samsung SM-A166P
Geekbench ML Score
250
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 17 2025 03:58 AM |
| 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 | 5.31 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
147
27.5 IPS |
|
|
Image Classification (F16)
|
100% |
113
21.1 IPS |
|
|
Image Classification (I8)
|
97% |
138
25.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
199
3.32 IPS |
|
|
Image Segmentation (F16)
|
100% |
200
3.34 IPS |
|
|
Image Segmentation (I8)
|
98% |
313
5.23 IPS |
|
|
Pose Estimation (F32)
|
100% |
374
0.45 IPS |
|
|
Pose Estimation (F16)
|
100% |
354
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1548
1.87 IPS |
|
|
Object Detection (F32)
|
100% |
124
9.23 IPS |
|
|
Object Detection (F16)
|
100% |
121
9.07 IPS |
|
|
Object Detection (I8)
|
61% |
202
15.1 IPS |
|
|
Face Detection (F32)
|
100% |
303
3.60 IPS |
|
|
Face Detection (F16)
|
100% |
321
3.82 IPS |
|
|
Face Detection (I8)
|
86% |
532
6.33 IPS |
|
|
Depth Estimation (F32)
|
100% |
306
2.37 IPS |
|
|
Depth Estimation (F16)
|
100% |
301
2.33 IPS |
|
|
Depth Estimation (I8)
|
95% |
605
4.69 IPS |
|
|
Style Transfer (F32)
|
100% |
615
0.81 IPS |
|
|
Style Transfer (F16)
|
100% |
613
0.81 IPS |
|
|
Style Transfer (I8)
|
98% |
1870
2.46 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
164
5.85 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
177
6.32 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
664
23.7 IPS |
|
|
Text Classification (F32)
|
100% |
81
116.8 IPS |
|
|
Text Classification (F16)
|
100% |
61
87.2 IPS |
|
|
Text Classification (I8)
|
92% |
68
97.7 IPS |
|
|
Machine Translation (F32)
|
100% |
140
2.58 IPS |
|
|
Machine Translation (F16)
|
100% |
179
3.29 IPS |
|
|
Machine Translation (I8)
|
64% |
151
2.79 IPS |
