samsung SM-S938B
Geekbench AI Score
2603
Single Precision Score
2616
Half Precision Score
4116
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 12 2025 12:47 PM |
| 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% |
2027
377.0 IPS |
|
|
Image Classification (HP)
|
100% |
2118
393.8 IPS |
|
|
Image Classification (Q)
|
100% |
4577
851.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2497
40.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2509
40.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
2223
36.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
5526
6.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
5535
6.46 IPS |
|
|
Pose Estimation (Q)
|
84% |
13176
15.6 IPS |
|
|
Object Detection (SP)
|
98% |
1652
131.5 IPS |
|
|
Object Detection (HP)
|
98% |
1613
128.3 IPS |
|
|
Object Detection (Q)
|
83% |
2437
196.8 IPS |
|
|
Face Detection (SP)
|
100% |
3771
44.8 IPS |
|
|
Face Detection (HP)
|
100% |
3994
47.5 IPS |
|
|
Face Detection (Q)
|
95% |
8847
105.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
3255
25.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
4572
35.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
11013
100.9 IPS |
|
|
Style Transfer (SP)
|
89% |
11621
15.1 IPS |
|
|
Style Transfer (HP)
|
89% |
10427
13.5 IPS |
|
|
Style Transfer (Q)
|
98% |
20946
27.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1927
71.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1901
70.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5483
203.2 IPS |
|
|
Text Classification (SP)
|
100% |
830
1.11 KIPS |
|
|
Text Classification (HP)
|
99% |
625
833.9 IPS |
|
|
Text Classification (Q)
|
88% |
655
883.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1357
23.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1400
24.1 IPS |
|
|
Machine Translation (Q)
|
50% |
584
20.7 IPS |
