 市場機會與未來展望

簡介目錄
Product Code: 67016

The graphics processing unit market size stands at USD 82.68 billion in 2025 and is forecast to reach USD 352.55 billion by 2030, delivering a 33.65% CAGR.

Graphics Processing Unit (GPU) - Market - IMG1

The surge reflects an industry pivot from graphics-only workloads to AI-centric compute, where GPUs function as the workhorses behind generative AI training, hyperscale inference, cloud gaming, and heterogeneous edge systems. Accelerated sovereign AI initiatives, corporate investment in domain-specific models, and the rapid maturation of 8K, ray-traced gaming continue to deepen demand for high-bandwidth devices. Tight advanced-node capacity, coupled with export-control complexity, is funneling orders toward multi-foundry supply strategies. Meanwhile, chiplet-based designs and open instruction sets are introducing new competitive vectors without dislodging the field's current concentration.

Global Graphics Processing Unit (GPU) Market Trends and Insights

Generative-AI Model Training GPU Intensity

Large-parameter transformer models routinely exceed 100 billion parameters, forcing enterprises to operate tens of thousands of GPUs in parallel for months-long training runs, elevating tensor throughput above traditional graphics metrics. High-bandwidth memory, lossless interconnects, and liquid-cooling racks have become standard purchase criteria. Healthcare, finance, and manufacturing firms now mirror hyperscalers by provisioning dedicated super-clusters for domain models, a pattern that broadens the graphics processing unit market's end-user base. Mixture-of-experts architectures amplify the demand, as workflows orchestrate heterogeneous GPU pools to handle context-specific shards. Power-density constraints inside legacy data halls further accelerate migration to purpose-built AI pods.

Sovereign-AI" Datacenter Build-outs

Governments view domestic AI compute as a strategic asset akin to energy or telecom backbone. Canada allocated USD 2 billion for a national AI compute strategy focused on GPU-powered supercomputers.India's IndiaAI Mission plans 10,000+ GPUs for indigenous language models. South Korea is stockpiling similar volumes to secure research parity. Such projects convert public budgets into multi-year purchase schedules, stabilizing baseline demand across the graphics processing unit market. Region-specific model training-ranging from industrial automation in the EU to energy analytics in the Gulf-expands architectural requirements beyond datacenter SKUs into ruggedized edge accelerators.

Export-Control Limits on <= 7 nm GPU Sales

The United States introduced tiered licensing for advanced computing ICs, effectively curbing shipments of state-of-the-art GPUs to China.NVIDIA booked a USD 4.5 billion charge tied to restricted H20 accelerators, illustrating revenue sensitivity to licensing shifts. Chinese firms responded by fast-tracking domestic GPU projects, potentially diluting future demand for U.S. IP. The bifurcated supply chain forces vendors to maintain multiple silicon variants, lifting operating costs and complicating inventory planning throughout the graphics processing unit market.

Other drivers and restraints analyzed in the detailed report include:

  1. AR/VR and AI-Led Heterogeneous Computing Demand
  2. Cloud-Gaming Service Roll-outs
  3. Chronic Advanced-Node Supply Constraints

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Discrete boards controlled 62.7% of the graphics processing unit market share in 2024, translating to the largest slice of the graphics processing unit market size for that year. Demand concentrates on high-bandwidth memory, dedicated tensor cores, and scalable interconnects suited for AI clusters. Enterprises favor modularity, enabling phased rack upgrades without motherboard swaps. Gaming continues to validate high-end variants by adopting ray tracing and 8K assets that integrated GPUs cannot sustain.

Chiplet adoption is lowering the cost per performance tier and improving yields by stitching smaller dies. AMD's multi-chiplet layout and NVIDIA's NVLink Fusion both extend discrete relevance into semi-custom server designs. Meanwhile, integrated GPUs remain indispensable for mobile and entry desktops where thermal budgets dominate. The graphics processing unit industry thus segments along a mobility-versus-throughput spectrum rather than a pure cost axis.

Servers and data-center accelerators are projected to register the fastest 37.6% CAGR through 2030, underpinning the swelling graphics processing unit market. Hyperscale operators provision entire AI factories holding tens of thousands of boards interconnected via optical NVLink or PCIe 6.0 fabrics. Sustained procurement contracts from cloud providers, public research consortia, and pharmaceutical pipelines jointly anchor demand at multi-year horizons.

Gaming systems remain the single largest installed-base category, but their growth curve is modest next to cloud and enterprise AI. Automotive, industrial robotics, and medical imaging represent smaller yet high-margin verticals thanks to functional-safety and long-life support requirements. Collectively, these edge cohorts diversify the graphics processing unit industry's revenue away from cyclical consumer cycles.

Graphics Processing Unit (GPU) Market is Segmented by GPU Type (Discrete GPU, Integrated GPU, and Others), Device Application (Mobile Devices and Tablets, Pcs and Workstations, and More), Deployment Model (On-Premises and Cloud), Instruction-Set Architecture (x86-64, Arm, and More), and by Geography. The Market Forecasts are Provided in Terms of Value (USD).

Geography Analysis

North America captured 43.7% graphics processing unit market share in 2024, anchored by Silicon Valley chip design, hyperscale cloud campuses, and deep venture funding pipelines. The region benefits from tight integration between semiconductor IP owners and AI software start-ups, accelerating time-to-volume for next-gen boards. Export-control regimes do introduce compliance overhead yet simultaneously channel domestic subsidies into advanced-node fabrication and packaging lines.

Asia-Pacific is the fastest-growing territory, expected to post a 37.4% CAGR to 2030. China accelerates indigenous GPU programs under technology-sovereignty mandates, while India's IndiaAI Mission finances national GPU facilities and statewide language models. South Korea's 10,000-GPU state compute hub and Japan's AI disaster-response initiatives extend regional demand beyond commercial clouds into public-sector supercomputing.

Europe balances stringent AI governance with industrial modernization goals. Germany partners with NVIDIA to build an industrial AI cloud targeting automotive and machinery digital twins. France, Italy, and the UK prioritize multilingual LLMs and fintech risk analytics, prompting localized GPU clusters housed in high-efficiency, district-cooled data centers. The Middle East, led by Saudi Arabia and the UAE, is investing heavily in AI factories to diversify economies, further broadening the graphics processing unit market footprint across emerging geographies.

  1. NVIDIA Corporation
  2. Advanced Micro Devices Inc.
  3. Intel Corporation
  4. Apple Inc.
  5. Samsung Electronics Co. Ltd.
  6. Qualcomm Technologies Inc.
  7. Arm Ltd.
  8. Imagination Technologies Group
  9. EVGA Corp.
  10. Sapphire Technology Ltd.
  11. ASUStek Computer Inc.
  12. Micro-Star International (MSI)
  13. Gigabyte Technology Co. Ltd.
  14. Zotac Technology Ltd.
  15. Palit Microsystems Ltd.
  16. Leadtek Research Inc.
  17. Colorful Technology Co. Ltd.
  18. Amazon Web Services (Elastic GPUs)
  19. Google LLC (Cloud TPU/GPU)
  20. Huawei HiSilicon
  21. Graphcore Ltd.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Evolving graphics realism in AAA gaming
    • 4.2.2 AR/VR and AI-led heterogeneous computing demand
    • 4.2.3 Cloud-gaming service roll-outs
    • 4.2.4 Generative-AI model training GPU intensity
    • 4.2.5 Sovereign-AI" datacenter build-outs"
    • 4.2.6 Chiplet-based custom GPU SKUs
  • 4.3 Market Restraints
    • 4.3.1 High upfront capex and BOM costs
    • 4.3.2 Chronic advanced-node supply constraints
    • 4.3.3 Export-control limits on greater than or equal to 7 nm GPU sales
    • 4.3.4 Cooling/power-density limits in hyperscale DCs
  • 4.4 Supply-Chain Analysis
  • 4.5 Regulatory Landscape
  • 4.6 Technological Outlook
  • 4.7 Porter's Five Force Analysis
    • 4.7.1 Bargaining Power of Suppliers
    • 4.7.2 Bargaining Power of Buyers
    • 4.7.3 Threat of New Entrants
    • 4.7.4 Threat of Substitutes
    • 4.7.5 Intensity of Competitive Rivalry
  • 4.8 Assesment of Macroeconomic Factors on the Market

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

  • 5.1 By GPU Type
    • 5.1.1 Discrete GPU
    • 5.1.2 Integrated GPU
    • 5.1.3 Others
  • 5.2 By Device Application
    • 5.2.1 Mobile Devices and Tablets
    • 5.2.2 PCs and Workstations
    • 5.2.3 Servers and Data-center Accelerators
    • 5.2.4 Gaming Consoles and Handhelds
    • 5.2.5 Automotive / ADAS
    • 5.2.6 Other Embedded and Edge Devices
  • 5.3 By Deployment Model
    • 5.3.1 On-Premise
    • 5.3.2 Cloud
  • 5.4 By Instruction-Set Architecture
    • 5.4.1 x86-64
    • 5.4.2 Arm
    • 5.4.3 RISC-V and OpenGPU
    • 5.4.4 Others (Power, MIPS)
  • 5.5 By Geography
    • 5.5.1 North America
      • 5.5.1.1 United States
      • 5.5.1.2 Canada
      • 5.5.1.3 Mexico
    • 5.5.2 South America
      • 5.5.2.1 Brazil
      • 5.5.2.2 Argentina
      • 5.5.2.3 Rest of South America
    • 5.5.3 Europe
      • 5.5.3.1 Germany
      • 5.5.3.2 United Kingdom
      • 5.5.3.3 France
      • 5.5.3.4 Italy
      • 5.5.3.5 Rest of Europe
    • 5.5.4 Asia-Pacific
      • 5.5.4.1 China
      • 5.5.4.2 Japan
      • 5.5.4.3 India
      • 5.5.4.4 South Korea
      • 5.5.4.5 Southeast Asia
      • 5.5.4.6 Rest of Asia-Pacific
    • 5.5.5 Middle East and Africa
      • 5.5.5.1 Middle East
      • 5.5.5.1.1 Saudi Arabia
      • 5.5.5.1.2 United Arab Emirates
      • 5.5.5.1.3 Turkey
      • 5.5.5.1.4 Rest of Middle East
      • 5.5.5.2 Africa
      • 5.5.5.2.1 South Africa
      • 5.5.5.2.2 Egypt
      • 5.5.5.2.3 Nigeria
      • 5.5.5.2.4 Rest of Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Market Concentration
  • 6.2 Strategic Moves
  • 6.3 Market Share Analysis
  • 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
    • 6.4.1 NVIDIA Corporation
    • 6.4.2 Advanced Micro Devices Inc.
    • 6.4.3 Intel Corporation
    • 6.4.4 Apple Inc.
    • 6.4.5 Samsung Electronics Co. Ltd.
    • 6.4.6 Qualcomm Technologies Inc.
    • 6.4.7 Arm Ltd.
    • 6.4.8 Imagination Technologies Group
    • 6.4.9 EVGA Corp.
    • 6.4.10 Sapphire Technology Ltd.
    • 6.4.11 ASUStek Computer Inc.
    • 6.4.12 Micro-Star International (MSI)
    • 6.4.13 Gigabyte Technology Co. Ltd.
    • 6.4.14 Zotac Technology Ltd.
    • 6.4.15 Palit Microsystems Ltd.
    • 6.4.16 Leadtek Research Inc.
    • 6.4.17 Colorful Technology Co. Ltd.
    • 6.4.18 Amazon Web Services (Elastic GPUs)
    • 6.4.19 Google LLC (Cloud TPU/GPU)
    • 6.4.20 Huawei HiSilicon
    • 6.4.21 Graphcore Ltd.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

  • 7.1 White-space and Unmet-need Assessment