Latam-GPT: Latin America’s Open-Source AI Model Fights Bias and Fosters Digital Sovereignty

A new era for artificial intelligence in Latin America has begun. Led by a massive collaborative effort based in Chile, Latam-GPT is the region's first open-source Large Language Model (LLM), trained specifically to understand the diverse cultural, linguistic, and social realities of the continent. The project is a strategic response to the pervasive bias and underrepresentation of Latin American data in global AI systems, aiming to strengthen regional technological sovereignty and empower local innovation.

What is Latam-GPT? Defining the ‘Sovereign’ LLM

Latam-GPT is an artificial intelligence foundation model developed by the Chilean National Center for Artificial Intelligence (CENIA), in partnership with institutions across more than 15 Latin American countries. Unlike proprietary models like those from major Silicon Valley firms, Latam-GPT is an open-source system designed to function as shared public infrastructure for the region, rather than a closed consumer chatbot.

The initiative was officially launched in early February 2026, marking a significant milestone in Latin America’s digital history. Its core objective is not to compete directly with global giants but to build an AI that is accurate and culturally relevant to its users. It provides an open technological foundation that local programmers and institutions can customize to develop region-specific applications, ensuring that the technology reflects local needs.

The Data Dilemma: Why the Region Needs its Own Model

Major global LLMs are predominantly trained on vast quantities of English-language content, meaning Latin American data—including Spanish and Portuguese content—represents a minuscule fraction of their training corpus (estimated at around 4% and 2%, respectively).

This lack of representation translates directly into problems of bias and hallucination when querying about local topics. For instance, a global model might struggle to accurately interpret regional slang, legal documents, local history, or cultural references, sometimes resorting to stereotypical or incorrect depictions.

Chilean President Gabriel Boric powerfully framed the project’s strategic importance, stating, “If we are not at the development table, we are going to be on the menu.” Latam-GPT is therefore an act of identity and digital preservation, ensuring that the region moves from being a passive consumer of AI to an active creator.

Pan-Regional Collaboration and Technical Specifications

The development of Latam-GPT is a testament to pan-regional collaboration, bringing together over 30 institutions and more than 60 AI experts from countries including Argentina, Brazil, Colombia, Mexico, Peru, and Uruguay. This diverse network contributes ethically sourced data from regional universities, government entities, libraries, and civil society organizations.

Key Technical Highlights:

• Training Data: The model was initially trained on over eight terabytes of regional and synthetic data, equivalent to millions of books.
• Architecture: Future versions of the model are expected to be based on an open-source architecture, such as Llama 3.1.
• Language Support: The initial focus is on refining its performance in Spanish and Portuguese.
• Indigenous Languages: A crucial long-term goal is the incorporation of Indigenous Latin American languages, such as Rapa Nui, Mapudungun, Quechua, Guaraní, and Aymara, to combat their lack of online presence and aid in cultural preservation.
• Infrastructure: The project was developed with a remarkably modest budget of about $550,000, funded by CENIA and the Development Bank of Latin America (CAF). While the initial version leveraged AWS cloud, future training will utilize a supercomputer located at the University of Tarapacá in northern Chile, reinforcing local infrastructure.

Public Impact and Practical Applications

Latam-GPT is designed to be accessible free of charge to companies, governments, and public institutions, reflecting its role as a public utility. Its open-source nature means the value of the model lies not in its raw parameters (which are smaller than frontier models) but in its context-specific data quality and its utility as a customizable base layer for regional applications.

The model’s impact is expected to be felt most immediately in the public sector and tailored business environments:

• Public Services: Potential applications include improving logistical management in hospitals, streamlining government public policy analysis, and supporting more agile public-sector processes.
• Education: It can be adapted to develop culturally specific curricula and tools aimed at reducing school dropout rates, leveraging training data that includes local textbooks and historical records.
• Enterprise: Local businesses, such as airlines and retailers, are interested in using Latam-GPT for customer service programs that can accurately recognize regional slang, idioms, and speech rates, providing a far more nuanced and effective user experience than generalized models.

Practical Takeaways for Latam Developers

For developers, researchers, and tech businesses in Latin America, Latam-GPT represents a significant step toward self-sufficiency. Its release means they no longer have to build custom AI tools by starting with a foreign, culturally alienated base model.

What to Do Next:

1. Explore the API/Codebase: Developers should monitor the CENIA and official Latam-GPT channels for the open-source code and API access to the foundation model (expected to have its first major version release in September 2026).
2. Fine-Tuning Opportunities: Given its foundation is tuned for regional Spanish and Portuguese, Latam-GPT offers a superior starting point for fine-tuning tasks related to specific country laws, local literature, or unique business jargon.
3. Contribute Data: Academic and civil society institutions are encouraged to continue contributing high-quality, ethically-sourced data to future iterations of the model, especially in underrepresented historical or linguistic areas, including Indigenous languages.

In essence, Latam-GPT is a technological declaration of independence. By prioritizing cultural accuracy, linguistic diversity, and open collaboration, the project ensures that Latin America’s AI future is built on its own terms and reflects its own rich reality.