Jetson Nano Developer Kit

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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
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  5 Hours, 20 Minutes

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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 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

Jetson TX2 Max-Q

Changed Processor to ARMv8 rev 3 @ 1.27GHz (4 Cores / 6 Threads).

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

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

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

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

Jetson Nano Developer KitProcessorMotherboardMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLVulkanCompilerFile-SystemScreen ResolutionJetson AGX XavierJetson TX2 Max-PJetson TX2 Max-QRaspberry Pi 3 Model B+ASUS TinkerBoardJetson TX1 Max-PODROID-XU4Jetson NanoARMv8 rev 0 @ 2.27GHz (8 Cores)jetson-xavier16384MB31GB HBG4a2NVIDIA Tegra XavierVE228Ubuntu 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 10.0ext41920x1080ARMv8 rev 3 @ 2.04GHz (4 Cores / 6 Threads)quill8192MB31GB 032G34NVIDIA TEGRAUbuntu 16.044.4.38-tegra (aarch64)Unity 7.4.0X Server 1.18.4NVIDIA 28.2.14.5.0GCC 5.4.0 20160609 + CUDA 9.0ARMv8 rev 3 @ 1.27GHz (4 Cores / 6 Threads)ARMv7 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 1.18.41024x768ARMv8 rev 1 @ 1.73GHz (4 Cores)jetson_tx14096MB16GB 016G32NVIDIA Tegra X1VE228Ubuntu 16.044.4.38-tegra (aarch64)Unity 7.4.5NVIDIA 28.1.04.5.01.0.8GCC 5.4.0 201606091920x1080ARMv7 rev 3 @ 1.50GHz (8 Cores)ODROID-XU4 Hardkernel Odroid XU42048MB16GB AJTD4Rllvmpipe 2GBUbuntu 18.044.14.37-135 (armv7l)X Server 1.19.63.3 Mesa 18.0.0-rc5 (LLVM 6.0 128 bits)GCC 7.3.0ARMv8 rev 1 @ 1.43GHz (4 Cores)jetson-nano4096MB32GB GB1QTNVIDIA TEGRARealtek RTL8111/8168/84114.9.140-tegra (aarch64)Unity 7.5.0NVIDIA 1.0.01.1.85GCC 7.3.0 + CUDA 10.0OpenBenchmarking.orgCompiler Details- 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 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 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 - 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 - 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 - 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 - 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 Processor Details- Jetson AGX Xavier: Scaling Governor: tegra_cpufreq schedutil- Jetson TX2 Max-P: Scaling Governor: tegra_cpufreq schedutil- Jetson TX2 Max-Q: Scaling Governor: tegra_cpufreq schedutil- Raspberry Pi 3 Model B+: Scaling Governor: BCM2835 Freq ondemand- ASUS TinkerBoard: Scaling Governor: cpufreq-dt interactive- Jetson TX1 Max-P: Scaling Governor: tegra-cpufreq interactive- ODROID-XU4: Scaling Governor: cpufreq-dt ondemand- Jetson Nano: Scaling Governor: tegra-cpufreq schedutilPython Details- Jetson AGX Xavier: Python 2.7.15rc1 + Python 3.6.7- Jetson TX2 Max-P: Python 2.7.12 + Python 3.5.2- Jetson TX2 Max-Q: Python 2.7.12 + Python 3.5.2- Raspberry Pi 3 Model B+: Python 2.7.13 + Python 3.5.3- ASUS TinkerBoard: Python 2.7.13 + Python 3.5.3- Jetson TX1 Max-P: Python 2.7.12 + Python 3.5.2- ODROID-XU4: Python 2.7.15rc1 + Python 3.6.7- Jetson Nano: Python 2.7.15rc1 + Python 3.6.7Kernel Details- ODROID-XU4: usbhid.quirks=0x0eef:0x0005:0x0004Graphics Details- ODROID-XU4: EXA

Jetson AGX XavierJetson TX2 Max-PJetson TX2 Max-QRaspberry Pi 3 Model B+ASUS TinkerBoardJetson TX1 Max-PODROID-XU4Jetson NanoLogarithmic 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 AGX XavierJetson TX2 Max-PJetson TX2 Max-QRaspberry Pi 3 Model B+ASUS TinkerBoardJetson TX1 Max-PODROID-XU4Jetson Nano1921235547.1354.47287647.629532515.01208.76303.78172.50265.81247.95475.08203.96394.661200114320383143547.50902.787961146224.19372.736361215.0810061693259.82493.22128300732.3771.9413380.0655935858.2465.0732.6417.5626.5614.3236.8719.9129.8315.9226418446230192.2849.9719711335.1118.2911159.6923313041.9122.072965408104.9649.26144.9732948696.77104.2825.9914.2421.0411.4529.8315.7923.9412.5921614837423772.0139.1515688.8827.3414.5086.0847.1517910432.6717.364938735170.2528.85253.8020132030339.532.74209131097.6917.66342.2328361718279.05115021821.0521.22496.62450875379.206339128.4545.09145.80412082797.03520.705009574.11180.6641.9640499214.07104.7764615.3714014.3511.5911884.1020112841.0420.9683.3747.8215.767.7646.5125.0898.9355.6617.38271.047084150.19132.6740.94129.87OpenBenchmarking.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 TestJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier4K8K12K16K20KSE +/- 18.00, N = 3SE +/- 89.16, N = 12SE +/- 13.43, N = 3SE +/- 34.93, N = 3SE +/- 23.74, N = 11SE +/- 13.05, N = 3SE +/- 20.85, N = 3SE +/- 274.18, N = 124049412045082836201332945593192121. (CXX) g++ options: -pipe -lpthread
OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 16.02Compress Speed TestJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier3K6K9K12K15KMin: 4025 / Avg: 4048.67 / Max: 4084Min: 3798 / Avg: 4120.25 / Max: 4934Min: 4483 / Avg: 4508 / Max: 4529Min: 2766 / Avg: 2835.67 / Max: 2875Min: 1778 / Avg: 2012.64 / Max: 2056Min: 3269 / Avg: 3294 / Max: 3313Min: 5571 / Avg: 5593.33 / Max: 5635Min: 16806 / Avg: 19211.83 / Max: 197801. (CXX) g++ options: -pipe -lpthread

OpenBenchmarking.orgMIPS Per Dollar, More Is Better7-Zip Compression 16.02Performance / Cost - Compress Speed TestJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier153045607540.9066.459.0342.9757.515.509.3414.791. Jetson Nano: $99 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX1 Max-P: $499 reported cost.4. ASUS TinkerBoard: $66 reported cost.5. Raspberry Pi 3 Model B+: $35 reported cost.6. Jetson TX2 Max-Q: $599 reported cost.7. Jetson TX2 Max-P: $599 reported cost.8. Jetson AGX Xavier: $1299 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 PixelJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier400800120016002000SE +/- 0.35, N = 3SE +/- 29.65, N = 9SE +/- 10.23, N = 3SE +/- 22.09, N = 3SE +/- 2.46, N = 3SE +/- 1.44, N = 3SE +/- 49.09, N = 9SE +/- 7.17, N = 9921827753171820308695853551. (CC) gcc options: -lm -lpthread -O3
OpenBenchmarking.orgSeconds, Fewer Is BetterC-Ray 1.1Total Time - 4K, 16 Rays Per PixelJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier400800120016002000Min: 920.71 / Avg: 921.21 / Max: 921.88Min: 747.78 / Avg: 827.04 / Max: 1020.68Min: 741.18 / Avg: 752.56 / Max: 772.97Min: 1673.94 / Avg: 1718.09 / Max: 1741.49Min: 2025.91 / Avg: 2029.72 / Max: 2034.33Min: 865.79 / Avg: 868.66 / Max: 870.17Min: 531.98 / Avg: 585.26 / Max: 977.76Min: 300.33 / Avg: 354.78 / Max: 364.691. (CC) gcc options: -lm -lpthread -O3

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterC-Ray 1.1Performance / Cost - Total Time - 4K, 16 Rays Per PixelJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier110K220K330K440K550K91179.0051274.00375747.00113388.0071050.00520531.00350415.00461145.001. Jetson Nano: $99 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX1 Max-P: $499 reported cost.4. ASUS TinkerBoard: $66 reported cost.5. Raspberry Pi 3 Model B+: $35 reported cost.6. Jetson TX2 Max-Q: $599 reported cost.7. Jetson TX2 Max-P: $599 reported cost.8. Jetson AGX Xavier: $1299 reported cost.

CUDA Mini-Nbody

OpenBenchmarking.org(NBody^2)/s, More Is BetterCUDA Mini-Nbody 2015-11-10Test: OriginalJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier1122334455SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 34.076.778.2447.13
OpenBenchmarking.org(NBody^2)/s, More Is BetterCUDA Mini-Nbody 2015-11-10Test: OriginalJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier1020304050Min: 4.07 / Avg: 4.07 / Max: 4.09Min: 6.71 / Avg: 6.77 / Max: 6.8Min: 8.23 / Avg: 8.24 / Max: 8.25Min: 47.12 / Avg: 47.13 / Max: 47.14

OpenBenchmarking.org(NBody^2)/s Per Dollar, More Is BetterCUDA Mini-Nbody 2015-11-10Performance / Cost - Test: OriginalJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.0090.0180.0270.0360.0450.040.010.010.041. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 FLACJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier70140210280350SE +/- 0.83, N = 5SE +/- 0.31, N = 5SE +/- 0.74, N = 5SE +/- 2.51, N = 5SE +/- 0.98, N = 5SE +/- 0.18, N = 5SE +/- 0.15, N = 5SE +/- 0.61, N = 5104.7797.0379.20279.05339.53104.2865.0754.471. (CXX) g++ options: -O2 -fvisibility=hidden -logg -lm
OpenBenchmarking.orgSeconds, Fewer Is BetterFLAC Audio Encoding 1.3.2WAV To FLACJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier60120180240300Min: 103.14 / Avg: 104.77 / Max: 107.75Min: 96.22 / Avg: 97.03 / Max: 98.12Min: 76.88 / Avg: 79.2 / Max: 80.64Min: 271.5 / Avg: 279.05 / Max: 286.25Min: 337.11 / Avg: 339.53 / Max: 342.57Min: 103.77 / Avg: 104.28 / Max: 104.76Min: 64.8 / Avg: 65.07 / Max: 65.64Min: 53.06 / Avg: 54.47 / Max: 56.731. (CXX) g++ options: -O2 -fvisibility=hidden -logg -lm

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterFLAC Audio Encoding 1.3.2Performance / Cost - WAV To FLACJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier15K30K45K60K75K10372.236015.8639520.8018417.3011883.5562463.7238976.9370756.531. Jetson Nano: $99 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX1 Max-P: $499 reported cost.4. ASUS TinkerBoard: $66 reported cost.5. Raspberry Pi 3 Model B+: $35 reported cost.6. Jetson TX2 Max-Q: $599 reported cost.7. Jetson TX2 Max-P: $599 reported cost.8. Jetson AGX Xavier: $1299 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 Xavier1122334455SE +/- 0.03, N = 3SE +/- 0.62, N = 715.3747.621. (CXX) g++ options: -lpthread -lz
OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.20.1Backend: BLASJetson NanoJetson AGX Xavier1020304050Min: 15.31 / Avg: 15.37 / Max: 15.4Min: 46.47 / Avg: 47.62 / Max: 51.31. (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 + cuDNNJetson NanoJetson AGX Xavier2004006008001000Min: 139.47 / Avg: 139.79 / Max: 140.31Min: 940.76 / Avg: 952.89 / Max: 960.651. (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 Xavier0.0360.0720.1080.1440.180.160.041. 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 + 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.

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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier50100150200250SE +/- 0.02, N = 2SE +/- 0.13, N = 3SE +/- 0.50, N = 4SE +/- 0.10, N = 314.3525.9932.64208.76
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier4080120160200Min: 14.33 / Avg: 14.35 / Max: 14.37Min: 25.73 / Avg: 25.99 / Max: 26.17Min: 31.7 / Avg: 32.64 / Max: 33.98Min: 208.63 / Avg: 208.76 / Max: 208.96

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: VGG16 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier50100150200250Min: 13.46 / Avg: 14.24 / Max: 14.6Min: 16.36 / Avg: 17.56 / Max: 18.11Min: 303.01 / Avg: 303.78 / Max: 304.61

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier4080120160200SE +/- 0.05, N = 2SE +/- 0.34, N = 3SE +/- 0.38, N = 3SE +/- 0.50, N = 311.5921.0426.56172.50
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG19 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier306090120150Min: 11.54 / Avg: 11.59 / Max: 11.64Min: 20.54 / Avg: 21.04 / Max: 21.7Min: 25.87 / Avg: 26.56 / Max: 27.2Min: 171.71 / Avg: 172.5 / Max: 173.43

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: VGG19 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier50100150200250Min: 10.99 / Avg: 11.45 / Max: 11.69Min: 13.63 / Avg: 14.32 / Max: 14.8Min: 265.44 / Avg: 265.81 / Max: 266.11

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: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier4080120160200Min: 29.48 / Avg: 29.83 / Max: 30.12Min: 36.25 / Avg: 36.87 / Max: 37.19Min: 247.73 / Avg: 247.95 / Max: 248.14

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: VGG16 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier80160240320400Min: 15.76 / Avg: 15.79 / Max: 15.81Min: 19.83 / Avg: 19.91 / Max: 19.99Min: 474.88 / Avg: 475.08 / Max: 475.2

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: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier4080120160200Min: 23.79 / Avg: 23.94 / Max: 24.04Min: 29.76 / Avg: 29.83 / Max: 29.94Min: 203.92 / Avg: 203.96 / Max: 204.03

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: VGG19 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier70140210280350Min: 12.53 / Avg: 12.59 / Max: 12.63Min: 15.81 / Avg: 15.92 / Max: 16Min: 394.4 / Avg: 394.66 / Max: 395.11

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier30060090012001500SE +/- 2.12, N = 12SE +/- 3.03, N = 6SE +/- 7.77, N = 12SE +/- 1.82, N = 31182162641200
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier2004006008001000Min: 104.75 / Avg: 118.34 / Max: 127.58Min: 202.59 / Avg: 216.45 / Max: 224.23Min: 222.34 / Avg: 263.9 / Max: 304.01Min: 1196.24 / Avg: 1199.87 / Max: 1201.91

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier2004006008001000SE +/- 0.72, N = 3SE +/- 0.91, N = 3SE +/- 2.79, N = 5SE +/- 2.59, N = 384.10148.00184.001143.00
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier2004006008001000Min: 82.88 / Avg: 84.1 / Max: 85.38Min: 146.67 / Avg: 148.2 / Max: 149.83Min: 175.71 / Avg: 184.09 / Max: 192.25Min: 1138.12 / Avg: 1142.71 / Max: 1147.08

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier400800120016002000SE +/- 1.59, N = 3SE +/- 2.82, N = 3SE +/- 7.68, N = 12SE +/- 2.07, N = 32013744622038
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier400800120016002000Min: 197.66 / Avg: 200.84 / Max: 202.54Min: 368.3 / Avg: 373.57 / Max: 377.97Min: 418.29 / Avg: 461.97 / Max: 493.49Min: 2035.4 / Avg: 2038.31 / Max: 2042.31

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier7001400210028003500SE +/- 0.06, N = 3SE +/- 1.39, N = 3SE +/- 0.52, N = 3SE +/- 1.06, N = 31282373013143
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier5001000150020002500Min: 127.47 / Avg: 127.59 / Max: 127.67Min: 235.62 / Avg: 237.06 / Max: 239.84Min: 300.06 / Avg: 300.95 / Max: 301.86Min: 3140.95 / Avg: 3142.61 / Max: 3144.59

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier120240360480600SE +/- 0.25, N = 3SE +/- 1.10, N = 12SE +/- 1.32, N = 12SE +/- 0.03, N = 341.0472.0192.28547.50
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier100200300400500Min: 40.75 / Avg: 41.04 / Max: 41.54Min: 65.28 / Avg: 72.01 / Max: 77.6Min: 85.37 / Avg: 92.28 / Max: 100.02Min: 547.46 / Avg: 547.5 / Max: 547.56

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier2004006008001000SE +/- 0.36, N = 3SE +/- 0.64, N = 3SE +/- 0.79, N = 4SE +/- 1.86, N = 320.9639.1549.97902.78
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier160320480640800Min: 20.29 / Avg: 20.96 / Max: 21.53Min: 37.88 / Avg: 39.15 / Max: 39.9Min: 47.92 / Avg: 49.97 / Max: 51.79Min: 899.76 / Avg: 902.78 / Max: 906.18

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier2004006008001000SE +/- 0.70, N = 3SE +/- 1.90, N = 12SE +/- 2.27, N = 3SE +/- 2.48, N = 383.37156.00197.00796.00
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier140280420560700Min: 82.6 / Avg: 83.37 / Max: 84.77Min: 146.96 / Avg: 156.25 / Max: 165.88Min: 193.49 / Avg: 197.4 / Max: 201.35Min: 790.77 / Avg: 795.65 / Max: 798.88

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier2004006008001000SE +/- 0.60, N = 3SE +/- 1.32, N = 3SE +/- 1.65, N = 3SE +/- 4.31, N = 347.8288.88113.001146.00
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier2004006008001000Min: 46.83 / Avg: 47.82 / Max: 48.89Min: 86.29 / Avg: 88.88 / Max: 90.62Min: 110.9 / Avg: 113.14 / Max: 116.36Min: 1137.32 / Avg: 1145.68 / Max: 1151.7

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier50100150200250SE +/- 0.04, N = 3SE +/- 0.34, N = 3SE +/- 0.36, N = 3SE +/- 0.22, N = 315.7627.3435.11224.19
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier4080120160200Min: 15.71 / Avg: 15.76 / Max: 15.83Min: 26.85 / Avg: 27.34 / Max: 27.98Min: 34.41 / Avg: 35.11 / Max: 35.61Min: 223.75 / Avg: 224.19 / Max: 224.48

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier80160240320400SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.14, N = 3SE +/- 1.59, N = 37.7614.5018.29372.73
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: INT8 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier70140210280350Min: 7.71 / Avg: 7.76 / Max: 7.8Min: 14.29 / Avg: 14.5 / Max: 14.8Min: 18.02 / Avg: 18.29 / Max: 18.46Min: 370.1 / Avg: 372.73 / Max: 375.59

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier140280420560700SE +/- 0.02, N = 3SE +/- 0.86, N = 3SE +/- 1.22, N = 3SE +/- 1.23, N = 346.5186.08111.00636.00
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier110220330440550Min: 46.48 / Avg: 46.51 / Max: 46.55Min: 84.39 / Avg: 86.08 / Max: 87.21Min: 108.57 / Avg: 110.71 / Max: 112.8Min: 633.64 / Avg: 635.99 / Max: 637.77

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier30060090012001500SE +/- 0.06, N = 3SE +/- 0.08, N = 3SE +/- 0.04, N = 3SE +/- 0.25, N = 325.0847.1559.691215.08
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet50 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier2004006008001000Min: 24.98 / Avg: 25.08 / Max: 25.19Min: 47.01 / Avg: 47.15 / Max: 47.28Min: 59.62 / Avg: 59.69 / Max: 59.74Min: 1214.64 / Avg: 1215.08 / Max: 1215.5

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier2004006008001000SE +/- 0.19, N = 3SE +/- 2.17, N = 8SE +/- 4.50, N = 3SE +/- 0.21, N = 398.93179.00233.001006.00
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier2004006008001000Min: 98.55 / Avg: 98.93 / Max: 99.16Min: 171.57 / Avg: 179.28 / Max: 186.27Min: 223.96 / Avg: 232.95 / Max: 237.67Min: 1005.65 / Avg: 1005.91 / Max: 1006.32

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier400800120016002000SE +/- 0.18, N = 3SE +/- 0.07, N = 3SE +/- 0.74, N = 3SE +/- 8.72, N = 355.66104.00130.001693.00
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier30060090012001500Min: 55.3 / Avg: 55.66 / Max: 55.89Min: 103.51 / Avg: 103.65 / Max: 103.76Min: 128.85 / Avg: 130.12 / Max: 131.41Min: 1675.82 / Avg: 1693.17 / Max: 1703.42

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier60120180240300SE +/- 0.01, N = 3SE +/- 0.10, N = 3SE +/- 0.07, N = 3SE +/- 0.26, N = 317.3832.6741.91259.82
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier50100150200250Min: 17.37 / Avg: 17.38 / Max: 17.4Min: 32.48 / Avg: 32.67 / Max: 32.81Min: 41.81 / Avg: 41.91 / Max: 42.04Min: 259.31 / Avg: 259.82 / Max: 260.15

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, More Is BetterNVIDIA TensorRT InferenceNeural Network: ResNet152 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier90180270360450Min: 17.35 / Avg: 17.36 / Max: 17.37Min: 22.03 / Avg: 22.07 / Max: 22.12Min: 491.63 / Avg: 493.22 / Max: 494.31

OpenBenchmarking.orgImages Per Second Per Dollar, More Is BetterNVIDIA TensorRT InferencePerformance / Cost - Neural Network: VGG16 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.0360.0720.1080.1440.180.140.040.050.161. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.02930.05860.08790.11720.14650.120.040.040.131. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.26780.53560.80341.07121.3391.190.360.440.921. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.1980.3960.5940.7920.990.850.250.310.881. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.45680.91361.37041.82722.2842.030.620.771.571. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.54451.0891.63352.1782.72251.290.400.502.421. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.09450.1890.28350.3780.47250.410.120.150.421. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.15530.31060.46590.62120.77650.210.070.080.691. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.1890.3780.5670.7560.9450.840.260.330.611. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.1980.3960.5940.7920.990.480.150.190.881. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.03830.07660.11490.15320.19150.160.050.060.171. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.06530.13060.19590.26120.32650.080.020.030.291. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.11030.22060.33090.44120.55150.470.140.190.491. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.21150.4230.63450.8461.05750.250.080.100.941. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.2250.450.6750.91.1251.000.300.390.771. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.29250.5850.87751.171.46250.560.170.221.301. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 NanoJetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.0450.090.1350.180.2250.180.050.070.201. Jetson Nano: $99 reported cost.2. Jetson TX2 Max-Q: $599 reported cost.3. Jetson TX2 Max-P: $599 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 3.3.0Jetson NanoODROID-XU4Raspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier110220330440550SE +/- 4.66, N = 9SE +/- 5.31, N = 3SE +/- 5.74, N = 3SE +/- 0.27, N = 3SE +/- 1.57, N = 3271.04520.702.74493.00296.00128.001. (CXX) g++ options: -std=c++11 -rdynamic
OpenBenchmarking.orgSeconds, Fewer Is BetterOpenCV Benchmark 3.3.0Jetson NanoODROID-XU4Raspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier90180270360450Min: 261.63 / Avg: 271.04 / Max: 304.63Min: 514.99 / Avg: 520.7 / Max: 531.3Min: 486.66 / Avg: 492.74 / Max: 504.22Min: 295.74 / Avg: 296.1 / Max: 296.62Min: 125.26 / Avg: 127.83 / Max: 130.691. (CXX) g++ options: -std=c++11 -rdynamic

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterOpenCV Benchmark 3.3.0Performance / Cost -Jetson NanoODROID-XU4Raspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier60K120K180K240K300K26832.9632283.4095.90295307.00177304.00166272.001. Jetson Nano: $99 reported cost.2. ODROID-XU4: $62 reported cost.3. Raspberry Pi 3 Model B+: $35 reported cost.4. Jetson TX2 Max-Q: $599 reported cost.5. Jetson TX2 Max-P: $599 reported cost.6. Jetson AGX Xavier: $1299 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 TimesJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier4K8K12K16K20KSE +/- 37.23, N = 3SE +/- 30.99, N = 3SE +/- 18.55, N = 3SE +/- 854.75, N = 9SE +/- 43.80, N = 3SE +/- 42.52, N = 3SE +/- 33.86, N = 3SE +/- 4.67, N = 37084500963391150220913873554083007
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyBench 2018-02-16Total For Average Test TimesJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier4K8K12K16K20KMin: 7031 / Avg: 7084.33 / Max: 7156Min: 4968 / Avg: 5009.33 / Max: 5070Min: 6303 / Avg: 6339.33 / Max: 6364Min: 9624 / Avg: 11502.33 / Max: 16297Min: 20826 / Avg: 20912.67 / Max: 20967Min: 8690 / Avg: 8735 / Max: 8820Min: 5366 / Avg: 5408 / Max: 5475Min: 2998 / Avg: 3006.67 / Max: 3014

OpenBenchmarking.orgMilliseconds x Dollar, Fewer Is BetterPyBench 2018-02-16Performance / Cost - Total For Average Test TimesJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier1.1M2.2M3.3M4.4M5.5M701316.00310558.003163161.00759132.00731955.005232265.003239392.003906093.001. Jetson Nano: $99 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX1 Max-P: $499 reported cost.4. ASUS TinkerBoard: $66 reported cost.5. Raspberry Pi 3 Model B+: $35 reported cost.6. Jetson TX2 Max-Q: $599 reported cost.7. Jetson TX2 Max-P: $599 reported cost.8. Jetson AGX Xavier: $1299 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 200,000,000Jetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier400800120016002000SE +/- 0.22, N = 3SE +/- 0.37, N = 3SE +/- 0.77, N = 3SE +/- 187.90, N = 6SE +/- 1.55, N = 3SE +/- 0.09, N = 3SE +/- 0.04, N = 3SE +/- 0.00, N = 3150.19574.11128.451821.051097.69170.25104.9632.37-ldl -lrt -lpthread -lgcc_s -lc -lm -lutil1. (CC) gcc options: -pie -nodefaultlibs
OpenBenchmarking.orgSeconds, Fewer Is BetterRust Prime BenchmarkPrime Number Test To 200,000,000Jetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier30060090012001500Min: 149.76 / Avg: 150.19 / Max: 150.43Min: 573.68 / Avg: 574.11 / Max: 574.84Min: 127 / Avg: 128.45 / Max: 129.6Min: 1407.01 / Avg: 1821.05 / Max: 2575.57Min: 1095.85 / Avg: 1097.69 / Max: 1100.76Min: 170.09 / Avg: 170.25 / Max: 170.41Min: 104.9 / Avg: 104.96 / Max: 105.04Min: 32.36 / Avg: 32.37 / Max: 32.371. (CC) gcc options: -pie -nodefaultlibs

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterRust Prime BenchmarkPerformance / Cost - Prime Number Test To 200,000,000Jetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier30K60K90K120K150K14868.8135594.8264096.55120189.3038419.15101979.7562871.0442048.631. Jetson Nano: $99 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX1 Max-P: $499 reported cost.4. ASUS TinkerBoard: $66 reported cost.5. Raspberry Pi 3 Model B+: $35 reported cost.6. Jetson TX2 Max-Q: $599 reported cost.7. Jetson TX2 Max-P: $599 reported cost.8. Jetson AGX Xavier: $1299 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 ImagesJetson NanoODROID-XU4Jetson AGX Xavier4080120160200SE +/- 1.50, N = 3SE +/- 1.38, N = 3SE +/- 0.89, N = 3132.67180.6671.94
OpenBenchmarking.orgSeconds, Fewer Is BetterTesseract OCR 4.0.0-beta.1Time To OCR 7 ImagesJetson NanoODROID-XU4Jetson AGX Xavier306090120150Min: 130.29 / Avg: 132.67 / Max: 135.45Min: 178.32 / Avg: 180.66 / Max: 183.09Min: 70.52 / Avg: 71.94 / Max: 73.57

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterTesseract OCR 4.0.0-beta.1Performance / Cost - Time To OCR 7 ImagesJetson NanoODROID-XU4Jetson AGX Xavier20K40K60K80K100K13134.3311200.9293450.061. Jetson Nano: $99 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson AGX Xavier: $1299 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 MappingJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier306090120150SE +/- 0.11, N = 3SE +/- 0.97, N = 9SE +/- 0.04, N = 3SE +/- 0.27, N = 9SE +/- 0.16, N = 3SE +/- 0.46, N = 4SE +/- 0.15, N = 3SE +/- 1.63, N = 1240.9441.9645.0921.2217.6628.8549.26133.001. (CXX) g++ options: -O3 -fomit-frame-pointer -ffast-math -mtune=native -flto -lSDL -fopenmp -fwhole-program -lstdc++
OpenBenchmarking.orgFPS, More Is BetterTTSIOD 3D Renderer 2.3bPhong Rendering With Soft-Shadow MappingJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier20406080100Min: 40.77 / Avg: 40.94 / Max: 41.15Min: 39.77 / Avg: 41.96 / Max: 49.13Min: 45.04 / Avg: 45.09 / Max: 45.16Min: 20.85 / Avg: 21.22 / Max: 23.35Min: 17.5 / Avg: 17.66 / Max: 17.98Min: 27.49 / Avg: 28.85 / Max: 29.39Min: 48.96 / Avg: 49.26 / Max: 49.42Min: 130.64 / Avg: 133.37 / Max: 150.981. (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 MappingJetson NanoODROID-XU4Jetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier0.1530.3060.4590.6120.7650.410.680.090.320.500.050.080.101. Jetson Nano: $99 reported cost.2. ODROID-XU4: $62 reported cost.3. Jetson TX1 Max-P: $499 reported cost.4. ASUS TinkerBoard: $66 reported cost.5. Raspberry Pi 3 Model B+: $35 reported cost.6. Jetson TX2 Max-Q: $599 reported cost.7. Jetson TX2 Max-P: $599 reported cost.8. Jetson AGX Xavier: $1299 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 19Jetson NanoJetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier110220330440550SE +/- 0.23, N = 3SE +/- 0.42, N = 3SE +/- 2.16, N = 3SE +/- 1.03, N = 3SE +/- 1.02, N = 3SE +/- 0.29, N = 3SE +/- 0.91, N = 3129.87145.80496.62342.23253.80144.9780.061. (CC) gcc options: -O3 -pthread -lz -llzma
OpenBenchmarking.orgSeconds, Fewer Is BetterZstd Compression 1.3.4Compressing ubuntu-16.04.3-server-i386.img, Compression Level 19Jetson NanoJetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier90180270360450Min: 129.55 / Avg: 129.87 / Max: 130.3Min: 144.97 / Avg: 145.8 / Max: 146.33Min: 493.98 / Avg: 496.62 / Max: 500.9Min: 340.32 / Avg: 342.23 / Max: 343.87Min: 252.57 / Avg: 253.8 / Max: 255.83Min: 144.4 / Avg: 144.97 / Max: 145.39Min: 78.26 / Avg: 80.06 / Max: 81.181. (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 19Jetson NanoJetson TX1 Max-PASUS TinkerBoardRaspberry Pi 3 Model B+Jetson TX2 Max-QJetson TX2 Max-PJetson AGX Xavier30K60K90K120K150K12857.1372754.2032776.9211978.05152026.2086837.03103997.941. Jetson Nano: $99 reported cost.2. Jetson TX1 Max-P: $499 reported cost.3. ASUS TinkerBoard: $66 reported cost.4. Raspberry Pi 3 Model B+: $35 reported cost.5. Jetson TX2 Max-Q: $599 reported cost.6. Jetson TX2 Max-P: $599 reported cost.7. Jetson AGX Xavier: $1299 reported cost.

76 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
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 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 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 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.

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.

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.

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.

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.