The vision-language models (vlm) for robotics market size has grown exponentially in recent years. It will grow from $1.93 billion in 2025 to $2.45 billion in 2026 at a compound annual growth rate (CAGR) of 26.7%. The growth in the historic period can be attributed to growth in industrial robotics adoption, expansion of machine vision systems, rise in robotic automation projects, improvement in robot sensors, increase in warehouse robotics.
The vision-language models (vlm) for robotics market size is expected to see exponential growth in the next few years. It will grow to $6.36 billion in 2030 at a compound annual growth rate (CAGR) of 27%. The growth in the forecast period can be attributed to expansion of autonomous robot fleets, rising AI driven robotics investment, growth in service robotics, higher demand for human robot interaction, increasing edge AI robotics platforms. Major trends in the forecast period include growth in multimodal robotic perception, rising vision guided command execution, expansion of language driven robot control, integration of scene understanding models, adoption of multimodal robotic training systems.
The increasing demand for industrial automation is expected to accelerate the growth of the vision-language models (VLM) for robotics market in the coming years. Industrial automation involves the application of advanced technologies such as robotics, artificial intelligence, and control systems to perform manufacturing and production activities with minimal human involvement, improving efficiency and precision. Demand for industrial automation is rising as manufacturers face continuous pressure to improve productivity while lowering operational costs, with automation systems enabling faster, more consistent output, reduced labor dependence, fewer errors, and improved equipment utilization across high-volume and precision-focused operations. As industries expand automation adoption to enhance productivity, robots equipped with VLMs capable of understanding both visual data and language commands become essential for flexible and intelligent performance in complex industrial environments. For example, in September 2024, according to the International Federation of Robotics (IFR), a Germany-based non-profit organization, factories worldwide operated approximately 4.28 million robotic units, reflecting around 10% year-over-year growth. Therefore, the increasing demand for industrial automation is advancing the growth of the vision-language models for robotics market.
Leading companies operating in the vision-language models (VLM) for robotics market are focusing on developing advanced solutions, such as lightweight open-source vision-language-action models, to enhance accessibility and performance in robotic perception and control. Vision-language-action models combine visual input, natural language understanding, and action prediction within a unified framework, allowing robots to interpret environments and perform complex tasks autonomously. For instance, in June 2025, Hugging Face, a US-based AI company, launched SmolVLA, a compact open-source vision-language-action model designed for robotics that runs efficiently on consumer hardware while delivering performance comparable to larger models. SmolVLA features a modular architecture with a lightweight SmolVLM-2 vision-language backbone and a transformer-based Action Expert that predicts robot actions from perceptual inputs and instructions. It reduces visual tokens for faster inference, applies layer skipping and interlaced attention for efficient multimodal processing, and supports asynchronous inference to allow action prediction during task execution, helping control computational demands and expand access to VLA technology.
In June 2024, ABB Robotics, a Switzerland-based company specializing in vision-language models for robotics, formed a strategic partnership with Landing AI to accelerate the development and implementation of AI-driven robotics applications. Through this partnership, ABB Robotics aims to simplify robot programming, increase operational flexibility, and speed up deployment across industrial environments by integrating advanced vision systems and AI software. Landing AI is a US-based provider of computer vision platforms and AI solutions that support rapid creation, training, and deployment of visual AI models for industrial automation and inspection.
Major companies operating in the vision-language models (vlm) for robotics market are Amazon.com Inc., Google LLC, Microsoft Corporation, Huawei Technologies Co. Ltd., Tesla Inc., Siemens AG, IBM Research, Meta Platforms Inc., ABB Ltd., NVIDIA Corporation, Samsung Electronics Co. Ltd., Intel Corporation, Baidu Inc., SenseTime, OpenAI LLC, Skild AI, 1X Technologies LLC, Agility Robotics, Covariant, and Preferred Networks.
Tariffs on robotic controllers, vision sensors, and edge AI processors are increasing system costs in the vision language models for robotics market. Import duties on cameras and embedded compute modules are impacting hardware intensive robotic platforms the most. Manufacturing and logistics robotics deployments in import dependent regions face higher project budgets. Industrial and service robotics segments are especially affected due to integrated hardware stacks. At the same time, tariffs are encouraging local robotics hardware assembly and regional supplier ecosystems. Vendors are increasing domestic sourcing of components. This improves supply stability while raising near term robot system costs.
The vision-language models (vlm) for robotics market research report is one of a series of new reports that provides vision-language models (vlm) for robotics market statistics, including vision-language models (vlm) for robotics industry global market size, regional shares, competitors with a vision-language models (vlm) for robotics market share, detailed vision-language models (vlm) for robotics market segments, market trends and opportunities, and any further data you may need to thrive in the vision-language models (vlm) for robotics industry. This vision-language models (vlm) for robotics market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.
Vision-language models for robotics involve AI systems that merge visual perception with natural language processing to allow robots to interpret both visual inputs and spoken or written instructions together. These models enable robots to understand surroundings, follow complex commands, and perform reasoning-based actions using combined image, video, and text data.
The primary components of vision-language models for robotics include software, hardware, and services. Software refers to platforms that allow robots to interpret and process visual and textual inputs to enhance perception, decision-making, and task performance. These solutions are deployed through on-premises, cloud, and other deployment models based on organizational infrastructure and operational requirements. The various applications involved include industrial robotics, service robotics, autonomous vehicles, healthcare robotics, consumer robotics, and other applications. The end users include manufacturing companies, healthcare providers, automotive firms, retail organizations, logistics service providers, defense organizations, and others.
The vision-language models (VLM) for robotics market consists of revenues earned by entities by providing services such as multimodal artificial intelligence model development, visual perception and language fusion platforms, robotic reasoning and decision-making software and real-time vision-language inference systems. The market value includes the value of related goods sold by the service provider or included within the service offering. The vision-language models (VLM) for robotics market also includes sales of trained model frameworks, robotic vision sensor integration modules and edge inference hardware and software toolkits for multimodal learning and deployment. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
This product will be delivered within 1-3 business days.
The vision-language models (vlm) for robotics market size is expected to see exponential growth in the next few years. It will grow to $6.36 billion in 2030 at a compound annual growth rate (CAGR) of 27%. The growth in the forecast period can be attributed to expansion of autonomous robot fleets, rising AI driven robotics investment, growth in service robotics, higher demand for human robot interaction, increasing edge AI robotics platforms. Major trends in the forecast period include growth in multimodal robotic perception, rising vision guided command execution, expansion of language driven robot control, integration of scene understanding models, adoption of multimodal robotic training systems.
The increasing demand for industrial automation is expected to accelerate the growth of the vision-language models (VLM) for robotics market in the coming years. Industrial automation involves the application of advanced technologies such as robotics, artificial intelligence, and control systems to perform manufacturing and production activities with minimal human involvement, improving efficiency and precision. Demand for industrial automation is rising as manufacturers face continuous pressure to improve productivity while lowering operational costs, with automation systems enabling faster, more consistent output, reduced labor dependence, fewer errors, and improved equipment utilization across high-volume and precision-focused operations. As industries expand automation adoption to enhance productivity, robots equipped with VLMs capable of understanding both visual data and language commands become essential for flexible and intelligent performance in complex industrial environments. For example, in September 2024, according to the International Federation of Robotics (IFR), a Germany-based non-profit organization, factories worldwide operated approximately 4.28 million robotic units, reflecting around 10% year-over-year growth. Therefore, the increasing demand for industrial automation is advancing the growth of the vision-language models for robotics market.
Leading companies operating in the vision-language models (VLM) for robotics market are focusing on developing advanced solutions, such as lightweight open-source vision-language-action models, to enhance accessibility and performance in robotic perception and control. Vision-language-action models combine visual input, natural language understanding, and action prediction within a unified framework, allowing robots to interpret environments and perform complex tasks autonomously. For instance, in June 2025, Hugging Face, a US-based AI company, launched SmolVLA, a compact open-source vision-language-action model designed for robotics that runs efficiently on consumer hardware while delivering performance comparable to larger models. SmolVLA features a modular architecture with a lightweight SmolVLM-2 vision-language backbone and a transformer-based Action Expert that predicts robot actions from perceptual inputs and instructions. It reduces visual tokens for faster inference, applies layer skipping and interlaced attention for efficient multimodal processing, and supports asynchronous inference to allow action prediction during task execution, helping control computational demands and expand access to VLA technology.
In June 2024, ABB Robotics, a Switzerland-based company specializing in vision-language models for robotics, formed a strategic partnership with Landing AI to accelerate the development and implementation of AI-driven robotics applications. Through this partnership, ABB Robotics aims to simplify robot programming, increase operational flexibility, and speed up deployment across industrial environments by integrating advanced vision systems and AI software. Landing AI is a US-based provider of computer vision platforms and AI solutions that support rapid creation, training, and deployment of visual AI models for industrial automation and inspection.
Major companies operating in the vision-language models (vlm) for robotics market are Amazon.com Inc., Google LLC, Microsoft Corporation, Huawei Technologies Co. Ltd., Tesla Inc., Siemens AG, IBM Research, Meta Platforms Inc., ABB Ltd., NVIDIA Corporation, Samsung Electronics Co. Ltd., Intel Corporation, Baidu Inc., SenseTime, OpenAI LLC, Skild AI, 1X Technologies LLC, Agility Robotics, Covariant, and Preferred Networks.
Tariffs on robotic controllers, vision sensors, and edge AI processors are increasing system costs in the vision language models for robotics market. Import duties on cameras and embedded compute modules are impacting hardware intensive robotic platforms the most. Manufacturing and logistics robotics deployments in import dependent regions face higher project budgets. Industrial and service robotics segments are especially affected due to integrated hardware stacks. At the same time, tariffs are encouraging local robotics hardware assembly and regional supplier ecosystems. Vendors are increasing domestic sourcing of components. This improves supply stability while raising near term robot system costs.
The vision-language models (vlm) for robotics market research report is one of a series of new reports that provides vision-language models (vlm) for robotics market statistics, including vision-language models (vlm) for robotics industry global market size, regional shares, competitors with a vision-language models (vlm) for robotics market share, detailed vision-language models (vlm) for robotics market segments, market trends and opportunities, and any further data you may need to thrive in the vision-language models (vlm) for robotics industry. This vision-language models (vlm) for robotics market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.
Vision-language models for robotics involve AI systems that merge visual perception with natural language processing to allow robots to interpret both visual inputs and spoken or written instructions together. These models enable robots to understand surroundings, follow complex commands, and perform reasoning-based actions using combined image, video, and text data.
The primary components of vision-language models for robotics include software, hardware, and services. Software refers to platforms that allow robots to interpret and process visual and textual inputs to enhance perception, decision-making, and task performance. These solutions are deployed through on-premises, cloud, and other deployment models based on organizational infrastructure and operational requirements. The various applications involved include industrial robotics, service robotics, autonomous vehicles, healthcare robotics, consumer robotics, and other applications. The end users include manufacturing companies, healthcare providers, automotive firms, retail organizations, logistics service providers, defense organizations, and others.
The vision-language models (VLM) for robotics market consists of revenues earned by entities by providing services such as multimodal artificial intelligence model development, visual perception and language fusion platforms, robotic reasoning and decision-making software and real-time vision-language inference systems. The market value includes the value of related goods sold by the service provider or included within the service offering. The vision-language models (VLM) for robotics market also includes sales of trained model frameworks, robotic vision sensor integration modules and edge inference hardware and software toolkits for multimodal learning and deployment. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
This product will be delivered within 1-3 business days.
Table of Contents
1. Executive Summary
2. Vision-Language Models (VLM) For Robotics Market Characteristics
3. Vision-Language Models (VLM) For Robotics Market Supply Chain Analysis
4. Global Vision-Language Models (VLM) For Robotics Market Trends and Strategies
5. Vision-Language Models (VLM) For Robotics Market Analysis Of End Use Industries
7. Global Vision-Language Models (VLM) For Robotics Strategic Analysis Framework, Current Market Size, Market Comparisons and Growth Rate Analysis
8. Global Vision-Language Models (VLM) For Robotics Total Addressable Market (TAM) Analysis for the Market
9. Vision-Language Models (VLM) For Robotics Market Segmentation
10. Vision-Language Models (VLM) For Robotics Market, Industry Metrics by Country
11. Vision-Language Models (VLM) For Robotics Market Regional and Country Analysis
12. Asia-Pacific Vision-Language Models (VLM) For Robotics Market
13. China Vision-Language Models (VLM) For Robotics Market
14. India Vision-Language Models (VLM) For Robotics Market
15. Japan Vision-Language Models (VLM) For Robotics Market
16. Australia Vision-Language Models (VLM) For Robotics Market
17. Indonesia Vision-Language Models (VLM) For Robotics Market
18. South Korea Vision-Language Models (VLM) For Robotics Market
19. Taiwan Vision-Language Models (VLM) For Robotics Market
20. South East Asia Vision-Language Models (VLM) For Robotics Market
21. Western Europe Vision-Language Models (VLM) For Robotics Market
22. UK Vision-Language Models (VLM) For Robotics Market
23. Germany Vision-Language Models (VLM) For Robotics Market
24. France Vision-Language Models (VLM) For Robotics Market
25. Italy Vision-Language Models (VLM) For Robotics Market
26. Spain Vision-Language Models (VLM) For Robotics Market
27. Eastern Europe Vision-Language Models (VLM) For Robotics Market
28. Russia Vision-Language Models (VLM) For Robotics Market
29. North America Vision-Language Models (VLM) For Robotics Market
30. USA Vision-Language Models (VLM) For Robotics Market
31. Canada Vision-Language Models (VLM) For Robotics Market
32. South America Vision-Language Models (VLM) For Robotics Market
33. Brazil Vision-Language Models (VLM) For Robotics Market
34. Middle East Vision-Language Models (VLM) For Robotics Market
35. Africa Vision-Language Models (VLM) For Robotics Market
37. Vision-Language Models (VLM) For Robotics Market Competitive Landscape and Company Profiles
38. Vision-Language Models (VLM) For Robotics Market Other Major and Innovative Companies
42. Vision-Language Models (VLM) For Robotics Market High Potential Countries, Segments and Strategies
43. Appendix
Executive Summary
Vision-Language Models (VLM) For Robotics Market Global Report 2026 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses vision-language models (vlm) for robotics market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
Reasons to Purchase:
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- Identify growth segments for investment.
- Outperform competitors using forecast data and the drivers and trends shaping the market.
- Understand customers based on end user analysis.
- Benchmark performance against key competitors based on market share, innovation, and brand strength.
- Evaluate the total addressable market (TAM) and market attractiveness scoring to measure market potential.
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- Report will be updated with the latest data and delivered to you along with an Excel data sheet for easy data extraction and analysis.
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Description
Where is the largest and fastest growing market for vision-language models (vlm) for robotics? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The vision-language models (vlm) for robotics market global report answers all these questions and many more.The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.
- The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
- The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
- The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
- The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
- The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
- The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
- The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
- The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
- Market segmentations break down the market into sub markets.
- The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
- Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
- The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
- The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.
Report Scope
Markets Covered:
1) By Component: Software; Hardware; Services2) By Deployment Mode: On Premises; Cloud; Other Deployment Modes
3) By Application: Industrial Robotics; Service Robotics; Autonomous Vehicles; Healthcare Robotics; Consumer Robotics; Other Applications
4) By End User: Manufacturing; Healthcare; Automotive; Retail; Logistics; Defense; Other End Users
Subsegments:
1) By Software: Vision Language Model Platforms; Perception and Scene Understanding Software; Natural Language Processing (NLP) Software; Robotics Operating System (ROS) Integration Software; Simulation and Training Software2) By Hardware: Cameras and Vision Sensors; Microphones and Audio Sensors; Edge Computing Processors; Graphics Processing Units (GPU); Robotic Controllers
3) By Services: System Integration Services; Model Training and Customization Services; Maintenance and Support Services; Consulting Services; Training and Education Services
Companies Mentioned: Amazon.com Inc.; Google LLC; Microsoft Corporation; Huawei Technologies Co. Ltd.; Tesla Inc.; Siemens AG; IBM Research; Meta Platforms Inc.; ABB Ltd.; NVIDIA Corporation; Samsung Electronics Co. Ltd.; Intel Corporation; Baidu Inc.; SenseTime; OpenAI LLC; Skild AI; 1X Technologies LLC; Agility Robotics; Covariant; and Preferred Networks.
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain
Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast.
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita.
Data Segmentation: Country and regional historic and forecast data, market share of competitors, market segments.
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
Delivery Format: Word, PDF or Interactive Report + Excel Dashboard
Added Benefits:
- Bi-Annual Data Update
- Customisation
- Expert Consultant Support
Companies Mentioned
The companies featured in this Vision-Language Models (VLM) for Robotics market report include:- Amazon.com Inc.
- Google LLC
- Microsoft Corporation
- Huawei Technologies Co. Ltd.
- Tesla Inc.
- Siemens AG
- IBM Research
- Meta Platforms Inc.
- ABB Ltd.
- NVIDIA Corporation
- Samsung Electronics Co. Ltd.
- Intel Corporation
- Baidu Inc.
- SenseTime
- OpenAI LLC
- Skild AI
- 1X Technologies LLC
- Agility Robotics
- Covariant
- and Preferred Networks.
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 250 |
| Published | March 2026 |
| Forecast Period | 2026 - 2030 |
| Estimated Market Value ( USD | $ 2.45 Billion |
| Forecasted Market Value ( USD | $ 6.36 Billion |
| Compound Annual Growth Rate | 27.0% |
| Regions Covered | Global |
| No. of Companies Mentioned | 21 |
