api

Deepgram API

Build with Deepgram's speech-to-text, text-to-speech, voice agent, and audio intelligence APIs.

"Flux" names two separate products. Flux STT is conversational speech-to-text on /v2/listen (model=flux-general-en). Flux TTS is turn-based speech synthesis on /v2/speak (model=flux-{voice}-{language}). They share a name and a design philosophy — turn-aware, built for voice agents — but they are different endpoints with different models, params, and messages. When a request just says "Flux", check whether it is about transcribing audio or producing it.

Getting Started

All API requests require authentication via API key or JWT:

• API Key: Authorization: Token <API_KEY>
• JWT: Authorization: Bearer <JWT>

Base servers:

• REST & STT/TTS WebSocket: https://api.deepgram.com
• Voice Agent WebSocket and Voice Agent REST: https://agent.deepgram.com

Voice Agent's REST endpoints live on the agent. host too, not on api.: GET /v1/agent/settings/think/models returns 404 on api.deepgram.com and 200 on agent.deepgram.com. Everything else REST stays on api.deepgram.com.

Regional endpoints

To keep processing inside a geography, swap the host. Same API keys, same paths, same SDKs — only the base URL changes. Requests are never routed out of region: if the region is unavailable they fail rather than fall back.

Region	Host
EU	api.eu.deepgram.com
Australia	api.au.deepgram.com
India	api.in.deepgram.com

The data plane is regional; the Projects management API is not. On all three regional hosts:

Endpoint	Regional
POST /v1/listen, wss://…/v1/listen	Yes
wss://…/v2/listen	Yes
POST /v1/speak, wss://…/v1/speak	Yes
POST /v2/speak, wss://…/v2/speak	Yes
POST /v1/read	Yes
wss://…/v1/agent/converse	Yes
GET /v1/models	Yes
POST /v1/auth/grant, GET /v1/auth/token	Yes
/v1/projects/* (keys, members, usage, billing)	No — 404

Two host rules that catch people out:

1. Voice Agent moves onto the api. host regionally. There is no agent.eu.deepgram.com (the name does not resolve). Use wss://api.eu.deepgram.com/v1/agent/converse. The Agent REST endpoints move with it. Globally it stays on agent.deepgram.com.
2. Keep management calls on api.deepgram.com. Point a client's management calls at a regional host and /v1/projects returns 404, so split the base URL by call type if your app both transcribes and manages keys.

Whisper models are not served in any of the three regions — use Nova or Flux STT models there.

For Deepgram Dedicated and self-hosted hosts, see Custom Endpoints; for the full per-region feature matrix and SDK snippets, see Regional Endpoints.

How Deepgram's APIs Fit Together

                   ┌──────────────────────────────┐
                   │       api.deepgram.com        │
                   └──────────────────────────────┘
                                │
  ┌───────────┬───────────┬─────┴─────┬───────────┬───────────┐
  ▼           ▼           ▼           ▼           ▼           ▼
  /v1/listen  /v2/listen  /v1/speak   /v2/speak   /v1/read    /v1/projects/*
  Nova — STT  Flux — STT  Aura — TTS  Flux — TTS  Text AI     Management
  REST + WSS  WSS only    REST + WSS  REST + WSS  REST only   REST only

                   ┌──────────────────────────────┐
                   │      agent.deepgram.com       │
                   └──────────────────────────────┘
                                │
                                ▼
                   /v1/agent/converse
                   WebSocket only
                   audio ──▶ STT ──▶ LLM ──▶ TTS ──▶ audio
                   (Deepgram orchestrates the full pipeline)

Which API Should I Use?

Audio → text (transcription)?
├─ General-purpose transcription (captions, batch, call logs, live streams with custom turn logic)
│  └─ Nova models via /v1/listen
│     ├─ Pre-recorded file    →  REST  POST https://api.deepgram.com/v1/listen?model=nova-3
│     └─ Live stream          →  WSS   wss://api.deepgram.com/v1/listen?model=nova-3
│
└─ Conversational audio / voice-agent-style turn detection
   └─ Flux STT models via /v2/listen
      └─ Live stream          →  WSS   wss://api.deepgram.com/v2/listen?model=flux-general-en

Text → audio (speech synthesis)?
├─ General-purpose TTS (broadest voice catalog, compressed/containerized audio)
│  └─ Aura models via /v1/speak
│     ├─ One-shot             →  REST  POST https://api.deepgram.com/v1/speak?model=aura-2-thalia-en
│     └─ Low-latency stream   →  WSS   wss://api.deepgram.com/v1/speak?model=aura-2-thalia-en
│
└─ Voice-agent TTS (turn-based lifecycle, barge-in, cross-turn consistency)
   └─ Flux TTS models via /v2/speak  — model is REQUIRED, and must be flux-*
      ├─ Pre-render a block   →  REST  POST https://api.deepgram.com/v2/speak?model=flux-alexis-en
      └─ Live conversation    →  WSS   wss://api.deepgram.com/v2/speak?model=flux-alexis-en

Full conversational voice agent (audio in, audio out)?
└─ WSS wss://agent.deepgram.com/v1/agent/converse
   Deepgram handles STT + your configured LLM + TTS internally

Analyze text for insights?
└─ REST POST /v1/read
   (summaries, sentiment, topics, intents)

Speech-to-Text: Nova (/v1/listen) vs Flux STT (/v2/listen)

Both model families are actively maintained and industry-leading. They solve different problems — pick the one that matches your use case.

	Nova (/v1/listen)	Flux STT (/v2/listen)
Endpoint	/v1/listen	/v2/listen
Available models	nova-3 (also nova-3-medical, nova-3-pharma), nova-2, nova, enhanced, base	flux-general-en, flux-general-multi
Best for	General transcription — captions, subtitles, call logs, batch	Conversational audio — voice agents, interactive assistants, turn-taking UIs
Output	Continuous transcript stream	Structured turn events + transcripts (built-in turn state machine)
Turn detection	Manual (utterance_end_ms, VAD events)	Built-in (EOT, eager-EOT, turn_index)
Transports	REST + WebSocket	WebSocket only
Intelligence overlays	Yes — summarize, sentiment, topics, intents, diarize_model, redact, etc.	No — smaller focused param set; no smart_format / diarize_model / punctuate
Mid-session reconfig	No (reconnect to change)	Yes (Configure message updates EOT thresholds + keyterms live)

Pick Nova (/v1/listen, model=nova-3) when:

• Generating captions, subtitles, or transcripts for recorded media
• Running batch transcription over files (REST)
• You need analytics overlays (summarize, sentiment, topics, intents, diarize_model, redact)
• You want WebSocket streaming with your own turn-detection logic

Pick Flux STT (/v2/listen, model=flux-general-en) when:

• Building an interactive voice agent or assistant
• You want end-of-turn detection handled for you
• You need low-latency turn signals and barge-in support
• You want to update EOT thresholds or keyterms mid-session without reconnecting

Migrating from Nova 3 to Flux STT? See the official Nova 3 → Flux migration guide.

Text-to-Speech: Aura (/v1/speak) vs Flux TTS (/v2/speak)

Both TTS families are actively maintained. /v2/speak is a new endpoint, not a replacement — /v1/speak is unchanged, and there is no aliasing, redirect, or deprecation. The families do not overlap: Aura voices are served only on /v1/speak, Flux TTS voices only on /v2/speak.

	Aura (/v1/speak)	Flux TTS (/v2/speak)
Endpoint	/v1/speak	/v2/speak
Models	aura-2-* (en, es, de, nl, fr, it, ja), aura-*	flux-{voice}-{language}, e.g. flux-alexis-en — English at launch
model param	Optional (defaults to aura-asteria-en)	Required; an aura-* string is rejected
Best for	Broadest voice catalog, multilingual, compressed audio, one-shot synthesis	Voice agents — streaming LLM output, barge-in, multi-turn conversations
Mental model	Text buffer → audio stream	Streaming-first, turn-based conversation
Turn lifecycle	None	SpeechStarted → audio → Flushed → SpeechMetadata per turn (server-assigned speech_id)
Cross-turn context	None (reconnect to reset)	Prosody persists across turns automatically — no API surface
Transports	REST + WebSocket	REST (batch) + WebSocket (streaming)
Streaming encodings	linear16, mulaw, alaw	linear16, mulaw, alaw — raw audio only
Batch encodings	mp3, opus, flac, aac, linear16, mulaw, alaw + container / bit_rate	Same — but batch-only; the socket rejects them
Interruption	Clear discards the buffer, no feedback	Interrupt → SpeechInterrupted with text_spoken / text_remaining
Mid-stream reconfig	No (fixed at connection)	Yes — Configure updates speed only
speed	0.7–1.5 — Aura-2, English and Spanish only	0.5–1.5 in 0.05 steps
expressivity	Not supported	-2…2, default 0 (beta; fixed for the connection)
Voice Agent provider.version	v1 (the default when a provider is specified)	v2 (required)

Pick Aura (/v1/speak) when:

• You need a language other than English, or a specific Aura voice
• You want compressed or containerized output (mp3, opus, flac, aac) from a stream
• You're doing one-shot synthesis and don't need a turn lifecycle
• You're already on Aura and nothing in Flux TTS is pulling you over — v1 is unchanged

Pick Flux TTS (/v2/speak) when:

• Building a voice agent, phone assistant, or customer-service bot
• You're streaming LLM tokens to a speaker in real time and want the lowest time-to-first-audio
• The user may barge in mid-response and you need to know what they actually heard
• You want tone to carry across turns without managing state yourself
• You're pre-rendering fixed audio (IVR prompts, notifications) with a Flux TTS voice — use the batch REST transport

Migrating from Aura? See the official Migrating from Aura to Flux TTS guide and Batch vs Streaming.

API Domains

Domain	REST	WebSocket	Reference
Listen v1 — STT, Nova models	POST /v1/listen	wss://api.deepgram.com/v1/listen	listen.md
Listen v2 — STT, Flux STT (conversational)	—	wss://api.deepgram.com/v2/listen	listen.md
Speak v1 — TTS, Aura models	POST /v1/speak	wss://api.deepgram.com/v1/speak	speak.md
Speak v2 — TTS, Flux TTS (turn-based)	POST /v2/speak	wss://api.deepgram.com/v2/speak	speak.md
Voice Agent	GET agent.deepgram.com/v1/agent/settings/think/models	wss://agent.deepgram.com/v1/agent/converse	agent.md
Read (Intelligence)	POST /v1/read	—	read.md
Models	GET /v1/models	—	models.md
Projects	/v1/projects/*	—	projects.md
Auth	POST /v1/auth/grant	—	auth.md
Self-Hosted	/v1/projects/*/self-hosted/*	—	self-hosted.md

Common Mistakes to Avoid

All APIs

1. Feature flags are query params — except for Voice Agent and the v2 mid-session updates. For /v1/listen, /v2/listen, /v1/speak, and /v2/speak, initial options go on the URL. The request body carries only audio data (REST) or audio frames (WebSocket). Exceptions: /v1/agent/converse has no URL query params at all (all config goes in the Settings message); /v2/listen supports a Configure message after connection to update EOT thresholds and keyterms mid-session; and /v2/speak supports a Configure message that updates speed only. Also note that /v2/listen has a much smaller param set than /v1/listen — flags like smart_format, diarize_model, and punctuate are not available.

2. Rate limits are concurrent connections, not total requests. A 429 means too many simultaneous open connections, not too high a request volume. Diarization and other compute-heavy features reduce your concurrency allowance further.

STT WebSocket (/v1/listen)

3. Send KeepAlive as a text frame, not binary. The connection closes after 10 seconds of no audio. Send {"type":"KeepAlive"} as a text (JSON) frame every 3–5 seconds during silence. Sending it as a binary frame causes transcription delays — the audio pipeline chokes — not a silent no-op.

4. Never send empty byte payloads. Sending a zero-length binary frame to /v1/listen is treated as a close — it terminates the connection. Always check that your audio packet has length before sending.

5. encoding must match the actual audio format. If encoding=linear16 but you're sending opus, you'll get a DATA-0000 error or garbled output. Omit encoding entirely when sending containerized formats (mp3, wav, ogg) — Deepgram detects them automatically.

6. Timestamps reset on reconnect. Each new WebSocket connection restarts timestamps at 00:00:00. For real-time apps, maintain a timestamp offset across reconnections or you'll silently corrupt your transcript timeline.

TTS WebSocket (/v1/speak)

7. Don't send empty text. A Speak message with an empty text field returns a 400 error. Always validate input before sending.

8. Character rate limiting (DATA-0001) means slow down, not retry. If you hit this, reduce how fast you're submitting text chunks — don't immediately retry or you'll compound the problem.

Flux TTS (/v2/speak)

9. model is required, and must be a flux-* voice. Unlike /v1/speak there is no default — a connection or request without model is rejected. Aura strings are rejected on /v2/speak, and Flux voices are not served by /v1/speak; the two families never mix. Model strings are flux-{voice}-{language}, e.g. flux-alexis-en. There is no version segment — generations roll forward behind a stable name, as with Flux STT.

10. Flush ends the turn — it is not a v1-style buffer flush. There is no Finalize; it's folded into Flush. Audio starts streaming on its own before you flush, so don't wait to send text. Use the turn's SpeechMetadata (not Flushed) as your end-of-turn signal — it arrives once all of the turn's audio has been sent, and carries the billing and timing counts, so you can drop client-side character or duration tracking. The server assigns the turn's speech_id; never send one yourself.

11. Streaming is raw audio only, and rejects anything it doesn't recognize. The WebSocket emits non-containerized audio, so encoding is limited to linear16 (default), mulaw, or alaw. The compressed and containerized encodings (mp3, opus, flac, aac) and the container, bit_rate, callback, callback_method, and priority params are batch-only — sending them to the socket fails the connection, as does any unknown or misspelled param. Use the batch REST transport when you need compressed output.

12. Insert whitespace between separate generations — the server won't. Text normalization runs before synthesis, but successive Speak messages are concatenated verbatim. Sending "Hello world." then "How are you?" is processed as "Hello world.How are you?", which causes sentence-boundary artifacts. Add a single space (or the right separator for non-whitespace languages) when you stitch a reply, a tool-call result, and another reply together. Send plain text: SSML and other markup is stripped, with an INPUT_MARKUP_STRIPPED warning.

Voice Agent (/v1/agent/converse)

13. Send the Settings message before any audio. The agent ignores everything until it receives and acknowledges the Settings configuration. Message ordering is strictly required.

14. agent.speak.provider.version selects the TTS family — and omitting agent.speak now gives you Flux TTS. Set version to v2 for Flux TTS or v1 for Aura; when you specify a provider but omit version, it defaults to v1. But if you omit agent.speak entirely, the agent defaults to Flux TTS with the flux-kit-en voice. Switch families by changing version and model together — a flux-* model under v1, or an aura-* model under v2, is invalid:

    { "agent": { "speak": { "provider": { "type": "deepgram", "version": "v2", "model": "flux-alexis-en" } } } }
    

15. The Voice Agent REST endpoints live on agent.deepgram.com, not api.deepgram.com. GET /v1/agent/settings/think/models — the list of LLMs you can name in agent.think.provider — returns 404 on api.deepgram.com and 200 on agent.deepgram.com. Same key, same path; only the host differs, so a client with one hardcoded base URL silently gets a 404 that looks like a missing feature. The three regional api.* hosts serve it as well.

Flux STT model (/v2/listen)

16. Use /v2/listen and a flux-general-* model. Two are served: flux-general-en (English) and flux-general-multi (multilingual, and the only model that accepts language_hint / language_hints). /v1/listen does not support Flux STT, and model=flux alone is not a valid value. Do not include language or encoding params for containerized audio.

17. Use Configure to update EOT thresholds and keyterms mid-session. Unlike /v1/listen, Flux STT supports live reconfiguration after connection — no need to reconnect to change turn detection sensitivity or boost new keyterms:

    { "type": "Configure", "thresholds": { "eot_threshold": "0.8", "eot_timeout_ms": "3000" }, "keyterms": ["Deepgram"] }
    

    The server responds with ConfigureSuccess (echoing back applied values) or ConfigureFailure. Omitted threshold fields keep their current values.

18. ForceEndTurn outside a turn is a Warning, not an error — and the socket stays open. Sending {"type":"ForceEndTurn"} while no turn is in progress returns {"type":"Warning","code":"FORCE_END_TURN_NO_ACTIVE_TURN","description":"Received ForceEndTurn while no turn was active; the request was ignored."} and the connection continues. Do not treat it as fatal or reconnect. Neither the Warning message nor this code is in the AsyncAPI spec yet, so references/listen.md cannot show them. When ForceEndTurn does land mid-turn, the resulting TurnInfo carries event: "EndOfTurn" with trigger: "manual" — trigger is model | manual | timeout, it appears on EndOfTurn and nowhere else, and it is an open enum, so tolerate values you do not recognize.

Nova diarization (/v1/listen)

19. Use diarize_model, and never send it alongside diarize. diarize is deprecated. diarize_model both enables diarization and picks the version, so you do not also need diarize=true — and sending both fails the request: 400 "diarize_model cannot be used together with diarize or diarize_version.". Values are latest, v1, and v2 for batch (latest is currently v2), and latest or v1 for streaming. When diarization is on, metadata.diarize_info reports which model actually ran ({"model_uuid": …, "arch": "v2"}), which is the only way to tell what latest resolved to.

Text and Audio Intelligence (/v1/read, /v1/listen)

20. language is required on /v1/read, and it is validated before anything else. There is no default, despite what references/read.md says: omitting it returns 400 INVALID_QUERY_PARAMETER — "Failed to deserialize query parameters: missing field language" — which masks every other problem in the request. English only — language=multi is rejected, and en-US is accepted but echoed back as en. Two more /v1/read shapes worth knowing: the JSON body takes exactly one of text or url (both or neither gives PAYLOAD_ERROR, and url must point at a plain-text document — audio gives REMOTE_CONTENT_ERROR), and it is POST-only (GET and a WebSocket upgrade both return 405). summarize on /v1/read accepts v2 as well as true, contrary to the reference. Result paths differ per endpoint: /v1/read returns results.summary.text, /v1/listen returns results.summary.short, so code that handles both has to branch. (sentiment maps to results.sentiments on both.)

21. On the Nova streaming socket, only detect_entities works — and the other four fail in three different ways. detect_entities=true is supported and puts entities at the top level of each Results message, beside channel, not inside channel.alternatives[0]. The other four are prerecorded-only: summarize fails the handshake with 400 "Summarization is not available for streaming."; topics and intents fail it with 403 UNAUTHORIZED_FEATURES_REQUESTED, which reads like a key-permissions problem even when the same key's prerecorded topics/intents calls return 200; and sentiment is the trap — the handshake succeeds, no error is ever sent, and sentiment simply never appears in the results.

Authentication

22. JWT TTL applies only to the initial handshake. Tokens default to 30 seconds. Once the WebSocket connection is established, the token expiring does not close it — tokens are only needed for the upgrade request.

SDK-Specific Skills

This api skill covers the product contracts (endpoints, query params, message shapes) that are identical across SDKs. For language-idiomatic code — imports, async patterns, builder APIs, common errors — install the SDK-specific skills. Each Deepgram SDK publishes 7 product skills named deepgram-{lang}-{product} (e.g. deepgram-python-speech-to-text, deepgram-js-voice-agent). The deepgram-{lang}- prefix avoids collisions when you install skills from multiple SDKs.

# Install all skills from a specific SDK
npx skills add deepgram/deepgram-python-sdk     # Python
npx skills add deepgram/deepgram-js-sdk         # JavaScript / TypeScript
npx skills add deepgram/deepgram-java-sdk       # Java
npx skills add deepgram/deepgram-go-sdk         # Go
npx skills add deepgram/deepgram-rust-sdk       # Rust
npx skills add deepgram/deepgram-dotnet-sdk     # C# / .NET

# Or install a specific product skill from one SDK (note the deepgram-{lang}- prefix)
npx skills add deepgram/deepgram-python-sdk --skill deepgram-python-speech-to-text
npx skills add deepgram/deepgram-js-sdk     --skill deepgram-js-voice-agent

Swift and Kotlin SDK skills are not listed because those repositories are not public and npx skills add cannot reach them. For browser work, open the browser-agent skill: it covers the four Browser Agent SDK packages published on npm (@deepgram/agents, @deepgram/react, @deepgram/ui, @deepgram/agents-widget).

Related Deepgram skills

Skill	Purpose
recipes	Minimal runnable snippets per feature per language
examples	Full integration examples with third-party platforms (Twilio, LiveKit, etc.)
starters	Runnable starter apps (framework × feature matrix)
docs	Navigate Deepgram documentation
audio-intelligence	The summarize, sentiment, topics, intents, and detect_entities parameters on /v1/listen
text-intelligence	POST /v1/read for text you already have
browser-agent	The Browser Agent SDK packages for running an agent in a browser
cli	deepctl for shell and CI work
self-hosted	Running Deepgram on your own GPUs
setup-mcp	Install the Deepgram MCP server

Documentation

• API Reference
• Speech-to-Text Getting Started
• Text-to-Speech Docs (Aura)
• Flux TTS Overview
• Voice Agent Docs
• Voice Agent TTS Models
• Audio Intelligence
• Self-Hosted Deployments
• Regional Endpoints
• Custom Endpoints