samsung SM-A166P
Geekbench ML Score
246
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 15 2025 10:21 AM |
| Views | 1 |
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% |
150
28.0 IPS |
|
|
Image Classification (F16)
|
100% |
81
15.1 IPS |
|
|
Image Classification (I8)
|
97% |
126
23.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
198
3.31 IPS |
|
|
Image Segmentation (F16)
|
100% |
200
3.34 IPS |
|
|
Image Segmentation (I8)
|
98% |
307
5.12 IPS |
|
|
Pose Estimation (F32)
|
100% |
355
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
364
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1489
1.80 IPS |
|
|
Object Detection (F32)
|
100% |
121
9.05 IPS |
|
|
Object Detection (F16)
|
100% |
128
9.59 IPS |
|
|
Object Detection (I8)
|
61% |
222
16.5 IPS |
|
|
Face Detection (F32)
|
100% |
299
3.56 IPS |
|
|
Face Detection (F16)
|
100% |
336
4.00 IPS |
|
|
Face Detection (I8)
|
86% |
506
6.01 IPS |
|
|
Depth Estimation (F32)
|
100% |
309
2.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
300
2.32 IPS |
|
|
Depth Estimation (I8)
|
95% |
562
4.36 IPS |
|
|
Style Transfer (F32)
|
100% |
621
0.82 IPS |
|
|
Style Transfer (F16)
|
100% |
609
0.80 IPS |
|
|
Style Transfer (I8)
|
98% |
1832
2.41 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
158
5.64 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
161
5.77 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
390
13.9 IPS |
|
|
Text Classification (F32)
|
100% |
216
310.5 IPS |
|
|
Text Classification (F16)
|
100% |
68
97.1 IPS |
|
|
Text Classification (I8)
|
92% |
55
79.4 IPS |
|
|
Machine Translation (F32)
|
100% |
133
2.45 IPS |
|
|
Machine Translation (F16)
|
100% |
137
2.52 IPS |
|
|
Machine Translation (I8)
|
64% |
168
3.09 IPS |
