samsung SM-A166P
Geekbench ML Score
298
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 10:04 PM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-A166P |
| Model ID | samsung SM-A166P |
| Motherboard | a16xm |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 3.35 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
119
22.2 IPS |
|
|
Image Classification (F16)
|
100% |
347
65.0 IPS |
|
|
Image Classification (I8)
|
97% |
70
13.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
225
3.76 IPS |
|
|
Image Segmentation (F16)
|
100% |
400
6.67 IPS |
|
|
Image Segmentation (I8)
|
98% |
86
1.43 IPS |
|
|
Pose Estimation (F32)
|
100% |
846
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
1907
2.31 IPS |
|
|
Pose Estimation (I8)
|
87% |
1143
1.38 IPS |
|
|
Object Detection (F32)
|
100% |
139
10.4 IPS |
|
|
Object Detection (F16)
|
100% |
296
22.1 IPS |
|
|
Object Detection (I8)
|
51% |
89
6.66 IPS |
|
|
Face Detection (F32)
|
25% |
536
6.37 IPS |
|
|
Face Detection (F16)
|
25% |
778
9.25 IPS |
|
|
Face Detection (I8)
|
87% |
96
1.15 IPS |
|
|
Depth Estimation (F32)
|
100% |
354
2.74 IPS |
|
|
Depth Estimation (F16)
|
74% |
447
3.46 IPS |
|
|
Depth Estimation (I8)
|
93% |
346
2.69 IPS |
|
|
Style Transfer (F32)
|
100% |
679
0.89 IPS |
|
|
Style Transfer (F16)
|
100% |
1210
1.59 IPS |
|
|
Style Transfer (I8)
|
98% |
1538
2.02 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
359
12.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
780
27.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
450
16.1 IPS |
|
|
Text Classification (F32)
|
100% |
76
108.7 IPS |
|
|
Text Classification (F16)
|
100% |
83
118.6 IPS |
|
|
Text Classification (I8)
|
94% |
64
92.5 IPS |
|
|
Machine Translation (F32)
|
100% |
204
3.76 IPS |
|
|
Machine Translation (F16)
|
100% |
251
4.62 IPS |
|
|
Machine Translation (I8)
|
57% |
155
2.85 IPS |
