motorola motorola edge 50 pro
Geekbench ML Score
528
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2024 08:01 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
319
59.7 IPS |
|
|
Image Classification (F16)
|
100% |
461
86.3 IPS |
|
|
Image Classification (I8)
|
99% |
351
65.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
497
8.30 IPS |
|
|
Image Segmentation (F16)
|
100% |
782
13.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
639
10.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
343
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
779
0.94 IPS |
|
|
Pose Estimation (I8)
|
100% |
758
0.92 IPS |
|
|
Object Detection (F32)
|
100% |
170
12.7 IPS |
|
|
Object Detection (F16)
|
100% |
196
14.7 IPS |
|
|
Object Detection (I8)
|
62% |
180
13.4 IPS |
|
|
Face Detection (F32)
|
100% |
1007
12.0 IPS |
|
|
Face Detection (F16)
|
97% |
1500
17.8 IPS |
|
|
Face Detection (I8)
|
86% |
1234
14.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
680
5.27 IPS |
|
|
Depth Estimation (F16)
|
100% |
1349
10.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
1306
10.1 IPS |
|
|
Style Transfer (F32)
|
100% |
1586
2.09 IPS |
|
|
Style Transfer (F16)
|
100% |
3256
4.28 IPS |
|
|
Style Transfer (I8)
|
98% |
3229
4.25 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
205
7.30 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
282
10.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
285
10.2 IPS |
|
|
Text Classification (F32)
|
100% |
187
268.5 IPS |
|
|
Text Classification (F16)
|
100% |
187
269.2 IPS |
|
|
Text Classification (I8)
|
92% |
331
475.9 IPS |
|
|
Machine Translation (F32)
|
100% |
329
6.06 IPS |
|
|
Machine Translation (F16)
|
100% |
331
6.09 IPS |
|
|
Machine Translation (I8)
|
64% |
404
7.43 IPS |
