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Intel Core i9-14900K testing with a ASUS PRIME Z790-P WIFI (1662 BIOS) and ASUS Intel RPL-S 16GB on Ubuntu 24.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2410191-PTS-DSDFDS2287&grs&sor.

LiteRT

Model: NASNet Mobile

LiteRT

Model: DeepLab V3

XNNPACK

Model: FP32MobileNetV1

XNNPACK

Model: FP16MobileNetV1

Mobile Neural Network

Model: squeezenetv1.1

LiteRT

Model: Mobilenet Quant

Mobile Neural Network

Model: mobilenetV3

LiteRT

Model: Inception ResNet V2

Mobile Neural Network

Model: MobileNetV2_224

XNNPACK

Model: FP16MobileNetV3Large

NAMD

Input: ATPase with 327,506 Atoms

LiteRT

Model: Quantized COCO SSD MobileNet v1

Apache Cassandra

Test: Writes

BYTE Unix Benchmark

Computational Test: Whetstone Double

oneDNN

Harness: Recurrent Neural Network Inference - Engine: CPU

XNNPACK

Model: FP32MobileNetV3Large

XNNPACK

Model: FP32MobileNetV2

XNNPACK

Model: FP32MobileNetV3Small

XNNPACK

Model: FP16MobileNetV3Small

Mobile Neural Network

Model: resnet-v2-50

LiteRT

Model: Inception V4

XNNPACK

Model: QS8MobileNetV2

Build2

Time To Compile

BYTE Unix Benchmark

Computational Test: Dhrystone 2

Mobile Neural Network

Model: SqueezeNetV1.0

LiteRT

Model: SqueezeNet

Mobile Neural Network

Model: nasnet

LiteRT

Model: Mobilenet Float

NAMD

Input: STMV with 1,066,628 Atoms

BYTE Unix Benchmark

Computational Test: Pipe

oneDNN

Harness: IP Shapes 1D - Engine: CPU

oneDNN

Harness: Deconvolution Batch shapes_3d - Engine: CPU

Mobile Neural Network

Model: inception-v3

oneDNN

Harness: Deconvolution Batch shapes_1d - Engine: CPU

BYTE Unix Benchmark

Computational Test: System Call

oneDNN

Harness: IP Shapes 3D - Engine: CPU

XNNPACK

Model: FP16MobileNetV2

oneDNN

Harness: Convolution Batch Shapes Auto - Engine: CPU

Mobile Neural Network

Model: mobilenet-v1-1.0

oneDNN

Harness: Recurrent Neural Network Training - Engine: CPU

Phoronix Test Suite v10.8.5