motorola moto g power - 2025
Geekbench ML Score
389
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 01 2025 08:02 PM |
| Views | 6 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
184
34.4 IPS |
|
|
Image Classification (F16)
|
100% |
183
34.2 IPS |
|
|
Image Classification (I8)
|
97% |
332
62.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
290
4.85 IPS |
|
|
Image Segmentation (F16)
|
100% |
285
4.76 IPS |
|
|
Image Segmentation (I8)
|
98% |
415
6.94 IPS |
|
|
Pose Estimation (F32)
|
100% |
389
0.47 IPS |
|
|
Pose Estimation (F16)
|
100% |
394
0.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
1795
2.17 IPS |
|
|
Object Detection (F32)
|
100% |
219
16.3 IPS |
|
|
Object Detection (F16)
|
100% |
220
16.4 IPS |
|
|
Object Detection (I8)
|
61% |
383
28.6 IPS |
|
|
Face Detection (F32)
|
100% |
432
5.14 IPS |
|
|
Face Detection (F16)
|
100% |
430
5.11 IPS |
|
|
Face Detection (I8)
|
86% |
885
10.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
420
3.26 IPS |
|
|
Depth Estimation (F16)
|
100% |
423
3.28 IPS |
|
|
Depth Estimation (I8)
|
95% |
853
6.62 IPS |
|
|
Style Transfer (F32)
|
100% |
658
0.87 IPS |
|
|
Style Transfer (F16)
|
100% |
666
0.88 IPS |
|
|
Style Transfer (I8)
|
98% |
2025
2.66 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
233
8.34 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
228
8.13 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
714
25.5 IPS |
|
|
Text Classification (F32)
|
100% |
240
345.1 IPS |
|
|
Text Classification (F16)
|
100% |
175
252.1 IPS |
|
|
Text Classification (I8)
|
92% |
203
291.4 IPS |
|
|
Machine Translation (F32)
|
100% |
407
7.50 IPS |
|
|
Machine Translation (F16)
|
100% |
440
8.10 IPS |
|
|
Machine Translation (I8)
|
64% |
209
3.84 IPS |
