samsung SM-S166V
Geekbench AI Score
524
Single Precision Score
522
Half Precision Score
1054
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Chance1111 |
| Upload Date | March 30 2025 08:17 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S166V |
| Model ID | samsung SM-S166V |
| 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% |
232
43.2 IPS |
|
|
Image Classification (HP)
|
100% |
229
42.6 IPS |
|
|
Image Classification (Q)
|
100% |
730
135.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
291
4.72 IPS |
|
|
Image Segmentation (HP)
|
100% |
293
4.76 IPS |
|
|
Image Segmentation (Q)
|
98% |
829
13.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1107
1.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
1089
1.27 IPS |
|
|
Pose Estimation (Q)
|
84% |
1704
2.02 IPS |
|
|
Object Detection (SP)
|
100% |
219
17.3 IPS |
|
|
Object Detection (HP)
|
100% |
217
17.2 IPS |
|
|
Object Detection (Q)
|
83% |
691
55.8 IPS |
|
|
Face Detection (SP)
|
100% |
763
9.06 IPS |
|
|
Face Detection (HP)
|
100% |
767
9.11 IPS |
|
|
Face Detection (Q)
|
95% |
1691
20.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
978
7.53 IPS |
|
|
Depth Estimation (HP)
|
99% |
961
7.40 IPS |
|
|
Depth Estimation (Q)
|
64% |
1623
14.9 IPS |
|
|
Style Transfer (SP)
|
89% |
1862
2.42 IPS |
|
|
Style Transfer (HP)
|
89% |
1879
2.44 IPS |
|
|
Style Transfer (Q)
|
98% |
4078
5.26 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
556
20.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
548
20.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
998
37.0 IPS |
|
|
Text Classification (SP)
|
100% |
277
370.3 IPS |
|
|
Text Classification (HP)
|
100% |
278
371.6 IPS |
|
|
Text Classification (Q)
|
88% |
583
786.4 IPS |
|
|
Machine Translation (SP)
|
100% |
450
7.75 IPS |
|
|
Machine Translation (HP)
|
100% |
455
7.84 IPS |
|
|
Machine Translation (Q)
|
50% |
367
13.0 IPS |
