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NVIDIA

NVIDIA 900-13834-0080-0A1 | Jetson Thor T5000 AI Module, 128GB, 2070 TFLOPS, USA

SKU:900-13834-0080-0A1

Stock Status: Enquire

$10,689.25 inc. GST
$9,717.50 ex. GST
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Description

The Jetson T5000 is the top module in NVIDIA's Jetson Thor series, built for humanoid robotics, physical AI, agentic AI, generative AI and high-speed sensor processing at the edge. It is an embedded system-on-module that pairs a Blackwell-architecture GPU with a 14-core Arm Neoverse-V3AE CPU. This 0A1 part number is the USA-origin version.

The module delivers 2070 TFLOPS of AI performance (FP4, sparse) from a 2560-core Blackwell GPU with fifth-generation Tensor Cores and Multi-Instance GPU support with 10 TPCs. It carries 128 GB of 256-bit LPDDR5X memory at 273 GB/s and offers 4x 25GbE networking. Power is configurable from 40 W to 130 W, and the 2070 TFLOPS figure is measured at 130 W. Camera support includes up to 20 cameras via Holoscan Sensor Bridge, plus MIPI CSI-2 inputs.

The T5000 runs NVIDIA Jetson Linux and JetPack. It connects through a 699-pin board-to-board connector and uses an integrated Thermal Transfer Plate with an optional fan or heat sink. The Jetson AGX Thor Developer Kit is the matching reference platform.

Enquire with XS Network Tech for new or used pricing and availability.

Features

- Up to 7.5x the AI performance and 3.5x the energy efficiency of Jetson AGX Orin
- Blackwell GPU for generative AI and large transformer models at the edge
- Multi-Instance GPU (MIG) support for partitioning GPU resources
- Supports open-source models through Jetson AI Lab
- Jetson agent skills and NVIDIA NemoClaw for building and deploying autonomous agents at the edge
- Robotic AI software stack aimed at humanoid robotics and physical AI
- Holoscan Sensor Bridge camera support via QSFP

Warranty

All products sold by XS Network Tech include a 12-month warranty on both new and used items. Our in-house technical team thoroughly tests used hardware prior to sale to ensure enterprise-grade reliability.

All technical data should be verified on the manufacturer data sheets.

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Technical Specifications

FAQs

Technical Specifications

- AI performance: 2070 TFLOPS (FP4, sparse)
- GPU: 2560-core NVIDIA Blackwell architecture with fifth-gen Tensor Cores
- Multi-Instance GPU (MIG): 10 TPCs
- GPU max frequency: 1.57 GHz
- CPU: 14-core Arm Neoverse-V3AE 64-bit
- CPU cache: 1 MB L2 per core, 16 MB shared system L3
- CPU max frequency: 2.6 GHz
- Vision accelerator: 1x PVA v3
- Memory: 128 GB 256-bit LPDDR5X, 273 GB/s
- Storage: NVMe through PCIe, SSD through USB 3.2
- Video encode: 2x NVENC
- Camera: up to 20 cameras via HSB, up to 6 cameras through 16 lanes MIPI CSI-2, up to 32 cameras using Virtual Channels
- Camera interfaces: C-PHY 2.1 (10.25 Gbps), D-PHY 2.1 (40 Gbps)
- PCIe: up to Gen5 (x8 lanes)
- USB: up to 3x USB 3.2 and 4x USB 2.0
- Networking: 4x 25GbE
- Display: 4x shared HDMI 2.1, VESA DisplayPort 1.4a HBR3 with MST
- Other I/O: 5x I2S/2x AHUB, 2x DMIC, 4x UART, 4x CAN, 3x SPI, 13x I2C, 6x PWM outputs
- Power: 40 W to 130 W configurable
- Dimensions: 100 mm x 87 mm
- Connector: 699-pin B2B with integrated Thermal Transfer Plate and heatpipe

FAQs

Q: Does the Jetson T5000 need a separate software licence?
A: No separate licence is stated for the module. It runs on NVIDIA Jetson Linux and JetPack, with features documented in the Jetson Linux Developer Guide.

Q: What power does the Jetson T5000 need?
A: The module has a configurable power envelope of 40 W to 130 W. The 2070 TFLOPS AI performance figure is measured at 130 W.

Q: How does this module connect to a carrier board?
A: It uses a 699-pin board-to-board connector and has an integrated Thermal Transfer Plate with heatpipe. An optional fan or heat sink can be fitted for cooling.

Q: What software and reference hardware does it work with?
A: It works with Jetson Linux and JetPack. The matching reference platform is the Jetson AGX Thor Developer Kit.

Q: What does the 0A1 part number indicate?
A: The 0A1 suffix identifies the USA-origin version of the 128GB Jetson T5000 module.

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