API Cost Optimization for LLM-Powered Applications The Challenge Running LLM-powered applications can get expensive fast. Here's how to minimize costs without sacrificing quality. Strategy 1: Response Caching Cache identical or similar prompts. A simple SQLite-based cache can save 30-50% on API calls. def cached_query ( prompt , model , ttl_hours = 24 ): cached = cache . get ( hash ( prompt + model )) if cached and cached . age < ttl_hours : return cached . response , True # cache hit response = api_call ( prompt , model ) cache . save ( hash ( prompt + model ), response ) return response , False # cache miss Enter fullscreen mode Exit fullscreen mode Strategy 2: Smart Model Selection Not every query needs GPT-4.…