samsung SM-A166W
Geekbench AI Score
318
Single Precision Score
559
Half Precision Score
462
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 19 2025 02:39 AM |
| Views | 7 |
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% |
168
31.3 IPS |
|
|
Image Classification (HP)
|
100% |
333
61.9 IPS |
|
|
Image Classification (Q)
|
97% |
310
57.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
272
4.42 IPS |
|
|
Image Segmentation (HP)
|
100% |
564
9.14 IPS |
|
|
Image Segmentation (Q)
|
98% |
538
8.74 IPS |
|
|
Pose Estimation (SP)
|
100% |
1127
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2116
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2077
2.43 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
325
25.8 IPS |
|
|
Object Detection (Q)
|
83% |
295
23.8 IPS |
|
|
Face Detection (SP)
|
100% |
612
7.27 IPS |
|
|
Face Detection (HP)
|
100% |
1396
16.6 IPS |
|
|
Face Detection (Q)
|
96% |
1268
15.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
862
6.64 IPS |
|
|
Depth Estimation (HP)
|
98% |
1491
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1181
11.2 IPS |
|
|
Style Transfer (SP)
|
100% |
1845
2.37 IPS |
|
|
Style Transfer (HP)
|
100% |
4020
5.17 IPS |
|
|
Style Transfer (Q)
|
98% |
3986
5.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
410
15.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
770
28.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
750
27.8 IPS |
|
|
Text Classification (SP)
|
35% |
11
96.5 IPS |
|
|
Text Classification (HP)
|
29% |
11
189.3 IPS |
|
|
Text Classification (Q)
|
32% |
12
158.5 IPS |
|
|
Machine Translation (SP)
|
100% |
268
4.61 IPS |
|
|
Machine Translation (HP)
|
100% |
327
5.64 IPS |
|
|
Machine Translation (Q)
|
43% |
81
4.74 IPS |
