Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2309136-PTS-LINUX66R72
Linux 6.6 Intel Core i9 13900K Raptor Lake
Intel Core i9-13900K Linux 6.4 / 6.5 / 6.6 Git benchmarks by Michael Larabel
,,"Linux 6.4.14","Linux 6.5.1","Linux 6.6-rc1"
Processor,,Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads),Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads),Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads)
Motherboard,,ASUS PRIME Z790-P WIFI (0812 BIOS),ASUS PRIME Z790-P WIFI (0812 BIOS),ASUS PRIME Z790-P WIFI (0812 BIOS)
Chipset,,Intel Device 7a27,Intel Device 7a27,Intel Device 7a27
Memory,,32GB,32GB,32GB
Disk,,1000GB Western Digital WDS100T1X0E-00AFY0,1000GB Western Digital WDS100T1X0E-00AFY0,1000GB Western Digital WDS100T1X0E-00AFY0
Graphics,,AMD Radeon RX 7700S/7600S/7600M XT 8GB (1940/1124MHz),AMD Radeon RX 7700S/7600S/7600M XT 8GB (1940/1124MHz),AMD Radeon RX 7700S/7600S/7600M XT 8GB (1940/1124MHz)
Audio,,Realtek ALC897,Realtek ALC897,Realtek ALC897
Monitor,,ASUS VP28U,ASUS VP28U,ASUS VP28U
OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04
Kernel,,6.4.14-060414-generic (x86_64),6.5.1-060501-generic (x86_64),6.6.0-060600rc1-generic (x86_64)
Desktop,,GNOME Shell 42.9,GNOME Shell 42.9,GNOME Shell 42.9
Display Server,,X Server 1.21.1.4 + Wayland,X Server 1.21.1.4 + Wayland,X Server 1.21.1.4 + Wayland
OpenGL,,4.6 Mesa 23.3~git2308070600.777734~oibaf~j (git-7777349 2023-08-07 jammy-oibaf-ppa) (LLVM 15.0.7 DRM 3.52),4.6 Mesa 23.3~git2308070600.777734~oibaf~j (git-7777349 2023-08-07 jammy-oibaf-ppa) (LLVM 15.0.7 DRM 3.54),4.6 Mesa 23.3~git2308070600.777734~oibaf~j (git-7777349 2023-08-07 jammy-oibaf-ppa) (LLVM 15.0.7 DRM 3.54)
OpenCL,,OpenCL 1.1 Mesa 23.3~git2308020600.4de7e0~oibaf~j (git-4de7e00 2023-08-02 jammy-oibaf-ppa) + OpenCL 3.0,OpenCL 1.1 Mesa 23.3~git2308020600.4de7e0~oibaf~j (git-4de7e00 2023-08-02 jammy-oibaf-ppa) + OpenCL 3.0,OpenCL 1.1 Mesa 23.3~git2308020600.4de7e0~oibaf~j (git-4de7e00 2023-08-02 jammy-oibaf-ppa) + OpenCL 3.0
Vulkan,,1.3.258,1.3.258,1.3.258
Compiler,,GCC 11.4.0 + Clang 16.0.6 + LLVM 16.0.6,GCC 11.4.0 + Clang 16.0.6 + LLVM 16.0.6,GCC 11.4.0 + Clang 16.0.6 + LLVM 16.0.6
File-System,,ext4,ext4,ext4
Screen Resolution,,3840x2160,3840x2160,3840x2160
,,"Linux 6.4.14","Linux 6.5.1","Linux 6.6-rc1"
"OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,5.21,4.56,5.22
"OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,3.34,2.99,3.33
"OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,3.30,2.95,3.32
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,363.88,317.31,359.56
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,16.54,14.82,16.84
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,872.96,781.75,854.42
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,425.19,385.73,431.89
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,59.60,54.23,60.06
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,1490.03,1335.97,1497.35
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,690.48,630.92,666.94
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,13875.03,12689.87,14053.46
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,15213.23,13817.99,15347.17
"AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K (FPS)",HIB,96.89,88.81,82.99
"AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K (FPS)",HIB,90.94,83.39,79.37
"AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K (FPS)",HIB,101.78,103.95,101.69
"AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K (FPS)",HIB,115.95,105.82,99.98
"AOM AV1 - Encoder Mode: Speed 11 Realtime - Input: Bosphorus 4K (FPS)",HIB,111.35,108.21,103.07
"AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p (FPS)",HIB,229.52,242.99,247.18
"AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p (FPS)",HIB,267.56,263.42,283.47
"AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p (FPS)",HIB,282.35,290.39,296.54
"AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p (FPS)",HIB,295.13,296.42,285.01
"AOM AV1 - Encoder Mode: Speed 11 Realtime - Input: Bosphorus 1080p (FPS)",HIB,295.92,305.18,300.50
"Kvazaar - Video Input: Bosphorus 4K - Video Preset: Medium (FPS)",HIB,18.31,16.34,17.96
"Kvazaar - Video Input: Bosphorus 1080p - Video Preset: Medium (FPS)",HIB,70.72,63.70,66.27
"Kvazaar - Video Input: Bosphorus 4K - Video Preset: Very Fast (FPS)",HIB,40.58,36.23,40.48
"Kvazaar - Video Input: Bosphorus 4K - Video Preset: Super Fast (FPS)",HIB,51.10,45.91,50.28
"Kvazaar - Video Input: Bosphorus 4K - Video Preset: Ultra Fast (FPS)",HIB,69.36,62.04,70.21
"Kvazaar - Video Input: Bosphorus 1080p - Video Preset: Very Fast (FPS)",HIB,155.33,139.82,139.94
"Kvazaar - Video Input: Bosphorus 1080p - Video Preset: Super Fast (FPS)",HIB,209.30,186.74,194.68
"Kvazaar - Video Input: Bosphorus 1080p - Video Preset: Ultra Fast (FPS)",HIB,260.80,246.33,246.36
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,5.118,4.570,5.079
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,73.421,63.283,74.361
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,176.666,171.524,178.672
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,186.331,180.877,179.803
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,14.948,13.277,14.415
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,132.886,128.519,132.919
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,518.133,509.356,511.298
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,582.209,564.988,582.351
"SVT-HEVC - Tuning: 1 - Input: Bosphorus 4K (FPS)",HIB,5.41,4.91,5.44
"SVT-HEVC - Tuning: 7 - Input: Bosphorus 4K (FPS)",HIB,96.82,89.44,96.09
"SVT-HEVC - Tuning: 10 - Input: Bosphorus 4K (FPS)",HIB,195.12,127.68,123.90
"SVT-HEVC - Tuning: 1 - Input: Bosphorus 1080p (FPS)",HIB,21.09,19.09,21.37
"SVT-HEVC - Tuning: 7 - Input: Bosphorus 1080p (FPS)",HIB,284.70,284.51,301.06
"SVT-HEVC - Tuning: 10 - Input: Bosphorus 1080p (FPS)",HIB,635.86,583.51,669.40
"SVT-VP9 - Tuning: VMAF Optimized - Input: Bosphorus 4K (FPS)",HIB,135.00,96.35,105.29
"SVT-VP9 - Tuning: VMAF Optimized - Input: Bosphorus 1080p (FPS)",HIB,457.51,456.32,486.87
"SVT-VP9 - Tuning: PSNR/SSIM Optimized - Input: Bosphorus 4K (FPS)",HIB,149.07,100.67,106.17
"SVT-VP9 - Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p (FPS)",HIB,453.70,460.39,494.53
"SVT-VP9 - Tuning: Visual Quality Optimized - Input: Bosphorus 4K (FPS)",HIB,120.36,99.15,102.07
"SVT-VP9 - Tuning: Visual Quality Optimized - Input: Bosphorus 1080p (FPS)",HIB,398.57,368.11,400.14
"uvg266 - Video Input: Bosphorus 4K - Video Preset: Medium (FPS)",HIB,13.18,11.93,13.28
"uvg266 - Video Input: Bosphorus 1080p - Video Preset: Medium (FPS)",HIB,51.37,48.34,50.42
"uvg266 - Video Input: Bosphorus 4K - Video Preset: Very Fast (FPS)",HIB,37.05,32.96,35.89
"uvg266 - Video Input: Bosphorus 4K - Video Preset: Super Fast (FPS)",HIB,39.78,35.72,38.69
"uvg266 - Video Input: Bosphorus 4K - Video Preset: Ultra Fast (FPS)",HIB,48.98,43.40,47.18
"uvg266 - Video Input: Bosphorus 1080p - Video Preset: Very Fast (FPS)",HIB,151.72,123.50,138.54
"uvg266 - Video Input: Bosphorus 1080p - Video Preset: Super Fast (FPS)",HIB,150.17,141.05,152.80
"uvg266 - Video Input: Bosphorus 1080p - Video Preset: Ultra Fast (FPS)",HIB,188.74,162.10,173.19
"VVenC - Video Input: Bosphorus 4K - Video Preset: Fast (FPS)",HIB,7.594,6.958,7.607
"VVenC - Video Input: Bosphorus 4K - Video Preset: Faster (FPS)",HIB,15.403,13.255,14.842
"VVenC - Video Input: Bosphorus 1080p - Video Preset: Fast (FPS)",HIB,21.386,18.823,21.025
"VVenC - Video Input: Bosphorus 1080p - Video Preset: Faster (FPS)",HIB,43.063,37.673,40.929
"x265 - Video Input: Bosphorus 4K (FPS)",HIB,32.24,29.39,32.45
"x265 - Video Input: Bosphorus 1080p (FPS)",HIB,86.16,84.27,85.24
"simdjson - Throughput Test: Kostya (GB/s)",HIB,5.37,5.31,5.31
"simdjson - Throughput Test: TopTweet (GB/s)",HIB,7.87,7.88,7.88
"simdjson - Throughput Test: LargeRandom (GB/s)",HIB,1.91,1.91,1.91
"simdjson - Throughput Test: PartialTweets (GB/s)",HIB,6.84,6.84,6.83
"simdjson - Throughput Test: DistinctUserID (GB/s)",HIB,8.1,8.1,8.09
"Selenium - Benchmark: Octane - Browser: Firefox (Geometric Mean)",HIB,57866,55011,58047
"Selenium - Benchmark: Octane - Browser: Google Chrome (Geometric Mean)",HIB,113361,108124,114315
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,15.5909,14.3944,15.7495
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,418.8814,378.5261,420.3307
"Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,177.5103,155.0658,178.5691
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,54.6711,48.8254,55.5626
"Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,217.0101,197.8312,218.5022
"Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,1380.0453,1248.9354,1390.0340
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,98.0197,87.9345,98.0054
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,18.9839,16.8019,18.7263
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,218.5281,197.8313,218.6929
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,96.3272,86.9965,96.4148
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,131.0559,117.4405,130.7895
"Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,20.8822,17.8768,21.0894
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,211.9237,191.4416,213.6458
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,64.9142,57.6708,65.2007
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,15.5228,14.2462,15.6165
"libjpeg-turbo tjbench - Test: Decompression Throughput (Megapixels/sec)",HIB,308.833302,309.220574,309.547454
"7-Zip Compression - Test: Compression Rating (MIPS)",HIB,181036,161199,179477
"7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,136248,121434,135435
"WebP Image Encode - Encode Settings: Default (MP/s)",HIB,25.65,25.80,25.83
"WebP Image Encode - Encode Settings: Quality 100 (MP/s)",HIB,16.59,16.60,16.58
"WebP Image Encode - Encode Settings: Quality 100, Lossless (MP/s)",HIB,2.35,2.34,2.34
"WebP Image Encode - Encode Settings: Quality 100, Highest Compression (MP/s)",HIB,5.16,5.17,5.16
"WebP Image Encode - Encode Settings: Quality 100, Lossless, Highest Compression (MP/s)",HIB,0.93,0.88,0.93
"ASTC Encoder - Preset: Fast (MT/s)",HIB,336.8333,339.5478,337.7643
"ASTC Encoder - Preset: Medium (MT/s)",HIB,120.0901,122.1162,120.4938
"ASTC Encoder - Preset: Thorough (MT/s)",HIB,14.4892,15.0178,14.8217
"ASTC Encoder - Preset: Exhaustive (MT/s)",HIB,1.3386,1.2359,1.3600
"John The Ripper - Test: bcrypt (Real C/S)",HIB,39253,31839,38225
"John The Ripper - Test: WPA PSK (Real C/S)",HIB,58478,50665,58861
"John The Ripper - Test: Blowfish (Real C/S)",HIB,39743,31828,37496
"John The Ripper - Test: HMAC-SHA512 (Real C/S)",HIB,69673333,57671917,63281250
"John The Ripper - Test: MD5 (Real C/S)",HIB,1838000,1598714,1648967
"Redis - Test: GET - Parallel Connections: 50 (Reqs/sec)",HIB,6372860.8,5409166.1,5432508.7
"Redis - Test: SET - Parallel Connections: 50 (Reqs/sec)",HIB,4341185.0,4091086.13,4207756.96
"Redis - Test: LPOP - Parallel Connections: 50 (Reqs/sec)",HIB,6527019.8,3608927.58,3574286.00
"Redis - Test: SADD - Parallel Connections: 50 (Reqs/sec)",HIB,4825673.1,4320145.38,4814183.7
"Redis - Test: LPUSH - Parallel Connections: 50 (Reqs/sec)",HIB,3673940.00,3712129.75,3842480.21
"nginx - Connections: 100 (Reqs/sec)",HIB,194643.92,173181.72,191219.52
"nginx - Connections: 200 (Reqs/sec)",HIB,195256.70,176902.95,192417.90
"nginx - Connections: 500 (Reqs/sec)",HIB,191291.62,171679.65,191326.52
"nginx - Connections: 1000 (Reqs/sec)",HIB,178781.88,159455.41,181548.67
"Selenium - Benchmark: Speedometer - Browser: Firefox (Runs/min)",HIB,399,400,398
"Selenium - Benchmark: Speedometer - Browser: Google Chrome (Runs/min)",HIB,441,440,437
"PHPBench - PHP Benchmark Suite (Score)",HIB,1608855,1473031,1641215
"Selenium - Benchmark: Jetstream 2 - Browser: Firefox (Score)",HIB,241.302,233.767,243.408
"Selenium - Benchmark: Jetstream 2 - Browser: Google Chrome (Score)",HIB,382.751,367.902,377.057
"PyBench - Total For Average Test Times (Milliseconds)",LIB,456,454,453
"PyPerformance - Benchmark: go (Milliseconds)",LIB,108,117,108
"PyPerformance - Benchmark: 2to3 (Milliseconds)",LIB,154,154,159
"PyPerformance - Benchmark: chaos (Milliseconds)",LIB,44.4,49.7,44.5
"PyPerformance - Benchmark: float (Milliseconds)",LIB,46.3,50.7,45.5
"PyPerformance - Benchmark: nbody (Milliseconds)",LIB,57.4,64.3,57.3
"PyPerformance - Benchmark: pathlib (Milliseconds)",LIB,8.74,8.78,8.78
"PyPerformance - Benchmark: raytrace (Milliseconds)",LIB,203,227,202
"PyPerformance - Benchmark: json_loads (Milliseconds)",LIB,11.7,11.8,11.7
"PyPerformance - Benchmark: crypto_pyaes (Milliseconds)",LIB,49.3,53.8,49.2
"PyPerformance - Benchmark: regex_compile (Milliseconds)",LIB,80.3,85.4,80.4
"PyPerformance - Benchmark: python_startup (Milliseconds)",LIB,8.99,9.12,13.2
"PyPerformance - Benchmark: django_template (Milliseconds)",LIB,20.9,23.3,21.0
"PyPerformance - Benchmark: pickle_pure_python (Milliseconds)",LIB,189,207,190
"OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,1530.67,1732.57,1527.69
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,2356.13,2638.93,2354.17
"OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,2376.85,2659.28,2358.66
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,21.96,25.18,22.17
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,480.58,537.88,472.84
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,9.15,10.23,9.22
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,56.34,62.12,55.47
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,134.10,147.34,133.02
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,16.10,17.95,16.02
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,11.57,12.66,11.91
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,1.72,1.88,1.70
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,1.57,1.73,1.56
"Selenium - Benchmark: Kraken - Browser: Firefox (ms)",LIB,513.9,505.1,508.1
"Selenium - Benchmark: Kraken - Browser: Google Chrome (ms)",LIB,351.0,355.3,354.2
"Selenium - Benchmark: WASM imageConvolute - Browser: Firefox (ms)",LIB,14.9,14.9,14.9
"Selenium - Benchmark: WASM collisionDetection - Browser: Firefox (ms)",LIB,222.0,222.3,222.6
"Selenium - Benchmark: WASM imageConvolute - Browser: Google Chrome (ms)",LIB,14.61,14.63,14.60
"Selenium - Benchmark: WASM collisionDetection - Browser: Google Chrome (ms)",LIB,179.61,176.38,181.58
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,763.8168,824.9693,759.0957
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,28.6116,31.6750,28.5176
"Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,67.5296,77.3031,67.1375
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,218.6991,244.9493,215.1177
"Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,55.2824,60.6204,54.8862
"Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,8.6853,9.5956,8.6225
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,122.3752,135.8479,122.3300
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,627.0945,706.2146,635.3426
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,54.8649,60.6321,54.8408
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,124.2028,137.6621,124.2673
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,91.4992,102.0895,91.6955
"Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,571.4478,664.9009,564.1260
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,56.5384,62.5842,56.0735
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,184.5694,207.7868,183.5038
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,769.8651,828.7640,765.2426
"Selenium - Benchmark: PSPDFKit WASM - Browser: Firefox (Score)",LIB,2161,2158,2164
"Selenium - Benchmark: PSPDFKit WASM - Browser: Google Chrome (Score)",LIB,2354,2357,2355
"WireGuard + Linux Networking Stack Stress Test - (sec)",LIB,95.211,95.084,112.562
"libavif avifenc - Encoder Speed: 0 (sec)",LIB,73.138,78.028,73.428
"libavif avifenc - Encoder Speed: 2 (sec)",LIB,35.381,38.534,35.582
"libavif avifenc - Encoder Speed: 6 (sec)",LIB,3.768,3.768,3.617
"libavif avifenc - Encoder Speed: 6, Lossless (sec)",LIB,5.378,6.081,5.336
"libavif avifenc - Encoder Speed: 10, Lossless (sec)",LIB,3.534,3.773,3.559
"Timed Godot Game Engine Compilation - Time To Compile (sec)",LIB,156.158,173.265,156.878
"Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,44.032,48.127,44.009
"Timed LLVM Compilation - Build System: Ninja (sec)",LIB,309.276,350.227,310.104
"FLAC Audio Encoding - WAV To FLAC (sec)",LIB,11.082,11.156,11.043
"SQLite Speedtest - Timed Time - Size 1,000 (sec)",LIB,31.268,31.137,30.835
"Darktable - Test: Boat - Acceleration: CPU-only (sec)",LIB,2.076,1.944,2.057
"Darktable - Test: Masskrug - Acceleration: CPU-only (sec)",LIB,2.084,2.002,2.070
"Darktable - Test: Server Rack - Acceleration: CPU-only (sec)",LIB,0.102,0.094,0.106
"Darktable - Test: Server Room - Acceleration: CPU-only (sec)",LIB,1.548,1.535,1.558
"GIMP - Test: resize (sec)",LIB,12.937,12.839,13.189
"GIMP - Test: rotate (sec)",LIB,9.806,9.467,9.696
"GIMP - Test: auto-levels (sec)",LIB,10.561,10.274,10.607
"GIMP - Test: unsharp-mask (sec)",LIB,12.248,11.906,12.215
"OCRMyPDF - Processing 60 Page PDF Document (sec)",LIB,9.244,9.652,9.179
"RawTherapee - Total Benchmark Time (sec)",LIB,32.811,33.495,33.657
"Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,59.09,64.84,58.80
"Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,81.66,89.90,81.12
"Git - Time To Complete Common Git Commands (sec)",LIB,32.053,32.062,31.986