Global Edge Inference Chips and Acceleration Cards Market 2025 by Company, Regions, Type and Application, Forecast to 2031
Description
According to our (Global Info Research) latest study, the global Edge Inference Chips and Acceleration Cards market size was valued at US$ 854 million in 2024 and is forecast to a readjusted size of USD 2926 million by 2031 with a CAGR of 19.5% during review period.
The design of edge inference chips and acceleration cards is mainly aimed at performing artificial intelligence tasks on edge devices, which are usually far away from data centers and directly face the actual usage environment of users or devices. They are specifically optimized to handle deep learning and other machine learning algorithms, enabling real-time data processing and decision-making locally, thereby reducing data transmission latency and improving response speed. This design makes edge inference chips and acceleration cards very suitable for application scenarios that require fast response and low latency, such as autonomous driving, smart finance, industrial automation, etc.
The need for real-time AI inference and decision-making is a significant driver behind the growth of edge inference chips and acceleration cards. Traditional cloud-based AI processing involves sending data to centralized servers for analysis, which introduces latency. As more applications, from autonomous vehicles to industrial automation, require instant data processing, the need to move AI workloads closer to the data source (edge computing) becomes increasingly apparent.
Edge inference chips and acceleration cards enable AI models to be deployed and run locally on devices like IoT sensors, smart cameras, and autonomous robots. This approach significantly reduces latency and bandwidth usage, as well as minimizes reliance on cloud infrastructure. The demand for instant decision-making in critical applications such as healthcare diagnostics, real-time video analytics, and autonomous driving is pushing edge computing solutions, including inference chips and acceleration cards, into high demand.
This report is a detailed and comprehensive analysis for global Edge Inference Chips and Acceleration Cards market. Both quantitative and qualitative analyses are presented by company, by region & country, by Type 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 Edge Inference Chips and Acceleration Cards market size and forecasts, in consumption value ($ Million), 2020-2031
Global Edge Inference Chips and Acceleration Cards market size and forecasts by region and country, in consumption value ($ Million), 2020-2031
Global Edge Inference Chips and Acceleration Cards market size and forecasts, by Type and by Application, in consumption value ($ Million), 2020-2031
Global Edge Inference Chips and Acceleration Cards market shares of main players, in revenue ($ Million), 2020-2025
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 Edge Inference Chips and Acceleration Cards
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 Edge Inference Chips and Acceleration Cards 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 NVIDIA, Cambrian, Hisilicon, Kunlun Core, AMD, Intel, Qualcomm, Hailo, Black Sesame Technologies, Corerain, etc.
This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.
Market segmentation
Edge Inference Chips and Acceleration Cards market is split by Type and by Application. For the period 2020-2031, the growth among segments provides accurate calculations and forecasts for Consumption Value by Type and by Application. This analysis can help you expand your business by targeting qualified niche markets.
Market segment by Type
Chips
Acceleration Cards
Market segment by Application
Smart Transportation
Smart Finance
Industrial Manufacturing
Other
Market segment by players, this report covers
NVIDIA
Cambrian
Hisilicon
Kunlun Core
AMD
Intel
Qualcomm
Hailo
Black Sesame Technologies
Corerain
Market segment by regions, regional analysis covers
North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia, Italy and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia and Rest of Asia-Pacific)
South America (Brazil, Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
The content of the study subjects, includes a total of 13 chapters:
Chapter 1, to describe Edge Inference Chips and Acceleration Cards product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top players of Edge Inference Chips and Acceleration Cards, with revenue, gross margin, and global market share of Edge Inference Chips and Acceleration Cards from 2020 to 2025.
Chapter 3, the Edge Inference Chips and Acceleration Cards competitive situation, revenue, and global market share of top players are analyzed emphatically by landscape contrast.
Chapter 4 and 5, to segment the market size by Type and by Application, with consumption value and growth rate by Type, by Application, from 2020 to 2031
Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2020 to 2025.and Edge Inference Chips and Acceleration Cards market forecast, by regions, by Type and by Application, with consumption value, from 2026 to 2031.
Chapter 11, market dynamics, drivers, restraints, trends, Porters Five Forces analysis.
Chapter 12, the key raw materials and key suppliers, and industry chain of Edge Inference Chips and Acceleration Cards.
Chapter 13, to describe Edge Inference Chips and Acceleration Cards research findings and conclusion.
The design of edge inference chips and acceleration cards is mainly aimed at performing artificial intelligence tasks on edge devices, which are usually far away from data centers and directly face the actual usage environment of users or devices. They are specifically optimized to handle deep learning and other machine learning algorithms, enabling real-time data processing and decision-making locally, thereby reducing data transmission latency and improving response speed. This design makes edge inference chips and acceleration cards very suitable for application scenarios that require fast response and low latency, such as autonomous driving, smart finance, industrial automation, etc.
The need for real-time AI inference and decision-making is a significant driver behind the growth of edge inference chips and acceleration cards. Traditional cloud-based AI processing involves sending data to centralized servers for analysis, which introduces latency. As more applications, from autonomous vehicles to industrial automation, require instant data processing, the need to move AI workloads closer to the data source (edge computing) becomes increasingly apparent.
Edge inference chips and acceleration cards enable AI models to be deployed and run locally on devices like IoT sensors, smart cameras, and autonomous robots. This approach significantly reduces latency and bandwidth usage, as well as minimizes reliance on cloud infrastructure. The demand for instant decision-making in critical applications such as healthcare diagnostics, real-time video analytics, and autonomous driving is pushing edge computing solutions, including inference chips and acceleration cards, into high demand.
This report is a detailed and comprehensive analysis for global Edge Inference Chips and Acceleration Cards market. Both quantitative and qualitative analyses are presented by company, by region & country, by Type 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 Edge Inference Chips and Acceleration Cards market size and forecasts, in consumption value ($ Million), 2020-2031
Global Edge Inference Chips and Acceleration Cards market size and forecasts by region and country, in consumption value ($ Million), 2020-2031
Global Edge Inference Chips and Acceleration Cards market size and forecasts, by Type and by Application, in consumption value ($ Million), 2020-2031
Global Edge Inference Chips and Acceleration Cards market shares of main players, in revenue ($ Million), 2020-2025
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 Edge Inference Chips and Acceleration Cards
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 Edge Inference Chips and Acceleration Cards 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 NVIDIA, Cambrian, Hisilicon, Kunlun Core, AMD, Intel, Qualcomm, Hailo, Black Sesame Technologies, Corerain, etc.
This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.
Market segmentation
Edge Inference Chips and Acceleration Cards market is split by Type and by Application. For the period 2020-2031, the growth among segments provides accurate calculations and forecasts for Consumption Value by Type and by Application. This analysis can help you expand your business by targeting qualified niche markets.
Market segment by Type
Chips
Acceleration Cards
Market segment by Application
Smart Transportation
Smart Finance
Industrial Manufacturing
Other
Market segment by players, this report covers
NVIDIA
Cambrian
Hisilicon
Kunlun Core
AMD
Intel
Qualcomm
Hailo
Black Sesame Technologies
Corerain
Market segment by regions, regional analysis covers
North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia, Italy and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia and Rest of Asia-Pacific)
South America (Brazil, Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
The content of the study subjects, includes a total of 13 chapters:
Chapter 1, to describe Edge Inference Chips and Acceleration Cards product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top players of Edge Inference Chips and Acceleration Cards, with revenue, gross margin, and global market share of Edge Inference Chips and Acceleration Cards from 2020 to 2025.
Chapter 3, the Edge Inference Chips and Acceleration Cards competitive situation, revenue, and global market share of top players are analyzed emphatically by landscape contrast.
Chapter 4 and 5, to segment the market size by Type and by Application, with consumption value and growth rate by Type, by Application, from 2020 to 2031
Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2020 to 2025.and Edge Inference Chips and Acceleration Cards market forecast, by regions, by Type and by Application, with consumption value, from 2026 to 2031.
Chapter 11, market dynamics, drivers, restraints, trends, Porters Five Forces analysis.
Chapter 12, the key raw materials and key suppliers, and industry chain of Edge Inference Chips and Acceleration Cards.
Chapter 13, to describe Edge Inference Chips and Acceleration Cards research findings and conclusion.
Table of Contents
87 Pages
- 1 Market Overview
- 2 Company Profiles
- 3 Market Competition, by Players
- 4 Market Size Segment by Type
- 5 Market Size Segment by Application
- 6 North America
- 7 Europe
- 8 Asia-Pacific
- 9 South America
- 10 Middle East & Africa
- 11 Market Dynamics
- 12 Industry Chain Analysis
- 13 Research Findings and Conclusion
- 14 Appendix
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