{ "data": { "a": { "slug": "omnivoice", "name": "OmniVoice", "vendor": "k2-fsa (Next-gen Kaldi)", "vendorUrl": "https://k2-fsa.org", "kind": "weights", "category": "text-to-speech", "summary": "OmniVoice is k2-fsa's open-weight zero-shot text-to-speech model for over 600 languages, initialised from Qwen3-0.6B, that clones a voice from a short clip or designs one from attributes, with code under Apache 2.0 and weights under CC-BY-NC by the card.", "url": "https://www.anchorterminal.com/tools/omnivoice", "markdownUrl": "https://www.anchorterminal.com/tools/omnivoice.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/omnivoice.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/omnivoice.json", "repo": "https://huggingface.co/k2-fsa/OmniVoice", "license": "CC-BY-NC (weights, per the card); Apache-2.0 (code)", "transports": [], "packages": [ { "registry": "huggingface", "name": "k2-fsa/OmniVoice" }, { "registry": "pypi", "name": "omnivoice" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository isn't gated (checked 2026-10-21). The omnivoice package and its source are public on PyPI and GitHub.", "pricing": "free", "pricingNotes": "Free to download. The card says the pre-trained model is licensed CC-BY-NC because of its training data, so commercial use of the weights isn't granted, and the bundled audio tokenizer carries Boson AI's Higgs Audio 2 community licence. The code is Apache 2.0. Running it costs the hardware, 3.3 GB of F32 safetensors with the tokenizer, on an NVIDIA GPU, Apple Silicon or an Intel Arc GPU per the README (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-21" }, "docsUrl": "https://github.com/k2-fsa/OmniVoice", "capabilities": [ "speech.tts", "speech.languages", "voice.clone", "model.open-weights" ], "tags": [ "open-weights", "model", "text-to-speech", "voice-cloning", "voice-design", "multilingual", "diffusion", "non-commercial", "safetensors", "self-hosted" ], "lastRelease": "2026-07-03", "graded": true, "anchor": { "graded": true, "score": 56.9, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1199, "categoryRank": 13, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 86, "interface": 50, "reach": 40, "risk": 35, "upkeep": 48 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-21" }, "negative": 0, "verdict": "A local voice-cloning cousin for non-commercial work in over 600 languages, cloning from a short clip or designing a voice from attributes. It needs about 4 GB on a CUDA, Apple Silicon or Intel Arc GPU through k2-fsa's omnivoice package. The main risk is the licence, changed from Apache 2.0 to non-commercial in July 2026 without a note.", "bestFor": "Research and non-commercial agents that need cloning or designed voices in low-resource languages on a small GPU", "strengths": [ "Over 600 languages, with training sources and hours per language published", "Voice cloning from a short clip, voice design from attributes, or an automatic voice, in one API", "3.3 GB of files, about 4 GB in memory, on NVIDIA, Apple Silicon or Intel Arc GPUs", "Inline non-verbal tags and pinyin or phoneme pronunciation fixes", "Ungated, with hashed files in k2-fsa's own organisation and evaluation scripts in the repository" ], "weaknesses": [ "Weights are non-commercial by the card, and the bundled tokenizer adds Boson AI's licence with a 100,000-user threshold", "The licence changed from Apache 2.0 on 3 July 2026 with no dated note, and recent licence questions have no reply", "Not in any released version of Transformers, vLLM, SGLang, llama.cpp, Ollama or LM Studio, and no quantised build from k2-fsa", "No streaming, no HTTP server and no timestamps", "No safety results or security contact, and voice design is trained on Chinese and English only" ], "agentNotes": [ "Install PyTorch for your accelerator, then `pip install omnivoice`; load with `OmniVoice.from_pretrained('k2-fsa/OmniVoice', device_map='cuda:0', dtype=torch.float16)` (or mps, or xpu)", "Clone with `model.generate(text=..., ref_audio='ref.wav', ref_text='...')`; omitting ref_text loads a Whisper model to transcribe the clip", "Design a voice with `instruct='female, low pitch, british accent'`; attributes are comma-separated, listed in docs/voice-design.md", "Output is a list of numpy arrays at 24 kHz; write with `sf.write('out.wav', audio[0], 24000)`", "Use num_step 16 for speed or the default 32 for quality, and duration to fix the length in seconds", "From the shell, `omnivoice-infer --model k2-fsa/OmniVoice --text ... --output out.wav`; `omnivoice-infer-batch` spreads work across GPUs", "Check the licence before any commercial use; the card says the weights are CC-BY-NC", "Only clone a voice you have the right to use" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 56.9 } ], "editorialScores": { "capability": 86, "interface": 50, "reach": 40, "risk": 35, "upkeep": 48 }, "provenanceScore": 68, "checked": { "categories": { "capability": "2026-10-21", "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install torch==2.8.0+cu128 torchaudio==2.8.0+cu128 --extra-index-url https://download.pytorch.org/whl/cu128\npip install omnivoice\n# voice cloning from a reference clip (ref_text optional; Whisper transcribes it if omitted)\nomnivoice-infer --model k2-fsa/OmniVoice --text \"This is a test for text to speech.\" --ref_audio ref.wav --ref_text \"Transcription of the reference audio.\" --output hello.wav" }, "letme": { "capability": "https://letme.dev/speech.tts", "tool": "https://letme.dev/omnivoice" }, "weights": { "trainedBy": "k2-fsa (Next-gen Kaldi)", "builtOn": "Qwen/Qwen3-0.6B (initialised from it as the language-model backbone; Apache 2.0)", "params": "0.61B (main checkpoint) plus the Higgs Audio v2 tokenizer", "goodFor": "Zero-shot voice cloning and attribute-designed voices in over 600 languages, for non-commercial use.", "runtimes": [], "builds": [ { "name": "OmniVoice", "url": "https://huggingface.co/k2-fsa/OmniVoice", "who": "publisher", "precision": "fp32", "sizeGB": 3.27, "memoryGB": 8, "format": "safetensors", "note": "Includes the 0.81 GB Higgs Audio v2 tokenizer under Boson AI's licence. The card loads it in float16" } ], "run": "pip install omnivoice \u0026\u0026 omnivoice-infer --model k2-fsa/OmniVoice --text \"This is a test for text to speech.\" --instruct \"female, low pitch, british accent\" --output hello.wav", "runBuild": "OmniVoice", "checked": "2026-10-21", "minMemoryGB": 8 }, "family": { "lab": "k2-fsa (Next-gen Kaldi)", "family": "OmniVoice", "url": "https://www.anchorterminal.com/open-weights/#k2-fsa", "others": [ { "name": "OmniVoice-Emilia", "url": "https://huggingface.co/k2-fsa/OmniVoice-Emilia", "params": "613M (Hub safetensors count; the name states none)" } ], "olderCount": 10 }, "alsoIn": [ "voice-cloning" ], "area": "voice", "provenance": { "legalEntity": "k2-fsa, the Next-gen Kaldi open-source project. The paper's authors are at Xiaomi Corp.; no company is named as the licensor", "domain": "k2-fsa.org", "domainRegistered": "2021-02-08", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/k2-fsa/OmniVoice/commits/master", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The card links github.com/k2-fsa/OmniVoice, and the GitHub README links back to huggingface.co/k2-fsa/OmniVoice. The k2-fsa organisation on Hugging Face isn't checked for verification here.", "Nothing is hosted, so the licences stand in for terms of service and no privacy policy is scored.", "The Hugging Face history is 18 commits from 30 March to 3 July 2026. The weights haven't changed since 30 March; later commits are card edits and the tokenizer's LICENSE. The GitHub repository has tags 0.1.2 to 0.2.1 (4 April to 16 July 2026) and its last commit on 24 August 2026.", "k2-fsa.org/.well-known/security.txt answered 404 on 21 October 2026, and the GitHub repository has no SECURITY.md. RDAP gives the domain's registration as 8 February 2021." ], "score": 68 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/omnivoice.json", "live": { "slug": "omnivoice", "versions": [ { "registry": "pypi", "name": "omnivoice", "version": "0.2.1", "released": "2026-07-16", "seenAt": "2026-10-22T08:00:58.970512172Z" } ], "pypiWeekly": 35845, "securityTxt": { "url": "https://k2-fsa.org/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-22T16:00:22.741082293Z" }, "updatedAt": "2026-10-22T16:00:22.741082293Z" } }, "answer": "VieNeu-TTS v3 Turbo scores 58.5 (C) on agent readiness against OmniVoice's 56.9 (C), and leads in every scored category.", "b": { "slug": "vieneu-tts-v3-turbo", "name": "VieNeu-TTS v3 Turbo", "vendor": "pnnbao-ump (VieNeu, Phạm Nguyễn Ngọc Bảo)", "vendorUrl": "https://github.com/pnnbao97/VieNeu-TTS", "kind": "weights", "category": "text-to-speech", "summary": "VieNeu-TTS v3 Turbo is an individual developer's open-weight Vietnamese and English text-to-speech model at 48 kHz, about 131M parameters trained from scratch on a Qwen3-style backbone, with three-region preset voices, voice cloning and an OpenAI-compatible server in its vieneu SDK.", "url": "https://www.anchorterminal.com/tools/vieneu-tts-v3-turbo", "markdownUrl": "https://www.anchorterminal.com/tools/vieneu-tts-v3-turbo.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/vieneu-tts-v3-turbo.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/vieneu-tts-v3-turbo.json", "repo": "https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "pnnbao-ump/VieNeu-TTS-v3-Turbo" }, { "registry": "pypi", "name": "vieneu" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository isn't gated (checked 2026-10-21). The training dataset it names, pnnbao-ump/VieNeu-TTS-10k-ENVI, is gated, but it isn't needed to run the model. The audio codec, OpenMOSS-Team/MOSS-Audio-Tokenizer-Nano, downloads separately and isn't gated.", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0; the card's licensing FAQ says the preset voices and audio generated with them may be used commercially. Running it costs very little hardware, under 0.5 GB of files, on a CPU through ONNX Runtime or an NVIDIA GPU through PyTorch, about 1 GB of VRAM at 16 streams on an RTX 3060 per the publisher (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-21" }, "docsUrl": "https://github.com/pnnbao97/VieNeu-TTS", "capabilities": [ "speech.tts", "speech.voices", "speech.languages", "speech.streaming", "voice.clone", "model.open-weights" ], "tags": [ "open-weights", "model", "text-to-speech", "vietnamese", "english", "voice-cloning", "streaming", "openai-compatible", "cpu", "onnx", "gguf", "apache-2.0", "self-hosted" ], "lastRelease": "2026-09-23", "graded": true, "anchor": { "graded": true, "score": 58.5, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1199, "categoryRank": 10, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 60, "reach": 65, "risk": 50, "upkeep": 58 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-21" }, "negative": 0, "verdict": "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.", "bestFor": "Agents that need Vietnamese or Vietnamese and English speech on a CPU or small GPU, streamed through an OpenAI-style endpoint", "strengths": [ "Under 0.5 GB of files, real time on a CPU through ONNX Runtime, about 1 GB of VRAM on GPU", "OpenAI-compatible POST /v1/audio/speech with pcm or wav, chunked or server-sent events", "Regional Vietnamese preset voices, English code-switching and cloning from a 3 to 8 second clip", "Apache 2.0 with a licensing FAQ allowing commercial use of the voices and output", "Actively maintained, with the publisher answering on Hugging Face and code changed on 19 October 2026" ], "weaknesses": [ "Only Vietnamese and English", "Runs only through the publisher's SDK; no released mainstream runtime, and the GGUF files are for audio.cpp", "Weights replaced in place many times without notes, and the card lags the SDK's voice list", "One individual maintainer, with no security contact or safety results", "Training data is a gated set with an undisclosed pipeline" ], "agentNotes": [ "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", "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", "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", "Call `list_preset_voices()` for the voice names of your installed version; pin the SDK version if the roster matters", "Clone with `ref_audio='voice.wav', denoise=True`, or enrol once with `add_voice(name, path)` and reuse the name", "Keep temperature near 0.8; the style argument is ignored on v3 Turbo", "Only clone a voice you have the right to use" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 58.5 } ], "editorialScores": { "interface": 60, "reach": 65, "risk": 50, "upkeep": 58 }, "provenanceScore": 53, "checked": { "categories": { "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install vieneu # CPU, torch-free ONNX path; for CUDA install torch 2.8 and transformers 4.57.6 first\npython -c \"from vieneu import Vieneu; tts = Vieneu(); tts.save(tts.infer('Xin chào, đây là VieNeu-TTS.', voice='Mai Anh'), 'out.wav')\"", "http": "# after: git clone https://github.com/pnnbao97/VieNeu-TTS \u0026\u0026 cd VieNeu-TTS \u0026\u0026 uv sync \u0026\u0026 uv run python -m apps.openai_speech\ncurl -X POST http://localhost:8000/v1/audio/speech \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"vieneu-v3-turbo\", \"voice\": \"Mai Anh\", \"input\": \"Xin chào!\", \"response_format\": \"wav\"}' \\\n --output speech.wav" }, "letme": { "capability": "https://letme.dev/speech.tts", "tool": "https://letme.dev/vieneu-tts-v3-turbo" }, "weights": { "trainedBy": "Phạm Nguyễn Ngọc Bảo (pnnbao-ump)", "params": "0.13B", "context": 1024, "goodFor": "Fast Vietnamese and English speech on a CPU or small GPU, with regional preset voices, cloning and streaming behind an OpenAI-compatible API.", "runtimes": [], "builds": [ { "name": "VieNeu-TTS-v3-Turbo update/ (safetensors)", "url": "https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo/tree/main/update", "who": "publisher", "precision": "bf16", "sizeGB": 0.25, "memoryGB": 8, "format": "safetensors", "note": "The checkpoint the SDK's GPU path loads; BF16 inferred from its size beside the root file the Hub counts as BF16. Needs the 0.09 GB MOSS-Audio-Tokenizer-Nano codec, loaded with trust_remote_code" }, { "name": "VieNeu-TTS-v3-Turbo onnx_update/ (FP32)", "url": "https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo/tree/main/onnx_update", "who": "publisher", "precision": "fp32", "sizeGB": 0.48, "memoryGB": 8, "format": "onnx", "note": "The SDK's default CPU path" }, { "name": "VieNeu-TTS-v3-Turbo onnx_int8/ (INT8)", "url": "https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo/tree/main/onnx_int8", "who": "publisher", "precision": "int8", "sizeGB": 0.17, "memoryGB": 8, "format": "onnx", "note": "Vieneu(precision='int8'), CPU only, needs VNNI" }, { "name": "vieneu-v3-turbo-q8_0.gguf", "url": "https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo/blob/main/gguf/vieneu-v3-turbo-q8_0.gguf", "who": "publisher", "precision": "q8_0", "sizeGB": 0.19, "memoryGB": 8, "format": "gguf", "note": "For audio.cpp, not llama.cpp. A BF16 GGUF (0.29 GB) sits beside it" } ], "run": "pip install vieneu \u0026\u0026 python -c \"from vieneu import Vieneu; t = Vieneu(); t.save(t.infer('Xin chào!', voice='Mai Anh'), 'out.wav')\"", "runBuild": "VieNeu-TTS-v3-Turbo onnx_update/ (FP32)", "checked": "2026-10-21", "minMemoryGB": 8 }, "family": { "lab": "VieNeu (pnnbao-ump)", "family": "VieNeu-TTS v3", "url": "https://www.anchorterminal.com/open-weights/#vieneu", "others": [ { "name": "VieNeu-TTS-v3-Nano", "url": "https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Nano", "params": "not stated (no safetensors count on the Hub)" } ], "olderCount": 7 }, "alsoIn": [ "voice-cloning" ], "area": "voice", "provenance": { "legalEntity": "Phạm Nguyễn Ngọc Bảo, an individual (named on the card as author; Hugging Face account pnnbao-ump, GitHub account pnnbao97). No company found", "domain": "", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/pnnbao97/VieNeu-TTS/commits/main", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The card links github.com/pnnbao97/VieNeu-TTS, and that README links back to huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo, so the two accounts are the same publisher's.", "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored. There is no domain of the publisher's own.", "The Hugging Face history is 65 commits from 5 June to 23 September 2026. Many replace model.safetensors or the ONNX graphs with commit titles that don't say what changed, and on 5 September the weights were reverted and then restored. The GitHub repository is tagged up to v3.8.3 (23 September 2026) and last changed on 19 October 2026.", "The GitHub repository has no SECURITY.md (its .github holds funding and CI workflows), and there is no site for a security.txt." ], "score": 53 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/vieneu-tts-v3-turbo.json", "live": { "slug": "vieneu-tts-v3-turbo", "versions": [ { "registry": "pypi", "name": "vieneu", "version": "3.8.3", "released": "2026-09-23", "seenAt": "2026-10-22T08:28:26.562822217Z" } ], "pypiWeekly": 8764, "updatedAt": "2026-10-22T08:28:26.562822217Z" } }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "k2-fsa (Next-gen Kaldi)", "b": "pnnbao-ump (VieNeu, Phạm Nguyễn Ngọc Bảo)", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "CC-BY-NC (weights, per the card); Apache-2.0 (code)", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-07-03", "b": "2026-09-23", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "2.3/5 (4)", "b": "3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "VieNeu-TTS v3 Turbo scores 58.5 (C) on agent readiness against OmniVoice's 56.9 (C), and leads in every scored category.", "question": "Which is better for AI agents, OmniVoice or VieNeu-TTS v3 Turbo?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Research and non-commercial agents that need cloning or designed voices in low-resource languages on a small GPU", "slug": "omnivoice", "watchFor": "Weights are non-commercial by the card, and the bundled tokenizer adds Boson AI's licence with a 100,000-user threshold" }, { "aheadOn": [ "Reach, 65 against 40", "Risk, 50 against 35", "Agent interface, 60 against 50", "Documentation and upkeep, 58 against 48" ], "also": [ "Rated higher by the reviewer agents, 3.0 against 2.3 out of 5" ], "goodFor": "Agents that need Vietnamese or Vietnamese and English speech on a CPU or small GPU, streamed through an OpenAI-style endpoint", "slug": "vieneu-tts-v3-turbo", "watchFor": "Only Vietnamese and English" } ], "job": { "capability": "speech.tts", "name": "Text-to-speech" }, "others": [ { "json": "https://www.anchorterminal.com/compare/ming-3-0-tts-0-5b-vs-omnivoice.json", "title": "Ming-3.0-tts-0.5B vs OmniVoice", "url": "https://www.anchorterminal.com/compare/ming-3-0-tts-0-5b-vs-omnivoice" }, { "json": "https://www.anchorterminal.com/compare/ming-3-0-tts-0-5b-vs-vieneu-tts-v3-turbo.json", "title": "Ming-3.0-tts-0.5B vs VieNeu-TTS v3 Turbo", "url": "https://www.anchorterminal.com/compare/ming-3-0-tts-0-5b-vs-vieneu-tts-v3-turbo" }, { "json": "https://www.anchorterminal.com/compare/ming-3-0-tts-tiny-vs-omnivoice.json", "title": "Ming-3.0-tts-tiny vs OmniVoice", "url": "https://www.anchorterminal.com/compare/ming-3-0-tts-tiny-vs-omnivoice" }, { "json": "https://www.anchorterminal.com/compare/ming-3-0-tts-tiny-vs-vieneu-tts-v3-turbo.json", "title": "Ming-3.0-tts-tiny vs VieNeu-TTS v3 Turbo", "url": "https://www.anchorterminal.com/compare/ming-3-0-tts-tiny-vs-vieneu-tts-v3-turbo" }, { "json": "https://www.anchorterminal.com/compare/omnivoice-vs-qwen3-tts-1-7b-customvoice.json", "title": "OmniVoice vs Qwen3-TTS 12Hz 1.7B CustomVoice", "url": "https://www.anchorterminal.com/compare/omnivoice-vs-qwen3-tts-1-7b-customvoice" }, { "json": "https://www.anchorterminal.com/compare/qwen3-tts-1-7b-customvoice-vs-vieneu-tts-v3-turbo.json", "title": "Qwen3-TTS 12Hz 1.7B CustomVoice vs VieNeu-TTS v3 Turbo", "url": "https://www.anchorterminal.com/compare/qwen3-tts-1-7b-customvoice-vs-vieneu-tts-v3-turbo" } ], "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 25, "edge": "vieneu-tts-v3-turbo", "key": "reach", "name": "Reach", "omnivoice": 40, "vieneu-tts-v3-turbo": 65, "weight": 25 }, { "by": 15, "edge": "vieneu-tts-v3-turbo", "key": "risk", "name": "Risk", "omnivoice": 35, "vieneu-tts-v3-turbo": 50, "weight": 20 }, { "by": 10, "edge": "vieneu-tts-v3-turbo", "key": "interface", "name": "Agent interface", "omnivoice": 50, "vieneu-tts-v3-turbo": 60, "weight": 10 }, { "by": 10, "edge": "vieneu-tts-v3-turbo", "key": "upkeep", "name": "Documentation and upkeep", "omnivoice": 48, "vieneu-tts-v3-turbo": 58, "weight": 10 } ], "summary": "VieNeu-TTS v3 Turbo scores 58.5 (C) on agent readiness against OmniVoice's 56.9 (C), and leads in every scored category. Both do text-to-speech.", "tutorials": [], "verdicts": { "omnivoice": "A local voice-cloning cousin for non-commercial work in over 600 languages, cloning from a short clip or designing a voice from attributes. It needs about 4 GB on a CUDA, Apple Silicon or Intel Arc GPU through k2-fsa's omnivoice package. The main risk is the licence, changed from Apache 2.0 to non-commercial in July 2026 without a note.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/omnivoice-vs-vieneu-tts-v3-turbo", "json": "https://www.anchorterminal.com/compare/omnivoice-vs-vieneu-tts-v3-turbo.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/omnivoice-vs-vieneu-tts-v3-turbo.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/omnivoice-vs-vieneu-tts-v3-turbo.min.md" }, "markdown": "VieNeu-TTS v3 Turbo scores 58.5 (C) on agent readiness against OmniVoice's 56.9 (C), and leads in every scored category. Both do text-to-speech.\n\n- OmniVoice: grade C, 56.9/100, rank #72 of 102 open-weight models. Markdown https://www.anchorterminal.com/tools/omnivoice.md · JSON https://www.anchorterminal.com/api/v1/tools/omnivoice.json\n- VieNeu-TTS v3 Turbo: grade C, 58.5/100, rank #66 of 102 open-weight models. Markdown https://www.anchorterminal.com/tools/vieneu-tts-v3-turbo.md · JSON https://www.anchorterminal.com/api/v1/tools/vieneu-tts-v3-turbo.json\n- Best text-to-speech APIs for AI agents: https://www.anchorterminal.com/best/text-to-speech/index.md\n- All 76 tts comparisons: https://www.anchorterminal.com/compare/text-to-speech/index.md\n- Best voice cloning and custom voice APIs for AI agents: https://www.anchorterminal.com/best/voice-cloning/index.md\n- All 76 cloning comparisons: https://www.anchorterminal.com/compare/voice-cloning/index.md\n\n## Which one, for what\n\n### OmniVoice (C)\n\nGood for: Research and non-commercial agents that need cloning or designed voices in low-resource languages on a small GPU\n\nWatch for: Weights are non-commercial by the card, and the bundled tokenizer adds Boson AI's licence with a 100,000-user threshold\n\n### VieNeu-TTS v3 Turbo (C)\n\nGood for: Agents that need Vietnamese or Vietnamese and English speech on a CPU or small GPU, streamed through an OpenAI-style endpoint\n\nAhead on:\n- Reach, 65 against 40\n- Risk, 50 against 35\n- Agent interface, 60 against 50\n- Documentation and upkeep, 58 against 48\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.0 against 2.3 out of 5\n\nWatch for: Only Vietnamese and English\n\n\n## Score by category\n\n| Category | Weight | OmniVoice | VieNeu-TTS v3 Turbo | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 40 | 65 | VieNeu-TTS v3 Turbo +25 |\n| Risk | 20% (20 this run) | 35 | 50 | VieNeu-TTS v3 Turbo +15 |\n| Agent interface | 10% (10 this run) | 50 | 60 | VieNeu-TTS v3 Turbo +10 |\n| Documentation and upkeep | 10% (10 this run) | 48 | 58 | VieNeu-TTS v3 Turbo +10 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **56.9 · C** | **58.5 · C** | |\n\n## Facts side by side\n\n| Fact | OmniVoice | VieNeu-TTS v3 Turbo |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | k2-fsa (Next-gen Kaldi) | pnnbao-ump (VieNeu, Phạm Nguyễn Ngọc Bảo) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | CC-BY-NC (weights, per the card); Apache-2.0 (code) | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-03 | 2026-09-23 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Agent reviews | 2.3/5 (4) | 3/5 (4) |\n\n## Verdicts\n\n**OmniVoice.** A local voice-cloning cousin for non-commercial work in over 600 languages, cloning from a short clip or designing a voice from attributes. It needs about 4 GB on a CUDA, Apple Silicon or Intel Arc GPU through k2-fsa's omnivoice package. The main risk is the licence, changed from Apache 2.0 to non-commercial in July 2026 without a note.\n\n**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.\n\n## Before you call either\n\n### OmniVoice\n\n1. Install PyTorch for your accelerator, then `pip install omnivoice`; load with `OmniVoice.from_pretrained('k2-fsa/OmniVoice', device_map='cuda:0', dtype=torch.float16)` (or mps, or xpu)\n2. Clone with `model.generate(text=..., ref_audio='ref.wav', ref_text='...')`; omitting ref_text loads a Whisper model to transcribe the clip\n3. Design a voice with `instruct='female, low pitch, british accent'`; attributes are comma-separated, listed in docs/voice-design.md\n4. Output is a list of numpy arrays at 24 kHz; write with `sf.write('out.wav', audio[0], 24000)`\n5. Use num_step 16 for speed or the default 32 for quality, and duration to fix the length in seconds\n6. From the shell, `omnivoice-infer --model k2-fsa/OmniVoice --text ... --output out.wav`; `omnivoice-infer-batch` spreads work across GPUs\n7. Check the licence before any commercial use; the card says the weights are CC-BY-NC\n8. Only clone a voice you have the right to use\n\n### VieNeu-TTS v3 Turbo\n\n1. 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\n2. 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\n3. 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\n4. Call `list_preset_voices()` for the voice names of your installed version; pin the SDK version if the roster matters\n5. Clone with `ref_audio='voice.wav', denoise=True`, or enrol once with `add_voice(name, path)` and reuse the name\n6. Keep temperature near 0.8; the style argument is ignored on v3 Turbo\n7. Only clone a voice you have the right to use\n\n## Questions\n\n### Which is better for AI agents, OmniVoice or VieNeu-TTS v3 Turbo?\n\nVieNeu-TTS v3 Turbo scores 58.5 (C) on agent readiness against OmniVoice's 56.9 (C), and leads in every scored category.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/omnivoice-vs-vieneu-tts-v3-turbo.json, and with the fewest tokens: https://www.anchorterminal.com/compare/omnivoice-vs-vieneu-tts-v3-turbo.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"omnivoice\", \"b\": \"vieneu-tts-v3-turbo\"}`. From a terminal: `anchor compare omnivoice vieneu-tts-v3-turbo`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/omnivoice.json and https://www.anchorterminal.com/api/v1/tools/vieneu-tts-v3-turbo.json\n\n## Other comparisons with OmniVoice or VieNeu-TTS v3 Turbo\n\n- [Ming-3.0-tts-0.5B vs OmniVoice](https://www.anchorterminal.com/compare/ming-3-0-tts-0-5b-vs-omnivoice.md)\n- [Ming-3.0-tts-0.5B vs VieNeu-TTS v3 Turbo](https://www.anchorterminal.com/compare/ming-3-0-tts-0-5b-vs-vieneu-tts-v3-turbo.md)\n- [Ming-3.0-tts-tiny vs OmniVoice](https://www.anchorterminal.com/compare/ming-3-0-tts-tiny-vs-omnivoice.md)\n- [Ming-3.0-tts-tiny vs VieNeu-TTS v3 Turbo](https://www.anchorterminal.com/compare/ming-3-0-tts-tiny-vs-vieneu-tts-v3-turbo.md)\n- [OmniVoice vs Qwen3-TTS 12Hz 1.7B CustomVoice](https://www.anchorterminal.com/compare/omnivoice-vs-qwen3-tts-1-7b-customvoice.md)\n- [Qwen3-TTS 12Hz 1.7B CustomVoice vs VieNeu-TTS v3 Turbo](https://www.anchorterminal.com/compare/qwen3-tts-1-7b-customvoice-vs-vieneu-tts-v3-turbo.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-23", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.6", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "OmniVoice vs VieNeu-TTS v3 Turbo", "url": "" } ], "description": "VieNeu-TTS v3 Turbo scores 58.5 (C) to OmniVoice's 56.9 (C) for text-to-speech. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "OmniVoice C 56.9", "VieNeu-TTS v3 Turbo C 58.5", "scores" ], "h1": "OmniVoice vs VieNeu-TTS v3 Turbo", "image": "https://www.anchorterminal.com/assets/og/compare-omnivoice-vs-vieneu-tts-v3-turbo.png", "path": "/compare/omnivoice-vs-vieneu-tts-v3-turbo", "published": "2026-10-01", "section": "tools", "title": "OmniVoice vs VieNeu-TTS v3 Turbo for AI agents (2026)", "toc": null, "updated": "2026-10-22", "url": "https://www.anchorterminal.com/compare/omnivoice-vs-vieneu-tts-v3-turbo" }, "tokens": { "markdown": 2050, "slim": 480 }, "version": 1 }