samsung SM-A166W
Geekbench AI Score
313
Single Precision Score
537
Half Precision Score
448
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 14 2026 10:21 AM |
| Views | 4 |
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% |
170
31.5 IPS |
|
|
Image Classification (HP)
|
100% |
333
61.8 IPS |
|
|
Image Classification (Q)
|
97% |
297
55.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
269
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
539
8.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
529
8.60 IPS |
|
|
Pose Estimation (SP)
|
100% |
1130
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2119
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2088
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
318
25.2 IPS |
|
|
Object Detection (Q)
|
83% |
293
23.7 IPS |
|
|
Face Detection (SP)
|
100% |
610
7.25 IPS |
|
|
Face Detection (HP)
|
100% |
1176
14.0 IPS |
|
|
Face Detection (Q)
|
96% |
1011
12.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
767
5.91 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% |
4009
5.15 IPS |
|
|
Style Transfer (Q)
|
98% |
3976
5.13 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
407
15.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
796
29.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
733
27.1 IPS |
|
|
Text Classification (SP)
|
35% |
11
102.7 IPS |
|
|
Text Classification (HP)
|
29% |
9
159.8 IPS |
|
|
Text Classification (Q)
|
32% |
12
158.7 IPS |
|
|
Machine Translation (SP)
|
100% |
266
4.57 IPS |
|
|
Machine Translation (HP)
|
100% |
333
5.73 IPS |
|
|
Machine Translation (Q)
|
43% |
83
4.80 IPS |
