This also is a misunderstanding.
The LLM can be fine, the training and data can be fine, but because the LLMs we use are non-deterministic (at least in regard to their being intentional attempts at entropy to avoid always failing certain scenarios) current algorithms are inherently by-design not going to always answer every question correctly that it potentially could have if the values that fall within a range had been specific values for that scenario. You roll the dice on every answer.