Vecow EAC-5000 Features NVIDIA Jetson AGX Orin SoM, Offering Server-Class Performance for Edge AI Applications

Vecow EAC-5000 Features NVIDIA Jetson AGX Orin SoM, Offering Server-Class Performance for Edge AI Applications

Vecow has launched a feature-rich edge AI computing system that guarantees power-efficient AI productivity, flexible integration, and mobile availability: the Vecow EAC-5000.

Designed to deliver faster and/or more energy-efficient performance for machine vision and automotive applications, the Vecow EAC-5000 embedded computer is powered by NVIDIA’s Jetson AGX Orin system-on-module, the latest and most powerful module in the Jetson family, capable of delivering 275 TOPS of AI performance (more than 8 times the AI performance of the earlier NVIDIA Jetson AGX Xavier module). The NVIDIA Jetson AGX Orin module also boasts of an Ampere architecture GPU with state-of-the-art graphics and parallel computing techniques, a 12-core Arm Cortex-A78AE CPU running at up to 2.2 GHz, and the second generation of NVIDIA DLA (Deep Learning Accelerators) with 9x times the performance of the previous generation. With other features like a multi-standard encoder and decoder, JPEG Codec, and the second generation of a Programmable Vision Accelerator supporting common computer vision kernels, the module no doubt is on a higher level when it comes to the performance achievable by embedded system-on-module.

Vecow EAC-5000 is also characterized by various wireless connectivity options such as WiFi, 5G, 4G LTE, 6x antennas, support for up to 8x GMLS2 cameras, 1x PCIe x8 slot, 2 GbE LAN, 5x USB, 2x SIM card sockets, 1x software ignition control, a wide range input DC of 9V to 50V, and temperature range of -20 to 70°C. It can be wall mounted with a mounting bracket, and the company offers an optional DIN Rail mount too.

The EAC-5000 system comes in two variants, depending on the version of the module it comes with. The specifications highlighted below give in-depth details about that.


  • SoM: NVIDIA Jetson AGX Orin 32GB/64GB
    • CPU:
      • EAC-5000-R32: 64-bit 8-core Arm Cortex A78AE v8.2 processor @ 2.2 GHz with 2MB L2, 4MB L3 cache
      • EAC-5000-R64: 64-bit 12-core Arm Cortex-A78AE v8.2 processor @ 2.2 GHz with 3MB L2, 6MB L6 cache
    • GPU:
      • EAC-5000-R32: NVIDIA Ampere architecture with 1792 NVIDIA CUDA cores and 56 Tensor Cores @ 1GHz
      • EAC-5000-R64: NVIDIA Ampere architecture with 2048 NVIDIA CUDA cores and 64 Tensor cores @ 1GHz
    • System Memory:
      • EAC-5000-R32: 32GB 256-bit LPDDR5 @ 204.8 GB/s
      • EAC-5000-R64: 64GB 256-bit LPDDR5 @ 204.8 GB/s
    • DL Accelerators:
      • EAC-5000-R32: 2x NVIDIA v2.0 @ up to 1.4 GHz
      • EAC-5000-R64: 2x NVIDIA v2.0 @ up to 1.6 GHz
    • Vision Accelerator: Programmable Vision Accelerator (PVA) v.2.0
    • AI Performance:
      • EAC-5000-R32: 200 TOPS @ 50W / 100 TOPS
      • EAC-5000-R64: 275 TOPS @ 50W / 100 TOPS
    • Video Encode:
      • EAC-5000-R32: 1x 4K@60; 3x 4K @30; 6x 1080p @60; 12x 1080p @30
      • EAC-5000-R64: 2x 4K@60; 4x 4K @30; 8x 1080p @60; 16x 1080p@30
    • Video Decode:
      • EAC-5000-R32: 1x 8K @30; 2x 4K @60; 4x 4K @30; 9x 1080p @60; 18x 1080p @30
      • EAC-5000-R64: 1x 8K @30; 3x 4K @60; 7x 4K @30; 11x 1080p@60; 22x 1080p @30
  • 2x M.2 Key M 2280 socket
  • MicroSD card socket
  • 1x 64GB eMMC 5.1
  • 1x Digital Display interface up to 8K60
  • 8x Fakra-Z connectors for GMSL2 automotive cameras
  • 2x GbE ports
  • 2x SIM card socket
  • Optional WiFi, 5G, 4G LTE connectivity through M.2 sockets
  • 6x antennas for WiFi, 5G, 4G LTE, UMTS, GPRS
  • 1x USB 3.1 Gen 2
  • 4x USB 3.1
  • 2x COM RS-232/422/485
  • 2x isolated CAN BUS
  • 1x PCIe Gen4 x8 slot
  • 1x M.2 Key B socket
  • 1x M.2 Key E socket
  • 8x DI, 8x DO
  • 1x Micro USB console debug port
  • 1x Micro USB OS flash port
  • Power and Rest Buttons
  • 2x User-programmable LEDs
  • 16-mode Software Ignition control
  • 3-pin Remote Switch terminal block
  • Remote power on/off and remote reset control
  • Power Input: DC 9V to 50V via 3-pin terminal block
  • Dimension: 260 mm x 182 mm x 69 mm
  • Weight: 3.8 kg
  • Temperature:
    • -20°C to 70°C (30W power mode)
    • -20°C to 55°C (Maximum power mode)
    • -40°C to 85°C (Storage)
  • Humidity: 5% to 95%, non-condensing
  • Operating System: Linux Ubuntu 20.04 OS with JetPack SDK
  • Certifications: CE, FCC, EN50155, EN50121-3-2

The rugged AI computing system is ideal for advanced edge AI applications such as robotic control, intelligent video analytics, in-vehicle computing, machine vision, mobile robots, etc.

Other useful details can be found on the product page, but no details on pricing and availability yet.

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About Emmanuel Odunlade

Hardware Design Engineer | #IoT Consultant |All things #ML | Entrepreneur | Serial Writer | Passionate about Innovation and technology as tools for solving problems in developing countries. Spare time is spent around writing and advocacy for the growth of the Maker/DIY Culture in Africa.

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