Building a National Large Language Model (“LLM”)

Key Design Choices and Considerations

National large language models (“LLMs”) are emerging as powerful tools customized to reflect a nation’s language culture legal framework and societal priorities. They support vital public sector applications in governance healthcare education and more while strengthening digital sovereignty. Countries such as the Netherlands (GPT NL), Italy (Modello Italia), and the UAE (ALLaM) have led the way by building models ranging from 7 to over 70 billion parameters tailored to their unique needs. Success in this domain depends on choosing purpose aligned architectures leveraging existing foundation models to control costs and ensuring sustained governmental commitment to updating and enhancing these systems.

Our team is ready to guide national LLM initiatives by defining clear investment and model development strategies aligned with long-term public objectives fostering partnerships across public institutions and private innovators and designing governance frameworks that ensure these models remain up-to-date robust and socially responsible.

Overview of LLMs explaining functions, training flow and key use cases like text generation, chatbots and translation.
World map infographic showing efforts to create national LLMs, with examples from Netherlands, Italy, KSA, UAE, and Singapore.
Infographic outlining three objectives for national LLMs: cultural contextualisation, data sovereignty, and socioeconomic development.
Infographic showing distinctive features of national LLMs: data sovereignty, low latency, enhanced security, and public sector support.
Infographic on four socioeconomic benefits of national LLMs: driving economic growth, building AI champions, developing local talent, and boosting exports.
Infographic on risks when building a national LLM, covering market, technical, and resource challenges such as funding, data, and talent.
Infographic on developing a national foundational LLM, showing objectives, model selection, applications, benefits, disadvantages, and applicability.
Infographic on developing a simple RAG layer on off-the-shelf models, showing objectives, model selection, benefits, disadvantages, and applicability.
Infographic comparing national foundational LLMs and RAG layers on existing models across cultural, security, and socioeconomic objectives.
Infographic highlighting three key learnings from national LLMs: model selection, leveraging regional or global models, and need for government funding.