samsung SM-S938U1
Geekbench AI Score
738
Single Precision Score
27789
Half Precision Score
62846
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 21 2025 02:31 AM |
| Views | 18 |
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% |
467
86.8 IPS |
|
|
Image Classification (HP)
|
100% |
21150
3.93 KIPS |
|
|
Image Classification (Q)
|
97% |
49799
9.29 KIPS |
|
|
Image Segmentation (SP)
|
100% |
594
9.63 IPS |
|
|
Image Segmentation (HP)
|
100% |
13593
220.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
42425
689.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
747
0.87 IPS |
|
|
Pose Estimation (HP)
|
100% |
123665
144.3 IPS |
|
|
Pose Estimation (Q)
|
98% |
478082
559.6 IPS |
|
|
Object Detection (SP)
|
100% |
435
34.5 IPS |
|
|
Object Detection (HP)
|
100% |
19978
1.58 KIPS |
|
|
Object Detection (Q)
|
85% |
22976
1.85 KIPS |
|
|
Face Detection (SP)
|
100% |
1106
13.1 IPS |
|
|
Face Detection (HP)
|
100% |
44479
528.5 IPS |
|
|
Face Detection (Q)
|
97% |
162355
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
961
7.40 IPS |
|
|
Depth Estimation (HP)
|
99% |
84476
650.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
145659
1.35 KIPS |
|
|
Style Transfer (SP)
|
100% |
1549
1.99 IPS |
|
|
Style Transfer (HP)
|
98% |
98709
127.3 IPS |
|
|
Style Transfer (Q)
|
98% |
493471
636.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
475
17.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54967
2.03 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134778
4.99 KIPS |
|
|
Text Classification (SP)
|
100% |
658
878.8 IPS |
|
|
Text Classification (HP)
|
100% |
3923
5.24 KIPS |
|
|
Text Classification (Q)
|
93% |
8041
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1047
18.0 IPS |
|
|
Machine Translation (HP)
|
100% |
4835
83.3 IPS |
|
|
Machine Translation (Q)
|
56% |
3275
84.4 IPS |
