motorola motorola edge 20
Geekbench ML Score
373
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 04:42 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | motorola motorola edge 20 |
| Model ID | motorola motorola edge 20 |
| Motherboard | berlin |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.21 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
201
37.6 IPS |
|
|
Image Classification (F16)
|
100% |
274
51.3 IPS |
|
|
Image Classification (I8)
|
97% |
263
49.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
315
5.25 IPS |
|
|
Image Segmentation (F16)
|
100% |
398
6.65 IPS |
|
|
Image Segmentation (I8)
|
98% |
390
6.51 IPS |
|
|
Pose Estimation (F32)
|
100% |
312
0.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
228
0.28 IPS |
|
|
Pose Estimation (I8)
|
100% |
224
0.27 IPS |
|
|
Object Detection (F32)
|
100% |
161
12.0 IPS |
|
|
Object Detection (F16)
|
100% |
192
14.3 IPS |
|
|
Object Detection (I8)
|
62% |
189
14.1 IPS |
|
|
Face Detection (F32)
|
100% |
668
7.94 IPS |
|
|
Face Detection (F16)
|
97% |
987
11.7 IPS |
|
|
Face Detection (I8)
|
87% |
922
11.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
494
3.83 IPS |
|
|
Depth Estimation (F16)
|
100% |
733
5.68 IPS |
|
|
Depth Estimation (I8)
|
95% |
731
5.67 IPS |
|
|
Style Transfer (F32)
|
100% |
951
1.25 IPS |
|
|
Style Transfer (F16)
|
100% |
1617
2.13 IPS |
|
|
Style Transfer (I8)
|
98% |
1584
2.08 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
217
7.74 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
385
13.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
394
14.1 IPS |
|
|
Text Classification (F32)
|
100% |
151
216.8 IPS |
|
|
Text Classification (F16)
|
100% |
151
217.1 IPS |
|
|
Text Classification (I8)
|
92% |
295
424.1 IPS |
|
|
Machine Translation (F32)
|
100% |
274
5.04 IPS |
|
|
Machine Translation (F16)
|
100% |
270
4.96 IPS |
|
|
Machine Translation (I8)
|
64% |
353
6.49 IPS |
