samsung SM-S938B
Geekbench AI Score
1045
Single Precision Score
1840
Half Precision Score
1833
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 24 2025 12:59 PM |
| Views | 1 |
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% |
557
103.5 IPS |
|
|
Image Classification (HP)
|
100% |
712
132.4 IPS |
|
|
Image Classification (Q)
|
99% |
986
183.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1254
20.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2339
37.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1838
29.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1226
1.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
2147
2.50 IPS |
|
|
Pose Estimation (Q)
|
96% |
2145
2.51 IPS |
|
|
Object Detection (SP)
|
100% |
433
34.3 IPS |
|
|
Object Detection (HP)
|
100% |
1027
81.5 IPS |
|
|
Object Detection (Q)
|
86% |
1010
81.1 IPS |
|
|
Face Detection (SP)
|
100% |
2444
29.0 IPS |
|
|
Face Detection (HP)
|
100% |
4288
51.0 IPS |
|
|
Face Detection (Q)
|
97% |
4286
51.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1285
9.90 IPS |
|
|
Depth Estimation (HP)
|
99% |
3503
27.1 IPS |
|
|
Depth Estimation (Q)
|
63% |
2891
26.9 IPS |
|
|
Style Transfer (SP)
|
100% |
4353
5.60 IPS |
|
|
Style Transfer (HP)
|
100% |
9344
12.0 IPS |
|
|
Style Transfer (Q)
|
98% |
9333
12.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
576
21.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1600
59.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1580
58.5 IPS |
|
|
Text Classification (SP)
|
100% |
577
770.3 IPS |
|
|
Text Classification (HP)
|
100% |
577
770.5 IPS |
|
|
Text Classification (Q)
|
91% |
887
1.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
930
16.0 IPS |
|
|
Machine Translation (HP)
|
100% |
939
16.2 IPS |
|
|
Machine Translation (Q)
|
57% |
673
16.4 IPS |
