Latency & TTFT

User experience in AI applications hinges on perceived speed. These guides help you understand, measure, and optimize the critical latency metrics that matter most.

In This Section

TTFT Explained Understand Time-to-First-Token and why it matters for UX.

Latency Debugging Systematic approaches to identify and fix latency bottlenecks.

GPU Selection Choose the right GPU for your inference performance needs.

Continuous Batching Implement efficient request batching for throughput.

KV Cache Optimization Understand and optimize key-value cache for faster inference.

Speculative Decoding Use draft models to accelerate token generation.

Model Serving Deploy models efficiently with modern serving frameworks.

Quantization for Latency Trade precision for speed with quantized models.

Prompt Latency Optimize prompt design for faster processing.

Batching at Scale Scale batching strategies for high-throughput systems.