Here's the comparison you asked for — both are Jetson Thor–based edge AI box PCs, and on the three attributes you named they're closer than you might expect:
| Vecow EAC-7200F-T5000 | Ecotron EATHA20 | |
|---|---|---|
| GMSL camera inputs | 16 (GMSL2) | 16 (GMSL/GMSL2) |
| CAN ports | 4 (isolated CAN) | 12 (CAN FD channels) |
| Memory | 128 GB | 128 GB |
Key differences on these three points: GMSL inputs and memory are identical at 16 cameras and 128 GB, but the CAN capability differs significantly — the EATHA20 targets automotive autonomous driving (Level 3–5, with an ASIL-D Infineon TC4D9 MCU) and carries 12 CAN FD channels, while the Vecow EAC-7200F-T5000 has 4 isolated CAN ports for in-vehicle/machine-vision and mobile-robot applications. vecow.com +2vecow.com ↗“up to 16x GMSL2 cameras, isolated CAN”ecotron.ai ↗“12 CAN FD channels, 128GB memory”vecow.com ↗“io.can_port_count=4”
A few related specs that may matter for your decision:
- Power input: Vecow accepts 9–50 V; Ecotron accepts DC 9–32 V. vecow.com +1vecow.com ↗“power_input=9-50 V”ecotron.ai ↗“DC 9～32V”
- Operating temperature: Both top out at 70 °C; the EATHA20 goes slightly lower at −25 °C vs −20 °C (the Vecow range requires airflow and depends on power mode). vecow.com +1vecow.com ↗“min_operating_temp_c=-20 °C”ecotron.ai ↗“min_operating_temp_c=-25 °C”
- Compute: The Vecow unit pairs with the Jetson T5000 128GB module at 1035 TOPS (INT8, sparse) and 2070 TFLOPS FP4. You can find full details in the Vecow EAC-7200F-T5000 product page and the Ecotron EATHA20 product page, including their datasheets. vecow.comvecow.com ↗“Jetson T5000 128GB, 1035 TOPS”