samsung SM-S938U1
Geekbench AI Score
683
Single Precision Score
27587
Half Precision Score
62305
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 20 2025 04:53 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| 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% |
465
86.5 IPS |
|
|
Image Classification (HP)
|
100% |
21103
3.92 KIPS |
|
|
Image Classification (Q)
|
97% |
49549
9.25 KIPS |
|
|
Image Segmentation (SP)
|
100% |
591
9.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
13684
221.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
42176
685.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
736
0.86 IPS |
|
|
Pose Estimation (HP)
|
100% |
123458
144.1 IPS |
|
|
Pose Estimation (Q)
|
98% |
478550
560.1 IPS |
|
|
Object Detection (SP)
|
100% |
367
29.1 IPS |
|
|
Object Detection (HP)
|
100% |
19558
1.55 KIPS |
|
|
Object Detection (Q)
|
85% |
22351
1.80 KIPS |
|
|
Face Detection (SP)
|
100% |
895
10.6 IPS |
|
|
Face Detection (HP)
|
100% |
42728
507.7 IPS |
|
|
Face Detection (Q)
|
97% |
154551
1.84 KIPS |
|
|
Depth Estimation (SP)
|
100% |
950
7.32 IPS |
|
|
Depth Estimation (HP)
|
99% |
84547
651.4 IPS |
|
|
Depth Estimation (Q)
|
63% |
146268
1.35 KIPS |
|
|
Style Transfer (SP)
|
100% |
1500
1.93 IPS |
|
|
Style Transfer (HP)
|
98% |
98881
127.5 IPS |
|
|
Style Transfer (Q)
|
98% |
492747
635.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
433
16.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54419
2.01 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134750
4.99 KIPS |
|
|
Text Classification (SP)
|
100% |
569
759.1 IPS |
|
|
Text Classification (HP)
|
100% |
3920
5.23 KIPS |
|
|
Text Classification (Q)
|
93% |
8048
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
957
16.5 IPS |
|
|
Machine Translation (HP)
|
100% |
4805
82.8 IPS |
|
|
Machine Translation (Q)
|
56% |
3265
84.1 IPS |
