motorola moto g54 5G
Geekbench ML Score
182
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 29 2025 07:58 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
68
12.7 IPS |
|
|
Image Classification (F16)
|
100% |
135
25.3 IPS |
|
|
Image Classification (I8)
|
0% |
126
23.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
94
1.57 IPS |
|
|
Image Segmentation (F16)
|
100% |
208
3.48 IPS |
|
|
Image Segmentation (I8)
|
98% |
209
3.49 IPS |
|
|
Pose Estimation (F32)
|
100% |
94
0.11 IPS |
|
|
Pose Estimation (F16)
|
100% |
182
0.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
187
0.23 IPS |
|
|
Object Detection (F32)
|
100% |
52
3.88 IPS |
|
|
Object Detection (F16)
|
100% |
111
8.31 IPS |
|
|
Object Detection (I8)
|
72% |
103
7.70 IPS |
|
|
Face Detection (F32)
|
100% |
178
2.12 IPS |
|
|
Face Detection (F16)
|
97% |
386
4.59 IPS |
|
|
Face Detection (I8)
|
86% |
388
4.61 IPS |
|
|
Depth Estimation (F32)
|
100% |
149
1.16 IPS |
|
|
Depth Estimation (F16)
|
100% |
294
2.28 IPS |
|
|
Depth Estimation (I8)
|
95% |
288
2.24 IPS |
|
|
Style Transfer (F32)
|
100% |
319
0.42 IPS |
|
|
Style Transfer (F16)
|
100% |
652
0.86 IPS |
|
|
Style Transfer (I8)
|
98% |
651
0.86 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
77
2.74 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
147
5.25 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
148
5.27 IPS |
|
|
Text Classification (F32)
|
100% |
138
198.6 IPS |
|
|
Text Classification (F16)
|
100% |
139
199.2 IPS |
|
|
Text Classification (I8)
|
92% |
281
403.6 IPS |
|
|
Machine Translation (F32)
|
100% |
248
4.56 IPS |
|
|
Machine Translation (F16)
|
100% |
247
4.54 IPS |
|
|
Machine Translation (I8)
|
64% |
327
6.01 IPS |
