Sabiá-4 Technical Report

TL;DR

This technical report presents Sabi-a-4 and Sabiazinho-4, a new generation of Portuguese language models with a focus on Brazilian Portuguese language, and shows improvements over previous generations in legal document drafting, multi-turn dialogue quality, and agentic task completion.

Abstract

This technical report presents Sabiá-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 Sabiá-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.

Figures (12)

• Figure 1: Total inference cost versus average benchmark accuracy. Optimal models appear in the upper-left quadrant (cheaper and better). Sabiá models highlighted in green. Currency conversion: BRL/USD = 5.4.
• Figure 2: Training pipeline overview. Pre-training consists of Portuguese continual learning on general and legal corpora, followed by long context training. Post-training includes supervised fine-tuning on diverse instruction data and preference alignment.
• Figure 3: Comparison of Sabiá generations on the MRCR benchmark. Sabiá-4 and Sabiazinho-4 are the new model generations.
• Figure 4: Sample from BRACEVal benchmark. Note that the example was translated to English for the paper. Original language is Portuguese.
• Figure 5: Sample from Climb benchmark. Note that the example was translated to English for the paper. Original language is Portuguese.