samsung SM-A166W
Geekbench AI Score
510
Single Precision Score
886
Half Precision Score
995
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 14 2026 09:30 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% |
235
43.7 IPS |
|
|
Image Classification (HP)
|
100% |
487
90.6 IPS |
|
|
Image Classification (Q)
|
99% |
667
124.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
285
4.63 IPS |
|
|
Image Segmentation (HP)
|
100% |
529
8.57 IPS |
|
|
Image Segmentation (Q)
|
98% |
778
12.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1186
1.38 IPS |
|
|
Pose Estimation (HP)
|
92% |
2377
2.79 IPS |
|
|
Pose Estimation (Q)
|
96% |
1733
2.03 IPS |
|
|
Object Detection (SP)
|
100% |
230
18.2 IPS |
|
|
Object Detection (HP)
|
97% |
455
36.2 IPS |
|
|
Object Detection (Q)
|
85% |
694
55.9 IPS |
|
|
Face Detection (SP)
|
100% |
786
9.34 IPS |
|
|
Face Detection (HP)
|
100% |
1386
16.5 IPS |
|
|
Face Detection (Q)
|
97% |
1608
19.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
930
7.17 IPS |
|
|
Depth Estimation (HP)
|
98% |
1779
13.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
1547
14.3 IPS |
|
|
Style Transfer (SP)
|
89% |
1878
2.44 IPS |
|
|
Style Transfer (HP)
|
88% |
2274
2.95 IPS |
|
|
Style Transfer (Q)
|
98% |
3240
4.18 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
501
18.5 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
860
32.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
786
29.1 IPS |
|
|
Text Classification (SP)
|
100% |
229
306.2 IPS |
|
|
Text Classification (HP)
|
100% |
383
511.0 IPS |
|
|
Text Classification (Q)
|
93% |
514
690.2 IPS |
|
|
Machine Translation (SP)
|
100% |
418
7.21 IPS |
|
|
Machine Translation (HP)
|
96% |
583
10.1 IPS |
|
|
Machine Translation (Q)
|
55% |
469
12.6 IPS |
