motorola motorola edge 20
Geekbench ML Score
555
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 04:54 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
296
55.4 IPS |
|
|
Image Classification (F16)
|
100% |
294
55.0 IPS |
|
|
Image Classification (I8)
|
97% |
669
125.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
341
5.70 IPS |
|
|
Image Segmentation (F16)
|
100% |
338
5.65 IPS |
|
|
Image Segmentation (I8)
|
98% |
487
8.14 IPS |
|
|
Pose Estimation (F32)
|
100% |
522
0.63 IPS |
|
|
Pose Estimation (F16)
|
100% |
523
0.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
2587
3.13 IPS |
|
|
Object Detection (F32)
|
100% |
283
21.1 IPS |
|
|
Object Detection (F16)
|
100% |
287
21.4 IPS |
|
|
Object Detection (I8)
|
61% |
698
52.1 IPS |
|
|
Face Detection (F32)
|
100% |
543
6.46 IPS |
|
|
Face Detection (F16)
|
100% |
546
6.49 IPS |
|
|
Face Detection (I8)
|
86% |
1379
16.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
528
4.10 IPS |
|
|
Depth Estimation (F16)
|
100% |
531
4.12 IPS |
|
|
Depth Estimation (I8)
|
95% |
1367
10.6 IPS |
|
|
Style Transfer (F32)
|
100% |
874
1.15 IPS |
|
|
Style Transfer (F16)
|
100% |
872
1.15 IPS |
|
|
Style Transfer (I8)
|
98% |
2247
2.96 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
354
12.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
356
12.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1197
42.7 IPS |
|
|
Text Classification (F32)
|
100% |
348
500.7 IPS |
|
|
Text Classification (F16)
|
100% |
381
547.9 IPS |
|
|
Text Classification (I8)
|
92% |
340
488.3 IPS |
|
|
Machine Translation (F32)
|
100% |
613
11.3 IPS |
|
|
Machine Translation (F16)
|
100% |
611
11.2 IPS |
|
|
Machine Translation (I8)
|
64% |
250
4.60 IPS |
