South Korea Large Language Model Market Research Report, 2030

South Korea’s large language model (LLM) industry is rapidly emerging as a critical pillar in the nation’s broader artificial intelligence ecosystem, reflecting the country’s strategic emphasis on cutting-edge technology, innovation, and digital transformation. Known globally for its leadership in information technology, telecommunications, and electronics, South Korea is uniquely positioned to capitalize on the advancements in natural language processing (NLP) and large-scale AI models to drive economic growth and enhance competitiveness across multiple sectors. The nation’s vibrant tech industry, supported by substantial government investment and robust R&D infrastructure, fuels the development and deployment of large language models tailored to the linguistic and cultural nuances of the Korean language, as well as other regional languages. South Korea’s population is highly digitally connected, with widespread adoption of smartphones, online services, and social media platforms, creating a fertile environment for AI-powered applications that improve user experience through personalized content generation, automated translation, virtual assistants, and intelligent customer support systems. The country’s educational institutions and research centers are deeply engaged in advancing AI technologies, often collaborating with industry leaders and startups to develop models that address both general and domain-specific language tasks. According to the research report, “South Korea Large Language Model Market Research Report, 2030” published by Actual Market Research, the South Korea market is projected to add USD 600 Million from 2025 to 2030. The government’s proactive AI policies emphasize ethical AI development, data privacy, and fostering a responsible AI ecosystem, ensuring that large language model innovations align with societal values and legal standards. South Korea’s global trade relationships and role as a gateway to the Asia-Pacific region further incentivize the creation of multilingual and culturally adaptive LLMs, facilitating international business and cross-border communication. The availability of extensive language data sets, combined with investments in high-performance computing infrastructure and cloud platforms, enables efficient training and scaling of large models within the country. South Korea also benefits from a strong culture of technological adoption among consumers and enterprises alike, driving demand for AI-enhanced solutions in sectors such as healthcare, finance, entertainment, manufacturing, and public administration. Challenges remain, including the need to balance rapid innovation with regulatory compliance and to address resource-intensive training costs, but ongoing advancements in model optimization and collaborative research efforts continue to propel the industry forward.

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LLM fine-tuning is experiencing significant growth in South Korea’s large language model industry due to the country’s strong demand for highly specialized and context-aware AI applications tailored to its unique linguistic, cultural, and industrial landscape. South Korea’s language, with its complex grammar, honorifics, and idiomatic expressions, requires fine-tuning of general large language models to ensure accuracy, nuance, and cultural relevance in real-world applications. Fine-tuning enables developers to adapt pre-trained models to specific sectors such as finance, healthcare, legal services, and entertainment industries that are critical to South Korea’s economy and demand AI solutions that understand domain-specific terminology, regulatory nuances, and user expectations. Additionally, the government’s push for AI adoption in public services and digital transformation initiatives encourages organizations to customize LLMs to local needs, improving efficiency and user engagement. Fine-tuning also offers a cost-effective alternative to training models from scratch, which is especially important in South Korea’s competitive tech environment where speed to market and resource optimization are crucial. The growing availability of high-quality, localized datasets and advanced computational infrastructure supports more precise and efficient fine-tuning workflows. Moreover, fine-tuning helps address privacy and data security concerns by enabling organizations to adapt models on-premises or within secure cloud environments, aligning with South Korea’s stringent data protection regulations. Collaborations between academia, industry, and government foster innovation in fine-tuning techniques, encouraging continuous improvement in model performance and ethical AI practices. As businesses seek to differentiate their AI-powered products and services through better contextual understanding and personalization, fine-tuning large language models becomes an indispensable strategy in South Korea’s AI development roadmap. The growth of large language models with above 500 billion parameters in South Korea’s LLM industry is driven by the country’s ambition to develop state-of-the-art AI systems that can handle increasingly complex, large-scale, and multilingual tasks demanded by its advanced digital economy and global technological aspirations. South Korea’s strong emphasis on innovation and technology leadership compels research institutions and tech companies to push the boundaries of AI capabilities by investing in ultra-large models that offer superior performance in understanding and generating natural language with remarkable accuracy and contextual depth. Models of this scale are essential for capturing the intricate nuances of the Korean language and its dialects, as well as facilitating seamless communication across multiple languages important to South Korea’s export-driven economy and regional partnerships in Asia and beyond. Moreover, above 500 billion parameter models provide the computational power necessary for sophisticated applications such as real-time translation, complex decision support systems in healthcare and finance, advanced content creation, and personalized virtual assistants, which are increasingly integral to South Korea’s smart industries and digital services. The country’s robust infrastructure, including high-performance computing resources and cloud platforms, combined with significant government funding and collaboration between academia and industry, enables the training and deployment of such massive models. Additionally, the rising demand for models capable of multimodal processing integrating text, speech, and vision further propels the adoption of ultra-large parameter LLMs. While these models require substantial computational investment, ongoing advances in optimization and efficient training methods help mitigate costs, making them more accessible. Furthermore, South Korea’s strict focus on AI ethics, data security, and privacy aligns with the controlled development and deployment of these powerful models to ensure responsible use and societal trust. Task-specific large language models (LLMs) are experiencing significant growth in South Korea’s AI industry due to the country’s strong focus on developing highly efficient, accurate, and context-aware AI solutions tailored to the specific needs of diverse sectors such as healthcare, finance, manufacturing, legal services, and customer support. Unlike general-purpose models, task-specific LLMs are fine-tuned and optimized to handle distinct language patterns, jargon, and workflows relevant to particular industries, enabling superior performance in specialized applications. South Korea’s technologically advanced economy demands AI systems that not only understand the Korean language’s unique linguistic structure but also cater to industry-specific regulations, cultural nuances, and operational intricacies. The surge in digital transformation initiatives across both public and private sectors propels the adoption of task-specific models that can automate complex tasks like medical diagnostics, legal document analysis, fraud detection, and supply chain management with higher precision and reliability. Moreover, task-specific LLMs help organizations overcome challenges related to data privacy and compliance by allowing localized model training on sensitive, domain-specific data within secure environments, an essential consideration given South Korea’s stringent data protection laws. The nation’s robust R&D ecosystem, supported by government funding and collaboration between academia and enterprises, accelerates innovation in creating models tailored to solve real-world problems efficiently. Additionally, these specialized models reduce computational overhead compared to massive generalist models by focusing resources on narrower, high-impact tasks, making them more accessible for businesses of varying sizes. As industries increasingly recognize the competitive advantage offered by AI-driven automation and enhanced decision-making, the demand for task-specific LLMs grows steadily, cementing their role as vital components in South Korea’s large language model landscape.

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Nikita Jabrela

Business Development Manager

Considered in this report • Historic Year: 2019 • Base year: 2024 • Estimated year: 2025 • Forecast year: 2030 Aspects covered in this report • Large Language Model Market with its value and forecast along with its segments • Various drivers and challenges • On-going trends and developments • Top profiled companies • Strategic recommendation By Service • Consulting • LLM Development • Integration • LLM Fine-Tuning • LLM-backed App Development • Prompt Engineering • Support & Maintenance

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By Model Size • Below 1 Billion Parameters • 1B to 10B Parameters • 10B to 50B Parameters • 50B to 100B Parameters • 100B to 200B Parameters • 200B to 500B Parameters • Above 500B Parameters By Type • General Purpose LLMs • Domain-Specific LLMs • Multilingual LLMs • Task-Specific LLMs • Others(open source, low source LLMs) By Modality • Text • Code • Image • Video • Others (Audio, 3D, Multimodal Combinations) The approach of the report: This report consists of a combined approach of primary as well as secondary research. Initially, secondary research was used to get an understanding of the market and listing out the companies that are present in the market. The secondary research consists of third-party sources such as press releases, annual report of companies, analyzing the government generated reports and databases. After gathering the data from secondary sources primary research was conducted by making telephonic interviews with the leading players about how the market is functioning and then conducted trade calls with dealers and distributors of the market. Post this we have started doing primary calls to consumers by equally segmenting consumers in regional aspects, tier aspects, age group, and gender. Once we have primary data with us we have started verifying the details obtained from secondary sources. Intended audience This report can be useful to industry consultants, manufacturers, suppliers, associations & organizations related to this industry, government bodies and other stakeholders to align their market-centric strategies. In addition to marketing & presentations, it will also increase competitive knowledge about the industry.