samsung SM-S938U1
Geekbench AI Score
767
Single Precision Score
27884
Half Precision Score
62976
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 21 2025 05:46 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% |
477
88.7 IPS |
|
|
Image Classification (HP)
|
100% |
21470
3.99 KIPS |
|
|
Image Classification (Q)
|
97% |
49586
9.25 KIPS |
|
|
Image Segmentation (SP)
|
100% |
616
9.99 IPS |
|
|
Image Segmentation (HP)
|
100% |
13736
222.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
42430
689.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
791
0.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
123946
144.6 IPS |
|
|
Pose Estimation (Q)
|
98% |
479687
561.4 IPS |
|
|
Object Detection (SP)
|
100% |
440
34.9 IPS |
|
|
Object Detection (HP)
|
100% |
19847
1.57 KIPS |
|
|
Object Detection (Q)
|
85% |
22997
1.85 KIPS |
|
|
Face Detection (SP)
|
100% |
1121
13.3 IPS |
|
|
Face Detection (HP)
|
100% |
44371
527.2 IPS |
|
|
Face Detection (Q)
|
97% |
163066
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
979
7.54 IPS |
|
|
Depth Estimation (HP)
|
99% |
84727
652.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
146690
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1608
2.07 IPS |
|
|
Style Transfer (HP)
|
98% |
98941
127.6 IPS |
|
|
Style Transfer (Q)
|
98% |
495850
639.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
517
19.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54898
2.03 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134840
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
691
922.5 IPS |
|
|
Text Classification (HP)
|
100% |
3921
5.23 KIPS |
|
|
Text Classification (Q)
|
93% |
8070
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1093
18.8 IPS |
|
|
Machine Translation (HP)
|
100% |
4892
84.3 IPS |
|
|
Machine Translation (Q)
|
56% |
3276
84.4 IPS |
