The large language models (llms) in robotics market size has grown exponentially in recent years. It will grow from $4.29 billion in 2025 to $6.1 billion in 2026 at a compound annual growth rate (CAGR) of 42%. The growth in the historic period can be attributed to early robotics automation adoption, advances in machine learning models, growth of industrial robotics, demand for intuitive robot interfaces, expansion of service robotics.
The large language models (llms) in robotics market size is expected to see exponential growth in the next few years. It will grow to $24.29 billion in 2030 at a compound annual growth rate (CAGR) of 41.3%. The growth in the forecast period can be attributed to integration of llms into autonomous systems, rising demand for collaborative robots, advancements in multimodal AI models, growth of humanoid and service robots, increasing investment in intelligent automation. Major trends in the forecast period include natural language robot control, cognitive robotics task planning, human robot interaction enhancement, multimodal perception and reasoning, adaptive robot learning systems.
The increasing demand for automation is expected to drive the growth of the large language models (LLMs) in robotics market. Automation involves using technology to perform tasks with minimal human input, leading to improved efficiency and accuracy. The demand for automation is rising due to the need for operational efficiency and cost reduction, as automation allows for faster task execution, reduces errors, and lessens reliance on manual labor. LLMs in robotics further enhance automation by enabling language-based control, making them suitable for dynamic and unstructured environments. They reduce the need for manual programming by allowing robots to understand and execute tasks from natural language commands, improving operational efficiency and flexibility. For example, in September 2024, the International Federation of Robotics, a Germany-based non-profit organization, reported that 4,281,585 robotic units were operating in factories globally in 2023, marking a 10% increase from 3,904,000 units in 2022. Therefore, the increasing demand for automation is fueling the growth of the LLMs in robotics market.
Leading companies in the LLMs in robotics market are focusing on developing innovative solutions, such as advanced AI models, to boost robot autonomy, improve human-robot interaction, and optimize task execution. An advanced AI model refers to sophisticated machine learning or deep learning systems, including LLMs, neural networks, and reinforcement learning algorithms, that allow robots to independently analyze complex data, adapt to their environment, and perform tasks with high flexibility and intelligence. For instance, in March 2025, DeepMind Technologies Limited, a UK-based software company, launched the Gemini Robotics AI model. This model integrates advanced vision-language-action (VLA) capabilities, enabling robots to perceive, adapt, and interact dynamically with their surroundings. Its benefits include generality for handling new tasks, interactivity for real-time adaptability, and dexterity for precise manipulation, making it ideal for use in dynamic environments such as factories and homes.
In January 2025, 1X Technologies, a U.S.-based AI and robotics company, acquired Kind Humanoid Inc. for an undisclosed amount. This acquisition aims to accelerate the development of intelligent humanoid robots by integrating Kind’s advanced bio-inspired designs with large language model capabilities. The integration will enhance human-robot interaction and expand 1X’s presence in the consumer and healthcare robotics markets. Kind Humanoid Inc. is a U.S.-based company that specializes in using LLMs in robotics.
Major companies operating in the large language models (llms) in robotics market are Microsoft Corporation, Meta Platforms Inc., Amazon Web Services Inc., Tesla Inc., Hitachi Ltd., Midea Group, NVIDIA Corporation, UiPath Inc., Google DeepMind Technologies Limited, United Robotics Group, UBTech Robotics Corp Ltd., PAL Robotics S.L., Agility Robotics Inc., Figure AI Inc., Sanctuary Cognitive Systems Corporation, Xandex Inc., OrionStar Technology Co. Ltd, Sereact GmbH, Physical Intelligence Inc, Intrinsic Innovation LLC.
North America was the largest region in the large language models (LLMs) in robotics market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the large language models (llms) in robotics market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the large language models (llms) in robotics market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Tariffs have impacted the llms in robotics market by increasing the cost of robotic hardware, sensors, processors, and AI computing modules. Robotics manufacturers deploying llm enabled systems have faced higher production and integration costs. Industrial and service robotics deployments in Asia Pacific, Europe, and North America are most affected due to global component sourcing. These tariffs may slow adoption in cost sensitive manufacturing environments. However, tariffs are encouraging localized robotics manufacturing and AI hardware development. This is strengthening domestic robotics ecosystems and supporting long-term innovation in intelligent robotic systems.
The large language models (llms) in robotics market research report is one of a series of new reports that provides large language models (llms) in robotics market statistics, including large language models (llms) in robotics industry global market size, regional shares, competitors with a large language models (llms) in robotics market share, detailed large language models (llms) in robotics market segments, market trends and opportunities, and any further data you may need to thrive in the large language models (llms) in robotics industry. This large language models (llms) in 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.
Large language models (LLMs) in robotics are AI systems designed to enable robots to understand and generate human-like language, reason through tasks, and interact more naturally with people. These models provide a high-level cognitive layer that helps robots interpret instructions, plan actions, and connect language to perception and control. Their main goal is to make robots more intelligent, adaptable, and user-friendly, allowing for control and learning through natural language.
The key functionalities of LLMs in robotics include natural language understanding, natural language generation, speech recognition and synthesis, computer vision integration, and multimodal processing. Natural language understanding (NLU) is a subfield of AI and natural language processing (NLP) that enables machines to comprehend, interpret, and derive meaning from human language in a way that is context-aware and useful. Deployment options for LLMs in robotics include both cloud-based and on-premises solutions. These models are used by both large enterprises and small-to-medium-sized enterprises (SMEs). Key industries utilizing LLMs in robotics include healthcare, manufacturing, retail and e-commerce, banking, financial services, insurance (BFSI), defense, security, and more. Applications for LLMs span industrial robotics, service robotics, autonomous vehicles, humanoid robots, drone technology, and various other use cases.
The large language models (LLMs) in robotics market consists of revenues earned by entities by providing services such as natural language-based robot control, task planning and decision-making, human-robot interaction interfaces, multi-modal perception integration and code generation for robotic actions. The market value includes the value of related goods sold by the service provider or included within the service offering. The large language models (LLMs) in robotics market also consist of sales of humanoid robots, AI-powered assistants, autonomous service robots, vision-language sensor systems, cloud-based robotic control solutions and artificial intelligence (AI) chatbots in robotics. 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 large language models (llms) in robotics market size is expected to see exponential growth in the next few years. It will grow to $24.29 billion in 2030 at a compound annual growth rate (CAGR) of 41.3%. The growth in the forecast period can be attributed to integration of llms into autonomous systems, rising demand for collaborative robots, advancements in multimodal AI models, growth of humanoid and service robots, increasing investment in intelligent automation. Major trends in the forecast period include natural language robot control, cognitive robotics task planning, human robot interaction enhancement, multimodal perception and reasoning, adaptive robot learning systems.
The increasing demand for automation is expected to drive the growth of the large language models (LLMs) in robotics market. Automation involves using technology to perform tasks with minimal human input, leading to improved efficiency and accuracy. The demand for automation is rising due to the need for operational efficiency and cost reduction, as automation allows for faster task execution, reduces errors, and lessens reliance on manual labor. LLMs in robotics further enhance automation by enabling language-based control, making them suitable for dynamic and unstructured environments. They reduce the need for manual programming by allowing robots to understand and execute tasks from natural language commands, improving operational efficiency and flexibility. For example, in September 2024, the International Federation of Robotics, a Germany-based non-profit organization, reported that 4,281,585 robotic units were operating in factories globally in 2023, marking a 10% increase from 3,904,000 units in 2022. Therefore, the increasing demand for automation is fueling the growth of the LLMs in robotics market.
Leading companies in the LLMs in robotics market are focusing on developing innovative solutions, such as advanced AI models, to boost robot autonomy, improve human-robot interaction, and optimize task execution. An advanced AI model refers to sophisticated machine learning or deep learning systems, including LLMs, neural networks, and reinforcement learning algorithms, that allow robots to independently analyze complex data, adapt to their environment, and perform tasks with high flexibility and intelligence. For instance, in March 2025, DeepMind Technologies Limited, a UK-based software company, launched the Gemini Robotics AI model. This model integrates advanced vision-language-action (VLA) capabilities, enabling robots to perceive, adapt, and interact dynamically with their surroundings. Its benefits include generality for handling new tasks, interactivity for real-time adaptability, and dexterity for precise manipulation, making it ideal for use in dynamic environments such as factories and homes.
In January 2025, 1X Technologies, a U.S.-based AI and robotics company, acquired Kind Humanoid Inc. for an undisclosed amount. This acquisition aims to accelerate the development of intelligent humanoid robots by integrating Kind’s advanced bio-inspired designs with large language model capabilities. The integration will enhance human-robot interaction and expand 1X’s presence in the consumer and healthcare robotics markets. Kind Humanoid Inc. is a U.S.-based company that specializes in using LLMs in robotics.
Major companies operating in the large language models (llms) in robotics market are Microsoft Corporation, Meta Platforms Inc., Amazon Web Services Inc., Tesla Inc., Hitachi Ltd., Midea Group, NVIDIA Corporation, UiPath Inc., Google DeepMind Technologies Limited, United Robotics Group, UBTech Robotics Corp Ltd., PAL Robotics S.L., Agility Robotics Inc., Figure AI Inc., Sanctuary Cognitive Systems Corporation, Xandex Inc., OrionStar Technology Co. Ltd, Sereact GmbH, Physical Intelligence Inc, Intrinsic Innovation LLC.
North America was the largest region in the large language models (LLMs) in robotics market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the large language models (llms) in robotics market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the large language models (llms) in robotics market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Tariffs have impacted the llms in robotics market by increasing the cost of robotic hardware, sensors, processors, and AI computing modules. Robotics manufacturers deploying llm enabled systems have faced higher production and integration costs. Industrial and service robotics deployments in Asia Pacific, Europe, and North America are most affected due to global component sourcing. These tariffs may slow adoption in cost sensitive manufacturing environments. However, tariffs are encouraging localized robotics manufacturing and AI hardware development. This is strengthening domestic robotics ecosystems and supporting long-term innovation in intelligent robotic systems.
The large language models (llms) in robotics market research report is one of a series of new reports that provides large language models (llms) in robotics market statistics, including large language models (llms) in robotics industry global market size, regional shares, competitors with a large language models (llms) in robotics market share, detailed large language models (llms) in robotics market segments, market trends and opportunities, and any further data you may need to thrive in the large language models (llms) in robotics industry. This large language models (llms) in 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.
Large language models (LLMs) in robotics are AI systems designed to enable robots to understand and generate human-like language, reason through tasks, and interact more naturally with people. These models provide a high-level cognitive layer that helps robots interpret instructions, plan actions, and connect language to perception and control. Their main goal is to make robots more intelligent, adaptable, and user-friendly, allowing for control and learning through natural language.
The key functionalities of LLMs in robotics include natural language understanding, natural language generation, speech recognition and synthesis, computer vision integration, and multimodal processing. Natural language understanding (NLU) is a subfield of AI and natural language processing (NLP) that enables machines to comprehend, interpret, and derive meaning from human language in a way that is context-aware and useful. Deployment options for LLMs in robotics include both cloud-based and on-premises solutions. These models are used by both large enterprises and small-to-medium-sized enterprises (SMEs). Key industries utilizing LLMs in robotics include healthcare, manufacturing, retail and e-commerce, banking, financial services, insurance (BFSI), defense, security, and more. Applications for LLMs span industrial robotics, service robotics, autonomous vehicles, humanoid robots, drone technology, and various other use cases.
The large language models (LLMs) in robotics market consists of revenues earned by entities by providing services such as natural language-based robot control, task planning and decision-making, human-robot interaction interfaces, multi-modal perception integration and code generation for robotic actions. The market value includes the value of related goods sold by the service provider or included within the service offering. The large language models (LLMs) in robotics market also consist of sales of humanoid robots, AI-powered assistants, autonomous service robots, vision-language sensor systems, cloud-based robotic control solutions and artificial intelligence (AI) chatbots in robotics. 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. Large Language Models (LLMs) in Robotics Market Characteristics
3. Large Language Models (LLMs) in Robotics Market Supply Chain Analysis
4. Global Large Language Models (LLMs) in Robotics Market Trends and Strategies
5. Large Language Models (LLMs) in Robotics Market Analysis of End Use Industries
7. Global Large Language Models (LLMs) in Robotics Strategic Analysis Framework, Current Market Size, Market Comparisons and Growth Rate Analysis
8. Global Large Language Models (LLMs) in Robotics Total Addressable Market (TAM) Analysis for the Market
9. Large Language Models (LLMs) in Robotics Market Segmentation
10. Large Language Models (LLMs) in Robotics Market, Industry Metrics by Country
11. Large Language Models (LLMs) in Robotics Market Regional and Country Analysis
12. Asia-Pacific Large Language Models (LLMs) in Robotics Market
13. China Large Language Models (LLMs) in Robotics Market
14. India Large Language Models (LLMs) in Robotics Market
15. Japan Large Language Models (LLMs) in Robotics Market
16. Australia Large Language Models (LLMs) in Robotics Market
17. Indonesia Large Language Models (LLMs) in Robotics Market
18. South Korea Large Language Models (LLMs) in Robotics Market
19. Taiwan Large Language Models (LLMs) in Robotics Market
20. South East Asia Large Language Models (LLMs) in Robotics Market
21. Western Europe Large Language Models (LLMs) in Robotics Market
22. UK Large Language Models (LLMs) in Robotics Market
23. Germany Large Language Models (LLMs) in Robotics Market
24. France Large Language Models (LLMs) in Robotics Market
25. Italy Large Language Models (LLMs) in Robotics Market
26. Spain Large Language Models (LLMs) in Robotics Market
27. Eastern Europe Large Language Models (LLMs) in Robotics Market
28. Russia Large Language Models (LLMs) in Robotics Market
29. North America Large Language Models (LLMs) in Robotics Market
30. USA Large Language Models (LLMs) in Robotics Market
31. Canada Large Language Models (LLMs) in Robotics Market
32. South America Large Language Models (LLMs) in Robotics Market
33. Brazil Large Language Models (LLMs) in Robotics Market
34. Middle East Large Language Models (LLMs) in Robotics Market
35. Africa Large Language Models (LLMs) in Robotics Market
37. Large Language Models (LLMs) in Robotics Market Competitive Landscape and Company Profiles
38. Large Language Models (LLMs) in Robotics Market Other Major and Innovative Companies
41. Large Language Models (LLMs) in Robotics Market High Potential Countries, Segments and Strategies
42. Appendix
Executive Summary
Large Language Models (LLMs) In Robotics Market Global Report 2026 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses large language models (llms) in 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.
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- Evaluate the total addressable market (TAM) and market attractiveness scoring to measure market potential.
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Description
Where is the largest and fastest growing market for large language models (llms) in 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 large language models (llms) in 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 Functionality: Natural Language Understanding; Natural Language Generation; Speech Recognition And Synthesis; Computer Vision Integration; Multimodal Processing2) By Deployment Mode: Cloud-Based Large Language Models (LLMs); On-Premises Large Language Models (LLMs)
3) By Enterprise Size: Large Enterprises; Small And Medium Enterprises
4) By Application: Industrial Robotics; Service Robotics; Autonomous Vehicles; Humanoid Robots; Drone Technology; Other Applications
5) By Industry: Healthcare; Manufacturing; Retail And E-Commerce; Banking, Financial Services, And Insurance; Defense And Security; Other Industries
Subsegments:
1) By Natural Language Understanding: Sentiment Analysis; Semantic Parsing; Named Entity Recognition (NER); Language Classification; Intent Recognition2) By Natural Language Generation: Text Generation; Report Generation; Summarization; Dialogue Systems; Machine Translation
3) By Speech Recognition And Synthesis: Speech-To-Text; Speaker Identification; Text-To-Speech (TTS); Speech Emotion Recognition; Voice Command Systems
4) By Computer Vision Integration: Object Detection; Visual Simultaneous Localization And Mapping; Image Classification; Scene Understanding; Facial Recognition
5) By Multimodal Processing: Text-Image Integration; Multimodal Sentiment Analysis; Audio-Visual Processing; Video Understanding; Text-Speech Integration
Companies Mentioned: Microsoft Corporation; Meta Platforms Inc.; Amazon Web Services Inc.; Tesla Inc.; Hitachi Ltd.; Midea Group; NVIDIA Corporation; UiPath Inc.; Google DeepMind Technologies Limited; United Robotics Group; UBTech Robotics Corp Ltd.; PAL Robotics S.L.; Agility Robotics Inc.; Figure AI Inc.; Sanctuary Cognitive Systems Corporation; Xandex Inc.; OrionStar Technology Co. Ltd; Sereact GmbH; Physical Intelligence Inc; Intrinsic Innovation LLC
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 Large Language Models (LLMs) in Robotics market report include:- Microsoft Corporation
- Meta Platforms Inc.
- Amazon Web Services Inc.
- Tesla Inc.
- Hitachi Ltd.
- Midea Group
- NVIDIA Corporation
- UiPath Inc.
- Google DeepMind Technologies Limited
- United Robotics Group
- UBTech Robotics Corp Ltd.
- PAL Robotics S.L.
- Agility Robotics Inc.
- Figure AI Inc.
- Sanctuary Cognitive Systems Corporation
- Xandex Inc.
- OrionStar Technology Co. Ltd
- Sereact GmbH
- Physical Intelligence Inc
- Intrinsic Innovation LLC
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 250 |
| Published | February 2026 |
| Forecast Period | 2026 - 2030 |
| Estimated Market Value ( USD | $ 6.1 Billion |
| Forecasted Market Value ( USD | $ 24.29 Billion |
| Compound Annual Growth Rate | 41.3% |
| Regions Covered | Global |
| No. of Companies Mentioned | 21 |
