엣지 AI GPU 시장 : 시장 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the edge AI GPU market size expanded from USD 2.97 billion in 2025 to USD 4.01 billion in 2031, registering a 37.99% CAGR from 2026 to 2031.

This report is Segmented by GPU Type (Integrated GPUs and Discrete GPUs), Deployment Type (Edge Servers/Gateways and Embedded Edge Devices), Application (Video Analytics and Surveillance, Industrial AI, Robotics and Automation, and More), and Geography (North America, Europe, Asia-Pacific, South America, and More). The Market Forecasts are Provided in Terms of Value (USD).

Global Edge AI GPU Market Trends and Insights

Proliferation of IoT Devices Requiring Low-Latency AI Processing

The global installed base of IoT endpoints needing on-device inference surpassed 15 billion units in 2025, forcing enterprises to abandon cloud-centric workflows. Round-trip latency of 80-120 milliseconds is incompatible with closed-loop robotics, surgical equipment, and industrial process control. Deploying GPU inference at the sensor collapses latency to under 5 milliseconds and cuts cycle times for collaborative robots by 40% in ABB field trials. Vendors now build 5 nm SoCs with dynamic voltage scaling to keep power under 15 watts, aligning with fanless industrial designs. The trend materially expands addressable edge AI GPU market demand across automotive lines, medical devices, and smart utilities.

Rapid Deployment of 5G Enhancing Edge Bandwidth

Standalone 5G deployments expanded significantly by mid-2025, enabling network slices that deliver sub-10-millisecond paths for edge inference. South Korean operators completed nationwide rollouts in 2024, supporting more than 2,000 GPU nodes at Seoul's Guro Digital Complex for real-time quality inspection. The European Union earmarked EUR 900 million (USD 1.01 billion) in 2025 to seed similar deployments, compelling carriers to co-locate GPU servers at base-station shelters. While the USD 150,000 CAPEX per standalone cell remains high in emerging economies, the value proposition for latency-sensitive analytics is now proven, widening the adoption of edge AI GPUs in telecom ecosystems.

High Power Consumption and Thermal Constraints of GPUs

Discrete GPUs drawing 75 watts generate 256 BTU per hour, overwhelming sealed IP65 enclosures. Vendors down-clock silicon, cutting throughput by up to 20% versus lab ratings, which narrows the advantage over sub-5-watt neural processors. Intel launched a 50-watt Arc A380E variant in 2025, but it faces NVIDIA's 30-watt Orin NX in cost-sensitive segments. European industrial sites pay EUR 95 (USD 107) in annual power for each 75-watt node, a charge that multiplies across 500-plus installations. Battery-powered field sensors, therefore, bypass GPUs for hybrid architectures, capping near-term edge AI GPU market penetration in ultra-low-power edge niches.

Other drivers and restraints analyzed in the detailed report include:

1. Rising Demand for Real-Time Video Analytics in Smart Cities
2. Growing Adoption of Autonomous Mobile Robots in Manufacturing
3. Supply-Chain Shortages of Advanced Packaging Capacity

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

Segment Analysis

Integrated GPUs held 61.59% share of the edge AI GPU market size in 2025, reflecting design wins in point-of-sale terminals, industrial HMI screens, and automotive infotainment. Snapdragon 8 Gen 3 and Dimensity 9300 SoCs fall within the 5-15 watt envelope, ideal for fanless chassis. Discrete GPUs, although smaller in volume, are expanding at a 38.48% CAGR to support 4K video analytics streams that require 12 TFLOPS at 30 FPS. Apple's 40-core M3 Max blurred category lines by packing 65 TFLOPS into an integrated form factor, rivaling entry discrete cards. European Ecodesign labeling, effective from 2024, privileges integrated silicon in public procurements, further anchoring this segment within the broader edge AI GPU market.

Discrete devices still dominate where raw parallelism trumps power limits. An RTX A2000 at 70 watts offers 26 TFLOPS, doubling real-time detections per camera in municipal traffic analytics. As transformer-based vision models swell past 100 million parameters, discrete SKUs with dedicated tensor cores accelerate uptake in factories and smart cities. Heterogeneous roadmaps now see SoCs stacking extra GPU tiles, converging the performance vectors of integrated and discrete solutions.

Geography Analysis

Asia-Pacific held 66.71% of the edge AI GPU market share in 2025 and is projected to grow at 38.83% CAGR to 2031. China ordered 800,000 GPU-ready nodes for smart-city programs under the New Infrastructure campaign. Japan budgeted JPY 50 billion (USD 340 million) in subsidies for small and medium manufacturers upgrading to edge AI. South Korea shipped 45,000 collaborative robots with GPU inference in 2025. India's mission aims to deploy 10,000 GPU nodes by 2027 across the agriculture and health sectors.

North America ranks second. The U.S. Department of Energy funded USD 450 million in grid-edge analytics pilots in 2025, installing GPU nodes at substations. Canadian auto plants used GPUs for welding vision-guidance and defect trimming. Europe's GDPR data-minimization principle directs enterprises toward local GPUs, and Germany's automakers cut downtime by 25% through predictive maintenance.

South America's share is smaller but rising as Brazilian farms and Chilean mines adopt GPU-based remote sensing. The Middle East and Africa are seeing early smart-city deployments in Dubai, including 5,000 GPU nodes for traffic analytics. Export-control rules limit shipments to Russia and select markets, modestly tempering wider geographic uptake of the edge AI GPU market.

1. NVIDIA Corporation
2. Intel Corporation
3. Advanced Micro Devices Inc.
4. Qualcomm Technologies Inc.
5. Huawei Technologies Co. Ltd.
6. Samsung Electronics Co. Ltd.
7. Apple Inc.
8. MediaTek Inc.
9. Dell Technologies Inc.
10. Hewlett Packard Enterprise Co.
11. Lenovo Group Ltd.
12. Super Micro Computer Inc.
13. ADLINK Technology Inc.
14. Advantech Co. Ltd.
15. Hailo Technologies Ltd.
16. Kneron Inc.

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 Proliferation of IoT Devices Requiring Low-Latency AI Processing
  • 4.2.2 Rapid Deployment of 5G Enhancing Edge Bandwidth
  • 4.2.3 Rising Demand for Real-Time Video Analytics in Smart Cities
  • 4.2.4 Growing Adoption of Autonomous Mobile Robots in Manufacturing
  • 4.2.5 Regulatory Push for Data Privacy Favouring On-Device Processing
  • 4.2.6 Emergence of Cold-Chain Edge Nodes in Pharmaceutical Logistics
• 4.3 Market Restraints
  • 4.3.1 High Power Consumption and Thermal Constraints of GPUs
  • 4.3.2 Supply-Chain Shortages of Advanced Packaging Capacity
  • 4.3.3 Skills Gap in Deploying Containerised GPU Stacks at Edge Sites
  • 4.3.4 Regulatory Export Controls Limiting GPU Availability
• 4.4 Industry Value-Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Impact of Macroeconomic Factors on the Market
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Threat of New Entrants
  • 4.8.2 Bargaining Power of Suppliers
  • 4.8.3 Bargaining Power of Buyers
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By GPU Type
  • 5.1.1 Integrated GPUs
  • 5.1.2 Discrete GPUs
• 5.2 By Deployment Type
  • 5.2.1 Edge Servers / Gateways
  • 5.2.2 Embedded Edge Devices
• 5.3 By Application
  • 5.3.1 Video Analytics and Surveillance
  • 5.3.2 Industrial AI
  • 5.3.3 Robotics and Automation
  • 5.3.4 Healthcare AI
• 5.4 By Geography
  • 5.4.1 North America
    • 5.4.1.1 United States
    • 5.4.1.2 Canada
    • 5.4.1.3 Mexico
  • 5.4.2 Europe
    • 5.4.2.1 Germany
    • 5.4.2.2 United Kingdom
    • 5.4.2.3 France
    • 5.4.2.4 Italy
    • 5.4.2.5 Rest of Europe
  • 5.4.3 Asia-Pacific
    • 5.4.3.1 China
    • 5.4.3.2 Japan
    • 5.4.3.3 South Korea
    • 5.4.3.4 India
    • 5.4.3.5 Southeast Asia
    • 5.4.3.6 Rest of Asia-Pacific
  • 5.4.4 South America
  • 5.4.5 Middle East
  • 5.4.6 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, Products and Services, Recent Developments)
  • 6.4.1 NVIDIA Corporation
  • 6.4.2 Intel Corporation
  • 6.4.3 Advanced Micro Devices Inc.
  • 6.4.4 Qualcomm Technologies Inc.
  • 6.4.5 Huawei Technologies Co. Ltd.
  • 6.4.6 Samsung Electronics Co. Ltd.
  • 6.4.7 Apple Inc.
  • 6.4.8 MediaTek Inc.
  • 6.4.9 Dell Technologies Inc.
  • 6.4.10 Hewlett Packard Enterprise Co.
  • 6.4.11 Lenovo Group Ltd.
  • 6.4.12 Super Micro Computer Inc.
  • 6.4.13 ADLINK Technology Inc.
  • 6.4.14 Advantech Co. Ltd.
  • 6.4.15 Hailo Technologies Ltd.
  • 6.4.16 Kneron Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment