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LLM Cost Optimizer

LLM Cost Optimizer

via Dev.to PythonThesius Code

LLM Cost Optimizer LLM API costs compound fast — a prototype that costs $5/day can become $500/day in production. This toolkit gives you the instrumentation and strategies to cut LLM spending by 40-70% without sacrificing output quality. Token usage tracking, intelligent model routing, semantic caching, batch processing, and budget alerts — all in one package. Key Features Token Usage Tracking — Instrument every LLM call with precise input/output token counts, costs, and latency per model, user, and feature Smart Model Routing — Automatically route simple queries to cheap models (GPT-4o-mini) and complex queries to powerful models (GPT-4o) based on task complexity scoring Semantic Caching — Cache responses by semantic similarity, not just exact match. "What's the weather in NYC?" and "NYC weather today?" hit the same cache entry Batch Processing — Queue non-urgent requests and process them in bulk at 50% lower cost using batch APIs Budget Alerting — Set daily/weekly/monthly spend limit

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