samsung SM-A166W
Geekbench AI Score
314
Single Precision Score
541
Half Precision Score
460
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 10 2025 12:51 PM |
| Views | 5 |
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
32.3 IPS |
|
|
Image Classification (HP)
|
100% |
353
65.6 IPS |
|
|
Image Classification (Q)
|
97% |
314
58.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
269
4.36 IPS |
|
|
Image Segmentation (HP)
|
100% |
555
8.99 IPS |
|
|
Image Segmentation (Q)
|
98% |
527
8.57 IPS |
|
|
Pose Estimation (SP)
|
100% |
1128
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2110
2.46 IPS |
|
|
Pose Estimation (Q)
|
95% |
2085
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
320
25.4 IPS |
|
|
Object Detection (Q)
|
83% |
302
24.4 IPS |
|
|
Face Detection (SP)
|
100% |
597
7.09 IPS |
|
|
Face Detection (HP)
|
100% |
1194
14.2 IPS |
|
|
Face Detection (Q)
|
96% |
1026
12.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
772
5.95 IPS |
|
|
Depth Estimation (HP)
|
98% |
1477
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1166
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1836
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4006
5.15 IPS |
|
|
Style Transfer (Q)
|
98% |
4001
5.16 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
415
15.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
790
29.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
759
28.1 IPS |
|
|
Text Classification (SP)
|
35% |
11
100.3 IPS |
|
|
Text Classification (HP)
|
29% |
9
156.5 IPS |
|
|
Text Classification (Q)
|
32% |
12
158.6 IPS |
|
|
Machine Translation (SP)
|
100% |
262
4.51 IPS |
|
|
Machine Translation (HP)
|
100% |
326
5.62 IPS |
|
|
Machine Translation (Q)
|
43% |
95
5.51 IPS |
