How does CodeRabbit manage context assembly to keep token costs low for complex reasoning models?

We do not let users choose a model. Instead, we use an ensemble of models behind the scenes. We use smaller models for context assembly and semantic analysis, and reserve the most expensive, reasoning-heavy models for the final review. This keeps our token consumption highly efficient.