HN user
I have tried plenty of other models with full FP32 as wel. However, in terms of balance between accuracy and speed, I found the Qwen 3.6 27B to be the sweet spot.
I have been using local LLMs for about a year and I have settled now on Qwen3.6 27b dense model in GGUF on Mac Studio with 512G of RAM with open code as the harness and llmster(LM Studio). I have also used the Qwen 3.6 35B-A3B but the dense model's accuracy is next level with the tradeoff being tokens/sec. With the Qwen3.6 27b, I usually get anywhere from 25-40 tokens/second. Initially I used them for simple tools but for the past 3-4 months, I have been actually doing production grade coding in C/C++ (Automotive Software stack) and Python (Tools) with Qwen3.6 27b.
The tokens/sec may be less but that kind of helps me in going at the right pace. The workflow I use for green field development / rewrites is to pair with Sonnet for design/architecture, reasoning and a detailed execution plan. I then feed this piece by piece with precise prompting and that does the job. For brown field, it is often a judgement call. There are occasions when I have found Local models to be limited in their reach and I resort to Claude Code
Some of my recent work using Qwen 3.6: 1. Complete rewrite of Power management Service in C using the existing C++ code as reference 2. Tool to parse contents from really complex specifications in Excel format 3. Tool to translate CJK contents to english for feeding into KG