CLMar 10

Sabiá-4 Technical Report

arXiv:2603.10213v131.72 citationsh-index: 9
Predicted impact top 9% in CL · last 90 daysOriginality Synthesis-oriented
AI Analysis

This is an incremental advancement for users needing efficient Portuguese language models, particularly in Brazilian contexts.

The paper tackles the development of Portuguese language models for Brazilian Portuguese, achieving a favorable cost-performance trade-off with improvements in legal drafting, dialogue quality, and agentic tasks.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes