Comment by orbital-decay

Tokenizers are typically optimized for efficiency, not morpheme separation. Even in the examples above it's not morphemes - proper morpheme separation would be un-believ-ably and дост-о-при-меч-а-тельн-ость.

Regardless of this, Gemini is still one of the best models when it comes for Slavic word formation and manipulation, it can express novel (non-existent) words pretty well and doesn't seem to be confused by wrong separation. This seems to be the result of extensive multilingual training, because e.g. GPT other than the discontinued 4.5-preview and many Chinese models have issues with basic coherency in languages that heavily rely on word formation, despite using similar tokenizers.