samsung SM-A166W
Geekbench AI Score
317
Single Precision Score
540
Half Precision Score
454
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 07 2026 08:16 AM |
| Views | 3 |
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% |
180
33.5 IPS |
|
|
Image Classification (HP)
|
100% |
349
64.8 IPS |
|
|
Image Classification (Q)
|
97% |
307
57.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
560
9.07 IPS |
|
|
Image Segmentation (Q)
|
98% |
530
8.62 IPS |
|
|
Pose Estimation (SP)
|
100% |
1130
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2121
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2077
2.43 IPS |
|
|
Object Detection (SP)
|
100% |
177
14.1 IPS |
|
|
Object Detection (HP)
|
99% |
316
25.0 IPS |
|
|
Object Detection (Q)
|
83% |
295
23.9 IPS |
|
|
Face Detection (SP)
|
100% |
614
7.29 IPS |
|
|
Face Detection (HP)
|
100% |
1205
14.3 IPS |
|
|
Face Detection (Q)
|
96% |
1038
12.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
772
5.95 IPS |
|
|
Depth Estimation (HP)
|
98% |
1482
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1156
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1829
2.35 IPS |
|
|
Style Transfer (HP)
|
100% |
4019
5.17 IPS |
|
|
Style Transfer (Q)
|
98% |
4003
5.16 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
428
15.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
757
27.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
778
28.8 IPS |
|
|
Text Classification (SP)
|
35% |
11
103.7 IPS |
|
|
Text Classification (HP)
|
29% |
9
160.0 IPS |
|
|
Text Classification (Q)
|
32% |
12
156.1 IPS |
|
|
Machine Translation (SP)
|
100% |
259
4.47 IPS |
|
|
Machine Translation (HP)
|
100% |
334
5.75 IPS |
|
|
Machine Translation (Q)
|
43% |
84
4.86 IPS |
