samsung SM-A166P
Geekbench ML Score
242
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 11:28 PM |
| Views | 4 |
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% |
129
24.1 IPS |
|
|
Image Classification (F16)
|
100% |
69
12.9 IPS |
|
|
Image Classification (I8)
|
97% |
128
24.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
183
3.05 IPS |
|
|
Image Segmentation (F16)
|
100% |
178
2.97 IPS |
|
|
Image Segmentation (I8)
|
98% |
254
4.25 IPS |
|
|
Pose Estimation (F32)
|
100% |
329
0.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
329
0.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
1250
1.51 IPS |
|
|
Object Detection (F32)
|
100% |
97
7.25 IPS |
|
|
Object Detection (F16)
|
100% |
99
7.39 IPS |
|
|
Object Detection (I8)
|
61% |
143
10.7 IPS |
|
|
Face Detection (F32)
|
100% |
283
3.36 IPS |
|
|
Face Detection (F16)
|
100% |
266
3.16 IPS |
|
|
Face Detection (I8)
|
86% |
403
4.79 IPS |
|
|
Depth Estimation (F32)
|
100% |
245
1.90 IPS |
|
|
Depth Estimation (F16)
|
100% |
272
2.11 IPS |
|
|
Depth Estimation (I8)
|
95% |
429
3.33 IPS |
|
|
Style Transfer (F32)
|
100% |
542
0.71 IPS |
|
|
Style Transfer (F16)
|
100% |
291
0.38 IPS |
|
|
Style Transfer (I8)
|
98% |
1053
1.39 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
127
4.55 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
158
5.63 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
553
19.7 IPS |
|
|
Text Classification (F32)
|
100% |
162
233.5 IPS |
|
|
Text Classification (F16)
|
100% |
163
234.9 IPS |
|
|
Text Classification (I8)
|
92% |
158
226.7 IPS |
|
|
Machine Translation (F32)
|
100% |
350
6.45 IPS |
|
|
Machine Translation (F16)
|
100% |
362
6.67 IPS |
|
|
Machine Translation (I8)
|
64% |
221
4.06 IPS |
