HP HP Spectre Notebook
Geekbench ML Score
500
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| Upload Date | August 16 2024 06:09 PM |
| Views | 1 |
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% |
384
71.8 IPS |
|
|
Image Classification (F16)
|
100% |
382
71.4 IPS |
|
|
Image Classification (I8)
|
99% |
219
41.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
446
7.45 IPS |
|
|
Image Segmentation (F16)
|
100% |
461
7.70 IPS |
|
|
Image Segmentation (I8)
|
98% |
251
4.19 IPS |
|
|
Pose Estimation (F32)
|
100% |
536
0.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
539
0.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
476
0.58 IPS |
|
|
Object Detection (F32)
|
100% |
403
30.1 IPS |
|
|
Object Detection (F16)
|
100% |
409
30.5 IPS |
|
|
Object Detection (I8)
|
65% |
249
18.6 IPS |
|
|
Face Detection (F32)
|
100% |
767
9.12 IPS |
|
|
Face Detection (F16)
|
100% |
786
9.34 IPS |
|
|
Face Detection (I8)
|
87% |
474
5.64 IPS |
|
|
Depth Estimation (F32)
|
100% |
680
5.27 IPS |
|
|
Depth Estimation (F16)
|
100% |
679
5.27 IPS |
|
|
Depth Estimation (I8)
|
95% |
566
4.39 IPS |
|
|
Style Transfer (F32)
|
100% |
990
1.30 IPS |
|
|
Style Transfer (F16)
|
100% |
988
1.30 IPS |
|
|
Style Transfer (I8)
|
98% |
1010
1.33 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
429
15.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
430
15.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
329
11.8 IPS |
|
|
Text Classification (F32)
|
100% |
600
863.0 IPS |
|
|
Text Classification (F16)
|
100% |
598
858.8 IPS |
|
|
Text Classification (I8)
|
92% |
248
356.9 IPS |
|
|
Machine Translation (F32)
|
100% |
899
16.6 IPS |
|
|
Machine Translation (F16)
|
100% |
843
15.5 IPS |
|
|
Machine Translation (I8)
|
62% |
332
6.11 IPS |
