samsung SM-A166P
Geekbench ML Score
226
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 04 2025 08:34 PM |
| Views | 2 |
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 | 7.27 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
129
24.2 IPS |
|
|
Image Classification (F16)
|
100% |
101
18.9 IPS |
|
|
Image Classification (I8)
|
97% |
129
24.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
207
3.46 IPS |
|
|
Image Segmentation (F16)
|
100% |
196
3.28 IPS |
|
|
Image Segmentation (I8)
|
98% |
297
4.96 IPS |
|
|
Pose Estimation (F32)
|
100% |
360
0.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
354
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1424
1.72 IPS |
|
|
Object Detection (F32)
|
100% |
106
7.94 IPS |
|
|
Object Detection (F16)
|
100% |
108
8.04 IPS |
|
|
Object Detection (I8)
|
61% |
181
13.5 IPS |
|
|
Face Detection (F32)
|
100% |
323
3.85 IPS |
|
|
Face Detection (F16)
|
100% |
285
3.39 IPS |
|
|
Face Detection (I8)
|
86% |
469
5.57 IPS |
|
|
Depth Estimation (F32)
|
100% |
280
2.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
290
2.25 IPS |
|
|
Depth Estimation (I8)
|
95% |
530
4.11 IPS |
|
|
Style Transfer (F32)
|
100% |
591
0.78 IPS |
|
|
Style Transfer (F16)
|
100% |
595
0.78 IPS |
|
|
Style Transfer (I8)
|
98% |
1766
2.32 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
191
6.83 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
159
5.68 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
357
12.8 IPS |
|
|
Text Classification (F32)
|
100% |
55
78.4 IPS |
|
|
Text Classification (F16)
|
100% |
51
72.7 IPS |
|
|
Text Classification (I8)
|
92% |
59
84.8 IPS |
|
|
Machine Translation (F32)
|
100% |
155
2.85 IPS |
|
|
Machine Translation (F16)
|
100% |
140
2.57 IPS |
|
|
Machine Translation (I8)
|
64% |
137
2.53 IPS |
