AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and AMD Radeon RX 6700 XT on Ubuntu 23.04 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 2308012-PTS-VULKANBE49
vulkan benchmarks
AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and AMD Radeon RX 6700 XT on Ubuntu 23.04 via the Phoronix Test Suite.
,,"a","b","c"
Processor,,AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads)
Motherboard,,ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS)
Chipset,,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8
Memory,,32GB,32GB,32GB
Disk,,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB
Graphics,,AMD Radeon RX 6700 XT (2855/1000MHz),AMD Radeon RX 6700 XT (2855/1000MHz),AMD Radeon RX 6700 XT (2855/1000MHz)
Audio,,AMD Navi 21/23,AMD Navi 21/23,AMD Navi 21/23
Monitor,,ASUS MG28U,ASUS MG28U,ASUS MG28U
Network,,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411
OS,,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04
Kernel,,6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64)
Desktop,,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2
Display Server,,X Server 1.21.1.7 + Wayland,X Server 1.21.1.7 + Wayland,X Server 1.21.1.7 + Wayland
OpenGL,,4.6 Mesa 23.3~git2307260600.87109c~oibaf~l (git-87109c3 2023-07-26 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.52),4.6 Mesa 23.3~git2307260600.87109c~oibaf~l (git-87109c3 2023-07-26 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.52),4.6 Mesa 23.3~git2307260600.87109c~oibaf~l (git-87109c3 2023-07-26 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.52)
Compiler,,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0
File-System,,ext4,ext4,ext4
Screen Resolution,,3840x2160,3840x2160,3840x2160
,,"a","b","c"
"vkpeak - fp32-scalar (GFLOPS)",HIB,13190.09,12807.06,12860.56
"vkpeak - fp32-vec4 (GFLOPS)",HIB,12730.08,12808.59,12822.01
"vkpeak - fp16-scalar (GFLOPS)",HIB,13154.15,13145.19,13136.79
"vkpeak - fp16-vec4 (GFLOPS)",HIB,23232.42,23390.44,23387.26
"vkpeak - fp64-scalar (GFLOPS)",HIB,841.40,839.2,839.01
"vkpeak - fp64-vec4 (GFLOPS)",HIB,841.80,836.55,836.16
"vkpeak - int32-scalar (GIOPS)",HIB,2272.62,2269.25,2269.06
"vkpeak - int32-vec4 (GIOPS)",HIB,2658.73,2640.08,2638.69
"vkpeak - int16-scalar (GIOPS)",HIB,13102.75,13070.81,13063.86
"vkpeak - int16-vec4 (GIOPS)",HIB,23123.77,23396.59,23385.44
"VkFFT - Test: FFT + iFFT R2C / C2R (Benchmark Score)",HIB,42105,42163,43021
"VkFFT - Test: FFT + iFFT C2C 1D batched in half precision (Benchmark Score)",HIB,91597,91812,91744
"VkFFT - Test: FFT + iFFT C2C Bluestein in single precision (Benchmark Score)",HIB,11340,11273,11311
"VkFFT - Test: FFT + iFFT C2C 1D batched in double precision (Benchmark Score)",HIB,20816,20822,20847
"VkFFT - Test: FFT + iFFT C2C 1D batched in single precision (Benchmark Score)",HIB,47887,47948,47971
"VkFFT - Test: FFT + iFFT C2C multidimensional in single precision (Benchmark Score)",HIB,33001,32751,32812
"VkFFT - Test: FFT + iFFT C2C Bluestein benchmark in double precision (Benchmark Score)",HIB,4717,4695,4670
"VkFFT - Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling (Benchmark Score)",HIB,50504,50643,50596
"VkResample - Upscale: 2x - Precision: Single (ms)",LIB,11.686,11.69,11.688
"NCNN - Target: CPU - Model: mobilenet (ms)",LIB,8.05,7.97,8.02
"NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,3.16,3.16,3.18
"NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,3.34,3.34,3.35
"NCNN - Target: CPU - Model: mnasnet (ms)",LIB,2.97,2.97,2.99
"NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,3.90,3.85,3.88
"NCNN - Target: CPU - Model: blazeface (ms)",LIB,1.38,1.38,1.39
"NCNN - Target: CPU - Model: googlenet (ms)",LIB,7.94,7.82,7.93
"NCNN - Target: CPU - Model: vgg16 (ms)",LIB,23.75,23.49,23.45
"NCNN - Target: CPU - Model: resnet18 (ms)",LIB,5.29,5.2,5.24
"NCNN - Target: CPU - Model: alexnet (ms)",LIB,4.41,4.32,4.31
"NCNN - Target: CPU - Model: resnet50 (ms)",LIB,10.20,10.01,10.11
"NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,12.90,12.74,12.81
"NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,7.07,7.06,7.1
"NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,8.18,8.18,8.27
"NCNN - Target: CPU - Model: vision_transformer (ms)",LIB,32.49,31.95,31.77
"NCNN - Target: CPU - Model: FastestDet (ms)",LIB,3.62,4.05,4.11
"NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.18,,3.17
"NCNN - Target: Vulkan GPU - Model: mobilenet (ms)",LIB,8.05,8.04,8.03
"NCNN - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,3.17,3.14,3.13
"NCNN - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.17,,3.2
"NCNN - Target: Vulkan GPU - Model: shufflenet-v2 (ms)",LIB,3.35,3.33,3.32
"NCNN - Target: Vulkan GPU - Model: mnasnet (ms)",LIB,2.98,2.95,2.96
"NCNN - Target: Vulkan GPU - Model: efficientnet-b0 (ms)",LIB,3.86,3.82,3.83
"NCNN - Target: Vulkan GPU - Model: blazeface (ms)",LIB,1.38,1.37,1.37
"NCNN - Target: Vulkan GPU - Model: googlenet (ms)",LIB,7.90,7.85,7.8
"NCNN - Target: Vulkan GPU - Model: vgg16 (ms)",LIB,23.51,23.56,23.54
"NCNN - Target: Vulkan GPU - Model: resnet18 (ms)",LIB,5.28,5.23,5.21
"NCNN - Target: Vulkan GPU - Model: alexnet (ms)",LIB,4.31,4.33,4.33
"NCNN - Target: Vulkan GPU - Model: resnet50 (ms)",LIB,10.01,10,10
"NCNN - Target: Vulkan GPU - Model: yolov4-tiny (ms)",LIB,12.84,12.87,12.81
"NCNN - Target: Vulkan GPU - Model: squeezenet_ssd (ms)",LIB,7.09,7.07,7.06
"NCNN - Target: Vulkan GPU - Model: regnety_400m (ms)",LIB,8.16,8.21,8
"NCNN - Target: Vulkan GPU - Model: vision_transformer (ms)",LIB,31.88,31.85,31.79
"NCNN - Target: Vulkan GPU - Model: FastestDet (ms)",LIB,4.1,4.07,4.09
"NCNN - Target: CPU-v3-v3-v3 - Model: mobilenet (ms)",LIB,,8.01,8
"NCNN - Target: CPU-v3-v3-v3-v2-v2 - Model: mobilenet-v2 (ms)",LIB,,3.15,3.14
"NCNN - Target: CPU-v3-v3-v3-v3-v3 - Model: mobilenet-v3 (ms)",LIB,,3.16,3.16
"NCNN - Target: CPU-v3-v3-v3 - Model: shufflenet-v2 (ms)",LIB,,3.33,3.34
"NCNN - Target: CPU-v3-v3-v3 - Model: mnasnet (ms)",LIB,,2.97,2.97
"NCNN - Target: CPU-v3-v3-v3 - Model: efficientnet-b0 (ms)",LIB,,3.82,3.89
"NCNN - Target: CPU-v3-v3-v3 - Model: blazeface (ms)",LIB,,1.37,1.38
"NCNN - Target: CPU-v3-v3-v3 - Model: googlenet (ms)",LIB,,7.84,7.88
"NCNN - Target: CPU-v3-v3-v3 - Model: vgg16 (ms)",LIB,,23.5,23.99
"NCNN - Target: CPU-v3-v3-v3 - Model: resnet18 (ms)",LIB,,5.21,5.26
"NCNN - Target: CPU-v3-v3-v3 - Model: alexnet (ms)",LIB,,4.29,4.28
"NCNN - Target: CPU-v3-v3-v3 - Model: resnet50 (ms)",LIB,,10.01,10.33
"NCNN - Target: CPU-v3-v3-v3 - Model: yolov4-tiny (ms)",LIB,,12.98,12.89
"NCNN - Target: CPU-v3-v3-v3 - Model: squeezenet_ssd (ms)",LIB,,7.03,7.04
"NCNN - Target: CPU-v3-v3-v3 - Model: regnety_400m (ms)",LIB,,8.05,8.14
"NCNN - Target: CPU-v3-v3-v3 - Model: vision_transformer (ms)",LIB,,31.65,31.78
"NCNN - Target: CPU-v3-v3-v3 - Model: FastestDet (ms)",LIB,,4.07,4.08
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: mobilenet (ms)",LIB,,8,7.95
"NCNN - Target: Vulkan GPU-v3-v3-v3-v2-v2 - Model: mobilenet-v2 (ms)",LIB,,3.15,3.15
"NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3 - Model: mobilenet-v3 (ms)",LIB,,3.16,3.17
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: shufflenet-v2 (ms)",LIB,,3.33,3.33
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: mnasnet (ms)",LIB,,2.96,2.96
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: efficientnet-b0 (ms)",LIB,,3.85,3.82
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: blazeface (ms)",LIB,,1.37,1.36
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: googlenet (ms)",LIB,,7.97,7.83
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: vgg16 (ms)",LIB,,23.42,23.54
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: resnet18 (ms)",LIB,,5.42,5.23
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: alexnet (ms)",LIB,,4.42,4.3
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: resnet50 (ms)",LIB,,9.87,10.03
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: yolov4-tiny (ms)",LIB,,12.77,12.86
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: squeezenet_ssd (ms)",LIB,,7.14,7.07
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: regnety_400m (ms)",LIB,,8.27,7.98
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: vision_transformer (ms)",LIB,,31.71,31.66
"NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: FastestDet (ms)",LIB,,4.06,3.69