HP HP ProBook 640 G2
Geekbench ML Score
855
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 13 2024 03:06 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% |
454
85.0 IPS |
|
|
Image Classification (F16)
|
100% |
462
86.5 IPS |
|
|
Image Classification (I8)
|
97% |
672
125.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
369
6.16 IPS |
|
|
Image Segmentation (F16)
|
100% |
377
6.30 IPS |
|
|
Image Segmentation (I8)
|
97% |
527
8.80 IPS |
|
|
Pose Estimation (F32)
|
100% |
1297
1.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
1168
1.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1907
2.31 IPS |
|
|
Object Detection (F32)
|
100% |
517
38.6 IPS |
|
|
Object Detection (F16)
|
100% |
432
32.3 IPS |
|
|
Object Detection (I8)
|
60% |
503
37.5 IPS |
|
|
Face Detection (F32)
|
100% |
987
11.7 IPS |
|
|
Face Detection (F16)
|
100% |
975
11.6 IPS |
|
|
Face Detection (I8)
|
87% |
1286
15.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1490
11.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
1399
10.8 IPS |
|
|
Depth Estimation (I8)
|
74% |
2122
16.5 IPS |
|
|
Style Transfer (F32)
|
100% |
2781
3.66 IPS |
|
|
Style Transfer (F16)
|
100% |
3150
4.14 IPS |
|
|
Style Transfer (I8)
|
85% |
3842
5.05 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
734
26.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
566
20.2 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
896
32.0 IPS |
|
|
Text Classification (F32)
|
100% |
544
781.4 IPS |
|
|
Text Classification (F16)
|
100% |
554
795.9 IPS |
|
|
Text Classification (I8)
|
94% |
262
376.1 IPS |
|
|
Machine Translation (F32)
|
100% |
839
15.4 IPS |
|
|
Machine Translation (F16)
|
100% |
796
14.7 IPS |
|
|
Machine Translation (I8)
|
67% |
773
14.2 IPS |
