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It's not thinking. Not in the way she probably meant. It can "think" that fast the same way a calculator can "think" that fast (kind of).

Because it's not human and not "thinking", it's mathematical algorithm

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to be fair, the model used for Chat Jimmy is not very smart, but the world where it is smart is very interesting.

It’s going to be really crazy when the bottle neck for agents is the speed of the tool calls rather than the speed of inference. Imagine an agent interacting with the terminal near instantly…

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I had the chance to try out MiMo v2.5 Pro Ultraspeed (600-1000tok/s) for a couple weeks and it is amazing.

Developing software becomes 95% about intent and requirements. Can’t wait for the next iteration of that.

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I asked it some old hardware command line questions I'd recently asked Gemini, it hallucinated parts of the answer.

The characters in the 3-act Shakespearean play had very little depth, many of the names were similar, and they were not very smart, but the simple plot was cohesive.

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Wait, is it even thinking? Or is it an instant model?
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It’s not reasoning, the hardware demo uses a 3.-something generation Llama 8B.

But it’s proven they can automate this (they didn’t etch eight billion weights by hand after all, obviously), so now the interesting question is whether they can scale it to more recent aka bigger models.

After all, there’s already very useful models even for productivity at 27 or 35B.

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My concern is that reasoning could involve some sequential steps that instant models don't.

Not sure if modern models "think" only by outputting <thinking> blocks, or there is a more complex mechanism at play.

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It's not really "instant", i.e. the text is still generated token-by-token, it's just super fast. Reasoning would work with this model without any changes to the chip but it's disabled for speed.
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