LLM Latency Optimization: From 5s to 500ms (2026)

Interactive AI applications suffer from significant user abandonment if response times exceed 2 seconds, and teams often misdiagnose the root of latency issues by treating them as a single problem. Instead, latency issues are divided into two categories: Time to First Token (TTFT), which is influenced by network delays and prefill processes, and Inter-Token Latency (ITL), which is affected by memory transfers during token generation. Effective optimization requires addressing these separately, starting with measuring accurate baselines and using techniques like prompt restructuring, streaming, model selection, and quantization. The proper sequence of optimizations, such as prefix caching, chunked prefill, speculative decoding, and parallelism, can significantly improve response times, making a dramatic difference in user experience. The document emphasizes that hardware upgrades should be a last resort after software optimizations are exhausted, and encourages ongoing monitoring to maintain performance gains.