2024 year

AMD Ryzen Threadripper PRO 5965WX 24-Cores testing with a ASUS Pro WS WRX80E-SAGE SE WIFI (1201 BIOS) and ASUS NVIDIA NV106 2GB on Ubuntu 23.10 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2402040-NE-2024YEAR116&grr&rdt.

2024 yearProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionabcdAMD Ryzen Threadripper PRO 5965WX 24-Cores @ 3.80GHz (24 Cores / 48 Threads)ASUS Pro WS WRX80E-SAGE SE WIFI (1201 BIOS)AMD Starship/Matisse8 x 16GB DDR4-2133MT/s Corsair CMK32GX4M2E3200C162048GB SOLIDIGM SSDPFKKW020X7ASUS NVIDIA NV106 2GBAMD Starship/MatisseVA24312 x Intel X550 + Intel Wi-Fi 6 AX200Ubuntu 23.106.5.0-13-generic (x86_64)GNOME Shell 45.0X Server + Waylandnouveau4.3 Mesa 23.2.1-1ubuntu3GCC 13.2.0ext41920x1080OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler Details- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v Processor Details- Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa008205Python Details- Python 3.11.6Security Details- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of safe RET no microcode + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

2024 yearlczero: BLASlczero: Eigenquicksilver: CTS2llama-cpp: llama-2-70b-chat.Q5_0.gguftensorflow: CPU - 16 - VGG-16quicksilver: CORAL2 P2cachebench: Readcachebench: Read / Modify / Writecachebench: Writetensorflow: CPU - 16 - ResNet-50llamafile: mistral-7b-instruct-v0.2.Q8_0 - CPUspeedb: Seq Fillrav1e: 1rav1e: 10deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Streamllamafile: wizardcoder-python-34b-v1.0.Q6_K - CPUpytorch: CPU - 256 - ResNet-50pytorch: CPU - 16 - ResNet-50speedb: Rand Fill Syncspeedb: Rand Fillspeedb: Update Randspeedb: Read While Writingspeedb: Read Rand Write Randspeedb: Rand Readrav1e: 5quicksilver: CORAL2 P1deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Streamtensorflow: CPU - 1 - VGG-16deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamllama-cpp: llama-2-13b.Q4_0.ggufdeepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Streamdeepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Streamrav1e: 6deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: ResNet-50, Baseline - Asynchronous Multi-Streamdeepsparse: ResNet-50, Baseline - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Streamdeepsparse: ResNet-50, Baseline - Synchronous Single-Streamdeepsparse: ResNet-50, Baseline - Synchronous Single-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Streamdeepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Streamdeepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Streamtensorflow: CPU - 16 - GoogLeNetpytorch: CPU - 1 - ResNet-50svt-av1: Preset 4 - Bosphorus 4Kcompress-lz4: 9 - Decompression Speedcompress-lz4: 9 - Compression Speedllama-cpp: llama-2-7b.Q4_0.ggufcompress-lz4: 3 - Decompression Speedcompress-lz4: 3 - Compression Speedcompress-lz4: 1 - Decompression Speedcompress-lz4: 1 - Compression Speedtensorflow: CPU - 16 - AlexNettensorflow: CPU - 1 - AlexNety-cruncher: 1Bllamafile: llava-v1.5-7b-q4 - CPUtensorflow: CPU - 1 - ResNet-50tensorflow: CPU - 1 - GoogLeNetsvt-av1: Preset 8 - Bosphorus 4Ksvt-av1: Preset 4 - Bosphorus 1080py-cruncher: 500Msvt-av1: Preset 12 - Bosphorus 4Ksvt-av1: Preset 13 - Bosphorus 4Ksvt-av1: Preset 8 - Bosphorus 1080psvt-av1: Preset 12 - Bosphorus 1080psvt-av1: Preset 13 - Bosphorus 1080pabcd173121206800001.948.512403000011543.372321130857.57756269134.68049819.8710.136206071.04410.634368.305132.518858.25417.161613.12976.13943.2531.9232.5047488558330431692700400723279111481348483.747242100005.2624189.909317.495685.1217446.631326.839435.762335.3479445.256526.911954.371618.387254.119418.47272.72392.958830.48945.997621.729653.4699224.180211.648.9109112.09145.95072012.20625.26179.8855150.042139.0436307.014679.1618151.466610.104698.91026.3518157.228639.0493306.991910.142498.5166.3619156.97011.3175757.163160.8540.686.6774840.544.2820.764595.9131.245019.5828.78100.446.2615.54517.228.859.9461.5318.8037.325190.916190.794122.948501.42543.554219146206466671.948.462402666711543.164687130069.84833869140.53099219.4510.156187761.04810.885369.772032.362158.349017.133713.238875.50673.2532.1532.1047708554997418848707040723076861474322143.791242300005.1753193.110617.5999681.0038448.907926.647835.9726333.3674448.040826.667254.536518.331754.334018.40002.70394.775930.280946.545321.474354.0612221.705311.328.9755111.28926.10101962.70475.29280.8465148.238839.3339304.771280.0470149.781810.121398.74566.4230155.483739.2555305.379510.136298.56356.4208155.54021.3252752.778460.1840.426.6694841.444.4820.954597.9131.105020.0829.36100.016.2315.49717.268.799.7461.83018.6827.349190.402192.726123.293506.596573.042225154206200001.958.482389000011543.096362130806.24568369142.43550319.6110.146047581.04410.957369.622832.421257.997817.237613.154575.98983.2531.5931.6547373557348423788704750223206701462857383.769242400005.1787192.980117.5377683.2461449.295626.674135.9278333.6358448.903126.70554.455418.358954.147418.46352.72393.834630.45146.091221.685353.7417223.051511.278.952111.58646.07471970.61065.28280.5729148.756139.1233306.502879.8946149.950710.14698.49796.4266155.40339.1181306.517510.127798.65266.4178155.61821.3025765.992360.0440.826.6784842.445.4920.744598131.45023.2829.15100.086.2315.53217.38.8516.4961.4718.4097.301192.157189.252122.95501.156580.467213151206000001.958.512384000011543.486939130851.3050769142.18885419.8110.136124281.05411.022369.5332.376258.409417.116213.20475.70733.2532.0732.2147267556675417457689600723168041464730363.891242900005.2804189.267317.5865681.5303449.160526.690235.837334.6424448.034926.543554.347118.395954.20418.44432.69394.375630.315946.133421.665553.8237222.723211.258.9586111.49656.10241962.15515.19180.2684149.268339.1902305.861480.052149.764710.106898.89126.4345155.201639.977299.829510.115198.76716.4346155.19261.3175757.271559.8240.356.6334844.544.5220.684596.7131.615019.5830.3799.96.2115.50117.258.899.7360.9518.9227.297192.683192.603122.616506.174565.906OpenBenchmarking.org

LeelaChessZero

Backend: BLAS

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.30Backend: BLASabcd50100150200250SE +/- 0.33, N = 31732192252131. (CXX) g++ options: -flto -pthread

LeelaChessZero

Backend: Eigen

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.30Backend: Eigenabcd306090120150SE +/- 2.08, N = 31211461541511. (CXX) g++ options: -flto -pthread

Quicksilver

Input: CTS2

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CTS2abcd4M8M12M16M20MSE +/- 6666.67, N = 3206800002064666720620000206000001. (CXX) g++ options: -fopenmp -O3 -march=native

Llama.cpp

Model: llama-2-70b-chat.Q5_0.gguf

OpenBenchmarking.orgTokens Per Second, More Is BetterLlama.cpp b1808Model: llama-2-70b-chat.Q5_0.ggufabcd0.43880.87761.31641.75522.194SE +/- 0.00, N = 31.941.941.951.951. (CXX) g++ options: -std=c++11 -fPIC -O3 -pthread -march=native -mtune=native -lopenblas

TensorFlow

Device: CPU - Batch Size: 16 - Model: VGG-16

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: VGG-16abcd246810SE +/- 0.03, N = 38.518.468.488.51

Quicksilver

Input: CORAL2 P2

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CORAL2 P2abcd5M10M15M20M25MSE +/- 3333.33, N = 3240300002402666723890000238400001. (CXX) g++ options: -fopenmp -O3 -march=native

CacheBench

Test: Read

OpenBenchmarking.orgMB/s, More Is BetterCacheBenchTest: Readabcd2K4K6K8K10KSE +/- 0.09, N = 311543.3711543.1611543.1011543.49MIN: 11542.37 / MAX: 11544.55MIN: 11542.65 / MAX: 11544.48MIN: 11542.7 / MAX: 11543.41MIN: 11542.8 / MAX: 11544.641. (CC) gcc options: -O3 -lrt

CacheBench

Test: Read / Modify / Write

OpenBenchmarking.orgMB/s, More Is BetterCacheBenchTest: Read / Modify / Writeabcd30K60K90K120K150KSE +/- 386.79, N = 3130857.58130069.85130806.25130851.31MIN: 112608.55 / MAX: 137126.28MIN: 101861.72 / MAX: 137133.31MIN: 112724.52 / MAX: 137125.96MIN: 112492.8 / MAX: 137124.991. (CC) gcc options: -O3 -lrt

CacheBench

Test: Write

OpenBenchmarking.orgMB/s, More Is BetterCacheBenchTest: Writeabcd15K30K45K60K75KSE +/- 3.29, N = 369134.6869140.5369142.4469142.19MIN: 68881.15 / MAX: 69208.76MIN: 68883.98 / MAX: 69225.86MIN: 68884.8 / MAX: 69218.23MIN: 68886.61 / MAX: 69217.361. (CC) gcc options: -O3 -lrt

TensorFlow

Device: CPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50abcd510152025SE +/- 0.08, N = 319.8719.4519.6119.81

Llamafile

Test: mistral-7b-instruct-v0.2.Q8_0 - Acceleration: CPU

OpenBenchmarking.orgTokens Per Second, More Is BetterLlamafile 0.6Test: mistral-7b-instruct-v0.2.Q8_0 - Acceleration: CPUabcd3691215SE +/- 0.01, N = 310.1310.1510.1410.13

Speedb

Test: Sequential Fill

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Sequential Fillabcd130K260K390K520K650KSE +/- 3239.87, N = 36206076187766047586124281. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

rav1e

Speed: 1

OpenBenchmarking.orgFrames Per Second, More Is Betterrav1e 0.7Speed: 1abcd0.23720.47440.71160.94881.186SE +/- 0.004, N = 31.0441.0481.0441.054

rav1e

Speed: 10

OpenBenchmarking.orgFrames Per Second, More Is Betterrav1e 0.7Speed: 10abcd3691215SE +/- 0.11, N = 510.6310.8910.9611.02

Neural Magic DeepSparse

Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Streamabcd80160240320400SE +/- 0.27, N = 3368.31369.77369.62369.53

Neural Magic DeepSparse

Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Streamabcd816243240SE +/- 0.05, N = 332.5232.3632.4232.38

Neural Magic DeepSparse

Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Streamabcd1326395265SE +/- 0.07, N = 358.2558.3558.0058.41

Neural Magic DeepSparse

Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Streamabcd48121620SE +/- 0.02, N = 317.1617.1317.2417.12

Neural Magic DeepSparse

Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Streamabcd3691215SE +/- 0.02, N = 313.1313.2413.1513.20

Neural Magic DeepSparse

Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Streamabcd20406080100SE +/- 0.14, N = 376.1475.5175.9975.71

Llamafile

Test: wizardcoder-python-34b-v1.0.Q6_K - Acceleration: CPU

OpenBenchmarking.orgTokens Per Second, More Is BetterLlamafile 0.6Test: wizardcoder-python-34b-v1.0.Q6_K - Acceleration: CPUabcd0.73131.46262.19392.92523.6565SE +/- 0.00, N = 33.253.253.253.25

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50abcd714212835SE +/- 0.11, N = 331.9232.1531.5932.07MIN: 30 / MAX: 32.18MIN: 30.21 / MAX: 32.69MIN: 29.73 / MAX: 32.12MIN: 30.1 / MAX: 32.3

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50abcd816243240SE +/- 0.12, N = 332.5032.1031.6532.21MIN: 30.56 / MAX: 32.75MIN: 29.1 / MAX: 32.53MIN: 29.55 / MAX: 31.86MIN: 30.29 / MAX: 32.43

Speedb

Test: Random Fill Sync

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Random Fill Syncabcd10K20K30K40K50KSE +/- 66.17, N = 3474884770847373472671. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

Speedb

Test: Random Fill

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Random Fillabcd120K240K360K480K600KSE +/- 4227.88, N = 35583305549975573485566751. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

Speedb

Test: Update Random

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Update Randomabcd90K180K270K360K450KSE +/- 4060.59, N = 34316924188484237884174571. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

Speedb

Test: Read While Writing

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Read While Writingabcd1.5M3M4.5M6M7.5MSE +/- 60887.57, N = 370040077070407704750268960071. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

Speedb

Test: Read Random Write Random

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Read Random Write Randomabcd500K1000K1500K2000K2500KSE +/- 1258.96, N = 323279112307686232067023168041. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

Speedb

Test: Random Read

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Random Readabcd30M60M90M120M150MSE +/- 81483.06, N = 31481348481474322141462857381464730361. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

rav1e

Speed: 5

OpenBenchmarking.orgFrames Per Second, More Is Betterrav1e 0.7Speed: 5abcd0.87551.7512.62653.5024.3775SE +/- 0.014, N = 33.7473.7913.7693.891

Quicksilver

Input: CORAL2 P1

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CORAL2 P1abcd5M10M15M20M25MSE +/- 11547.01, N = 3242100002423000024240000242900001. (CXX) g++ options: -fopenmp -O3 -march=native

Neural Magic DeepSparse

Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Streamabcd1.18812.37623.56434.75245.9405SE +/- 0.0173, N = 35.26245.17535.17875.2804

Neural Magic DeepSparse

Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Streamabcd4080120160200SE +/- 0.65, N = 3189.91193.11192.98189.27

Neural Magic DeepSparse

Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Streamabcd48121620SE +/- 0.02, N = 317.5017.6017.5417.59

Neural Magic DeepSparse

Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Streamabcd150300450600750SE +/- 0.83, N = 3685.12681.00683.25681.53

Neural Magic DeepSparse

Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Streamabcd100200300400500SE +/- 0.27, N = 3446.63448.91449.30449.16

Neural Magic DeepSparse

Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Streamabcd612182430SE +/- 0.05, N = 326.8426.6526.6726.69

Neural Magic DeepSparse

Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Streamabcd816243240SE +/- 0.05, N = 335.7635.9735.9335.84

Neural Magic DeepSparse

Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Streamabcd70140210280350SE +/- 0.44, N = 3335.35333.37333.64334.64

Neural Magic DeepSparse

Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Streamabcd100200300400500SE +/- 0.32, N = 3445.26448.04448.90448.03

Neural Magic DeepSparse

Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Streamabcd612182430SE +/- 0.03, N = 326.9126.6726.7126.54

Neural Magic DeepSparse

Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Streamabcd1224364860SE +/- 0.02, N = 354.3754.5454.4654.35

Neural Magic DeepSparse

Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Streamabcd510152025SE +/- 0.01, N = 318.3918.3318.3618.40

Neural Magic DeepSparse

Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streamabcd1224364860SE +/- 0.03, N = 354.1254.3354.1554.20

Neural Magic DeepSparse

Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streamabcd510152025SE +/- 0.01, N = 318.4718.4018.4618.44

TensorFlow

Device: CPU - Batch Size: 1 - Model: VGG-16

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: VGG-16abcd0.6121.2241.8362.4483.06SE +/- 0.01, N = 32.722.702.722.69

Neural Magic DeepSparse

Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Streamabcd90180270360450SE +/- 0.41, N = 3392.96394.78393.83394.38

Neural Magic DeepSparse

Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Streamabcd714212835SE +/- 0.02, N = 330.4930.2830.4530.32

Neural Magic DeepSparse

Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Streamabcd1122334455SE +/- 0.12, N = 346.0046.5546.0946.13

Neural Magic DeepSparse

Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Streamabcd510152025SE +/- 0.05, N = 321.7321.4721.6921.67

Neural Magic DeepSparse

Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Streamabcd1224364860SE +/- 0.03, N = 353.4754.0653.7453.82

Neural Magic DeepSparse

Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Streamabcd50100150200250SE +/- 0.12, N = 3224.18221.71223.05222.72

Llama.cpp

Model: llama-2-13b.Q4_0.gguf

OpenBenchmarking.orgTokens Per Second, More Is BetterLlama.cpp b1808Model: llama-2-13b.Q4_0.ggufabcd3691215SE +/- 0.06, N = 311.6411.3211.2711.251. (CXX) g++ options: -std=c++11 -fPIC -O3 -pthread -march=native -mtune=native -lopenblas

Neural Magic DeepSparse

Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Streamabcd3691215SE +/- 0.0211, N = 38.91098.97558.95208.9586

Neural Magic DeepSparse

Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Streamabcd306090120150SE +/- 0.26, N = 3112.09111.29111.59111.50

Neural Magic DeepSparse

Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Streamabcd246810SE +/- 0.0329, N = 35.95076.10106.07476.1024

Neural Magic DeepSparse

Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Streamabcd400800120016002000SE +/- 10.49, N = 32012.211962.701970.611962.16

rav1e

Speed: 6

OpenBenchmarking.orgFrames Per Second, More Is Betterrav1e 0.7Speed: 6abcd1.19072.38143.57214.76285.9535SE +/- 0.008, N = 35.2615.2925.2825.191

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Streamabcd20406080100SE +/- 0.20, N = 379.8980.8580.5780.27

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Streamabcd306090120150SE +/- 0.36, N = 3150.04148.24148.76149.27

Neural Magic DeepSparse

Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Streamabcd918273645SE +/- 0.01, N = 339.0439.3339.1239.19

Neural Magic DeepSparse

Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Streamabcd70140210280350SE +/- 0.13, N = 3307.01304.77306.50305.86

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Streamabcd20406080100SE +/- 0.02, N = 379.1680.0579.8980.05

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Streamabcd306090120150SE +/- 0.01, N = 3151.47149.78149.95149.76

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Streamabcd3691215SE +/- 0.03, N = 310.1010.1210.1510.11

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Streamabcd20406080100SE +/- 0.29, N = 398.9198.7598.5098.89

Neural Magic DeepSparse

Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Synchronous Single-Streamabcd246810SE +/- 0.0106, N = 36.35186.42306.42666.4345

Neural Magic DeepSparse

Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Synchronous Single-Streamabcd306090120150SE +/- 0.26, N = 3157.23155.48155.40155.20

Neural Magic DeepSparse

Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Streamabcd918273645SE +/- 0.09, N = 339.0539.2639.1239.98

Neural Magic DeepSparse

Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Streamabcd70140210280350SE +/- 0.76, N = 3306.99305.38306.52299.83

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Streamabcd3691215SE +/- 0.01, N = 310.1410.1410.1310.12

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Streamabcd20406080100SE +/- 0.09, N = 398.5298.5698.6598.77

Neural Magic DeepSparse

Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Streamabcd246810SE +/- 0.0037, N = 36.36196.42086.41786.4346

Neural Magic DeepSparse

Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Streamabcd306090120150SE +/- 0.08, N = 3156.97155.54155.62155.19

Neural Magic DeepSparse

Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Streamabcd0.29820.59640.89461.19281.491SE +/- 0.0024, N = 31.31751.32521.30251.3175

Neural Magic DeepSparse

Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Streamabcd170340510680850SE +/- 1.33, N = 3757.16752.78765.99757.27

TensorFlow

Device: CPU - Batch Size: 16 - Model: GoogLeNet

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetabcd1428425670SE +/- 0.36, N = 360.8560.1860.0459.82

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50abcd918273645SE +/- 0.19, N = 340.6840.4240.8240.35MIN: 37.73 / MAX: 40.91MIN: 37.5 / MAX: 41MIN: 37.73 / MAX: 41.05MIN: 37.34 / MAX: 40.65

SVT-AV1

Encoder Mode: Preset 4 - Input: Bosphorus 4K

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 4 - Input: Bosphorus 4Kabcd246810SE +/- 0.015, N = 36.6776.6696.6786.6331. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

LZ4 Compression

Compression Level: 9 - Decompression Speed

OpenBenchmarking.orgMB/s, More Is BetterLZ4 Compression 1.9.4Compression Level: 9 - Decompression Speedabcd10002000300040005000SE +/- 1.12, N = 34840.54841.44842.44844.51. (CC) gcc options: -O3

LZ4 Compression

Compression Level: 9 - Compression Speed

OpenBenchmarking.orgMB/s, More Is BetterLZ4 Compression 1.9.4Compression Level: 9 - Compression Speedabcd1020304050SE +/- 0.02, N = 344.2844.4845.4944.521. (CC) gcc options: -O3

Llama.cpp

Model: llama-2-7b.Q4_0.gguf

OpenBenchmarking.orgTokens Per Second, More Is BetterLlama.cpp b1808Model: llama-2-7b.Q4_0.ggufabcd510152025SE +/- 0.24, N = 420.7620.9520.7420.681. (CXX) g++ options: -std=c++11 -fPIC -O3 -pthread -march=native -mtune=native -lopenblas

LZ4 Compression

Compression Level: 3 - Decompression Speed

OpenBenchmarking.orgMB/s, More Is BetterLZ4 Compression 1.9.4Compression Level: 3 - Decompression Speedabcd10002000300040005000SE +/- 0.63, N = 34595.94597.94598.04596.71. (CC) gcc options: -O3

LZ4 Compression

Compression Level: 3 - Compression Speed

OpenBenchmarking.orgMB/s, More Is BetterLZ4 Compression 1.9.4Compression Level: 3 - Compression Speedabcd306090120150SE +/- 0.30, N = 3131.24131.10131.40131.611. (CC) gcc options: -O3

LZ4 Compression

Compression Level: 1 - Decompression Speed

OpenBenchmarking.orgMB/s, More Is BetterLZ4 Compression 1.9.4Compression Level: 1 - Decompression Speedabcd11002200330044005500SE +/- 1.42, N = 35019.55020.05023.25019.51. (CC) gcc options: -O3

LZ4 Compression

Compression Level: 1 - Compression Speed

OpenBenchmarking.orgMB/s, More Is BetterLZ4 Compression 1.9.4Compression Level: 1 - Compression Speedabcd2004006008001000SE +/- 0.63, N = 3828.78829.36829.15830.371. (CC) gcc options: -O3

TensorFlow

Device: CPU - Batch Size: 16 - Model: AlexNet

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: AlexNetabcd20406080100SE +/- 0.20, N = 3100.44100.01100.0899.90

TensorFlow

Device: CPU - Batch Size: 1 - Model: AlexNet

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: AlexNetabcd246810SE +/- 0.01, N = 36.266.236.236.21

Y-Cruncher

Pi Digits To Calculate: 1B

OpenBenchmarking.orgSeconds, Fewer Is BetterY-Cruncher 0.8.3Pi Digits To Calculate: 1Babcd48121620SE +/- 0.01, N = 315.5515.5015.5315.50

Llamafile

Test: llava-v1.5-7b-q4 - Acceleration: CPU

OpenBenchmarking.orgTokens Per Second, More Is BetterLlamafile 0.6Test: llava-v1.5-7b-q4 - Acceleration: CPUabcd48121620SE +/- 0.01, N = 317.2217.2617.3017.25

TensorFlow

Device: CPU - Batch Size: 1 - Model: ResNet-50

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: ResNet-50abcd246810SE +/- 0.05, N = 38.858.798.858.89

TensorFlow

Device: CPU - Batch Size: 1 - Model: GoogLeNet

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: GoogLeNetabcd48121620SE +/- 0.09, N = 39.949.7416.499.73

SVT-AV1

Encoder Mode: Preset 8 - Input: Bosphorus 4K

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 8 - Input: Bosphorus 4Kabcd1428425670SE +/- 0.07, N = 361.5361.8361.4760.951. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

SVT-AV1

Encoder Mode: Preset 4 - Input: Bosphorus 1080p

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 4 - Input: Bosphorus 1080pabcd510152025SE +/- 0.08, N = 318.8018.6818.4118.921. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Y-Cruncher

Pi Digits To Calculate: 500M

OpenBenchmarking.orgSeconds, Fewer Is BetterY-Cruncher 0.8.3Pi Digits To Calculate: 500Mabcd246810SE +/- 0.007, N = 37.3257.3497.3017.297

SVT-AV1

Encoder Mode: Preset 12 - Input: Bosphorus 4K

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 12 - Input: Bosphorus 4Kabcd4080120160200SE +/- 1.08, N = 3190.92190.40192.16192.681. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

SVT-AV1

Encoder Mode: Preset 13 - Input: Bosphorus 4K

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 13 - Input: Bosphorus 4Kabcd4080120160200SE +/- 0.80, N = 3190.79192.73189.25192.601. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

SVT-AV1

Encoder Mode: Preset 8 - Input: Bosphorus 1080p

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 8 - Input: Bosphorus 1080pabcd306090120150SE +/- 0.59, N = 3122.95123.29122.95122.621. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

SVT-AV1

Encoder Mode: Preset 12 - Input: Bosphorus 1080p

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 12 - Input: Bosphorus 1080pabcd110220330440550SE +/- 5.37, N = 5501.42506.60501.16506.171. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

SVT-AV1

Encoder Mode: Preset 13 - Input: Bosphorus 1080p

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 13 - Input: Bosphorus 1080pabcd130260390520650SE +/- 7.15, N = 3543.55573.04580.47565.911. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq


Phoronix Test Suite v10.8.5