Zyphra Open-Sources ZONOS3-Mini TTS: 800M-Parameter MoE With 100M Active, Apache 2.0, Real-Time in a Phone Browser, Word-Level Delivery Control and Voice Cloning
Zyphra released ZONOS3-Mini, an open-source text-to-speech model, on November 9, with weights on Hugging Face under Apache 2.0. It is a sparse MoE with 800 million total and about 100 million active parameters per token, trained on 112 H100s in 2.5 days. By Zyphra's numbers, time to first audio is under 570 ms in the browser on a Pixel 9 and under 150 ms on an M3 MacBook Air, and it ranks first among open models on the capability index of its new ZTTS2-Eval benchmark (35 languages of read speech plus 20 in-the-wild), ahead of Fish S2 Pro and MOSS TTS v1.5. It supports voice cloning, age, accent and gender steering, and word-level delivery control, with WebGPU, SGLang, vLLM, GGML and MLX runtimes.
Key Takeaways
- Scale: 800M total, about 100M active parameters (64 experts, top-2 routing), versus 8B for the previous ZONOS2; open weights under Apache 2.0
- Speed (Zyphra figures): under 570 ms time to first audio in a Pixel 9 browser and under 150 ms on an M3 MacBook Air; 80 ms median at 8 concurrent requests and peak 457 seconds of audio per second on one H100
- The new ZAC-1 codec runs at 15 Hz versus 86 Hz for DAC and cuts word error rate about 10x under similar data; one generation can produce up to 10 minutes of 44.1 kHz audio
- Evaluation: ZTTS2-Eval covers 35 languages of read speech plus 20 in-the-wild; on its 420-item capability index ZONOS3-Mini ranks first among open models, followed by Fish S2 Pro and MOSS TTS v1.5 (Zyphra's own benchmark, not yet independently reproduced)
- Get started: try it in the browser via WebGPU with no install, or run
sgl-omni serve --model-path Zyphra/ZONOS3-Minifor an OpenAI-compatible /v1/audio/speech endpoint


