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 09:26 PM |
| Views | 6 |
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% |
101
18.9 IPS |
|
|
Image Classification (F16)
|
100% |
177
33.1 IPS |
|
|
Image Classification (I8)
|
97% |
171
32.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
138
2.31 IPS |
|
|
Image Segmentation (F16)
|
100% |
226
3.78 IPS |
|
|
Image Segmentation (I8)
|
98% |
236
3.94 IPS |
|
|
Pose Estimation (F32)
|
100% |
92
0.11 IPS |
|
|
Pose Estimation (F16)
|
100% |
110
0.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
110
0.13 IPS |
|
|
Object Detection (F32)
|
100% |
88
6.58 IPS |
|
|
Object Detection (F16)
|
100% |
143
10.7 IPS |
|
|
Object Detection (I8)
|
62% |
134
10.0 IPS |
|
|
Face Detection (F32)
|
100% |
323
3.84 IPS |
|
|
Face Detection (F16)
|
98% |
470
5.59 IPS |
|
|
Face Detection (I8)
|
86% |
460
5.47 IPS |
|
|
Depth Estimation (F32)
|
100% |
184
1.43 IPS |
|
|
Depth Estimation (F16)
|
100% |
241
1.87 IPS |
|
|
Depth Estimation (I8)
|
95% |
240
1.86 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% |
99
3.53 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
153
5.47 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
152
5.43 IPS |
|
|
Text Classification (F32)
|
100% |
140
201.7 IPS |
|
|
Text Classification (F16)
|
100% |
141
202.7 IPS |
|
|
Text Classification (I8)
|
92% |
237
340.9 IPS |
|
|
Machine Translation (F32)
|
100% |
250
4.60 IPS |
|
|
Machine Translation (F16)
|
100% |
249
4.59 IPS |
|
|
Machine Translation (I8)
|
64% |
284
5.22 IPS |
