Search  for anything...
NVIDIA

NVIDIA Jetson Thor Developer Kit

  • Based on 0 reviews
Condition: New
Checking for the best price...
$3,499.99 Why this price?

Buy Now, Pay Later

As low as / mo
  • – Up to 36-month term if approved
  • – No impact on credit to apply
  • – Instant approval decision
  • – Secure and straightforward checkout

Ready to go? Add this product to your cart and select a plan during checkout.

Payment plans are offered through our trusted finance partners Klarna, Affirm, Afterpay, Apple Pay, and PayTomorrow. No-credit-needed leasing options through Acima may also be available at checkout.

Learn more about financing & leasing here.

Free shipping on this product

FREE 30-day refund/replacement

To qualify for a full refund, items must be returned in their original, unused condition. If an item is returned in a used, damaged, or materially different state, you may be granted a partial refund.

To initiate a return, please visit our Returns Center.

View our full returns policy here.

Availability: Only 3 left in stock, order soon!
Fulfilled by Amazon
Arrives Monday, Apr 27
Order within 17 hours and 4 minutes
Available payment plans shown during checkout
Protection Plan Protect Your Purchase
Checking for protection plans...

Recently Viewed

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 GHz


Video Output Interface: DisplayPort, HDMI


Graphics Coprocessor: NVIDIA Blackwell GPU


Graphics Card Ram: 128 GB


GPU Clock Speed: 1.57 GHz


Video Output Interface: DisplayPort, HDMI


Graphics Ram Type: GDDR6X


Compatible Devices: Humanoid Robots, Specialized AI/robotics Systems


Display Resolution Maximum: 3840x2160


Graphics Card Interface: PCI-Express x16


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


Manufacturer: NVIDIA Corporation


UPC: 810152850435


Item Weight: 6.5 Pounds


Unit Count: 1.0 Count


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: Monday, Apr 27

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.

  • Klarna Financing
  • Affirm Pay in 4
  • Affirm Financing
  • Afterpay Financing
  • PayTomorrow Financing
  • Financing through Apple Pay
Leasing options through Acima may also be available during checkout.

Learn more about financing & leasing here.

Similar Products

Top Amazon Reviews

    • Best Edge AI & Robotics Device by far
Great product, easy to setup and powerful. By far the best hardware for Edge AI and Robotics. Note that the device is not optimized to run Omniverse or IsaacLab.
Reviewed in the United States on December 15, 2025 by Manuel Villanueva
    • I LOVE ROBOTS
Runs o llama 70b instruct model perfectly. Had it casually talking to me within a couple hours out the box
Reviewed in the United States on March 11, 2026 by Brayden Z
    • Basically a cheaper DGX spark w/ different cluster capability
Good device, be prepared to navigate bios for setup. Its a dev device.
Reviewed in the United States on March 9, 2026 by Brook
    • 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
    • Great for running LLMs
Jetson Thor performs very well and if you are happy building latest from source you get very good results with vllm.
Reviewed in the United States on February 1, 2026 by Jeff S
    • A must buy for Robotics Engineers
It’s fantastic, the only issue I see is that it needs to be shipped with a 4Tb SSD
Reviewed in the United States on December 14, 2025 by Victor Williams
    • Whack-a-mole!
Observed behavior: - usbipd “endless attach loop” on a BUSID is insufficient because BUSID changes when the USB identity changes. - Device may vanish from Connected list and remain only as Persisted, indicating the USB device is not enumerating on the host (cable/port/power management sensitivity). - Host component installs (Nsight Perf SDK) fail due to missing utilities (unzip) or symlink collisions (file exists), creating false “installation failed” signals unrelated to the device wipe objective. ... show more
Reviewed in the United States on January 10, 2026 by Kim
    • Does not work out of the box
Initial boot fails to flash the operating system. $3k for a computer that does not work out of the box.
Reviewed in the United States on December 8, 2025 by hdub

Can't find a product?

Find it on Amazon first, then paste the link below.
Checking for best price...