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

According to Mordor Intelligence, the europe data center GPU market is expected to grow from USD 10.62 billion in 2026 to USD 19.42 billion by 2031, at a 12.83% CAGR over 2026-2031.

This report is Segmented by Deployment Type (Cloud Data Centers, and More), GPU Type (Training GPUs and Inference GPUs), Interconnect (PCIe-Based GPUs and High-Bandwidth Interconnect GPUs), Workload Type (AI and ML, HPC, and More), End-User (Hyperscalers/CSPs, Enterprises, and More), and by Country (Germany, United Kingdom, France, Italy, and More). The Market Forecasts are Provided in Value (USD).

Europe Data Center GPU Market Trends and Insights

Accelerating Demand for AI Model Training Capacity Across European Hyperscale Campuses

Hyperscale operators are commissioning GPU clusters with more than 10,000 accelerators to meet the compute intensity of foundation-model training, with deployments in Munich, Paris, and the Nordic states pushing regional exascale thresholds. Flexible power contracts and low-carbon grids attract capital to Northern Europe, while sovereign-cloud rules in Germany and France ensure that a sizeable share of this capacity remains domestically controlled. The scale of these clusters necessitates high-bandwidth fabrics such as NVLink 6, which reduces all-reduce latency and keeps GPU utilization above 90%. Collectively, these investments expand the addressable market for complementary interconnects, cooling systems, and on-premises AI services, boosting the European data center GPU market. However, they also magnify exposure to advanced packaging bottlenecks, compelling operators to secure multi-vendor contracts to hedge supply risk.

Growing Adoption of GPU-Powered Analytics Platforms in Financial Services and Telecom Sectors

Banks and carriers are embedding GPUs into fraud-detection, risk-modeling, and network-optimization pipelines, trimming inference times from minutes to milliseconds. Deutsche Bank, ING, Vodafone, and Orange each reported double-digit latency improvements after migrating analytical workloads to GPU clusters, validating the return on investment for accelerator upgrades. The surge of transactional and telemetry data streaming through European networks necessitates real-time processing, which CPU-only platforms cannot sustain cost-effectively. As a result, the Europe data center GPU market benefits from recurring hardware refresh cycles, software stack integrations, and managed service offerings tailored to regulated industries. Vendor support for open-source frameworks further lowers adoption barriers, allowing smaller institutions to harness GPU acceleration without proprietary lock-in.

Supply Chain Concentration Risk Around Advanced Packaging in Taiwan and South Korea

CoWoS and HBM3e capacity constraints extend delivery lead times for flagship GPUs beyond 50 weeks, disrupting rollout schedules for European cloud and research projects. Samsung and SK hynix prioritize larger North American contracts, compelling EU operators to consider alternative vendors or older GPU SKUs. The shortage inflates spot-market pricing, narrowing project margins and delaying revenue recognition across the Europe data center GPU market. Contingency actions, such as dual-sourcing strategies and inventory buffers, partially mitigate risk but add working-capital burdens.

Other drivers and restraints analyzed in the detailed report include:

1. EU Green Deal Incentives Pushing Energy-Efficient GPU Upgrades in Data Centers
2. Rising Uptake of Sovereign Cloud Initiatives Requiring On-Prem GPU Clusters
3. High Electricity Prices in Key European Colocation Hubs Denting TCO Economics

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

Segment Analysis

Edge facilities contributed a modest slice of 2025 revenue, yet are projected to outpace the Europe data center GPU market average with a 14.66% CAGR. Rapid adoption stems from autonomous-vehicle telemetry, industrial IoT sensor fusion, and augmented-reality streaming, all of which require under 10 ms round-trip latency. Cloud campuses retained 55.67% of turnover in 2025, reflecting hyperscale training clusters and multi-tenant inference farms anchored in Germany and France. Enterprises and private clouds fill the remainder, driven by compliance mandates favoring on-prem GPUs for sensitive financial and healthcare data.

Edge deployments benefit from micro-modular designs, fanless liquid cooling, and real-time orchestration stacks that push inference closer to subscribers. Telcos deploy GPU-enabled nodes at 5G base stations to dynamically slice bandwidth, while retail chains pilot in-store computer vision systems to enhance shopper analytics. Cloud providers respond by offering distributed inference services, creating hybrid architectures that span central campuses and regional aggregation points. This decentralized pattern expands the addressable market for Europe data center GPU markets beyond metropolitan hubs, unlocking opportunities for specialized integrators and carrier-neutral exchanges.

Training GPUs accounted for 59.87% of 2025 sales because multi-rack clusters powered foundation-model development, but inference accelerators are forecast to post a 14.78% CAGR as enterprises shift budgets toward production deployment. NVIDIA's L40S and L4 attract edge and enterprise buyers seeking high performance per watt for chatbots and fraud detection. AMD's MI300X provides a lower-cost path for both training and inference at CoreWeave and Lambda Labs sites in Frankfurt and Paris.

Banks now channel most incremental capex toward inference, allocating memory-rich GPUs that handle millions of transactions per second without network round-trips to cloud campuses. Telecom operators prioritize latency and energy efficiency, selecting accelerators with on-package networking to minimize PCIe overhead. Training remains mission-critical for hyperscalers and research institutes, but its proportional share declines as mature models age into inference-heavy life-cycle phases.

List of Companies Covered in this Report:

1. NVIDIA Corporation
2. Advanced Micro Devices Inc.
3. Intel Corporation
4. Samsung Electronics Co. Ltd.
5. International Business Machines Corporation
6. Atos SE
7. Inspur Group Co. Ltd.
8. Hewlett Packard Enterprise Company
9. Dell Technologies Inc.
10. Lenovo Group Limited
11. Giga Computing Technology Co. Ltd.
12. Graphcore Ltd.
13. OVH Groupe SAS

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 Accelerating demand for AI model training capacity across European hyperscale campuses
  • 4.2.2 Growing adoption of GPU-powered analytics platforms in financial services and telecom sectors
  • 4.2.3 EU Green Deal incentives pushing energy-efficient GPU upgrades in data centers
  • 4.2.4 Rising uptake of sovereign cloud initiatives requiring on-prem GPU clusters
  • 4.2.5 Emergence of liquid-cooling retrofits enabling higher GPU rack densities
  • 4.2.6 Proliferation of synthetic data generation startups driving burst GPU leasing
• 4.3 Market Restraints
  • 4.3.1 Supply chain concentration risk around advanced packaging in Taiwan and South Korea
  • 4.3.2 High electricity prices in key European colocation hubs denting TCO economics
  • 4.3.3 Emerging EU chip-sovereignty rules complicating cross-border GPU fleet sharing
  • 4.3.4 Growing scrutiny over water usage for liquid-cooled GPU farms in drought-prone regions
• 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 Industry Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Deployment Type
  • 5.1.1 Cloud Data Centers
  • 5.1.2 Enterprise / Private Data Centers
  • 5.1.3 Edge Data Centers
• 5.2 By GPU Type
  • 5.2.1 Training GPUs
  • 5.2.2 Inference GPUs
• 5.3 By Interconnect
  • 5.3.1 PCIe-Based GPUs
  • 5.3.2 High-Bandwidth Interconnect GPUs
• 5.4 By Workload Type
  • 5.4.1 Artificial Intelligence (AI) and Machine Learning (ML)
  • 5.4.2 High-Performance Computing (HPC) (non-AI scientific computing)
  • 5.4.3 Data Analytics (database acceleration, query processing)
  • 5.4.4 Graphics and Visualization (VDI, rendering, digital twins)
• 5.5 By End-User
  • 5.5.1 Hyperscalers / Cloud Service Providers
  • 5.5.2 Enterprises
  • 5.5.3 Government and Research Institutions
• 5.6 By Country
  • 5.6.1 Germany
  • 5.6.2 United Kingdom
  • 5.6.3 France
  • 5.6.4 Italy
  • 5.6.5 Rest of Europe

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 Samsung Electronics Co. Ltd.
  • 6.4.5 International Business Machines Corporation
  • 6.4.6 Atos SE
  • 6.4.7 Inspur Group Co. Ltd.
  • 6.4.8 Hewlett Packard Enterprise Company
  • 6.4.9 Dell Technologies Inc.
  • 6.4.10 Lenovo Group Limited
  • 6.4.11 Giga Computing Technology Co. Ltd.
  • 6.4.12 Graphcore Ltd.
  • 6.4.13 OVH Groupe SAS

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment