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by ankit219
506 days ago
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At this point, it's a function of how many thinking tokens can a model generate. (when it comes to o1 and r1). o3 is likely going to be superior because they used the training data generated from o1 (amongst other things). o1-pro has a longer "thinking" token length, so it comes out as better. Same goes with o1 and API where you can control the thinking length. I have not seen the implementation for r1 api as such, but if they provide that option, the output could be even better. |
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