ryzen 7 3700x dec AMD Ryzen 7 3700X 8-Core testing with a Gigabyte A320M-S2H-CF (F52a BIOS) and HIS AMD Radeon HD 7750/8740 / R7 250E 1GB on Ubuntu 20.04 via the Phoronix Test Suite. 1: Processor: AMD Ryzen 7 3700X 8-Core @ 3.60GHz (8 Cores / 16 Threads), Motherboard: Gigabyte A320M-S2H-CF (F52a BIOS), Chipset: AMD Starship/Matisse, Memory: 8GB, Disk: 240GB TOSHIBA RC100, Graphics: HIS AMD Radeon HD 7750/8740 / R7 250E 1GB, Audio: AMD Oland/Hainan/Cape, Monitor: VA2431, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.04, Kernel: 5.8.1-050801-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.5 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 2: Processor: AMD Ryzen 7 3700X 8-Core @ 3.60GHz (8 Cores / 16 Threads), Motherboard: Gigabyte A320M-S2H-CF (F52a BIOS), Chipset: AMD Starship/Matisse, Memory: 8GB, Disk: 240GB TOSHIBA RC100, Graphics: HIS AMD Radeon HD 7750/8740 / R7 250E 1GB, Audio: AMD Oland/Hainan/Cape, Monitor: VA2431, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.04, Kernel: 5.8.1-050801-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.5 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 3: Processor: AMD Ryzen 7 3700X 8-Core @ 3.60GHz (8 Cores / 16 Threads), Motherboard: Gigabyte A320M-S2H-CF (F52a BIOS), Chipset: AMD Starship/Matisse, Memory: 8GB, Disk: 240GB TOSHIBA RC100, Graphics: HIS AMD Radeon HD 7750/8740 / R7 250E 1GB, Audio: AMD Oland/Hainan/Cape, Monitor: VA2431, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.04, Kernel: 5.8.1-050801-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.5 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 4: Processor: AMD Ryzen 7 3700X 8-Core @ 3.60GHz (8 Cores / 16 Threads), Motherboard: Gigabyte A320M-S2H-CF (F52a BIOS), Chipset: AMD Starship/Matisse, Memory: 8GB, Disk: 240GB TOSHIBA RC100, Graphics: HIS AMD Radeon HD 7750/8740 / R7 250E 1GB, Audio: AMD Oland/Hainan/Cape, Monitor: VA2431, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.04, Kernel: 5.8.1-050801-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.5 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 High Performance Conjugate Gradient 3.1 GFLOP/s > Higher Is Better 1 . 4.15940 |================================================================== 2 . 4.13952 |================================================================= 3 . 4.14396 |================================================================= 4 . 4.18942 |================================================================== CLOMP 1.2 Static OMP Speedup Speedup > Higher Is Better 1 . 23.0 |==================================================================== 2 . 23.4 |===================================================================== 3 . 23.4 |===================================================================== 4 . 23.2 |==================================================================== Timed HMMer Search 3.3.1 Pfam Database Search Seconds < Lower Is Better 1 . 107.50 |=================================================================== 2 . 107.86 |=================================================================== 3 . 108.07 |=================================================================== 4 . 107.12 |================================================================== simdjson 0.7.1 Throughput Test: Kostya GB/s > Higher Is Better 1 . 0.59 |===================================================================== 2 . 0.59 |===================================================================== 3 . 0.59 |===================================================================== 4 . 0.59 |===================================================================== simdjson 0.7.1 Throughput Test: LargeRandom GB/s > Higher Is Better 1 . 0.43 |===================================================================== 2 . 0.42 |=================================================================== 3 . 0.43 |===================================================================== 4 . 0.43 |===================================================================== simdjson 0.7.1 Throughput Test: PartialTweets GB/s > Higher Is Better 1 . 0.69 |===================================================================== 2 . 0.68 |==================================================================== 3 . 0.67 |=================================================================== 4 . 0.68 |==================================================================== simdjson 0.7.1 Throughput Test: DistinctUserID GB/s > Higher Is Better 1 . 0.70 |===================================================================== 2 . 0.70 |===================================================================== 3 . 0.70 |===================================================================== 4 . 0.70 |===================================================================== LZ4 Compression 1.9.3 Compression Level: 1 - Compression Speed MB/s > Higher Is Better 1 . 9360.33 |================================================================== 2 . 9307.53 |================================================================== 3 . 9368.21 |================================================================== 4 . 9333.49 |================================================================== LZ4 Compression 1.9.3 Compression Level: 1 - Decompression Speed MB/s > Higher Is Better 1 . 10310.6 |================================================================== 2 . 10300.3 |================================================================== 3 . 10277.4 |================================================================== 4 . 10229.8 |================================================================= LZ4 Compression 1.9.3 Compression Level: 3 - Compression Speed MB/s > Higher Is Better 1 . 51.50 |=================================================================== 2 . 50.73 |================================================================== 3 . 51.59 |=================================================================== 4 . 52.10 |==================================================================== LZ4 Compression 1.9.3 Compression Level: 3 - Decompression Speed MB/s > Higher Is Better 1 . 9919.0 |=================================================================== 2 . 9895.1 |=================================================================== 3 . 9901.3 |=================================================================== 4 . 9944.8 |=================================================================== LZ4 Compression 1.9.3 Compression Level: 9 - Compression Speed MB/s > Higher Is Better 1 . 50.69 |==================================================================== 2 . 49.77 |=================================================================== 3 . 50.47 |==================================================================== 4 . 50.16 |=================================================================== LZ4 Compression 1.9.3 Compression Level: 9 - Decompression Speed MB/s > Higher Is Better 1 . 9942.5 |=================================================================== 2 . 9964.5 |=================================================================== 3 . 9943.8 |=================================================================== 4 . 9903.2 |=================================================================== Crafty 25.2 Elapsed Time Nodes Per Second > Higher Is Better 1 . 8546471 |=============================================================== 2 . 8920559 |================================================================== 3 . 8893425 |================================================================== 4 . 8823060 |================================================================= oneDNN 2.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 6.41982 |================================================================== 2 . 5.63807 |========================================================== 3 . 5.71737 |=========================================================== 4 . 5.47702 |======================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 9.36757 |================================================================== 2 . 9.21133 |================================================================ 3 . 9.43065 |================================================================== 4 . 9.22956 |================================================================= oneDNN 2.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.59978 |================================================================= 2 . 2.62207 |================================================================== 3 . 2.61510 |================================================================== 4 . 2.60889 |================================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1.92313 |====================================================== 2 . 2.24347 |=============================================================== 3 . 2.35658 |================================================================== 4 . 2.32680 |================================================================= oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 21.88 |================================================================= 2 . 22.50 |=================================================================== 3 . 22.18 |================================================================== 4 . 22.73 |==================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 5.46401 |================================================================== 2 . 5.09666 |============================================================== 3 . 5.14679 |============================================================== 4 . 5.06969 |============================================================= oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 6.98587 |================================================================== 2 . 6.73147 |================================================================ 3 . 6.76584 |================================================================ 4 . 6.69818 |=============================================================== oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 20.40 |================================================================== 2 . 20.60 |=================================================================== 3 . 20.91 |==================================================================== 4 . 20.61 |=================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 6.51376 |================================================================== 2 . 6.43594 |================================================================= 3 . 6.37617 |================================================================= 4 . 6.33997 |================================================================ oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 5.32109 |================================================================== 2 . 5.30594 |================================================================== 3 . 5.26936 |================================================================= 4 . 5.28923 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3822.92 |================================================================= 2 . 3843.11 |================================================================= 3 . 3876.27 |================================================================== 4 . 3804.05 |================================================================= oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 2647.28 |================================================================ 2 . 2716.83 |================================================================== 3 . 2700.05 |================================================================== 4 . 2668.89 |================================================================= oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3848.17 |================================================================= 2 . 3841.65 |================================================================= 3 . 3906.57 |================================================================== 4 . 3828.50 |================================================================= oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2870.93 |================================================================== 2 . 2680.98 |============================================================= 3 . 2686.22 |============================================================== 4 . 2877.16 |================================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 4.18422 |======================================================== 2 . 4.46430 |============================================================ 3 . 4.42827 |=========================================================== 4 . 4.92533 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 3905.20 |================================================================== 2 . 3828.39 |================================================================= 3 . 3885.91 |================================================================== 4 . 3872.86 |================================================================= oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 2691.72 |================================================================== 2 . 2671.70 |================================================================= 3 . 2656.26 |================================================================= 4 . 2707.27 |================================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.95246 |================================================================== 2 . 2.90638 |================================================================= 3 . 2.86008 |================================================================ 4 . 2.84703 |================================================================ rav1e 0.4 Alpha Speed: 1 Frames Per Second > Higher Is Better 1 . 0.402 |==================================================================== 2 . 0.402 |==================================================================== 3 . 0.398 |=================================================================== 4 . 0.400 |==================================================================== rav1e 0.4 Alpha Speed: 5 Frames Per Second > Higher Is Better 1 . 1.186 |==================================================================== 2 . 1.183 |==================================================================== 3 . 1.185 |==================================================================== 4 . 1.178 |==================================================================== rav1e 0.4 Alpha Speed: 6 Frames Per Second > Higher Is Better 1 . 1.587 |==================================================================== 2 . 1.586 |==================================================================== 3 . 1.582 |==================================================================== 4 . 1.582 |==================================================================== rav1e 0.4 Alpha Speed: 10 Frames Per Second > Higher Is Better 1 . 3.457 |==================================================================== 2 . 3.450 |==================================================================== 3 . 3.447 |==================================================================== 4 . 3.455 |==================================================================== Coremark 1.0 CoreMark Size 666 - Iterations Per Second Iterations/Sec > Higher Is Better 1 . 353574.86 |================================================================ 2 . 353496.41 |================================================================ 3 . 352288.84 |=============================================================== 4 . 355783.64 |================================================================ Stockfish 12 Total Time Nodes Per Second > Higher Is Better 1 . 20160779 |================================================================= 2 . 19613677 |=============================================================== 3 . 19737025 |================================================================ 4 . 19931000 |================================================================ asmFish 2018-07-23 1024 Hash Memory, 26 Depth Nodes/second > Higher Is Better 1 . 27502562 |================================================================ 2 . 27582263 |================================================================ 3 . 27974508 |================================================================= 4 . 27935855 |================================================================= Timed Clash Compilation Time To Compile Seconds < Lower Is Better 1 . 248.03 |=================================================================== 2 . 249.58 |=================================================================== 3 . 247.21 |================================================================== 4 . 245.51 |================================================================== Timed FFmpeg Compilation 4.2.2 Time To Compile Seconds < Lower Is Better 1 . 56.28 |==================================================================== 2 . 56.17 |==================================================================== 3 . 56.01 |=================================================================== 4 . 56.45 |==================================================================== Build2 0.13 Time To Compile Seconds < Lower Is Better 1 . 119.01 |=================================================================== 2 . 118.89 |================================================================== 3 . 117.14 |================================================================= 4 . 119.84 |=================================================================== Timed Eigen Compilation 3.3.9 Time To Compile Seconds < Lower Is Better 1 . 74.18 |==================================================================== 2 . 74.09 |==================================================================== 3 . 74.08 |==================================================================== 4 . 73.35 |=================================================================== Monkey Audio Encoding 3.99.6 WAV To APE Seconds < Lower Is Better 1 . 11.57 |==================================================================== 2 . 11.60 |==================================================================== 3 . 11.50 |=================================================================== 4 . 11.52 |==================================================================== Ogg Audio Encoding 1.3.4 WAV To Ogg Seconds < Lower Is Better 1 . 18.84 |==================================================================== 2 . 18.90 |==================================================================== 3 . 18.85 |==================================================================== 4 . 18.77 |==================================================================== Opus Codec Encoding 1.3.1 WAV To Opus Encode Seconds < Lower Is Better 1 . 7.194 |==================================================================== 2 . 7.213 |==================================================================== 3 . 7.204 |==================================================================== 4 . 7.212 |==================================================================== Node.js V8 Web Tooling Benchmark runs/s > Higher Is Better 1 . 12.06 |=================================================================== 2 . 12.13 |==================================================================== 3 . 12.17 |==================================================================== 4 . 12.09 |==================================================================== ASTC Encoder 2.0 Preset: Fast Seconds < Lower Is Better 1 . 5.97 |=================================================================== 2 . 6.02 |==================================================================== 3 . 6.11 |===================================================================== 4 . 5.99 |==================================================================== ASTC Encoder 2.0 Preset: Medium Seconds < Lower Is Better 1 . 8.68 |===================================================================== 2 . 8.69 |===================================================================== 3 . 8.69 |===================================================================== 4 . 8.69 |===================================================================== ASTC Encoder 2.0 Preset: Thorough Seconds < Lower Is Better 1 . 26.68 |==================================================================== 2 . 26.70 |==================================================================== 3 . 26.64 |==================================================================== 4 . 26.64 |==================================================================== ASTC Encoder 2.0 Preset: Exhaustive Seconds < Lower Is Better 1 . 215.92 |=================================================================== 2 . 216.19 |=================================================================== 3 . 215.24 |=================================================================== 4 . 214.69 |=================================================================== SQLite Speedtest 3.30 Timed Time - Size 1,000 Seconds < Lower Is Better 1 . 59.24 |=================================================================== 2 . 59.93 |==================================================================== 3 . 59.49 |==================================================================== 4 . 59.41 |=================================================================== NCNN 20201218 Target: CPU - Model: mobilenet ms < Lower Is Better 1 . 19.21 |=================================================================== 2 . 19.36 |==================================================================== 3 . 19.27 |==================================================================== 4 . 19.28 |==================================================================== NCNN 20201218 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 6.18 |===================================================================== 2 . 6.12 |==================================================================== 3 . 6.20 |===================================================================== 4 . 6.19 |===================================================================== NCNN 20201218 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 5.23 |===================================================================== 2 . 5.18 |==================================================================== 3 . 5.25 |===================================================================== 4 . 5.25 |===================================================================== NCNN 20201218 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 6.72 |===================================================================== 2 . 6.70 |===================================================================== 3 . 6.71 |===================================================================== 4 . 6.69 |===================================================================== NCNN 20201218 Target: CPU - Model: mnasnet ms < Lower Is Better 1 . 5.14 |===================================================================== 2 . 5.11 |==================================================================== 3 . 5.13 |===================================================================== 4 . 5.16 |===================================================================== NCNN 20201218 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 8.14 |===================================================================== 2 . 8.16 |===================================================================== 3 . 8.17 |===================================================================== 4 . 8.13 |===================================================================== NCNN 20201218 Target: CPU - Model: blazeface ms < Lower Is Better 1 . 2.38 |===================================================================== 2 . 2.38 |===================================================================== 3 . 2.31 |=================================================================== 4 . 2.33 |==================================================================== NCNN 20201218 Target: CPU - Model: googlenet ms < Lower Is Better 1 . 17.02 |==================================================================== 2 . 17.14 |==================================================================== 3 . 16.86 |=================================================================== 4 . 16.96 |=================================================================== NCNN 20201218 Target: CPU - Model: vgg16 ms < Lower Is Better 1 . 67.04 |==================================================================== 2 . 67.23 |==================================================================== 3 . 67.05 |==================================================================== 4 . 66.95 |==================================================================== NCNN 20201218 Target: CPU - Model: resnet18 ms < Lower Is Better 1 . 17.87 |==================================================================== 2 . 17.96 |==================================================================== 3 . 17.80 |=================================================================== 4 . 17.86 |==================================================================== NCNN 20201218 Target: CPU - Model: alexnet ms < Lower Is Better 1 . 14.20 |==================================================================== 2 . 14.19 |==================================================================== 3 . 14.22 |==================================================================== 4 . 14.21 |==================================================================== NCNN 20201218 Target: CPU - Model: resnet50 ms < Lower Is Better 1 . 32.59 |==================================================================== 2 . 32.61 |==================================================================== 3 . 32.76 |==================================================================== 4 . 32.58 |==================================================================== NCNN 20201218 Target: CPU - Model: yolov4-tiny ms < Lower Is Better 1 . 28.75 |=================================================================== 2 . 29.07 |==================================================================== 3 . 29.08 |==================================================================== 4 . 29.05 |==================================================================== NCNN 20201218 Target: CPU - Model: squeezenet_ssd ms < Lower Is Better 1 . 23.51 |==================================================================== 2 . 23.63 |==================================================================== 3 . 23.41 |=================================================================== 4 . 23.34 |=================================================================== NCNN 20201218 Target: CPU - Model: regnety_400m ms < Lower Is Better 1 . 18.67 |==================================================================== 2 . 18.66 |==================================================================== 3 . 18.69 |==================================================================== 4 . 18.67 |==================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU FPS > Higher Is Better 1 . 1.90 |===================================================================== 2 . 1.91 |===================================================================== 3 . 1.89 |==================================================================== 4 . 1.91 |===================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU ms < Lower Is Better 1 . 2105.37 |================================================================== 2 . 2092.82 |================================================================== 3 . 2107.64 |================================================================== 4 . 2092.01 |================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU FPS > Higher Is Better 1 . 1.88 |===================================================================== 2 . 1.88 |===================================================================== 3 . 1.88 |===================================================================== 4 . 1.88 |===================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU ms < Lower Is Better 1 . 2125.78 |================================================================== 2 . 2128.47 |================================================================== 3 . 2120.16 |================================================================== 4 . 2129.83 |================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU FPS > Higher Is Better 1 . 1.50 |==================================================================== 2 . 1.53 |===================================================================== 3 . 1.53 |===================================================================== 4 . 1.53 |===================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU ms < Lower Is Better 1 . 2640.59 |================================================================== 2 . 2586.64 |================================================================= 3 . 2584.40 |================================================================= 4 . 2579.88 |================================================================ OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU FPS > Higher Is Better 1 . 1.52 |===================================================================== 2 . 1.51 |===================================================================== 3 . 1.52 |===================================================================== 4 . 1.50 |==================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU ms < Lower Is Better 1 . 2589.43 |================================================================== 2 . 2600.09 |================================================================== 3 . 2598.96 |================================================================== 4 . 2601.17 |================================================================== OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU FPS > Higher Is Better 1 . 6575.88 |================================================================= 2 . 6385.20 |=============================================================== 3 . 6637.86 |================================================================== 4 . 6685.19 |================================================================== OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU ms < Lower Is Better 1 . 0.60 |=================================================================== 2 . 0.62 |===================================================================== 3 . 0.59 |================================================================== 4 . 0.59 |================================================================== OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU FPS > Higher Is Better 1 . 6689.73 |================================================================= 2 . 6618.49 |================================================================ 3 . 6784.44 |================================================================== 4 . 6715.20 |================================================================= OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU ms < Lower Is Better 1 . 0.59 |==================================================================== 2 . 0.60 |===================================================================== 3 . 0.58 |=================================================================== 4 . 0.59 |==================================================================== PHPBench 0.8.1 PHP Benchmark Suite Score > Higher Is Better 1 . 674200 |=================================================================== 2 . 669279 |=================================================================== 3 . 670904 |=================================================================== 4 . 668752 |================================================================== WavPack Audio Encoding 5.3 WAV To WavPack Seconds < Lower Is Better 1 . 12.62 |==================================================================== 2 . 12.60 |==================================================================== 3 . 12.51 |=================================================================== 4 . 12.46 |=================================================================== BRL-CAD 7.30.8 VGR Performance Metric VGR Performance Metric > Higher Is Better 1 . 120993 |================================================================== 2 . 119540 |================================================================== 3 . 121138 |================================================================== 4 . 122061 |=================================================================== Unpacking Firefox 84.0 Extracting: firefox-84.0.source.tar.xz Seconds < Lower Is Better 1 . 18.13 |================================================================== 2 . 18.22 |================================================================== 3 . 18.40 |=================================================================== 4 . 18.78 |====================================================================