A base model is a trained model used as the starting point for later specialization or deployment. Developers may fine-tune it, add retrieval, give it tools or wrap it in a larger system designed for a particular task.
Separating the base model from the full system matters when evaluating results. Performance may come from prompts, test-time methods, data selection, tools and human decisions rather than from the unchanged model alone.
