⚡Going hybrid: cloud + local

You now have two worlds at hand: a fearsomely smart cloud agent (Claude Code), and models that run for free at home (Ollama). The wrong question is “which one to choose?” The right answer is: both, at the same time, each in its place.

That’s the hybrid setup. And the central role goes to Claude Code, as the conductor. It doesn’t do everything itself, it decides who does what, and delegates the bulk work to the local model.

Why mix rather than choose

The two worlds have opposite strengths, and that’s exactly what makes them complementary:

• The cloud (Claude) is unbeatable on hard reasoning, long tasks, reliable tool use, architecture. But every call costs, and your data goes to a third party.
• Local (Ollama) is free to use, private, available offline, and largely good enough for bounded and repetitive tasks. But it tires on long agentics and cutting-edge reasoning (we talked about it bluntly in Choosing your model).

The hybrid setup takes the best of each: you keep cutting-edge intelligence where it really matters, and you knock down cost and data leaks on everything else, that is, 80% of the volume.

Claude Code as orchestrator: how it works

The thing that makes this possible: Claude Code can run commands. And Ollama exposes a dead-simple local API on http://localhost:11434. So Claude Code can call your local model, via a curl, a script, or a small tool, exactly as it would call any other command.

Concretely, you tell Claude: “for this bulk task, don’t do it yourself, delegate it to the local model via the Ollama API.” It writes the script that loops over your files, hits the local model for each one, and brings back the consolidated result. It keeps the big picture; local does the grunt work.

# The basic move Claude Code orchestrates: call the local model
curl -s http://localhost:11434/api/generate -d '{
  "model": "qwen3-coder:30b",
  "prompt": "Summarize this file in 3 bullets: '"$(cat report.md)"'",
  "stream": false
}' | jq -r .response

Four concrete ways to route the work

Wiring both up, in practice

# Hybrid strategy
- For repetitive, bulk tasks (rewriting, classification,
  summaries, boilerplate generation), delegate to the local model via the
  Ollama API (http://localhost:11434), don't do them yourself.
- Keep complex reasoning, architecture, and review for yourself.
- Code and data marked "sensitive": local model only.