Data Center Accelerator Market to Reach USD 605.42 Billion by 2035 as Rack-Scale AI Systems and Inference Demand Accelerate Deployment - DC Market Insights
PR Newswire
PUNE, India, Oct. 9, 2026
Global market grows at 13.56% CAGR; rack-scale systems are projected to capture 61.8% of value by 2035 as hyperscaler and neocloud investment expands
PUNE, India, Oct. 9, 2026 /PRNewswire/ -- The "Data Center Accelerator Market - Growth, Share, Opportunities & Competitive Analysis, 2026-2035" report has been added to the DC Market Insights offering. The global Data Center Accelerator Market reached USD 169.77 billion in 2025 and is projected to reach USD 605.42 billion by 2035, registering a CAGR of 13.56%. The market is shifting from add-in accelerator cards toward tightly integrated rack-scale systems, while inference workloads and custom AI ASICs expand the supplier opportunity beyond training-focused GPUs.
Key Takeaways
- Operator capital expenditure approaching USD 750 billion is supporting an unprecedented build cycle for AI compute and accelerator-rich infrastructure.
- Rack-scale systems are projected to reach 61.8% of accelerator market value by 2035 as buyers purchase integrated compute, networking and cooling platforms.
- North America held 59.4% of the market in 2025, reflecting the concentration of hyperscalers, AI labs, neoclouds and leading accelerator suppliers.
- Inference accelerators are broadening competition because throughput, power efficiency and total cost per token create room for custom ASICs and specialized architectures.
- Export controls and geopolitical restrictions remain a material constraint for suppliers, affecting product mix and addressable demand in selected markets.
Scope & Segmentation - Data Center Accelerator Market
The report covers GPUs, custom AI ASICs, FPGAs and other accelerators deployed for AI training, AI inference, HPC, scientific computing, data analytics and video workloads. It also analyzes rack-scale systems, multi-accelerator baseboards and PCIe cards, HBM-based and non-HBM architectures and major end-user groups.
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"Accelerator demand is moving up the system stack. Buyers are no longer evaluating a chip in isolation; they are evaluating a rack, a network fabric, memory capacity and cooling as one performance envelope. That shift favors suppliers that can deliver integrated platforms, but inference also creates space for lower-cost custom architectures where economics matter more than absolute training performance." - Amit Jain, Senior Consultant, ICT & Emerging Technologies, DC Market Insights, report author |
Why This Report Matters
Accelerators are the largest value driver behind today's AI data center buildout. Their economics affect server design, network topology, liquid cooling, power density and the pace of campus construction. The report helps buyers and suppliers evaluate how accelerator type, form factor and workload mix change the total market opportunity.
Market Overview
DC Market Insights estimates the market increased from USD 9.61 billion in 2020 to USD 169.77 billion in 2025. Growth was driven by rapid scaling of hyperscale AI clusters and the transition from experimental deployments to production training and inference. The forecast assumes strong unit expansion but progressively slower average selling price growth as custom ASICs and more efficient inference architectures gain share.
Market Insights
Three forces define the next phase: rack-scale integration, supplier diversification and inference economics. Rack-scale platforms concentrate more value in integrated systems, while custom accelerators from cloud providers shift share away from a purely merchant model. At the same time, sovereign AI programs and neocloud providers are creating new channels for accelerator demand outside traditional hyperscalers.
Key Attributes
Attribute | Details |
Historical Market Size (2020) | USD 9.61 billion |
Market Size (2025) | USD 169.77 billion |
Forecast Market Size (2035) | USD 605.42 billion |
CAGR (2025-2035) | 13.56 % |
Leading Region / District | North America - 59.4% |
Base Year | 2025 |
Forecast Period | 2026-2035 |
Report Author | Amit Jain, Senior Consultant, ICT & Emerging Technologies |
Report Updated | Oct. 7, 2026 |
Segmentation
Accelerator Type: GPUs; Custom AI ASICs; FPGAs; Other Accelerators.
Workload: AI Training; AI Inference; HPC and Scientific Computing; Data Analytics; Video and Other.
Form Factor: Rack-Scale Systems; Multi-Accelerator Baseboards; PCIe Cards.
Memory: HBM-Based; Non-HBM.
End User: Hyperscale Cloud Providers; GPU Cloud and Neocloud Providers; Enterprises; Government, Sovereign AI and Research.
Regional Analysis
North America led the market in 2025 with 59.4% share. The full regional distribution was North America 59.4%; Asia Pacific 24.6%; Europe 9.2%; Middle East and Africa 4.9%; Latin America 1.9%. The regional outlook reflects differences in hyperscale investment, AI adoption, power availability, semiconductor or equipment ecosystems and local data center construction pipelines.
Competitive Landscape
NVIDIA remains the reference platform for large-scale AI training, while AMD is expanding through multiyear deployment agreements and hyperscalers continue to scale custom accelerators. Broadcom, Marvell and specialist suppliers are positioned around custom silicon and connectivity. The competitive field is therefore widening even as leading platforms retain strong ecosystem advantages.
Companies profiled: NVIDIA, AMD, Broadcom, Google (TPU), Amazon Web Services (Trainium), Microsoft (Maia), Intel, Marvell Technology, Huawei (Ascend), Qualcomm, Groq, Cerebras Systems, Cambricon Technologies and Alchip Technologies.
Recent Developments
- NVIDIA and OpenAI signed a letter of intent to deploy at least 10 GW of NVIDIA systems, with NVIDIA indicating potential investment of up to USD 100 billion as capacity is deployed.
- AMD and OpenAI announced a multiyear agreement covering 6 GW of AMD GPUs, starting with 1 GW of Instinct MI450 capacity in the second half of 2026.
- OpenAI and Broadcom agreed to deploy 10 GW of OpenAI-designed custom accelerators through 2029.
- Anthropic agreed to expand its use of Google Cloud TPUs to as many as one million chips, representing well over a gigawatt of capacity.
Full report: https://www.dcmarketinsights.com/report/data-center-accelerator-market
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