RTX 4070 SUPER

Intel Core i9-13900K testing with a ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS) and NVIDIA GeForce RTX 4070 Ti 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 2401307-NE-2401299NE85
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BLAS (Basic Linear Algebra Sub-Routine) Tests 3 Tests
C++ Boost Tests 2 Tests
CPU Massive 5 Tests
Creator Workloads 4 Tests
HPC - High Performance Computing 8 Tests
Machine Learning 6 Tests
Multi-Core 6 Tests
NVIDIA GPU Compute 25 Tests
OpenCL 5 Tests
Python Tests 5 Tests
Renderers 3 Tests
Server CPU Tests 2 Tests
Vulkan Compute 7 Tests
Common Workstation Benchmarks 2 Tests

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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
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  1 Day, 1 Hour, 52 Minutes

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RTX 4070 SUPER Intel Core i9-13900K testing with a ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS) and NVIDIA GeForce RTX 4070 Ti 12GB on EndeavourOS rolling via the Phoronix Test Suite. ,,"NVIDIA RTX 4070 SUPER","NVIDIA RTX 4070","NVIDIA RTX 4070 TI" Processor,,Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads),Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads),Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads) Motherboard,,ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS),ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS),ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS) Chipset,,Intel Device 7a27,Intel Device 7a27,Intel Device 7a27 Memory,,32GB,32GB,32GB Disk,,4001GB Seagate ZP4000GP304001,4001GB Seagate ZP4000GP304001,4001GB Seagate ZP4000GP304001 Graphics,,ASUS NVIDIA GeForce RTX 4070 SUPER 12GB,MSI NVIDIA GeForce RTX 4070 12GB,NVIDIA GeForce RTX 4070 Ti 12GB Audio,,Realtek ALC1220,Realtek ALC1220,Realtek ALC1220 Monitor,,ARZOPA,ARZOPA,ARZOPA Network,,Intel I226-V + Intel Device 7a70,Intel I226-V + Intel Device 7a70,Intel I226-V + Intel Device 7a70 OS,,EndeavourOS rolling,EndeavourOS rolling,EndeavourOS rolling Kernel,,6.7.1-arch1-1 (x86_64),6.7.1-arch1-1 (x86_64),6.7.1-arch1-1 (x86_64) Desktop,,KDE Plasma 5.27.10,KDE Plasma 5.27.10,KDE Plasma 5.27.10 Display Server,,X Server 1.21.1.11,X Server 1.21.1.11,X Server 1.21.1.11 Display Driver,,NVIDIA 550.40.07,NVIDIA 550.40.07,NVIDIA 550.40.07 OpenGL,,4.6.0,4.6.0,4.6.0 OpenCL,,OpenCL 3.0 CUDA 12.4.74,OpenCL 3.0 CUDA 12.4.74,OpenCL 3.0 CUDA 12.4.74 Compiler,,GCC 13.2.1 20230801,GCC 13.2.1 20230801 + CUDA 12.3,GCC 13.2.1 20230801 + CUDA 12.3 File-System,,ext4,ext4,ext4 Screen Resolution,,1920x1080,1920x1080,1920x1080 ,,"NVIDIA RTX 4070 SUPER","NVIDIA RTX 4070","NVIDIA RTX 4070 TI" "clpeak - OpenCL Test: Integer Compute INT (GIOPS)",HIB,18170.54,14555.19,19821.10 "clpeak - OpenCL Test: Single-Precision Float (GFLOPS)",HIB,35492.69,28479.39,38691.73 "Hashcat - Benchmark: MD5 (H/s)",HIB,67583033333,56147866667,73312233333 "Hashcat - Benchmark: TrueCrypt RIPEMD160 + XTS (H/s)",HIB,802967,660967,858600 "ProjectPhysX OpenCL-Benchmark - Operation: INT8 Compute (TIOPs/s)",HIB,14.307,12.116,15.731 "Hashcat - Benchmark: SHA-512 (H/s)",HIB,3232733333,2673300000,3462500000 "GpuOwl - Exponent: 332220523 (Iterations / Second)",HIB,137.44,112.61,145.84 "clpeak - OpenCL Test: Double-Precision Double (GFLOPS)",HIB,630.11,515.17,667.05 "ProjectPhysX OpenCL-Benchmark - Operation: FP64 Compute (TFLOPs/s)",HIB,0.621,0.510,0.660 "Hashcat - Benchmark: SHA1 (H/s)",HIB,22132600000,18202466667,23532400000 "Hashcat - Benchmark: 7-Zip (H/s)",HIB,1176467,976967,1262633 "ViennaCL - Test: OpenCL BLAS - dGEMM-TT (GFLOPs/s)",HIB,613,502,648 "VkResample - Upscale: 2x - Precision: Double (ms)",LIB,339.593,415.160,322.064 "ProjectPhysX OpenCL-Benchmark - Operation: FP32 Compute (TFLOPs/s)",HIB,38.594,31.768,40.914 "GpuOwl - Exponent: 57885161 (Iterations / Second)",HIB,869.07,714.80,919.13 "ProjectPhysX OpenCL-Benchmark - Operation: INT32 Compute (TIOPs/s)",HIB,19.889,16.377,21.047 "ProjectPhysX OpenCL-Benchmark - Operation: INT64 Compute (TIOPs/s)",HIB,4.214,3.443,4.420 "ViennaCL - Test: OpenCL BLAS - dGEMM-TN (GFLOPs/s)",HIB,599,494,634 "ViennaCL - Test: OpenCL BLAS - dGEMM-NT (GFLOPs/s)",HIB,584,477,612 "ProjectPhysX OpenCL-Benchmark - Operation: INT16 Compute (TIOPs/s)",HIB,17.170,14.284,18.281 "ViennaCL - Test: OpenCL BLAS - dGEMM-NN (GFLOPs/s)",HIB,577,473,604 "GpuOwl - Exponent: 77936867 (Iterations / Second)",HIB,646.41,530.32,676.59 "RealSR-NCNN - Scale: 4x - TAA: Yes (sec)",LIB,34.885,42.852,33.626 "Libplacebo - Test: deband_heavy (FPS)",HIB,2186.70,1843.26,2306.56 "Libplacebo - Test: polar_nocompute (FPS)",HIB,2327.55,1968.37,2459.03 "Rodinia - Test: OpenCL Particle Filter (sec)",LIB,3.480,4.098,3.291 "LuxCoreRender - Scene: Danish Mood - Acceleration: GPU (M samples/sec)",HIB,10.56,8.89,10.99 "Blender - Blend File: Fishy Cat - Compute: NVIDIA OptiX (sec)",LIB,9.45,11.03,9.02 "LuxCoreRender - Scene: LuxCore Benchmark - Acceleration: GPU (M samples/sec)",HIB,12.82,10.92,13.23 "Blender - Blend File: Classroom - Compute: NVIDIA OptiX (sec)",LIB,12.60,14.86,12.30 "FAHBench - (Ns/Day)",HIB,366.0576,317.1952,382.1637 "MandelGPU - OpenCL Device: GPU (Samples/sec)",HIB,587219538.2,516770131.2,619106132.5 "VkFFT - Test: FFT + iFFT C2C Bluestein benchmark in double precision (Benchmark Score)",HIB,4451,3886,4647 "LuxCoreRender - Scene: Rainbow Colors and Prism - Acceleration: GPU (M samples/sec)",HIB,27.67,23.26,27.71 "LuxCoreRender - Scene: DLSC - Acceleration: GPU (M samples/sec)",HIB,13.59,11.74,13.95 "Blender - Blend File: Pabellon Barcelona - Compute: NVIDIA OptiX (sec)",LIB,14.29,16.55,13.97 "VkFFT - Test: FFT + iFFT R2C / C2R (Benchmark Score)",HIB,54794,47097,55446 "Blender - Blend File: Barbershop - Compute: NVIDIA OptiX (sec)",LIB,51.30,58.44,50.73 "Blender - Blend File: BMW27 - Compute: NVIDIA OptiX (sec)",LIB,5.57,6.21,5.43 "LuxCoreRender - Scene: Orange Juice - Acceleration: GPU (M samples/sec)",HIB,11.72,10.40,11.89 "VkFFT - Test: FFT + iFFT C2C 1D batched in double precision (Benchmark Score)",HIB,24317,22390,25431 "OctaneBench - Total Score (Score)",HIB,720.973789,647.997867,735.940593 "IndigoBench - Acceleration: OpenCL GPU - Scene: Bedroom (M samples/s)",HIB,19.801,18.203,20.256 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,509.45,458.39,502.92 "Waifu2x-NCNN Vulkan - Scale: 2x - Denoise: 3 - TAA: Yes (sec)",LIB,2.855,3.168,2.854 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50 (batches/sec)",HIB,507.45,458.36,505.62 "VkFFT - Test: FFT + iFFT C2C Bluestein in single precision (Benchmark Score)",HIB,15166,13714,15125 "NAMD CUDA - ATPase Simulation - 327,506 Atoms (days/ns)",LIB,0.06791,0.07498,0.06788 "IndigoBench - Acceleration: OpenCL GPU - Scene: Supercar (M samples/s)",HIB,52.813,48.517,53.589 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50 (batches/sec)",HIB,501.50,459.94,505.55 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50 (batches/sec)",HIB,504.27,459.27,504.66 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50 (batches/sec)",HIB,504.67,459.93, "VkFFT - Test: FFT + iFFT C2C multidimensional in single precision (Benchmark Score)",HIB,50299,47212,51528 "ViennaCL - Test: CPU BLAS - dGEMM-TN (GFLOPs/s)",HIB,115,121,125 "Libplacebo - Test: hdr_peakdetect (FPS)",HIB,3292.37,3310.02,3475.06 "TensorFlow - Device: GPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,13.92,14.04,14.79 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152 (batches/sec)",HIB,195.39,187.69,198.82 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152 (batches/sec)",HIB,196.07,186.63,197.02 "VkFFT - Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling (Benchmark Score)",HIB,75078,79057,75141 "VkFFT - Test: FFT + iFFT C2C 1D batched in single precision (Benchmark Score)",HIB,73929,77774,73942 "ViennaCL - Test: CPU BLAS - dGEMM-TT (GFLOPs/s)",HIB,122,118,124 "VkFFT - Test: FFT + iFFT C2C 1D batched in half precision (Benchmark Score)",HIB,131705,137762,136210 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152 (batches/sec)",HIB,194.58,187.27,195.86 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,195.40,187.26,194.29 "ViennaCL - Test: CPU BLAS - dGEMM-NT (GFLOPs/s)",HIB,117,122,118 "ViennaCL - Test: CPU BLAS - dGEMM-NN (GFLOPs/s)",HIB,119,122,117 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152 (batches/sec)",HIB,195.30,187.51,194.87 "ViennaCL - Test: OpenCL BLAS - dAXPY (GB/s)",HIB,437,455,437 "VkResample - Upscale: 2x - Precision: Single (ms)",LIB,18.489,18.016,18.456 "TensorFlow - Device: GPU - Batch Size: 1 - Model: VGG-16 (images/sec)",HIB,1.35,1.36,1.38 "ViennaCL - Test: OpenCL BLAS - sDOT (GB/s)",HIB,370,362,365 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l (batches/sec)",HIB,103.57,101.43,103.50 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,106.37,107.59,108.59 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l (batches/sec)",HIB,103.17,101.24,103.24 "ViennaCL - Test: CPU BLAS - sAXPY (GB/s)",HIB,156,153,156 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152 (batches/sec)",HIB,201.94,198.18,201.19 "ViennaCL - Test: OpenCL BLAS - sCOPY (GB/s)",HIB,334,330,336 "ViennaCL - Test: CPU BLAS - sDOT (GB/s)",HIB,165,166,168 "Libplacebo - Test: hdr_lut (FPS)",HIB,3905.98,3927.11,3971.61 "Libplacebo - Test: av1_grain_lap (FPS)",HIB,4171.00,4103.40,4140.87 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_l (batches/sec)",HIB,102.60,101.55,103.20 "cl-mem - Benchmark: Write (GB/s)",HIB,407.5,406.7,412.2 "TensorFlow - Device: GPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,1.48,1.50,1.49 "TensorFlow - Device: GPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,12.62,12.78,12.79 "TensorFlow - Device: GPU - Batch Size: 256 - Model: AlexNet (images/sec)",HIB,34.16,,34.61 "TensorFlow - Device: GPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,15.61,15.63,15.81 "ViennaCL - Test: OpenCL BLAS - dGEMV-T (GB/s)",HIB,389,387,391 "ViennaCL - Test: OpenCL BLAS - sAXPY (GB/s)",HIB,392,389,393 "ViennaCL - Test: CPU BLAS - dGEMV-N (GB/s)",HIB,102,103,103 "ProjectPhysX OpenCL-Benchmark - Operation: Memory Bandwidth Coalesced Write (GB/s)",HIB,455.01,459.43,457.17 "TensorFlow - Device: GPU - Batch Size: 512 - Model: AlexNet (images/sec)",HIB,35.10,35.21,35.44 "ViennaCL - Test: OpenCL BLAS - dGEMV-N (GB/s)",HIB,210,209,211 "TensorFlow - Device: GPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,5.51,5.55,5.50 "cl-mem - Benchmark: Copy (GB/s)",HIB,331.8,330.3,333.3 "TensorFlow - Device: GPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,31.59,31.45,31.70 "ViennaCL - Test: CPU BLAS - sCOPY (GB/s)",HIB,132,131,132 "ViennaCL - Test: CPU BLAS - dCOPY (GB/s)",HIB,70.8,71.0,71.3 "TensorFlow - Device: GPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,4.35,4.34,4.32 "ViennaCL - Test: CPU BLAS - dAXPY (GB/s)",HIB,87.2,86.8,87.3 "TensorFlow - Device: GPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,5.46,5.49,5.46 "ViennaCL - Test: OpenCL BLAS - dDOT (GB/s)",HIB,458,456,457 "ViennaCL - Test: CPU BLAS - dDOT (GB/s)",HIB,96.8,96.7,96.4 "TensorFlow - Device: GPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,33.97,33.93,34.06 "TensorFlow - Device: GPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,5.55,5.55,5.53 "TensorFlow - Device: GPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,33.4,33.32,33.29 "TensorFlow - Device: GPU - Batch Size: 64 - Model: GoogLeNet (images/sec)",HIB,15.52,15.54,15.50 "ViennaCL - Test: OpenCL BLAS - dCOPY (GB/s)",HIB,423,423,424 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,,103.68,103.45 "TensorFlow - Device: GPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,15.67,15.66,15.69 "clpeak - OpenCL Test: Global Memory Bandwidth (GBPS)",HIB,437.65,437.21,437.63 "ProjectPhysX OpenCL-Benchmark - Operation: Memory Bandwidth Coalesced Read (GB/s)",HIB,464.86,465.18,465.07 "cl-mem - Benchmark: Read (GB/s)",HIB,446.2,446.3,446.3 "TensorFlow - Device: GPU - Batch Size: 256 - Model: VGG-16 (images/sec)",HIB,,,1.5 "TensorFlow - Device: GPU - Batch Size: 64 - Model: VGG-16 (images/sec)",HIB,,1.50,1.5 "TensorFlow - Device: GPU - Batch Size: 32 - Model: VGG-16 (images/sec)",HIB,1.50,1.5,1.5 "NeatBench - Acceleration: GPU (FPS)",HIB,4070,4070,4070 "NCNN - Target: Vulkan GPU - Model: FastestDet (ms)",LIB,2.86,2.67,3.04 "NCNN - Target: Vulkan GPU - Model: vision_transformer (ms)",LIB,844.61,382.82,497.66 "NCNN - Target: Vulkan GPU - Model: regnety_400m (ms)",LIB,11.11,6.50,5.97 "NCNN - Target: Vulkan GPU - Model: squeezenet_ssd (ms)",LIB,6.86,5.27,6.13 "NCNN - Target: Vulkan GPU - Model: yolov4-tiny (ms)",LIB,63.82,25.11,16.47 "NCNN - Target: Vulkan GPU - Model: resnet50 (ms)",LIB,46.26,8.72,14.32 "NCNN - Target: Vulkan GPU - Model: alexnet (ms)",LIB,16.17,9.33,6.07 "NCNN - Target: Vulkan GPU - Model: resnet18 (ms)",LIB,8.97,8.58,7.74 "NCNN - Target: Vulkan GPU - Model: vgg16 (ms)",LIB,117.81,54.54,34.49 "NCNN - Target: Vulkan GPU - Model: googlenet (ms)",LIB,11.04,6.06,7.37 "NCNN - Target: Vulkan GPU - Model: blazeface (ms)",LIB,0.84,0.84,0.82 "NCNN - Target: Vulkan GPU - Model: efficientnet-b0 (ms)",LIB,5.07,3.59,3.49 "NCNN - Target: Vulkan GPU - Model: mnasnet (ms)",LIB,3.85,2.24,4.14 "NCNN - Target: Vulkan GPU - Model: shufflenet-v2 (ms)",LIB,2.31,2.11,2.03 "NCNN - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,2.25,8.71,2.09 "NCNN - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,3.03,4.69,2.54 "NCNN - Target: Vulkan GPU - Model: mobilenet (ms)",LIB,8.62,10.14,8.43 "TensorFlow - Device: GPU - Batch Size: 512 - Model: VGG-16 (images/sec)",HIB,,, "PlaidML - FP16: No - Mode: Inference - Network: DenseNet 201 - Device: OpenCL (Examples/sec)",HIB,,, "PlaidML - FP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCL (Examples/sec)",HIB,,, "PlaidML - FP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCL (Examples/sec)",HIB,,, "PlaidML - FP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCL (Examples/sec)",HIB,,, "PlaidML - FP16: No - Mode: Training - Network: Mobilenet - Device: OpenCL (Examples/sec)",HIB,,, "NCNN - Target: Vulkan GPU (ms)",LIB,,, "Caffe - Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 1000 (ms)",LIB,,, "Caffe - Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 200 (ms)",LIB,,, "Caffe - Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 100 (ms)",LIB,,, "Caffe - Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 1000 (ms)",LIB,,, "Caffe - Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 200 (ms)",LIB,,, "Caffe - Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 100 (ms)",LIB,,, "ViennaCL - Test: CPU BLAS - dGEMV-T (GB/s)",HIB,109,109,102.7 "FinanceBench - Benchmark: Black-Scholes OpenCL (ms)",LIB,5.912,6.906,5.226 "ArrayFire - Test: Conjugate Gradient OpenCL ()",LIB,,, "LeelaChessZero - Backend: OpenCL (Nodes/s)",HIB,,, "Libplacebo - (FPS)",HIB,,, "Waifu2x-NCNN Vulkan - Scale: 2x - Denoise: 3 - TAA: No (sec)",LIB,,, "RealSR-NCNN - Scale: 4x - TAA: No (sec)",LIB,6.323,7.092,5.962 "vkpeak - (GFLOPS)",HIB,,, "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l (batches/sec)",HIB,102.60,102.90,96.50 "PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,557.73,546.76,535.39