samsung SM-A166W
Geekbench AI Score
316
Single Precision Score
547
Half Precision Score
450
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 24 2025 05:59 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
178
33.1 IPS |
|
|
Image Classification (HP)
|
100% |
371
69.1 IPS |
|
|
Image Classification (Q)
|
97% |
306
57.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
548
8.89 IPS |
|
|
Image Segmentation (Q)
|
98% |
531
8.63 IPS |
|
|
Pose Estimation (SP)
|
100% |
1129
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2161
2.52 IPS |
|
|
Pose Estimation (Q)
|
95% |
2082
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
318
25.2 IPS |
|
|
Object Detection (Q)
|
83% |
293
23.6 IPS |
|
|
Face Detection (SP)
|
100% |
611
7.26 IPS |
|
|
Face Detection (HP)
|
100% |
1171
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
995
11.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
768
5.92 IPS |
|
|
Depth Estimation (HP)
|
98% |
1479
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1163
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1842
2.37 IPS |
|
|
Style Transfer (HP)
|
100% |
3993
5.13 IPS |
|
|
Style Transfer (Q)
|
98% |
3988
5.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
417
15.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
754
27.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
758
28.1 IPS |
|
|
Text Classification (SP)
|
35% |
11
98.7 IPS |
|
|
Text Classification (HP)
|
29% |
10
171.6 IPS |
|
|
Text Classification (Q)
|
32% |
12
154.8 IPS |
|
|
Machine Translation (SP)
|
100% |
265
4.56 IPS |
|
|
Machine Translation (HP)
|
100% |
330
5.69 IPS |
|
|
Machine Translation (Q)
|
43% |
83
4.82 IPS |
