ThinkPad X13s Gen 1

Snapdragon 8cx Gen 3 testing with a Lenovo ThinkPad X13s Gen 1 (21BX0007US) on Ubuntu 22.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2208112-NE-THINKPADX35
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Result
Identifier
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Performance Per
Dollar
Date
Run
  Test
  Duration
ThinkPad X13s Gen 1 - Snapdragon 8cx Gen 3
August 11 2022
  1 Hour, 13 Minutes
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ThinkPad X13s Gen 1 Snapdragon 8cx Gen 3 testing with a Lenovo ThinkPad X13s Gen 1 (21BX0007US) on Ubuntu 22.04 via the Phoronix Test Suite. ,,"ThinkPad X13s Gen 1 - Snapdragon 8cx Gen 3" Processor,,Snapdragon @ 2.44GHz (4 Cores / 8 Threads) Motherboard,,LENOVO 21BX0007US (N3HET40W 1.12 BIOS) Memory,,16GB Disk,,512GB UMIS RPJTJ512MGE1QDQ Graphics,,llvmpipe Network,,Qualcomm Atheros QCNFA765 OS,,Ubuntu 22.04 Kernel,,5.19.0-rc7-next-20220720-12121-g35b9cb33a357 (aarch64) Desktop,,GNOME Shell 42.2 Display Server,,X Server 1.21.1.3 OpenGL,,4.5 Mesa 22.0.5 (LLVM 13.0.1 128 bits) Compiler,,GCC 11.2.0 File-System,,ext4 Screen Resolution,,1920x1200 ,,"ThinkPad X13s Gen 1 - Snapdragon 8cx Gen 3" "PyBench - Total For Average Test Times (Milliseconds)",LIB,1033 "NCNN - Target: CPU - Model: mobilenet (ms)",LIB,16.84 "NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,4.11 "NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.74 "NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,2.93 "NCNN - Target: CPU - Model: mnasnet (ms)",LIB,3.58 "NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,6.24 "NCNN - Target: CPU - Model: blazeface (ms)",LIB,1.34 "NCNN - Target: CPU - Model: googlenet (ms)",LIB,11.97 "NCNN - Target: CPU - Model: vgg16 (ms)",LIB,66.66 "NCNN - Target: CPU - Model: resnet18 (ms)",LIB,9.76 "NCNN - Target: CPU - Model: alexnet (ms)",LIB,11.92 "NCNN - Target: CPU - Model: resnet50 (ms)",LIB,22.16 "NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,27.53 "NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,20.34 "NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,7.19 "TNN - Target: CPU - Model: DenseNet (ms)",LIB,3531.764 "TNN - Target: CPU - Model: MobileNet v2 (ms)",LIB,251.798 "TNN - Target: CPU - Model: SqueezeNet v2 (ms)",LIB,62.759 "TNN - Target: CPU - Model: SqueezeNet v1.1 (ms)",LIB,231.114