motorola moto g54 5G
Geekbench ML Score
227
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 29 2025 08:09 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | motorola moto g54 5G |
| Model ID | motorola moto g54 5G |
| Motherboard | cancunf |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 7.43 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
181
33.8 IPS |
|
|
Image Classification (F16)
|
97% |
340
63.6 IPS |
|
|
Image Classification (I8)
|
97% |
22
4.07 IPS |
|
|
Image Segmentation (F32)
|
100% |
246
4.11 IPS |
|
|
Image Segmentation (F16)
|
100% |
625
10.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
24
0.40 IPS |
|
|
Pose Estimation (F32)
|
100% |
1001
1.21 IPS |
|
|
Pose Estimation (F16)
|
100% |
2182
2.64 IPS |
|
|
Pose Estimation (I8)
|
80% |
1192
1.44 IPS |
|
|
Object Detection (F32)
|
100% |
176
13.1 IPS |
|
|
Object Detection (F16)
|
100% |
322
24.0 IPS |
|
|
Object Detection (I8)
|
51% |
37
2.79 IPS |
|
|
Face Detection (F32)
|
100% |
604
7.18 IPS |
|
|
Face Detection (F16)
|
97% |
1142
13.6 IPS |
|
|
Face Detection (I8)
|
87% |
41
0.49 IPS |
|
|
Depth Estimation (F32)
|
98% |
672
5.21 IPS |
|
|
Depth Estimation (F16)
|
98% |
1513
11.7 IPS |
|
|
Depth Estimation (I8)
|
93% |
187
1.45 IPS |
|
|
Style Transfer (F32)
|
99% |
902
1.19 IPS |
|
|
Style Transfer (F16)
|
99% |
1254
1.65 IPS |
|
|
Style Transfer (I8)
|
98% |
1791
2.36 IPS |
|
|
Image Super-Resolution (F32)
|
98% |
459
16.4 IPS |
|
|
Image Super-Resolution (F16)
|
0
|
||
|
Image Super-Resolution (I8)
|
98% |
503
18.0 IPS |
|
|
Text Classification (F32)
|
36% |
39
56.2 IPS |
|
|
Text Classification (F16)
|
36% |
35
49.8 IPS |
|
|
Text Classification (I8)
|
94% |
72
103.0 IPS |
|
|
Machine Translation (F32)
|
100% |
150
2.76 IPS |
|
|
Machine Translation (F16)
|
100% |
252
4.63 IPS |
|
|
Machine Translation (I8)
|
57% |
198
3.64 IPS |
