samsung SM-A166P
Geekbench ML Score
196
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 11 2025 11:35 AM |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
117
21.8 IPS |
|
|
Image Classification (F16)
|
100% |
69
12.9 IPS |
|
|
Image Classification (I8)
|
97% |
100
18.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
190
3.17 IPS |
|
|
Image Segmentation (F16)
|
100% |
183
3.06 IPS |
|
|
Image Segmentation (I8)
|
98% |
261
4.36 IPS |
|
|
Pose Estimation (F32)
|
100% |
349
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
344
0.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
1375
1.66 IPS |
|
|
Object Detection (F32)
|
100% |
101
7.51 IPS |
|
|
Object Detection (F16)
|
100% |
99
7.40 IPS |
|
|
Object Detection (I8)
|
61% |
159
11.9 IPS |
|
|
Face Detection (F32)
|
100% |
279
3.32 IPS |
|
|
Face Detection (F16)
|
100% |
299
3.55 IPS |
|
|
Face Detection (I8)
|
86% |
428
5.09 IPS |
|
|
Depth Estimation (F32)
|
100% |
279
2.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
311
2.41 IPS |
|
|
Depth Estimation (I8)
|
95% |
560
4.35 IPS |
|
|
Style Transfer (F32)
|
100% |
561
0.74 IPS |
|
|
Style Transfer (F16)
|
100% |
574
0.76 IPS |
|
|
Style Transfer (I8)
|
98% |
1742
2.29 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
143
5.10 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
143
5.12 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
327
11.7 IPS |
|
|
Text Classification (F32)
|
100% |
32
45.9 IPS |
|
|
Text Classification (F16)
|
100% |
40
57.6 IPS |
|
|
Text Classification (I8)
|
92% |
41
58.7 IPS |
|
|
Machine Translation (F32)
|
100% |
85
1.57 IPS |
|
|
Machine Translation (F16)
|
100% |
92
1.70 IPS |
|
|
Machine Translation (I8)
|
64% |
119
2.19 IPS |
