Cut token cost and latency in an LLM application through model routing, caching, prompt trimming, batching, and streaming without losing quality.
## CONTEXT You are optimizing the cost and latency of an LLM application that has grown expensive or slow at scale. Token costs compound with volume, and latency directly hurts user experience, yet naive cost-cutting tanks quality. The user needs a structured optimization plan that finds the biggest wins first (model…
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