CHICAGO, March 20, 2024 /PRNewswire/ — Future developments in natural language comprehension and multimodal integration, as well as greater industry integration, will drive the Large Language Model (LLM) Market. While regulatory norms and edge deployment will guide the market’s progression towards personalised, varied, and privacy-conscious apps, ethical considerations, privacy concerns, and collaboration with domain-specific AI models will drive responsible development.
The Large Language Model Market is set to experience rapid growth, projected to surge from USD 6.4 billion in 2024 to USD 36.1 billion by 2030, at a CAGR of 33.2% during the forecast period of 2024–2030, according to a new report by MarketsandMarkets™. The growing imperative for improved communication between humans and machines and escalating demand for automated content creation and curation, increasing accessibility of extensive datasets are driving forces propelling the Large Language Model Market forward.
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393 – Tables
101 – Figures
448 – Pages
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Scope of the Report
Report Metrics |
Details |
Market size available for years |
2021–2030 |
Base year considered |
2023 |
Forecast period |
2024–2030 |
Forecast units |
USD (Million) |
Segments covered |
Offering, Architecture, Modality, Model Size, Application, End-user, and Region |
Geographies covered |
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
Companies covered |
Google (US), OpenAI (US), Anthropic (US), Meta (US), Microsoft (US), NVIDIA (US), AWS (US), IBM (US), Oracle (US), HPE (US), Tencent (China), Yandex (Russia), Naver (South Korea), AI21 Labs (Israel), Hugging Face (US), Baidu (China), SenseTime (Hong Kong), Huawei (China), FedML (US), DynamoFL (US), Together AI (US), Upstage (South Korea), Mistral AI (France), Adept (US), Neuralfinity (Germany), Mosaic ML (US), Stability AI (UK), LightOn (France), Cohere (Canada), Turing (US), Lightning AI (US), and WhyLabs (US) |
By software, general-purpose LLMs segment to register the largest market share during the forecast period
General-purpose LLMs versatility enables applications across various industries, from customer service chatbots to content generation in marketing. Their adaptability to different tasks without significant retraining makes them highly attractive to businesses seeking cost-effective solutions. Additionally, advancements in model architecture and training techniques enhance their performance, allowing them to handle complex language tasks with greater accuracy and efficiency. Moreover, the increasing demand for AI-driven automation and natural language understanding further drives the adoption of general-purpose LLMs. With their ability to comprehend and generate human-like text, these models are becoming indispensable in automating repetitive tasks and enhancing user experiences across digital platforms. The convergence of these factors positions general-purpose LLMs as the frontrunners in capturing the largest market share in Large Language Model Market.
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By modality, video segment is poised for the fastest growth rate during the forecast period
The proliferation of online video content across platforms like YouTube, TikTok, and streaming services has created an immense demand for LLM-powered video analysis and recommendation systems. Additionally, the advent of deep learning techniques such as few-shot learning, zero-shot learning and transfer learning, particularly in natural language processing (NLP) and computer vision, enables more sophisticated understanding and generation of video content. Furthermore, the integration of LLMs into video editing software facilitates advanced editing functionalities, such as automatic captioning and scene segmentation. As businesses increasingly recognize the value of video content for marketing and communication, the need for LLMs to analyze and generate such content grows exponentially.
By region, North America to account for the largest market during forecast period
North America is home to leading tech giants like Google, Microsoft, and OpenAI, which are at the forefront of developing and deploying LLMs. Their substantial investments in research and development, coupled with a robust ecosystem of skilled professionals, contribute to the region’s dominance. Additionally, North America boasts a significant concentration of industries that heavily rely on LLMs, such as finance, healthcare, and e-commerce, driving the demand for these technologies. Moreover, the region’s proactive approach toward adopting advanced technologies and its favorable regulatory environment further fuel market growth. As LLMs continue to evolve and penetrate various sectors, North America’s market share is expected to expand, solidifying its position as the primary hub for LLM development and adoption.
Top Key Companies in Large Language Model (LLM) Market:
Some major players in the Large Language Model Market include Google (US), OpenAI (US), Anthropic (US), Meta (US), Microsoft (US), NVIDIA (US), AWS (US), IBM (US), Oracle (US), HPE (US), Tencent (China), Yandex (Russia), Naver (South Korea), AI21 Labs (Israel), Hugging Face (US), Baidu (China), SenseTime (Hong Kong), Huawei (China).
Recent Developments:
- In February 2024, Google made a notable LLM announcement, unveiling Gemini 1.5 with significant advancements. The search giant unveiled Gemini 1.5, an updated AI model that comes with long context understanding across different modalities. Google also launched Gemma, a new family of lightweight open-weight models. Starting with Gemma 2B and Gemma 7B, these new models were “inspired by Gemini” and are available for commercial and research usage.
- In February 2024, Kyndryl announced an expanded partnership with Google Cloud to develop responsible generative AI solutions. The partnership will focus on coupling Google Cloud’s in-house AI capabilities, including Gemini, Google’s most advanced Large Language Model (LLM), with Kyndryl’s expertise and managed services to develop and deploy generative AI solutions for customers.
- In January 2024, Capgemini and AWS expanded their strategic collaboration to enable broad enterprise generative AI adoption. Through this collaboration, Capgemini and AWS are focused on helping clients realize the business value of adopting generative AI while navigating challenges, including cost, scale, and trust.
- In December 2023, Microsoft launched InsightPilot, an automated data exploration system powered by a Large Language Model (LLM). This innovative system is specifically designed to simplify the data exploration process. InsightPilot incorporates a set of meticulously designed analysis actions to simplify data exploration.
- In December 2023, Google unveiled an unprecedented Large Language Model (LLM) named VideoPoet, which is multimodal and capable of generating videos. This groundbreaking model introduces video generation functionalities previously unseen in LLMs.
- In December 2023, Axel Springer and OpenAI announced a global partnership to strengthen independent journalism in the age of artificial intelligence (AI). The initiative will enrich users’ experience with ChatGPT by adding recent and authoritative content on various topics and explicitly values the publisher’s role in contributing to OpenAI’s products
- In November 2023, OpenAI announced the launch of GPT-4 Turbo, a next-generation model of GPT-4. GPT-4 Turbo is more capable and has knowledge of world events up to April 2023. It has a 128k context window to fit the equivalent of more than 300 pages of text in a single prompt.
- In October 2023, Dell and Meta partnered to bring Llama 2 open-source AI to enterprise users on-premises. Dell announced that it is adding support for Llama 2 models to its lineup of Dell Validated Design for Generative AI hardware and its generative AI solutions for on-premises deployments.
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Large Language Model (LLM) Market Advantages:
- Natural language understanding is an area in which LLMs shine. This allows them to provide precise and contextually appropriate answers to inquiries, improving user experience across a range of applications, including chatbots, virtual assistants, and customer support systems.
- Content generation, document summarising, and personalised recommendations in content platforms are all made easier by LLMs’ capacity to produce logical and contextually relevant text.
- Language translation and localization services are supported by LLMs, which facilitate cross-cultural communication, enable worldwide corporate operations, and increase an organization’s market reach.
- Large-scale text data analysis, insight extraction, pattern and trend identification, and sentiment analysis are all made possible by LLMs, which enable businesses to make data-driven decisions and obtain insightful business information.
- By automating repetitive processes like data entry, report creation, and information retrieval, LLMs help firms cut costs by increasing productivity and freeing up human resources to work on higher-value projects.
- Personalised recommendation systems in e-commerce, social media, and multimedia streaming are powered by LLMs. They employ past user data and user preferences to provide relevant and interesting items, services, and content.
- By offering text-to-speech features, voice-enabled interfaces, and language translation services, LLMs improve accessibility and inclusion by improving the usability of information and services for people with impairments and multilingualism.
- By helping users locate pertinent information more quickly and effectively, LLMs increase search accuracy and information retrieval in search engines and knowledge management systems, which raises user satisfaction and engagement.
Report Objectives
- To define, describe, and predict the Large Language Model Market by offering (software and services), architecture, modality, model size, application, end-user, and region
- To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
- To analyze the micro markets with respect to individual growth trends, prospects, and their contribution to the total market
- To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the Large Language Model Market
- To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
- To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, Middle East Africa, and Latin America
- To profile key players and comprehensively analyze their market rankings and core competencies.
- To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the Large Language Model Market
- To analyze the impact of recession across all the regions across the Large Language Model Market
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