I'm not sure if this was mentioned in the paper somewhere, but how much does the super large 265k tokenizer vocabulary influence inference speed and how much hi

I'm not sure if this was mentioned in the paper somewhere, but how much does the super large 265k tokenizer vocabulary influence inference speed and how much higher is the average text compression compared to llama's usual 30k? In short, is it really worth going beyond GPT 4's 100k?