samsung SM-A166P
Geekbench ML Score
281
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2025 12:16 AM |
| Views | 3 |
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 | 3.35 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
114
21.3 IPS |
|
|
Image Classification (F16)
|
100% |
343
64.1 IPS |
|
|
Image Classification (I8)
|
97% |
43
8.04 IPS |
|
|
Image Segmentation (F32)
|
100% |
219
3.66 IPS |
|
|
Image Segmentation (F16)
|
100% |
409
6.83 IPS |
|
|
Image Segmentation (I8)
|
98% |
82
1.37 IPS |
|
|
Pose Estimation (F32)
|
100% |
845
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
1904
2.31 IPS |
|
|
Pose Estimation (I8)
|
87% |
1100
1.33 IPS |
|
|
Object Detection (F32)
|
100% |
139
10.3 IPS |
|
|
Object Detection (F16)
|
100% |
288
21.5 IPS |
|
|
Object Detection (I8)
|
51% |
85
6.36 IPS |
|
|
Face Detection (F32)
|
25% |
541
6.44 IPS |
|
|
Face Detection (F16)
|
25% |
766
9.11 IPS |
|
|
Face Detection (I8)
|
87% |
119
1.42 IPS |
|
|
Depth Estimation (F32)
|
100% |
329
2.55 IPS |
|
|
Depth Estimation (F16)
|
74% |
412
3.20 IPS |
|
|
Depth Estimation (I8)
|
93% |
307
2.38 IPS |
|
|
Style Transfer (F32)
|
100% |
656
0.86 IPS |
|
|
Style Transfer (F16)
|
100% |
1153
1.52 IPS |
|
|
Style Transfer (I8)
|
98% |
1397
1.84 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
357
12.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
750
26.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
349
12.5 IPS |
|
|
Text Classification (F32)
|
100% |
77
110.1 IPS |
|
|
Text Classification (F16)
|
100% |
74
106.6 IPS |
|
|
Text Classification (I8)
|
94% |
64
92.6 IPS |
|
|
Machine Translation (F32)
|
100% |
184
3.39 IPS |
|
|
Machine Translation (F16)
|
100% |
224
4.12 IPS |
|
|
Machine Translation (I8)
|
57% |
138
2.53 IPS |
