Fish Audio Drama 3 vs VieNeu-TTS v3 Turbo

Fish Audio Drama 3

A local voice cousin for directed speech, multi-character scenes, voice cloning and word-level edits in about 80 languages. It needs an NVIDIA GPU, about 29 GB for the int4 build or at least 48 GB for FP8, through SGLang-Omni or fish-speech. The main risk is the licence, revocable, capped at USD 500,000 revenue for commercial use and barring hosted services.

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.

Fish Audio Drama 3

1. Install SGLang-Omni from source with uv pip install --prerelease=allow -e ".[fishaudio]", then sgl-omni serve --model-path fishaudio/drama-3-int4 --port 8000 (or fishaudio/drama-3 for FP8 on 48 GB or more)
2. POST JSON to /v1/audio/speech with input, optional references (audio_path and its transcript) and previous_takes; set response_format and stream for the output
3. Start each line with <|speaker:N|> (N from 0 to 15) for several voices, and separate lines with <|audio_separator|>
4. Direct with point tags like [sighs], scoped tags like <whisper>...</whisper>, a bracketed style prefix, or Direction: and Line: for a director's note
5. The int4 build needs compute capability 8.0 or newer; only the triton attention backend is accepted
6. Keep each reference clip under 60 seconds and the prompt under 8,192 rows, about 21.5 rows per second of reference audio
7. Check the licence before commercial use or exposing it to other users, and only clone voices with consent
8. Treat text from untrusted sources as a script that can carry directions and speaker tags

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