QWEN3.6-27B-MLX-8bit (29.5GIG) Is Excellent

Reddit r/openclaw Models
local-models ai-inference memory-optimization qwen-model mac-studio performance-tuning workflow-automation

Summary

A user shares their experience switching to the QWEN3.6-27B-MLX-8bit model for local AI tasks, finding it performs comparably to larger models while saving significant RAM on a Mac Studio, improving workflow stability.

For anyone using local models for orchestration, research, and writing, I had been using QWEN3.5-122B-a10-uncensored-hauhaucs-aggressive (79GIG)as my main driver. It's an excellent model and drives eight hour workflows reliably. With an M3Ultra Mac Studio with 256 GIG of RAM, however, when I'd get to the video generation portion of my workflow, I would easily push 93% of memory usage and periodically be forced to start closing applications. I did a lot of testing the past few days (I posted about it recently) and found no other models amongst QWEN or Nemotron that were comparable. However, today I found that QWEN3.6-27B-MLX-8big (29.5GIG) performed as good at all of these tasks, but was slower. However, until I get my newer Mac Studio to add to this one dedicated only to video work, it gives me back 50 GIG of RAM to work with. That frees up a lot of headspace to avoid crashes. Just sharing, for those who embrace local models.
Original Article

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