samsung SM-S938B
Geekbench AI Score
2623
Single Precision Score
2581
Half Precision Score
4610
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | October 20 2025 04:16 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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 | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2124
395.1 IPS |
|
|
Image Classification (HP)
|
100% |
2111
392.6 IPS |
|
|
Image Classification (Q)
|
100% |
4696
873.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2523
40.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2490
40.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
5497
89.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
5679
6.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
5417
6.32 IPS |
|
|
Pose Estimation (Q)
|
84% |
13588
16.1 IPS |
|
|
Object Detection (SP)
|
98% |
1791
142.5 IPS |
|
|
Object Detection (HP)
|
98% |
1762
140.2 IPS |
|
|
Object Detection (Q)
|
83% |
4084
329.9 IPS |
|
|
Face Detection (SP)
|
100% |
4451
52.9 IPS |
|
|
Face Detection (HP)
|
100% |
4221
50.2 IPS |
|
|
Face Detection (Q)
|
95% |
8710
104.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
3976
30.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
4631
35.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
10773
98.7 IPS |
|
|
Style Transfer (SP)
|
89% |
11667
15.1 IPS |
|
|
Style Transfer (HP)
|
89% |
11732
15.2 IPS |
|
|
Style Transfer (Q)
|
98% |
23842
30.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2289
84.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2019
74.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4715
174.7 IPS |
|
|
Text Classification (SP)
|
100% |
436
581.5 IPS |
|
|
Text Classification (HP)
|
99% |
415
553.8 IPS |
|
|
Text Classification (Q)
|
88% |
524
706.3 IPS |
|
|
Machine Translation (SP)
|
100% |
1375
23.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1363
23.5 IPS |
|
|
Machine Translation (Q)
|
50% |
548
19.5 IPS |
