NVIDIA Jetson AGX Thor Overview and Developer Resources

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Welcome to RidgeRun's guide to NVIDIA®Jetson AGX Thor™



NVIDIA® Jetson AGX Thor is a high-performance computing platform for advanced physical AI and robotics—particularly humanoid robots. It features a Blackwell-architecture GPU and 128 GB LPDDR5X, delivering up to 2070 FP4 TFLOPS of AI compute for high-speed sensor processing and real-time control.

NVIDIA Jetson AGX Thor

NVIDIA Jetson AGX Thor developer kit

The NVIDIA Jetson AGX Thor Developer Kit is NVIDIA's reference platform for the Jetson Thor: it exposes high-bandwidth I/O, power delivery, and thermal design so you can profile end-to-end workloads (LLMs, VLMs, sensor fusion) under realistic conditions.

NVIDIA Jetson AGX Thor SoM

Jetson AGX Thor System-on-Module (SoM)

At the heart of the developer kit is the Jetson AGX Thor SoM, a production-ready compute module that integrates CPU, GPU, memory, and accelerators. The SoM is designed to be embedded directly into final products—robots, autonomous machines, and edge servers—where size, power, and reliability constraints matter.

What is new in NVIDIA Jetson AGX Thor?

NVIDIA® Jetson AGX Thor is the latest flagship in the NVIDIA Jetson lineup, pushing edge AI computing to a new level of performance and scalability. Some of its main features are:

Feature Description
CPU Complex 14-core Arm® Neoverse V3AE (64-bit) with SMP architecture
GPU Architecture Blackwell Architecture with 2560 CUDA Cores and 96 4th Gen Tensor Cores, including a new Transformer Engine and support for Multi-Instance GPU (MIG)
Memory 128 GB LPDDR5X
Memory Bandwidth 256-bit bus @ 4266 MHz, delivering up to 273 GB/s – optimized for Large Language Models
On-Edge AI Performance Up to 2070 TFLOPs (FP4) | 1035 TFLOPs (FP8)
Holoscan Sensor Bridge Open sensor-to-compute bridge that streams multimodal data over Ethernet with GPU-direct, eliminating PCIe/USB bottlenecks for low latency and scalable bandwidth
Multi-Instance GPU (MIG) GPU GPC blocks can be partitioned into two independent MIG instances, each behaving as a standalone GPU
PVA 3.0 Programmable Vision Accelerator v3.0: 165 GFLOPs (FP32) | 320 GFLOPs (FP16)

What are the potential applications of NVIDIA Jetson AGX Thor?

Jetson AGX Thor is purpose-built for advanced edge AI and robotics use cases, including:

  • Autonomous Machines – Industrial robots, collaborative robots, and autonomous mobile robots requiring real-time multimodal sensor fusion.
  • AI-Enhanced Healthcare – Medical imaging, surgical robotics, and Holoscan-enabled sensor-driven diagnostics.
  • Smart Cities & Infrastructure – Intelligent traffic systems, real-time video analytics, and large-scale sensor network management.
  • Next-Gen Vehicles – Autonomous driving, driver-assist systems, and software-defined vehicle platforms.
  • Generative AI on the Edge – Running large transformer-based LLMs, vision-language models, and generative applications in disconnected or low-latency environments.
  • Defense & Aerospace – Rugged AI deployments for UAVs, drones, and mission-critical sensor fusion workloads.

NVIDIA Jetson AGX Thor represents the convergence of HPC, AI, and sensor integration — all at the edge.



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The following video from NVIDIA provides a nice overview of the NVIDIA Jetson AGX Thor.


RidgeRun Support

RidgeRun is an official NVIDIA Partner, and we have created this extensive set of documentation to support our joint customers. If you have any questions on the content, please contact us through our contact us page.

RidgeRun provides support for embedded Linux Camera Driver development for NVIDIA's platforms, specializing in the use of hardware accelerators in multimedia applications. RidgeRun's products take full advantage of the accelerators that NVIDIA exposes to perform transformations on the video streams, achieving great performance on complex processes.

This page contains detailed guides and information on how to get started with the NVIDIA Jetson AGX Thor and start using its full capabilities.

To get up-to-speed with your NVIDIA Jetson AGX Thor board, start by clicking below:



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