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NVIDIA's Nemotron 3.5 ASR introduces a cache-aware architecture that eliminates redundant computation in streaming audio processing, significantly reducing latency while maintaining accuracy. By consolidating 40 language locales into a single 600M-parameter checkpoint with native punctuation handling, the model offers a streamlined solution for both low-latency live transcription and high-throughput batch workloads. The release is available as open weights under the OpenMDW-1.1 license, providing immediate utility for production environments without the need for model swapping.
NVIDIA Releases Nemotron 3.5 ASR: A 600M-Parameter Cache-Aware Streaming Model Transcribing 40 Language-Locales in Real Time
NVIDIA released Nemotron 3.5 ASR, a cache-aware 600M streaming model transcribing 40 language-locales in real time from one checkpoint. The post NVIDIA Releases Nemotron 3.5 ASR: A 600M-Parameter Cache-Aware Streaming Model Transcribing 40 Language-Locales in Real Time appeared first on MarkTechPost.
NVIDIA’s Nemotron Speech team has released Nemotron 3.5 ASR. It is a 600M-parameter streaming Automatic Speech Recognition (ASR) model. A single checkpoint transcribes 40 language-locales in real time. Punctuation and capitalization are built in natively. The model ships as open weights on Hugging Face. The license is OpenMDW-1.1. The architecture is a Cache-Aware FastConformer-RNNT. What is Nemotron 3.5 ASR Nemotron 3.5 ASR extends nvidia/nemotron-speech-streaming-en-0.6b to many languages. It adds prompt-based language-ID conditioning to the base model. That lets one 600M-parameter checkpoint cover 40 language-locales. No per-language model or model-swapping is required. The model targets two workloads. The first is low-latency streaming for live audio. The second is high-throughput batch transcription. Output is production-ready text with proper…
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