NVIDIA Nemotron 3.5 Transcribe has landed: a 30B-A4B open-weight model that turns up to an hour of recorded speech into searchable transcripts, speaker labels, translations, and answers.
🤖 https://modelscope.ai/collections/nv-community/Nemotron-35-Transcribe
🏆 Leading transcription and speaker attribution: Ranks first among open-weight models on the Hugging Face English Open ASR Leaderboard, and first on both David AI’s multilingual diarization benchmark and VoiceArena’s 14-system comparison.
🌍 One checkpoint, multiple speech tasks: Transcribes 40 languages, translates 31 languages to and from English, and supports speaker attribution in 13 languages for recordings with up to eight speakers.
🎯 Guide the output with natural language: Prompt for domain terms, transcript conventions, translations, speaker labels, or questions about the recording. Language support differs by task; audio Q&A is trained in English.
🔧 Adapt it to your domain: Granary v2 and NeMo Speech fine-tuning tools extend prompt-level control to training. In the medical case study, fine-tuning reduced held-out WER by 45.8% over the best prompt-only baseline.
⚡ Built for self-hosted batch transcription: Runs on a single GPU, from DGX Spark to Blackwell data-center systems.
📜 License: openmdw-1.1