APO RESEARCH · REPORT
Deep Learning Chipset
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.
Product & engineering
Understand the product.
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.
Selected research
Industry Research
Deep Learning Chipset Industry Research Report 2026
Market perspective
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.
Report Scope
Read the full market overview
This report quantifies the global Deep Learning Chipset market in revenue (US$ million) and, where applicable, sales volume (K Units), using 2025 as the base year and providing annual historical and forecast data for 2021–2032.
It standardizes definitions of types and applications, harmonizes vendor attribution, and presents comparable time series by company, type, application, and region/country, including indicative price bands (US$/K Units) and concentration ratios (CR5/CR10).
The outputs are intended to support strategy development, budgeting, and performance benchmarking for manufacturers, new entrants, channel partners, and investors; the report also reviews technology shifts and notable product introductions relevant to Deep Learning Chipset.
Key Companies & Market Share Insights
This section profiles leading manufacturers, combining 2021–2025 results with a 2026–2032 outlook. It reports revenue, market share, price bands, product and application mix, regional and channel mix, and key developments (M&A, capacity additions, certifications). It also provides global revenue, average price, and—where applicable—sales volume by manufacturer, and calculates CR5/CR10 and rank changes to support comparative benchmarking.
Deep Learning Chipset Market by Company
NVIDIA
Intel
IBM
Qualcomm
CEVA
KnuEdge
AMD
Xilinx
ARM
Graphcore
TeraDeep
Wave Computing
BrainChip
Deep Learning Chipset Segment by Type
Graphics Processing Units (GPUs)
Central Processing Units (CPUs)
Application Specific Integrated Circuits (ASICs)
Field Programmable Gate Arrays (FPGAs)
Others
Deep Learning Chipset Segment by Application
Consumer
Aerospace, Military & Defense
Automotive
Industrial
Medical
Others
Deep Learning Chipset Segment by Region
North America
United States
Canada
Mexico
Europe
Germany
France
U.K.
Italy
Russia
Spain
Netherlands
Switzerland
Sweden
Poland
Asia-Pacific
China
Japan
South Korea
India
Australia
Taiwan
Southeast Asia
South America
Brazil
Argentina
Chile
Middle East & Africa
Egypt
South Africa
Israel
Türkiye
GCC Countries
Key Drivers & Barriers
High-impact rendering factors and drivers have been studied in this report to aid the readers to understand the general development. Moreover, the report includes restraints and challenges that may act as stumbling blocks on the way of the players. This will assist the users to be attentive and make informed decisions related to business. Specialists have also laid their focus on the upcoming business prospects.
Reasons to Buy This Report
1. This report will help the readers to understand the competition within the industries and strategies for the competitive environment to enhance the potential profit. The report also focuses on the competitive landscape of the global Deep Learning Chipset market, and introduces in detail the market share, industry ranking, competitor ecosystem, market performance, new product development, operation situation, expansion, and acquisition. etc. of the main players, which helps the readers to identify the main competitors and deeply understand the competition pattern of the market.
2. This report will help stakeholders to understand the global industry status and trends of Deep Learning Chipset and provides them with information on key market drivers, restraints, challenges, and opportunities.
3. This report will help stakeholders to understand competitors better and gain more insights to strengthen their position in their businesses. The competitive landscape section includes the market share and rank (in volume and value), competitor ecosystem, new product development, expansion, and acquisition.
4. This report stays updated with novel technology integration, features, and the latest developments in the market
5. This report helps stakeholders to gain insights into which regions to target globally
6. This report helps stakeholders to gain insights into the end-user perception concerning the adoption of Deep Learning Chipset.
7. This report helps stakeholders to identify some of the key players in the market and understand their valuable contribution.
Chapter Outline
Chapter 1: Research objectives, research methods, data sources, data cross-validation;
Chapter 2: 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.
Chapter 3: Detailed analysis of Deep Learning Chipset manufacturers competitive landscape, price, production and value market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product production/output, value, price, gross margin, product introduction, recent development, etc.
Chapter 5: Production/output, value of Deep Learning Chipset by region/country. It provides a quantitative analysis of the market size and development potential of each region in the next six years.
Chapter 6: Consumption of Deep Learning Chipset 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 production of each country in the world.
Chapter 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.
Chapter 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.
Chapter 9: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 10: Introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 11: The main points and conclusions of the report.
More report detail
Tables and figures
Scope & coverage.
Types
- Graphics Processing Units (GPUs)
- Central Processing Units (CPUs)
- Application Specific Integrated Circuits (ASICs)
- Field Programmable Gate Arrays (FPGAs)
- Others
Applications
- Consumer
- Aerospace, Military & Defense
- Automotive
- Industrial
- Medical
- Others
Companies covered
- NVIDIA
- Intel
- IBM
- Qualcomm
- CEVA
- KnuEdge
- AMD
- Xilinx
- ARM
- Graphcore
- TeraDeep
- Wave Computing
- BrainChip
Inside the report.
1 Preface
- 1.1 Scope of Report
- 1.2 Reasons for Doing This Study
- 1.3 Research Methodology
- 1.4 Research Process
- 1.5 Data Source
- 1.5.1 Secondary Sources
- 1.5.2 Primary Sources
2 Market Overview
- 2.1 Product Definition
- 2.2 Deep Learning Chipset by Type
- 2.2.1 Market Value Comparison by Type (2021 VS 2025 VS 2032) & (US$ Million)
- 2.2.2 Graphics Processing Units (GPUs)
- 2.2.3 Central Processing Units (CPUs)
- 2.2.4 Application Specific Integrated Circuits (ASICs)
- 2.2.5 Field Programmable Gate Arrays (FPGAs)
- 2.2.6 Others
- 2.3 Deep Learning Chipset by Application
- 2.3.1 Market Value Comparison by Application (2021 VS 2025 VS 2032) & (US$ Million)
- 2.3.2 Consumer
- 2.3.3 Aerospace, Military & Defense
- 2.3.4 Automotive
- 2.3.5 Industrial
- 2.3.6 Medical
- 2.3.7 Others
- 2.4 Global Market Growth Prospects
- 2.4.1 Global Deep Learning Chipset Production Value Estimates and Forecasts (2021-2032)
- 2.4.2 Global Deep Learning Chipset Production Capacity Estimates and Forecasts (2021-2032)
- 2.4.3 Global Deep Learning Chipset Production Estimates and Forecasts (2021-2032)
- 2.4.4 Global Deep Learning Chipset Market Average Price (2021-2032)
3 Market Competitive Landscape by Manufacturers
- 3.1 Global Deep Learning Chipset Production by Manufacturers (2021-2026)
- 3.2 Global Deep Learning Chipset Production Value by Manufacturers (2021-2026)
- 3.3 Global Deep Learning Chipset Average Price by Manufacturers (2021-2026)
- 3.4 Global Deep Learning Chipset Industry Manufacturers Ranking, 2024 VS 2025 VS 2026
- 3.5 Global Deep Learning Chipset Key Manufacturers, Manufacturing Sites & Headquarters
- 3.6 Global Deep Learning Chipset Manufacturers, Product Type & Application
- 3.7 Global Deep Learning Chipset Manufacturers Established Date
- 3.8 Global Deep Learning Chipset Market CR5 and HHI
- 3.9 Global Manufacturers Mergers & Acquisition
4 Manufacturers Profiled
- 4.1 NVIDIA
- 4.1.1 NVIDIA Deep Learning Chipset Company Information
- 4.1.2 NVIDIA Deep Learning Chipset Business Overview
- 4.1.3 NVIDIA Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.1.4 NVIDIA Product Portfolio
- 4.1.5 NVIDIA Recent Developments
- 4.2 Intel
- 4.2.1 Intel Deep Learning Chipset Company Information
- 4.2.2 Intel Deep Learning Chipset Business Overview
- 4.2.3 Intel Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.2.4 Intel Product Portfolio
- 4.2.5 Intel Recent Developments
- 4.3 IBM
- 4.3.1 IBM Deep Learning Chipset Company Information
- 4.3.2 IBM Deep Learning Chipset Business Overview
- 4.3.3 IBM Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.3.4 IBM Product Portfolio
- 4.3.5 IBM Recent Developments
- 4.4 Qualcomm
- 4.4.1 Qualcomm Deep Learning Chipset Company Information
- 4.4.2 Qualcomm Deep Learning Chipset Business Overview
- 4.4.3 Qualcomm Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.4.4 Qualcomm Product Portfolio
- 4.4.5 Qualcomm Recent Developments
- 4.5 CEVA
- 4.5.1 CEVA Deep Learning Chipset Company Information
- 4.5.2 CEVA Deep Learning Chipset Business Overview
- 4.5.3 CEVA Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.5.4 CEVA Product Portfolio
- 4.5.5 CEVA Recent Developments
- 4.6 KnuEdge
- 4.6.1 KnuEdge Deep Learning Chipset Company Information
- 4.6.2 KnuEdge Deep Learning Chipset Business Overview
- 4.6.3 KnuEdge Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.6.4 KnuEdge Product Portfolio
- 4.6.5 KnuEdge Recent Developments
- 4.7 AMD
- 4.7.1 AMD Deep Learning Chipset Company Information
- 4.7.2 AMD Deep Learning Chipset Business Overview
- 4.7.3 AMD Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.7.4 AMD Product Portfolio
- 4.7.5 AMD Recent Developments
- 4.8 Xilinx
- 4.8.1 Xilinx Deep Learning Chipset Company Information
- 4.8.2 Xilinx Deep Learning Chipset Business Overview
- 4.8.3 Xilinx Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.8.4 Xilinx Product Portfolio
- 4.8.5 Xilinx Recent Developments
- 4.9 ARM
- 4.9.1 ARM Deep Learning Chipset Company Information
- 4.9.2 ARM Deep Learning Chipset Business Overview
- 4.9.3 ARM Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.9.4 ARM Product Portfolio
- 4.9.5 ARM Recent Developments
- 4.10 Google
- 4.10.1 Google Deep Learning Chipset Company Information
- 4.10.2 Google Deep Learning Chipset Business Overview
- 4.10.3 Google Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.10.4 Google Product Portfolio
- 4.10.5 Google Recent Developments
- 4.11 Graphcore
- 4.11.1 Graphcore Deep Learning Chipset Company Information
- 4.11.2 Graphcore Deep Learning Chipset Business Overview
- 4.11.3 Graphcore Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.11.4 Graphcore Product Portfolio
- 4.11.5 Graphcore Recent Developments
- 4.12 TeraDeep
- 4.12.1 TeraDeep Deep Learning Chipset Company Information
- 4.12.2 TeraDeep Deep Learning Chipset Business Overview
- 4.12.3 TeraDeep Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.12.4 TeraDeep Product Portfolio
- 4.12.5 TeraDeep Recent Developments
- 4.13 Wave Computing
- 4.13.1 Wave Computing Deep Learning Chipset Company Information
- 4.13.2 Wave Computing Deep Learning Chipset Business Overview
- 4.13.3 Wave Computing Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.13.4 Wave Computing Product Portfolio
- 4.13.5 Wave Computing Recent Developments
- 4.14 BrainChip
- 4.14.1 BrainChip Deep Learning Chipset Company Information
- 4.14.2 BrainChip Deep Learning Chipset Business Overview
- 4.14.3 BrainChip Deep Learning Chipset Production, Value and Gross Margin (2021-2026)
- 4.14.4 BrainChip Product Portfolio
- 4.14.5 BrainChip Recent Developments
5 Global Deep Learning Chipset Production by Region
- 5.1 Global Deep Learning Chipset Production Estimates and Forecasts by Region: 2021 VS 2025 VS 2032
- 5.2 Global Deep Learning Chipset Production by Region: 2021-2032
- 5.2.1 Global Deep Learning Chipset Production by Region: 2021-2026
- 5.2.2 Global Deep Learning Chipset Production Forecast by Region (2027-2032)
- 5.3 Global Deep Learning Chipset Production Value Estimates and Forecasts by Region: 2021 VS 2025 VS 2032
- 5.4 Global Deep Learning Chipset Production Value by Region: 2021-2032
- 5.4.1 Global Deep Learning Chipset Production Value by Region: 2021-2026
- 5.4.2 Global Deep Learning Chipset Production Value Forecast by Region (2027-2032)
- 5.5 Global Deep Learning Chipset Market Price Analysis by Region (2021-2026)
- 5.6 Global Deep Learning Chipset Production and Value, YOY Growth
- 5.6.1 North America Deep Learning Chipset Production Value Estimates and Forecasts (2021-2032)
- 5.6.2 Europe Deep Learning Chipset Production Value Estimates and Forecasts (2021-2032)
- 5.6.3 China Deep Learning Chipset Production Value Estimates and Forecasts (2021-2032)
- 5.6.4 Japan Deep Learning Chipset Production Value Estimates and Forecasts (2021-2032)
6 Global Deep Learning Chipset Consumption by Region
- 6.1 Global Deep Learning Chipset Consumption Estimates and Forecasts by Region: 2021 VS 2025 VS 2032
- 6.2 Global Deep Learning Chipset Consumption by Region (2021-2032)
- 6.2.1 Global Deep Learning Chipset Consumption by Region: 2021-2026
- 6.2.2 Global Deep Learning Chipset Forecasted Consumption by Region (2027-2032)
- 6.3 North America
- 6.3.1 North America Deep Learning Chipset Consumption Growth Rate by Country: 2021 VS 2025 VS 2032
- 6.3.2 North America Deep Learning Chipset Consumption by Country (2021-2032)
- 6.3.3 United States
- 6.3.4 Canada
- 6.3.5 Mexico
- 6.4 Europe
- 6.4.1 Europe Deep Learning Chipset Consumption Growth Rate by Country: 2021 VS 2025 VS 2032
- 6.4.2 Europe Deep Learning Chipset Consumption by Country (2021-2032)
- 6.4.3 Germany
- 6.4.4 France
- 6.4.5 U.K.
- 6.4.6 Italy
- 6.4.7 Russia
- 6.4.8 Spain
- 6.4.9 Netherlands
- 6.4.10 Switzerland
- 6.4.11 Sweden
- 6.4.12 Poland
- 6.5 Asia Pacific
- 6.5.1 Asia Pacific Deep Learning Chipset Consumption Growth Rate by Country: 2021 VS 2025 VS 2032
- 6.5.2 Asia Pacific Deep Learning Chipset Consumption by Country (2021-2032)
- 6.5.3 China
- 6.5.4 Japan
- 6.5.5 South Korea
- 6.5.6 India
- 6.5.7 Australia
- 6.5.8 Taiwan
- 6.5.9 Southeast Asia
- 6.6 South America, Middle East & Africa
- 6.6.1 South America, Middle East & Africa Deep Learning Chipset Consumption Growth Rate by Country: 2021 VS 2025 VS 2032
- 6.6.2 South America, Middle East & Africa Deep Learning Chipset Consumption by Country (2021-2032)
- 6.6.3 Brazil
- 6.6.4 Argentina
- 6.6.5 Chile
- 6.6.6 Turkey
- 6.6.7 GCC Countries
7 Segment by Type
- 7.1 Global Deep Learning Chipset Production by Type (2021-2032)
- 7.1.1 Global Deep Learning Chipset Production by Type (2021-2032) & (K Units)
- 7.1.2 Global Deep Learning Chipset Production Market Share by Type (2021-2032)
- 7.2 Global Deep Learning Chipset Production Value by Type (2021-2032)
- 7.2.1 Global Deep Learning Chipset Production Value by Type (2021-2032) & (US$ Million)
- 7.2.2 Global Deep Learning Chipset Production Value Market Share by Type (2021-2032)
- 7.3 Global Deep Learning Chipset Price by Type (2021-2032)
8 Segment by Application
- 8.1 Global Deep Learning Chipset Production by Application (2021-2032)
- 8.1.1 Global Deep Learning Chipset Production by Application (2021-2032) & (K Units)
- 8.1.2 Global Deep Learning Chipset Production Market Share by Application (2021-2032)
- 8.2 Global Deep Learning Chipset Production Value by Application (2021-2032)
- 8.2.1 Global Deep Learning Chipset Production Value by Application (2021-2032) & (US$ Million)
- 8.2.2 Global Deep Learning Chipset Production Value Market Share by Application (2021-2032)
- 8.3 Global Deep Learning Chipset Price by Application (2021-2032)
9 Value Chain and Sales Channels Analysis of the Market
- 9.1 Deep Learning Chipset Value Chain Analysis
- 9.1.1 Deep Learning Chipset Key Raw Materials
- 9.1.2 Raw Materials Key Suppliers
- 9.1.3 Deep Learning Chipset Production Mode & Process
- 9.2 Deep Learning Chipset Sales Channels Analysis
- 9.2.1 Direct Comparison with Distribution Share
- 9.2.2 Deep Learning Chipset Distributors
- 9.2.3 Deep Learning Chipset Customers
10 Global Deep Learning Chipset Analyzing Market Dynamics
- 10.1 Deep Learning Chipset Industry Trends
- 10.2 Deep Learning Chipset Industry Drivers
- 10.3 Deep Learning Chipset Industry Opportunities and Challenges
- 10.4 Deep Learning Chipset Industry Restraints
11 Report Conclusion
12 Disclaimer
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