samsung SM-A176U1
Geekbench ML Score
273
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 02 2026 06:17 PM |
| Views | 10 |
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% |
204
38.2 IPS |
|
|
Image Classification (F16)
|
100% |
198
37.0 IPS |
|
|
Image Classification (I8)
|
97% |
388
72.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
226
3.77 IPS |
|
|
Image Segmentation (F16)
|
100% |
214
3.58 IPS |
|
|
Image Segmentation (I8)
|
98% |
226
3.78 IPS |
|
|
Pose Estimation (F32)
|
100% |
408
0.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
395
0.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
2141
2.59 IPS |
|
|
Object Detection (F32)
|
100% |
202
15.1 IPS |
|
|
Object Detection (F16)
|
100% |
266
19.9 IPS |
|
|
Object Detection (I8)
|
61% |
90
6.71 IPS |
|
|
Face Detection (F32)
|
100% |
240
2.85 IPS |
|
|
Face Detection (F16)
|
100% |
227
2.70 IPS |
|
|
Face Detection (I8)
|
86% |
275
3.26 IPS |
|
|
Depth Estimation (F32)
|
100% |
437
3.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
362
2.81 IPS |
|
|
Depth Estimation (I8)
|
95% |
366
2.83 IPS |
|
|
Style Transfer (F32)
|
100% |
688
0.91 IPS |
|
|
Style Transfer (F16)
|
100% |
732
0.96 IPS |
|
|
Style Transfer (I8)
|
98% |
1710
2.25 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
320
11.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
322
11.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
378
13.5 IPS |
|
|
Text Classification (F32)
|
100% |
12
16.6 IPS |
|
|
Text Classification (F16)
|
100% |
264
379.7 IPS |
|
|
Text Classification (I8)
|
92% |
219
314.1 IPS |
|
|
Machine Translation (F32)
|
100% |
393
7.24 IPS |
|
|
Machine Translation (F16)
|
100% |
221
4.07 IPS |
|
|
Machine Translation (I8)
|
64% |
25
0.46 IPS |
