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-Kokoro is a frontier TTS model for its size of 82 million parameters.
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-On the 25th of December, 2024, Kokoro v0 point 19 weights were permissively released in full fp32 precision along with 2 voicepacks (Bella and Sarah), all under an Apache 2 license.
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-At the time of release, Kokoro v0 point 19 was the number 1 ranked model in TTS Spaces Arena. With 82 million parameters trained for under 20 epics on under 100 total hours of audio, Kokoro achieved higher Eelo in this single-voice Arena setting, over larger models. Kokoro's ability to top this Eelo ladder using relatively low compute and data, suggests that the scaling law for traditional TTS models might have a steeper slope than previously expected.
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-Licenses. Apache 2 weights in this repository. MIT inference code. GPLv3 dependency in espeak NG.
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-The inference code was originally MIT licensed by the paper author. Note that this card applies only to this model, Kokoro.
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-Evaluation. Metric: Eelo rating. Leaderboard: TTS Spaces Arena.
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-The voice ranked in the Arena is a 50 50 mix of Bella and Sarah. For your convenience, this mix is included in this repository as A-F dot PT, but you can trivially re-produce it.
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-Training Details.
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-Compute: Kokoro was trained on "A100 80GB v-ram instances" rented from Vast.ai. Vast was chosen over other compute providers due to its competitive on-demand hourly rates. The average hourly cost for the A100 80GB v-ram instances used for training was below $1 per hour per GPU, which was around half the quoted rates from other providers at the time.
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-Data: Kokoro was trained exclusively on permissive non-copyrighted audio data and IPA phoneme labels. Examples of permissive non-copyrighted audio include:
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-Public domain audio. Audio licensed under Apache, MIT, etc.
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-Synthetic audio[1] generated by closed[2] TTS models from large providers.
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-Epics: Less than 20 Epics. Total Dataset Size: Less than 100 hours of audio.
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-Limitations. Kokoro v0 point 19 is limited in some ways, in its training set and architecture:
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-Lacks voice cloning capability, likely due to small, under 100 hour training set.
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-Relies on external g2p, which introduces a class of g2p failure modes.
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-Training dataset is mostly long-form reading and narration, not conversation.
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-At 82 million parameters, Kokoro almost certainly falls to a well-trained 1B+ parameter diffusion transformer, or a many-billion-parameter M LLM like GPT 4o or Gemini 2 Flash.
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-Multilingual capability is architecturally feasible, but training data is almost entirely English.
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-Will the other voicepacks be released?
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-There is currently no release date scheduled for the other voicepacks, but in the meantime you can try them in the hosted demo.
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-Acknowledgements. yL4 5 7 9 for architecting StyleTTS 2.
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-Pendrokar for adding Kokoro as a contender in the TTS Spaces Arena.
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-Model Card Contact. @rzvzn on Discord.