Athenas-Symbiote-9B: A Parameter-Efficient Fine-Tuned LLM for Brazilian Portuguese Legal and Academic Domains

Athenas-Symbiote-9B is an open-weights large language model optimized for Brazilian Portuguese through parameter-efficient fine-tuning (PEFT). Built on the Qwen3.5-9B-Base architecture, the model employs LoRA adapters with rsLoRA scaling, trained on constrained-compute hardware (1× NVIDIA T4, 16 GB VRAM, via Kaggle) using 4-bit quantization and the Unsloth optimization framework. Despite this extreme compute restriction, the model achieves 63.23% accuracy on the Brazilian Bar Examination (OAB) and 80.90% on the National High School Exam (ENEM), both evaluated in a 3-shot configuration using the EleutherAI lm-evaluation-harness on H100 infrastructure.