HP HP Notebook - 14s-cr2003tx
Geekbench ML Score
1247
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | LinFengJun |
| Upload Date | August 29 2024 03:19 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% |
738
138.2 IPS |
|
|
Image Classification (F16)
|
100% |
764
143.0 IPS |
|
|
Image Classification (I8)
|
97% |
1125
210.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
485
8.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
486
8.12 IPS |
|
|
Image Segmentation (I8)
|
97% |
947
15.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
2069
2.51 IPS |
|
|
Pose Estimation (F16)
|
100% |
1702
2.06 IPS |
|
|
Pose Estimation (I8)
|
100% |
4189
5.07 IPS |
|
|
Object Detection (F32)
|
100% |
682
50.9 IPS |
|
|
Object Detection (F16)
|
100% |
662
49.4 IPS |
|
|
Object Detection (I8)
|
60% |
606
45.3 IPS |
|
|
Face Detection (F32)
|
100% |
826
9.82 IPS |
|
|
Face Detection (F16)
|
100% |
840
9.99 IPS |
|
|
Face Detection (I8)
|
87% |
1527
18.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2230
17.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
2167
16.8 IPS |
|
|
Depth Estimation (I8)
|
74% |
4189
32.5 IPS |
|
|
Style Transfer (F32)
|
100% |
5079
6.68 IPS |
|
|
Style Transfer (F16)
|
100% |
4912
6.46 IPS |
|
|
Style Transfer (I8)
|
85% |
5548
7.30 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1165
41.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1147
41.0 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1626
58.1 IPS |
|
|
Text Classification (F32)
|
100% |
929
1.33 KIPS |
|
|
Text Classification (F16)
|
100% |
937
1.35 KIPS |
|
|
Text Classification (I8)
|
94% |
314
451.8 IPS |
|
|
Machine Translation (F32)
|
100% |
921
17.0 IPS |
|
|
Machine Translation (F16)
|
100% |
822
15.1 IPS |
|
|
Machine Translation (I8)
|
67% |
986
18.1 IPS |
