samsung SM-A166W
Geekbench AI Score
311
Single Precision Score
540
Half Precision Score
457
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 04 2025 08:24 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
178
33.1 IPS |
|
|
Image Classification (HP)
|
100% |
343
63.8 IPS |
|
|
Image Classification (Q)
|
97% |
308
57.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
269
4.35 IPS |
|
|
Image Segmentation (HP)
|
100% |
558
9.05 IPS |
|
|
Image Segmentation (Q)
|
98% |
533
8.67 IPS |
|
|
Pose Estimation (SP)
|
100% |
1127
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2111
2.46 IPS |
|
|
Pose Estimation (Q)
|
95% |
2089
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
326
25.9 IPS |
|
|
Object Detection (Q)
|
83% |
299
24.2 IPS |
|
|
Face Detection (SP)
|
100% |
612
7.27 IPS |
|
|
Face Detection (HP)
|
100% |
1163
13.8 IPS |
|
|
Face Detection (Q)
|
96% |
1034
12.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
766
5.90 IPS |
|
|
Depth Estimation (HP)
|
98% |
1481
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1167
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1838
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4127
5.31 IPS |
|
|
Style Transfer (Q)
|
98% |
3985
5.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
420
15.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
763
28.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
744
27.6 IPS |
|
|
Text Classification (SP)
|
35% |
9
84.2 IPS |
|
|
Text Classification (HP)
|
29% |
9
160.3 IPS |
|
|
Text Classification (Q)
|
32% |
13
171.5 IPS |
|
|
Machine Translation (SP)
|
100% |
281
4.84 IPS |
|
|
Machine Translation (HP)
|
100% |
329
5.67 IPS |
|
|
Machine Translation (Q)
|
43% |
85
4.93 IPS |
