samsung SM-A166P
Geekbench ML Score
198
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 17 2025 09:20 AM |
| 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 | 5.31 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% |
183
34.3 IPS |
|
|
Image Classification (I8)
|
97% |
174
32.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
139
2.33 IPS |
|
|
Image Segmentation (F16)
|
100% |
240
4.00 IPS |
|
|
Image Segmentation (I8)
|
98% |
233
3.89 IPS |
|
|
Pose Estimation (F32)
|
100% |
93
0.11 IPS |
|
|
Pose Estimation (F16)
|
100% |
111
0.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
110
0.13 IPS |
|
|
Object Detection (F32)
|
100% |
87
6.52 IPS |
|
|
Object Detection (F16)
|
100% |
140
10.4 IPS |
|
|
Object Detection (I8)
|
62% |
136
10.2 IPS |
|
|
Face Detection (F32)
|
100% |
329
3.91 IPS |
|
|
Face Detection (F16)
|
98% |
483
5.75 IPS |
|
|
Face Detection (I8)
|
86% |
472
5.61 IPS |
|
|
Depth Estimation (F32)
|
100% |
184
1.43 IPS |
|
|
Depth Estimation (F16)
|
100% |
242
1.87 IPS |
|
|
Depth Estimation (I8)
|
95% |
240
1.86 IPS |
|
|
Style Transfer (F32)
|
100% |
362
0.48 IPS |
|
|
Style Transfer (F16)
|
100% |
510
0.67 IPS |
|
|
Style Transfer (I8)
|
98% |
509
0.67 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
99
3.53 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
154
5.50 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
153
5.45 IPS |
|
|
Text Classification (F32)
|
100% |
143
205.8 IPS |
|
|
Text Classification (F16)
|
100% |
143
205.4 IPS |
|
|
Text Classification (I8)
|
92% |
250
359.4 IPS |
|
|
Machine Translation (F32)
|
100% |
258
4.74 IPS |
|
|
Machine Translation (F16)
|
100% |
259
4.76 IPS |
|
|
Machine Translation (I8)
|
64% |
294
5.41 IPS |
