Guide
What is LLM Latency?
Understanding and optimizing AI response times for production applications.
LLM latency measures how long it takes for an AI model to respond. Unlike traditional APIs, LLM latency has multiple components that affect user experience differently.
Key Latency Metrics
Time to First Token (TTFT)
How long until the first token appears. Critical for perceived responsiveness. Target: under 500ms for good UX.
Inter-Token Latency (ITL)
Time between each token. Affects streaming smoothness. Target: under 50ms for natural reading speed.
Tokens Per Second (TPS)
Generation throughput. Higher is better for long responses.
End-to-End Latency
Total time from request to complete response. Includes network, processing, and generation.
Industry Benchmarks
Latency Targets by Industry
- E-commerce: Under 700ms (users abandon at 3s)
- Healthcare: Under 1000ms
- Finance: Under 800ms
- Voice AI: Under 300ms for natural conversation
Optimization Strategies
- Streaming: Show tokens as they generate
- Caching: Cache common responses
- Model selection: Smaller models for simple tasks
- Prompt optimization: Shorter prompts = faster processing
FAQ
What's acceptable LLM latency?
Under 1 second for most applications. Users lose patience after 1 second and abandon at 3 seconds. Voice applications need under 300ms.
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