samsung SM-S938B
Geekbench AI Score
2783
Single Precision Score
2792
Half Precision Score
4996
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 17 2025 04:57 AM |
| Views | 2 |
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% |
1904
354.0 IPS |
|
|
Image Classification (HP)
|
100% |
1905
354.2 IPS |
|
|
Image Classification (Q)
|
100% |
4072
757.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2321
37.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2244
36.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
4186
68.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
5226
6.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
5505
6.42 IPS |
|
|
Pose Estimation (Q)
|
84% |
13880
16.5 IPS |
|
|
Object Detection (SP)
|
98% |
1743
138.7 IPS |
|
|
Object Detection (HP)
|
98% |
1745
138.9 IPS |
|
|
Object Detection (Q)
|
83% |
3981
321.6 IPS |
|
|
Face Detection (SP)
|
100% |
4171
49.6 IPS |
|
|
Face Detection (HP)
|
100% |
4369
51.9 IPS |
|
|
Face Detection (Q)
|
95% |
9482
113.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
4593
35.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
4683
36.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
10927
100.1 IPS |
|
|
Style Transfer (SP)
|
89% |
11443
14.9 IPS |
|
|
Style Transfer (HP)
|
89% |
11489
14.9 IPS |
|
|
Style Transfer (Q)
|
98% |
25813
33.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2380
87.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2352
86.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6606
244.8 IPS |
|
|
Text Classification (SP)
|
100% |
966
1.29 KIPS |
|
|
Text Classification (HP)
|
99% |
969
1.29 KIPS |
|
|
Text Classification (Q)
|
88% |
1048
1.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
1378
23.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1309
22.5 IPS |
|
|
Machine Translation (Q)
|
50% |
556
19.8 IPS |
