samsung SM-A166P
Geekbench ML Score
195
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 09:12 PM |
| 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 | 3.35 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
100
18.7 IPS |
|
|
Image Classification (F16)
|
100% |
177
33.2 IPS |
|
|
Image Classification (I8)
|
97% |
170
31.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
140
2.33 IPS |
|
|
Image Segmentation (F16)
|
100% |
222
3.70 IPS |
|
|
Image Segmentation (I8)
|
98% |
237
3.97 IPS |
|
|
Pose Estimation (F32)
|
100% |
92
0.11 IPS |
|
|
Pose Estimation (F16)
|
100% |
111
0.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
110
0.13 IPS |
|
|
Object Detection (F32)
|
100% |
88
6.58 IPS |
|
|
Object Detection (F16)
|
100% |
145
10.8 IPS |
|
|
Object Detection (I8)
|
62% |
134
9.97 IPS |
|
|
Face Detection (F32)
|
100% |
326
3.87 IPS |
|
|
Face Detection (F16)
|
98% |
477
5.68 IPS |
|
|
Face Detection (I8)
|
86% |
455
5.41 IPS |
|
|
Depth Estimation (F32)
|
100% |
183
1.42 IPS |
|
|
Depth Estimation (F16)
|
100% |
241
1.87 IPS |
|
|
Depth Estimation (I8)
|
95% |
241
1.87 IPS |
|
|
Style Transfer (F32)
|
100% |
361
0.48 IPS |
|
|
Style Transfer (F16)
|
100% |
508
0.67 IPS |
|
|
Style Transfer (I8)
|
98% |
508
0.67 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
98
3.51 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
153
5.48 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
153
5.46 IPS |
|
|
Text Classification (F32)
|
100% |
139
199.7 IPS |
|
|
Text Classification (F16)
|
100% |
141
202.0 IPS |
|
|
Text Classification (I8)
|
92% |
241
346.9 IPS |
|
|
Machine Translation (F32)
|
100% |
249
4.59 IPS |
|
|
Machine Translation (F16)
|
100% |
249
4.57 IPS |
|
|
Machine Translation (I8)
|
64% |
282
5.20 IPS |
