samsung SM-A166W
Geekbench AI Score
483
Single Precision Score
833
Half Precision Score
953
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 01 2026 09:56 AM |
| Views | 6 |
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% |
404
75.1 IPS |
|
|
Image Classification (Q)
|
99% |
621
115.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
268
4.34 IPS |
|
|
Image Segmentation (HP)
|
100% |
515
8.36 IPS |
|
|
Image Segmentation (Q)
|
98% |
745
12.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1111
1.30 IPS |
|
|
Pose Estimation (HP)
|
92% |
2054
2.41 IPS |
|
|
Pose Estimation (Q)
|
96% |
1643
1.92 IPS |
|
|
Object Detection (SP)
|
100% |
219
17.4 IPS |
|
|
Object Detection (HP)
|
97% |
416
33.2 IPS |
|
|
Object Detection (Q)
|
85% |
606
48.9 IPS |
|
|
Face Detection (SP)
|
100% |
657
7.81 IPS |
|
|
Face Detection (HP)
|
100% |
1253
14.9 IPS |
|
|
Face Detection (Q)
|
97% |
1468
17.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
888
6.84 IPS |
|
|
Depth Estimation (HP)
|
98% |
1604
12.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
1341
12.4 IPS |
|
|
Style Transfer (SP)
|
89% |
1748
2.27 IPS |
|
|
Style Transfer (HP)
|
88% |
2378
3.09 IPS |
|
|
Style Transfer (Q)
|
98% |
3483
4.49 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
460
17.0 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
838
31.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
831
30.8 IPS |
|
|
Text Classification (SP)
|
100% |
237
316.1 IPS |
|
|
Text Classification (HP)
|
100% |
392
522.6 IPS |
|
|
Text Classification (Q)
|
93% |
508
681.9 IPS |
|
|
Machine Translation (SP)
|
100% |
414
7.13 IPS |
|
|
Machine Translation (HP)
|
96% |
581
10.0 IPS |
|
|
Machine Translation (Q)
|
55% |
464
12.5 IPS |
