samsung SM-S938B
Geekbench AI Score
641
Single Precision Score
653
Half Precision Score
1437
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | xDJoelDx |
| Upload Date | February 27 2025 05:42 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
374
69.6 IPS |
|
|
Image Classification (HP)
|
100% |
408
75.9 IPS |
|
|
Image Classification (Q)
|
99% |
994
185.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
527
8.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
534
8.66 IPS |
|
|
Image Segmentation (Q)
|
98% |
1056
17.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
704
0.82 IPS |
|
|
Pose Estimation (HP)
|
100% |
690
0.81 IPS |
|
|
Pose Estimation (Q)
|
98% |
2669
3.12 IPS |
|
|
Object Detection (SP)
|
100% |
405
32.1 IPS |
|
|
Object Detection (HP)
|
100% |
405
32.1 IPS |
|
|
Object Detection (Q)
|
87% |
1010
81.0 IPS |
|
|
Face Detection (SP)
|
100% |
922
11.0 IPS |
|
|
Face Detection (HP)
|
100% |
774
9.20 IPS |
|
|
Face Detection (Q)
|
97% |
1792
21.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
842
6.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
896
6.91 IPS |
|
|
Depth Estimation (Q)
|
64% |
2130
19.3 IPS |
|
|
Style Transfer (SP)
|
100% |
1295
1.66 IPS |
|
|
Style Transfer (HP)
|
100% |
1446
1.86 IPS |
|
|
Style Transfer (Q)
|
98% |
3944
5.09 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
417
15.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
424
15.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1499
55.6 IPS |
|
|
Text Classification (SP)
|
100% |
538
717.5 IPS |
|
|
Text Classification (HP)
|
100% |
539
719.3 IPS |
|
|
Text Classification (Q)
|
91% |
830
1.12 KIPS |
|
|
Machine Translation (SP)
|
100% |
925
15.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1011
17.4 IPS |
|
|
Machine Translation (Q)
|
57% |
711
17.4 IPS |
