samsung SM-A166W
Geekbench AI Score
316
Single Precision Score
540
Half Precision Score
453
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 01 2026 08:01 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-A166W |
| Model ID | samsung SM-A166W |
| 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 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
186
34.6 IPS |
|
|
Image Classification (HP)
|
100% |
338
62.9 IPS |
|
|
Image Classification (Q)
|
97% |
320
59.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
272
4.41 IPS |
|
|
Image Segmentation (HP)
|
100% |
553
8.97 IPS |
|
|
Image Segmentation (Q)
|
98% |
528
8.58 IPS |
|
|
Pose Estimation (SP)
|
100% |
1135
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2107
2.46 IPS |
|
|
Pose Estimation (Q)
|
95% |
2077
2.43 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
320
25.4 IPS |
|
|
Object Detection (Q)
|
83% |
316
25.5 IPS |
|
|
Face Detection (SP)
|
100% |
615
7.31 IPS |
|
|
Face Detection (HP)
|
100% |
1183
14.1 IPS |
|
|
Face Detection (Q)
|
96% |
981
11.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
765
5.90 IPS |
|
|
Depth Estimation (HP)
|
98% |
1478
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1161
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1842
2.37 IPS |
|
|
Style Transfer (HP)
|
100% |
4015
5.16 IPS |
|
|
Style Transfer (Q)
|
98% |
4004
5.16 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
433
16.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
832
30.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
750
27.8 IPS |
|
|
Text Classification (SP)
|
35% |
10
88.6 IPS |
|
|
Text Classification (HP)
|
29% |
9
150.9 IPS |
|
|
Text Classification (Q)
|
32% |
12
156.8 IPS |
|
|
Machine Translation (SP)
|
100% |
267
4.60 IPS |
|
|
Machine Translation (HP)
|
100% |
323
5.57 IPS |
|
|
Machine Translation (Q)
|
43% |
81
4.70 IPS |
