HP HP ProDesk 600 G3 MT
Geekbench ML Score
1293
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | January 05 2024 08:56 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | HP HP ProDesk 600 G3 MT |
| Motherboard | HP 829D |
| Power Plan | Equilibrado |
| CPU Information | |
|---|---|
| Name | Intel Core i5-7500 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 9 |
| Base Frequency | 3.41 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 2 |
| L1 Data Cache | 32.0 KB x 2 |
| L2 Cache | 256 KB x 2 |
| L3 Cache | 6.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
718
134.3 IPS |
|
|
Image Classification (F16)
|
100% |
706
132.1 IPS |
|
|
Image Classification (I8)
|
97% |
1058
197.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
527
8.80 IPS |
|
|
Image Segmentation (F16)
|
100% |
518
8.66 IPS |
|
|
Image Segmentation (I8)
|
97% |
934
15.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
2175
2.63 IPS |
|
|
Pose Estimation (F16)
|
100% |
2234
2.71 IPS |
|
|
Pose Estimation (I8)
|
100% |
4077
4.94 IPS |
|
|
Object Detection (F32)
|
100% |
721
53.8 IPS |
|
|
Object Detection (F16)
|
100% |
681
50.8 IPS |
|
|
Object Detection (I8)
|
60% |
738
55.1 IPS |
|
|
Face Detection (F32)
|
100% |
922
11.0 IPS |
|
|
Face Detection (F16)
|
100% |
979
11.6 IPS |
|
|
Face Detection (I8)
|
87% |
1744
20.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
2356
18.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
2419
18.8 IPS |
|
|
Depth Estimation (I8)
|
74% |
3907
30.3 IPS |
|
|
Style Transfer (F32)
|
100% |
5283
6.95 IPS |
|
|
Style Transfer (F16)
|
100% |
5257
6.91 IPS |
|
|
Style Transfer (I8)
|
85% |
6111
8.04 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1010
36.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1167
41.7 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1621
57.9 IPS |
|
|
Text Classification (F32)
|
100% |
833
1.20 KIPS |
|
|
Text Classification (F16)
|
100% |
849
1.22 KIPS |
|
|
Text Classification (I8)
|
94% |
281
404.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1017
18.7 IPS |
|
|
Machine Translation (F16)
|
100% |
989
18.2 IPS |
|
|
Machine Translation (I8)
|
67% |
1007
18.5 IPS |
