Comment by great_psy
11 hours ago
Is there any provided reason from anthropic why they changed the tokenizer ?
Is there a quality increase from this change or is it a money grab ?
11 hours ago
Is there any provided reason from anthropic why they changed the tokenizer ?
Is there a quality increase from this change or is it a money grab ?
The tokenizer is an important part of overall model training and performance. It’s only one piece of the overall cost per request. If a tokenizer that produces more tokens also leads to a model that gets to the correct answer more quickly and requires fewer re-prompts because it didn’t give the right answer, the overall cost can still be lower.
Comparisons are still ongoing but I have already seen some that suggest that Opus 4.7 might on average arrive at the answer with fewer tokens spent, even with the additional tokenizer overhead.
So, no, not a money grab.
How would it be a money grab? If the new tokenizer requires more tokens to encode the same information, it costs them more money for inference. The point of charging per token is that the cost is proportional to the number of tokens. That's my understanding anyway
Because everyone burns through their limits much faster, forcing them to upgrade to higher limits or new tiers.
I think someone would much sooner switch to a competitor than up their tier.
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They could just increase the token cost no? There’s little need for cute conspiracies like these
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Not necessarily with speculative decoding. Whitespace would be trivial to predict and they would petty much keep using the same amount of compute as before.
I don't think that's their primary motive for doing this but it is a side effect.
If they wanted they could always just double the $/token. They don't seem to be able to keep up with their current demand and that's what companies normally do in that circumstance if they're looking to money grab, no need for the bankshot approach.
It's a better model in my usage. I have benchmarks.