Nemotron 3.5 Transcribe vs Granite Speech 5.0

Official Nemotron 3.5 Transcribe hero figure from the NVIDIA Hugging Face card — nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B hero.png. Source · License: NVIDIA card image.

Official Granite Speech 5.0 2B English ASR comparison figure from the IBM model card — ibm-granite/granite-speech-5.0-2b card assets/granite-5.0-2b-vs-open-english.png. Source · License: Apache-2.0.

Verdict. Pick Nemotron 3.5 Transcribe if you want NVIDIA’s ungated 30B-A4B offline speech SALM (OpenMDW-1.1; in-checkpoint speaker tags; 40-language card; vendor H100-class serve). Pick Granite Speech 5.0 if you want IBM’s Apache-2.0 ~2.3B file ASR/AST family (speaker tags on the 4.1-2B Plus sibling). Same job class (file transcription), different size and license. Vendor WER tables stay self-reported. We have no sourced bake-off.

Compare Nemotron 3.5 Transcribe and Granite Speech 5.0.

Dimension	Nemotron 3.5 Transcribe	Granite Speech 5.0	Source
License (weights)	OpenMDW-1.1 (LICENSE file + license_name)	Apache-2.0 (card tag; 5.0-2B siblings list had no LICENSE blob)	Hugging Face (2026-10-29 / 2026-10-24)
Gating	No	No	Hugging Face API
Developer	NVIDIA Corporation	IBM	Official cards
Parameters	Card 34B / 4.3B active (30B-A4B name); safetensors 33,697,781,029	~2.3B on the 5.0-2B card; safetensors 2,313,207,132	Official cards / HF API
Job	Offline file ASR/AST + in-checkpoint speaker tags; not streaming	File ASR + bidirectional AST; Plus sibling does speaker tags	Official cards
Languages (card)	40 on cardData.language	Six-language ASR on 5.0-2B (en/fr/de/es/pt/ja)	Official cards
Serving named	vLLM 0.32.0 + NeMo Speech; Transformers; SGLang-Omni named	Transformers, vLLM, llama.cpp, mlx-audio (family blog)	Official cards / IBM blog
Hugging Face likes	182 (2026-10-29)	48 (5.0-2B, 2026-10-24)	Hugging Face API
Quality vs Otter / Descript	Not independently tested	Not independently tested	n/a

When to choose which

NVIDIA OpenMDW-1.1 30B-class offline ASR with in-model speaker tags: Nemotron 3.5 Transcribe — Identification of the card, not a quality rank. Vendor H100-class serve.
Compact Apache-2.0 ~2.3B file ASR/AST: Granite Speech 5.0 — Size is not a quality claim.
Speaker tags without loading a 30B-class SALM: Granite Speech 5.0 — Tags live on granite-speech-4.1-2b-plus. Nemotron also does speaker-attributed ASR on this card.
Live simultaneous speech-to-speech: neither — Use Hy-SimulMT or Hibiki-Zero. Both of these cards are file/offline ASR.

Read the entity pages: Nemotron 3.5 Transcribe and Granite Speech 5.0. Both hang off Otter.ai alternatives and Descript alternatives. Nemotron 3.5 Transcribe is not Nemotron 3.5 Bolt or Nemotron 3.5 Super VL.

Why this comparison exists

Searchers who want open file transcription now have NVIDIA’s 30B-A4B Transcribe card next to IBM’s ~2.3B Granite Speech 5.0 family. Same job class (offline / file ASR). Different size, license, and speaker-tag path. This is identification, not a bake-off.

Sourced snapshot (2026-10-29)

Field	Nemotron 3.5 Transcribe	Granite Speech 5.0-2B
Host	huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B (not gated)	huggingface.co/ibm-granite/granite-speech-5.0-2b (not gated)
HF likes	182 (2026-10-29)	48 (2026-10-24)
License	OpenMDW-1.1 (LICENSE file)	Apache-2.0 (card tag)
Size	Card 34B / 4.3B active; ~33.7B tensors	~2.31B tensors
Job	Offline file ASR/AST; in-checkpoint speaker tags	File ASR + bidirectional AST
Serve path	vLLM 0.32.0 + NeMo Speech (vendor H100)	Transformers / vLLM (card)
Quality vs Otter / Descript	Not independently tested	Not independently tested

License

Nemotron: OpenMDW-1.1 LICENSE file. Granite 5.0-2B: card tag apache-2.0; no LICENSE blob in the siblings list we opened on 2026-10-24. Not legal advice.

How to choose

Need NVIDIA’s 30B-class offline ASR (OpenMDW-1.1, in-model speaker tags): Nemotron 3.5 Transcribe.
Need compact Apache-2.0 file ASR/AST (~2.3B): Granite Speech 5.0.
Need live Chinese–English simultaneous speech-to-speech: Hy-SimulMT — Hy-SimulMT vs Granite Speech 5.0.
Need live French / Spanish / Portuguese / German → English S2ST: Hibiki-Zero.
Need diarization-only speaker turns: pyannote community-1.
Need local Whisper STT: whisper.cpp.
Need a chat VLM, not speech: Nemotron 3.5 Bolt or Nemotron 3.5 Super VL.

FAQ

Which is more accurate?

We have no sourced bake-off. Nemotron’s Open ASR Leaderboard / cpWER rows and Granite’s Cap-F1 / WER rows stay vendor. Do not merge those tables.

Can either replace Otter or Descript?

No. Neither page is a meeting-notes product or a timeline editor. See Otter.ai alternatives and Descript alternatives.

Is Transcribe the same as Nemotron 3.5 Bolt?

No. Bolt is a vision-language local-agent MoE. Super VL is a larger VLM. Transcribe is speech in → text out.

Why this pairing?

Both are published file ASR/AST pages on this site. Hy-SimulMT and Hibiki-Zero are streaming S2ST — already compared with Granite.

Sources & verification

Last verified 2026-10-29 · Last updated 2026-10-29· Edited by forkalt editors · Editorial policy

License notes are not legal advice. Read the original LICENSE. Trademark & disclaimer.