samsung SM-A166P
Geekbench ML Score
247
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 17 2025 02:55 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 | 5.31 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
148
27.6 IPS |
|
|
Image Classification (F16)
|
100% |
114
21.3 IPS |
|
|
Image Classification (I8)
|
97% |
134
25.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
208
3.47 IPS |
|
|
Image Segmentation (F16)
|
100% |
204
3.40 IPS |
|
|
Image Segmentation (I8)
|
98% |
303
5.05 IPS |
|
|
Pose Estimation (F32)
|
100% |
355
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
365
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1529
1.85 IPS |
|
|
Object Detection (F32)
|
100% |
120
8.96 IPS |
|
|
Object Detection (F16)
|
100% |
114
8.51 IPS |
|
|
Object Detection (I8)
|
61% |
193
14.4 IPS |
|
|
Face Detection (F32)
|
100% |
320
3.80 IPS |
|
|
Face Detection (F16)
|
100% |
300
3.57 IPS |
|
|
Face Detection (I8)
|
86% |
529
6.29 IPS |
|
|
Depth Estimation (F32)
|
100% |
299
2.32 IPS |
|
|
Depth Estimation (F16)
|
100% |
309
2.40 IPS |
|
|
Depth Estimation (I8)
|
95% |
866
6.72 IPS |
|
|
Style Transfer (F32)
|
100% |
610
0.80 IPS |
|
|
Style Transfer (F16)
|
100% |
615
0.81 IPS |
|
|
Style Transfer (I8)
|
98% |
1859
2.45 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
199
7.10 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
165
5.90 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
421
15.0 IPS |
|
|
Text Classification (F32)
|
100% |
65
92.8 IPS |
|
|
Text Classification (F16)
|
100% |
87
124.8 IPS |
|
|
Text Classification (I8)
|
92% |
64
92.6 IPS |
|
|
Machine Translation (F32)
|
100% |
135
2.49 IPS |
|
|
Machine Translation (F16)
|
100% |
147
2.70 IPS |
|
|
Machine Translation (I8)
|
64% |
157
2.90 IPS |
