산업용 GPU : 시장 점유율 분석, 업계 동향과 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the industrial GPU market size is expected to increase from USD 4.32 billion in 2025 to USD 5.18 billion in 2026 and reach USD 12.09 billion by 2031, growing at a CAGR of 18.47% over 2026-2031.

This report is Segmented by GPU Architecture (Discrete GPU Accelerators, and More), Hardware Form Factor (PCIe Add-In Cards, and More), Application (Machine Vision and Quality Vision, Robotics and Autonomous Material Handling, and More), End-User Industry (Manufacturing, Logistics and Warehousing, Healthcare and Life Sciences, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Industrial GPU Market Trends and Insights

Rising Edge AI Inference Demand in Industrial Automation

The industrial GPU market is being reshaped by the movement of AI inference from centralized computing environments to production lines, inspection stations, and autonomous mobile systems. Physical AI workloads now combine visual reasoning, sensor fusion, and machine coordination, which places parallel processing at the center of industrial compute design. NVIDIA positioned IGX Thor for industrial and medical edge deployments with real-time physical AI capabilities, showing how the industrial GPU market is shifting toward purpose-built edge platforms rather than adapted data center hardware. Cognex reinforced this direction in April 2026, when it launched the In-Sight 6900 Vision Controller powered by NVIDIA Jetson technology for edge AI inspection workloads. As deployments move closer to the line, buyers are treating GPU-based edge systems as core industrial infrastructure, not as temporary pilot tools, which supports longer, deeper procurement cycles across the industrial GPU market.

Increasing Adoption of Discrete GPUs in High-Throughput Industrial Workloads

Discrete accelerators remain central to the industrial GPU market because they let operators add compute capacity without replacing qualified server and industrial PC platforms. This modular path matters in retrofits, where every system change can trigger cost, downtime, and compliance work that plant teams try to avoid. Advantech supported this model in January 2026 with MIC-78 Series expansion modules for the MIC-780 modular industrial computer, including a PCIe Gen 5 GPU module for edge AI inference and machine vision up to 250W. The company extended that push in March 2026 with mass production of the SKY-MXM series based on NVIDIA RTX PRO Blackwell Embedded GPUs for compact, real-time, AI-intensive industrial systems. These launches show that the industrial GPU market is still rewarding form factors that combine upgrade flexibility, installed-base compatibility, and support for high-throughput inspection and simulation tasks.

High Thermal and Power Constraints in Rugged Industrial Environments

Thermal and power limits continue to hold back part of the industrial GPU market because many industrial environments were not built for data center-class accelerator profiles. Premio noted that industrial systems often operate over wide temperature ranges, in sealed enclosures, and under dust and vibration, all of which reduce usable headroom for high-performance GPU hardware. The same source also pointed to dust-related cooling losses that can degrade thermal performance over time, increasing the risk of throttling and shorter component lifespans in harsh deployments. This creates a design gap between the power draw of advanced AI accelerators and the lower thermal envelope that many rugged platforms can sustain. The industrial GPU market, therefore, continues to depend on specialized embedded systems, fanless designs, and careful workload balancing when deployments move beyond climate-controlled facilities.

Other drivers and restraints analyzed in the detailed report include:

1. Growing Deployment of Digital Twins and Simulation in Smart Factories
2. Expanding Use of Functional-Safety-Ready GPU Platforms in Robotics
3. Long Validation Cycles For Safety-Critical Industrial Deployments

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

Segment Analysis

Discrete GPU accelerators held a 43.84% share of the industrial GPU market in 2025, making them the leading architecture for line-side AI servers and rack-mounted edge systems. Their position reflects the practical advantage of modular upgrades, broad PCIe compatibility, and the ability to fit into existing industrial compute environments without a full redesign. In many brownfield plants, that flexibility reduces disruption and makes it easier to expand visual inspection, simulation, and AI control capacity in stages. The industrial GPU market still rewards that approach because many operators prefer incremental performance additions over full platform replacement. Even so, the segment is no longer defined solely by raw accelerator cards, as buyers increasingly evaluate power envelope, lifecycle support, and software integration simultaneously.

GPU-enabled heterogeneous edge SoCs are projected to expand at a 19.42% CAGR through 2031, indicating a faster shift toward compact integration at the edge. These devices combine a GPU, an NPU, image processing, and safety support into a single package that fits more easily into low-power industrial enclosures than larger discrete systems. AMD moved into this direction in January 2026 with the Ryzen AI Embedded P100 Series, which combined Zen 5 CPU cores, a 50-TOPS XDNA 2 NPU, and integrated Radeon graphics for machine vision IPCs, autonomous mobile robots, and 3D medical imaging. Integrated GPU processors and APUs remain important for supervisory visualization, HMI, and lighter inference tasks where capital budgets and thermal limits are tighter. Across the industrial GPU market, this mix shows that discrete systems still anchor performance-heavy use cases, while compact SoC designs are accelerating wherever deployment density, power control, and simplified qualification matter more.

PCIe add-in cards accounted for 36.42% of the market share in 2025, making them the largest hardware form factor in the industrial GPU market. Their strength lies in compatibility with existing industrial servers and the straightforward upgrade path they offer for rack-level machine vision, AI analytics, and simulation tasks. This is especially valuable in sites that want to raise compute density without changing the surrounding system architecture. Advantech's January 2026 MIC-78 GPU expansion module and its March 2026 SKY-MXM launch both showed continued investment in modular accelerator paths for industrial computing. That pattern suggests the industrial GPU market still depends heavily on standards-based cards where serviceability and installed-base fit remain high priorities.

SoMs and CoMs are projected to grow at a 19.64% CAGR through 2031, which makes them the fastest-growing form factor in the industrial GPU market. OEMs are moving toward standardized modules because they shorten development cycles and allow hardware refresh with less redesign effort than fully custom boards. Advantech's March 2026 rollout of GPU-rich embedded modules for compact industrial systems reflected that move toward higher density within tighter space envelopes. MXM and mezzanine graphics modules continue to serve rugged and transit-oriented applications where soldered-down interconnect stability matters, while single-board computers and carrier-board solutions stay relevant for cameras, gateways, and low-power edge nodes. Soldered-down GPU and SoC designs also have a place in high-volume products where bill-of-materials control and compact packaging matter more than field replaceability, broadening the form-factor spread across the industrial GPU market.

Complete Report Scope:

• By GPU Architecture
  • Discrete GPU Accelerators
  • Integrated GPU Processors and APUs
  • GPU-Enabled Heterogeneous Edge SoCs
• By Hardware Form Factor
  • PCIe Add-In Cards
  • MXM and Mezzanine Graphics Modules
  • System-on-Modules and Computer-on-Modules
  • Single-Board Computers and Embedded GPU Carrier Boards
  • Soldered-Down GPU/SoC Solutions
• By Application
  • Machine Vision and Quality Inspection
  • Robotics and Autonomous Material Handling
  • Digital Twin and Industrial Simulation
  • Industrial HMI and Visualization
  • Edge AI Analytics and Predictive Maintenance
  • Medical and Critical Imaging
• By End-User Industry
  • Manufacturing
  • Logistics and Warehousing
  • Healthcare and Life Sciences
  • Energy and Utilities
  • Aerospace and Defense
  • Other End-User Industries
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • South Korea
    • India
    • Southeast Asia
    • Rest of Asia-Pacific
  • South America
  • Middle East and Africa

Geography Analysis

Asia-Pacific held 46.63% share of the industrial GPU market size in 2025 and is projected to expand at a 19.38% CAGR through 2031. The region remains the largest deployment base because it combines dense electronics manufacturing, automotive production, semiconductor capacity, and aggressive factory modernization programs. Japan added to that momentum in February 2026, when SmartVision introduced the EAC-7000 Series, powered by NVIDIA Jetson Thor, for next-generation edge AI robotics. Hitachi also stated in April 2026 that its edge AI semiconductor work had moved into implementation for manufacturing, inspection, robotics, and logistics hardware, with energy efficiency gains of more than 10 times compared with general-purpose GPU processing. These moves show why the industrial GPU market remains strongest in Asia-Pacific, where new factory programs and embedded hardware development continue to reinforce each other.

North America and Europe are the next two major regional clusters in the industrial GPU market, but their demand profiles differ from those in Asia-Pacific. North America benefits from a deep ecosystem around accelerated computing, robotics software, and simulation platforms that can be qualified across multiple industrial use cases. Europe places greater emphasis on safety-led procurement, especially in collaborative robotics, machine control, and regulated industrial environments, where stronger compliance pathways are required. NVIDIA's June 2025 industrial AI cloud initiative for European manufacturing highlighted how digital twin tools are being deployed across large manufacturing networks in the region. The industrial GPU market in both regions is therefore shaped less by sheer unit volume and more by certified deployment models, deep software integration, and long lifecycle platform support.

South America, the Middle East, and Africa remain smaller parts of the industrial graphics processing unit (GPU) market, but they matter because their use cases differ from the leading regions. In South America, mining, process industries, and distributed manufacturing sites create demand for predictive maintenance, machine vision, and edge systems that support remote support. In the Middle East and Africa, smart infrastructure, construction, logistics, and energy projects are creating early openings for GPU-enabled industrial automation. These markets are still developing, but they expand the industrial GPU market beyond climate-controlled factory settings and increase the need for rugged, power-aware, and deployment-specific hardware designs.

1. NVIDIA Corporation
2. Advanced Micro Devices, Inc.
3. Imagination Technologies Limited
4. Moore Threads Intelligent Technology (Beijing) Co., Ltd.
5. Biren Technology Co., Ltd.
6. VeriSilicon Microelectronics (Shanghai) Co., Ltd.
7. Zhaoxin Semiconductor Co., Ltd.
8. VIA Technologies, Inc.
9. UNISOC Technologies Co., Ltd.
10. Rockchip Electronics Co., Ltd.
11. Loongson Technology Corporation Limited
12. Matrox Electronic Systems Ltd.
13. ASPEED Technology Inc.
14. Qualcomm Incorporated
15. Huawei Technologies Co., Ltd.
16. Apple Inc.
17. Samsung Electronics Co., Ltd.
18. MediaTek Inc.
19. Renesas Electronics Corporation
20. NXP Semiconductors N.V.

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 Impact of Macroeconomic Factors on the Market
• 4.3 Market Drivers
  • 4.3.1 Rising Edge AI Inference Demand in Industrial Automation
  • 4.3.2 Increasing Adoption of Discrete GPUs in High-Throughput Industrial Workloads
  • 4.3.3 Growing Deployment of Digital Twins and Simulation in Smart Factories
  • 4.3.4 Expanding Use of Functional-Safety-Ready GPU Platforms in Robotics
  • 4.3.5 Rising Visualization Intensity in Machine Vision and Quality Inspection
  • 4.3.6 Increasing Software-Defined Industrial Compute Architectures
• 4.4 Market Restraints
  • 4.4.1 High Thermal and Power Constraints in Rugged Industrial Environments
  • 4.4.2 Long Validation Cycles for Safety-Critical Industrial Deployments
  • 4.4.3 Fragmented Software Portability Across GPU Ecosystems
  • 4.4.4 Supply Chain Volatility in Advanced Semiconductor Packaging
• 4.5 Industry Value Chain Analysis
• 4.6 Regulatory Landscape
• 4.7 Technological Outlook
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Bargaining Power of Suppliers
  • 4.8.2 Bargaining Power of Buyers
  • 4.8.3 Threat of New Entrants
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By GPU Architecture
  • 5.1.1 Discrete GPU Accelerators
  • 5.1.2 Integrated GPU Processors and APUs
  • 5.1.3 GPU-Enabled Heterogeneous Edge SoCs
• 5.2 By Hardware Form Factor
  • 5.2.1 PCIe Add-In Cards
  • 5.2.2 MXM and Mezzanine Graphics Modules
  • 5.2.3 System-on-Modules and Computer-on-Modules
  • 5.2.4 Single-Board Computers and Embedded GPU Carrier Boards
  • 5.2.5 Soldered-Down GPU/SoC Solutions
• 5.3 By Application
  • 5.3.1 Machine Vision and Quality Inspection
  • 5.3.2 Robotics and Autonomous Material Handling
  • 5.3.3 Digital Twin and Industrial Simulation
  • 5.3.4 Industrial HMI and Visualization
  • 5.3.5 Edge AI Analytics and Predictive Maintenance
  • 5.3.6 Medical and Critical Imaging
• 5.4 By End-User Industry
  • 5.4.1 Manufacturing
  • 5.4.2 Logistics and Warehousing
  • 5.4.3 Healthcare and Life Sciences
  • 5.4.4 Energy and Utilities
  • 5.4.5 Aerospace and Defense
  • 5.4.6 Other End-User Industries
• 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 Europe
    • 5.5.2.1 Germany
    • 5.5.2.2 United Kingdom
    • 5.5.2.3 France
    • 5.5.2.4 Italy
    • 5.5.2.5 Rest of Europe
  • 5.5.3 Asia-Pacific
    • 5.5.3.1 China
    • 5.5.3.2 Japan
    • 5.5.3.3 South Korea
    • 5.5.3.4 India
    • 5.5.3.5 Southeast Asia
    • 5.5.3.6 Rest of Asia-Pacific
  • 5.5.4 South America
  • 5.5.5 Middle East and Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Positioning 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 Advanced Micro Devices, Inc.
  • 6.4.3 Imagination Technologies Limited
  • 6.4.4 Moore Threads Intelligent Technology (Beijing) Co., Ltd.
  • 6.4.5 Biren Technology Co., Ltd.
  • 6.4.6 VeriSilicon Microelectronics (Shanghai) Co., Ltd.
  • 6.4.7 Zhaoxin Semiconductor Co., Ltd.
  • 6.4.8 VIA Technologies, Inc.
  • 6.4.9 UNISOC Technologies Co., Ltd.
  • 6.4.10 Rockchip Electronics Co., Ltd.
  • 6.4.11 Loongson Technology Corporation Limited
  • 6.4.12 Matrox Electronic Systems Ltd.
  • 6.4.13 ASPEED Technology Inc.
  • 6.4.14 Qualcomm Incorporated
  • 6.4.15 Huawei Technologies Co., Ltd.
  • 6.4.16 Apple Inc.
  • 6.4.17 Samsung Electronics Co., Ltd.
  • 6.4.18 MediaTek Inc.
  • 6.4.19 Renesas Electronics Corporation
  • 6.4.20 NXP Semiconductors N.V.

7 Market Opportunities and Future Outlook

• 7.1 White-Space and Unmet-Need Assessment