A better metric is price per byte. Most thinking traces, prompts, skills are in plain English, which is roughly 1 byte per character, assuming UTF-8 encoding (even code should not be much more either). As an aside, it is common to use bits-per-byte as a loss metric instead of the per token calculation, precisely because of the effect of different tokenizers.
It's going to vary dramatically based on which text you put in. Really it's hard to make one benchmark number that's relevant to all cases. But maybe we can make something a little more specific, like regular English text, code, the model's own thinking tokens, image inputs etc.
