AINewsnow

Qwen3.6-35B-A3B (22 GB, 4-bit) on a 16 GB Mac mini M4 through stock llama.cpp: speed, a 4-agent crew, and executed code scores

There's a running assumption that multi-agent coding pipelines on consumer hardware are too slow to be practical, or fall apart on real unit tests. We built Kraits, a plugin for stock llama.cpp that runs Unsloth's 22 GB Qwen3.6-35B-A3B 4-bit file on a 16 GB Mac. We ran it on a single prompt and on…

Read the full story at r/LocalLLM ↗

Timeline · 1 report

  1. 2026-10-20 21:01 · r/LocalLLM
    Qwen3.6-35B-A3B (22 GB, 4-bit) on a 16 GB Mac mini M4 through stock llama.cpp: speed, a 4-agent crew, and executed code scores

More stories

  1. DeepSeek V4.1 Flash is now available in Token Pass — Vercel Blog
  2. Basalt: NVFP4 + faster prefill for Qwen3.8 Flash-Next on Blackwell (single 5090) — r/LocalLLaMA
  3. Intel Arc B580 now beats an RTX 5060 Ti on llama.cpp prompt processing (Llama 2 7B), plus 1.5x faster long chats — r/LocalLLM
  4. Geezuz kernel: Qwen3.8-27B at 190 tok/s (620~ tok/s at 8 requests) on two 3090s — r/LocalLLaMA
  5. 12GB VRAM + 16GB RAM is enough for very smart local AI with 120K+ context — r/LocalLLM
  6. Qwen3-4B in 1.24 GB at perplexity 16.6 (IQ2_XXS at the same size: 28.6) - a tiny 8-state trellis quant for llama.cpp — r/LocalLLM
  7. llama.cpp support for Cohere models — r/LocalLLaMA
  8. Budget rig for local LLM inference + distillation: 2x RTX 3060 12GB vs 2x Tesla P100 16GB? — r/LocalLLM

Get the daily brief of stories like this at 6:30 every morning →