Latency

The time between “user finishes speaking/typing” and “avatar starts responding on screen” is the sum of several stages, and most of them are yours to tune.

Where the time goes

1. Your input pipeline: speech-to-text, if you’re doing voice input (entirely your stack, not covered by this API).
2. Your brain: however long your LLM (or logic) takes to decide on a reply. See Bring your own brain.
3. Speech synthesis: either 2wai’s TTS (/speak) or your own (/audio).
4. Lipsync and encoding: 2wai renders the frames and streams them out.
5. Network and buffering: the WebSocket hop and however much your MediaSource buffers before playback.

Stages 1-3 usually dominate; 4 is typically the fastest part once a session is warm.

Tips

• Stream your LLM output and speak in sentence chunks. Waiting for a full paragraph before calling /speak adds the model’s entire generation time to your latency budget. Flushing at sentence boundaries lets the avatar start talking within a second or two of the first tokens arriving. See the streaming example in Bring your own brain.
• Keep sessions warm. Creating a session has setup cost. For a multi-turn conversation, create one session and drive it with repeated /speak//audio calls rather than creating a new session per turn.
• Use /interrupt on barge-in. If your product supports the user talking over the avatar, call POST /v1/sessions/{id}/interrupt the moment you detect new input, rather than letting a stale reply finish and queuing the new one behind it.
• If you bring your own TTS, prefer a streaming-capable engine. Chunking audio to /audio as it’s generated (more=true between chunks) avoids waiting for the entire clip to synthesize before any of it can render. See Bring your own TTS.
• Don’t over-buffer client-side. A MediaSource player that queues many segments before starting playback trades a smoother start for added latency. The player in Streaming into your app appends segments as they arrive rather than batching them.

Note

Exact latency numbers depend heavily on your own LLM/TTS choices and where your server is deployed relative to api.2wai.ai. The levers above are the ones within your control regardless of those choices.

Next

• Sessions for keeping a session alive across a whole conversation instead of recreating it.
• Limits & concurrency: running near your concurrency cap can itself introduce queuing delay.