samsung SM-S356V
Geekbench AI Score
881
Single Precision Score
869
Half Precision Score
1852
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 21 2025 02:53 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S356V |
| Model ID | samsung SM-S356V |
| 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% |
439
81.7 IPS |
|
|
Image Classification (HP)
|
100% |
441
82.1 IPS |
|
|
Image Classification (Q)
|
100% |
1372
255.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
528
8.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
503
8.15 IPS |
|
|
Image Segmentation (Q)
|
98% |
1615
26.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1875
2.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
1856
2.17 IPS |
|
|
Pose Estimation (Q)
|
84% |
3450
4.09 IPS |
|
|
Object Detection (SP)
|
100% |
400
31.7 IPS |
|
|
Object Detection (HP)
|
100% |
403
32.0 IPS |
|
|
Object Detection (Q)
|
83% |
1229
99.3 IPS |
|
|
Face Detection (SP)
|
100% |
1134
13.5 IPS |
|
|
Face Detection (HP)
|
100% |
1131
13.4 IPS |
|
|
Face Detection (Q)
|
95% |
3170
37.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1512
11.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
1476
11.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
3094
28.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3319
4.31 IPS |
|
|
Style Transfer (HP)
|
89% |
3520
4.57 IPS |
|
|
Style Transfer (Q)
|
98% |
7948
10.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
895
33.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
887
32.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1937
71.8 IPS |
|
|
Text Classification (SP)
|
100% |
480
640.2 IPS |
|
|
Text Classification (HP)
|
100% |
476
635.9 IPS |
|
|
Text Classification (Q)
|
88% |
883
1.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
670
11.5 IPS |
|
|
Machine Translation (HP)
|
100% |
602
10.4 IPS |
|
|
Machine Translation (Q)
|
50% |
379
13.5 IPS |
