> A significant effort was also devoted to enhancing the model’s reasoning capabilities. One of the key focus areas during training was to minimize the model’s tendency to “hallucinate” or generate plausible-sounding but factually incorrect or irrelevant information. This was achieved by fine-tuning the model to be more cautious and discerning in its responses, ensuring that it provides reliable and accurate outputs.

Is there a benchmark or something similar that compares this "quality" across different models?