samsung SM-S938U1 S25U samsung SM-S938U1
Geekbench AI Score
1151
Single Precision Score
1961
Half Precision Score
1924
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | jeradhill |
| Upload Date | September 03 2025 03:16 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938U1 |
| Model ID | samsung SM-S938U1 |
| 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% |
515
95.8 IPS |
|
|
Image Classification (HP)
|
100% |
942
175.2 IPS |
|
|
Image Classification (Q)
|
99% |
1125
209.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1585
25.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2198
35.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
1972
32.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1670
1.95 IPS |
|
|
Pose Estimation (HP)
|
100% |
1955
2.28 IPS |
|
|
Pose Estimation (Q)
|
96% |
2150
2.52 IPS |
|
|
Object Detection (SP)
|
100% |
455
36.1 IPS |
|
|
Object Detection (HP)
|
100% |
1082
85.8 IPS |
|
|
Object Detection (Q)
|
86% |
1021
82.0 IPS |
|
|
Face Detection (SP)
|
100% |
2543
30.2 IPS |
|
|
Face Detection (HP)
|
100% |
4440
52.8 IPS |
|
|
Face Detection (Q)
|
97% |
3687
44.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
1407
10.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
3869
29.9 IPS |
|
|
Depth Estimation (Q)
|
63% |
3249
30.2 IPS |
|
|
Style Transfer (SP)
|
100% |
4790
6.16 IPS |
|
|
Style Transfer (HP)
|
100% |
10164
13.1 IPS |
|
|
Style Transfer (Q)
|
98% |
9862
12.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
567
20.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1606
59.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1581
58.6 IPS |
|
|
Text Classification (SP)
|
100% |
670
893.8 IPS |
|
|
Text Classification (HP)
|
100% |
679
906.8 IPS |
|
|
Text Classification (Q)
|
91% |
1080
1.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
1019
17.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1010
17.4 IPS |
|
|
Machine Translation (Q)
|
57% |
708
17.3 IPS |
