samsung SM-A166P
Geekbench ML Score
195
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 11 2025 01:48 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% |
123
23.1 IPS |
|
|
Image Classification (F16)
|
100% |
68
12.7 IPS |
|
|
Image Classification (I8)
|
97% |
132
24.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
180
3.00 IPS |
|
|
Image Segmentation (F16)
|
100% |
184
3.07 IPS |
|
|
Image Segmentation (I8)
|
98% |
269
4.50 IPS |
|
|
Pose Estimation (F32)
|
100% |
338
0.41 IPS |
|
|
Pose Estimation (F16)
|
100% |
337
0.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1271
1.54 IPS |
|
|
Object Detection (F32)
|
100% |
91
6.80 IPS |
|
|
Object Detection (F16)
|
100% |
94
7.02 IPS |
|
|
Object Detection (I8)
|
61% |
159
11.9 IPS |
|
|
Face Detection (F32)
|
100% |
265
3.15 IPS |
|
|
Face Detection (F16)
|
100% |
278
3.31 IPS |
|
|
Face Detection (I8)
|
86% |
408
4.86 IPS |
|
|
Depth Estimation (F32)
|
100% |
251
1.95 IPS |
|
|
Depth Estimation (F16)
|
100% |
265
2.05 IPS |
|
|
Depth Estimation (I8)
|
95% |
743
5.77 IPS |
|
|
Style Transfer (F32)
|
100% |
593
0.78 IPS |
|
|
Style Transfer (F16)
|
100% |
520
0.68 IPS |
|
|
Style Transfer (I8)
|
98% |
1639
2.16 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
146
5.21 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
141
5.04 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
309
11.0 IPS |
|
|
Text Classification (F32)
|
100% |
31
45.1 IPS |
|
|
Text Classification (F16)
|
100% |
48
68.4 IPS |
|
|
Text Classification (I8)
|
92% |
39
56.1 IPS |
|
|
Machine Translation (F32)
|
100% |
100
1.83 IPS |
|
|
Machine Translation (F16)
|
100% |
85
1.56 IPS |
|
|
Machine Translation (I8)
|
64% |
123
2.26 IPS |
