motorola moto g54 5G
Geekbench ML Score
228
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 29 2024 12:08 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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% |
182
34.0 IPS |
|
|
Image Classification (F16)
|
97% |
344
64.5 IPS |
|
|
Image Classification (I8)
|
97% |
25
4.64 IPS |
|
|
Image Segmentation (F32)
|
100% |
246
4.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
631
10.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
26
0.44 IPS |
|
|
Pose Estimation (F32)
|
100% |
1004
1.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
2196
2.66 IPS |
|
|
Pose Estimation (I8)
|
80% |
1211
1.47 IPS |
|
|
Object Detection (F32)
|
100% |
176
13.1 IPS |
|
|
Object Detection (F16)
|
100% |
322
24.0 IPS |
|
|
Object Detection (I8)
|
51% |
34
2.53 IPS |
|
|
Face Detection (F32)
|
100% |
605
7.19 IPS |
|
|
Face Detection (F16)
|
97% |
1149
13.7 IPS |
|
|
Face Detection (I8)
|
87% |
33
0.39 IPS |
|
|
Depth Estimation (F32)
|
98% |
675
5.23 IPS |
|
|
Depth Estimation (F16)
|
98% |
1523
11.8 IPS |
|
|
Depth Estimation (I8)
|
93% |
188
1.45 IPS |
|
|
Style Transfer (F32)
|
99% |
910
1.20 IPS |
|
|
Style Transfer (F16)
|
99% |
1272
1.67 IPS |
|
|
Style Transfer (I8)
|
98% |
1803
2.37 IPS |
|
|
Image Super-Resolution (F32)
|
98% |
460
16.4 IPS |
|
|
Image Super-Resolution (F16)
|
0
|
||
|
Image Super-Resolution (I8)
|
98% |
505
18.0 IPS |
|
|
Text Classification (F32)
|
36% |
40
58.1 IPS |
|
|
Text Classification (F16)
|
36% |
37
53.8 IPS |
|
|
Text Classification (I8)
|
94% |
70
100.7 IPS |
|
|
Machine Translation (F32)
|
100% |
154
2.83 IPS |
|
|
Machine Translation (F16)
|
100% |
252
4.64 IPS |
|
|
Machine Translation (I8)
|
57% |
198
3.64 IPS |
