HP HP ProBook 640 G2
Geekbench ML Score
887
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 13 2024 03:16 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | HP HP ProBook 640 G2 |
| Motherboard | HP 80FD |
| CPU Information | |
|---|---|
| Name | Intel Core i7-6600U |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 78 Stepping 3 |
| Base Frequency | 2.81 GHz |
| Cluster 1 | 2 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 | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
500
93.6 IPS |
|
|
Image Classification (F16)
|
100% |
487
91.2 IPS |
|
|
Image Classification (I8)
|
97% |
678
126.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
400
6.69 IPS |
|
|
Image Segmentation (F16)
|
100% |
401
6.70 IPS |
|
|
Image Segmentation (I8)
|
97% |
514
8.58 IPS |
|
|
Pose Estimation (F32)
|
100% |
1231
1.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
1163
1.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
2176
2.63 IPS |
|
|
Object Detection (F32)
|
100% |
522
38.9 IPS |
|
|
Object Detection (F16)
|
100% |
521
38.9 IPS |
|
|
Object Detection (I8)
|
60% |
487
36.3 IPS |
|
|
Face Detection (F32)
|
100% |
1037
12.3 IPS |
|
|
Face Detection (F16)
|
100% |
991
11.8 IPS |
|
|
Face Detection (I8)
|
87% |
1316
15.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1507
11.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
1351
10.5 IPS |
|
|
Depth Estimation (I8)
|
74% |
2115
16.4 IPS |
|
|
Style Transfer (F32)
|
100% |
2899
3.81 IPS |
|
|
Style Transfer (F16)
|
100% |
2889
3.80 IPS |
|
|
Style Transfer (I8)
|
85% |
3873
5.09 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
735
26.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
735
26.2 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1032
36.8 IPS |
|
|
Text Classification (F32)
|
100% |
558
802.0 IPS |
|
|
Text Classification (F16)
|
100% |
553
794.6 IPS |
|
|
Text Classification (I8)
|
94% |
261
375.5 IPS |
|
|
Machine Translation (F32)
|
100% |
847
15.6 IPS |
|
|
Machine Translation (F16)
|
100% |
827
15.2 IPS |
|
|
Machine Translation (I8)
|
67% |
827
15.2 IPS |
