GoKawiil
Tech News
Reddit user markpronkin bought a rusty, untested nine-GPU crypto mining rig found in a damp garage for about $35 (3,000 rubles) after the seller refused a pre-purchase test. The rig's nine Nvidia P106-100 cards, each with 6GB of GDDR5, provided 54GB of combined VRAM and worked on the first attempt, running Alibaba's 35-billion-parameter Qwen3.6-35B-A3B model in Ollama at over 30 tokens per second.
A developer detailed a personal setup running local language models on an Apple M4 Pro Mac mini, using Qwen and Gemma models served through an inference tool called oMLX, connected across devices via Tailscale. The setup powers an agent backend called Hermes plus various chat and coding tools, and reportedly takes about 30 minutes to configure.
A user ran Alibaba's new Qwen3.8 27B model locally on a Mac Studio M3 Ultra for 10 days, using it for daily tasks like summarizing RSS feeds and renaming scanned PDFs, then formally benchmarked it against its predecessor. The Q4_K_M version generated at about 14 tokens per second versus 28.6 tokens/s for Qwen3.6 27B, but produced answers using roughly a third as many tokens, making total response time nearly equal. A 1-bit quantized version ran much faster at 27 tokens/s and stayed factually accurate but struggled to commit to definitive answers.
A hobbyist built CarWatch, a system that puts a Raspberry Pi 5 in a car running a 35-billion-parameter Qwen model locally, no internet or subscription required. It joins chat rooms as an AI agent, sending trip summaries, dashcam clips, and answers sourced from the car's 745-page owner's manual, and also supports hands-free voice queries via on-device speech recognition.