motorola moto g32
Geekbench AI Score
370
Single Precision Score
369
Half Precision Score
474
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Evropa |
| Upload Date | March 19 2025 06:34 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | motorola moto g32 |
| Model ID | motorola moto g32 |
| Motherboard | devon |
| 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 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
173
32.1 IPS |
|
|
Image Classification (HP)
|
100% |
170
31.6 IPS |
|
|
Image Classification (Q)
|
100% |
315
58.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
214
3.46 IPS |
|
|
Image Segmentation (HP)
|
100% |
216
3.51 IPS |
|
|
Image Segmentation (Q)
|
98% |
396
6.44 IPS |
|
|
Pose Estimation (SP)
|
100% |
813
0.95 IPS |
|
|
Pose Estimation (HP)
|
100% |
812
0.95 IPS |
|
|
Pose Estimation (Q)
|
84% |
699
0.83 IPS |
|
|
Object Detection (SP)
|
100% |
167
13.2 IPS |
|
|
Object Detection (HP)
|
100% |
167
13.3 IPS |
|
|
Object Detection (Q)
|
83% |
315
25.5 IPS |
|
|
Face Detection (SP)
|
100% |
460
5.46 IPS |
|
|
Face Detection (HP)
|
100% |
464
5.52 IPS |
|
|
Face Detection (Q)
|
95% |
731
8.73 IPS |
|
|
Depth Estimation (SP)
|
100% |
666
5.13 IPS |
|
|
Depth Estimation (HP)
|
99% |
678
5.23 IPS |
|
|
Depth Estimation (Q)
|
64% |
736
6.74 IPS |
|
|
Style Transfer (SP)
|
89% |
1415
1.84 IPS |
|
|
Style Transfer (HP)
|
89% |
1412
1.83 IPS |
|
|
Style Transfer (Q)
|
98% |
1883
2.43 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
351
13.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
352
13.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
413
15.3 IPS |
|
|
Text Classification (SP)
|
100% |
198
264.2 IPS |
|
|
Text Classification (HP)
|
100% |
194
258.8 IPS |
|
|
Text Classification (Q)
|
88% |
291
393.0 IPS |
|
|
Machine Translation (SP)
|
100% |
322
5.55 IPS |
|
|
Machine Translation (HP)
|
100% |
315
5.43 IPS |
|
|
Machine Translation (Q)
|
50% |
173
6.14 IPS |
