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NVIDIA

NVIDIA Jetson Nano Developer Kit (945-13450-0000-100)

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Availability: In Stock.
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Arrives Monday, May 6
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Features

  • The NVIDIA Jetson Nano Developer Kit delivers the compute performance to run modern AI workloads at unprecedented size, power, and cost. Developers, learners, and makers can now run AI frameworks and models for applications like image classification, object detection, segmentation, and speech processing.
  • The developer kit can be powered by micro-USB and comes with extensive I/Os, ranging from GPIO to CSI. This makes it simple for developers to connect a diverse set of new sensors to enable a variety of AI applications. And it is incredibly power-efficient, consuming as little as 5 watts.
  • Jetson Nano is also supported by NVIDIA JetPack, which includes a board support package (BSP), Linux OS, NVIDIA CUDA, cuDNN, and TensorRT software libraries for deep learning, computer vision, GPU computing, multimedia processing, and much more. The software is even available using an easy-to-flash SD card image, making it fast and easy to get started.
  • The same JetPack SDK is used across the entire NVIDIA Jetson family of products and is fully compatible with NVIDIAs world-leading AI platform for training and deploying AI software. This proven software stack reduces complexity and overall effort for developers.

Description

The NVIDIA Jetson Nano Developer Kit delivers the compute performance to run modern AI workloads at unprecedented size, power, and cost. Developers, learners, and makers can now run AI frameworks and models for applications like image classification, object detection, segmentation, and speech processing. The developer kit can be powered by micro-USB and comes with extensive I/Os, ranging from GPIO to CSI. This makes it simple for developers to connect a diverse set of new sensors to enable a variety of AI applications. And it is incredibly power-efficient, consuming as little as 5 watts. Jetson Nano is also supported by NVIDIA JetPack, which includes a board support package (BSP), Linux OS, NVIDIA CUDA, cuDNN, and TensorRT software libraries for deep learning, computer vision, GPU computing, multimedia processing, and much more. The software is even available using an easy-to- flash SD card image, making it fast and easy to get started. The same JetPack SDK is used across the entire NVIDIA Jetson family of products and is fully compatible with NVIDIA’s world-leading AI platform for training and deploying AI software. This proven software stack reduces complexity and overall effort for developers.

Brand: NVIDIA


Model Name: 945-13450-0000-100


Memory Storage Capacity: 4 GB


Connectivity Technology: USB, GPIO


Operating System: Linux


RAM: ‎4 GB


Chipset Brand: ‎NVIDIA


Wireless Type: ‎Bluetooth


Brand: ‎NVIDIA


Series: ‎945-13450-0000-100


Item model number: ‎945-13450-0000-100


Operating System: ‎Linux


Item Weight: ‎8.5 ounces


Product Dimensions: ‎2.72 x 1.77 x 1.77 inches


Item Dimensions LxWxH: ‎2.72 x 1.77 x 1.77 inches


Processor Brand: ‎NVIDIA


Number of Processors: ‎1


Computer Memory Type: ‎DDR SDRAM


Manufacturer: ‎NVIDIA Corporation


Country of Origin: ‎China


Date First Available: ‎February 10, 2020


Frequently asked questions

If you place your order now, the estimated arrival date for this product is: Monday, May 6

Yes, absolutely! You may return this product for a full refund within 30 days of receiving it.

To initiate a return, please visit our Returns Center.

View our full returns policy here.

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Top Amazon Reviews

    • Perfect platform for AI/ML for CUDA leaning tasks
Jetson Nano is great for not only robotics/edge AI, you can use ML for science usage such as medical imaging or environmental data to speed up your workflow. From personal experience even an underclocked dual-core power save mode on the Jetson Nano will still be faster on CUDA AI/ML tasks than a Raspberry Pi 4, however your workflow may vary. If you use AI/ML that isn't optimized for CUDA, in some cases a Pi 4 raw CPU compute can edge out the Nano. I would say if you pair a Pi 4 with any AI/ML accelerator it'll cost more than a Jetson Nano and your mileage is still going to vary. Depending upon how you use a Jetson Nano, for robotics/automation you can actually run four cameras via USB and use the camera interface. Performance wise if you do opt to run a Jetson Nano using USB power, your mileage is going to vary as not all USB power adapters provide a stable voltage which means checking the specs--I reused a Canakit USB power adapter from a retired Pi 3 and never had any voltage warnings but if you plan to run a Jetson Nano hard like a Pi 4 you'll want to use the barrel power adapter for extra power stability when using multiple USB devices+GPIO. Thermal wise I've compared a fanless vs fan equipped Jetson Nano, even under sustained load the heatsink size prevents it from thermal throttling too much. This B01 version has two camera connectors which is geared for stereo imaging however you can run two cameras at a small performance loss and also fixed the networking issue which occurred on the original Jetson Nano A01/A02. From a performance per watt/dollar ratio, if you're going to dive deeper into AI/ML a Jetson NX is more ideal. With a Jetson Nano if you're pushing four cameras and LIDAR it'll require a bit of tweaking to get optimal performance and still remain at about 3.5GB of memory usage. ... show more
Reviewed in the United States on April 12, 2021 by Science4Life
    • its working
good
Reviewed in the United States on November 23, 2023 by genesis hafalla
    • So far so good
After repairs from shipping damage. Not the sellers fault. It works great. I'm using it as the brain for my r2d2 project and so far it's doing everything I ask it to.
Reviewed in the United States on April 11, 2023 by Zach pinkerton
    • If your mobile project needs a GPU, this is your starting point.
I hope Nvidia keeps producing these. The price/performance point is perfect for the application I am using it in.
Reviewed in the United States on May 20, 2023 by Eric T.
    • Awesome
Exactly as it describes.
Reviewed in the United States on July 13, 2023 by Tyler
    • Way past its prime
I expected this to be, basically, a Raspberry Pi with a GPU. A computer I could flash with any arm64/aarch64 OS and it Just Work. Boy, was I wrong. Despite being called a "Dev Kit", this is just the device itself. Nvidia just calls it a " non-production-grade" product, so Dev Kit is just a euphemism for it being a low-quality product, on purpose. The docs say you need a 5V 2A power supply, but that is not true. It will not even boot unless it has at least 4A, so make sure you buy the right one. The Jetson Linux SD card image in the Getting Started docs is half a decade old. Even the most current version of Jetson Linux available for this product is based on Ubuntu 18.04, which reaches EOL in May 2023. Nvidia is *not* releasing updates for Jetson Linux that are compatible with this product, so it will be obsolete and wholly unsupported by both Nvidia and Canonical after May 2023. So you're on your own. Even after getting Jetson Linux up and running, it's stuffed with bloatware like OS-integrated Facebook search (circa 2018) and a variety of games and a vastly outdated version of the whole Libreoffice suite. The default desktop theme and wallpaper is nausea-inducingly garish, reminiscent of the fad around lightning and dragon themed bowling shirts, circa 1998. It is possible to upgrade the OS from Ubuntu 18.04 all the way up to 21.04 if you're motivated enough. Each upgrade causes more volatility and instability, though, so YMMV and if you're planning to do this, be very cautious and make backups along the way. I spent 7 hours attending this process (yes, you have to attend it because along the way, there are random confirmations you actually have to read, because sometimes the default is to abort the process, setting you back an hour or more. Ask me how I know this). After carefully upgrading, one major version at a time (bionic to focal, focal to jammy), the upgrade from jammy to koala bricked the OS and none of my recovery attempts were fruitful. The problem with just using Jetson Linux right out of the box, without upgrading, is that you have to work within the time capsule of what was available at that time. Modern tools, AI models, etc, developed since will either not have the necessary dependencies, or taken as a whole, will not work with such an antiquated system. Combine that with this product being effectively abandoned with no future in sight for official support or continued development, and even if you're a seasoned, highly competent software engineer, you're in for a world of hurt. If you do buy this product, I hope you have a lot of patience and tolerance for disorder and chaos. You're going to need all of it. ... show more
Reviewed in the United States on May 6, 2023 by Devin Canterberry
    • poor support
I couldn't start both of the Nano jetson kits. I called NDIVIA support from India, a technician event listing. Need to set the jumper to to work
Reviewed in the United States on January 15, 2023 by murat
    • A welcome upgrade from the 2gb
The 4gb gives my belabor extra computer power. That's great for multitasking and encoding.
Reviewed in the United States on May 8, 2023 by Amazon Customer

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