RTX 4070 SUPER

Intel Core i9-13900K testing with a ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS) and NVIDIA GeForce RTX 3090 24GB 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 2402116-SADD-240207012
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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
NVIDIA RTX 3090
February 07
  1 Day, 10 Hours, 51 Minutes
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RTX 4070 SUPERProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLCompilerFile-SystemScreen ResolutionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090Intel 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 12GBNVIDIA GeForce RTX 3090 24GBPI-KVM Video6.7.4-arch1-1 (x86_64)OpenBenchmarking.orgKernel Details- Transparent Huge Pages: alwaysCompiler Details- NVIDIA RTX 4070 SUPER: --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 - NVIDIA RTX 4070: --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 - NVIDIA RTX 4070 TI: --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 - NVIDIA RTX 3090: --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,m2,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: 95.04.31.00.36- NVIDIA RTX 3090: BAR1 / Visible vRAM Size: 256 MiB - vBIOS Version: 94.02.26.08.baSecurity 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, NVIDIA RTX 3090: NVCC_PREPEND_FLAGS="-ccbin /opt/cuda/bin"Python Details- NVIDIA RTX 4070, NVIDIA RTX 4070 TI, NVIDIA RTX 3090: Python 3.11.6

NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090Result OverviewPhoronix Test Suite100%119%137%156%174%NCNNNAMD CUDAcl-memVkResampleclpeakVkFFTRealSR-NCNNFinanceBenchNeatBenchProjectPhysX OpenCL-BenchmarkHashcatGpuOwlMandelGPURodiniaTensorFlowLuxCoreRenderFAHBenchBlenderPyTorchOctaneBenchWaifu2x-NCNN VulkanLibplaceboIndigoBenchViennaCL

RTX 4070 SUPERvkfft: FFT + iFFT C2C 1D batched in half precisionopencl-benchmark: Memory Bandwidth Coalesced Writevkfft: FFT + iFFT C2C 1D batched in single precision, no reshufflingvkfft: FFT + iFFT C2C 1D batched in single precisionclpeak: Global Memory Bandwidthopencl-benchmark: Memory Bandwidth Coalesced Readcl-mem: Writecl-mem: Readvkresample: 2x - Singleviennacl: OpenCL BLAS - dAXPYnamd-cuda: ATPase Simulation - 327,506 Atomslibplacebo: hdr_peakdetectviennacl: OpenCL BLAS - dDOTluxcorerender: Rainbow Colors and Prism - GPUviennacl: OpenCL BLAS - dCOPYrealsr-ncnn: 4x - Yesopencl-benchmark: INT64 Computevkfft: FFT + iFFT C2C 1D batched in double precisionclpeak: Integer Compute INTclpeak: Single-Precision Floatneatbench: GPUhashcat: 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 Computeviennacl: OpenCL BLAS - dGEMM-TNviennacl: OpenCL BLAS - dGEMM-NTviennacl: OpenCL BLAS - sAXPYopencl-benchmark: INT16 Computemandelgpu: GPUviennacl: OpenCL BLAS - dGEMM-NNgpuowl: 77936867libplacebo: deband_heavylibplacebo: polar_nocomputerodinia: OpenCL Particle Filterblender: Classroom - NVIDIA OptiXblender: Pabellon Barcelona - NVIDIA OptiXluxcorerender: Danish Mood - GPUblender: Fishy Cat - NVIDIA OptiXpytorch: NVIDIA CUDA GPU - 256 - ResNet-152pytorch: NVIDIA CUDA GPU - 32 - ResNet-152pytorch: NVIDIA CUDA GPU - 16 - ResNet-50pytorch: NVIDIA CUDA GPU - 512 - ResNet-50luxcorerender: LuxCore Benchmark - GPUpytorch: NVIDIA CUDA GPU - 64 - ResNet-50pytorch: NVIDIA CUDA GPU - 256 - ResNet-50fahbench: pytorch: NVIDIA CUDA GPU - 32 - ResNet-50pytorch: NVIDIA CUDA GPU - 64 - ResNet-152libplacebo: hdr_lutvkfft: FFT + iFFT C2C Bluestein benchmark in double precisionpytorch: NVIDIA CUDA GPU - 16 - ResNet-152pytorch: NVIDIA CUDA GPU - 512 - ResNet-152vkfft: FFT + iFFT R2C / C2Rluxcorerender: Orange Juice - GPUblender: BMW27 - NVIDIA OptiXblender: Barbershop - NVIDIA OptiXindigobench: OpenCL GPU - Bedroomoctanebench: Total Scoreviennacl: OpenCL BLAS - dGEMV-Nwaifu2x-ncnn: 2x - 3 - Yesvkfft: FFT + iFFT C2C Bluestein in single precisionindigobench: OpenCL GPU - Supercarviennacl: OpenCL BLAS - sCOPYviennacl: CPU BLAS - dGEMM-TTcl-mem: Copyvkfft: FFT + iFFT C2C multidimensional in single precisionviennacl: CPU BLAS - dGEMM-TNviennacl: CPU BLAS - dGEMM-NNtensorflow: GPU - 1 - AlexNetpytorch: NVIDIA CUDA GPU - 16 - Efficientnet_v2_lviennacl: OpenCL BLAS - dGEMV-Tpytorch: NVIDIA CUDA GPU - 512 - Efficientnet_v2_lviennacl: CPU BLAS - dGEMM-NTviennacl: OpenCL BLAS - sDOTpytorch: NVIDIA CUDA GPU - 256 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 64 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 1 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 1 - ResNet-152tensorflow: GPU - 1 - VGG-16viennacl: CPU BLAS - sAXPYlibplacebo: av1_grain_laptensorflow: GPU - 16 - AlexNetviennacl: CPU BLAS - dDOTtensorflow: GPU - 1 - GoogLeNetviennacl: CPU BLAS - dCOPYtensorflow: GPU - 512 - AlexNettensorflow: GPU - 16 - VGG-16tensorflow: GPU - 256 - AlexNettensorflow: GPU - 32 - GoogLeNetviennacl: CPU BLAS - dAXPYtensorflow: GPU - 32 - ResNet-50viennacl: CPU BLAS - dGEMV-Ntensorflow: GPU - 64 - GoogLeNetvkpeak: fp32-vec4viennacl: CPU BLAS - sCOPYtensorflow: GPU - 64 - ResNet-50tensorflow: GPU - 32 - AlexNettensorflow: GPU - 1 - ResNet-50tensorflow: GPU - 256 - VGG-16tensorflow: GPU - 64 - VGG-16tensorflow: GPU - 16 - ResNet-50vkpeak: fp32-scalartensorflow: GPU - 64 - AlexNetvkpeak: int16-scalarvkpeak: fp16-scalarvkpeak: fp16-vec4vkpeak: int16-vec4tensorflow: GPU - 16 - GoogLeNetvkpeak: int32-scalarvkpeak: fp64-vec4vkpeak: int32-vec4vkpeak: fp64-scalartensorflow: GPU - 32 - VGG-16ncnn: 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-Tviennacl: CPU BLAS - sDOTfinancebench: Black-Scholes OpenCLluxcorerender: DLSC - GPUrealsr-ncnn: 4x - Nopytorch: NVIDIA CUDA GPU - 32 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 1 - ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090131705455.017507873929437.65464.86407.5446.218.4894370.067913292.3745827.6742334.8854.2142431718170.5435492.6940706758303333380296714.3073232733333137.44630.110.621221326000001176467613339.59338.594869.0719.88959958439217.170587219538.2577646.412186.702327.553.48012.6014.2910.569.45194.58195.39509.45504.2712.82507.45504.67366.0576501.50196.073905.984451195.40195.305479411.725.5751.3019.801720.9737892102.8551516652.813334122331.85029911511913.92389103.57117370103.17102.60106.37201.941.351564171.0031.5996.812.6270.835.101.4834.1615.6187.25.5110215.521325.5533.44.355.4633.9715.671.502.86844.6111.116.8663.8246.2616.178.97117.8111.040.845.073.852.312.253.038.621091655.91213.596.323102.60557.73137762459.437905777774437.21465.18406.7446.318.0164550.074983310.0245623.2642342.8523.4432239014555.1928479.3940705614786666766096712.1162673300000112.61515.170.51018202466667976967502415.16031.768714.8016.37749447738914.284516770131.2473530.321847.981972.784.09814.8616.558.8911.03187.27187.69458.39459.2710.92458.36459.93317.1952459.94186.633927.113886187.26187.514709710.406.2158.4418.203647.9978672093.1681371448.517330118330.34721212112214.04103.68387101.43122362101.24101.55107.59198.181.361534103.4031.4596.712.7871.035.211.5015.6386.85.5510315.541315.5533.324.341.505.4933.9315.661.52.34281.566.505.2725.118.249.338.5854.546.060.843.462.222.118.714.6910.141091666.90611.747.092102.90546.76136210457.177514173942437.63465.07412.2446.318.4564370.067883544.6045727.7142433.6264.4202543119821.1038691.7340707331223333385860015.7313462500000145.84667.050.660235324000001262633648322.06440.914919.1321.04763461239318.281619106132.5604676.592306.672461.233.29112.3013.9710.999.02195.86198.82502.92504.6613.23505.62382.1637505.55197.023971.614647194.29194.875544611.895.4350.7320.256735.9405932112.8541512553.589336124333.35152812511714.79103.45391103.50118365103.24103.20108.59201.191.381564140.8731.7096.412.7971.335.441.4934.6115.8187.35.5010315.501325.5333.294.321.51.55.4634.0615.691.52.84390.185.975.3616.4714.323.745.4732.055.870.813.492.302.032.092.438.43102.71685.22613.955.96296.50535.39273221887.31144311141876816.55864.11753.8825.810.3237240.108224997.0865933.2960530.3133.1353091217923.3334906.7930906717730000079783313.7273081866667137.32642.230.637213237333331056000593333.63939.395866.3120.02759459549817.001484098913.8592645.992017.752119.893.84415.2617.3010.2010.64161.01163.74419.76416.2013.12419.03416.89343.0199420.29164.143313.264195164.14164.354841812.146.3154.3020.959674.2509121873.2021420552.014363113360.85085612111314.4598.1137499.2511937699.4399.84105.55197.121.381544126.8931.9895.212.8270.235.581.4934.4615.6786.25.5710315.6326563.721325.5733.534.351.511.515.4920263.1333.9313259.9720080.4739771.9716331.1615.6820280.33638.7219996.92638.701.56.38663.248.066.6326.8527.773.6917.41145.727.490.8613.872.244.173.192.6512.07110132.15.74112.995.55699.05525.12OpenBenchmarking.org

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in half precisionNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER60K120K180K240K300KSE +/- 160.60, N = 3SE +/- 1708.38, N = 3SE +/- 1301.92, N = 3SE +/- 159.17, N = 32732211362101377621317051. (CXX) g++ options: -O3 -lrt

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER2004006008001000SE +/- 0.06, N = 3SE +/- 0.11, N = 3SE +/- 0.16, N = 3SE +/- 0.14, N = 3887.31457.17459.43455.011. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in single precision, no reshufflingNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER30K60K90K120K150KSE +/- 37.44, N = 3SE +/- 28.54, N = 3SE +/- 5.84, N = 3SE +/- 37.77, N = 31443117514179057750781. (CXX) g++ options: -O3 -lrt

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in single precisionNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER30K60K90K120K150KSE +/- 9.64, N = 3SE +/- 0.88, N = 3SE +/- 13.72, N = 3SE +/- 7.94, N = 31418767394277774739291. (CXX) g++ options: -O3 -lrt

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER2004006008001000SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3816.55437.63437.21437.651. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER2004006008001000SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3864.11465.07465.18464.861. (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: WriteNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER160320480640800SE +/- 0.83, N = 3SE +/- 0.12, N = 3SE +/- 0.55, N = 3SE +/- 1.11, N = 3753.8412.2406.7407.51. (CC) gcc options: -O2 -flto -lOpenCL

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: ReadNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER2004006008001000SE +/- 0.32, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.12, N = 3825.8446.3446.3446.21. (CC) gcc options: -O2 -flto -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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER510152025SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 310.3218.4618.0218.491. (CXX) g++ options: -O3

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER160320480640800SE +/- 0.58, N = 3SE +/- 0.33, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 37244374554371. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.02430.04860.07290.09720.1215SE +/- 0.00042, N = 3SE +/- 0.00061, N = 3SE +/- 0.00021, N = 3SE +/- 0.00031, N = 30.108220.067880.074980.06791

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER11002200330044005500SE +/- 43.13, N = 3SE +/- 99.97, N = 3SE +/- 11.75, N = 3SE +/- 3.65, N = 34997.083544.603310.023292.371. (CXX) g++ options: -lm -pthread -ldl -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -MD -MQ -MF

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER140280420560700SE +/- 0.88, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 36594574564581. (CXX) g++ options: -fopenmp -O3 -rdynamic -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: Rainbow Colors and Prism - Acceleration: GPUNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER816243240SE +/- 0.36, N = 5SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 333.2927.7123.2627.67MIN: 30.4 / MAX: 36.21MIN: 25.01 / MAX: 29.15MIN: 20.92 / MAX: 24.3MIN: 24.87 / MAX: 29.03

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER130260390520650SE +/- 0.58, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.33, N = 36054244234231. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER1020304050SE +/- 0.06, N = 3SE +/- 0.03, N = 3SE +/- 0.23, N = 3SE +/- 0.02, N = 330.3133.6342.8534.89

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: INT64 ComputeNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.99451.9892.98353.9784.9725SE +/- 0.003, N = 3SE +/- 0.016, N = 3SE +/- 0.004, N = 3SE +/- 0.015, N = 33.1354.4203.4434.2141. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in double precisionNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER7K14K21K28K35KSE +/- 50.66, N = 3SE +/- 302.46, N = 3SE +/- 125.94, N = 3SE +/- 146.69, N = 3309122543122390243171. (CXX) g++ options: -O3 -lrt

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER4K8K12K16K20KSE +/- 16.49, N = 3SE +/- 2.50, N = 3SE +/- 15.26, N = 3SE +/- 3.14, N = 317923.3319821.1014555.1918170.541. (CXX) g++ options: -O3

OpenBenchmarking.orgGFLOPS, More Is Betterclpeak 1.1.2OpenCL Test: Single-Precision FloatNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER8K16K24K32K40KSE +/- 113.39, N = 3SE +/- 11.67, N = 3SE +/- 5.46, N = 3SE +/- 0.99, N = 334906.7938691.7328479.3935492.691. (CXX) g++ options: -O3

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER9001800270036004500SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 33090407040704070

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER16000M32000M48000M64000M80000MSE +/- 53667246.37, N = 3SE +/- 11283665.68, N = 3SE +/- 33772046.30, N = 3SE +/- 22430807.19, N = 367177300000733122333335614786666767583033333

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: TrueCrypt RIPEMD160 + XTSNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER200K400K600K800K1000KSE +/- 1757.21, N = 3SE +/- 888.82, N = 3SE +/- 176.38, N = 3SE +/- 633.33, N = 3797833858600660967802967

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 0.07, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.05, N = 313.7315.7312.1214.311. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER700M1400M2100M2800M3500MSE +/- 3288532.26, N = 3SE +/- 721110.26, N = 3SE +/- 1059874.21, N = 3SE +/- 1530068.99, N = 33081866667346250000026733000003232733333

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER306090120150SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3137.32145.84112.61137.44

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER140280420560700SE +/- 1.63, N = 3SE +/- 1.33, N = 3SE +/- 0.21, N = 3SE +/- 0.98, N = 3642.23667.05515.17630.111. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.14850.2970.44550.5940.7425SE +/- 0.001, N = 3SE +/- 0.001, N = 3SE +/- 0.001, N = 3SE +/- 0.000, N = 30.6370.6600.5100.6211. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER5000M10000M15000M20000M25000MSE +/- 26244639.66, N = 3SE +/- 15926811.78, N = 3SE +/- 6318315.53, N = 3SE +/- 5140363.15, N = 321323733333235324000001820246666722132600000

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: 7-ZipNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER300K600K900K1200K1500KSE +/- 1587.45, N = 3SE +/- 2339.04, N = 3SE +/- 2062.63, N = 3SE +/- 1991.93, N = 3105600012626339769671176467

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER140280420560700SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.00, N = 35936485026131. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER90180270360450SE +/- 0.30, N = 3SE +/- 0.35, N = 3SE +/- 0.77, N = 3SE +/- 0.30, N = 3333.64322.06415.16339.591. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER918273645SE +/- 0.10, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 339.4040.9131.7738.591. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER2004006008001000SE +/- 2.01, N = 3SE +/- 2.53, N = 3SE +/- 0.00, N = 3SE +/- 1.26, N = 3866.31919.13714.80869.07

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER510152025SE +/- 0.06, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 320.0321.0516.3819.891. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER140280420560700SE +/- 2.03, N = 3SE +/- 0.67, N = 3SE +/- 0.33, N = 3SE +/- 0.00, N = 35946344945991. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-NTNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER130260390520650SE +/- 2.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.00, N = 35956124775841. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sAXPYNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER110220330440550SE +/- 0.58, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 34983933893921. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 317.0018.2814.2817.171. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER130M260M390M520M650MSE +/- 794770.01, N = 3SE +/- 1202791.77, N = 3SE +/- 1783157.89, N = 3SE +/- 467034.80, N = 3484098913.8619106132.5516770131.2587219538.21. (CC) gcc options: -O3 -lm -ftree-vectorize -funroll-loops -lglut -lOpenCL -lGL

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER130260390520650SE +/- 2.31, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.00, N = 35926044735771. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER150300450600750SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.09, N = 3SE +/- 0.00, N = 3645.99676.59530.32646.41

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER5001000150020002500SE +/- 4.93, N = 3SE +/- 0.56, N = 3SE +/- 0.08, N = 3SE +/- 2.26, N = 32017.752306.671847.982186.701. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER5001000150020002500SE +/- 7.22, N = 3SE +/- 0.26, N = 3SE +/- 0.16, N = 3SE +/- 0.24, N = 32119.892461.231972.782327.551. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.92211.84422.76633.68844.6105SE +/- 0.030, N = 15SE +/- 0.002, N = 3SE +/- 0.008, N = 3SE +/- 0.039, N = 43.8443.2914.0983.4801. (CXX) g++ options: -O2 -lOpenCL

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 315.2612.3014.8612.60

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Pabellon Barcelona - Compute: NVIDIA OptiXNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 317.3013.9716.5514.29

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER3691215SE +/- 0.04, N = 3SE +/- 0.11, N = 3SE +/- 0.06, N = 3SE +/- 0.08, N = 310.2010.998.8910.56MIN: 4.07 / MAX: 11.93MIN: 4.17 / MAX: 12.71MIN: 3.32 / MAX: 10.26MIN: 3.7 / MAX: 12.17

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER3691215SE +/- 0.08, N = 9SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 1310.649.0211.039.45

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER4080120160200SE +/- 0.19, N = 2SE +/- 0.17, N = 3SE +/- 1.14, N = 2161.01195.86187.27194.58MIN: 138.12 / MAX: 165.16MIN: 181.64 / MAX: 199.2MIN: 179.9 / MAX: 188.08MIN: 183.74 / MAX: 198.52

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER4080120160200SE +/- 0.29, N = 3163.74198.82187.69195.39MIN: 144.93 / MAX: 165.03MIN: 188.33 / MAX: 201.47MIN: 182.03 / MAX: 188.31MIN: 183.94 / MAX: 198.7

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER110220330440550SE +/- 0.89, N = 2SE +/- 2.23, N = 3SE +/- 0.26, N = 3419.76502.92458.39509.45MIN: 376.2 / MAX: 422.17MIN: 415.65 / MAX: 520.39MIN: 404.5 / MAX: 461.01MIN: 430.1 / MAX: 516.48

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER110220330440550SE +/- 0.40, N = 3SE +/- 0.83, N = 2SE +/- 0.43, N = 2SE +/- 4.43, N = 2416.20504.66459.27504.27MIN: 355.45 / MAX: 419.05MIN: 424.27 / MAX: 509.08MIN: 405.48 / MAX: 461.88MIN: 418.22 / MAX: 512.44

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER3691215SE +/- 0.03, N = 2SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 313.1213.2310.9212.82MIN: 4.85 / MAX: 15.21MIN: 5.41 / MAX: 15.13MIN: 4.45 / MAX: 12.42MIN: 4.84 / MAX: 14.62

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER110220330440550SE +/- 0.24, N = 3SE +/- 1.92, N = 3SE +/- 0.27, N = 3SE +/- 0.92, N = 3419.03505.62458.36507.45MIN: 376 / MAX: 422MIN: 426.6 / MAX: 513.25MIN: 404.89 / MAX: 461.01MIN: 423.41 / MAX: 512.88

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50NVIDIA RTX 3090NVIDIA RTX 4070NVIDIA RTX 4070 SUPER110220330440550SE +/- 0.14, N = 3SE +/- 0.34, N = 3SE +/- 1.39, N = 3416.89459.93504.67MIN: 329.77 / MAX: 420.82MIN: 403.65 / MAX: 462.74MIN: 412.34 / MAX: 514.07

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

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER80160240320400SE +/- 0.26, N = 3SE +/- 0.26, N = 3SE +/- 0.12, N = 3SE +/- 0.39, N = 3343.02382.16317.20366.06

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER110220330440550SE +/- 1.69, N = 3SE +/- 0.13, N = 2SE +/- 2.17, N = 2420.29505.55459.94501.50MIN: 376.81 / MAX: 421.58MIN: 419.93 / MAX: 512.69MIN: 403.65 / MAX: 462.59MIN: 415.94 / MAX: 510.69

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER4080120160200SE +/- 0.78, N = 2SE +/- 0.34, N = 3SE +/- 0.51, N = 3164.14197.02186.63196.07MIN: 149 / MAX: 165MIN: 183.92 / MAX: 200.54MIN: 180.51 / MAX: 187.79MIN: 171.95 / MAX: 199.96

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER9001800270036004500SE +/- 13.62, N = 3SE +/- 5.47, N = 3SE +/- 10.06, N = 3SE +/- 12.09, N = 33313.263971.613927.113905.981. (CXX) g++ options: -lm -pthread -ldl -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -MD -MQ -MF

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C Bluestein benchmark in double precisionNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER10002000300040005000SE +/- 9.84, N = 3SE +/- 11.35, N = 3SE +/- 4.51, N = 3SE +/- 12.55, N = 341954647388644511. (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: 16 - Model: ResNet-152NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER4080120160200SE +/- 0.29, N = 3164.14194.29187.26195.40MIN: 145.67 / MAX: 165.38MIN: 182.25 / MAX: 197.39MIN: 179.81 / MAX: 188.21MIN: 186.09 / MAX: 197.7

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER4080120160200SE +/- 0.33, N = 2SE +/- 0.05, N = 3SE +/- 1.38, N = 2164.35194.87187.51195.30MIN: 149.91 / MAX: 166.09MIN: 180.8 / MAX: 198MIN: 181.57 / MAX: 188.05MIN: 182 / MAX: 199.43

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT R2C / C2RNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER12K24K36K48K60KSE +/- 320.62, N = 3SE +/- 520.37, N = 3SE +/- 745.02, N = 13SE +/- 702.53, N = 15484185544647097547941. (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: Orange Juice - Acceleration: GPUNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER3691215SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.07, N = 312.1411.8910.4011.72MIN: 10.24 / MAX: 16.71MIN: 9.85 / MAX: 15.88MIN: 8.31 / MAX: 13.9MIN: 9.6 / MAX: 15.44

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: BMW27 - Compute: NVIDIA OptiXNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER246810SE +/- 0.06, N = 14SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.06, N = 136.315.436.215.57

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Barbershop - Compute: NVIDIA OptiXNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER1326395265SE +/- 0.02, N = 2SE +/- 0.05, N = 3SE +/- 0.04, N = 3SE +/- 0.10, N = 354.3050.7358.4451.30

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER510152025SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 320.9620.2618.2019.80

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER160320480640800674.25735.94648.00720.97

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER50100150200250SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 31872112092101. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.72051.4412.16152.8823.6025SE +/- 0.011, N = 3SE +/- 0.009, N = 3SE +/- 0.028, N = 3SE +/- 0.014, N = 33.2022.8543.1682.855

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C Bluestein in single precisionNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER3K6K9K12K15KSE +/- 115.62, N = 3SE +/- 118.41, N = 3SE +/- 52.09, N = 3SE +/- 102.52, N = 3142051512513714151661. (CXX) g++ options: -O3 -lrt

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER1224364860SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 352.0153.5948.5252.81

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 - sCOPYNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER80160240320400SE +/- 1.00, N = 3SE +/- 0.00, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 33633363303341. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-TTNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER306090120150SE +/- 0.88, N = 3SE +/- 2.08, N = 3SE +/- 1.20, N = 3SE +/- 2.08, N = 31131241181221. (CXX) g++ options: -fopenmp -O3 -rdynamic -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: CopyNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER80160240320400SE +/- 0.22, N = 3SE +/- 0.00, N = 3SE +/- 0.09, N = 3SE +/- 0.03, N = 3360.8333.3330.3331.81. (CC) gcc options: -O2 -flto -lOpenCL

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C multidimensional in single precisionNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER11K22K33K44K55KSE +/- 407.28, N = 15SE +/- 417.77, N = 15SE +/- 476.57, N = 5SE +/- 407.19, N = 15508565152847212502991. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER306090120150SE +/- 2.08, N = 3SE +/- 2.08, N = 3SE +/- 2.31, N = 3SE +/- 1.00, N = 21211251211151. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-NNNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER306090120150SE +/- 1.86, N = 3SE +/- 1.15, N = 3SE +/- 1.86, N = 3SE +/- 4.04, N = 31131171221191. (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: AlexNetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 0.20, N = 15SE +/- 0.06, N = 2SE +/- 0.16, N = 3SE +/- 0.22, N = 214.4514.7914.0413.92

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 3090NVIDIA RTX 4070 TINVIDIA RTX 407020406080100SE +/- 0.53, N = 2SE +/- 0.52, N = 298.11103.45103.68MIN: 89.88 / MAX: 100.25MIN: 95.22 / MAX: 105.88MIN: 96.86 / MAX: 105.56

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'

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER80160240320400SE +/- 0.33, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 33743913873891. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER20406080100SE +/- 0.19, N = 3SE +/- 0.36, N = 2SE +/- 0.39, N = 399.25103.50101.43103.57MIN: 91.16 / MAX: 101.18MIN: 94.95 / MAX: 105.61MIN: 93.27 / MAX: 103.58MIN: 95.95 / MAX: 105.54

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER306090120150SE +/- 3.28, N = 3SE +/- 1.20, N = 3SE +/- 1.76, N = 3SE +/- 2.08, N = 31191181221171. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sDOTNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER80160240320400SE +/- 0.58, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 33763653623701. (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: 256 - Model: Efficientnet_v2_lNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER20406080100SE +/- 0.57, N = 3SE +/- 0.05, N = 299.43103.24101.24103.17MIN: 90.49 / MAX: 101.97MIN: 95.41 / MAX: 104.9MIN: 93.33 / MAX: 102.92MIN: 95.79 / MAX: 105.15

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_lNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER20406080100SE +/- 0.14, N = 3SE +/- 0.39, N = 2SE +/- 0.45, N = 3SE +/- 1.49, N = 299.84103.20101.55102.60MIN: 92.73 / MAX: 101.46MIN: 95.31 / MAX: 105.27MIN: 93.44 / MAX: 103.08MIN: 79.69 / MAX: 105.28

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_lNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER20406080100SE +/- 0.33, N = 3SE +/- 0.55, N = 3105.55108.59107.59106.37MIN: 91.76 / MAX: 107.42MIN: 99.04 / MAX: 110.68MIN: 98.77 / MAX: 109.43MIN: 97.91 / MAX: 108.16

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER4080120160200SE +/- 0.09, N = 2SE +/- 0.73, N = 3SE +/- 0.36, N = 3197.12201.19198.18201.94MIN: 137.37 / MAX: 198.9MIN: 180.79 / MAX: 203.92MIN: 181.27 / MAX: 200.06MIN: 183.53 / MAX: 206.5

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.31050.6210.93151.2421.5525SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 21.381.381.361.35

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER306090120150SE +/- 0.33, N = 3SE +/- 2.00, N = 3SE +/- 4.81, N = 3SE +/- 2.19, N = 31541561531561. (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: av1_grain_lapNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER9001800270036004500SE +/- 12.99, N = 3SE +/- 21.66, N = 3SE +/- 66.69, N = 3SE +/- 5.52, N = 34126.894140.874103.404171.001. (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: 16 - Model: AlexNetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER714212835SE +/- 0.07, N = 3SE +/- 0.08, N = 3SE +/- 0.17, N = 331.9831.7031.4531.59

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 - dDOTNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER20406080100SE +/- 0.84, N = 3SE +/- 0.58, N = 3SE +/- 0.22, N = 3SE +/- 0.09, N = 395.296.496.796.81. (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: GoogLeNetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER3691215SE +/- 0.07, N = 3SE +/- 0.30, N = 2SE +/- 0.10, N = 3SE +/- 0.17, N = 212.8212.7912.7812.62

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 - dCOPYNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER1632486480SE +/- 0.72, N = 3SE +/- 0.74, N = 3SE +/- 0.25, N = 3SE +/- 0.32, N = 370.271.371.070.81. (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: 512 - Model: AlexNetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER816243240SE +/- 0.01, N = 3SE +/- 0.09, N = 2SE +/- 0.03, N = 3SE +/- 0.02, N = 235.5835.4435.2135.10

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 16 - Model: VGG-16NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.33750.6751.01251.351.6875SE +/- 0.00, N = 3SE +/- 0.01, N = 2SE +/- 0.00, N = 21.491.491.501.48

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 256 - Model: AlexNetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070 SUPER816243240SE +/- 0.07, N = 3SE +/- 0.07, N = 2SE +/- 0.01, N = 334.4634.6134.16

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 0.06, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 215.6715.8115.6315.61

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER20406080100SE +/- 0.94, N = 3SE +/- 0.57, N = 3SE +/- 0.44, N = 3SE +/- 0.12, N = 386.287.386.887.21. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER1.25332.50663.75995.01326.2665SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 2SE +/- 0.01, N = 25.575.505.555.51

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-NNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER20406080100SE +/- 0.88, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 31031031031021. (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: GoogLeNetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 0.08, N = 3SE +/- 0.06, N = 2SE +/- 0.07, N = 315.6315.5015.5415.52

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.

OpenBenchmarking.orgGFLOPS, More Is Bettervkpeak 20230730fp32-vec4NVIDIA RTX 30906K12K18K24K30KSE +/- 1.51, N = 326563.72

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER306090120150SE +/- 1.20, N = 3SE +/- 0.88, N = 3SE +/- 1.20, N = 3SE +/- 1.20, N = 31321321311321. (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: ResNet-50NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER1.25332.50663.75995.01326.2665SE +/- 0.01, N = 3SE +/- 0.01, N = 2SE +/- 0.00, N = 3SE +/- 0.01, N = 25.575.535.555.55

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 32 - Model: AlexNetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER816243240SE +/- 0.05, N = 3SE +/- 0.04, N = 3SE +/- 0.18, N = 3SE +/- 0.15, N = 233.5333.2933.3233.40

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 1 - Model: ResNet-50NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.97881.95762.93643.91524.894SE +/- 0.03, N = 3SE +/- 0.02, N = 2SE +/- 0.01, N = 34.354.324.344.35

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 256 - Model: VGG-16NVIDIA RTX 3090NVIDIA RTX 4070 TI0.33980.67961.01941.35921.699SE +/- 0.00, N = 31.511.50

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 3090NVIDIA RTX 4070 TINVIDIA RTX 40700.33980.67961.01941.35921.699SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 31.511.501.50

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: 16 - Model: ResNet-50NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER1.23532.47063.70594.94126.1765SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 25.495.465.495.46

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.

OpenBenchmarking.orgGFLOPS, More Is Bettervkpeak 20230730fp32-scalarNVIDIA RTX 30904K8K12K16K20KSE +/- 36.15, N = 320263.13

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER816243240SE +/- 0.08, N = 3SE +/- 0.06, N = 3SE +/- 0.14, N = 333.9334.0633.9333.97

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.

OpenBenchmarking.orgGIOPS, More Is Bettervkpeak 20230730int16-scalarNVIDIA RTX 30903K6K9K12K15KSE +/- 0.21, N = 313259.97

OpenBenchmarking.orgGFLOPS, More Is Bettervkpeak 20230730fp16-scalarNVIDIA RTX 30904K8K12K16K20KSE +/- 34.71, N = 320080.47

OpenBenchmarking.orgGFLOPS, More Is Bettervkpeak 20230730fp16-vec4NVIDIA RTX 30909K18K27K36K45KSE +/- 69.71, N = 339771.97

OpenBenchmarking.orgGIOPS, More Is Bettervkpeak 20230730int16-vec4NVIDIA RTX 30904K8K12K16K20KSE +/- 1.52, N = 316331.16

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 0.05, N = 3SE +/- 0.07, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 315.6815.6915.6615.67

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.

OpenBenchmarking.orgGIOPS, More Is Bettervkpeak 20230730int32-scalarNVIDIA RTX 30904K8K12K16K20KSE +/- 3.21, N = 320280.33

OpenBenchmarking.orgGFLOPS, More Is Bettervkpeak 20230730fp64-vec4NVIDIA RTX 3090140280420560700SE +/- 0.02, N = 3638.72

OpenBenchmarking.orgGIOPS, More Is Bettervkpeak 20230730int32-vec4NVIDIA RTX 30904K8K12K16K20KSE +/- 2.34, N = 319996.92

OpenBenchmarking.orgGFLOPS, More Is Bettervkpeak 20230730fp64-scalarNVIDIA RTX 3090140280420560700SE +/- 0.03, N = 3638.70

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: VGG-16NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.33750.6751.01251.351.6875SE +/- 0.00, N = 3SE +/- 0.00, N = 2SE +/- 0.00, N = 3SE +/- 0.00, N = 31.501.501.501.50

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER246810SE +/- 2.14, N = 6SE +/- 0.12, N = 8SE +/- 0.10, N = 9SE +/- 0.29, N = 96.382.842.342.86MIN: 2.14 / MAX: 1476.09MIN: 2.4 / MAX: 5.07MIN: 2 / MAX: 3.86MIN: 2.17 / MAX: 577.171. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: vision_transformerNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER2004006008001000SE +/- 76.74, N = 6SE +/- 25.65, N = 9SE +/- 61.31, N = 9SE +/- 87.53, N = 9663.24390.18281.56844.61MIN: 46.42 / MAX: 1833.21MIN: 46.49 / MAX: 1816.77MIN: 46.48 / MAX: 1913.33MIN: 46.34 / MAX: 1866.931. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: regnety_400mNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER3691215SE +/- 1.17, N = 6SE +/- 0.24, N = 9SE +/- 0.31, N = 8SE +/- 3.28, N = 98.065.976.5011.11MIN: 5.43 / MAX: 1922.26MIN: 5.49 / MAX: 7.35MIN: 5.52 / MAX: 460.02MIN: 5.49 / MAX: 4942.191. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: squeezenet_ssdNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER246810SE +/- 1.57, N = 6SE +/- 0.29, N = 9SE +/- 0.17, N = 9SE +/- 1.76, N = 96.635.365.276.86MIN: 4.43 / MAX: 1636.66MIN: 4.55 / MAX: 496.3MIN: 4.53 / MAX: 7.53MIN: 4.34 / MAX: 1630.011. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: yolov4-tinyNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER1428425670SE +/- 5.27, N = 6SE +/- 2.58, N = 9SE +/- 7.50, N = 9SE +/- 10.56, N = 926.8516.4725.1163.82MIN: 10.35 / MAX: 853.14MIN: 10.61 / MAX: 826.68MIN: 10.66 / MAX: 857.35MIN: 10.28 / MAX: 858.441. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: resnet50NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER1020304050SE +/- 11.48, N = 6SE +/- 4.23, N = 9SE +/- 0.10, N = 9SE +/- 14.70, N = 927.7714.328.2446.26MIN: 7.77 / MAX: 1603.33MIN: 7.9 / MAX: 1787.49MIN: 7.87 / MAX: 9.87MIN: 7.71 / MAX: 1829.991. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: alexnetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 0.02, N = 6SE +/- 0.03, N = 9SE +/- 3.71, N = 9SE +/- 5.86, N = 93.693.749.3316.17MIN: 3.59 / MAX: 7.37MIN: 3.61 / MAX: 3.98MIN: 3.5 / MAX: 430.03MIN: 3.52 / MAX: 436.521. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: resnet18NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 6.10, N = 6SE +/- 1.33, N = 9SE +/- 3.20, N = 9SE +/- 3.49, N = 917.415.478.588.97MIN: 4.05 / MAX: 900.27MIN: 3.95 / MAX: 726.67MIN: 3.98 / MAX: 912.04MIN: 3.94 / MAX: 922.041. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: vgg16NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER306090120150SE +/- 22.21, N = 6SE +/- 11.81, N = 9SE +/- 19.29, N = 9SE +/- 29.60, N = 9145.7232.0554.54117.81MIN: 17.46 / MAX: 648.88MIN: 17.34 / MAX: 644.35MIN: 17.54 / MAX: 646.66MIN: 17.16 / MAX: 647.671. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: googlenetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER3691215SE +/- 1.05, N = 6SE +/- 0.14, N = 9SE +/- 0.14, N = 9SE +/- 1.21, N = 97.495.876.0611.04MIN: 5.46 / MAX: 1242.73MIN: 5.2 / MAX: 6.88MIN: 5.33 / MAX: 8.36MIN: 5.28 / MAX: 1769.191. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: blazefaceNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.19580.39160.58740.78320.979SE +/- 0.03, N = 6SE +/- 0.03, N = 9SE +/- 0.03, N = 9SE +/- 0.04, N = 90.860.810.840.84MIN: 0.64 / MAX: 3.3MIN: 0.61 / MAX: 1.19MIN: 0.64 / MAX: 0.96MIN: 0.65 / MAX: 4.631. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: efficientnet-b0NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 9.20, N = 6SE +/- 0.06, N = 9SE +/- 0.09, N = 9SE +/- 0.97, N = 913.873.493.465.07MIN: 2.86 / MAX: 2218.7MIN: 3.18 / MAX: 4.03MIN: 2.91 / MAX: 3.79MIN: 3.22 / MAX: 1124.21. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: mnasnetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.93151.8632.79453.7264.6575SE +/- 0.06, N = 5SE +/- 0.05, N = 9SE +/- 0.08, N = 8SE +/- 1.31, N = 92.242.302.223.85MIN: 2.07 / MAX: 6.02MIN: 2.15 / MAX: 2.58MIN: 1.83 / MAX: 2.54MIN: 1.89 / MAX: 1093.291. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: shufflenet-v2NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER0.93831.87662.81493.75324.6915SE +/- 2.18, N = 6SE +/- 0.10, N = 8SE +/- 0.12, N = 7SE +/- 0.34, N = 84.172.032.112.31MIN: 1.83 / MAX: 1393.33MIN: 1.84 / MAX: 2.58MIN: 1.77 / MAX: 2.53MIN: 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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER246810SE +/- 1.14, N = 6SE +/- 0.09, N = 9SE +/- 6.77, N = 8SE +/- 0.16, N = 93.192.098.712.25MIN: 1.82 / MAX: 1210.31MIN: 1.78 / MAX: 2.85MIN: 1.73 / MAX: 1561.29MIN: 1.75 / MAX: 343.71. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER1.05532.11063.16594.22125.2765SE +/- 0.13, N = 6SE +/- 0.07, N = 9SE +/- 2.36, N = 9SE +/- 0.44, N = 92.652.434.693.03MIN: 2.23 / MAX: 6.49MIN: 2.09 / MAX: 5.8MIN: 1.91 / MAX: 1305.64MIN: 2.38 / MAX: 970.871. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: mobilenetNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER3691215SE +/- 4.97, N = 6SE +/- 0.98, N = 9SE +/- 2.50, N = 9SE +/- 0.47, N = 912.078.4310.148.62MIN: 6.42 / MAX: 1193.34MIN: 6.51 / MAX: 1023.8MIN: 6.53 / MAX: 1509.26MIN: 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

NVIDIA RTX 3090: 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.

NVIDIA RTX 3090: 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.

NVIDIA RTX 3090: 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.

NVIDIA RTX 3090: 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.

NVIDIA RTX 3090: 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.

NVIDIA RTX 3090: 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()

NVIDIA RTX 3090: 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: @ 0x7792f141e450 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()

NVIDIA RTX 3090: 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: @ 0x7bfcc77e3450 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()

NVIDIA RTX 3090: 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: @ 0x7522f0d76450 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()

NVIDIA RTX 3090: 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: @ 0x7d66735f5450 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()

NVIDIA RTX 3090: 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: @ 0x7ace5f7b4450 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()

NVIDIA RTX 3090: 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: @ 0x77ed97de3450 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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER20406080100SE +/- 0.33, N = 3SE +/- 6.30, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3110.0102.7109.0109.01. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - sDOTNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER4080120160200SE +/- 35.40, N = 3SE +/- 2.40, N = 3SE +/- 3.76, N = 3SE +/- 2.73, N = 3132.1168.0166.0165.01. (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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER246810SE +/- 0.006, N = 3SE +/- 0.003, N = 3SE +/- 0.003, N = 3SE +/- 0.114, N = 155.7415.2266.9065.9121. (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

NVIDIA RTX 3090: 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

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: DLSC - Acceleration: GPUNVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER48121620SE +/- 1.13, N = 12SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 312.9913.9511.7413.59MIN: 0.52 / MAX: 14.69MIN: 13.67 / MAX: 14.14MIN: 11.35 / MAX: 11.83MIN: 12.52 / MAX: 13.84

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.

NVIDIA RTX 3090: 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.

NVIDIA RTX 3090: 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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER246810SE +/- 0.016, N = 3SE +/- 0.039, N = 3SE +/- 0.006, N = 3SE +/- 0.150, N = 155.5565.9627.0926.323

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 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER20406080100SE +/- 0.13, N = 3SE +/- 6.65, N = 599.0596.50102.90102.60MIN: 91.8 / MAX: 100.69MIN: 64.35 / MAX: 104.79MIN: 95.98 / MAX: 104.54MIN: 94.84 / MAX: 104.25

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50NVIDIA RTX 3090NVIDIA RTX 4070 TINVIDIA RTX 4070NVIDIA RTX 4070 SUPER120240360480600SE +/- 11.16, N = 12SE +/- 3.09, N = 3525.12535.39546.76557.73MIN: 458.54 / MAX: 542.46MIN: 428.43 / MAX: 572.99MIN: 195.25 / MAX: 556.94MIN: 513.63 / MAX: 563.37

148 Results Shown

VkFFT
ProjectPhysX OpenCL-Benchmark
VkFFT:
  FFT + iFFT C2C 1D batched in single precision, no reshuffling
  FFT + iFFT C2C 1D batched in single precision
clpeak
ProjectPhysX OpenCL-Benchmark
cl-mem:
  Write
  Read
VkResample
ViennaCL
NAMD CUDA
Libplacebo
ViennaCL
LuxCoreRender
ViennaCL
RealSR-NCNN
ProjectPhysX OpenCL-Benchmark
VkFFT
clpeak:
  Integer Compute INT
  Single-Precision Float
NeatBench
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
ViennaCL:
  OpenCL BLAS - dGEMM-TN
  OpenCL BLAS - dGEMM-NT
  OpenCL BLAS - sAXPY
ProjectPhysX OpenCL-Benchmark
MandelGPU
ViennaCL
GpuOwl
Libplacebo:
  deband_heavy
  polar_nocompute
Rodinia
Blender:
  Classroom - NVIDIA OptiX
  Pabellon Barcelona - NVIDIA OptiX
LuxCoreRender
Blender
PyTorch:
  NVIDIA CUDA GPU - 256 - ResNet-152
  NVIDIA CUDA GPU - 32 - ResNet-152
  NVIDIA CUDA GPU - 16 - ResNet-50
  NVIDIA CUDA GPU - 512 - ResNet-50
LuxCoreRender
PyTorch:
  NVIDIA CUDA GPU - 64 - ResNet-50
  NVIDIA CUDA GPU - 256 - ResNet-50
FAHBench
PyTorch:
  NVIDIA CUDA GPU - 32 - ResNet-50
  NVIDIA CUDA GPU - 64 - ResNet-152
Libplacebo
VkFFT
PyTorch:
  NVIDIA CUDA GPU - 16 - ResNet-152
  NVIDIA CUDA GPU - 512 - ResNet-152
VkFFT
LuxCoreRender
Blender:
  BMW27 - NVIDIA OptiX
  Barbershop - NVIDIA OptiX
IndigoBench
OctaneBench
ViennaCL
Waifu2x-NCNN Vulkan
VkFFT
IndigoBench
ViennaCL:
  OpenCL BLAS - sCOPY
  CPU BLAS - dGEMM-TT
cl-mem
VkFFT
ViennaCL:
  CPU BLAS - dGEMM-TN
  CPU BLAS - dGEMM-NN
TensorFlow
PyTorch
ViennaCL
PyTorch
ViennaCL:
  CPU BLAS - dGEMM-NT
  OpenCL BLAS - sDOT
PyTorch:
  NVIDIA CUDA GPU - 256 - Efficientnet_v2_l
  NVIDIA CUDA GPU - 64 - Efficientnet_v2_l
  NVIDIA CUDA GPU - 1 - Efficientnet_v2_l
  NVIDIA CUDA GPU - 1 - ResNet-152
TensorFlow
ViennaCL
Libplacebo
TensorFlow
ViennaCL
TensorFlow
ViennaCL
TensorFlow:
  GPU - 512 - AlexNet
  GPU - 16 - VGG-16
  GPU - 256 - AlexNet
  GPU - 32 - GoogLeNet
ViennaCL
TensorFlow
ViennaCL
TensorFlow
vkpeak
ViennaCL
TensorFlow:
  GPU - 64 - ResNet-50
  GPU - 32 - AlexNet
  GPU - 1 - ResNet-50
  GPU - 256 - VGG-16
  GPU - 64 - VGG-16
  GPU - 16 - ResNet-50
vkpeak
TensorFlow
vkpeak:
  int16-scalar
  fp16-scalar
  fp16-vec4
  int16-vec4
TensorFlow
vkpeak:
  int32-scalar
  fp64-vec4
  int32-vec4
  fp64-scalar
TensorFlow
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:
  CPU BLAS - dGEMV-T
  CPU BLAS - sDOT
FinanceBench
LuxCoreRender
RealSR-NCNN
PyTorch:
  NVIDIA CUDA GPU - 32 - Efficientnet_v2_l
  NVIDIA CUDA GPU - 1 - ResNet-50