samsung SM-S938B
Geekbench AI Score
2445
Single Precision Score
2368
Half Precision Score
3247
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 26 2025 10:24 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938B |
| Model ID | samsung SM-S938B |
| 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% |
2159
401.6 IPS |
|
|
Image Classification (HP)
|
100% |
2085
387.7 IPS |
|
|
Image Classification (Q)
|
100% |
4229
786.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2510
40.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2463
39.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
2259
36.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
5155
6.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
3870
4.52 IPS |
|
|
Pose Estimation (Q)
|
84% |
6510
7.72 IPS |
|
|
Object Detection (SP)
|
98% |
1079
85.8 IPS |
|
|
Object Detection (HP)
|
98% |
1164
92.6 IPS |
|
|
Object Detection (Q)
|
83% |
1596
129.0 IPS |
|
|
Face Detection (SP)
|
100% |
3987
47.4 IPS |
|
|
Face Detection (HP)
|
100% |
4033
47.9 IPS |
|
|
Face Detection (Q)
|
95% |
7555
90.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
4445
34.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
4476
34.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
10029
91.9 IPS |
|
|
Style Transfer (SP)
|
89% |
11211
14.6 IPS |
|
|
Style Transfer (HP)
|
89% |
11416
14.8 IPS |
|
|
Style Transfer (Q)
|
98% |
19584
25.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1661
61.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1349
49.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3191
118.3 IPS |
|
|
Text Classification (SP)
|
100% |
575
767.2 IPS |
|
|
Text Classification (HP)
|
99% |
649
865.8 IPS |
|
|
Text Classification (Q)
|
88% |
530
715.1 IPS |
|
|
Machine Translation (SP)
|
100% |
1340
23.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1332
22.9 IPS |
|
|
Machine Translation (Q)
|
50% |
524
18.6 IPS |
