samsung SM-S938B
Geekbench AI Score
1193
Single Precision Score
1953
Half Precision Score
1855
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | bassiek |
| Upload Date | June 26 2025 10:08 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
656
122.0 IPS |
|
|
Image Classification (HP)
|
100% |
829
154.2 IPS |
|
|
Image Classification (Q)
|
99% |
782
145.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1607
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2171
35.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1163
18.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1660
1.94 IPS |
|
|
Pose Estimation (HP)
|
100% |
2457
2.87 IPS |
|
|
Pose Estimation (Q)
|
96% |
2424
2.84 IPS |
|
|
Object Detection (SP)
|
100% |
464
36.8 IPS |
|
|
Object Detection (HP)
|
100% |
1029
81.7 IPS |
|
|
Object Detection (Q)
|
86% |
1071
86.1 IPS |
|
|
Face Detection (SP)
|
100% |
2627
31.2 IPS |
|
|
Face Detection (HP)
|
100% |
3418
40.6 IPS |
|
|
Face Detection (Q)
|
97% |
4237
50.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
1292
9.95 IPS |
|
|
Depth Estimation (HP)
|
99% |
4370
33.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
3504
32.6 IPS |
|
|
Style Transfer (SP)
|
100% |
5122
6.58 IPS |
|
|
Style Transfer (HP)
|
100% |
10420
13.4 IPS |
|
|
Style Transfer (Q)
|
98% |
10785
13.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
595
22.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1680
62.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1798
66.6 IPS |
|
|
Text Classification (SP)
|
100% |
681
908.6 IPS |
|
|
Text Classification (HP)
|
100% |
672
896.3 IPS |
|
|
Text Classification (Q)
|
91% |
1097
1.47 KIPS |
|
|
Machine Translation (SP)
|
100% |
1023
17.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1011
17.4 IPS |
|
|
Machine Translation (Q)
|
57% |
649
15.9 IPS |
