samsung SM-A176U1
Geekbench ML Score
281
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 02 2026 06:03 PM |
| Views | 7 |
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
34.4 IPS |
|
|
Image Classification (F16)
|
100% |
205
38.4 IPS |
|
|
Image Classification (I8)
|
97% |
396
74.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
180
3.01 IPS |
|
|
Image Segmentation (F16)
|
100% |
178
2.97 IPS |
|
|
Image Segmentation (I8)
|
98% |
231
3.86 IPS |
|
|
Pose Estimation (F32)
|
100% |
382
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
387
0.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
2148
2.60 IPS |
|
|
Object Detection (F32)
|
100% |
270
20.1 IPS |
|
|
Object Detection (F16)
|
100% |
263
19.6 IPS |
|
|
Object Detection (I8)
|
61% |
102
7.61 IPS |
|
|
Face Detection (F32)
|
100% |
213
2.53 IPS |
|
|
Face Detection (F16)
|
100% |
221
2.63 IPS |
|
|
Face Detection (I8)
|
86% |
288
3.42 IPS |
|
|
Depth Estimation (F32)
|
100% |
411
3.19 IPS |
|
|
Depth Estimation (F16)
|
100% |
289
2.24 IPS |
|
|
Depth Estimation (I8)
|
95% |
322
2.50 IPS |
|
|
Style Transfer (F32)
|
100% |
682
0.90 IPS |
|
|
Style Transfer (F16)
|
100% |
702
0.92 IPS |
|
|
Style Transfer (I8)
|
98% |
1793
2.36 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
241
8.60 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
300
10.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
192
6.85 IPS |
|
|
Text Classification (F32)
|
100% |
260
374.4 IPS |
|
|
Text Classification (F16)
|
100% |
345
496.5 IPS |
|
|
Text Classification (I8)
|
92% |
447
643.0 IPS |
|
|
Machine Translation (F32)
|
100% |
37
0.67 IPS |
|
|
Machine Translation (F16)
|
100% |
298
5.48 IPS |
|
|
Machine Translation (I8)
|
64% |
44
0.82 IPS |
