motorola moto g power - 2025
Geekbench ML Score
192
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 01 2025 08:12 PM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | motorola moto g power - 2025 |
| Model ID | motorola moto g power - 2025 |
| Motherboard | vegas |
| 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 | 7.48 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
106
19.8 IPS |
|
|
Image Classification (F16)
|
100% |
188
35.2 IPS |
|
|
Image Classification (I8)
|
97% |
167
31.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
137
2.28 IPS |
|
|
Image Segmentation (F16)
|
100% |
241
4.02 IPS |
|
|
Image Segmentation (I8)
|
98% |
236
3.93 IPS |
|
|
Pose Estimation (F32)
|
100% |
93
0.11 IPS |
|
|
Pose Estimation (F16)
|
100% |
112
0.14 IPS |
|
|
Pose Estimation (I8)
|
100% |
111
0.13 IPS |
|
|
Object Detection (F32)
|
100% |
85
6.36 IPS |
|
|
Object Detection (F16)
|
100% |
135
10.1 IPS |
|
|
Object Detection (I8)
|
62% |
123
9.21 IPS |
|
|
Face Detection (F32)
|
100% |
314
3.74 IPS |
|
|
Face Detection (F16)
|
98% |
446
5.30 IPS |
|
|
Face Detection (I8)
|
86% |
433
5.15 IPS |
|
|
Depth Estimation (F32)
|
100% |
184
1.42 IPS |
|
|
Depth Estimation (F16)
|
100% |
242
1.87 IPS |
|
|
Depth Estimation (I8)
|
95% |
240
1.86 IPS |
|
|
Style Transfer (F32)
|
100% |
363
0.48 IPS |
|
|
Style Transfer (F16)
|
100% |
511
0.67 IPS |
|
|
Style Transfer (I8)
|
98% |
511
0.67 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
98
3.51 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
153
5.48 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
152
5.44 IPS |
|
|
Text Classification (F32)
|
100% |
134
192.4 IPS |
|
|
Text Classification (F16)
|
100% |
136
194.9 IPS |
|
|
Text Classification (I8)
|
92% |
250
359.8 IPS |
|
|
Machine Translation (F32)
|
100% |
230
4.24 IPS |
|
|
Machine Translation (F16)
|
100% |
230
4.24 IPS |
|
|
Machine Translation (I8)
|
64% |
248
4.57 IPS |
