nemotron-speech-streaming-en

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[!Note] June 4, 2026: New multilingual model released: NVIDIA Nemotron 3.5 ASR Streaming 0.6B extends this English streaming ASR model to 40 language-locales in a single 600M-parameter model. It supports language-ID prompt conditioning, optional automatic language detection, punctuation and capitalization, and configurable low-latency streaming chunk sizes.

March 12, 2026: nemotron-asr-streaming was released with updated checkpoint (trained on larger corpora). For the older checkpoint released in January 2026, please refer to the nemotron-speech-streaming-jan2026 branch.

Nemotron-ASR-Streaming is an English, streaming Automatic Speech Recognition (ASR) engineered to deliver high-quality English transcription across both low-latency streaming and high-throughput batch workloads. Developed by NVIDIA, this 600M parameter model transcribes speech into text with native support for punctuation and capitalization and offers runtime flexibility with configurable chunk sizes, including 80ms, 160ms, 560ms, and 1120ms.

By leveraging the state-of-the-art Cache-Aware FastConformer-RNNT architecture, the model eliminates redundant overlapping computations common in traditional "buffered" streaming. This allows it to process only new audio chunks while reusing cached encoder context, significantly improving computational efficiency and minimizing end-to-end delay without sacrificing accuracy.

It transcribes speech into the English alphabet, spaces, and apostrophes, with full support for punctuation and capitalization. Trained on the ASRSet, a massive dataset of approximately 250,000 hours of US English (en-US) speech, it is engineered to perform across diverse and challenging acoustic conditions.

Why Choose nvidia/nemotron-asr-streaming?

• Native Streaming Architecture: Cache-aware design enables efficient processing of continuous audio streams, designed and optimized for low-latency voice agent applications interaction.

• Improved Operational Efficiency: Delivers superior throughput compared to traditional buffered streaming approaches. This allows for a higher number of parallel streams within the same GPU memory constraints, directly reducing operational costs for production environments.

• Dynamic Runtime Flexibility: Enables you to choose the optimal operating point on the latency-accuracy Pareto curve at inference time. No re-training is required to adjust for different use-case requirements.

• Punctuation & Capitalization: Built-in support for punctuation and capitalization in output text

  Nemotron-asr-streaming, outperforming Jan26 version, allows users to choose the optimal operating point on the latency-accuracy pareto curve at inference time, without requiring any re-training. Further, the cache-aware streaming mechanism scales much better than buffered streaming approaches, consistently outperforming production models like parakeet-ctc-1_1b-asr across chunk sizes.

This model consists of a cache-aware streaming 🦜 Parakeet (FastConformer) encoder with an RNN-T decoder. It is designed for real-time speech-to-text applications where low latency is critical, such as voice assistants, live captioning, and conversational AI systems. Unlike traditional "buffered" streaming, the cache-aware architecture enables continuous transcription by processing only new audio chunks while reusing cached encoder context. This significantly improves computational efficiency and minimizes end-to-end delay without sacrificing accuracy.

🗣️ Experience Nemotron-Speech-Streaming-En-0.6b in action here: https://huggingface.co/spaces/nvidia/nemotron-speech-streaming-en-0.6b

This model is ready for commercial/non-commercial use.

Read more about the model in the dev blog and check out the paper.

License/Terms of Use:

Governing Terms: Use of the model is governed by the NVIDIA Open Model License Agreement.

Deployment Geography:

Global

Use Case:

This model is for transcription of English audio.

Release Date:

• Build.Nvidia.com [03/13/2026] via https://build.nvidia.com/nvidia/nemotron-asr-streaming/
• Hugging Face [03/13/2026] via https://huggingface.co/nvidia/nemotron-speech-streaming-en-0.6b (older checkpoint [01/05/2026] via https://huggingface.co/nvidia/nemotron-speech-streaming-en-0.6b/tree/nemotron-speech-streaming-jan2026)
• NGC [03/13/2026] via https://catalog.ngc.nvidia.com/orgs/nvidia/collections/nemotron-asr-streaming

Explore more from NVIDIA:

For documentation, deployment guides, enterprise-ready APIs, and the latest open models—including Nemotron and other cutting-edge speech, translation, and generative AI—visit the NVIDIA Developer Portal at developer.nvidia.com. Join the community to access tools, support, and resources to accelerate your development with NVIDIA's NeMo, Riva, NIM, and foundation models.

What is Nemotron? NVIDIA Developer Nemotron [NVIDIA Riva Speech](https://developer.nvidia.com/riva?sortBy=developer_learning_library%2Fsort%2Ffeatured_in.r