motorola moto g stylus - 2025
Geekbench AI Score
138
Single Precision Score
139
Half Precision Score
391
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | December 27 2025 06:08 PM |
| Views | 1 |
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% |
80
15.0 IPS |
|
|
Image Classification (HP)
|
100% |
81
15.0 IPS |
|
|
Image Classification (Q)
|
99% |
256
47.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
110
1.79 IPS |
|
|
Image Segmentation (HP)
|
100% |
111
1.80 IPS |
|
|
Image Segmentation (Q)
|
98% |
300
4.88 IPS |
|
|
Pose Estimation (SP)
|
100% |
139
0.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
139
0.16 IPS |
|
|
Pose Estimation (Q)
|
98% |
574
0.67 IPS |
|
|
Object Detection (SP)
|
100% |
79
6.28 IPS |
|
|
Object Detection (HP)
|
100% |
79
6.29 IPS |
|
|
Object Detection (Q)
|
87% |
267
21.4 IPS |
|
|
Face Detection (SP)
|
100% |
232
2.75 IPS |
|
|
Face Detection (HP)
|
100% |
234
2.78 IPS |
|
|
Face Detection (Q)
|
97% |
619
7.39 IPS |
|
|
Depth Estimation (SP)
|
100% |
183
1.41 IPS |
|
|
Depth Estimation (HP)
|
99% |
183
1.41 IPS |
|
|
Depth Estimation (Q)
|
64% |
517
4.69 IPS |
|
|
Style Transfer (SP)
|
100% |
331
0.43 IPS |
|
|
Style Transfer (HP)
|
100% |
331
0.43 IPS |
|
|
Style Transfer (Q)
|
98% |
1059
1.36 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
86
3.19 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
86
3.19 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
332
12.3 IPS |
|
|
Text Classification (SP)
|
100% |
112
149.9 IPS |
|
|
Text Classification (HP)
|
100% |
113
150.9 IPS |
|
|
Text Classification (Q)
|
91% |
278
373.7 IPS |
|
|
Machine Translation (SP)
|
100% |
198
3.42 IPS |
|
|
Machine Translation (HP)
|
100% |
198
3.42 IPS |
|
|
Machine Translation (Q)
|
57% |
230
5.63 IPS |
