{
  "data": {
    "a": {
      "slug": "cohere-transcribe-03-2026",
      "name": "Cohere Transcribe 03-2026",
      "vendor": "Cohere",
      "vendorUrl": "https://cohere.com",
      "kind": "weights",
      "category": "speech-to-text",
      "summary": "Cohere Transcribe 03-2026 is Cohere's open-weight speech recognition model, a 2B Conformer encoder with a light Transformer decoder trained from scratch, transcribing 14 languages from a pre-specified language, under Apache 2.0, in a gated Hugging Face repository.",
      "url": "https://www.anchorterminal.com/tools/cohere-transcribe-03-2026",
      "markdownUrl": "https://www.anchorterminal.com/tools/cohere-transcribe-03-2026.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cohere-transcribe-03-2026.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cohere-transcribe-03-2026.json",
      "repo": "https://huggingface.co/CohereLabs/cohere-transcribe-03-2026",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "CohereLabs/cohere-transcribe-03-2026"
        }
      ],
      "auth": "none",
      "authNotes": "The repository is gated (gated: auto on 2026-10-21). The card and file list are public, but the files open only after a signed-in Hugging Face user accepts the conditions, which are approved automatically. We didn't accept them, so this listing is graded from what's public.",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0, once the gate is accepted. Cohere also serves the model on its Audio Transcriptions API (free with rate limits on a trial key, or a dedicated Model Vault priced per hour-instance), and fal serves it as a Hugging Face inference provider. Running the weights costs the hardware, 4.13 GB of BF16 safetensors (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://docs.cohere.com/docs/transcribe",
      "llmsTxt": "https://docs.cohere.com/llms.txt",
      "capabilities": [
        "speech.stt",
        "speech.batch",
        "speech.languages",
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "speech-to-text",
        "asr",
        "conformer",
        "multilingual",
        "apache-2.0",
        "safetensors",
        "gated",
        "self-hosted"
      ],
      "lastRelease": "2026-04-28",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 59.3,
        "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": 18,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 66,
          "interface": 45,
          "reach": 65,
          "risk": 50,
          "upkeep": 54
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "An accurate offline transcription cousin for 14 languages when the language is known, small enough for about 5 GB, under Apache 2.0, and also on Cohere's API. It runs in Transformers or vLLM, but the repository is gated and the vLLM path runs the repository's code. Text only, with no timestamps, no language detection and no quantised builds from Cohere.",
        "bestFor": "Agents that need accurate batch transcription of known-language audio in 14 languages on a small GPU",
        "strengths": [
          "Publisher-reported 5.42 average WER on the Open ASR Leaderboard's English sets, with results in the repository to check",
          "2B parameters, 4.13 GB of BF16 safetensors, about 5 GB in memory",
          "Native in released Transformers and vLLM, with long-form chunking and batching documented",
          "Apache 2.0 with nothing added, and Cohere's own API serves the same model",
          "Every report of a broken file got a reply from Cohere"
        ],
        "weaknesses": [
          "Gated, so an agent needs a Hugging Face account and must accept the conditions before downloading",
          "The documented vLLM command uses --trust-remote-code",
          "No timestamps, diarisation, language detection or JSON output; one language must be given",
          "No quantised build from Cohere and no llama.cpp, Ollama or LM Studio support",
          "No safety results, training data without sources or cut-off, and no replies in the repository since April"
        ],
        "agentNotes": [
          "A person has to accept the conditions on the Hugging Face page with an account, then `hf auth login`, before the files download",
          "Offline, `pip install \"transformers\u003e=5.4.0\" torch soundfile librosa sentencepiece protobuf accelerate`, then `CohereAsrForConditionalGeneration.from_pretrained(\"CohereLabs/cohere-transcribe-03-2026\", device_map=\"auto\")` with no remote code",
          "Always pass language= (en, de, fr, it, es, pt, el, nl, pl, zh, ja, ko, vi, ar); there's no auto-detection",
          "For long audio, keep audio_chunk_index from the processor and pass it to processor.decode to reassemble the chunks",
          "Serving, `vllm serve CohereLabs/cohere-transcribe-03-2026 --trust-remote-code`, then POST to /v1/audio/transcriptions",
          "Put voice activity detection in front of it, since it transcribes noise and can hallucinate on silence",
          "Without the hardware or the gate, Cohere's API serves the same model as cohere-transcribe-03-2026",
          "Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 59.3
          }
        ],
        "editorialScores": {
          "capability": 66,
          "interface": 45,
          "reach": 65,
          "risk": 50,
          "upkeep": 54
        },
        "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": "# accept the conditions on the Hugging Face page first, then log in with hf auth login\npip install \"transformers\u003e=5.4.0\" torch soundfile librosa sentencepiece protobuf accelerate",
        "http": "# after: vllm serve CohereLabs/cohere-transcribe-03-2026 --trust-remote-code\ncurl -X POST http://localhost:8000/v1/audio/transcriptions \\\n  -F file=@/path/to/speech.wav \\\n  -F model=CohereLabs/cohere-transcribe-03-2026"
      },
      "letme": {
        "capability": "https://letme.dev/speech.stt",
        "tool": "https://letme.dev/cohere-transcribe-03-2026"
      },
      "sameCompany": [
        "cohere-chat",
        "cohere-embed",
        "cohere-north"
      ],
      "weights": {
        "trainedBy": "Cohere (Cohere Labs)",
        "params": "2.07B",
        "goodFor": "Accurate offline and batch transcription in 14 languages when the language is known, on a small GPU.",
        "runtimes": [
          "vLLM",
          "Transformers"
        ],
        "builds": [
          {
            "name": "cohere-transcribe-03-2026",
            "url": "https://huggingface.co/CohereLabs/cohere-transcribe-03-2026",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 4.13,
            "memoryGB": 8,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "Transformers"
            ],
            "note": "Gated, a click-through with automatic approval that needs a Hugging Face account"
          }
        ],
        "run": "vllm serve CohereLabs/cohere-transcribe-03-2026 --trust-remote-code",
        "runBuild": "cohere-transcribe-03-2026",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "Cohere (Cohere Labs)",
        "family": "Cohere Transcribe",
        "url": "https://www.anchorterminal.com/open-weights/#cohere",
        "others": [
          {
            "name": "cohere-transcribe-arabic-07-2026",
            "url": "https://huggingface.co/CohereLabs/cohere-transcribe-arabic-07-2026",
            "params": "2.07B (Hub safetensors count; the name states none)"
          }
        ],
        "olderCount": 29
      },
      "area": "voice",
      "provenance": {
        "legalEntity": "Cohere Inc.",
        "domain": "cohere.com",
        "domainRegistered": "2000-03-07",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://docs.cohere.com/changelog/cohere-transcribe-03-2026",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The card says Developed by Cohere and Cohere Labs. The files sit in the verified CohereLabs organisation, which cohere.com's Transcribe announcement links to. Legal entity and domain registration are carried from the cohere-chat listing (checked 2026-10-09).",
          "Nothing is hosted in this listing, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored. Cohere's own API serves the model; no Cohere transcription API is listed here yet.",
          "The repository's commit history is behind the gate. Per-file last commits from the public file list show the weights from 25 March 2026, tokenizer fixes on 27 March, a modeling fix on 26 March, a configuration change on 28 April and card edits up to 7 October 2026.",
          "cohere.com/.well-known/security.txt answered 404 on 21 October 2026. The cohere-chat listing records a responsible disclosure policy and bug bounty in Cohere's trust centre."
        ],
        "score": 73
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/cohere-transcribe-03-2026.json"
    },
    "answer": "Nemotron 3.5 ASR Streaming 0.6B and Cohere Transcribe 03-2026 score within a point of each other on agent readiness, 59.8 (C) and 59.3 (C). Cohere Transcribe 03-2026 leads on capability.",
    "b": {
      "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"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Cohere",
        "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": "Apache-2.0",
        "b": "OpenMDW-1.1",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-04-28",
        "b": "2026-09-10",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "3/5 (4)",
        "b": "2.8/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Nemotron 3.5 ASR Streaming 0.6B and Cohere Transcribe 03-2026 score within a point of each other on agent readiness, 59.8 (C) and 59.3 (C). Cohere Transcribe 03-2026 leads on capability.",
        "question": "Which is better for AI agents, Cohere Transcribe 03-2026 or Nemotron 3.5 ASR Streaming 0.6B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Capability, 66 against 54"
        ],
        "also": null,
        "goodFor": "Agents that need accurate batch transcription of known-language audio in 14 languages on a small GPU",
        "slug": "cohere-transcribe-03-2026",
        "watchFor": "Gated, so an agent needs a Hugging Face account and must accept the conditions before downloading"
      },
      {
        "aheadOn": [
          "Reach, 70 against 65",
          "Risk, 60 against 50",
          "Agent interface, 50 against 45",
          "Documentation and upkeep, 64 against 54"
        ],
        "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"
      }
    ],
    "job": {
      "capability": "speech.stt",
      "name": "Speech-to-text"
    },
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        "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-ming-3-0-asr-tiny.json",
        "title": "Cohere Transcribe 03-2026 vs Ming-3.0-asr-tiny",
        "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-ming-3-0-asr-tiny"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-ming-3-0-audio-flash.json",
        "title": "Cohere Transcribe 03-2026 vs Ming-3.0-audio-flash",
        "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-ming-3-0-audio-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-ming-3-0-audio-tiny.json",
        "title": "Cohere Transcribe 03-2026 vs Ming-3.0-audio-tiny",
        "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-ming-3-0-audio-tiny"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Cohere Transcribe 03-2026 vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "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-qwen3-asr-0-6b.json",
        "title": "Cohere Transcribe 03-2026 vs Qwen3-ASR-0.6B",
        "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-qwen3-asr-0-6b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-qwen3-asr-1-7b.json",
        "title": "Cohere Transcribe 03-2026 vs Qwen3-ASR-1.7B",
        "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-qwen3-asr-1-7b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Cohere Transcribe 03-2026 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-underdog-bark-3.json",
        "title": "Cohere Transcribe 03-2026 vs Underdog Bark 3.0",
        "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-underdog-bark-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-voxtral-mini-4b-realtime-2602.json",
        "title": "Cohere Transcribe 03-2026 vs Voxtral Mini 4B Realtime 2602",
        "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-voxtral-mini-4b-realtime-2602"
      },
      {
        "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-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-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/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-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-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"
      }
    ],
    "scores": [
      {
        "by": 12,
        "cohere-transcribe-03-2026": 66,
        "edge": "cohere-transcribe-03-2026",
        "key": "capability",
        "name": "Capability",
        "nemotron-3-5-asr-streaming-0-6b": 54,
        "weight": 35
      },
      {
        "by": 5,
        "cohere-transcribe-03-2026": 65,
        "edge": "nemotron-3-5-asr-streaming-0-6b",
        "key": "reach",
        "name": "Reach",
        "nemotron-3-5-asr-streaming-0-6b": 70,
        "weight": 25
      },
      {
        "by": 10,
        "cohere-transcribe-03-2026": 50,
        "edge": "nemotron-3-5-asr-streaming-0-6b",
        "key": "risk",
        "name": "Risk",
        "nemotron-3-5-asr-streaming-0-6b": 60,
        "weight": 20
      },
      {
        "by": 5,
        "cohere-transcribe-03-2026": 45,
        "edge": "nemotron-3-5-asr-streaming-0-6b",
        "key": "interface",
        "name": "Agent interface",
        "nemotron-3-5-asr-streaming-0-6b": 50,
        "weight": 10
      },
      {
        "by": 10,
        "cohere-transcribe-03-2026": 54,
        "edge": "nemotron-3-5-asr-streaming-0-6b",
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "nemotron-3-5-asr-streaming-0-6b": 64,
        "weight": 10
      }
    ],
    "summary": "Nemotron 3.5 ASR Streaming 0.6B and Cohere Transcribe 03-2026 score within a point of each other on agent readiness, 59.8 (C) and 59.3 (C). Cohere Transcribe 03-2026 leads on capability. Both do speech-to-text.",
    "tutorials": [],
    "verdicts": {
      "cohere-transcribe-03-2026": "An accurate offline transcription cousin for 14 languages when the language is known, small enough for about 5 GB, under Apache 2.0, and also on Cohere's API. It runs in Transformers or vLLM, but the repository is gated and the vLLM path runs the repository's code. Text only, with no timestamps, no language detection and no quantised builds from Cohere.",
      "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."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "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-nemotron-3-5-asr-streaming-0-6b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-asr-streaming-0-6b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-asr-streaming-0-6b.min.md"
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  "markdown": "Nemotron 3.5 ASR Streaming 0.6B and Cohere Transcribe 03-2026 score within a point of each other on agent readiness, 59.8 (C) and 59.3 (C). Cohere Transcribe 03-2026 leads on capability. Both do speech-to-text.\n\n- Cohere Transcribe 03-2026: grade C, 59.3/100, rank #61 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/cohere-transcribe-03-2026.md · JSON https://www.anchorterminal.com/api/v1/tools/cohere-transcribe-03-2026.json\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- 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### Cohere Transcribe 03-2026 (C)\n\nGood for: Agents that need accurate batch transcription of known-language audio in 14 languages on a small GPU\n\nAhead on:\n- Capability, 66 against 54\n\nWatch for: Gated, so an agent needs a Hugging Face account and must accept the conditions before downloading\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- Risk, 60 against 50\n- Agent interface, 50 against 45\n- Documentation and upkeep, 64 against 54\n\nWatch for: Not in vLLM, SGLang, llama.cpp, Ollama or LM Studio; the GGUF needs NVIDIA's NeMo-Speech.cpp\n\n\n## Score by category\n\n| Category | Weight | Cohere Transcribe 03-2026 | Nemotron 3.5 ASR Streaming 0.6B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 66 | 54 | Cohere Transcribe 03-2026 +12 |\n| Reach | 25% (25 this run) | 65 | 70 | Nemotron 3.5 ASR Streaming 0.6B +5 |\n| Risk | 20% (20 this run) | 50 | 60 | Nemotron 3.5 ASR Streaming 0.6B +10 |\n| Agent interface | 10% (10 this run) | 45 | 50 | Nemotron 3.5 ASR Streaming 0.6B +5 |\n| Documentation and upkeep | 10% (10 this run) | 54 | 64 | Nemotron 3.5 ASR Streaming 0.6B +10 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59.3 · C** | **59.8 · C** | |\n\n## Facts side by side\n\n| Fact | Cohere Transcribe 03-2026 | Nemotron 3.5 ASR Streaming 0.6B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Cohere | 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 | Apache-2.0 | OpenMDW-1.1 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-04-28 | 2026-09-10 |\n| Terms last updated | no document linked | 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 | 3/5 (4) | 2.8/5 (4) |\n\n## Verdicts\n\n**Cohere Transcribe 03-2026.** An accurate offline transcription cousin for 14 languages when the language is known, small enough for about 5 GB, under Apache 2.0, and also on Cohere's API. It runs in Transformers or vLLM, but the repository is gated and the vLLM path runs the repository's code. Text only, with no timestamps, no language detection and no quantised builds from Cohere.\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## Before you call either\n\n### Cohere Transcribe 03-2026\n\n1. A person has to accept the conditions on the Hugging Face page with an account, then `hf auth login`, before the files download\n2. Offline, `pip install \"transformers\u003e=5.4.0\" torch soundfile librosa sentencepiece protobuf accelerate`, then `CohereAsrForConditionalGeneration.from_pretrained(\"CohereLabs/cohere-transcribe-03-2026\", device_map=\"auto\")` with no remote code\n3. Always pass language= (en, de, fr, it, es, pt, el, nl, pl, zh, ja, ko, vi, ar); there's no auto-detection\n4. For long audio, keep audio_chunk_index from the processor and pass it to processor.decode to reassemble the chunks\n5. Serving, `vllm serve CohereLabs/cohere-transcribe-03-2026 --trust-remote-code`, then POST to /v1/audio/transcriptions\n6. Put voice activity detection in front of it, since it transcribes noise and can hallucinate on silence\n7. Without the hardware or the gate, Cohere's API serves the same model as cohere-transcribe-03-2026\n8. Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions\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## Questions\n\n### Which is better for AI agents, Cohere Transcribe 03-2026 or Nemotron 3.5 ASR Streaming 0.6B?\n\nNemotron 3.5 ASR Streaming 0.6B and Cohere Transcribe 03-2026 score within a point of each other on agent readiness, 59.8 (C) and 59.3 (C). Cohere Transcribe 03-2026 leads on capability.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-asr-streaming-0-6b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-asr-streaming-0-6b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cohere-transcribe-03-2026\", \"b\": \"nemotron-3-5-asr-streaming-0-6b\"}`. From a terminal: `anchor compare cohere-transcribe-03-2026 nemotron-3-5-asr-streaming-0-6b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cohere-transcribe-03-2026.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-5-asr-streaming-0-6b.json\n\n## Other comparisons with Cohere Transcribe 03-2026 or Nemotron 3.5 ASR Streaming 0.6B\n\n- [Cohere Transcribe 03-2026 vs Ming-3.0-asr-tiny](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-ming-3-0-asr-tiny.md)\n- [Cohere Transcribe 03-2026 vs Ming-3.0-audio-flash](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-ming-3-0-audio-flash.md)\n- [Cohere Transcribe 03-2026 vs Ming-3.0-audio-tiny](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-ming-3-0-audio-tiny.md)\n- [Cohere Transcribe 03-2026 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-nano-omni-30b-a3b-reasoning.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- [Cohere Transcribe 03-2026 vs Qwen3-ASR-0.6B](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-qwen3-asr-0-6b.md)\n- [Cohere Transcribe 03-2026 vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-qwen3-asr-1-7b.md)\n- [Cohere Transcribe 03-2026 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Cohere Transcribe 03-2026 vs Underdog Bark 3.0](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-underdog-bark-3.md)\n- [Cohere Transcribe 03-2026 vs Voxtral Mini 4B Realtime 2602](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-voxtral-mini-4b-realtime-2602.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-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-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- [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 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 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",
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    "description": "Nemotron 3.5 ASR Streaming 0.6B and Cohere Transcribe 03-2026 score within a point of each other for speech-to-text, 59.8 and 59.3 out of 100. Prices, MCP, x402, uptime and agent notes side by side.",
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    "title": "Cohere Transcribe 03-2026 vs Nemotron 3.5 ASR Streaming 0.6B (2026)",
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