NeMo

Checkout our HuggingFace🤗 collection for the latest open
weight checkpoints and demos!
Updates
> NeMo Speech 3.0 is now available as release v3.0.0
> and in the 26.07.00 NeMo Speech NGC container.
> The final NeMo release before the repository split was
> v2.7.3, available in the
> 26.04 NeMo NGC container.
- 2026-07: MagpieTTS v2607 has been released with support
for 3 new languages (Ar, Ko, Pt) + 9 existing languages (En, Es, De, Fr, Vi, It, Zh, Hi, Ja). Try out
the demo!
- 2026-06: Nemotron-3.5-ASR-Streaming-0.6B has been released with 40 languages supported, controllable latency 80ms-1s, and 240-2400 1xH100 concurrent streams. Built on cache-aware Fastconformer architecture.
- 2026-04: Parakeet-unified-en-0.6b has been released with high-quality offline and streaming (with a minimum latency of 160ms) inference in one model for English language with punctuation and capitalization support.
- 2026-03: Nemotron 3 VoiceChat is now released in Early Access. Built on the Nemotron Nano v2 LLM backbone with Nemotron speech and TTS decoder, VoiceChat delivers full-duplex, natural, interruptible conversations with low latency. Try out the demo and apply for early access.
- 2026-03: Nemotron-Speech-Streaming v2603 has been
updated. It has been trained on a larger and more diverse corpus, resulting in lower WER across all latency modes.
Try out the demo and check out
the NIM.
- 2026-03: MagpieTTS v2602 has been released with support
for 9 languages (En, Es, De, Fr, Vi, It, Zh, Hi, Ja).
- 2026-01: Nemotron-Speech-Streaming was released: One checkpoint that enables users to pick their optimal point
on the latency-accuracy Pareto curve!
- 2026-01: MagpieTTS v2512 was released.
- 2026: This repo has pivoted to focus on audio, speech, and multimodal LLMs. For the final pre-split NeMo release with
support for additional modalities, see v2.7.3.
- 2025-08: Parakeet V3 and
Canary V2 have been released with speech recognition and translation
support for 25 European languages.
- 2025-06: Canary-Qwen-2.5B has been released with record-setting
5.63% WER on English Open ASR Leaderboard.
Introduction
NVIDIA NeMo Speech is built for researchers and PyTorch developers working on Speech models including Automatic Speech
Recognition (ASR), Text to Speech (TTS), and Speech LLMs. It is designed to help you efficiently create, customize, and
deploy new AI models by leveraging existing code and pre-trained model checkpoints.
For technical documentation, please see the
NeMo Speech Developer Documentation.
Requirements
NeMo Speech works with the **Python, PyTorch, and CUDA versions of your choosing**:
- Python 3.12 or above
- PyTorch 2.7 or above (CPU, CUDA, etc. — your choice)
- NVIDIA GPU + CUDA (required for training; recommended for inference)
If you already have a Python/PyTorch/CUDA stack that satisfies those minimums, NeMo Speech installs on top of it **without replacing it**, so your existing PyTorch build is kept (see the install options below). The versions pinned in uv.lock and shipped in the official container — Python 3.13, PyTorch 2.11 with CUDA 12.9 or PyTorch 2.12 with CUDA 13.2 — are simply the combinations we actively test and support. They make setup turnkey and reproducible, but they are **not** a hard requirement.