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Sabi\'a-2: A New Generation of Portuguese Large Language Models

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arxiv 2403.09887 v2 pith:CTSK5N4W submitted 2024-03-14 cs.CL cs.AI

classification cs.CLcs.AI
keywords examssabimodelsgpt-4languagelargemediummodel
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We introduce Sabi\'a-2, a family of large language models trained on Portuguese texts. The models are evaluated on a diverse range of exams, including entry-level tests for Brazilian universities, professional certification exams, and graduate-level exams for various disciplines such as accounting, economics, engineering, law and medicine. Our results reveal that our best model so far, Sabi\'a-2 Medium, matches or surpasses GPT-4's performance in 23 out of 64 exams and outperforms GPT-3.5 in 58 out of 64 exams. Notably, specialization has a significant impact on a model's performance without the need to increase its size, allowing us to offer Sabi\'a-2 Medium at a price per token that is 10 times cheaper than GPT-4. Finally, we identified that math and coding are key abilities that need improvement.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Zero-shot Performance of Generative AI in Brazilian Portuguese Medical Exam

    cs.CL 2025-07 conditional novelty 6.0 of 10

    On an authentic Brazilian Portuguese residency exam, top general-purpose AI models scored near the human average on text-only questions but dropped when questions included medical images.

  2. BRoverbs -- Measuring how much LLMs understand Portuguese proverbs

    cs.CL 2025-09 conditional novelty 5.0 of 10

    BRoverbs lets researchers test whether language models understand Portuguese proverbs; commercial models nearly master it, small models often guess randomly.

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