FOSSiBOT F102
Geekbench ML Score
417
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 26 2024 05:14 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | FOSSiBOT F102 |
| Model ID | FOSSiBOT F102 |
| Motherboard | k6789v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 11.52 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
198
37.1 IPS |
|
|
Image Classification (F16)
|
100% |
199
37.2 IPS |
|
|
Image Classification (I8)
|
97% |
364
68.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
305
5.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
305
5.10 IPS |
|
|
Image Segmentation (I8)
|
98% |
433
7.22 IPS |
|
|
Pose Estimation (F32)
|
100% |
401
0.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
406
0.49 IPS |
|
|
Pose Estimation (I8)
|
100% |
1903
2.31 IPS |
|
|
Object Detection (F32)
|
100% |
234
17.4 IPS |
|
|
Object Detection (F16)
|
100% |
230
17.2 IPS |
|
|
Object Detection (I8)
|
61% |
409
30.5 IPS |
|
|
Face Detection (F32)
|
100% |
448
5.33 IPS |
|
|
Face Detection (F16)
|
100% |
454
5.40 IPS |
|
|
Face Detection (I8)
|
86% |
903
10.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
435
3.37 IPS |
|
|
Depth Estimation (F16)
|
100% |
433
3.35 IPS |
|
|
Depth Estimation (I8)
|
95% |
917
7.11 IPS |
|
|
Style Transfer (F32)
|
100% |
663
0.87 IPS |
|
|
Style Transfer (F16)
|
100% |
663
0.87 IPS |
|
|
Style Transfer (I8)
|
98% |
2046
2.69 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
259
9.23 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
254
9.05 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
740
26.4 IPS |
|
|
Text Classification (F32)
|
100% |
242
348.5 IPS |
|
|
Text Classification (F16)
|
100% |
252
362.1 IPS |
|
|
Text Classification (I8)
|
92% |
202
290.8 IPS |
|
|
Machine Translation (F32)
|
100% |
500
9.19 IPS |
|
|
Machine Translation (F16)
|
100% |
488
8.98 IPS |
|
|
Machine Translation (I8)
|
64% |
259
4.77 IPS |
