samsung SM-A176U1
Geekbench ML Score
327
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 02 2026 05:46 PM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-A176U1 |
| Model ID | samsung SM-A176U1 |
| Motherboard | s5e8535 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 3.37 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
184
34.5 IPS |
|
|
Image Classification (F16)
|
100% |
201
37.6 IPS |
|
|
Image Classification (I8)
|
97% |
399
74.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
176
2.94 IPS |
|
|
Image Segmentation (F16)
|
100% |
198
3.31 IPS |
|
|
Image Segmentation (I8)
|
98% |
249
4.16 IPS |
|
|
Pose Estimation (F32)
|
100% |
415
0.50 IPS |
|
|
Pose Estimation (F16)
|
100% |
410
0.50 IPS |
|
|
Pose Estimation (I8)
|
100% |
2303
2.79 IPS |
|
|
Object Detection (F32)
|
100% |
101
7.54 IPS |
|
|
Object Detection (F16)
|
100% |
269
20.1 IPS |
|
|
Object Detection (I8)
|
61% |
186
13.9 IPS |
|
|
Face Detection (F32)
|
100% |
215
2.56 IPS |
|
|
Face Detection (F16)
|
100% |
225
2.68 IPS |
|
|
Face Detection (I8)
|
86% |
279
3.32 IPS |
|
|
Depth Estimation (F32)
|
100% |
447
3.46 IPS |
|
|
Depth Estimation (F16)
|
100% |
384
2.98 IPS |
|
|
Depth Estimation (I8)
|
95% |
552
4.28 IPS |
|
|
Style Transfer (F32)
|
100% |
720
0.95 IPS |
|
|
Style Transfer (F16)
|
100% |
750
0.99 IPS |
|
|
Style Transfer (I8)
|
98% |
1656
2.18 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
322
11.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
326
11.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1059
37.8 IPS |
|
|
Text Classification (F32)
|
100% |
264
378.9 IPS |
|
|
Text Classification (F16)
|
100% |
203
291.5 IPS |
|
|
Text Classification (I8)
|
92% |
443
637.1 IPS |
|
|
Machine Translation (F32)
|
100% |
358
6.59 IPS |
|
|
Machine Translation (F16)
|
100% |
388
7.14 IPS |
|
|
Machine Translation (I8)
|
64% |
27
0.50 IPS |
