A graphics processing unit (GPU) is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. GPUs are used in embedded systems, mobile phones, personal computers, workstations, and game consoles. Modern GPUs are very efficient at manipulating computer graphics and image processing, and their highly parallel structure makes them more efficient than general-purpose CPUs for algorithms where the processing of large blocks of data is done in parallel. In a personal computer, a GPU can be present on a video card, or it can be embedded on the motherboard or—in certain CPUs—on the CPU die.
The global GPU for Deep Learning market was valued at US$ million in 2023 and is anticipated to reach US$ million by 2030, witnessing a CAGR of % during the forecast period 2024-2030.
North American market for GPU for Deep Learning is estimated to increase from $ million in 2023 to reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Asia-Pacific market for GPU for Deep Learning is estimated to increase from $ million in 2023 to reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The major global manufacturers of GPU for Deep Learning include Nvidia, AMD and Intel, etc. In 2023, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for GPU for Deep Learning, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding GPU for Deep Learning.
Report Scope
The GPU for Deep Learning market size, estimations, and forecasts are provided in terms of output/shipments (K Units) and revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global GPU for Deep Learning market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the GPU for Deep Learning manufacturers, new entrants, and industry chain related companies in this market with information on the revenues, production, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
Nvidia
AMD
Intel
Segment by Type
RAM Below 4GB
RAM 4~8 GB
RAM 8~12GB
RAM Above 12GB
Segment by Application
Personal Computers
Workstations
Game Consoles
Production by Region
North America
Europe
China
Japan
South Korea
Consumption by Region
North America
U.S.
Canada
Europe
Germany
France
U.K.
Italy
Russia
Asia-Pacific
China
Japan
South Korea
China Taiwan
Southeast Asia
India
Latin America, Middle East & Africa
Mexico
Brazil
Turkey
GCC Countries
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by region, by Type, by 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 2: Detailed analysis of GPU for Deep Learning manufacturers competitive landscape, price, production and value market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Production/output, value of GPU for Deep Learning by region/country. It provides a quantitative analysis of the market size and development potential of each region in the next six years.
Chapter 4: Consumption of GPU for Deep Learning 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 5: 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 6: 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 7: 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 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: 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 10: The main points and conclusions of the report.
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1 GPU for Deep Learning Market Overview
1.1 Product Definition
1.2 GPU for Deep Learning Segment by Type
1.2.1 Global GPU for Deep Learning Market Value Growth Rate Analysis by Type 2023 VS 2030
1.2.2 RAM Below 4GB
1.2.3 RAM 4~8 GB
1.2.4 RAM 8~12GB
1.2.5 RAM Above 12GB
1.3 GPU for Deep Learning Segment by Application
1.3.1 Global GPU for Deep Learning Market Value Growth Rate Analysis by Application: 2023 VS 2030
1.3.2 Personal Computers
1.3.3 Workstations
1.3.4 Game Consoles
1.4 Global Market Growth Prospects
1.4.1 Global GPU for Deep Learning Production Value Estimates and Forecasts (2019-2030)
1.4.2 Global GPU for Deep Learning Production Capacity Estimates and Forecasts (2019-2030)
1.4.3 Global GPU for Deep Learning Production Estimates and Forecasts (2019-2030)
1.4.4 Global GPU for Deep Learning Market Average Price Estimates and Forecasts (2019-2030)
1.5 Assumptions and Limitations
2 Market Competition by Manufacturers
2.1 Global GPU for Deep Learning Production Market Share by Manufacturers (2019-2024)
2.2 Global GPU for Deep Learning Production Value Market Share by Manufacturers (2019-2024)
2.3 Global Key Players of GPU for Deep Learning, Industry Ranking, 2022 VS 2023 VS 2024
2.4 Global GPU for Deep Learning Market Share by Company Type (Tier 1, Tier 2 and Tier 3)
2.5 Global GPU for Deep Learning Average Price by Manufacturers (2019-2024)
2.6 Global Key Manufacturers of GPU for Deep Learning, Manufacturing Base Distribution and Headquarters
2.7 Global Key Manufacturers of GPU for Deep Learning, Product Offered and Application
2.8 Global Key Manufacturers of GPU for Deep Learning, Date of Enter into This Industry
2.9 GPU for Deep Learning Market Competitive Situation and Trends
2.9.1 GPU for Deep Learning Market Concentration Rate
2.9.2 Global 5 and 10 Largest GPU for Deep Learning Players Market Share by Revenue
2.10 Mergers & Acquisitions, Expansion
3 GPU for Deep Learning Production by Region
3.1 Global GPU for Deep Learning Production Value Estimates and Forecasts by Region: 2019 VS 2023 VS 2030
3.2 Global GPU for Deep Learning Production Value by Region (2019-2030)
3.2.1 Global GPU for Deep Learning Production Value Market Share by Region (2019-2024)
3.2.2 Global Forecasted Production Value of GPU for Deep Learning by Region (2025-2030)
3.3 Global GPU for Deep Learning Production Estimates and Forecasts by Region: 2019 VS 2023 VS 2030
3.4 Global GPU for Deep Learning Production by Region (2019-2030)
3.4.1 Global GPU for Deep Learning Production Market Share by Region (2019-2024)
3.4.2 Global Forecasted Production of GPU for Deep Learning by Region (2025-2030)
3.5 Global GPU for Deep Learning Market Price Analysis by Region (2019-2024)
3.6 Global GPU for Deep Learning Production and Value, Year-over-Year Growth
3.6.1 North America GPU for Deep Learning Production Value Estimates and Forecasts (2019-2030)
3.6.2 Europe GPU for Deep Learning Production Value Estimates and Forecasts (2019-2030)
3.6.3 China GPU for Deep Learning Production Value Estimates and Forecasts (2019-2030)
3.6.4 Japan GPU for Deep Learning Production Value Estimates and Forecasts (2019-2030)
3.6.5 South Korea GPU for Deep Learning Production Value Estimates and Forecasts (2019-2030)
4 GPU for Deep Learning Consumption by Region
4.1 Global GPU for Deep Learning Consumption Estimates and Forecasts by Region: 2019 VS 2023 VS 2030
4.2 Global GPU for Deep Learning Consumption by Region (2019-2030)
4.2.1 Global GPU for Deep Learning Consumption by Region (2019-2024)
4.2.2 Global GPU for Deep Learning Forecasted Consumption by Region (2025-2030)
4.3 North America
4.3.1 North America GPU for Deep Learning Consumption Growth Rate by Country: 2019 VS 2023 VS 2030
4.3.2 North America GPU for Deep Learning Consumption by Country (2019-2030)
4.3.3 U.S.
4.3.4 Canada
4.4 Europe
4.4.1 Europe GPU for Deep Learning Consumption Growth Rate by Country: 2019 VS 2023 VS 2030
4.4.2 Europe GPU for Deep Learning Consumption by Country (2019-2030)
4.4.3 Germany
4.4.4 France
4.4.5 U.K.
4.4.6 Italy
4.4.7 Russia
4.5 Asia Pacific
4.5.1 Asia Pacific GPU for Deep Learning Consumption Growth Rate by Region: 2019 VS 2023 VS 2030
4.5.2 Asia Pacific GPU for Deep Learning Consumption by Region (2019-2030)
4.5.3 China
4.5.4 Japan
4.5.5 South Korea
4.5.6 China Taiwan
4.5.7 Southeast Asia
4.5.8 India
4.6 Latin America, Middle East & Africa
4.6.1 Latin America, Middle East & Africa GPU for Deep Learning Consumption Growth Rate by Country: 2019 VS 2023 VS 2030
4.6.2 Latin America, Middle East & Africa GPU for Deep Learning Consumption by Country (2019-2030)
4.6.3 Mexico
4.6.4 Brazil
4.6.5 Turkey
5 Segment by Type
5.1 Global GPU for Deep Learning Production by Type (2019-2030)
5.1.1 Global GPU for Deep Learning Production by Type (2019-2024)
5.1.2 Global GPU for Deep Learning Production by Type (2025-2030)
5.1.3 Global GPU for Deep Learning Production Market Share by Type (2019-2030)
5.2 Global GPU for Deep Learning Production Value by Type (2019-2030)
5.2.1 Global GPU for Deep Learning Production Value by Type (2019-2024)
5.2.2 Global GPU for Deep Learning Production Value by Type (2025-2030)
5.2.3 Global GPU for Deep Learning Production Value Market Share by Type (2019-2030)
5.3 Global GPU for Deep Learning Price by Type (2019-2030)
6 Segment by Application
6.1 Global GPU for Deep Learning Production by Application (2019-2030)
6.1.1 Global GPU for Deep Learning Production by Application (2019-2024)
6.1.2 Global GPU for Deep Learning Production by Application (2025-2030)
6.1.3 Global GPU for Deep Learning Production Market Share by Application (2019-2030)
6.2 Global GPU for Deep Learning Production Value by Application (2019-2030)
6.2.1 Global GPU for Deep Learning Production Value by Application (2019-2024)
6.2.2 Global GPU for Deep Learning Production Value by Application (2025-2030)
6.2.3 Global GPU for Deep Learning Production Value Market Share by Application (2019-2030)
6.3 Global GPU for Deep Learning Price by Application (2019-2030)
7 Key Companies Profiled
7.1 Nvidia
7.1.1 Nvidia GPU for Deep Learning Corporation Information
7.1.2 Nvidia GPU for Deep Learning Product Portfolio
7.1.3 Nvidia GPU for Deep Learning Production, Value, Price and Gross Margin (2019-2024)
7.1.4 Nvidia Main Business and Markets Served
7.1.5 Nvidia Recent Developments/Updates
7.2 AMD
7.2.1 AMD GPU for Deep Learning Corporation Information
7.2.2 AMD GPU for Deep Learning Product Portfolio
7.2.3 AMD GPU for Deep Learning Production, Value, Price and Gross Margin (2019-2024)
7.2.4 AMD Main Business and Markets Served
7.2.5 AMD Recent Developments/Updates
7.3 Intel
7.3.1 Intel GPU for Deep Learning Corporation Information
7.3.2 Intel GPU for Deep Learning Product Portfolio
7.3.3 Intel GPU for Deep Learning Production, Value, Price and Gross Margin (2019-2024)
7.3.4 Intel Main Business and Markets Served
7.3.5 Intel Recent Developments/Updates
8 Industry Chain and Sales Channels Analysis
8.1 GPU for Deep Learning Industry Chain Analysis
8.2 GPU for Deep Learning Key Raw Materials
8.2.1 Key Raw Materials
8.2.2 Raw Materials Key Suppliers
8.3 GPU for Deep Learning Production Mode & Process
8.4 GPU for Deep Learning Sales and Marketing
8.4.1 GPU for Deep Learning Sales Channels
8.4.2 GPU for Deep Learning Distributors
8.5 GPU for Deep Learning Customers
9 GPU for Deep Learning Market Dynamics
9.1 GPU for Deep Learning Industry Trends
9.2 GPU for Deep Learning Market Drivers
9.3 GPU for Deep Learning Market Challenges
9.4 GPU for Deep Learning Market Restraints
10 Research Finding and Conclusion
11 Methodology and Data Source
11.1 Methodology/Research Approach
11.1.1 Research Programs/Design
11.1.2 Market Size Estimation
11.1.3 Market Breakdown and Data Triangulation
11.2 Data Source
11.2.1 Secondary Sources
11.2.2 Primary Sources
11.3 Author List
11.4 Disclaimer
Nvidia
AMD
Intel
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*If Applicable.
