samsung SM-A166W
Geekbench AI Score
493
Single Precision Score
485
Half Precision Score
919
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | December 12 2025 03:22 AM |
| Views | 8 |
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% |
230
42.7 IPS |
|
|
Image Classification (HP)
|
100% |
230
42.8 IPS |
|
|
Image Classification (Q)
|
100% |
699
129.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
276
4.47 IPS |
|
|
Image Segmentation (HP)
|
100% |
294
4.76 IPS |
|
|
Image Segmentation (Q)
|
98% |
801
13.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1170
1.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
1087
1.27 IPS |
|
|
Pose Estimation (Q)
|
84% |
1644
1.95 IPS |
|
|
Object Detection (SP)
|
100% |
222
17.6 IPS |
|
|
Object Detection (HP)
|
100% |
216
17.2 IPS |
|
|
Object Detection (Q)
|
83% |
634
51.2 IPS |
|
|
Face Detection (SP)
|
100% |
746
8.86 IPS |
|
|
Face Detection (HP)
|
100% |
662
7.87 IPS |
|
|
Face Detection (Q)
|
95% |
1443
17.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
897
6.91 IPS |
|
|
Depth Estimation (HP)
|
99% |
889
6.85 IPS |
|
|
Depth Estimation (Q)
|
64% |
1337
12.2 IPS |
|
|
Style Transfer (SP)
|
89% |
1675
2.17 IPS |
|
|
Style Transfer (HP)
|
89% |
1678
2.18 IPS |
|
|
Style Transfer (Q)
|
98% |
3410
4.40 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
493
18.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
500
18.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
819
30.3 IPS |
|
|
Text Classification (SP)
|
100% |
234
312.2 IPS |
|
|
Text Classification (HP)
|
100% |
235
313.6 IPS |
|
|
Text Classification (Q)
|
88% |
488
658.2 IPS |
|
|
Machine Translation (SP)
|
100% |
402
6.92 IPS |
|
|
Machine Translation (HP)
|
100% |
397
6.84 IPS |
|
|
Machine Translation (Q)
|
50% |
282
10.0 IPS |
