RTX 4070 SUPER

Intel Core i9-13900K testing with a ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS) and NVIDIA GeForce RTX 4070 Ti 12GB on EndeavourOS rolling via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2402070-SADD-240129900
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NVIDIA RTX 4070 SUPER
January 25
  23 Hours, 51 Minutes
NVIDIA RTX 4070
January 28
  22 Hours, 26 Minutes
NVIDIA RTX 4070 TI
January 29
  1 Day, 7 Hours, 18 Minutes
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RTX 4070 SUPERProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLCompilerFile-SystemScreen ResolutionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TIIntel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads)ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS)Intel Device 7a2732GB4001GB Seagate ZP4000GP304001ASUS NVIDIA GeForce RTX 4070 SUPER 12GBRealtek ALC1220ARZOPAIntel I226-V + Intel Device 7a70EndeavourOS rolling6.7.1-arch1-1 (x86_64)KDE Plasma 5.27.10X Server 1.21.1.11NVIDIA 550.40.074.6.0OpenCL 3.0 CUDA 12.4.74GCC 13.2.1 20230801ext41920x1080MSI NVIDIA GeForce RTX 4070 12GBGCC 13.2.1 20230801 + CUDA 12.3NVIDIA GeForce RTX 4070 Ti 12GBOpenBenchmarking.orgKernel Details- Transparent Huge Pages: alwaysCompiler Details- --disable-libssp --disable-libstdcxx-pch --disable-werror --enable-__cxa_atexit --enable-bootstrap --enable-cet=auto --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-default-ssp --enable-gnu-indirect-function --enable-gnu-unique-object --enable-languages=ada,c,c++,d,fortran,go,lto,objc,obj-c++ --enable-libstdcxx-backtrace --enable-link-serialization=1 --enable-lto --enable-multilib --enable-plugin --enable-shared --enable-threads=posix --mandir=/usr/share/man --with-build-config=bootstrap-lto --with-linker-hash-style=gnu Processor Details- Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0x11dGraphics Details- NVIDIA RTX 4070 SUPER: BAR1 / Visible vRAM Size: 16384 MiB - vBIOS Version: 95.04.69.00.c1- NVIDIA RTX 4070: BAR1 / Visible vRAM Size: 16384 MiB - vBIOS Version: 95.04.3e.40.2a- NVIDIA RTX 4070 TI: BAR1 / Visible vRAM Size: 16384 MiB - vBIOS Version: 95.04.31.00.36Security Details- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced / Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected Environment Details- NVIDIA RTX 4070, NVIDIA RTX 4070 TI: NVCC_PREPEND_FLAGS="-ccbin /opt/cuda/bin"Python Details- NVIDIA RTX 4070, NVIDIA RTX 4070 TI: Python 3.11.6

NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TIResult OverviewPhoronix Test Suite100%119%137%156%174%NCNNFinanceBenchHashcatGpuOwlRodiniaclpeakRealSR-NCNNTensorFlowProjectPhysX OpenCL-BenchmarkFAHBenchMandelGPULuxCoreRenderBlenderOctaneBenchVkResampleLibplaceboWaifu2x-NCNN VulkanIndigoBenchNAMD CUDAPyTorchVkFFTViennaCLcl-memNeatBench

RTX 4070 SUPERclpeak: Integer Compute INTclpeak: Single-Precision Floathashcat: MD5hashcat: TrueCrypt RIPEMD160 + XTSopencl-benchmark: INT8 Computehashcat: SHA-512gpuowl: 332220523clpeak: Double-Precision Doubleopencl-benchmark: FP64 Computehashcat: SHA1hashcat: 7-Zipviennacl: OpenCL BLAS - dGEMM-TTvkresample: 2x - Doubleopencl-benchmark: FP32 Computegpuowl: 57885161opencl-benchmark: INT32 Computeopencl-benchmark: INT64 Computeviennacl: OpenCL BLAS - dGEMM-TNviennacl: OpenCL BLAS - dGEMM-NTopencl-benchmark: INT16 Computeviennacl: OpenCL BLAS - dGEMM-NNgpuowl: 77936867realsr-ncnn: 4x - Yeslibplacebo: deband_heavylibplacebo: polar_nocomputerodinia: OpenCL Particle Filterluxcorerender: Danish Mood - GPUblender: Fishy Cat - NVIDIA OptiXluxcorerender: LuxCore Benchmark - GPUblender: Classroom - NVIDIA OptiXfahbench: mandelgpu: GPUvkfft: FFT + iFFT C2C Bluestein benchmark in double precisionluxcorerender: Rainbow Colors and Prism - GPUluxcorerender: DLSC - GPUblender: Pabellon Barcelona - NVIDIA OptiXvkfft: FFT + iFFT R2C / C2Rblender: Barbershop - NVIDIA OptiXblender: BMW27 - NVIDIA OptiXluxcorerender: Orange Juice - GPUvkfft: FFT + iFFT C2C 1D batched in double precisionoctanebench: Total Scoreindigobench: OpenCL GPU - Bedroompytorch: NVIDIA CUDA GPU - 16 - ResNet-50waifu2x-ncnn: 2x - 3 - Yespytorch: NVIDIA CUDA GPU - 64 - ResNet-50vkfft: FFT + iFFT C2C Bluestein in single precisionnamd-cuda: ATPase Simulation - 327,506 Atomsindigobench: OpenCL GPU - Supercarpytorch: NVIDIA CUDA GPU - 32 - ResNet-50pytorch: NVIDIA CUDA GPU - 512 - ResNet-50pytorch: NVIDIA CUDA GPU - 256 - ResNet-50vkfft: FFT + iFFT C2C multidimensional in single precisionviennacl: CPU BLAS - dGEMM-TNlibplacebo: hdr_peakdetecttensorflow: GPU - 1 - AlexNetpytorch: NVIDIA CUDA GPU - 32 - ResNet-152pytorch: NVIDIA CUDA GPU - 64 - ResNet-152vkfft: FFT + iFFT C2C 1D batched in single precision, no reshufflingvkfft: FFT + iFFT C2C 1D batched in single precisionviennacl: CPU BLAS - dGEMM-TTvkfft: FFT + iFFT C2C 1D batched in half precisionpytorch: NVIDIA CUDA GPU - 256 - ResNet-152pytorch: NVIDIA CUDA GPU - 16 - ResNet-152viennacl: CPU BLAS - dGEMM-NTviennacl: CPU BLAS - dGEMM-NNpytorch: NVIDIA CUDA GPU - 512 - ResNet-152viennacl: OpenCL BLAS - dAXPYvkresample: 2x - Singletensorflow: GPU - 1 - VGG-16viennacl: OpenCL BLAS - sDOTpytorch: NVIDIA CUDA GPU - 512 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 1 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 256 - Efficientnet_v2_lviennacl: CPU BLAS - sAXPYpytorch: NVIDIA CUDA GPU - 1 - ResNet-152viennacl: OpenCL BLAS - sCOPYviennacl: CPU BLAS - sDOTlibplacebo: hdr_lutlibplacebo: av1_grain_lappytorch: NVIDIA CUDA GPU - 64 - Efficientnet_v2_lcl-mem: Writetensorflow: GPU - 16 - VGG-16tensorflow: GPU - 1 - GoogLeNettensorflow: GPU - 256 - AlexNettensorflow: GPU - 32 - GoogLeNetviennacl: OpenCL BLAS - dGEMV-Tviennacl: OpenCL BLAS - sAXPYviennacl: CPU BLAS - dGEMV-Nopencl-benchmark: Memory Bandwidth Coalesced Writetensorflow: GPU - 512 - AlexNetviennacl: OpenCL BLAS - dGEMV-Ntensorflow: GPU - 32 - ResNet-50cl-mem: Copytensorflow: GPU - 16 - AlexNetviennacl: CPU BLAS - sCOPYviennacl: CPU BLAS - dCOPYtensorflow: GPU - 1 - ResNet-50viennacl: CPU BLAS - dAXPYtensorflow: GPU - 16 - ResNet-50viennacl: OpenCL BLAS - dDOTviennacl: CPU BLAS - dDOTtensorflow: GPU - 64 - AlexNettensorflow: GPU - 64 - ResNet-50tensorflow: GPU - 32 - AlexNettensorflow: GPU - 64 - GoogLeNetviennacl: OpenCL BLAS - dCOPYpytorch: NVIDIA CUDA GPU - 16 - Efficientnet_v2_ltensorflow: GPU - 16 - GoogLeNetclpeak: Global Memory Bandwidthopencl-benchmark: Memory Bandwidth Coalesced Readcl-mem: Readtensorflow: GPU - 256 - VGG-16tensorflow: GPU - 64 - VGG-16tensorflow: GPU - 32 - VGG-16neatbench: GPUncnn: Vulkan GPU - FastestDetncnn: Vulkan GPU - vision_transformerncnn: Vulkan GPU - regnety_400mncnn: Vulkan GPU - squeezenet_ssdncnn: Vulkan GPU - yolov4-tinyncnn: Vulkan GPU - resnet50ncnn: Vulkan GPU - alexnetncnn: Vulkan GPU - resnet18ncnn: Vulkan GPU - vgg16ncnn: Vulkan GPU - googlenetncnn: Vulkan GPU - blazefacencnn: Vulkan GPU - efficientnet-b0ncnn: Vulkan GPU - mnasnetncnn: Vulkan GPU - shufflenet-v2ncnn: Vulkan GPU-v3-v3 - mobilenet-v3ncnn: Vulkan GPU-v2-v2 - mobilenet-v2ncnn: Vulkan GPU - mobilenetviennacl: CPU BLAS - dGEMV-Tfinancebench: Black-Scholes OpenCLrealsr-ncnn: 4x - Nopytorch: NVIDIA CUDA GPU - 32 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 1 - ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI18170.5435492.696758303333380296714.3073232733333137.44630.110.621221326000001176467613339.59338.594869.0719.8894.21459958417.170577646.4134.8852186.702327.553.48010.569.4512.8212.60366.0576587219538.2445127.6713.5914.295479451.305.5711.7224317720.97378919.801509.452.855507.45151660.0679152.813501.50504.27504.67502991153292.3713.92195.39196.077507873929122131705194.58195.40117119195.3043718.4891.35370103.57106.37103.17156201.943341653905.984171.00102.60407.51.4812.6234.1615.61389392102455.0135.102105.51331.831.5913270.84.3587.25.4645896.833.975.5533.415.5242315.67437.65464.86446.21.5040702.86844.6111.116.8663.8246.2616.178.97117.8111.040.845.073.852.312.253.038.621095.9126.323102.60557.7314555.1928479.395614786666766096712.1162673300000112.61515.170.51018202466667976967502415.16031.768714.8016.3773.44349447714.284473530.3242.8521847.981972.784.0988.8911.0310.9214.86317.1952516770131.2388623.2611.7416.554709758.446.2110.4022390647.99786718.203458.393.168458.36137140.0749848.517459.94459.27459.93472121213310.0214.04187.69186.637905777774118137762187.27187.26122122187.5145518.0161.36362101.43107.59101.24153198.183301663927.114103.40101.55406.71.5012.7815.63387389103459.4335.212095.55330.331.4513171.04.3486.85.4945696.733.935.5533.3215.54423103.6815.66437.21465.18446.31.501.540702.34281.566.505.2725.118.249.338.5854.546.060.843.462.222.118.714.6910.141096.9067.092102.90546.7619821.1038691.737331223333385860015.7313462500000145.84667.050.660235324000001262633648322.06440.914919.1321.0474.42063461218.281604676.5933.6262306.672461.233.29110.999.0213.2312.30382.1637619106132.5464727.7113.9513.975544650.735.4311.8925431735.94059320.256502.922.854505.62151250.0678853.589505.55504.66515281253544.6014.79198.82197.027514173942124136210195.86194.29118117194.8743718.4561.38365103.50108.59103.24156201.193361683971.614140.87103.20412.21.4912.7934.6115.81391393103457.1735.442115.50333.331.7013271.34.3287.35.4645796.434.065.5333.2915.50424103.4515.69437.63465.07446.31.51.51.540702.84390.185.975.3616.4714.323.745.4732.055.870.813.492.302.032.092.438.43102.75.2265.96296.50535.39OpenBenchmarking.org

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGIOPS, More Is Betterclpeak 1.1.2OpenCL Test: Integer Compute INTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI4K8K12K16K20KSE +/- 3.14, N = 3SE +/- 15.26, N = 3SE +/- 2.50, N = 318170.5414555.1919821.101. (CXX) g++ options: -O3

OpenBenchmarking.orgGFLOPS, More Is Betterclpeak 1.1.2OpenCL Test: Single-Precision FloatNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI8K16K24K32K40KSE +/- 0.99, N = 3SE +/- 5.46, N = 3SE +/- 11.67, N = 335492.6928479.3938691.731. (CXX) g++ options: -O3

Hashcat

Hashcat is an open-source, advanced password recovery tool supporting GPU acceleration with OpenCL, NVIDIA CUDA, and Radeon ROCm. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: MD5NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI16000M32000M48000M64000M80000MSE +/- 22430807.19, N = 3SE +/- 33772046.30, N = 3SE +/- 11283665.68, N = 3675830333335614786666773312233333

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: TrueCrypt RIPEMD160 + XTSNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI200K400K600K800K1000KSE +/- 633.33, N = 3SE +/- 176.38, N = 3SE +/- 888.82, N = 3802967660967858600

ProjectPhysX OpenCL-Benchmark

ProjectPhysX OpenCL-Benchmark provides various OpenCL compute and memory bandwidth micro-benchmarks Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTIOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: INT8 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI48121620SE +/- 0.05, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 314.3112.1215.731. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

Hashcat

Hashcat is an open-source, advanced password recovery tool supporting GPU acceleration with OpenCL, NVIDIA CUDA, and Radeon ROCm. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: SHA-512NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI700M1400M2100M2800M3500MSE +/- 1530068.99, N = 3SE +/- 1059874.21, N = 3SE +/- 721110.26, N = 3323273333326733000003462500000

GpuOwl

GpuOwl is a Mersenne primality tester leveraging OpenCL for cross-vendor GPU acceleration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations / Second, More Is BetterGpuOwl 7.2.1Exponent: 332220523NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI306090120150SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3137.44112.61145.84

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is Betterclpeak 1.1.2OpenCL Test: Double-Precision DoubleNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI140280420560700SE +/- 0.98, N = 3SE +/- 0.21, N = 3SE +/- 1.33, N = 3630.11515.17667.051. (CXX) g++ options: -O3

ProjectPhysX OpenCL-Benchmark

ProjectPhysX OpenCL-Benchmark provides various OpenCL compute and memory bandwidth micro-benchmarks Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTFLOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: FP64 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI0.14850.2970.44550.5940.7425SE +/- 0.000, N = 3SE +/- 0.001, N = 3SE +/- 0.001, N = 30.6210.5100.6601. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

Hashcat

Hashcat is an open-source, advanced password recovery tool supporting GPU acceleration with OpenCL, NVIDIA CUDA, and Radeon ROCm. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: SHA1NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI5000M10000M15000M20000M25000MSE +/- 5140363.15, N = 3SE +/- 6318315.53, N = 3SE +/- 15926811.78, N = 3221326000001820246666723532400000

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: 7-ZipNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI300K600K900K1200K1500KSE +/- 1991.93, N = 3SE +/- 2062.63, N = 3SE +/- 2339.04, N = 311764679769671262633

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-TTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI140280420560700SE +/- 0.00, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 36135026481. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

VkResample

VkResample is a Vulkan-based image upscaling library based on VkFFT. The sample input file is upscaling a 4K image to 8K using Vulkan-based GPU acceleration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterVkResample 1.0Upscale: 2x - Precision: DoubleNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI90180270360450SE +/- 0.30, N = 3SE +/- 0.77, N = 3SE +/- 0.35, N = 3339.59415.16322.061. (CXX) g++ options: -O3

ProjectPhysX OpenCL-Benchmark

ProjectPhysX OpenCL-Benchmark provides various OpenCL compute and memory bandwidth micro-benchmarks Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTFLOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: FP32 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI918273645SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 338.5931.7740.911. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

GpuOwl

GpuOwl is a Mersenne primality tester leveraging OpenCL for cross-vendor GPU acceleration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations / Second, More Is BetterGpuOwl 7.2.1Exponent: 57885161NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI2004006008001000SE +/- 1.26, N = 3SE +/- 0.00, N = 3SE +/- 2.53, N = 3869.07714.80919.13

ProjectPhysX OpenCL-Benchmark

ProjectPhysX OpenCL-Benchmark provides various OpenCL compute and memory bandwidth micro-benchmarks Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTIOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: INT32 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI510152025SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 319.8916.3821.051. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

OpenBenchmarking.orgTIOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: INT64 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI0.99451.9892.98353.9784.9725SE +/- 0.015, N = 3SE +/- 0.004, N = 3SE +/- 0.016, N = 34.2143.4434.4201. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-TNNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI140280420560700SE +/- 0.00, N = 3SE +/- 0.33, N = 3SE +/- 0.67, N = 35994946341. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-NTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI130260390520650SE +/- 0.00, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 35844776121. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

ProjectPhysX OpenCL-Benchmark

ProjectPhysX OpenCL-Benchmark provides various OpenCL compute and memory bandwidth micro-benchmarks Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTIOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: INT16 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI48121620SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 317.1714.2818.281. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-NNNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI130260390520650SE +/- 0.00, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 35774736041. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

GpuOwl

GpuOwl is a Mersenne primality tester leveraging OpenCL for cross-vendor GPU acceleration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations / Second, More Is BetterGpuOwl 7.2.1Exponent: 77936867NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI150300450600750SE +/- 0.00, N = 3SE +/- 0.09, N = 3SE +/- 0.00, N = 3646.41530.32676.59

RealSR-NCNN

RealSR-NCNN is an NCNN neural network implementation of the RealSR project and accelerated using the Vulkan API. RealSR is the Real-World Super Resolution via Kernel Estimation and Noise Injection. NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. This test profile times how long it takes to increase the resolution of a sample image by a scale of 4x with Vulkan. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRealSR-NCNN 20200818Scale: 4x - TAA: YesNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI1020304050SE +/- 0.02, N = 3SE +/- 0.23, N = 3SE +/- 0.03, N = 334.8942.8533.63

Libplacebo

Libplacebo is a multimedia rendering library based on the core rendering code of the MPV player. The libplacebo benchmark relies on the Vulkan API and tests various primitives. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterLibplacebo 5.229.1Test: deband_heavyNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER5001000150020002500SE +/- 0.15, N = 3SE +/- 0.40, N = 3SE +/- 2.26, N = 31844.082306.562186.701. (CXX) g++ options: -lm -pthread -ldl -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -MD -MQ -MF

OpenBenchmarking.orgFPS, More Is BetterLibplacebo 5.229.1Test: polar_nocomputeNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER5001000150020002500SE +/- 0.29, N = 3SE +/- 1.70, N = 3SE +/- 0.24, N = 31969.192459.032327.551. (CXX) g++ options: -lm -pthread -ldl -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -MD -MQ -MF

Rodinia

Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes select OpenCL, NVIDIA CUDA and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenCL Particle FilterNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI0.92211.84422.76633.68844.6105SE +/- 0.039, N = 4SE +/- 0.008, N = 3SE +/- 0.002, N = 33.4804.0983.2911. (CXX) g++ options: -O2 -lOpenCL

LuxCoreRender

LuxCoreRender is an open-source 3D physically based renderer formerly known as LuxRender. LuxCoreRender supports CPU-based rendering as well as GPU acceleration via OpenCL, NVIDIA CUDA, and NVIDIA OptiX interfaces. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: Danish Mood - Acceleration: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI3691215SE +/- 0.08, N = 3SE +/- 0.06, N = 3SE +/- 0.11, N = 310.568.8910.99MIN: 3.7 / MAX: 12.17MIN: 3.32 / MAX: 10.26MIN: 4.17 / MAX: 12.71

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Fishy Cat - Compute: NVIDIA OptiXNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI3691215SE +/- 0.06, N = 13SE +/- 0.03, N = 3SE +/- 0.01, N = 39.4511.039.02

LuxCoreRender

LuxCoreRender is an open-source 3D physically based renderer formerly known as LuxRender. LuxCoreRender supports CPU-based rendering as well as GPU acceleration via OpenCL, NVIDIA CUDA, and NVIDIA OptiX interfaces. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: LuxCore Benchmark - Acceleration: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI3691215SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 312.8210.9213.23MIN: 4.84 / MAX: 14.62MIN: 4.45 / MAX: 12.42MIN: 5.41 / MAX: 15.13

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Classroom - Compute: NVIDIA OptiXNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI48121620SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 312.6014.8612.30

FAHBench

FAHBench is a Folding@Home benchmark on the GPU. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNs Per Day, More Is BetterFAHBench 2.3.2NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI80160240320400SE +/- 0.39, N = 3SE +/- 0.12, N = 3SE +/- 0.26, N = 3366.06317.20382.16

MandelGPU

MandelGPU is an OpenCL benchmark and this test runs with the OpenCL rendering float4 kernel with a maximum of 4096 iterations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSamples/sec, More Is BetterMandelGPU 1.3pts1OpenCL Device: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI130M260M390M520M650MSE +/- 467034.80, N = 3SE +/- 1783157.89, N = 3SE +/- 1202791.77, N = 3587219538.2516770131.2619106132.51. (CC) gcc options: -O3 -lm -ftree-vectorize -funroll-loops -lglut -lOpenCL -lGL

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C Bluestein benchmark in double precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI10002000300040005000SE +/- 12.55, N = 3SE +/- 4.51, N = 3SE +/- 11.35, N = 34451388646471. (CXX) g++ options: -O3 -lrt

LuxCoreRender

LuxCoreRender is an open-source 3D physically based renderer formerly known as LuxRender. LuxCoreRender supports CPU-based rendering as well as GPU acceleration via OpenCL, NVIDIA CUDA, and NVIDIA OptiX interfaces. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: Rainbow Colors and Prism - Acceleration: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI714212835SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 327.6723.2627.71MIN: 24.87 / MAX: 29.03MIN: 20.92 / MAX: 24.3MIN: 25.01 / MAX: 29.15

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: DLSC - Acceleration: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI48121620SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 313.5911.7413.95MIN: 12.52 / MAX: 13.84MIN: 11.35 / MAX: 11.83MIN: 13.67 / MAX: 14.14

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Pabellon Barcelona - Compute: NVIDIA OptiXNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI48121620SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 314.2916.5513.97

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT R2C / C2RNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI12K24K36K48K60KSE +/- 702.53, N = 15SE +/- 745.02, N = 13SE +/- 520.37, N = 35479447097554461. (CXX) g++ options: -O3 -lrt

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Barbershop - Compute: NVIDIA OptiXNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI1326395265SE +/- 0.10, N = 3SE +/- 0.04, N = 3SE +/- 0.05, N = 351.3058.4450.73

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: BMW27 - Compute: NVIDIA OptiXNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI246810SE +/- 0.06, N = 13SE +/- 0.01, N = 3SE +/- 0.02, N = 35.576.215.43

LuxCoreRender

LuxCoreRender is an open-source 3D physically based renderer formerly known as LuxRender. LuxCoreRender supports CPU-based rendering as well as GPU acceleration via OpenCL, NVIDIA CUDA, and NVIDIA OptiX interfaces. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: Orange Juice - Acceleration: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI3691215SE +/- 0.07, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 311.7210.4011.89MIN: 9.6 / MAX: 15.44MIN: 8.31 / MAX: 13.9MIN: 9.85 / MAX: 15.88

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in double precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI5K10K15K20K25KSE +/- 146.69, N = 3SE +/- 125.94, N = 3SE +/- 302.46, N = 32431722390254311. (CXX) g++ options: -O3 -lrt

OctaneBench

OctaneBench is a test of the OctaneRender on the GPU and requires the use of NVIDIA CUDA. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterOctaneBench 2020.1Total ScoreNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI160320480640800720.97648.00735.94

IndigoBench

This is a test of Indigo Renderer's IndigoBench benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/s, More Is BetterIndigoBench 4.4Acceleration: OpenCL GPU - Scene: BedroomNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI510152025SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 319.8018.2020.26

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI110220330440550SE +/- 0.26, N = 3SE +/- 2.23, N = 3509.45458.39502.92MIN: 430.1 / MAX: 516.48MIN: 404.5 / MAX: 461.01MIN: 415.65 / MAX: 520.39

Waifu2x-NCNN Vulkan

Waifu2x-NCNN is an NCNN neural network implementation of the Waifu2x converter project and accelerated using the Vulkan API. NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. This test profile times how long it takes to increase the resolution of a sample image with Vulkan. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterWaifu2x-NCNN Vulkan 20200818Scale: 2x - Denoise: 3 - TAA: YesNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI0.71281.42562.13842.85123.564SE +/- 0.014, N = 3SE +/- 0.028, N = 3SE +/- 0.009, N = 32.8553.1682.854

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI110220330440550SE +/- 0.92, N = 3SE +/- 0.27, N = 3SE +/- 1.92, N = 3507.45458.36505.62MIN: 423.41 / MAX: 512.88MIN: 404.89 / MAX: 461.01MIN: 426.6 / MAX: 513.25

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C Bluestein in single precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI3K6K9K12K15KSE +/- 102.52, N = 3SE +/- 52.09, N = 3SE +/- 118.41, N = 31516613714151251. (CXX) g++ options: -O3 -lrt

NAMD CUDA

NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD was developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. This version of the NAMD test profile uses CUDA GPU acceleration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgdays/ns, Fewer Is BetterNAMD CUDA 2.14ATPase Simulation - 327,506 AtomsNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI0.01690.03380.05070.06760.0845SE +/- 0.00031, N = 3SE +/- 0.00021, N = 3SE +/- 0.00061, N = 30.067910.074980.06788

IndigoBench

This is a test of Indigo Renderer's IndigoBench benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/s, More Is BetterIndigoBench 4.4Acceleration: OpenCL GPU - Scene: SupercarNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI1224364860SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 352.8148.5253.59

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI110220330440550SE +/- 2.17, N = 2SE +/- 0.13, N = 2SE +/- 1.69, N = 3501.50459.94505.55MIN: 415.94 / MAX: 510.69MIN: 403.65 / MAX: 462.59MIN: 419.93 / MAX: 512.69

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI110220330440550SE +/- 4.43, N = 2SE +/- 0.43, N = 2SE +/- 0.83, N = 2504.27459.27504.66MIN: 418.22 / MAX: 512.44MIN: 405.48 / MAX: 461.88MIN: 424.27 / MAX: 509.08

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070110220330440550SE +/- 1.39, N = 3SE +/- 0.34, N = 3504.67459.93MIN: 412.34 / MAX: 514.07MIN: 403.65 / MAX: 462.74

Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50

NVIDIA RTX 4070 TI: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: TypeError: 'NoneType' object is not callable

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C multidimensional in single precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI11K22K33K44K55KSE +/- 407.19, N = 15SE +/- 476.57, N = 5SE +/- 417.77, N = 155029947212515281. (CXX) g++ options: -O3 -lrt

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-TNNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI306090120150SE +/- 1.00, N = 2SE +/- 2.31, N = 3SE +/- 2.08, N = 31151211251. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

Libplacebo

Libplacebo is a multimedia rendering library based on the core rendering code of the MPV player. The libplacebo benchmark relies on the Vulkan API and tests various primitives. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterLibplacebo 5.229.1Test: hdr_peakdetectNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER8001600240032004000SE +/- 144.09, N = 3SE +/- 165.74, N = 3SE +/- 3.65, N = 33452.433475.063292.371. (CXX) g++ options: -lm -pthread -ldl -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -MD -MQ -MF

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 1 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI48121620SE +/- 0.22, N = 2SE +/- 0.16, N = 3SE +/- 0.06, N = 213.9214.0414.79

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI4080120160200195.39187.69198.82MIN: 183.94 / MAX: 198.7MIN: 182.03 / MAX: 188.31MIN: 188.33 / MAX: 201.47

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI4080120160200SE +/- 0.51, N = 3SE +/- 0.34, N = 3SE +/- 0.78, N = 2196.07186.63197.02MIN: 171.95 / MAX: 199.96MIN: 180.51 / MAX: 187.79MIN: 183.92 / MAX: 200.54

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in single precision, no reshufflingNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI20K40K60K80K100KSE +/- 37.77, N = 3SE +/- 5.84, N = 3SE +/- 28.54, N = 37507879057751411. (CXX) g++ options: -O3 -lrt

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in single precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI17K34K51K68K85KSE +/- 7.94, N = 3SE +/- 13.72, N = 3SE +/- 0.88, N = 37392977774739421. (CXX) g++ options: -O3 -lrt

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-TTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI306090120150SE +/- 2.08, N = 3SE +/- 1.20, N = 3SE +/- 2.08, N = 31221181241. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in half precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI30K60K90K120K150KSE +/- 159.17, N = 3SE +/- 1301.92, N = 3SE +/- 1708.38, N = 31317051377621362101. (CXX) g++ options: -O3 -lrt

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI4080120160200SE +/- 1.14, N = 2SE +/- 0.17, N = 3SE +/- 0.19, N = 2194.58187.27195.86MIN: 183.74 / MAX: 198.52MIN: 179.9 / MAX: 188.08MIN: 181.64 / MAX: 199.2

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI4080120160200SE +/- 0.29, N = 3195.40187.26194.29MIN: 186.09 / MAX: 197.7MIN: 179.81 / MAX: 188.21MIN: 182.25 / MAX: 197.39

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-NTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI306090120150SE +/- 2.08, N = 3SE +/- 1.76, N = 3SE +/- 1.20, N = 31171221181. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-NNNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI306090120150SE +/- 4.04, N = 3SE +/- 1.86, N = 3SE +/- 1.15, N = 31191221171. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI4080120160200SE +/- 1.38, N = 2SE +/- 0.05, N = 3195.30187.51194.87MIN: 182 / MAX: 199.43MIN: 181.57 / MAX: 188.05MIN: 180.8 / MAX: 198

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dAXPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI100200300400500SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.33, N = 34374554371. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

VkResample

VkResample is a Vulkan-based image upscaling library based on VkFFT. The sample input file is upscaling a 4K image to 8K using Vulkan-based GPU acceleration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterVkResample 1.0Upscale: 2x - Precision: SingleNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI510152025SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 318.4918.0218.461. (CXX) g++ options: -O3

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 1 - Model: VGG-16NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI0.31050.6210.93151.2421.5525SE +/- 0.01, N = 2SE +/- 0.01, N = 31.351.361.38

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sDOTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI80160240320400SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 33703623651. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_lNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI20406080100SE +/- 0.39, N = 3SE +/- 0.36, N = 2103.57101.43103.50MIN: 95.95 / MAX: 105.54MIN: 93.27 / MAX: 103.58MIN: 94.95 / MAX: 105.61

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_lNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI20406080100SE +/- 0.55, N = 3106.37107.59108.59MIN: 97.91 / MAX: 108.16MIN: 98.77 / MAX: 109.43MIN: 99.04 / MAX: 110.68

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_lNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI20406080100SE +/- 0.05, N = 2103.17101.24103.24MIN: 95.79 / MAX: 105.15MIN: 93.33 / MAX: 102.92MIN: 95.41 / MAX: 104.9

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - sAXPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI306090120150SE +/- 2.19, N = 3SE +/- 4.81, N = 3SE +/- 2.00, N = 31561531561. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI4080120160200SE +/- 0.36, N = 3SE +/- 0.73, N = 3201.94198.18201.19MIN: 183.53 / MAX: 206.5MIN: 181.27 / MAX: 200.06MIN: 180.79 / MAX: 203.92

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sCOPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI70140210280350SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.00, N = 33343303361. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - sDOTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI4080120160200SE +/- 2.73, N = 3SE +/- 3.76, N = 3SE +/- 2.40, N = 31651661681. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

Libplacebo

Libplacebo is a multimedia rendering library based on the core rendering code of the MPV player. The libplacebo benchmark relies on the Vulkan API and tests various primitives. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterLibplacebo 5.229.1Test: hdr_lutNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER9001800270036004500SE +/- 0.24, N = 3SE +/- 33.96, N = 3SE +/- 12.09, N = 33940.403976.043905.981. (CXX) g++ options: -lm -pthread -ldl -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -MD -MQ -MF

OpenBenchmarking.orgFPS, More Is BetterLibplacebo 5.229.1Test: av1_grain_lapNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER9001800270036004500SE +/- 72.31, N = 3SE +/- 35.33, N = 3SE +/- 5.52, N = 34126.404143.964171.001. (CXX) g++ options: -lm -pthread -ldl -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -MD -MQ -MF

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_lNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI20406080100SE +/- 1.49, N = 2SE +/- 0.45, N = 3SE +/- 0.39, N = 2102.60101.55103.20MIN: 79.69 / MAX: 105.28MIN: 93.44 / MAX: 103.08MIN: 95.31 / MAX: 105.27

cl-mem

A basic OpenCL memory benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: WriteNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI90180270360450SE +/- 1.11, N = 3SE +/- 0.55, N = 3SE +/- 0.12, N = 3407.5406.7412.21. (CC) gcc options: -O2 -flto -lOpenCL

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 16 - Model: VGG-16NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI0.33750.6751.01251.351.6875SE +/- 0.00, N = 2SE +/- 0.01, N = 21.481.501.49

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 1 - Model: GoogLeNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI3691215SE +/- 0.17, N = 2SE +/- 0.10, N = 3SE +/- 0.30, N = 212.6212.7812.79

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 256 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070 TI816243240SE +/- 0.01, N = 3SE +/- 0.07, N = 234.1634.61

Device: GPU - Batch Size: 256 - Model: AlexNet

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: UnboundLocalError: cannot access local variable 'kind' where it is not associated with a value

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 32 - Model: GoogLeNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI48121620SE +/- 0.01, N = 2SE +/- 0.03, N = 3SE +/- 0.03, N = 315.6115.6315.81

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMV-TNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI80160240320400SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.33, N = 33893873911. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sAXPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI90180270360450SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 33923893931. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMV-NNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI20406080100SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 31021031031. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

ProjectPhysX OpenCL-Benchmark

ProjectPhysX OpenCL-Benchmark provides various OpenCL compute and memory bandwidth micro-benchmarks Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: Memory Bandwidth Coalesced WriteNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI100200300400500SE +/- 0.14, N = 3SE +/- 0.16, N = 3SE +/- 0.11, N = 3455.01459.43457.171. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 512 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI816243240SE +/- 0.02, N = 2SE +/- 0.03, N = 3SE +/- 0.09, N = 235.1035.2135.44

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMV-NNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI50100150200250SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 32102092111. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 32 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI1.24882.49763.74644.99526.244SE +/- 0.01, N = 2SE +/- 0.01, N = 2SE +/- 0.02, N = 35.515.555.50

cl-mem

A basic OpenCL memory benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: CopyNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI70140210280350SE +/- 0.03, N = 3SE +/- 0.09, N = 3SE +/- 0.00, N = 3331.8330.3333.31. (CC) gcc options: -O2 -flto -lOpenCL

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 16 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI714212835SE +/- 0.17, N = 3SE +/- 0.08, N = 331.5931.4531.70

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - sCOPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI306090120150SE +/- 1.20, N = 3SE +/- 1.20, N = 3SE +/- 0.88, N = 31321311321. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dCOPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI1632486480SE +/- 0.32, N = 3SE +/- 0.25, N = 3SE +/- 0.74, N = 370.871.071.31. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 1 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI0.97881.95762.93643.91524.894SE +/- 0.01, N = 3SE +/- 0.02, N = 24.354.344.32

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dAXPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI20406080100SE +/- 0.12, N = 3SE +/- 0.44, N = 3SE +/- 0.57, N = 387.286.887.31. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 16 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI1.23532.47063.70594.94126.1765SE +/- 0.00, N = 2SE +/- 0.02, N = 3SE +/- 0.01, N = 35.465.495.46

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dDOTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI100200300400500SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 34584564571. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dDOTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI20406080100SE +/- 0.09, N = 3SE +/- 0.22, N = 3SE +/- 0.58, N = 396.896.796.41. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 64 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI816243240SE +/- 0.14, N = 3SE +/- 0.06, N = 333.9733.9334.06

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 64 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI1.24882.49763.74644.99526.244SE +/- 0.01, N = 2SE +/- 0.00, N = 3SE +/- 0.01, N = 25.555.555.53

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 32 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI816243240SE +/- 0.15, N = 2SE +/- 0.18, N = 3SE +/- 0.04, N = 333.4033.3233.29

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 64 - Model: GoogLeNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI48121620SE +/- 0.07, N = 3SE +/- 0.06, N = 215.5215.5415.50

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dCOPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI90180270360450SE +/- 0.33, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 34234234241. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_lNVIDIA RTX 4070NVIDIA RTX 4070 TI20406080100SE +/- 0.52, N = 2103.68103.45MIN: 96.86 / MAX: 105.56MIN: 95.22 / MAX: 105.88

Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: 'tuple' object has no attribute '_compiled_call_impl'

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 16 - Model: GoogLeNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI48121620SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.07, N = 315.6715.6615.69

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGBPS, More Is Betterclpeak 1.1.2OpenCL Test: Global Memory BandwidthNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI90180270360450SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3437.65437.21437.631. (CXX) g++ options: -O3

ProjectPhysX OpenCL-Benchmark

ProjectPhysX OpenCL-Benchmark provides various OpenCL compute and memory bandwidth micro-benchmarks Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: Memory Bandwidth Coalesced ReadNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI100200300400500SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3464.86465.18465.071. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

cl-mem

A basic OpenCL memory benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: ReadNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI100200300400500SE +/- 0.12, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3446.2446.3446.31. (CC) gcc options: -O2 -flto -lOpenCL

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 256 - Model: VGG-16NVIDIA RTX 4070 TI0.33750.6751.01251.351.68751.5

Device: GPU - Batch Size: 256 - Model: VGG-16

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: 'collections.OrderedDict' object has no attribute 'empty'

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 64 - Model: VGG-16NVIDIA RTX 4070NVIDIA RTX 4070 TI0.33750.6751.01251.351.6875SE +/- 0.00, N = 3SE +/- 0.00, N = 31.501.50

Device: GPU - Batch Size: 64 - Model: VGG-16

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: UnboundLocalError: cannot access local variable 'decorators' where it is not associated with a value

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 32 - Model: VGG-16NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI0.33750.6751.01251.351.6875SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 21.501.501.50

NeatBench

NeatBench is a benchmark of the cross-platform Neat Video software on the CPU and optional GPU (OpenCL / CUDA) support. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterNeatBench 5Acceleration: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI9001800270036004500SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3407040704070

NCNN

NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: FastestDetNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER0.6841.3682.0522.7363.42SE +/- 0.13, N = 12SE +/- 0.32, N = 10SE +/- 0.29, N = 92.673.042.86MIN: 2.04 / MAX: 3.47MIN: 2.14 / MAX: 847.58MIN: 2.17 / MAX: 577.171. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: vision_transformerNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER2004006008001000SE +/- 58.37, N = 12SE +/- 58.07, N = 12SE +/- 87.53, N = 9382.82497.66844.61MIN: 46.51 / MAX: 1840MIN: 46.41 / MAX: 1886.67MIN: 46.34 / MAX: 1866.931. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: regnety_400mNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER3691215SE +/- 0.24, N = 12SE +/- 0.18, N = 12SE +/- 3.28, N = 96.215.8911.11MIN: 5.53 / MAX: 8.99MIN: 5.42 / MAX: 7.57MIN: 5.49 / MAX: 4942.191. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: squeezenet_ssdNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER246810SE +/- 0.12, N = 12SE +/- 0.93, N = 12SE +/- 1.76, N = 95.186.136.86MIN: 4.67 / MAX: 6.88MIN: 4.75 / MAX: 1633.33MIN: 4.34 / MAX: 1630.011. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: yolov4-tinyNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER1428425670SE +/- 5.37, N = 12SE +/- 3.10, N = 12SE +/- 10.56, N = 920.7416.3763.82MIN: 10.3 / MAX: 854.36MIN: 10.57 / MAX: 855.36MIN: 10.28 / MAX: 858.441. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: resnet50NVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER1020304050SE +/- 0.49, N = 12SE +/- 4.00, N = 12SE +/- 14.70, N = 98.7212.2546.26MIN: 7.94 / MAX: 935.44MIN: 8 / MAX: 1777.17MIN: 7.71 / MAX: 1829.991. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: alexnetNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER48121620SE +/- 1.70, N = 12SE +/- 2.33, N = 12SE +/- 5.86, N = 95.786.0716.17MIN: 3.6 / MAX: 397.75MIN: 3.63 / MAX: 432.24MIN: 3.52 / MAX: 436.521. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: resnet18NVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER3691215SE +/- 0.73, N = 12SE +/- 1.74, N = 12SE +/- 3.49, N = 95.117.748.97MIN: 3.99 / MAX: 916.69MIN: 3.96 / MAX: 898.97MIN: 3.94 / MAX: 922.041. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: vgg16NVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER306090120150SE +/- 13.24, N = 12SE +/- 8.53, N = 12SE +/- 29.60, N = 945.5234.49117.81MIN: 17.49 / MAX: 643.35MIN: 17.35 / MAX: 644.35MIN: 17.16 / MAX: 647.671. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: googlenetNVIDIA RTX 4070 TINVIDIA RTX 4070 SUPERNVIDIA RTX 40703691215SE +/- 1.04, N = 12SE +/- 1.21, N = 9SE +/- 0.14, N = 97.3711.046.06MIN: 5.33 / MAX: 1653.33MIN: 5.28 / MAX: 1769.19MIN: 5.33 / MAX: 8.361. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: blazefaceNVIDIA RTX 4070 TINVIDIA RTX 4070 SUPERNVIDIA RTX 40700.1890.3780.5670.7560.945SE +/- 0.03, N = 12SE +/- 0.04, N = 9SE +/- 0.03, N = 90.820.840.84MIN: 0.63 / MAX: 2.58MIN: 0.65 / MAX: 4.63MIN: 0.64 / MAX: 0.961. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: efficientnet-b0NVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER1.14082.28163.42244.56325.704SE +/- 0.20, N = 12SE +/- 0.07, N = 12SE +/- 0.97, N = 93.593.465.07MIN: 3.02 / MAX: 509.97MIN: 3.13 / MAX: 7.03MIN: 3.22 / MAX: 1124.21. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: mnasnetNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER0.93151.8632.79453.7264.6575SE +/- 0.05, N = 10SE +/- 1.94, N = 12SE +/- 1.31, N = 92.244.143.85MIN: 2 / MAX: 2.6MIN: 1.95 / MAX: 1020MIN: 1.89 / MAX: 1093.291. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: shufflenet-v2NVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER0.51981.03961.55942.07922.599SE +/- 0.09, N = 11SE +/- 0.08, N = 12SE +/- 0.34, N = 82.082.012.31MIN: 1.82 / MAX: 2.59MIN: 1.73 / MAX: 3.86MIN: 1.76 / MAX: 421.421. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3NVIDIA RTX 4070NVIDIA RTX 4070 SUPERNVIDIA RTX 4070 TI246810SE +/- 0.08, N = 12SE +/- 0.16, N = 9SE +/- 0.09, N = 92.152.252.09MIN: 1.81 / MAX: 2.58MIN: 1.75 / MAX: 343.7MIN: 1.78 / MAX: 2.851. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2NVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER1.05532.11063.16594.22125.2765SE +/- 0.07, N = 12SE +/- 0.06, N = 12SE +/- 0.44, N = 92.482.543.03MIN: 2.02 / MAX: 5.82MIN: 2.07 / MAX: 15.69MIN: 2.38 / MAX: 970.871. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: mobilenetNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER3691215SE +/- 0.21, N = 12SE +/- 0.25, N = 12SE +/- 0.47, N = 97.207.458.62MIN: 6.2 / MAX: 11.13MIN: 6.87 / MAX: 734.65MIN: 6.42 / MAX: 1101.31. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

Device: GPU - Batch Size: 512 - Model: VGG-16

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: Fatal Python error: Segmentation fault

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: 'function' object has no attribute 'empty'

NVIDIA RTX 4070 TI: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: Fatal Python error: Segmentation fault

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

FP16: No - Mode: Inference - Network: DenseNet 201 - Device: OpenCL

NVIDIA RTX 4070 SUPER: The test run did not produce a result. The test quit with a non-zero exit status. The test run did not produce a result.

NVIDIA RTX 4070: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NVIDIA RTX 4070 TI: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

FP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCL

NVIDIA RTX 4070 SUPER: The test run did not produce a result. The test run did not produce a result. The test quit with a non-zero exit status. E: AttributeError: 'method_descriptor' object has no attribute 'default'

NVIDIA RTX 4070: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NVIDIA RTX 4070 TI: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

FP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCL

NVIDIA RTX 4070 SUPER: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NVIDIA RTX 4070: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NVIDIA RTX 4070 TI: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

FP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCL

NVIDIA RTX 4070 SUPER: The test run did not produce a result. The test run did not produce a result. The test quit with a non-zero exit status.

NVIDIA RTX 4070: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NVIDIA RTX 4070 TI: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

FP16: No - Mode: Training - Network: Mobilenet - Device: OpenCL

NVIDIA RTX 4070 SUPER: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test run did not produce a result.

NVIDIA RTX 4070 TI: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NCNN

NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.

Target: Vulkan GPU

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ncnn: line 3: ./benchncnn: No such file or directory

Caffe

This is a benchmark of the Caffe deep learning framework and currently supports the AlexNet and Googlenet model and execution on both CPUs and NVIDIA GPUs. Learn more via the OpenBenchmarking.org test page.

Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 1000

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x74746a490450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7493bdbbc450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070 TI: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7338f7773450 google::LogMessageFatal::~LogMessageFatal()

Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 200

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7d7151816450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7e64df79d450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070 TI: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x761e63d48450 google::LogMessageFatal::~LogMessageFatal()

Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 100

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x73552c3e3450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x71f0ea05a450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070 TI: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7898abd73450 google::LogMessageFatal::~LogMessageFatal()

Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 1000

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7670bcda4450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7bb89c5be450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070 TI: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x72248ee5c450 google::LogMessageFatal::~LogMessageFatal()

Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 200

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7b5ea59be450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7c31ed79d450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070 TI: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7ba579075450 google::LogMessageFatal::~LogMessageFatal()

Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 100

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7dd7c6de3450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x7b80311e3450 google::LogMessageFatal::~LogMessageFatal()

NVIDIA RTX 4070 TI: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: @ 0x736df4b59450 google::LogMessageFatal::~LogMessageFatal()

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMV-TNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI20406080100SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 6.30, N = 3109.0109.0102.71. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

FinanceBench

FinanceBench is a collection of financial program benchmarks with support for benchmarking on the GPU via OpenCL and CPU benchmarking with OpenMP. The FinanceBench test cases are focused on Black-Sholes-Merton Process with Analytic European Option engine, QMC (Sobol) Monte-Carlo method (Equity Option Example), Bonds Fixed-rate bond with flat forward curve, and Repo Securities repurchase agreement. FinanceBench was originally written by the Cavazos Lab at University of Delaware. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterFinanceBench 2016-07-25Benchmark: Black-Scholes OpenCLNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI246810SE +/- 0.114, N = 15SE +/- 0.003, N = 3SE +/- 0.003, N = 35.9126.9065.2261. (CXX) g++ options: -O3 -march=native -fopenmp

ArrayFire

ArrayFire is an GPU and CPU numeric processing library, this test uses the built-in CPU and OpenCL ArrayFire benchmarks. Learn more via the OpenBenchmarking.org test page.

Test: Conjugate Gradient OpenCL

NVIDIA RTX 4070 SUPER: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result. E: arrayfire: line 3: ./cg_opencl: No such file or directory

NVIDIA RTX 4070: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result. E: arrayfire: line 3: ./cg_opencl: No such file or directory

NVIDIA RTX 4070 TI: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result. E: arrayfire: line 3: ./cg_opencl: No such file or directory

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.

Backend: OpenCL

NVIDIA RTX 4070 SUPER: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NVIDIA RTX 4070: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NVIDIA RTX 4070 TI: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

Libplacebo

Libplacebo is a multimedia rendering library based on the core rendering code of the MPV player. The libplacebo benchmark relies on the Vulkan API and tests various primitives. Learn more via the OpenBenchmarking.org test page.

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: libplacebo: line 3: ./src/bench: No such file or directory

Waifu2x-NCNN Vulkan

Waifu2x-NCNN is an NCNN neural network implementation of the Waifu2x converter project and accelerated using the Vulkan API. NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. This test profile times how long it takes to increase the resolution of a sample image with Vulkan. Learn more via the OpenBenchmarking.org test page.

Scale: 2x - Denoise: 3 - TAA: No

NVIDIA RTX 4070 SUPER: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NVIDIA RTX 4070: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

NVIDIA RTX 4070 TI: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.

RealSR-NCNN

RealSR-NCNN is an NCNN neural network implementation of the RealSR project and accelerated using the Vulkan API. RealSR is the Real-World Super Resolution via Kernel Estimation and Noise Injection. NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. This test profile times how long it takes to increase the resolution of a sample image by a scale of 4x with Vulkan. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRealSR-NCNN 20200818Scale: 4x - TAA: NoNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI246810SE +/- 0.150, N = 15SE +/- 0.006, N = 3SE +/- 0.039, N = 36.3237.0925.962

vkpeak

Vkpeak is a Vulkan compute benchmark inspired by OpenCL's clpeak. Vkpeak provides Vulkan compute performance measurements for FP16 / FP32 / FP64 / INT16 / INT32 scalar and vec4 performance. Learn more via the OpenBenchmarking.org test page.

NVIDIA RTX 4070 SUPER: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.

NVIDIA RTX 4070: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.

NVIDIA RTX 4070 TI: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_lNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI20406080100SE +/- 6.65, N = 5102.60102.9096.50MIN: 94.84 / MAX: 104.25MIN: 95.98 / MAX: 104.54MIN: 64.35 / MAX: 104.79

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TI120240360480600SE +/- 3.09, N = 3SE +/- 11.16, N = 12557.73546.76535.39MIN: 513.63 / MAX: 563.37MIN: 195.25 / MAX: 556.94MIN: 428.43 / MAX: 572.99

138 Results Shown

clpeak:
  Integer Compute INT
  Single-Precision Float
Hashcat:
  MD5
  TrueCrypt RIPEMD160 + XTS
ProjectPhysX OpenCL-Benchmark
Hashcat
GpuOwl
clpeak
ProjectPhysX OpenCL-Benchmark
Hashcat:
  SHA1
  7-Zip
ViennaCL
VkResample
ProjectPhysX OpenCL-Benchmark
GpuOwl
ProjectPhysX OpenCL-Benchmark:
  INT32 Compute
  INT64 Compute
ViennaCL:
  OpenCL BLAS - dGEMM-TN
  OpenCL BLAS - dGEMM-NT
ProjectPhysX OpenCL-Benchmark
ViennaCL
GpuOwl
RealSR-NCNN
Libplacebo:
  deband_heavy
  polar_nocompute
Rodinia
LuxCoreRender
Blender
LuxCoreRender
Blender
FAHBench
MandelGPU
VkFFT
LuxCoreRender:
  Rainbow Colors and Prism - GPU
  DLSC - GPU
Blender
VkFFT
Blender:
  Barbershop - NVIDIA OptiX
  BMW27 - NVIDIA OptiX
LuxCoreRender
VkFFT
OctaneBench
IndigoBench
PyTorch
Waifu2x-NCNN Vulkan
PyTorch
VkFFT
NAMD CUDA
IndigoBench
PyTorch:
  NVIDIA CUDA GPU - 32 - ResNet-50
  NVIDIA CUDA GPU - 512 - ResNet-50
  NVIDIA CUDA GPU - 256 - ResNet-50
VkFFT
ViennaCL
Libplacebo
TensorFlow
PyTorch:
  NVIDIA CUDA GPU - 32 - ResNet-152
  NVIDIA CUDA GPU - 64 - ResNet-152
VkFFT:
  FFT + iFFT C2C 1D batched in single precision, no reshuffling
  FFT + iFFT C2C 1D batched in single precision
ViennaCL
VkFFT
PyTorch:
  NVIDIA CUDA GPU - 256 - ResNet-152
  NVIDIA CUDA GPU - 16 - ResNet-152
ViennaCL:
  CPU BLAS - dGEMM-NT
  CPU BLAS - dGEMM-NN
PyTorch
ViennaCL
VkResample
TensorFlow
ViennaCL
PyTorch:
  NVIDIA CUDA GPU - 512 - Efficientnet_v2_l
  NVIDIA CUDA GPU - 1 - Efficientnet_v2_l
  NVIDIA CUDA GPU - 256 - Efficientnet_v2_l
ViennaCL
PyTorch
ViennaCL:
  OpenCL BLAS - sCOPY
  CPU BLAS - sDOT
Libplacebo:
  hdr_lut
  av1_grain_lap
PyTorch
cl-mem
TensorFlow:
  GPU - 16 - VGG-16
  GPU - 1 - GoogLeNet
  GPU - 256 - AlexNet
  GPU - 32 - GoogLeNet
ViennaCL:
  OpenCL BLAS - dGEMV-T
  OpenCL BLAS - sAXPY
  CPU BLAS - dGEMV-N
ProjectPhysX OpenCL-Benchmark
TensorFlow
ViennaCL
TensorFlow
cl-mem
TensorFlow
ViennaCL:
  CPU BLAS - sCOPY
  CPU BLAS - dCOPY
TensorFlow
ViennaCL
TensorFlow
ViennaCL:
  OpenCL BLAS - dDOT
  CPU BLAS - dDOT
TensorFlow:
  GPU - 64 - AlexNet
  GPU - 64 - ResNet-50
  GPU - 32 - AlexNet
  GPU - 64 - GoogLeNet
ViennaCL
PyTorch
TensorFlow
clpeak
ProjectPhysX OpenCL-Benchmark
cl-mem
TensorFlow:
  GPU - 256 - VGG-16
  GPU - 64 - VGG-16
  GPU - 32 - VGG-16
NeatBench
NCNN:
  Vulkan GPU - FastestDet
  Vulkan GPU - vision_transformer
  Vulkan GPU - regnety_400m
  Vulkan GPU - squeezenet_ssd
  Vulkan GPU - yolov4-tiny
  Vulkan GPU - resnet50
  Vulkan GPU - alexnet
  Vulkan GPU - resnet18
  Vulkan GPU - vgg16
  Vulkan GPU - googlenet
  Vulkan GPU - blazeface
  Vulkan GPU - efficientnet-b0
  Vulkan GPU - mnasnet
  Vulkan GPU - shufflenet-v2
  Vulkan GPU-v3-v3 - mobilenet-v3
  Vulkan GPU-v2-v2 - mobilenet-v2
  Vulkan GPU - mobilenet
ViennaCL
FinanceBench
RealSR-NCNN
PyTorch:
  NVIDIA CUDA GPU - 32 - Efficientnet_v2_l
  NVIDIA CUDA GPU - 1 - ResNet-50