samsung SM-A166P
Geekbench ML Score
262
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 09:34 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
138
25.8 IPS |
|
|
Image Classification (F16)
|
100% |
77
14.5 IPS |
|
|
Image Classification (I8)
|
97% |
106
19.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
187
3.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
190
3.18 IPS |
|
|
Image Segmentation (I8)
|
98% |
254
4.25 IPS |
|
|
Pose Estimation (F32)
|
100% |
350
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
352
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1372
1.66 IPS |
|
|
Object Detection (F32)
|
100% |
92
6.88 IPS |
|
|
Object Detection (F16)
|
100% |
155
11.6 IPS |
|
|
Object Detection (I8)
|
61% |
161
12.0 IPS |
|
|
Face Detection (F32)
|
100% |
263
3.13 IPS |
|
|
Face Detection (F16)
|
100% |
267
3.18 IPS |
|
|
Face Detection (I8)
|
86% |
602
7.16 IPS |
|
|
Depth Estimation (F32)
|
100% |
266
2.07 IPS |
|
|
Depth Estimation (F16)
|
100% |
258
2.00 IPS |
|
|
Depth Estimation (I8)
|
95% |
468
3.63 IPS |
|
|
Style Transfer (F32)
|
100% |
384
0.50 IPS |
|
|
Style Transfer (F16)
|
100% |
406
0.53 IPS |
|
|
Style Transfer (I8)
|
98% |
1699
2.23 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
184
6.56 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
200
7.13 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
565
20.2 IPS |
|
|
Text Classification (F32)
|
100% |
177
253.9 IPS |
|
|
Text Classification (F16)
|
100% |
162
232.4 IPS |
|
|
Text Classification (I8)
|
92% |
163
234.2 IPS |
|
|
Machine Translation (F32)
|
100% |
332
6.11 IPS |
|
|
Machine Translation (F16)
|
100% |
357
6.58 IPS |
|
|
Machine Translation (I8)
|
64% |
233
4.29 IPS |
