samsung SM-S938B
Geekbench AI Score
2853
Single Precision Score
2848
Half Precision Score
5104
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 22 2025 03:03 AM |
| Views | 1 |
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% |
1992
370.5 IPS |
|
|
Image Classification (HP)
|
100% |
2065
384.0 IPS |
|
|
Image Classification (Q)
|
100% |
4483
833.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2381
38.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2478
40.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
4994
81.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
5446
6.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
5316
6.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
13213
15.7 IPS |
|
|
Object Detection (SP)
|
98% |
1749
139.2 IPS |
|
|
Object Detection (HP)
|
98% |
1720
136.9 IPS |
|
|
Object Detection (Q)
|
83% |
3991
322.4 IPS |
|
|
Face Detection (SP)
|
100% |
4425
52.6 IPS |
|
|
Face Detection (HP)
|
100% |
4428
52.6 IPS |
|
|
Face Detection (Q)
|
95% |
9627
114.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
4602
35.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
4673
36.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
10601
97.1 IPS |
|
|
Style Transfer (SP)
|
89% |
11809
15.3 IPS |
|
|
Style Transfer (HP)
|
89% |
11461
14.9 IPS |
|
|
Style Transfer (Q)
|
98% |
25182
32.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2388
88.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2432
89.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6635
245.9 IPS |
|
|
Text Classification (SP)
|
100% |
995
1.33 KIPS |
|
|
Text Classification (HP)
|
99% |
957
1.28 KIPS |
|
|
Text Classification (Q)
|
88% |
1037
1.40 KIPS |
|
|
Machine Translation (SP)
|
100% |
1386
23.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1362
23.5 IPS |
|
|
Machine Translation (Q)
|
50% |
575
20.4 IPS |
