Jetson Nano Developer Kit

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  Test
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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 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 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 7.3.01920x1080OpenBenchmarking.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 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 ondemandPython 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 3.6.7Kernel 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-XU4Logarithmic Result OverviewPhoronix Test Suite7-Zip CompressionTTSIOD 3D RendererPyBenchFLAC Audio EncodingRust Prime BenchmarkC-Ray

Jetson Nano Developer Kitcuda-mini-nbody: Originalttsiod-renderer: Phong Rendering With Soft-Shadow Mappingtensorrt-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 - Disabledtensorrt-inference: VGG16 - FP16 - 4 - Disabledtensorrt-inference: VGG19 - FP16 - 4 - Disabledtensorrt-inference: VGG16 - INT8 - 4 - Disabledcompress-7zip: Compress Speed Testlczero: CUDA + cuDNNlczero: CUDA + cuDNN FP16lczero: BLASglmark2: 1920 x 1080pybench: Total For Average Test Timesc-ray: Total Time - 4K, 16 Rays Per Pixelrust-prime: Prime Number Test To 200,000,000compress-zstd: Compressing ubuntu-16.04.3-server-i386.img, Compression Level 19encode-flac: WAV To FLACopencv-bench: tesseract-ocr: Time To OCR 7 ImagesJetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU445.0945086339753128.45145.8079.206.7728.8511.4529.8315.7923.9412.5921614837423772.0139.1515688.8827.3414.5086.0847.1517910432.6717.3625.9921.0414.2432948735869170.25253.80104.284938.2449.2614.3236.8719.9129.8315.9226418446230192.2849.9719711335.1118.2911159.6923313041.9122.0732.6426.5617.5655935408585104.96144.9765.0729647.13133265.81247.95475.08203.96394.661200114320383143547.50902.787961146224.19372.736361215.0810061693259.82493.22208.76172.50303.78192129532515.0147.622876300735532.3780.0654.4712871.944.0740.9411884.1020112841.0420.9683.3747.8215.767.7646.5125.0898.9355.6617.3814.3511.59404914015.376467084921150.19129.87104.77271.04132.6717.6620132091320301097.69342.23339.532.7421.2228361150217181821.05496.62279.0541.9641205009827574.1197.03520.70180.66OpenBenchmarking.org

CUDA Mini-Nbody

OpenBenchmarking.org(NBody^2)/s Per Dollar, More Is BetterCUDA Mini-Nbody 2015-11-10Performance / Cost - Test: OriginalJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson Nano0.0090.0180.0270.0360.0450.010.010.040.041. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 reported cost.

OpenBenchmarking.org(NBody^2)/s, More Is BetterCUDA Mini-Nbody 2015-11-10Test: OriginalJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson Nano1122334455SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 36.778.2447.134.07

TTSIOD 3D Renderer

OpenBenchmarking.orgFPS Per Dollar, More Is BetterTTSIOD 3D Renderer 2.3bPerformance / Cost - Phong Rendering With Soft-Shadow MappingJetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU40.1530.3060.4590.6120.7650.090.050.080.100.410.500.320.681. Jetson TX1 Max-P: $499 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.5. Jetson Nano: $99 reported cost.6. Raspberry Pi 3 Model B+: $35 reported cost.7. ASUS TinkerBoard: $66 reported cost.8. ODROID-XU4: $62 reported cost.

OpenBenchmarking.orgFPS, More Is BetterTTSIOD 3D Renderer 2.3bPhong Rendering With Soft-Shadow MappingJetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU4306090120150SE +/- 0.04, N = 3SE +/- 0.46, N = 4SE +/- 0.15, N = 3SE +/- 1.63, N = 12SE +/- 0.11, N = 3SE +/- 0.16, N = 3SE +/- 0.27, N = 9SE +/- 0.97, N = 945.0928.8549.26133.0040.9417.6621.2241.961. (CXX) g++ options: -O3 -fomit-frame-pointer -ffast-math -mtune=native -flto -lSDL -fopenmp -fwhole-program -lstdc++

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: 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 AGX XavierJetson Nano30060090012001500SE +/- 3.03, N = 6SE +/- 7.77, N = 12SE +/- 1.82, N = 3SE +/- 2.12, N = 122162641200118

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 AGX XavierJetson Nano2004006008001000SE +/- 0.91, N = 3SE +/- 2.79, N = 5SE +/- 2.59, N = 3SE +/- 0.72, N = 3148.00184.001143.0084.10

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 AGX XavierJetson Nano400800120016002000SE +/- 2.82, N = 3SE +/- 7.68, N = 12SE +/- 2.07, N = 3SE +/- 1.59, N = 33744622038201

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 AGX XavierJetson Nano7001400210028003500SE +/- 1.39, N = 3SE +/- 0.52, N = 3SE +/- 1.06, N = 3SE +/- 0.06, N = 32373013143128

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 AGX XavierJetson Nano120240360480600SE +/- 1.10, N = 12SE +/- 1.32, N = 12SE +/- 0.03, N = 3SE +/- 0.25, N = 372.0192.28547.5041.04

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 AGX XavierJetson Nano2004006008001000SE +/- 0.64, N = 3SE +/- 0.79, N = 4SE +/- 1.86, N = 3SE +/- 0.36, N = 339.1549.97902.7820.96

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 AGX XavierJetson Nano2004006008001000SE +/- 1.90, N = 12SE +/- 2.27, N = 3SE +/- 2.48, N = 3SE +/- 0.70, N = 3156.00197.00796.0083.37

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 AGX XavierJetson Nano2004006008001000SE +/- 1.32, N = 3SE +/- 1.65, N = 3SE +/- 4.31, N = 3SE +/- 0.60, N = 388.88113.001146.0047.82

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 AGX XavierJetson Nano50100150200250SE +/- 0.34, N = 3SE +/- 0.36, N = 3SE +/- 0.22, N = 3SE +/- 0.04, N = 327.3435.11224.1915.76

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 AGX XavierJetson Nano80160240320400SE +/- 0.15, N = 3SE +/- 0.14, N = 3SE +/- 1.59, N = 3SE +/- 0.03, N = 314.5018.29372.737.76

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 AGX XavierJetson Nano140280420560700SE +/- 0.86, N = 3SE +/- 1.22, N = 3SE +/- 1.23, N = 3SE +/- 0.02, N = 386.08111.00636.0046.51

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 AGX XavierJetson Nano30060090012001500SE +/- 0.08, N = 3SE +/- 0.04, N = 3SE +/- 0.25, N = 3SE +/- 0.06, N = 347.1559.691215.0825.08

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 AGX XavierJetson Nano2004006008001000SE +/- 2.17, N = 8SE +/- 4.50, N = 3SE +/- 0.21, N = 3SE +/- 0.19, N = 3179.00233.001006.0098.93

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 AGX XavierJetson Nano400800120016002000SE +/- 0.07, N = 3SE +/- 0.74, N = 3SE +/- 8.72, N = 3SE +/- 0.18, N = 3104.00130.001693.0055.66

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 AGX XavierJetson Nano60120180240300SE +/- 0.10, N = 3SE +/- 0.07, N = 3SE +/- 0.26, N = 3SE +/- 0.01, N = 332.6741.91259.8217.38

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 AGX XavierJetson Nano0.0360.0720.1080.1440.180.040.050.160.141. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 reported cost.

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: 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 AGX XavierJetson Nano0.02930.05860.08790.11720.14650.040.040.130.121. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson Nano50100150200250SE +/- 0.13, N = 3SE +/- 0.50, N = 4SE +/- 0.10, N = 3SE +/- 0.02, N = 225.9932.64208.7614.35

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 AGX XavierJetson Nano0.26780.53560.80341.07121.3390.360.440.921.191. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.1980.3960.5940.7920.990.250.310.880.851. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.45680.91361.37041.82722.2840.620.771.572.031. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.54451.0891.63352.1782.72250.400.502.421.291. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 reported cost.

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 AGX XavierJetson Nano4080120160200SE +/- 0.34, N = 3SE +/- 0.38, N = 3SE +/- 0.50, N = 3SE +/- 0.05, N = 221.0426.56172.5011.59

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: ResNet50 - Precision: FP16 - Batch Size: 4 - DLA Cores: DisabledJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson Nano0.09450.1890.28350.3780.47250.120.150.420.411. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.15530.31060.46590.62120.77650.070.080.690.211. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.1890.3780.5670.7560.9450.260.330.610.841. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.1980.3960.5940.7920.990.150.190.880.481. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.03830.07660.11490.15320.19150.050.060.170.161. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.06530.13060.19590.26120.32650.020.030.290.081. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.11030.22060.33090.44120.55150.140.190.490.471. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.21150.4230.63450.8461.05750.080.100.940.251. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.2250.450.6750.91.1250.300.390.771.001. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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 AGX XavierJetson Nano0.29250.5850.87751.171.46250.170.221.300.561. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 reported cost.

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 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 AGX XavierJetson Nano0.0450.090.1350.180.2250.050.070.200.181. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 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.

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 TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU44K8K12K16K20KSE +/- 13.43, N = 3SE +/- 13.05, N = 3SE +/- 20.85, N = 3SE +/- 274.18, N = 12SE +/- 18.00, N = 3SE +/- 23.74, N = 11SE +/- 34.93, N = 3SE +/- 89.16, N = 124508329455931921240492013283641201. (CXX) g++ options: -pipe -lpthread

OpenBenchmarking.orgMIPS Per Dollar, More Is Better7-Zip Compression 16.02Performance / Cost - Compress Speed TestJetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU415304560759.035.509.3414.7940.9057.5142.9766.451. Jetson TX1 Max-P: $499 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.5. Jetson Nano: $99 reported cost.6. Raspberry Pi 3 Model B+: $35 reported cost.7. ASUS TinkerBoard: $66 reported cost.8. ODROID-XU4: $62 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: CUDA + cuDNNJetson AGX XavierJetson Nano2004006008001000SE +/- 6.14, N = 3SE +/- 0.26, N = 39531401. (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 AGX XavierJetson Nano0.0360.0720.1080.1440.180.040.161. Jetson AGX Xavier: $1299 reported cost.2. Jetson Nano: $99 reported cost.

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.20.1Backend: BLASJetson AGX XavierJetson Nano1122334455SE +/- 0.62, N = 7SE +/- 0.03, N = 347.6215.371. (CXX) g++ options: -lpthread -lz

OpenBenchmarking.orgNodes Per Second Per Dollar, More Is BetterLeelaChessZero 0.20.1Performance / Cost - Backend: CUDA + cuDNNJetson AGX XavierJetson Nano0.31730.63460.95191.26921.58650.731.411. Jetson AGX Xavier: $1299 reported cost.2. Jetson Nano: $99 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.

GLmark2

OpenBenchmarking.orgScore Per Dollar, More Is BetterGLmark2Performance / Cost - Resolution: 1920 x 1080Jetson AGX XavierJetson Nano2468102.216.531. Jetson AGX Xavier: $1299 reported cost.2. Jetson Nano: $99 reported cost.

OpenBenchmarking.orgScore, More Is BetterGLmark2Resolution: 1920 x 1080Jetson AGX XavierJetson Nano60012001800240030002876646

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 TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU44K8K12K16K20KSE +/- 18.55, N = 3SE +/- 42.52, N = 3SE +/- 33.86, N = 3SE +/- 4.67, N = 3SE +/- 37.23, N = 3SE +/- 43.80, N = 3SE +/- 854.75, N = 9SE +/- 30.99, N = 36339873554083007708420913115025009

OpenBenchmarking.orgMilliseconds x Dollar, Fewer Is BetterPyBench 2018-02-16Performance / Cost - Total For Average Test TimesJetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU41.1M2.2M3.3M4.4M5.5M3163161.005232265.003239392.003906093.00701316.00731955.00759132.00310558.001. Jetson TX1 Max-P: $499 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.5. Jetson Nano: $99 reported cost.6. Raspberry Pi 3 Model B+: $35 reported cost.7. ASUS TinkerBoard: $66 reported cost.8. ODROID-XU4: $62 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 TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU4400800120016002000SE +/- 10.23, N = 3SE +/- 1.44, N = 3SE +/- 49.09, N = 9SE +/- 7.17, N = 9SE +/- 0.35, N = 3SE +/- 2.46, N = 3SE +/- 22.09, N = 3SE +/- 29.65, N = 9753869585355921203017188271. (CC) gcc options: -lm -lpthread -O3

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 TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU4400800120016002000SE +/- 0.77, N = 3SE +/- 0.09, N = 3SE +/- 0.04, N = 3SE +/- 0.00, N = 3SE +/- 0.22, N = 3SE +/- 1.55, N = 3SE +/- 187.90, N = 6SE +/- 0.37, N = 3128.45170.25104.9632.37150.191097.691821.05574.11-ldl -lrt -lpthread -lgcc_s -lc -lm -lutil1. (CC) gcc options: -pie -nodefaultlibs

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 TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoard110220330440550SE +/- 0.42, N = 3SE +/- 1.02, N = 3SE +/- 0.29, N = 3SE +/- 0.91, N = 3SE +/- 0.23, N = 3SE +/- 1.03, N = 3SE +/- 2.16, N = 3145.80253.80144.9780.06129.87342.23496.621. (CC) gcc options: -O3 -pthread -lz -llzma

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 TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU470140210280350SE +/- 0.74, N = 5SE +/- 0.18, N = 5SE +/- 0.15, N = 5SE +/- 0.61, N = 5SE +/- 0.83, N = 5SE +/- 0.98, N = 5SE +/- 2.51, N = 5SE +/- 0.31, N = 579.20104.2865.0754.47104.77339.53279.0597.031. (CXX) g++ options: -O2 -fvisibility=hidden -logg -lm

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 TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ODROID-XU4110220330440550SE +/- 5.74, N = 3SE +/- 0.27, N = 3SE +/- 1.57, N = 3SE +/- 4.66, N = 9SE +/- 5.31, N = 3493.00296.00128.00271.042.74520.701. (CXX) g++ options: -std=c++11 -rdynamic

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 AGX XavierJetson NanoODROID-XU44080120160200SE +/- 0.89, N = 3SE +/- 1.50, N = 3SE +/- 1.38, N = 371.94132.67180.66

C-Ray

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterC-Ray 1.1Performance / Cost - Total Time - 4K, 16 Rays Per PixelJetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU4110K220K330K440K550K375747.00520531.00350415.00461145.0091179.0071050.00113388.0051274.001. Jetson TX1 Max-P: $499 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.5. Jetson Nano: $99 reported cost.6. Raspberry Pi 3 Model B+: $35 reported cost.7. ASUS TinkerBoard: $66 reported cost.8. ODROID-XU4: $62 reported cost.

Rust Prime Benchmark

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterRust Prime BenchmarkPerformance / Cost - Prime Number Test To 200,000,000Jetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU430K60K90K120K150K64096.55101979.7562871.0442048.6314868.8138419.15120189.3035594.821. Jetson TX1 Max-P: $499 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.5. Jetson Nano: $99 reported cost.6. Raspberry Pi 3 Model B+: $35 reported cost.7. ASUS TinkerBoard: $66 reported cost.8. ODROID-XU4: $62 reported cost.

Zstd Compression

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterZstd Compression 1.3.4Performance / Cost - 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 TinkerBoard30K60K90K120K150K72754.20152026.2086837.03103997.9412857.1311978.0532776.921. Jetson TX1 Max-P: $499 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.5. Jetson Nano: $99 reported cost.6. Raspberry Pi 3 Model B+: $35 reported cost.7. ASUS TinkerBoard: $66 reported cost.

FLAC Audio Encoding

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterFLAC Audio Encoding 1.3.2Performance / Cost - WAV To FLACJetson TX1 Max-PJetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ASUS TinkerBoardODROID-XU415K30K45K60K75K39520.8062463.7238976.9370756.5310372.2311883.5518417.306015.861. Jetson TX1 Max-P: $499 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.5. Jetson Nano: $99 reported cost.6. Raspberry Pi 3 Model B+: $35 reported cost.7. ASUS TinkerBoard: $66 reported cost.8. ODROID-XU4: $62 reported cost.

OpenCV Benchmark

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterOpenCV Benchmark 3.3.0Performance / Cost -Jetson TX2 Max-QJetson TX2 Max-PJetson AGX XavierJetson NanoRaspberry Pi 3 Model B+ODROID-XU460K120K180K240K300K295307.00177304.00166272.0026832.9695.9032283.401. Jetson TX2 Max-Q: $599 reported cost.2. Jetson TX2 Max-P: $599 reported cost.3. Jetson AGX Xavier: $1299 reported cost.4. Jetson Nano: $99 reported cost.5. Raspberry Pi 3 Model B+: $35 reported cost.6. ODROID-XU4: $62 reported cost.

Tesseract OCR

OpenBenchmarking.orgSeconds x Dollar, Fewer Is BetterTesseract OCR 4.0.0-beta.1Performance / Cost - Time To OCR 7 ImagesJetson AGX XavierJetson NanoODROID-XU420K40K60K80K100K93450.0613134.3311200.921. Jetson AGX Xavier: $1299 reported cost.2. Jetson Nano: $99 reported cost.3. ODROID-XU4: $62 reported cost.

76 Results Shown

CUDA Mini-Nbody
CUDA Mini-Nbody
TTSIOD 3D Renderer
TTSIOD 3D Renderer
NVIDIA TensorRT Inference:
  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
NVIDIA TensorRT Inference
NVIDIA TensorRT Inference
NVIDIA TensorRT Inference:
  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
NVIDIA TensorRT Inference
NVIDIA TensorRT Inference:
  Performance / Cost - AlexNet - FP16 - 4 - Disabled
  Performance / Cost - AlexNet - INT8 - 4 - Disabled
  Performance / Cost - AlexNet - FP16 - 32 - Disabled
  Performance / Cost - AlexNet - INT8 - 32 - Disabled
NVIDIA TensorRT Inference
NVIDIA TensorRT Inference:
  Performance / Cost - VGG19 - 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
NVIDIA TensorRT Inference
NVIDIA TensorRT Inference:
  Performance / Cost - ResNet152 - FP16 - 32 - Disabled
  Performance / Cost - ResNet152 - INT8 - 32 - Disabled
7-Zip Compression
7-Zip Compression
LeelaChessZero:
  CUDA + cuDNN
  CUDA + cuDNN FP16
LeelaChessZero
LeelaChessZero
LeelaChessZero:
  Performance / Cost - CUDA + cuDNN
  Performance / Cost - CUDA + cuDNN FP16
  Performance / Cost - 1920 x 1080
GLmark2
PyBench
PyBench
C-Ray
Rust Prime Benchmark
Zstd Compression
FLAC Audio Encoding
OpenCV Benchmark
Tesseract OCR
C-Ray:
  Performance / Cost - Total Time - 4K, 16 Rays Per Pixel
  Performance / Cost - Prime Number Test To 200,000,000
  Performance / Cost - Compressing ubuntu-16.04.3-server-i386.img, Compression Level 19
  Performance / Cost - WAV To FLAC
  Performance / Cost -
  Performance / Cost - Time To OCR 7 Images