Core i3 8100 December Intel Core i3-8100 testing with a ASRock Z370M-ITX/ac (P4.10 BIOS) and Intel 8th Gen Core Gaussian Mixture Model 3GB on Ubuntu 20.04 via the Phoronix Test Suite. 1: Processor: Intel Core i3-8100 @ 3.60GHz (4 Cores), Motherboard: ASRock Z370M-ITX/ac (P4.10 BIOS), Chipset: Intel 8th Gen Core 4-core Desktop, Memory: 8GB, Disk: 60GB DREVO X1 SSD, Graphics: Intel 8th Gen Core Gaussian Mixture Model 3GB (1100MHz), Audio: Realtek ALC892, Monitor: VA2431, Network: Intel I219-V + Intel I211 + Intel Dual Band-AC 3168NGW OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc1daily20200819-generic (x86_64) 20200818, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 2: Processor: Intel Core i3-8100 @ 3.60GHz (4 Cores), Motherboard: ASRock Z370M-ITX/ac (P4.10 BIOS), Chipset: Intel 8th Gen Core 4-core Desktop, Memory: 8GB, Disk: 60GB DREVO X1 SSD, Graphics: Intel 8th Gen Core Gaussian Mixture Model 3GB (1100MHz), Audio: Realtek ALC892, Monitor: VA2431, Network: Intel I219-V + Intel I211 + Intel Dual Band-AC 3168NGW OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc1daily20200819-generic (x86_64) 20200818, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 3: Processor: Intel Core i3-8100 @ 3.60GHz (4 Cores), Motherboard: ASRock Z370M-ITX/ac (P4.10 BIOS), Chipset: Intel 8th Gen Core 4-core Desktop, Memory: 8GB, Disk: 60GB DREVO X1 SSD, Graphics: Intel 8th Gen Core Gaussian Mixture Model 3GB (1100MHz), Audio: Realtek ALC892, Monitor: VA2431, Network: Intel I219-V + Intel I211 + Intel Dual Band-AC 3168NGW OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc1daily20200819-generic (x86_64) 20200818, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 VkFFT 1.1.1 Benchmark Score > Higher Is Better 1 . 1367 |===================================================================== 2 . 1369 |===================================================================== 3 . 1368 |===================================================================== Betsy GPU Compressor 1.1 Beta Codec: ETC1 - Quality: Highest Seconds < Lower Is Better 1 . 10.91 |=================================================================== 2 . 11.08 |==================================================================== 3 . 10.37 |================================================================ Betsy GPU Compressor 1.1 Beta Codec: ETC2 RGB - Quality: Highest Seconds < Lower Is Better 1 . 7.541 |==================================================================== VkResample 1.0 Upscale: 2x - Precision: Double ms < Lower Is Better 1 . 1013.83 |================================================================== 2 . 1010.50 |================================================================== 3 . 1011.01 |================================================================== VkResample 1.0 Upscale: 2x - Precision: Single ms < Lower Is Better 1 . 478.83 |=================================================================== 2 . 422.23 |=========================================================== 3 . 421.64 |=========================================================== VKMark 2020-05-21 Resolution: 1280 x 1024 VKMark Score > Higher Is Better 1 . 977 |====================================================================== 2 . 969 |===================================================================== 3 . 964 |===================================================================== VKMark 2020-05-21 Resolution: 1920 x 1080 VKMark Score > Higher Is Better 1 . 657 |====================================================================== 2 . 658 |====================================================================== 3 . 658 |====================================================================== CLOMP 1.2 Static OMP Speedup Speedup > Higher Is Better 1 . 1.7 |====================================================================== 2 . 1.7 |====================================================================== 3 . 1.7 |====================================================================== Timed HMMer Search 3.3.1 Pfam Database Search Seconds < Lower Is Better 1 . 126.16 |=================================================================== 2 . 126.20 |=================================================================== 3 . 126.15 |=================================================================== Timed MAFFT Alignment 7.471 Multiple Sequence Alignment - LSU RNA Seconds < Lower Is Better 1 . 11.94 |==================================================================== 2 . 11.92 |==================================================================== 3 . 12.00 |==================================================================== simdjson 0.7.1 Throughput Test: Kostya GB/s > Higher Is Better 1 . 0.57 |==================================================================== 2 . 0.58 |===================================================================== 3 . 0.58 |===================================================================== simdjson 0.7.1 Throughput Test: LargeRandom GB/s > Higher Is Better 1 . 0.35 |===================================================================== 2 . 0.35 |===================================================================== 3 . 0.35 |===================================================================== simdjson 0.7.1 Throughput Test: PartialTweets GB/s > Higher Is Better 1 . 0.52 |===================================================================== 2 . 0.52 |===================================================================== 3 . 0.52 |===================================================================== simdjson 0.7.1 Throughput Test: DistinctUserID GB/s > Higher Is Better 1 . 0.54 |===================================================================== 2 . 0.54 |===================================================================== 3 . 0.54 |===================================================================== LZ4 Compression 1.9.3 Compression Level: 1 - Compression Speed MB/s > Higher Is Better 1 . 7608.28 |================================================================== 2 . 7630.56 |================================================================== 3 . 7612.81 |================================================================== LZ4 Compression 1.9.3 Compression Level: 1 - Decompression Speed MB/s > Higher Is Better 1 . 9201.5 |=================================================================== 2 . 9212.4 |=================================================================== 3 . 9216.9 |=================================================================== LZ4 Compression 1.9.3 Compression Level: 3 - Compression Speed MB/s > Higher Is Better 1 . 40.97 |==================================================================== 2 . 41.02 |==================================================================== 3 . 40.99 |==================================================================== LZ4 Compression 1.9.3 Compression Level: 3 - Decompression Speed MB/s > Higher Is Better 1 . 9058.0 |=================================================================== 2 . 9051.3 |=================================================================== 3 . 9057.3 |=================================================================== LZ4 Compression 1.9.3 Compression Level: 9 - Compression Speed MB/s > Higher Is Better 1 . 40.08 |==================================================================== 2 . 39.76 |=================================================================== 3 . 39.98 |==================================================================== LZ4 Compression 1.9.3 Compression Level: 9 - Decompression Speed MB/s > Higher Is Better 1 . 9077.6 |=================================================================== 2 . 9053.2 |=================================================================== 3 . 9066.9 |=================================================================== oneDNN 2.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 8.47060 |================================================================== 2 . 8.47988 |================================================================== 3 . 8.46603 |================================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 9.06142 |=============================================================== 2 . 9.52884 |================================================================== 3 . 9.18889 |================================================================ oneDNN 2.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 5.58876 |================================================================== 2 . 5.58671 |================================================================== 3 . 5.57958 |================================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3.59647 |================================================================= 2 . 3.63768 |================================================================== 3 . 3.59274 |================================================================= oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 18.53 |=================================================================== 2 . 18.71 |==================================================================== 3 . 18.54 |=================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 11.52 |==================================================================== 2 . 11.50 |==================================================================== 3 . 11.47 |==================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 14.46 |==================================================================== 2 . 14.36 |==================================================================== 3 . 14.41 |==================================================================== oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 17.71 |==================================================================== 2 . 17.81 |==================================================================== 3 . 17.76 |==================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 14.55 |==================================================================== 2 . 14.54 |==================================================================== 3 . 14.54 |==================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 11.25 |==================================================================== 2 . 11.23 |==================================================================== 3 . 11.23 |==================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 6759.55 |================================================================== 2 . 6761.68 |================================================================== 3 . 6761.79 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3873.75 |================================================================== 2 . 3860.52 |================================================================== 3 . 3874.23 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 6758.25 |================================================================== 2 . 6759.25 |================================================================== 3 . 6767.39 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3855.79 |================================================================== 2 . 3858.99 |================================================================== 3 . 3852.80 |================================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 4.71186 |================================================================== 2 . 4.71931 |================================================================== 3 . 4.71943 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 6758.84 |================================================================== 2 . 6804.34 |================================================================== 3 . 6764.33 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 3856.20 |================================================================== 2 . 3860.15 |================================================================== 3 . 3855.49 |================================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 7.50114 |================================================================== 2 . 7.50639 |================================================================== 3 . 7.50482 |================================================================== rav1e 0.4 Alpha Speed: 1 Frames Per Second > Higher Is Better 1 . 0.344 |==================================================================== 2 . 0.344 |==================================================================== 3 . 0.343 |==================================================================== rav1e 0.4 Alpha Speed: 5 Frames Per Second > Higher Is Better 1 . 0.984 |==================================================================== 2 . 0.984 |==================================================================== 3 . 0.983 |==================================================================== rav1e 0.4 Alpha Speed: 6 Frames Per Second > Higher Is Better 1 . 1.308 |==================================================================== 2 . 1.308 |==================================================================== 3 . 1.308 |==================================================================== rav1e 0.4 Alpha Speed: 10 Frames Per Second > Higher Is Better 1 . 2.890 |==================================================================== 2 . 2.887 |==================================================================== 3 . 2.889 |==================================================================== Coremark 1.0 CoreMark Size 666 - Iterations Per Second Iterations/Sec > Higher Is Better 1 . 98117.51 |=============================================================== 2 . 100468.35 |================================================================ 3 . 92000.14 |=========================================================== Stockfish 12 Total Time Nodes Per Second > Higher Is Better 1 . 6456585 |================================================================= 2 . 6551982 |================================================================== 3 . 6451727 |================================================================= asmFish 2018-07-23 1024 Hash Memory, 26 Depth Nodes/second > Higher Is Better 1 . 8988021 |================================================================== 2 . 9008380 |================================================================== 3 . 8912458 |================================================================= Timed FFmpeg Compilation 4.2.2 Time To Compile Seconds < Lower Is Better 1 . 151.63 |=================================================================== 2 . 151.68 |=================================================================== 3 . 151.78 |=================================================================== Build2 0.13 Time To Compile Seconds < Lower Is Better 1 . 338.86 |=================================================================== 2 . 337.99 |=================================================================== 3 . 337.58 |=================================================================== Timed Eigen Compilation 3.3.9 Time To Compile Seconds < Lower Is Better 1 . 93.51 |==================================================================== 2 . 93.15 |==================================================================== 3 . 93.09 |==================================================================== Monkey Audio Encoding 3.99.6 WAV To APE Seconds < Lower Is Better 1 . 13.62 |==================================================================== 2 . 13.70 |==================================================================== 3 . 13.64 |==================================================================== Opus Codec Encoding 1.3.1 WAV To Opus Encode Seconds < Lower Is Better 1 . 10.65 |==================================================================== 2 . 10.65 |==================================================================== 3 . 10.65 |==================================================================== Node.js V8 Web Tooling Benchmark runs/s > Higher Is Better 1 . 10.17 |=================================================================== 2 . 10.39 |==================================================================== 3 . 10.29 |=================================================================== ASTC Encoder 2.0 Preset: Fast Seconds < Lower Is Better 1 . 5.76 |===================================================================== 2 . 5.75 |===================================================================== 3 . 5.75 |===================================================================== ASTC Encoder 2.0 Preset: Medium Seconds < Lower Is Better 1 . 14.28 |==================================================================== 2 . 14.29 |==================================================================== 3 . 14.29 |==================================================================== ASTC Encoder 2.0 Preset: Thorough Seconds < Lower Is Better 1 . 92.92 |==================================================================== 2 . 92.88 |==================================================================== 3 . 92.95 |==================================================================== ASTC Encoder 2.0 Preset: Exhaustive Seconds < Lower Is Better 1 . 738.37 |=================================================================== 2 . 737.79 |=================================================================== 3 . 738.44 |=================================================================== SQLite Speedtest 3.30 Timed Time - Size 1,000 Seconds < Lower Is Better 1 . 79.43 |==================================================================== 2 . 79.66 |==================================================================== 3 . 78.92 |=================================================================== NCNN 20201218 Target: CPU - Model: mobilenet ms < Lower Is Better 1 . 28.15 |==================================================================== 2 . 28.15 |==================================================================== 3 . 28.17 |==================================================================== NCNN 20201218 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 7.18 |===================================================================== 2 . 7.14 |===================================================================== 3 . 7.13 |===================================================================== NCNN 20201218 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 6.24 |===================================================================== 2 . 6.25 |===================================================================== 3 . 6.24 |===================================================================== NCNN 20201218 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 9.34 |===================================================================== 2 . 9.34 |===================================================================== 3 . 9.36 |===================================================================== NCNN 20201218 Target: CPU - Model: mnasnet ms < Lower Is Better 1 . 6.55 |===================================================================== 2 . 6.51 |===================================================================== 3 . 6.53 |===================================================================== NCNN 20201218 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 10.39 |==================================================================== 2 . 10.36 |==================================================================== 3 . 10.37 |==================================================================== NCNN 20201218 Target: CPU - Model: blazeface ms < Lower Is Better 1 . 2.36 |===================================================================== 2 . 2.36 |===================================================================== 3 . 2.36 |===================================================================== NCNN 20201218 Target: CPU - Model: googlenet ms < Lower Is Better 1 . 21.69 |==================================================================== 2 . 21.75 |==================================================================== 3 . 21.74 |==================================================================== NCNN 20201218 Target: CPU - Model: vgg16 ms < Lower Is Better 1 . 87.35 |==================================================================== 2 . 87.32 |==================================================================== 3 . 87.34 |==================================================================== NCNN 20201218 Target: CPU - Model: resnet18 ms < Lower Is Better 1 . 22.55 |==================================================================== 2 . 22.56 |==================================================================== 3 . 22.56 |==================================================================== NCNN 20201218 Target: CPU - Model: alexnet ms < Lower Is Better 1 . 19.32 |==================================================================== 2 . 19.34 |==================================================================== 3 . 19.33 |==================================================================== NCNN 20201218 Target: CPU - Model: resnet50 ms < Lower Is Better 1 . 47.83 |==================================================================== 2 . 47.90 |==================================================================== 3 . 47.88 |==================================================================== NCNN 20201218 Target: CPU - Model: yolov4-tiny ms < Lower Is Better 1 . 38.99 |==================================================================== 2 . 38.97 |==================================================================== 3 . 38.97 |==================================================================== NCNN 20201218 Target: CPU - Model: squeezenet_ssd ms < Lower Is Better 1 . 40.40 |==================================================================== 2 . 40.46 |==================================================================== 3 . 40.45 |==================================================================== NCNN 20201218 Target: CPU - Model: regnety_400m ms < Lower Is Better 1 . 14.55 |==================================================================== 2 . 14.50 |==================================================================== 3 . 14.55 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: mobilenet ms < Lower Is Better 1 . 28.16 |==================================================================== 2 . 28.14 |==================================================================== 3 . 28.13 |==================================================================== NCNN 20201218 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 7.16 |===================================================================== 2 . 7.15 |===================================================================== 3 . 7.14 |===================================================================== NCNN 20201218 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 6.26 |===================================================================== 2 . 6.26 |===================================================================== 3 . 6.25 |===================================================================== NCNN 20201218 Target: Vulkan GPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 9.36 |===================================================================== 2 . 9.37 |===================================================================== 3 . 9.34 |===================================================================== NCNN 20201218 Target: Vulkan GPU - Model: mnasnet ms < Lower Is Better 1 . 6.54 |===================================================================== 2 . 6.54 |===================================================================== 3 . 6.53 |===================================================================== NCNN 20201218 Target: Vulkan GPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 10.37 |==================================================================== 2 . 10.37 |==================================================================== 3 . 10.39 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: blazeface ms < Lower Is Better 1 . 2.36 |===================================================================== 2 . 2.36 |===================================================================== 3 . 2.36 |===================================================================== NCNN 20201218 Target: Vulkan GPU - Model: googlenet ms < Lower Is Better 1 . 21.68 |==================================================================== 2 . 21.72 |==================================================================== 3 . 21.69 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: vgg16 ms < Lower Is Better 1 . 87.28 |==================================================================== 2 . 87.24 |==================================================================== 3 . 87.23 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: resnet18 ms < Lower Is Better 1 . 22.52 |==================================================================== 2 . 22.52 |==================================================================== 3 . 22.53 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: alexnet ms < Lower Is Better 1 . 19.28 |==================================================================== 2 . 19.31 |==================================================================== 3 . 19.30 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: resnet50 ms < Lower Is Better 1 . 47.84 |==================================================================== 2 . 47.79 |==================================================================== 3 . 47.93 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: yolov4-tiny ms < Lower Is Better 1 . 38.97 |==================================================================== 2 . 38.96 |==================================================================== 3 . 38.94 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: squeezenet_ssd ms < Lower Is Better 1 . 40.52 |==================================================================== 2 . 40.46 |==================================================================== 3 . 40.44 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: regnety_400m ms < Lower Is Better 1 . 14.55 |==================================================================== 2 . 14.53 |==================================================================== 3 . 14.56 |==================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU FPS > Higher Is Better 1 . 1.16 |==================================================================== 2 . 1.17 |===================================================================== 3 . 1.16 |==================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU ms < Lower Is Better 1 . 3426.15 |================================================================== 2 . 3422.79 |================================================================== 3 . 3426.05 |================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU FPS > Higher Is Better 1 . 1.15 |===================================================================== 2 . 1.15 |===================================================================== 3 . 1.15 |===================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU ms < Lower Is Better 1 . 3436.65 |================================================================== 2 . 3436.56 |================================================================== 3 . 3437.37 |================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU FPS > Higher Is Better 1 . 0.71 |===================================================================== 2 . 0.71 |===================================================================== 3 . 0.71 |===================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU ms < Lower Is Better 1 . 5641.28 |================================================================== 2 . 5638.32 |================================================================== 3 . 5642.32 |================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU FPS > Higher Is Better 1 . 0.70 |==================================================================== 2 . 0.71 |===================================================================== 3 . 0.70 |==================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU ms < Lower Is Better 1 . 5648.20 |================================================================== 2 . 5638.59 |================================================================== 3 . 5650.56 |================================================================== OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU FPS > Higher Is Better 1 . 2549.49 |================================================================== 2 . 2516.51 |================================================================= 3 . 2562.17 |================================================================== OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU ms < Lower Is Better 1 . 1.45 |===================================================================== 2 . 1.45 |===================================================================== 3 . 1.46 |===================================================================== OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU FPS > Higher Is Better 1 . 2543.51 |================================================================== 2 . 2551.41 |================================================================== 3 . 2552.27 |================================================================== OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU ms < Lower Is Better 1 . 1.46 |===================================================================== 2 . 1.45 |===================================================================== 3 . 1.45 |===================================================================== WavPack Audio Encoding 5.3 WAV To WavPack Seconds < Lower Is Better 1 . 17.97 |==================================================================== 2 . 17.94 |==================================================================== 3 . 17.95 |==================================================================== Unpacking Firefox 84.0 Extracting: firefox-84.0.source.tar.xz Seconds < Lower Is Better 1 . 23.26 |=================================================================== 2 . 23.39 |=================================================================== 3 . 23.67 |==================================================================== BRL-CAD 7.30.8 VGR Performance Metric VGR Performance Metric > Higher Is Better 1 . 36580 |==================================================================== 2 . 36247 |=================================================================== 3 . 36569 |====================================================================