| --- |
| license: apache-2.0 |
| pipeline_tag: text-to-speech |
| library_name: ZONOS2 |
| --- |
| |
| # ZONOS2 |
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|
| <p align="center"> |
| <img src="./assets/ZONOS2BlogThumbnail.png" alt="ZONOS2 title card" width="750" /> |
| </p> |
|
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| <div align="center"> |
| <a href="https://discord.gg/gTW9JwST8q" target="_blank"> |
| <img src="https://img.shields.io/badge/Join%20Our%20Discord-7289DA?style=for-the-badge&logo=discord&logoColor=white" alt="Discord"> |
| </a> |
| </div> |
| |
| --- |
|
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|
| ZONOS2 is our latest text-to-speech model trained on more than 6 million hours of varied multilingual speech, delivering expressiveness and quality on par with—or even surpassing—top TTS providers at low latency with MoE. ZONOS2 excels at high-fidelity and naturalistic voice cloning. |
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| During inference we use nemo TN normalized UTF-8 bytes and an ECAPA-TDNN embedding to generate DAC tokens with our MoE backbone. An inference overview can be seen below. |
| <p align="center"> |
| <img src="./assets/zonos2_arlooop_animated.gif" alt="ZONOS2 title card" width="750" /> |
| </p> |
|
|
| Language support is as follows. |
| | Tier | Languages | |
| | ------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | |
| | Tier 1 | English, Mandarin Chinese, Japanese | |
| | Tier 2 | Korean, Russian, Italian, Portuguese, French, Spanish, Vietnamese, German, Hebrew, Dutch | |
| | Tier 3 | Swedish, Hindi, Tamil, Telugu, Thai, Norwegian, Bengali, Tagalog, Arabic, Danish, Indonesian, Polish, Ukrainian, Romanian, Finnish, Hungarian, Lithuanian, Estonian, Slovak, Croatian, Latvian | |
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| For local inference we provide a high-performance TTS inference server built on [Mini-SGLang](https://github.com/sgl-project/mini-sglang). |
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| **For more details and speech samples, check out our [blog](https://www.zyphra.com/our-work/zonos2).** |
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| **We also have a hosted version available at [cloud.zyphra.com/audio-playground](https://cloud.zyphra.com/audio-playground).** |
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| --- |
|
|
| ## Quick Start |
|
|
| > **Platform Support**: Linux only (x86_64). Requires NVIDIA GPU with CUDA toolkit matching your driver version (`nvidia-smi` to check). |
| |
| ### 1. Installation |
| |
| Requires [uv](https://docs.astral.sh/uv/getting-started/installation/). |
| |
| ```bash |
| git clone https://github.com/Zyphra/ZONOS2.git |
| cd ZONOS2 |
| uv sync |
| ``` |
| |
| ### 2. Launch the TTS Server |
| |
| ```bash |
| uv run python -m minisgl --model-path Zyphra/ZONOS2 --tts-default-voices-dir ./default_voices/ |
| ``` |
| |
| `uv run` always uses the project environment, so no venv activation is needed. |
| |
| The server starts on `http://localhost:1919` by default. TTS mode is auto-detected for zonos2 models. |
| `--tts-default-voices-dir <folder>` pre-populates the web UI with voice-clone |
| speakers from disk; the folder is scanned recursively for speaker audio |
| (`.wav`, `.mp3`, `.flac`, `.m4a`, `.ogg`, `.opus`, `.aac`, `.webm`) and saved |
| embeddings (`.npy`, `.npz`). The newest voice is selected automatically on |
| startup. |
| |
| ### 3. Generate Speech |
| |
| **curl:** |
| |
| ```bash |
| curl -X POST http://localhost:1919/tts/generate \ |
| -H "Content-Type: application/json" \ |
| -d '{"text": "Hello world", "stream": true}' \ |
| --output output.pcm |
|
|
| # Convert to WAV |
| ffmpeg -f f32le -ar 44100 -ac 1 -i output.pcm output.wav |
| ``` |
| |
| **Web UI:** Open `http://localhost:1919/` in your browser. |
| |
| ## Python API (offline inference) |
| |
| You can also run the engine directly in a Python script, without starting a |
| server, via `TTSLLM`: |
| |
| ```python |
| from minisgl.message import TTSSamplingParams |
| from minisgl.tts import TTSLLM |
|
|
| tts = TTSLLM(model_path="Zyphra/ZONOS2") |
| |
| results = tts.generate( |
| ["Hello from the offline Python API.", "Batched prompts work too."], |
| TTSSamplingParams(seed=42), |
| ) |
| |
| for i, result in enumerate(results): |
| print(f"frames={len(result['audio_tokens'])}, eos_frame={result['eos_frame']}") |
| tts.save_audio(result["audio"], f"output_{i}.wav") |
| ``` |
| |
|
|
| ## Citation |
| If you find this model useful in an academic context please cite as: |
| ``` |
| @misc{zyphra2025zonos, |
| title = {Zonos V2 Technical Report}, |
| author = {Gabriel Clark, Sofian Mejjoute, Mohamed Osman, George Close, Beren Millidge}, |
| year = {2026}, |
| } |
| ``` |
|
|
