samsung SM-S938B
Geekbench AI Score
2842
Single Precision Score
2813
Half Precision Score
4719
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | angelpradomx |
| Upload Date | February 22 2025 08:37 PM |
| Views | 6 |
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% |
2147
399.2 IPS |
|
|
Image Classification (HP)
|
100% |
2165
402.5 IPS |
|
|
Image Classification (Q)
|
100% |
4675
869.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2495
40.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2387
38.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
5406
87.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
5712
6.67 IPS |
|
|
Pose Estimation (HP)
|
100% |
5399
6.30 IPS |
|
|
Pose Estimation (Q)
|
84% |
13343
15.8 IPS |
|
|
Object Detection (SP)
|
98% |
1765
140.5 IPS |
|
|
Object Detection (HP)
|
98% |
1809
144.0 IPS |
|
|
Object Detection (Q)
|
83% |
4040
326.4 IPS |
|
|
Face Detection (SP)
|
100% |
4472
53.1 IPS |
|
|
Face Detection (HP)
|
100% |
4585
54.5 IPS |
|
|
Face Detection (Q)
|
95% |
9838
117.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
4720
36.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
4544
35.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
10576
96.9 IPS |
|
|
Style Transfer (SP)
|
89% |
11902
15.5 IPS |
|
|
Style Transfer (HP)
|
89% |
11590
15.0 IPS |
|
|
Style Transfer (Q)
|
98% |
24144
31.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2325
85.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2279
84.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5130
190.1 IPS |
|
|
Text Classification (SP)
|
100% |
811
1.08 KIPS |
|
|
Text Classification (HP)
|
99% |
853
1.14 KIPS |
|
|
Text Classification (Q)
|
88% |
570
769.0 IPS |
|
|
Machine Translation (SP)
|
100% |
1345
23.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1312
22.6 IPS |
|
|
Machine Translation (Q)
|
50% |
548
19.4 IPS |
