samsung SM-S938B
Geekbench AI Score
2891
Single Precision Score
2877
Half Precision Score
5199
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 20 2025 12:35 PM |
| 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% |
1958
364.1 IPS |
|
|
Image Classification (HP)
|
100% |
2146
399.0 IPS |
|
|
Image Classification (Q)
|
100% |
4635
862.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2515
40.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2488
40.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
5501
89.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
5802
6.77 IPS |
|
|
Pose Estimation (HP)
|
100% |
5539
6.46 IPS |
|
|
Pose Estimation (Q)
|
84% |
13681
16.2 IPS |
|
|
Object Detection (SP)
|
98% |
1688
134.3 IPS |
|
|
Object Detection (HP)
|
98% |
1773
141.1 IPS |
|
|
Object Detection (Q)
|
83% |
3996
322.8 IPS |
|
|
Face Detection (SP)
|
100% |
4531
53.8 IPS |
|
|
Face Detection (HP)
|
100% |
4463
53.0 IPS |
|
|
Face Detection (Q)
|
95% |
9863
117.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
4747
36.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
4603
35.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
10848
99.4 IPS |
|
|
Style Transfer (SP)
|
89% |
11688
15.2 IPS |
|
|
Style Transfer (HP)
|
89% |
11347
14.7 IPS |
|
|
Style Transfer (Q)
|
98% |
24513
31.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2485
91.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2469
91.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6528
241.9 IPS |
|
|
Text Classification (SP)
|
100% |
976
1.30 KIPS |
|
|
Text Classification (HP)
|
99% |
942
1.26 KIPS |
|
|
Text Classification (Q)
|
88% |
1099
1.48 KIPS |
|
|
Machine Translation (SP)
|
100% |
1389
23.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1368
23.6 IPS |
|
|
Machine Translation (Q)
|
50% |
551
19.6 IPS |
