{ "data": { "a": { "slug": "fish-audio-drama-3", "name": "Fish Audio Drama 3", "vendor": "Fish Audio", "vendorUrl": "https://fish.audio", "kind": "weights", "category": "text-to-speech", "summary": "Fish Audio Drama 3 is Fish Audio's open-weight text-to-speech model, a 35B mixture of experts with 3B active built on Qwen3.5-35B-A3B, that clones voices, takes plain-language direction and voices multi-speaker scenes, under the Fish Audio Community License.", "url": "https://www.anchorterminal.com/tools/fish-audio-drama-3", "markdownUrl": "https://www.anchorterminal.com/tools/fish-audio-drama-3.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/fish-audio-drama-3.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/fish-audio-drama-3.json", "repo": "https://huggingface.co/fishaudio/drama-3", "license": "Fish Audio Community License 1.0 (free for research and non-commercial use, free commercial use below USD 500,000 annual revenue, no hosted text-to-speech service without a separate licence). The card's metadata still names fish-audio-research-license", "transports": [], "packages": [ { "registry": "huggingface", "name": "fishaudio/drama-3" }, { "registry": "huggingface", "name": "fishaudio/drama-3-int4" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither fishaudio/drama-3 nor fishaudio/drama-3-int4 is gated (checked 2026-10-23). The licence says using or accessing the files binds you to it. The fish-speech code is public on GitHub.", "pricing": "free", "pricingNotes": "Free to download. Under the Fish Audio Community License 1.0 (13 October 2026), research and non-commercial use is free, commercial use is free while you and your affiliates have under USD 500,000 annual revenue, and offering it as a hosted text-to-speech, voice or cloning service needs a separate written licence at any size. Running it costs the hardware, an NVIDIA GPU with at least 48 GB for the FP8 build per Fish Audio's install guide. Fish Audio's own API sells `drama-3` at $50 per million UTF-8 bytes, $10 until 12 November 2026 (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", "moe", "text-to-speech", "voice-cloning", "multi-speaker", "speech-editing", "inline-tags", "multilingual", "revenue-threshold", "fp8", "int4", "safetensors", "self-hosted", "new" ], "lastRelease": "2026-10-17", "graded": true, "anchor": { "graded": true, "score": 55.6, "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": 1201, "categoryRank": 15, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 67, "interface": 70, "reach": 60, "risk": 25, "upkeep": 51 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-23" }, "negative": 0, "verdict": "A local voice cousin for directed speech, multi-character scenes, voice cloning and word-level edits in about 80 languages. It needs an NVIDIA GPU, about 29 GB for the int4 build or at least 48 GB for FP8, through SGLang-Omni or fish-speech. The main risk is the licence, revocable, capped at USD 500,000 revenue for commercial use and barring hosted services.", "bestFor": "Agents with an NVIDIA GPU of 32 GB or more producing directed multi-character audio, dubbing or narration, for organisations under USD 500,000 revenue or non-commercial use", "strengths": [ "Up to 16 voices per request, cloning from several references, revision by note and word-level editing by infilling, all in one model", "Independently run on the Open TTS Leaderboard, with an English WER of 1.19% without cloning and 2.66% with it", "An int4 build in Fish Audio's organisation that roughly halves the files to 24.0 GB", "Every prompt format and control is written out in the technical report, and SGLang-Omni serves it behind an OpenAI-style speech endpoint with streaming", "Hashed files in Fish Audio's own organisation, ungated" ], "weaknesses": [ "Commercial use is free only below USD 500,000 annual revenue, hosted services always need a separate licence, and the grant is revocable", "The card's licence metadata still names the Research License with a broken link, after a release-day licence switch", "NVIDIA only, and not in any released version of Transformers, vLLM, SGLang, llama.cpp, Ollama or LM Studio", "The codec ships as a PyTorch pickle, and there are no safety results or security contact", "No reply from Fish Audio to any of its 6 Hugging Face discussions" ], "agentNotes": [ "Install SGLang-Omni from source with `uv pip install --prerelease=allow -e \".[fishaudio]\"`, then `sgl-omni serve --model-path fishaudio/drama-3-int4 --port 8000` (or fishaudio/drama-3 for FP8 on 48 GB or more)", "POST JSON to /v1/audio/speech with `input`, optional `references` (audio_path and its transcript) and `previous_takes`; set `response_format` and `stream` for the output", "Start each line with `\u003c|speaker:N|\u003e` (N from 0 to 15) for several voices, and separate lines with `\u003c|audio_separator|\u003e`", "Direct with point tags like `[sighs]`, scoped tags like `\u003cwhisper\u003e...\u003c/whisper\u003e`, a bracketed style prefix, or `Direction:` and `Line:` for a director's note", "The int4 build needs compute capability 8.0 or newer; only the triton attention backend is accepted", "Keep each reference clip under 60 seconds and the prompt under 8,192 rows, about 21.5 rows per second of reference audio", "Check the licence before commercial use or exposing it to other users, and only clone voices with consent", "Treat text from untrusted sources as a script that can carry directions and speaker tags" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 55.6 } ], "editorialScores": { "capability": 67, "interface": 70, "reach": 60, "risk": 25, "upkeep": 51 }, "provenanceScore": 63, "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/sgl-project/sglang-omni.git \u0026\u0026 cd sglang-omni\nuv venv -p 3.12 .venv \u0026\u0026 . .venv/bin/activate\nuv pip install --prerelease=allow -e \".[fishaudio]\"\nhf download fishaudio/drama-3-int4 # or fishaudio/drama-3 for the FP8 build\nsgl-omni serve --model-path fishaudio/drama-3-int4 --port 8000", "http": "curl -X POST http://localhost:8000/v1/audio/speech \\\n -H \"Content-Type: application/json\" \\\n -d '{\"input\": \"\u003c|speaker:0|\u003e [sighs] Fine. If we miss it, it is on you.\", \"references\": [{\"audio_path\": \"/path/to/reference.wav\", \"text\": \"Transcript of the reference clip.\"}], \"response_format\": \"wav\"}' \\\n --output out.wav" }, "letme": { "capability": "https://letme.dev/speech.tts", "tool": "https://letme.dev/fish-audio-drama-3" }, "sameCompany": [ "fish-audio-s2-pro", "fish-audio-tts", "fish-audio-voice-cloning" ], "weights": { "trainedBy": "Fish Audio", "builtOn": "Qwen/Qwen3.5-35B-A3B (named in the technical report as the backbone it's initialised from, not on the card; Apache 2.0)", "params": "35.9B (35B backbone with about 3B active per token, per the card; 35,899,643,008 by the Hub's count)", "context": 16384, "goodFor": "Directed, expressive speech for multi-character scenes, long-form narration and dubbing, with voice cloning, revision by note and word-level editing, on an NVIDIA GPU.", "runtimes": [], "builds": [ { "name": "drama-3-int4", "url": "https://huggingface.co/fishaudio/drama-3-int4", "who": "publisher", "precision": "int4", "sizeGB": 24, "memoryGB": 32, "format": "safetensors", "note": "W4A16 GPTQ-format experts and attention projections, round-to-nearest with no calibration, quantised by AK (akhaliq) and duplicated into the fishaudio organisation on 14 October 2026; its card calls it unofficial. 22.1 GB of safetensors plus codec.pth, excluding the evaluation audio. Needs compute capability 8.0 or newer" }, { "name": "drama-3", "url": "https://huggingface.co/fishaudio/drama-3", "who": "publisher", "precision": "fp8", "sizeGB": 41.5, "memoryGB": 64, "format": "safetensors", "note": "The release itself, MoE experts in block-scaled FP8 with the rest in BF16, plus the 1.87 GB codec.pth pickle. Fish Audio's install guide asks for at least 48 GB on an NVIDIA GPU" } ], "run": "git clone https://github.com/sgl-project/sglang-omni.git \u0026\u0026 cd sglang-omni \u0026\u0026 uv pip install --prerelease=allow -e \".[fishaudio]\" \u0026\u0026 hf download fishaudio/drama-3-int4 \u0026\u0026 sgl-omni serve --model-path fishaudio/drama-3-int4 --port 8000", "runBuild": "drama-3-int4", "checked": "2026-10-23", "minMemoryGB": 32 }, "family": { "lab": "Fish Audio", "family": "Drama", "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 Community 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/drama-3/blob/main/LICENSE", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/fishaudio/drama-3/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, the technical report and Fish Audio's launch post 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 nine commits from 13 to 17 October 2026 (the upload, the licence file and its rename, card edits, the report link and vLLM-Omni instructions). The weights haven't changed since the first commit. fishaudio/drama-3-int4 has two commits on 14 October 2026.", "fish.audio/.well-known/security.txt answered 404 on 23 October 2026 and fishaudio/fish-speech has no SECURITY.md. The domain registration date is carried from the fish-audio-tts check of 17 October 2026." ], "score": 63 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/fish-audio-drama-3.json", "live": { "slug": "fish-audio-drama-3", "securityTxt": { "url": "https://fish.audio/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-23T15:24:36.233836361Z" }, "updatedAt": "2026-10-23T15:24:36.233836361Z" } }, "answer": "Fish Audio Drama 3 scores 55.6 (C) on agent readiness against Ming-3.0-tts-tiny's 52.2 (D), and leads in 3 of 4 scored categories. Ming-3.0-tts-tiny leads on risk.", "b": { "slug": "ming-3-0-tts-tiny", "name": "Ming-3.0-tts-tiny", "vendor": "inclusionAI (Ant Group)", "vendorUrl": "https://www.inclusion-ai.org", "kind": "weights", "category": "text-to-speech", "summary": "Ming-3.0-tts-tiny is inclusionAI's open-weight text-to-speech model, a Ling V3 mixture of experts with 7.9B backbone parameters and about 1.3B active, for voice cloning, voice design and controlled speech in seven languages, under MIT.", "url": "https://www.anchorterminal.com/tools/ming-3-0-tts-tiny", "markdownUrl": "https://www.anchorterminal.com/tools/ming-3-0-tts-tiny.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/ming-3-0-tts-tiny.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/ming-3-0-tts-tiny.json", "repo": "https://huggingface.co/inclusionAI/Ming-3.0-tts-tiny", "license": "MIT", "transports": [], "packages": [ { "registry": "huggingface", "name": "inclusionAI/Ming-3.0-tts-tiny" } ], "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). Inference needs the publisher's GitHub repository, which is public.", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under the MIT licence. inclusionAI sells no per-call access to these weights. Running them costs the hardware, about 17.7 GB of BF16 safetensors, on an NVIDIA H800 as the publisher recommends (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/inclusionAI/Ming-3.0-tts", "capabilities": [ "speech.tts", "speech.voices", "speech.languages", "voice.clone", "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "text-to-speech", "voice-cloning", "multilingual", "mit", "safetensors", "self-hosted", "new" ], "lastRelease": "2026-10-20", "graded": true, "anchor": { "graded": true, "score": 52.2, "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": 1201, "categoryRank": 17, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 60, "reach": 50, "risk": 55, "upkeep": 44 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-21" }, "negative": 0, "verdict": "A text-to-speech cousin for voice cloning, voice design and multi-speaker podcast audio in seven languages, under MIT. It needs the publisher's own code or SGLang-Omni and about 22 GB of GPU memory, with CUDA 11.8 pinned. The main risks are that loading runs repository code, no safety work is published and it can clone a voice from a short clip.", "bestFor": "Agents on a 24 GB NVIDIA GPU that need Chinese or English narration, voice cloning or multi-speaker audio under MIT", "strengths": [ "Plain MIT licence, no gate and no account", "BF16 files of 18.0 GB fit a 24 GB GPU", "Ten task modes documented with the inputs each accepts, from cloning to voice design and podcast scripts", "An OpenAI-compatible /v1/audio/speech endpoint through SGLang-Omni, with the command on the card", "Safetensors with a SHA-256 for every large file, and active upkeep in its first week" ], "weaknesses": [ "No runtime among llama.cpp, Ollama, vLLM, SGLang, LM Studio or Transformers runs it from its own code", "Loading runs the publisher's Python code, pinned to transformers 4.46.3, torch 2.7.1 and CUDA 11.8", "No quantised build from inclusionAI and no hosted provider", "No training data or safety evaluation, and no security route of its own", "One task per call, no streaming and no timestamps", "The card's generate() temperature disagrees with the config files" ], "agentNotes": [ "Install from the GitHub repository, `git clone https://github.com/inclusionAI/Ming-3.0-tts.git \u0026\u0026 cd Ming-3.0-tts \u0026\u0026 pip install -r requirements-tiny.txt`, in its own Python 3.10.15 environment, since the 0.5B model pins different versions", "Quick start is `bash examples/one_click/run_seed.sh`, which clones from the bundled reference clip", "To serve, run `sgl-omni serve --model-path inclusionAI/Ming-3.0-tts-tiny` from SGLang-Omni's main branch and POST to /v1/audio/speech with input, response_format and, for cloning, ref_audio plus ref_text", "Pick one task per call (seed, multilingual, paralinguistic, podcast, basic, emotion, dialect, freeform, voice_design, ip) and pass only the inputs that task accepts", "Expect one complete audio body, since there is no streaming, and no timestamps", "Pass temperature yourself, since the reference generate() uses 0 and SGLang-Omni takes 1.5 from the config", "Run `python tools/preflight_tiny.py --model_path \u003cdir\u003e` on the downloaded checkpoint before first use", "Label output as synthetic speech where it could pass for a real recording, as the card asks" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "D", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.2 } ], "editorialScores": { "interface": 60, "reach": 50, "risk": 55, "upkeep": 44 }, "provenanceScore": 57, "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": "git clone https://github.com/inclusionAI/Ming-3.0-tts.git \u0026\u0026 cd Ming-3.0-tts\nconda create -n ming-tiny python=3.10.15 -y \u0026\u0026 conda activate ming-tiny\npip install -r requirements-tiny.txt\n# zero-shot cloning from the bundled reference clip (writes outputs/seed.wav)\nbash examples/one_click/run_seed.sh", "http": "# after: sgl-omni serve --model-path inclusionAI/Ming-3.0-tts-tiny\ncurl -X POST http://127.0.0.1:8000/v1/audio/speech \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"inclusionAI/Ming-3.0-tts-tiny\", \"input\": \"Get the trust fund to the bank early.\", \"response_format\": \"wav\", \"seed\": 123}' \\\n --output speech.wav" }, "letme": { "capability": "https://letme.dev/speech.tts", "tool": "https://letme.dev/ming-3-0-tts-tiny" }, "sameCompany": [ "ming-3-0-asr-tiny", "ming-3-0-audio-flash", "ming-3-0-audio-tiny", "ling-3-0-tiny" ], "weights": { "trainedBy": "inclusionAI (Ant Group)", "builtOn": "Ling V3", "params": "7.9B", "active": "1.3B", "goodFor": "Text to speech with voice cloning, voice design and controlled speech in seven languages, on a mixture-of-experts backbone.", "runtimes": [], "builds": [ { "name": "Ming-3.0-tts-tiny", "url": "https://huggingface.co/inclusionAI/Ming-3.0-tts-tiny", "who": "publisher", "precision": "bf16", "sizeGB": 18, "memoryGB": 24, "format": "safetensors", "note": "Runs with inclusionAI's code or SGLang-Omni, none of the runtimes listed for the machine" } ], "run": "git clone https://github.com/inclusionAI/Ming-3.0-tts.git \u0026\u0026 cd Ming-3.0-tts \u0026\u0026 pip install -r requirements-tiny.txt \u0026\u0026 bash examples/one_click/run_seed.sh", "runBuild": "Ming-3.0-tts-tiny", "checked": "2026-10-21", "minMemoryGB": 24 }, "family": { "lab": "inclusionAI (Ant Group)", "family": "Ming 3.0", "url": "https://www.anchorterminal.com/open-weights/#inclusionai", "others": [ { "name": "Ming-3.0-tts-0.5B", "url": "https://huggingface.co/inclusionAI/Ming-3.0-tts-0.5B", "params": "0.5B (dense)", "listing": "https://www.anchorterminal.com/tools/ming-3-0-tts-0-5b" }, { "name": "Ming-3.0-audio-flash", "url": "https://huggingface.co/inclusionAI/Ming-3.0-audio-flash", "params": "126B total, 6.5B active", "listing": "https://www.anchorterminal.com/tools/ming-3-0-audio-flash" }, { "name": "Ming-3.0-audio-tiny", "url": "https://huggingface.co/inclusionAI/Ming-3.0-audio-tiny", "params": "9.3B total, 2.7B active", "listing": "https://www.anchorterminal.com/tools/ming-3-0-audio-tiny" }, { "name": "Ming-3.0-asr-tiny", "url": "https://huggingface.co/inclusionAI/Ming-3.0-asr-tiny", "params": "not stated on the card (Hub metadata counts 8,865,800,992 in the files)", "listing": "https://www.anchorterminal.com/tools/ming-3-0-asr-tiny" } ], "olderCount": 54 }, "alsoIn": [ "voice-cloning" ], "area": "voice", "provenance": { "legalEntity": "inclusionAI, Ant Group (named in the site footer of inclusion-ai.org; the LICENSE copyright line reads inclusionAI)", "domain": "inclusion-ai.org", "domainRegistered": "2025-04-03", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/inclusionAI/Ming-3.0-tts-tiny/commits/main", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "inclusion-ai.org links to huggingface.co/inclusionAI and github.com/inclusionAI, and the GitHub organisation's profile describes inclusionAI as Ant Group's open-source projects. The footer reads \"© 2026 inclusionAI, Ant Group\". No registered company name was found.", "Nothing is hosted, so the MIT licence stands in for terms of service and no privacy policy is scored.", "The changelog is the Hugging Face commit history, whose 24 messages say what changed (a corrected parameter description, updated metrics, the SGLang-Omni instructions).", "inclusion-ai.org/.well-known/security.txt answered 404 on 21 October 2026. Domain registration date from RDAP (rdap.org) on 21 October 2026.", "Ant Group runs a company-wide security response centre, AntSRC (https://security.alipay.com/, read on 21 October 2026). Nothing on inclusionAI's card or sites links it." ], "score": 57 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/ming-3-0-tts-tiny.json", "live": { "slug": "ming-3-0-tts-tiny", "securityTxt": { "url": "https://inclusion-ai.org/.well-known/security.txt", "state": "unknown", "checkedAt": "2026-10-23T15:23:26.507720168Z" }, "pages": [ { "url": "https://huggingface.co/inclusionAI/Ming-3.0-tts-tiny/commits/main", "kind": "changelog", "status": 200, "checkedAt": "2026-10-23T01:49:33.459085571Z", "changedAt": "2026-10-23T01:49:33.459085571Z", "fingerprint": "9e588bd9ac1c" } ], "updatedAt": "2026-10-23T15:23:26.507720168Z" } }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Fish Audio", "b": "inclusionAI (Ant Group)", "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": "Fish Audio Community License 1.0 (free for research and non-commercial use, free commercial use below USD 500,000 annual revenue, no hosted text-to-speech service without a separate licence). The card's metadata still names fish-audio-research-license", "b": "MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-17", "b": "2026-10-20", "name": "Last release" }, { "a": "", "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": "2.8/5 (4)", "b": "2.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Fish Audio Drama 3 scores 55.6 (C) on agent readiness against Ming-3.0-tts-tiny's 52.2 (D), and leads in 3 of 4 scored categories. Ming-3.0-tts-tiny leads on risk.", "question": "Which is better for AI agents, Fish Audio Drama 3 or Ming-3.0-tts-tiny?" } ], "goodFor": [ { "aheadOn": [ "Reach, 60 against 50", "Agent interface, 70 against 60", "Documentation and upkeep, 51 against 44" ], "also": null, "goodFor": "Agents with an NVIDIA GPU of 32 GB or more producing directed multi-character audio, dubbing or narration, for organisations under USD 500,000 revenue or non-commercial use", "slug": "fish-audio-drama-3", "watchFor": "Commercial use is free only below USD 500,000 annual revenue, hosted services always need a separate licence, and the grant is revocable" }, { "aheadOn": [ "Risk, 55 against 25" ], "also": null, "goodFor": "Agents on a 24 GB NVIDIA GPU that need Chinese or English narration, voice cloning or multi-speaker audio under MIT", "slug": "ming-3-0-tts-tiny", "watchFor": "No runtime among llama.cpp, Ollama, vLLM, SGLang, LM Studio or Transformers runs it from its own code" } ], "job": { "capability": "speech.tts", "name": "Text-to-speech" }, "others": [ { "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-drama-3-vs-ming-3-0-tts-0-5b.json", "title": "Fish Audio Drama 3 vs Ming-3.0-tts-0.5B", "url": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-ming-3-0-tts-0-5b" }, { "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-drama-3-vs-qwen3-tts-1-7b-customvoice.json", "title": "Fish Audio Drama 3 vs Qwen3-TTS 12Hz 1.7B CustomVoice", "url": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-qwen3-tts-1-7b-customvoice" }, { "json": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-vieneu-tts-v3-turbo.json", "title": "Fish Audio Drama 3 vs VieNeu-TTS v3 Turbo", "url": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-vieneu-tts-v3-turbo" }, { "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/ming-3-0-tts-0-5b-vs-ming-3-0-tts-tiny.json", "title": "Ming-3.0-tts-0.5B vs Ming-3.0-tts-tiny", "url": "https://www.anchorterminal.com/compare/ming-3-0-tts-0-5b-vs-ming-3-0-tts-tiny" }, { "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-qwen3-tts-1-7b-customvoice.json", "title": "Ming-3.0-tts-tiny vs Qwen3-TTS 12Hz 1.7B CustomVoice", "url": "https://www.anchorterminal.com/compare/ming-3-0-tts-tiny-vs-qwen3-tts-1-7b-customvoice" }, { "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" } ], "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 10, "edge": "fish-audio-drama-3", "fish-audio-drama-3": 60, "key": "reach", "ming-3-0-tts-tiny": 50, "name": "Reach", "weight": 25 }, { "by": 30, "edge": "ming-3-0-tts-tiny", "fish-audio-drama-3": 25, "key": "risk", "ming-3-0-tts-tiny": 55, "name": "Risk", "weight": 20 }, { "by": 10, "edge": "fish-audio-drama-3", "fish-audio-drama-3": 70, "key": "interface", "ming-3-0-tts-tiny": 60, "name": "Agent interface", "weight": 10 }, { "by": 7, "edge": "fish-audio-drama-3", "fish-audio-drama-3": 51, "key": "upkeep", "ming-3-0-tts-tiny": 44, "name": "Documentation and upkeep", "weight": 10 } ], "summary": "Fish Audio Drama 3 scores 55.6 (C) on agent readiness against Ming-3.0-tts-tiny's 52.2 (D), and leads in 3 of 4 scored categories. Ming-3.0-tts-tiny leads on risk. Both do text-to-speech.", "tutorials": [], "verdicts": { "fish-audio-drama-3": "A local voice cousin for directed speech, multi-character scenes, voice cloning and word-level edits in about 80 languages. It needs an NVIDIA GPU, about 29 GB for the int4 build or at least 48 GB for FP8, through SGLang-Omni or fish-speech. The main risk is the licence, revocable, capped at USD 500,000 revenue for commercial use and barring hosted services.", "ming-3-0-tts-tiny": "A text-to-speech cousin for voice cloning, voice design and multi-speaker podcast audio in seven languages, under MIT. It needs the publisher's own code or SGLang-Omni and about 22 GB of GPU memory, with CUDA 11.8 pinned. The main risks are that loading runs repository code, no safety work is published and it can clone a voice from a short clip." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-ming-3-0-tts-tiny", "json": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-ming-3-0-tts-tiny.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-ming-3-0-tts-tiny.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-ming-3-0-tts-tiny.min.md" }, "markdown": "Fish Audio Drama 3 scores 55.6 (C) on agent readiness against Ming-3.0-tts-tiny's 52.2 (D), and leads in 3 of 4 scored categories. Ming-3.0-tts-tiny leads on risk. Both do text-to-speech.\n\n- Fish Audio Drama 3: grade C, 55.6/100, rank #82 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/fish-audio-drama-3.md · JSON https://www.anchorterminal.com/api/v1/tools/fish-audio-drama-3.json\n- Ming-3.0-tts-tiny: grade D, 52.2/100, rank #93 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/ming-3-0-tts-tiny.md · JSON https://www.anchorterminal.com/api/v1/tools/ming-3-0-tts-tiny.json\n- Best text-to-speech APIs for AI agents: https://www.anchorterminal.com/best/text-to-speech/index.md\n- All 87 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 87 cloning comparisons: https://www.anchorterminal.com/compare/voice-cloning/index.md\n\n## Which one, for what\n\n### Fish Audio Drama 3 (C)\n\nGood for: Agents with an NVIDIA GPU of 32 GB or more producing directed multi-character audio, dubbing or narration, for organisations under USD 500,000 revenue or non-commercial use\n\nAhead on:\n- Reach, 60 against 50\n- Agent interface, 70 against 60\n- Documentation and upkeep, 51 against 44\n\nWatch for: Commercial use is free only below USD 500,000 annual revenue, hosted services always need a separate licence, and the grant is revocable\n\n### Ming-3.0-tts-tiny (D)\n\nGood for: Agents on a 24 GB NVIDIA GPU that need Chinese or English narration, voice cloning or multi-speaker audio under MIT\n\nAhead on:\n- Risk, 55 against 25\n\nWatch for: No runtime among llama.cpp, Ollama, vLLM, SGLang, LM Studio or Transformers runs it from its own code\n\n\n## Score by category\n\n| Category | Weight | Fish Audio Drama 3 | Ming-3.0-tts-tiny | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 60 | 50 | Fish Audio Drama 3 +10 |\n| Risk | 20% (20 this run) | 25 | 55 | Ming-3.0-tts-tiny +30 |\n| Agent interface | 10% (10 this run) | 70 | 60 | Fish Audio Drama 3 +10 |\n| Documentation and upkeep | 10% (10 this run) | 51 | 44 | Fish Audio Drama 3 +7 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **55.6 · C** | **52.2 · D** | |\n\n## Facts side by side\n\n| Fact | Fish Audio Drama 3 | Ming-3.0-tts-tiny |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Fish Audio | inclusionAI (Ant Group) |\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 | Fish Audio Community License 1.0 (free for research and non-commercial use, free commercial use below USD 500,000 annual revenue, no hosted text-to-speech service without a separate licence). The card's metadata still names fish-audio-research-license | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-17 | 2026-10-20 |\n| Terms last updated | | 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 | 2.8/5 (4) | 2.5/5 (4) |\n\n## Verdicts\n\n**Fish Audio Drama 3.** A local voice cousin for directed speech, multi-character scenes, voice cloning and word-level edits in about 80 languages. It needs an NVIDIA GPU, about 29 GB for the int4 build or at least 48 GB for FP8, through SGLang-Omni or fish-speech. The main risk is the licence, revocable, capped at USD 500,000 revenue for commercial use and barring hosted services.\n\n**Ming-3.0-tts-tiny.** A text-to-speech cousin for voice cloning, voice design and multi-speaker podcast audio in seven languages, under MIT. It needs the publisher's own code or SGLang-Omni and about 22 GB of GPU memory, with CUDA 11.8 pinned. The main risks are that loading runs repository code, no safety work is published and it can clone a voice from a short clip.\n\n## Before you call either\n\n### Fish Audio Drama 3\n\n1. Install SGLang-Omni from source with `uv pip install --prerelease=allow -e \".[fishaudio]\"`, then `sgl-omni serve --model-path fishaudio/drama-3-int4 --port 8000` (or fishaudio/drama-3 for FP8 on 48 GB or more)\n2. POST JSON to /v1/audio/speech with `input`, optional `references` (audio_path and its transcript) and `previous_takes`; set `response_format` and `stream` for the output\n3. Start each line with `\u003c|speaker:N|\u003e` (N from 0 to 15) for several voices, and separate lines with `\u003c|audio_separator|\u003e`\n4. Direct with point tags like `[sighs]`, scoped tags like `\u003cwhisper\u003e...\u003c/whisper\u003e`, a bracketed style prefix, or `Direction:` and `Line:` for a director's note\n5. The int4 build needs compute capability 8.0 or newer; only the triton attention backend is accepted\n6. Keep each reference clip under 60 seconds and the prompt under 8,192 rows, about 21.5 rows per second of reference audio\n7. Check the licence before commercial use or exposing it to other users, and only clone voices with consent\n8. Treat text from untrusted sources as a script that can carry directions and speaker tags\n\n### Ming-3.0-tts-tiny\n\n1. Install from the GitHub repository, `git clone https://github.com/inclusionAI/Ming-3.0-tts.git \u0026\u0026 cd Ming-3.0-tts \u0026\u0026 pip install -r requirements-tiny.txt`, in its own Python 3.10.15 environment, since the 0.5B model pins different versions\n2. Quick start is `bash examples/one_click/run_seed.sh`, which clones from the bundled reference clip\n3. To serve, run `sgl-omni serve --model-path inclusionAI/Ming-3.0-tts-tiny` from SGLang-Omni's main branch and POST to /v1/audio/speech with input, response_format and, for cloning, ref_audio plus ref_text\n4. Pick one task per call (seed, multilingual, paralinguistic, podcast, basic, emotion, dialect, freeform, voice_design, ip) and pass only the inputs that task accepts\n5. Expect one complete audio body, since there is no streaming, and no timestamps\n6. Pass temperature yourself, since the reference generate() uses 0 and SGLang-Omni takes 1.5 from the config\n7. Run `python tools/preflight_tiny.py --model_path \u003cdir\u003e` on the downloaded checkpoint before first use\n8. Label output as synthetic speech where it could pass for a real recording, as the card asks\n\n## Questions\n\n### Which is better for AI agents, Fish Audio Drama 3 or Ming-3.0-tts-tiny?\n\nFish Audio Drama 3 scores 55.6 (C) on agent readiness against Ming-3.0-tts-tiny's 52.2 (D), and leads in 3 of 4 scored categories. Ming-3.0-tts-tiny leads on risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-ming-3-0-tts-tiny.json, and with the fewest tokens: https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-ming-3-0-tts-tiny.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"fish-audio-drama-3\", \"b\": \"ming-3-0-tts-tiny\"}`. From a terminal: `anchor compare fish-audio-drama-3 ming-3-0-tts-tiny`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/fish-audio-drama-3.json and https://www.anchorterminal.com/api/v1/tools/ming-3-0-tts-tiny.json\n\n## Other comparisons with Fish Audio Drama 3 or Ming-3.0-tts-tiny\n\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 Drama 3 vs Ming-3.0-tts-0.5B](https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-ming-3-0-tts-0-5b.md)\n- [Fish Audio Drama 3 vs OmniVoice](https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-omnivoice.md)\n- [Fish Audio Drama 3 vs Qwen3-TTS 12Hz 1.7B CustomVoice](https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-qwen3-tts-1-7b-customvoice.md)\n- [Fish Audio Drama 3 vs VieNeu-TTS v3 Turbo](https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-vieneu-tts-v3-turbo.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- [Ming-3.0-tts-0.5B vs Ming-3.0-tts-tiny](https://www.anchorterminal.com/compare/ming-3-0-tts-0-5b-vs-ming-3-0-tts-tiny.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 Qwen3-TTS 12Hz 1.7B CustomVoice](https://www.anchorterminal.com/compare/ming-3-0-tts-tiny-vs-qwen3-tts-1-7b-customvoice.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", "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": "Fish Audio Drama 3 vs Ming-3.0-tts-tiny", "url": "" } ], "description": "Fish Audio Drama 3 scores 55.6 (C) to Ming-3.0-tts-tiny's 52.2 (D) for text-to-speech. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Fish Audio Drama 3 C 55.6", "Ming-3.0-tts-tiny D 52.2", "scores" ], "h1": "Fish Audio Drama 3 vs Ming-3.0-tts-tiny", "image": "https://www.anchorterminal.com/assets/og/compare-fish-audio-drama-3-vs-ming-3-0-tts-tiny.png", "path": "/compare/fish-audio-drama-3-vs-ming-3-0-tts-tiny", "published": "2026-10-01", "section": "tools", "title": "Fish Audio Drama 3 vs Ming-3.0-tts-tiny for AI agents (2026)", "toc": null, "updated": "2026-10-23", "url": "https://www.anchorterminal.com/compare/fish-audio-drama-3-vs-ming-3-0-tts-tiny" }, "tokens": { "markdown": 2350, "slim": 530 }, "version": 1 }