motorola motorola edge 20
Geekbench ML Score
248
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 04:50 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
113
21.1 IPS |
|
|
Image Classification (F16)
|
100% |
113
21.1 IPS |
|
|
Image Classification (I8)
|
97% |
303
56.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
147
2.46 IPS |
|
|
Image Segmentation (F16)
|
100% |
148
2.47 IPS |
|
|
Image Segmentation (I8)
|
98% |
325
5.44 IPS |
|
|
Pose Estimation (F32)
|
100% |
199
0.24 IPS |
|
|
Pose Estimation (F16)
|
100% |
196
0.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
705
0.85 IPS |
|
|
Object Detection (F32)
|
100% |
109
8.14 IPS |
|
|
Object Detection (F16)
|
100% |
109
8.11 IPS |
|
|
Object Detection (I8)
|
61% |
304
22.7 IPS |
|
|
Face Detection (F32)
|
100% |
275
3.27 IPS |
|
|
Face Detection (F16)
|
100% |
274
3.26 IPS |
|
|
Face Detection (I8)
|
86% |
634
7.54 IPS |
|
|
Depth Estimation (F32)
|
100% |
239
1.85 IPS |
|
|
Depth Estimation (F16)
|
100% |
239
1.85 IPS |
|
|
Depth Estimation (I8)
|
95% |
679
5.26 IPS |
|
|
Style Transfer (F32)
|
100% |
408
0.54 IPS |
|
|
Style Transfer (F16)
|
100% |
407
0.54 IPS |
|
|
Style Transfer (I8)
|
98% |
1153
1.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
121
4.32 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
121
4.31 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
428
15.3 IPS |
|
|
Text Classification (F32)
|
100% |
141
202.6 IPS |
|
|
Text Classification (F16)
|
100% |
141
203.3 IPS |
|
|
Text Classification (I8)
|
92% |
275
395.3 IPS |
|
|
Machine Translation (F32)
|
100% |
257
4.74 IPS |
|
|
Machine Translation (F16)
|
100% |
256
4.72 IPS |
|
|
Machine Translation (I8)
|
64% |
332
6.11 IPS |
