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Audio & Voice AI

Mlx Audio

Mlx Audio is a Python library built on Apple’s MLX framework for text-to-speech, speech-to-text and speech-to-speech processing on Apple Silicon.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Mlx Audio — OpenViST project profile in Audio & Voice AI.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Mlx Audio when developing or prototyping audio workflows on Apple Silicon and you want to choose among documented models and use them through Python or the command line.

Who it is for

  • Developers building speech or audio-processing applications for Apple Silicon.
  • Python users who want command-line or library-based access to speech generation and transcription workflows.

Documented uses

  • Generate speech from text with a selected model and voice.
  • Transcribe audio files with a speech-recognition model.
  • Prototype speech-to-speech and other documented audio-processing workflows.
  • Add model-based speech processing to a Python project.
Before you choose

Requirements & limits

The project is a public repository with an MIT license. The README documents pip and uv installation routes.

  • The documented target is Apple Silicon, including M-series chips.
  • Model architectures and language coverage differ, so select a model for the required task and language.
  • Some model workflows need additional packages; the README specifies Misaki and language extras for Kokoro.
  • The project provides developer interfaces, including a CLI and Python API; its README also describes a web interface and OpenAI-compatible REST API.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Generate speech from text with the command line

Use the documented CLI example to generate speech with a selected model and voice.

Before you start

  • Apple Silicon hardware, the library’s documented target.
  • Mlx Audio installed; the README documents pip installation.
  • A model identifier and voice shown in the example.

Steps

  1. Install the package with pip install mlx-audio.

  2. Run mlx_audio.tts.generate with the documented Qwen3-TTS model identifier, text and voice, such as Vivian.

  3. Add --play to play the generated audio, or use --output_path to specify a save location.

Expected outcome

The command generates speech from the supplied text; the example documents playback or saving to a specified directory.

Guide limitations

  • The documented example uses a particular model and voice; available options depend on the chosen model.
  • This recipe follows the README’s instructions and is not a human execution test.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
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Sources checked
13 October 2026
Original website title
Blaizzy/mlx-audio · Official homepage title · retained in its source language
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