Use Gemini TTS Models to convert your prompts to real audio.

fal-ai/gemini-tts

Use Gemini TTS Models to convert your prompts to real audio.

Inference

Commercial use

Partner

Schema

LLMs

Playground API

About

Generate speech from text using Google's Gemini TTS models.

Supports 30 distinct voice presets and natural-language prompting for fine-grained control over style, pace, accent, and emotion.

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/gemini-tts", {
  input: {
    prompt: "Host: Welcome back to AI Frontiers, the podcast where we explore the latest breakthroughs in artificial intelligence. Today we have a very special guest. Doctor Chen, thank you for joining us!
  DrChen: Thanks for having me! I'm excited to be here.
  Host: So, let's dive right in. Your recent paper on neural architecture search has been making waves. Can you tell our listeners what inspired this research?
  DrChen: Absolutely. It all started when we noticed that most existing approaches were optimizing for the wrong metrics. We asked ourselves, what if we could let the model design itself?"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In an environment where you cannot set environment variables, you can configure the API key manually on the client.

import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Protect your API Key

When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY. Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide.

3. Queue#

Long-running requests

For long-running requests, such as training jobs or models with slower inference times, it is recommended to check the Queue status and rely on Webhooks instead of blocking while waiting for the result.

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/gemini-tts", {
  input: {
    prompt: "Host: Welcome back to AI Frontiers, the podcast where we explore the latest breakthroughs in artificial intelligence. Today we have a very special guest. Doctor Chen, thank you for joining us!
  DrChen: Thanks for having me! I'm excited to be here.
  Host: So, let's dive right in. Your recent paper on neural architecture search has been making waves. Can you tell our listeners what inspired this research?
  DrChen: Absolutely. It all started when we noticed that most existing approaches were optimizing for the wrong metrics. We asked ourselves, what if we could let the model design itself?"
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/gemini-tts", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/gemini-tts", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).

Read more about file handling in our file upload guide.

5. Schema#

Input#

prompt string* required

The text to convert to speech. Gemini TTS supports natural-language prompting for style, pace, accent, and emotional expression — include delivery instructions inline with the text (e.g. 'Say cheerfully: Have a wonderful day!'). For multi-speaker synthesis, prefix lines with speaker aliases defined in the speakers field (e.g. 'Alice: Hello! Bob: Hi!'). Supports inline pace/style markers like [slowly], [whispering], [excited], [extremely fast].

style_instructions string

Optional style and delivery instructions prepended to the prompt. Controls expressiveness, accent, pace, tone, and emotional expression using natural language. Use this to separate style control from the text content. Examples: 'Speak warmly and slowly', 'Read this as a dramatic newscast', 'Use a British accent with a cheerful tone', 'Whisper mysteriously'.

voice VoiceEnum

Voice preset for single-speaker synthesis. 30 distinct voices are available. Ignored when speakers is set. Popular choices: Kore (strong, firm female), Puck (upbeat, lively male), Charon (calm, professional male), Zephyr (bright, clear female), Aoede (warm, melodic female). Default value: "Kore"

Possible enum values: Achernar, Achird, Algenib, Algieba, Alnilam, Aoede, Autonoe, Callirrhoe, Charon, Despina, Enceladus, Erinome, Fenrir, Gacrux, Iapetus, Kore, Laomedeia, Leda, Orus, Pulcherrima, Puck, Rasalgethi, Sadachbia, Sadaltager, Schedar, Sulafat, Umbriel, Vindemiatrix, Zephyr, Zubenelgenubi

model ModelEnum

Which Gemini TTS model to use. gemini-2.5-flash-tts: low latency, cost-efficient for everyday applications (recommended). gemini-2.5-pro-tts: highest quality, best for structured workflows like podcasts, audiobooks, and customer support. Default value: "gemini-2.5-flash-tts"

Possible enum values: gemini-2.5-flash-tts, gemini-2.5-pro-tts

language_code Enum

Language for multilingual synthesis. When set, steers the model to speak in the specified language. Supports 24 GA languages and 60+ Preview languages. If not set, the model auto-detects the language from the text.

Possible enum values: Arabic (Egypt), Bangla (Bangladesh), Dutch (Netherlands), English (India), English (US), French (France), German (Germany), Hindi (India), Indonesian (Indonesia), Italian (Italy), Japanese (Japan), Korean (South Korea), Marathi (India), Polish (Poland), Portuguese (Brazil), Romanian (Romania), Russian (Russia), Spanish (Spain), Tamil (India), Telugu (India), Thai (Thailand), Turkish (Turkey), Ukrainian (Ukraine), Vietnamese (Vietnam), Afrikaans (South Africa), Albanian (Albania), Amharic (Ethiopia), Arabic (World), Armenian (Armenia), Azerbaijani (Azerbaijan), Basque (Spain), Belarusian (Belarus), Bulgarian (Bulgaria), Burmese (Myanmar), Catalan (Spain), Cebuano (Philippines), Chinese Mandarin (China), Chinese Mandarin (Taiwan), Croatian (Croatia), Czech (Czech Republic), Danish (Denmark), English (Australia), English (UK), Estonian (Estonia), Filipino (Philippines), Finnish (Finland), French (Canada), Galician (Spain), Georgian (Georgia), Greek (Greece), Gujarati (India), Haitian Creole (Haiti), Hebrew (Israel), Hungarian (Hungary), Icelandic (Iceland), Javanese (Java), Kannada (India), Konkani (India), Lao (Laos), Latin (Vatican City), Latvian (Latvia), Lithuanian (Lithuania), Luxembourgish (Luxembourg), Macedonian (North Macedonia), Maithili (India), Malagasy (Madagascar), Malay (Malaysia), Malayalam (India), Mongolian (Mongolia), Nepali (Nepal), Norwegian Bokmal (Norway), Norwegian Nynorsk (Norway), Odia (India), Pashto (Afghanistan), Persian (Iran), Portuguese (Portugal), Punjabi (India), Serbian (Serbia), Sindhi (India), Sinhala (Sri Lanka), Slovak (Slovakia), Slovenian (Slovenia), Spanish (Latin America), Spanish (Mexico), Swahili (Kenya), Swedish (Sweden), Urdu (Pakistan)

speakers list<SpeakerConfig>

Multi-speaker voice configuration. When set, enables multi-speaker synthesis where different parts of the text are spoken by different voices. Each speaker needs a voice and a speaker_id (alias) that matches prefixes in the prompt. Requires gemini-2.5-pro-tts or gemini-2.5-flash-tts model. Not supported with gemini-2.5-flash-lite-preview-tts.

temperature float

Controls the randomness of the speech output. Higher values produce more creative and varied delivery, while lower values make the output more predictable and focused. Default value: 1

output_format OutputFormatEnum

Audio output format. mp3: compressed, small file size (recommended). wav: uncompressed PCM wrapped in WAV (24 kHz, 16-bit mono). ogg_opus: Ogg container with Opus codec, good quality-to-size ratio. Default value: "mp3"

Possible enum values: wav, mp3, ogg_opus

{
  "prompt": "Host: Welcome back to AI Frontiers, the podcast where we explore the latest breakthroughs in artificial intelligence. Today we have a very special guest. Doctor Chen, thank you for joining us!\nDrChen: Thanks for having me! I'm excited to be here.\nHost: So, let's dive right in. Your recent paper on neural architecture search has been making waves. Can you tell our listeners what inspired this research?\nDrChen: Absolutely. It all started when we noticed that most existing approaches were optimizing for the wrong metrics. We asked ourselves, what if we could let the model design itself?",
  "style_instructions": "Say the following in a warm, conversational tone",
  "voice": "Kore",
  "model": "gemini-2.5-flash-tts",
  "language_code": "English (US)",
  "speakers": [
    {
      "speaker_id": "Host",
      "voice": "Charon"
    },
    {
      "speaker_id": "DrChen",
      "voice": "Kore"
    }
  ],
  "temperature": 1,
  "output_format": "mp3"
}

Output#

audio File* required

The generated audio file.

{
  "audio": {
    "url": "https://v3b.fal.media/files/b/0a935d4f/Ez4NpcnFTuGsu2FHDaJTR_gemini_tts_output.mp3"
  }
}

Other types#

File#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

SpeakerConfig#

voice VoiceEnum* required

Voice preset for this speaker.

speaker_id string* required

Alias used to identify this speaker in the prompt. Use this alias as a prefix in the prompt field, e.g. 'Alice: Hello! Bob: Hi there!'. Must be alphanumeric with no whitespace.

1. Calling the API

2. Authentication

API Key

3. Queue

4. Files

5. Schema

About

Generate speech from text using Google's Gemini TTS models.

Supports 30 distinct voice presets and natural-language prompting for fine-grained control over style, pace, accent, and emotion.

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/gemini-tts", {
  input: {
    prompt: "Host: Welcome back to AI Frontiers, the podcast where we explore the latest breakthroughs in artificial intelligence. Today we have a very special guest. Doctor Chen, thank you for joining us!
  DrChen: Thanks for having me! I'm excited to be here.
  Host: So, let's dive right in. Your recent paper on neural architecture search has been making waves. Can you tell our listeners what inspired this research?
  DrChen: Absolutely. It all started when we noticed that most existing approaches were optimizing for the wrong metrics. We asked ourselves, what if we could let the model design itself?"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In an environment where you cannot set environment variables, you can configure the API key manually on the client.

import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/gemini-tts", {
  input: {
    prompt: "Host: Welcome back to AI Frontiers, the podcast where we explore the latest breakthroughs in artificial intelligence. Today we have a very special guest. Doctor Chen, thank you for joining us!
  DrChen: Thanks for having me! I'm excited to be here.
  Host: So, let's dive right in. Your recent paper on neural architecture search has been making waves. Can you tell our listeners what inspired this research?
  DrChen: Absolutely. It all started when we noticed that most existing approaches were optimizing for the wrong metrics. We asked ourselves, what if we could let the model design itself?"
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/gemini-tts", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/gemini-tts", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).

Read more about file handling in our file upload guide.

5. Schema#

Input#

prompt string* required

style_instructions string

voice VoiceEnum

model ModelEnum

Possible enum values: gemini-2.5-flash-tts, gemini-2.5-pro-tts

language_code Enum

speakers list<SpeakerConfig>

temperature float

Controls the randomness of the speech output. Higher values produce more creative and varied delivery, while lower values make the output more predictable and focused. Default value: 1

output_format OutputFormatEnum

Possible enum values: wav, mp3, ogg_opus

{
  "prompt": "Host: Welcome back to AI Frontiers, the podcast where we explore the latest breakthroughs in artificial intelligence. Today we have a very special guest. Doctor Chen, thank you for joining us!\nDrChen: Thanks for having me! I'm excited to be here.\nHost: So, let's dive right in. Your recent paper on neural architecture search has been making waves. Can you tell our listeners what inspired this research?\nDrChen: Absolutely. It all started when we noticed that most existing approaches were optimizing for the wrong metrics. We asked ourselves, what if we could let the model design itself?",
  "style_instructions": "Say the following in a warm, conversational tone",
  "voice": "Kore",
  "model": "gemini-2.5-flash-tts",
  "language_code": "English (US)",
  "speakers": [
    {
      "speaker_id": "Host",
      "voice": "Charon"
    },
    {
      "speaker_id": "DrChen",
      "voice": "Kore"
    }
  ],
  "temperature": 1,
  "output_format": "mp3"
}

Output#

audio File* required

The generated audio file.

{
  "audio": {
    "url": "https://v3b.fal.media/files/b/0a935d4f/Ez4NpcnFTuGsu2FHDaJTR_gemini_tts_output.mp3"
  }
}

Other types#

File#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

SpeakerConfig#

voice VoiceEnum* required

Voice preset for this speaker.

speaker_id string* required

Alias used to identify this speaker in the prompt. Use this alias as a prefix in the prompt field, e.g. 'Alice: Hello! Bob: Hi there!'. Must be alphanumeric with no whitespace.

fal-ai/gemini-tts

Table of contents

Table of contents

fal-ai/gemini-tts

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

File#

SpeakerConfig#

Table of contents

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

File#

SpeakerConfig#