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.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2401264-NE-RTX4070SU09
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BLAS (Basic Linear Algebra Sub-Routine) Tests 3 Tests
C++ Boost Tests 2 Tests
CPU Massive 4 Tests
Creator Workloads 5 Tests
Game Development 2 Tests
HPC - High Performance Computing 9 Tests
Machine Learning 6 Tests
Multi-Core 7 Tests
NVIDIA GPU Compute 29 Tests
OpenCL 6 Tests
OpenMPI Tests 2 Tests
Python Tests 4 Tests
Renderers 3 Tests
Scientific Computing 2 Tests
Server CPU Tests 2 Tests
Vulkan Compute 8 Tests
Common Workstation Benchmarks 2 Tests

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NVIDIA RTX 4070 SUPER
January 25
  27 Minutes
RTX 4070 SUPER
January 26
  5 Minutes
NVIDIA 4070 SUPER
January 26
  1 Hour, 27 Minutes
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RTX 4070 SUPER Suite 1.0.0 System Test suite extracted from RTX 4070 SUPER. pts/betsy-1.0.0 --codec=etc2_rgb --quality=2 Codec: ETC2 RGB - Quality: Highest pts/plaidml-1.0.4 --no-fp16 --train mobilenet OPENCL FP16: No - Mode: Training - Network: Mobilenet - Device: OpenCL pts/plaidml-1.0.4 --no-fp16 --no-train imdb_lstm OPENCL FP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCL pts/plaidml-1.0.4 --no-fp16 --no-train mobilenet OPENCL FP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCL pts/opencl-benchmark-1.0.0 Operation: Memory Bandwidth Coalesced Write pts/plaidml-1.0.4 --fp16 --no-train mobilenet OPENCL FP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCL pts/opencl-benchmark-1.0.0 Operation: INT8 Compute pts/opencl-benchmark-1.0.0 Operation: Memory Bandwidth Coalesced Read pts/opencl-benchmark-1.0.0 Operation: INT16 Compute pts/opencl-benchmark-1.0.0 Operation: INT32 Compute pts/opencl-benchmark-1.0.0 Operation: INT64 Compute pts/betsy-1.0.0 --codec=etc1 --quality=2 Codec: ETC1 - Quality: Highest pts/plaidml-1.0.4 --no-fp16 --no-train densenet201 OPENCL FP16: No - Mode: Inference - Network: DenseNet 201 - Device: OpenCL pts/lczero-1.7.0 -b opencl Backend: OpenCL pts/pytorch-1.0.1 cuda 1 resnet50 Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50 pts/pytorch-1.0.1 cuda 1 resnet152 Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152 pts/pytorch-1.0.1 cuda 16 resnet50 Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50 pts/pytorch-1.0.1 cuda 32 resnet50 Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50 pts/pytorch-1.0.1 cuda 64 resnet50 Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50 pts/pytorch-1.0.1 cuda 16 resnet152 Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152 pts/pytorch-1.0.1 cuda 256 resnet50 Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50 pts/pytorch-1.0.1 cuda 512 resnet50 Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50 pts/pytorch-1.0.1 cuda 64 resnet152 Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152 pts/gpuowl-1.0.0 -iters 20000 -prp 332220523 Exponent: 332220523 pts/gpuowl-1.0.0 -iters 100000 -prp 57885161 Exponent: 57885161 pts/gpuowl-1.0.0 -iters 100000 -prp 77936867 Exponent: 77936867 pts/pytorch-1.0.1 cuda 32 resnet152 Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152 pts/pytorch-1.0.1 cuda 256 resnet152 Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152 pts/pytorch-1.0.1 cuda 512 resnet152 Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152 pts/pytorch-1.0.1 cuda 1 efficientnet_v2_l Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l pts/pytorch-1.0.1 cuda 16 efficientnet_v2_l Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l pts/pytorch-1.0.1 cuda 32 efficientnet_v2_l Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l pts/pytorch-1.0.1 cuda 64 efficientnet_v2_l Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_l pts/pytorch-1.0.1 cuda 256 efficientnet_v2_l Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l pts/pytorch-1.0.1 cuda 512 efficientnet_v2_l Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -gpu all -iterations 100 Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 100 pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -gpu all -iterations 200 Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 200 pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -gpu all -iterations 1000 Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 1000 pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -gpu all -iterations 100 Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 100 pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -gpu all -iterations 200 Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 200 pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -gpu all -iterations 1000 Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 1000 pts/shoc-1.2.0 -opencl -benchmark S3D Target: OpenCL - Benchmark: S3D pts/shoc-1.2.0 -opencl -benchmark Triad Target: OpenCL - Benchmark: Triad pts/shoc-1.2.0 -opencl -benchmark FFT Target: OpenCL - Benchmark: FFT SP pts/shoc-1.2.0 -opencl -benchmark MD5Hash Target: OpenCL - Benchmark: MD5 Hash pts/shoc-1.2.0 -opencl -benchmark Reduction Target: OpenCL - Benchmark: Reduction pts/shoc-1.2.0 -opencl -benchmark GEMM Target: OpenCL - Benchmark: GEMM SGEMM_N pts/shoc-1.2.0 -opencl -benchmark MaxFlops Target: OpenCL - Benchmark: Max SP Flops pts/shoc-1.2.0 -opencl -benchmark BusSpeedDownload Target: OpenCL - Benchmark: Bus Speed Download pts/shoc-1.2.0 -opencl -benchmark BusSpeedReadback Target: OpenCL - Benchmark: Bus Speed Readback pts/shoc-1.2.0 -opencl -benchmark DeviceMemory Target: OpenCL - Benchmark: Texture Read Bandwidth pts/ncnn-1.5.0 Target: Vulkan GPU pts/gromacs-1.8.0 cuda-build water-cut1.0_GMX50_bare/1536 Implementation: NVIDIA CUDA GPU - Input: water_GMX50_bare pts/rodinia-1.3.2 OCL_PARTICLEFILTER Test: OpenCL Particle Filter pts/arrayfire-1.2.0 cg_opencl Test: Conjugate Gradient OpenCL pts/blender-4.0.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device OPTIX Blend File: BMW27 - Compute: NVIDIA OptiX pts/blender-4.0.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device OPTIX Blend File: Classroom - Compute: NVIDIA OptiX pts/blender-4.0.0 -b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device OPTIX Blend File: Fishy Cat - Compute: NVIDIA OptiX pts/blender-4.0.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device OPTIX Blend File: Barbershop - Compute: NVIDIA OptiX pts/blender-4.0.0 -b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device OPTIX Blend File: Pabellon Barcelona - Compute: NVIDIA OptiX pts/neatbench-1.0.4 gpu Acceleration: GPU pts/indigobench-1.1.0 --gpuonly --scenes bedroom Acceleration: OpenCL GPU - Scene: Bedroom pts/indigobench-1.1.0 --gpuonly --scenes supercar Acceleration: OpenCL GPU - Scene: Supercar pts/luxcorerender-1.4.0 DLSC/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: DLSC - Acceleration: GPU pts/luxcorerender-1.4.0 DanishMood/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: Danish Mood - Acceleration: GPU pts/opencl-benchmark-1.0.0 Operation: FP32 Compute pts/luxcorerender-1.4.0 OrangeJuice/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: Orange Juice - Acceleration: GPU pts/luxcorerender-1.4.0 LuxCore2.1Benchmark/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: LuxCore Benchmark - Acceleration: GPU pts/luxcorerender-1.4.0 RainbowColorsAndPrism/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: Rainbow Colors and Prism - Acceleration: GPU pts/fahbench-1.0.2 pts/hashcat-1.1.1 -m 0 Benchmark: MD5 pts/hashcat-1.1.1 -m 100 Benchmark: SHA1 pts/hashcat-1.1.1 -m 11600 Benchmark: 7-Zip pts/hashcat-1.1.1 -m 1700 Benchmark: SHA-512 pts/hashcat-1.1.1 -m 6211 Benchmark: TrueCrypt RIPEMD160 + XTS pts/mixbench-1.1.1 mixbench-ocl-ro GIOPS Backend: OpenCL - Benchmark: Integer pts/mixbench-1.1.1 mixbench-cuda-ro GIOPS Backend: NVIDIA CUDA - Benchmark: Integer pts/mixbench-1.1.1 mixbench-ocl-ro DPGFLOPS Backend: OpenCL - Benchmark: Double Precision pts/mixbench-1.1.1 mixbench-ocl-ro SPGFLOPS Backend: OpenCL - Benchmark: Single Precision pts/mixbench-1.1.1 mixbench-cuda-ro HPGFLOPS Backend: NVIDIA CUDA - Benchmark: Half Precision pts/mixbench-1.1.1 mixbench-cuda-ro DPGFLOPS Backend: NVIDIA CUDA - Benchmark: Double Precision pts/mixbench-1.1.1 mixbench-cuda-ro SPGFLOPS Backend: NVIDIA CUDA - Benchmark: Single Precision pts/namd-cuda-1.1.1 ATPase Simulation - 327,506 Atoms pts/octanebench-1.3.0 Total Score pts/financebench-1.1.1 Black-Scholes/OpenCL/blackScholesAnalyticEngine.exe Benchmark: Black-Scholes OpenCL pts/cl-mem-1.0.1 COPY Benchmark: Copy pts/cl-mem-1.0.1 READ Benchmark: Read pts/cl-mem-1.0.1 WRITE Benchmark: Write pts/clpeak-1.1.0 --compute-integer OpenCL Test: Integer Compute INT pts/clpeak-1.1.0 --compute-sp OpenCL Test: Single-Precision Float pts/clpeak-1.1.0 --compute-dp OpenCL Test: Double-Precision Double pts/clpeak-1.1.0 --global-bandwidth OpenCL Test: Global Memory Bandwidth pts/mandelgpu-1.3.1 0 1 OpenCL Device: GPU pts/opencl-benchmark-1.0.0 Operation: FP64 Compute pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sCOPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sAXPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sDOT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dCOPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dAXPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dDOT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMV-N pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMV-T pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-NN pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-NT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-TN pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-TT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - sCOPY pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - sAXPY pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - sDOT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dCOPY pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dAXPY pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dDOT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMV-N pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMV-T pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-NN pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-NT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-TN pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-TT pts/libplacebo-1.1.0 pts/realsr-ncnn-1.0.0 -s 4 Scale: 4x - TAA: No pts/realsr-ncnn-1.0.0 -s 4 -x Scale: 4x - TAA: Yes pts/vkfft-1.2.0 -vkfft 6 Test: FFT + iFFT R2C / C2R pts/vkfft-1.2.0 -vkfft 2 Test: FFT + iFFT C2C 1D batched in half precision pts/vkfft-1.2.0 -vkfft 7 Test: FFT + iFFT C2C Bluestein in single precision pts/vkfft-1.2.0 -vkfft 1 Test: FFT + iFFT C2C 1D batched in double precision pts/vkfft-1.2.0 -vkfft 0 Test: FFT + iFFT C2C 1D batched in single precision pts/vkfft-1.2.0 -vkfft 3 Test: FFT + iFFT C2C multidimensional in single precision pts/vkfft-1.2.0 -vkfft 8 Test: FFT + iFFT C2C Bluestein benchmark in double precision pts/vkfft-1.2.0 -vkfft 5 Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling pts/vkpeak-1.1.0 pts/vkresample-1.0.2 -u 2 -p 1 Upscale: 2x - Precision: Double pts/vkresample-1.0.2 -u 2 -p 0 Upscale: 2x - Precision: Single pts/waifu2x-ncnn-1.0.0 -s 2 -n 3 Scale: 2x - Denoise: 3 - TAA: No pts/waifu2x-ncnn-1.0.0 -s 2 -n 3 -x Scale: 2x - Denoise: 3 - TAA: Yes