Multimodal models are designed to process and generate content using multiple modalities, such as text, images, audio, or video. These models combine information from different modalities to gain a better understanding of the input data and generate more comprehensive outputs.
The global Multimodal Models market was valued at US$ 158 million in 2023 and is anticipated to reach US$ 10640 million by 2030, witnessing a CAGR of 52.0% during the forecast period 2024-2030.
North American market for Multimodal Models 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 Multimodal Models 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 global market for Multimodal Models in Medical is estimated to increase from $ million in 2023 to $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The major global companies of Multimodal Models include OpenAI, Gemini (Google), Meta, Twelve Labs, Pika, Runway, Adept, Inworld AI, Hundsun Technologies, Zhejiang Jinke Tom Culture Industry, 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 Multimodal Models, 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 Multimodal Models.
The Multimodal Models market size, estimations, and forecasts are provided in terms of 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 Multimodal Models 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 Multimodal Models companies, new entrants, and industry chain related companies in this market with information on the revenues 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
OpenAI
Gemini (Google)
Meta
Twelve Labs
Pika
Runway
Adept
Inworld AI
Hundsun Technologies
Zhejiang Jinke Tom Culture Industry
Dahua Technology
ThunderSoft
Taichu
Nanjing Tuodao Medical Technology
HiDream.ai
Suzhou Keda Technology
Segment by Type
Multimodal Representation
Translation
Alignment
Multimodal Fusion
Co-learning
Segment by Application
Medical
Finance
Retail and E-commerce
Entertainment
Others
By Region
North America
United States
Canada
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Europe
Germany
France
U.K.
Italy
Russia
Nordic Countries
Rest of Europe
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (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: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Multimodal Models company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: 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 5: 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 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. 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 capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
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1 Multimodal Models Overview
1.1 Multimodal Models Market Overview and Study Scope
1.2 Market Analysis by Type
1.2.1 Multimodal Representation
1.2.2 Translation
1.2.3 Alignment
1.2.4 Multimodal Fusion
1.2.5 Co-learning
1.3 Global Multimodal Models Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.4 Global Multimodal Models Market Size by Type (2019-2030)
1.4.1 Global Multimodal Models Historic Market Size by Type (2019-2024)
1.4.2 Global Multimodal Models Forecasted Market Size by Type (2025-2030)
1.4.3 Global Multimodal Models Revenue Market Share by Type (2019-2030)
1.5 China Multimodal Models Market Size by Type (2019-2030)
1.5.1 China Multimodal Models Historic Market Size by Type (2019-2024)
1.5.2 China Multimodal Models Forecasted Market Size by Type (2025-2030)
1.5.3 China Multimodal Models Revenue Market Share by Type (2019-2030)
2 Market by Application
2.1 Market Analysis by Application
2.1.1 Medical
2.1.2 Finance
2.1.3 Retail and E-commerce
2.1.4 Entertainment
2.1.5 Others
2.2 Global Multimodal Models Market Share by Application: 2019 VS 2023 VS 2030
2.3 Global Multimodal Models Market Size by Application
2.3.1 Global Multimodal Models Historic Market Size by Application (2019-2024)
2.3.2 Global Multimodal Models Forecasted Market Size by Application (2025-2030)
2.3.3 Global Multimodal Models Revenue Market Share by Application (2019-2030)
2.4 China Multimodal Models Market Size by Application
2.4.1 China Multimodal Models Historic Market Size by Application (2019-2024)
2.4.2 China Multimodal Models Forecasted Market Size by Application (2025-2030)
2.4.3 China Multimodal Models Revenue Market Share by Application (2019-2030)
3 Multimodal Models Market Size by Region
3.1 Global Multimodal Models Market Size by Region: 2019 VS 2023 VS 2030
3.1.1 Global Multimodal Models Historic Market Size by Region (2019-2024)
3.1.2 Global Multimodal Models Forecasted Market Size by Region (2025-2030)
3.1.3 Global Multimodal Models Market Share by Region (2019-2030)
3.2 North America Multimodal Models Market Size YoY Growth (2019-2030)
3.3 Europe Multimodal Models Market Size YoY Growth (2019-2030)
3.4 Japan Multimodal Models Market Size YoY Growth (2019-2030)
3.5 China Multimodal Models Market Size YoY Growth (2019-2030)
3.6 Southeast Asia Multimodal Models Market Size YoY Growth (2019-2030)
3.7 India Multimodal Models Market Size YoY Growth (2019-2030)
4 Global Competition Landscape by Players
4.1 Global Multimodal Models Revenue by Players (2019-2024)
4.2 Global Multimodal Models Competition by Players
4.2.1 Global Multimodal Models Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
4.2.2 Global Top 10 and Top 5 Companies by Multimodal Models Revenue in 2023
4.3 Global Key Players of Multimodal Models, Ranking by Revenue, 2022 VS 2023 VS 2024
4.4 Global Key Players of Multimodal Models Head office and Area Served
4.5 Global Key Players of Multimodal Models, Product and Application
4.6 Global Key Players of Multimodal Models, Date of Enter into This Industry
4.7 Mergers & Acquisitions, Expansion Plans
4.8 Global Multimodal Models Leading Companies SWOT Analysis
5 China Multimodal Models Competition Analysis by Players
5.1 China Top Multimodal Models Players by Revenue (2019-2024)
5.2 China Top 3 and Top 5 Companies by Multimodal Models Revenue in 2023
6 Key Players Profiles
6.1 OpenAI
6.1.1 OpenAI Company Details
6.1.2 OpenAI Multimodal Models Introduction
6.1.3 OpenAI Revenue in Multimodal Models Business (2019-2024)
6.1.4 OpenAI Profile and Main Business
6.1.5 OpenAI Recent Development
6.2 Gemini (Google)
6.2.1 Gemini (Google) Company Details
6.2.2 Gemini (Google) Multimodal Models Introduction
6.2.3 Gemini (Google) Revenue in Multimodal Models Business (2019-2024)
6.2.4 Gemini (Google) Profile and Main Business
6.2.5 Gemini (Google) Recent Development
6.3 Meta
6.3.1 Meta Company Details
6.3.2 Meta Multimodal Models Introduction
6.3.3 Meta Revenue in Multimodal Models Business (2019-2024)
6.3.4 Meta Profile and Main Business
6.3.5 Meta Recent Development
6.4 Twelve Labs
6.4.1 Twelve Labs Company Details
6.4.2 Twelve Labs Multimodal Models Introduction
6.4.3 Twelve Labs Revenue in Multimodal Models Business (2019-2024)
6.4.4 Twelve Labs Profile and Main Business
6.4.5 Twelve Labs Recent Development
6.5 Pika
6.5.1 Pika Company Details
6.5.2 Pika Multimodal Models Introduction
6.5.3 Pika Revenue in Multimodal Models Business (2019-2024)
6.5.4 Pika Profile and Main Business
6.5.5 Pika Recent Development
6.6 Runway
6.6.1 Runway Company Details
6.6.2 Runway Multimodal Models Introduction
6.6.3 Runway Revenue in Multimodal Models Business (2019-2024)
6.6.4 Runway Profile and Main Business
6.6.5 Runway Recent Development
6.7 Adept
6.7.1 Adept Company Details
6.7.2 Adept Multimodal Models Introduction
6.7.3 Adept Revenue in Multimodal Models Business (2019-2024)
6.7.4 Adept Profile and Main Business
6.7.5 Adept Recent Development
6.8 Inworld AI
6.8.1 Inworld AI Company Details
6.8.2 Inworld AI Multimodal Models Introduction
6.8.3 Inworld AI Revenue in Multimodal Models Business (2019-2024)
6.8.4 Inworld AI Profile and Main Business
6.8.5 Inworld AI Recent Development
6.9 Hundsun Technologies
6.9.1 Hundsun Technologies Company Details
6.9.2 Hundsun Technologies Multimodal Models Introduction
6.9.3 Hundsun Technologies Revenue in Multimodal Models Business (2019-2024)
6.9.4 Hundsun Technologies Profile and Main Business
6.9.5 Hundsun Technologies Recent Development
6.10 Zhejiang Jinke Tom Culture Industry
6.10.1 Zhejiang Jinke Tom Culture Industry Company Details
6.10.2 Zhejiang Jinke Tom Culture Industry Multimodal Models Introduction
6.10.3 Zhejiang Jinke Tom Culture Industry Revenue in Multimodal Models Business (2019-2024)
6.10.4 Zhejiang Jinke Tom Culture Industry Profile and Main Business
6.10.5 Zhejiang Jinke Tom Culture Industry Recent Development
6.11 Dahua Technology
6.11.1 Dahua Technology Company Details
6.11.2 Dahua Technology Multimodal Models Introduction
6.11.3 Dahua Technology Revenue in Multimodal Models Business (2019-2024)
6.11.4 Dahua Technology Profile and Main Business
6.11.5 Dahua Technology Recent Development
6.12 ThunderSoft
6.12.1 ThunderSoft Company Details
6.12.2 ThunderSoft Multimodal Models Introduction
6.12.3 ThunderSoft Revenue in Multimodal Models Business (2019-2024)
6.12.4 ThunderSoft Profile and Main Business
6.12.5 ThunderSoft Recent Development
6.13 Taichu
6.13.1 Taichu Company Details
6.13.2 Taichu Multimodal Models Introduction
6.13.3 Taichu Revenue in Multimodal Models Business (2019-2024)
6.13.4 Taichu Profile and Main Business
6.13.5 Taichu Recent Development
6.14 Nanjing Tuodao Medical Technology
6.14.1 Nanjing Tuodao Medical Technology Company Details
6.14.2 Nanjing Tuodao Medical Technology Multimodal Models Introduction
6.14.3 Nanjing Tuodao Medical Technology Revenue in Multimodal Models Business (2019-2024)
6.14.4 Nanjing Tuodao Medical Technology Profile and Main Business
6.14.5 Nanjing Tuodao Medical Technology Recent Development
6.15 HiDream.ai
6.15.1 HiDream.ai Company Details
6.15.2 HiDream.ai Multimodal Models Introduction
6.15.3 HiDream.ai Revenue in Multimodal Models Business (2019-2024)
6.15.4 HiDream.ai Profile and Main Business
6.15.5 HiDream.ai Recent Development
6.16 Suzhou Keda Technology
6.16.1 Suzhou Keda Technology Company Details
6.16.2 Suzhou Keda Technology Multimodal Models Introduction
6.16.3 Suzhou Keda Technology Revenue in Multimodal Models Business (2019-2024)
6.16.4 Suzhou Keda Technology Profile and Main Business
6.16.5 Suzhou Keda Technology Recent Development
7 Industry Development Environment Analysis
7.1 Multimodal Models Industry Trends
7.2 Multimodal Models Market Drivers
7.3 Multimodal Models Market Challenges
7.4 Multimodal Models Market Restraints
8 Analyst's Viewpoints/Conclusions
9 Appendix
9.1 Research Methodology
9.1.1 Methodology/Research Approach
9.1.1.1 Research Programs/Design
9.1.1.2 Market Size Estimation
9.1.1.3 Market Breakdown and Data Triangulation
9.1.2 Data Source
9.1.2.1 Secondary Sources
9.1.2.2 Primary Sources
9.2 Author Details
9.3 Disclaimer
OpenAI
Gemini (Google)
Meta
Twelve Labs
Pika
Runway
Adept
Inworld AI
Hundsun Technologies
Zhejiang Jinke Tom Culture Industry
Dahua Technology
ThunderSoft
Taichu
Nanjing Tuodao Medical Technology
HiDream.ai
Suzhou Keda Technology
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*If Applicable.
