10600K pre RKL Intel Core i5-10600K testing with a ASUS PRIME Z490M-PLUS (1001 BIOS) and ASUS Intel UHD 630 3GB on Ubuntu 20.04 via the Phoronix Test Suite. 1: Processor: Intel Core i5-10600K @ 4.80GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z490M-PLUS (1001 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: Samsung SSD 970 EVO 500GB, Graphics: ASUS Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC887-VD, Monitor: LG Ultra HD, Network: Intel OS: Ubuntu 20.04, Kernel: 5.9.0-050900daily20201012-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.9, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160 2: Processor: Intel Core i5-10600K @ 4.80GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z490M-PLUS (1001 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: Samsung SSD 970 EVO 500GB, Graphics: ASUS Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC887-VD, Monitor: LG Ultra HD, Network: Intel OS: Ubuntu 20.04, Kernel: 5.9.0-050900daily20201012-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.9, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160 3: Processor: Intel Core i5-10600K @ 4.80GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z490M-PLUS (1001 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: Samsung SSD 970 EVO 500GB, Graphics: ASUS Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC887-VD, Monitor: LG Ultra HD, Network: Intel OS: Ubuntu 20.04, Kernel: 5.9.0-050900daily20201012-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.9, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160 Sysbench 1.0.20 Test: CPU Events Per Second > Higher Is Better 1 . 14374.26 |================================================================= 2 . 14373.47 |================================================================= 3 . 14375.35 |================================================================= AOM AV1 2.1-rc Encoder Mode: Speed 0 Two-Pass Frames Per Second > Higher Is Better 1 . 0.23 |===================================================================== 2 . 0.23 |===================================================================== 3 . 0.23 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 4 Two-Pass Frames Per Second > Higher Is Better 1 . 5.96 |===================================================================== 2 . 5.97 |===================================================================== 3 . 5.97 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 6 Realtime Frames Per Second > Higher Is Better 1 . 20.83 |==================================================================== 2 . 20.67 |=================================================================== 3 . 20.75 |==================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 6 Two-Pass Frames Per Second > Higher Is Better 1 . 17.05 |==================================================================== 2 . 17.09 |==================================================================== 3 . 17.06 |==================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 8 Realtime Frames Per Second > Higher Is Better 1 . 96.50 |==================================================================== 2 . 96.22 |==================================================================== 3 . 96.59 |==================================================================== SVT-HEVC 1.5.0 Tuning: 1 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 5.43 |===================================================================== 2 . 5.44 |===================================================================== 3 . 5.44 |===================================================================== SVT-HEVC 1.5.0 Tuning: 7 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 86.08 |==================================================================== 2 . 86.61 |==================================================================== 3 . 86.69 |==================================================================== SVT-HEVC 1.5.0 Tuning: 10 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 185.05 |=================================================================== 2 . 185.25 |=================================================================== 3 . 184.69 |=================================================================== SVT-VP9 0.3 Tuning: VMAF Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 149.76 |=================================================================== 2 . 149.49 |=================================================================== 3 . 149.77 |=================================================================== SVT-VP9 0.3 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 152.32 |=================================================================== 2 . 151.96 |=================================================================== 3 . 152.34 |=================================================================== SVT-VP9 0.3 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 119.95 |=================================================================== 2 . 120.03 |=================================================================== 3 . 120.00 |=================================================================== simdjson 0.8.2 Throughput Test: Kostya GB/s > Higher Is Better 1 . 3.06 |===================================================================== 2 . 3.05 |===================================================================== 3 . 3.05 |===================================================================== simdjson 0.8.2 Throughput Test: LargeRandom GB/s > Higher Is Better 1 . 1.1 |====================================================================== 2 . 1.1 |====================================================================== 3 . 1.1 |====================================================================== simdjson 0.8.2 Throughput Test: PartialTweets GB/s > Higher Is Better 1 . 4.30 |===================================================================== 2 . 4.29 |===================================================================== 3 . 4.29 |===================================================================== simdjson 0.8.2 Throughput Test: DistinctUserID GB/s > Higher Is Better 1 . 4.92 |===================================================================== 2 . 4.92 |===================================================================== 3 . 4.92 |===================================================================== Sysbench 1.0.20 Test: RAM / Memory MiB/sec > Higher Is Better 1 . 26132.76 |================================================================= 2 . 25903.89 |================================================================ 3 . 26135.31 |================================================================= oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 4.32120 |================================================================== 2 . 4.31466 |================================================================== 3 . 4.28025 |================================================================= oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 7.66238 |================================================================= 2 . 7.73529 |================================================================== 3 . 7.47684 |================================================================ oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.04154 |================================================================== 2 . 2.03699 |================================================================== 3 . 2.01397 |================================================================= oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.39200 |================================================================== 2 . 2.38521 |================================================================== 3 . 2.39279 |================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 15.11 |==================================================================== 2 . 15.12 |==================================================================== 3 . 15.08 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 10.04714 |================================================================= 2 . 10.08070 |================================================================= 3 . 9.98148 |================================================================ oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 8.51089 |================================================================== 2 . 8.51927 |================================================================== 3 . 8.52282 |================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 13.73 |=================================================================== 2 . 13.81 |==================================================================== 3 . 13.84 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.66876 |================================================================== 2 . 2.65983 |================================================================== 3 . 2.65906 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 5.36600 |================================================================== 2 . 5.31671 |================================================================= 3 . 5.36398 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3990.01 |================================================================== 2 . 3998.99 |================================================================== 3 . 3986.56 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 2379.62 |================================================================= 2 . 2403.36 |================================================================== 3 . 2374.75 |================================================================= oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3992.29 |================================================================== 2 . 3996.07 |================================================================== 3 . 3987.23 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2381.10 |================================================================== 2 . 2394.46 |================================================================== 3 . 2372.73 |================================================================= oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3.38413 |================================================================== 2 . 3.37849 |================================================================== 3 . 3.39558 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 4002.18 |================================================================== 2 . 3995.94 |================================================================== 3 . 3987.15 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 2382.71 |================================================================== 2 . 2397.83 |================================================================== 3 . 2372.19 |================================================================= oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3.46010 |================================================================== 2 . 3.47494 |================================================================== 3 . 3.46459 |================================================================== Mobile Neural Network 1.1.3 Model: SqueezeNetV1.0 ms < Lower Is Better 1 . 4.514 |==================================================================== 2 . 4.508 |==================================================================== 3 . 4.452 |=================================================================== Mobile Neural Network 1.1.3 Model: resnet-v2-50 ms < Lower Is Better 1 . 28.55 |==================================================================== 2 . 28.58 |==================================================================== 3 . 28.47 |==================================================================== Mobile Neural Network 1.1.3 Model: MobileNetV2_224 ms < Lower Is Better 1 . 2.546 |==================================================================== 2 . 2.549 |==================================================================== 3 . 2.559 |==================================================================== Mobile Neural Network 1.1.3 Model: mobilenet-v1-1.0 ms < Lower Is Better 1 . 3.260 |==================================================================== 2 . 3.240 |==================================================================== 3 . 3.231 |=================================================================== Mobile Neural Network 1.1.3 Model: inception-v3 ms < Lower Is Better 1 . 33.77 |==================================================================== 2 . 33.98 |==================================================================== 3 . 33.93 |==================================================================== Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 129 Cells Per Direction Seconds < Lower Is Better 1 . 37.29 |================================================================== 2 . 38.21 |==================================================================== 3 . 37.77 |=================================================================== Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 193 Cells Per Direction Seconds < Lower Is Better 1 . 131.98 |================================================================== 2 . 131.82 |================================================================== 3 . 133.00 |=================================================================== Timed Mesa Compilation 21.0 Time To Compile Seconds < Lower Is Better 1 . 69.65 |==================================================================== 2 . 69.69 |==================================================================== 3 . 69.81 |==================================================================== Timed Node.js Compilation 15.11 Time To Compile Seconds < Lower Is Better 1 . 596.49 |=================================================================== 2 . 596.97 |=================================================================== 3 . 597.22 |=================================================================== ASTC Encoder 2.4 Preset: Medium Seconds < Lower Is Better 1 . 6.0128 |=================================================================== 2 . 6.0240 |=================================================================== 3 . 6.0152 |=================================================================== ASTC Encoder 2.4 Preset: Thorough Seconds < Lower Is Better 1 . 18.33 |==================================================================== 2 . 18.34 |==================================================================== 3 . 18.29 |==================================================================== ASTC Encoder 2.4 Preset: Exhaustive Seconds < Lower Is Better 1 . 144.63 |=================================================================== 2 . 144.59 |=================================================================== 3 . 143.53 |================================================================== Basis Universal 1.13 Settings: ETC1S Seconds < Lower Is Better 1 . 25.52 |==================================================================== 2 . 25.51 |==================================================================== 3 . 25.37 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 0 Seconds < Lower Is Better 1 . 7.600 |==================================================================== 2 . 7.601 |==================================================================== 3 . 7.603 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 2 Seconds < Lower Is Better 1 . 41.23 |==================================================================== 2 . 41.21 |==================================================================== 3 . 41.22 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 3 Seconds < Lower Is Better 1 . 79.67 |==================================================================== 2 . 79.68 |==================================================================== 3 . 79.66 |====================================================================