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Displaying 269 results

TAO Toolkit
NVIDIA
Docker containers distributed as part of the TAO Toolkit package
Container
Triton Inference Server
NVIDIA
Triton Inference Server is an open source software that lets teams deploy trained AI models from any framework, from local or cloud storage and on any GPU- or CPU-based infrastructure in the cloud, data center, or embedded devices.
Container
PyTorch
NVIDIA
PyTorch is a GPU accelerated tensor computational framework. Functionality can be extended with common Python libraries such as NumPy and SciPy. Automatic differentiation is done with a tape-based system at the functional and neural network layer levels.
Container
TensorFlow
Google
TensorFlow is an open source platform for machine learning. It provides comprehensive tools and libraries in a flexible architecture allowing easy deployment across a variety of platforms and devices.
Container
TensorRT LLM Release
NVIDIA
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.
Container
TensorRT
NVIDIA
NVIDIA TensorRT is a C++ library that facilitates high-performance inference on NVIDIA graphics processing units (GPUs). TensorRT takes a trained network and produces a highly optimized runtime engine that performs inference for that network.
Container
vLLM
NVIDIA
vLLM is a fast and easy-to-use library for LLM inference and serving. The NVIDIA vLLM NGC Container is optimized for GPU acceleration, and contains a validated set of libraries that enable and optimize GPU performance.
Container
CUDA Deep Learning
NVIDIA
CUDA is a parallel computing platform and programming model that enhances computing performance using NVIDIA GPUs. CUDA Deep Learning integrates networking and GPU-accelerated libraries like cuDNN, cuTensor, NCCL, HPC-x, and the CUDA Toolkit.
Container
NVIDIA Optimized Deep Learning Framework powered by Apache MXNet
Apache Software Foundation
NVIDIA Optimized Deep Learning Framework, powered by Apache MXNet is a deep learning framework that allows you to mix the flavors of symbolic programming and imperative programming to maximize efficiency and productivity.
Container
Allegro Trains Agent
Allegro AI
Allegro Trains delivers an optimized, seamless, and scalable solution for training on DGX machines with ML-Ops and experiment management features.
Container
NVIDIA Magnum IO Developer Environment
NVIDIA
NVIDIA Magnum IO is the I/O technologies from NVIDIA and Mellanox that enable applications at scale. The Magnum IO Developer Environment container allows developers to begin scaling their applications on a laptop, desktop, workstation, or in the cloud.
Container
JAX
NVIDIA
JAX is a framework for high-performance numerical computing and machine learning research. It includes Numpy-like APIs, automatic differentiation, XLA acceleration and simple primitives for scaling across GPUs and supports an ecosystem of libraries.
Container
Dynamo Platform
NVIDIA
A comprehensive Helm chart for deploying the NVIDIA Dynamo operator and its dependencies
Helm Chart
CUDA GL
NVIDIA
CUDA is a parallel computing platform and programming model that enables dramatic increases in computing performance by harnessing the power of the NVIDIA GPUs. These images extend the CUDA images to include OpenGL support through libglvnd.
Container
TensorRT LLM Develop
NVIDIA
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.
Container
Kaldi
NVIDIA
Kaldi is an open-source software framework for speech processing.
Container
PyG
NVIDIA
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
Container
sglang-runtime-nightly
NVIDIA
The Dynamo SGLang runtime nightly image is a containerized build of Dynamo + SGLang which serves as the base runtime environment for sglang based inference with Dynamo's distributed inference framework which is published every night.
Container
vllm-runtime-nightly
NVIDIA
The Dynamo vLLM runtime nightly image is a containerized build of Dynamo + vLLM which serves as the base runtime environment for vLLM based inference with Dynamo's distributed inference framework published at a nightly cadence.
Container
tensorrtllm-runtime-nightly
NVIDIA
The Dynamo TensorRT-LLM runtime nightly image is a containerized build of Dynamo + TensorRT-LLM which serves as the base runtime environment for tensorrt-llm based inference with Dynamo's distributed inference framework published at a nightly cadence.
Container
Getting Start with Recommender System
NVIDIA
The Variational Autoencoder for collaborative filtering focuses on providing recommendations.
Resource
SGLang
NVIDIA
SGLang is a fast serving framework for large language models and vision language models. The NVIDIA SGLang NGC Container is optimized for GPU acceleration, and contains a validated set of libraries that enable and optimize GPU performance.
Container
Triton Inference Server PB October 2025 (PB 25h2)
NVIDIA
Triton Inference Server PB October 2025 (PB 25h2) offers a 9-month lifecycle for API stability, with monthly patches for high and critical software vulnerabilities.
Container
DGL
NVIDIA
Deep Graph Library (DGL) is a Python package built for the implementation and training of graph neural networks on top of existing DL frameworks. The DGL NGC Container is built with the latest versions of DGL, PyTorch, and their dependencies.
Container
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