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GPU Accelerator Card - Market Size, Share, Trends, and Growth Forecasts, 2026-2031 | AI Infrastructure Investment to Propel the Market to USD 74.86 Billion by 2031

globenewswire.com
NVDA NVIDIA is a key player in the GPU accelerator card market, with its H100 units integrated into major systems. The company benefits from strong demand driven by AI, ML, and HPC workloads, and holds multiyear allocations for critical components. Its proprietary NVLink technology also supports specialized demand. AMD AMD is mentioned as a holder of multiyear allocations for critical GPU components, indicating its significant role in the market. The company is positioned to benefit from the growing demand for AI and HPC workloads, and its products like Radeon Instinct are relevant. INTC Intel is listed as a company holding multiyear allocations for critical GPU components. While mentioned in the context of supply chain dynamics, the article doesn't provide specific details on its market performance or future outlook within the GPU accelerator card sector. MU Micron is identified as a key supplier of HBM (High Bandwidth Memory), which is crucial for GPU accelerator cards. The article highlights the growing demand for HBM and its significant market revenue share, positioning Micron favorably. QCOM Qualcomm is listed as a company in the competitive landscape. While it operates in related technology areas, the article does not provide specific details about its current or future involvement in the GPU accelerator card market. DELL Dell Technologies is mentioned as a company in the competitive landscape. The article does not provide specific details about its current or future involvement in the GPU accelerator card market, beyond its role as a potential hardware provider. HPE Hewlett Packard Enterprise is listed as a company in the competitive landscape. The article does not provide specific details about its current or future involvement in the GPU accelerator card market, beyond its role as a potential hardware provider. SMCI Super Micro Computer is mentioned as a company in the competitive landscape. The article does not provide specific details about its current or future involvement in the GPU accelerator card market, beyond its role as a potential hardware provider.

GPU Accelerator Card - Market Size, Share, Trends, and Growth Forecasts, 2026-2031 | AI Infrastructure Investment to Propel the Market to USD 74.86 Billion by 2031 Dublin, Oct. 27, 2026 (GLOBE NEWSWIRE) -- "GPU Accelerator Card - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026-2031)" has been added to ResearchAndMarkets.com's offering.

The global GPU accelerator card market is projected to expand from USD 29.18 billion in 2025 to USD 35.23 billion in 2026, reaching USD 74.86 billion by 2031. The market is expected to register a CAGR of 20.74% from 2026 to 2031, supported by rapid growth in artificial intelligence, machine learning, cloud gaming, generative AI, and high-performance computing workloads.

AI and Machine Learning Workloads Drive Market Growth

Expanding AI model sizes and rising computational requirements are transforming demand for GPU accelerator cards. Model parameter counts have increased from 1.8 trillion to more than 10 trillion, requiring clusters with over 100,000 accelerators and interconnect fabrics exceeding 400 Gbps per GPU. Frontier systems at U.S. national laboratories now integrate more than 28,000 NVIDIA H100 units, while hyperscalers each invested over USD 70 billion in AI capacity expansion during 2025.

AI training jobs require sustained utilization near 90%, changing total cost-of-ownership calculations and encouraging long multi-year hardware procurement pipelines. With pre-training expenses exceeding USD 100 million per run, advanced AI development is increasingly concentrated among capital-intensive organizations. This trend is strengthening demand for premium GPU accelerator cards, maintaining elevated average selling prices and extending supply constraints.

Cloud Gaming and Streaming Expand Accelerator Deployment

Cloud gaming revenue reached USD 8.5 billion in 2025 as leading platforms moved toward 4 K gaming at 240 fps with sub-40 ms latency. Providers face significant evening demand peaks, creating three-to-one utilization swings. To improve infrastructure efficiency, many operators redirect overnight capacity toward generative AI inference, increasing asset utilization from approximately 35% to 65%.

Latency requirements below 50 ms are also encouraging investment in edge data centers located closer to end users. This shift supports demand for compact, passively cooled accelerator cards capable of reliable remote operation. As competitive esports and high-resolution gaming increasingly move to cloud platforms, service providers are expected to shorten hardware refresh cycles to improve performance and reduce customer churn.

Advanced Substrate and HBM Supply Remain Key Constraints

Persistent supply chain limitations continue to affect GPU accelerator card availability. Ajinomoto Build-up Film substrates are fully booked through 2027, with lead times extending to 52 weeks. NVIDIA, AMD, and Intel hold multiyear allocations from a limited group of Taiwanese and Korean suppliers, reducing availability for smaller market participants. Substrates account for up to one-fifth of a board's bill of materials, meaning price increases directly affect finished accelerator card costs.

HBM represented 84% of market revenue in 2025, supported by supply from SK Hynix, Samsung, and Micron. Each HBM3e stack delivers 1.15 TB/s, while leading accelerators combine eight or more stacks to provide approximately 8 TB/s of aggregate bandwidth. Buyers continue to accept the 8x premium over GDDR6 because AI model sizes are growing faster than conventional semiconductor performance gains.

GDDR-based cards retained a 16% share, serving workstations and edge inference applications where cost per GB is more important than peak bandwidth. HBM4 is scheduled for 2027 and is expected to deliver 2 TB/s per stack. However, initial unit costs are likely to remain high, while new capacity in South Korea and the United States may not reach volume production until 2028.

OAM Modules Gain Momentum While PCIe Maintains Market Leadership

PCIe add-in cards accounted for 52% of GPU accelerator card revenue in 2025, reflecting strong enterprise demand for hot-swappable hardware and flexible server upgrades. OAM modules are forecast to grow at a 21.34% CAGR from 2026 to 2031 as hyperscalers prioritize higher density and improved energy efficiency.

OAM architectures allow operators to install 72 accelerators drawing 1.4 MW within a 42U rack, reducing floor-space requirements by 40% compared with PCIe equivalents. Direct-liquid-cooled OAM systems can support 700-W GPUs while improving power efficiency by 25%. SXM modules held a 28% share and are expected to retain specialized demand among customers seeking proprietary NVLink bandwidth.

Regional GPU Accelerator Card Market Outlook

North America generated 46% of global revenue in 2025, driven by hyperscaler spending exceeding USD 300 billion. The region is projected to grow at a 19.8% CAGR, with grid interconnection delays and power permitting challenges limiting data center expansion. Canada is attracting new facilities through hydro-powered infrastructure, while U.S. export restrictions on advanced GPU sales to China are redirecting demand toward the domestic market.

Asia-Pacific is forecast to record the fastest regional CAGR at 21.82%. Japan allocated JPY 4 trillion, or USD 26 billion, to AI research infrastructure, while India's INR 103.07 billion initiative is expected to add 10,000 GPUs. Singapore is targeting 50 PFLOPS through a USD 500 million development program. China shipped USD 8 billion in domestically produced accelerators during 2025, while South Korea remains strategically important due to its leadership in HBM production.

Europe held an 18% market share in 2025, supported by EuroHPC investments in Germany, Italy, and Spain. Regional sustainability requirements are increasing demand for energy-efficient GPU infrastructure. South America and the Middle East and Africa collectively represented 8% of revenue, with investment supported by sovereign wealth funds in Brazil, the United Arab Emirates, and Saudi Arabia. Although power capacity and workforce shortages remain barriers, infrastructure upgrades could support stronger growth after 2028.

Key Topics Covered:

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 Explosive Growth in AI and Machine Learning Training Workloads

4.2.2 Surging Adoption of Cloud Gaming and Streaming Platforms

4.2.3 Accelerated Enterprise Roll-outs of Generative AI Applications

4.2.4 Rising Demand for High-Performance Computing in Academia and Government

4.2.5 EU Sustainability Rules Accelerating Procurement of Energy-Efficient GPUs

4.2.6 Open Accelerator Module (OAM) Standard Enabling Multi-Vendor Interoperability

4.3 Market Restraints

4.3.1 Persistent Supply Chain Constraints in Advanced Substrates

4.3.2 High Total Cost of Ownership of Datacenter GPU Infrastructure

4.3.3 HBM Capacity Bottlenecks Limiting Board-Level Memory Expansion

4.3.4 Export-Control Restrictions Curtailing Cross-Border GPU Shipments

4.4 Impact of Macroeconomic Factors on the Market

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 Form Factor

5.1.1 PCIe Add-In Cards

5.1.2 SXM / Mezzanine

5.1.3 OAM

5.2 By Memory Type

5.2.1 HBM

5.2.2 GDDR

5.3 By Cooling

5.3.1 Passive

5.3.2 Active

5.4 By Deployment

5.4.1 Data Center / Server

5.4.2 Workstation

5.4.3 Edge / Embedded

5.5 By Industry Vertical

5.5.1 Cloud Service Providers

5.5.2 Enterprise IT

5.5.3 Government and Research

5.5.4 Media and Entertainment

5.5.5 Automotive / Edge AI

5.6 By Geography

5.6.1 North America

5.6.1.1 United States

5.6.1.2 Canada

5.6.1.3 Mexico

5.6.2 Europe

5.6.2.1 United Kingdom

5.6.2.2 Germany

5.6.2.3 France

5.6.2.4 Rest of Europe

5.6.3 Asia-Pacific

5.6.3.1 China

5.6.3.2 Japan

5.6.3.3 India

5.6.3.4 South Korea

5.6.3.5 Rest of Asia Pacific

5.6.4 South America

5.6.5 Middle East and 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 Advanced Micro Devices, Inc.

6.4.3 Intel Corporation

6.4.4 Huawei Technologies Co., Ltd. (Ascend Series)

6.4.5 Graphcore Ltd.

6.4.6 Tenstorrent Inc.

6.4.7 Qualcomm Technologies, Inc.

6.4.8 Samsung Electronics Co., Ltd.

6.4.9 Alibaba Group Holding Limited (T-Head)

6.4.10 Baidu, Inc. (Kunlun)

6.4.11 Cerebras Systems Inc.

6.4.12 Advanced Micro Devices, Inc. (Xilinx VCK, Radeon Instinct)

6.4.13 Giga Computing Technology Co., Ltd.

6.4.14 Mellanox Technologies Ltd. (NVIDIA Networking)

6.4.15 Broadcom Inc.

6.4.16 ASUStek Computer Inc.

6.4.17 Dell Technologies Inc.

6.4.18 Hewlett Packard Enterprise Company

6.4.19 Lenovo Group Limited

6.4.20 Super Micro Computer, Inc.

6.4.21 Inspur Group Co., Ltd.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

7.1 White-Space and Unmet-Need Assessment

For more information about this report visit https://www.researchandmarkets.com/r/8r2drd

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