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    "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.",
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    "license": "OpenMDW-1.1",
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    "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).",
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      "endpoints": []
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      "npmWeekly": null,
      "pypiWeekly": null,
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      "speech.languages",
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      "open-weights",
      "model",
      "speech-to-text",
      "asr",
      "streaming",
      "multilingual",
      "rnnt",
      "fastconformer",
      "safetensors",
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      "self-hosted"
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        "interface": 50,
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          "points": 18.9,
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          "checked": "2026-10-21"
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          "interface": "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, the language prompt and the chunk settings, and the language-tagged output with how to strip the tag in Transformers and NeMo (25). It was trained for one stream with one language prompt at a time (10). Timestamps and confidence scores are claimed in a subcard with no way shown to ask for them (5). The chat template line gets 10 because the language prompt is given only as processor or script arguments. Reasoning control and context score 0, with no reasoning and no stated context.",
          "reach": "Memory earns the full 30 because NVIDIA's own Q8_0 GGUF is 0.74 GB and even the F32 safetensors need only about 3 GB. Runtimes get 5, for Transformers from v5.13.0; vLLM points to a third party's plugin, SGLang and llama.cpp have only a Parakeet encoder for multimodal models, and Ollama and LM Studio have nothing. NVIDIA's NeMo and NeMo-Speech.cpp run it but aren't among the six. Builds get 10 for one quantised build, the Q8_0 GGUF. Terms get 10 because OpenMDW-1.1 is permissive with nothing added but isn't OSI-approved. Download gets 10 for an ungated repository and hosted too gets 5 for fal, Together and DeepInfra.",
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        "sources": [
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            "url": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b",
            "seen": "2026-10-21"
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            "seen": "2026-10-21"
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            "seen": "2026-10-21"
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            "what": "inference providers, fal, Together and DeepInfra live",
            "url": "https://huggingface.co/api/models/nvidia/nemotron-3.5-asr-streaming-0.6b?expand[]=inferenceProviderMapping",
            "seen": "2026-10-21"
          },
          {
            "what": "explainability subcard",
            "url": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b/blob/main/explainability.md",
            "seen": "2026-10-21"
          },
          {
            "what": "bias subcard",
            "url": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b/blob/main/bias.md",
            "seen": "2026-10-21"
          },
          {
            "what": "safety subcard",
            "url": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b/blob/main/safety.md",
            "seen": "2026-10-21"
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            "seen": "2026-10-21"
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            "seen": "2026-10-21"
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            "seen": "2026-10-21"
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            "seen": "2026-10-21"
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            "url": "https://raw.githubusercontent.com/NVIDIA-NeMo/NeMo/main/nemo/core/connectors/save_restore_connector.py",
            "seen": "2026-10-21"
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            "what": "NVIDIA's C++ runtime (git clone), last commit 20 October 2026",
            "url": "https://github.com/NVIDIA/NeMo-Speech.cpp",
            "seen": "2026-10-21"
          },
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            "what": "Ollama library, no entry",
            "url": "https://ollama.com/search?q=nemotron-3.5-asr",
            "seen": "2026-10-21"
          },
          {
            "what": "LM Studio catalogue, no entry (404)",
            "url": "https://lmstudio.ai/models/nemotron-3.5-asr",
            "seen": "2026-10-21"
          },
          {
            "what": "NVIDIA PSIRT, disclosure policy and bulletins",
            "url": "https://www.nvidia.com/en-us/security/",
            "seen": "2026-10-21"
          },
          {
            "what": "Independent benchmark result used for Capability",
            "url": "https://huggingface.co/spaces/hf-audio/open_asr_leaderboard",
            "seen": "2026-10-21"
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        "openQuestions": [
          "Terms read OpenMDW-1.1 as a custom licence (10) because it isn't OSI-approved, though it adds no use policy or threshold; if the founder treats it as equivalent to an OSI licence, terms would be 15",
          "Last change reads NeMo-Speech.cpp's 20 October 2026 ASR weight-loading change as library-wide; counted as a change to the code that runs this model, the line would be 20",
          "Whether NVIDIA's own API (build.nvidia.com or a Speech NIM) serves this exact checkpoint wasn't checked; hosted too is met by three providers anyway"
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      "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"
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      "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"
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      "metrics": {
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        "measured": false
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        "ruling": "The GGUF re-conversion of 10 September 2026 through pull request 32 with no card note, 17 of 24 discussions answered, the Greek final-sigma report of 14 June unanswered, the English predecessor kept and NeMo-Speech.cpp's library-wide change of 20 October match the upkeep items."
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        "toolUrl": "https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b",
        "rating": 3,
        "title": "0.74 GB speech model, run mostly by NVIDIA's own tools",
        "body": "Hardware barely matters here. NVIDIA's Q8_0 GGUF is 0.74 GB, about 0.89 GB with a fifth added, and the F32 safetensors are 2.55 GB. Of the six major runtimes only Transformers from v5.13.0 runs it, and the GGUF needs NVIDIA's NeMo-Speech.cpp, not llama.cpp. OpenMDW-1.1 allows free commercial use with nothing added. fal, Together and DeepInfra host it, with no price for any of them in the dossier.",
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          "GGUF needs NeMo-Speech.cpp",
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      {
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        "toolUrl": "https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b",
        "rating": 3,
        "title": "Streaming chunks and a language tag to strip",
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        "themes": {
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            "independent ASR results"
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          "struggles": [
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          "requests": [
            "show how to request timestamps"
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            "rating": 3,
            "verdict": {
              "title": "Streaming chunks and a language tag to strip",
              "pros": [
                "Streaming chunk settings documented",
                "Language tag parsing in two runtimes",
                "Independent WER and speed results"
              ],
              "cons": [
                "Timestamps claimed without a request method",
                "One stream at a time",
                "No JSON output"
              ],
              "text": "NVIDIA documents 16 kHz mono input, a locale or auto, and att_context_size chunk settings for cache-aware streaming, and output as punctuated text with an `\u003cxx-XX\u003e` language tag that skip_special_tokens or NeMo's strip_lang_tags removes. One stream and one language prompt run at a time. A subcard claims timestamps and confidence scores without showing how to ask for them. The Open ASR Leaderboard records 9.75 average WER on English short-form and an RTFx of 1343.21."
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      },
      {
        "id": "rev_3942",
        "tool": "nemotron-3-5-asr-streaming-0-6b",
        "toolUrl": "https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b",
        "rating": 2,
        "title": "A pickled NeMo checkpoint on one documented path",
        "body": "Nemotron 3.5 ASR Streaming 0.6B ships safetensors and GGUF, but the NeMo checkpoint beside them holds weights written with torch.save, and NeMo's from_pretrained, one of the card's documented paths, loads that pickle. Transformers carries the model natively, so its route runs no repository code. The card names NVIDIA's vulnerability submission page and PSIRT publishes bulletins. Guidance stops at accuracy cautions, and the bias subcard describes an evaluation without publishing results.",
        "pros": [
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          "OpenMDW-1.1"
        ],
        "cons": [
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          "No safety results",
          "General accuracy cautions only"
        ],
        "themes": {
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            "named reporting route",
            "checksummed files"
          ],
          "struggles": [
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          "requests": [
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            "publish the bias evaluation"
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        },
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        "outcome": "partial",
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        "basisNote": "Desk review, written from public documentation, pricing, terms, source and status history on 21 October 2026. No calls made.",
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        "document": {
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            "rating": 2,
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                "Native Transformers route without remote code",
                "Verified organisation, hash on every file",
                "PSIRT route on the card",
                "OpenMDW-1.1"
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              "cons": [
                "NeMo path loads a pickle",
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                "General accuracy cautions only"
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              "text": "Nemotron 3.5 ASR Streaming 0.6B ships safetensors and GGUF, but the NeMo checkpoint beside them holds weights written with torch.save, and NeMo's from_pretrained, one of the card's documented paths, loads that pickle. Transformers carries the model natively, so its route runs no repository code. The card names NVIDIA's vulnerability submission page and PSIRT publishes bulletins. Guidance stops at accuracy cautions, and the bias subcard describes an evaluation without publishing results."
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        {
          "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",
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          "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"
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        {
          "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"
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        {
          "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"
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        {
          "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"
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        {
          "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"
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        {
          "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"
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        {
          "name": "Nemotron 3.5 Bolt 74B-A9B",
          "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-BF16",
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        },
        {
          "name": "Nemotron Labs 3 Puzzle 75B-A9B",
          "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-Labs-3-Puzzle-75B-A9B-BF16",
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        {
          "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"
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      ],
      "olderCount": 43
    },
    "notable": [
      "1,220,513 downloads in 30 days and 1,223 likes on Hugging Face on 21 October 2026 (https://huggingface.co/api/models/nvidia/nemotron-3.5-asr-streaming-0.6b)",
      "NVIDIA's card gives an average FLEURS WER of 10.38% at 80 ms chunks and 9.12% at 560 ms across its 19 transcription-ready locales with the language given, and 25.86% to 23.09% across 13 broad-coverage locales. These are the publisher's numbers, not our measurement (https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b)",
      "NVIDIA says one H100 sustains about 240 concurrent streams at 80 ms chunks and 2,400 at 1.12 s, against 14 and 400 for Parakeet RNNT 1.1B multilingual on buffered streaming. The publisher's claim",
      "The multilingual extension of nvidia/nemotron-speech-streaming-en-0.6b, which stays published in its own repository and which NVIDIA still recommends for English-only use",
      "In Hugging Face Transformers since v5.13.0, and served by fal, Together and DeepInfra through Hugging Face's inference providers (https://huggingface.co/api/models/nvidia/nemotron-3.5-asr-streaming-0.6b?expand[]=inferenceProviderMapping)"
    ],
    "area": "voice",
    "details": [
      {
        "label": "Surface graded",
        "value": "The open weights at huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b, read from the model card and its four subcards (bias, explainability, privacy, safety), the files and their metadata, the commit history, the OpenMDW-1.1 licence, NVIDIA's NeMo and NeMo-Speech.cpp repositories and the runtimes' own code on 21 October 2026. Nothing was downloaded or run"
      },
      {
        "label": "Model",
        "value": "A cache-aware FastConformer encoder (24 layers, hidden size 1024, 128 mel bins, 8x subsampling) with an RNN-T decoder (2 layers, hidden 640) and a 128-way one-hot language-ID prompt concatenated to every frame. 600M parameters on the card, 637,997,088 by Hugging Face's safetensors count. Developed from nvidia/nemotron-speech-streaming-en-0.6b"
      },
      {
        "label": "Languages",
        "value": "40 language-locales in three tiers. 19 transcription-ready (English US and UK, Spanish US and Spain, French France and Canada, Italian, Portuguese Brazil and Portugal, Dutch, German, Turkish, Russian, Arabic, Hindi, Japanese, Korean, Vietnamese, Ukrainian), 13 broad-coverage (Polish, Swedish, Czech, Norwegian Bokmal, Danish, Bulgarian, Finnish, Croatian, Slovak, Mandarin, Hungarian, Romanian, Estonian) and 8 adaptation-ready that need fine-tuning (Greek, Lithuanian, Latvian, Maltese, Slovenian, Hebrew, Thai, Norwegian Nynorsk). target_lang=auto detects the language"
      },
      {
        "label": "Files",
        "value": "model.safetensors (2.55 GB, F32), the NeMo checkpoint nemotron-3.5-asr-streaming-0.6b.nemo (2.37 GB, a tar archive whose weights are a PyTorch pickle, model_weights.ckpt) and nemotron-3.5-asr-streaming-0.6b.q8_0.gguf (0.74 GB) for NeMo-Speech.cpp. Hugging Face lists a SHA-256 for every LFS file. No chat template; the tokenizer is a Parakeet tokenizer with the language tags as special tokens"
      },
      {
        "label": "Licence",
        "value": "OpenMDW-1.1, the Linux Foundation's permissive licence for model materials, governing per the card and every subcard. No LICENSE file in the repository. On release (4 June 2026) the card's metadata named the NVIDIA Open Model License while its body named OpenMDW-1.1; three commits titled Update License on 5 June 2026 corrected the metadata"
      },
      {
        "label": "Runtimes",
        "value": "Hugging Face Transformers from v5.13.0 (native Nemotron3_5Asr, no remote code). NVIDIA NeMo from its main branch, and NVIDIA's own NeMo-Speech.cpp C++ runtime with the Q8_0 GGUF. vLLM lists it only as an out-of-tree architecture served by a third party's plugin. Not in SGLang, llama.cpp (its Parakeet projector is the audio encoder of multimodal language models, not this RNN-T), Ollama or LM Studio"
      },
      {
        "label": "Input and output",
        "value": "16 kHz mono audio and a language locale, a bare code or auto. Output is punctuated, capitalised text; in auto mode a language tag such as \u003cen-US\u003e follows the terminal punctuation, removed by skip_special_tokens=True in Transformers or strip_lang_tags=true in NeMo. Streams through Transformers' TextIteratorStreamer or NeMo's cache-aware streaming script. The explainability subcard says the output carries timestamps and confidence scores, which the card's usage doesn't show how to get"
      },
      {
        "label": "Recommended settings",
        "value": "att_context_size [56, r] in 80 ms frames, with r of 0, 1, 3, 6 or 13 for chunks of 80, 160, 320, 560 or 1,120 ms; larger chunks are more accurate. The default was set to [56,3] (320 ms) on 30 May 2026. In Transformers, set_num_lookahead_tokens chooses the latency"
      },
      {
        "label": "Hardware",
        "value": "NVIDIA GPUs from Volta to Blackwell and Jetson on Linux, per the card's software integration section. Throughput was measured on one H100. Maximum audio length depends on GPU memory. NeMo-Speech.cpp is NVIDIA's local C++ path with the 0.74 GB GGUF"
      },
      {
        "label": "Training data",
        "value": "A blend of NVIDIA's proprietary Riva multilingual set, NVIDIA Granary, Multilingual LibriSpeech, Common Voice, FLEURS and VoxPopuli/Europarl, between 10,000 and 1 million hours, with human labels and synthetic labels from an ensemble of ASR models. No collection cut-off is given"
      }
    ],
    "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,
      "checks": [
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          "check": "Legal entity named",
          "value": "NVIDIA Corporation",
          "points": 20,
          "max": 20,
          "state": "ok"
        },
        {
          "check": "Domain age",
          "value": "nvidia.com, registered 1993-04-20 (33 years)",
          "points": 15,
          "max": 15,
          "state": "ok"
        },
        {
          "check": "Endpoint on the vendor's domain",
          "value": "no hosted endpoint",
          "points": 0,
          "max": 0,
          "state": "na"
        },
        {
          "check": "Terms of service",
          "value": "nothing hosted, so the OpenMDW-1.1 licence stands in",
          "points": 10,
          "max": 10,
          "state": "ok"
        },
        {
          "check": "Privacy policy",
          "value": "nothing hosted, not scored",
          "points": 0,
          "max": 0,
          "state": "na"
        },
        {
          "check": "Status page",
          "value": "not found",
          "points": 0,
          "max": 10,
          "state": "no"
        },
        {
          "check": "Changelog",
          "value": "published",
          "points": 10,
          "max": 10,
          "state": "ok"
        },
        {
          "check": "security.txt",
          "value": "could not be fetched",
          "points": 0,
          "max": 10,
          "state": "no"
        }
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}