HP HP Spectre Notebook
Geekbench ML Score
498
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| Upload Date | August 16 2024 06:13 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Linux Mint 22 |
| Model | HP HP Spectre Notebook |
| Motherboard | HP 8255 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-7500U |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 142 Stepping 9 |
| Base Frequency | 3.50 GHz |
| Cluster 1 | 0 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 | 7.52 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
382
71.5 IPS |
|
|
Image Classification (F16)
|
100% |
378
70.8 IPS |
|
|
Image Classification (I8)
|
99% |
219
41.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
467
7.80 IPS |
|
|
Image Segmentation (F16)
|
100% |
434
7.26 IPS |
|
|
Image Segmentation (I8)
|
98% |
243
4.06 IPS |
|
|
Pose Estimation (F32)
|
100% |
537
0.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
538
0.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
474
0.57 IPS |
|
|
Object Detection (F32)
|
100% |
400
29.9 IPS |
|
|
Object Detection (F16)
|
100% |
392
29.3 IPS |
|
|
Object Detection (I8)
|
65% |
246
18.3 IPS |
|
|
Face Detection (F32)
|
100% |
780
9.27 IPS |
|
|
Face Detection (F16)
|
100% |
781
9.29 IPS |
|
|
Face Detection (I8)
|
87% |
476
5.65 IPS |
|
|
Depth Estimation (F32)
|
100% |
695
5.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
668
5.18 IPS |
|
|
Depth Estimation (I8)
|
95% |
569
4.41 IPS |
|
|
Style Transfer (F32)
|
100% |
991
1.30 IPS |
|
|
Style Transfer (F16)
|
100% |
984
1.29 IPS |
|
|
Style Transfer (I8)
|
98% |
1019
1.34 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
430
15.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
432
15.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
340
12.1 IPS |
|
|
Text Classification (F32)
|
100% |
590
847.9 IPS |
|
|
Text Classification (F16)
|
100% |
610
876.0 IPS |
|
|
Text Classification (I8)
|
92% |
246
353.0 IPS |
|
|
Machine Translation (F32)
|
100% |
867
15.9 IPS |
|
|
Machine Translation (F16)
|
100% |
848
15.6 IPS |
|
|
Machine Translation (I8)
|
62% |
333
6.12 IPS |
