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%123%146%169%192%NCNNNAMD CUDAcl-memVkResampleclpeakVkFFTRealSR-NCNNFinanceBenchNeatBenchProjectPhysX OpenCL-BenchmarkHashcatGpuOwlMandelGPURodiniaTensorFlowLuxCoreRenderFAHBenchBlenderPyTorchOctaneBenchWaifu2x-NCNN VulkanIndigoBenchLibplaceboViennaCL

RTX 4070 SUPERtensorflow: GPU - 256 - VGG-16tensorflow: GPU - 64 - VGG-16tensorflow: GPU - 32 - VGG-16tensorflow: GPU - 512 - AlexNettensorflow: GPU - 64 - ResNet-50tensorflow: GPU - 16 - 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 - efficientnet-b0ncnn: Vulkan GPU - mnasnetncnn: Vulkan GPU - shufflenet-v2ncnn: Vulkan GPU-v2-v2 - mobilenet-v2ncnn: Vulkan GPU - mobilenetncnn: Vulkan GPU - googlenetncnn: Vulkan GPU - blazefacencnn: Vulkan GPU-v3-v3 - mobilenet-v3tensorflow: GPU - 256 - AlexNettensorflow: GPU - 32 - ResNet-50tensorflow: GPU - 64 - GoogLeNettensorflow: GPU - 16 - ResNet-50vkpeak: int16-vec4vkpeak: int16-scalarvkpeak: int32-vec4vkpeak: int32-scalarvkpeak: fp64-vec4vkpeak: fp64-scalarvkpeak: fp16-vec4vkpeak: fp16-scalarvkpeak: fp32-vec4vkpeak: fp32-scalartensorflow: GPU - 32 - GoogLeNettensorflow: GPU - 64 - AlexNetgpuowl: 77936867gpuowl: 332220523octanebench: Total Scorevkfft: FFT + iFFT C2C multidimensional in single precisiongpuowl: 57885161tensorflow: GPU - 16 - GoogLeNetluxcorerender: DLSC - GPUvkfft: FFT + iFFT C2C Bluestein benchmark in double precisiontensorflow: GPU - 32 - AlexNetfahbench: vkresample: 2x - Doubleindigobench: OpenCL GPU - Bedroomvkfft: FFT + iFFT C2C 1D batched in double precisionindigobench: OpenCL GPU - Supercarluxcorerender: LuxCore Benchmark - GPUvkfft: FFT + iFFT C2C Bluestein in single precisionluxcorerender: Orange Juice - GPUluxcorerender: Danish Mood - GPUtensorflow: GPU - 1 - VGG-16blender: Barbershop - NVIDIA OptiXvkfft: FFT + iFFT C2C 1D batched in single precisionvkfft: FFT + iFFT C2C 1D batched in single precision, no reshufflingvkfft: FFT + iFFT R2C / C2Rtensorflow: GPU - 16 - AlexNetlibplacebo: av1_grain_laplibplacebo: hdr_lutlibplacebo: hdr_peakdetectlibplacebo: polar_nocomputelibplacebo: deband_heavyrealsr-ncnn: 4x - Yesvkfft: FFT + iFFT C2C 1D batched in half precisionnamd-cuda: ATPase Simulation - 327,506 Atomsblender: Fishy Cat - NVIDIA OptiXpytorch: NVIDIA CUDA GPU - 32 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 64 - Efficientnet_v2_ltensorflow: GPU - 1 - ResNet-50viennacl: CPU BLAS - dGEMM-TTviennacl: CPU BLAS - dGEMM-TNviennacl: CPU BLAS - dGEMM-NTviennacl: CPU BLAS - dGEMM-NNviennacl: CPU BLAS - dGEMV-Tviennacl: CPU BLAS - dGEMV-Nviennacl: CPU BLAS - dDOTviennacl: CPU BLAS - dAXPYviennacl: CPU BLAS - dCOPYviennacl: CPU BLAS - sDOTviennacl: CPU BLAS - sAXPYviennacl: CPU BLAS - sCOPYpytorch: NVIDIA CUDA GPU - 512 - Efficientnet_v2_lviennacl: OpenCL BLAS - dGEMM-TTviennacl: OpenCL BLAS - dGEMM-TNviennacl: OpenCL BLAS - dGEMM-NTviennacl: OpenCL BLAS - dGEMM-NNviennacl: OpenCL BLAS - dGEMV-Tviennacl: OpenCL BLAS - dGEMV-Nviennacl: OpenCL BLAS - dDOTviennacl: OpenCL BLAS - dAXPYviennacl: OpenCL BLAS - dCOPYviennacl: OpenCL BLAS - sDOTviennacl: OpenCL BLAS - sAXPYviennacl: OpenCL BLAS - sCOPYpytorch: NVIDIA CUDA GPU - 256 - Efficientnet_v2_ltensorflow: GPU - 1 - AlexNetblender: BMW27 - NVIDIA OptiXblender: Pabellon Barcelona - NVIDIA OptiXblender: Classroom - NVIDIA OptiXpytorch: NVIDIA CUDA GPU - 16 - Efficientnet_v2_lopencl-benchmark: Memory Bandwidth Coalesced Writeopencl-benchmark: Memory Bandwidth Coalesced Readopencl-benchmark: INT8 Computeopencl-benchmark: INT16 Computeopencl-benchmark: INT32 Computeopencl-benchmark: INT64 Computeopencl-benchmark: FP32 Computeopencl-benchmark: FP64 Computerealsr-ncnn: 4x - Nopytorch: NVIDIA CUDA GPU - 512 - ResNet-152pytorch: NVIDIA CUDA GPU - 64 - ResNet-152pytorch: NVIDIA CUDA GPU - 256 - ResNet-152pytorch: NVIDIA CUDA GPU - 1 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 32 - ResNet-152tensorflow: GPU - 1 - GoogLeNetvkresample: 2x - Singleclpeak: Double-Precision Doublepytorch: NVIDIA CUDA GPU - 16 - ResNet-152luxcorerender: Rainbow Colors and Prism - GPUpytorch: NVIDIA CUDA GPU - 1 - ResNet-50pytorch: NVIDIA CUDA GPU - 64 - ResNet-50rodinia: OpenCL Particle Filterhashcat: MD5hashcat: SHA1hashcat: SHA-512pytorch: NVIDIA CUDA GPU - 256 - ResNet-50pytorch: NVIDIA CUDA GPU - 1 - ResNet-152pytorch: NVIDIA CUDA GPU - 16 - ResNet-50pytorch: NVIDIA CUDA GPU - 512 - ResNet-50pytorch: NVIDIA CUDA GPU - 32 - ResNet-50hashcat: TrueCrypt RIPEMD160 + XTScl-mem: Copycl-mem: Writecl-mem: Readhashcat: 7-Zipwaifu2x-ncnn: 2x - 3 - Yesclpeak: Global Memory Bandwidthmandelgpu: GPUfinancebench: Black-Scholes OpenCLclpeak: Integer Compute INTclpeak: Single-Precision Floatneatbench: GPUarrayfire: Conjugate Gradient OpenCLNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901.5035.105.551.482.86844.6111.116.8663.8246.2616.178.97117.815.073.852.313.038.6211.040.842.2534.165.5115.525.4615.6133.97646.41137.44720.97378950299869.0715.6713.59445133.4366.0576339.59319.8012431752.81312.821516611.7210.561.3551.3073929750785479431.594171.003905.983292.372327.552186.7034.8851317050.067919.45102.60102.604.3512211511711910910296.887.270.8165156132103.57613599584577389210458437423370392334103.1713.925.5714.2912.60455.01464.8614.30717.17019.8894.21438.5940.6216.323195.30196.07194.58106.37195.3912.6218.489630.11195.4027.67557.73507.453.48067583033333221326000003232733333504.67201.94509.45504.27501.50802967331.8407.5446.211764672.855437.65587219538.25.91218170.5435492.6940701.501.535.215.551.502.67382.826.215.1820.748.725.785.1145.523.592.242.082.487.206.060.842.155.5515.545.4915.6333.93530.32112.61647.99786747212714.8015.6611.74388633.32317.1952415.16018.2032239048.51710.921371410.408.891.3658.4477774790574709731.454152.413946.903329.261968.371843.2642.8521377620.0749811.03102.90101.554.3411812112212210910396.786.871.0166153131101.43502494477473387209456455423362389330101.2414.046.2116.5514.86103.68459.43465.1812.11614.28416.3773.44331.7680.5107.092187.51186.63187.27107.59187.6912.7818.016515.17187.2623.26546.76458.364.09856147866667182024666672673300000459.93198.18458.39459.27459.94660967330.3406.7446.39769673.168437.21516770131.26.90614555.1928479.3940701.51.51.535.445.531.493.04497.665.896.1316.3712.256.077.7434.493.464.142.012.547.457.370.822.0934.615.5015.505.4615.8134.06676.59145.84735.94059351528919.1315.6913.95464733.29382.1637322.06420.2562543153.58913.231512511.8910.991.3850.7373942751415544631.704143.963976.043475.062459.032306.5633.6261362100.067889.0296.50103.204.32124125118117102.710396.487.371.3168156132103.50648634612604391211457437424365393336103.2414.795.4313.9712.30103.45457.17465.0715.73118.28121.0474.42040.9140.6605.962194.87197.02195.86108.59198.8212.7918.456667.05194.2927.71535.39505.623.29173312233333235324000003462500000201.19502.92504.66505.55858600333.3412.2446.312626332.854437.63619106132.55.22619821.1038691.7340701.511.511.535.585.571.492.65354.576.734.9011.2912.703.604.1217.883.342.162.042.347.276.140.872.2134.465.5715.635.4916329.7213264.9120009.7320295.27638.74638.8439860.8020151.4426699.6620353.9515.6733.93645.99137.32674.25091250856866.3115.6812.99419533.53343.0199333.63920.9593091252.01413.121420512.1410.201.3854.301418761443114841831.984100.363369.885055.882116.792020.1630.3132732210.1082210.6499.0599.844.3511312111911311010395.286.270.2132.115413299.2559359459559237418765972460537649836399.4314.456.3117.3015.2698.11887.31864.1113.72717.00120.0273.13539.3950.6375.556164.35164.14161.01105.55163.7412.8210.323642.23164.1433.29525.12419.033.84467177300000213237333333081866667416.89197.12419.76416.20420.29797833360.8753.8825.810560003.202816.55484098913.85.74117923.3334906.793090OpenBenchmarking.org

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 256 - Model: VGG-16NVIDIA RTX 4070 TINVIDIA RTX 30900.33980.67961.01941.35921.699SE +/- 0.00, N = 31.501.51

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

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

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 64 - Model: VGG-16NVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.33980.67961.01941.35921.699SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 31.501.501.51

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

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 32 - Model: VGG-16NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.33750.6751.01251.351.6875SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 2SE +/- 0.00, N = 31.501.501.501.50

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 512 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090816243240SE +/- 0.02, N = 2SE +/- 0.03, N = 3SE +/- 0.09, N = 2SE +/- 0.01, N = 335.1035.2135.4435.58

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 64 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901.25332.50663.75995.01326.2665SE +/- 0.01, N = 2SE +/- 0.00, N = 3SE +/- 0.01, N = 2SE +/- 0.01, N = 35.555.555.535.57

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 16 - Model: VGG-16NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.33750.6751.01251.351.6875SE +/- 0.00, N = 2SE +/- 0.01, N = 2SE +/- 0.00, N = 31.481.501.491.49

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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090246810SE +/- 0.29, N = 9SE +/- 0.10, N = 9SE +/- 0.12, N = 8SE +/- 2.14, N = 62.862.342.846.38MIN: 2.17 / MAX: 577.17MIN: 2 / MAX: 3.86MIN: 2.4 / MAX: 5.07MIN: 2.14 / MAX: 1476.091. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: vision_transformerNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30902004006008001000SE +/- 87.53, N = 9SE +/- 61.31, N = 9SE +/- 25.65, N = 9SE +/- 76.74, N = 6844.61281.56390.18663.24MIN: 46.34 / MAX: 1866.93MIN: 46.48 / MAX: 1913.33MIN: 46.49 / MAX: 1816.77MIN: 46.42 / MAX: 1833.211. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: regnety_400mNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30903691215SE +/- 3.28, N = 9SE +/- 0.31, N = 8SE +/- 0.24, N = 9SE +/- 1.17, N = 611.116.505.978.06MIN: 5.49 / MAX: 4942.19MIN: 5.52 / MAX: 460.02MIN: 5.49 / MAX: 7.35MIN: 5.43 / MAX: 1922.261. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: squeezenet_ssdNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090246810SE +/- 1.76, N = 9SE +/- 0.17, N = 9SE +/- 0.29, N = 9SE +/- 1.57, N = 66.865.275.366.63MIN: 4.34 / MAX: 1630.01MIN: 4.53 / MAX: 7.53MIN: 4.55 / MAX: 496.3MIN: 4.43 / MAX: 1636.661. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: yolov4-tinyNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901428425670SE +/- 10.56, N = 9SE +/- 7.50, N = 9SE +/- 2.58, N = 9SE +/- 5.27, N = 663.8225.1116.4726.85MIN: 10.28 / MAX: 858.44MIN: 10.66 / MAX: 857.35MIN: 10.61 / MAX: 826.68MIN: 10.35 / MAX: 853.141. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: resnet50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901020304050SE +/- 14.70, N = 9SE +/- 0.10, N = 9SE +/- 4.23, N = 9SE +/- 11.48, N = 646.268.2414.3227.77MIN: 7.71 / MAX: 1829.99MIN: 7.87 / MAX: 9.87MIN: 7.9 / MAX: 1787.49MIN: 7.77 / MAX: 1603.331. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: alexnetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 5.86, N = 9SE +/- 3.71, N = 9SE +/- 0.03, N = 9SE +/- 0.02, N = 616.179.333.743.69MIN: 3.52 / MAX: 436.52MIN: 3.5 / MAX: 430.03MIN: 3.61 / MAX: 3.98MIN: 3.59 / MAX: 7.371. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: resnet18NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 3.49, N = 9SE +/- 3.20, N = 9SE +/- 1.33, N = 9SE +/- 6.10, N = 68.978.585.4717.41MIN: 3.94 / MAX: 922.04MIN: 3.98 / MAX: 912.04MIN: 3.95 / MAX: 726.67MIN: 4.05 / MAX: 900.271. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: vgg16NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090306090120150SE +/- 29.60, N = 9SE +/- 19.29, N = 9SE +/- 11.81, N = 9SE +/- 22.21, N = 6117.8154.5432.05145.72MIN: 17.16 / MAX: 647.67MIN: 17.54 / MAX: 646.66MIN: 17.34 / MAX: 644.35MIN: 17.46 / MAX: 648.881. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: efficientnet-b0NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 0.97, N = 9SE +/- 0.09, N = 9SE +/- 0.06, N = 9SE +/- 9.20, N = 65.073.463.4913.87MIN: 3.22 / MAX: 1124.2MIN: 2.91 / MAX: 3.79MIN: 3.18 / MAX: 4.03MIN: 2.86 / MAX: 2218.71. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: mnasnetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.93151.8632.79453.7264.6575SE +/- 1.31, N = 9SE +/- 0.08, N = 8SE +/- 0.05, N = 9SE +/- 0.06, N = 53.852.222.302.24MIN: 1.89 / MAX: 1093.29MIN: 1.83 / MAX: 2.54MIN: 2.15 / MAX: 2.58MIN: 2.07 / MAX: 6.021. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: shufflenet-v2NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.93831.87662.81493.75324.6915SE +/- 0.34, N = 8SE +/- 0.12, N = 7SE +/- 0.10, N = 8SE +/- 2.18, N = 62.312.112.034.17MIN: 1.76 / MAX: 421.42MIN: 1.77 / MAX: 2.53MIN: 1.84 / MAX: 2.58MIN: 1.83 / MAX: 1393.331. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901.05532.11063.16594.22125.2765SE +/- 0.44, N = 9SE +/- 2.36, N = 9SE +/- 0.07, N = 9SE +/- 0.13, N = 63.034.692.432.65MIN: 2.38 / MAX: 970.87MIN: 1.91 / MAX: 1305.64MIN: 2.09 / MAX: 5.8MIN: 2.23 / MAX: 6.491. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: mobilenetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30903691215SE +/- 0.47, N = 9SE +/- 2.50, N = 9SE +/- 0.98, N = 9SE +/- 4.97, N = 68.6210.148.4312.07MIN: 6.42 / MAX: 1101.3MIN: 6.53 / MAX: 1509.26MIN: 6.51 / MAX: 1023.8MIN: 6.42 / MAX: 1193.341. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: googlenetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30903691215SE +/- 1.21, N = 9SE +/- 0.14, N = 9SE +/- 0.14, N = 9SE +/- 1.05, N = 611.046.065.877.49MIN: 5.28 / MAX: 1769.19MIN: 5.33 / MAX: 8.36MIN: 5.2 / MAX: 6.88MIN: 5.46 / MAX: 1242.731. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: blazefaceNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.19580.39160.58740.78320.979SE +/- 0.04, N = 9SE +/- 0.03, N = 9SE +/- 0.03, N = 9SE +/- 0.03, N = 60.840.840.810.86MIN: 0.65 / MAX: 4.63MIN: 0.64 / MAX: 0.96MIN: 0.61 / MAX: 1.19MIN: 0.64 / MAX: 3.31. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090246810SE +/- 0.16, N = 9SE +/- 6.77, N = 8SE +/- 0.09, N = 9SE +/- 1.14, N = 62.258.712.093.19MIN: 1.75 / MAX: 343.7MIN: 1.73 / MAX: 1561.29MIN: 1.78 / MAX: 2.85MIN: 1.82 / MAX: 1210.311. (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.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 256 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070 TINVIDIA RTX 3090816243240SE +/- 0.01, N = 3SE +/- 0.07, N = 2SE +/- 0.07, N = 334.1634.6134.46

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: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901.25332.50663.75995.01326.2665SE +/- 0.01, N = 2SE +/- 0.01, N = 2SE +/- 0.02, N = 3SE +/- 0.01, N = 35.515.555.505.57

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 64 - Model: GoogLeNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 0.07, N = 3SE +/- 0.06, N = 2SE +/- 0.08, N = 315.5215.5415.5015.63

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 16 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901.23532.47063.70594.94126.1765SE +/- 0.00, N = 2SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 35.465.495.465.49

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-vec4NVIDIA RTX 30904K8K12K16K20KSE +/- 1.52, N = 316331.16

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

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

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

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

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

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

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: 32 - Model: GoogLeNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 0.01, N = 2SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 315.6115.6315.8115.67

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 64 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090816243240SE +/- 0.14, N = 3SE +/- 0.06, N = 3SE +/- 0.08, N = 333.9733.9334.0633.93

GpuOwl

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

OpenBenchmarking.orgIterations / Second, More Is BetterGpuOwl 7.2.1Exponent: 77936867NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090150300450600750SE +/- 0.00, N = 3SE +/- 0.09, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3646.41530.32676.59645.99

OpenBenchmarking.orgIterations / Second, More Is BetterGpuOwl 7.2.1Exponent: 332220523NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090306090120150SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3137.44112.61145.84137.32

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

OctaneBench

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

OpenBenchmarking.orgScore, More Is BetterOctaneBench 2020.1Total ScoreNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090160320480640800720.97648.00735.94674.25

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C multidimensional in single precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309011K22K33K44K55KSE +/- 407.19, N = 15SE +/- 476.57, N = 5SE +/- 417.77, N = 15SE +/- 407.28, N = 15502994721251528508561. (CXX) g++ options: -O3 -lrt

GpuOwl

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

OpenBenchmarking.orgIterations / Second, More Is BetterGpuOwl 7.2.1Exponent: 57885161NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30902004006008001000SE +/- 1.26, N = 3SE +/- 0.00, N = 3SE +/- 2.53, N = 3SE +/- 2.01, N = 3869.07714.80919.13866.31

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 16 - Model: GoogLeNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.07, N = 3SE +/- 0.05, N = 315.6715.6615.6915.68

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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 1.13, N = 1213.5911.7413.9512.99MIN: 12.52 / MAX: 13.84MIN: 11.35 / MAX: 11.83MIN: 13.67 / MAX: 14.14MIN: 0.52 / MAX: 14.69

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C Bluestein benchmark in double precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309010002000300040005000SE +/- 12.55, N = 3SE +/- 4.51, N = 3SE +/- 11.35, N = 3SE +/- 9.84, N = 344513886464741951. (CXX) g++ options: -O3 -lrt

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.

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: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090816243240SE +/- 0.15, N = 2SE +/- 0.18, N = 3SE +/- 0.04, N = 3SE +/- 0.05, N = 333.4033.3233.2933.53

FAHBench

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

OpenBenchmarking.orgNs Per Day, More Is BetterFAHBench 2.3.2NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309080160240320400SE +/- 0.39, N = 3SE +/- 0.12, N = 3SE +/- 0.26, N = 3SE +/- 0.26, N = 3366.06317.20382.16343.02

VkResample

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

OpenBenchmarking.orgms, Fewer Is BetterVkResample 1.0Upscale: 2x - Precision: DoubleNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309090180270360450SE +/- 0.30, N = 3SE +/- 0.77, N = 3SE +/- 0.35, N = 3SE +/- 0.30, N = 3339.59415.16322.06333.641. (CXX) g++ options: -O3

IndigoBench

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

OpenBenchmarking.orgM samples/s, More Is BetterIndigoBench 4.4Acceleration: OpenCL GPU - Scene: BedroomNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090510152025SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 319.8018.2020.2620.96

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in double precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30907K14K21K28K35KSE +/- 146.69, N = 3SE +/- 125.94, N = 3SE +/- 302.46, N = 3SE +/- 50.66, N = 3243172239025431309121. (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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901224364860SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 352.8148.5253.5952.01

LuxCoreRender

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

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: LuxCore Benchmark - Acceleration: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30903691215SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 212.8210.9213.2313.12MIN: 4.84 / MAX: 14.62MIN: 4.45 / MAX: 12.42MIN: 5.41 / MAX: 15.13MIN: 4.85 / MAX: 15.21

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C Bluestein in single precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30903K6K9K12K15KSE +/- 102.52, N = 3SE +/- 52.09, N = 3SE +/- 118.41, N = 3SE +/- 115.62, N = 3151661371415125142051. (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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30903691215SE +/- 0.07, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 311.7210.4011.8912.14MIN: 9.6 / MAX: 15.44MIN: 8.31 / MAX: 13.9MIN: 9.85 / MAX: 15.88MIN: 10.24 / MAX: 16.71

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: Danish Mood - Acceleration: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30903691215SE +/- 0.08, N = 3SE +/- 0.06, N = 3SE +/- 0.11, N = 3SE +/- 0.04, N = 310.568.8910.9910.20MIN: 3.7 / MAX: 12.17MIN: 3.32 / MAX: 10.26MIN: 4.17 / MAX: 12.71MIN: 4.07 / MAX: 11.93

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 1 - Model: VGG-16NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.31050.6210.93151.2421.5525SE +/- 0.01, N = 2SE +/- 0.01, N = 3SE +/- 0.01, N = 31.351.361.381.38

Blender

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

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Barbershop - Compute: NVIDIA OptiXNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901326395265SE +/- 0.10, N = 3SE +/- 0.04, N = 3SE +/- 0.05, N = 3SE +/- 0.02, N = 251.3058.4450.7354.30

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in single precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309030K60K90K120K150KSE +/- 7.94, N = 3SE +/- 13.72, N = 3SE +/- 0.88, N = 3SE +/- 9.64, N = 37392977774739421418761. (CXX) g++ options: -O3 -lrt

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in single precision, no reshufflingNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309030K60K90K120K150KSE +/- 37.77, N = 3SE +/- 5.84, N = 3SE +/- 28.54, N = 3SE +/- 37.44, N = 37507879057751411443111. (CXX) g++ options: -O3 -lrt

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT R2C / C2RNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309012K24K36K48K60KSE +/- 702.53, N = 15SE +/- 745.02, N = 13SE +/- 520.37, N = 3SE +/- 320.62, N = 3547944709755446484181. (CXX) g++ options: -O3 -lrt

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 16 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090714212835SE +/- 0.17, N = 3SE +/- 0.08, N = 3SE +/- 0.07, N = 331.5931.4531.7031.98

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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30909001800270036004500SE +/- 5.52, N = 3SE +/- 66.69, N = 3SE +/- 21.66, N = 3SE +/- 12.99, N = 34171.004103.404140.874126.891. (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: hdr_lutNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30909001800270036004500SE +/- 12.09, N = 3SE +/- 10.06, N = 3SE +/- 5.47, N = 3SE +/- 13.62, N = 33905.983927.113971.613313.261. (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: hdr_peakdetectNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309011002200330044005500SE +/- 3.65, N = 3SE +/- 11.75, N = 3SE +/- 99.97, N = 3SE +/- 43.13, N = 33292.373310.023544.604997.081. (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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30905001000150020002500SE +/- 0.24, N = 3SE +/- 0.16, N = 3SE +/- 0.26, N = 3SE +/- 7.22, N = 32327.551972.782461.232119.891. (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: deband_heavyNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30905001000150020002500SE +/- 2.26, N = 3SE +/- 0.08, N = 3SE +/- 0.56, N = 3SE +/- 4.93, N = 32186.701847.982306.672017.751. (CXX) g++ options: -lm -pthread -ldl -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -MD -MQ -MF

RealSR-NCNN

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

OpenBenchmarking.orgSeconds, Fewer Is BetterRealSR-NCNN 20200818Scale: 4x - TAA: YesNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901020304050SE +/- 0.02, N = 3SE +/- 0.23, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 334.8942.8533.6330.31

VkFFT

OpenBenchmarking.orgBenchmark Score, More Is BetterVkFFT 1.2.31Test: FFT + iFFT C2C 1D batched in half precisionNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309060K120K180K240K300KSE +/- 159.17, N = 3SE +/- 1301.92, N = 3SE +/- 1708.38, N = 3SE +/- 160.60, N = 31317051377621362102732211. (CXX) g++ options: -O3 -lrt

NAMD CUDA

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

OpenBenchmarking.orgdays/ns, Fewer Is BetterNAMD CUDA 2.14ATPase Simulation - 327,506 AtomsNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.02430.04860.07290.09720.1215SE +/- 0.00031, N = 3SE +/- 0.00021, N = 3SE +/- 0.00061, N = 3SE +/- 0.00042, N = 30.067910.074980.067880.10822

Blender

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

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Fishy Cat - Compute: NVIDIA OptiXNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30903691215SE +/- 0.06, N = 13SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.08, N = 99.4511.039.0210.64

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_lNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309020406080100SE +/- 6.65, N = 5SE +/- 0.13, N = 3102.60102.9096.5099.05MIN: 94.84 / MAX: 104.25MIN: 95.98 / MAX: 104.54MIN: 64.35 / MAX: 104.79MIN: 91.8 / MAX: 100.69

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_lNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309020406080100SE +/- 1.49, N = 2SE +/- 0.45, N = 3SE +/- 0.39, N = 2SE +/- 0.14, N = 3102.60101.55103.2099.84MIN: 79.69 / MAX: 105.28MIN: 93.44 / MAX: 103.08MIN: 95.31 / MAX: 105.27MIN: 92.73 / MAX: 101.46

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 1 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.97881.95762.93643.91524.894SE +/- 0.01, N = 3SE +/- 0.02, N = 2SE +/- 0.03, N = 34.354.344.324.35

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.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-TTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090306090120150SE +/- 2.08, N = 3SE +/- 1.20, N = 3SE +/- 2.08, N = 3SE +/- 0.88, N = 31221181241131. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-TNNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090306090120150SE +/- 1.00, N = 2SE +/- 2.31, N = 3SE +/- 2.08, N = 3SE +/- 2.08, N = 31151211251211. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-NTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090306090120150SE +/- 2.08, N = 3SE +/- 1.76, N = 3SE +/- 1.20, N = 3SE +/- 3.28, N = 31171221181191. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-NNNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090306090120150SE +/- 4.04, N = 3SE +/- 1.86, N = 3SE +/- 1.15, N = 3SE +/- 1.86, N = 31191221171131. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMV-TNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309020406080100SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 6.30, N = 3SE +/- 0.33, N = 3109.0109.0102.7110.01. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMV-NNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309020406080100SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.88, N = 31021031031031. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dDOTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309020406080100SE +/- 0.09, N = 3SE +/- 0.22, N = 3SE +/- 0.58, N = 3SE +/- 0.84, N = 396.896.796.495.21. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dAXPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309020406080100SE +/- 0.12, N = 3SE +/- 0.44, N = 3SE +/- 0.57, N = 3SE +/- 0.94, N = 387.286.887.386.21. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dCOPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30901632486480SE +/- 0.32, N = 3SE +/- 0.25, N = 3SE +/- 0.74, N = 3SE +/- 0.72, N = 370.871.071.370.21. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - sDOTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30904080120160200SE +/- 2.73, N = 3SE +/- 3.76, N = 3SE +/- 2.40, N = 3SE +/- 35.40, N = 3165.0166.0168.0132.11. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - sAXPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090306090120150SE +/- 2.19, N = 3SE +/- 4.81, N = 3SE +/- 2.00, N = 3SE +/- 0.33, N = 31561531561541. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - sCOPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090306090120150SE +/- 1.20, N = 3SE +/- 1.20, N = 3SE +/- 0.88, N = 3SE +/- 1.20, N = 31321311321321. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_lNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309020406080100SE +/- 0.39, N = 3SE +/- 0.36, N = 2SE +/- 0.19, N = 3103.57101.43103.5099.25MIN: 95.95 / MAX: 105.54MIN: 93.27 / MAX: 103.58MIN: 94.95 / MAX: 105.61MIN: 91.16 / MAX: 101.18

ViennaCL

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

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-TTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090140280420560700SE +/- 0.00, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 36135026485931. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-TNNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090140280420560700SE +/- 0.00, N = 3SE +/- 0.33, N = 3SE +/- 0.67, N = 3SE +/- 2.03, N = 35994946345941. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-NTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090130260390520650SE +/- 0.00, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 2.33, N = 35844776125951. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-NNNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090130260390520650SE +/- 0.00, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 2.31, N = 35774736045921. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMV-TNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309080160240320400SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.33, N = 33893873913741. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMV-NNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309050100150200250SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 32102092111871. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dDOTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090140280420560700SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.88, N = 34584564576591. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dAXPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090160320480640800SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.33, N = 3SE +/- 0.58, N = 34374554377241. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dCOPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090130260390520650SE +/- 0.33, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.58, N = 34234234246051. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sDOTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309080160240320400SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.58, N = 33703623653761. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sAXPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090110220330440550SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.58, N = 33923893934981. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sCOPYNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309080160240320400SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.00, N = 3SE +/- 1.00, N = 33343303363631. (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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309020406080100SE +/- 0.05, N = 2SE +/- 0.57, N = 3103.17101.24103.2499.43MIN: 95.79 / MAX: 105.15MIN: 93.33 / MAX: 102.92MIN: 95.41 / MAX: 104.9MIN: 90.49 / MAX: 101.97

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: GPU - Batch Size: 1 - Model: AlexNetNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 0.22, N = 2SE +/- 0.16, N = 3SE +/- 0.06, N = 2SE +/- 0.20, N = 1513.9214.0414.7914.45

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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090246810SE +/- 0.06, N = 13SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.06, N = 145.576.215.436.31

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Pabellon Barcelona - Compute: NVIDIA OptiXNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 314.2916.5513.9717.30

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Classroom - Compute: NVIDIA OptiXNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 312.6014.8612.3015.26

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_lNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309020406080100SE +/- 0.52, N = 2SE +/- 0.53, N = 2103.68103.4598.11MIN: 96.86 / MAX: 105.56MIN: 95.22 / MAX: 105.88MIN: 89.88 / MAX: 100.25

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'

ProjectPhysX OpenCL-Benchmark

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

OpenBenchmarking.orgGB/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: Memory Bandwidth Coalesced WriteNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30902004006008001000SE +/- 0.14, N = 3SE +/- 0.16, N = 3SE +/- 0.11, N = 3SE +/- 0.06, N = 3455.01459.43457.17887.311. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: Memory Bandwidth Coalesced ReadNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30902004006008001000SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3464.86465.18465.07864.111. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

OpenBenchmarking.orgTIOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: INT8 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 0.05, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.07, N = 314.3112.1215.7313.731. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

OpenBenchmarking.orgTIOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: INT16 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309048121620SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 317.1714.2818.2817.001. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

OpenBenchmarking.orgTIOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: INT32 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090510152025SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.06, N = 319.8916.3821.0520.031. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

OpenBenchmarking.orgTIOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: INT64 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.99451.9892.98353.9784.9725SE +/- 0.015, N = 3SE +/- 0.004, N = 3SE +/- 0.016, N = 3SE +/- 0.003, N = 34.2143.4434.4203.1351. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

OpenBenchmarking.orgTFLOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: FP32 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090918273645SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.10, N = 338.5931.7740.9139.401. (CXX) g++ options: -std=c++17 -pthread -lOpenCL

OpenBenchmarking.orgTFLOPs/s, More Is BetterProjectPhysX OpenCL-Benchmark 1.2Operation: FP64 ComputeNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.14850.2970.44550.5940.7425SE +/- 0.000, N = 3SE +/- 0.001, N = 3SE +/- 0.001, N = 3SE +/- 0.001, N = 30.6210.5100.6600.6371. (CXX) g++ options: -std=c++17 -pthread -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: NoNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090246810SE +/- 0.150, N = 15SE +/- 0.006, N = 3SE +/- 0.039, N = 3SE +/- 0.016, N = 36.3237.0925.9625.556

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30904080120160200SE +/- 1.38, N = 2SE +/- 0.05, N = 3SE +/- 0.33, N = 2195.30187.51194.87164.35MIN: 182 / MAX: 199.43MIN: 181.57 / MAX: 188.05MIN: 180.8 / MAX: 198MIN: 149.91 / MAX: 166.09

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30904080120160200SE +/- 0.51, N = 3SE +/- 0.34, N = 3SE +/- 0.78, N = 2196.07186.63197.02164.14MIN: 171.95 / MAX: 199.96MIN: 180.51 / MAX: 187.79MIN: 183.92 / MAX: 200.54MIN: 149 / MAX: 165

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30904080120160200SE +/- 1.14, N = 2SE +/- 0.17, N = 3SE +/- 0.19, N = 2194.58187.27195.86161.01MIN: 183.74 / MAX: 198.52MIN: 179.9 / MAX: 188.08MIN: 181.64 / MAX: 199.2MIN: 138.12 / MAX: 165.16

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_lNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309020406080100SE +/- 0.55, N = 3SE +/- 0.33, N = 3106.37107.59108.59105.55MIN: 97.91 / MAX: 108.16MIN: 98.77 / MAX: 109.43MIN: 99.04 / MAX: 110.68MIN: 91.76 / MAX: 107.42

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30904080120160200SE +/- 0.29, N = 3195.39187.69198.82163.74MIN: 183.94 / MAX: 198.7MIN: 182.03 / MAX: 188.31MIN: 188.33 / MAX: 201.47MIN: 144.93 / MAX: 165.03

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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30903691215SE +/- 0.17, N = 2SE +/- 0.10, N = 3SE +/- 0.30, N = 2SE +/- 0.07, N = 312.6212.7812.7912.82

VkResample

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

OpenBenchmarking.orgms, Fewer Is BetterVkResample 1.0Upscale: 2x - Precision: SingleNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090510152025SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 318.4918.0218.4610.321. (CXX) g++ options: -O3

clpeak

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

OpenBenchmarking.orgGFLOPS, More Is Betterclpeak 1.1.2OpenCL Test: Double-Precision DoubleNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090140280420560700SE +/- 0.98, N = 3SE +/- 0.21, N = 3SE +/- 1.33, N = 3SE +/- 1.63, N = 3630.11515.17667.05642.231. (CXX) g++ options: -O3

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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30904080120160200SE +/- 0.29, N = 3195.40187.26194.29164.14MIN: 186.09 / MAX: 197.7MIN: 179.81 / MAX: 188.21MIN: 182.25 / MAX: 197.39MIN: 145.67 / MAX: 165.38

LuxCoreRender

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

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: Rainbow Colors and Prism - Acceleration: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090816243240SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.36, N = 527.6723.2627.7133.29MIN: 24.87 / MAX: 29.03MIN: 20.92 / MAX: 24.3MIN: 25.01 / MAX: 29.15MIN: 30.4 / MAX: 36.21

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090120240360480600SE +/- 3.09, N = 3SE +/- 11.16, N = 12557.73546.76535.39525.12MIN: 513.63 / MAX: 563.37MIN: 195.25 / MAX: 556.94MIN: 428.43 / MAX: 572.99MIN: 458.54 / MAX: 542.46

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090110220330440550SE +/- 0.92, N = 3SE +/- 0.27, N = 3SE +/- 1.92, N = 3SE +/- 0.24, N = 3507.45458.36505.62419.03MIN: 423.41 / MAX: 512.88MIN: 404.89 / MAX: 461.01MIN: 426.6 / MAX: 513.25MIN: 376 / MAX: 422

Rodinia

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

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenCL Particle FilterNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.92211.84422.76633.68844.6105SE +/- 0.039, N = 4SE +/- 0.008, N = 3SE +/- 0.002, N = 3SE +/- 0.030, N = 153.4804.0983.2913.8441. (CXX) g++ options: -O2 -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: MD5NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309016000M32000M48000M64000M80000MSE +/- 22430807.19, N = 3SE +/- 33772046.30, N = 3SE +/- 11283665.68, N = 3SE +/- 53667246.37, N = 367583033333561478666677331223333367177300000

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: SHA1NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30905000M10000M15000M20000M25000MSE +/- 5140363.15, N = 3SE +/- 6318315.53, N = 3SE +/- 15926811.78, N = 3SE +/- 26244639.66, N = 322132600000182024666672353240000021323733333

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: SHA-512NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090700M1400M2100M2800M3500MSE +/- 1530068.99, N = 3SE +/- 1059874.21, N = 3SE +/- 721110.26, N = 3SE +/- 3288532.26, N = 33232733333267330000034625000003081866667

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-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 3090110220330440550SE +/- 1.39, N = 3SE +/- 0.34, N = 3SE +/- 0.14, N = 3504.67459.93416.89MIN: 412.34 / MAX: 514.07MIN: 403.65 / MAX: 462.74MIN: 329.77 / MAX: 420.82

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30904080120160200SE +/- 0.36, N = 3SE +/- 0.73, N = 3SE +/- 0.09, N = 2201.94198.18201.19197.12MIN: 183.53 / MAX: 206.5MIN: 181.27 / MAX: 200.06MIN: 180.79 / MAX: 203.92MIN: 137.37 / MAX: 198.9

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090110220330440550SE +/- 0.26, N = 3SE +/- 2.23, N = 3SE +/- 0.89, N = 2509.45458.39502.92419.76MIN: 430.1 / MAX: 516.48MIN: 404.5 / MAX: 461.01MIN: 415.65 / MAX: 520.39MIN: 376.2 / MAX: 422.17

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090110220330440550SE +/- 4.43, N = 2SE +/- 0.43, N = 2SE +/- 0.83, N = 2SE +/- 0.40, N = 3504.27459.27504.66416.20MIN: 418.22 / MAX: 512.44MIN: 405.48 / MAX: 461.88MIN: 424.27 / MAX: 509.08MIN: 355.45 / MAX: 419.05

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50NVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090110220330440550SE +/- 2.17, N = 2SE +/- 0.13, N = 2SE +/- 1.69, N = 3501.50459.94505.55420.29MIN: 415.94 / MAX: 510.69MIN: 403.65 / MAX: 462.59MIN: 419.93 / MAX: 512.69MIN: 376.81 / MAX: 421.58

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: TrueCrypt RIPEMD160 + XTSNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090200K400K600K800K1000KSE +/- 633.33, N = 3SE +/- 176.38, N = 3SE +/- 888.82, N = 3SE +/- 1757.21, N = 3802967660967858600797833

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: 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.

cl-mem

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

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: CopyNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 309080160240320400SE +/- 0.03, N = 3SE +/- 0.09, N = 3SE +/- 0.00, N = 3SE +/- 0.22, N = 3331.8330.3333.3360.81. (CC) gcc options: -O2 -flto -lOpenCL

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: WriteNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090160320480640800SE +/- 1.11, N = 3SE +/- 0.55, N = 3SE +/- 0.12, N = 3SE +/- 0.83, N = 3407.5406.7412.2753.81. (CC) gcc options: -O2 -flto -lOpenCL

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: ReadNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30902004006008001000SE +/- 0.12, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.32, N = 3446.2446.3446.3825.81. (CC) gcc options: -O2 -flto -lOpenCL

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.

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: 7-ZipNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090300K600K900K1200K1500KSE +/- 1991.93, N = 3SE +/- 2062.63, N = 3SE +/- 2339.04, N = 3SE +/- 1587.45, N = 3117646797696712626331056000

Waifu2x-NCNN Vulkan

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

OpenBenchmarking.orgSeconds, Fewer Is BetterWaifu2x-NCNN Vulkan 20200818Scale: 2x - Denoise: 3 - TAA: YesNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30900.72051.4412.16152.8823.6025SE +/- 0.014, N = 3SE +/- 0.028, N = 3SE +/- 0.009, N = 3SE +/- 0.011, N = 32.8553.1682.8543.202

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: 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: 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: 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()

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: 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: 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()

clpeak

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

OpenBenchmarking.orgGBPS, More Is Betterclpeak 1.1.2OpenCL Test: Global Memory BandwidthNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30902004006008001000SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3437.65437.21437.63816.551. (CXX) g++ options: -O3

MandelGPU

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

OpenBenchmarking.orgSamples/sec, More Is BetterMandelGPU 1.3pts1OpenCL Device: GPUNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090130M260M390M520M650MSE +/- 467034.80, N = 3SE +/- 1783157.89, N = 3SE +/- 1202791.77, N = 3SE +/- 794770.01, N = 3587219538.2516770131.2619106132.5484098913.81. (CC) gcc options: -O3 -lm -ftree-vectorize -funroll-loops -lglut -lOpenCL -lGL

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: 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.

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.

FinanceBench

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

OpenBenchmarking.orgms, Fewer Is BetterFinanceBench 2016-07-25Benchmark: Black-Scholes OpenCLNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 3090246810SE +/- 0.114, N = 15SE +/- 0.003, N = 3SE +/- 0.003, N = 3SE +/- 0.006, N = 35.9126.9065.2265.7411. (CXX) g++ options: -O3 -march=native -fopenmp

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: 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.

clpeak

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

OpenBenchmarking.orgGIOPS, More Is Betterclpeak 1.1.2OpenCL Test: Integer Compute INTNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30904K8K12K16K20KSE +/- 3.14, N = 3SE +/- 15.26, N = 3SE +/- 2.50, N = 3SE +/- 16.49, N = 318170.5414555.1919821.1017923.331. (CXX) g++ options: -O3

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: 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.

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: Single-Precision FloatNVIDIA RTX 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30908K16K24K32K40KSE +/- 0.99, N = 3SE +/- 5.46, N = 3SE +/- 11.67, N = 3SE +/- 113.39, N = 335492.6928479.3938691.7334906.791. (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 4070 SUPERNVIDIA RTX 4070NVIDIA RTX 4070 TINVIDIA RTX 30909001800270036004500SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 34070407040703090

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

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

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

148 Results Shown

TensorFlow:
  GPU - 256 - VGG-16
  GPU - 64 - VGG-16
  GPU - 32 - VGG-16
  GPU - 512 - AlexNet
  GPU - 64 - ResNet-50
  GPU - 16 - VGG-16
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 - efficientnet-b0
  Vulkan GPU - mnasnet
  Vulkan GPU - shufflenet-v2
  Vulkan GPU-v2-v2 - mobilenet-v2
  Vulkan GPU - mobilenet
  Vulkan GPU - googlenet
  Vulkan GPU - blazeface
  Vulkan GPU-v3-v3 - mobilenet-v3
TensorFlow:
  GPU - 256 - AlexNet
  GPU - 32 - ResNet-50
  GPU - 64 - GoogLeNet
  GPU - 16 - ResNet-50
vkpeak:
  int16-vec4
  int16-scalar
  int32-vec4
  int32-scalar
  fp64-vec4
  fp64-scalar
  fp16-vec4
  fp16-scalar
  fp32-vec4
  fp32-scalar
TensorFlow:
  GPU - 32 - GoogLeNet
  GPU - 64 - AlexNet
GpuOwl:
  77936867
  332220523
OctaneBench
VkFFT
GpuOwl
TensorFlow
LuxCoreRender
VkFFT
TensorFlow
FAHBench
VkResample
IndigoBench
VkFFT
IndigoBench
LuxCoreRender
VkFFT
LuxCoreRender:
  Orange Juice - GPU
  Danish Mood - GPU
TensorFlow
Blender
VkFFT:
  FFT + iFFT C2C 1D batched in single precision
  FFT + iFFT C2C 1D batched in single precision, no reshuffling
  FFT + iFFT R2C / C2R
TensorFlow
Libplacebo:
  av1_grain_lap
  hdr_lut
  hdr_peakdetect
  polar_nocompute
  deband_heavy
RealSR-NCNN
VkFFT
NAMD CUDA
Blender
PyTorch:
  NVIDIA CUDA GPU - 32 - Efficientnet_v2_l
  NVIDIA CUDA GPU - 64 - Efficientnet_v2_l
TensorFlow
ViennaCL:
  CPU BLAS - dGEMM-TT
  CPU BLAS - dGEMM-TN
  CPU BLAS - dGEMM-NT
  CPU BLAS - dGEMM-NN
  CPU BLAS - dGEMV-T
  CPU BLAS - dGEMV-N
  CPU BLAS - dDOT
  CPU BLAS - dAXPY
  CPU BLAS - dCOPY
  CPU BLAS - sDOT
  CPU BLAS - sAXPY
  CPU BLAS - sCOPY
PyTorch
ViennaCL:
  OpenCL BLAS - dGEMM-TT
  OpenCL BLAS - dGEMM-TN
  OpenCL BLAS - dGEMM-NT
  OpenCL BLAS - dGEMM-NN
  OpenCL BLAS - dGEMV-T
  OpenCL BLAS - dGEMV-N
  OpenCL BLAS - dDOT
  OpenCL BLAS - dAXPY
  OpenCL BLAS - dCOPY
  OpenCL BLAS - sDOT
  OpenCL BLAS - sAXPY
  OpenCL BLAS - sCOPY
PyTorch
TensorFlow
Blender:
  BMW27 - NVIDIA OptiX
  Pabellon Barcelona - NVIDIA OptiX
  Classroom - NVIDIA OptiX
PyTorch
ProjectPhysX OpenCL-Benchmark:
  Memory Bandwidth Coalesced Write
  Memory Bandwidth Coalesced Read
  INT8 Compute
  INT16 Compute
  INT32 Compute
  INT64 Compute
  FP32 Compute
  FP64 Compute
RealSR-NCNN
PyTorch:
  NVIDIA CUDA GPU - 512 - ResNet-152
  NVIDIA CUDA GPU - 64 - ResNet-152
  NVIDIA CUDA GPU - 256 - ResNet-152
  NVIDIA CUDA GPU - 1 - Efficientnet_v2_l
  NVIDIA CUDA GPU - 32 - ResNet-152
TensorFlow
VkResample
clpeak
PyTorch
LuxCoreRender
PyTorch:
  NVIDIA CUDA GPU - 1 - ResNet-50
  NVIDIA CUDA GPU - 64 - ResNet-50
Rodinia
Hashcat:
  MD5
  SHA1
  SHA-512
PyTorch:
  NVIDIA CUDA GPU - 256 - ResNet-50
  NVIDIA CUDA GPU - 1 - ResNet-152
  NVIDIA CUDA GPU - 16 - ResNet-50
  NVIDIA CUDA GPU - 512 - ResNet-50
  NVIDIA CUDA GPU - 32 - ResNet-50
Hashcat
cl-mem:
  Copy
  Write
  Read
Hashcat
Waifu2x-NCNN Vulkan
clpeak
MandelGPU
FinanceBench
clpeak:
  Integer Compute INT
  Single-Precision Float
NeatBench