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Sabi\'a-4 Technical Report

arXiv cs.CL / 3/12/2026

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Key Points

  • Sabi'a-4 and Sabiazinho-4 are introduced as new generation Portuguese language models with a focus on Brazilian Portuguese.
  • They were developed through a four-stage training pipeline consisting of continued pre-training on Portuguese and Brazilian legal corpora, a long-context extension to 128K tokens, supervised fine-tuning on instruction data spanning chat, code, legal tasks, and function calling, and preference alignment.
  • They were evaluated across six benchmarks, including conversational capabilities in Brazilian Portuguese, knowledge of Brazilian legislation, long-context understanding, instruction following, standardized exams, and agentic capabilities including tool use and web navigation.
  • They show a favorable cost-performance trade-off and improvements over previous generations in legal document drafting, multi-turn dialogue quality, and agentic task completion, positioning them well on the pricing-accuracy chart.

Abstract

This technical report presents Sabi\'a-4 and Sabiazinho-4, a new generation of Portuguese language models with a focus on Brazilian Portuguese language. The models were developed through a four-stage training pipeline: continued pre-training on Portuguese and Brazilian legal corpora, long-context extension to 128K tokens, supervised fine-tuning on instruction data spanning chat, code, legal tasks, and function calling, and preference alignment. We evaluate the models on six benchmark categories: conversational capabilities in Brazilian Portuguese, knowledge of Brazilian legislation, long-context understanding, instruction following, standardized exams, and agentic capabilities including tool use and web navigation. Results show that Sabi\'a-4 and Sabiazinho-4 achieve a favorable cost-performance trade-off compared to other models, positioning them in the upper-left region of the pricing-accuracy chart. The models show improvements over previous generations in legal document drafting, multi-turn dialogue quality, and agentic task completion.