100% Free Claude Code | Run Claude Code with Local LLM with Ollama and Qwen 3.5

2026-03-17 · Source: Venelin Valkov · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, medium

Summary

This content demonstrates how to integrate a local Large Language Model (LLM) with a Quad Code instance using Ollama as the inference provider. The process involves installing the unmodified Quad Code, then launching it via `Ollama launch quad` or `Ollama launch quad --model <model_name>`. The demonstration uses the Quant 3.5 35 billion parameter Mixture-of-Experts model, which is suitable for consumer hardware. Testing was conducted on a complex repository, revealing that while the local LLM struggled with initial project overview, it performed well when directed to analyze specific files and even successfully implemented an auto-edit to fix a bug. The author notes that larger models might yield better overall repository understanding, but the 35 billion parameter model showed promising results for directed tasks.

Key takeaway

For AI Engineers evaluating local LLM integration for coding assistance, this demonstrates that a 35 billion parameter model can effectively handle specific file analysis and auto-editing within Quad Code via Ollama. While general project overviews remain challenging for smaller local models, focusing on directed tasks can yield practical benefits, potentially reducing reliance on external API costs and improving data privacy. Consider experimenting with local models for targeted code review and refactoring.

Key insights

Local LLMs can be integrated with Quad Code via Ollama for specific coding tasks, offering a viable alternative to API-based solutions.

Principles

• Ollama enables local LLM inference for Quad Code.
• Model size impacts general project understanding.
• Directed tasks yield better local LLM performance.

Method

Launch Quad Code using `Ollama launch quad` or `Ollama launch quad --model <model_name>` to connect it with a local Ollama instance for LLM inference.

In practice

• Use `Ollama launch quad` for local LLM integration.
• Specify models with `--model quant-3-5-35b`.
• Direct LLM to specific files for better analysis.

Topics

• Quad Code
• Local LLM
• Ollama
• Qwen 3.5
• Code Analysis

Best for: AI Engineer, MLOps Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Venelin Valkov.