pytorch.txt ARMv8 Cortex-A78E testing with a NVIDIA Jetson Orin NX Engineering Developer Kit (36.3.0-gcid-36191598 BIOS) and Orin on Ubuntu 22.04 via the Phoronix Test Suite. all of them: Processor: ARMv8 Cortex-A78E @ 1.98GHz (8 Cores), Motherboard: NVIDIA Jetson Orin NX Engineering Developer Kit (36.3.0-gcid-36191598 BIOS), Memory: 16GB, Disk: 128GB FORESEE XP1000F128G, Graphics: Orin, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 22.04, Kernel: 5.15.136-tegra (aarch64), Desktop: GNOME Shell 42.9, Display Server: X Server 1.21.1.4, Display Driver: NVIDIA, Vulkan: 1.3.251, Compiler: GCC 11.4.0 + CUDA 12.2, File-System: ext4, Screen Resolution: 6582x1234 TensorFlow Lite 2022-05-18 Model: Inception V4 Microseconds < Lower Is Better all of them . 128466 |========================================================= TensorFlow Lite 2022-05-18 Model: Inception ResNet V2 Microseconds < Lower Is Better all of them . 117511 |========================================================= TensorFlow Lite 2022-05-18 Model: NASNet Mobile Microseconds < Lower Is Better all of them . 22370.4 |======================================================== TensorFlow Lite 2022-05-18 Model: Mobilenet Float Microseconds < Lower Is Better all of them . 6848.70 |======================================================== TensorFlow Lite 2022-05-18 Model: SqueezeNet Microseconds < Lower Is Better all of them . 8886.22 |======================================================== TensorFlow Lite 2022-05-18 Model: Mobilenet Quant Microseconds < Lower Is Better all of them . 3307.88 |========================================================