samsung SM-S938Q
Geekbench AI Score
586
Single Precision Score
584
Half Precision Score
1268
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | idanbo |
| Upload Date | February 02 2025 04:22 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938Q |
| Model ID | samsung SM-S938Q |
| 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% |
429
79.7 IPS |
|
|
Image Classification (HP)
|
100% |
417
77.6 IPS |
|
|
Image Classification (Q)
|
99% |
1067
199.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
544
8.82 IPS |
|
|
Image Segmentation (HP)
|
100% |
544
8.82 IPS |
|
|
Image Segmentation (Q)
|
98% |
1091
17.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
714
0.83 IPS |
|
|
Pose Estimation (HP)
|
100% |
609
0.71 IPS |
|
|
Pose Estimation (Q)
|
98% |
2111
2.47 IPS |
|
|
Object Detection (SP)
|
100% |
335
26.6 IPS |
|
|
Object Detection (HP)
|
100% |
358
28.4 IPS |
|
|
Object Detection (Q)
|
87% |
967
77.6 IPS |
|
|
Face Detection (SP)
|
100% |
849
10.1 IPS |
|
|
Face Detection (HP)
|
100% |
845
10.0 IPS |
|
|
Face Detection (Q)
|
97% |
1958
23.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
758
5.84 IPS |
|
|
Depth Estimation (HP)
|
99% |
690
5.31 IPS |
|
|
Depth Estimation (Q)
|
64% |
1473
13.4 IPS |
|
|
Style Transfer (SP)
|
100% |
1089
1.40 IPS |
|
|
Style Transfer (HP)
|
100% |
1091
1.40 IPS |
|
|
Style Transfer (Q)
|
98% |
2955
3.81 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
338
12.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
361
13.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1286
47.6 IPS |
|
|
Text Classification (SP)
|
100% |
466
621.7 IPS |
|
|
Text Classification (HP)
|
100% |
462
616.7 IPS |
|
|
Text Classification (Q)
|
91% |
718
965.6 IPS |
|
|
Machine Translation (SP)
|
100% |
775
13.3 IPS |
|
|
Machine Translation (HP)
|
100% |
887
15.3 IPS |
|
|
Machine Translation (Q)
|
57% |
575
14.1 IPS |
