samsung SM-A166P
Geekbench ML Score
248
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 17 2025 03:27 AM |
| Views | 3 |
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
27.8 IPS |
|
|
Image Classification (F16)
|
100% |
96
17.9 IPS |
|
|
Image Classification (I8)
|
97% |
141
26.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
206
3.44 IPS |
|
|
Image Segmentation (F16)
|
100% |
200
3.34 IPS |
|
|
Image Segmentation (I8)
|
98% |
367
6.13 IPS |
|
|
Pose Estimation (F32)
|
100% |
367
0.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
363
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1513
1.83 IPS |
|
|
Object Detection (F32)
|
100% |
115
8.61 IPS |
|
|
Object Detection (F16)
|
100% |
114
8.50 IPS |
|
|
Object Detection (I8)
|
61% |
217
16.2 IPS |
|
|
Face Detection (F32)
|
100% |
336
4.00 IPS |
|
|
Face Detection (F16)
|
100% |
302
3.59 IPS |
|
|
Face Detection (I8)
|
86% |
561
6.67 IPS |
|
|
Depth Estimation (F32)
|
100% |
309
2.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
306
2.37 IPS |
|
|
Depth Estimation (I8)
|
95% |
564
4.38 IPS |
|
|
Style Transfer (F32)
|
100% |
612
0.81 IPS |
|
|
Style Transfer (F16)
|
100% |
618
0.81 IPS |
|
|
Style Transfer (I8)
|
98% |
1866
2.45 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
203
7.23 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
179
6.38 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
427
15.2 IPS |
|
|
Text Classification (F32)
|
100% |
77
110.2 IPS |
|
|
Text Classification (F16)
|
100% |
82
117.5 IPS |
|
|
Text Classification (I8)
|
92% |
64
92.6 IPS |
|
|
Machine Translation (F32)
|
100% |
140
2.57 IPS |
|
|
Machine Translation (F16)
|
100% |
135
2.49 IPS |
|
|
Machine Translation (I8)
|
64% |
171
3.15 IPS |
