Interestingly enough this library doesn't provide grapheme cluster tokenization and/or boundary checking which is one of the most useful primitive for this.
If you’re in control of all data representations in your entire stack, then yes of course, but that’s hardly ever the case and different tradeoffs are made at different times (eg storage in UTF-8 because of efficiency, but in-memory representation in UTF-32 because of speed).
Modern processors are generally computing stuff way faster than they can load and store bytes from main memory.
The code which does on the fly normalization only needs to normalize a small window. If you’re careful, you can even keep that window in registers, which have single CPU cycle access latency and ridiculously high throughput like 500GB/sec. Even if you have to store and reload, on-the-fly normalization is likely to handle tiny windows which fit in the in-core L1D cache. The access cost for L1D is like ~5 cycles of latency, and equally high throughput because many modern processors can load two 64-bytes vectors and store one vector each and every cycle.