Global Deep Learning Chipset Market 2025 by Manufacturers, Regions, Type and Application, Forecast to 2031

According to our (Global Info Research) latest study, the global Deep Learning Chipset market size was valued at US$ 6216 million in 2024 and is forecast to a readjusted size of USD 52990 million by 2031 with a CAGR of 36.2% during review period.

Deep learning technology is driving the evolution of artificial intelligence (AI) and has become one of the hottest topics of discussion within the technology world and beyond. Given the rate at which deep learning is progressing, some industry observers are predicting it will bring about a doomsday scenario, while others strive for a time when the technology can transform business processes and create new business models through scalable, more efficient automation and predictive capabilities. The current market climate is ripe for innovation in hardware in general, and chipsets more specifically.In the industry, NVIDIA profits most in 2016 and recent years, while Intel and IBM ranked 2 and 3.The market share of them is 26.72%, 20.57% and 12.56% in 2016.The gap of market share is keep on enlarged due to different strategy.

NVIDIA, Intel and IBM are the leaders of the Deep Learning Chipset industry, which take about 50% market share. United States is the major region of the global market, which takes about 70% market share.

This report is a detailed and comprehensive analysis for global Deep Learning Chipset market. Both quantitative and qualitative analyses are presented by manufacturers, 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 Deep Learning Chipset market size and forecasts, in consumption value ($ Million), sales quantity (K Units), and average selling prices (USD/Unit), 2020-2031

Global Deep Learning Chipset market size and forecasts by region and country, in consumption value ($ Million), sales quantity (K Units), and average selling prices (USD/Unit), 2020-2031

Global Deep Learning Chipset market size and forecasts, by Type and by Application, in consumption value ($ Million), sales quantity (K Units), and average selling prices (USD/Unit), 2020-2031

Global Deep Learning Chipset market shares of main players, shipments in revenue ($ Million), sales quantity (K Units), and ASP (USD/Unit), 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 Deep Learning Chipset

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 Deep Learning Chipset 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 NVIDIA, Intel, IBM, Qualcomm, CEVA, KnuEdge, AMD, Xilinx, ARM, Google, etc.

This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.

Market Segmentation

Deep Learning Chipset 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 in terms of volume and value. This analysis can help you expand your business by targeting qualified niche markets.

Market segment by Type
Graphics Processing Units (GPUs)
Central Processing Units (CPUs)
Application Specific Integrated Circuits (ASICs)
Field Programmable Gate Arrays (FPGAs)
Others

Market segment by Application
Consumer
Aerospace, Military & Defense
Automotive
Industrial
Medical
Others

Major players covered
NVIDIA
Intel
IBM
Qualcomm
CEVA
KnuEdge
AMD
Xilinx
ARM
Google
Graphcore
TeraDeep
Wave Computing
BrainChip

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 Deep Learning Chipset product scope, market overview, market estimation caveats and base year.

Chapter 2, to profile the top manufacturers of Deep Learning Chipset, with price, sales quantity, revenue, and global market share of Deep Learning Chipset from 2020 to 2025.

Chapter 3, the Deep Learning Chipset competitive situation, sales quantity, revenue, and global market share of top manufacturers are analyzed emphatically by landscape contrast.

Chapter 4, the Deep Learning Chipset breakdown data are shown at the regional level, to show the sales quantity, consumption value, and growth by regions, from 2020 to 2031.

Chapter 5 and 6, to segment the sales by Type and by Application, with sales market share and growth rate by Type, by Application, from 2020 to 2031.

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 2020 to 2025.and Deep Learning Chipset market forecast, by regions, by Type, and by Application, with sales and revenue, from 2026 to 2031.

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 Deep Learning Chipset.

Chapter 14 and 15, to describe Deep Learning Chipset sales channel, distributors, customers, research findings and conclusion.