[rgbrgb]

> Personally, the comparison to Claude and 4o doesn't quite seem apples-to-apples. If you were to have 4o/Claude take multiple rounds to review and reflect on their initial drafts, would we see similar gains? I suspect they would improve massively as well.

They may already implement this technique, we can't know.

[astrange]

Claude 3.5 does have some "thinking" ability - I've seen it pause and even say it was thinking before. Presumably this is just some output it decides not to show you.

[cchance]

THIS!!!!!!! People act like Claude and 4o are base models with no funny business behind the scenes, we don't know just how much additional prompt steps are going on for each queue, all we know is what the API or Chat interface dump out, what is happening behind that is anyones guess.. The thinking step and refinement steps likely do exist on all the major commercial models. It's such a big gain for a minimal expenditure of backend tokens, WTF wouldn't they be doing it to improve the outputs?

[astrange]

Well they can't do a /lot/ of hidden stuff because they have APIs, so you can see the raw output and compare it to the web interface.

But they can do a little.

[baq]

As if they couldn’t postprocess the api output before they send it to the client…

[astrange]

No, I mean they sell API access and you can query it.

[Tiberium]

That's only in the web version, it's just that they prompt it to do some CoT in the antThinking XML tag, and hide the output from inside that tag in the UI.

[jph00]

The API does it too for some of their models in some situations.

[KTibow]

Interesting, is there any documentation on this or a way to view the thinking?

[kgeist]

I suspect GPT4o already has training for CoT. I've noticed it often responds by saying something like "let's break it down step by step". Or maybe it's the system prompt.

[bluejay2387]

I am not sure, but you seem to be implying that the Reflection model is running through multiple rounds? If so, that is not what is happening here. The token generation is still linear next token prediction. It does not require multiple rounds to generate the chain of thought response. It does that in one query pass.

I have been testing the model for the last few hours and it does seem to be an improvement on LLAMA 3.1 upon which it is based. I have not tried to compare it to Claude or GPT4o because I don't expect a 70b model to outperform models of that class no matter how good it is. I would happy to be wrong though...