samsung SM-A166P
Geekbench ML Score
299
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 15 2025 10:40 AM |
| Views | 1 |
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% |
120
22.4 IPS |
|
|
Image Classification (F16)
|
100% |
348
65.1 IPS |
|
|
Image Classification (I8)
|
97% |
52
9.67 IPS |
|
|
Image Segmentation (F32)
|
100% |
224
3.73 IPS |
|
|
Image Segmentation (F16)
|
100% |
407
6.79 IPS |
|
|
Image Segmentation (I8)
|
98% |
89
1.48 IPS |
|
|
Pose Estimation (F32)
|
100% |
848
1.03 IPS |
|
|
Pose Estimation (F16)
|
100% |
1913
2.32 IPS |
|
|
Pose Estimation (I8)
|
87% |
1154
1.40 IPS |
|
|
Object Detection (F32)
|
100% |
140
10.5 IPS |
|
|
Object Detection (F16)
|
100% |
301
22.5 IPS |
|
|
Object Detection (I8)
|
51% |
94
7.00 IPS |
|
|
Face Detection (F32)
|
25% |
541
6.44 IPS |
|
|
Face Detection (F16)
|
25% |
786
9.35 IPS |
|
|
Face Detection (I8)
|
87% |
141
1.68 IPS |
|
|
Depth Estimation (F32)
|
100% |
356
2.76 IPS |
|
|
Depth Estimation (F16)
|
74% |
456
3.53 IPS |
|
|
Depth Estimation (I8)
|
93% |
361
2.80 IPS |
|
|
Style Transfer (F32)
|
100% |
698
0.92 IPS |
|
|
Style Transfer (F16)
|
100% |
1226
1.61 IPS |
|
|
Style Transfer (I8)
|
98% |
1615
2.12 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
362
12.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
766
27.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
398
14.2 IPS |
|
|
Text Classification (F32)
|
100% |
70
101.2 IPS |
|
|
Text Classification (F16)
|
100% |
80
114.9 IPS |
|
|
Text Classification (I8)
|
94% |
63
90.3 IPS |
|
|
Machine Translation (F32)
|
100% |
205
3.77 IPS |
|
|
Machine Translation (F16)
|
100% |
249
4.59 IPS |
|
|
Machine Translation (I8)
|
57% |
154
2.83 IPS |
