samsung SM-A166P
Geekbench ML Score
296
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 04 2025 08:54 PM |
| Views | 12 |
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 | 7.27 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
118
22.1 IPS |
|
|
Image Classification (F16)
|
100% |
350
65.5 IPS |
|
|
Image Classification (I8)
|
97% |
68
12.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
226
3.77 IPS |
|
|
Image Segmentation (F16)
|
100% |
406
6.77 IPS |
|
|
Image Segmentation (I8)
|
98% |
85
1.42 IPS |
|
|
Pose Estimation (F32)
|
100% |
853
1.03 IPS |
|
|
Pose Estimation (F16)
|
100% |
1920
2.32 IPS |
|
|
Pose Estimation (I8)
|
87% |
1098
1.33 IPS |
|
|
Object Detection (F32)
|
100% |
138
10.3 IPS |
|
|
Object Detection (F16)
|
100% |
299
22.3 IPS |
|
|
Object Detection (I8)
|
51% |
89
6.65 IPS |
|
|
Face Detection (F32)
|
25% |
543
6.45 IPS |
|
|
Face Detection (F16)
|
25% |
786
9.34 IPS |
|
|
Face Detection (I8)
|
87% |
135
1.60 IPS |
|
|
Depth Estimation (F32)
|
100% |
356
2.76 IPS |
|
|
Depth Estimation (F16)
|
74% |
442
3.43 IPS |
|
|
Depth Estimation (I8)
|
93% |
348
2.70 IPS |
|
|
Style Transfer (F32)
|
100% |
685
0.90 IPS |
|
|
Style Transfer (F16)
|
100% |
1191
1.57 IPS |
|
|
Style Transfer (I8)
|
98% |
1503
1.98 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
363
13.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
771
27.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
373
13.3 IPS |
|
|
Text Classification (F32)
|
100% |
68
98.2 IPS |
|
|
Text Classification (F16)
|
100% |
79
112.8 IPS |
|
|
Text Classification (I8)
|
94% |
63
90.9 IPS |
|
|
Machine Translation (F32)
|
100% |
200
3.68 IPS |
|
|
Machine Translation (F16)
|
100% |
240
4.42 IPS |
|
|
Machine Translation (I8)
|
57% |
148
2.72 IPS |
