Kokoro-82M โ€” Q8/FP16 ONNX

ONNX export of hexgrad/Kokoro-82M, an open-weight English text-to-speech model, in a Q8/FP16 mixed-precision format. It is not a newly trained model. This is an unofficial community conversion; hexgrad is the original model author.

"Q8F16" refers to 8-bit weights with FP16 activations (or FP16 weights with Q8 compute paths, depending on the export configuration). Quantization follows the ONNX Community model_q8f16.onnx export. This variant targets CPU or lower-VRAM GPU execution where the FP16 model is too large or too slow.

Source

Field Value
Upstream model onnx-community/Kokoro-82M-v1.0-ONNX
Upstream source revision 1939ad2a8e416c0acfeecc08a694d14ef25f2231
Export tool/script Mirrored from onnx-community (no re-export)
Quantization recipe Pre-quantized Q8F16 ONNX mirrored from onnx/model_q8f16.onnx

Files

File Size Description
onnx/model_q8f16.onnx ~82 MB Q8/FP16 ONNX model (self-contained)

Intended Use

An English text-to-speech model packaged for local inference via ONNX Runtime. The Q8/FP16 variant targets CPU or constrained-GPU execution where the FP16 model exceeds the available memory or compute budget. The FP16 variant is in tonythethompson/kokoro-82m-fp16-onnx.

Runtime Notes

  • Designed for ONNX Runtime compatible runtimes.
  • Target: CPU or GPU with limited VRAM.
  • Sample rate: 24 kHz (inherited from Kokoro-82M).
  • Mixed quantization: execution-provider behavior depends on the ONNX Runtime version and hardware. Validate on the target execution provider before production use.

Precision and Packaging

Export tooling, precision, and quantization are recorded in the Source table above. This packaging mirror does not publish independent parity benchmarks; validate on your target execution provider before production use.

Limitations

  • English-only TTS.
  • No parity evaluation against the original PyTorch or FP16 ONNX model is documented here.
  • Audio quality degradation relative to FP16 is possible; validate on your target use case.

Safety and Responsible Use

Kokoro-82M produces realistic synthetic speech (from preset voice styles, not arbitrary speaker cloning).

  • Do not use to impersonate real individuals without their explicit consent.
  • Do not generate synthetic speech intended to deceive listeners about a speaker's identity.
  • Disclose AI-generated audio where listeners would reasonably expect a human voice.
  • Users are responsible for compliance with applicable laws governing synthetic media in their jurisdiction.

License

Apache 2.0 โ€” inherited from hexgrad/Kokoro-82M. This packaging repo adds no new license terms.

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