samsung SM-A166P
Geekbench ML Score
293
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 06:22 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% |
349
65.3 IPS |
|
|
Image Classification (I8)
|
97% |
49
9.09 IPS |
|
|
Image Segmentation (F32)
|
100% |
221
3.69 IPS |
|
|
Image Segmentation (F16)
|
100% |
401
6.70 IPS |
|
|
Image Segmentation (I8)
|
98% |
86
1.43 IPS |
|
|
Pose Estimation (F32)
|
100% |
847
1.03 IPS |
|
|
Pose Estimation (F16)
|
100% |
1899
2.30 IPS |
|
|
Pose Estimation (I8)
|
87% |
1161
1.41 IPS |
|
|
Object Detection (F32)
|
100% |
139
10.4 IPS |
|
|
Object Detection (F16)
|
100% |
294
21.9 IPS |
|
|
Object Detection (I8)
|
51% |
90
6.72 IPS |
|
|
Face Detection (F32)
|
25% |
539
6.41 IPS |
|
|
Face Detection (F16)
|
25% |
772
9.18 IPS |
|
|
Face Detection (I8)
|
87% |
130
1.55 IPS |
|
|
Depth Estimation (F32)
|
100% |
341
2.65 IPS |
|
|
Depth Estimation (F16)
|
74% |
446
3.46 IPS |
|
|
Depth Estimation (I8)
|
93% |
333
2.59 IPS |
|
|
Style Transfer (F32)
|
100% |
672
0.88 IPS |
|
|
Style Transfer (F16)
|
100% |
1193
1.57 IPS |
|
|
Style Transfer (I8)
|
98% |
1495
1.97 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
366
13.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
772
27.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
380
13.6 IPS |
|
|
Text Classification (F32)
|
100% |
72
102.9 IPS |
|
|
Text Classification (F16)
|
100% |
82
118.4 IPS |
|
|
Text Classification (I8)
|
94% |
70
101.0 IPS |
|
|
Machine Translation (F32)
|
100% |
199
3.67 IPS |
|
|
Machine Translation (F16)
|
100% |
243
4.47 IPS |
|
|
Machine Translation (I8)
|
57% |
149
2.74 IPS |
