samsung SM-A356B
Geekbench AI Score
196
Single Precision Score
359
Half Precision Score
514
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | kszycho |
| Upload Date | September 24 2025 09:39 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-A356B |
| Model ID | samsung SM-A356B |
| 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 | 7.26 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
126
23.4 IPS |
|
|
Image Classification (HP)
|
100% |
126
23.5 IPS |
|
|
Image Classification (Q)
|
99% |
337
62.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
312
5.05 IPS |
|
|
Image Segmentation (HP)
|
100% |
445
7.22 IPS |
|
|
Image Segmentation (Q)
|
98% |
377
6.12 IPS |
|
|
Pose Estimation (SP)
|
100% |
93
0.11 IPS |
|
|
Pose Estimation (HP)
|
99% |
2467
2.88 IPS |
|
|
Pose Estimation (Q)
|
98% |
884
1.03 IPS |
|
|
Object Detection (SP)
|
100% |
126
10.0 IPS |
|
|
Object Detection (HP)
|
100% |
126
10.0 IPS |
|
|
Object Detection (Q)
|
87% |
365
29.3 IPS |
|
|
Face Detection (SP)
|
100% |
326
3.88 IPS |
|
|
Face Detection (HP)
|
100% |
328
3.90 IPS |
|
|
Face Detection (Q)
|
97% |
734
8.75 IPS |
|
|
Depth Estimation (SP)
|
100% |
279
2.15 IPS |
|
|
Depth Estimation (HP)
|
99% |
280
2.15 IPS |
|
|
Depth Estimation (Q)
|
64% |
682
6.19 IPS |
|
|
Style Transfer (SP)
|
100% |
480
0.62 IPS |
|
|
Style Transfer (HP)
|
100% |
482
0.62 IPS |
|
|
Style Transfer (Q)
|
98% |
1341
1.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
79
2.92 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
860
31.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
483
17.9 IPS |
|
|
Text Classification (SP)
|
100% |
180
240.4 IPS |
|
|
Text Classification (HP)
|
100% |
180
240.8 IPS |
|
|
Text Classification (Q)
|
91% |
344
462.0 IPS |
|
|
Machine Translation (SP)
|
100% |
304
5.23 IPS |
|
|
Machine Translation (HP)
|
100% |
306
5.27 IPS |
|
|
Machine Translation (Q)
|
57% |
287
7.00 IPS |
