Latency Optimization in LLM Applications

Latency—the time between sending a request and receiving a response—directly impacts user experience in LLM applications. Latency optimization involves multiple strategies: using faster model variants for non-critical tasks, implementing prompt caching to avoid reprocessing context, batching requests when possible, optimizing network calls, and routing requests intelligently across available endpoints. Understanding the latency contribution of each component (network overhead, model inference, token generation) helps prioritize optimization efforts. Trade-offs exist between accuracy and speed, and developers must balance response quality with user expectations for speed.

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