cost-aware-model-routing

To optimize LLM costs, route tasks based on complexity: assign Opus for complex reasoning and Sonnet for pattern matching or review. This tiered assignment ensures you only pay for advanced reasoning when necessary, significantly reducing operational expenses.

Use Opus over Sonnet for agents requiring complex reasoning, such as a planner agent. Conversely, assign Sonnet to agents following checklists or performing code reviews to maintain quality while actively controlling operational costs.

You can dynamically re-route agents between model tiers using established switching rules. These guidelines help adjust assignments on the fly, ensuring cost efficiency does not compromise the quality assurance of the output.

Model routing for cost optimization works without specific framework dependencies. It provides a framework of guidelines for assigning model tiers based on task complexity, making it adaptable to various AI development environments.

The best way to reduce LLM operational expenses is implementing a cost reduction strategy that defines task types suitable for Opus versus Sonnet. Assigning models based on reasoning needs ensures substantial cost savings over time.

Using a single expensive LLM model for all tasks increases operational costs because simple tasks waste advanced reasoning capabilities. Routing pattern matching tasks to cheaper models like Sonnet optimizes expenses while maintaining quality.