samsung SM-A166W
Geekbench AI Score
323
Single Precision Score
560
Half Precision Score
467
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 14 2026 09:37 AM |
| Views | 7 |
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% |
185
34.4 IPS |
|
|
Image Classification (HP)
|
100% |
337
62.6 IPS |
|
|
Image Classification (Q)
|
97% |
315
58.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
275
4.45 IPS |
|
|
Image Segmentation (HP)
|
100% |
546
8.85 IPS |
|
|
Image Segmentation (Q)
|
98% |
541
8.80 IPS |
|
|
Pose Estimation (SP)
|
100% |
1143
1.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
2116
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2087
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
325
25.8 IPS |
|
|
Object Detection (Q)
|
83% |
301
24.3 IPS |
|
|
Face Detection (SP)
|
100% |
614
7.29 IPS |
|
|
Face Detection (HP)
|
100% |
1218
14.5 IPS |
|
|
Face Detection (Q)
|
96% |
1071
12.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
774
5.96 IPS |
|
|
Depth Estimation (HP)
|
98% |
1483
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1162
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1856
2.39 IPS |
|
|
Style Transfer (HP)
|
100% |
4009
5.15 IPS |
|
|
Style Transfer (Q)
|
98% |
3975
5.13 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
457
16.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
917
33.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
793
29.4 IPS |
|
|
Text Classification (SP)
|
35% |
11
103.6 IPS |
|
|
Text Classification (HP)
|
29% |
11
191.6 IPS |
|
|
Text Classification (Q)
|
32% |
13
168.9 IPS |
|
|
Machine Translation (SP)
|
100% |
282
4.86 IPS |
|
|
Machine Translation (HP)
|
100% |
332
5.72 IPS |
|
|
Machine Translation (Q)
|
43% |
92
5.35 IPS |
