A good language model predicts upcoming tokens with high accuracy to produce sensible and logically coherent text. For example, given the context "It is raining", a high-quality model might suggest "outside", which is both grammatically and semantically appropriate. A lower-quality model might propose "banana tree", generating a nonsensical extension that still demonstrates basic spelling and word correlation. A poorly trained model that fails to fit the data would output random characters, such as "piouw;kcj pwepoiut".