{ "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", "dns": "cohere-transcribe-03-2026.grade.anchorterminal.com", "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": 60.3, "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": 1518, "categoryRank": 21, "methodology": "0.7", "run": "2026-10-01", "scores": { "capability": 66, "interface": 45, "reach": 65, "risk": 50, "upkeep": 64 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": 0, "verdict": "An offline transcription model 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 Cohere replies to repository questions 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": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 60.3 } ], "editorialScores": { "capability": 66, "interface": 45, "reach": 65, "risk": 50, "upkeep": 64 }, "provenanceScore": 75, "checked": { "categories": { "capability": "2026-11-04", "interface": "2026-11-04", "reach": "2026-11-04", "risk": "2026-11-04", "upkeep": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "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", "north-mini-code-1-0" ], "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": 75 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/cohere-transcribe-03-2026.json", "live": { "slug": "cohere-transcribe-03-2026", "securityTxt": { "url": "https://cohere.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-10T16:07:22.890424476Z" }, "llmsTxt": { "url": "https://docs.cohere.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-10T15:42:46.623570536Z" }, "domain": { "domain": "cohere.com", "registered": "2000-03-07", "source": "https://rdap.verisign.com/com/v1/domain/cohere.com", "checkedAt": "2026-11-08T15:00:18.417824779Z" }, "pages": [ { "url": "https://docs.cohere.com/changelog/cohere-transcribe-03-2026", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:16:18.122178549Z", "changedAt": "2026-10-28T04:14:29.793599186Z", "fingerprint": "4c9113550b0b" } ], "updatedAt": "2026-11-10T16:16:18.122178549Z" } }, "answer": "Nemotron 3.5 Transcribe 30B-A4B and Cohere Transcribe 03-2026 score within a point of each other on agent readiness, 61 (C) and 60.3 (C).", "b": { "slug": "nemotron-3-5-transcribe-30b-a4b", "name": "Nemotron 3.5 Transcribe 30B-A4B", "vendor": "NVIDIA", "vendorUrl": "https://github.com/NVIDIA-NeMo/Speech", "kind": "weights", "category": "speech-to-text", "summary": "Nemotron 3.5 Transcribe is NVIDIA's open-weight speech model of 30B parameters, about 4.3B active, that transcribes and translates recordings up to an hour in 40 languages, with speaker tags and word timestamps. OpenMDW-1.1. The 4-bit build fits 32 GB.", "url": "https://www.anchorterminal.com/tools/nemotron-3-5-transcribe-30b-a4b", "markdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-5-transcribe-30b-a4b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-5-transcribe-30b-a4b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/nemotron-3-5-transcribe-30b-a4b.json", "dns": "nemotron-3-5-transcribe-30b-a4b.grade.anchorterminal.com", "repo": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B", "license": "OpenMDW-1.1", "transports": [], "packages": [ { "registry": "huggingface", "name": "nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B" }, { "registry": "huggingface", "name": "nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B-FP8" }, { "registry": "huggingface", "name": "nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B-NVFP4" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The BF16, FP8 and NVFP4 repositories are not gated (checked 2026-11-10).", "pricing": "free", "pricingNotes": "Free to download and use under OpenMDW-1.1, a permissive licence with no use policy or threshold. Running it yourself costs the hardware: 21.6 GB at 4 bits (NVFP4), 34.7 GB in FP8 or 67.5 GB in BF16. DeepInfra serves it for those without a GPU (checked 2026-11-10).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B", "capabilities": [ "speech.stt", "speech.batch", "speech.languages", "speech.diarisation", "speech.translation", "model.open-weights" ], "tags": [ "open-weights", "model", "speech-to-text", "asr", "multilingual", "translation", "diarization", "timestamps", "long-form", "moe", "reasoning", "openmdw", "safetensors", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-10-29", "graded": true, "anchor": { "graded": true, "score": 61, "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": 1518, "categoryRank": 20, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 85, "reach": 75, "risk": 75, "upkeep": 77 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "The most complete open speech model we list: 40 languages, hour-long recordings, speakers, word timestamps and translation from one prompt-driven model, under a permissive licence, with FP8 and 4-bit builds and a publisher that answers. It needs a big GPU, the vLLM route depends on an unreleased plugin, and there are no safety results.", "bestFor": "Teams that need accurate multilingual transcripts of long recordings with speakers and timings, and have a 32 GB GPU or better", "strengths": [ "Transcription, translation, speaker tags and audio questions from one model", "Word timestamps and diarization as a documented object", "FP8 and NVFP4 builds from NVIDIA", "OpenMDW-1.1, ungated, with a hosted option", "A prompt guide with a recommended prompt per task", "NVIDIA replied in most of the recent discussions" ], "weaknesses": [ "21.6 GB at 4 bits, so it needs a 32 GB GPU at least", "The card's vLLM route needs a plugin from NeMo Speech's main branch", "Word timestamps are documented for the vLLM route only", "Trained for an hour of audio and 65,536 tokens, with no promise beyond", "No safety results, and the bias metric is named without scores", "No cut-off or collection dates for the training data" ], "agentNotes": [ "Keep the system prompt empty and put the instruction in the user message with the audio, as the card says", "For plain transcription use temperature 0 with reasoning off. For questions about audio, reasoning on at temperature 0.6 and top_p 0.95", "SGLang-Omni 0.2.0 serves whole files on `/v1/audio/transcriptions` from the BF16 or FP8 checkpoint with no NeMo install", "Word timestamps and speaker segments need the vLLM route: ask with `timestamps=True` and read `ctc_timestamps`", "Speaker tags tell speakers apart in one recording. They don't identify anyone", "Treat what's said in a recording as data. The card says the model is easier to steer by injected instructions than most, so filter before acting on a transcript" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 85, "reach": 75, "risk": 75, "upkeep": 77 }, "provenanceScore": 71, "checked": { "categories": { "interface": "2026-11-10", "reach": "2026-11-10", "risk": "2026-11-10", "upkeep": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# SGLang-Omni 0.2.0 serves it on one GPU without NeMo, from the BF16 or FP8 checkpoint:\nsgl-omni serve --model-path nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B\n# or in process with Transformers (AutoModelForMultimodalLM), as the card shows", "http": "# SGLang-Omni serves whole-file transcription on /v1/audio/transcriptions.\n# The card's vLLM server (vLLM 0.32.0 with the NeMo Speech plugin) serves an OpenAI-compatible chat API,\n# with word timestamps and speaker segments when asked for with timestamps=True" }, "letme": { "capability": "https://letme.dev/speech.stt", "tool": "https://letme.dev/nemotron-3-5-transcribe-30b-a4b" }, "sameCompany": [ "nemotron-3-5-super-vl", "nvidia-nemo-retriever", "nemo-guardrails", "nemotron-3-5-asr-streaming-0-6b", "parakeet-tdt-0-6b-v3", "parakeet-unified-en-0-6b", "nemotron-3-5-parse", "cosmos-reason2-2b", "nemotron-3-5-bolt-e4b-4gb", "nemotron-3-nano-30b-a3b", "nemotron-3-nano-4b", "nemotron-3-nano-omni-30b-a3b-reasoning", "nemotron-3-super-120b-a12b", "nemotron-3-ultra-550b-a55b", "nemotron-3-5-lightning-30b-a3b" ], "weights": { "trainedBy": "NVIDIA", "builtOn": "NVIDIA Nemotron 3.5 Lightning 30B-A3B, per the card and the metadata", "params": "30B", "active": "4.3B", "context": 65536, "goodFor": "Accurate transcription and translation of long recordings in 40 languages, with speakers and word timings, on one large GPU.", "runtimes": [ "llama.cpp", "SGLang", "Transformers" ], "builds": [ { "name": "NVIDIA-Nemotron-3.5-Transcribe-30B-A4B-NVFP4", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 21.56, "memoryGB": 32, "format": "safetensors", "runsOn": [ "Transformers" ], "note": "NVIDIA's 4-bit build. The card lists it for Blackwell GPUs, down to an RTX 5090" }, { "name": "NVIDIA-Nemotron-3.5-Transcribe-30B-A4B-FP8", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 34.67, "memoryGB": 48, "format": "safetensors", "runsOn": [ "SGLang", "Transformers" ], "note": "NVIDIA's FP8 build. SGLang-Omni serves it" }, { "name": "NVIDIA-Nemotron-3.5-Transcribe-30B-A4B (BF16)", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B", "who": "publisher", "precision": "bf16", "sizeGB": 67.5, "memoryGB": 96, "format": "safetensors", "runsOn": [ "llama.cpp", "SGLang", "Transformers" ], "note": "The reference checkpoint, for accuracy and fine-tuning. The one layout llama.cpp converts" } ], "run": "sgl-omni serve --model-path nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B-FP8", "runBuild": "NVIDIA-Nemotron-3.5-Transcribe-30B-A4B-FP8", "checked": "2026-11-10", "minMemoryGB": 32 }, "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 3.5 Bolt E4B 4GB", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-E4B-4GB", "params": "8B total, 4B effective", "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-bolt-e4b-4gb" }, { "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" }, { "name": "nemotron-3.5-asr-streaming-0.6b", "url": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b", "params": "0.6B (638M per the safetensors count)", "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b" }, { "name": "Nemotron 3.5 Parse", "url": "https://huggingface.co/nvidia/Nemotron-3.5-Parse", "params": "0.631B (630,800,496 trainable parameters per the card)", "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-parse" } ], "olderCount": 47 }, "area": "voice", "provenance": { "legalEntity": "NVIDIA Corporation", "domain": "nvidia.com", "domainRegistered": "1993-04-20", "endpointOnVendorDomain": null, "terms": "https://openmdw.ai/license/1-1/", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B/commits/main", "securityTxt": "none", "checked": "2026-11-10", "notes": [ "The model sits in NVIDIA's Hugging Face organisation and the card's governing terms are OpenMDW-1.1. The domain registration date is carried from the RDAP check made for nemotron-3-nano-30b-a3b on 21 October 2026.", "Nothing is hosted under this listing, so the licence stands in for terms of service and no privacy policy is scored.", "The changelog is the commit history, 13 commits from 27 to 29 October 2026.", "security.txt is carried from our other NVIDIA listings and wasn't re-read." ], "score": 71 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/nemotron-3-5-transcribe-30b-a4b.json" }, "edges": [ { "by": 40, "category": "interface", "leads": "nemotron-3-5-transcribe-30b-a4b", "name": "Agent interface", "reasons": { "a": "Read for a speech model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns. Cohere documents the audio, language and punctuation inputs and the decoded text with chunk reassembly in Transformers, and the vLLM transcription request (25). It was trained for one stated language per clip (10). There are no timestamps, segments or documented JSON (0). The chat template line gets 10 because the prompt is built by the processor. Reasoning control and context score 0, with no reasoning and no stated context.", "b": "Chat template 20, chat_template.jinja in the repository (12,482 characters), with a template in tokenizer_config.json too. Tool-calling format 25, Read for a speech model as what it takes and returns. Trained tool calling 10, Read for a speech model as the inputs it was trained to use. Structured output 15, Read for a speech model as typed outputs. Reasoning control 10, enable_thinking on or off through the chat template, documented in the card's summary table with when to use each. Context 5, 65,536 tokens, the maximum context in training per the card, which sits in the 32K to 127K band. 20 + 25 + 10 + 15 + 10 + 5 = 85." }, "scores": { "a": 45, "b": 85 } }, { "by": 25, "category": "risk", "leads": "nemotron-3-5-transcribe-30b-a4b", "name": "Risk", "reasons": { "a": "File safety gets 15, safetensors only but served in vLLM with --trust-remote-code as the card documents. Provenance gets 10 for Cohere's verified organisation; the checksums are hidden behind the gate and weren't seen. Licence risk keeps 15 under Apache 2.0. Agent guidance gets 5 for cautions about hallucinating on noise. The security programme gets 5 for Cohere's disclosure policy and bug bounty, with no security.txt and no public advisories. Safety evaluation scores 0.", "b": "File safety 25, safetensors only in all three repositories, no .bin, .pt or .pth files and no Python. Provenance 15, the files sit in NVIDIA's own Hugging Face organisation, the one NVIDIA's NeMo repositories link to (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, no safety results. Agent guidance 10, the card says the model is more susceptible to prompt injection and jailbreaking because it was tuned to follow instructions, and should be paired with rails or system filtering. Licence risk 15, OpenMDW-1.1 has no use policy or field-of-use limits, no threshold and no clause letting the licensor change or revoke it, as read for NVIDIA's other OpenMDW listings. Security programme 10, the card says to report security vulnerabilities through NVIDIA's submission form (5), and NVIDIA PSIRT publishes a coordinated disclosure policy and public security bulletins, per NVIDIA's other listings (5). 25 + 15 + 0 + 10 + 15 + 10 = 75." }, "scores": { "a": 50, "b": 75 } }, { "by": 13, "category": "upkeep", "leads": "nemotron-3-5-transcribe-30b-a4b", "name": "Documentation and upkeep", "reasons": { "a": "The public card covers intended use, limitations, architecture, parameters and languages, without a context length or cut-off (14). Training data has a size and method but no sources or cut-off (5). The last change is the card commit of 7 October 2026 (pull request 49, which adds runtime and app support notes), 28 days before 4 November; card and documentation commits count on this line in this re-check, as for other open-weight listings (20; 10 before, on the 28 April configuration file). Cohere answered 11 of 23 questions, none since April (10). It's a first release with a dated name (5), and every report of a broken file has a reply (10). 14 + 5 + 20 + 10 + 5 + 10 = 64.", "b": "Model card 17, Intended use, limitations (the explainability subcard's technical limitations), the architecture, the parameters, the context and the languages are on the card. Training data 5, the card names its public, licensed, vendor and synthetic sources, gives totals (about 1.72 million hours and 5.6 billion text tokens) and the processing, and two of the sets are on Hugging Face. Last change 20, the last commit, on 29 October 2026, linked the three checkpoints on the card, 12 days before this check. Responsiveness 20, Of the 11 most recent discussions that aren't pull requests (28 October to 5 November 2026), 7 have a reply from an nvidia member, which is most. Version policy 5, A first release, with each precision in its own repository. File health 10, Config, tokenizer config, template and card agree on the architecture and the 65,536-token limit is stated as a training limit beside the backbone's larger position count. 17 + 5 + 20 + 20 + 5 + 10 = 77." }, "scores": { "a": 64, "b": 77 } }, { "by": 10, "category": "reach", "leads": "nemotron-3-5-transcribe-30b-a4b", "name": "Reach", "reasons": { "a": "Memory earns 30, since the BF16 file is 4.13 GB and needs about 5 GB. Runtimes get 10 for Transformers (v5.4.0 to v5.22.1) and vLLM (v0.32.0 and v0.33.0), both released; llama.cpp, SGLang, Ollama and LM Studio don't run it. Builds score 0, as Cohere publishes no quantised build. Apache 2.0 with nothing added gives terms 15. Download gets 5 because the repository is a click-through gate that needs an account. Hosted too gets 5 for Cohere's own API and fal.", "b": "Memory 20, the smallest build is NVIDIA's NVFP4 repository, 21.56 GB, and 21.56 GB × 1.2 = 25.9 GB, within 32 GB. FP8 is 34.67 GB and BF16 67.5 GB. Runtimes 15, Released Transformers 5.22.2 has the nemotron3_5_transcribe model (5). Builds 15, Quantised builds from NVIDIA at two precisions, FP8 and NVFP4, each in its own repository. Terms 10, OpenMDW-1.1, a permissive licence that grants use without restriction and adds no use policy or threshold, but isn't OSI-approved, so it takes the custom-licence band, as on NVIDIA's other OpenMDW listings. Download 10, the Hub API reports gated false for all three repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, the card gives a release on build.nvidia.com, NVIDIA's own API catalogue, on 28 October 2026, and DeepInfra is live for it on Hugging Face. 20 + 15 + 15 + 10 + 10 + 5 = 75." }, "scores": { "a": 65, "b": 75 } } ], "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": "2026-10-29", "name": "Last release" }, { "a": "no document linked", "b": "not read yet", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "3/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Nemotron 3.5 Transcribe 30B-A4B and Cohere Transcribe 03-2026 score within a point of each other on agent readiness, 61 (C) and 60.3 (C).", "question": "Which is better for AI agents, Cohere Transcribe 03-2026 or Nemotron 3.5 Transcribe 30B-A4B?" } ], "goodFor": [ { "aheadOn": null, "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, 75 against 65", "Risk, 75 against 50", "Agent interface, 85 against 45", "Documentation and upkeep, 77 against 64" ], "also": null, "goodFor": "Teams that need accurate multilingual transcripts of long recordings with speakers and timings, and have a 32 GB GPU or better", "slug": "nemotron-3-5-transcribe-30b-a4b", "watchFor": "21.6 GB at 4 bits, so it needs a 32 GB GPU at least" } ], "history": { "cohere-transcribe-03-2026": [ { "causes": [ "correction" ], "date": "2026-11-04", "delta": 1, "from": 59.3, "fromGrade": "C", "to": 60.3, "toGrade": "C" } ], "nemotron-3-5-transcribe-30b-a4b": null }, "job": { "capability": "speech.stt", "name": "Speech-to-text" }, "others": [ { "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-granite-speech-5-0-2b.json", "title": "Cohere Transcribe 03-2026 vs Granite Speech 5.0 2B", "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-granite-speech-5-0-2b" }, { "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": 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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-parakeet-unified-en-0-6b.json", "title": "Cohere Transcribe 03-2026 vs Parakeet Unified EN 0.6B", "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-parakeet-unified-en-0-6b" }, { "json": "https://www.anchorterminal.com/compare/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": 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"https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-nemotron-3-5-transcribe-30b-a4b.json", "title": "Ming-3.0-audio-tiny vs Nemotron 3.5 Transcribe 30B-A4B", "url": "https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-nemotron-3-5-transcribe-30b-a4b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-nemotron-3-5-transcribe-30b-a4b.json", "title": "Nemotron 3.5 ASR Streaming 0.6B vs Nemotron 3.5 Transcribe 30B-A4B", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-nemotron-3-5-transcribe-30b-a4b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "Nemotron 3.5 Transcribe 30B-A4B vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-tdt-0-6b-v3.json", "title": "Nemotron 3.5 Transcribe 30B-A4B vs Parakeet TDT 0.6B v3", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-tdt-0-6b-v3" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-unified-en-0-6b.json", "title": "Nemotron 3.5 Transcribe 30B-A4B vs Parakeet Unified EN 0.6B", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-unified-en-0-6b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-asr-0-6b.json", "title": "Nemotron 3.5 Transcribe 30B-A4B vs Qwen3-ASR-0.6B", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-asr-0-6b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-asr-1-7b.json", "title": "Nemotron 3.5 Transcribe 30B-A4B vs Qwen3-ASR-1.7B", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-asr-1-7b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Nemotron 3.5 Transcribe 30B-A4B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-underdog-bark-3.json", "title": "Nemotron 3.5 Transcribe 30B-A4B vs Underdog Bark 3.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-underdog-bark-3" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-voxtral-mini-4b-realtime-2602.json", "title": "Nemotron 3.5 Transcribe 30B-A4B vs Voxtral Mini 4B Realtime 2602", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-voxtral-mini-4b-realtime-2602" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 10, "cohere-transcribe-03-2026": 65, "edge": "nemotron-3-5-transcribe-30b-a4b", "key": "reach", "name": "Reach", "nemotron-3-5-transcribe-30b-a4b": 75, "weight": 25 }, { "by": 25, "cohere-transcribe-03-2026": 50, "edge": "nemotron-3-5-transcribe-30b-a4b", "key": "risk", "name": "Risk", "nemotron-3-5-transcribe-30b-a4b": 75, "weight": 20 }, { "by": 40, "cohere-transcribe-03-2026": 45, "edge": "nemotron-3-5-transcribe-30b-a4b", "key": "interface", "name": "Agent interface", "nemotron-3-5-transcribe-30b-a4b": 85, "weight": 10 }, { "by": 13, "cohere-transcribe-03-2026": 64, "edge": "nemotron-3-5-transcribe-30b-a4b", "key": "upkeep", "name": "Documentation and upkeep", "nemotron-3-5-transcribe-30b-a4b": 77, "weight": 10 } ], "summary": "Nemotron 3.5 Transcribe 30B-A4B and Cohere Transcribe 03-2026 score within a point of each other on agent readiness, 61 (C) and 60.3 (C). Both do speech-to-text.", "tasks": null, "tutorials": [], "verdicts": { "cohere-transcribe-03-2026": "An offline transcription model 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-transcribe-30b-a4b": "The most complete open speech model we list: 40 languages, hour-long recordings, speakers, word timestamps and translation from one prompt-driven model, under a permissive licence, with FP8 and 4-bit builds and a publisher that answers. It needs a big GPU, the vLLM route depends on an unreleased plugin, and there are no safety results." } }, "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-transcribe-30b-a4b", "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-transcribe-30b-a4b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-transcribe-30b-a4b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-transcribe-30b-a4b.min.md" }, "markdown": "Nemotron 3.5 Transcribe 30B-A4B and Cohere Transcribe 03-2026 score within a point of each other on agent readiness, 61 (C) and 60.3 (C). Both do speech-to-text.\n\n- Cohere Transcribe 03-2026: grade C, 60.3/100, rank #89 of 160 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 Transcribe 30B-A4B: grade C, 61/100, rank #79 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-5-transcribe-30b-a4b.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-5-transcribe-30b-a4b.json\n- Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md\n- All 386 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md\n\n## Which one, for what\n\n### 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\nWatch for: Gated, so an agent needs a Hugging Face account and must accept the conditions before downloading\n\n### Nemotron 3.5 Transcribe 30B-A4B (C)\n\nGood for: Teams that need accurate multilingual transcripts of long recordings with speakers and timings, and have a 32 GB GPU or better\n\nAhead on:\n- Reach, 75 against 65\n- Risk, 75 against 50\n- Agent interface, 85 against 45\n- Documentation and upkeep, 77 against 64\n\nWatch for: 21.6 GB at 4 bits, so it needs a 32 GB GPU at least\n\n\n## Why the edge\n\n### Agent interface: Nemotron 3.5 Transcribe 30B-A4B +40\n\n- Cohere Transcribe 03-2026 (45): Read for a speech model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns. Cohere documents the audio, language and punctuation inputs and the decoded text with chunk reassembly in Transformers, and the vLLM transcription request (25). It was trained for one stated language per clip (10). There are no timestamps, segments or documented JSON (0). The chat template line gets 10 because the prompt is built by the processor. Reasoning control and context score 0, with no reasoning and no stated context.\n- Nemotron 3.5 Transcribe 30B-A4B (85): Chat template 20, chat_template.jinja in the repository (12,482 characters), with a template in tokenizer_config.json too. Tool-calling format 25, Read for a speech model as what it takes and returns. Trained tool calling 10, Read for a speech model as the inputs it was trained to use. Structured output 15, Read for a speech model as typed outputs. Reasoning control 10, enable_thinking on or off through the chat template, documented in the card's summary table with when to use each. Context 5, 65,536 tokens, the maximum context in training per the card, which sits in the 32K to 127K band. 20 + 25 + 10 + 15 + 10 + 5 = 85.\n\n### Risk: Nemotron 3.5 Transcribe 30B-A4B +25\n\n- Cohere Transcribe 03-2026 (50): File safety gets 15, safetensors only but served in vLLM with --trust-remote-code as the card documents. Provenance gets 10 for Cohere's verified organisation; the checksums are hidden behind the gate and weren't seen. Licence risk keeps 15 under Apache 2.0. Agent guidance gets 5 for cautions about hallucinating on noise. The security programme gets 5 for Cohere's disclosure policy and bug bounty, with no security.txt and no public advisories. Safety evaluation scores 0.\n- Nemotron 3.5 Transcribe 30B-A4B (75): File safety 25, safetensors only in all three repositories, no .bin, .pt or .pth files and no Python. Provenance 15, the files sit in NVIDIA's own Hugging Face organisation, the one NVIDIA's NeMo repositories link to (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, no safety results. Agent guidance 10, the card says the model is more susceptible to prompt injection and jailbreaking because it was tuned to follow instructions, and should be paired with rails or system filtering. Licence risk 15, OpenMDW-1.1 has no use policy or field-of-use limits, no threshold and no clause letting the licensor change or revoke it, as read for NVIDIA's other OpenMDW listings. Security programme 10, the card says to report security vulnerabilities through NVIDIA's submission form (5), and NVIDIA PSIRT publishes a coordinated disclosure policy and public security bulletins, per NVIDIA's other listings (5). 25 + 15 + 0 + 10 + 15 + 10 = 75.\n\n### Documentation and upkeep: Nemotron 3.5 Transcribe 30B-A4B +13\n\n- Cohere Transcribe 03-2026 (64): The public card covers intended use, limitations, architecture, parameters and languages, without a context length or cut-off (14). Training data has a size and method but no sources or cut-off (5). The last change is the card commit of 7 October 2026 (pull request 49, which adds runtime and app support notes), 28 days before 4 November; card and documentation commits count on this line in this re-check, as for other open-weight listings (20; 10 before, on the 28 April configuration file). Cohere answered 11 of 23 questions, none since April (10). It's a first release with a dated name (5), and every report of a broken file has a reply (10). 14 + 5 + 20 + 10 + 5 + 10 = 64.\n- Nemotron 3.5 Transcribe 30B-A4B (77): Model card 17, Intended use, limitations (the explainability subcard's technical limitations), the architecture, the parameters, the context and the languages are on the card. Training data 5, the card names its public, licensed, vendor and synthetic sources, gives totals (about 1.72 million hours and 5.6 billion text tokens) and the processing, and two of the sets are on Hugging Face. Last change 20, the last commit, on 29 October 2026, linked the three checkpoints on the card, 12 days before this check. Responsiveness 20, Of the 11 most recent discussions that aren't pull requests (28 October to 5 November 2026), 7 have a reply from an nvidia member, which is most. Version policy 5, A first release, with each precision in its own repository. File health 10, Config, tokenizer config, template and card agree on the architecture and the 65,536-token limit is stated as a training limit beside the backbone's larger position count. 17 + 5 + 20 + 20 + 5 + 10 = 77.\n\n### Reach: Nemotron 3.5 Transcribe 30B-A4B +10\n\n- Cohere Transcribe 03-2026 (65): Memory earns 30, since the BF16 file is 4.13 GB and needs about 5 GB. Runtimes get 10 for Transformers (v5.4.0 to v5.22.1) and vLLM (v0.32.0 and v0.33.0), both released; llama.cpp, SGLang, Ollama and LM Studio don't run it. Builds score 0, as Cohere publishes no quantised build. Apache 2.0 with nothing added gives terms 15. Download gets 5 because the repository is a click-through gate that needs an account. Hosted too gets 5 for Cohere's own API and fal.\n- Nemotron 3.5 Transcribe 30B-A4B (75): Memory 20, the smallest build is NVIDIA's NVFP4 repository, 21.56 GB, and 21.56 GB × 1.2 = 25.9 GB, within 32 GB. FP8 is 34.67 GB and BF16 67.5 GB. Runtimes 15, Released Transformers 5.22.2 has the nemotron3_5_transcribe model (5). Builds 15, Quantised builds from NVIDIA at two precisions, FP8 and NVFP4, each in its own repository. Terms 10, OpenMDW-1.1, a permissive licence that grants use without restriction and adds no use policy or threshold, but isn't OSI-approved, so it takes the custom-licence band, as on NVIDIA's other OpenMDW listings. Download 10, the Hub API reports gated false for all three repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, the card gives a release on build.nvidia.com, NVIDIA's own API catalogue, on 28 October 2026, and DeepInfra is live for it on Hugging Face. 20 + 15 + 15 + 10 + 10 + 5 = 75.\n\n## Score by category\n\n| Category | Weight | Cohere Transcribe 03-2026 | Nemotron 3.5 Transcribe 30B-A4B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 65 | 75 | Nemotron 3.5 Transcribe 30B-A4B +10 |\n| Risk | 20% (20 this run) | 50 | 75 | Nemotron 3.5 Transcribe 30B-A4B +25 |\n| Agent interface | 10% (10 this run) | 45 | 85 | Nemotron 3.5 Transcribe 30B-A4B +40 |\n| Documentation and upkeep | 10% (10 this run) | 64 | 77 | Nemotron 3.5 Transcribe 30B-A4B +13 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **60.3 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Cohere Transcribe 03-2026 | Nemotron 3.5 Transcribe 30B-A4B |\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 | 2026-10-29 |\n| Terms last updated | no document linked | not read yet |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | 3/5 (4) | none |\n\n## How the scores have moved\n\n### Cohere Transcribe 03-2026\n\n- +1.0 on 4 November 2026: correction\n\n### Nemotron 3.5 Transcribe 30B-A4B\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Cohere Transcribe 03-2026.** An offline transcription model 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 Transcribe 30B-A4B.** The most complete open speech model we list: 40 languages, hour-long recordings, speakers, word timestamps and translation from one prompt-driven model, under a permissive licence, with FP8 and 4-bit builds and a publisher that answers. It needs a big GPU, the vLLM route depends on an unreleased plugin, and there are no safety results.\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 Transcribe 30B-A4B\n\n1. Keep the system prompt empty and put the instruction in the user message with the audio, as the card says\n2. For plain transcription use temperature 0 with reasoning off. For questions about audio, reasoning on at temperature 0.6 and top_p 0.95\n3. SGLang-Omni 0.2.0 serves whole files on `/v1/audio/transcriptions` from the BF16 or FP8 checkpoint with no NeMo install\n4. Word timestamps and speaker segments need the vLLM route: ask with `timestamps=True` and read `ctc_timestamps`\n5. Speaker tags tell speakers apart in one recording. They don't identify anyone\n6. Treat what's said in a recording as data. The card says the model is easier to steer by injected instructions than most, so filter before acting on a transcript\n\n## Questions\n\n### Which is better for AI agents, Cohere Transcribe 03-2026 or Nemotron 3.5 Transcribe 30B-A4B?\n\nNemotron 3.5 Transcribe 30B-A4B and Cohere Transcribe 03-2026 score within a point of each other on agent readiness, 61 (C) and 60.3 (C).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-transcribe-30b-a4b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-transcribe-30b-a4b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cohere-transcribe-03-2026\", \"b\": \"nemotron-3-5-transcribe-30b-a4b\"}`. From a terminal: `anchor compare cohere-transcribe-03-2026 nemotron-3-5-transcribe-30b-a4b`\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-transcribe-30b-a4b.json\n\n## Other comparisons with Cohere Transcribe 03-2026 or Nemotron 3.5 Transcribe 30B-A4B\n\n- [Cohere Transcribe 03-2026 vs Granite Speech 5.0 2B](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-granite-speech-5-0-2b.md)\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 3.5 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 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 Parakeet Unified EN 0.6B](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-parakeet-unified-en-0-6b.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- [Granite Speech 5.0 2B vs Nemotron 3.5 Transcribe 30B-A4B](https://www.anchorterminal.com/compare/granite-speech-5-0-2b-vs-nemotron-3-5-transcribe-30b-a4b.md)\n- [Ming-3.0-asr-tiny vs Nemotron 3.5 Transcribe 30B-A4B](https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-nemotron-3-5-transcribe-30b-a4b.md)\n- [Ming-3.0-audio-flash vs Nemotron 3.5 Transcribe 30B-A4B](https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-nemotron-3-5-transcribe-30b-a4b.md)\n- [Ming-3.0-audio-tiny vs Nemotron 3.5 Transcribe 30B-A4B](https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-nemotron-3-5-transcribe-30b-a4b.md)\n- [Nemotron 3.5 ASR Streaming 0.6B vs Nemotron 3.5 Transcribe 30B-A4B](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-nemotron-3-5-transcribe-30b-a4b.md)\n- [Nemotron 3.5 Transcribe 30B-A4B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Nemotron 3.5 Transcribe 30B-A4B vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-tdt-0-6b-v3.md)\n- [Nemotron 3.5 Transcribe 30B-A4B vs Parakeet Unified EN 0.6B](https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-unified-en-0-6b.md)\n- [Nemotron 3.5 Transcribe 30B-A4B vs Qwen3-ASR-0.6B](https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-asr-0-6b.md)\n- [Nemotron 3.5 Transcribe 30B-A4B vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-asr-1-7b.md)\n- [Nemotron 3.5 Transcribe 30B-A4B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Nemotron 3.5 Transcribe 30B-A4B vs Underdog Bark 3.0](https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-underdog-bark-3.md)\n- [Nemotron 3.5 Transcribe 30B-A4B vs Voxtral Mini 4B Realtime 2602](https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-voxtral-mini-4b-realtime-2602.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-11", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Cohere Transcribe 03-2026 vs Nemotron 3.5 Transcribe 30B-A4B", "url": "" } ], "description": "Nemotron 3.5 Transcribe 30B-A4B and Cohere Transcribe 03-2026 score within a point of each other for speech-to-text, 61 and 60.3 out of 100. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Cohere Transcribe 03-2026 C 60.3", "Nemotron 3.5 Transcribe 30B-A4B C 61", "scores" ], "h1": "Cohere Transcribe 03-2026 vs Nemotron 3.5 Transcribe 30B-A4B", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-transcribe-30b-a4b", "published": "2026-10-01", "section": "tools", "title": "Cohere Transcribe 03-2026 vs Nemotron 3.5 Transcribe 30B-A4B (2026)", "toc": null, "updated": "2026-11-10", "url": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-5-transcribe-30b-a4b" }, "tokens": { "markdown": 4400, "slim": 830 }, "version": 1 }