HP HP Notebook - 14s-cr2003tx
Geekbench ML Score
1243
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | LinFengJun |
| Upload Date | August 22 2024 01:14 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 (64-bit) |
| Model | HP HP Notebook - 14s-cr2003tx |
| Motherboard | HP 8659 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-10210U |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 142 Stepping 12 |
| Base Frequency | 2.11 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 4 |
| L1 Data Cache | 32.0 KB x 4 |
| L2 Cache | 256 KB x 4 |
| 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% |
720
134.7 IPS |
|
|
Image Classification (F16)
|
100% |
748
140.0 IPS |
|
|
Image Classification (I8)
|
97% |
1172
219.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
517
8.64 IPS |
|
|
Image Segmentation (F16)
|
100% |
501
8.37 IPS |
|
|
Image Segmentation (I8)
|
97% |
944
15.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1968
2.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
2171
2.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
4233
5.13 IPS |
|
|
Object Detection (F32)
|
100% |
689
51.4 IPS |
|
|
Object Detection (F16)
|
100% |
683
51.0 IPS |
|
|
Object Detection (I8)
|
60% |
765
57.1 IPS |
|
|
Face Detection (F32)
|
100% |
801
9.53 IPS |
|
|
Face Detection (F16)
|
100% |
851
10.1 IPS |
|
|
Face Detection (I8)
|
87% |
1556
18.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
2105
16.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
2156
16.7 IPS |
|
|
Depth Estimation (I8)
|
74% |
4035
31.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2932
3.86 IPS |
|
|
Style Transfer (F16)
|
100% |
4241
5.58 IPS |
|
|
Style Transfer (I8)
|
85% |
5513
7.25 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1149
41.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1161
41.5 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1621
57.9 IPS |
|
|
Text Classification (F32)
|
100% |
934
1.34 KIPS |
|
|
Text Classification (F16)
|
100% |
919
1.32 KIPS |
|
|
Text Classification (I8)
|
94% |
347
498.6 IPS |
|
|
Machine Translation (F32)
|
100% |
932
17.1 IPS |
|
|
Machine Translation (F16)
|
100% |
843
15.5 IPS |
|
|
Machine Translation (I8)
|
67% |
1012
18.6 IPS |
