samsung SM-A166P
Geekbench ML Score
296
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 09:37 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% |
117
21.9 IPS |
|
|
Image Classification (F16)
|
100% |
349
65.3 IPS |
|
|
Image Classification (I8)
|
97% |
69
13.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
219
3.65 IPS |
|
|
Image Segmentation (F16)
|
100% |
401
6.69 IPS |
|
|
Image Segmentation (I8)
|
98% |
86
1.43 IPS |
|
|
Pose Estimation (F32)
|
100% |
846
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
1904
2.31 IPS |
|
|
Pose Estimation (I8)
|
87% |
1128
1.37 IPS |
|
|
Object Detection (F32)
|
100% |
138
10.3 IPS |
|
|
Object Detection (F16)
|
100% |
294
21.9 IPS |
|
|
Object Detection (I8)
|
51% |
89
6.64 IPS |
|
|
Face Detection (F32)
|
25% |
529
6.29 IPS |
|
|
Face Detection (F16)
|
25% |
767
9.12 IPS |
|
|
Face Detection (I8)
|
87% |
131
1.56 IPS |
|
|
Depth Estimation (F32)
|
100% |
345
2.67 IPS |
|
|
Depth Estimation (F16)
|
74% |
439
3.40 IPS |
|
|
Depth Estimation (I8)
|
93% |
332
2.57 IPS |
|
|
Style Transfer (F32)
|
100% |
671
0.88 IPS |
|
|
Style Transfer (F16)
|
100% |
1192
1.57 IPS |
|
|
Style Transfer (I8)
|
98% |
1538
2.02 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
354
12.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
770
27.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
384
13.7 IPS |
|
|
Text Classification (F32)
|
100% |
72
102.8 IPS |
|
|
Text Classification (F16)
|
100% |
83
119.6 IPS |
|
|
Text Classification (I8)
|
94% |
71
102.6 IPS |
|
|
Machine Translation (F32)
|
100% |
194
3.57 IPS |
|
|
Machine Translation (F16)
|
100% |
242
4.44 IPS |
|
|
Machine Translation (I8)
|
57% |
148
2.73 IPS |
