motorola moto g54 5G
Geekbench ML Score
433
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 29 2025 08:15 AM |
| Views | 2 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
196
36.6 IPS |
|
|
Image Classification (F16)
|
100% |
198
37.1 IPS |
|
|
Image Classification (I8)
|
97% |
422
78.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
295
4.93 IPS |
|
|
Image Segmentation (F16)
|
100% |
292
4.88 IPS |
|
|
Image Segmentation (I8)
|
98% |
493
8.23 IPS |
|
|
Pose Estimation (F32)
|
100% |
419
0.51 IPS |
|
|
Pose Estimation (F16)
|
100% |
401
0.49 IPS |
|
|
Pose Estimation (I8)
|
100% |
1939
2.35 IPS |
|
|
Object Detection (F32)
|
100% |
215
16.0 IPS |
|
|
Object Detection (F16)
|
100% |
218
16.3 IPS |
|
|
Object Detection (I8)
|
61% |
428
32.0 IPS |
|
|
Face Detection (F32)
|
100% |
452
5.38 IPS |
|
|
Face Detection (F16)
|
100% |
458
5.45 IPS |
|
|
Face Detection (I8)
|
86% |
1028
12.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
455
3.53 IPS |
|
|
Depth Estimation (F16)
|
100% |
453
3.52 IPS |
|
|
Depth Estimation (I8)
|
95% |
1092
8.47 IPS |
|
|
Style Transfer (F32)
|
100% |
783
1.03 IPS |
|
|
Style Transfer (F16)
|
100% |
785
1.03 IPS |
|
|
Style Transfer (I8)
|
98% |
2121
2.79 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
264
9.44 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
252
8.98 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
730
26.1 IPS |
|
|
Text Classification (F32)
|
100% |
251
360.0 IPS |
|
|
Text Classification (F16)
|
100% |
243
349.9 IPS |
|
|
Text Classification (I8)
|
92% |
212
304.9 IPS |
|
|
Machine Translation (F32)
|
100% |
472
8.69 IPS |
|
|
Machine Translation (F16)
|
100% |
509
9.37 IPS |
|
|
Machine Translation (I8)
|
64% |
303
5.57 IPS |
