Samsung Galaxy A16
Geekbench AI Score
364
Single Precision Score
628
Half Precision Score
530
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | Coolooooooo |
| Upload Date | March 05 2026 11:10 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Samsung Exynos 1330 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy A16 |
| Model ID | samsung SM-A166B |
| 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 | 7.29 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
193
35.9 IPS |
|
|
Image Classification (HP)
|
100% |
392
72.8 IPS |
|
|
Image Classification (Q)
|
97% |
366
68.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
285
4.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
602
9.76 IPS |
|
|
Image Segmentation (Q)
|
98% |
581
9.45 IPS |
|
|
Pose Estimation (SP)
|
100% |
1192
1.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
2230
2.60 IPS |
|
|
Pose Estimation (Q)
|
95% |
2203
2.58 IPS |
|
|
Object Detection (SP)
|
100% |
199
15.8 IPS |
|
|
Object Detection (HP)
|
99% |
395
31.3 IPS |
|
|
Object Detection (Q)
|
83% |
368
29.7 IPS |
|
|
Face Detection (SP)
|
100% |
700
8.32 IPS |
|
|
Face Detection (HP)
|
100% |
1403
16.7 IPS |
|
|
Face Detection (Q)
|
96% |
1246
14.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
862
6.64 IPS |
|
|
Depth Estimation (HP)
|
98% |
1622
12.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1277
12.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1940
2.49 IPS |
|
|
Style Transfer (HP)
|
100% |
4168
5.36 IPS |
|
|
Style Transfer (Q)
|
98% |
4127
5.32 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
505
18.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
913
33.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
895
33.2 IPS |
|
|
Text Classification (SP)
|
35% |
16
144.2 IPS |
|
|
Text Classification (HP)
|
29% |
14
244.9 IPS |
|
|
Text Classification (Q)
|
32% |
19
243.5 IPS |
|
|
Machine Translation (SP)
|
100% |
337
5.80 IPS |
|
|
Machine Translation (HP)
|
100% |
379
6.52 IPS |
|
|
Machine Translation (Q)
|
43% |
92
5.35 IPS |
