Using Local Coding Agents
Ahead of AI Sebastian Raschka, PhD ● Covered by 2 sources
A tutorial explains how to set up a local coding agent using open-source tools and open-weight LLMs like Qwen3.6 35B-A3B, with Ollama as the model serving engine and Qwen-Code as the harness. The Qwen3.6 35B-A3B model requires approximately 30-40 GB of RAM and achieves strong performance on code generation benchmarks compared to alternatives like North Mini Code. Users can evaluate local setup performance using speed benchmarking scripts and avoid vendor lock-in with proprietary services like OpenAI Codex or Anthropic Claude Code.
Why it matters
Using Open-Weight Models in Local Coding Harnesses as an Alternative to Claude Code and Codex Subscriptions