HP HP Pavilion x360 Convertible 14-ba0xx
Geekbench ML Score
722
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | paisarn |
| Upload Date | September 21 2024 07:01 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Home (64-bit) |
| Model | HP HP Pavilion x360 Convertible 14-ba0xx |
| Motherboard | HP 8310 |
| Power Plan | HP Recommended |
| CPU Information | |
|---|---|
| Name | Intel Core i5-7200U |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 142 Stepping 9 |
| Base Frequency | 2.71 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 | 3.00 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% |
411
76.9 IPS |
|
|
Image Classification (F16)
|
100% |
397
74.4 IPS |
|
|
Image Classification (I8)
|
97% |
571
106.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
327
5.46 IPS |
|
|
Image Segmentation (F16)
|
100% |
328
5.48 IPS |
|
|
Image Segmentation (I8)
|
97% |
436
7.29 IPS |
|
|
Pose Estimation (F32)
|
100% |
1018
1.23 IPS |
|
|
Pose Estimation (F16)
|
100% |
1000
1.21 IPS |
|
|
Pose Estimation (I8)
|
100% |
1806
2.19 IPS |
|
|
Object Detection (F32)
|
100% |
387
28.9 IPS |
|
|
Object Detection (F16)
|
100% |
404
30.2 IPS |
|
|
Object Detection (I8)
|
60% |
415
31.0 IPS |
|
|
Face Detection (F32)
|
100% |
646
7.68 IPS |
|
|
Face Detection (F16)
|
100% |
616
7.33 IPS |
|
|
Face Detection (I8)
|
87% |
1025
12.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1170
9.07 IPS |
|
|
Depth Estimation (F16)
|
100% |
1159
8.99 IPS |
|
|
Depth Estimation (I8)
|
74% |
1923
14.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2597
3.42 IPS |
|
|
Style Transfer (F16)
|
100% |
2654
3.49 IPS |
|
|
Style Transfer (I8)
|
85% |
2923
3.84 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
532
19.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
616
22.0 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
820
29.3 IPS |
|
|
Text Classification (F32)
|
100% |
522
749.9 IPS |
|
|
Text Classification (F16)
|
100% |
496
712.3 IPS |
|
|
Text Classification (I8)
|
94% |
256
367.4 IPS |
|
|
Machine Translation (F32)
|
100% |
617
11.4 IPS |
|
|
Machine Translation (F16)
|
100% |
646
11.9 IPS |
|
|
Machine Translation (I8)
|
67% |
738
13.6 IPS |
