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Jon Peddie Research (JPR), the market research and consulting firm covering graphics, AI processors, and visual computing, released FPGAs in AI, a new market intelligence report analyzing the emerging class of field-programmable chips designed for AI inference at the edge and in the cloud, and for IoT.
FPGA processors are not a replacement for GPUs or NPUs — they are typically used as test chips and low-volume devices where the time and cost of designing and building an ASIC don’t make sense. The JPR report covers the architecture, competitive landscape, and commercial trajectory of FPGAs for AI chips from Altera/Intel, AMD/Xilinx, Flex Logix, Lattice Semiconductor, and QuickLogic.
The FPGA in AI chip-only market sits at $3.2 billion in 2025, growing at a 9.8% CAGR. IoT applications account for 45% of forecast revenue, device inference 30%, and autonomous systems 20%. Blended ASP compresses from $45 in 2025 toward $9–$12 by 2031 as consumer wearables and hearables drive volume. Unit shipments climb from 3–8 million in 2025 to more than 100 million by 2031.
“FPGA chips solve a problem that GPUs cannot address economically, and get to proof of concept faster and even into low-volume production before committing to an ASIC. The software ecosystem is well developed by multiple vendors, and benchmark standards exist and are being further developed for the AI workloads. We expect this segment to compound faster than mainstream FPGA through the end of the decade,” said Jon Peddie, President, Jon Peddie Research.
The report includes competitive profiles, an AI FPGA supplier table, market size and unit shipment forecasts through 2031, ASP analysis by segment, and an inflection signal assessment evaluating whether adoption represents a structural shift in AI hardware procurement.
