motorola moto g62 5G
Geekbench AI Score
500
Single Precision Score
493
Half Precision Score
923
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | NBH |
| Upload Date | April 25 2025 12:09 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | motorola moto g62 5G |
| Model ID | motorola moto g62 5G |
| Motherboard | rhodei |
| 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 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 5.35 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
240
44.5 IPS |
|
|
Image Classification (HP)
|
100% |
239
44.5 IPS |
|
|
Image Classification (Q)
|
100% |
730
135.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
312
5.06 IPS |
|
|
Image Segmentation (HP)
|
100% |
312
5.06 IPS |
|
|
Image Segmentation (Q)
|
98% |
814
13.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1186
1.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
1070
1.25 IPS |
|
|
Pose Estimation (Q)
|
84% |
1497
1.78 IPS |
|
|
Object Detection (SP)
|
100% |
210
16.7 IPS |
|
|
Object Detection (HP)
|
100% |
210
16.7 IPS |
|
|
Object Detection (Q)
|
83% |
613
49.5 IPS |
|
|
Face Detection (SP)
|
100% |
710
8.43 IPS |
|
|
Face Detection (HP)
|
100% |
711
8.45 IPS |
|
|
Face Detection (Q)
|
95% |
1490
17.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
935
7.21 IPS |
|
|
Depth Estimation (HP)
|
99% |
937
7.22 IPS |
|
|
Depth Estimation (Q)
|
64% |
1342
12.3 IPS |
|
|
Style Transfer (SP)
|
89% |
1729
2.24 IPS |
|
|
Style Transfer (HP)
|
89% |
1732
2.25 IPS |
|
|
Style Transfer (Q)
|
98% |
3319
4.28 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
467
17.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
468
17.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
822
30.5 IPS |
|
|
Text Classification (SP)
|
100% |
240
320.1 IPS |
|
|
Text Classification (HP)
|
100% |
236
315.4 IPS |
|
|
Text Classification (Q)
|
88% |
476
642.1 IPS |
|
|
Machine Translation (SP)
|
100% |
410
7.06 IPS |
|
|
Machine Translation (HP)
|
100% |
400
6.90 IPS |
|
|
Machine Translation (Q)
|
50% |
317
11.2 IPS |
