Reducing LLM Costs with Prompt Caching, Batches API, and Model Routing
Explore methods to reduce LLM costs for the Claude API: prompt caching, Batches API, and model routing.
LLM expenses can be treated as an engineering variable that can be measured and reduced. This article outlines three methods to lower costs for the Python-based Claude API without switching providers. The strategies include prompt caching, using the Batches API, and routing requests to cheaper models, ensuring efficiency without compromising model performance.