RTX 4070 SUPER Intel Core i9-13900K testing with a ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS) and ASUS NVIDIA GeForce RTX 4070 SUPER 12GB on EndeavourOS rolling via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2401253-NE-RTX4070SU64 .
RTX 4070 SUPER Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server Display Driver OpenGL OpenCL Compiler File-System Screen Resolution NVIDIA RTX 4070 SUPER RTX 4070 SUPER Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads) ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS) Intel Device 7a27 32GB 4001GB Seagate ZP4000GP304001 ASUS NVIDIA GeForce RTX 4070 SUPER 12GB Realtek ALC1220 ARZOPA Intel I226-V + Intel Device 7a70 EndeavourOS rolling 6.7.1-arch1-1 (x86_64) KDE Plasma 5.27.10 X Server 1.21.1.11 NVIDIA 550.40.07 4.6.0 OpenCL 3.0 CUDA 12.4.74 GCC 13.2.1 20230801 ext4 1920x1080 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: always Compiler 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 Processor Details - Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0x11d Graphics Details - NVIDIA RTX 4070 SUPER: BAR1 / Visible vRAM Size: 16384 MiB - vBIOS Version: 95.04.69.00.c1 Security 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 Python Details - RTX 4070 SUPER: Python 3.11.6
RTX 4070 SUPER opencl-benchmark: FP64 Compute opencl-benchmark: FP32 Compute opencl-benchmark: INT64 Compute opencl-benchmark: INT32 Compute opencl-benchmark: INT16 Compute opencl-benchmark: INT8 Compute opencl-benchmark: Memory Bandwidth Coalesced Read opencl-benchmark: Memory Bandwidth Coalesced Write pytorch: NVIDIA CUDA GPU - 1 - ResNet-152 pytorch: NVIDIA CUDA GPU - 16 - ResNet-50 pytorch: NVIDIA CUDA GPU - 64 - ResNet-50 pytorch: NVIDIA CUDA GPU - 32 - ResNet-152 pytorch: NVIDIA CUDA GPU - 512 - ResNet-50 pytorch: NVIDIA CUDA GPU - 256 - ResNet-152 pytorch: NVIDIA CUDA GPU - 1 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 32 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 256 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 512 - Efficientnet_v2_l gpuowl: 57885161 gpuowl: 77936867 gpuowl: 332220523 NVIDIA RTX 4070 SUPER RTX 4070 SUPER 0.621 38.594 4.214 19.889 17.170 14.307 464.86 455.01 869.07 646.41 137.44 201.94 509.45 507.45 195.39 504.27 194.58 106.37 102.60 103.17 103.57 OpenBenchmarking.org
ProjectPhysX OpenCL-Benchmark Operation: FP64 Compute OpenBenchmarking.org TFLOPs/s, More Is Better ProjectPhysX OpenCL-Benchmark 1.2 Operation: FP64 Compute NVIDIA RTX 4070 SUPER 0.1397 0.2794 0.4191 0.5588 0.6985 SE +/- 0.000, N = 3 0.621 1. (CXX) g++ options: -std=c++17 -pthread -lOpenCL
ProjectPhysX OpenCL-Benchmark Operation: FP32 Compute OpenBenchmarking.org TFLOPs/s, More Is Better ProjectPhysX OpenCL-Benchmark 1.2 Operation: FP32 Compute NVIDIA RTX 4070 SUPER 9 18 27 36 45 SE +/- 0.03, N = 3 38.59 1. (CXX) g++ options: -std=c++17 -pthread -lOpenCL
ProjectPhysX OpenCL-Benchmark Operation: INT64 Compute OpenBenchmarking.org TIOPs/s, More Is Better ProjectPhysX OpenCL-Benchmark 1.2 Operation: INT64 Compute NVIDIA RTX 4070 SUPER 0.9482 1.8964 2.8446 3.7928 4.741 SE +/- 0.015, N = 3 4.214 1. (CXX) g++ options: -std=c++17 -pthread -lOpenCL
ProjectPhysX OpenCL-Benchmark Operation: INT32 Compute OpenBenchmarking.org TIOPs/s, More Is Better ProjectPhysX OpenCL-Benchmark 1.2 Operation: INT32 Compute NVIDIA RTX 4070 SUPER 5 10 15 20 25 SE +/- 0.00, N = 3 19.89 1. (CXX) g++ options: -std=c++17 -pthread -lOpenCL
ProjectPhysX OpenCL-Benchmark Operation: INT16 Compute OpenBenchmarking.org TIOPs/s, More Is Better ProjectPhysX OpenCL-Benchmark 1.2 Operation: INT16 Compute NVIDIA RTX 4070 SUPER 4 8 12 16 20 SE +/- 0.00, N = 3 17.17 1. (CXX) g++ options: -std=c++17 -pthread -lOpenCL
ProjectPhysX OpenCL-Benchmark Operation: INT8 Compute OpenBenchmarking.org TIOPs/s, More Is Better ProjectPhysX OpenCL-Benchmark 1.2 Operation: INT8 Compute NVIDIA RTX 4070 SUPER 4 8 12 16 20 SE +/- 0.05, N = 3 14.31 1. (CXX) g++ options: -std=c++17 -pthread -lOpenCL
ProjectPhysX OpenCL-Benchmark Operation: Memory Bandwidth Coalesced Read OpenBenchmarking.org GB/s, More Is Better ProjectPhysX OpenCL-Benchmark 1.2 Operation: Memory Bandwidth Coalesced Read NVIDIA RTX 4070 SUPER 100 200 300 400 500 SE +/- 0.01, N = 3 464.86 1. (CXX) g++ options: -std=c++17 -pthread -lOpenCL
ProjectPhysX OpenCL-Benchmark Operation: Memory Bandwidth Coalesced Write OpenBenchmarking.org GB/s, More Is Better ProjectPhysX OpenCL-Benchmark 1.2 Operation: Memory Bandwidth Coalesced Write NVIDIA RTX 4070 SUPER 100 200 300 400 500 SE +/- 0.14, N = 3 455.01 1. (CXX) g++ options: -std=c++17 -pthread -lOpenCL
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152 RTX 4070 SUPER 40 80 120 160 200 201.94 MIN: 183.53 / MAX: 206.5
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50 RTX 4070 SUPER 110 220 330 440 550 509.45 MIN: 430.1 / MAX: 516.48
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50 RTX 4070 SUPER 110 220 330 440 550 SE +/- 0.92, N = 3 507.45 MIN: 423.41 / MAX: 512.88
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152 RTX 4070 SUPER 40 80 120 160 200 195.39 MIN: 183.94 / MAX: 198.7
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50 RTX 4070 SUPER 110 220 330 440 550 SE +/- 4.43, N = 2 504.27 MIN: 418.22 / MAX: 512.44
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152 RTX 4070 SUPER 40 80 120 160 200 SE +/- 1.14, N = 2 194.58 MIN: 183.74 / MAX: 198.52
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l RTX 4070 SUPER 20 40 60 80 100 106.37 MIN: 97.91 / MAX: 108.16
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l RTX 4070 SUPER 20 40 60 80 100 102.60 MIN: 94.84 / MAX: 104.25
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l RTX 4070 SUPER 20 40 60 80 100 103.17 MIN: 95.79 / MAX: 105.15
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l RTX 4070 SUPER 20 40 60 80 100 103.57 MIN: 95.95 / MAX: 105.54
GpuOwl Exponent: 57885161 OpenBenchmarking.org Iterations / Second, More Is Better GpuOwl 7.2.1 Exponent: 57885161 NVIDIA RTX 4070 SUPER 200 400 600 800 1000 SE +/- 1.26, N = 3 869.07
GpuOwl Exponent: 77936867 OpenBenchmarking.org Iterations / Second, More Is Better GpuOwl 7.2.1 Exponent: 77936867 NVIDIA RTX 4070 SUPER 140 280 420 560 700 SE +/- 0.00, N = 3 646.41
GpuOwl Exponent: 332220523 OpenBenchmarking.org Iterations / Second, More Is Better GpuOwl 7.2.1 Exponent: 332220523 NVIDIA RTX 4070 SUPER 30 60 90 120 150 SE +/- 0.00, N = 3 137.44
Phoronix Test Suite v10.8.4