Time-to-First-Token (TTFT)

Metric measuring how quickly an LLM begins generating its response after receiving input. This metric is measured in milliseconds and directly correlates with user satisfaction scores. Industry benchmarks suggest keeping Time-to-First-Token (TTFT) under specific thresholds for optimal caller experience.

Slow TTFT creates awkward pauses in conversation, users think the system is broken. Optimizing Time-to-First-Token (TTFT) directly impacts caller experience, system performance, and operational costs. Even small improvements can significantly enhance user satisfaction.

Time-to-First-Token (TTFT) is calculated by measuring the time between specific events in the voice agent pipeline. The measurement starts when the triggering event occurs and ends when the measured outcome is achieved. Platforms like Technical documentation each implement Time-to-First-Token (TTFT) with different approaches and optimizations.

Organizations implementing Time-to-First-Token (TTFT) frequently encounter challenges with measurement accuracy, inconsistent performance across different network conditions, and difficulty achieving target benchmarks. High Time-to-First-Token (TTFT) often results from inadequate infrastructure, unoptimized models, or poor network connectivity. Automated testing and monitoring can help identify these issues before they impact production callers.

To optimize Time-to-First-Token (TTFT), start by establishing baseline measurements using monitoring tools. Set realistic targets based on your use case - customer service applications typically require performance within industry benchmarks. Implement caching strategies, optimize model selection, and use edge deployment where possible.