Model reference · open weights

Kokoro

Audio hexgrad Text→speech 1 build Open weights 11.8M dl/mo

Kokoro is an open-weight audio or speech model from hexgrad. Kokoro-82M (BF16) weighs 327 MB; the smallest configuration that runs it is RTX 3060 12 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • Kokoro is an open-weight text-to-speech model developed by hexgrad with 82 million parameters.
  • It uses the StyleTTS 2 architecture and is trained on a few hundred hours of permissive audio data.
  • The model supports English and is released under the Apache 2.0 license.

Summary of the hexgrad/Kokoro-82M model card, 2026-10-01

What it is

Released byhexgrad
Released2024-12-26
VRAM327 MB for the weights

What it runs on

Memory and cards for Kokoro-82M (BF16)

327 MBweights, file size
1.6 GBruntime overhead
CardOne streamMemory
RTX 3060 12 GBfits11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

From the model card

What hexgrad says about Kokoro

Read the model card

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.

🐈 GitHub: https://github.com/hexgrad/kokoro

🚀 Demo: https://hf.co/spaces/hexgrad/Kokoro-TTS

[!NOTE] As of April 2025, the market rate of Kokoro served over API is under $1 per million characters of text input, or under $0.06 per hour of audio output. (On average, 1000 characters of input is about 1 minute of output.) Sources: ArtificialAnalysis/Replicate at 65 cents per M chars and DeepInfra at 80 cents per M chars.

This is an Apache-licensed model, and Kokoro has been deployed in numerous projects and commercial APIs. We welcome the deployment of the model in real use cases.

[!CAUTION] Fake websites like kokorottsai_com (snapshot: https://archive.ph/nRRnk) and kokorotts_net (snapshot: https://archive.ph/60opa) are likely scams masquerading under the banner of a popular model.

Any website containing "kokoro" in its root domain (e.g. kokorottsai_com, kokorotts_net) is NOT owned by and NOT affiliated with this model page or its author, and attempts to imply otherwise are red flags.

Releases

ModelPublishedTraining DataLangs & VoicesSHA256
v1.02025 Jan 27Few hundred hrs8 & 54496dba11
v0.192024 Dec 25<100 hrs1 & 103b0c392f
Training Costsv0.19v1.0Total
in A100 80GB GPU hours5005001000
average hourly rate$0.80/h$1.20/h$1/h
in USD$400$600$1000

Usage

!pip install -q kokoro>=0.9.2 soundfile
!apt-get -qq -y install espeak-ng > /dev/null 2>&1
from kokoro import KPipeline
from IPython.display import display, Audio
import soundfile as sf
import torch
pipeline = KPipeline(lang_code='a')
text = '''
[Kokoro](/kˈOkəɹO/) 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](/kˈOkəɹO/) can be deployed anywhere from production environments to personal projects.
'''
generator = pipeline(text, voice='af_heart')
for i, (gs, ps, audio) in enumerate(generator):
    print(i, gs, ps)
    display(Audio(data=audio, rate=24000, autoplay=i==0))
    sf.write(f'{i}.wav', audio, 24000)

Under the hood, kokoro uses misaki, a G2P library at https://github.com/hexgrad/misaki

Model Facts

Architecture:

  • StyleTTS 2: https://arxiv.org/abs/2306.07691
  • ISTFTNet: https://arxiv.org/abs/2203.02395
  • Decoder only: no diffusion, no encoder release

Architected by: Li et al @ https://github.com/yl4579/StyleTTS2

Trained by: @rzvzn on Discord

Languages: Multiple

Model SHA256 Hash: 496dba118d1a58f5f3db2efc88dbdc216e0483fc89fe6e47ee1f2c53f18ad1e4

Training Details

Data: Kokoro was trained exclusively on permissive/non-copyrighted audio data and IPA phoneme labels. Examples of permissive/non-copyrighted audio include:

  • Public domain audio
  • Audio licensed under Apache, MIT, etc
  • Synthetic audio[1] generated by closed[2] TTS models from large providers [1] https://copyright.gov/ai/ai_policy_guidance.pdf [2] No synthetic audio from open TTS models or "custom voice clones"

Total Dataset Size: A few hundred hours of audio

Total Training Cost: About $1000 for 1000 hours of A100 80GB vRAM

Creative Commons Attribution

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

Audio DataDuration UsedLicenseAdded to Training Set After
Koniwa tnc<1hCC BY 3.0v0.19 / 22 Nov 2024
SIWIS<11hCC BY 4.0v0.19 / 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". It is also the name of an AI in the Terminator franchise.

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

How it works

How audio & music work

Audio or textinputAudio modelrecognise / synthesiseText or audiooutputSpeech-to-text turns audio into text; text-to-speech and music models turn text into audio.
© 2026 AxForge · EU-hosted AI infrastructure Pricing Docs Trust Privacy Terms