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NVIDIA

NVIDIA Jetson AGX Orin 64GB Development Board 945137300050000

SKU CH-6BMD-BMRZK MPN 945137300050000

Edge AI developer kit delivering 275 TOPS via 12-core Arm CPU, 2048 CUDA cores, 64 tensor cores and 64 GB LPDDR5

  • CPU12-core Arm Cortex-A78AE v8.2 64-bit CPU 3MB L2 + 6MB L3
  • Memory64GB 256-bit LPDDR5 204.8GB/s
  • FeaturesJetson AGX Orin 64GB Developer Kit GPU: NVIDIA Ampere archit

Model Jetson AGX Orin Developer Kit

  • Up to 275 TOPS AI performance from Ampere GPU with 2048 CUDA cores and 64 tensor cores
  • 64GB LPDDR5 memory delivers 204.8GB/s bandwidth for large model workloads
  • 12-core Arm Cortex-A78AE CPU provides deterministic real-time processing for robotics
  • Reference carrier board includes 10GbE RJ45 and multiple PCIe Gen4 expansion slots
  • Complete kit with module, heat sink, wireless NIC, power adapter and cables for immediate prototyping

What this kit is for

The NVIDIA Jetson AGX Orin 64GB Developer Kit bundles a production-ready module with a reference carrier board, wireless controller, power adapter and cables. It targets engineers prototyping autonomous machines and advanced robotics that demand up to 275 TOPS of AI compute in a compact form factor.

The spec that decides fit

On-board memory is 64GB 256-bit LPDDR5 running at 204.8GB/s, paired with 64GB eMMC 5.1 storage. This fixed capacity suits workloads fitting within that footprint; buyers who want more storage or user-replaceable memory must look elsewhere.

Build integration

The carrier board exposes a 16-lane MIPI CSI-2 camera connector, an x16 PCIe slot operating at x8 Gen4, M.2 Key M and Key E slots, dual USB 3.2 Gen2 Type-C ports, four Type-A USB ports, DisplayPort 1 and up to 10GbE RJ45. Power input ranges from 15W to 60W, so the supplied adapter covers the full envelope.

Kohokohdat

  • Up to 275 TOPS AI performance from Ampere GPU with 2048 CUDA cores and 64 tensor cores
  • 64GB LPDDR5 memory delivers 204.8GB/s bandwidth for large model workloads
  • 12-core Arm Cortex-A78AE CPU provides deterministic real-time processing for robotics
  • Reference carrier board includes 10GbE RJ45 and multiple PCIe Gen4 expansion slots
  • Complete kit with module, heat sink, wireless NIC, power adapter and cables for immediate prototyping

Tekniset tiedot

BrandNVIDIA
ModelJetson AGX Orin Developer Kit
Part Number945137300050000
CPU12-core Arm Cortex-A78AE v8.2 64-bit CPU 3MB L2 + 6MB L3
Memory64GB 256-bit LPDDR5 204.8GB/s
FeaturesJetson AGX Orin 64GB Developer Kit
GPU: NVIDIA Ampere architecture with 2048 NVIDIA CUDA® cores and 64 tensor cores
CPU: 12-core Arm Cortex-A78AE v8.2 64-bit CPU 3MB L2 + 6MB L3
DL Accelerator: 2x NVDLA v2.0
Vision Accelerator: PVA v2.0
Memory: 64GB 256-bit LPDDR5 204.8GB/s
Storage: 64GB eMMC 5.1
Video Encode: 2x 4K60 | 4x 4K30 | 8x 1080p60 | 16x 1080p30 (H.265)
Video Decode: 1x 8K30 | 3x 4K60 | 7x 4K30 | 11x 1080p60 | 22x 1080p30 (H.265)
Power: 15W-60W
Reference Carrier Board
Camera: 16-lane MIPI CSI-2 connector
PCIe: x16 PCIe slot supporting: x8 PCIe Gen4
RJ45: Up to 10GbE
M.2 Key
Lähetyspaino2.16 kg
Pakkauksen mitat254 × 213 × 140 mm

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Kysymyksiä tästä tuotteesta

What does 275 TOPS of AI performance mean when the kit is running a real workload?

The 275 TOPS rating is the peak throughput of the Ampere GPU with 2048 CUDA cores, 64 tensor cores, 2x NVDLA v2.0 and PVA v2.0 combined; sustained throughput will be lower depending on model precision, memory bandwidth and the 15W-60W power budget.

The carrier board has a PCIe x16 slot — what speed and lane width does it actually deliver?

The slot supports x8 PCIe Gen4, so an add-in card receives eight Gen4 lanes rather than the full physical x16 width.

What clearance and mounting provisions does the 64GB module with its attached heat sink need inside an enclosure?

The developer kit includes the Jetson AGX Orin 64GB module with heat sink pre-mounted on the reference carrier board; the board uses standard mounting holes and the heat sink fits within the module outline, so no extra vertical clearance beyond the carrier board stack height is required.

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