computer science

Nvidia Jetson

Nvidia Jetson is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Nvidia Jetson rather than just read about it. In short: Nvidia Jetson is a series of embedded computing boards from Nvidia. The Jetson TK1, TX1 and TX2 models all carry a Tegra processor (or SoC) from Nvidia that integrates an ARM architecture central processing unit (CPU).

Key takeaways

Nvidia Jetson belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Nvidia Jetson to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Nvidia Jetson from memory before moving on to harder problems.

Reference excerpt

Nvidia Jetson is a series of embedded computing boards from Nvidia. The Jetson TK1, TX1 and TX2 models all carry a Tegra processor (or SoC) from Nvidia that integrates an ARM architecture central processing unit (CPU). Jetson is a low-power system and is designed for accelerating machine learning applications.

Hardware

The Jetson family includes the following boards:

In late April 2014, Nvidia shipped the Nvidia Jetson TK1 development board containing a Tegra K1 SoC in the T124 variant and running Ubuntu Linux. The Nvidia Jetson TX1 development board bears a Tegra X1 of model T210. The Nvidia Jetson TX2 board bears a Tegra X2 of microarchitecture GP10B (SoC type T186 or very similar). This board and the associated development platform was announced in March 2017 as a compact card design for low power scenarios, e.g. for the use in smaller camera drones such as the Skydio 2. A matrix describing a set of performance modes was provided by the media along with that. Further a TX2i variant, said to be rugged and suitable for industrial use cases, is mentioned. The Nvidia Jetson Xavier was announced as a development kit in end of August 2018. Indications were given that a 20x acceleration for certain application cases compared to predecessor devices should be expected, and that the application power efficiency is 10x improved. Nvidia Jetson Xavier NX has a 6-core Nvidia Carmel ARMv8.2. The Nvidia Jetson AGX Xavier is the 8-core version on the same core architecture (Carmel Armv8.2).

The Nvidia Jetson Nano was announced as a development system in mid-March 2019 The intended market is for hobbyist robotics due to the low price point. The final specs expose the board being sort of a power-optimized, stripped-down version of what a full Tegra X1 system would mean. Only half of the CPU (only 4x A57 @ 1.43 GHz) and GPU (128 cores of Maxwell generation @ 921 MHz) cores are present and only half of the maximum possible RAM is attached (4 GB LPDDR4 @ 64 bit + 1.6 GHz = 25.6 GB/s) whilst the available or usable interfacing is determined by the baseboard design and is further subject of implementation decisions and specifics in an end user specific design for an application case. The Nvidia Jetson Nano Developer Kit.

In September 2022 Nvidia announced the Jetson Orin Nano. The modules have the same 260-pin SO-DIMM connector and 69.6 mm x 45 mm dimensions, and come in two variants. The 4 GB variant provides 20 Sparse or 10 Dense TOPs, using a 512-core Ampere GPU with 16 Tensor cores, while the 8 GB variant doubles those numbers to 40/20 TOPs, a 1024-core GPU and 16 Tensor cores. Both have 6 Arm Cortex-A78AE cores. The 4 GB module starts at $199 and the 8 GB variant for $299, when purchasing 1000 units. In December 2024, Nvidia announced the updated Orin Nano with a claimed 1.7x performance improvement and a price reduction of the development kit from $499 to $249 In August 2025, the Jetson AGX Thor was released. It features 128 GiB memory and a Blackwell GPU capable of 2,070 FP4 TFLOPS. Nvidia claims the AGX Thor delivers 7.5x more computing power and 3.5x the efficiency compared to the previous generation Orin.

Performance There are various versions of the Jetson board available.

Maxwell architecture The published operation modes of the Nvidia Jetson Nano are:

Pascal architecture

The published performance modes of the Nvidia Jetson TX2 are as follows.

Jetson TX2 also has 5 power modes, numbered 0 through 4 as published by NVIDIA. The default mode is mode 3 (MAX-P).

Volta architecture

Ampere architecture

Software Various operating systems and software might be able to run on the Jetson board series.

Linux JetPack is a software development kit (SDK) from Nvidia for their Jetson board series. It includes the Linux for Tegra (L4T) operating system and other tools. The official Nvidia download page bears an entry for JetPack 3.2 (uploaded there on 2018-03-08) that states:

JetPack 3.2 adds support for the Linux for Tegra r28.2 image for the Jetson OS. It is packaged with newer versions of Tegra System Profiler, TensorRT, and cuDNN from the last release. RedHawk Linux is a high-performance RTOS available for the Jetson platform, along with associated NightStar real-time development tools, CUDA/GPU enhancements, and a framework for hardware-in-the-loop and man-in-the-loop simulations.

QNX The QNX operating system also available for the Jetson platform, though it is not widely announced. There are success reports of installing and running specific QNX packages on certain Nvidia Jetson board variants. Namely the package qnx-V3Q-23.16.01 that is seemingly in parts based on Nvidia's Vibrante Linux distribution is reported to run on the Jetson TK1 Pro board.

Reported military and export-control issues In August 2026, Ukrainian military intelligence alleged that a Jetson Orin module was present in Russia's S-71 'Monochrome' cruise missile, though Nvidia stated the product is not export-controlled and not officially sold in Russia.

The module in question is reportedly an Orin NX 8GB/16GB, rated up to 157 sparse INT8 TOPS on an Ampere-architecture GPU with 1024 CUDA cores, and has been shipping commercially since 2023.

The specific module (Orin NX 8GB/16GB), its spec (up to 157 sparse INT8 TOPS, Ampere GPU, 1024 CUDA cores), and shipping history (available since 2023).

See also Computer vision Raspberry Pi Movidius neural compute stick

References

Illustrations

Worked examples

Example 1 — a first encounter with Nvidia Jetson

Start with the simplest possible case. Write down what Nvidia Jetson claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Nvidia Jetson before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Nvidia Jetson ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Nvidia Jetson

In research: Nvidia Jetson appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Nvidia Jetson in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Nvidia Jetson is common in secondary-school and first-year university syllabi. It links to neighbouring topics ARM-based single-board computers, Linux-based devices, Nvidia products, so understanding it makes those chapters shorter.
In everyday life: Look for Nvidia Jetson outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Nvidia Jetson in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Nvidia Jetson means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Nvidia Jetson out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Nvidia Jetson in simple terms?

Why does Nvidia Jetson matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Nvidia Jetson?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Nvidia Jetson.