motorola moto g54 5G
Geekbench ML Score
434
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 29 2024 08:30 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| 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 | 11.35 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
196
36.6 IPS |
|
|
Image Classification (F16)
|
100% |
201
37.6 IPS |
|
|
Image Classification (I8)
|
97% |
440
82.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
295
4.92 IPS |
|
|
Image Segmentation (F16)
|
100% |
298
4.98 IPS |
|
|
Image Segmentation (I8)
|
98% |
506
8.46 IPS |
|
|
Pose Estimation (F32)
|
100% |
421
0.51 IPS |
|
|
Pose Estimation (F16)
|
100% |
429
0.52 IPS |
|
|
Pose Estimation (I8)
|
100% |
1975
2.39 IPS |
|
|
Object Detection (F32)
|
100% |
225
16.8 IPS |
|
|
Object Detection (F16)
|
100% |
222
16.6 IPS |
|
|
Object Detection (I8)
|
61% |
493
36.8 IPS |
|
|
Face Detection (F32)
|
100% |
471
5.60 IPS |
|
|
Face Detection (F16)
|
100% |
476
5.65 IPS |
|
|
Face Detection (I8)
|
86% |
1088
12.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
463
3.59 IPS |
|
|
Depth Estimation (F16)
|
100% |
465
3.61 IPS |
|
|
Depth Estimation (I8)
|
95% |
1150
8.92 IPS |
|
|
Style Transfer (F32)
|
100% |
784
1.03 IPS |
|
|
Style Transfer (F16)
|
100% |
783
1.03 IPS |
|
|
Style Transfer (I8)
|
98% |
2076
2.73 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
253
9.02 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
249
8.89 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
689
24.6 IPS |
|
|
Text Classification (F32)
|
100% |
228
328.2 IPS |
|
|
Text Classification (F16)
|
100% |
222
319.3 IPS |
|
|
Text Classification (I8)
|
92% |
187
268.4 IPS |
|
|
Machine Translation (F32)
|
100% |
493
9.07 IPS |
|
|
Machine Translation (F16)
|
100% |
482
8.87 IPS |
|
|
Machine Translation (I8)
|
64% |
262
4.83 IPS |
