samsung SM-S938B
Geekbench AI Score
476
Single Precision Score
503
Half Precision Score
995
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | riussi |
| Upload Date | February 04 2025 01:55 PM |
| Views | 9 |
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% |
403
75.0 IPS |
|
|
Image Classification (HP)
|
100% |
403
75.0 IPS |
|
|
Image Classification (Q)
|
99% |
680
126.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
375
6.08 IPS |
|
|
Image Segmentation (HP)
|
100% |
377
6.11 IPS |
|
|
Image Segmentation (Q)
|
98% |
720
11.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
514
0.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
522
0.61 IPS |
|
|
Pose Estimation (Q)
|
98% |
1704
1.99 IPS |
|
|
Object Detection (SP)
|
100% |
240
19.1 IPS |
|
|
Object Detection (HP)
|
100% |
284
22.5 IPS |
|
|
Object Detection (Q)
|
87% |
764
61.2 IPS |
|
|
Face Detection (SP)
|
100% |
740
8.79 IPS |
|
|
Face Detection (HP)
|
100% |
737
8.75 IPS |
|
|
Face Detection (Q)
|
97% |
1680
20.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
654
5.04 IPS |
|
|
Depth Estimation (HP)
|
99% |
612
4.71 IPS |
|
|
Depth Estimation (Q)
|
64% |
1226
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1010
1.30 IPS |
|
|
Style Transfer (HP)
|
100% |
1074
1.38 IPS |
|
|
Style Transfer (Q)
|
98% |
2299
2.97 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
246
9.07 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
312
11.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1107
41.0 IPS |
|
|
Text Classification (SP)
|
100% |
400
534.2 IPS |
|
|
Text Classification (HP)
|
100% |
401
534.8 IPS |
|
|
Text Classification (Q)
|
91% |
617
828.8 IPS |
|
|
Machine Translation (SP)
|
100% |
668
11.5 IPS |
|
|
Machine Translation (HP)
|
100% |
770
13.3 IPS |
|
|
Machine Translation (Q)
|
57% |
466
11.4 IPS |
