AMALIA Technical Report: A Fully Open Source Large Language Model for European Portuguese

arXiv cs.CL / 3/30/2026

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Key Points

  • The AMALIA technical report introduces a fully open-source large language model designed to better serve European Portuguese (pt-PT), addressing the language’s underrepresentation in training and native evaluations.
  • The model is trained with more high-quality pt-PT data during both mid-training and post-training to reduce gaps caused by relying on machine-translated resources.
  • The authors release a suite of pt-PT-focused benchmarks, including both translated standard tasks and new datasets aimed at pt-PT generation, linguistic competence, and pt-PT/pt-BR bias measurement.
  • Experimental results indicate AMALIA performs comparably to strong baselines on translated benchmarks while delivering substantially improved results on pt-PT-specific evaluations, reinforcing the value of targeted training and native benchmarking.

Abstract

Despite rapid progress in open large language models (LLMs), European Portuguese (pt-PT) remains underrepresented in both training data and native evaluation, with machine-translated benchmarks likely missing the variant's linguistic and cultural nuances. We introduce AMALIA, a fully open LLM that prioritizes pt-PT by using more high-quality pt-PT data during both the mid- and post-training stages. To evaluate pt-PT more faithfully, we release a suite of pt-PT benchmarks that includes translated standard tasks and four new datasets targeting pt-PT generation, linguistic competence, and pt-PT/pt-BR bias. Experiments show that AMALIA matches strong baselines on translated benchmarks while substantially improving performance on pt-PT-specific evaluations, supporting the case for targeted training and native benchmarking for European Portuguese.