samsung SM-S938N
Geekbench AI Score
2513
Single Precision Score
2560
Half Precision Score
3905
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 23 2025 01:40 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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 | 14.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2050
381.2 IPS |
|
|
Image Classification (HP)
|
100% |
1994
370.9 IPS |
|
|
Image Classification (Q)
|
100% |
4467
830.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2358
38.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2325
37.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
5433
88.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
5426
6.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
4838
5.64 IPS |
|
|
Pose Estimation (Q)
|
84% |
12118
14.4 IPS |
|
|
Object Detection (SP)
|
98% |
1603
127.6 IPS |
|
|
Object Detection (HP)
|
98% |
1585
126.1 IPS |
|
|
Object Detection (Q)
|
83% |
2027
163.7 IPS |
|
|
Face Detection (SP)
|
100% |
4148
49.3 IPS |
|
|
Face Detection (HP)
|
100% |
3661
43.5 IPS |
|
|
Face Detection (Q)
|
95% |
7328
87.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
3477
26.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
4003
30.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
8536
78.2 IPS |
|
|
Style Transfer (SP)
|
89% |
10927
14.2 IPS |
|
|
Style Transfer (HP)
|
89% |
11546
15.0 IPS |
|
|
Style Transfer (Q)
|
98% |
23907
30.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2124
78.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2103
77.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4343
160.9 IPS |
|
|
Text Classification (SP)
|
100% |
547
729.7 IPS |
|
|
Text Classification (HP)
|
99% |
729
973.0 IPS |
|
|
Text Classification (Q)
|
88% |
465
627.5 IPS |
|
|
Machine Translation (SP)
|
100% |
1307
22.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1315
22.7 IPS |
|
|
Machine Translation (Q)
|
50% |
459
16.3 IPS |
