Latency Optimization Techniques for Production LLM Applications

In production LLM applications, latency directly impacts user experience and business outcomes. Every second of delay can reduce conversion rates and user satisfaction.

Streaming responses is the most impactful optimization. Instead of waiting for the complete response, stream tokens as they're generated. This reduces perceived latency and allows users to start reading immediately.

Intelligent caching eliminates latency for repeated queries. Implement semantic caching that matches similar queries, not just exact duplicates. This can serve 30-40% of requests from cache with sub-100ms latency.

Parallel processing splits complex tasks across multiple models simultaneously. For example, generate multiple response candidates in parallel and select the best one, or process different sections of a document concurrently.

Model selection based on latency requirements ensures fast models handle time-sensitive requests while complex tasks use more capable but slower models. This balances speed and quality based on user needs.