samsung SM-A356N
Geekbench AI Score
522
Single Precision Score
841
Half Precision Score
655
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | September 06 2025 07:07 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-A356N |
| Model ID | samsung SM-A356N |
| Motherboard | s5e8835 |
| 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 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.30 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
286
53.1 IPS |
|
|
Image Classification (HP)
|
100% |
305
56.7 IPS |
|
|
Image Classification (Q)
|
97% |
357
66.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
545
8.83 IPS |
|
|
Image Segmentation (HP)
|
100% |
1105
17.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1043
17.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2417
2.82 IPS |
|
|
Pose Estimation (HP)
|
100% |
4689
5.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
4576
5.36 IPS |
|
|
Object Detection (SP)
|
100% |
347
27.6 IPS |
|
|
Object Detection (HP)
|
99% |
488
38.7 IPS |
|
|
Object Detection (Q)
|
83% |
444
35.8 IPS |
|
|
Face Detection (SP)
|
100% |
1219
14.5 IPS |
|
|
Face Detection (HP)
|
100% |
2277
27.1 IPS |
|
|
Face Detection (Q)
|
96% |
1939
23.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1588
12.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
2955
22.8 IPS |
|
|
Depth Estimation (Q)
|
62% |
2231
21.2 IPS |
|
|
Style Transfer (SP)
|
100% |
3724
4.79 IPS |
|
|
Style Transfer (HP)
|
100% |
8595
11.0 IPS |
|
|
Style Transfer (Q)
|
98% |
8414
10.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
804
29.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1490
55.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1163
43.1 IPS |
|
|
Text Classification (SP)
|
35% |
8
75.5 IPS |
|
|
Text Classification (HP)
|
35% |
13
120.0 IPS |
|
|
Text Classification (Q)
|
32% |
9
119.5 IPS |
|
|
Machine Translation (SP)
|
100% |
251
4.33 IPS |
|
|
Machine Translation (HP)
|
100% |
206
3.54 IPS |
|
|
Machine Translation (Q)
|
43% |
51
2.99 IPS |
