NVIDIA Corporationの公開GitHubフットプリント

Run agents like Hermes, LangChain Deep Agents, and OpenClaw more securely inside NVIDIA OpenShell with managed inference

Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, security risks, prompt injection, data exfiltration, and supply-chain risks in Claude Code, Codex, and MCP skills before you install them.

OpenShell is the safe, private runtime for autonomous AI agents.

Ongoing research training transformer models at scale

NVIDIA Linux open GPU kernel module source

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. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.

NVIDIA Cosmos is an open platform of world models, datasets, and tools that enables developers to build Physical AI for robots, autonomous vehicles, smart infrastructure, and more.

PersonaPlex code.

CUDA Templates and Python DSLs for High-Performance Linear Algebra

cuDF - GPU DataFrame Library

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

the LLM vulnerability scanner

NVIDIA Isaac GR00T N1.7 - A Foundation Model for Generalist Robots.

A Python framework for GPU-accelerated simulation, robotics, and machine learning.

A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.

NVIDIA cuML: GPU-Accelerated Machine Learning

Tacotron 2 - PyTorch implementation with faster-than-realtime inference

Optimized primitives for collective multi-GPU communication

Build and run containers leveraging NVIDIA GPUs

NVIDIA device plugin for Kubernetes

NVIDIA's CUDA platform for Rust. Host runtime crates plus Tile (cutile-rs) and SIMT (cuda-oxide) kernel programming models in idiomatic Rust.

Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end.

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory utilization in both training and inference.

CUDA Python: Performance meets Productivity

Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods

NVIDIA GPU Operator creates, configures, and manages GPUs in Kubernetes

The NVIDIA NeMo Agent toolkit is an open-source library for efficiently connecting and optimizing teams of AI agents.

CUDA Core Compute Libraries

CUDA Library Samples

`std::execution`, the standard C++ framework for asynchronous and parallel programming.

AIStore: scalable storage for AI applications

NVIDIA GPU metrics exporter for Prometheus leveraging DCGM

Router that virtually distributes inference across connected devices in the home.

This repo contains the source code for RULER: What’s the Real Context Size of Your Long-Context Language Models?

NVIDIA DLSS is a new and improved deep learning neural network that boosts frame rates and generates beautiful, sharp images for your games

Collection of step-by-step playbooks for setting up AI/ML workloads on NVIDIA DGX Spark devices with Blackwell architecture.

An efficient C++20 GPU numerical computing library with Python-like syntax

Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.

C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

A simple yet powerful tool to turn traditional container/OS images into unprivileged sandboxes.

GPU accelerated decision optimization

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

NVIDIA cuDF for Apache Spark plugin - accelerate Apache Spark with GPUs

NVIDIA Federated Learning Application Runtime Environment

cuDNN Frontend is NVIDIA's modern, open-source entry point to the cuDNN library and a growing collection of high-performance open-source kernels.

cuVS - a library for vector search and clustering on the GPU

SOMA BVH to humanoid robot motion retargeting library built with Newton and NVIDIA Warp

このリポジトリに関する説明は提供されていません。

Caffe: a fast open framework for deep learning.

Multi-tier framework for evaluating AI agent skills with quality gates, semantic overlap detection, synthetic evaluation dataset generation, and live agent evaluation that measures how skills affect agent behavior.

Our inference and training framework to run on the Cosmos Models

repo collection for NVIDIA Audio2Face-3D models and tools

NVIDIA cuOpt examples for decision optimization

Container plugin for Slurm Workload Manager

Shared capture infrastructure for teleoperation and egocentric data.

NVSentinel detects and remediates GPU faults on Kubernetes nodes

Foundation Models for Structured Data

Massively parallel training of machine-learning based weather and climate models

NVIDIA Kaggle Plugin gives agents end-to-end Kaggle competition workflows through a single skill, nvidia-kaggle-skill. It can gather competition context, study public writeups and notebooks, reproduce kernels locally, submit to competitions, and manage Ka

From PyTorch model to end-to-end TensorRT inference experience in two commands—AI-native, cross-platform, and built for the best possible user experience.

OptiX + GL based implementations of ANARI

The developer-first platform for scaling complex Physical AI workloads across heterogeneous compute—unifying training GPUs, simulation clusters, and edge devices in a simple YAML

MIG Partition Editor for NVIDIA GPUs

Platform for deploying and routing GPU-accelerated inference, streaming, and batch workloads at scale.

NVIDIA DLA-SW, the recipes and tools for running deep learning workloads on NVIDIA DLA cores for inference applications.

Auto Ontology is a Python framework for building semantic, graph-based reasoning layers over data. It enables deterministic query generation, better context retrieval, and more explainable AI for LLM and agent workflows.

Multi-language agent runtime and library for execution scope management, lifecycle events, and middleware on tool and LLM calls.

ALCHEMI Toolkit is a developer toolkit for accelerating training and inference for AI in chemistry and material science.

SimReady Foundation is a central repository for defining simulation content specifications based on various runtime use cases.

Accelerated libraries for quantum-classical computing built on CUDA-Q.

The UI SDK and agent-ready developer toolkit for AI factories, robotics, and autonomous vehicles.

DOCA Platform manages provisioning and service orchestration for Bluefield DPUs

:coffee:️ Simulate NVIDIA GPU infrastructure on CPU nodes in Kubernetes

XR AI

Unified high-performance Python client for object and file stores.

knavigator is a development, testing, and optimization toolkit for AI/ML scheduling systems at scale on Kubernetes.

NVIDIA Cluster Readiness Engine

NVIDIA cuDF plugin JNI For Apache Spark

Linux kernel source tree

Synthetic Data Generation Workflows for Physical AI

NVIDIA NeMo Fabric

🧪 OpenShell's Research Journal

Deploy AI agents to investigate cluster issues and streamline governed AI factory operations.

The open-source model suite for robotics data engine by NVIDIA GEAR

Diffusion-based pipeline for generating photorealistic, mask-aligned synthetic anomaly images for industrial visual inspection from only a few real examples

CUDA-accelerated Python tools for astronomical and multi-dimensional data access, image subtraction, warping, candidate classification, and scientific review.

Accelerated algorithm libraries for quantum-classical computing built on CUDA-Q

Packages for the Skyhook Kubernetes Operator.

A do everything Redfish, KVM, GUI, and DBus webserver for OpenBMC

Synthetic data generation engine using NVIDIA Isaac Sim and Omniverse Replicator to render photorealistic, fully labeled PCB inspection imagery, including golden and defect boards

One Python client for NVIDIA's structured-data foundation models: ask a predictive question of one table or of a whole relational schema, and get an answer without training anything.

A machine learning compiler for GPUs, CPUs, and ML accelerators

Reusable GitHub Actions workflows and common scripts for Spark RAPIDS

Visualization Engine & Libraries on ANARI

YAML-preserving + Protobuf round-trip in-toto signing format, seeking evolutionary hardening through public collaboration.

Scaled workflows for PAIDF

yaml-sigil-spec Rust implementation workspace (core + api libs)

Run-time JSON driven system configuration manager