samsung SM-S938B
Geekbench AI Score
2371
Single Precision Score
2485
Half Precision Score
3907
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 29 2025 01:18 PM |
| Views | 3 |
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% |
2049
381.1 IPS |
|
|
Image Classification (HP)
|
100% |
1977
367.7 IPS |
|
|
Image Classification (Q)
|
100% |
4439
825.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2395
38.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2412
39.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
5250
85.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
4960
5.79 IPS |
|
|
Pose Estimation (HP)
|
100% |
5150
6.01 IPS |
|
|
Pose Estimation (Q)
|
84% |
13768
16.3 IPS |
|
|
Object Detection (SP)
|
98% |
1349
107.3 IPS |
|
|
Object Detection (HP)
|
98% |
1298
103.3 IPS |
|
|
Object Detection (Q)
|
83% |
2766
223.5 IPS |
|
|
Face Detection (SP)
|
100% |
3446
40.9 IPS |
|
|
Face Detection (HP)
|
100% |
3408
40.5 IPS |
|
|
Face Detection (Q)
|
95% |
7776
92.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
4404
34.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
4653
36.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
7242
66.3 IPS |
|
|
Style Transfer (SP)
|
89% |
11402
14.8 IPS |
|
|
Style Transfer (HP)
|
89% |
11234
14.6 IPS |
|
|
Style Transfer (Q)
|
98% |
17152
22.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1599
59.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1609
59.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3203
118.7 IPS |
|
|
Text Classification (SP)
|
100% |
444
592.7 IPS |
|
|
Text Classification (HP)
|
99% |
723
964.8 IPS |
|
|
Text Classification (Q)
|
88% |
592
797.9 IPS |
|
|
Machine Translation (SP)
|
100% |
1397
24.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1363
23.5 IPS |
|
|
Machine Translation (Q)
|
50% |
511
18.1 IPS |
