Laptops

AMD Ryzen 7 7840U testing with a Framework FRANMDCP07 (03.03 BIOS) and AMD Phoenix1 512MB on Ubuntu 23.10 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2312162-NE-LAPTOPS1429&grs.

OpenSCAD

Render: Leonardo Phone Case Slim

OpenSCAD

Render: Projector Mount Swivel

OpenSCAD

Render: Mini-ITX Case

OpenSCAD

Render: Retro Car

OpenSCAD

Render: Pistol

GNU Octave Benchmark

OCRMyPDF

Processing 60 Page PDF Document

Inkscape

Operation: SVG Files To PNG

GEGL

Operation: Rotate 90 Degrees

GEGL

Operation: Color Enhance

GEGL

Operation: Wavelet Blur

GEGL

Operation: Tile Glass

GEGL

Operation: Antialias

GEGL

Operation: Reflect

GEGL

Operation: Cartoon

GEGL

Operation: Scale

GEGL

Operation: Crop

R Benchmark

GNU Radio

Test: Hilbert Transform

GNU Radio

Test: FM Deemphasis Filter

GNU Radio

Test: IIR Filter

GNU Radio

Test: FIR Filter

GNU Radio

Test: Signal Source (Cosine)

GNU Radio

Test: Five Back to Back FIR Filters

LuaRadio

Test: Complex Phase

LuaRadio

Test: Hilbert Transform

LuaRadio

Test: FM Deemphasis Filter

LuaRadio

Test: Five Back to Back FIR Filters

Unpacking Firefox

Extracting: firefox-84.0.source.tar.xz

Git

Time To Complete Common Git Commands

PHPBench

PHP Benchmark Suite

PyPerformance

Benchmark: python_startup

PyPerformance

Benchmark: regex_compile

PyPerformance

Benchmark: crypto_pyaes

PyPerformance

Benchmark: json_loads

PyPerformance

Benchmark: raytrace

PyBench

Total For Average Test Times

ASKAP

Test: tConvolve MT - Gridding

ScyllaDB

Test: Writes

RocksDB

Test: Read Random Write Random

RocksDB

Test: Read While Writing

RocksDB

Test: Update Random

RocksDB

Test: Random Read

IndigoBench

Acceleration: CPU - Scene: Supercar

IndigoBench

Acceleration: CPU - Scene: Bedroom

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU

OpenVINO

Model: Handwritten English Recognition FP16-INT8 - Device: CPU

OpenVINO

Model: Handwritten English Recognition FP16-INT8 - Device: CPU

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU

OpenVINO

Model: Weld Porosity Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Weld Porosity Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Road Segmentation ADAS FP16-INT8 - Device: CPU

OpenVINO

Model: Road Segmentation ADAS FP16-INT8 - Device: CPU

OpenVINO

Model: Face Detection Retail FP16-INT8 - Device: CPU

OpenVINO

Model: Face Detection Retail FP16-INT8 - Device: CPU

OpenVINO

Model: Vehicle Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Vehicle Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Person Detection FP16 - Device: CPU

OpenVINO

Model: Person Detection FP16 - Device: CPU

TensorFlow Lite

Model: Inception ResNet V2

TensorFlow Lite

Model: Mobilenet Quant

TensorFlow Lite

Model: Mobilenet Float

TensorFlow Lite

Model: NASNet Mobile

TensorFlow Lite

Model: Inception V4

TensorFlow Lite

Model: SqueezeNet

TensorFlow

Device: CPU - Batch Size: 32 - Model: ResNet-50

TensorFlow

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

PyTorch

Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l

PyTorch

Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l

PyTorch

Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-152

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-152

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-50

PyTorch

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

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-152

PyTorch

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

Whisper.cpp

Model: ggml-small.en - Input: 2016 State of the Union

Whisper.cpp

Model: ggml-base.en - Input: 2016 State of the Union

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

Neural Magic DeepSparse

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

RawTherapee

Total Benchmark Time

GIMP

Test: unsharp-mask

GIMP

Test: auto-levels

GIMP

Test: rotate

GIMP

Test: resize

Darktable

Test: Server Room - Acceleration: CPU-only

Darktable

Test: Server Rack - Acceleration: CPU-only

Darktable

Test: Masskrug - Acceleration: CPU-only

Darktable

Test: Boat - Acceleration: CPU-only

SQLite Speedtest

Timed Time - Size 1,000

OpenCV

Test: Core

Scikit-Learn

Benchmark: 20 Newsgroups / Logistic Regression

Scikit-Learn

Benchmark: Hist Gradient Boosting Adult

Scikit-Learn

Benchmark: Hist Gradient Boosting

Scikit-Learn

Benchmark: TSNE MNIST Dataset

Scikit-Learn

Benchmark: Isolation Forest

Scikit-Learn

Benchmark: SGD Regression

Scikit-Learn

Benchmark: MNIST Dataset

PyHPC Benchmarks

Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Isoneutral Mixing

PyHPC Benchmarks

Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Equation of State

Numenta Anomaly Benchmark

Detector: Contextual Anomaly Detector OSE

Numenta Anomaly Benchmark

Detector: Bayesian Changepoint

Numenta Anomaly Benchmark

Detector: Earthgecko Skyline

Numenta Anomaly Benchmark

Detector: Windowed Gaussian

Numenta Anomaly Benchmark

Detector: Relative Entropy

Numenta Anomaly Benchmark

Detector: KNN CAD

NCNN

Target: CPU - Model: FastestDet

NCNN

Target: CPU - Model: vision_transformer

NCNN

Target: CPU - Model: regnety_400m

NCNN

Target: CPU - Model: yolov4-tiny

NCNN

Target: CPU - Model: resnet50

NCNN

Target: CPU - Model: alexnet

NCNN

Target: CPU - Model: vgg16

NCNN

Target: CPU - Model: blazeface

NCNN

Target: CPU - Model: efficientnet-b0

NCNN

Target: CPU - Model: mnasnet

NCNN

Target: CPU - Model: shufflenet-v2

NCNN

Target: CPU-v3-v3 - Model: mobilenet-v3

NCNN

Target: CPU-v2-v2 - Model: mobilenet-v2

NCNN

Target: CPU - Model: mobilenet

RNNoise

Stargate Digital Audio Workstation

Sample Rate: 480000 - Buffer Size: 1024

Stargate Digital Audio Workstation

Sample Rate: 192000 - Buffer Size: 1024

Stargate Digital Audio Workstation

Sample Rate: 96000 - Buffer Size: 1024

Stargate Digital Audio Workstation

Sample Rate: 44100 - Buffer Size: 1024

libjpeg-turbo tjbench

Test: Decompression Throughput

libavif avifenc

Encoder Speed: 10, Lossless

libavif avifenc

Encoder Speed: 6, Lossless

libavif avifenc

Encoder Speed: 6

libavif avifenc

Encoder Speed: 2

libavif avifenc

Encoder Speed: 0

ASTC Encoder

Preset: Exhaustive

ASTC Encoder

Preset: Thorough