motorola moto g - 2025
Geekbench ML Score
278
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 23 2025 10:27 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | motorola moto g - 2025 |
| Model ID | motorola moto g - 2025 |
| Motherboard | kansas |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 3.56 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
132
24.7 IPS |
|
|
Image Classification (F16)
|
100% |
439
82.1 IPS |
|
|
Image Classification (I8)
|
97% |
23
4.39 IPS |
|
|
Image Segmentation (F32)
|
100% |
251
4.18 IPS |
|
|
Image Segmentation (F16)
|
100% |
486
8.12 IPS |
|
|
Image Segmentation (I8)
|
98% |
25
0.41 IPS |
|
|
Pose Estimation (F32)
|
100% |
901
1.09 IPS |
|
|
Pose Estimation (F16)
|
100% |
2086
2.53 IPS |
|
|
Pose Estimation (I8)
|
87% |
1225
1.48 IPS |
|
|
Object Detection (F32)
|
100% |
160
11.9 IPS |
|
|
Object Detection (F16)
|
100% |
340
25.4 IPS |
|
|
Object Detection (I8)
|
51% |
32
2.36 IPS |
|
|
Face Detection (F32)
|
25% |
712
8.47 IPS |
|
|
Face Detection (F16)
|
25% |
1016
12.1 IPS |
|
|
Face Detection (I8)
|
87% |
37
0.44 IPS |
|
|
Depth Estimation (F32)
|
100% |
385
2.98 IPS |
|
|
Depth Estimation (F16)
|
74% |
487
3.78 IPS |
|
|
Depth Estimation (I8)
|
93% |
152
1.18 IPS |
|
|
Style Transfer (F32)
|
100% |
723
0.95 IPS |
|
|
Style Transfer (F16)
|
100% |
1296
1.70 IPS |
|
|
Style Transfer (I8)
|
98% |
1706
2.24 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
388
13.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
906
32.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
471
16.8 IPS |
|
|
Text Classification (F32)
|
100% |
88
126.2 IPS |
|
|
Text Classification (F16)
|
100% |
105
150.3 IPS |
|
|
Text Classification (I8)
|
94% |
70
100.2 IPS |
|
|
Machine Translation (F32)
|
100% |
235
4.32 IPS |
|
|
Machine Translation (F16)
|
100% |
236
4.35 IPS |
|
|
Machine Translation (I8)
|
57% |
178
3.27 IPS |
