Hydra | Smallest AI Docs

Latest Release

Hydra is Smallest AI’s speech-to-speech model. A single WebSocket carries microphone audio from your client to the model and streams synthesised response audio back. There is no STT → LLM → TTS pipeline in the middle, and no transcript on the wire.

Audio in, audio out

One model. One socket. No glue code.

Full-duplex

Barge-in handled by the model. In-flight responses cancel automatically.

Tool calling

Standard JSON-schema function calls, executed on your side.

Bot speaks first

generate_initial_response: true for greetings.

Model Overview


Developed by	Smallest AI
Model type	Full-duplex speech-to-speech
API surface	WebSocket (`wss://api.smallest.ai/waves/v1/s2s`)
Model ID (query param)	`model=hydra`
Wire version	v1
License	Proprietary, hosted API

Key capabilities

6 voices

wren, sloane, marlowe, reed, knox, tate.

Tool calling

JSON-schema tools, streamed args, client-side execution.

Mid-session updates

Live-patch tools without reconnecting via session.update.

Audio formats

Direction	Format	Sample rate	Channels	Encoding
Input (client → server)	PCM16, signed little-endian	16 kHz	mono	base64 inside `input_audio_buffer.append`
Output (server → client)	PCM16, signed little-endian	48 kHz	mono	base64 inside `response.output_audio.delta`

Languages

Hydra currently supports English only. Additional languages are on the roadmap.

Language	ISO code	Status
English	`en`	✅ Production

Voices

Six voice IDs are accepted on session.configure.session.voice and frozen at handshake.

Voice ID	Notes
`wren`	Default (server-side default if `voice` is omitted).
`sloane`	—
`marlowe`	—
`reed`	—
`knox`	—
`tate`	—

Performance & benchmarks

Hydra is benchmarked against eight other production-grade voice / realtime models. Full methodology and metric definitions live on the dedicated Performance and Metrics Overview pages.

AIEWF S2S — 10 runs × 30 turns, `aiwf_medium_context`

Model	Pass rate	Non-tool V2V median	Non-tool V2V max	Tool V2V mean
ultravox-v0.7	97.7 %	864 ms	1888 ms	2406 ms
gpt-realtime-2 (low)	96.0 %	1728 ms	4032 ms	2005 ms
Hydra	95.9 %	864 ms	1984 ms	1624 ms
grok-voice-think-fast-1.0	95.3 %	2336 ms	4800 ms	2753 ms
gpt-realtime-1.5	93.3 %	1152 ms	2304 ms	2251 ms
gemini-3.1-flash-live-preview	91.7 %	1632 ms	5664 ms	3172 ms
gpt-realtime	86.7 %	1536 ms	4672 ms	2199 ms
gemini-live	86.0 %	2624 ms	30000 ms	4082 ms
nova-2-sonic	—	1280 ms	3232 ms	1689 ms

Reading the table:

Tool V2V mean latency: Hydra is the fastest of 9 (1624 ms — beats nova-2-sonic at 1689 ms, gpt-realtime-2 low at 2005 ms, ultravox at 2406 ms).
Non-tool V2V median latency: tied-fastest (864 ms with ultravox).
Pass rate: #3 of 8 (within ~2 pp of the leader; nova-2-sonic did not report pass rate).

Latency numbers are computed from transcript.jsonl across all 10 runs (n = 224 non-tool turns, n = 64 tool turns). Pass rate is the fraction of turns that completed the expected interaction.

Hydra is evaluated on voice-agent axes — voice-to-voice latency, turn-taking accuracy, barge-in handling, and tool-call reliability under realistic conditions. Generic LLM benchmarks (MMLU, IFEval) target a different objective and aren’t the right yardstick for a realtime voice model.

Operational metrics

Metric	Value
Idle timeout	~30 s with no traffic from either side. Keep streaming audio (silence frames are fine) to hold the connection.

Capacity & rate limits

One voice session per WebSocket connection.
Concurrency follows your plan’s WebSocket pool. Excess connections receive error with code: "server_full" followed by close code 1013 — back off with jitter and retry.

For higher limits, contact your account manager.

Pricing

Contact your Smallest AI account manager for current pricing. Hydra is billed by session minute; usage per turn is reported on response.done when available.

Use cases

Direct use

Realtime voice assistants — companion apps, concierge bots, in-app tutors.
Phone agents — restaurant reservations, banking concierges, customer support.
Voice copilots embedded in web and mobile apps.
Accessibility — voice-first interfaces for visually-impaired users.
Voice-controlled IoT and games — kiosks, in-car assistants, gaming companions.

Downstream use

Conversational analytics over recorded phone-call audio (transcribe the captured audio with Pulse STT afterwards).
Multi-agent voice systems where Hydra is one specialised speaker.
Hybrid voice + text agents where a text fallback is needed for compliance.

Specs & API surface


Endpoint	`wss://api.smallest.ai/waves/v1/s2s?model=hydra&api_key=<KEY>`
Frame format	JSON (UTF-8 text frames). No binary frames.
Authentication	`api_key` query parameter (browser clients should mint a short-lived token server-side).
Close codes	`1000` normal, `1013` server full — auth failures are HTTP 401 during the WS handshake (no close code)

See the documentation hub for the full event catalog, session config, tool calling, interruption handling, and errors.

Safety & responsible use

Hydra is intended for voice-agent and conversational workloads. Customers building user-facing applications should layer their own content moderation, prompt-injection defenses, and PII handling appropriate to their domain. Hydra does not currently apply content moderation server-side — outputs reflect the model’s training and the prompts you provide.

For voice-agent applications handling regulated content (financial, healthcare), the standard pattern applies: keep PII out of prompts where practical, apply post-processing redaction on outputs, and — if you need a transcript for compliance — transcribe the PCM you sent/received via the Pulse STT API and store that transcript with your moderation log.

Quickstart

Clone the reference client, paste your API key, and talk to Hydra in your browser.

Overview

Full event reference, tool calling, interruption, errors.