{ "data": { "a": { "slug": "parakeet-tdt-0-6b-v3", "name": "Parakeet TDT 0.6B v3", "vendor": "NVIDIA", "vendorUrl": "https://github.com/NVIDIA/NeMo", "kind": "weights", "category": "speech-to-text", "summary": "Parakeet TDT 0.6B v3 is NVIDIA's open-weight speech recognition model for 25 European languages, a 0.6B-parameter FastConformer encoder with a TDT decoder that detects the language and returns punctuated text with word and segment timestamps, under CC BY 4.0.", "url": "https://www.anchorterminal.com/tools/parakeet-tdt-0-6b-v3", "markdownUrl": "https://www.anchorterminal.com/tools/parakeet-tdt-0-6b-v3.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/parakeet-tdt-0-6b-v3.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/parakeet-tdt-0-6b-v3.json", "dns": "parakeet-tdt-0-6b-v3.grade.anchorterminal.com", "repo": "https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3", "license": "CC-BY-4.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "nvidia/parakeet-tdt-0.6b-v3" } ], "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).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under CC BY 4.0, which asks for attribution. Running it costs the hardware; the card says at least 2 GB of RAM to load it. The files are 2.5 GB in FP32 safetensors or 0.7 GB as NVIDIA's Q8_0 GGUF (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://huggingface.co/nvidia/parakeet-tdt-0.6b-v3", "capabilities": [ "speech.stt", "speech.batch", "speech.streaming", "speech.languages", "model.open-weights" ], "tags": [ "open-weights", "model", "speech-to-text", "asr", "multilingual", "timestamps", "fastconformer", "tdt", "nemo", "cc-by-4.0", "safetensors", "gguf", "self-hosted" ], "lastRelease": "2026-08-05", "graded": true, "anchor": { "graded": true, "score": 66.9, "grade": "B", "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": 1518, "categoryRank": 11, "methodology": "0.7", "run": "2026-10-01", "scores": { "capability": 74, "interface": 50, "reach": 65, "risk": 60, "upkeep": 77 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "A small, fast transcription cousin for 25 European languages that detects the language and returns punctuated text with word timestamps. It fits in under 1 GB as NVIDIA's GGUF and runs in Transformers, NeMo or NVIDIA's C++ runtime, under CC BY 4.0. Few other runtimes load it, and it takes no language hint.", "bestFor": "Agents that need cheap local transcription with timestamps in English and other European languages", "strengths": [ "Small enough for any machine, 0.71 GB as NVIDIA's Q8_0 GGUF or 2.5 GB in FP32", "25 European languages detected automatically, with punctuation, capitalisation and word, segment and char timestamps", "CC BY 4.0, ungated, files hashed in NVIDIA's own organisation", "Training data listed by corpus with hours, much of it published as Granary", "Kept current, with Transformers support added in 2026 and NVIDIA's C++ runtime changing its ASR weight loading on 20 October 2026" ], "weaknesses": [ "Among the six runtimes only Transformers runs it; vLLM, SGLang, llama.cpp, Ollama and LM Studio don't", "The NeMo archive, the card's main path, loads a PyTorch pickle", "No language hint or hotwords, and an open report's title says it can drift into other languages without one", "No safety results and only general cautions", "NVIDIA answered 9 of the 40 latest questions, none since February 2026" ], "agentNotes": [ "For the smallest setup, `hf download nvidia/parakeet-tdt-0.6b-v3 parakeet-tdt-0.6b-v3.q8_0.gguf --local-dir models`, then `nemo-speech transcribe speech.wav --model models/parakeet-tdt-0.6b-v3.q8_0.gguf` with NeMo-Speech.cpp", "In Python, `pipeline('automatic-speech-recognition', model='nvidia/parakeet-tdt-0.6b-v3')` works on Transformers 5.10.0 or later, despite the card's note to install from source", "Resample to 16 kHz mono first; it takes wav or flac", "Ask for timestamps with `timestamps=True` in NeMo, or pass `durations=output.durations` to `processor.decode` in Transformers", "For audio longer than about 24 minutes, switch NeMo to local attention with `change_attention_model(\"rel_pos_local_attn\", [256, 256])`", "Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 4, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 66.9 } ], "editorialScores": { "capability": 74, "interface": 50, "reach": 65, "risk": 60, "upkeep": 77 }, "provenanceScore": 73, "checked": { "categories": { "capability": "2026-11-01", "interface": "2026-11-01", "reach": "2026-11-01", "risk": "2026-11-01", "upkeep": "2026-11-01" }, "last": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install -U \"transformers\u003e=5.10\" torch\npython -c \"from transformers import pipeline; print(pipeline('automatic-speech-recognition', model='nvidia/parakeet-tdt-0.6b-v3')('speech.wav'))\"\n# or with NVIDIA's C++ runtime, NeMo-Speech.cpp:\nhf download nvidia/parakeet-tdt-0.6b-v3 parakeet-tdt-0.6b-v3.q8_0.gguf --local-dir models\nnemo-speech transcribe speech.wav --model models/parakeet-tdt-0.6b-v3.q8_0.gguf", "http": "# after starting NeMo-Speech.cpp's server with this model (it binds 127.0.0.1:8080)\ncurl http://127.0.0.1:8080/v1/audio/transcriptions -F file=@speech.wav" }, "letme": { "capability": "https://letme.dev/speech.stt", "tool": "https://letme.dev/parakeet-tdt-0-6b-v3" }, "sameCompany": [ "nemotron-3-5-super-vl", "nvidia-nemo-retriever", "nemo-guardrails", "nemotron-3-5-asr-streaming-0-6b", "nemotron-3-5-transcribe-30b-a4b", "parakeet-unified-en-0-6b", "nemotron-3-5-parse", "cosmos-reason2-2b", "nemotron-3-5-bolt-e4b-4gb", "nemotron-3-nano-30b-a3b", "nemotron-3-nano-4b", "nemotron-3-nano-omni-30b-a3b-reasoning", "nemotron-3-super-120b-a12b", "nemotron-3-ultra-550b-a55b", "nemotron-3-5-lightning-30b-a3b" ], "weights": { "trainedBy": "NVIDIA", "params": "0.6B", "goodFor": "Fast multilingual transcription in 25 European languages with automatic language detection, punctuation and word-level timestamps.", "runtimes": [ "Transformers" ], "builds": [ { "name": "parakeet-tdt-0.6b-v3 (safetensors)", "url": "https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3/blob/main/model.safetensors", "who": "publisher", "precision": "fp32", "sizeGB": 2.5, "memoryGB": 8, "format": "safetensors", "runsOn": [ "Transformers" ] }, { "name": "parakeet-tdt-0.6b-v3.nemo", "url": "https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3/blob/main/parakeet-tdt-0.6b-v3.nemo", "who": "publisher", "precision": "fp32", "sizeGB": 2.5, "memoryGB": 8, "format": "nemo", "runsOn": [ "NeMo" ], "note": "A NeMo archive holding a PyTorch checkpoint (pickle), loaded by NeMo's ASRModel.from_pretrained" }, { "name": "parakeet-tdt-0.6b-v3.q8_0.gguf", "url": "https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3/blob/main/parakeet-tdt-0.6b-v3.q8_0.gguf", "who": "publisher", "precision": "q8_0", "sizeGB": 0.71, "memoryGB": 8, "format": "gguf", "runsOn": [ "NeMo-Speech.cpp" ], "note": "For NVIDIA's NeMo-Speech.cpp, not llama.cpp, which has no TDT decoder" } ], "run": "nemo-speech transcribe speech.wav --model models/parakeet-tdt-0.6b-v3.q8_0.gguf", "runBuild": "parakeet-tdt-0.6b-v3.q8_0.gguf", "checked": "2026-10-21", "minMemoryGB": 8 }, "family": { "lab": "NVIDIA (Nemotron)", "family": "Parakeet", "url": "https://www.anchorterminal.com/open-weights/#nvidia", "others": [ { "name": "parakeet-rnnt-1.1b", "url": "https://huggingface.co/nvidia/parakeet-rnnt-1.1b", "params": "1.1B" }, { "name": "parakeet-ctc-1.1b", "url": "https://huggingface.co/nvidia/parakeet-ctc-1.1b", "params": "1.1B" }, { "name": "parakeet-rnnt-0.6b", "url": "https://huggingface.co/nvidia/parakeet-rnnt-0.6b", "params": "0.6B" }, { "name": "parakeet-ctc-0.6b", "url": "https://huggingface.co/nvidia/parakeet-ctc-0.6b", "params": "0.6B" }, { "name": "parakeet-tdt-1.1b", "url": "https://huggingface.co/nvidia/parakeet-tdt-1.1b", "params": "1.1B" }, { "name": "parakeet-tdt_ctc-1.1b", "url": "https://huggingface.co/nvidia/parakeet-tdt_ctc-1.1b", "params": "1.1B" }, { "name": "parakeet-tdt_ctc-0.6b-ja", "url": "https://huggingface.co/nvidia/parakeet-tdt_ctc-0.6b-ja", "params": "0.6B" }, { "name": "parakeet-tdt_ctc-110m", "url": "https://huggingface.co/nvidia/parakeet-tdt_ctc-110m", "params": "110M" }, { "name": "parakeet-tdt-0.6b-v2", "url": "https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2", "params": "0.6B" }, { "name": "parakeet-rnnt-110m-da-dk", "url": "https://huggingface.co/nvidia/parakeet-rnnt-110m-da-dk", "params": "110M" }, { "name": "parakeet_realtime_eou_120m-v1", "url": "https://huggingface.co/nvidia/parakeet_realtime_eou_120m-v1", "params": "120M" }, { "name": "multitalker-parakeet-streaming-0.6b-v1", "url": "https://huggingface.co/nvidia/multitalker-parakeet-streaming-0.6b-v1", "params": "0.6B" }, { "name": "parakeet-ctc-0.6b-Vietnamese", "url": "https://huggingface.co/nvidia/parakeet-ctc-0.6b-Vietnamese", "params": "0.6B" }, { "name": "parakeet-unified-en-0.6b", "url": "https://huggingface.co/nvidia/parakeet-unified-en-0.6b", "params": "0.6B", "listing": "https://www.anchorterminal.com/tools/parakeet-unified-en-0-6b" } ], "olderCount": 47 }, "area": "voice", "provenance": { "legalEntity": "NVIDIA Corporation", "domain": "nvidia.com", "domainRegistered": "1993-04-20", "endpointOnVendorDomain": null, "terms": "https://creativecommons.org/licenses/by/4.0/legalcode.en", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3/commits/main", "securityTxt": "none", "checked": "2026-11-01", "notes": [ "The model sits in NVIDIA's Hugging Face organisation and the card's governing terms are CC BY 4.0. The domain registration date is carried from the RDAP check made for nemotron-3-nano-30b-a3b on 21 October 2026.", "Nothing is hosted for this listing, so the licence stands in for terms of service and no privacy policy is scored.", "The changelog is the commit history, 28 commits from 4 August 2025 to 5 August 2026. Recent messages say what changed (Transformers integration on 16 April and 19 May 2026, an eos_token for vLLM on 19 May, Open ASR Leaderboard results on 29 June, the Q8_0 GGUF on 5 August).", "www.nvidia.com/.well-known/security.txt answered 403 at the 21 October 2026 check for nemotron-3-nano-30b-a3b. The card links NVIDIA's security vulnerability form, and NeMo-Speech.cpp ships a SECURITY.md pointing to NVIDIA PSIRT." ], "score": 73 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/parakeet-tdt-0-6b-v3.json", "live": { "slug": "parakeet-tdt-0-6b-v3", "securityTxt": { "url": "https://nvidia.com/.well-known/security.txt", "state": "unknown", "checkedAt": "2026-11-10T16:08:00.271598775Z" }, "domain": { "domain": "nvidia.com", "registered": "1993-04-20", "source": "https://rdap.verisign.com/com/v1/domain/nvidia.com", "checkedAt": "2026-11-08T15:03:11.895084282Z" }, "pages": [ { "url": "https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3/commits/main", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:23:34.797887041Z", "changedAt": "2026-11-10T16:23:34.797887041Z", "fingerprint": "9ba96031809c" }, { "url": "https://creativecommons.org/licenses/by/4.0/legalcode.en", "kind": "terms", "status": 304, "checkedAt": "2026-11-10T16:12:40.045016004Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e331da57c17e" } ], "updatedAt": "2026-11-10T16:23:34.797887041Z" } }, "answer": "Parakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Parakeet Unified EN 0.6B's 47.5 (D), and leads in 3 of 4 scored categories.", "b": { "slug": "parakeet-unified-en-0-6b", "name": "Parakeet Unified EN 0.6B", "vendor": "NVIDIA", "vendorUrl": "https://github.com/NVIDIA/NeMo", "kind": "weights", "category": "speech-to-text", "summary": "Parakeet Unified EN 0.6B is NVIDIA's open-weight English speech recognition model, a 600M FastConformer encoder with an RNN-T decoder trained for both offline and streaming use down to 160 ms of latency, with punctuation, published as a NeMo archive.", "url": "https://www.anchorterminal.com/tools/parakeet-unified-en-0-6b", "markdownUrl": "https://www.anchorterminal.com/tools/parakeet-unified-en-0-6b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/parakeet-unified-en-0-6b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/parakeet-unified-en-0-6b.json", "dns": "parakeet-unified-en-0-6b.grade.anchorterminal.com", "repo": "https://huggingface.co/nvidia/parakeet-unified-en-0.6b", "license": "NVIDIA Open Model License", "transports": [], "packages": [ { "registry": "huggingface", "name": "nvidia/parakeet-unified-en-0.6b" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-11-10).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under the NVIDIA Open Model License. Running it yourself costs little hardware, a 2.47 GB NeMo archive in FP32 (checked 2026-11-10).", "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 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://huggingface.co/nvidia/parakeet-unified-en-0.6b", "capabilities": [ "speech.stt", "speech.batch", "speech.streaming", "model.open-weights" ], "tags": [ "open-weights", "model", "speech-to-text", "asr", "english", "streaming", "fastconformer", "rnnt", "nemo", "nvidia-open-model-license", "self-hosted" ], "lastRelease": "2026-06-09", "graded": true, "anchor": { "graded": true, "score": 47.5, "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": 1518, "categoryRank": 31, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 35, "reach": 50, "risk": 35, "upkeep": 79 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "One English model for batch and live transcription, with a well-documented data list and an NVIDIA team that answers. It runs only in NVIDIA NeMo from a pickle-format archive, with no safetensors, GGUF or quantised build, returns plain text without timestamps, and hasn't changed since June.", "bestFor": "English voice agents and captioning that want one small model for both recorded and live audio and already run NeMo", "strengths": [ "One model for offline and streaming transcription, down to 160 ms of latency", "Small: a 2.47 GB file that fits any machine", "Training datasets listed by name with hours", "NVIDIA replied in every discussion on the repository", "A security reporting route and public bulletins from NVIDIA" ], "weaknesses": [ "The only file is a NeMo archive holding a pickle checkpoint", "NVIDIA NeMo is the only runtime; none of the six we count runs it", "No timestamps or other typed output documented", "English only", "A custom licence with a use policy that NVIDIA can change", "No commit since 9 June 2026" ], "agentNotes": [ "Load it with NeMo: `nemo_asr.models.ASRModel.from_pretrained(model_name='nvidia/parakeet-unified-en-0.6b')`, then `transcribe([path])[0].text`", "Loading a .nemo archive unpickles a PyTorch checkpoint, so only load it from NVIDIA's repository", "Send mono wav audio. English only", "For live audio use NeMo's chunked RNN-T streaming script with a 5.6 s left context, and pick the chunk and right context from the card's table", "Below 240 ms of latency accuracy drops, and at 80 ms NVIDIA recommends its nemotron-speech-streaming-en-0.6b instead", "If you need word timestamps, use Parakeet TDT 0.6B v3" ], "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": 47.5 } ], "editorialScores": { "interface": 35, "reach": 50, "risk": 35, "upkeep": 79 }, "provenanceScore": 74, "checked": { "categories": { "interface": "2026-11-10", "reach": "2026-11-10", "risk": "2026-11-10", "upkeep": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install -U \"nemo_toolkit[asr]\"\npython -c \"import nemo.collections.asr as nemo_asr; m = nemo_asr.models.ASRModel.from_pretrained(model_name='nvidia/parakeet-unified-en-0.6b'); print(m.transcribe(['speech.wav'])[0].text)\"", "http": "# no HTTP server ships with it. For streaming, NeMo's script:\npython examples/asr/asr_chunked_inference/rnnt/speech_to_text_streaming_infer_rnnt.py \\\n pretrained_name=nvidia/parakeet-unified-en-0.6b dataset_manifest=manifest.json \\\n left_context_secs=5.6 chunk_secs=0.56 right_context_secs=0.56 att_context_size_as_chunk=true" }, "letme": { "capability": "https://letme.dev/speech.stt", "tool": "https://letme.dev/parakeet-unified-en-0-6b" }, "sameCompany": [ "nemotron-3-5-super-vl", "nvidia-nemo-retriever", "nemo-guardrails", "nemotron-3-5-asr-streaming-0-6b", "nemotron-3-5-transcribe-30b-a4b", "parakeet-tdt-0-6b-v3", "nemotron-3-5-parse", "cosmos-reason2-2b", "nemotron-3-5-bolt-e4b-4gb", "nemotron-3-nano-30b-a3b", "nemotron-3-nano-4b", "nemotron-3-nano-omni-30b-a3b-reasoning", "nemotron-3-super-120b-a12b", "nemotron-3-ultra-550b-a55b", "nemotron-3-5-lightning-30b-a3b" ], "weights": { "trainedBy": "NVIDIA", "params": "0.6B", "goodFor": "English transcription from one model in both batch and live use, with punctuation and capitalisation, where latency of 160 ms to 2 s matters.", "runtimes": [], "builds": [ { "name": "parakeet-unified-en-0.6b.nemo", "url": "https://huggingface.co/nvidia/parakeet-unified-en-0.6b/blob/main/parakeet-unified-en-0.6b.nemo", "who": "publisher", "precision": "fp32", "sizeGB": 2.47, "memoryGB": 8, "format": "nemo", "runsOn": [ "NeMo" ], "note": "A NeMo archive holding a PyTorch checkpoint (pickle), loaded by NeMo's ASRModel.from_pretrained. The only build" } ], "run": "python -c \"import nemo.collections.asr as nemo_asr; print(nemo_asr.models.ASRModel.from_pretrained(model_name='nvidia/parakeet-unified-en-0.6b').transcribe(['speech.wav'])[0].text)\"", "runBuild": "parakeet-unified-en-0.6b.nemo", "checked": "2026-11-10", "minMemoryGB": 8 }, "family": { "lab": "NVIDIA (Nemotron)", "family": "Parakeet", "url": "https://www.anchorterminal.com/open-weights/#nvidia", "others": [ { "name": "parakeet-rnnt-1.1b", "url": "https://huggingface.co/nvidia/parakeet-rnnt-1.1b", "params": "1.1B" }, { "name": "parakeet-ctc-1.1b", "url": "https://huggingface.co/nvidia/parakeet-ctc-1.1b", "params": "1.1B" }, { "name": "parakeet-rnnt-0.6b", "url": "https://huggingface.co/nvidia/parakeet-rnnt-0.6b", "params": "0.6B" }, { "name": "parakeet-ctc-0.6b", "url": "https://huggingface.co/nvidia/parakeet-ctc-0.6b", "params": "0.6B" }, { "name": "parakeet-tdt-1.1b", "url": "https://huggingface.co/nvidia/parakeet-tdt-1.1b", "params": "1.1B" }, { "name": "parakeet-tdt_ctc-1.1b", "url": "https://huggingface.co/nvidia/parakeet-tdt_ctc-1.1b", "params": "1.1B" }, { "name": "parakeet-tdt_ctc-0.6b-ja", "url": "https://huggingface.co/nvidia/parakeet-tdt_ctc-0.6b-ja", "params": "0.6B" }, { "name": "parakeet-tdt_ctc-110m", "url": "https://huggingface.co/nvidia/parakeet-tdt_ctc-110m", "params": "110M" }, { "name": "parakeet-tdt-0.6b-v2", "url": "https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2", "params": "0.6B" }, { "name": "parakeet-rnnt-110m-da-dk", "url": "https://huggingface.co/nvidia/parakeet-rnnt-110m-da-dk", "params": "110M" }, { "name": "parakeet-tdt-0.6b-v3", "url": "https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3", "params": "0.6B (627M per the safetensors count)", "listing": "https://www.anchorterminal.com/tools/parakeet-tdt-0-6b-v3" }, { "name": "parakeet_realtime_eou_120m-v1", "url": "https://huggingface.co/nvidia/parakeet_realtime_eou_120m-v1", "params": "120M" }, { "name": "multitalker-parakeet-streaming-0.6b-v1", "url": "https://huggingface.co/nvidia/multitalker-parakeet-streaming-0.6b-v1", "params": "0.6B" }, { "name": "parakeet-ctc-0.6b-Vietnamese", "url": "https://huggingface.co/nvidia/parakeet-ctc-0.6b-Vietnamese", "params": "0.6B" } ], "olderCount": 47 }, "area": "voice", "provenance": { "legalEntity": "NVIDIA Corporation", "domain": "nvidia.com", "domainRegistered": "1993-04-20", "endpointOnVendorDomain": null, "terms": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/nvidia/parakeet-unified-en-0.6b/commits/main", "securityTxt": "none", "checked": "2026-11-10", "notes": [ "The model sits in NVIDIA's Hugging Face organisation and the card's governing terms are the NVIDIA Open Model License. The domain registration date is carried from the RDAP check made for nemotron-3-nano-30b-a3b on 21 October 2026.", "Nothing is hosted for this listing, so the licence stands in for terms of service and no privacy policy is scored.", "The changelog is the commit history, 19 commits from 7 April to 9 June 2026, mostly card edits.", "www.nvidia.com/.well-known/security.txt answered 403 at the 21 October 2026 check for nemotron-3-nano-30b-a3b. The card links NVIDIA's security vulnerability form." ], "score": 74 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/parakeet-unified-en-0-6b.json" }, "edges": [ { "by": 25, "category": "risk", "leads": "parakeet-tdt-0-6b-v3", "name": "Risk", "reasons": { "a": "File safety gets 15 because the NeMo archive, the card's main loading path, holds a PyTorch pickle beside the safetensors and GGUF, with no remote code. Provenance gets 15 for files in NVIDIA's organisation with SHA-256 hashes. CC BY 4.0 carries none of the deductions, so licence risk keeps 15. The PSIRT route and bulletins give the security programme 10. Agent guidance gets 5 for general accuracy cautions, and safety evaluation 0 with none published.", "b": "File safety 0, the only weights file is parakeet-unified-en-0.6b.nemo, a NeMo archive whose weights are a PyTorch checkpoint read with torch.load, a pickle format, and the card's documented path loads it. Provenance 15, the file sits in NVIDIA's own Hugging Face organisation, the one NVIDIA's NeMo repositories link to (10), and the Hub gives a SHA-256 for the archive and git hashes for the rest (5). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions only. Licence risk 5, 15 less 5 for a use policy beyond the law (NVIDIA's Trustworthy AI terms and the guardrail clause) and 5 for terms the licensor can change or revoke, as read for NVIDIA's other listings under the same licence. Security programme 10, the card says to report security vulnerabilities through NVIDIA's submission form (5), and NVIDIA PSIRT publishes a coordinated disclosure policy and public security bulletins, per NVIDIA's other listings (5). 0 + 15 + 0 + 5 + 5 + 10 = 35." }, "scores": { "a": 60, "b": 35 } }, { "by": 15, "category": "reach", "leads": "parakeet-tdt-0-6b-v3", "name": "Reach", "reasons": { "a": "Memory earns the full 30, NVIDIA's Q8_0 GGUF being 0.71 GB and even the FP32 files under 3 GB with the fifth added. Runtimes score 5, since among the six only Transformers runs it in a release; it otherwise runs on NVIDIA's own NeMo and NeMo-Speech.cpp. One quantised build from NVIDIA, the Q8_0 GGUF, gives builds 10. CC BY 4.0 allows free commercial use but isn't OSI-approved, so terms get 10. Ungated files give download the full 10, and hosted too stays 0, since Hugging Face's mapping lists no inference provider on 1 November (Together on 21 October) and no NVIDIA API serving v3 was confirmed. Runtimes re-read on 1 November at vLLM v0.33.0 and llama.cpp b12032, still no TDT decoder.", "b": "Memory 30, the only build is the FP32 NeMo archive, 2.47 GB, and 2.47 GB × 1.2 = 3.0 GB, under 16 GB. Runtimes 0, none of the six runs it in a released version. Builds 0, NVIDIA publishes no quantised build of it. Terms 10, the NVIDIA Open Model License is a custom licence, not OSI-approved, that lets anyone use the model commercially for free under a use policy, which is the custom-licence band, as on NVIDIA's other listings. Download 10, the Hub API reports gated false on 10 November 2026, so the file downloads with no account and nothing to accept. Hosted 0, Hugging Face's inference provider mapping is empty on 10 November 2026, and the card names no NVIDIA API that serves it. 30 + 0 + 0 + 10 + 10 + 0 = 50." }, "scores": { "a": 65, "b": 50 } }, { "by": 15, "category": "interface", "leads": "parakeet-tdt-0-6b-v3", "name": "Agent interface", "reasons": { "a": "Read for a speech model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns. NVIDIA documents the audio it takes and the text and timestamps it returns, with code to read them (25). It takes one clip with no hints or prompt (10). Timestamps at three levels are documented with how to ask for them (15). There is no chat template, reasoning or token context to score, so those lines are 0 under the checklist's no not-applicable rule.", "b": "Chat template 0, no chat template and no prompt. Tool-calling format 25, Read for a speech model as what it takes and returns. Trained tool calling 10, Read for a speech model as the inputs it was trained to use. Structured output 0, Read for a speech model as typed outputs. Reasoning control 0, A speech recognition model with no reasoning. Context 0, no token context is stated. 0 + 25 + 10 + 0 + 0 + 0 = 35." }, "scores": { "a": 50, "b": 35 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "NVIDIA", "b": "NVIDIA", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "CC-BY-4.0", "b": "NVIDIA Open Model License", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-08-05", "b": "2026-06-09", "name": "Last release" }, { "a": "no date given", "b": "2025-10-24", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "yes", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "4/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Parakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Parakeet Unified EN 0.6B's 47.5 (D), and leads in 3 of 4 scored categories.", "question": "Which is better for AI agents, Parakeet TDT 0.6B v3 or Parakeet Unified EN 0.6B?" } ], "goodFor": [ { "aheadOn": [ "Reach, 65 against 50", "Risk, 60 against 35", "Agent interface, 50 against 35" ], "also": null, "goodFor": "Agents that need cheap local transcription with timestamps in English and other European languages", "slug": "parakeet-tdt-0-6b-v3", "watchFor": "Among the six runtimes only Transformers runs it; vLLM, SGLang, llama.cpp, Ollama and LM Studio don't" }, { "aheadOn": null, "also": null, "goodFor": "English voice agents and captioning that want one small model for both recorded and live audio and already run NeMo", "slug": "parakeet-unified-en-0-6b", "watchFor": "The only file is a NeMo archive holding a pickle checkpoint" } ], "history": null, "job": { "capability": "speech.stt", "name": "Speech-to-text" }, "others": [ { "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-parakeet-tdt-0-6b-v3.json", "title": "Cohere Transcribe 03-2026 vs Parakeet TDT 0.6B v3", "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-parakeet-tdt-0-6b-v3" }, { "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-parakeet-unified-en-0-6b.json", "title": "Cohere Transcribe 03-2026 vs Parakeet Unified EN 0.6B", "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-parakeet-unified-en-0-6b" }, { "json": "https://www.anchorterminal.com/compare/granite-speech-5-0-2b-vs-parakeet-tdt-0-6b-v3.json", "title": "Granite Speech 5.0 2B vs Parakeet TDT 0.6B v3", "url": "https://www.anchorterminal.com/compare/granite-speech-5-0-2b-vs-parakeet-tdt-0-6b-v3" }, { "json": "https://www.anchorterminal.com/compare/granite-speech-5-0-2b-vs-parakeet-unified-en-0-6b.json", "title": "Granite Speech 5.0 2B vs Parakeet Unified EN 0.6B", "url": "https://www.anchorterminal.com/compare/granite-speech-5-0-2b-vs-parakeet-unified-en-0-6b" }, { "json": "https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-parakeet-tdt-0-6b-v3.json", "title": "Ming-3.0-asr-tiny vs Parakeet TDT 0.6B v3", "url": "https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-parakeet-tdt-0-6b-v3" }, { "json": "https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-parakeet-unified-en-0-6b.json", "title": "Ming-3.0-asr-tiny vs Parakeet Unified EN 0.6B", "url": "https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-parakeet-unified-en-0-6b" }, { "json": "https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-parakeet-tdt-0-6b-v3.json", "title": "Ming-3.0-audio-flash vs Parakeet TDT 0.6B v3", "url": "https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-parakeet-tdt-0-6b-v3" }, { "json": "https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-parakeet-unified-en-0-6b.json", "title": "Ming-3.0-audio-flash vs Parakeet Unified EN 0.6B", "url": "https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-parakeet-unified-en-0-6b" }, { "json": "https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-parakeet-tdt-0-6b-v3.json", "title": "Ming-3.0-audio-tiny vs Parakeet TDT 0.6B v3", "url": "https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-parakeet-tdt-0-6b-v3" }, { "json": "https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-parakeet-unified-en-0-6b.json", "title": "Ming-3.0-audio-tiny vs Parakeet Unified EN 0.6B", "url": "https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-parakeet-unified-en-0-6b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-parakeet-tdt-0-6b-v3.json", "title": "Nemotron 3.5 ASR Streaming 0.6B vs Parakeet TDT 0.6B v3", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-parakeet-tdt-0-6b-v3" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-parakeet-unified-en-0-6b.json", "title": "Nemotron 3.5 ASR Streaming 0.6B vs Parakeet Unified EN 0.6B", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-parakeet-unified-en-0-6b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-tdt-0-6b-v3.json", "title": "Nemotron 3.5 Transcribe 30B-A4B vs Parakeet TDT 0.6B v3", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-tdt-0-6b-v3" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-unified-en-0-6b.json", "title": "Nemotron 3.5 Transcribe 30B-A4B vs Parakeet Unified EN 0.6B", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-unified-en-0-6b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-parakeet-tdt-0-6b-v3.json", "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Parakeet TDT 0.6B v3", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-parakeet-tdt-0-6b-v3" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-parakeet-unified-en-0-6b.json", "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Parakeet Unified EN 0.6B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-parakeet-unified-en-0-6b" }, { "json": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-0-6b.json", "title": "Parakeet TDT 0.6B v3 vs Qwen3-ASR-0.6B", "url": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-0-6b" }, { "json": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-1-7b.json", "title": "Parakeet TDT 0.6B v3 vs Qwen3-ASR-1.7B", "url": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-1-7b" }, { "json": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Parakeet TDT 0.6B v3 vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-underdog-bark-3.json", "title": "Parakeet TDT 0.6B v3 vs Underdog Bark 3.0", "url": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-underdog-bark-3" }, { "json": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-voxtral-mini-4b-realtime-2602.json", "title": "Parakeet TDT 0.6B v3 vs Voxtral Mini 4B Realtime 2602", "url": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-voxtral-mini-4b-realtime-2602" }, { "json": "https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-qwen3-asr-0-6b.json", "title": "Parakeet Unified EN 0.6B vs Qwen3-ASR-0.6B", "url": "https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-qwen3-asr-0-6b" }, { "json": "https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-qwen3-asr-1-7b.json", "title": "Parakeet Unified EN 0.6B vs Qwen3-ASR-1.7B", "url": "https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-qwen3-asr-1-7b" }, { "json": "https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Parakeet Unified EN 0.6B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-underdog-bark-3.json", "title": "Parakeet Unified EN 0.6B vs Underdog Bark 3.0", "url": "https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-underdog-bark-3" }, { "json": "https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-voxtral-mini-4b-realtime-2602.json", "title": "Parakeet Unified EN 0.6B vs Voxtral Mini 4B Realtime 2602", "url": "https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-voxtral-mini-4b-realtime-2602" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 15, "edge": "parakeet-tdt-0-6b-v3", "key": "reach", "name": "Reach", "parakeet-tdt-0-6b-v3": 65, "parakeet-unified-en-0-6b": 50, "weight": 25 }, { "by": 25, "edge": "parakeet-tdt-0-6b-v3", "key": "risk", "name": "Risk", "parakeet-tdt-0-6b-v3": 60, "parakeet-unified-en-0-6b": 35, "weight": 20 }, { "by": 15, "edge": "parakeet-tdt-0-6b-v3", "key": "interface", "name": "Agent interface", "parakeet-tdt-0-6b-v3": 50, "parakeet-unified-en-0-6b": 35, "weight": 10 }, { "by": 2, "edge": "parakeet-unified-en-0-6b", "key": "upkeep", "name": "Documentation and upkeep", "parakeet-tdt-0-6b-v3": 77, "parakeet-unified-en-0-6b": 79, "weight": 10 } ], "summary": "Parakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Parakeet Unified EN 0.6B's 47.5 (D), and leads in 3 of 4 scored categories. Both do speech-to-text.", "tasks": null, "tutorials": [], "verdicts": { "parakeet-tdt-0-6b-v3": "A small, fast transcription cousin for 25 European languages that detects the language and returns punctuated text with word timestamps. It fits in under 1 GB as NVIDIA's GGUF and runs in Transformers, NeMo or NVIDIA's C++ runtime, under CC BY 4.0. Few other runtimes load it, and it takes no language hint.", "parakeet-unified-en-0-6b": "One English model for batch and live transcription, with a well-documented data list and an NVIDIA team that answers. It runs only in NVIDIA NeMo from a pickle-format archive, with no safetensors, GGUF or quantised build, returns plain text without timestamps, and hasn't changed since June." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-parakeet-unified-en-0-6b", "json": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-parakeet-unified-en-0-6b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-parakeet-unified-en-0-6b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-parakeet-unified-en-0-6b.min.md" }, "markdown": "Parakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Parakeet Unified EN 0.6B's 47.5 (D), and leads in 3 of 4 scored categories. Both do speech-to-text.\n\n- Parakeet TDT 0.6B v3: grade B, 66.9/100, rank #14 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/parakeet-tdt-0-6b-v3.md · JSON https://www.anchorterminal.com/api/v1/tools/parakeet-tdt-0-6b-v3.json\n- Parakeet Unified EN 0.6B: grade D, 47.5/100, rank #154 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/parakeet-unified-en-0-6b.md · JSON https://www.anchorterminal.com/api/v1/tools/parakeet-unified-en-0-6b.json\n- Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md\n- All 386 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md\n\n## Which one, for what\n\n### Parakeet TDT 0.6B v3 (B)\n\nGood for: Agents that need cheap local transcription with timestamps in English and other European languages\n\nAhead on:\n- Reach, 65 against 50\n- Risk, 60 against 35\n- Agent interface, 50 against 35\n\nWatch for: Among the six runtimes only Transformers runs it; vLLM, SGLang, llama.cpp, Ollama and LM Studio don't\n\n### Parakeet Unified EN 0.6B (D)\n\nGood for: English voice agents and captioning that want one small model for both recorded and live audio and already run NeMo\n\nWatch for: The only file is a NeMo archive holding a pickle checkpoint\n\n\n## Why the edge\n\n### Risk: Parakeet TDT 0.6B v3 +25\n\n- Parakeet TDT 0.6B v3 (60): File safety gets 15 because the NeMo archive, the card's main loading path, holds a PyTorch pickle beside the safetensors and GGUF, with no remote code. Provenance gets 15 for files in NVIDIA's organisation with SHA-256 hashes. CC BY 4.0 carries none of the deductions, so licence risk keeps 15. The PSIRT route and bulletins give the security programme 10. Agent guidance gets 5 for general accuracy cautions, and safety evaluation 0 with none published.\n- Parakeet Unified EN 0.6B (35): File safety 0, the only weights file is parakeet-unified-en-0.6b.nemo, a NeMo archive whose weights are a PyTorch checkpoint read with torch.load, a pickle format, and the card's documented path loads it. Provenance 15, the file sits in NVIDIA's own Hugging Face organisation, the one NVIDIA's NeMo repositories link to (10), and the Hub gives a SHA-256 for the archive and git hashes for the rest (5). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions only. Licence risk 5, 15 less 5 for a use policy beyond the law (NVIDIA's Trustworthy AI terms and the guardrail clause) and 5 for terms the licensor can change or revoke, as read for NVIDIA's other listings under the same licence. Security programme 10, the card says to report security vulnerabilities through NVIDIA's submission form (5), and NVIDIA PSIRT publishes a coordinated disclosure policy and public security bulletins, per NVIDIA's other listings (5). 0 + 15 + 0 + 5 + 5 + 10 = 35.\n\n### Reach: Parakeet TDT 0.6B v3 +15\n\n- Parakeet TDT 0.6B v3 (65): Memory earns the full 30, NVIDIA's Q8_0 GGUF being 0.71 GB and even the FP32 files under 3 GB with the fifth added. Runtimes score 5, since among the six only Transformers runs it in a release; it otherwise runs on NVIDIA's own NeMo and NeMo-Speech.cpp. One quantised build from NVIDIA, the Q8_0 GGUF, gives builds 10. CC BY 4.0 allows free commercial use but isn't OSI-approved, so terms get 10. Ungated files give download the full 10, and hosted too stays 0, since Hugging Face's mapping lists no inference provider on 1 November (Together on 21 October) and no NVIDIA API serving v3 was confirmed. Runtimes re-read on 1 November at vLLM v0.33.0 and llama.cpp b12032, still no TDT decoder.\n- Parakeet Unified EN 0.6B (50): Memory 30, the only build is the FP32 NeMo archive, 2.47 GB, and 2.47 GB × 1.2 = 3.0 GB, under 16 GB. Runtimes 0, none of the six runs it in a released version. Builds 0, NVIDIA publishes no quantised build of it. Terms 10, the NVIDIA Open Model License is a custom licence, not OSI-approved, that lets anyone use the model commercially for free under a use policy, which is the custom-licence band, as on NVIDIA's other listings. Download 10, the Hub API reports gated false on 10 November 2026, so the file downloads with no account and nothing to accept. Hosted 0, Hugging Face's inference provider mapping is empty on 10 November 2026, and the card names no NVIDIA API that serves it. 30 + 0 + 0 + 10 + 10 + 0 = 50.\n\n### Agent interface: Parakeet TDT 0.6B v3 +15\n\n- Parakeet TDT 0.6B v3 (50): Read for a speech model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns. NVIDIA documents the audio it takes and the text and timestamps it returns, with code to read them (25). It takes one clip with no hints or prompt (10). Timestamps at three levels are documented with how to ask for them (15). There is no chat template, reasoning or token context to score, so those lines are 0 under the checklist's no not-applicable rule.\n- Parakeet Unified EN 0.6B (35): Chat template 0, no chat template and no prompt. Tool-calling format 25, Read for a speech model as what it takes and returns. Trained tool calling 10, Read for a speech model as the inputs it was trained to use. Structured output 0, Read for a speech model as typed outputs. Reasoning control 0, A speech recognition model with no reasoning. Context 0, no token context is stated. 0 + 25 + 10 + 0 + 0 + 0 = 35.\n\n## Score by category\n\n| Category | Weight | Parakeet TDT 0.6B v3 | Parakeet Unified EN 0.6B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 65 | 50 | Parakeet TDT 0.6B v3 +15 |\n| Risk | 20% (20 this run) | 60 | 35 | Parakeet TDT 0.6B v3 +25 |\n| Agent interface | 10% (10 this run) | 50 | 35 | Parakeet TDT 0.6B v3 +15 |\n| Documentation and upkeep | 10% (10 this run) | 77 | 79 | Parakeet Unified EN 0.6B +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **66.9 · B** | **47.5 · D** | |\n\n## Facts side by side\n\n| Fact | Parakeet TDT 0.6B v3 | Parakeet Unified EN 0.6B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | NVIDIA | NVIDIA |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | CC-BY-4.0 | NVIDIA Open Model License |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-05 | 2026-06-09 |\n| Terms last updated | no date given | 2025-10-24 |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | not found in the text | yes |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Agent reviews | 4/5 (4) | none |\n\n## Verdicts\n\n**Parakeet TDT 0.6B v3.** A small, fast transcription cousin for 25 European languages that detects the language and returns punctuated text with word timestamps. It fits in under 1 GB as NVIDIA's GGUF and runs in Transformers, NeMo or NVIDIA's C++ runtime, under CC BY 4.0. Few other runtimes load it, and it takes no language hint.\n\n**Parakeet Unified EN 0.6B.** One English model for batch and live transcription, with a well-documented data list and an NVIDIA team that answers. It runs only in NVIDIA NeMo from a pickle-format archive, with no safetensors, GGUF or quantised build, returns plain text without timestamps, and hasn't changed since June.\n\n## Before you call either\n\n### Parakeet TDT 0.6B v3\n\n1. For the smallest setup, `hf download nvidia/parakeet-tdt-0.6b-v3 parakeet-tdt-0.6b-v3.q8_0.gguf --local-dir models`, then `nemo-speech transcribe speech.wav --model models/parakeet-tdt-0.6b-v3.q8_0.gguf` with NeMo-Speech.cpp\n2. In Python, `pipeline('automatic-speech-recognition', model='nvidia/parakeet-tdt-0.6b-v3')` works on Transformers 5.10.0 or later, despite the card's note to install from source\n3. Resample to 16 kHz mono first; it takes wav or flac\n4. Ask for timestamps with `timestamps=True` in NeMo, or pass `durations=output.durations` to `processor.decode` in Transformers\n5. For audio longer than about 24 minutes, switch NeMo to local attention with `change_attention_model(\"rel_pos_local_attn\", [256, 256])`\n6. Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions\n\n### Parakeet Unified EN 0.6B\n\n1. Load it with NeMo: `nemo_asr.models.ASRModel.from_pretrained(model_name='nvidia/parakeet-unified-en-0.6b')`, then `transcribe([path])[0].text`\n2. Loading a .nemo archive unpickles a PyTorch checkpoint, so only load it from NVIDIA's repository\n3. Send mono wav audio. English only\n4. For live audio use NeMo's chunked RNN-T streaming script with a 5.6 s left context, and pick the chunk and right context from the card's table\n5. Below 240 ms of latency accuracy drops, and at 80 ms NVIDIA recommends its nemotron-speech-streaming-en-0.6b instead\n6. If you need word timestamps, use Parakeet TDT 0.6B v3\n\n## Questions\n\n### Which is better for AI agents, Parakeet TDT 0.6B v3 or Parakeet Unified EN 0.6B?\n\nParakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Parakeet Unified EN 0.6B's 47.5 (D), and leads in 3 of 4 scored categories.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-parakeet-unified-en-0-6b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-parakeet-unified-en-0-6b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"parakeet-tdt-0-6b-v3\", \"b\": \"parakeet-unified-en-0-6b\"}`. From a terminal: `anchor compare parakeet-tdt-0-6b-v3 parakeet-unified-en-0-6b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/parakeet-tdt-0-6b-v3.json and https://www.anchorterminal.com/api/v1/tools/parakeet-unified-en-0-6b.json\n\n## Other comparisons with Parakeet TDT 0.6B v3 or Parakeet Unified EN 0.6B\n\n- [Cohere Transcribe 03-2026 vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-parakeet-tdt-0-6b-v3.md)\n- [Cohere Transcribe 03-2026 vs Parakeet Unified EN 0.6B](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-parakeet-unified-en-0-6b.md)\n- [Granite Speech 5.0 2B vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/granite-speech-5-0-2b-vs-parakeet-tdt-0-6b-v3.md)\n- [Granite Speech 5.0 2B vs Parakeet Unified EN 0.6B](https://www.anchorterminal.com/compare/granite-speech-5-0-2b-vs-parakeet-unified-en-0-6b.md)\n- [Ming-3.0-asr-tiny vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-parakeet-tdt-0-6b-v3.md)\n- [Ming-3.0-asr-tiny vs Parakeet Unified EN 0.6B](https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-parakeet-unified-en-0-6b.md)\n- [Ming-3.0-audio-flash vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-parakeet-tdt-0-6b-v3.md)\n- [Ming-3.0-audio-flash vs Parakeet Unified EN 0.6B](https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-parakeet-unified-en-0-6b.md)\n- [Ming-3.0-audio-tiny vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-parakeet-tdt-0-6b-v3.md)\n- [Ming-3.0-audio-tiny vs Parakeet Unified EN 0.6B](https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-parakeet-unified-en-0-6b.md)\n- [Nemotron 3.5 ASR Streaming 0.6B vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-parakeet-tdt-0-6b-v3.md)\n- [Nemotron 3.5 ASR Streaming 0.6B vs Parakeet Unified EN 0.6B](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-parakeet-unified-en-0-6b.md)\n- [Nemotron 3.5 Transcribe 30B-A4B vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-tdt-0-6b-v3.md)\n- [Nemotron 3.5 Transcribe 30B-A4B vs Parakeet Unified EN 0.6B](https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-unified-en-0-6b.md)\n- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-parakeet-tdt-0-6b-v3.md)\n- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Parakeet Unified EN 0.6B](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-parakeet-unified-en-0-6b.md)\n- [Parakeet TDT 0.6B v3 vs Qwen3-ASR-0.6B](https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-0-6b.md)\n- [Parakeet TDT 0.6B v3 vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-1-7b.md)\n- [Parakeet TDT 0.6B v3 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Parakeet TDT 0.6B v3 vs Underdog Bark 3.0](https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-underdog-bark-3.md)\n- [Parakeet TDT 0.6B v3 vs Voxtral Mini 4B Realtime 2602](https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-voxtral-mini-4b-realtime-2602.md)\n- [Parakeet Unified EN 0.6B vs Qwen3-ASR-0.6B](https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-qwen3-asr-0-6b.md)\n- [Parakeet Unified EN 0.6B vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-qwen3-asr-1-7b.md)\n- [Parakeet Unified EN 0.6B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Parakeet Unified EN 0.6B vs Underdog Bark 3.0](https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-underdog-bark-3.md)\n- [Parakeet Unified EN 0.6B vs Voxtral Mini 4B Realtime 2602](https://www.anchorterminal.com/compare/parakeet-unified-en-0-6b-vs-voxtral-mini-4b-realtime-2602.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": "2026-11-11", "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": "Parakeet TDT 0.6B v3 vs Parakeet Unified EN 0.6B", "url": "" } ], "description": "Parakeet TDT 0.6B v3 scores 66.9 (B) to Parakeet Unified EN 0.6B's 47.5 (D) for speech-to-text. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Parakeet TDT 0.6B v3 B 66.9", "Parakeet Unified EN 0.6B D 47.5", "scores" ], "h1": "Parakeet TDT 0.6B v3 vs Parakeet Unified EN 0.6B", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/parakeet-tdt-0-6b-v3-vs-parakeet-unified-en-0-6b", "published": "2026-10-01", "section": "tools", "title": "Parakeet TDT 0.6B v3 vs Parakeet Unified EN 0.6B for AI agents (2026)", "toc": null, "updated": "2026-11-10", "url": "https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-parakeet-unified-en-0-6b" }, "tokens": { "markdown": 3700, "slim": 730 }, "version": 1 }