Nvidia Releases Open Nemotron 3.5 Transcribe Model for 40 Languages

Nvidia released Nemotron 3.5 Transcribe on Wednesday, October 28, as an open-weight speech model covering 40 languages. One checkpoint handles transcription, speaker labels, translation and spoken-question answering on recordings up to an hour long.

At a Glance

• Nemotron 3.5 Transcribe translates 31 languages to or from English and attributes speakers in 13, telling up to eight apart.
• The model averages a 5.33% word error rate on the English track of Hugging Face’s Open ASR Leaderboard.
• Transcribe posted the lowest speaker-attribution error rate among 14 systems on David AI’s 21-language diarization leaderboard.
• Granary v2, Nvidia’s updated open speech dataset, lists 463,062 hours across 48 languages, up from 25 in version 1.

Nvidia folds speaker labels into the transcript

Nvidia is pitching the model at developers building meeting tools and medical dictation, one of the older footholds for AI in healthcare. One prompt can turn a meeting recording into a speaker-labeled transcript, and another can pull out the decisions made. Nvidia trained audio question answering only in English, and the model card warns that language support differs by task.

Transcribe pairs a speech encoder with a hybrid Mamba-Transformer mixture-of-experts language model. Only about 4 billion of its 30 billion parameters are active per token. That keeps each token far cheaper than the full size suggests. Speaker cues from Nvidia’s Sortformer reach the language model…