{ "data": { "a": { "slug": "audio8-tts-realistic-0-6b", "name": "Audio8-TTS-Realistic 0.6B", "vendor": "Edge0", "vendorUrl": "https://edge0.ai", "kind": "weights", "category": "text-to-speech", "summary": "Audio8-TTS-Realistic 0.6B is Edge0's open-weight text-to-speech model for 23 languages, a 0.6B dual-autoregressive model with a bundled 44.1 kHz codec that speaks with or without a reference voice cloned from one clip and its transcript.", "url": "https://www.anchorterminal.com/tools/audio8-tts-realistic-0-6b", "markdownUrl": "https://www.anchorterminal.com/tools/audio8-tts-realistic-0-6b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/audio8-tts-realistic-0-6b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/audio8-tts-realistic-0-6b.json", "repo": "https://huggingface.co/Edge0/Audio8-TTS-Realistic-0.6b", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "Edge0/Audio8-TTS-Realistic-0.6b" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository isn't gated (checked 2026-10-30). The inference, fine-tuning and SGLang Omni adapter code is public at github.com/Edge0-AI/Audio8_TTS.", "pricing": "free", "pricingNotes": "Free to download under Apache 2.0 for the code and the weights, by the card and the LICENSE file in both repositories. Running it costs the hardware, 2.57 GB of files (BF16 safetensors plus a pickled codec), on a CUDA GPU as the card recommends. Edge0 runs no paid API for it; the Hugging Face Playground runs on ZeroGPU with a daily allowance (checked 2026-10-30).", "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 2026-10-30).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-30" }, "docsUrl": "https://github.com/Edge0-AI/Audio8_TTS", "capabilities": [ "speech.tts", "speech.languages", "speech.streaming", "voice.clone", "model.open-weights" ], "tags": [ "open-weights", "model", "text-to-speech", "voice-cloning", "multilingual", "dual-ar", "custom-code", "safetensors", "self-hosted" ], "lastRelease": "2026-10-27", "graded": true, "anchor": { "graded": true, "score": 51.5, "grade": "D", "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": 1239, "categoryRank": 18, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 60, "reach": 55, "risk": 40, "upkeep": 57 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-30" }, "negative": 0, "verdict": "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.", "bestFor": "Agents that need multilingual voice cloning on a small CUDA GPU under a permissive licence, and can accept remote code", "strengths": [ "Apache 2.0 for code and weights, ungated, with no use policy or threshold", "2.57 GB of files, about 3.1 GB in memory, 601M parameters plus the codec", "23 languages with per-language error rates published, including the weak ones", "An OpenAI-compatible /v1/audio/speech service through Edge0's SGLang Omni plugin, with wav, pcm or codec-code output and opt-in streaming", "Fine-tuning scripts and inference code in Edge0's public GitHub repository" ], "weaknesses": [ "Loads only with trust_remote_code, and the codec ships as a 1.35 GB PyTorch pickle", "Not in any released version of Transformers, vLLM, SGLang, llama.cpp, Ollama or LM Studio, and no quantised build from Edge0", "No independent benchmark result; the card's numbers are Edge0's own, and the TTS Arena claim couldn't be checked", "A 2,048-position context shared by the reference, its transcript and the text, so long passages must be split", "No safety results, watermarking or security contact, for a model that clones a voice from one clip" ], "agentNotes": [ "Pin `transformers\u003e=4.57.0,\u003c5`; Transformers 5 can produce all-zero codes with this custom code", "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", "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", "Decode with `model.decode_audio(output.codes)` and write at `model.config.codec_sample_rate` (44,100 Hz)", "Split long text into short utterances; reference, transcript and text share 2,048 positions", "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", "Only clone a voice you have permission to use, and disclose synthetic audio" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 51.5 } ], "editorialScores": { "interface": 60, "reach": 55, "risk": 40, "upkeep": 57 }, "provenanceScore": 61, "checked": { "categories": { "interface": "2026-10-30", "reach": "2026-10-30", "risk": "2026-10-30", "upkeep": "2026-10-30" }, "last": "2026-10-30", "oldest": "2026-10-30", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "git clone https://github.com/Edge0-AI/Audio8_TTS.git \u0026\u0026 cd Audio8_TTS\npip install -r requirements.txt\n# voice cloning; drop the two reference flags to speak without a reference\npython audio8_tts_infer.py --model Edge0/Audio8-TTS-Realistic-0.6b --text \"Welcome to Audio8 TTS.\" --reference-audio reference.wav --reference-text \"The exact transcript of the recording.\" --output outputs/realistic.wav" }, "letme": { "capability": "https://letme.dev/speech.tts", "tool": "https://letme.dev/audio8-tts-realistic-0-6b" }, "weights": { "trainedBy": "Edge0", "builtOn": "Edge0/Audio8-TTS-Preview-0.6b (the card's base_model, fine-tuned from it; Apache 2.0), whose slow branch is Qwen2.5 0.5B by the technical report (Apache 2.0)", "params": "0.6B (601,159,424 BF16 parameters by the Hub's count, without the bundled codec)", "context": 2048, "goodFor": "Zero-shot voice cloning from one clip and its transcript, or speech without a reference, in 23 languages, on a small CUDA GPU, under Apache 2.0.", "runtimes": [], "builds": [ { "name": "Audio8-TTS-Realistic-0.6b", "url": "https://huggingface.co/Edge0/Audio8-TTS-Realistic-0.6b", "who": "publisher", "precision": "bf16", "sizeGB": 2.57, "memoryGB": 8, "format": "safetensors", "note": "model.safetensors 1.20 GB plus the codec as codec.pth, a 1.35 GB PyTorch pickle, and the tokenizer; 2,565,567,480 bytes summed from the Hub's file list. 2.57 GB × 1.2 = 3.1 GB" } ], "run": "git clone https://github.com/Edge0-AI/Audio8_TTS.git \u0026\u0026 cd Audio8_TTS \u0026\u0026 pip install -r requirements.txt \u0026\u0026 python audio8_tts_infer.py --model Edge0/Audio8-TTS-Realistic-0.6b --text \"Welcome to Audio8 TTS.\" --output outputs/realistic.wav", "runBuild": "Audio8-TTS-Realistic-0.6b", "checked": "2026-10-30", "minMemoryGB": 8 }, "family": { "lab": "Edge0", "family": "Audio8-TTS", "url": "https://www.anchorterminal.com/open-weights/#edge0", "others": [ { "name": "Audio8-TTS-Preview-0.6b", "url": "https://huggingface.co/Edge0/Audio8-TTS-Preview-0.6b", "params": "0.6B (601,159,424 by the Hub's count, without the codec)" }, { "name": "Audio8-TTS-Preview-0.1b", "url": "https://huggingface.co/Edge0/Audio8-TTS-Preview-0.1b", "params": "0.17B (169,779,904 by the Hub's count)" } ], "olderCount": 2 }, "alsoIn": [ "voice-cloning" ], "area": "voice", "provenance": { "legalEntity": "Edge0 (edge0.ai), which names no legal entity or location on its site. The technical report's authors give their affiliation as AutoArk, and commit metadata in Edge0-AI/Audio8_TTS uses an autoark.ai domain", "domain": "edge0.ai", "domainRegistered": "2026-09-02", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/Edge0/Audio8-TTS-Realistic-0.6b/commits/main", "securityTxt": "none", "checked": "2026-10-30", "notes": [ "edge0.ai links huggingface.co/Edge0 and github.com/Edge0-AI, and the card links back to github.com/Edge0-AI/Audio8_TTS. Hugging Face shows the Edge0 organisation as not verified. The earlier Hugging Face organisation name Audio8 redirects to Edge0, and the GitHub repository's older merges came from an Audio8-AI organisation.", "Nothing is hosted, so the licence stands in for terms of service and no privacy policy is scored.", "The Hugging Face repository was created on 14 October 2026 with a commit titled as a private release; the weights and code were last changed that day. The GitHub release commit and the Playground came on 27 October 2026, the earliest dated public release found, so firstReleased is 27 October. The Hub doesn't say when the repository was made public.", "edge0.ai/.well-known/security.txt answered 404 and edge0.ai serves no robots.txt on 30 October 2026. RDAP gives the domain's registration as 2 September 2026." ], "score": 61 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/audio8-tts-realistic-0-6b.json" }, "answer": "OmniVoice scores 56.9 (C) on agent readiness against Audio8-TTS-Realistic 0.6B's 51.5 (D), and leads in 0 of 4 scored categories. Audio8-TTS-Realistic 0.6B leads on reach, risk, agent interface and documentation and upkeep.", "b": { "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": 1239, "categoryRank": 13, "methodology": "0.7", "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": "0.7", "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": 70, "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": 70 }, "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": "2026-10-30T14:32:54.919785957Z" } ], "pypiWeekly": 40403, "securityTxt": { "url": "https://k2-fsa.org/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-30T15:39:35.184501156Z" }, "domain": { "domain": "k2-fsa.org", "registered": "2021-02-08", "source": "https://rdap.publicinterestregistry.org/rdap/domain/k2-fsa.org", "checkedAt": "2026-10-25T13:55:24.392656518Z" }, "updatedAt": "2026-10-30T15:39:35.184501156Z" } }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Edge0", "b": "k2-fsa (Next-gen Kaldi)", "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": "Apache-2.0", "b": "CC-BY-NC (weights, per the card); Apache-2.0 (code)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-27", "b": "2026-07-03", "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": "none", "b": "2.3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "OmniVoice scores 56.9 (C) on agent readiness against Audio8-TTS-Realistic 0.6B's 51.5 (D), and leads in 0 of 4 scored categories. Audio8-TTS-Realistic 0.6B leads on reach, risk, agent interface and documentation and upkeep.", "question": "Which is better for AI agents, Audio8-TTS-Realistic 0.6B or OmniVoice?" } ], "goodFor": [ { "aheadOn": [ "Reach, 55 against 40", "Risk, 40 against 35", "Agent interface, 60 against 50", "Documentation and upkeep, 57 against 48" ], "also": null, "goodFor": "Agents that need multilingual voice cloning on a small CUDA GPU under a permissive licence, and can accept remote code", "slug": "audio8-tts-realistic-0-6b", "watchFor": "Loads only with trust_remote_code, and the codec ships as a 1.35 GB PyTorch pickle" }, { "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" } ], "job": { "capability": "speech.tts", "name": "Text-to-speech" }, "others": [ { "json": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-drama-3.json", "title": "Audio8-TTS-Realistic 0.6B vs Fish Audio Drama 3", "url": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-drama-3" }, { "json": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro.json", "title": "Audio8-TTS-Realistic 0.6B vs Fish Audio S2 Pro", "url": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro" }, { "json": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-ming-3-0-tts-0-5b.json", "title": "Audio8-TTS-Realistic 0.6B vs Ming-3.0-tts-0.5B", "url": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-ming-3-0-tts-0-5b" }, { "json": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-ming-3-0-tts-tiny.json", "title": "Audio8-TTS-Realistic 0.6B vs Ming-3.0-tts-tiny", "url": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-ming-3-0-tts-tiny" }, { "json": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-qwen3-tts-1-7b-customvoice.json", "title": "Audio8-TTS-Realistic 0.6B vs Qwen3-TTS 12Hz 1.7B CustomVoice", "url": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-qwen3-tts-1-7b-customvoice" }, { "json": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-vieneu-tts-v3-turbo.json", "title": "Audio8-TTS-Realistic 0.6B vs VieNeu-TTS v3 Turbo", "url": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-vieneu-tts-v3-turbo" }, { "json": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-omnivoice.json", "title": "Fish Audio Drama 3 vs OmniVoice", "url": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-omnivoice" }, { "json": "https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-omnivoice.json", "title": "Fish Audio S2 Pro vs OmniVoice", "url": "https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-omnivoice" }, { "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-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/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/omnivoice-vs-vieneu-tts-v3-turbo.json", "title": "OmniVoice vs VieNeu-TTS v3 Turbo", "url": "https://www.anchorterminal.com/compare/omnivoice-vs-vieneu-tts-v3-turbo" } ], "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "audio8-tts-realistic-0-6b": 55, "by": 15, "edge": "audio8-tts-realistic-0-6b", "key": "reach", "name": "Reach", "omnivoice": 40, "weight": 25 }, { "audio8-tts-realistic-0-6b": 40, "by": 5, "edge": "audio8-tts-realistic-0-6b", "key": "risk", "name": "Risk", "omnivoice": 35, "weight": 20 }, { "audio8-tts-realistic-0-6b": 60, "by": 10, "edge": "audio8-tts-realistic-0-6b", "key": "interface", "name": "Agent interface", "omnivoice": 50, "weight": 10 }, { "audio8-tts-realistic-0-6b": 57, "by": 9, "edge": "audio8-tts-realistic-0-6b", "key": "upkeep", "name": "Documentation and upkeep", "omnivoice": 48, "weight": 10 } ], "summary": "OmniVoice scores 56.9 (C) on agent readiness against Audio8-TTS-Realistic 0.6B's 51.5 (D), and leads in 0 of 4 scored categories. Audio8-TTS-Realistic 0.6B leads on reach, risk, agent interface and documentation and upkeep. Both do text-to-speech.", "tutorials": [], "verdicts": { "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.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-omnivoice", "json": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-omnivoice.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-omnivoice.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-omnivoice.min.md" }, "markdown": "OmniVoice scores 56.9 (C) on agent readiness against Audio8-TTS-Realistic 0.6B's 51.5 (D), and leads in 0 of 4 scored categories. Audio8-TTS-Realistic 0.6B leads on reach, risk, agent interface and documentation and upkeep. Both do text-to-speech.\n\n- Audio8-TTS-Realistic 0.6B: grade D, 51.5/100, rank #103 of 117 open-weight models. Markdown https://www.anchorterminal.com/tools/audio8-tts-realistic-0-6b.md · JSON https://www.anchorterminal.com/api/v1/tools/audio8-tts-realistic-0-6b.json\n- OmniVoice: grade C, 56.9/100, rank #79 of 117 open-weight models. Markdown https://www.anchorterminal.com/tools/omnivoice.md · JSON https://www.anchorterminal.com/api/v1/tools/omnivoice.json\n- Best text-to-speech APIs for AI agents: https://www.anchorterminal.com/best/text-to-speech/index.md\n- All 94 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 94 cloning comparisons: https://www.anchorterminal.com/compare/voice-cloning/index.md\n\n## Which one, for what\n\n### Audio8-TTS-Realistic 0.6B (D)\n\nGood for: Agents that need multilingual voice cloning on a small CUDA GPU under a permissive licence, and can accept remote code\n\nAhead on:\n- Reach, 55 against 40\n- Risk, 40 against 35\n- Agent interface, 60 against 50\n- Documentation and upkeep, 57 against 48\n\nWatch for: Loads only with trust_remote_code, and the codec ships as a 1.35 GB PyTorch pickle\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\n## Score by category\n\n| Category | Weight | Audio8-TTS-Realistic 0.6B | OmniVoice | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 55 | 40 | Audio8-TTS-Realistic 0.6B +15 |\n| Risk | 20% (20 this run) | 40 | 35 | Audio8-TTS-Realistic 0.6B +5 |\n| Agent interface | 10% (10 this run) | 60 | 50 | Audio8-TTS-Realistic 0.6B +10 |\n| Documentation and upkeep | 10% (10 this run) | 57 | 48 | Audio8-TTS-Realistic 0.6B +9 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **51.5 · D** | **56.9 · C** | |\n\n## Facts side by side\n\n| Fact | Audio8-TTS-Realistic 0.6B | OmniVoice |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Edge0 | k2-fsa (Next-gen Kaldi) |\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 | Apache-2.0 | CC-BY-NC (weights, per the card); Apache-2.0 (code) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-27 | 2026-07-03 |\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 | none | 2.3/5 (4) |\n\n## Verdicts\n\n**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.\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## Before you call either\n\n### Audio8-TTS-Realistic 0.6B\n\n1. Pin `transformers\u003e=4.57.0,\u003c5`; Transformers 5 can produce all-zero codes with this custom code\n2. 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\n3. 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\n4. Decode with `model.decode_audio(output.codes)` and write at `model.config.codec_sample_rate` (44,100 Hz)\n5. Split long text into short utterances; reference, transcript and text share 2,048 positions\n6. 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\n7. Only clone a voice you have permission to use, and disclose synthetic audio\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## Questions\n\n### Which is better for AI agents, Audio8-TTS-Realistic 0.6B or OmniVoice?\n\nOmniVoice scores 56.9 (C) on agent readiness against Audio8-TTS-Realistic 0.6B's 51.5 (D), and leads in 0 of 4 scored categories. Audio8-TTS-Realistic 0.6B leads on reach, risk, agent interface and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-omnivoice.json, and with the fewest tokens: https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-omnivoice.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"audio8-tts-realistic-0-6b\", \"b\": \"omnivoice\"}`. From a terminal: `anchor compare audio8-tts-realistic-0-6b omnivoice`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/audio8-tts-realistic-0-6b.json and https://www.anchorterminal.com/api/v1/tools/omnivoice.json\n\n## Other comparisons with Audio8-TTS-Realistic 0.6B or OmniVoice\n\n- [Audio8-TTS-Realistic 0.6B vs Fish Audio Drama 3](https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-drama-3.md)\n- [Audio8-TTS-Realistic 0.6B vs Fish Audio S2 Pro](https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro.md)\n- [Audio8-TTS-Realistic 0.6B vs Ming-3.0-tts-0.5B](https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-ming-3-0-tts-0-5b.md)\n- [Audio8-TTS-Realistic 0.6B vs Ming-3.0-tts-tiny](https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-ming-3-0-tts-tiny.md)\n- [Audio8-TTS-Realistic 0.6B vs Qwen3-TTS 12Hz 1.7B CustomVoice](https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-qwen3-tts-1-7b-customvoice.md)\n- [Audio8-TTS-Realistic 0.6B vs VieNeu-TTS v3 Turbo](https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-vieneu-tts-v3-turbo.md)\n- [Fish Audio Drama 3 vs OmniVoice](https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-omnivoice.md)\n- [Fish Audio S2 Pro vs OmniVoice](https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-omnivoice.md)\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-tiny vs OmniVoice](https://www.anchorterminal.com/compare/ming-3-0-tts-tiny-vs-omnivoice.md)\n- [OmniVoice vs Qwen3-TTS 12Hz 1.7B CustomVoice](https://www.anchorterminal.com/compare/omnivoice-vs-qwen3-tts-1-7b-customvoice.md)\n- [OmniVoice vs VieNeu-TTS v3 Turbo](https://www.anchorterminal.com/compare/omnivoice-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": "2026-10-31", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "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": "Audio8-TTS-Realistic 0.6B vs OmniVoice", "url": "" } ], "description": "OmniVoice scores 56.9 (C) to Audio8-TTS-Realistic 0.6B's 51.5 (D) for text-to-speech. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Audio8-TTS-Realistic 0.6B D 51.5", "OmniVoice C 56.9", "scores" ], "h1": "Audio8-TTS-Realistic 0.6B vs OmniVoice", "image": "https://www.anchorterminal.com/assets/og/compare-audio8-tts-realistic-0-6b-vs-omnivoice.png", "path": "/compare/audio8-tts-realistic-0-6b-vs-omnivoice", "published": "2026-10-01", "section": "tools", "title": "Audio8-TTS-Realistic 0.6B vs OmniVoice for AI agents (2026)", "toc": null, "updated": "2026-10-30", "url": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-omnivoice" }, "tokens": { "markdown": 2300, "slim": 480 }, "version": 1 }