motorola moto g54 5G
Geekbench ML Score
397
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 29 2025 07:42 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
181
33.8 IPS |
|
|
Image Classification (F16)
|
100% |
177
33.2 IPS |
|
|
Image Classification (I8)
|
97% |
351
65.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
263
4.39 IPS |
|
|
Image Segmentation (F16)
|
100% |
267
4.47 IPS |
|
|
Image Segmentation (I8)
|
98% |
455
7.61 IPS |
|
|
Pose Estimation (F32)
|
100% |
378
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
373
0.45 IPS |
|
|
Pose Estimation (I8)
|
100% |
1685
2.04 IPS |
|
|
Object Detection (F32)
|
100% |
198
14.8 IPS |
|
|
Object Detection (F16)
|
100% |
202
15.1 IPS |
|
|
Object Detection (I8)
|
61% |
419
31.3 IPS |
|
|
Face Detection (F32)
|
100% |
424
5.05 IPS |
|
|
Face Detection (F16)
|
100% |
428
5.09 IPS |
|
|
Face Detection (I8)
|
86% |
955
11.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
424
3.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
416
3.23 IPS |
|
|
Depth Estimation (I8)
|
95% |
984
7.63 IPS |
|
|
Style Transfer (F32)
|
100% |
725
0.95 IPS |
|
|
Style Transfer (F16)
|
100% |
734
0.97 IPS |
|
|
Style Transfer (I8)
|
98% |
1999
2.63 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
246
8.79 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
246
8.80 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
698
24.9 IPS |
|
|
Text Classification (F32)
|
100% |
218
313.2 IPS |
|
|
Text Classification (F16)
|
100% |
218
313.8 IPS |
|
|
Text Classification (I8)
|
92% |
180
258.8 IPS |
|
|
Machine Translation (F32)
|
100% |
467
8.59 IPS |
|
|
Machine Translation (F16)
|
100% |
462
8.49 IPS |
|
|
Machine Translation (I8)
|
64% |
265
4.87 IPS |
