samsung SM-S938N
Geekbench AI Score
571
Single Precision Score
555
Half Precision Score
1175
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | dlwlrma |
| Upload Date | February 25 2025 01:07 PM |
| Views | 16 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938N |
| Model ID | samsung SM-S938N |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
427
79.4 IPS |
|
|
Image Classification (HP)
|
100% |
421
78.3 IPS |
|
|
Image Classification (Q)
|
99% |
1049
195.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
540
8.75 IPS |
|
|
Image Segmentation (HP)
|
100% |
535
8.67 IPS |
|
|
Image Segmentation (Q)
|
98% |
1049
17.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
651
0.76 IPS |
|
|
Pose Estimation (HP)
|
100% |
523
0.61 IPS |
|
|
Pose Estimation (Q)
|
98% |
1971
2.31 IPS |
|
|
Object Detection (SP)
|
100% |
302
23.9 IPS |
|
|
Object Detection (HP)
|
100% |
304
24.1 IPS |
|
|
Object Detection (Q)
|
87% |
806
64.7 IPS |
|
|
Face Detection (SP)
|
100% |
785
9.32 IPS |
|
|
Face Detection (HP)
|
100% |
785
9.32 IPS |
|
|
Face Detection (Q)
|
97% |
1804
21.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
752
5.80 IPS |
|
|
Depth Estimation (HP)
|
99% |
656
5.05 IPS |
|
|
Depth Estimation (Q)
|
64% |
1318
12.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1166
1.50 IPS |
|
|
Style Transfer (HP)
|
100% |
1078
1.39 IPS |
|
|
Style Transfer (Q)
|
98% |
2459
3.17 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
340
12.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
362
13.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1286
47.6 IPS |
|
|
Text Classification (SP)
|
100% |
466
622.1 IPS |
|
|
Text Classification (HP)
|
100% |
466
622.4 IPS |
|
|
Text Classification (Q)
|
91% |
718
964.9 IPS |
|
|
Machine Translation (SP)
|
100% |
752
13.0 IPS |
|
|
Machine Translation (HP)
|
100% |
838
14.4 IPS |
|
|
Machine Translation (Q)
|
57% |
536
13.1 IPS |
