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Separate the Harness From the Model
Claude Code is partly an interface: terminal workflow, file edits, planning, confirmations, and tool calls. A router can keep that interface while sending requests to OpenRouter, Ollama, or another provider. Treat this as a routing experiment, not a replacement for the native stack.
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Verify the Real Model
The CLI may still show Anthropic model names even when another model is answering through a router. Check provider logs, token usage, and request history before trusting the label in the coding tool. This matters when you are comparing cost, latency, or output quality across models.
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Use Cheap Models for Bounded Work
Routed models are best for small features, refactors, experiments, and side projects where a bad turn costs minutes, not a release. Give them narrow tasks with clear acceptance criteria and inspect the diff before moving on. For complex agentic work, native model and harness pairings are still usually faster and more reliable.
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Cost Is Not Just Token Price
A cheaper model can become expensive if it overthinks, misses tool calls, ignores schemas, or takes twice as many turns to finish. Measure total job cost: dollars, elapsed time, failed attempts, and review effort. If the model needs constant correction, the lower token price is a distraction.
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Trim Context Before Swapping Models
Before changing providers, check what your coding agent loads at session start. Large default context can burn tokens before any useful work begins. Reducing unnecessary files, docs, and memories can lower cost without weakening the model you already trust.
Why it matters
Small businesses do not need the cheapest possible AI setup. They need a setup that ships work predictably. Model routing is useful when you classify tasks by risk: cheaper models for bounded chores, stronger native stacks for work where tool reliability, speed, and fewer retries matter more than token price.