qwen3-tts-apple-silicon

Synthesize Chinese speech offline on Apple Silicon with Qwen3-TTS and MLX models.

30|1|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/qianleigood/crawclaw --skill qwen3-tts-apple-silicon
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: qwen3-tts-apple-silicon
Source: https://github.com/qianleigood/crawclaw/tree/main/skills-optional/qwen3-tts-apple-silicon
Command: npx skills add https://github.com/qianleigood/crawclaw --skill qwen3-tts-apple-silicon

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires mlx, mlx-metal, mlx-lm, transformers, mlx-audio, soundfile, librosa, huggingface_hub, numpy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Local TTS generation of Chinese speech on Apple Silicon using Qwen3-TTS with an offline setup, enabling fast, private voice synthesis without cloud dependencies.

Core Features & Use Cases

  • Offline Chinese speech synthesis on Apple Silicon using MLX-backed Qwen3-TTS.
  • Supports synthesis, cloning from reference audio, and voice design from text, plus listing available speakers locally.
  • Suitable for local testing, prototyping dubbing workflows, and offline voice experiments on macOS.

Quick Start

Run the local setup and generate speech with the built-in CLI, for example by executing setup_env.sh and then calling qwen3_tts.py synth with your text and a speaker.

Frequently Asked Questions about qwen3-tts-apple-silicon

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate Chinese speech synthesis locally on Apple Silicon without cloud dependencies?▼

Generate Chinese speech synthesis locally on Apple Silicon by using MLX-backed Qwen3-TTS models. This offline setup enables fast, private voice generation by running scripts to configure the mlx-audio backend and synthesize text directly on your macOS device.

Can I clone a voice from reference audio using Qwen3-TTS on macOS?▼

Yes, you can clone a voice from reference audio using Qwen3-TTS on macOS. The provided scripts support audio cloning workflows alongside standard text-to-speech and voice design, operating entirely offline using the mlx-audio backend.

What Python environment and dependencies are required for offline MLX text-to-speech?▼

Offline MLX text-to-speech requires Python 3.10+ with dependencies including mlx, mlx-lm, mlx-audio, transformers, and soundfile. You must configure the local model caches and run the provided setup_env.sh script before synthesis.

Does the mlx-audio backend support local voice design workflows for developers?▼

Yes, the mlx-audio backend supports local voice design workflows for developers. It allows you to design voices from text, list available local speakers, and prototype dubbing workflows entirely offline using Qwen3-TTS and MLX models on Apple Silicon.

Why does local Chinese TTS require specific MLX model caches on Apple Silicon?▼

Local Chinese TTS requires specific MLX model caches on Apple Silicon to enable offline inference without cloud connectivity. These caches store the Qwen3-TTS model weights and configuration locally, ensuring fast synthesis and privacy by eliminating external API calls.

What is the best way to prototype offline dubbing workflows on macOS using Qwen3-TTS?▼

The best way to prototype offline dubbing workflows on macOS is using Qwen3-TTS with the mlx-audio backend. It provides local synthesis, reference audio cloning, and voice design scripts that run entirely on Apple Silicon without requiring network access.