ODROID-N2 benchmarks for a future article.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 1904251-HV-ODROIDN2760
ODROID-N2 Benchmark Comparison
ODROID-N2 benchmarks for a future article.
Jetson AGX Xavier:
Processor: ARMv8 rev 0 @ 2.27GHz (8 Cores), Motherboard: jetson-xavier, Memory: 16384MB, Disk: 31GB HBG4a2, Graphics: NVIDIA Tegra Xavier, Monitor: VE228
OS: Ubuntu 18.04, Kernel: 4.9.108-tegra (aarch64), Desktop: Unity 7.5.0, Display Server: X Server 1.19.6, Display Driver: NVIDIA 31.0.2, OpenGL: 4.6.0, Vulkan: 1.1.76, Compiler: GCC 7.3.0 + CUDA 10.0, File-System: ext4, Screen Resolution: 1920x1080
Jetson TX2 Max-P:
Processor: ARMv8 rev 3 @ 2.04GHz (4 Cores / 6 Threads), Motherboard: quill, Memory: 8192MB, Disk: 31GB 032G34, Graphics: NVIDIA TEGRA, Monitor: VE228
OS: Ubuntu 16.04, Kernel: 4.4.38-tegra (aarch64), Desktop: Unity 7.4.0, Display Server: X Server 1.18.4, Display Driver: NVIDIA 28.2.1, OpenGL: 4.5.0, Compiler: GCC 5.4.0 20160609 + CUDA 9.0, File-System: ext4, Screen Resolution: 1920x1080
Jetson TX2 Max-Q:
Processor: ARMv8 rev 3 @ 1.27GHz (4 Cores / 6 Threads), Motherboard: quill, Memory: 8192MB, Disk: 31GB 032G34, Graphics: NVIDIA TEGRA, Monitor: VE228
OS: Ubuntu 16.04, Kernel: 4.4.38-tegra (aarch64), Desktop: Unity 7.4.0, Display Server: X Server 1.18.4, Display Driver: NVIDIA 28.2.1, OpenGL: 4.5.0, Compiler: GCC 5.4.0 20160609 + CUDA 9.0, File-System: ext4, Screen Resolution: 1920x1080
Raspberry Pi 3 Model B+:
Processor: ARMv7 rev 4 @ 1.40GHz (4 Cores), Motherboard: BCM2835 Raspberry Pi 3 Model B Plus Rev 1.3, Memory: 926MB, Disk: 32GB GB2MW, Graphics: BCM2708
OS: Raspbian 9.6, Kernel: 4.19.23-v7+ (armv7l), Desktop: LXDE, Display Server: X Server 1.19.2, Compiler: GCC 6.3.0 20170516, File-System: ext4, Screen Resolution: 656x416
ASUS TinkerBoard:
Processor: ARMv7 rev 1 @ 1.80GHz (4 Cores), Motherboard: Rockchip (Device Tree), Memory: 2048MB, Disk: 32GB GB1QT
OS: Debian 9.0, Kernel: 4.4.16-00006-g4431f98-dirty (armv7l), Desktop: LXDE, Display Server: X Server 1.18.4, Compiler: GCC 6.3.0 20170516, File-System: ext4, Screen Resolution: 1024x768
Jetson TX1 Max-P:
Processor: ARMv8 rev 1 @ 1.73GHz (4 Cores), Motherboard: jetson_tx1, Memory: 4096MB, Disk: 16GB 016G32, Graphics: NVIDIA Tegra X1, Monitor: VE228
OS: Ubuntu 16.04, Kernel: 4.4.38-tegra (aarch64), Desktop: Unity 7.4.5, Display Server: X Server 1.18.4, Display Driver: NVIDIA 28.1.0, OpenGL: 4.5.0, Vulkan: 1.0.8, Compiler: GCC 5.4.0 20160609, File-System: ext4, Screen Resolution: 1920x1080
ODROID-XU4:
Processor: ARMv7 rev 3 @ 1.50GHz (8 Cores), Motherboard: ODROID-XU4 Hardkernel Odroid XU4, Memory: 2048MB, Disk: 16GB AJTD4R, Graphics: llvmpipe 2GB, Monitor: VE228
OS: Ubuntu 18.04, Kernel: 4.14.37-135 (armv7l), Display Server: X Server 1.19.6, OpenGL: 3.3 Mesa 18.0.0-rc5 (LLVM 6.0 128 bits), Compiler: GCC 7.3.0, File-System: ext4, Screen Resolution: 1920x1080
Jetson Nano:
Processor: ARMv8 rev 1 @ 1.43GHz (4 Cores), Motherboard: jetson-nano, Memory: 4096MB, Disk: 32GB GB1QT, Graphics: NVIDIA TEGRA, Monitor: VE228, Network: Realtek RTL8111/8168/8411
OS: Ubuntu 18.04, Kernel: 4.9.140-tegra (aarch64), Desktop: Unity 7.5.0, Display Server: X Server 1.19.6, Display Driver: NVIDIA 1.0.0, Vulkan: 1.1.85, Compiler: GCC 7.3.0 + CUDA 10.0, File-System: ext4, Screen Resolution: 1920x1080
ODROID-N2:
Processor: ARMv8 Cortex-A73 @ 1.90GHz (6 Cores), Motherboard: Hardkernel ODROID-N2, Memory: 4096MB, Disk: 16GB AJTD4R, Graphics: OSD
OS: Ubuntu 18.04, Kernel: 4.9.156-14 (aarch64), Compiler: GCC 7.3.0, File-System: ext4, Screen Resolution: 1920x2160
ODROID-C2:
Processor: Amlogic ARMv8 Cortex-A53 @ 1.54GHz (4 Cores), Motherboard: ODROID-C2, Memory: 2048MB, Disk: 32GB GB1QT, Graphics: OSD
OS: Ubuntu 18.04, Kernel: 3.16.57-20 (aarch64), Display Server: X Server 1.19.6, Compiler: GCC 7.3.0, File-System: ext4, Screen Resolution: 1920x1080
LeelaChessZero 0.20.1
Backend: BLAS
Nodes Per Second > Higher Is Better
Jetson AGX Xavier . 47.62 |====================================================
Jetson Nano ....... 15.37 |=================
ODROID-N2 ......... 24.39 |===========================
ODROID-C2 ......... 7.33 |========
C-Ray 1.1
Total Time - 4K, 16 Rays Per Pixel
Seconds < Lower Is Better
Jetson AGX Xavier ....... 355 |========
Jetson TX2 Max-P ........ 585 |==============
Jetson TX2 Max-Q ........ 869 |====================
Raspberry Pi 3 Model B+ . 2030 |===============================================
ASUS TinkerBoard ........ 1718 |========================================
Jetson TX1 Max-P ........ 753 |=================
ODROID-XU4 .............. 827 |===================
Jetson Nano ............. 921 |=====================
ODROID-N2 ............... 492 |===========
ODROID-C2 ............... 1535 |====================================
Rust Prime Benchmark
Prime Number Test To 200,000,000
Seconds < Lower Is Better
Jetson AGX Xavier ....... 32.37 |=
Jetson TX2 Max-P ........ 104.96 |===
Jetson TX2 Max-Q ........ 170.25 |====
Raspberry Pi 3 Model B+ . 1097.69 |===========================
ASUS TinkerBoard ........ 1821.05 |============================================
Jetson TX1 Max-P ........ 128.45 |===
ODROID-XU4 .............. 574.11 |==============
Jetson Nano ............. 150.19 |====
ODROID-N2 ............... 73.11 |==
ODROID-C2 ............... 125.81 |===
TTSIOD 3D Renderer 2.3b
Phong Rendering With Soft-Shadow Mapping
FPS > Higher Is Better
Jetson AGX Xavier ....... 133.00 |=============================================
Jetson TX2 Max-P ........ 49.26 |=================
Jetson TX2 Max-Q ........ 28.85 |==========
Raspberry Pi 3 Model B+ . 17.66 |======
ASUS TinkerBoard ........ 21.22 |=======
Jetson TX1 Max-P ........ 45.09 |===============
ODROID-XU4 .............. 41.96 |==============
Jetson Nano ............. 40.94 |==============
ODROID-N2 ............... 57.42 |===================
ODROID-C2 ............... 22.10 |=======
CUDA Mini-Nbody 2015-11-10
Test: Original
(NBody^2)/s > Higher Is Better
Jetson AGX Xavier . 47.13 |====================================================
Jetson TX2 Max-P .. 8.24 |=========
Jetson TX2 Max-Q .. 6.77 |=======
Jetson Nano ....... 4.07 |====
OpenCV Benchmark 3.3.0
Seconds < Lower Is Better
Jetson AGX Xavier ....... 128.00 |===========
Jetson TX2 Max-P ........ 296.00 |==========================
Jetson TX2 Max-Q ........ 493.00 |===========================================
Raspberry Pi 3 Model B+ . 2.74 |
ODROID-XU4 .............. 520.70 |=============================================
Jetson Nano ............. 271.04 |=======================
ODROID-N2 ............... 243.05 |=====================
ODROID-C2 ............... 474.35 |=========================================
NVIDIA TensorRT Inference
Neural Network: ResNet152 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 259.82 |===================================================
Jetson TX2 Max-P .. 41.91 |========
Jetson TX2 Max-Q .. 32.67 |======
Jetson Nano ....... 17.38 |===
NVIDIA TensorRT Inference
Neural Network: ResNet152 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 493.22 |===================================================
Jetson TX2 Max-P .. 22.07 |==
Jetson TX2 Max-Q .. 17.36 |==
NVIDIA TensorRT Inference
Neural Network: VGG19 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 394.66 |===================================================
Jetson TX2 Max-P .. 15.92 |==
Jetson TX2 Max-Q .. 12.59 |==
NVIDIA TensorRT Inference
Neural Network: VGG19 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 203.96 |===================================================
Jetson TX2 Max-P .. 29.83 |=======
Jetson TX2 Max-Q .. 23.94 |======
NVIDIA TensorRT Inference
Neural Network: ResNet152 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 372.73 |===================================================
Jetson TX2 Max-P .. 18.29 |===
Jetson TX2 Max-Q .. 14.50 |==
Jetson Nano ....... 7.76 |=
NVIDIA TensorRT Inference
Neural Network: VGG16 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 475.08 |===================================================
Jetson TX2 Max-P .. 19.91 |==
Jetson TX2 Max-Q .. 15.79 |==
PyBench 2018-02-16
Total For Average Test Times
Milliseconds < Lower Is Better
Jetson AGX Xavier ....... 3007 |=======
Jetson TX2 Max-P ........ 5408 |============
Jetson TX2 Max-Q ........ 8735 |===================
Raspberry Pi 3 Model B+ . 20913 |==============================================
ASUS TinkerBoard ........ 11502 |=========================
Jetson TX1 Max-P ........ 6339 |==============
ODROID-XU4 .............. 5009 |===========
Jetson Nano ............. 7084 |================
ODROID-N2 ............... 5231 |============
ODROID-C2 ............... 12184 |===========================
FLAC Audio Encoding 1.3.2
WAV To FLAC
Seconds < Lower Is Better
Jetson AGX Xavier ....... 54.47 |=======
Jetson TX2 Max-P ........ 65.07 |=========
Jetson TX2 Max-Q ........ 104.28 |==============
Raspberry Pi 3 Model B+ . 339.53 |=============================================
ASUS TinkerBoard ........ 279.05 |=====================================
Jetson TX1 Max-P ........ 79.20 |==========
ODROID-XU4 .............. 97.03 |=============
Jetson Nano ............. 104.77 |==============
ODROID-N2 ............... 95.59 |=============
ODROID-C2 ............... 262.31 |===================================
NVIDIA TensorRT Inference
Neural Network: VGG16 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 247.95 |===================================================
Jetson TX2 Max-P .. 36.87 |========
Jetson TX2 Max-Q .. 29.83 |======
Zstd Compression 1.3.4
Compressing ubuntu-16.04.3-server-i386.img, Compression Level 19
Seconds < Lower Is Better
Jetson AGX Xavier ....... 80.06 |=======
Jetson TX2 Max-P ........ 144.97 |=============
Jetson TX2 Max-Q ........ 253.80 |=======================
Raspberry Pi 3 Model B+ . 342.23 |===============================
ASUS TinkerBoard ........ 496.62 |=============================================
Jetson TX1 Max-P ........ 145.80 |=============
Jetson Nano ............. 129.87 |============
ODROID-N2 ............... 152.04 |==============
ODROID-C2 ............... 314.33 |============================
NVIDIA TensorRT Inference
Neural Network: ResNet152 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 224.19 |===================================================
Jetson TX2 Max-P .. 35.11 |========
Jetson TX2 Max-Q .. 27.34 |======
Jetson Nano ....... 15.76 |====
NVIDIA TensorRT Inference
Neural Network: ResNet50 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 547.50 |===================================================
Jetson TX2 Max-P .. 92.28 |=========
Jetson TX2 Max-Q .. 72.01 |=======
Jetson Nano ....... 41.04 |====
NVIDIA TensorRT Inference
Neural Network: VGG16 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 303.78 |===================================================
Jetson TX2 Max-P .. 17.56 |===
Jetson TX2 Max-Q .. 14.24 |==
NVIDIA TensorRT Inference
Neural Network: ResNet50 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 1215.08 |==================================================
Jetson TX2 Max-P .. 59.69 |==
Jetson TX2 Max-Q .. 47.15 |==
Jetson Nano ....... 25.08 |=
Tesseract OCR 4.0.0-beta.1
Time To OCR 7 Images
Seconds < Lower Is Better
Jetson AGX Xavier . 71.94 |=================
ODROID-XU4 ........ 180.66 |==========================================
Jetson Nano ....... 132.67 |===============================
ODROID-N2 ......... 110.73 |==========================
ODROID-C2 ......... 220.44 |===================================================
NVIDIA TensorRT Inference
Neural Network: VGG19 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 172.50 |===================================================
Jetson TX2 Max-P .. 26.56 |========
Jetson TX2 Max-Q .. 21.04 |======
Jetson Nano ....... 11.59 |===
NVIDIA TensorRT Inference
Neural Network: VGG16 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 208.76 |===================================================
Jetson TX2 Max-P .. 32.64 |========
Jetson TX2 Max-Q .. 25.99 |======
Jetson Nano ....... 14.35 |====
NVIDIA TensorRT Inference
Neural Network: ResNet50 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 636.00 |===================================================
Jetson TX2 Max-P .. 111.00 |=========
Jetson TX2 Max-Q .. 86.08 |=======
Jetson Nano ....... 46.51 |====
7-Zip Compression 16.02
Compress Speed Test
MIPS > Higher Is Better
Jetson AGX Xavier ....... 19212 |==============================================
Jetson TX2 Max-P ........ 5593 |=============
Jetson TX2 Max-Q ........ 3294 |========
Raspberry Pi 3 Model B+ . 2013 |=====
ASUS TinkerBoard ........ 2836 |=======
Jetson TX1 Max-P ........ 4508 |===========
ODROID-XU4 .............. 4120 |==========
Jetson Nano ............. 4049 |==========
ODROID-N2 ............... 5970 |==============
ODROID-C2 ............... 2121 |=====
NVIDIA TensorRT Inference
Neural Network: VGG19 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 265.81 |===================================================
Jetson TX2 Max-P .. 14.32 |===
Jetson TX2 Max-Q .. 11.45 |==
NVIDIA TensorRT Inference
Neural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 1006.00 |==================================================
Jetson TX2 Max-P .. 233.00 |============
Jetson TX2 Max-Q .. 179.00 |=========
Jetson Nano ....... 98.93 |=====
NVIDIA TensorRT Inference
Neural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 1693.00 |==================================================
Jetson TX2 Max-P .. 130.00 |====
Jetson TX2 Max-Q .. 104.00 |===
Jetson Nano ....... 55.66 |==
NVIDIA TensorRT Inference
Neural Network: AlexNet - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 1200 |=====================================================
Jetson TX2 Max-P .. 264 |============
Jetson TX2 Max-Q .. 216 |==========
Jetson Nano ....... 118 |=====
GLmark2
Resolution: 1920 x 1080
Score > Higher Is Better
Jetson AGX Xavier . 2876 |=====================================================
Jetson Nano ....... 646 |============
NVIDIA TensorRT Inference
Neural Network: GoogleNet - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 796.00 |===================================================
Jetson TX2 Max-P .. 197.00 |=============
Jetson TX2 Max-Q .. 156.00 |==========
Jetson Nano ....... 83.37 |=====
NVIDIA TensorRT Inference
Neural Network: ResNet50 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 902.78 |===================================================
Jetson TX2 Max-P .. 49.97 |===
Jetson TX2 Max-Q .. 39.15 |==
Jetson Nano ....... 20.96 |=
NVIDIA TensorRT Inference
Neural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 2038 |=====================================================
Jetson TX2 Max-P .. 462 |============
Jetson TX2 Max-Q .. 374 |==========
Jetson Nano ....... 201 |=====
NVIDIA TensorRT Inference
Neural Network: GoogleNet - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 1146.00 |==================================================
Jetson TX2 Max-P .. 113.00 |=====
Jetson TX2 Max-Q .. 88.88 |====
Jetson Nano ....... 47.82 |==
LeelaChessZero 0.20.1
Backend: CUDA + cuDNN
Nodes Per Second > Higher Is Better
Jetson AGX Xavier . 953 |======================================================
Jetson Nano ....... 140 |========
NVIDIA TensorRT Inference
Neural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 3143 |=====================================================
Jetson TX2 Max-P .. 301 |=====
Jetson TX2 Max-Q .. 237 |====
Jetson Nano ....... 128 |==
NVIDIA TensorRT Inference
Neural Network: AlexNet - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second > Higher Is Better
Jetson AGX Xavier . 1143.00 |==================================================
Jetson TX2 Max-P .. 184.00 |========
Jetson TX2 Max-Q .. 148.00 |======
Jetson Nano ....... 84.10 |====
LeelaChessZero 0.20.1
Backend: CUDA + cuDNN FP16
Nodes Per Second > Higher Is Better
Jetson AGX Xavier . 2515.01 |==================================================
Meta Performance Per Dollar
Performance Per Dollar
Performance Per Dollar > Higher Is Better
ODROID-N2 . 19.17 |============================================================
Tesseract OCR 4.0.0-beta.1
Performance / Cost - Time To OCR 7 Images
Seconds x Dollar < Lower Is Better
Jetson AGX Xavier . 93450.06 |=================================================
ODROID-XU4 ........ 11200.92 |======
Jetson Nano ....... 13134.33 |=======
ODROID-N2 ......... 7191.91 |====
LeelaChessZero 0.20.1
Performance / Cost - Backend: CUDA + cuDNN FP16
Nodes Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 1.94 |=====================================================
LeelaChessZero 0.20.1
Performance / Cost - Backend: CUDA + cuDNN
Nodes Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.73 |===========================
Jetson Nano ....... 1.41 |=====================================================
LeelaChessZero 0.20.1
Performance / Cost - Backend: BLAS
Nodes Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.04 |======
Jetson Nano ....... 0.16 |======================
ODROID-N2 ......... 0.38 |=====================================================
GLmark2
Performance / Cost - Resolution: 1920 x 1080
Score Per Dollar > Higher Is Better
Jetson AGX Xavier . 2.21 |==================
Jetson Nano ....... 6.53 |=====================================================
OpenCV Benchmark 3.3.0
Performance / Cost -
Seconds x Dollar < Lower Is Better
Jetson AGX Xavier ....... 166272.00 |========================
Jetson TX2 Max-P ........ 177304.00 |=========================
Jetson TX2 Max-Q ........ 295307.00 |==========================================
Raspberry Pi 3 Model B+ . 95.90 |
ODROID-XU4 .............. 32283.40 |=====
Jetson Nano ............. 26832.96 |====
ODROID-N2 ............... 15786.10 |==
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: ResNet152 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.38 |=====================================================
Jetson TX2 Max-P .. 0.04 |======
Jetson TX2 Max-Q .. 0.03 |====
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: ResNet152 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.20 |=====================================================
Jetson TX2 Max-P .. 0.07 |===================
Jetson TX2 Max-Q .. 0.05 |=============
Jetson Nano ....... 0.18 |================================================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 1.30 |=====================================================
Jetson TX2 Max-P .. 0.22 |=========
Jetson TX2 Max-Q .. 0.17 |=======
Jetson Nano ....... 0.56 |=======================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.77 |=========================================
Jetson TX2 Max-P .. 0.39 |=====================
Jetson TX2 Max-Q .. 0.30 |================
Jetson Nano ....... 1.00 |=====================================================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: ResNet50 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.94 |=====================================================
Jetson TX2 Max-P .. 0.10 |======
Jetson TX2 Max-Q .. 0.08 |=====
Jetson Nano ....... 0.25 |==============
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: ResNet50 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.49 |=====================================================
Jetson TX2 Max-P .. 0.19 |=====================
Jetson TX2 Max-Q .. 0.14 |===============
Jetson Nano ....... 0.47 |===================================================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: ResNet152 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.29 |=====================================================
Jetson TX2 Max-P .. 0.03 |=====
Jetson TX2 Max-Q .. 0.02 |====
Jetson Nano ....... 0.08 |===============
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: ResNet152 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.17 |=====================================================
Jetson TX2 Max-P .. 0.06 |===================
Jetson TX2 Max-Q .. 0.05 |================
Jetson Nano ....... 0.16 |==================================================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: GoogleNet - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.88 |=====================================================
Jetson TX2 Max-P .. 0.19 |===========
Jetson TX2 Max-Q .. 0.15 |=========
Jetson Nano ....... 0.48 |=============================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: GoogleNet - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.61 |======================================
Jetson TX2 Max-P .. 0.33 |=====================
Jetson TX2 Max-Q .. 0.26 |================
Jetson Nano ....... 0.84 |=====================================================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: ResNet50 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.69 |=====================================================
Jetson TX2 Max-P .. 0.08 |======
Jetson TX2 Max-Q .. 0.07 |=====
Jetson Nano ....... 0.21 |================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: ResNet50 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.42 |=====================================================
Jetson TX2 Max-P .. 0.15 |===================
Jetson TX2 Max-Q .. 0.12 |===============
Jetson Nano ....... 0.41 |====================================================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 2.42 |=====================================================
Jetson TX2 Max-P .. 0.50 |===========
Jetson TX2 Max-Q .. 0.40 |=========
Jetson Nano ....... 1.29 |============================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 1.57 |=========================================
Jetson TX2 Max-P .. 0.77 |====================
Jetson TX2 Max-Q .. 0.62 |================
Jetson Nano ....... 2.03 |=====================================================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: AlexNet - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.88 |=====================================================
Jetson TX2 Max-P .. 0.31 |===================
Jetson TX2 Max-Q .. 0.25 |===============
Jetson Nano ....... 0.85 |===================================================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: AlexNet - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.92 |=========================================
Jetson TX2 Max-P .. 0.44 |====================
Jetson TX2 Max-Q .. 0.36 |================
Jetson Nano ....... 1.19 |=====================================================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: VGG19 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.30 |=====================================================
Jetson TX2 Max-P .. 0.03 |=====
Jetson TX2 Max-Q .. 0.02 |====
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: VGG19 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.16 |=====================================================
Jetson TX2 Max-P .. 0.05 |=================
Jetson TX2 Max-Q .. 0.04 |=============
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: VGG16 - Precision: INT8 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.37 |=====================================================
Jetson TX2 Max-P .. 0.03 |====
Jetson TX2 Max-Q .. 0.03 |====
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: VGG16 - Precision: FP16 - Batch Size: 32 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.19 |=====================================================
Jetson TX2 Max-P .. 0.06 |=================
Jetson TX2 Max-Q .. 0.05 |==============
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: VGG19 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.20 |=====================================================
Jetson TX2 Max-P .. 0.02 |=====
Jetson TX2 Max-Q .. 0.02 |=====
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: VGG19 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.13 |=====================================================
Jetson TX2 Max-P .. 0.04 |================
Jetson TX2 Max-Q .. 0.04 |================
Jetson Nano ....... 0.12 |=================================================
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: VGG16 - Precision: INT8 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.23 |=====================================================
Jetson TX2 Max-P .. 0.03 |=======
Jetson TX2 Max-Q .. 0.02 |=====
NVIDIA TensorRT Inference
Performance / Cost - Neural Network: VGG16 - Precision: FP16 - Batch Size: 4 - DLA Cores: Disabled
Images Per Second Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.16 |=====================================================
Jetson TX2 Max-P .. 0.05 |=================
Jetson TX2 Max-Q .. 0.04 |=============
Jetson Nano ....... 0.14 |==============================================
CUDA Mini-Nbody 2015-11-10
Performance / Cost - Test: Original
(NBody^2)/s Per Dollar > Higher Is Better
Jetson AGX Xavier . 0.04 |=====================================================
Jetson TX2 Max-P .. 0.01 |=============
Jetson TX2 Max-Q .. 0.01 |=============
Jetson Nano ....... 0.04 |=====================================================
PyBench 2018-02-16
Performance / Cost - Total For Average Test Times
Milliseconds x Dollar < Lower Is Better
Jetson AGX Xavier ....... 3906093.00 |===============================
Jetson TX2 Max-P ........ 3239392.00 |=========================
Jetson TX2 Max-Q ........ 5232265.00 |=========================================
Raspberry Pi 3 Model B+ . 731955.00 |======
ASUS TinkerBoard ........ 759132.00 |======
Jetson TX1 Max-P ........ 3163161.00 |=========================
ODROID-XU4 .............. 310558.00 |==
Jetson Nano ............. 701316.00 |=====
ODROID-N2 ............... 339753.45 |===
FLAC Audio Encoding 1.3.2
Performance / Cost - WAV To FLAC
Seconds x Dollar < Lower Is Better
Jetson AGX Xavier ....... 70756.53 |===========================================
Jetson TX2 Max-P ........ 38976.93 |========================
Jetson TX2 Max-Q ........ 62463.72 |======================================
Raspberry Pi 3 Model B+ . 11883.55 |=======
ASUS TinkerBoard ........ 18417.30 |===========
Jetson TX1 Max-P ........ 39520.80 |========================
ODROID-XU4 .............. 6015.86 |====
Jetson Nano ............. 10372.23 |======
ODROID-N2 ............... 6208.57 |====
Zstd Compression 1.3.4
Performance / Cost - Compressing ubuntu-16.04.3-server-i386.img, Compression Level 19
Seconds x Dollar < Lower Is Better
Jetson AGX Xavier ....... 103997.94 |=============================
Jetson TX2 Max-P ........ 86837.03 |========================
Jetson TX2 Max-Q ........ 152026.20 |==========================================
Raspberry Pi 3 Model B+ . 11978.05 |===
ASUS TinkerBoard ........ 32776.92 |=========
Jetson TX1 Max-P ........ 72754.20 |====================
Jetson Nano ............. 12857.13 |====
ODROID-N2 ............... 9875.00 |===
Rust Prime Benchmark
Performance / Cost - Prime Number Test To 200,000,000
Seconds x Dollar < Lower Is Better
Jetson AGX Xavier ....... 42048.63 |===============
Jetson TX2 Max-P ........ 62871.04 |======================
Jetson TX2 Max-Q ........ 101979.75 |====================================
Raspberry Pi 3 Model B+ . 38419.15 |=============
ASUS TinkerBoard ........ 120189.30 |==========================================
Jetson TX1 Max-P ........ 64096.55 |======================
ODROID-XU4 .............. 35594.82 |============
Jetson Nano ............. 14868.81 |=====
ODROID-N2 ............... 4748.49 |==
C-Ray 1.1
Performance / Cost - Total Time - 4K, 16 Rays Per Pixel
Seconds x Dollar < Lower Is Better
Jetson AGX Xavier ....... 461145.00 |=====================================
Jetson TX2 Max-P ........ 350415.00 |============================
Jetson TX2 Max-Q ........ 520531.00 |==========================================
Raspberry Pi 3 Model B+ . 71050.00 |======
ASUS TinkerBoard ........ 113388.00 |=========
Jetson TX1 Max-P ........ 375747.00 |==============================
ODROID-XU4 .............. 51274.00 |====
Jetson Nano ............. 91179.00 |=======
ODROID-N2 ............... 31940.46 |===
7-Zip Compression 16.02
Performance / Cost - Compress Speed Test
MIPS Per Dollar > Higher Is Better
Jetson AGX Xavier ....... 14.79 |=======
Jetson TX2 Max-P ........ 9.34 |=====
Jetson TX2 Max-Q ........ 5.50 |===
Raspberry Pi 3 Model B+ . 57.51 |=============================
ASUS TinkerBoard ........ 42.97 |======================
Jetson TX1 Max-P ........ 9.03 |=====
ODROID-XU4 .............. 66.45 |=================================
Jetson Nano ............. 40.90 |====================
ODROID-N2 ............... 91.92 |==============================================
TTSIOD 3D Renderer 2.3b
Performance / Cost - Phong Rendering With Soft-Shadow Mapping
FPS Per Dollar > Higher Is Better
Jetson AGX Xavier ....... 0.10 |=====
Jetson TX2 Max-P ........ 0.08 |====
Jetson TX2 Max-Q ........ 0.05 |===
Raspberry Pi 3 Model B+ . 0.50 |===========================
ASUS TinkerBoard ........ 0.32 |=================
Jetson TX1 Max-P ........ 0.09 |=====
ODROID-XU4 .............. 0.68 |====================================
Jetson Nano ............. 0.41 |======================
ODROID-N2 ............... 0.88 |===============================================