Intel Core i9-13900K testing with a ASUS TUF GAMING Z790-PRO WIFI (1630 BIOS) and ASUS NVIDIA GeForce RTX 4070 Ti SUPER 16GB 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 2402174-SADD-240211636
RTX 4070 SUPER
Intel Core i9-13900K testing with a ASUS TUF GAMING Z790-PRO WIFI (1630 BIOS) and ASUS NVIDIA GeForce RTX 4070 Ti SUPER 16GB on EndeavourOS rolling via the Phoronix Test Suite.
,,"NVIDIA RTX 4070 SUPER","NVIDIA RTX 4070","NVIDIA RTX 4070 TI","NVIDIA RTX 3090","NVIDIA RTX 4070 TI SUPER"
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),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),ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS),ASUS TUF GAMING Z790-PRO WIFI (1630 BIOS)
Chipset,,Intel Device 7a27,Intel Device 7a27,Intel Device 7a27,Intel Device 7a27,Intel Raptor Lake-S PCH
Memory,,32GB,32GB,32GB,32GB,32GB
Disk,,4001GB Seagate ZP4000GP304001,4001GB Seagate ZP4000GP304001,4001GB Seagate ZP4000GP304001,4001GB Seagate ZP4000GP304001,4001GB Seagate ZP4000GP304001 + 0GB CD-ROM Drive
Graphics,,ASUS NVIDIA GeForce RTX 4070 SUPER 12GB,MSI NVIDIA GeForce RTX 4070 12GB,NVIDIA GeForce RTX 4070 Ti 12GB,NVIDIA GeForce RTX 3090 24GB,ASUS NVIDIA GeForce RTX 4070 Ti SUPER 16GB
Audio,,Realtek ALC1220,Realtek ALC1220,Realtek ALC1220,Realtek ALC1220,Realtek ALC1220
Monitor,,ARZOPA,ARZOPA,ARZOPA,PI-KVM Video,PI-KVM Video
Network,,Intel I226-V + Intel Device 7a70,Intel I226-V + Intel Device 7a70,Intel I226-V + Intel Device 7a70,Intel I226-V + Intel Device 7a70,Intel I226-V + Intel Raptor Lake-S PCH CNVi WiFi
OS,,EndeavourOS rolling,EndeavourOS rolling,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),6.7.4-arch1-1 (x86_64),6.7.4-arch1-1 (x86_64)
Desktop,,KDE Plasma 5.27.10,KDE Plasma 5.27.10,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,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,NVIDIA 550.40.07,NVIDIA 550.40.07
OpenGL,,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0
OpenCL,,OpenCL 3.0 CUDA 12.4.74,OpenCL 3.0 CUDA 12.4.74,OpenCL 3.0 CUDA 12.4.74,OpenCL 3.0 CUDA 12.4.74,OpenCL 2.1 AMD-APP (3602.0) + 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,GCC 13.2.1 20230801 + CUDA 12.3,GCC 13.2.1 20230801 + CUDA 12.3
File-System,,ext4,ext4,ext4,ext4,ext4
Screen Resolution,,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080
,,"NVIDIA RTX 4070 SUPER","NVIDIA RTX 4070","NVIDIA RTX 4070 TI","NVIDIA RTX 3090","NVIDIA RTX 4070 TI SUPER"
"TensorFlow - Device: GPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,13.92,14.04,14.79,14.45,12.26
"TensorFlow - Device: GPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,1.48,1.50,1.49,1.49,1.45
"TensorFlow - Device: GPU - Batch Size: 32 - Model: VGG-16 (images/sec)",HIB,1.50,1.5,1.5,1.5,1.46
"TensorFlow - Device: GPU - Batch Size: 64 - Model: VGG-16 (images/sec)",HIB,,1.50,1.5,1.51,1.46
"TensorFlow - Device: GPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,31.59,31.45,31.70,31.98,31.10
"TensorFlow - Device: GPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,33.4,33.32,33.29,33.53,32.88
"ProjectPhysX OpenCL-Benchmark - Operation: Memory Bandwidth Coalesced Write (GB/s)",HIB,455.01,459.43,457.17,887.31,608.94
"TensorFlow - Device: GPU - Batch Size: 1 - Model: VGG-16 (images/sec)",HIB,1.35,1.36,1.38,1.38,1.32
"ProjectPhysX OpenCL-Benchmark - Operation: INT8 Compute (TIOPs/s)",HIB,14.307,12.116,15.731,13.727,17.615
"ProjectPhysX OpenCL-Benchmark - Operation: Memory Bandwidth Coalesced Read (GB/s)",HIB,464.86,465.18,465.07,864.11,619.03
"ProjectPhysX OpenCL-Benchmark - Operation: INT16 Compute (TIOPs/s)",HIB,17.170,14.284,18.281,17.001,20.503
"ProjectPhysX OpenCL-Benchmark - Operation: INT32 Compute (TIOPs/s)",HIB,19.889,16.377,21.047,20.027,23.660
"ProjectPhysX OpenCL-Benchmark - Operation: INT64 Compute (TIOPs/s)",HIB,4.214,3.443,4.420,3.135,4.414
"TensorFlow - Device: GPU - Batch Size: 256 - Model: VGG-16 (images/sec)",HIB,,,1.5,1.51,1.47
"TensorFlow - Device: GPU - Batch Size: 512 - Model: VGG-16 (images/sec)",HIB,,,,,
"TensorFlow - Device: GPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,33.97,33.93,34.06,33.93,33.55
"GpuOwl - Exponent: 77936867 (Iterations / Second)",HIB,646.41,530.32,676.59,645.99,761.61
"GpuOwl - Exponent: 332220523 (Iterations / Second)",HIB,137.44,112.61,145.84,137.32,163.41
"TensorFlow - Device: GPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,12.62,12.78,12.79,12.82,12.24
"GpuOwl - Exponent: 57885161 (Iterations / Second)",HIB,869.07,714.80,919.13,866.31,1025.99
"TensorFlow - Device: GPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,4.35,4.34,4.32,4.35,4.14
"TensorFlow - Device: GPU - Batch Size: 256 - Model: AlexNet (images/sec)",HIB,34.16,,34.61,34.46,33.95
"TensorFlow - Device: GPU - Batch Size: 512 - Model: AlexNet (images/sec)",HIB,35.10,35.21,35.44,35.58,35.02
"TensorFlow - Device: GPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,15.67,15.66,15.69,15.68,15.29
"TensorFlow - Device: GPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,5.46,5.49,5.46,5.49,5.32
"TensorFlow - Device: GPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,15.61,15.63,15.81,15.67,15.11
"TensorFlow - Device: GPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,5.51,5.55,5.50,5.57,5.35
"TensorFlow - Device: GPU - Batch Size: 64 - Model: GoogLeNet (images/sec)",HIB,15.52,15.54,15.50,15.63,15.00
"TensorFlow - Device: GPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,5.55,5.55,5.53,5.57,5.33
"PlaidML - FP16: No - Mode: Training - Network: Mobilenet - Device: OpenCL (Examples/sec)",HIB,,,,,
"PlaidML - FP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCL (Examples/sec)",HIB,,,,,
"PlaidML - FP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCL (Examples/sec)",HIB,,,,,
"PlaidML - FP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCL (Examples/sec)",HIB,,,,,
"PlaidML - FP16: No - Mode: Inference - Network: DenseNet 201 - Device: OpenCL (Examples/sec)",HIB,,,,,
"LeelaChessZero - Backend: OpenCL (Nodes/s)",HIB,,,,,
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,557.73,546.76,535.39,525.12,558.82
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152 (batches/sec)",HIB,201.94,198.18,201.19,197.12,200.46
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,509.45,458.39,502.92,419.76,531.96
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50 (batches/sec)",HIB,501.50,459.94,505.55,420.29,532.77
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50 (batches/sec)",HIB,507.45,458.36,505.62,419.03,527.82
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,195.40,187.26,194.29,164.14,198.58
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50 (batches/sec)",HIB,504.67,459.93,,416.89,529.14
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152 (batches/sec)",HIB,195.39,187.69,198.82,163.74,197.82
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50 (batches/sec)",HIB,504.27,459.27,504.66,416.20,529.49
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152 (batches/sec)",HIB,196.07,186.63,197.02,164.14,196.50
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152 (batches/sec)",HIB,194.58,187.27,195.86,161.01,198.70
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152 (batches/sec)",HIB,195.30,187.51,194.87,164.35,198.01
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,106.37,107.59,108.59,105.55,105.86
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,,103.68,103.45,98.11,103.66
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l (batches/sec)",HIB,102.60,102.90,96.50,99.05,102.83
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_l (batches/sec)",HIB,102.60,101.55,103.20,99.84,103.49
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l (batches/sec)",HIB,103.17,101.24,103.24,99.43,102.83
"PyTorch - Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l (batches/sec)",HIB,103.57,101.43,103.50,99.25,103.53
"Caffe - Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 100 (ms)",LIB,,,,,
"Caffe - Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 200 (ms)",LIB,,,,,
"Caffe - Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 1000 (ms)",LIB,,,,,
"Caffe - Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 100 (ms)",LIB,,,,,
"Caffe - Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 200 (ms)",LIB,,,,,
"Caffe - Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 1000 (ms)",LIB,,,,,
"NCNN - Target: Vulkan GPU (ms)",LIB,,,,,
"NCNN - Target: Vulkan GPU - Model: mobilenet (ms)",LIB,8.62,7.20,7.45,6.92,6.28
"NCNN - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,3.03,2.48,2.43,2.34,2.42
"NCNN - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,2.25,2.15,2.09,2.20,1.87
"NCNN - Target: Vulkan GPU - Model: shufflenet-v2 (ms)",LIB,2.31,2.08,2.01,2.04,2.05
"NCNN - Target: Vulkan GPU - Model: mnasnet (ms)",LIB,3.85,2.22,2.30,2.16,2.21
"NCNN - Target: Vulkan GPU - Model: efficientnet-b0 (ms)",LIB,5.07,3.46,3.46,3.34,3.36
"NCNN - Target: Vulkan GPU - Model: blazeface (ms)",LIB,0.84,0.84,0.81,0.84,0.86
"NCNN - Target: Vulkan GPU - Model: googlenet (ms)",LIB,11.04,6.06,5.87,6.11,6.25
"NCNN - Target: Vulkan GPU - Model: vgg16 (ms)",LIB,117.81,45.52,32.05,17.88,21.76
"NCNN - Target: Vulkan GPU - Model: resnet18 (ms)",LIB,8.97,5.11,5.47,4.12,4.64
"NCNN - Target: Vulkan GPU - Model: alexnet (ms)",LIB,16.17,5.78,3.74,3.60,4.38
"NCNN - Target: Vulkan GPU - Model: resnet50 (ms)",LIB,46.26,8.24,12.25,8.20,8.58
"NCNN - Target: Vulkan GPU - Model: yolov4-tiny (ms)",LIB,63.82,20.74,16.37,11.29,14.26
"NCNN - Target: Vulkan GPU - Model: squeezenet_ssd (ms)",LIB,6.86,5.18,5.36,4.90,5.11
"NCNN - Target: Vulkan GPU - Model: regnety_400m (ms)",LIB,11.11,6.21,5.89,6.47,6.59
"NCNN - Target: Vulkan GPU - Model: vision_transformer (ms)",LIB,844.61,281.56,390.18,327.82,312.10
"NCNN - Target: Vulkan GPU - Model: FastestDet (ms)",LIB,2.86,2.34,2.84,2.50,2.54
"Rodinia - Test: OpenCL Particle Filter (sec)",LIB,3.480,4.098,3.291,3.844,2.973
"ArrayFire - Test: Conjugate Gradient OpenCL ()",LIB,,,,,
"ProjectPhysX OpenCL-Benchmark - Operation: FP32 Compute (TFLOPs/s)",HIB,38.594,31.768,40.914,39.395,45.950
"Blender - Blend File: BMW27 - Compute: NVIDIA OptiX (sec)",LIB,5.57,6.21,5.43,6.31,5.04
"Blender - Blend File: Classroom - Compute: NVIDIA OptiX (sec)",LIB,12.60,14.86,12.30,15.26,11.20
"Blender - Blend File: Fishy Cat - Compute: NVIDIA OptiX (sec)",LIB,9.45,11.03,9.02,10.64,8.32
"Blender - Blend File: Barbershop - Compute: NVIDIA OptiX (sec)",LIB,51.30,58.44,50.73,54.30,44.49
"Blender - Blend File: Pabellon Barcelona - Compute: NVIDIA OptiX (sec)",LIB,14.29,16.55,13.97,17.30,12.56
"NeatBench - Acceleration: GPU (FPS)",HIB,4070,4070,4070,3090,2084.1
"IndigoBench - Acceleration: OpenCL GPU - Scene: Bedroom (M samples/s)",HIB,19.801,18.203,20.256,20.959,24.570
"IndigoBench - Acceleration: OpenCL GPU - Scene: Supercar (M samples/s)",HIB,52.813,48.517,53.589,52.014,61.338
"LuxCoreRender - Scene: DLSC - Acceleration: GPU (M samples/sec)",HIB,13.59,11.74,13.95,12.99,16.23
"LuxCoreRender - Scene: Danish Mood - Acceleration: GPU (M samples/sec)",HIB,10.56,8.89,10.99,10.20,12.42
"LuxCoreRender - Scene: Orange Juice - Acceleration: GPU (M samples/sec)",HIB,11.72,10.40,11.89,12.14,13.64
"LuxCoreRender - Scene: LuxCore Benchmark - Acceleration: GPU (M samples/sec)",HIB,12.82,10.92,13.23,13.12,14.61
"LuxCoreRender - Scene: Rainbow Colors and Prism - Acceleration: GPU (M samples/sec)",HIB,27.67,23.26,27.71,33.29,31.86
"FAHBench - (Ns/Day)",HIB,366.0576,317.1952,382.1637,343.0199,394.7356
"Hashcat - Benchmark: MD5 (H/s)",HIB,67583033333,56147866667,73312233333,67177300000,82004966667
"Hashcat - Benchmark: SHA1 (H/s)",HIB,22132600000,18202466667,23532400000,21323733333,26388600000
"Hashcat - Benchmark: 7-Zip (H/s)",HIB,1176467,976967,1262633,1056000,1420700
"Hashcat - Benchmark: SHA-512 (H/s)",HIB,3232733333,2673300000,3462500000,3081866667,3887033333
"Hashcat - Benchmark: TrueCrypt RIPEMD160 + XTS (H/s)",HIB,802967,660967,858600,797833,961733
"NAMD CUDA - ATPase Simulation - 327,506 Atoms (days/ns)",LIB,0.06791,0.07498,0.06788,0.10822,0.07715
"OctaneBench - Total Score (Score)",HIB,720.973789,647.997867,735.940593,674.250912,876.436994
"FinanceBench - Benchmark: Black-Scholes OpenCL (ms)",LIB,5.912,6.906,5.226,5.741,0.501
"cl-mem - Benchmark: Copy (GB/s)",HIB,331.8,330.3,333.3,360.8,370.7
"cl-mem - Benchmark: Read (GB/s)",HIB,446.2,446.3,446.3,825.8,595.2
"cl-mem - Benchmark: Write (GB/s)",HIB,407.5,406.7,412.2,753.8,551.9
"clpeak - OpenCL Test: Integer Compute INT (GIOPS)",HIB,18170.54,14555.19,19821.10,17923.33,22171.25
"clpeak - OpenCL Test: Single-Precision Float (GFLOPS)",HIB,35492.69,28479.39,38691.73,34906.79,43244.79
"clpeak - OpenCL Test: Double-Precision Double (GFLOPS)",HIB,630.11,515.17,667.05,642.23,750.36
"clpeak - OpenCL Test: Global Memory Bandwidth (GBPS)",HIB,437.65,437.21,437.63,816.55,582.84
"MandelGPU - OpenCL Device: GPU (Samples/sec)",HIB,587219538.2,516770131.2,619106132.5,484098913.8,656484783.7
"ViennaCL - Test: CPU BLAS - sCOPY (GB/s)",HIB,132,131,132,132,107
"ViennaCL - Test: CPU BLAS - sAXPY (GB/s)",HIB,156,153,156,154,120
"ViennaCL - Test: CPU BLAS - sDOT (GB/s)",HIB,165,166,168,132.1,129
"ViennaCL - Test: CPU BLAS - dCOPY (GB/s)",HIB,70.8,71.0,71.3,70.2,52.7
"ViennaCL - Test: CPU BLAS - dAXPY (GB/s)",HIB,87.2,86.8,87.3,86.2,64.3
"ViennaCL - Test: CPU BLAS - dDOT (GB/s)",HIB,96.8,96.7,96.4,95.2,70.8
"ViennaCL - Test: CPU BLAS - dGEMV-N (GB/s)",HIB,102,103,103,103,78.5
"ViennaCL - Test: CPU BLAS - dGEMV-T (GB/s)",HIB,109,109,102.7,110,82.6
"ViennaCL - Test: CPU BLAS - dGEMM-NN (GFLOPs/s)",HIB,119,122,117,113,122
"ViennaCL - Test: CPU BLAS - dGEMM-NT (GFLOPs/s)",HIB,117,122,118,119,119
"ViennaCL - Test: CPU BLAS - dGEMM-TN (GFLOPs/s)",HIB,115,121,125,121,120
"ViennaCL - Test: CPU BLAS - dGEMM-TT (GFLOPs/s)",HIB,122,118,124,113,117
"ViennaCL - Test: OpenCL BLAS - sCOPY (GB/s)",HIB,334,330,336,363,373
"ViennaCL - Test: OpenCL BLAS - sAXPY (GB/s)",HIB,392,389,393,498,469
"ViennaCL - Test: OpenCL BLAS - sDOT (GB/s)",HIB,370,362,365,376,410
"ViennaCL - Test: OpenCL BLAS - dCOPY (GB/s)",HIB,423,423,424,605,512
"ViennaCL - Test: OpenCL BLAS - dAXPY (GB/s)",HIB,437,455,437,724,585
"ViennaCL - Test: OpenCL BLAS - dDOT (GB/s)",HIB,458,456,457,659,575
"ViennaCL - Test: OpenCL BLAS - dGEMV-N (GB/s)",HIB,210,209,211,187,218
"ViennaCL - Test: OpenCL BLAS - dGEMV-T (GB/s)",HIB,389,387,391,374,424
"ViennaCL - Test: OpenCL BLAS - dGEMM-NN (GFLOPs/s)",HIB,577,473,604,592,681
"ViennaCL - Test: OpenCL BLAS - dGEMM-NT (GFLOPs/s)",HIB,584,477,612,595,689
"ViennaCL - Test: OpenCL BLAS - dGEMM-TN (GFLOPs/s)",HIB,599,494,634,594,714
"ViennaCL - Test: OpenCL BLAS - dGEMM-TT (GFLOPs/s)",HIB,613,502,648,593,731
"Libplacebo - (FPS)",HIB,,,,,
"Libplacebo - Test: deband_heavy (FPS)",HIB,2186.70,1843.26,2306.56,2015.93,2493.29
"Libplacebo - Test: polar_nocompute (FPS)",HIB,2327.55,1968.37,2459.03,2116.50,2646.70
"Libplacebo - Test: hdr_peakdetect (FPS)",HIB,3292.37,3310.02,3475.06,4969.74,3913.34
"Libplacebo - Test: hdr_lut (FPS)",HIB,3905.98,3927.11,3971.61,3313.26,3822.16
"Libplacebo - Test: av1_grain_lap (FPS)",HIB,4171.00,4103.40,4140.87,4096.48,4044.72
"RealSR-NCNN - Scale: 4x - TAA: No (sec)",LIB,6.323,7.092,5.962,5.556,5.633
"RealSR-NCNN - Scale: 4x - TAA: Yes (sec)",LIB,34.885,42.852,33.626,30.313,30.724
"VkFFT - Test: FFT + iFFT R2C / C2R (Benchmark Score)",HIB,54794,47097,55446,48418,59378
"VkFFT - Test: FFT + iFFT C2C 1D batched in half precision (Benchmark Score)",HIB,131705,137762,136210,273221,143992
"VkFFT - Test: FFT + iFFT C2C Bluestein in single precision (Benchmark Score)",HIB,15166,13714,15125,14205,16141
"VkFFT - Test: FFT + iFFT C2C 1D batched in double precision (Benchmark Score)",HIB,24317,22390,25431,30912,27947
"VkFFT - Test: FFT + iFFT C2C 1D batched in single precision (Benchmark Score)",HIB,73929,77774,73942,141876,104003
"VkFFT - Test: FFT + iFFT C2C multidimensional in single precision (Benchmark Score)",HIB,50299,47212,51528,50856,59790
"VkFFT - Test: FFT + iFFT C2C Bluestein benchmark in double precision (Benchmark Score)",HIB,4451,3886,4647,4195,5047
"VkFFT - Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling (Benchmark Score)",HIB,75078,79057,75141,144311,105549
"vkpeak - (GFLOPS)",HIB,,,,,
"vkpeak - fp32-scalar (GFLOPS)",HIB,,,,20263.13,23883.53
"vkpeak - fp32-vec4 (GFLOPS)",HIB,,,,26563.72,31591.71
"vkpeak - fp16-scalar (GFLOPS)",HIB,,,,20080.47,23825.05
"vkpeak - fp16-vec4 (GFLOPS)",HIB,,,,39746.91,47192.56
"vkpeak - fp64-scalar (GFLOPS)",HIB,,,,638.70,750.47
"vkpeak - fp64-vec4 (GFLOPS)",HIB,,,,638.72,749.76
"vkpeak - int32-scalar (GIOPS)",HIB,,,,20280.33,23874.85
"vkpeak - int32-vec4 (GIOPS)",HIB,,,,19996.92,23733.30
"vkpeak - int16-scalar (GIOPS)",HIB,,,,13225.17,15859.37
"vkpeak - int16-vec4 (GIOPS)",HIB,,,,16302.58,21124.09
"ProjectPhysX OpenCL-Benchmark - Operation: FP64 Compute (TFLOPs/s)",HIB,0.621,0.510,0.660,0.637,0.743
"VkResample - Upscale: 2x - Precision: Double (ms)",LIB,339.593,415.160,322.064,333.639,285.988
"VkResample - Upscale: 2x - Precision: Single (ms)",LIB,18.489,18.016,18.456,10.323,13.363
"Waifu2x-NCNN Vulkan - Scale: 2x - Denoise: 3 - TAA: No (sec)",LIB,,,,,
"Waifu2x-NCNN Vulkan - Scale: 2x - Denoise: 3 - TAA: Yes (sec)",LIB,2.855,3.168,2.854,3.202,2.660