Audio8-TTS-Realistic 0.6B vs VieNeu-TTS v3 Turbo

Audio8-TTS-Realistic 0.6B

A small local voice-cloning cousin for 23 languages under Apache 2.0, cloning from one clip and its exact transcript. It needs about 3 GB on a CUDA GPU through Transformers with Edge0's remote code, or Edge0's SGLang Omni plugin for a speech endpoint. The main risks are remote code and a pickled codec, and no independent benchmark yet.

VieNeu-TTS v3 Turbo

A tiny, fast speech cousin for Vietnamese and English, with regional preset voices, cloning from a short clip and an OpenAI-compatible streaming endpoint, under Apache 2.0. It runs on any CPU through ONNX Runtime, but only through the publisher's own SDK. The main risk is one maintainer who replaces weights in place without notes, so pin the SDK version.

Audio8-TTS-Realistic 0.6B

1. Pin transformers>=4.57.0,<5; Transformers 5 can produce all-zero codes with this custom code
2. Load with AutoProcessor.from_pretrained('Edge0/Audio8-TTS-Realistic-0.6b', trust_remote_code=True) and AutoModel.from_pretrained(..., trust_remote_code=True, dtype=torch.bfloat16); review the four .py files first
3. Clone with processor(text=[...], reference_audio=['ref.wav'], reference_text=['exact transcript'], return_tensors='pt'); a transcript that doesn't match the clip lowers stability
4. Decode with model.decode_audio(output.codes) and write at model.config.codec_sample_rate (44,100 Hz)
5. Split long text into short utterances; reference, transcript and text share 2,048 positions
6. For an HTTP endpoint, install Edge0's SGLang Omni adapter at the pinned SGLang Omni 0.1.0 and call /v1/audio/speech; start the server with AUDIO8_TTS_STREAM_ENABLED=1 for streaming
7. Only clone a voice you have permission to use, and disclose synthetic audio

VieNeu-TTS v3 Turbo

1. On CPU, pip install vieneu, then from vieneu import Vieneu; tts = Vieneu(); tts.save(tts.infer(text, voice='Mai Anh'), 'out.wav'); Vieneu(precision='int8') is about twice as fast on a CPU with VNNI
2. On GPU, install torch 2.8 for CUDA 12.8 and transformers 4.57.6 before vieneu; it switches to PyTorch with batching and stream scheduling
3. Serve with uv run python -m apps.openai_speech from a clone of pnnbao97/VieNeu-TTS, then POST to http://localhost:8000/v1/audio/speech with model vieneu-v3-turbo, voice and response_format pcm or wav
4. Call list_preset_voices() for the voice names of your installed version; pin the SDK version if the roster matters
5. Clone with ref_audio='voice.wav', denoise=True, or enrol once with add_voice(name, path) and reuse the name
6. Keep temperature near 0.8; the style argument is ignored on v3 Turbo
7. Only clone a voice you have the right to use