qwen3-tts-apple-silicon

Name: qwen3-tts-apple-silicon
Availability: InStock
Author: qianleigood

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

30|1|Updated Apr 15, 2026

Search Tags:#local #tts #audio-generation #speech-synthesis #apple-silicon #voice-design

Ready to run

npx skills add https://github.com/qianleigood/crawclaw --skill qwen3-tts-apple-silicon

💬 Prompt for ChatGPT / Claude Chat▼

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.