model-routing

Model Routing: Cloud Orchestration + Local Code Generation

Use expensive cloud models (Opus, Sonnet) for planning, review, and orchestration. Delegate token-heavy code generation to on-device models via Ollama. This can reduce costs 10-50x for coding-heavy sessions.

Prerequisites

• Ollama installed and running (ollama serve)
• A coding-capable model pulled: ollama pull qwen3-coder:30b (recommended) or ollama pull glm-4.7-flash
• Minimum 16GB RAM (24GB+ recommended for best results)

How It Works

You (developer)
  |
  v
Cloud Model (Sonnet/Opus) — orchestration, planning, review
  |
  |-- "Write the service layer for Projects"
  |       |
  |       v
  |   Local Model (Ollama) — code generation subagent
  |       |
  |       returns generated code
  |
  |-- Reviews output, checks against project conventions
  |-- Requests corrections if needed
  |-- Commits the final result

The cloud model decides WHAT to build and HOW it should work. The local model does the token-heavy GENERATION. The cloud model reviews the output.

Setup

Option 1: Claude Code Subagent (Recommended)

Create a custom subagent definition in your project that delegates to a local Ollama instance. In your .claude/settings.json or project config:

{
  "subagents": {
    "local-coder": {
      "description": "Fast local model for code generation tasks",
      "provider": "ollama",
      "model": "qwen3-coder:30b",
      "base_url": "http://localhost:11434",
      "tools": ["Read", "Write", "Edit", "Glob", "Grep", "Bash"],
      "prompt": "You are a code generation assistant. Follow the project conventions described below exactly. Generate only the requested code — no explanations unless asked."
    }
  }
}

Then in your workflow, the orchestrating model can delegate: "Use the local-coder subagent to generate the service file for Projects following the template in .skills/scaffold/SKILL.md."

Option 2: Ollama as Primary with Cloud Fallback