NVIDIA Corporation
@nvidia • Open source projects from nvidia. Use this route to separate flagship concentration from portfolio breadth before you treat a publisher as broadly strong.
Portfolio concentration
75%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
30 repos
Visible snapshot
30 repositories updated in the last 90 days.
Leading language
Python
Portfolio mix
Python (14), C++ (5), TypeScript (2)
Average size
22
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
Updated: 2026-07-25(11d ago)GitHub API fallback30 repositories
75%
of the visible star count comes from this organization's top three repositories.
22
stars per repository in this same snapshot.
Python
is the most common language here, with 30 repositories updated in the last 90 days.
Why this rank
This organization stands out because its public portfolio is relatively balanced across 30 repositories.
Balanced portfolio across 30 reposTop 3 share 75%
Organization pages work best when you separate portfolio breadth from flagship concentration. In NVIDIA Corporation's case, the visible top three repositories account for about 75% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is Python (14), C++ (5), TypeScript (2). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
Top Repositories
| # | Repository | Language | Stars |
|---|---|---|---|
| 1 | nvidia/nvidia-kaggle 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 | Python | 280 |
| 2 | nvidia/instant-nurec InstantNuRec: Feed-Forward 3D Gaussian Reconstruction from Driving Logs | Python | 154 |
| 3 | nvidia/halos-outside-in-safety NVIDIA Halos Outside-In Safety Blueprint extends robot perception beyond on-board sensors by using external infrastructure cameras and AI agents to dynamically control robot behavior and perform at maximum efficiency. | C++ | 60 |
| 4 | nvidia/nccl-extensions Communication patterns for AI, built on top of NCCL device and host APIs | Cuda | 25 |
| 5 | nvidia/nv-config-manager NVIDIA Switch Infrastructure - Config Manager | Python | 21 |
| 6 | nvidia/NeMo-Fabric NVIDIA NeMo Fabric | Python | 20 |
| 7 | nvidia/aerial-omniverse-digital-twin Aerial Omniverse Digital Twin (AODT) | TypeScript | 15 |
| 8 | nvidia/NPPDx NVIDIA Pipeline Processing Device Extensions | C++ | 14 |
| 9 | nvidia/game-agent-sdk NVIDIA Game Agent SDK | C++ | 13 |
| 10 | nvidia/Spatial-IQ A diagnostic framework that decomposes 3D object counting into nine hierarchical spatial perception and cognition sub-tasks. Analysis code for the paper Spatial-IQ: Deconstructing Spatial Intelligence via Hierarchical Capability Tests. | Python | 12 |
| 11 | nvidia/boro Linux patch review and testing CLI with a multi-stage agentic workflow | Rust | 9 |
| 12 | nvidia/srt-slurm-recipes Official NVIDIA/srt-slurm sweep configs for benchmarking LLMs across NVIDIA GPUs and frameworks, spanning aggregated and disaggregated serving on single- and multi-node setups. | Python | 6 |
| 13 | nvidia/nv-telemetry Collection of libraries for bare-metal telemetry collection | Rust | 5 |
| 14 | nvidia/OpenShell-Research 🧪 OpenShell's Research Journal | Python | 5 |
| 15 | nvidia/oncrpc-ping A ping-like utility to measure ONC RPC (Sun RPC) service latency | C | 4 |
| 16 | nvidia/SkillEvaluator 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. | Python | 4 |
| 17 | nvidia/nvidia-azure-samples This repository maintains sample applications designed for NVIDIA software tools integrated with Microsoft Azure. For select demonstrations, the sample code is contained within this repository. | Python | 3 |
| 18 | nvidia/dream-team DreamTeam is a multi-agent solver for interactive ARC-AGI-3 environments | Python | 2 |
| 19 | nvidia/NeMo-Speech.cpp NeMo-Speech.cpp is a GGML optimized C++ inference solution for Speech models | C++ | 2 |
| 20 | nvidia/go-nvfm Go Bindings for the NVIDIA Fabric Manager SDK (NVFM) | C | 2 |
| 21 | nvidia/media-function-operator-kit Media Function Operator Kit | Go | 2 |
| 22 | nvidia/calibro Calibro is a comprehensive, platform-agnostic specification that defines what data should be captured when running a benchmark — field names, types, units, semantics, justifications, and collection methods. | 1 | |
| 23 | nvidia/mctp-utils MCTP tool running on Host to communicate with devices via USB and other transport layers. | Python | 1 |
| 24 | nvidia/storage-lender A service that lends NVMe I/O queues to unprivileged clients over a Unix domain socket. | C++ | 0 |
| 25 | nvidia/gdbscripts This repository contains the GDB Toolbox to be used with an official GDB to debug Tegra SOCs | Python | 0 |
| 26 | nvidia/paidf-orchestration Scaled workflows for PAIDF | Python | 0 |
| 27 | nvidia/nvidia-aws-samples NVIDIA GPU Accelerated Application Samples in Amazon Web Services (AWS) | Jupyter Notebook | 0 |
| 28 | nvidia/gmmts_lib The official code for the paper GMMTS | Python | 0 |
| 29 | nvidia/nvidia-oci-samples NVIDIA GPU Accelerated Application Samples in Oracle Cloud Infrastructure (OCI) | TypeScript | 0 |
| 30 | nvidia/pytorch-windows-ci Out of tree repo to run pytorch CI tests on Nvidia GPUs for Windows | PowerShell | 0 |
Next step after the organization read
Open a flagship repository, compare a couple of portfolio leaders, or return to the organization map when you want a broader concentration read.
Learn and methodology
Keep trust-building context reachable, but behind the first data read instead of ahead of it.
How to read this organization snapshot
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.