samsung SM-A166W
Geekbench AI Score
494
Single Precision Score
487
Half Precision Score
905
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 21 2025 02:12 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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
43.3 IPS |
|
|
Image Classification (HP)
|
100% |
231
42.9 IPS |
|
|
Image Classification (Q)
|
100% |
549
102.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
267
4.33 IPS |
|
|
Image Segmentation (HP)
|
100% |
291
4.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
796
12.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1150
1.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
1093
1.28 IPS |
|
|
Pose Estimation (Q)
|
84% |
1570
1.86 IPS |
|
|
Object Detection (SP)
|
100% |
227
18.0 IPS |
|
|
Object Detection (HP)
|
100% |
222
17.6 IPS |
|
|
Object Detection (Q)
|
83% |
607
49.0 IPS |
|
|
Face Detection (SP)
|
100% |
665
7.90 IPS |
|
|
Face Detection (HP)
|
100% |
753
8.95 IPS |
|
|
Face Detection (Q)
|
95% |
1513
18.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
919
7.08 IPS |
|
|
Depth Estimation (HP)
|
99% |
836
6.44 IPS |
|
|
Depth Estimation (Q)
|
64% |
1340
12.3 IPS |
|
|
Style Transfer (SP)
|
89% |
1746
2.27 IPS |
|
|
Style Transfer (HP)
|
89% |
1653
2.15 IPS |
|
|
Style Transfer (Q)
|
98% |
3658
4.72 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
512
18.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
471
17.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
825
30.6 IPS |
|
|
Text Classification (SP)
|
100% |
234
312.3 IPS |
|
|
Text Classification (HP)
|
100% |
235
313.9 IPS |
|
|
Text Classification (Q)
|
88% |
489
659.3 IPS |
|
|
Machine Translation (SP)
|
100% |
418
7.19 IPS |
|
|
Machine Translation (HP)
|
100% |
403
6.94 IPS |
|
|
Machine Translation (Q)
|
50% |
297
10.5 IPS |
