Installation

This page covers how to install NVIDIA NeMo for speech AI tasks (ASR, TTS, speaker tasks, audio processing, and speech language models).

Prerequisites

Before installing NeMo, ensure you have:

1. Python 3.12 or above

2. PyTorch 2.7+ (install before NeMo so CUDA wheels match your GPU driver)

3. NVIDIA GPU (required for training; CPU-only inference is possible but slow)

Recommended installation order

Install dependencies in this order when setting up a local GPU environment:

1. Create and activate a Python environment.

2. Install a CUDA toolkit (or rely on a driver + PyTorch bundle that matches your CUDA major version).

3. Install PyTorch (and torchvision if you need it) from the index that matches your CUDA build.

4. Install NeMo (from PyPI or editable source) with the extras for the collections you need (asr, tts, etc.).

Putting PyTorch in place first avoids mismatched CUDA runtimes and makes NeMo’s optional GPU-dependent packages resolve correctly.

Example (conda + pip, CUDA 13.0 PyTorch wheels):

# 1) New environment (adjust Python version if your platform requires it)
conda create -n nemo python=3.12 -y
conda activate nemo

# 2) CUDA toolkit from conda (optional if you already have a compatible toolkit via the driver)
conda install nvidia::cuda-toolkit

# 3) PyTorch built for CUDA 13.x — change cu130 / URL if you use cu124 or CPU-only
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu130

# 4) NeMo: use extras for ASR/TTS/etc. For a clone of the repo, use editable install (see below)
pip install nemo_toolkit[asr,tts]

Adjust the PyTorch --index-url (e.g. cu124, cu121, or CPU) to match PyTorch’s install matrix and your NVIDIA driver.

Install from PyPI

The quickest way to install NeMo is via pip. Install only the collections you need:

# Install ASR and TTS (most common)
pip install nemo_toolkit[asr,tts]

# Install everything speech-related
pip install nemo_toolkit[asr,tts,audio]

Available extras:

Extra	What it includes
asr	Automatic Speech Recognition models, data loaders, and utilities
tts	Text-to-Speech models, vocoders, and audio codecs
audio	Audio processing models (enhancement, separation)

Install from Source

For the latest development version or if you plan to contribute, clone the repository and install in editable mode.

The test extra pulls in pytest and tooling for the test suite. It does not install NeMo collection dependencies (ASR, TTS, audio, etc.). Add those extras explicitly or imports like nemo.collections.asr will fail.

git clone https://github.com/NVIDIA/NeMo.git
cd NeMo

# After PyTorch is installed (see Recommended installation order above):
# Collections you need for development (required for nemo.collections.* imports)
pip install -e '.[asr,tts]'

# Optional: add test to run pytest with NeMo’s dev test dependencies
# pip install -e '.[asr,tts,test]'

Using Docker

NVIDIA provides Docker containers with NeMo pre-installed. Check the NeMo GitHub releases for the latest container tags.

Verify Installation

After installing, verify that NeMo is working:

import nemo.collections.asr as nemo_asr
print("NeMo ASR installed successfully!")

# Quick test: load a pretrained model
model = nemo_asr.models.ASRModel.from_pretrained("nvidia/parakeet-tdt-0.6b-v2")
print(f"Model loaded: {model.__class__.__name__}")

What’s Next?

• NeMo Speech Inference in 5 Minutes — A quick tour of NeMo’s speech capabilities

• Key Concepts in Speech AI — Understand the fundamentals of speech AI

• Choosing a Model — Find the right model for your use case