samsung SM-A166W
Geekbench AI Score
492
Single Precision Score
842
Half Precision Score
989
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 22 2026 08:28 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
233
43.4 IPS |
|
|
Image Classification (HP)
|
100% |
389
72.3 IPS |
|
|
Image Classification (Q)
|
99% |
619
115.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
285
4.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
528
8.57 IPS |
|
|
Image Segmentation (Q)
|
98% |
776
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1117
1.30 IPS |
|
|
Pose Estimation (HP)
|
92% |
2184
2.57 IPS |
|
|
Pose Estimation (Q)
|
96% |
1737
2.04 IPS |
|
|
Object Detection (SP)
|
100% |
221
17.5 IPS |
|
|
Object Detection (HP)
|
97% |
419
33.3 IPS |
|
|
Object Detection (Q)
|
85% |
644
51.9 IPS |
|
|
Face Detection (SP)
|
100% |
675
8.02 IPS |
|
|
Face Detection (HP)
|
100% |
1249
14.8 IPS |
|
|
Face Detection (Q)
|
97% |
1545
18.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
908
6.99 IPS |
|
|
Depth Estimation (HP)
|
98% |
1682
13.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
1417
13.1 IPS |
|
|
Style Transfer (SP)
|
89% |
1754
2.28 IPS |
|
|
Style Transfer (HP)
|
88% |
2448
3.18 IPS |
|
|
Style Transfer (Q)
|
98% |
3433
4.43 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
458
16.9 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
860
32.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
892
33.1 IPS |
|
|
Text Classification (SP)
|
100% |
249
332.0 IPS |
|
|
Text Classification (HP)
|
100% |
411
549.0 IPS |
|
|
Text Classification (Q)
|
93% |
536
720.1 IPS |
|
|
Machine Translation (SP)
|
100% |
421
7.25 IPS |
|
|
Machine Translation (HP)
|
96% |
527
9.12 IPS |
|
|
Machine Translation (Q)
|
55% |
464
12.5 IPS |
