Global Compute-in-Memory AI Accelerator Chips Supply, Demand and Key Producers, 2026-2032
The global Compute-in-Memory AI Accelerator Chips market size is expected to reach $ 42322 million by 2032, rising at a market growth of 109.7% CAGR during the forecast period (2026-2032).
Compute-in-Memory (CIM) AI Accelerator Chips are specialized hardware accelerators that execute AI computations directly within or adjacent to memory arrays, enabling operations such as multiply–accumulate (MAC) to be performed where data is stored. By drastically reducing data movement between memory and processing units, CIM accelerator chips lower power consumption, reduce latency, and alleviate memory bandwidth bottlenecks associated with conventional von Neumann architectures. These chips are particularly effective for AI inference workloads dominated by matrix and vector operations, and are commonly implemented using SRAM, DRAM, or emerging non-volatile memories (e.g., ReRAM, MRAM), making them a key technology path for energy-efficient edge AI and next-generation AI computing systems.
This report studies the global Compute-in-Memory AI Accelerator Chips demand, key companies, and key regions.
This report is a detailed and comprehensive analysis of the world market for Compute-in-Memory AI Accelerator Chips, and provides market size (US$ million) and Year-over-Year (YoY) growth, considering 2025 as the base year. This report explores demand trends and competition, as well as details the characteristics of Compute-in-Memory AI Accelerator Chips that contribute to its increasing demand across many markets.
Highlights and key features of the study
Global Compute-in-Memory AI Accelerator Chips total market, 2021-2032, (USD Million)
Global Compute-in-Memory AI Accelerator Chips total market by region & country, CAGR, 2021-2032, (USD Million)
U.S. VS China: Compute-in-Memory AI Accelerator Chips total market, key domestic companies, and share, (USD Million)
Global Compute-in-Memory AI Accelerator Chips revenue by player, revenue and market share 2021-2026, (USD Million)
Global Compute-in-Memory AI Accelerator Chips total market by Type, CAGR, 2021-2032, (USD Million)
Global Compute-in-Memory AI Accelerator Chips total market by Application, CAGR, 2021-2032, (USD Million)
This report profiles major players in the global Compute-in-Memory AI Accelerator Chips market based on the following parameters - company overview, revenue, gross margin, product portfolio, geographical presence, and key developments. Key companies covered as a part of this study include Samsung, SK Hynix, Syntiant, D-Matrix, Mythic, Graphcore, EnCharge AI, Axelera AI, Hangzhou Zhicun (Witmem) Technology, Suzhou Yizhu Intelligent Technology, etc.
This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.
Stakeholders would have ease in decision-making through various strategy matrices used in analyzing the world Compute-in-Memory AI Accelerator Chips market
Detailed Segmentation:
Each section contains quantitative market data including market by value (US$ Millions), by player, by regions, by Type, and by Application. Data is given for the years 2021-2032 by year with 2025 as the base year, 2026 as the estimate year, and 2027-2032 as the forecast year.
Global Compute-in-Memory AI Accelerator Chips Market, By Region:
1. How big is the global Compute-in-Memory AI Accelerator Chips market?
2. What is the demand of the global Compute-in-Memory AI Accelerator Chips market?
3. What is the year over year growth of the global Compute-in-Memory AI Accelerator Chips market?
4. What is the total value of the global Compute-in-Memory AI Accelerator Chips market?
5. Who are the Major Players in the global Compute-in-Memory AI Accelerator Chips market?
6. What are the growth factors driving the market demand?
Compute-in-Memory (CIM) AI Accelerator Chips are specialized hardware accelerators that execute AI computations directly within or adjacent to memory arrays, enabling operations such as multiply–accumulate (MAC) to be performed where data is stored. By drastically reducing data movement between memory and processing units, CIM accelerator chips lower power consumption, reduce latency, and alleviate memory bandwidth bottlenecks associated with conventional von Neumann architectures. These chips are particularly effective for AI inference workloads dominated by matrix and vector operations, and are commonly implemented using SRAM, DRAM, or emerging non-volatile memories (e.g., ReRAM, MRAM), making them a key technology path for energy-efficient edge AI and next-generation AI computing systems.
This report studies the global Compute-in-Memory AI Accelerator Chips demand, key companies, and key regions.
This report is a detailed and comprehensive analysis of the world market for Compute-in-Memory AI Accelerator Chips, and provides market size (US$ million) and Year-over-Year (YoY) growth, considering 2025 as the base year. This report explores demand trends and competition, as well as details the characteristics of Compute-in-Memory AI Accelerator Chips that contribute to its increasing demand across many markets.
Highlights and key features of the study
Global Compute-in-Memory AI Accelerator Chips total market, 2021-2032, (USD Million)
Global Compute-in-Memory AI Accelerator Chips total market by region & country, CAGR, 2021-2032, (USD Million)
U.S. VS China: Compute-in-Memory AI Accelerator Chips total market, key domestic companies, and share, (USD Million)
Global Compute-in-Memory AI Accelerator Chips revenue by player, revenue and market share 2021-2026, (USD Million)
Global Compute-in-Memory AI Accelerator Chips total market by Type, CAGR, 2021-2032, (USD Million)
Global Compute-in-Memory AI Accelerator Chips total market by Application, CAGR, 2021-2032, (USD Million)
This report profiles major players in the global Compute-in-Memory AI Accelerator Chips market based on the following parameters - company overview, revenue, gross margin, product portfolio, geographical presence, and key developments. Key companies covered as a part of this study include Samsung, SK Hynix, Syntiant, D-Matrix, Mythic, Graphcore, EnCharge AI, Axelera AI, Hangzhou Zhicun (Witmem) Technology, Suzhou Yizhu Intelligent Technology, etc.
This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.
Stakeholders would have ease in decision-making through various strategy matrices used in analyzing the world Compute-in-Memory AI Accelerator Chips market
Detailed Segmentation:
Each section contains quantitative market data including market by value (US$ Millions), by player, by regions, by Type, and by Application. Data is given for the years 2021-2032 by year with 2025 as the base year, 2026 as the estimate year, and 2027-2032 as the forecast year.
Global Compute-in-Memory AI Accelerator Chips Market, By Region:
- United States
- China
- Europe
- Japan
- South Korea
- ASEAN
- India
- Rest of World
- Near-in-memory Computation (PNM)
- In-memory Processing (PIM)
- In-memory Computation (CIM)
- SRAM-based CIM
- DRAM-based PIM
- NVM-based CIM
- Small Computing Power
- Large Computing Power
- Samsung
- SK Hynix
- Syntiant
- D-Matrix
- Mythic
- Graphcore
- EnCharge AI
- Axelera AI
- Hangzhou Zhicun (Witmem) Technology
- Suzhou Yizhu Intelligent Technology
- Shenzhen Reexen Technology
- Beijing Houmo Technology
- AistarTek
- Beijing Pingxin Technology
1. How big is the global Compute-in-Memory AI Accelerator Chips market?
2. What is the demand of the global Compute-in-Memory AI Accelerator Chips market?
3. What is the year over year growth of the global Compute-in-Memory AI Accelerator Chips market?
4. What is the total value of the global Compute-in-Memory AI Accelerator Chips market?
5. Who are the Major Players in the global Compute-in-Memory AI Accelerator Chips market?
6. What are the growth factors driving the market demand?
