{"id":122171,"date":"2025-09-05T16:09:13","date_gmt":"2025-09-05T16:09:13","guid":{"rendered":"https:\/\/www.newsbeep.com\/ca\/122171\/"},"modified":"2025-09-05T16:09:13","modified_gmt":"2025-09-05T16:09:13","slug":"global-edge-computing-ai-accelerator-cards-market-to-reach-usd","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ca\/122171\/","title":{"rendered":"Global Edge Computing AI Accelerator Cards Market to Reach USD"},"content":{"rendered":"

\"Global<\/a>The Edge Computing AI Accelerator Cards market is entering a high-velocity growth phase. According to QYResearch Report Global Edge Computing AI Accelerator Cards Sales Market Report, Competitive Analysis and Regional Opportunities 2025-2031, the market reached US$ 26,805 million in 2024 and is projected to hit US$ 99,014 million by 2031 at a 21.9% CAGR (2025-2031). Momentum is reinforced by a series of 2024-2025 product launches that are pushing generative, vision, and robotics workloads to the edge while slashing latency and energy cost per inference. Nvidia introduced Jetson AGX Thor bringing Blackwell-class compute to robots, Hailo launched the Hailo-10H M.2 GenAI accelerator at single-digit watts, AMD rolled out Versal AI Edge Gen 2 doubling down on deterministic, safety-critical edge performance, Intel expanded its Data Center GPU Flex family for edge inference, and Huawei advanced its Atlas 300I Pro with improved Ascend architecture.<\/p>\n

Get Full PDF Sample Copy of Report: (Including Full TOC, List of Tables & Figures, Chart) https:\/\/www.qyresearch.com\/sample\/4937058<\/p>\n

Latest Data

\n\u2022\tGlobal Market Size 2024: US$ 26,805 million

\n\u2022\tForecast 2031: US$ 99,014 million

\n\u2022\tCAGR 2025-2031: 21.9%

\n\u2022\tRegions: North America, Europe, Asia Pacific, South America, Middle East & Africa

\n\u2022\tForecast Units: USD million (value)

\n\u2022\tCoverage: Revenue & volume forecast, company share, competitive benchmarking, growth factors and restraints, regulation, and risk analysis<\/p>\n

Classification

\n\u2022\tCloud Deployment

\n\u2022\tDevice Deployment<\/p>\n

Applications

\n\u2022\tSmart Grid

\n\u2022\tSmart Manufacturing

\n\u2022\tSmart Rail Transit

\n\u2022\tSmart Finance

\n\u2022\tOther<\/p>\n

Leading Companies

\nNVIDIA

\nAMD

\nIntel

\nHuawei

\nQualcomm

\nIBM

\nHailo

\nDenglin Technology

\nHaiguang Information Technology

\nAchronix Semiconductor

\nGraphcore

\nSuyuan

\nKunlun Core

\nCambricon

\nDeepX

\nAdvantech<\/p>\n

Five Product Snapshots

\nNVIDIA – Jetson AGX Thor

\n\u2022\tBlackwell-based edge module for robotics and physical AI

\n\u2022\tUp to 7.5\u00d7 AI compute compared with Jetson Orin

\n\u2022\tUp to 3.5\u00d7 higher energy efficiency

\n\u2022\tSupports up to 128 GB LPDDR5X memory

\n\u2022\tDeveloper kit listed at US$ 3,499; production modules US$ 2,999

\nAMD – Versal AI Edge Series Gen 2

\n\u2022\tUp to 3\u00d7 TOPS per Watt vs. previous generation

\n\u2022\tUp to 10\u00d7 more scalar compute

\n\u2022\tDesigned for deterministic real-time control and functional safety

\n\u2022\tTargeting industrial automation, medical imaging, aerospace, and defense

\nIntel – Data Center GPU Flex 170

\n\u2022\t32 Xe cores with 512 XMX engines

\n\u2022\t16 GB GDDR6, 576 GB\/s bandwidth, 150 W power envelope

\n\u2022\tPCIe Gen4 x16 interface

\n\u2022\tOptimized for video analytics and media-rich pipelines at the edge

\nHuawei – Atlas 300I Pro Inference Card

\n\u2022\tAscend 310 series processor with 8 AI cores and 8 CPU cores

\n\u2022\t24 GB LPDDR4X memory with ~204.8 GB\/s bandwidth

\n\u2022\tHalf-height, half-length PCIe card for industrial deployment

\n\u2022\tCapable of approximately 140 INT8 TOPS

\nHailo – Hailo-10H

\n\u2022\tAround 40 TOPS (INT4) or 20 TOPS (INT8) performance at 2.5 W

\n\u2022\tM.2 form factor (2242\/2280) with PCIe Gen3 x4

\n\u2022\tEquipped with 4-8 GB LPDDR4\/4X memory

\n\u2022\tFocused on running GenAI workloads locally on PCs and embedded systems<\/p>\n

Verified Downstream Users

\nAmazon Robotics

\nCaterpillar

\nFigure AI

\nMeta Platforms

\nSiemens

\nJohn Deere

\nApptronik

\nFoxconn

\nH3C Technologies

\nZTE

\nLenovo

\nDell Technologies

\nHewlett Packard Enterprise

\nSupermicro

\nCisco Systems<\/p>\n

Market Trend

\nPhysical AI goes mainstream in robotics

\nRobotics vendors are moving LLM and VLM reasoning from the cloud to on-device compute for lower latency, privacy, and resilience. NVIDIA’s Jetson AGX Thor brings a 7.5\u00d7 performance uplift over Orin with 3.5\u00d7 better efficiency, enabling robots to handle multi-modal perception and interaction directly at the edge. Early adopters include Amazon Robotics, Caterpillar, Meta, and Figure AI, with agriculture, logistics, and manufacturing poised to expand adoption.<\/p>\n

Low-power GenAI with quantized inference

\nEdge accelerators are adopting INT4 and INT8 quantization to allow transformer models and diffusion networks to run on small devices. Hailo-10H exemplifies this with 40 TOPS INT4 performance at just 2.5 W. This trend makes on-device copilots and real-time inspections feasible without relying on high-power GPUs or cloud servers.<\/p>\n

Adaptive SoCs for safety-critical applications

\nIndustrial, medical, and rail environments require deterministic performance and functional safety. AMD’s Versal AI Edge Gen 2 delivers up to 3\u00d7 TOPS per Watt with stronger real-time control and safety features. These adaptive SoCs and FPGA solutions are gaining traction in regulated industries that demand consistent latency and certified safety standards.<\/p>\n

Memory-rich edge accelerators for GenAI

\nAccelerator cards are increasingly equipped with larger onboard memory to support bigger models and reduce round-trips to the cloud. Qualcomm’s Cloud AI 100 Ultra with 128 GB on-card memory achieves lower latency on generative workloads like Stable Diffusion, and scales throughput by multi-device scheduling, proving that high-memory PCIe cards are now vital for edge GenAI.<\/p>\n

Industrial adoption through platform partnerships

\nIndustrial ecosystems are expanding by integrating accelerator cards with complete software platforms. Siemens has strengthened its partnership with NVIDIA, embedding GPU-powered AI into industrial PCs for predictive maintenance and inspection. Such partnerships are accelerating adoption in smart manufacturing and smart grid sectors.<\/p>\n

Regional ecosystems and localized supply chains

\nIn China, accelerator providers like Cambricon and Baidu Kunlunxin have secured large orders from H3C and ZTE for edge deployments, driven by national priorities for domestic AI hardware. Local supply chains are fostering CUDA-compatible alternatives and new PCIe-based edge cards tailored for surveillance, transport, and utilities.<\/p>\n

Open-source enablement

\nFirmware and drivers for AI accelerators are being upstreamed into major Linux distributions, cutting deployment time and easing fleet management. Qualcomm’s AIC100 firmware inclusion in linux-firmware in 2024 exemplifies how open-source contributions accelerate adoption across enterprise edge systems.<\/p>\n

Request for Pre-Order Enquiry On This Report https:\/\/www.qyresearch.com\/customize\/4937058<\/p>\n

Diversified form factors and power envelopes

\nThe product spectrum is widening from 2.5 W M.2 modules to 150 W PCIe cards, allowing customers to right-size AI acceleration for their application. PCIe Gen4 and Gen5 adoption is expanding, with device-level accelerators serving mobile robots and cameras, while server-class cards address retail, utilities, and transportation back-ends.<\/p>\n

Strategic Takeaways

\n\u2022\tRobotics and industrial AI will be the strongest growth engines through 2025, powered by Blackwell-class modules and low-power GenAI at the edge.

\n\u2022\tQuantization and memory-centric designs will define leadership, with INT4\/INT8 compute and high onboard memory emerging as critical metrics.

\n\u2022\tAdaptive SoCs and FPGA-based accelerators are set to dominate regulated industries requiring functional safety and deterministic performance.<\/p>\n

Chapter Outline:<\/p>\n

Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by region, product type, application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.

\nChapter 2: key insights, key emerging trends, etc.

\nChapter 3: Manufacturers competitive analysis, detailed analysis of the product manufacturers competitive landscape, price, sales and revenue market share, latest development plan, merger, and acquisition information, etc.

\nChapter 4: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.

\nChapter 5 & 6: Sales, revenue of the product in regional level and country level. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and market size of each country in the world.

\nChapter 7: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.

\nChapter 8: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.

\nChapter 9: Analysis of industrial chain, including the upstream and downstream of the industry.

\nChapter 10: The main points and conclusions of the report.<\/p>\n

Contact Details

\nTel: +1 626 2952 442 ; +41 765899438(Tel & Whatsapp); +86-1082945717

\nEmail: john@qyresearch.com; global@qyresearch.com

\nWebsite: www.qyresearch.com<\/p>\n

About us:

\nQY Research has established close partnerships with over 71,000 global leading players. With more than 20,000 industry experts worldwide, we maintain a strong global network to efficiently gather insights and raw data.<\/p>\n

Our 36-step verification system ensures the reliability and quality of our data. With over 2 million reports, we have become the world’s largest market report vendor. Our global database spans more than 2,000 sources and covers data from most countries, including import and export details.<\/p>\n

We have partners in over 160 countries, providing comprehensive coverage of both sales and research networks. A 90% client return rate and long-term cooperation with key partners demonstrate the high level of service and quality QY Research delivers.<\/p>\n

More than 30 IPOs and over 5,000 global media outlets and major corporations have used our data, solidifying QY Research as a global leader in data supply. We are committed to delivering services that exceed both client and societal expectations.<\/p>\n

This release was published on openPR.
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