Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model

· ai llm open-source · Source ↗

Article

TL;DR

Qwen3.6-27B runs in 16.8GB, delivers flagship coding at 25 tok/s on a 32GB Mac.

Key Takeaways

  • Runs at 25 tok/s on M5 Pro; fits comfortably on 32GB RAM or 24GB VRAM machines
  • Noticeable improvement over 3.5-27B; threatens paid Claude plan value for local coders
  • Wait 2 weeks before judging — early quants routinely have bugs the community irons out

Discussion

Top comments:

  • [simonw]: Ran it on M5 Pro 128GB; only needs ~20GB, better pelican than Opus 4.7

    I ran it on an M5 Pro with 128GB of RAM, but it only needs ~20GB of that. I expect it will run OK on a 32GB machine.

  • [syntaxing]: Covers 95% of real coding needs fully local on M4 MBP
  • [originalvichy]: Wait weeks for community to find inference backend bugs before judging quality
  • [jameson]: Open-source models at fraction of Anthropic pricing erode closed-model moat

Discuss on HN