Evidently, Claude's tokenizer vocabulary size is ~15k[1]. On one hand, it's quite mind blowing. On the other hand, Anthropic models' token (in)efficiency makes a lot of sense in that light.
[1]: https://xcancel.com/magikarp_tokens/status/20878591737488549...
Not just that, they normalize everything into lowercase and use a special character to capitalize words (what about languages with non-trivial normalization/capitalization?) and mark beginning and end of each word, all of that diluting already small vocabulary. That smells like manual tuning of what should be done statistically, I wonder what technical merit they saw in that - I know they mentioned better generalization, but this is pretty counterintuitive.