alphanumericuser / kokoro-82m

Kokoro v1.0 - text-to-speech (82M params, based on StyleTTS2)

Cold

Public
1.2K runs
T4
GitHub
Weights
License

Run with an API

Playground API Examples README Versions

Input

text

string

Shift + Return to add a new line

Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.

Text to convert to speech

Default: "Hi! I'm Kokoro, a text-to-speech voice crafted by hexgrad — based on StyleTTS2."

language_code

string

Language of the text

Default: "a"

voice

string

Voice to use for synthesis

Default: "af_heart"

speed

number

(minimum: 0.1, maximum: 5)

Speed of speech

Default: 1

Run this model in Node.js with one line of code:

npx create-replicate --model=alphanumericuser/kokoro-82m

or set up a project from scratch

Install Replicate’s Node.js client library

npm install replicate

Set the REPLICATE_API_TOKEN environment variable

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run alphanumericuser/kokoro-82m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "alphanumericuser/kokoro-82m:89b6fa84e4fa2dd6bd3a96be3e1f12827a3516c9fda8fddbac7a0be131c9a6f5",
  {
    input: {
      text: "Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.",
      speed: 1,
      voice: "af_heart",
      language_code: "a"
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library

pip install replicate

Set the REPLICATE_API_TOKEN environment variable

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client

import replicate

Run alphanumericuser/kokoro-82m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "alphanumericuser/kokoro-82m:89b6fa84e4fa2dd6bd3a96be3e1f12827a3516c9fda8fddbac7a0be131c9a6f5",
    input={
        "text": "Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.",
        "speed": 1,
        "voice": "af_heart",
        "language_code": "a"
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run alphanumericuser/kokoro-82m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "89b6fa84e4fa2dd6bd3a96be3e1f12827a3516c9fda8fddbac7a0be131c9a6f5",
    "input": {
      "text": "Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.",
      "speed": 1,
      "voice": "af_heart",
      "language_code": "a"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

Video Player is loading.

Current Time 00:00:000

Duration 00:00:000

Loaded: 0%

Stream Type LIVE

Remaining Time 00:00:000

{
  "completed_at": "2025-02-08T22:38:22.285663Z",
  "created_at": "2025-02-08T22:36:22.047000Z",
  "data_removed": false,
  "error": null,
  "id": "619hq7zekxrga0cmwytbygnj4r",
  "input": {
    "text": "Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.",
    "speed": 1,
    "voice": "af_heart",
    "language_code": "a"
  },
  "logs": "/usr/local/lib/python3.10/site-packages/torch/nn/modules/rnn.py:123: UserWarning: dropout option adds dropout after all but last recurrent layer, so non-zero dropout expects num_layers greater than 1, but got dropout=0.2 and num_layers=1\nwarnings.warn(\n/usr/local/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py:143: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.\nWeightNorm.apply(module, name, dim)\nCollecting en-core-web-sm==3.8.0\nDownloading https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.8.0/en_core_web_sm-3.8.0-py3-none-any.whl (12.8 MB)\n     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.8/12.8 MB 58.5 MB/s eta 0:00:00\nInstalling collected packages: en-core-web-sm\nSuccessfully installed en-core-web-sm-3.8.0\nWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\n[notice] A new release of pip is available: 23.0.1 -> 25.0\n[notice] To update, run: pip install --upgrade pip\n\u001b[38;5;2m✔ Download and installation successful\u001b[0m\nYou can now load the package via spacy.load('en_core_web_sm')",
  "metrics": {
    "predict_time": 18.001196151,
    "total_time": 120.238663
  },
  "output": "https://replicate.delivery/czjl/8Mw94y2JN3o9HhK30eokfeqq2EotPllY2D9USqXDIe34tj1QB/tmpyulkh5io.wav",
  "started_at": "2025-02-08T22:38:04.284467Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/fddq-232yowacugrpqt7qdinzo6q2gbkp4ucyzztpikgcxrvey3zubw4q",
    "get": "https://api.replicate.com/v1/predictions/619hq7zekxrga0cmwytbygnj4r",
    "cancel": "https://api.replicate.com/v1/predictions/619hq7zekxrga0cmwytbygnj4r/cancel"
  },
  "version": "89b6fa84e4fa2dd6bd3a96be3e1f12827a3516c9fda8fddbac7a0be131c9a6f5"
}

Generated in

18.0 seconds

Tweak it ShareReport

Run time and cost

This model costs approximately $0.0014 to run on Replicate, or 714 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia T4 GPU hardware. Predictions typically complete within 7 seconds. The predict time for this model varies significantly based on the inputs.

Readme

license: apache-2.0 language: - en base_model: - yl4579/StyleTTS2-LJSpeech pipeline_tag: text-to-speech

Disclaimer

This is a fork of the original Kokoro repo, in order to provide easy inference on Replicate. I am not affiliated with the original Kokoro authors, and this is not an official release of the Kokoro model. Similar to the Huggingface Space, this implementation provides automatic text splitting to support long form text inputs. See the original README below for more details.

Voices

🇺🇸 American English
🇬🇧 British English
🇯🇵 Japanese
🇨🇳 Mandarin Chinese
🇪🇸 Spanish
🇫🇷 French
🇮🇳 Hindi
🇮🇹 Italian
🇧🇷 Brazilian Portuguese

American English

lang_code='a' in misaki[en]
espeak-ng en-us fallback

Name	Traits	Target Quality	Training Duration	Overall Grade	SHA256
af_heart	🚺❤️			A	`0ab5709b`
af_alloy	🚺	B	MM minutes	C	`6d877149`
af_aoede	🚺	B	H hours	C+	`c03bd1a4`
af_bella	🚺🔥	A	HH hours	A-	`8cb64e02`
af_jessica	🚺	C	MM minutes	D	`cdfdccb8`
af_kore	🚺	B	H hours	C+	`8bfbc512`
af_nicole	🚺🎧	B	HH hours	B-	`c5561808`
af_nova	🚺	B	MM minutes	C	`e0233676`
af_river	🚺	C	MM minutes	D	`e149459b`
af_sarah	🚺	B	H hours	C+	`49bd364e`
af_sky	🚺	B	M minutes 🤏	C-	`c799548a`
am_adam	🚹	D	H hours	F+	`ced7e284`
am_echo	🚹	C	MM minutes	D	`8bcfdc85`
am_eric	🚹	C	MM minutes	D	`ada66f0e`
am_fenrir	🚹	B	H hours	C+	`98e507ec`
am_liam	🚹	C	MM minutes	D	`c8255075`
am_michael	🚹	B	H hours	C+	`9a443b79`
am_onyx	🚹	C	MM minutes	D	`e8452be1`
am_puck	🚹	B	H hours	C+	`dd1d8973`
am_santa	🚹	C	M minutes 🤏	D-	`7f2f7582`

British English

lang_code='b' in misaki[en]
espeak-ng en-gb fallback

Name	Traits	Target Quality	Training Duration	Overall Grade	SHA256
bf_alice	🚺	C	MM minutes	D	`d292651b`
bf_emma	🚺	B	HH hours	B-	`d0a423de`
bf_isabella	🚺	B	MM minutes	C	`cdd4c370`
bf_lily	🚺	C	MM minutes	D	`6e09c2e4`
bm_daniel	🚹	C	MM minutes	D	`fc3fce4e`
bm_fable	🚹	B	MM minutes	C	`d44935f3`
bm_george	🚹	B	MM minutes	C	`f1bc8122`
bm_lewis	🚹	C	H hours	D+	`b5204750`

Japanese

lang_code='j' in misaki[ja]
Total Japanese training data: H hours

Name	Traits	Target Quality	Training Duration	Overall Grade	SHA256	CC BY
jf_alpha	🚺	B	H hours	C+	`1bf4c9dc`
jf_gongitsune	🚺	B	MM minutes	C	`1b171917`	gongitsune
jf_nezumi	🚺	B	M minutes 🤏	C-	`d83f007a`	nezuminoyomeiri
jf_tebukuro	🚺	B	MM minutes	C	`0d691790`	tebukurowokaini
jm_kumo	🚹	B	M minutes 🤏	C-	`98340afd`	kumonoito

Mandarin Chinese

lang_code='z' in misaki[zh]
Total Mandarin Chinese training data: H hours

Name	Traits	Target Quality	Training Duration	Overall Grade	SHA256
zf_xiaobei	🚺	C	MM minutes	D	`9b76be63`
zf_xiaoni	🚺	C	MM minutes	D	`95b49f16`
zf_xiaoxiao	🚺	C	MM minutes	D	`cfaf6f2d`
zf_xiaoyi	🚺	C	MM minutes	D	`b5235dba`
zm_yunjian	🚹	C	MM minutes	D	`76cbf8ba`
zm_yunxi	🚹	C	MM minutes	D	`dbe6e1ce`
zm_yunxia	🚹	C	MM minutes	D	`bb2b03b0`
zm_yunyang	🚹	C	MM minutes	D	`5238ac22`

Spanish

lang_code='e' in misaki[en]
espeak-ng es

Name	Traits	SHA256
ef_dora	🚺	`d9d69b0f`
em_alex	🚹	`5eac53f7`
em_santa	🚹	`aa8620cb`

French

lang_code='f' in misaki[en]
espeak-ng fr-fr
Total French training data: <11 hours

Name	Traits	Target Quality	Training Duration	Overall Grade	SHA256	CC BY
ff_siwis	🚺	B	<11 hours	B-	`8073bf2d`	SIWIS

Hindi

lang_code='h' in misaki[en]
espeak-ng hi
Total Hindi training data: H hours

Name	Traits	Target Quality	Training Duration	Overall Grade	SHA256
hf_alpha	🚺	B	MM minutes	C	`06906fe0`
hf_beta	🚺	B	MM minutes	C	`63c0a1a6`
hm_omega	🚹	B	MM minutes	C	`b55f02a8`
hm_psi	🚹	B	MM minutes	C	`2f0f055c`

Italian

lang_code='i' in misaki[en]
espeak-ng it
Total Italian training data: H hours

Name	Traits	Target Quality	Training Duration	Overall Grade	SHA256
if_sara	🚺	B	MM minutes	C	`6c0b253b`
im_nicola	🚹	B	MM minutes	C	`234ed066`

Brazilian Portuguese

lang_code='p' in misaki[en]
espeak-ng pt-br

Name	Traits	SHA256
pf_dora	🚺	`07e4ff98`
pm_alex	🚹	`cf0ba8c5`
pm_santa	🚹	`d4210316`

✨ You can now pip install kokoro! See Usage.

Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.

Creative Commons Attribution

The following CC BY audio was part of the dataset used to train Kokoro v1.0.

Audio Data	Duration Used	License	Added to Training Set After
Koniwa `tnc`	<1h	CC BY 3.0	v0.19 / 22 Nov 2024
SIWIS	<11h	CC BY 4.0	v0.19 / 22 Nov 2024

Acknowledgements

🛠️ @yl4579 for architecting StyleTTS 2.
🏆 @Pendrokar for adding Kokoro as a contender in the TTS Spaces Arena.
📊 Thank you to everyone who contributed synthetic training data.
❤️ Special thanks to all compute sponsors.
👾 Discord server: https://discord.gg/QuGxSWBfQy
🪽 Kokoro is a Japanese word that translates to “heart” or “spirit”. Kokoro is also the name of an AI in the Terminator franchise.

kokoro