> Why: LLMs are increasingly becoming multimodal, so an image "token" or video "token" is not as simple as a text token.
For autoregressive token-based multimodal models, image tokens are as straightforward as text tokens, and there is no reason video tokens wouldn’t also be. (If models also switch architecture and multimodal diffusion models, say, become more common, then, sure, a different pricing model more tied to actual compute cost drivers for that architecture are likely but... even that isn’t likely to be bytes.)
> Also, it's difficult to compare across competitors because tokenization is different.
That’s a reason for incumbents to prefer not to switch, though, not a reason for them to switch.
> Eventually prices will just be in $/Mb of data processed.
More likely they would be in floatint point operations expended processing them, but using tokens (which are the primary drivers for the current LLM architectures) will probably continue as long as the architecture itself is doninant.