motorola motorola edge 50 pro
Geekbench ML Score
323
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2024 08:07 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | motorola motorola edge 50 pro |
| Model ID | motorola motorola edge 50 pro |
| Motherboard | eqe |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.63 GHz |
| Memory Information | |
|---|---|
| Size | 11.03 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
141
26.3 IPS |
|
|
Image Classification (F16)
|
100% |
141
26.3 IPS |
|
|
Image Classification (I8)
|
97% |
379
71.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
185
3.09 IPS |
|
|
Image Segmentation (F16)
|
100% |
185
3.10 IPS |
|
|
Image Segmentation (I8)
|
98% |
401
6.70 IPS |
|
|
Pose Estimation (F32)
|
100% |
245
0.30 IPS |
|
|
Pose Estimation (F16)
|
100% |
245
0.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
951
1.15 IPS |
|
|
Object Detection (F32)
|
100% |
146
10.9 IPS |
|
|
Object Detection (F16)
|
100% |
146
10.9 IPS |
|
|
Object Detection (I8)
|
61% |
417
31.1 IPS |
|
|
Face Detection (F32)
|
100% |
371
4.41 IPS |
|
|
Face Detection (F16)
|
100% |
371
4.41 IPS |
|
|
Face Detection (I8)
|
86% |
860
10.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
313
2.43 IPS |
|
|
Depth Estimation (F16)
|
100% |
313
2.43 IPS |
|
|
Depth Estimation (I8)
|
95% |
920
7.13 IPS |
|
|
Style Transfer (F32)
|
100% |
527
0.69 IPS |
|
|
Style Transfer (F16)
|
100% |
526
0.69 IPS |
|
|
Style Transfer (I8)
|
98% |
1608
2.12 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
161
5.75 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
161
5.75 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
596
21.3 IPS |
|
|
Text Classification (F32)
|
100% |
187
268.1 IPS |
|
|
Text Classification (F16)
|
100% |
187
268.3 IPS |
|
|
Text Classification (I8)
|
92% |
331
475.6 IPS |
|
|
Machine Translation (F32)
|
100% |
329
6.06 IPS |
|
|
Machine Translation (F16)
|
100% |
331
6.09 IPS |
|
|
Machine Translation (I8)
|
64% |
402
7.40 IPS |
