Tucano 2 Cool: Better Open Source {LLMs} for Portuguese

We present Tucano 2, a fully open suite of large language models ({LLMs}) with 0.5-3.7 billion parameters, designed to address certain gaps in open-source development for Portuguese {LLMs}. Following our previous works, we now extend our dataset, {GigaVerbo}-v2, to a new degree of quality and scale, while also introducing a new synthetic dataset, {GigaVerbo}-v2 Synth, aimed at filling missing gaps in {GigaVerbo}-v2, and two post-training datasets, {GigaVerbo}-v2 {SFT} and {GigaVerbo}-v2 Preferences, that allow Portuguese {LLMs} to be trained in domains like retrieval augmented generation, coding, tool use, chain-of-thought reasoning, and many other domains of interest. Through extensive ablation studies, we design both pretraining and continual pretraining recipes for the Tucano 2 suite (Base, Instruct, and Think), which achieve state-of-the-art performance on several Portuguese-language modeling benchmarks. We also extend and refine the evaluation harness introduced in our earlier work, yielding a comprehensive evaluation suite that provides strong signals across different pretraining, continual pretraining, and post-training regimes. All artifacts associated with Tucano 2 are openly released, including training recipes, logs, and source code, ensuring that our work is reproducible, accessible, and extendable by the broader Portuguese {NLP} community.