samsung SM-A166P
Geekbench ML Score
295
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 11 2025 01:59 PM |
| Views | 4 |
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% |
115
21.5 IPS |
|
|
Image Classification (F16)
|
100% |
346
64.7 IPS |
|
|
Image Classification (I8)
|
97% |
69
13.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
221
3.69 IPS |
|
|
Image Segmentation (F16)
|
100% |
400
6.69 IPS |
|
|
Image Segmentation (I8)
|
98% |
86
1.43 IPS |
|
|
Pose Estimation (F32)
|
100% |
844
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
1907
2.31 IPS |
|
|
Pose Estimation (I8)
|
87% |
1116
1.35 IPS |
|
|
Object Detection (F32)
|
100% |
141
10.5 IPS |
|
|
Object Detection (F16)
|
100% |
285
21.3 IPS |
|
|
Object Detection (I8)
|
51% |
86
6.41 IPS |
|
|
Face Detection (F32)
|
25% |
536
6.37 IPS |
|
|
Face Detection (F16)
|
25% |
801
9.52 IPS |
|
|
Face Detection (I8)
|
87% |
130
1.55 IPS |
|
|
Depth Estimation (F32)
|
100% |
342
2.65 IPS |
|
|
Depth Estimation (F16)
|
74% |
434
3.37 IPS |
|
|
Depth Estimation (I8)
|
93% |
330
2.56 IPS |
|
|
Style Transfer (F32)
|
100% |
673
0.89 IPS |
|
|
Style Transfer (F16)
|
100% |
1190
1.57 IPS |
|
|
Style Transfer (I8)
|
98% |
1527
2.01 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
359
12.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
771
27.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
386
13.8 IPS |
|
|
Text Classification (F32)
|
100% |
72
103.9 IPS |
|
|
Text Classification (F16)
|
100% |
80
114.4 IPS |
|
|
Text Classification (I8)
|
94% |
72
103.6 IPS |
|
|
Machine Translation (F32)
|
100% |
190
3.50 IPS |
|
|
Machine Translation (F16)
|
100% |
244
4.49 IPS |
|
|
Machine Translation (I8)
|
57% |
148
2.73 IPS |
