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Speech-to-Speech Model

also called S2S model, Real-time voice model

A model that hears audio and answers in audio, with no text step in the middle.

Definition

A model built for live voice conversation: it takes audio in and produces audio out directly, instead of chaining speech-to-text, a text model, and text-to-speech. Skipping the text middle steps is what keeps latency low enough for a phone call, where even a second of delay makes people talk over each other. Modern voice models also reason and call tools inside the call. xAI shipped Grok Voice 3.0, a speech-to-speech model for its Voice Agent API, on October 14, 2026.

The hard parts of a voice model are conversational, not just acoustic: detecting when the caller has finished speaking, handling interruptions and background noise, and keeping the turn-taking natural. Benchmarks built for this measure pauses and interruptions (Full Duplex Bench) and simulated support calls with accents and noise (tau-Voice), rather than transcription accuracy alone.

Voice models are usually API-only services, priced per minute rather than per token, which changes how you budget them: cost scales with call duration, not with output length. The alias question matters here too: xAI moved callers on the grok-voice-latest alias to 3.0 automatically, so pinning a versioned id is what keeps a voice deployment stable.

How people use it
Choosing between a voice model and a text pipeline for a support line.
"If callers need to interrupt and be interrupted, use a speech-to-speech model. A text pipeline will always feel a beat behind on a live call."
Worked example

The support line that stops talking over callers

Choosing between a speech-to-speech model and a transcription-plus-text chain for a support line.

Pick speech-to-speech when callers need to interrupt and be interrupted: the text chain adds a beat at every handoff. Judge the choice on turn-taking (Full Duplex Bench-style pauses and interruptions) and simulated support calls (tau-Voice-style accents and noise), not on transcription accuracy, and budget by call duration rather than tokens.

Avoid

Judging a voice model by transcription accuracy alone. The failure modes that lose callers are pauses, talk-over, and wrong turn-taking, not misheard words.

Sources
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