Graphics Processing Unit (GPU) Market Size & Share Analysis - Growth Trends and Forecast (2026 - 2031)

Global Graphics Processing Unit (GPU) Market Trends and Insights

Evolving Graphics Realism in AAA Gaming

Ray-tracing, neural rendering, and path-tracing have lifted compute requirements for blockbuster titles. Cyberpunk 2077 Phantom Liberty and Alan Wake 2 now recommend discrete GPUs with at least 12 GB VRAM to sustain native 4K at 60 fps. NVIDIA’s RTX 5090, released in January 2025, integrates 24,576 CUDA cores and 24 GB GDDR7 memory for 120 teraflops of shader throughput.^{[1]NVIDIA Corp., “RTX 5090 Launch,” NVIDIA Newsroom, nvidianews.nvidia.com} AMD’s RDNA 4 architecture, shipping in mid-2025, doubles floating-point throughput per clock and narrows the rasterization gap with NVIDIA. Console refresh cycles add momentum, as Sony’s PlayStation 5 Pro deploys a custom RDNA 3 GPU that sets new cross-platform baselines. Unreal Engine 5 features such as Nanite and Lumen further compress the lifespan of mid-range cards, accelerating replacement demand in the GPU market.

AR/VR and AI-Led Heterogeneous Computing Demand

Mixed-reality headsets combine CPU logic with dedicated GPU cores to maintain sub-12 ms motion-to-photon latency. Apple’s Vision Pro pairs an M2 chip with an R1 coprocessor to process 12 camera feeds and 5 LiDAR streams. Meta’s Quest 3 uses Snapdragon XR2 Gen 2 silicon to deliver 4K-per-eye rendering and has sold more than 15 million units through 2025. Enterprises extend these capabilities to surgical training and industrial maintenance, with Siemens deploying 10,000 VR workstations powered by NVIDIA RTX A6000 GPUs to reduce factory-layout prototyping costs by 30%. Cross-vendor frameworks such as oneAPI and ROCm simplify development, though API fragmentation still locks many creators into single-vendor ecosystems.

Generative-AI Model-Training GPU Intensity

Training models exceeding 100 billion parameters requires petaflop-scale clusters with multi-terabyte-per-second memory bandwidth. Meta’s 405-billion-parameter Llama 3.1 run trained on 16,384 H100 GPUs for 54 days. NVIDIA’s H200, shipping in late 2025, delivers 4.8 TB/s bandwidth and 141 GB HBM3e memory, cutting training time by 40% relative to H100. Hyperscalers also develop custom silicon, yet NVIDIA retains dominance in the GPU market because CUDA tools and FP8 precision remain unmatched. Efficiency gains from quantization and mixture-of-experts architectures are offset by multimodal model proliferation, sustaining demand for high-memory GPUs through 2031.

Sovereign-AI Datacenter Build-outs

Governments are pursuing domestic AI clusters to localize data and reduce their dependency on foreign clouds. Saudi Arabia allocated USD 40 billion in 2024 to build a 200,000-GPU complex supporting Arabic language models in the NEOM project. The UAE expanded its Falcon LLM program to 4,096 H100 GPUs in 2025. India, Japan, and others are launching similar initiatives that fragment global supply chains and accelerate domestic packaging capabilities.

High Upfront Capex and BOM Costs

Flagship datacenter GPUs exceed USD 3,000 bill-of-materials because HBM3 prices remain high and CoWoS interposer yields stay tight. Consumer cards feel similar inflation, NVIDIA’s RTX 5080 launched at USD 1,199 in January 2025, 20% above its predecessor. Many small enterprises postpone accelerator purchases or rent cloud GPUs, yet an 8-H100 cloud node still costs roughly USD 30,000 per month, making the economics unfavorable for long, continuous training runs.

Chronic Advanced-Node Supply Constraints

TSMC’s 3 nm and 5 nm fabs operated above 95% utilization in 2025, with Apple, NVIDIA, AMD, and Qualcomm signing multi-year allocations. Delivery times stretched to 12 months, forcing AIB partners to ration the issuance of discrete cards. Intel’s USD 43.5 billion fab build-out in Arizona and Ohio will not meaningfully ease the tightness until 2027, as Intel's 18A yields lag expectations.

Segment Analysis

By GPU Type: Discrete Accelerators Outpace Integrated Cores

Integrated GPUs commanded 54.81% of GPU market share in 2025, reflecting their inclusion in virtually every smartphone and entry-level laptop. Qualcomm’s Snapdragon 8 Gen 3 shipped in over 200 million devices, and Apple’s M4 chip improved performance-per-watt by 25% over M3.^{[2]Apple Inc., “M4 Chip Launch,” Apple Newsroom, apple.com} Despite this dominance, discrete accelerators such as NVIDIA’s H200 and AMD’s MI300X are growing at a 26.41% CAGR, lifting the discrete slice of the GPU market size for datacenter workloads. NVIDIA’s discrete datacenter GPU revenue hit USD 47.5 billion in fiscal 2025.  

Integrated designs minimize board cost and power draw, making them ideal for thin-and-light form factors. Intel’s Meteor Lake integrates Xe graphics for AV1 encoding, and Arm’s Immortalis-G720 brings variable-rate shading to mobile chips. Discrete GPUs dominate workloads that need sustained parallel throughput, including 8K video editing and AI model training, ensuring both segments grow in tandem within the broader GPU market.

Note: Segment shares of all individual segments available upon report purchase

By Device Application: Datacenters Eclipse Consumer Segments

Mobile devices and tablets held a 38.24% share of the GPU market in 2025 as smartphone shipments topped 1.2 billion. Qualcomm’s Snapdragon X Elite boosted Windows-on-Arm laptops, and Samsung’s Galaxy S25 featured RDNA-based graphics. Servers and data center accelerators, however, are the fastest-growing segment, expanding at a 27.78% CAGR as hyperscalers deployed more than 4 million GPUs in 2025.  

PCs and workstations benefit from AI PC initiatives that integrate NPUs, while gaming consoles maintain a modest share, pending the release of Nintendo’s next-generation Switch. Automotive use cases grow quickly as autonomous platforms, such as NVIDIA Drive Thor, integrate 2,000 TOPS of GPU compute. Edge devices, such as smart cameras, adopt low-power GPUs, broadening the addressable demand across the GPU market.

By Deployment Model: Cloud Dominance Reflects Capex Aversion

Cloud deployments captured 63.12% of the GPU market share in 2025 and are projected to rise at a 26.12% CAGR as organizations increasingly prefer pay-as-you-go models. AWS P5e instances featuring H200 GPUs cost USD 98.32 per hour and underpin large-scale training jobs. Google Cloud, Microsoft Azure, and Oracle Cloud follow suit with H100- and MI300X-based offerings that cut start-up times for AI projects.  

On-premise clusters remain vital where data residency or long training cycles result in a lower lifetime cost than cloud rental. JPMorgan installed a 1,024-GPU cluster to avoid egress fees. Hybrid orchestration enables firms to burst to the cloud during peaks, striking a balance between flexibility and budget within the GPU market.

By Instruction-Set Architecture: Arm Gains Ground in Power-Constrained Segments

Arm-based GPUs controlled 46.37% of the GPU market share in 2025 and are forecast to expand at a 26.15% CAGR through 2031. Smartphone dominance and Apple’s Mac transition fuel volume, while AWS Graviton4 servers pair Arm CPUs with discrete GPUs for inference tasks.  

x86-64 CPUs still anchor training clusters given CUDA lock-in and AVX-512 support. AMD’s MI300A combines Zen 4 CPU cores with CDNA 3 GPUs on a single package, serving exascale systems. RISC-V remains a niche technology but is growing in academia, where open instruction sets enable customization.

Geography Analysis

Asia Pacific led the GPU market with 44.71% revenue share in 2025, supported by China’s 700 million smartphone output and Taiwan’s foundry dominance. TSMC fabricated more than 80% of advanced-node GPU dies, supplying NVIDIA, AMD, Apple, and Qualcomm. Japan’s automotive tier-1 suppliers have integrated Drive Orin and Snapdragon Ride chips into over 2 million vehicles, thereby enhancing ADAS penetration.  

The Middle East is experiencing the fastest expansion, with a 27.61% CAGR, as Saudi Arabia, the UAE, and Qatar fund sovereign AI clusters. Saudi Arabia alone ordered 200,000 H200 GPUs for a 1.5 GW data center in NEOM. The UAE’s Technology Innovation Institute scaled its Falcon infrastructure to 4,096 H100 GPUs in 2025.  

North America, with a mid-30s share, remains the innovation hub. Microsoft, Google, Meta, and Amazon spent over USD 100 billion on GPU infrastructure in 2025. Europe accelerates sovereign AI moves as France’s Mistral AI deploys 2,048 GPUs and Germany’s Aleph Alpha leverages A100 clusters for enterprise inference. South America and Africa remain nascent, though research institutes in Brazil and South Africa have started to add H100 and MI250X nodes, signaling early adoption trends in the global GPU market.