samsung SM-A166P
Geekbench ML Score
204
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 09:02 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
139
26.0 IPS |
|
|
Image Classification (F16)
|
100% |
90
16.8 IPS |
|
|
Image Classification (I8)
|
97% |
94
17.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
184
3.08 IPS |
|
|
Image Segmentation (F16)
|
100% |
189
3.16 IPS |
|
|
Image Segmentation (I8)
|
98% |
286
4.78 IPS |
|
|
Pose Estimation (F32)
|
100% |
353
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
349
0.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
1265
1.53 IPS |
|
|
Object Detection (F32)
|
100% |
94
6.99 IPS |
|
|
Object Detection (F16)
|
100% |
96
7.19 IPS |
|
|
Object Detection (I8)
|
61% |
140
10.4 IPS |
|
|
Face Detection (F32)
|
100% |
277
3.29 IPS |
|
|
Face Detection (F16)
|
100% |
268
3.18 IPS |
|
|
Face Detection (I8)
|
86% |
443
5.27 IPS |
|
|
Depth Estimation (F32)
|
100% |
297
2.31 IPS |
|
|
Depth Estimation (F16)
|
100% |
263
2.04 IPS |
|
|
Depth Estimation (I8)
|
95% |
480
3.72 IPS |
|
|
Style Transfer (F32)
|
100% |
598
0.79 IPS |
|
|
Style Transfer (F16)
|
100% |
575
0.76 IPS |
|
|
Style Transfer (I8)
|
98% |
1657
2.18 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
140
5.01 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
152
5.44 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
312
11.1 IPS |
|
|
Text Classification (F32)
|
100% |
38
54.3 IPS |
|
|
Text Classification (F16)
|
100% |
37
52.7 IPS |
|
|
Text Classification (I8)
|
92% |
148
212.8 IPS |
|
|
Machine Translation (F32)
|
100% |
90
1.66 IPS |
|
|
Machine Translation (F16)
|
100% |
86
1.58 IPS |
|
|
Machine Translation (I8)
|
64% |
113
2.08 IPS |
