MLX Port for 24-Language Voice-Clone TTS Reduces Model Size by 73%

The significant reduction in model size for a 24-language voice-clone TTS model enhances accessibility and reduces computational overhead, particularly for local deployment on Apple Silicon. This development lowers the barrier to entry for high-quality, multilingual AI voice generation in applications such as dubbing, content creation, and accessibility tools. The industry will be watching how this improved efficiency translates into wider adoption and new use cases for on-device TTS capabilities.

The availability of MLX-optimized TTS models like dots.tts-mlx highlights a growing trend in local AI inference on Apple Silicon. Several other projects are also leveraging MLX for speech synthesis and processing. For instance, appautomaton/mlx-speech provides local speech synthesis on Apple Silicon for TTS, voice cloning, and dialogue, supporting various models like MossTTSLocal and VibeVoice (GitHub, March 2026). Similarly, louiscoetzee/mlx-tts-studio is a native macOS app for high-quality TTS using Qwen3-TTS models, offering voice cloning and design features entirely on-device (GitHub, February 2026). Furthermore, the mlx-tts-server project offers an OpenAI-compatible Text-to-Speech server for Apple Silicon, powered by Qwen3-TTS and MLX, indicating a move towards standardized API access for local models (PyPI, March 2026). These parallel developments underscore increased developer focus on maximizing the on-device AI capabilities of Apple hardware, reducing reliance on cloud-based solutions and potentially improving privacy and latency for real-time streaming applications.