alt Hacker NewsI have tried the Thinking cap and the Swift model for QWEN-3.8 27B and my experience was its not as smart and capable, the results on the same task were less impressive. For the amount of tokens saved it might very well be worth it but I wanted to run the xhigh precisely because I wanted the peak result. I haven't tested this but I suspect it ends up much the same trade off, in theory it does well in the benchmarks but in practice on your own tasks its not as capable.
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But Qwen 3.8 27b is unbearable slow, you get 10minutes of "let me think" over any trivial stuff.
For most folks in this thread running old M1 Max like me, look into MTPLX models (and the namesake inference engine).
I’ve built something custom that’s pretty darn fast but not ready for prime time yet. Might share it eventually.
This is my experience with Fireworks Ember-1 (reduced thinking Kimi K3)
It hallucinated and claimed task completion almost every session. Zero trust for this concept of fine tuning out excessive thinking, seems to do more harm than good. Eventually, as token vendors continue to commoditize, we will not care.
Yeah. I didn't find these any good either.
However, Gemma 4 26B is a reasonably good general chat inquiry model (it's also not too bad at commonplace code questions, if not as good for agentic code).
So this could be a good, fast model for that, in some situations; I may test it.
I still broadly just prefer working with Muse Glimmer, to be honest; we get along OK. I am trying out the Nemotron Bolt 74B/A9B MoE and I really do think it could be quite good, but it's still slow on Metal.