samsung SM-A166P
Geekbench ML Score
282
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 08 2025 11:57 PM |
| Views | 3 |
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% |
116
21.6 IPS |
|
|
Image Classification (F16)
|
100% |
343
64.2 IPS |
|
|
Image Classification (I8)
|
97% |
60
11.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
219
3.66 IPS |
|
|
Image Segmentation (F16)
|
100% |
391
6.52 IPS |
|
|
Image Segmentation (I8)
|
98% |
75
1.25 IPS |
|
|
Pose Estimation (F32)
|
100% |
842
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
1899
2.30 IPS |
|
|
Pose Estimation (I8)
|
87% |
1007
1.22 IPS |
|
|
Object Detection (F32)
|
100% |
137
10.2 IPS |
|
|
Object Detection (F16)
|
100% |
280
20.9 IPS |
|
|
Object Detection (I8)
|
51% |
79
5.92 IPS |
|
|
Face Detection (F32)
|
25% |
528
6.28 IPS |
|
|
Face Detection (F16)
|
25% |
764
9.09 IPS |
|
|
Face Detection (I8)
|
87% |
119
1.42 IPS |
|
|
Depth Estimation (F32)
|
100% |
335
2.60 IPS |
|
|
Depth Estimation (F16)
|
74% |
416
3.23 IPS |
|
|
Depth Estimation (I8)
|
93% |
308
2.39 IPS |
|
|
Style Transfer (F32)
|
100% |
659
0.87 IPS |
|
|
Style Transfer (F16)
|
100% |
1151
1.51 IPS |
|
|
Style Transfer (I8)
|
98% |
1385
1.82 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
362
12.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
767
27.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
362
12.9 IPS |
|
|
Text Classification (F32)
|
100% |
70
100.5 IPS |
|
|
Text Classification (F16)
|
100% |
81
116.9 IPS |
|
|
Text Classification (I8)
|
94% |
65
94.0 IPS |
|
|
Machine Translation (F32)
|
100% |
188
3.47 IPS |
|
|
Machine Translation (F16)
|
100% |
223
4.10 IPS |
|
|
Machine Translation (I8)
|
57% |
139
2.55 IPS |
