samsung SM-A166P
Geekbench ML Score
261
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 05:38 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
133
24.9 IPS |
|
|
Image Classification (F16)
|
100% |
78
14.6 IPS |
|
|
Image Classification (I8)
|
97% |
95
17.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
182
3.03 IPS |
|
|
Image Segmentation (F16)
|
100% |
190
3.17 IPS |
|
|
Image Segmentation (I8)
|
98% |
272
4.54 IPS |
|
|
Pose Estimation (F32)
|
100% |
346
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
329
0.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
1291
1.56 IPS |
|
|
Object Detection (F32)
|
100% |
94
7.02 IPS |
|
|
Object Detection (F16)
|
100% |
129
9.64 IPS |
|
|
Object Detection (I8)
|
61% |
323
24.1 IPS |
|
|
Face Detection (F32)
|
100% |
265
3.15 IPS |
|
|
Face Detection (F16)
|
100% |
263
3.13 IPS |
|
|
Face Detection (I8)
|
86% |
461
5.48 IPS |
|
|
Depth Estimation (F32)
|
100% |
275
2.13 IPS |
|
|
Depth Estimation (F16)
|
100% |
254
1.97 IPS |
|
|
Depth Estimation (I8)
|
95% |
440
3.41 IPS |
|
|
Style Transfer (F32)
|
100% |
578
0.76 IPS |
|
|
Style Transfer (F16)
|
100% |
461
0.61 IPS |
|
|
Style Transfer (I8)
|
98% |
1318
1.73 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
153
5.45 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
176
6.28 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
534
19.1 IPS |
|
|
Text Classification (F32)
|
100% |
163
234.2 IPS |
|
|
Text Classification (F16)
|
100% |
170
244.4 IPS |
|
|
Text Classification (I8)
|
92% |
165
236.9 IPS |
|
|
Machine Translation (F32)
|
100% |
351
6.46 IPS |
|
|
Machine Translation (F16)
|
100% |
367
6.75 IPS |
|
|
Machine Translation (I8)
|
64% |
206
3.78 IPS |
