samsung SM-S938U
Geekbench AI Score
474
Single Precision Score
454
Half Precision Score
966
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | dgbrownnt |
| Upload Date | April 16 2025 03:29 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938U |
| Model ID | samsung SM-S938U |
| 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% |
431
80.1 IPS |
|
|
Image Classification (HP)
|
100% |
426
79.2 IPS |
|
|
Image Classification (Q)
|
99% |
1053
196.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
549
8.90 IPS |
|
|
Image Segmentation (HP)
|
100% |
550
8.92 IPS |
|
|
Image Segmentation (Q)
|
98% |
1093
17.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
629
0.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
473
0.55 IPS |
|
|
Pose Estimation (Q)
|
98% |
1680
1.97 IPS |
|
|
Object Detection (SP)
|
100% |
264
20.9 IPS |
|
|
Object Detection (HP)
|
100% |
267
21.2 IPS |
|
|
Object Detection (Q)
|
87% |
681
54.6 IPS |
|
|
Face Detection (SP)
|
100% |
689
8.19 IPS |
|
|
Face Detection (HP)
|
100% |
683
8.12 IPS |
|
|
Face Detection (Q)
|
97% |
1428
17.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
560
4.31 IPS |
|
|
Depth Estimation (HP)
|
99% |
496
3.82 IPS |
|
|
Depth Estimation (Q)
|
64% |
1056
9.58 IPS |
|
|
Style Transfer (SP)
|
100% |
899
1.16 IPS |
|
|
Style Transfer (HP)
|
100% |
895
1.15 IPS |
|
|
Style Transfer (Q)
|
98% |
2284
2.95 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
244
9.02 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
241
8.90 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
873
32.3 IPS |
|
|
Text Classification (SP)
|
100% |
318
424.5 IPS |
|
|
Text Classification (HP)
|
100% |
319
426.4 IPS |
|
|
Text Classification (Q)
|
91% |
492
661.4 IPS |
|
|
Machine Translation (SP)
|
100% |
551
9.48 IPS |
|
|
Machine Translation (HP)
|
100% |
551
9.49 IPS |
|
|
Machine Translation (Q)
|
57% |
367
8.97 IPS |
