Building a National LLM: Key design choices and considerations

National LLMs are emerging as transformative tools tailored to a country's unique linguistic, cultural, legal, and societal context. Unlike widely-used private-sector models, such as those from OpenAI or Google AI, national LLMs serve to enhance digital sovereignty by aligning with local priorities and addressing specific needs in government, healthcare, education, and other public sectors. They provide advanced capabilities such as text generation, content summarization, code generation, and sentiment analysis, contributing to a range of use cases that support citizen engagement and governmental services.

Countries like the Netherlands (GPT-NL), Italy (Modello Italia), and the UAE (ALLaM) have led efforts in this area, with models boasting parameters ranging from 7 billion to over 70 billion. These national LLMs underscore the growing trend of using AI to foster regional innovation while competing with established, privately developed LLMs. Based on insights from leading examples, three essential considerations emerge for successful national LLMs: selecting an LLM model aligned with clear objectives, leveraging foundational models to minimize costs, and ensuring ongoing government support for updates and enhancements.