Comment by vidarh

I get decent results with Kimi, but I agree with your overall premise. You do need to realise that while you can save money on a lot of tasks with those models, for the hardest tasks the "sticker price" of cost per million tokens isn't what matters.

It's also worth noting that the approach given in the link also benefits Sonnet and Opus. Not just as much - they are more forgiving - but put it in a harness that allows for various verification and repair and they too end up producing much better results than the "raw" model. And it's not clear that a harness around MiniMax, Kimi, or Qwen can measure up then.

I use those models a lot, and hope to use them more as my harnesses get better at discriminating which tasks they are cost effective for, but it's not straightforward to cost optimize this.

If I cared about running everything locally, then sure, it's amazing you can get to those kinds of results at all.