> You can ask GPT to spell a word, or provide the words as individual "S P A C E D" characters and it will similarly do poorly- it has nothing to do with tokenization. GPT is capable of spelling, it can even identify that it is not playing well if you ask if something is a good guess- but continues to give poor answers.

Yeah, because 99.99% of the time when it sees words they are not written in the way. It's true that the model can just about figure out how to break a word up into characters, but it has to work hard at that and seemingly doesn't have many layers left for completing the actual task.

I would expect that a model trained with single character tokens would do far better at these word games (wordle, hangman, etc.) at the cost of being worse at almost everything else.