motorola moto g stylus 5G - 2023
Geekbench AI Score
160
Single Precision Score
225
Half Precision Score
226
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | qwertyyfluff |
| Upload Date | February 26 2025 09:11 PM |
| Views | 18 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | motorola moto g stylus 5G - 2023 |
| Model ID | motorola moto g stylus 5G - 2023 |
| Motherboard | genevn |
| 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 @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 5.37 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
124
23.1 IPS |
|
|
Image Classification (HP)
|
100% |
222
41.3 IPS |
|
|
Image Classification (Q)
|
97% |
205
38.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
185
2.99 IPS |
|
|
Image Segmentation (HP)
|
100% |
234
3.79 IPS |
|
|
Image Segmentation (Q)
|
98% |
227
3.70 IPS |
|
|
Pose Estimation (SP)
|
100% |
177
0.21 IPS |
|
|
Pose Estimation (HP)
|
100% |
283
0.33 IPS |
|
|
Pose Estimation (Q)
|
95% |
284
0.33 IPS |
|
|
Object Detection (SP)
|
100% |
98
7.79 IPS |
|
|
Object Detection (HP)
|
100% |
149
11.8 IPS |
|
|
Object Detection (Q)
|
89% |
142
11.4 IPS |
|
|
Face Detection (SP)
|
100% |
367
4.36 IPS |
|
|
Face Detection (HP)
|
100% |
508
6.03 IPS |
|
|
Face Detection (Q)
|
97% |
480
5.72 IPS |
|
|
Depth Estimation (SP)
|
100% |
274
2.11 IPS |
|
|
Depth Estimation (HP)
|
99% |
446
3.44 IPS |
|
|
Depth Estimation (Q)
|
63% |
368
3.46 IPS |
|
|
Style Transfer (SP)
|
100% |
603
0.77 IPS |
|
|
Style Transfer (HP)
|
100% |
1203
1.55 IPS |
|
|
Style Transfer (Q)
|
98% |
1217
1.57 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
112
4.14 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
138
5.09 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
135
5.02 IPS |
|
|
Text Classification (SP)
|
100% |
48
63.5 IPS |
|
|
Text Classification (HP)
|
100% |
48
64.6 IPS |
|
|
Text Classification (Q)
|
91% |
92
124.3 IPS |
|
|
Machine Translation (SP)
|
100% |
85
1.46 IPS |
|
|
Machine Translation (HP)
|
100% |
85
1.46 IPS |
|
|
Machine Translation (Q)
|
57% |
71
1.74 IPS |
