@tobi: I’ve had very good results running autoresearch with local qwen 3.6 26b model as long as I had a simple vibed pi “advis…
Summary
@tobi reports good results using a local Qwen 3.6 26b model for autoresearch with a 'vibed pi advisor' extension that periodically consults GPT 5.5 for ideas, suggesting this direction has merit.
Similar Articles
@ivanfioravanti: Autoresearch from @karpathy in action locally using gemma-4-26b-a4b-it-6bit with oMLX on an M5 Max to train Gemma 4 E2B…
Developer Ivan Fioravanti demonstrates running Andrej Karpathy's autoresearch project locally with a 6-bit quantized Gemma-4-26B model on Apple Silicon, suggesting successful training of Gemma 4 E2B IT variant.
@ChrisHayduk: GPT 5.5 is an effective autoresearcher in structural biology! I've had goal mode running for over 150 hours straight, l…
A user reports that GPT 5.5 successfully conducts autonomous research in structural biology, improving AlphaFold2's performance after 150+ hours of goal mode.
Qwen 35b a3b surprises me
User reports positive experience with Qwen 35b a3b for agentic coding tasks, noting it outperforms Gemma4 26b in their use case and works well for demo/data analytics, especially in agentic mode versus chat.
Running Qwen3.6-35B-A3B Locally for Coding Agent: My Setup & Working Config
A detailed guide for running the 35B-parameter Qwen3.6 model locally on Apple Silicon with llama.cpp to power the pi coding agent, including optimized configuration flags and sampling parameters.
@davis7: @0xSero helped me setup local models properly and I uh, had no idea these things had gotten this good Are they frontier…
The author highlights the impressive capabilities of the open-source Qwen 3.6-27B model running locally on an RTX 5090, noting its strong performance on programming tasks and comparing it favorably to commercial models, despite the complexity of local deployment.