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.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2103183-IB-10600KPRE35
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Timed Code Compilation 2 Tests
C/C++ Compiler Tests 3 Tests
CPU Massive 4 Tests
Creator Workloads 6 Tests
Encoding 3 Tests
Game Development 2 Tests
HPC - High Performance Computing 3 Tests
Machine Learning 2 Tests
Multi-Core 7 Tests
Programmer / Developer System Benchmarks 3 Tests
Python Tests 2 Tests
Server CPU Tests 4 Tests
Texture Compression 2 Tests
Video Encoding 3 Tests

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March 18 2021
  2 Hours, 28 Minutes
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March 18 2021
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March 18 2021
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10600K pre RKL, "AOM AV1 2.1-rc - Encoder Mode: Speed 0 Two-Pass", Higher Results Are Better "1",0.23,0.23,0.23 "2",0.23,0.23,0.23 "3",0.23,0.23,0.23 "AOM AV1 2.1-rc - Encoder Mode: Speed 4 Two-Pass", Higher Results Are Better "1",5.96,5.96,5.96 "2",5.99,5.93,5.98 "3",5.98,5.96,5.98 "AOM AV1 2.1-rc - Encoder Mode: Speed 6 Realtime", Higher Results Are Better "1",20.95,20.86,20.69 "2",20.74,20.89,20.37 "3",20.87,20.53,20.85 "AOM AV1 2.1-rc - Encoder Mode: Speed 6 Two-Pass", Higher Results Are Better "1",17.01,17.02,17.11 "2",17.09,17.09,17.1 "3",17.1,17.07,17.01 "AOM AV1 2.1-rc - Encoder Mode: Speed 8 Realtime", Higher Results Are Better "1",96.82,96.25,96.43 "2",95.89,96.26,96.52 "3",96.7,96.44,96.64 "ASTC Encoder 2.4 - Preset: Medium", Lower Results Are Better "1",5.9999,6.0197,6.0187 "2",6.0215,6.0259,6.0245 "3",6.018,6.0158,6.0118 "ASTC Encoder 2.4 - Preset: Thorough", Lower Results Are Better "1",18.2866,18.3369,18.367 "2",18.2902,18.3348,18.3956 "3",18.2864,18.2964,18.2839 "ASTC Encoder 2.4 - Preset: Exhaustive", Lower Results Are Better "1",144.2032,144.7836,144.9151 "2",144.0712,144.8481,144.8562 "3",142.9299,143.8655,143.8004 "Basis Universal 1.13 - Settings: ETC1S", Lower Results Are Better "1",25.571,25.532,25.455 "2",25.569,25.49,25.483 "3",25.432,25.296,25.367 "Basis Universal 1.13 - Settings: UASTC Level 0", Lower Results Are Better "1",7.598,7.607,7.594 "2",7.604,7.606,7.593 "3",7.6,7.611,7.599 "Basis Universal 1.13 - Settings: UASTC Level 2", Lower Results Are Better "1",41.206,41.227,41.243 "2",41.21,41.215,41.206 "3",41.215,41.24,41.209 "Basis Universal 1.13 - Settings: UASTC Level 3", Lower Results Are Better "1",79.665,79.662,79.675 "2",79.666,79.678,79.692 "3",79.654,79.662,79.671 "Mobile Neural Network 1.1.3 - Model: SqueezeNetV1.0", Lower Results Are Better "1",4.503,4.533,4.505 "2",4.522,4.497,4.506 "3",4.445,4.46,4.452 "Mobile Neural Network 1.1.3 - Model: resnet-v2-50", Lower Results Are Better "1",28.358,28.683,28.594 "2",28.461,28.615,28.653 "3",28.392,28.477,28.544 "Mobile Neural Network 1.1.3 - Model: MobileNetV2_224", Lower Results Are Better "1",2.57,2.537,2.532 "2",2.565,2.528,2.555 "3",2.523,2.579,2.574 "Mobile Neural Network 1.1.3 - Model: mobilenet-v1-1.0", Lower Results Are Better "1",3.239,3.273,3.269 "2",3.239,3.237,3.244 "3",3.205,3.227,3.262 "Mobile Neural Network 1.1.3 - Model: inception-v3", Lower Results Are Better "1",33.7,33.791,33.819 "2",33.896,33.76,34.285 "3",33.66,33.84,34.284 "oneDNN 2.1.2 - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",4.30426,4.33357,4.32578 "2",4.2889,4.31149,4.34358 "3",4.2443,4.29489,4.30156 "oneDNN 2.1.2 - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",7.62569,7.68509,7.67636 "2",7.70796,7.7519,7.74602 "3",7.44501,7.49981,7.4857 "oneDNN 2.1.2 - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",2.02505,2.0508,2.04876 "2",2.0161,2.0427,2.05217 "3",2.00278,2.01419,2.02494 "oneDNN 2.1.2 - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",2.37826,2.40378,2.39396 "2",2.37534,2.38454,2.39576 "3",2.37063,2.411,2.39673 "oneDNN 2.1.2 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",15.075,15.2025,15.0575 "2",15.0638,15.2208,15.0775 "3",15.0304,15.1847,15.0198 "oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",9.95322,10.0719,10.1163 "2",10.0378,10.0671,10.1371 "3",10.0016,9.97064,9.97219 "oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",8.5245,8.50798,8.50018 "2",8.53105,8.50602,8.52074 "3",8.53728,8.52372,8.50747 "oneDNN 2.1.2 - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",13.6037,13.8286,13.7513 "2",13.8542,13.8651,13.7234 "3",13.7635,14.0105,13.7524 "oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",2.64627,2.66368,2.69632 "2",2.64897,2.6644,2.66612 "3",2.65213,2.65739,2.66765 "oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",5.38873,5.3621,5.34717 "2",5.28832,5.3195,5.34232 "3",5.373,5.37228,5.34665 "oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",3989.91,3991.02,3989.11 "2",3995.21,3997.01,4004.76 "3",3984.12,3987.19,3988.36 "oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",2385.28,2375.57,2378.01 "2",2400.64,2397.63,2411.8 "3",2378.5,2372.51,2373.24 "oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",3991.78,3991.66,3993.44 "2",3996.17,3994.12,3997.91 "3",3990.66,3985.41,3985.63 "oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",2386.48,2379.31,2377.5 "2",2396.39,2393.62,2393.36 "3",2374.58,2370.25,2373.35 "oneDNN 2.1.2 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",3.37977,3.38829,3.38432 "2",3.3629,3.38984,3.38272 "3",3.40487,3.39283,3.38904 "oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "1",4020.15,3992.22,3994.16 "2",3997.9,3993.75,3996.16 "3",3985.31,3989.34,3986.81 "oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "1",2379.39,2384.01,2384.72 "2",2399.21,2398.77,2395.52 "3",2373.12,2374.11,2369.33 "oneDNN 2.1.2 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",3.43455,3.4672,3.47855 "2",3.47344,3.47645,3.47492 "3",3.46642,3.467,3.46036 "simdjson 0.8.2 - Throughput Test: Kostya", Higher Results Are Better "1",3.06,3.06,3.06 "2",3.06,3.05,3.05 "3",3.05,3.06,3.05 "simdjson 0.8.2 - Throughput Test: LargeRandom", Higher Results Are Better "1",1.1,1.1,1.1 "2",1.1,1.1,1.1 "3",1.1,1.1,1.1 "simdjson 0.8.2 - Throughput Test: PartialTweets", Higher Results Are Better "1",4.29,4.3,4.3 "2",4.28,4.3,4.3 "3",4.29,4.28,4.29 "simdjson 0.8.2 - Throughput Test: DistinctUserID", Higher Results Are Better "1",4.9,4.93,4.92 "2",4.91,4.92,4.93 "3",4.92,4.92,4.93 "SVT-HEVC 1.5.0 - Tuning: 1 - Input: Bosphorus 1080p", Higher Results Are Better "1",5.45,5.42,5.43 "2",5.45,5.43,5.43 "3",5.48,5.43,5.42 "SVT-HEVC 1.5.0 - Tuning: 7 - Input: Bosphorus 1080p", Higher Results Are Better "1",85.95,86.12,86.18 "2",86.52,86.62,86.68 "3",86.62,86.72,86.74 "SVT-HEVC 1.5.0 - Tuning: 10 - Input: Bosphorus 1080p", Higher Results Are Better "1",185.13,184.96,185.07 "2",184.62,185.19,185.93 "3",184.11,185.41,184.56 "SVT-VP9 0.3 - Tuning: VMAF Optimized - Input: Bosphorus 1080p", Higher Results Are Better "1",150.29,149.27,149.73 "2",149.39,149.59,149.48 "3",150,149.7,149.61 "SVT-VP9 0.3 - Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p", Higher Results Are Better "1",152.39,151.8,152.77 "2",152.01,152.12,151.75 "3",151.76,152.53,152.72 "SVT-VP9 0.3 - Tuning: Visual Quality Optimized - Input: Bosphorus 1080p", Higher Results Are Better "1",119.73,119.94,120.19 "2",120.31,119.84,119.93 "3",119.55,120.12,120.33 "Sysbench 1.0.20 - Test: RAM / Memory", Higher Results Are Better "1",26489.87,26020.53,25887.87 "2",25816.5,25932.39,25962.79 "3",25792.32,26183.14,26430.48 "Sysbench 1.0.20 - Test: CPU", Higher Results Are Better "1",14376.21,14372.4,14374.17 "2",14375.95,14370.64,14373.83 "3",14375.16,14375.76,14375.13 "Timed Mesa Compilation 21.0 - Time To Compile", Lower Results Are Better "1",69.428,70.001,69.532 "2",69.768,69.578,69.721 "3",69.798,69.788,69.837 "Timed Node.js Compilation 15.11 - Time To Compile", Lower Results Are Better "1",596.318,596.445,596.711 "2",596.493,597.074,597.344 "3",596.981,597.317,597.349 "Xcompact3d Incompact3d 2021-03-11 - Input: input.i3d 129 Cells Per Direction", Lower Results Are Better "1",36.9744759,38.01231,36.896904 "2",38.0745201,38.268795,38.2863884 "3",38.0784874,37.0784302,38.1503296 "Xcompact3d Incompact3d 2021-03-11 - Input: input.i3d 193 Cells Per Direction", Lower Results Are Better "1",133.124374,132.957123,129.846298 "2",132.70047,132.958862,129.796112 "3",132.86763,133.289001,132.835007