Most teams run everything on one model. That’s the mistake.
I run the same agent across 6 LLMs.
Here’s what I actually use in production.
OpenClaw lets you plug multiple models into one agent and switch based on the task.
My stack:
Claude (Sonnet / Opus) → deep reasoning, debugging, system design
Codex → primary execution engine, clean code, fast refactors
Gemini 2.5 Flash → cheap + fast for scraping, formatting, summaries
Local (Mistral / DeepSeek / Qwen) → free throughput, background work
Different models excel at different things. Once you see that, routing becomes obvious.
Use cheaper models for predictable tasks.
Use stronger models when judgment matters.
Same agent. Different brains doing different jobs.