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hexgrad

hexgrad/Kokoro-82M

Dedicated text-to-speech serving recipe for Kokoro.

Start this recipeView on Hugging Face
Model metadata
CategoryTTSParams82MContextNot applicableBackendsCUDA, METAL, ROCMTasksTTS
Recipe authorship · Recorded configuration verification

Recipe authorship: Curated

Curated and generated describe how this recipe was written, not whether it ran successfully.

Recorded configuration verification

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Command builder

Hardware
Variant

mlx-community/Kokoro-82M-bf16

Mode: Server
Advanced
Features
This feature is not available in the selected mode.
Memory estimation: Why unavailable?

This feature is not available in the selected mode.

Estimated memory use

approx

Approximate memory allocation in GB. These estimates are not measured peak usage.

  • Weights: ≈ 0.1 GB
  • KV: ≈ 0.0 GB
  • Drafter: ≈ 0.0 GB
  • Runtime allowance: ≈ 1.0 GB

Estimated to leave ≈ 4.2 GB of the ≈ 5.4 GB available memory.

Next: prepare the executable

Notes

  • Memory estimates are approximate because hexgrad/Kokoro-82M geometry is incomplete.
  • bf16 weights run as f16 on Apple Silicon.
  • This audio runtime must run as a dedicated process and cannot share a server with text generation.
  • This tier is estimated from nearby measurements.

1. Install

Install in your terminal. Uncached model IDs download automatically on first use.

MLXCEL_INSTALL_DIR="${MLXCEL_INSTALL_DIR:-$HOME/.local/share/mlxcel}" \
  && mkdir -p "$MLXCEL_INSTALL_DIR" \
  && curl -fL -o "$MLXCEL_INSTALL_DIR/mlxcel.zip" https://github.com/lablup/mlxcel/releases/download/v0.8.1/mlxcel-macos-aarch64.zip \
  && unzip -o "$MLXCEL_INSTALL_DIR/mlxcel.zip" -d "$MLXCEL_INSTALL_DIR/mlxcel-macos-aarch64" \
  && export PATH="$MLXCEL_INSTALL_DIR/mlxcel-macos-aarch64:$PATH" \
  && mlxcel --version
Installation and download help

Run the install command in your terminal. The selected executable should then be available on PATH. If it is not found, repeat the displayed PATH export in the same terminal.

Model IDs download automatically when first used. The optional download command prepares the checkpoint ahead of time. Uncached models require internet access and enough disk space; gated models also require access approval and credentials.

2. Run

Run this command in the same terminal after preparation. For server modes, keep it running and wait for the listening/ready message. If memory is insufficient, select a smaller checkpoint or reduce context/concurrency in advanced settings.

Copy all includes the selected installation, checkpoint download, and displayed run commands, in that order. Run them in the same shell; multi-node commands belong on their respective machines.

mlxcel serve

This installation provides the full CLI. Use mlxcel serve; select a source build to use the standalone server.

mlxcel serve -m mlx-community/Kokoro-82M-bf16 --alias kokoro-82m
Command flag help
-m
Selects the model or checkpoint repository.
--alias
Sets the served model name used by API clients.

3. Check the first result

For a server, use a second terminal after it is ready. A text chat request returns JSON with choices[0].message.content; specialized endpoints return their task output. Replace sample file paths with your own inputs where shown. Connection refused: check the server address/port and terminal logs. Model access/download errors: check the model ID, permissions, internet connection, and free disk space.

curl http://127.0.0.1:8080/v1/audio/speech \
  -H "Content-Type: application/json" \
  -d '{"model":"kokoro-82m","input":"Hello from mlxcel","voice":"af_heart"}' \
  --output speech.mp3

Performance evidence

No benchmark is recorded for this selected checkpoint and hardware combination. Commands and memory estimates use the catalog's model information.

Memory fit is a model-based estimate, separate from measured throughput and successful inference verification.

No measurement is available for this hardware yet. See the family page for related profiles. Family

Prerequisites

  • Install the mlxcel build for your selected hardware and check the selected checkpoint's memory estimate.
  • Allow internet access and enough disk space to download an uncached checkpoint; obtain Hugging Face access approval when the checkpoint requires it.

Recipe options

  • • Run Kokoro in a dedicated audio process; it cannot share a text-generation server.

Family

Kokoro (StyleTTS2 + iSTFTNet)

TTS

Sibling recipes

pending

Guide

Kokoro 82M

Kokoro is served by mlxcel's dedicated text-to-speech runtime. It must run in its own process rather than sharing a text-generation server.

Prerequisites

Install mlxcel, then download the checkpoint:

mlxcel download mlx-community/Kokoro-82M-bf16

The Kokoro checkpoint also requires voices/af_heart.safetensors from its voices/*.safetensors assets.

After starting the recipe's server command, request speech with /v1/audio/speech or copy one of the OpenAI SDK snippets from the builder.

References