samsung SM-S938B
Geekbench AI Score
777
Single Precision Score
862
Half Precision Score
1740
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 23 2025 10:10 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-S938B |
| Model ID | samsung SM-S938B |
| Motherboard | exynos2100 |
| Governor | energy_step |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 revision 0 |
| Base Frequency | 2.21 GHz |
| Cluster 1 | 4 Cores @ 2.21 GHz |
| Cluster 2 | 3 Cores @ 2.81 GHz |
| Cluster 3 | 1 Core @ 2.91 GHz |
| Memory Information | |
|---|---|
| Size | 7.04 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
124
23.1 IPS |
|
|
Image Classification (HP)
|
100% |
257
47.9 IPS |
|
|
Image Classification (Q)
|
100% |
958
178.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
276
4.48 IPS |
|
|
Image Segmentation (HP)
|
100% |
378
6.13 IPS |
|
|
Image Segmentation (Q)
|
98% |
1408
22.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1935
2.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
1955
2.28 IPS |
|
|
Pose Estimation (Q)
|
84% |
3155
3.74 IPS |
|
|
Object Detection (SP)
|
100% |
427
33.8 IPS |
|
|
Object Detection (HP)
|
100% |
427
33.9 IPS |
|
|
Object Detection (Q)
|
83% |
1116
90.2 IPS |
|
|
Face Detection (SP)
|
100% |
1238
14.7 IPS |
|
|
Face Detection (HP)
|
100% |
1278
15.2 IPS |
|
|
Face Detection (Q)
|
95% |
2955
35.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1712
13.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
1734
13.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
3067
28.1 IPS |
|
|
Style Transfer (SP)
|
89% |
3380
4.39 IPS |
|
|
Style Transfer (HP)
|
89% |
3376
4.38 IPS |
|
|
Style Transfer (Q)
|
98% |
7434
9.59 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1048
38.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1039
38.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1826
67.7 IPS |
|
|
Text Classification (SP)
|
100% |
511
682.1 IPS |
|
|
Text Classification (HP)
|
100% |
516
688.3 IPS |
|
|
Text Classification (Q)
|
88% |
904
1.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
746
12.8 IPS |
|
|
Machine Translation (HP)
|
100% |
703
12.1 IPS |
|
|
Machine Translation (Q)
|
50% |
482
17.1 IPS |
