samsung SM-A166P
Geekbench ML Score
297
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 09:22 PM |
| Views | 5 |
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% |
348
65.0 IPS |
|
|
Image Classification (I8)
|
97% |
69
12.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
220
3.67 IPS |
|
|
Image Segmentation (F16)
|
100% |
399
6.66 IPS |
|
|
Image Segmentation (I8)
|
98% |
87
1.45 IPS |
|
|
Pose Estimation (F32)
|
100% |
844
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
1893
2.29 IPS |
|
|
Pose Estimation (I8)
|
87% |
1103
1.34 IPS |
|
|
Object Detection (F32)
|
100% |
139
10.4 IPS |
|
|
Object Detection (F16)
|
100% |
297
22.1 IPS |
|
|
Object Detection (I8)
|
51% |
92
6.85 IPS |
|
|
Face Detection (F32)
|
25% |
530
6.30 IPS |
|
|
Face Detection (F16)
|
25% |
797
9.48 IPS |
|
|
Face Detection (I8)
|
87% |
136
1.62 IPS |
|
|
Depth Estimation (F32)
|
100% |
349
2.71 IPS |
|
|
Depth Estimation (F16)
|
74% |
443
3.44 IPS |
|
|
Depth Estimation (I8)
|
93% |
345
2.68 IPS |
|
|
Style Transfer (F32)
|
100% |
683
0.90 IPS |
|
|
Style Transfer (F16)
|
100% |
1192
1.57 IPS |
|
|
Style Transfer (I8)
|
98% |
1520
2.00 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
373
13.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
768
27.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
390
13.9 IPS |
|
|
Text Classification (F32)
|
100% |
71
101.7 IPS |
|
|
Text Classification (F16)
|
100% |
79
113.7 IPS |
|
|
Text Classification (I8)
|
94% |
71
101.9 IPS |
|
|
Machine Translation (F32)
|
100% |
195
3.60 IPS |
|
|
Machine Translation (F16)
|
100% |
244
4.49 IPS |
|
|
Machine Translation (I8)
|
57% |
148
2.73 IPS |
