samsung SM-A166P
Geekbench ML Score
197
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 09:53 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
101
18.9 IPS |
|
|
Image Classification (F16)
|
100% |
179
33.5 IPS |
|
|
Image Classification (I8)
|
97% |
171
32.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
136
2.26 IPS |
|
|
Image Segmentation (F16)
|
100% |
228
3.80 IPS |
|
|
Image Segmentation (I8)
|
98% |
239
4.00 IPS |
|
|
Pose Estimation (F32)
|
100% |
92
0.11 IPS |
|
|
Pose Estimation (F16)
|
100% |
111
0.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
111
0.13 IPS |
|
|
Object Detection (F32)
|
100% |
85
6.32 IPS |
|
|
Object Detection (F16)
|
100% |
144
10.8 IPS |
|
|
Object Detection (I8)
|
62% |
132
9.89 IPS |
|
|
Face Detection (F32)
|
100% |
324
3.86 IPS |
|
|
Face Detection (F16)
|
98% |
475
5.65 IPS |
|
|
Face Detection (I8)
|
86% |
464
5.51 IPS |
|
|
Depth Estimation (F32)
|
100% |
184
1.42 IPS |
|
|
Depth Estimation (F16)
|
100% |
242
1.88 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% |
99
3.52 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
153
5.47 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
154
5.50 IPS |
|
|
Text Classification (F32)
|
100% |
145
208.4 IPS |
|
|
Text Classification (F16)
|
100% |
143
206.0 IPS |
|
|
Text Classification (I8)
|
92% |
251
360.6 IPS |
|
|
Machine Translation (F32)
|
100% |
258
4.75 IPS |
|
|
Machine Translation (F16)
|
100% |
261
4.80 IPS |
|
|
Machine Translation (I8)
|
64% |
293
5.40 IPS |
