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Global Near-Memory AI Accelerator Chip Market 2026 by Manufacturers, Regions, Type and Application, Forecast to 2032

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1 Market Overview

  • 1.1 Product Overview and Scope
  • 1.2 Market Estimation Caveats and Base Year
  • 1.3 Market Analysis by Technology Paradigm
    • 1.3.1 Overview: Global Near-Memory AI Accelerator Chip Consumption Value by Technology Paradigm: 2021 Versus 2025 Versus 2032
    • 1.3.2 Digital In-Memory Computing
    • 1.3.3 Analog In-Memory Computing
    • 1.3.4 Processing-in-Memory
    • 1.3.5 Other
  • 1.4 Market Analysis by Data Precision
    • 1.4.1 Overview: Global Near-Memory AI Accelerator Chip Consumption Value by Data Precision: 2021 Versus 2025 Versus 2032
    • 1.4.2 INT4
    • 1.4.3 INT8
    • 1.4.4 FP8
    • 1.4.5 BF16
    • 1.4.6 Mixed Precision
  • 1.5 Market Analysis by Integration Location
    • 1.5.1 Overview: Global Near-Memory AI Accelerator Chip Consumption Value by Integration Location: 2021 Versus 2025 Versus 2032
    • 1.5.2 Inside Memory Array
    • 1.5.3 Near On-Chip Cache
    • 1.5.4 Memory Buffer Chip
    • 1.5.5 Inside HBM Stack
    • 1.5.6 Inside DRAM Module
    • 1.5.7 Beside Accelerator Card Local Memory
  • 1.6 Market Analysis by Application
    • 1.6.1 Overview: Global Near-Memory AI Accelerator Chip Consumption Value by Application: 2021 Versus 2025 Versus 2032
    • 1.6.2 Data Center LLM Inference
    • 1.6.3 Edge Vision Inference
    • 1.6.4 Low-Power Sensing Inference
    • 1.6.5 Vector Search Acceleration
    • 1.6.6 Recommendation System Acceleration
    • 1.6.7 Mobile AI Inference
    • 1.6.8 In-Memory Database Acceleration
  • 1.7 Global Near-Memory AI Accelerator Chip Market Size & Forecast
    • 1.7.1 Global Near-Memory AI Accelerator Chip Consumption Value (2021 & 2025 & 2032)
    • 1.7.2 Global Near-Memory AI Accelerator Chip Sales Quantity (2021-2032)
    • 1.7.3 Global Near-Memory AI Accelerator Chip Average Price (2021-2032)

2 Manufacturers Profiles

  • 2.1 d-Matrix
    • 2.1.1 d-Matrix Details
    • 2.1.2 d-Matrix Major Business
    • 2.1.3 d-Matrix Near-Memory AI Accelerator Chip Product and Services
    • 2.1.4 d-Matrix Near-Memory AI Accelerator Chip Sales Quantity, Average Price, Revenue, Gross Margin and Market Share (2021-2026)
    • 2.1.5 d-Matrix Recent Developments/Updates
  • 2.2 EnCharge AI
    • 2.2.1 EnCharge AI Details
    • 2.2.2 EnCharge AI Major Business
    • 2.2.3 EnCharge AI Near-Memory AI Accelerator Chip Product and Services
    • 2.2.4 EnCharge AI Near-Memory AI Accelerator Chip Sales Quantity, Average Price, Revenue, Gross Margin and Market Share (2021-2026)
    • 2.2.5 EnCharge AI Recent Developments/Updates
  • 2.3 Mythic
    • 2.3.1 Mythic Details
    • 2.3.2 Mythic Major Business
    • 2.3.3 Mythic Near-Memory AI Accelerator Chip Product and Services
    • 2.3.4 Mythic Near-Memory AI Accelerator Chip Sales Quantity, Average Price, Revenue, Gross Margin and Market Share (2021-2026)
    • 2.3.5 Mythic Recent Developments/Updates
  • 2.4 TetraMem
    • 2.4.1 TetraMem Details
    • 2.4.2 TetraMem Major Business
    • 2.4.3 TetraMem Near-Memory AI Accelerator Chip Product and Services
    • 2.4.4 TetraMem Near-Memory AI Accelerator Chip Sales Quantity, Average Price, Revenue, Gross Margin and Market Share (2021-2026)
    • 2.4.5 TetraMem Recent Developments/Updates
  • 2.5 Axelera AI
    • 2.5.1 Axelera AI Details
    • 2.5.2 Axelera AI Major Business
    • 2.5.3 Axelera AI Near-Memory AI Accelerator Chip Product and Services
    • 2.5.4 Axelera AI Near-Memory AI Accelerator Chip Sales Quantity, Average Price, Revenue, Gross Margin and Market Share (2021-2026)
    • 2.5.5 Axelera AI Recent Developments/Updates
  • 2.6 GSI Technology
    • 2.6.1 GSI Technology Details
    • 2.6.2 GSI Technology Major Business
    • 2.6.3 GSI Technology Near-Memory AI Accelerator Chip Product and Services
    • 2.6.4 GSI Technology Near-Memory AI Accelerator Chip Sales Quantity, Average Price, Revenue, Gross Margin and Market Share (2021-2026)
    • 2.6.5 GSI Technology Recent Developments/Updates
  • 2.7 Samsung Electronics
    • 2.7.1 Samsung Electronics Details
    • 2.7.2 Samsung Electronics Major Business
    • 2.7.3 Samsung Electronics Near-Memory AI Accelerator Chip Product and Services
    • 2.7.4 Samsung Electronics Near-Memory AI Accelerator Chip Sales Quantity, Average Price, Revenue, Gross Margin and Market Share (2021-2026)
    • 2.7.5 Samsung Electronics Recent Developments/Updates
  • 2.8 SK hynix
    • 2.8.1 SK hynix Details
    • 2.8.2 SK hynix Major Business
    • 2.8.3 SK hynix Near-Memory AI Accelerator Chip Product and Services
    • 2.8.4 SK hynix Near-Memory AI Accelerator Chip Sales Quantity, Average Price, Revenue, Gross Margin and Market Share (2021-2026)
    • 2.8.5 SK hynix Recent Developments/Updates

3 Competitive Environment: Near-Memory AI Accelerator Chip by Manufacturer

  • 3.1 Global Near-Memory AI Accelerator Chip Sales Quantity by Manufacturer (2021-2026)
  • 3.2 Global Near-Memory AI Accelerator Chip Revenue by Manufacturer (2021-2026)
  • 3.3 Global Near-Memory AI Accelerator Chip Average Price by Manufacturer (2021-2026)
  • 3.4 Market Share Analysis (2025)
    • 3.4.1 Producer Shipments of Near-Memory AI Accelerator Chip by Manufacturer Revenue ($MM) and Market Share (%): 2025
    • 3.4.2 Top 3 Near-Memory AI Accelerator Chip Manufacturer Market Share in 2025
    • 3.4.3 Top 6 Near-Memory AI Accelerator Chip Manufacturer Market Share in 2025
  • 3.5 Near-Memory AI Accelerator Chip Market: Overall Company Footprint Analysis
    • 3.5.1 Near-Memory AI Accelerator Chip Market: Region Footprint
    • 3.5.2 Near-Memory AI Accelerator Chip Market: Company Product Type Footprint
    • 3.5.3 Near-Memory AI Accelerator Chip Market: Company Product Application Footprint
  • 3.6 New Market Entrants and Barriers to Market Entry
  • 3.7 Mergers, Acquisition, Agreements, and Collaborations

4 Consumption Analysis by Region

  • 4.1 Global Near-Memory AI Accelerator Chip Market Size by Region
    • 4.1.1 Global Near-Memory AI Accelerator Chip Sales Quantity by Region (2021-2032)
    • 4.1.2 Global Near-Memory AI Accelerator Chip Consumption Value by Region (2021-2032)
    • 4.1.3 Global Near-Memory AI Accelerator Chip Average Price by Region (2021-2032)
  • 4.2 North America Near-Memory AI Accelerator Chip Consumption Value (2021-2032)
  • 4.3 Europe Near-Memory AI Accelerator Chip Consumption Value (2021-2032)
  • 4.4 Asia-Pacific Near-Memory AI Accelerator Chip Consumption Value (2021-2032)
  • 4.5 South America Near-Memory AI Accelerator Chip Consumption Value (2021-2032)
  • 4.6 Middle East & Africa Near-Memory AI Accelerator Chip Consumption Value (2021-2032)

5 Market Segment by Technology Paradigm

  • 5.1 Global Near-Memory AI Accelerator Chip Sales Quantity by Technology Paradigm (2021-2032)
  • 5.2 Global Near-Memory AI Accelerator Chip Consumption Value by Technology Paradigm (2021-2032)
  • 5.3 Global Near-Memory AI Accelerator Chip Average Price by Technology Paradigm (2021-2032)

6 Market Segment by Application

  • 6.1 Global Near-Memory AI Accelerator Chip Sales Quantity by Application (2021-2032)
  • 6.2 Global Near-Memory AI Accelerator Chip Consumption Value by Application (2021-2032)
  • 6.3 Global Near-Memory AI Accelerator Chip Average Price by Application (2021-2032)

7 North America

  • 7.1 North America Near-Memory AI Accelerator Chip Sales Quantity by Technology Paradigm (2021-2032)
  • 7.2 North America Near-Memory AI Accelerator Chip Sales Quantity by Application (2021-2032)
  • 7.3 North America Near-Memory AI Accelerator Chip Market Size by Country
    • 7.3.1 North America Near-Memory AI Accelerator Chip Sales Quantity by Country (2021-2032)
    • 7.3.2 North America Near-Memory AI Accelerator Chip Consumption Value by Country (2021-2032)
    • 7.3.3 United States Market Size and Forecast (2021-2032)
    • 7.3.4 Canada Market Size and Forecast (2021-2032)
    • 7.3.5 Mexico Market Size and Forecast (2021-2032)

8 Europe

  • 8.1 Europe Near-Memory AI Accelerator Chip Sales Quantity by Technology Paradigm (2021-2032)
  • 8.2 Europe Near-Memory AI Accelerator Chip Sales Quantity by Application (2021-2032)
  • 8.3 Europe Near-Memory AI Accelerator Chip Market Size by Country
    • 8.3.1 Europe Near-Memory AI Accelerator Chip Sales Quantity by Country (2021-2032)
    • 8.3.2 Europe Near-Memory AI Accelerator Chip Consumption Value by Country (2021-2032)
    • 8.3.3 Germany Market Size and Forecast (2021-2032)
    • 8.3.4 France Market Size and Forecast (2021-2032)
    • 8.3.5 United Kingdom Market Size and Forecast (2021-2032)
    • 8.3.6 Russia Market Size and Forecast (2021-2032)
    • 8.3.7 Italy Market Size and Forecast (2021-2032)

9 Asia-Pacific

  • 9.1 Asia-Pacific Near-Memory AI Accelerator Chip Sales Quantity by Technology Paradigm (2021-2032)
  • 9.2 Asia-Pacific Near-Memory AI Accelerator Chip Sales Quantity by Application (2021-2032)
  • 9.3 Asia-Pacific Near-Memory AI Accelerator Chip Market Size by Region
    • 9.3.1 Asia-Pacific Near-Memory AI Accelerator Chip Sales Quantity by Region (2021-2032)
    • 9.3.2 Asia-Pacific Near-Memory AI Accelerator Chip Consumption Value by Region (2021-2032)
    • 9.3.3 China Market Size and Forecast (2021-2032)
    • 9.3.4 Japan Market Size and Forecast (2021-2032)
    • 9.3.5 South Korea Market Size and Forecast (2021-2032)
    • 9.3.6 India Market Size and Forecast (2021-2032)
    • 9.3.7 Southeast Asia Market Size and Forecast (2021-2032)
    • 9.3.8 Australia Market Size and Forecast (2021-2032)

10 South America

  • 10.1 South America Near-Memory AI Accelerator Chip Sales Quantity by Technology Paradigm (2021-2032)
  • 10.2 South America Near-Memory AI Accelerator Chip Sales Quantity by Application (2021-2032)
  • 10.3 South America Near-Memory AI Accelerator Chip Market Size by Country
    • 10.3.1 South America Near-Memory AI Accelerator Chip Sales Quantity by Country (2021-2032)
    • 10.3.2 South America Near-Memory AI Accelerator Chip Consumption Value by Country (2021-2032)
    • 10.3.3 Brazil Market Size and Forecast (2021-2032)
    • 10.3.4 Argentina Market Size and Forecast (2021-2032)

11 Middle East & Africa

  • 11.1 Middle East & Africa Near-Memory AI Accelerator Chip Sales Quantity by Technology Paradigm (2021-2032)
  • 11.2 Middle East & Africa Near-Memory AI Accelerator Chip Sales Quantity by Application (2021-2032)
  • 11.3 Middle East & Africa Near-Memory AI Accelerator Chip Market Size by Country
    • 11.3.1 Middle East & Africa Near-Memory AI Accelerator Chip Sales Quantity by Country (2021-2032)
    • 11.3.2 Middle East & Africa Near-Memory AI Accelerator Chip Consumption Value by Country (2021-2032)
    • 11.3.3 Turkey Market Size and Forecast (2021-2032)
    • 11.3.4 Egypt Market Size and Forecast (2021-2032)
    • 11.3.5 Saudi Arabia Market Size and Forecast (2021-2032)
    • 11.3.6 South Africa Market Size and Forecast (2021-2032)

12 Market Dynamics

  • 12.1 Near-Memory AI Accelerator Chip Market Drivers
  • 12.2 Near-Memory AI Accelerator Chip Market Restraints
  • 12.3 Near-Memory AI Accelerator Chip Trends Analysis
  • 12.4 Porters Five Forces Analysis
    • 12.4.1 Threat of New Entrants
    • 12.4.2 Bargaining Power of Suppliers
    • 12.4.3 Bargaining Power of Buyers
    • 12.4.4 Threat of Substitutes
    • 12.4.5 Competitive Rivalry

13 Raw Material and Industry Chain

  • 13.1 Raw Material of Near-Memory AI Accelerator Chip and Key Manufacturers
  • 13.2 Manufacturing Costs Percentage of Near-Memory AI Accelerator Chip
  • 13.3 Near-Memory AI Accelerator Chip Production Process
  • 13.4 Industry Value Chain Analysis

14 Shipments by Distribution Channel

  • 14.1 Sales Channel
    • 14.1.1 Direct to End-User
    • 14.1.2 Distributors
  • 14.2 Near-Memory AI Accelerator Chip Typical Distributors
  • 14.3 Near-Memory AI Accelerator Chip Typical Customers

15 Research Findings and Conclusion

    16 Appendix

    • 16.1 Methodology
    • 16.2 Research Process and Data Source

    According to our (Global Info Research) latest study, the global Near-Memory AI Accelerator Chip market size was valued at US$ 256 million in 2025 and is forecast to a readjusted size of US$ 1052 million by 2032 with a CAGR of 15.0% during review period.
    A near-memory AI accelerator chip is a dedicated processor or acceleration hardware category designed around the data-movement bottleneck in artificial intelligence workloads. Its core positioning is not merely to increase the number of arithmetic units, but to place compute capability inside memory arrays, near memory chips, within memory buffer chips, or alongside high-bandwidth memory channels, so that neural network weights, activations, and retrieval vectors can complete reading, multiply-accumulate, reduction, search, and inference operations over shorter data paths. These products typically adopt digital in-memory computing, analog in-memory computing, processing-in-memory, near-data dataflow, large on-chip SRAM, RRAM arrays, HBM-PIM, GDDR-AiM, or associative processing array architectures. Their main purpose is to improve energy efficiency, latency, and throughput for large-model inference, recommendation systems, edge vision, low-power sensing, vector search, and memory-intensive AI workloads. Common delivery forms include standalone chips, AI accelerator cards, in-memory computing SoCs, PIM memory modules, server inference platforms, and customer-specific ASICs. Major customers include cloud computing providers, server vendors, edge device manufacturers, industrial vision system providers, automotive electronics companies, wearable device makers, and high-performance search system integrators.
    The core industrial logic of near-memory AI accelerator chips is that artificial intelligence computing is shifting from a pure pursuit of peak compute performance to a combined pursuit of data access efficiency, system-level energy efficiency, and inference cost per unit. Traditional processor architectures frequently move model weights, activations, and intermediate results between external memory and compute cores. As large-model inference, recommendation systems, vector search, and multi-channel video analytics become mainstream workloads, the power consumption, latency, and bandwidth occupation caused by data movement are becoming system-level bottlenecks. Near-memory computing, in-memory computing, and processing-in-memory approaches shorten data paths by placing part of matrix multiplication, reduction, search, or preprocessing tasks inside memory arrays or near memory channels, thereby improving overall AI system efficiency.
    From a technology-route perspective, near-memory AI accelerator chips are not a single product form, but an industrial cluster formed by multiple architectural routes. Digital in-memory computing typically relies on SRAM and standard CMOS processes, emphasizing manufacturability, stable accuracy, and software toolchain compatibility, making it suitable for edge vision, industrial inspection, and multi-channel video analytics. Analog in-memory computing usually uses flash memory, RRAM, or other memory arrays to perform matrix operations, offering strong energy-efficiency potential and fitting low-power devices and inference tasks that are highly sensitive to data movement. PIM and AiM routes are more often driven by memory manufacturers, embedding compute capability into HBM, GDDR, DIMM, or mobile DRAM to improve data efficiency in existing AI accelerator systems.
    From a market outlook perspective, the growth potential of near-memory AI accelerator chips comes from the simultaneous expansion of two types of demand. The first is data center large-model inference. As generative AI shifts from training competition toward online inference, agents, multimodal generation, and enterprise private deployment, inference cost, latency, and energy consumption will become important hardware procurement criteria. The second is edge and endpoint AI demand. Wearables, smart cameras, industrial sensing, robotics, automotive perception, and AR/VR devices require local AI model execution while being constrained by power, size, thermal design, and privacy. Near-memory computing approaches are expected to create differentiated value in these scenarios.
    This report is a detailed and comprehensive analysis for global Near-Memory AI Accelerator Chip market. Both quantitative and qualitative analyses are presented by manufacturers, by region & country, by Technology Paradigm and by Application. As the market is constantly changing, this report explores the competition, supply and demand trends, as well as key factors that contribute to its changing demands across many markets. Company profiles and product examples of selected competitors, along with market share estimates of some of the selected leaders for the year 2025, are provided.
    Key Features:
    Global Near-Memory AI Accelerator Chip market size and forecasts, in consumption value ($ Million), sales quantity (Million Units), and average selling prices (US$/Unit), 2021-2032
    Global Near-Memory AI Accelerator Chip market size and forecasts by region and country, in consumption value ($ Million), sales quantity (Million Units), and average selling prices (US$/Unit), 2021-2032
    Global Near-Memory AI Accelerator Chip market size and forecasts, by Technology Paradigm and by Application, in consumption value ($ Million), sales quantity (Million Units), and average selling prices (US$/Unit), 2021-2032
    Global Near-Memory AI Accelerator Chip market shares of main players, shipments in revenue ($ Million), sales quantity (Million Units), and ASP (US$/Unit), 2021-2026
    The Primary Objectives in This Report Are:
    To determine the size of the total market opportunity of global and key countries
    To assess the growth potential for Near-Memory AI Accelerator Chip
    To forecast future growth in each product and end-use market
    To assess competitive factors affecting the marketplace
    This report profiles key players in the global Near-Memory AI Accelerator Chip market based on the following parameters - company overview, sales quantity, revenue, price, gross margin, product portfolio, geographical presence, and key developments. Key companies covered as a part of this study include d-Matrix, EnCharge AI, Mythic, TetraMem, Axelera AI, GSI Technology, Samsung Electronics, SK hynix, etc.
    This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.
    Market Segmentation
    Near-Memory AI Accelerator Chip market is split by Technology Paradigm and by Application. For the period 2021-2032, the growth among segments provides accurate calculations and forecasts for consumption value by Technology Paradigm, and by Application in terms of volume and value. This analysis can help you expand your business by targeting qualified niche markets.
    Market segment by Technology Paradigm
    Digital In-Memory Computing
    Analog In-Memory Computing
    Processing-in-Memory
    Other
    Market segment by Data Precision
    INT4
    INT8
    FP8
    BF16
    Mixed Precision
    Market segment by Integration Location
    Inside Memory Array
    Near On-Chip Cache
    Memory Buffer Chip
    Inside HBM Stack
    Inside DRAM Module
    Beside Accelerator Card Local Memory
    Market segment by Application
    Data Center LLM Inference
    Edge Vision Inference
    Low-Power Sensing Inference
    Vector Search Acceleration
    Recommendation System Acceleration
    Mobile AI Inference
    In-Memory Database Acceleration
    Major players covered
    d-Matrix
    EnCharge AI
    Mythic
    TetraMem
    Axelera AI
    GSI Technology
    Samsung Electronics
    SK hynix
    Market segment by region, regional analysis covers
    North America (United States, Canada, and Mexico)
    Europe (Germany, France, United Kingdom, Russia, Italy, and Rest of Europe)
    Asia-Pacific (China, Japan, Korea, India, Southeast Asia, and Australia)
    South America (Brazil, Argentina, Colombia, and Rest of South America)
    Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa, and Rest of Middle East & Africa)
    The content of the study subjects, includes a total of 15 chapters:
    Chapter 1, to describe Near-Memory AI Accelerator Chip product scope, market overview, market estimation caveats and base year.
    Chapter 2, to profile the top manufacturers of Near-Memory AI Accelerator Chip, with price, sales quantity, revenue, and global market share of Near-Memory AI Accelerator Chip from 2021 to 2026.
    Chapter 3, the Near-Memory AI Accelerator Chip competitive situation, sales quantity, revenue, and global market share of top manufacturers are analyzed emphatically by landscape contrast.
    Chapter 4, the Near-Memory AI Accelerator Chip breakdown data are shown at the regional level, to show the sales quantity, consumption value, and growth by regions, from 2021 to 2032.
    Chapter 5 and 6, to segment the sales by Technology Paradigm and by Application, with sales market share and growth rate by Technology Paradigm, by Application, from 2021 to 2032.
    Chapter 7, 8, 9, 10 and 11, to break the sales data at the country level, with sales quantity, consumption value, and market share for key countries in the world, from 2021 to 2026.and Near-Memory AI Accelerator Chip market forecast, by regions, by Technology Paradigm, and by Application, with sales and revenue, from 2027 to 2032.
    Chapter 12, market dynamics, drivers, restraints, trends, and Porters Five Forces analysis.
    Chapter 13, the key raw materials and key suppliers, and industry chain of Near-Memory AI Accelerator Chip.
    Chapter 14 and 15, to describe Near-Memory AI Accelerator Chip sales channel, distributors, customers, research findings and conclusion.

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