Jetson Nano Developer Kit

ODROID-N2

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C/C++ Compiler Tests 4 Tests
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Programmer / Developer System Benchmarks 2 Tests
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Jetson TX1 Max-P
March 17 2019
  1 Hour, 20 Minutes
Jetson TX2 Max-Q
March 16 2019
  7 Hours, 23 Minutes
Jetson TX2 Max-P
March 15 2019
  6 Hours, 25 Minutes
Jetson AGX Xavier
March 15 2019
  4 Hours, 1 Minute
Jetson Nano
March 17 2019
  7 Hours, 18 Minutes
Raspberry Pi 3 Model B+
March 16 2019
  4 Hours, 32 Minutes
ASUS TinkerBoard
March 16 2019
  7 Hours, 20 Minutes
ODROID-XU4
March 17 2019
  4 Hours, 21 Minutes
ARMv8 Cortex-A73
April 21 2019
  1 Hour, 59 Minutes
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  4 Hours, 58 Minutes

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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

Compiler Notes: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v
Processor Notes: Scaling Governor: tegra-cpufreq interactive
Python Notes: Python 2.7.12 + Python 3.5.2

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

Compiler Notes: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v
Processor Notes: Scaling Governor: tegra_cpufreq schedutil
Python Notes: Python 2.7.12 + Python 3.5.2

Jetson TX2 Max-P

Changed Processor to ARMv8 rev 3 @ 2.04GHz (4 Cores / 6 Threads).

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

Compiler Notes: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v
Processor Notes: Scaling Governor: tegra_cpufreq schedutil
Python Notes: Python 2.7.15rc1 + Python 3.6.7

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

Compiler Notes: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v
Processor Notes: Scaling Governor: tegra-cpufreq schedutil
Python Notes: Python 2.7.15rc1 + Python 3.6.7

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

Compiler Notes: --build=arm-linux-gnueabihf --disable-browser-plugin --disable-libitm --disable-libquadmath --disable-sjlj-exceptions --enable-checking=release --enable-clocale=gnu --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=arm-linux-gnueabihf --program-prefix=arm-linux-gnueabihf- --target=arm-linux-gnueabihf --with-arch-directory=arm --with-arch=armv6 --with-default-libstdcxx-abi=new --with-float=hard --with-fpu=vfp --with-target-system-zlib -v
Processor Notes: Scaling Governor: BCM2835 Freq ondemand
Python Notes: Python 2.7.13 + Python 3.5.3

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

Compiler Notes: --build=arm-linux-gnueabihf --disable-browser-plugin --disable-libitm --disable-libquadmath --disable-sjlj-exceptions --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=arm-linux-gnueabihf --program-prefix=arm-linux-gnueabihf- --target=arm-linux-gnueabihf --with-arch-directory=arm --with-arch=armv7-a --with-default-libstdcxx-abi=new --with-float=hard --with-fpu=vfpv3-d16 --with-mode=thumb --with-target-system-zlib -v
Processor Notes: Scaling Governor: cpufreq-dt interactive
Python Notes: Python 2.7.13 + Python 3.5.3

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

Kernel Notes: usbhid.quirks=0x0eef:0x0005:0x0004
Compiler Notes: --build=arm-linux-gnueabihf --disable-libitm --disable-libquadmath --disable-libquadmath-support --disable-sjlj-exceptions --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-multilib --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=arm-linux-gnueabihf --program-prefix=arm-linux-gnueabihf- --target=arm-linux-gnueabihf --with-arch=armv7-a --with-default-libstdcxx-abi=new --with-float=hard --with-fpu=vfpv3-d16 --with-gcc-major-version-only --with-mode=thumb --with-target-system-zlib -v
Processor Notes: Scaling Governor: cpufreq-dt ondemand
Graphics Notes: EXA
Python Notes: Python 2.7.15rc1 + Python 3.6.7

ARMv8 Cortex-A73

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

Compiler Notes: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v
Processor Notes: Scaling Governor: arm-big-little performance
Python Notes: Python 2.7.15rc1 + Python 3.6.7

Jetson Nano Developer KitProcessorMotherboardMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLVulkanCompilerFile-SystemScreen ResolutionJetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU4ARMv8 Cortex-A73ARMv8 rev 1 @ 1.73GHz (4 Cores)jetson_tx14096MB16GB 016G32NVIDIA Tegra X1VE228Ubuntu 16.044.4.38-tegra (aarch64)Unity 7.4.5X Server 1.18.4NVIDIA 28.1.04.5.01.0.8GCC 5.4.0 20160609ext41920x1080ARMv8 rev 3 @ 1.27GHz (4 Cores / 6 Threads)quill8192MB31GB 032G34NVIDIA TEGRAUnity 7.4.0NVIDIA 28.2.1GCC 5.4.0 20160609 + CUDA 9.0ARMv8 rev 3 @ 2.04GHz (4 Cores / 6 Threads)ARMv8 rev 0 @ 2.27GHz (8 Cores)jetson-xavier16384MB31GB HBG4a2NVIDIA Tegra XavierUbuntu 18.044.9.108-tegra (aarch64)Unity 7.5.0X Server 1.19.6NVIDIA 31.0.24.6.01.1.76GCC 7.3.0 + CUDA 10.0ARMv8 rev 1 @ 1.43GHz (4 Cores)jetson-nano4096MB32GB GB1QTNVIDIA TEGRARealtek RTL8111/8168/84114.9.140-tegra (aarch64)NVIDIA 1.0.01.1.85ARMv7 rev 4 @ 1.40GHz (4 Cores)BCM2835 Raspberry Pi 3 Model B Plus Rev 1.3926MB32GB GB2MWBCM2708Raspbian 9.64.19.23-v7+ (armv7l)LXDEX Server 1.19.2GCC 6.3.0 20170516656x416ARMv7 rev 1 @ 1.80GHz (4 Cores)Rockchip (Device Tree)2048MB32GB GB1QTDebian 9.04.4.16-00006-g4431f98-dirty (armv7l)X Server 1.18.41024x768ARMv7 rev 3 @ 1.50GHz (8 Cores)ODROID-XU4 Hardkernel Odroid XU416GB AJTD4Rllvmpipe 2GBVE228Ubuntu 18.044.14.37-135 (armv7l)X Server 1.19.63.3 Mesa 18.0.0-rc5 (LLVM 6.0 128 bits)GCC 7.3.01920x1080ARMv8 Cortex-A73 @ 1.90GHz (6 Cores)Hardkernel ODROID-N24096MBOSD4.9.156-14 (aarch64)1920x2160OpenBenchmarking.orgCompiler Details- Jetson TX1 Max-P: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v - Jetson TX2 Max-Q: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v - Jetson TX2 Max-P: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v - Jetson AGX Xavier: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v - Jetson Nano: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v - Raspberry Pi 3 Model B+: --build=arm-linux-gnueabihf --disable-browser-plugin --disable-libitm --disable-libquadmath --disable-sjlj-exceptions --enable-checking=release --enable-clocale=gnu --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=arm-linux-gnueabihf --program-prefix=arm-linux-gnueabihf- --target=arm-linux-gnueabihf --with-arch-directory=arm --with-arch=armv6 --with-default-libstdcxx-abi=new --with-float=hard --with-fpu=vfp --with-target-system-zlib -v - ASUS TinkerBoard: --build=arm-linux-gnueabihf --disable-browser-plugin --disable-libitm --disable-libquadmath --disable-sjlj-exceptions --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=arm-linux-gnueabihf --program-prefix=arm-linux-gnueabihf- --target=arm-linux-gnueabihf --with-arch-directory=arm --with-arch=armv7-a --with-default-libstdcxx-abi=new --with-float=hard --with-fpu=vfpv3-d16 --with-mode=thumb --with-target-system-zlib -v - ODROID-XU4: --build=arm-linux-gnueabihf --disable-libitm --disable-libquadmath --disable-libquadmath-support --disable-sjlj-exceptions --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-multilib --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=arm-linux-gnueabihf --program-prefix=arm-linux-gnueabihf- --target=arm-linux-gnueabihf --with-arch=armv7-a --with-default-libstdcxx-abi=new --with-float=hard --with-fpu=vfpv3-d16 --with-gcc-major-version-only --with-mode=thumb --with-target-system-zlib -v - ARMv8 Cortex-A73: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v Processor Details- Jetson TX1 Max-P: Scaling Governor: tegra-cpufreq interactive- Jetson TX2 Max-Q: Scaling Governor: tegra_cpufreq schedutil- Jetson TX2 Max-P: Scaling Governor: tegra_cpufreq schedutil- Jetson AGX Xavier: Scaling Governor: tegra_cpufreq schedutil- Jetson Nano: Scaling Governor: tegra-cpufreq schedutil- Raspberry Pi 3 Model B+: Scaling Governor: BCM2835 Freq ondemand- ASUS TinkerBoard: Scaling Governor: cpufreq-dt interactive- ODROID-XU4: Scaling Governor: cpufreq-dt ondemand- ARMv8 Cortex-A73: Scaling Governor: arm-big-little performancePython Details- Jetson TX1 Max-P: Python 2.7.12 + Python 3.5.2- Jetson TX2 Max-Q: Python 2.7.12 + Python 3.5.2- Jetson TX2 Max-P: Python 2.7.12 + Python 3.5.2- Jetson AGX Xavier: Python 2.7.15rc1 + Python 3.6.7- Jetson Nano: Python 2.7.15rc1 + Python 3.6.7- Raspberry Pi 3 Model B+: Python 2.7.13 + Python 3.5.3- ASUS TinkerBoard: Python 2.7.13 + Python 3.5.3- ODROID-XU4: Python 2.7.15rc1 + Python 3.6.7- ARMv8 Cortex-A73: Python 2.7.15rc1 + Python 3.6.7Kernel Details- ODROID-XU4: usbhid.quirks=0x0eef:0x0005:0x0004Graphics Details- ODROID-XU4: EXA

Jetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU4ARMv8 Cortex-A73Logarithmic Result OverviewPhoronix Test Suite7-Zip CompressionTTSIOD 3D RendererPyBenchFLAC Audio EncodingRust Prime BenchmarkC-Ray

Jetson Nano Developer Kitcompress-7zip: Compress Speed Testc-ray: Total Time - 4K, 16 Rays Per Pixelcuda-mini-nbody: Originalencode-flac: WAV To FLACglmark2: 1920 x 1080lczero: BLASlczero: CUDA + cuDNNlczero: CUDA + cuDNN FP16tensorrt-inference: VGG16 - FP16 - 4 - Disabledtensorrt-inference: VGG16 - INT8 - 4 - Disabledtensorrt-inference: VGG19 - FP16 - 4 - Disabledtensorrt-inference: VGG19 - INT8 - 4 - Disabledtensorrt-inference: VGG16 - FP16 - 32 - Disabledtensorrt-inference: VGG16 - INT8 - 32 - Disabledtensorrt-inference: VGG19 - FP16 - 32 - Disabledtensorrt-inference: VGG19 - INT8 - 32 - Disabledtensorrt-inference: AlexNet - FP16 - 4 - Disabledtensorrt-inference: AlexNet - INT8 - 4 - Disabledtensorrt-inference: AlexNet - FP16 - 32 - Disabledtensorrt-inference: AlexNet - INT8 - 32 - Disabledtensorrt-inference: ResNet50 - FP16 - 4 - Disabledtensorrt-inference: ResNet50 - INT8 - 4 - Disabledtensorrt-inference: GoogleNet - FP16 - 4 - Disabledtensorrt-inference: GoogleNet - INT8 - 4 - Disabledtensorrt-inference: ResNet152 - FP16 - 4 - Disabledtensorrt-inference: ResNet152 - INT8 - 4 - Disabledtensorrt-inference: ResNet50 - FP16 - 32 - Disabledtensorrt-inference: ResNet50 - INT8 - 32 - Disabledtensorrt-inference: GoogleNet - FP16 - 32 - Disabledtensorrt-inference: GoogleNet - INT8 - 32 - Disabledtensorrt-inference: ResNet152 - FP16 - 32 - Disabledtensorrt-inference: ResNet152 - INT8 - 32 - Disabledopencv-bench: pybench: Total For Average Test Timesrust-prime: Prime Number Test To 200,000,000tesseract-ocr: Time To OCR 7 Imagesttsiod-renderer: Phong Rendering With Soft-Shadow Mappingcompress-zstd: Compressing ubuntu-16.04.3-server-i386.img, Compression Level 19Jetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU4ARMv8 Cortex-A73450875379.206339128.4545.09145.8032948696.77104.2825.9914.2421.0411.4529.8315.7923.9412.5921614837423772.0139.1515688.8827.3414.5086.0847.1517910432.6717.364938735170.2528.85253.8055935858.2465.0732.6417.5626.5614.3236.8719.9129.8315.9226418446230192.2849.9719711335.1118.2911159.6923313041.9122.072965408104.9649.26144.971921235547.1354.47287647.629532515.01208.76303.78172.50265.81247.95475.08203.96394.661200114320383143547.50902.787961146224.19372.736361215.0810061693259.82493.22128300732.3771.9413380.0640499214.07104.7764615.3714014.3511.5911884.1020112841.0420.9683.3747.8215.767.7646.5125.0898.9355.6617.38271.047084150.19132.6740.94129.8720132030339.532.74209131097.6917.66342.2328361718279.05115021821.0521.22496.62412082797.03520.705009574.11180.6641.96597049295.5924.39243.05523173.11110.7357.42152.04OpenBenchmarking.org

7-Zip Compression

This is a test of 7-Zip using p7zip with its integrated benchmark feature or upstream 7-Zip for the Windows x64 build. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 16.02Compress Speed TestRaspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A734K8K12K16K20KSE +/- 23.74, N = 11SE +/- 89.16, N = 12SE +/- 13.05, N = 3SE +/- 20.85, N = 3SE +/- 13.43, N = 3SE +/- 18.00, N = 3SE +/- 274.18, N = 12SE +/- 34.93, N = 3SE +/- 2.40, N = 320134120329455934508404919212283659701. (CXX) g++ options: -pipe -lpthread

OpenBenchmarking.orgMIPS Per Dollar, More Is Better7-Zip Compression 16.02Performance / Cost - Compress Speed TestRaspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A732040608010057.5166.455.509.349.0340.9014.7942.9791.921. Raspberry Pi 3 Model B+: $35 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX2 Max-Q: $599 reported cost.4. Jetson TX2 Max-P: $599 reported cost.5. Jetson TX1 Max-P: $499 reported cost.6. Jetson Nano: $99 reported cost.7. Jetson AGX Xavier: $1299 reported cost.8. ASUS TinkerBoard: $66 reported cost.9. ARMv8 Cortex-A73: $64.95 reported cost.

C-Ray

This is a test of C-Ray, a simple raytracer designed to test the floating-point CPU performance. This test is multi-threaded (16 threads per core), will shoot 8 rays per pixel for anti-aliasing, and will generate a 1600 x 1200 image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterC-Ray 1.1Total Time - 4K, 16 Rays Per PixelRaspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A73400800120016002000SE +/- 2.46, N = 3SE +/- 29.65, N = 9SE +/- 1.44, N = 3SE +/- 49.09, N = 9SE +/- 10.23, N = 3SE +/- 0.35, N = 3SE +/- 7.17, N = 9SE +/- 22.09, N = 3SE +/- 0.25, N = 3203082786958575392135517184921. (CC) gcc options: -lm -lpthread -O3

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterC-Ray 1.1Performance / Cost - Total Time - 4K, 16 Rays Per PixelRaspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A73110K220K330K440K550K71050.0051274.00520531.00350415.00375747.0091179.00461145.00113388.0031940.461. Raspberry Pi 3 Model B+: $35 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX2 Max-Q: $599 reported cost.4. Jetson TX2 Max-P: $599 reported cost.5. Jetson TX1 Max-P: $499 reported cost.6. Jetson Nano: $99 reported cost.7. Jetson AGX Xavier: $1299 reported cost.8. ASUS TinkerBoard: $66 reported cost.9. ARMv8 Cortex-A73: $64.95 reported cost.

CUDA Mini-Nbody

OpenBenchmarking.org(NBody^2)/s, More Is BetterCUDA Mini-Nbody 2015-11-10Test: OriginalJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier1122334455SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 36.778.244.0747.13

OpenBenchmarking.org(NBody^2)/s Per Dollar, More Is BetterCUDA Mini-Nbody 2015-11-10Performance / Cost - Test: OriginalJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.0090.0180.0270.0360.0450.010.010.040.041. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

FLAC Audio Encoding

This test times how long it takes to encode a sample WAV file to FLAC format five times. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterFLAC Audio Encoding 1.3.2WAV To FLACRaspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A7370140210280350SE +/- 0.98, N = 5SE +/- 0.31, N = 5SE +/- 0.18, N = 5SE +/- 0.15, N = 5SE +/- 0.74, N = 5SE +/- 0.83, N = 5SE +/- 0.61, N = 5SE +/- 2.51, N = 5SE +/- 0.27, N = 5339.5397.03104.2865.0779.20104.7754.47279.0595.591. (CXX) g++ options: -O2 -fvisibility=hidden -logg -lm

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterFLAC Audio Encoding 1.3.2Performance / Cost - WAV To FLACRaspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A7315K30K45K60K75K11883.556015.8662463.7238976.9339520.8010372.2370756.5318417.306208.571. Raspberry Pi 3 Model B+: $35 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX2 Max-Q: $599 reported cost.4. Jetson TX2 Max-P: $599 reported cost.5. Jetson TX1 Max-P: $499 reported cost.6. Jetson Nano: $99 reported cost.7. Jetson AGX Xavier: $1299 reported cost.8. ASUS TinkerBoard: $66 reported cost.9. ARMv8 Cortex-A73: $64.95 reported cost.

GLmark2

This is a test of any system-installed GLMark2 OpenGL benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterGLmark2Resolution: 1920 x 1080Jetson NanoJetson AGX Xavier60012001800240030006462876

OpenBenchmarking.orgScore Per Dollar, More Is BetterGLmark2Performance / Cost - Resolution: 1920 x 1080Jetson NanoJetson AGX Xavier2468106.532.211. Jetson Nano: $99 reported cost.2. Jetson AGX Xavier: $1299 reported cost.

LeelaChessZero

LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.20.1Backend: BLASJetson NanoJetson AGX XavierARMv8 Cortex-A731122334455SE +/- 0.03, N = 3SE +/- 0.62, N = 7SE +/- 0.10, N = 315.3747.6224.391. (CXX) g++ options: -lpthread -lz

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.20.1Backend: CUDA + cuDNNJetson NanoJetson AGX Xavier2004006008001000SE +/- 0.26, N = 3SE +/- 6.14, N = 31409531. (CXX) g++ options: -lpthread -lz

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.20.1Backend: CUDA + cuDNN FP16Jetson AGX Xavier5001000150020002500SE +/- 7.60, N = 32515.011. (CXX) g++ options: -lpthread -lz

OpenBenchmarking.orgNodes Per Second Per Dollar, More Is BetterLeelaChessZero 0.20.1Performance / Cost - Backend: BLASJetson NanoJetson AGX XavierARMv8 Cortex-A730.08550.1710.25650.3420.42750.160.040.381. Jetson Nano: $99 reported cost.2. Jetson AGX Xavier: $1299 reported cost.3. ARMv8 Cortex-A73: $64.95 reported cost.

OpenBenchmarking.orgNodes Per Second Per Dollar, More Is BetterLeelaChessZero 0.20.1Performance / Cost - Backend: CUDA + cuDNNJetson NanoJetson AGX Xavier0.31730.63460.95191.26921.58651.410.731. Jetson Nano: $99 reported cost.2. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgNodes Per Second Per Dollar, More Is BetterLeelaChessZero 0.20.1Performance / Cost - Backend: CUDA + cuDNN FP16Jetson AGX Xavier0.43650.8731.30951.7462.18251.941. $1299 reported cost.

Meta Performance Per Dollar

OpenBenchmarking.orgPerformance Per Dollar, More Is BetterMeta Performance Per DollarPerformance Per DollarARMv8 Cortex-A7351015202519.171. $64.95 reported value. Average value: 1244.91.

NVIDIA TensorRT Inference

This test profile uses any existing system installation of NVIDIA TensorRT for carrying out inference benchmarks with various neural networks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier50100150200250SE +/- 0.13, N = 3SE +/- 0.50, N = 4SE +/- 0.02, N = 2SE +/- 0.10, N = 325.9932.6414.35208.76

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier70140210280350SE +/- 0.20, N = 5SE +/- 0.25, N = 6SE +/- 0.46, N = 314.2417.56303.78

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier4080120160200SE +/- 0.34, N = 3SE +/- 0.38, N = 3SE +/- 0.05, N = 2SE +/- 0.50, N = 321.0426.5611.59172.50

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier60120180240300SE +/- 0.23, N = 3SE +/- 0.25, N = 4SE +/- 0.20, N = 311.4514.32265.81

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier50100150200250SE +/- 0.18, N = 3SE +/- 0.31, N = 3SE +/- 0.12, N = 329.8336.87247.95

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier100200300400500SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.10, N = 315.7919.91475.08

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier4080120160200SE +/- 0.07, N = 3SE +/- 0.05, N = 3SE +/- 0.04, N = 323.9429.83203.96

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier90180270360450SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.23, N = 312.5915.92394.66

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier30060090012001500SE +/- 3.03, N = 6SE +/- 7.77, N = 12SE +/- 2.12, N = 12SE +/- 1.82, N = 32162641181200

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier2004006008001000SE +/- 0.91, N = 3SE +/- 2.79, N = 5SE +/- 0.72, N = 3SE +/- 2.59, N = 3148.00184.0084.101143.00

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier400800120016002000SE +/- 2.82, N = 3SE +/- 7.68, N = 12SE +/- 1.59, N = 3SE +/- 2.07, N = 33744622012038

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier7001400210028003500SE +/- 1.39, N = 3SE +/- 0.52, N = 3SE +/- 0.06, N = 3SE +/- 1.06, N = 32373011283143

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier120240360480600SE +/- 1.10, N = 12SE +/- 1.32, N = 12SE +/- 0.25, N = 3SE +/- 0.03, N = 372.0192.2841.04547.50

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier2004006008001000SE +/- 0.64, N = 3SE +/- 0.79, N = 4SE +/- 0.36, N = 3SE +/- 1.86, N = 339.1549.9720.96902.78

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier2004006008001000SE +/- 1.90, N = 12SE +/- 2.27, N = 3SE +/- 0.70, N = 3SE +/- 2.48, N = 3156.00197.0083.37796.00

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier2004006008001000SE +/- 1.32, N = 3SE +/- 1.65, N = 3SE +/- 0.60, N = 3SE +/- 4.31, N = 388.88113.0047.821146.00

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier50100150200250SE +/- 0.34, N = 3SE +/- 0.36, N = 3SE +/- 0.04, N = 3SE +/- 0.22, N = 327.3435.1115.76224.19

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier80160240320400SE +/- 0.15, N = 3SE +/- 0.14, N = 3SE +/- 0.03, N = 3SE +/- 1.59, N = 314.5018.297.76372.73

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier140280420560700SE +/- 0.86, N = 3SE +/- 1.22, N = 3SE +/- 0.02, N = 3SE +/- 1.23, N = 386.08111.0046.51636.00

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier30060090012001500SE +/- 0.08, N = 3SE +/- 0.04, N = 3SE +/- 0.06, N = 3SE +/- 0.25, N = 347.1559.6925.081215.08

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier2004006008001000SE +/- 2.17, N = 8SE +/- 4.50, N = 3SE +/- 0.19, N = 3SE +/- 0.21, N = 3179.00233.0098.931006.00

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier400800120016002000SE +/- 0.07, N = 3SE +/- 0.74, N = 3SE +/- 0.18, N = 3SE +/- 8.72, N = 3104.00130.0055.661693.00

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier60120180240300SE +/- 0.10, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.26, N = 332.6741.9117.38259.82

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier110220330440550SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.81, N = 317.3622.07493.22

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: VGG16 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.0360.0720.1080.1440.180.040.050.140.161. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: VGG16 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.05180.10360.15540.20720.2590.020.030.231. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: VGG19 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.02930.05860.08790.11720.14650.040.040.120.131. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: VGG19 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.0450.090.1350.180.2250.020.020.201. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: VGG16 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.04280.08560.12840.17120.2140.050.060.191. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: VGG16 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.08330.16660.24990.33320.41650.030.030.371. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: VGG19 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.0360.0720.1080.1440.180.040.050.161. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: VGG19 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.06750.1350.20250.270.33750.020.030.301. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: AlexNet - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.26780.53560.80341.07121.3390.360.441.190.921. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: AlexNet - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.1980.3960.5940.7920.990.250.310.850.881. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.45680.91361.37041.82722.2840.620.772.031.571. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.54451.0891.63352.1782.72250.400.501.292.421. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: ResNet50 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.09450.1890.28350.3780.47250.120.150.410.421. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: ResNet50 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.15530.31060.46590.62120.77650.070.080.210.691. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: GoogleNet - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.1890.3780.5670.7560.9450.260.330.840.611. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: GoogleNet - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.1980.3960.5940.7920.990.150.190.480.881. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: ResNet152 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.03830.07660.11490.15320.19150.050.060.160.171. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: ResNet152 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.06530.13060.19590.26120.32650.020.030.080.291. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: ResNet50 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.11030.22060.33090.44120.55150.140.190.470.491. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: ResNet50 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.21150.4230.63450.8461.05750.080.100.250.941. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.2250.450.6750.91.1250.300.391.000.771. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.29250.5850.87751.171.46250.170.220.561.301. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: ResNet152 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX Xavier0.0450.090.1350.180.2250.050.070.180.201. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson Nano: $99 reported cost.4. Jetson AGX Xavier: $1299 reported cost.

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: ResNet152 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.08550.1710.25650.3420.42750.030.040.381. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.

OpenCV Benchmark

Stress benchmark tests to measure time consumed by the OpenCV libraries installed Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenCV Benchmark 3.3.0Raspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX XavierARMv8 Cortex-A73110220330440550SE +/- 5.31, N = 3SE +/- 5.74, N = 3SE +/- 0.27, N = 3SE +/- 4.66, N = 9SE +/- 1.57, N = 3SE +/- 0.26, N = 32.74520.70493.00296.00271.04128.00243.051. (CXX) g++ options: -std=c++11 -rdynamic

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterOpenCV Benchmark 3.3.0Performance / Cost -Raspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson NanoJetson AGX XavierARMv8 Cortex-A7360K120K180K240K300K95.9032283.40295307.00177304.0026832.96166272.0015786.101. Raspberry Pi 3 Model B+: $35 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX2 Max-Q: $599 reported cost.4. Jetson TX2 Max-P: $599 reported cost.5. Jetson Nano: $99 reported cost.6. Jetson AGX Xavier: $1299 reported cost.7. ARMv8 Cortex-A73: $64.95 reported cost.

PyBench

This test profile reports the total time of the different average timed test results from PyBench. PyBench reports average test times for different functions such as BuiltinFunctionCalls and NestedForLoops, with this total result providing a rough estimate as to Python's average performance on a given system. This test profile runs PyBench each time for 20 rounds. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyBench 2018-02-16Total For Average Test TimesRaspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A734K8K12K16K20KSE +/- 43.80, N = 3SE +/- 30.99, N = 3SE +/- 42.52, N = 3SE +/- 33.86, N = 3SE +/- 18.55, N = 3SE +/- 37.23, N = 3SE +/- 4.67, N = 3SE +/- 854.75, N = 9SE +/- 9.24, N = 320913500987355408633970843007115025231

OpenBenchmarking.orgMilliseconds x Dollar, Fewer Is BetterPyBench 2018-02-16Performance / Cost - Total For Average Test TimesRaspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A731.1M2.2M3.3M4.4M5.5M731955.00310558.005232265.003239392.003163161.00701316.003906093.00759132.00339753.451. Raspberry Pi 3 Model B+: $35 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX2 Max-Q: $599 reported cost.4. Jetson TX2 Max-P: $599 reported cost.5. Jetson TX1 Max-P: $499 reported cost.6. Jetson Nano: $99 reported cost.7. Jetson AGX Xavier: $1299 reported cost.8. ASUS TinkerBoard: $66 reported cost.9. ARMv8 Cortex-A73: $64.95 reported cost.

Rust Prime Benchmark

Based on petehunt/rust-benchmark, this is a prime number benchmark that is multi-threaded and written in Rustlang. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRust Prime BenchmarkPrime Number Test To 200,000,000Raspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A73400800120016002000SE +/- 1.55, N = 3SE +/- 0.37, N = 3SE +/- 0.09, N = 3SE +/- 0.04, N = 3SE +/- 0.77, N = 3SE +/- 0.22, N = 3SE +/- 0.00, N = 3SE +/- 187.90, N = 6SE +/- 0.02, N = 31097.69574.11170.25104.96128.45150.1932.371821.0573.11-ldl -lrt -lpthread -lgcc_s -lc -lm -lutil1. (CC) gcc options: -pie -nodefaultlibs

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterRust Prime BenchmarkPerformance / Cost - Prime Number Test To 200,000,000Raspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A7330K60K90K120K150K38419.1535594.82101979.7562871.0464096.5514868.8142048.63120189.304748.491. Raspberry Pi 3 Model B+: $35 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX2 Max-Q: $599 reported cost.4. Jetson TX2 Max-P: $599 reported cost.5. Jetson TX1 Max-P: $499 reported cost.6. Jetson Nano: $99 reported cost.7. Jetson AGX Xavier: $1299 reported cost.8. ASUS TinkerBoard: $66 reported cost.9. ARMv8 Cortex-A73: $64.95 reported cost.

Tesseract OCR

Tesseract-OCR is the open-source optical character recognition (OCR) engine for the conversion of text within images to raw text output. This test profile relies upon a system-supplied Tesseract installation. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTesseract OCR 4.0.0-beta.1Time To OCR 7 ImagesODROID-XU4Jetson NanoJetson AGX XavierARMv8 Cortex-A734080120160200SE +/- 1.38, N = 3SE +/- 1.50, N = 3SE +/- 0.89, N = 3SE +/- 0.05, N = 3180.66132.6771.94110.73

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterTesseract OCR 4.0.0-beta.1Performance / Cost - Time To OCR 7 ImagesODROID-XU4Jetson NanoJetson AGX XavierARMv8 Cortex-A7320K40K60K80K100K11200.9213134.3393450.067191.911. ODROID-XU4: $62 reported cost.2. Jetson Nano: $99 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. ARMv8 Cortex-A73: $64.95 reported cost.

TTSIOD 3D Renderer

A portable GPL 3D software renderer that supports OpenMP and Intel Threading Building Blocks with many different rendering modes. This version does not use OpenGL but is entirely CPU/software based. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterTTSIOD 3D Renderer 2.3bPhong Rendering With Soft-Shadow MappingRaspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A73306090120150SE +/- 0.16, N = 3SE +/- 0.97, N = 9SE +/- 0.46, N = 4SE +/- 0.15, N = 3SE +/- 0.04, N = 3SE +/- 0.11, N = 3SE +/- 1.63, N = 12SE +/- 0.27, N = 9SE +/- 0.05, N = 317.6641.9628.8549.2645.0940.94133.0021.2257.421. (CXX) g++ options: -O3 -fomit-frame-pointer -ffast-math -mtune=native -flto -lSDL -fopenmp -fwhole-program -lstdc++

OpenBenchmarking.orgFPS Per Dollar, More Is BetterTTSIOD 3D Renderer 2.3bPerformance / Cost - Phong Rendering With Soft-Shadow MappingRaspberry Pi 3 Model B+ODROID-XU4Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A730.1980.3960.5940.7920.990.500.680.050.080.090.410.100.320.881. Raspberry Pi 3 Model B+: $35 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX2 Max-Q: $599 reported cost.4. Jetson TX2 Max-P: $599 reported cost.5. Jetson TX1 Max-P: $499 reported cost.6. Jetson Nano: $99 reported cost.7. Jetson AGX Xavier: $1299 reported cost.8. ASUS TinkerBoard: $66 reported cost.9. ARMv8 Cortex-A73: $64.95 reported cost.

Zstd Compression

This test measures the time needed to compress a sample file (an Ubuntu file-system image) using Zstd compression. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterZstd Compression 1.3.4Compressing ubuntu-16.04.3-server-i386.img, Compression Level 19Raspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A73110220330440550SE +/- 1.03, N = 3SE +/- 1.02, N = 3SE +/- 0.29, N = 3SE +/- 0.42, N = 3SE +/- 0.23, N = 3SE +/- 0.91, N = 3SE +/- 2.16, N = 3SE +/- 1.77, N = 3342.23253.80144.97145.80129.8780.06496.62152.041. (CC) gcc options: -O3 -pthread -lz -llzma

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterZstd Compression 1.3.4Performance / Cost - Compressing ubuntu-16.04.3-server-i386.img, Compression Level 19Raspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson TX1 Max-PJetson NanoJetson AGX XavierASUS TinkerBoardARMv8 Cortex-A7330K60K90K120K150K11978.05152026.2086837.0372754.2012857.13103997.9432776.929875.001. Raspberry Pi 3 Model B+: $35 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 reported cost.4. Jetson TX1 Max-P: $499 reported cost.5. Jetson Nano: $99 reported cost.6. Jetson AGX Xavier: $1299 reported cost.7. ASUS TinkerBoard: $66 reported cost.8. ARMv8 Cortex-A73: $64.95 reported cost.

77 Results Shown

7-Zip Compression
7-Zip Compression
C-Ray
C-Ray
CUDA Mini-Nbody
CUDA Mini-Nbody
FLAC Audio Encoding
FLAC Audio Encoding
GLmark2
GLmark2
LeelaChessZero:
  BLAS
  CUDA + cuDNN
  CUDA + cuDNN FP16
LeelaChessZero:
  Performance / Cost - BLAS
  Performance / Cost - CUDA + cuDNN
  Performance / Cost - CUDA + cuDNN FP16
  Performance Per Dollar
NVIDIA TensorRT Inference:
  VGG16 - FP16 - 4 - Disabled
  VGG16 - INT8 - 4 - Disabled
  VGG19 - FP16 - 4 - Disabled
  VGG19 - INT8 - 4 - Disabled
  VGG16 - FP16 - 32 - Disabled
  VGG16 - INT8 - 32 - Disabled
  VGG19 - FP16 - 32 - Disabled
  VGG19 - INT8 - 32 - Disabled
  AlexNet - FP16 - 4 - Disabled
  AlexNet - INT8 - 4 - Disabled
  AlexNet - FP16 - 32 - Disabled
  AlexNet - INT8 - 32 - Disabled
  ResNet50 - FP16 - 4 - Disabled
  ResNet50 - INT8 - 4 - Disabled
  GoogleNet - FP16 - 4 - Disabled
  GoogleNet - INT8 - 4 - Disabled
  ResNet152 - FP16 - 4 - Disabled
  ResNet152 - INT8 - 4 - Disabled
  ResNet50 - FP16 - 32 - Disabled
  ResNet50 - INT8 - 32 - Disabled
  GoogleNet - FP16 - 32 - Disabled
  GoogleNet - INT8 - 32 - Disabled
  ResNet152 - FP16 - 32 - Disabled
  ResNet152 - INT8 - 32 - Disabled
NVIDIA TensorRT Inference:
  Performance / Cost - VGG16 - FP16 - 4 - Disabled
  Performance / Cost - VGG16 - INT8 - 4 - Disabled
  Performance / Cost - VGG19 - FP16 - 4 - Disabled
  Performance / Cost - VGG19 - INT8 - 4 - Disabled
  Performance / Cost - VGG16 - FP16 - 32 - Disabled
  Performance / Cost - VGG16 - INT8 - 32 - Disabled
  Performance / Cost - VGG19 - FP16 - 32 - Disabled
  Performance / Cost - VGG19 - INT8 - 32 - Disabled
  Performance / Cost - AlexNet - FP16 - 4 - Disabled
  Performance / Cost - AlexNet - INT8 - 4 - Disabled
  Performance / Cost - AlexNet - FP16 - 32 - Disabled
  Performance / Cost - AlexNet - INT8 - 32 - Disabled
  Performance / Cost - ResNet50 - FP16 - 4 - Disabled
  Performance / Cost - ResNet50 - INT8 - 4 - Disabled
  Performance / Cost - GoogleNet - FP16 - 4 - Disabled
  Performance / Cost - GoogleNet - INT8 - 4 - Disabled
  Performance / Cost - ResNet152 - FP16 - 4 - Disabled
  Performance / Cost - ResNet152 - INT8 - 4 - Disabled
  Performance / Cost - ResNet50 - FP16 - 32 - Disabled
  Performance / Cost - ResNet50 - INT8 - 32 - Disabled
  Performance / Cost - GoogleNet - FP16 - 32 - Disabled
  Performance / Cost - GoogleNet - INT8 - 32 - Disabled
  Performance / Cost - ResNet152 - FP16 - 32 - Disabled
  Performance / Cost - ResNet152 - INT8 - 32 - Disabled
OpenCV Benchmark
OpenCV Benchmark
PyBench
PyBench
Rust Prime Benchmark
Rust Prime Benchmark
Tesseract OCR
Tesseract OCR
TTSIOD 3D Renderer
TTSIOD 3D Renderer
Zstd Compression
Zstd Compression

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

Compiler Notes: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v
Processor Notes: Scaling Governor: tegra-cpufreq interactive
Python Notes: Python 2.7.12 + Python 3.5.2

Testing initiated at 17 March 2019 00:43 by user root.

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

Compiler Notes: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v
Processor Notes: Scaling Governor: tegra_cpufreq schedutil
Python Notes: Python 2.7.12 + Python 3.5.2

Testing initiated at 16 March 2019 01:16 by user NVIDIA.

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

Compiler Notes: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v
Processor Notes: Scaling Governor: tegra_cpufreq schedutil
Python Notes: Python 2.7.12 + Python 3.5.2

Testing initiated at 15 March 2019 18:32 by user NVIDIA.

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

Compiler Notes: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v
Processor Notes: Scaling Governor: tegra_cpufreq schedutil
Python Notes: Python 2.7.15rc1 + Python 3.6.7

Testing initiated at 15 March 2019 06:47 by user NVIDIA.

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

Compiler Notes: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v
Processor Notes: Scaling Governor: tegra-cpufreq schedutil
Python Notes: Python 2.7.15rc1 + Python 3.6.7

Testing initiated at 17 March 2019 15:12 by user phoronix.

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

Compiler Notes: --build=arm-linux-gnueabihf --disable-browser-plugin --disable-libitm --disable-libquadmath --disable-sjlj-exceptions --enable-checking=release --enable-clocale=gnu --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=arm-linux-gnueabihf --program-prefix=arm-linux-gnueabihf- --target=arm-linux-gnueabihf --with-arch-directory=arm --with-arch=armv6 --with-default-libstdcxx-abi=new --with-float=hard --with-fpu=vfp --with-target-system-zlib -v
Processor Notes: Scaling Governor: BCM2835 Freq ondemand
Python Notes: Python 2.7.13 + Python 3.5.3

Testing initiated at 16 March 2019 06:12 by user pi.

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

Compiler Notes: --build=arm-linux-gnueabihf --disable-browser-plugin --disable-libitm --disable-libquadmath --disable-sjlj-exceptions --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=arm-linux-gnueabihf --program-prefix=arm-linux-gnueabihf- --target=arm-linux-gnueabihf --with-arch-directory=arm --with-arch=armv7-a --with-default-libstdcxx-abi=new --with-float=hard --with-fpu=vfpv3-d16 --with-mode=thumb --with-target-system-zlib -v
Processor Notes: Scaling Governor: cpufreq-dt interactive
Python Notes: Python 2.7.13 + Python 3.5.3

Testing initiated at 16 March 2019 16:10 by user root.

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

Kernel Notes: usbhid.quirks=0x0eef:0x0005:0x0004
Compiler Notes: --build=arm-linux-gnueabihf --disable-libitm --disable-libquadmath --disable-libquadmath-support --disable-sjlj-exceptions --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-multilib --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=arm-linux-gnueabihf --program-prefix=arm-linux-gnueabihf- --target=arm-linux-gnueabihf --with-arch=armv7-a --with-default-libstdcxx-abi=new --with-float=hard --with-fpu=vfpv3-d16 --with-gcc-major-version-only --with-mode=thumb --with-target-system-zlib -v
Processor Notes: Scaling Governor: cpufreq-dt ondemand
Graphics Notes: EXA
Python Notes: Python 2.7.15rc1 + Python 3.6.7

Testing initiated at 17 March 2019 11:10 by user odroid.

ARMv8 Cortex-A73

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

Compiler Notes: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v
Processor Notes: Scaling Governor: arm-big-little performance
Python Notes: Python 2.7.15rc1 + Python 3.6.7

Testing initiated at 21 April 2019 01:09 by user root.