Latency

Latency in lip sync workflows has multiple components: network latency for uploading video and audio to the processing server, queue latency while waiting for available GPU resources, processing latency for the actual lip sync model inference, and download latency for retrieving the result. Each component can be optimized differently: network latency through CDN and regional endpoints, queue latency through capacity scaling and priority queues, processing latency through model optimization and hardware selection, and download latency through efficient encoding and delivery.

For real-time applications, end-to-end latency must be minimized across all components simultaneously.

Latency relates to several other concepts in the AI lip sync pipeline: Inference Time , and Throughput .