NVIDIA JetPack
NVIDIA JetPack™ is the official software stack for the NVIDIA Jetson™ platform, giving you a comprehensive suite of tools and libraries for building AI-powered edge applications. JetPack 7, the latest evolution in the series, is the most advanced software stack yet, purpose-built to enable cutting-edge robotics and generative AI at the edge. It’s agentic-ready with NVIDIA® NemoClaw™ and purpose-built Jetson agent skills, so you can set up edge AI workflows with a single command. With full support for NVIDIA Jetson platforms, JetPack 7 provides ultra-low latency, deterministic performance, and scalable deployment for machines that interact with the physical world.
JetPack Downloads and NotesJetson Linux Developer GuideDeveloper Forum
JetPack 7 Overview
JetPack 7 gives you full support for the NVIDIA Jetson Orin™ and Thor™ platform, preemptable real-time kernel, Multi-Instance GPU (MIG), and integrated Holoscan Sensor Bridge. Built on Linux Kernel 6.8 and Ubuntu 24.04 LTS, and designed with a modular, cloud-native architecture, it integrates the latest NVIDIA AI compute stack and seamlessly integrates with NVIDIA AI workflows. Whether you’re developing humanoid robots or building an application with the most demanding generative AI workload, JetPack 7 delivers the software foundation to bring them to life.
JetPack 7 is also agent-friendly and optimized for popular AI agents with purpose-built Jetson agent skills. This lets developers quickly set up agentic workflows and accelerate development time. JetPack 7.2 also officially supports the Yocto Project on Jetson, enabling custom, reproducible Linux distributions for optimized performance and deterministic edge AI deployments.
Jetson agent skills help developers build, configure, optimize, and measure Jetson applications through reusable workflows. Key skills include Jetson Linux customization for faster time to market through automated BSP bring-up for custom carrier boards, memory optimization to run more capable workloads on smaller memory footprints and lower TCO, and model benchmarking to find the optimal model configuration for each Jetson device.
With JetPack 7, Jetson software aligns with the Server Base System Architecture (SBSA), positioning Jetson Thor alongside industry-standard Arm server design. SBSA standardizes critical hardware and firmware interfaces, delivering stronger OS support, simpler software portability, and smoother enterprise integration. Building on this foundation, Jetson Thor now supports a unified NVIDIA® CUDA® 13.0 installation across all Arm targets, streamlining development, reducing fragmentation, and ensuring consistency from server-class systems to Jetson Thor.
Click Image to Enlarge
Agentic Frameworks on JetPack SDK
Note: Jetson Thor is based on the SBSA stack. Please use the SBSA installer when installing from the links below.
NemoClaw
JetPack 7 is built for agentic AI. Starting with JetPack 7.2, NVIDIA NemoClaw can be installed with a single command, enabling developers to easily run and orchestrate both local and cloud AI models on Jetson devices. This simplifies building intelligent, autonomous, and multimodal edge AI applications.
Jetson Agent Skills
Agent skills package NVIDIA expertise into reusable, agent-deployable workflows that help developers build, configure, optimize, and validate systems with clear guidance and developer-in-the-loop controls, turning manual tasks like BSP customization, memory optimization, and model benchmarking into structured workflows that reduce risk, time to market, and TCO.
Components of the JetPack SDK
AI Compute Stack
Note: Jetson Thor is based on the SBSA stack. Please use the SBSA installer when installing from the links below.
CUDA
The NVIDIA® CUDA® Toolkit provides a powerful development environment for creating GPU-accelerated applications, including a compiler, math libraries, and debugging tools.
cuDNN
The NVIDIA cuDNN (CUDA Deep Neural Network) library offers high-performance primitives for deep learning, with optimized implementations for convolution, pooling, normalization, and activation layers.
TensorRT
NVIDIA TensorRT™ is a high-performance inference runtime that optimizes and accelerates deep learning models, delivering low latency and high throughput across major frameworks.
AI Frameworks
PyTorch
PyTorch is a fast, flexible deep learning framework with NGC containers for easy deployment across AI tasks like NLP, computer vision, and recommendation systems.
SGLang
SGLang is a fast serving framework for large language models and vision language models.
Triton Inference Server
NVIDIA Triton Inference Server™ enables seamless AI deployment across cloud and edge environments, ensuring consistency and performance optimization.
Jetson Linux Components and Libraries
Flashing
Jetson devices can be flashed with Jetson Linux through multiple methods, from command-line tools to automated scripts, with NVIDIA SDK Manager offering the most user-friendly option.
Security
Jetson Linux delivers a comprehensive suite of security features spanning edge to cloud, including secure boot, disk encryption, runtime integrity, fTPM, and secure OTA updates.
OTA
OTA (Over-the-Air) updates on Jetson enable seamless, remote delivery of software and security upgrades, keeping devices up-to-date without manual intervention.
Graphics Libraries
Jetson supports various graphics APIs, including OpenGL, Vulkan, and EGL, enabling GPU-accelerated rendering and compute for advanced 3D graphics and UI rendering.
Multimedia APIs
Jetson Linux Multimedia APIs provide low-level access to camera and video processing hardware. This lets you create high-performance applications with fine-grained control over multimedia pipelines.
Computer Vision Libraries
JetPack includes optimized computer vision libraries like OpenCV and VisionWorks that accelerate image processing and vision tasks on Jetson platforms using GPUs and dedicated hardware.
The Yocto Project Support
NVIDIA now officially supports Yocto Project , making it easier for developers to build custom embedded Linux distributions for Jetson platforms. Full-stack, NVIDIA-validated recipes and reference images are available through OE4T, providing a streamlined foundation for creating production-ready, secure, and optimized embedded AI systems.
Other JetPack Components
Cloud-Native Design
Cloud-native design on Jetson helps you create scalable AI applications at the edge with containerized development, Kubernetes, and microservices, bridging cloud and edge development.
Nsight Developer Tools
NVIDIA Nsight™ developer tools provide powerful profiling, debugging, and performance analysis for optimizing GPU-accelerated applications across AI, graphics, and compute workloads.
Supported SDKs
NVIDIA DeepStream SDK
This SDK gives you a powerful toolkit for building AI-powered vision applications, enabling real-time video analytics with accelerated inference and object tracking.
NVIDIA Isaac ROS
NVIDIA Isaac ROS is a collection of hardware-accelerated ROS 2 packages for NVIDIA Jetson. It’s ideal for high-performance perception, localization, and AI in robotics applications.
NVIDIA Holoscan SDK
NVIDIA Holoscan SDK is a streaming AI framework for building real-time sensor-processing applications at the edge. It enables high-performance pipelines for healthcare, robotics, and industrial use cases.
Community Support
Jetson AI Lab
Jetson AI Lab is an interactive platform for learning and experimenting with AI on NVIDIA Jetson, offering hands-on projects, tutorials, and tools tailored for edge AI development.
Developer Forums
NVIDIA Developer Forums are a community hub for developers to ask questions, share knowledge, and get support on NVIDIA technologies, platforms, and SDKs..
Ethical AI
NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.
For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety & Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns here.