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/2401252-NE-RTX4070SU41&grs&sro .
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 pytorch: NVIDIA CUDA GPU - 512 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 256 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 32 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 1 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 256 - ResNet-152 pytorch: NVIDIA CUDA GPU - 512 - ResNet-50 pytorch: NVIDIA CUDA GPU - 32 - ResNet-152 pytorch: NVIDIA CUDA GPU - 64 - ResNet-50 pytorch: NVIDIA CUDA GPU - 16 - ResNet-50 pytorch: NVIDIA CUDA GPU - 1 - ResNet-152 opencl-benchmark: Memory Bandwidth Coalesced Write opencl-benchmark: Memory Bandwidth Coalesced Read opencl-benchmark: INT8 Compute opencl-benchmark: INT16 Compute opencl-benchmark: INT32 Compute opencl-benchmark: INT64 Compute opencl-benchmark: FP32 Compute opencl-benchmark: FP64 Compute pytorch: NVIDIA CUDA GPU - 1 - ResNet-50 NVIDIA RTX 4070 SUPER RTX 4070 SUPER 455.01 464.86 14.307 17.170 19.889 4.214 38.594 0.621 103.57 103.17 102.60 106.37 194.58 504.27 195.39 507.45 509.45 201.94 OpenBenchmarking.org
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
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: 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: 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: 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: 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: 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: 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: 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: 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
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
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: 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: 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: 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: 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: 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: 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
Phoronix Test Suite v10.8.5