12600k sept
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.
HTML result view exported from: https://openbenchmarking.org/result/2209087-PTS-12600KSE38&grw.
Unvanquished
Resolution: 2560 x 1440 - Effects Quality: Medium
Unvanquished
Resolution: 3840 x 2160 - Effects Quality: Medium
Unvanquished
Resolution: 1920 x 1080 - Effects Quality: Medium
Unvanquished
Resolution: 1920 x 1200 - Effects Quality: Medium
Unvanquished
Resolution: 2560 x 1440 - Effects Quality: Ultra
Unvanquished
Resolution: 3840 x 2160 - Effects Quality: Ultra
Unvanquished
Resolution: 1920 x 1080 - Effects Quality: Ultra
Unvanquished
Resolution: 1920 x 1200 - Effects Quality: Ultra
Unvanquished
Resolution: 3840 x 2160 - Effects Quality: High
Unvanquished
Resolution: 2560 x 1440 - Effects Quality: High
Unvanquished
Resolution: 1920 x 1200 - Effects Quality: High
BRL-CAD
VGR Performance Metric
ASTC Encoder
Preset: Fast
ASTC Encoder
Preset: Medium
ASTC Encoder
Preset: Thorough
ASTC Encoder
Preset: Exhaustive
AI Benchmark Alpha
Device Inference Score
AI Benchmark Alpha
Device Training Score
AI Benchmark Alpha
Device AI Score
Mobile Neural Network
Model: nasnet
Mobile Neural Network
Model: mobilenetV3
Mobile Neural Network
Model: squeezenetv1.1
Mobile Neural Network
Model: resnet-v2-50
Mobile Neural Network
Model: SqueezeNetV1.0
Mobile Neural Network
Model: MobileNetV2_224
Mobile Neural Network
Model: mobilenet-v1-1.0
Mobile Neural Network
Model: inception-v3
NCNN
Target: CPU - Model: mobilenet
NCNN
Target: CPU-v2-v2 - Model: mobilenet-v2
NCNN
Target: CPU-v3-v3 - Model: mobilenet-v3
NCNN
Target: CPU - Model: shufflenet-v2
NCNN
Target: CPU - Model: mnasnet
NCNN
Target: CPU - Model: efficientnet-b0
NCNN
Target: CPU - Model: blazeface
NCNN
Target: CPU - Model: googlenet
NCNN
Target: CPU - Model: vgg16
NCNN
Target: CPU - Model: resnet18
NCNN
Target: CPU - Model: alexnet
NCNN
Target: CPU - Model: resnet50
NCNN
Target: CPU - Model: yolov4-tiny
NCNN
Target: CPU - Model: squeezenet_ssd
NCNN
Target: CPU - Model: regnety_400m
NCNN
Target: CPU - Model: vision_transformer
NCNN
Target: CPU - Model: FastestDet
NCNN
Target: Vulkan GPU - Model: mobilenet
NCNN
Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2
NCNN
Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3
NCNN
Target: Vulkan GPU - Model: shufflenet-v2
NCNN
Target: Vulkan GPU - Model: mnasnet
NCNN
Target: Vulkan GPU - Model: efficientnet-b0
NCNN
Target: Vulkan GPU - Model: blazeface
NCNN
Target: Vulkan GPU - Model: googlenet
NCNN
Target: Vulkan GPU - Model: vgg16
NCNN
Target: Vulkan GPU - Model: resnet18
NCNN
Target: Vulkan GPU - Model: alexnet
NCNN
Target: Vulkan GPU - Model: resnet50
NCNN
Target: Vulkan GPU - Model: yolov4-tiny
NCNN
Target: Vulkan GPU - Model: squeezenet_ssd
NCNN
Target: Vulkan GPU - Model: regnety_400m
NCNN
Target: Vulkan GPU - Model: vision_transformer
NCNN
Target: Vulkan GPU - Model: FastestDet
LAMMPS Molecular Dynamics Simulator
Model: 20k Atoms
LAMMPS Molecular Dynamics Simulator
Model: Rhodopsin Protein
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
Aircrack-ng
Primesieve
Length: 1e12
Primesieve
Length: 1e13
7-Zip Compression
Test: Compression Rating
7-Zip Compression
Test: Decompression Rating
Timed PHP Compilation
Time To Compile
GraphicsMagick
Operation: Swirl
GraphicsMagick
Operation: Rotate
GraphicsMagick
Operation: Sharpen
GraphicsMagick
Operation: Enhanced
GraphicsMagick
Operation: Resizing
GraphicsMagick
Operation: Noise-Gaussian
GraphicsMagick
Operation: HWB Color Space
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 10 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 10 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
Blender
Blend File: BMW27 - Compute: CPU-Only
Blender
Blend File: Classroom - Compute: CPU-Only
Blender
Blend File: Fishy Cat - Compute: CPU-Only
Blender
Blend File: Barbershop - Compute: CPU-Only
Blender
Blend File: Pabellon Barcelona - Compute: CPU-Only
Natron
Input: Spaceship
Timed CPython Compilation
Build Configuration: Default
Timed CPython Compilation
Build Configuration: Released Build, PGO + LTO Optimized
Timed Erlang/OTP Compilation
Time To Compile
Timed Node.js Compilation
Time To Compile
Timed Wasmer Compilation
Time To Compile
C-Blosc
Test: blosclz shuffle
C-Blosc
Test: blosclz bitshuffle
srsRAN
Test: OFDM_Test
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM
srsRAN
Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM
srsRAN
Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM
Apache Spark
Row Count: 1000000 - Partitions: 100 - SHA-512 Benchmark Time
Apache Spark
Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark
Apache Spark
Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 1000000 - Partitions: 100 - Group By Test Time
Apache Spark
Row Count: 1000000 - Partitions: 100 - Repartition Test Time
Apache Spark
Row Count: 1000000 - Partitions: 100 - Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 100 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 500 - SHA-512 Benchmark Time
Unvanquished
Resolution: 1920 x 1080 - Effects Quality: High
Apache Spark
Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark
Apache Spark
Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 1000000 - Partitions: 500 - Group By Test Time
Apache Spark
Row Count: 1000000 - Partitions: 500 - Repartition Test Time
Apache Spark
Row Count: 1000000 - Partitions: 500 - Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 500 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 1000 - SHA-512 Benchmark Time
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Group By Test Time
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Repartition Test Time
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 2000 - SHA-512 Benchmark Time
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Group By Test Time
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Repartition Test Time
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 10000000 - Partitions: 100 - SHA-512 Benchmark Time
Apache Spark
Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmark
Apache Spark
Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 10000000 - Partitions: 100 - Group By Test Time
Apache Spark
Row Count: 10000000 - Partitions: 100 - Repartition Test Time
Apache Spark
Row Count: 10000000 - Partitions: 100 - Inner Join Test Time
Apache Spark
Row Count: 10000000 - Partitions: 100 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 10000000 - Partitions: 500 - SHA-512 Benchmark Time
Apache Spark
Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmark
Apache Spark
Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 10000000 - Partitions: 500 - Group By Test Time
Apache Spark
Row Count: 10000000 - Partitions: 500 - Repartition Test Time
Apache Spark
Row Count: 10000000 - Partitions: 500 - Inner Join Test Time
Apache Spark
Row Count: 10000000 - Partitions: 500 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 20000000 - Partitions: 100 - SHA-512 Benchmark Time
Apache Spark
Row Count: 20000000 - Partitions: 100 - Calculate Pi Benchmark
Apache Spark
Row Count: 20000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 20000000 - Partitions: 100 - Group By Test Time
Apache Spark
Row Count: 20000000 - Partitions: 100 - Repartition Test Time
Apache Spark
Row Count: 20000000 - Partitions: 100 - Inner Join Test Time
Apache Spark
Row Count: 20000000 - Partitions: 100 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 20000000 - Partitions: 500 - SHA-512 Benchmark Time
Apache Spark
Row Count: 20000000 - Partitions: 500 - Calculate Pi Benchmark
Apache Spark
Row Count: 20000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 20000000 - Partitions: 500 - Group By Test Time
Apache Spark
Row Count: 20000000 - Partitions: 500 - Repartition Test Time
Apache Spark
Row Count: 20000000 - Partitions: 500 - Inner Join Test Time
Apache Spark
Row Count: 20000000 - Partitions: 500 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 40000000 - Partitions: 100 - SHA-512 Benchmark Time
Apache Spark
Row Count: 40000000 - Partitions: 100 - Calculate Pi Benchmark
Apache Spark
Row Count: 40000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 40000000 - Partitions: 100 - Group By Test Time
Apache Spark
Row Count: 40000000 - Partitions: 100 - Repartition Test Time
Apache Spark
Row Count: 40000000 - Partitions: 100 - Inner Join Test Time
Apache Spark
Row Count: 40000000 - Partitions: 100 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 40000000 - Partitions: 500 - SHA-512 Benchmark Time
Apache Spark
Row Count: 40000000 - Partitions: 500 - Calculate Pi Benchmark
Apache Spark
Row Count: 40000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 40000000 - Partitions: 500 - Group By Test Time
Apache Spark
Row Count: 40000000 - Partitions: 500 - Repartition Test Time
Apache Spark
Row Count: 40000000 - Partitions: 500 - Inner Join Test Time
Apache Spark
Row Count: 40000000 - Partitions: 500 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 10000000 - Partitions: 1000 - SHA-512 Benchmark Time
Apache Spark
Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmark
Apache Spark
Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 10000000 - Partitions: 1000 - Group By Test Time
Apache Spark
Row Count: 10000000 - Partitions: 1000 - Repartition Test Time
Apache Spark
Row Count: 10000000 - Partitions: 1000 - Inner Join Test Time
Apache Spark
Row Count: 10000000 - Partitions: 1000 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 10000000 - Partitions: 2000 - SHA-512 Benchmark Time
Apache Spark
Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmark
Apache Spark
Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 10000000 - Partitions: 2000 - Group By Test Time
Apache Spark
Row Count: 10000000 - Partitions: 2000 - Repartition Test Time
Apache Spark
Row Count: 10000000 - Partitions: 2000 - Inner Join Test Time
Apache Spark
Row Count: 10000000 - Partitions: 2000 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 20000000 - Partitions: 1000 - SHA-512 Benchmark Time
Apache Spark
Row Count: 20000000 - Partitions: 1000 - Calculate Pi Benchmark
Apache Spark
Row Count: 20000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 20000000 - Partitions: 1000 - Group By Test Time
Apache Spark
Row Count: 20000000 - Partitions: 1000 - Repartition Test Time
Apache Spark
Row Count: 20000000 - Partitions: 1000 - Inner Join Test Time
Apache Spark
Row Count: 20000000 - Partitions: 1000 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 20000000 - Partitions: 2000 - SHA-512 Benchmark Time
Apache Spark
Row Count: 20000000 - Partitions: 2000 - Calculate Pi Benchmark
Apache Spark
Row Count: 20000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 20000000 - Partitions: 2000 - Group By Test Time
Apache Spark
Row Count: 20000000 - Partitions: 2000 - Repartition Test Time
Apache Spark
Row Count: 20000000 - Partitions: 2000 - Inner Join Test Time
Apache Spark
Row Count: 20000000 - Partitions: 2000 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 40000000 - Partitions: 1000 - SHA-512 Benchmark Time
Apache Spark
Row Count: 40000000 - Partitions: 1000 - Calculate Pi Benchmark
Apache Spark
Row Count: 40000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 40000000 - Partitions: 1000 - Group By Test Time
Apache Spark
Row Count: 40000000 - Partitions: 1000 - Repartition Test Time
Apache Spark
Row Count: 40000000 - Partitions: 1000 - Inner Join Test Time
Apache Spark
Row Count: 40000000 - Partitions: 1000 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 40000000 - Partitions: 2000 - SHA-512 Benchmark Time
Apache Spark
Row Count: 40000000 - Partitions: 2000 - Calculate Pi Benchmark
Apache Spark
Row Count: 40000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 40000000 - Partitions: 2000 - Group By Test Time
Apache Spark
Row Count: 40000000 - Partitions: 2000 - Repartition Test Time
Apache Spark
Row Count: 40000000 - Partitions: 2000 - Inner Join Test Time
Apache Spark
Row Count: 40000000 - Partitions: 2000 - Broadcast Inner Join Test Time
Dragonflydb
Clients: 50 - Set To Get Ratio: 1:1
Dragonflydb
Clients: 50 - Set To Get Ratio: 1:5
Dragonflydb
Clients: 50 - Set To Get Ratio: 5:1
Dragonflydb
Clients: 200 - Set To Get Ratio: 1:1
Dragonflydb
Clients: 200 - Set To Get Ratio: 1:5
Dragonflydb
Clients: 200 - Set To Get Ratio: 5:1
etcd
Test: PUT - Connections: 50 - Clients: 100
etcd
Test: PUT - Connections: 50 - Clients: 100 - Average Latency
etcd
Test: PUT - Connections: 100 - Clients: 100
etcd
Test: PUT - Connections: 100 - Clients: 100 - Average Latency
etcd
Test: PUT - Connections: 50 - Clients: 1000
etcd
Test: PUT - Connections: 50 - Clients: 1000 - Average Latency
etcd
Test: PUT - Connections: 500 - Clients: 100
etcd
Test: PUT - Connections: 500 - Clients: 100 - Average Latency
etcd
Test: PUT - Connections: 100 - Clients: 1000
etcd
Test: PUT - Connections: 100 - Clients: 1000 - Average Latency
etcd
Test: PUT - Connections: 500 - Clients: 1000
etcd
Test: PUT - Connections: 500 - Clients: 1000 - Average Latency
etcd
Test: RANGE - Connections: 50 - Clients: 100
etcd
Test: RANGE - Connections: 50 - Clients: 100 - Average Latency
etcd
Test: RANGE - Connections: 100 - Clients: 100
etcd
Test: RANGE - Connections: 100 - Clients: 100 - Average Latency
etcd
Test: RANGE - Connections: 50 - Clients: 1000
etcd
Test: RANGE - Connections: 50 - Clients: 1000 - Average Latency
etcd
Test: RANGE - Connections: 500 - Clients: 100
etcd
Test: RANGE - Connections: 500 - Clients: 100 - Average Latency
etcd
Test: RANGE - Connections: 100 - Clients: 1000
etcd
Test: RANGE - Connections: 100 - Clients: 1000 - Average Latency
etcd
Test: RANGE - Connections: 500 - Clients: 1000
etcd
Test: RANGE - Connections: 500 - Clients: 1000 - Average Latency
memtier_benchmark
Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:1
memtier_benchmark
Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:5
memtier_benchmark
Protocol: Redis - Clients: 50 - Set To Get Ratio: 5:1
memtier_benchmark
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:1
memtier_benchmark
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5
memtier_benchmark
Protocol: Redis - Clients: 100 - Set To Get Ratio: 5:1
memtier_benchmark
Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10
memtier_benchmark
Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:1
memtier_benchmark
Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:5
memtier_benchmark
Protocol: Redis - Clients: 500 - Set To Get Ratio: 5:1
memtier_benchmark
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10
memtier_benchmark
Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:10
Redis
Test: GET - Parallel Connections: 50
Redis
Test: SET - Parallel Connections: 50
Redis
Test: GET - Parallel Connections: 500
Redis
Test: LPOP - Parallel Connections: 50
Redis
Test: SADD - Parallel Connections: 50
Redis
Test: SET - Parallel Connections: 500
Redis
Test: GET - Parallel Connections: 1000
Redis
Test: LPOP - Parallel Connections: 500
Redis
Test: LPUSH - Parallel Connections: 50
Redis
Test: SADD - Parallel Connections: 500
Redis
Test: SET - Parallel Connections: 1000
Redis
Test: LPOP - Parallel Connections: 1000
Redis
Test: LPUSH - Parallel Connections: 500
Redis
Test: LPUSH - Parallel Connections: 1000
Facebook RocksDB
Test: Random Fill
Facebook RocksDB
Test: Random Read
Facebook RocksDB
Test: Update Random
Facebook RocksDB
Test: Sequential Fill
Facebook RocksDB
Test: Random Fill Sync
Facebook RocksDB
Test: Read While Writing
Facebook RocksDB
Test: Read Random Write Random
Node.js V8 Web Tooling Benchmark
Unpacking The Linux Kernel
linux-5.19.tar.xz
Redis
Test: SADD - Parallel Connections: 1000
Phoronix Test Suite v10.8.5