## Basic model info

- Model name: google/google gemini-3.8-flash-tts
- Model description: Gemini 3.8 Flash TTS — Google's studio-grade text-to-speech model. 30 prebuilt voices across 130 languages, per-turn delivery direction (emotion, pacing, whispering) via a style field, inline vocal-event tags such as <laugh> and <sigh>, and two-speaker conversational dialogue in a single request. Outputs 24 kHz WAV.
- Endpoint name: text-to-dialogue


## Model schema

The model schema is defined in the OpenAPI schema: [OpenAPI Schema](https://oapi.sunra.ai/main/google/gemini-3.8-flash-tts/latest.json)

### Model input schema

The model input schema is:



```json
{
  "properties": {
    "inputs": {
      "description": "Ordered dialogue turns. Up to 2 distinct voices and 5000 total text characters.",
      "items": {
        "properties": {
          "style": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "description": "Delivery direction for this passage: tone, pacing, or emotion (e.g. whispering).",
            "title": "Style"
          },
          "text": {
            "description": "Text to read verbatim. Supports inline vocal-event tags <laugh>, <sigh>, <cough>, <breath>, and <short pause>.",
            "maxLength": 5000,
            "minLength": 1,
            "title": "Text",
            "type": "string"
          },
          "voice": {
            "description": "Zephyr Bright / Puck Upbeat / Charon Informative / Kore Firm / Fenrir Excitable / Leda Youthful / Orus Firm / Aoede Breezy / Callirrhoe Easy-going / Autonoe Bright / Enceladus Breathy / Iapetus Clear / Umbriel Easy-going / Algieba Smooth / Despina Smooth / Erinome Clear / Algenib Gravelly / Rasalgethi Informative / Laomedeia Upbeat / Achernar Soft / Alnilam Firm / Schedar Even / Gacrux Mature / Pulcherrima Forward / Achird Friendly / Zubenelgenubi Casual / Vindemiatrix Gentle / Sadachbia Lively / Sadaltager Knowledgeable / Sulafat Warm",
            "enum": [
              "Zephyr",
              "Puck",
              "Charon",
              "Kore",
              "Fenrir",
              "Leda",
              "Orus",
              "Aoede",
              "Callirrhoe",
              "Autonoe",
              "Enceladus",
              "Iapetus",
              "Umbriel",
              "Algieba",
              "Despina",
              "Erinome",
              "Algenib",
              "Rasalgethi",
              "Laomedeia",
              "Achernar",
              "Alnilam",
              "Schedar",
              "Gacrux",
              "Pulcherrima",
              "Achird",
              "Zubenelgenubi",
              "Vindemiatrix",
              "Sadachbia",
              "Sadaltager",
              "Sulafat"
            ],
            "title": "Voice",
            "type": "string"
          }
        },
        "required": [
          "text",
          "voice"
        ],
        "title": "DialogueTurn",
        "type": "object"
      },
      "minItems": 1,
      "title": "Inputs",
      "type": "array",
      "x-sr-order": 201
    }
  },
  "required": [
    "inputs"
  ],
  "title": "TextToDialogueInput",
  "type": "object"
}
```



### Model output schema

The model output schema is:



```json
{
  "properties": {
    "audio": {
      "properties": {
        "content_type": {
          "description": "The mime type of the file.",
          "title": "Content Type",
          "type": "string"
        },
        "file_name": {
          "description": "The name of the file. It will be auto-generated if not provided.",
          "title": "File Name",
          "type": "string"
        },
        "file_size": {
          "description": "The size of the file in bytes.",
          "title": "File Size",
          "type": "integer"
        },
        "url": {
          "description": "The URL where the file can be downloaded from.",
          "title": "Url",
          "type": "string"
        }
      },
      "required": [
        "content_type",
        "file_name",
        "file_size",
        "url"
      ],
      "title": "SunraFile",
      "type": "object"
    },
    "units": {
      "description": "Token cost in USD, used for post-calculated billing",
      "title": "Units",
      "type": "number"
    },
    "usage": {
      "additionalProperties": true,
      "description": "Google input/output token usage by modality and totals",
      "title": "Usage",
      "type": "object"
    }
  },
  "required": [
    "audio",
    "usage",
    "units"
  ],
  "title": "GeminiTTSOutput",
  "type": "object"
}
```



## Example inputs and outputs

Use the following example inputs and outputs to understand the model.

### Input example



```json
{
  "inputs": [
  ]
}
```



### Output example



```json
{
}
```



## Model code examples

### JavaScript



```javascript
import { sunra } from "@sunra/client";

const result = await sunra.subscribe("google/gemini-3.8-flash-tts/text-to-dialogue", {
  input: {
  	inputs: []
  },
  logs: true,
  onQueueUpdate: (update) => {
    console.log(`Status Update: ${update.status}, Request ID: ${update.request_id}`);
  },
});
console.log(result.data);
console.log(result.requestId);
```



### Python



```python
import sunra_client

result = sunra_client.subscribe(
    "google/gemini-3.8-flash-tts/text-to-dialogue",
    arguments={
        "inputs": []
    },

    with_logs=True,
    on_enqueue=print,
    on_queue_update=print,
)
print(result)
```



### Java



```java
import ai.sunra.client.*;
import java.util.Map;
import com.google.gson.JsonObject;

var client = SunraClient.withEnvCredentials();

var response = client.subscribe(
    "google/gemini-3.8-flash-tts/text-to-dialogue",
    SubscribeOptions.<JsonObject>builder()
        .input(Map.of(
            "inputs", ))

        .resultType(JsonObject.class)
        .onQueueUpdate(update -> System.out.printf(
            "\nStatus Update: %s, Request ID: %s%n",
            update.getStatus(),
            update.getRequestId()
        ))
        .logs(true)
        .build()
);

System.out.println("Completed!");
System.out.println(response.getData());
  
```



### Kotlin



```kotlin
import ai.sunra.client.kt.*
import com.google.gson.JsonObject

val client = createSunraClient()

val response = client.subscribe<JsonObject>(
    endpointId = "google/gemini-3.8-flash-tts/text-to-dialogue",
    input = mapOf(
            "inputs" to ),
    options = ai.sunra.client.kt.SubscribeOptions(logs = true),
    onUpdate = { update ->
        println("\nStatus Update: ${update.status}, Request ID: ${update.requestId}")
    }
)

println("Completed!")
println(response.data)
  
```



### Curl



```bash

curl --request POST \
  --url https://api.sunra.ai/v1/queue/google/gemini-3.8-flash-tts/text-to-dialogue \
  --header "Authorization: Key $SUNRA_KEY" \
  --header "Content-Type: application/json" \
  --data '{"inputs":[]}'
    
```



## Model readme

>