Recent performance data on my M1 Max 32GB MacBook using oMLX. I have been working on identifying suitable model and config for my use case and system. Using a refactor and suggest improvements prompt for a specific Django code block using VSCode Cline extension.

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Qwen3.8-27B-4bit, Prompt Processing (PP) 66.3 tok/s, Token Generation (TG) 11.8 tok/s

Ornith-1.5-35B-A3B-MLX-4bit, PP 379.7, TG 45.8

Ornith-1.5-35B-A3B-MLX-4bit, PP 381.5, TG 46.4

Qwen3.6-35B-A3B-mxfp4, PP 389.6, TG 47.6

Qwen3.6-35B-A3B-OptiQ-4bit, PP 342.6, TG 44.4

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Qwen3.8-27B-4bit generally runs out of output token before completing the task though excellent partial results.

Ornith-1.5-35B-A3B-MLX-4bit seems to get in the loop often specially with tool calls.

Qwen3.6-35B-A3B-mxfp4 seems to be optimal with speed and quality output.

I am going to test Qwen3.6-35B-A3B-4bit soon with same code block just to check my intuition that any derivatives don't seem to perform better than the originals.