fgds Intel Core i5-12600K testing with a ASUS PRIME Z690-P WIFI D4 (0605 BIOS) and ASUS Intel ADL-S GT1 15GB on Ubuntu 22.04 via the Phoronix Test Suite. A: Processor: Intel Core i5-12600K @ 6.30GHz (10 Cores / 16 Threads), Motherboard: ASUS PRIME Z690-P WIFI D4 (0605 BIOS), Chipset: Intel Device 7aa7, Memory: 16GB, Disk: 1000GB Western Digital WDS100T1X0E-00AFY0, Graphics: ASUS Intel ADL-S GT1 15GB (1450MHz), Audio: Realtek ALC897, Monitor: ASUS MG28U, Network: Realtek RTL8125 2.5GbE + Intel Device 7af0 OS: Ubuntu 22.04, Kernel: 5.19.0-051900rc6daily20220716-generic (x86_64), Desktop: GNOME Shell 42.1, Display Server: X Server 1.21.1.3 + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.2.204, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 3840x2160 B: Processor: Intel Core i5-12600K @ 6.30GHz (10 Cores / 16 Threads), Motherboard: ASUS PRIME Z690-P WIFI D4 (0605 BIOS), Chipset: Intel Device 7aa7, Memory: 16GB, Disk: 1000GB Western Digital WDS100T1X0E-00AFY0, Graphics: ASUS Intel ADL-S GT1 15GB (1450MHz), Audio: Realtek ALC897, Monitor: ASUS MG28U, Network: Realtek RTL8125 2.5GbE + Intel Device 7af0 OS: Ubuntu 22.04, Kernel: 5.19.0-051900rc6daily20220716-generic (x86_64), Desktop: GNOME Shell 42.1, Display Server: X Server 1.21.1.3 + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.2.204, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 3840x2160 C: Processor: Intel Core i5-12600K @ 6.30GHz (10 Cores / 16 Threads), Motherboard: ASUS PRIME Z690-P WIFI D4 (0605 BIOS), Chipset: Intel Device 7aa7, Memory: 16GB, Disk: 1000GB Western Digital WDS100T1X0E-00AFY0, Graphics: ASUS Intel ADL-S GT1 15GB (1450MHz), Audio: Realtek ALC897, Monitor: ASUS MG28U, Network: Realtek RTL8125 2.5GbE + Intel Device 7af0 OS: Ubuntu 22.04, Kernel: 5.19.0-051900rc6daily20220716-generic (x86_64), Desktop: GNOME Shell 42.1, Display Server: X Server 1.21.1.3 + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.2.204, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 3840x2160 SMHasher 2022-08-22 Hash: wyhash MiB/sec > Higher Is Better A . 29154.23 |================================================================= B . 29184.54 |================================================================= C . 29220.87 |================================================================= SMHasher 2022-08-22 Hash: wyhash cycles/hash < Lower Is Better A . 18.55 |==================================================================== B . 18.55 |==================================================================== C . 18.55 |==================================================================== SMHasher 2022-08-22 Hash: SHA3-256 MiB/sec > Higher Is Better A . 244.07 |=================================================================== B . 245.01 |=================================================================== C . 245.08 |=================================================================== SMHasher 2022-08-22 Hash: SHA3-256 cycles/hash < Lower Is Better A . 1599.28 |================================================================== B . 1595.18 |================================================================== C . 1596.08 |================================================================== SMHasher 2022-08-22 Hash: Spooky32 MiB/sec > Higher Is Better A . 17969.01 |================================================================= B . 17981.71 |================================================================= C . 17979.56 |================================================================= SMHasher 2022-08-22 Hash: Spooky32 cycles/hash < Lower Is Better A . 33.85 |==================================================================== B . 33.78 |==================================================================== C . 33.82 |==================================================================== SMHasher 2022-08-22 Hash: fasthash32 MiB/sec > Higher Is Better A . 7604.24 |================================================================== B . 7603.85 |================================================================== C . 7604.38 |================================================================== SMHasher 2022-08-22 Hash: fasthash32 cycles/hash < Lower Is Better A . 28.19 |==================================================================== B . 28.19 |==================================================================== C . 28.19 |==================================================================== SMHasher 2022-08-22 Hash: FarmHash128 MiB/sec > Higher Is Better A . 19170.14 |================================================================= B . 19201.69 |================================================================= C . 19197.59 |================================================================= SMHasher 2022-08-22 Hash: FarmHash128 cycles/hash < Lower Is Better A . 53.74 |==================================================================== B . 53.74 |==================================================================== C . 53.74 |==================================================================== SMHasher 2022-08-22 Hash: t1ha2_atonce MiB/sec > Higher Is Better A . 21936.55 |================================================================= B . 21929.77 |================================================================= C . 21936.73 |================================================================= SMHasher 2022-08-22 Hash: t1ha2_atonce cycles/hash < Lower Is Better A . 25.30 |==================================================================== B . 25.30 |==================================================================== C . 25.30 |==================================================================== SMHasher 2022-08-22 Hash: FarmHash32 x86_64 AVX MiB/sec > Higher Is Better A . 26888.83 |================================================================= B . 26897.98 |================================================================= C . 26713.68 |================================================================= SMHasher 2022-08-22 Hash: FarmHash32 x86_64 AVX cycles/hash < Lower Is Better A . 32.83 |==================================================================== B . 32.61 |==================================================================== C . 32.82 |==================================================================== SMHasher 2022-08-22 Hash: t1ha0_aes_avx2 x86_64 MiB/sec > Higher Is Better A . 72005.91 |================================================================= B . 72004.31 |================================================================= C . 71999.16 |================================================================= SMHasher 2022-08-22 Hash: t1ha0_aes_avx2 x86_64 cycles/hash < Lower Is Better A . 25.07 |==================================================================== B . 25.07 |==================================================================== C . 25.07 |==================================================================== SMHasher 2022-08-22 Hash: MeowHash x86_64 AES-NI MiB/sec > Higher Is Better A . 49353.69 |================================================================= B . 48796.81 |================================================================ C . 49349.97 |================================================================= SMHasher 2022-08-22 Hash: MeowHash x86_64 AES-NI cycles/hash < Lower Is Better A . 54.28 |==================================================================== B . 54.33 |==================================================================== C . 54.32 |==================================================================== OpenRadioss 2022.10.13 Model: Bumper Beam Seconds < Lower Is Better A . 247.09 |=================================================================== B . 229.96 |============================================================== C . 228.07 |============================================================== OpenRadioss 2022.10.13 Model: Cell Phone Drop Test Seconds < Lower Is Better A . 176.92 |=================================================================== B . 167.33 |=============================================================== C . 164.08 |============================================================== OpenRadioss 2022.10.13 Model: Bird Strike on Windshield Seconds < Lower Is Better A . 385.82 |=================================================================== B . 372.34 |================================================================= C . 375.12 |================================================================= OpenRadioss 2022.10.13 Model: Rubber O-Ring Seal Installation Seconds < Lower Is Better A . 288.06 |=================================================================== B . 285.73 |================================================================== C . 284.58 |================================================================== OpenRadioss 2022.10.13 Model: INIVOL and Fluid Structure Interaction Drop Container Seconds < Lower Is Better A . 801.99 |=================================================================== B . 783.86 |================================================================= C . 785.09 |================================================================== QuadRay 2022.05.25 Scene: 1 - Resolution: 4K FPS > Higher Is Better A . 4.97 |===================================================================== B . 4.98 |===================================================================== C . 4.97 |===================================================================== QuadRay 2022.05.25 Scene: 2 - Resolution: 4K FPS > Higher Is Better A . 1.42 |===================================================================== B . 1.42 |===================================================================== C . 1.42 |===================================================================== QuadRay 2022.05.25 Scene: 3 - Resolution: 4K FPS > Higher Is Better A . 1.18 |===================================================================== B . 1.18 |===================================================================== C . 1.18 |===================================================================== QuadRay 2022.05.25 Scene: 5 - Resolution: 4K FPS > Higher Is Better A . 0.32 |===================================================================== B . 0.32 |===================================================================== C . 0.32 |===================================================================== QuadRay 2022.05.25 Scene: 1 - Resolution: 1080p FPS > Higher Is Better A . 19.50 |==================================================================== B . 19.57 |==================================================================== C . 19.49 |==================================================================== QuadRay 2022.05.25 Scene: 2 - Resolution: 1080p FPS > Higher Is Better A . 5.60 |===================================================================== B . 5.61 |===================================================================== C . 5.61 |===================================================================== QuadRay 2022.05.25 Scene: 3 - Resolution: 1080p FPS > Higher Is Better A . 4.59 |===================================================================== B . 4.60 |===================================================================== C . 4.60 |===================================================================== QuadRay 2022.05.25 Scene: 5 - Resolution: 1080p FPS > Higher Is Better A . 1.25 |================================================================= B . 1.30 |==================================================================== C . 1.32 |===================================================================== AOM AV1 3.5 Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K Frames Per Second > Higher Is Better A . 0.24 |===================================================================== B . 0.24 |===================================================================== C . 0.24 |===================================================================== AOM AV1 3.5 Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K Frames Per Second > Higher Is Better A . 7.14 |==================================================================== B . 7.17 |===================================================================== C . 7.21 |===================================================================== AOM AV1 3.5 Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K Frames Per Second > Higher Is Better A . 32.46 |=================================================================== B . 33.16 |==================================================================== C . 32.90 |=================================================================== AOM AV1 3.5 Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K Frames Per Second > Higher Is Better A . 12.81 |=================================================================== B . 12.87 |==================================================================== C . 12.94 |==================================================================== AOM AV1 3.5 Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K Frames Per Second > Higher Is Better A . 47.81 |================================================================== B . 49.44 |==================================================================== C . 49.03 |=================================================================== AOM AV1 3.5 Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K Frames Per Second > Higher Is Better A . 66.80 |=================================================================== B . 67.47 |=================================================================== C . 68.15 |==================================================================== AOM AV1 3.5 Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K Frames Per Second > Higher Is Better A . 67.80 |=================================================================== B . 68.67 |==================================================================== C . 68.96 |==================================================================== AOM AV1 3.5 Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p Frames Per Second > Higher Is Better A . 0.71 |==================================================================== B . 0.72 |===================================================================== C . 0.72 |===================================================================== AOM AV1 3.5 Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p Frames Per Second > Higher Is Better A . 16.65 |================================================================= B . 17.49 |==================================================================== C . 17.49 |==================================================================== AOM AV1 3.5 Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p Frames Per Second > Higher Is Better A . 58.85 |=============================================================== B . 57.88 |============================================================== C . 63.46 |==================================================================== AOM AV1 3.5 Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p Frames Per Second > Higher Is Better A . 40.35 |================================================================== B . 41.89 |==================================================================== C . 41.88 |==================================================================== AOM AV1 3.5 Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p Frames Per Second > Higher Is Better A . 120.56 |=============================================================== B . 127.40 |=================================================================== C . 125.13 |================================================================== AOM AV1 3.5 Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p Frames Per Second > Higher Is Better A . 143.74 |================================================================ B . 149.25 |=================================================================== C . 149.74 |=================================================================== AOM AV1 3.5 Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p Frames Per Second > Higher Is Better A . 152.85 |========================================================= B . 178.37 |=================================================================== C . 153.46 |========================================================== Y-Cruncher 0.7.10.9513 Pi Digits To Calculate: 1B Seconds < Lower Is Better A . 43.40 |=================================================================== B . 43.47 |=================================================================== C . 44.05 |==================================================================== Y-Cruncher 0.7.10.9513 Pi Digits To Calculate: 500M Seconds < Lower Is Better A . 20.71 |==================================================================== B . 20.58 |==================================================================== C . 20.34 |=================================================================== oneDNN 2.7 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 4.02417 |================================================================== B . 3.91825 |================================================================ C . 3.98114 |================================================================= oneDNN 2.7 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 10.60 |=================================================================== B . 10.70 |==================================================================== C . 10.70 |==================================================================== oneDNN 2.7 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 1.46342 |================================================================== B . 1.46173 |================================================================== C . 1.46136 |================================================================== oneDNN 2.7 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 2.16332 |=============================================================== B . 2.28320 |================================================================== C . 2.27602 |================================================================== oneDNN 2.7 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 14.33 |==================================================================== B . 14.43 |==================================================================== C . 14.39 |==================================================================== oneDNN 2.7 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 9.81485 |================================================================ B . 9.81997 |================================================================ C . 10.02650 |================================================================= oneDNN 2.7 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 8.14523 |================================================================== B . 8.06747 |================================================================= C . 8.11715 |================================================================== oneDNN 2.7 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 12.32 |=================================================================== B . 12.45 |==================================================================== C . 12.19 |=================================================================== oneDNN 2.7 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 2.09297 |================================================================= B . 2.11167 |================================================================== C . 2.09377 |================================================================= oneDNN 2.7 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 3.21457 |================================================================== B . 2.97401 |============================================================= C . 3.14484 |================================================================= oneDNN 2.7 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 4508.32 |================================================================== B . 4410.31 |================================================================= C . 4439.89 |================================================================= oneDNN 2.7 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 2177.70 |================================================================== B . 2160.58 |================================================================= C . 2179.57 |================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 4474.24 |================================================================== B . 4409.87 |================================================================= C . 4439.06 |================================================================= oneDNN 2.7 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 2168.08 |================================================================== B . 2159.81 |================================================================= C . 2183.19 |================================================================== oneDNN 2.7 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 2.81573 |================================================================== B . 2.74589 |================================================================ C . 2.54921 |============================================================ oneDNN 2.7 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better A . 4439.64 |================================================================== B . 4407.58 |================================================================== C . 4429.54 |================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better A . 2161.75 |================================================================= B . 2160.41 |================================================================= C . 2182.09 |================================================================== oneDNN 2.7 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 1.15139 |========================================================== B . 1.01232 |=================================================== C . 1.30001 |================================================================== TensorFlow 2.10 Device: CPU - Batch Size: 16 - Model: AlexNet images/sec > Higher Is Better A . 80.04 |==================================================================== B . 80.10 |==================================================================== C . 80.04 |==================================================================== TensorFlow 2.10 Device: CPU - Batch Size: 32 - Model: AlexNet images/sec > Higher Is Better A . 102.28 |================================================================== B . 102.95 |=================================================================== C . 103.34 |=================================================================== TensorFlow 2.10 Device: CPU - Batch Size: 16 - Model: GoogLeNet images/sec > Higher Is Better A . 52.52 |==================================================================== B . 52.25 |==================================================================== C . 52.37 |==================================================================== TensorFlow 2.10 Device: CPU - Batch Size: 16 - Model: ResNet-50 images/sec > Higher Is Better A . 17.83 |==================================================================== B . 17.88 |==================================================================== C . 17.93 |==================================================================== TensorFlow 2.10 Device: CPU - Batch Size: 32 - Model: GoogLeNet images/sec > Higher Is Better A . 54.43 |==================================================================== B . 54.06 |==================================================================== C . 54.29 |==================================================================== TensorFlow 2.10 Device: CPU - Batch Size: 32 - Model: ResNet-50 images/sec > Higher Is Better A . 18.44 |==================================================================== B . 18.39 |==================================================================== C . 18.47 |==================================================================== Neural Magic DeepSparse 1.1 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better A . 6.8952 |================================================================== B . 6.9928 |=================================================================== C . 6.8642 |================================================================== Neural Magic DeepSparse 1.1 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better A . 718.18 |=================================================================== B . 713.09 |================================================================== C . 720.94 |=================================================================== Neural Magic DeepSparse 1.1 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream items/sec > Higher Is Better A . 6.5652 |================================================================== B . 6.5403 |================================================================== C . 6.6166 |=================================================================== Neural Magic DeepSparse 1.1 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better A . 152.31 |=================================================================== B . 152.90 |=================================================================== C . 151.13 |================================================================== Neural Magic DeepSparse 1.1 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better A . 27.45 |==================================================================== B . 27.59 |==================================================================== C . 27.16 |=================================================================== Neural Magic DeepSparse 1.1 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better A . 181.39 |================================================================== B . 180.40 |================================================================== C . 183.74 |=================================================================== Neural Magic DeepSparse 1.1 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better A . 22.93 |==================================================================== B . 22.91 |==================================================================== C . 22.87 |==================================================================== Neural Magic DeepSparse 1.1 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better A . 43.61 |==================================================================== B . 43.63 |==================================================================== C . 43.72 |==================================================================== Neural Magic DeepSparse 1.1 Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better A . 44.11 |==================================================================== B . 44.23 |==================================================================== C . 43.78 |=================================================================== Neural Magic DeepSparse 1.1 Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better A . 112.51 |=================================================================== B . 112.26 |================================================================== C . 113.28 |=================================================================== Neural Magic DeepSparse 1.1 Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream items/sec > Higher Is Better A . 38.35 |==================================================================== B . 38.27 |==================================================================== C . 37.96 |=================================================================== Neural Magic DeepSparse 1.1 Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better A . 26.07 |=================================================================== B . 26.12 |=================================================================== C . 26.34 |==================================================================== Neural Magic DeepSparse 1.1 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better A . 87.76 |==================================================================== B . 88.32 |==================================================================== C . 88.07 |==================================================================== Neural Magic DeepSparse 1.1 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better A . 56.78 |==================================================================== B . 56.42 |==================================================================== C . 56.74 |==================================================================== Neural Magic DeepSparse 1.1 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream items/sec > Higher Is Better A . 70.86 |==================================================================== B . 70.74 |==================================================================== C . 70.66 |==================================================================== Neural Magic DeepSparse 1.1 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better A . 14.11 |==================================================================== B . 14.13 |==================================================================== C . 14.15 |==================================================================== Neural Magic DeepSparse 1.1 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better A . 56.69 |==================================================================== B . 56.79 |==================================================================== C . 55.69 |=================================================================== Neural Magic DeepSparse 1.1 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better A . 87.71 |=================================================================== B . 87.68 |=================================================================== C . 89.28 |==================================================================== Neural Magic DeepSparse 1.1 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream items/sec > Higher Is Better A . 48.79 |==================================================================== B . 48.60 |==================================================================== C . 48.05 |=================================================================== Neural Magic DeepSparse 1.1 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better A . 20.49 |=================================================================== B . 20.57 |=================================================================== C . 20.81 |==================================================================== Neural Magic DeepSparse 1.1 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better A . 28.61 |==================================================================== B . 28.39 |=================================================================== C . 28.76 |==================================================================== Neural Magic DeepSparse 1.1 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better A . 174.68 |=================================================================== B . 175.71 |=================================================================== C . 172.62 |================================================================== Neural Magic DeepSparse 1.1 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better A . 24.37 |=================================================================== B . 24.16 |================================================================== C . 24.90 |==================================================================== Neural Magic DeepSparse 1.1 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better A . 41.03 |=================================================================== B . 41.39 |==================================================================== C . 40.16 |================================================================== Neural Magic DeepSparse 1.1 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better A . 6.8935 |=================================================================== B . 6.8793 |=================================================================== C . 6.8706 |=================================================================== Neural Magic DeepSparse 1.1 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better A . 719.46 |=================================================================== B . 720.35 |=================================================================== C . 720.18 |=================================================================== Neural Magic DeepSparse 1.1 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better A . 6.4771 |================================================================== B . 6.4710 |================================================================== C . 6.5651 |=================================================================== Neural Magic DeepSparse 1.1 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better A . 154.39 |=================================================================== B . 154.53 |=================================================================== C . 152.32 |================================================================== spaCy 3.4.1 Model: en_core_web_lg tokens/sec > Higher Is Better A . 17226 |==================================================================== B . 17254 |==================================================================== C . 17118 |=================================================================== spaCy 3.4.1 Model: en_core_web_trf tokens/sec > Higher Is Better A . 1089 |===================================================================== B . 1070 |==================================================================== C . 1074 |====================================================================