> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://developers.deepgram.com/docs/flux/nova-3-migration/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://developers.deepgram.com/_mcp/server.

# Migrating from Nova-3 to Flux

## Key Benefits of Flux

* **Model-integrated turn detection** (`StartOfTurn`, `EagerEndOfTurn`, `TurnResumed`, `EndOfTurn`)
* **Ultra-low latency** \~260ms end-of-turn detection (p50 at defaults)
* **EagerEndOfTurn events** let you **start LLM responses early**
* **Turn-based transcripts** for clean agent logic
* **Same Nova 3 transcription quality**
* **Simplified development** one API replaces complex STT+VAD+endpointing pipelines, and conversation-native events.
* **High configurability** - Configurable end-of-turn detection sensitivity, eager response thresholds, and turn-taking dynamics for optimized conversational flow

## Audio Requirements

* **Encoding:** See [Audio Format Requirements](#audio-format-requirements) table below
* **Sample rates:** See [Audio Format Requirements](#audio-format-requirements) table below
* **Channels:** Mono only
* **Chunk size:** **80ms strongly recommended** for optimal model performance and latency.

### Audio Format Requirements

| Audio Type    | Encoding                                                    | Container | `encoding` param | `sample_rate` param | Supported Sample Rates                     |
| ------------- | ----------------------------------------------------------- | --------- | ---------------- | ------------------- | ------------------------------------------ |
| Raw           | `linear16`, `linear32`, `mulaw`, `alaw`, `opus`, `ogg-opus` | None      | **Required**     | **Required**        | `8000`, `16000`, `24000`, `44100`, `48000` |
| Containerized | `linear16`                                                  | WAV       | **Omit**         | **Omit**            | Auto-detected from container               |
| Containerized | `opus`                                                      | Ogg       | **Omit**         | **Omit**            | Auto-detected from container               |
| Containerized | `opus`                                                      | WebM      | **Omit**         | **Omit**            | Auto-detected from container               |

## Migrating from Nova 3 to Flux

This guide will help you migrate from Nova 3 to Flux by highlighting key differences, setup changes, and implementation patterns.

### Differences

| Nova 3                                             | Flux                                        |
| -------------------------------------------------- | ------------------------------------------- |
| Streams transcripts continuously                   | Emits structured turn events                |
| Requires custom logic for barge-in and turn-taking | Has built-in turn state machine             |
| Returns transcripts only                           | Returns conversation events and transcripts |
| Designed for general real-time transcription       | Designed for conversational voice agents    |
| Focuses on accuracy and speed                      | Focuses on accuracy and turn awareness      |

#### Endpoint Usage

**Nova 3:**

Uses the listen v1 endpoint with the `nova-3` model option.

```
wss://api.deepgram.com/v1/listen?model=nova-3
```

**Flux:**

Uses the listen v2 endpoint with the `flux-general-en` model option.

```
wss://api.deepgram.com/v2/listen?model=flux-general-en
```

### Response Message Structure

#### Nova 3

```json
{
  "type": "Results",
  "channel": "transcript",
  "alternatives": [...]
}
```

#### Flux

```json
{
  "type": "TurnInfo",
  "request_id": "2ba892a1-6c0d-4d92-9b89-0000000000",
  "event": "Update",
  "turn_index": 0,
  "audio_window_start": 0,
  "audio_window_end": 0.47999996,
  "transcript": "",
  "words": [...],
  "end_of_turn_confidence": 0.0009,
  "sequence_id": 2
}
```

In addition to the transcript, flux responses include the:

* `event` field for turn-state changes
* `turn_index` to track turn lifecycle
* `audio_window_start` and `audio_window_end` to track the audio window.
* `end_of_turn_confidence` to track the confidence of the end of turn.
* `sequence_id` to track the sequence id of the messages.
* `words` array with word-level `start` and `end` timestamps (type `double`) on each word object, along with `word` and `confidence`.

### Implementation Pattern Changes

#### Nova 3 Approach

> Requires custom logic for barge-in and turn-taking.

* Send audio
* Receive streaming partial transcripts
* Decide when to interrupt your agent manually

#### Flux Approach

> Listens for structured events and removes the need for custom VAD or barge-in logic.

* `StartOfTurn`: Interrupt agent if it’s speaking
* `EagerEndOfTurn`: Medium-confidence end → start LLM reply
* `TurnResumed`: User kept talking → cancel reply
* `EndOfTurn`: High-confidence end → send transcript to LLM

By default, Flux only emits `Update`, `StartOfTurn`, and `EndOfTurn`.

### Simple Approach: Enabling End of Turn

> **Info**
>
> For more information on using Flux with EndOfTurn only see the [Flux Getting Started Guide](/docs/flux/quickstart)

This is a simple approach using only `EndOfTurn` (lower latency, less complex, less LLM calls).

To enable end of turn use the `eot_threshold` parameter which allows for a confidence of (0.5–1.0) for `EndOfTurn` events.

#### Example

```text
wss://api.deepgram.com/v2/listen?model=flux-general-en&sample_rate=16000&encoding=linear16&eot_threshold=0.8
```

### Optimized Approach: Enabling EagerEndOfTurn + EndOfTurn

This is an optimized approach using both EagerEndOfTurn and EndOfTurn (lower latency, slightly more complex, more LLM calls)

To enable eager end of turn use the `eager_eot_threshold` parameter which allows for a Confidence of (0.3–0.9). You can also set the `eot_threshold` with a confidence of (0.5–1.0) to handle `EndOfTurn` events and use the `eot_timeout_ms` which defaults to 5000 ms to force a timeout after a specified time.

#### Example

```text
wss://api.deepgram.com/v2/listen?model=flux-general-en&sample_rate=16000&encoding=linear16&eager_eot_threshold=0.6&eot_threshold=0.8&eot_timeout_ms=7000
```

### Keeping Your Own Turn Detection

If you already have a turn detection stack you want to keep (VAD, endpointing, or push-to-talk), you don't have to adopt Flux's native detection. Set `eot_threshold=1.0` to suppress natural end-of-turn, then send a [`ForceEndTurn`](/docs/flux/force-end-turn) message when your own detector fires. See [Bring Your Own Turn Detection](/docs/flux/own-turn-detection) for the full recipe.

#### Example

```text
wss://api.deepgram.com/v2/listen?model=flux-general-en&sample_rate=16000&encoding=linear16&eot_threshold=1.0
```

### Nova 3 Migration Checklist

* [ ] Update WebSocket endpoint to `/v2/listen`
* [ ] Set `model=flux-general-en` and `encoding=linear16`
* [ ] Adjust client to parse `TurnInfo` messages
* [ ] Implement turn event handling (start, eager end of turn, turn resumed, end)
* [ ] Tune `eager_eot_threshold` and `eot_threshold` for your use case
* [ ] Remove custom VAD/barge-in logic (Flux handles this natively) — or keep it and drive turns with [`ForceEndTurn`](/docs/flux/force-end-turn); see [Bring Your Own Turn Detection](/docs/flux/own-turn-detection)

> Migrate from Nova-3 to Flux, Deepgram's conversational speech recognition purpose-built for interactive voice agents.