motorola moto g52
Geekbench ML Score
173
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 27 2024 02:33 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | motorola moto g52 |
| Model ID | motorola moto g52 |
| Motherboard | rhode |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.53 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
58
10.8 IPS |
|
|
Image Classification (F16)
|
100% |
169
31.6 IPS |
|
|
Image Classification (I8)
|
97% |
67
12.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
212
3.54 IPS |
|
|
Image Segmentation (F16)
|
100% |
210
3.51 IPS |
|
|
Image Segmentation (I8)
|
98% |
181
3.02 IPS |
|
|
Pose Estimation (F32)
|
100% |
314
0.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
255
0.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
833
1.01 IPS |
|
|
Object Detection (F32)
|
100% |
167
12.5 IPS |
|
|
Object Detection (F16)
|
100% |
77
5.74 IPS |
|
|
Object Detection (I8)
|
61% |
93
6.95 IPS |
|
|
Face Detection (F32)
|
100% |
310
3.69 IPS |
|
|
Face Detection (F16)
|
100% |
214
2.55 IPS |
|
|
Face Detection (I8)
|
86% |
604
7.18 IPS |
|
|
Depth Estimation (F32)
|
100% |
200
1.55 IPS |
|
|
Depth Estimation (F16)
|
100% |
315
2.44 IPS |
|
|
Depth Estimation (I8)
|
95% |
291
2.25 IPS |
|
|
Style Transfer (F32)
|
100% |
422
0.56 IPS |
|
|
Style Transfer (F16)
|
100% |
404
0.53 IPS |
|
|
Style Transfer (I8)
|
98% |
1176
1.55 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
119
4.24 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
202
7.20 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
419
15.0 IPS |
|
|
Text Classification (F32)
|
100% |
14
19.8 IPS |
|
|
Text Classification (F16)
|
100% |
14
19.8 IPS |
|
|
Text Classification (I8)
|
92% |
15
21.9 IPS |
|
|
Machine Translation (F32)
|
100% |
392
7.22 IPS |
|
|
Machine Translation (F16)
|
100% |
218
4.02 IPS |
|
|
Machine Translation (I8)
|
64% |
93
1.70 IPS |
