My amateur intuition, having played around with local llms a little bit and seeing things load a token at a time, is that they're conceptually like if you took

My amateur intuition, having played around with local llms a little bit and seeing things load a token at a time, is that they're conceptually like if you took all n-grams for all lengths n, then sorted them by frequency in the training data, and truncated that list at some point. So the most common words, or even most common words+punctuation, will be one token, less common words with "normal" spelling will be a few tokens, while unusual words with atypical letter combinations will be many tokens. So, e.g., " the" will probably be one token, but "qzxv" will probably be four, depending on what the training set was (something mostly trained on Wikipedia will have different tokens than something mostly trained on code).