Kokoro TTS
Apache-licensed 82M-parameter text-to-speech model and Python inference library
You are leaving botconomy for the provider’s website. Link verified 9/22/2026.
What this product helps you do
Kokoro-82M is a compact open-weight text-to-speech model released with Apache-licensed weights. The official repository and PyPI package provide a Python KPipeline that converts text to phonemes and 24 kHz audio, with documented support for American and British English, Spanish, French, Hindi, Italian, Japanese, Brazilian Portuguese, and Mandarin Chinese. Version 1.0 lists 54 voices across eight language groups. The weights and library are free to use, while local compute, storage, integration, and any third-party hosted API cost are separate. The model author explicitly says kokorottsai.com, the catalog's former URL, is unaffiliated and likely a scam.
Problems it solves
- Cloud-only speech services can create recurring cost, latency, and provider dependency
- Developers need a lightweight TTS model that can run in their own environment
- Multilingual speech generation requires language-specific phonemization and voice choices
- Teams need inspectable weights, code, samples, and licensing before integrating TTS
Kokoro-82M is an open-weight text-to-speech model with an official Python inference library, downloadable weights, samples, multiple language groups, and a hosted Hugging Face demo. It emits 24 kHz audio and uses the Misaki grapheme-to-phoneme library.
The model and weights are Apache licensed and free to run, with infrastructure and integration costs left to the deployer. Botconomy now links to the official model page instead of an unaffiliated Kokoro-branded website.
Information
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Kokoro TTS
Apache-licensed 82M-parameter text-to-speech model and Python inference library
Kokoro-82M is an open-weight text-to-speech model with an official Python inference library, downloadable weights, samples, multiple language groups, and a hosted Hugging Face demo. It emits 24 kHz audio and uses the Misaki grapheme-to-phoneme library.
The model and weights are Apache licensed and free to run, with infrastructure and integration costs left to the deployer. Botconomy now links to the official model page instead of an unaffiliated Kokoro-branded website.
What this product helps you do
Kokoro-82M is a compact open-weight text-to-speech model released with Apache-licensed weights. The official repository and PyPI package provide a Python KPipeline that converts text to phonemes and 24 kHz audio, with documented support for American and British English, Spanish, French, Hindi, Italian, Japanese, Brazilian Portuguese, and Mandarin Chinese. Version 1.0 lists 54 voices across eight language groups. The weights and library are free to use, while local compute, storage, integration, and any third-party hosted API cost are separate. The model author explicitly says kokorottsai.com, the catalog's former URL, is unaffiliated and likely a scam.
Problems it solves
- Cloud-only speech services can create recurring cost, latency, and provider dependency
- Developers need a lightweight TTS model that can run in their own environment
- Multilingual speech generation requires language-specific phonemization and voice choices
- Teams need inspectable weights, code, samples, and licensing before integrating TTS
Information
You are leaving botconomy for the provider’s website. Link verified 9/22/2026.
Related AI products
GenSphere
GenSphere is an MIT-licensed Python framework for defining LLM applications as YAML graphs whose nodes can call functions, model APIs, or nested graphs, with visualization and an open push-and-pull project hub.
Griptape Framework
Griptape Framework supplies modular Python abstractions for agents, sequential pipelines, parallel workflows, tools, memory, retrieval, evaluation, multimodal engines, and swappable model, data, storage, and observability drivers.
Daizy
Daizy provides AI agents designed to enhance marketing, sales, and research efforts within financial services, automating tasks such as content generation and client engagement to increase productivity.