{ "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": "Fish Audio S2 Pro scores 52.5 (D) on agent readiness against Audio8-TTS-Realistic 0.6B's 51.5 (D), and leads in 1 of 4 scored categories. Audio8-TTS-Realistic 0.6B leads on reach and risk.", "b": { "slug": "fish-audio-s2-pro", "name": "Fish Audio S2 Pro", "vendor": "Fish Audio", "vendorUrl": "https://fish.audio", "kind": "weights", "category": "text-to-speech", "summary": "Fish Audio S2 Pro is Fish Audio's open-weight text-to-speech model of March 2026, a 4B plus 0.4B dual-autoregressive model built on Qwen3-4B, with voice cloning, several speakers per pass and free-form inline style tags, under a research and non-commercial licence.", "url": "https://www.anchorterminal.com/tools/fish-audio-s2-pro", "markdownUrl": "https://www.anchorterminal.com/tools/fish-audio-s2-pro.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/fish-audio-s2-pro.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/fish-audio-s2-pro.json", "repo": "https://huggingface.co/fishaudio/s2-pro", "license": "Fish Audio Research License (weights; research and non-commercial use only); the fish-speech code that runs it is under the Fish Audio Community License 1.0 since 13 October 2026", "transports": [], "packages": [ { "registry": "huggingface", "name": "fishaudio/s2-pro" }, { "registry": "github", "name": "fishaudio/fish-speech" }, { "registry": "docker", "name": "fishaudio/fish-speech:server-cuda" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub API reports gated false and a weights file resolves for a public user, though the card's metadata still carries unused gate fields (a non-commercial checkbox). Checked 2026-10-23.", "pricing": "free", "pricingNotes": "Free to download for research and non-commercial use under the Fish Audio Research License. Commercial use needs a separate written licence from Fish Audio, with no public price. Running it costs the hardware, 11.0 GB of files (9.1 GB of BF16 safetensors and a 1.9 GB codec), and Fish Audio's install guide asks for at least 24 GB of GPU memory. Fish Audio's own API serves `s2-pro` at $15 per million UTF-8 bytes (checked 2026-10-23).", "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 2026-10-23).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-23" }, "docsUrl": "https://speech.fish.audio/inference/", "capabilities": [ "speech.tts", "speech.languages", "speech.streaming", "voice.clone", "model.open-weights" ], "tags": [ "open-weights", "model", "text-to-speech", "voice-cloning", "multi-speaker", "inline-tags", "multilingual", "non-commercial", "safetensors", "self-hosted" ], "lastRelease": "2026-03-11", "graded": true, "anchor": { "graded": true, "score": 52.5, "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": 16, "methodology": "0.7", "run": "2026-10-01", "scores": { "capability": 61, "interface": 70, "reach": 50, "risk": 30, "upkeep": 56 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-23" }, "negative": 0, "verdict": "A local speech cousin that clones voices from a short clip, voices several speakers in one pass and follows free-form inline style tags in 80+ languages, with independent results near the top of the Open TTS Leaderboard. It needs Fish Audio's own code and about a 24 GB GPU. The main limit is the licence, research and non-commercial use only.", "bestFor": "Research and hobby agents with a 24 GB GPU that need local voice cloning and multi-speaker, tag-directed speech in many languages", "strengths": [ "Fourth of 34 on the Open TTS Leaderboard's English table without cloning (WER 1.06%) and third of 18 with cloning (WER 1.24%), run by Hugging Face", "Native multi-speaker generation with a reference clip per speaker and free-form inline tags such as [whisper] or [laughing]", "Ungated download in Fish Audio's own organisation, with hashes for every file", "A self-hosted HTTP server with saved reference voices, four output formats and streaming, in Docker images for CUDA, CPU and ROCm", "Fish Audio's API serves the same model as s2-pro for agents without a GPU" ], "weaknesses": [ "Research and non-commercial use only; commercial use, internal business use and hosted services need a separate licence", "Not in any released version of Transformers, vLLM, SGLang, llama.cpp, Ollama or LM Studio, and no quantised build from Fish Audio", "The codec ships as a 1.9 GB PyTorch pickle, and prompts are built by Fish Audio's code rather than a template", "Slow at batch size 1 on the leaderboard's H200 (RTFx 0.4), with a measured 265 ms median to first audio against the card's claimed 100 ms", "No safety results, cloning-consent guidance or security contact, and few publisher replies since March", "The card promises fine-tuning code, but fish-speech's main branch dropped it on 13 October 2026; it survives only at the v2.0.0-beta tag" ], "agentNotes": [ "Install fish-speech from GitHub (`uv sync --python 3.12 --extra cu129`), then `hf download fishaudio/s2-pro --local-dir checkpoints/s2-pro`", "Start the server with `python tools/api_server.py --listen 127.0.0.1:8080 --llama-checkpoint-path checkpoints/s2-pro --decoder-checkpoint-path checkpoints/s2-pro/codec.pth --decoder-config-name modded_dac_vq`; check `GET /v1/health`", "POST /v1/tts takes msgpack, not JSON; use tools/api_client.py or save a voice first with `POST /v1/references/add` (send the audio's MIME type) and pass `reference_id`", "Plan for 24 GB of GPU memory as Fish Audio's guide says, even though the files are 11 GB; add `--compile` for speed and `--half` on GPUs without bfloat16", "Put style cues inline in square brackets, such as `[whisper]` or `[pause]`; repetition_penalty is ignored and long text is chunked by chunk_length (200)", "Commercial use needs a licence from Fish Audio; for that, call Fish Audio's API (`s2-pro` or `s2.1-pro`) instead" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.5 } ], "editorialScores": { "capability": 61, "interface": 70, "reach": 50, "risk": 30, "upkeep": 56 }, "provenanceScore": 65, "checked": { "categories": { "capability": "2026-10-23", "interface": "2026-10-23", "reach": "2026-10-23", "risk": "2026-10-23", "upkeep": "2026-10-23" }, "last": "2026-10-23", "oldest": "2026-10-23", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "git clone https://github.com/fishaudio/fish-speech \u0026\u0026 cd fish-speech\napt install portaudio19-dev libsox-dev ffmpeg\nuv sync --python 3.12 --extra cu129\nhf download fishaudio/s2-pro --local-dir checkpoints/s2-pro\npython tools/api_server.py --listen 127.0.0.1:8080 --llama-checkpoint-path checkpoints/s2-pro --decoder-checkpoint-path checkpoints/s2-pro/codec.pth --decoder-config-name modded_dac_vq" }, "letme": { "capability": "https://letme.dev/speech.tts", "tool": "https://letme.dev/fish-audio-s2-pro" }, "sameCompany": [ "fish-audio-drama-3", "fish-audio-voice-cloning" ], "sameModel": [ "fish-audio-tts" ], "weights": { "trainedBy": "Fish Audio", "builtOn": "Qwen/Qwen3-4B (the slow AR is initialised from it, per the technical report and Fish Audio's changelog; Apache 2.0)", "params": "4.56B (slow AR 4B plus fast AR 0.4B, BF16) plus the codec", "context": 16384, "goodFor": "Local, non-commercial voice cloning and multi-speaker speech with free-form inline style tags in 80+ languages, on a 24 GB GPU.", "runtimes": [], "builds": [ { "name": "s2-pro", "url": "https://huggingface.co/fishaudio/s2-pro", "who": "publisher", "precision": "bf16", "sizeGB": 11.01, "memoryGB": 16, "format": "safetensors", "note": "9.12 GB of safetensors plus the 1.87 GB codec.pth pickle, summed from the Hub's file list. Fish Audio's install guide asks for at least 24 GB of GPU memory. Runs through Fish Audio's fish-speech code" } ], "run": "python tools/api_server.py --listen 127.0.0.1:8080 --llama-checkpoint-path checkpoints/s2-pro --decoder-checkpoint-path checkpoints/s2-pro/codec.pth --decoder-config-name modded_dac_vq", "runBuild": "s2-pro", "checked": "2026-10-23", "minMemoryGB": 16 }, "family": { "lab": "Fish Audio", "family": "S2", "url": "https://www.anchorterminal.com/open-weights/#fishaudio", "olderCount": 8 }, "alsoIn": [ "voice-cloning" ], "area": "voice", "provenance": { "legalEntity": "39 AI, Inc. (the licensor named in the Fish Audio Research License). fish.audio's terms of use name Hanabi AI Inc. as the provider of the hosted services", "domain": "fish.audio", "domainRegistered": "2023-12-11", "endpointOnVendorDomain": null, "terms": "https://huggingface.co/fishaudio/s2-pro/blob/main/LICENSE.md", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/fishaudio/s2-pro/commits/main", "securityTxt": "none", "checked": "2026-10-23", "notes": [ "The files sit in the fishaudio organisation on Hugging Face, which github.com/fishaudio/fish-speech and docs.fish.audio's changelog link to.", "Nothing is hosted for this listing, so the licence stands in for terms of service and no privacy policy is scored.", "The Hugging Face history is six commits from 9 to 11 March 2026 (upload, codec upload, card and citation edits). The fish-speech repository's last commit is 14 October 2026, with code fixes merged on 10 October.", "https://fish.audio/.well-known/security.txt returned 404 on 2026-10-23. The domain registration date is carried from the fish-audio-tts check of 17 October 2026." ], "score": 65 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/fish-audio-s2-pro.json", "live": { "slug": "fish-audio-s2-pro", "securityTxt": { "url": "https://fish.audio/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-30T15:38:15.607348268Z" }, "domain": { "domain": "fish.audio", "registered": "2023-12-11", "source": "https://rdap.centralnic.com/audio/domain/fish.audio", "checkedAt": "2026-10-25T13:53:06.631962844Z" }, "pages": [ { "url": "https://huggingface.co/fishaudio/s2-pro/commits/main", "kind": "changelog", "status": 200, "checkedAt": "2026-10-30T05:41:50.17293381Z", "changedAt": "2026-10-30T05:41:50.17293381Z", "fingerprint": "8a7970b49810" }, { "url": "https://huggingface.co/fishaudio/s2-pro/blob/main/LICENSE.md", "kind": "terms", "status": 200, "checkedAt": "2026-10-30T05:41:47.858370427Z", "changedAt": "2026-10-30T05:41:47.858370427Z", "fingerprint": "6bd2f2aecc9a" } ], "updatedAt": "2026-10-30T15:38:15.607348268Z" } }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Edge0", "b": "Fish Audio", "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": "Fish Audio Research License (weights; research and non-commercial use only); the fish-speech code that runs it is under the Fish Audio Community License 1.0 since 13 October 2026", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-27", "b": "2026-03-11", "name": "Last release" }, { "a": "no document linked", "b": "2026-03-07", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "b": "yes", "name": "Customer content may train models" }, { "a": "", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "2.3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Fish Audio S2 Pro scores 52.5 (D) on agent readiness against Audio8-TTS-Realistic 0.6B's 51.5 (D), and leads in 1 of 4 scored categories. Audio8-TTS-Realistic 0.6B leads on reach and risk.", "question": "Which is better for AI agents, Audio8-TTS-Realistic 0.6B or Fish Audio S2 Pro?" } ], "goodFor": [ { "aheadOn": [ "Reach, 55 against 50", "Risk, 40 against 30" ], "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": [ "Agent interface, 70 against 60" ], "also": null, "goodFor": "Research and hobby agents with a 24 GB GPU that need local voice cloning and multi-speaker, tag-directed speech in many languages", "slug": "fish-audio-s2-pro", "watchFor": "Research and non-commercial use only; commercial use, internal business use and hosted services need a separate licence" } ], "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-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-omnivoice.json", "title": "Audio8-TTS-Realistic 0.6B vs OmniVoice", "url": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-omnivoice" }, { "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-fish-audio-s2-pro.json", "title": "Fish Audio Drama 3 vs Fish Audio S2 Pro", "url": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-fish-audio-s2-pro" }, { "json": "https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-ming-3-0-tts-0-5b.json", "title": "Fish Audio S2 Pro vs Ming-3.0-tts-0.5B", "url": "https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-ming-3-0-tts-0-5b" }, { "json": "https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-ming-3-0-tts-tiny.json", "title": "Fish Audio S2 Pro vs Ming-3.0-tts-tiny", "url": "https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-ming-3-0-tts-tiny" }, { "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/fish-audio-s2-pro-vs-qwen3-tts-1-7b-customvoice.json", "title": "Fish Audio S2 Pro vs Qwen3-TTS 12Hz 1.7B CustomVoice", "url": "https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-qwen3-tts-1-7b-customvoice" }, { "json": "https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-vieneu-tts-v3-turbo.json", "title": "Fish Audio S2 Pro vs VieNeu-TTS v3 Turbo", "url": "https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-vieneu-tts-v3-turbo" } ], "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "audio8-tts-realistic-0-6b": 55, "by": 5, "edge": "audio8-tts-realistic-0-6b", "fish-audio-s2-pro": 50, "key": "reach", "name": "Reach", "weight": 25 }, { "audio8-tts-realistic-0-6b": 40, "by": 10, "edge": "audio8-tts-realistic-0-6b", "fish-audio-s2-pro": 30, "key": "risk", "name": "Risk", "weight": 20 }, { "audio8-tts-realistic-0-6b": 60, "by": 10, "edge": "fish-audio-s2-pro", "fish-audio-s2-pro": 70, "key": "interface", "name": "Agent interface", "weight": 10 }, { "audio8-tts-realistic-0-6b": 57, "by": 1, "edge": "audio8-tts-realistic-0-6b", "fish-audio-s2-pro": 56, "key": "upkeep", "name": "Documentation and upkeep", "weight": 10 } ], "summary": "Fish Audio S2 Pro scores 52.5 (D) on agent readiness against Audio8-TTS-Realistic 0.6B's 51.5 (D), and leads in 1 of 4 scored categories. Audio8-TTS-Realistic 0.6B leads on reach and risk. 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.", "fish-audio-s2-pro": "A local speech cousin that clones voices from a short clip, voices several speakers in one pass and follows free-form inline style tags in 80+ languages, with independent results near the top of the Open TTS Leaderboard. It needs Fish Audio's own code and about a 24 GB GPU. The main limit is the licence, research and non-commercial use only." } }, "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-fish-audio-s2-pro", "json": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro.min.md" }, "markdown": "Fish Audio S2 Pro scores 52.5 (D) on agent readiness against Audio8-TTS-Realistic 0.6B's 51.5 (D), and leads in 1 of 4 scored categories. Audio8-TTS-Realistic 0.6B leads on reach and risk. 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- Fish Audio S2 Pro: grade D, 52.5/100, rank #97 of 117 open-weight models. Markdown https://www.anchorterminal.com/tools/fish-audio-s2-pro.md · JSON https://www.anchorterminal.com/api/v1/tools/fish-audio-s2-pro.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 50\n- Risk, 40 against 30\n\nWatch for: Loads only with trust_remote_code, and the codec ships as a 1.35 GB PyTorch pickle\n\n### Fish Audio S2 Pro (D)\n\nGood for: Research and hobby agents with a 24 GB GPU that need local voice cloning and multi-speaker, tag-directed speech in many languages\n\nAhead on:\n- Agent interface, 70 against 60\n\nWatch for: Research and non-commercial use only; commercial use, internal business use and hosted services need a separate licence\n\n\n## Score by category\n\n| Category | Weight | Audio8-TTS-Realistic 0.6B | Fish Audio S2 Pro | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 55 | 50 | Audio8-TTS-Realistic 0.6B +5 |\n| Risk | 20% (20 this run) | 40 | 30 | Audio8-TTS-Realistic 0.6B +10 |\n| Agent interface | 10% (10 this run) | 60 | 70 | Fish Audio S2 Pro +10 |\n| Documentation and upkeep | 10% (10 this run) | 57 | 56 | Audio8-TTS-Realistic 0.6B +1 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **51.5 · D** | **52.5 · D** | |\n\n## Facts side by side\n\n| Fact | Audio8-TTS-Realistic 0.6B | Fish Audio S2 Pro |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Edge0 | Fish Audio |\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 | Fish Audio Research License (weights; research and non-commercial use only); the fish-speech code that runs it is under the Fish Audio Community License 1.0 since 13 October 2026 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-27 | 2026-03-11 |\n| Terms last updated | no document linked | 2026-03-07 |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | | yes |\n| Terms restrict automated access | | not found in the text |\n| Terms restrict benchmarking | | not found in the text |\n| Terms or service can change without notice | | not found in the text |\n| Arbitration or class-action waiver | | not found in the text |\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**Fish Audio S2 Pro.** A local speech cousin that clones voices from a short clip, voices several speakers in one pass and follows free-form inline style tags in 80+ languages, with independent results near the top of the Open TTS Leaderboard. It needs Fish Audio's own code and about a 24 GB GPU. The main limit is the licence, research and non-commercial use only.\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### Fish Audio S2 Pro\n\n1. Install fish-speech from GitHub (`uv sync --python 3.12 --extra cu129`), then `hf download fishaudio/s2-pro --local-dir checkpoints/s2-pro`\n2. Start the server with `python tools/api_server.py --listen 127.0.0.1:8080 --llama-checkpoint-path checkpoints/s2-pro --decoder-checkpoint-path checkpoints/s2-pro/codec.pth --decoder-config-name modded_dac_vq`; check `GET /v1/health`\n3. POST /v1/tts takes msgpack, not JSON; use tools/api_client.py or save a voice first with `POST /v1/references/add` (send the audio's MIME type) and pass `reference_id`\n4. Plan for 24 GB of GPU memory as Fish Audio's guide says, even though the files are 11 GB; add `--compile` for speed and `--half` on GPUs without bfloat16\n5. Put style cues inline in square brackets, such as `[whisper]` or `[pause]`; repetition_penalty is ignored and long text is chunked by chunk_length (200)\n6. Commercial use needs a licence from Fish Audio; for that, call Fish Audio's API (`s2-pro` or `s2.1-pro`) instead\n\n## Questions\n\n### Which is better for AI agents, Audio8-TTS-Realistic 0.6B or Fish Audio S2 Pro?\n\nFish Audio S2 Pro scores 52.5 (D) on agent readiness against Audio8-TTS-Realistic 0.6B's 51.5 (D), and leads in 1 of 4 scored categories. Audio8-TTS-Realistic 0.6B leads on reach and risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro.json, and with the fewest tokens: https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"audio8-tts-realistic-0-6b\", \"b\": \"fish-audio-s2-pro\"}`. From a terminal: `anchor compare audio8-tts-realistic-0-6b fish-audio-s2-pro`\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/fish-audio-s2-pro.json\n\n## Other comparisons with Audio8-TTS-Realistic 0.6B or Fish Audio S2 Pro\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 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 OmniVoice](https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-omnivoice.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 Fish Audio S2 Pro](https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-fish-audio-s2-pro.md)\n- [Fish Audio S2 Pro vs Ming-3.0-tts-0.5B](https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-ming-3-0-tts-0-5b.md)\n- [Fish Audio S2 Pro vs Ming-3.0-tts-tiny](https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-ming-3-0-tts-tiny.md)\n- [Fish Audio S2 Pro vs OmniVoice](https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-omnivoice.md)\n- [Fish Audio S2 Pro vs Qwen3-TTS 12Hz 1.7B CustomVoice](https://www.anchorterminal.com/compare/fish-audio-s2-pro-vs-qwen3-tts-1-7b-customvoice.md)\n- [Fish Audio S2 Pro vs VieNeu-TTS v3 Turbo](https://www.anchorterminal.com/compare/fish-audio-s2-pro-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 Fish Audio S2 Pro", "url": "" } ], "description": "Fish Audio S2 Pro scores 52.5 (D) 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", "Fish Audio S2 Pro D 52.5", "scores" ], "h1": "Audio8-TTS-Realistic 0.6B vs Fish Audio S2 Pro", "image": "https://www.anchorterminal.com/assets/og/compare-audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro.png", "path": "/compare/audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro", "published": "2026-10-01", "section": "tools", "title": "Audio8-TTS-Realistic 0.6B vs Fish Audio S2 Pro for AI agents (2026)", "toc": null, "updated": "2026-10-30", "url": "https://www.anchorterminal.com/compare/audio8-tts-realistic-0-6b-vs-fish-audio-s2-pro" }, "tokens": { "markdown": 2400, "slim": 580 }, "version": 1 }