Data
Connected views of AI infrastructure supply, demand, forecasts, and market signals.
Supply model
JP Data’s supply model follows the companies and products that can fill data-center infrastructure demand. The estimates cover server processors, accelerators, memory, and enterprise flash, using vendor revenue, product mix, capacity, and market availability to keep every component on a consistent dollar basis.
Data Center CPU
Tracks Intel and AMD x86 server processors alongside Arm-based server CPUs and other suppliers. The view compares total supply with vendor mix and includes the processors used in both general-purpose and accelerated servers.
Accelerators
Covers NVIDIA data-center GPUs, AMD Instinct products, and captive or merchant AI ASICs—including Google TPU, AWS Trainium, Microsoft Maia, Meta MTIA, and Intel Gaudi—used for training and inference.
RAM
Estimates server DRAM supply from SK hynix, Samsung, and Micron. Products include high-bandwidth memory (HBM) attached to AI accelerators and server DDR, while consumer memory is excluded.
Flash
Tracks enterprise SSD supply from Samsung, SK hynix, Kioxia, Sandisk, Micron, and Solidigm. The model focuses on server and data-center flash products rather than the broader client and consumer NAND market.
Demand model
The demand model starts with server spending by OEMs, ODMs, and hyperscalers, separates accelerated from general-purpose systems, and then rolls the bill of materials into CPU, accelerator, RAM, and enterprise flash demand.
Servers
Sizes total server spending and separates accelerated AI systems from non-accelerated servers. Channel detail includes OEM, ODM, and hyperscaler-direct purchases, including large cloud providers and neocloud operators.
CPU
Converts the server bill of materials into processor demand for x86 and Arm or other architectures. It includes CPUs installed in AI servers as well as general-purpose data-center systems.
Accelerators
Separates accelerator demand into GPUs and custom ASICs or TPUs. The view captures merchant products and hyperscaler-designed silicon used for AI training and inference workloads.
RAM
Splits server memory demand into HBM and DDR. HBM follows accelerated systems and their GPU or ASIC configurations, while DDR represents the main memory installed across the server base.
Flash
Measures enterprise and server SSD demand across OEM, ODM, and hyperscaler-direct channels. It is the data-center portion of storage spending and excludes client NAND and the full consumer flash market.
Forecast
The long-range forecast combines model history with JP Data’s outlook through 2032. Each row links to the detailed forecast page and the relevant product chart.
Server forecast
Extends total server spending as AI infrastructure deployment matures and growth shifts from the initial build-out toward replacement, expansion, and inference capacity.
CPU forecast
Projects server CPU demand and supply while accounting for the mix of general-purpose and accelerated systems and the continued role of x86 and Arm processors.
GPU forecast
Shows the outlook for merchant AI accelerators as availability improves, demand remains elevated, and GPU supply gradually moves toward a less constrained market.
ASIC forecast
Tracks custom and merchant AI silicon as hyperscalers expand internal accelerator programs and purpose-built products take a larger share of AI compute.
Signals
Signals connect component availability with delivery conditions and the capital spending that funds AI infrastructure demand.
Coverage
Compares supply with demand for CPU, accelerators, RAM, and enterprise SSD. Values below 100% indicate a tighter market; values above 100% indicate that modeled supply is ahead of demand.
Lead time
Tracks modeled delivery time for CPU, GPU, and HBM against market survey bands. Longer lead times generally indicate tighter availability, allocation, and stronger vendor pricing power.
Hyperscaler spend
Follows capital expenditure by major cloud providers, broader MANGOS companies, and neoclouds. These investments fund server, accelerator, memory, networking, and storage demand.