motorola moto g54 5G
Geekbench ML Score
193
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 16 2025 07:25 AM |
| Views | 4 |
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% |
181
33.8 IPS |
|
|
Image Classification (F16)
|
97% |
340
63.7 IPS |
|
|
Image Classification (I8)
|
97% |
12
2.17 IPS |
|
|
Image Segmentation (F32)
|
100% |
243
4.06 IPS |
|
|
Image Segmentation (F16)
|
100% |
611
10.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
13
0.21 IPS |
|
|
Pose Estimation (F32)
|
100% |
1003
1.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
2187
2.65 IPS |
|
|
Pose Estimation (I8)
|
80% |
1037
1.26 IPS |
|
|
Object Detection (F32)
|
100% |
170
12.7 IPS |
|
|
Object Detection (F16)
|
100% |
316
23.6 IPS |
|
|
Object Detection (I8)
|
51% |
16
1.22 IPS |
|
|
Face Detection (F32)
|
100% |
581
6.90 IPS |
|
|
Face Detection (F16)
|
97% |
1084
12.9 IPS |
|
|
Face Detection (I8)
|
87% |
19
0.23 IPS |
|
|
Depth Estimation (F32)
|
98% |
671
5.20 IPS |
|
|
Depth Estimation (F16)
|
98% |
1513
11.7 IPS |
|
|
Depth Estimation (I8)
|
93% |
104
0.81 IPS |
|
|
Style Transfer (F32)
|
99% |
879
1.16 IPS |
|
|
Style Transfer (F16)
|
99% |
1204
1.58 IPS |
|
|
Style Transfer (I8)
|
98% |
1625
2.14 IPS |
|
|
Image Super-Resolution (F32)
|
98% |
453
16.2 IPS |
|
|
Image Super-Resolution (F16)
|
0
|
||
|
Image Super-Resolution (I8)
|
98% |
439
15.7 IPS |
|
|
Text Classification (F32)
|
36% |
37
52.5 IPS |
|
|
Text Classification (F16)
|
36% |
33
47.5 IPS |
|
|
Text Classification (I8)
|
94% |
58
83.9 IPS |
|
|
Machine Translation (F32)
|
100% |
141
2.60 IPS |
|
|
Machine Translation (F16)
|
100% |
224
4.13 IPS |
|
|
Machine Translation (I8)
|
57% |
156
2.86 IPS |
