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.

Sabi'a-2 是一种基于葡萄牙语文本训练的大型语言模型，通过在各种考试中进行评估，包括巴西大学的入学考试、专业认证考试以及各种学科的研究生考试，发现 Sabi'a-2 Medium 在 64 场考试中有 23 场性能超过或与 GPT-4 相当，有 58 场性能超过 GPT-3.5，且专业化能显著提高模型的性能而无需增加大小，使 Sabi'a-2 Medium 的每个标记的价格比 GPT-4 便宜 10 倍，此外，我们发现数学和编码是需要改进的关键能力。