motorola moto g stylus - 2025
Geekbench AI Score
138
Single Precision Score
139
Half Precision Score
392
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | December 27 2025 05:38 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | motorola moto g stylus - 2025 |
| Model ID | motorola moto g stylus - 2025 |
| Motherboard | mona |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.24 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
81
15.0 IPS |
|
|
Image Classification (HP)
|
100% |
81
15.0 IPS |
|
|
Image Classification (Q)
|
99% |
256
47.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
110
1.79 IPS |
|
|
Image Segmentation (HP)
|
100% |
111
1.80 IPS |
|
|
Image Segmentation (Q)
|
98% |
300
4.89 IPS |
|
|
Pose Estimation (SP)
|
100% |
139
0.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
139
0.16 IPS |
|
|
Pose Estimation (Q)
|
98% |
575
0.67 IPS |
|
|
Object Detection (SP)
|
100% |
79
6.30 IPS |
|
|
Object Detection (HP)
|
100% |
80
6.32 IPS |
|
|
Object Detection (Q)
|
87% |
269
21.5 IPS |
|
|
Face Detection (SP)
|
100% |
230
2.73 IPS |
|
|
Face Detection (HP)
|
100% |
234
2.78 IPS |
|
|
Face Detection (Q)
|
97% |
622
7.42 IPS |
|
|
Depth Estimation (SP)
|
100% |
182
1.40 IPS |
|
|
Depth Estimation (HP)
|
99% |
182
1.40 IPS |
|
|
Depth Estimation (Q)
|
64% |
516
4.68 IPS |
|
|
Style Transfer (SP)
|
100% |
332
0.43 IPS |
|
|
Style Transfer (HP)
|
100% |
331
0.43 IPS |
|
|
Style Transfer (Q)
|
98% |
1057
1.36 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
87
3.20 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
86
3.19 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
334
12.4 IPS |
|
|
Text Classification (SP)
|
100% |
113
150.9 IPS |
|
|
Text Classification (HP)
|
100% |
113
151.4 IPS |
|
|
Text Classification (Q)
|
91% |
278
373.5 IPS |
|
|
Machine Translation (SP)
|
100% |
199
3.42 IPS |
|
|
Machine Translation (HP)
|
100% |
198
3.41 IPS |
|
|
Machine Translation (Q)
|
57% |
231
5.64 IPS |
