[Late catch] Nemotron 3.5 Transcribe: NVIDIA's open-weight model for transcription, speaker labels and translation in 40 languages

Nemotron 3.5 Transcribe is an open-weight model that turns recorded speech into text. It's a mixture-of-experts (MoE) model with 34B parameters in total, of which about 4.3B are active per token. It transcribes 40 languages, translates 31 of them to or from English, and labels up to eight speakers in recordings up to an hour long. You can steer the output format or the spelling of domain terms with plain-language instructions, and it ships in BF16, FP8 and NVFP4. It loads directly in Transformers.

pip install -U transformers accelerate

NVIDIA says it posts the lowest error rates among open-weight models: a 4.71% mean WERVendor claim across the nine English sets of the Hugging Face Open ASR Leaderboard and 4.62%Vendor claim across seven languages. That means a single model can power meeting notes, call centers or medical dictation where you need speaker labels and translation together, and it runs on your own GPUs so audio never leaves your network. NVIDIA also released the Granary v2 training data and fine-tuning recipes, which makes adapting it to domain vocabulary easier.