samsung SM-A166W
Geekbench AI Score
315
Single Precision Score
551
Half Precision Score
454
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 31 2026 08:56 PM |
| Views | 9 |
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% |
181
33.6 IPS |
|
|
Image Classification (HP)
|
100% |
352
65.4 IPS |
|
|
Image Classification (Q)
|
97% |
310
57.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
273
4.42 IPS |
|
|
Image Segmentation (HP)
|
100% |
555
8.99 IPS |
|
|
Image Segmentation (Q)
|
98% |
529
8.60 IPS |
|
|
Pose Estimation (SP)
|
100% |
1145
1.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
2115
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2095
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
318
25.3 IPS |
|
|
Object Detection (Q)
|
83% |
299
24.1 IPS |
|
|
Face Detection (SP)
|
100% |
609
7.24 IPS |
|
|
Face Detection (HP)
|
100% |
1171
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
1017
12.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
769
5.93 IPS |
|
|
Depth Estimation (HP)
|
98% |
1482
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1163
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1839
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4019
5.17 IPS |
|
|
Style Transfer (Q)
|
98% |
3966
5.11 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
440
16.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
780
28.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
729
27.0 IPS |
|
|
Text Classification (SP)
|
35% |
10
94.7 IPS |
|
|
Text Classification (HP)
|
29% |
11
189.8 IPS |
|
|
Text Classification (Q)
|
32% |
13
161.7 IPS |
|
|
Machine Translation (SP)
|
100% |
260
4.48 IPS |
|
|
Machine Translation (HP)
|
100% |
330
5.69 IPS |
|
|
Machine Translation (Q)
|
43% |
83
4.82 IPS |
