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NVIDIA

NVIDIA Jetson Thor Developer Kit

  • Based on 30 reviews
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Availability: 11 left in stock
Fulfilled by Kemp IT, Inc.
Arrives Wednesday, Aug 26
Order within 2 hours and 19 minutes
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Features

  • GPU:2560-core NVIDIA Blackwell architecture GPU with 96 fifth-gen Tensor Cores
  • AI Performance:2070 TFLOPS

Description

NVIDIA Jetson Thor Developer Kit

Graphics Coprocessor: NVIDIA Blackwell GPU


Brand: NVIDIA


Graphics Ram Size: 128 GB


GPU Clock Speed: 1.57 gigahertz


Video Output Interface: DisplayPort, HDMI


Graphics Coprocessor: NVIDIA Blackwell GPU


Graphics Card Ram: 128 GB


GPU Clock Speed: 1.57 gigahertz


Video Output Interface: DisplayPort, HDMI


Graphics Ram Type: GDDR6X


Compatible Devices: Humanoid Robots, Specialized AI/robotics Systems


Graphics Card Interface: PCI-Express x16


Display Maximum Resolution: 3840 x 2160


Display Resolution Maximum: 3840x2160


Brand: NVIDIA


Video Processor: NVIDIA


Antenna Location: Artificial Intelligence, Autonomous Machines, Edge Computing, Generative AI, Humanoid Robotics, Industrial Automation, Physical AI, Robotics, Vision AI


Built-In Media: Information Not Available


Model Name: Jetson Thor Developer Kit


Graphics Description: NVIDIA Blackwell GPU, 128 GB graphics memory


Unit Count: 1 Count


Number of Packs: 1


Manufacturer: NVIDIA Corporation


Number of Items: 1


UPC: 810152850435


Item Weight: 6.5 pounds


Model Number: 945-14070-0080-000


Mfr Part Number: 945-14070-0080-000


Warranty Description: 1 year warranty for development use only


Frequently asked questions

If you place your order now, the estimated arrival date for this product is: Wednesday, Aug 26

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

    • Nvidia’s best
Review Image by Amazon Customer
Amazing product! Arrived fast with no issues
Reviewed in the United States on July 6, 2026 by Amazon Customer
    • Slow bandwidth, still amazing
Writing this June 23rd 2026. Anemic memory bandwidth, calibrate your expectations accordingly. It is still amazing to see things running locally and doing real work pretty much immediately.
Reviewed in the United States on June 23, 2026 by Gary
    • One to rule them all
If you are looking for a great server to help with your AI tasks, this is the one. This is the best of the best. Read the specs. The performance is a great value for your money. Nvidia did most of the heavy lifting for you. If you know what you doing, get this one. This is one of those if you know you know situations. ... show more
Reviewed in the United States on May 20, 2026 by Chris Lewis
    • Love this
This is impressive!
Reviewed in the United States on June 7, 2026 by Arthur
    • Not easy to use
Nice hardware, but not consumer friendly. The Nvidia software stack is currently broken for this, so some demos do not work.
Reviewed in the United States on April 21, 2026 by Roger Schlafly
    • Expensive junk that does not work.
Does not work, flashing does not work, libraries don't work. This is an overpriced, useless junk. Get Mac mini, or Mac Studio, or just build a MicroATX, it will work better and faster.
Reviewed in the United States on April 11, 2026 by Gene
    • Incomplete disorganized documentation, SDK lackluster
Disclaimer: I know this is intended for robotics with companies like Anduril, Lockheed, Raytheon, etc. likely being the target demo but the marketing copy had me convinced this would be an easy button for running containers with CUDA and unified memory. Well, that’s only true if you like running one-off commands from CLI or using desktop GUIs. Don’t get your hopes up if you use containers, unless you love “docker run” syntax and don’t care about security. The documentation is all over the place. Important repos disappear from their site, for which you then have to find a random mirror some private citizen put on GitHub and pray it works. The SDK (Jetpack) and jetson-containers project are designed to wrap docker, NOT podman|systemd|kubernetes|etc. so if your preference is not docker or baremetal be prepared to suffer. “Jetson OS” (Linux for Tegra or L4T rebranded) is built on Ubuntu LTS 22.04 with so many outdated packages for container support - be prepared to build low level dependencies and common tool chains from source while spending hours stumbling through Nvidia’s forums to find a stray comment from an employee that offers a clue to resolving a permissions issue introduced by an undocumented security patch. Hey Nvidia I want a functional declarative container stack, not being limited to “docker run” please. dusty-nv’s “jetson-containers” repo is cool for finding prebuilt container images designed to work with the CUDA samples already in place for the T5000/Blackwell, but I don’t want to use DOCKER! Let alone run on bare metal... You need to improve general LXC support and keep the repos up to date with latest dependencies and toolchains. At the very least you should ship your own flavor of minikube or similar with jetson-containers bundled, to keep the official packages from getting trampled while us users hack around the broken pieces… I should be able to copy my existing declarative container configs (YAML|TOML|JSON, k8s for compose|quadlet|podlet, don’t care which) to this machine and run them with minimal adaption necessary. The Nvidia hooks/wrappers and syntax for using the CTK need to be collocated and/or config paths clearly documented in one KB page. Overall, if you buy this instead of a MINISFORUM/Beelink/Mac Studio, you’re paying a premium for CUDA support that’s only officially offered two ways: Baremetal or Docker (just Docker-anything else you’re on your own). The added complexity of ARM builds always being an afterthought for many projects is almost enough to make me wish I did a custom multi-4090 GPU x86 rig instead. P.S. Some announcement about who is taking over dusty-nv’s work and what the future of Jetson looks like would be nice. ... show more
Reviewed in the United States on January 8, 2026 by FFW
    • It works
This device is taken by those who know why they take it. So the review “it works”.
Reviewed in the United States on April 20, 2026 by Kirill Keker

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