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Audio8 Open Weight TTS 600M

Edge0-AI released Audio8-TTS-Realistic-0.6B, an open-weight text-to-speech model that keeps the 0.6B architecture and zero-shot voice cloning of Audio8-TTS-Preview while adding 12 languages for 23 total, including Arabic, Hindi, Portuguese, Russian and Vietnamese. On the Seed-TTS benchmark the Realistic model posts 1.25% error for English and Chinese versus 1.23% for Preview, with speaker similarity rising to 0.704 from 0.682, and it records 4.56% error on the 8-language CV3 subset and 5.89% across 24 MiniMax languages. The model is published on Hugging Face with a Python 3.10+ inference script, but no Realistic ONNX export exists yet.

read3 min views4 publishedOct 30, 2026
Audio8 Open Weight TTS 600M
Image: Michielbdejong (auto-discovered)

0.6B family #

Audio8-TTS-Realistic-0.6B builds on Preview with substantially improved speech realism, retaining the same compact 0.6B architecture and zero-shot voice cloning. It supports 23 languages, adding 12 languages compared with Preview.

Audio8 is also participating in TTS Arena, where it has received encouraging ratings from listeners. We are grateful to everyone who has listened and voted.

Release Focus and languages Model Listen Guide
Realistic 0.6B Realism and prosody Β· 23 languages HF Demo Details

ONNX: There is currently no Realistic ONNX export.

0.6B details: languages, quick start, and evaluation #

Coverage Languages
11 languages supported in Preview Cantonese, Chinese, Dutch, English, French, German, Italian, Japanese, Korean, Polish, Spanish
12 additions in Realistic Arabic, Finnish, Hindi, Indonesian, Malay, Norwegian, Portuguese, Russian, Swedish, Thai, Turkish, Vietnamese

Note: Quality varies by language; benchmark coverage differs from the supported-language list. Per-language results.

Use Python 3.10+ and a CUDA-capable GPU. Run from the repository root. The explicit model ID selects Realistic independently of the scripts' existing Preview default.

git clone https://github.com/Edge0-AI/Audio8_TTS.git
cd Audio8_TTS
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

python audio8_tts_infer.py \
  --model Edge0/Audio8-TTS-Realistic-0.6b \
  --text "Welcome to Audio8 TTS. It is wonderful to hear from you." \
  --output outputs/realistic.wav

For voice cloning, add --reference-audio reference.wav --reference-text "The exact transcript of the recording.".

Installation, cloning and batch inference Β· Supervised fine-tuning

Error rates are percentages (lower is better). SIM uses a 0–1 scale (higher is better). Neither directly measures speech realism.

Audio8-TTS-Preview and Audio8-TTS-Realistic, both 0.6B:

Benchmark Coverage Preview error % ↓ Realistic error % ↓ Preview SIM ↑ Realistic SIM ↑
Seed-TTS English / Chinese 1.23 1.25 0.682 0.704
CV3 8 shared languages 4.80 4.56 β€” 0.663
CV3 9 core languages β€” 4.86 β€” 0.661
MiniMax 24 evaluated languages β€” 5.89 β€” 0.754

Note: Values are unweighted language macro averages. Preview results are calculated from its published model card, with SIM converted from percentages to a 0–1 scale. The two releases were evaluated separately. A dash means the corresponding result was not reported on Preview's card.

Seed-TTS averages English WER and Chinese CER, excluding hard Chinese. The shared CV3 subset is Chinese, English, Japanese, Korean, German, French, Spanish, and Italian; the 9-language set also includes Russian. CV3 averages exclude hard subsets and the 13 additional languages. MiniMax averages all 24 evaluated languages, including languages outside the supported list.

Full Realistic evaluation and comparison notes Β· Original Preview evaluation

0.1B family #

Meet Audio8-TTS-0.1B: a compact, portable text-to-speech model with zero-shot voice cloning.

Designed for a smaller deployment footprint, with Chinese and English as its primary languages. The dedicated ONNX INT8 runtime supports CPU inference, streaming, and local web/HTTP serving.

Release Focus and languages Model Listen Guide
Preview 0.1B Compact hybrid Β· primarily Chinese / English HF Demo Details

0.1B quick start Β· CPU / ONNX runtime Β· 0.1B deployment Β· Model license

Installation and inference Β· Supervised fine-tuning

The shared tools accept an explicit model ID. Use the quick-start and deployment instructions for your chosen release.

SGLang Omni provides paged attention, dynamic batching, and an OpenAI-compatible speech API. The 0.6B family and the 0.1B hybrid model have their own configurations. Existing performance results remain paired with their original model, hardware, and test conditions in the deployment guide.

Deployment matrix, installation and server configuration Β· API, streaming and troubleshooting

The repository code and both 0.6B releases use Apache License 2.0. The 0.1B checkpoint has its own model license; consult the license packaged with each model/export. See NOTICE for attribution. We thank the Fish Audio team for the DualAR architecture used in Fish Audio S2 Pro.

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