{
  "data": {
    "a": {
      "slug": "nemotron-3-5-asr-streaming-0-6b",
      "name": "Nemotron 3.5 ASR Streaming 0.6B",
      "vendor": "NVIDIA",
      "vendorUrl": "https://developer.nvidia.com/nemotron",
      "kind": "weights",
      "category": "speech-to-text",
      "summary": "Nemotron 3.5 ASR Streaming 0.6B is NVIDIA's open-weight streaming speech recognition model, a 600M-parameter FastConformer with an RNN-T decoder, transcribing 32 language-locales with punctuation and an optional detected-language tag at chunk sizes from 80 ms to 1.12 s, under OpenMDW-1.1.",
      "url": "https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b",
      "markdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/nemotron-3-5-asr-streaming-0-6b.json",
      "repo": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b",
      "license": "OpenMDW-1.1",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "nvidia/nemotron-3.5-asr-streaming-0.6b"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository isn't gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under OpenMDW-1.1 (the Linux Foundation's permissive model licence). NVIDIA sells no per-call access to these weights in this listing. Running them costs the hardware, about 2.6 GB of F32 safetensors or a 0.74 GB Q8_0 GGUF. fal, Together and DeepInfra serve it as inference providers on Hugging Face (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/docs/transformers/en/model_doc/nemotron3_5_asr",
      "capabilities": [
        "speech.stt",
        "speech.streaming",
        "speech.batch",
        "speech.languages",
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "speech-to-text",
        "asr",
        "streaming",
        "multilingual",
        "rnnt",
        "fastconformer",
        "safetensors",
        "gguf",
        "self-hosted"
      ],
      "lastRelease": "2026-09-10",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 59.8,
        "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": 1197,
        "categoryRank": 17,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 54,
          "interface": 50,
          "reach": 70,
          "risk": 60,
          "upkeep": 64
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A small streaming transcription cousin for live audio in about 32 languages, with language detection and 80 ms to 1.12 s latency. It runs in under 8 GB in Transformers or as a 0.74 GB GGUF in NeMo-Speech.cpp, and several providers host it. The main gaps are no documented timestamps and weak accuracy outside the top 19 locales.",
        "bestFor": "Voice agents and call pipelines that need low-latency multilingual streaming transcription on a small GPU or a laptop",
        "strengths": [
          "Tiny, 0.64B parameters, with a 0.74 GB Q8_0 GGUF from NVIDIA and F32 safetensors of 2.55 GB",
          "True cache-aware streaming with chunk sizes from 80 ms to 1.12 s chosen at run time",
          "One model for 32 working locales with automatic language detection and a language tag in the output",
          "Native in Transformers from v5.13.0, no remote code, and hosted by fal, Together and DeepInfra",
          "OpenMDW-1.1, permissive with no use policy, ungated, and NVIDIA answers most discussions"
        ],
        "weaknesses": [
          "Not in vLLM, SGLang, llama.cpp, Ollama or LM Studio; the GGUF needs NVIDIA's NeMo-Speech.cpp",
          "A pickled NeMo checkpoint sits beside the safetensors and NeMo's documented path loads it",
          "Plain text out; timestamps and confidence scores are claimed in a subcard but not documented",
          "Publisher WERs of 23% to 26% across the 13 broad-coverage locales, and 8 locales need fine-tuning",
          "No safety results, and training data without a cut-off"
        ],
        "agentNotes": [
          "Quickest local run, `pip install \"transformers\u003e=5.13.0\"`, then `pipeline(\"automatic-speech-recognition\", model=\"nvidia/nemotron-3.5-asr-streaming-0.6b\")`; the pipeline uses en-US, so pass language= to the processor for anything else",
          "With NeMo-Speech.cpp, `nemo-speech transcribe audio.wav --model nemotron-3.5-asr-streaming-0.6b.q8_0.gguf --language auto`",
          "Pass a locale such as de-DE or a bare code such as de, or auto; in auto mode decode with skip_special_tokens=False to keep the \u003cxx-XX\u003e tag, True to drop it",
          "Pick latency with att_context_size [56, r], r in 0, 1, 3, 6, 13 (80 to 1,120 ms chunks), or processor.set_num_lookahead_tokens in Transformers; bigger chunks are more accurate",
          "Use nvidia/nemotron-speech-streaming-en-0.6b instead for English only, as NVIDIA recommends",
          "Prefer model.safetensors or the GGUF over the .nemo file, which is a pickle",
          "Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions"
        ],
        "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": 59.8
          }
        ],
        "editorialScores": {
          "capability": 54,
          "interface": 50,
          "reach": 70,
          "risk": 60,
          "upkeep": 64
        },
        "provenanceScore": 73,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "pip install \"transformers\u003e=5.13.0\"\npython -c \"from transformers import pipeline; print(pipeline('automatic-speech-recognition', model='nvidia/nemotron-3.5-asr-streaming-0.6b')('speech.wav'))\""
      },
      "letme": {
        "capability": "https://letme.dev/speech.stt",
        "tool": "https://letme.dev/nemotron-3-5-asr-streaming-0-6b"
      },
      "sameCompany": [
        "nemotron-3-5-super-vl",
        "nvidia-nemo-retriever",
        "nemo-guardrails",
        "parakeet-tdt-0-6b-v3",
        "cosmos-reason2-2b",
        "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",
        "builtOn": "nvidia/nemotron-speech-streaming-en-0.6b (NVIDIA's own English model, extended to 40 locales)",
        "params": "0.64B",
        "goodFor": "Low-latency streaming transcription in 32 languages from one small model, with automatic language detection, for voice agents and many parallel streams.",
        "runtimes": [
          "Transformers"
        ],
        "builds": [
          {
            "name": "nemotron-3.5-asr-streaming-0.6b (safetensors)",
            "url": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b/blob/main/model.safetensors",
            "who": "publisher",
            "precision": "fp32",
            "sizeGB": 2.55,
            "memoryGB": 8,
            "format": "safetensors",
            "runsOn": [
              "Transformers"
            ]
          },
          {
            "name": "nemotron-3.5-asr-streaming-0.6b.nemo",
            "url": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b/blob/main/nemotron-3.5-asr-streaming-0.6b.nemo",
            "who": "publisher",
            "precision": "fp32",
            "sizeGB": 2.37,
            "memoryGB": 8,
            "format": "nemo",
            "note": "NeMo checkpoint, a tar archive holding a PyTorch pickle; loads with NeMo from its main branch"
          },
          {
            "name": "nemotron-3.5-asr-streaming-0.6b.q8_0.gguf",
            "url": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b/blob/main/nemotron-3.5-asr-streaming-0.6b.q8_0.gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 0.74,
            "memoryGB": 8,
            "format": "gguf",
            "note": "For NVIDIA's NeMo-Speech.cpp, not llama.cpp (GGUF architecture asr). Re-converted with an embedded SentencePiece tokenizer on 10 September 2026"
          }
        ],
        "run": "hf download nvidia/nemotron-3.5-asr-streaming-0.6b nemotron-3.5-asr-streaming-0.6b.q8_0.gguf --local-dir models \u0026\u0026 nemo-speech transcribe audio.wav --model models/nemotron-3.5-asr-streaming-0.6b.q8_0.gguf --language auto",
        "runBuild": "nemotron-3.5-asr-streaming-0.6b.q8_0.gguf",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "NVIDIA (Nemotron)",
        "family": "Nemotron 3",
        "url": "https://www.anchorterminal.com/open-weights/#nvidia",
        "others": [
          {
            "name": "Nemotron 3 Nano 30B-A3B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16",
            "params": "30B total, 3B active (31.6B per the safetensors index)",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b"
          },
          {
            "name": "Nemotron 3 Nano 30B-A3B Base",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16",
            "params": "30B total, 3B active"
          },
          {
            "name": "Nemotron 3 Super 120B-A12B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16",
            "params": "120B total, 12B active",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-super-120b-a12b"
          },
          {
            "name": "Nemotron 3 Super 120B-A12B Base",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-Base-BF16",
            "params": "120B total, 12B active"
          },
          {
            "name": "Nemotron 3 Nano 4B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-nano-4b"
          },
          {
            "name": "Nemotron 3 Nano Omni 30B-A3B Reasoning",
            "url": "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16",
            "params": "30B total, 3B active",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning"
          },
          {
            "name": "Nemotron 3 Ultra 550B-A55B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16",
            "params": "550B total, 55B active",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b"
          },
          {
            "name": "Nemotron 3 Ultra 550B-A55B Base",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-Base-BF16",
            "params": "550B total, 55B active"
          },
          {
            "name": "Nemotron 3 Ultra 550B-A55B GenRM",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-GenRM",
            "params": "550B total, 55B active"
          },
          {
            "name": "Nemotron 3.5 Lightning 30B-A3B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16",
            "params": "30B total, 3B active",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-lightning-30b-a3b"
          },
          {
            "name": "Nemotron 3.5 Lightning 30B-A3B Base",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-Base-BF16",
            "params": "30B total, 3B active"
          },
          {
            "name": "Nemotron 3.5 Super VL 120B-A12B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16",
            "params": "120B total, 12B active",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-super-vl"
          },
          {
            "name": "Nemotron 3.5 Super VL 120B-A12B Base",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-Base-BF16",
            "params": "120B total, 12B active"
          },
          {
            "name": "Nemotron 3.5 Bolt 74B-A9B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-BF16",
            "params": "74B total, 9B active"
          },
          {
            "name": "Nemotron Labs 3 Elastic 30B-A3B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16",
            "params": "30B total, 3B active"
          },
          {
            "name": "Nemotron Labs 3 Puzzle 75B-A9B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-Labs-3-Puzzle-75B-A9B-BF16",
            "params": "75B total, 9B active"
          },
          {
            "name": "Nemotron 3 Labs Ultra Math SFT",
            "url": "https://huggingface.co/nvidia/Nemotron-3-Labs-Ultra-Math-SFT",
            "params": "550B total, 55B active"
          },
          {
            "name": "Nemotron 3 Labs Ultra Math RL",
            "url": "https://huggingface.co/nvidia/Nemotron-3-Labs-Ultra-Math-RL",
            "params": "550B total, 55B active"
          },
          {
            "name": "Nemotron Labs 3 Competitive Coding 550B-A55B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-Labs-3-Competitive-Coding-550B-A55B-NVFP4",
            "params": "550B total, 55B active"
          }
        ],
        "olderCount": 43
      },
      "area": "voice",
      "provenance": {
        "legalEntity": "NVIDIA Corporation",
        "domain": "nvidia.com",
        "domainRegistered": "1993-04-20",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b/commits/main",
        "securityTxt": "unknown",
        "checked": "2026-10-21",
        "notes": [
          "The card says the model was developed by NVIDIA and the files sit in NVIDIA's verified nvidia organisation on Hugging Face, which developer.nvidia.com links to. The domain registration date is carried from the RDAP check made for nemotron-3-super-120b-a12b on 21 October 2026.",
          "Nothing is hosted in this listing, so the OpenMDW-1.1 licence stands in for terms of service and no privacy policy is scored. The privacy subcard links NVIDIA's privacy policy.",
          "The changelog is the repository's commit history, 36 commits from 15 May to 10 September 2026, the last re-converting the GGUF with an embedded SentencePiece tokenizer.",
          "www.nvidia.com/.well-known/security.txt was not requested again; earlier NVIDIA listings record a 403. The card links NVIDIA's vulnerability submission page."
        ],
        "score": 73
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b.json"
    },
    "answer": "Parakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Nemotron 3.5 ASR Streaming 0.6B's 59.8 (C), and leads in 2 of 5 scored categories. Nemotron 3.5 ASR Streaming 0.6B leads on reach.",
    "b": {
      "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",
      "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": 1197,
        "categoryRank": 11,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 74,
          "interface": 50,
          "reach": 65,
          "risk": 60,
          "upkeep": 77
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-21"
        },
        "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 this month"
        ],
        "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": "0.6",
            "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": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "pip install -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",
        "cosmos-reason2-2b",
        "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"
          }
        ],
        "olderCount": 43
      },
      "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": "2026-10-21",
        "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"
    },
    "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": "OpenMDW-1.1",
        "b": "CC-BY-4.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-09-10",
        "b": "2026-08-05",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "",
        "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": "4/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Parakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Nemotron 3.5 ASR Streaming 0.6B's 59.8 (C), and leads in 2 of 5 scored categories. Nemotron 3.5 ASR Streaming 0.6B leads on reach.",
        "question": "Which is better for AI agents, Nemotron 3.5 ASR Streaming 0.6B or Parakeet TDT 0.6B v3?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 70 against 65"
        ],
        "also": null,
        "goodFor": "Voice agents and call pipelines that need low-latency multilingual streaming transcription on a small GPU or a laptop",
        "slug": "nemotron-3-5-asr-streaming-0-6b",
        "watchFor": "Not in vLLM, SGLang, llama.cpp, Ollama or LM Studio; the GGUF needs NVIDIA's NeMo-Speech.cpp"
      },
      {
        "aheadOn": [
          "Capability, 74 against 54",
          "Documentation and upkeep, 77 against 64"
        ],
        "also": [
          "Rated higher by the reviewer agents, 4.0 against 2.8 out of 5"
        ],
        "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"
      }
    ],
    "job": {
      "capability": "speech.stt",
      "name": "Speech-to-text"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-asr-streaming-0-6b.json",
        "title": "Cohere Transcribe 03-2026 vs Nemotron 3.5 ASR Streaming 0.6B",
        "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-asr-streaming-0-6b"
      },
      {
        "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/ming-3-0-asr-tiny-vs-nemotron-3-5-asr-streaming-0-6b.json",
        "title": "Ming-3.0-asr-tiny vs Nemotron 3.5 ASR Streaming 0.6B",
        "url": "https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-nemotron-3-5-asr-streaming-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-audio-flash-vs-nemotron-3-5-asr-streaming-0-6b.json",
        "title": "Ming-3.0-audio-flash vs Nemotron 3.5 ASR Streaming 0.6B",
        "url": "https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-nemotron-3-5-asr-streaming-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-tiny-vs-nemotron-3-5-asr-streaming-0-6b.json",
        "title": "Ming-3.0-audio-tiny vs Nemotron 3.5 ASR Streaming 0.6B",
        "url": "https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-nemotron-3-5-asr-streaming-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/nemotron-3-5-asr-streaming-0-6b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Nemotron 3.5 ASR Streaming 0.6B vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-qwen3-asr-0-6b.json",
        "title": "Nemotron 3.5 ASR Streaming 0.6B vs Qwen3-ASR-0.6B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-qwen3-asr-0-6b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-qwen3-asr-1-7b.json",
        "title": "Nemotron 3.5 ASR Streaming 0.6B vs Qwen3-ASR-1.7B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-qwen3-asr-1-7b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Nemotron 3.5 ASR Streaming 0.6B vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-underdog-bark-3.json",
        "title": "Nemotron 3.5 ASR Streaming 0.6B vs Underdog Bark 3.0",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-underdog-bark-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-voxtral-mini-4b-realtime-2602.json",
        "title": "Nemotron 3.5 ASR Streaming 0.6B vs Voxtral Mini 4B Realtime 2602",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-voxtral-mini-4b-realtime-2602"
      },
      {
        "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/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"
      }
    ],
    "scores": [
      {
        "by": 20,
        "edge": "parakeet-tdt-0-6b-v3",
        "key": "capability",
        "name": "Capability",
        "nemotron-3-5-asr-streaming-0-6b": 54,
        "parakeet-tdt-0-6b-v3": 74,
        "weight": 35
      },
      {
        "by": 5,
        "edge": "nemotron-3-5-asr-streaming-0-6b",
        "key": "reach",
        "name": "Reach",
        "nemotron-3-5-asr-streaming-0-6b": 70,
        "parakeet-tdt-0-6b-v3": 65,
        "weight": 25
      },
      {
        "by": 0,
        "edge": "",
        "key": "risk",
        "name": "Risk",
        "nemotron-3-5-asr-streaming-0-6b": 60,
        "parakeet-tdt-0-6b-v3": 60,
        "weight": 20
      },
      {
        "by": 0,
        "edge": "",
        "key": "interface",
        "name": "Agent interface",
        "nemotron-3-5-asr-streaming-0-6b": 50,
        "parakeet-tdt-0-6b-v3": 50,
        "weight": 10
      },
      {
        "by": 13,
        "edge": "parakeet-tdt-0-6b-v3",
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "nemotron-3-5-asr-streaming-0-6b": 64,
        "parakeet-tdt-0-6b-v3": 77,
        "weight": 10
      }
    ],
    "summary": "Parakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Nemotron 3.5 ASR Streaming 0.6B's 59.8 (C), and leads in 2 of 5 scored categories. Nemotron 3.5 ASR Streaming 0.6B leads on reach. Both do speech-to-text.",
    "tutorials": [],
    "verdicts": {
      "nemotron-3-5-asr-streaming-0-6b": "A small streaming transcription cousin for live audio in about 32 languages, with language detection and 80 ms to 1.12 s latency. It runs in under 8 GB in Transformers or as a 0.74 GB GGUF in NeMo-Speech.cpp, and several providers host it. The main gaps are no documented timestamps and weak accuracy outside the top 19 locales.",
      "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."
    }
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  "markdown": "Parakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Nemotron 3.5 ASR Streaming 0.6B's 59.8 (C), and leads in 2 of 5 scored categories. Nemotron 3.5 ASR Streaming 0.6B leads on reach. Both do speech-to-text.\n\n- Nemotron 3.5 ASR Streaming 0.6B: grade C, 59.8/100, rank #58 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-5-asr-streaming-0-6b.json\n- Parakeet TDT 0.6B v3: grade B, 66.9/100, rank #13 of 100 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- Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md\n- All 231 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md\n\n## Which one, for what\n\n### Nemotron 3.5 ASR Streaming 0.6B (C)\n\nGood for: Voice agents and call pipelines that need low-latency multilingual streaming transcription on a small GPU or a laptop\n\nAhead on:\n- Reach, 70 against 65\n\nWatch for: Not in vLLM, SGLang, llama.cpp, Ollama or LM Studio; the GGUF needs NVIDIA's NeMo-Speech.cpp\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- Capability, 74 against 54\n- Documentation and upkeep, 77 against 64\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 4.0 against 2.8 out of 5\n\nWatch for: Among the six runtimes only Transformers runs it; vLLM, SGLang, llama.cpp, Ollama and LM Studio don't\n\n\n## Score by category\n\n| Category | Weight | Nemotron 3.5 ASR Streaming 0.6B | Parakeet TDT 0.6B v3 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 54 | 74 | Parakeet TDT 0.6B v3 +20 |\n| Reach | 25% (25 this run) | 70 | 65 | Nemotron 3.5 ASR Streaming 0.6B +5 |\n| Risk | 20% (20 this run) | 60 | 60 | even |\n| Agent interface | 10% (10 this run) | 50 | 50 | even |\n| Documentation and upkeep | 10% (10 this run) | 64 | 77 | Parakeet TDT 0.6B v3 +13 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59.8 · C** | **66.9 · B** | |\n\n## Facts side by side\n\n| Fact | Nemotron 3.5 ASR Streaming 0.6B | Parakeet TDT 0.6B v3 |\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 | OpenMDW-1.1 | CC-BY-4.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-09-10 | 2026-08-05 |\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) | 4/5 (4) |\n\n## Verdicts\n\n**Nemotron 3.5 ASR Streaming 0.6B.** A small streaming transcription cousin for live audio in about 32 languages, with language detection and 80 ms to 1.12 s latency. It runs in under 8 GB in Transformers or as a 0.74 GB GGUF in NeMo-Speech.cpp, and several providers host it. The main gaps are no documented timestamps and weak accuracy outside the top 19 locales.\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## Before you call either\n\n### Nemotron 3.5 ASR Streaming 0.6B\n\n1. Quickest local run, `pip install \"transformers\u003e=5.13.0\"`, then `pipeline(\"automatic-speech-recognition\", model=\"nvidia/nemotron-3.5-asr-streaming-0.6b\")`; the pipeline uses en-US, so pass language= to the processor for anything else\n2. With NeMo-Speech.cpp, `nemo-speech transcribe audio.wav --model nemotron-3.5-asr-streaming-0.6b.q8_0.gguf --language auto`\n3. Pass a locale such as de-DE or a bare code such as de, or auto; in auto mode decode with skip_special_tokens=False to keep the \u003cxx-XX\u003e tag, True to drop it\n4. Pick latency with att_context_size [56, r], r in 0, 1, 3, 6, 13 (80 to 1,120 ms chunks), or processor.set_num_lookahead_tokens in Transformers; bigger chunks are more accurate\n5. Use nvidia/nemotron-speech-streaming-en-0.6b instead for English only, as NVIDIA recommends\n6. Prefer model.safetensors or the GGUF over the .nemo file, which is a pickle\n7. Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions\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## Questions\n\n### Which is better for AI agents, Nemotron 3.5 ASR Streaming 0.6B or Parakeet TDT 0.6B v3?\n\nParakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Nemotron 3.5 ASR Streaming 0.6B's 59.8 (C), and leads in 2 of 5 scored categories. Nemotron 3.5 ASR Streaming 0.6B leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-parakeet-tdt-0-6b-v3.json, and with the fewest tokens: https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-parakeet-tdt-0-6b-v3.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"nemotron-3-5-asr-streaming-0-6b\", \"b\": \"parakeet-tdt-0-6b-v3\"}`. From a terminal: `anchor compare nemotron-3-5-asr-streaming-0-6b parakeet-tdt-0-6b-v3`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/nemotron-3-5-asr-streaming-0-6b.json and https://www.anchorterminal.com/api/v1/tools/parakeet-tdt-0-6b-v3.json\n\n## Other comparisons with Nemotron 3.5 ASR Streaming 0.6B or Parakeet TDT 0.6B v3\n\n- [Cohere Transcribe 03-2026 vs Nemotron 3.5 ASR Streaming 0.6B](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-asr-streaming-0-6b.md)\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- [Ming-3.0-asr-tiny vs Nemotron 3.5 ASR Streaming 0.6B](https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-nemotron-3-5-asr-streaming-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-audio-flash vs Nemotron 3.5 ASR Streaming 0.6B](https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-nemotron-3-5-asr-streaming-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-tiny vs Nemotron 3.5 ASR Streaming 0.6B](https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-nemotron-3-5-asr-streaming-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- [Nemotron 3.5 ASR Streaming 0.6B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Nemotron 3.5 ASR Streaming 0.6B vs Qwen3-ASR-0.6B](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-qwen3-asr-0-6b.md)\n- [Nemotron 3.5 ASR Streaming 0.6B vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-qwen3-asr-1-7b.md)\n- [Nemotron 3.5 ASR Streaming 0.6B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Nemotron 3.5 ASR Streaming 0.6B vs Underdog Bark 3.0](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-underdog-bark-3.md)\n- [Nemotron 3.5 ASR Streaming 0.6B vs Voxtral Mini 4B Realtime 2602](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-voxtral-mini-4b-realtime-2602.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- [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",
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    "title": "Nemotron 3.5 ASR Streaming 0.6B vs Parakeet TDT 0.6B v3 (2026)",
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