samsung SM-A166W
Geekbench AI Score
318
Single Precision Score
539
Half Precision Score
459
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 10 2025 02:50 AM |
| Views | 7 |
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% |
174
32.4 IPS |
|
|
Image Classification (HP)
|
100% |
332
61.7 IPS |
|
|
Image Classification (Q)
|
97% |
327
60.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
567
9.20 IPS |
|
|
Image Segmentation (Q)
|
98% |
548
8.91 IPS |
|
|
Pose Estimation (SP)
|
100% |
1129
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2114
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2080
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
176
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
325
25.8 IPS |
|
|
Object Detection (Q)
|
83% |
301
24.3 IPS |
|
|
Face Detection (SP)
|
100% |
622
7.39 IPS |
|
|
Face Detection (HP)
|
100% |
1175
14.0 IPS |
|
|
Face Detection (Q)
|
96% |
1076
12.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
773
5.96 IPS |
|
|
Depth Estimation (HP)
|
98% |
1509
11.7 IPS |
|
|
Depth Estimation (Q)
|
62% |
1169
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1844
2.37 IPS |
|
|
Style Transfer (HP)
|
100% |
4090
5.26 IPS |
|
|
Style Transfer (Q)
|
98% |
3994
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
459
16.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
769
28.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
752
27.9 IPS |
|
|
Text Classification (SP)
|
35% |
11
99.7 IPS |
|
|
Text Classification (HP)
|
29% |
9
160.4 IPS |
|
|
Text Classification (Q)
|
32% |
12
160.4 IPS |
|
|
Machine Translation (SP)
|
100% |
260
4.49 IPS |
|
|
Machine Translation (HP)
|
100% |
323
5.56 IPS |
|
|
Machine Translation (Q)
|
43% |
82
4.75 IPS |
