motorola moto g - 2025
Geekbench ML Score
389
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 23 2025 10:44 PM |
| Views | 13 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
186
34.9 IPS |
|
|
Image Classification (F16)
|
100% |
188
35.3 IPS |
|
|
Image Classification (I8)
|
97% |
338
63.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
289
4.83 IPS |
|
|
Image Segmentation (F16)
|
100% |
288
4.80 IPS |
|
|
Image Segmentation (I8)
|
98% |
404
6.75 IPS |
|
|
Pose Estimation (F32)
|
100% |
394
0.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
410
0.50 IPS |
|
|
Pose Estimation (I8)
|
100% |
1806
2.19 IPS |
|
|
Object Detection (F32)
|
100% |
213
15.9 IPS |
|
|
Object Detection (F16)
|
100% |
216
16.1 IPS |
|
|
Object Detection (I8)
|
61% |
411
30.7 IPS |
|
|
Face Detection (F32)
|
100% |
434
5.16 IPS |
|
|
Face Detection (F16)
|
100% |
436
5.19 IPS |
|
|
Face Detection (I8)
|
86% |
891
10.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
433
3.36 IPS |
|
|
Depth Estimation (F16)
|
100% |
432
3.35 IPS |
|
|
Depth Estimation (I8)
|
95% |
927
7.19 IPS |
|
|
Style Transfer (F32)
|
100% |
540
0.71 IPS |
|
|
Style Transfer (F16)
|
100% |
662
0.87 IPS |
|
|
Style Transfer (I8)
|
98% |
2016
2.65 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
212
7.58 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
211
7.54 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
671
24.0 IPS |
|
|
Text Classification (F32)
|
100% |
240
345.6 IPS |
|
|
Text Classification (F16)
|
100% |
233
334.4 IPS |
|
|
Text Classification (I8)
|
92% |
189
272.0 IPS |
|
|
Machine Translation (F32)
|
100% |
378
6.96 IPS |
|
|
Machine Translation (F16)
|
100% |
403
7.42 IPS |
|
|
Machine Translation (I8)
|
64% |
234
4.30 IPS |
