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Well given the price $15.00 / 1M input tokens and $60.00 / 1M output* tokens, I would hope so. Given the price, I think it is fair to say it is doing a lot of checks in the background.

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It is expensive. But if I'm correct about o1, it means user mistrust of LLMs is going to be a short-lived thing as costs come down and more people use o1 (or better) models as their daily driver.

> mistrust of LLMs is going to be a short-lived thing as costs come down and more people use o1

I think the biggest question is, is o1 scalable. I think o1 does well because it is going back and forth hundreds if not thousands of times. Somebody mentioned in a thread that I was participating in that they let o1 crunch things for 10 minutes. It sounded like it saved them a lot work, so it was well worth it.

Whether or not o1 is practical for the general public is something we will have to wait and see.

I'm going to wager "yes" because o3-mini (High) gets equal benchmark scores to o1 despite using 1/3rd as much compute, and because the consistent trend has been towards rapid order-of-magnitude decreases in price for a fixed level of intelligence (trend has many components dovetailing, both hardware and software related). Can't forecast the future, but this would be my bet on a time horizon of < 3 years.

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