samsung SM-S938U1
Geekbench AI Score
761
Single Precision Score
27643
Half Precision Score
62925
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 20 2025 05:17 PM |
| Views | 16 |
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% |
480
89.2 IPS |
|
|
Image Classification (HP)
|
100% |
21520
4.00 KIPS |
|
|
Image Classification (Q)
|
97% |
49574
9.25 KIPS |
|
|
Image Segmentation (SP)
|
100% |
617
10.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
13660
221.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
42308
688.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
796
0.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
120223
140.3 IPS |
|
|
Pose Estimation (Q)
|
98% |
480431
562.3 IPS |
|
|
Object Detection (SP)
|
100% |
437
34.6 IPS |
|
|
Object Detection (HP)
|
100% |
19229
1.53 KIPS |
|
|
Object Detection (Q)
|
85% |
22985
1.85 KIPS |
|
|
Face Detection (SP)
|
100% |
1120
13.3 IPS |
|
|
Face Detection (HP)
|
100% |
44406
527.6 IPS |
|
|
Face Detection (Q)
|
97% |
163443
1.95 KIPS |
|
|
Depth Estimation (SP)
|
100% |
973
7.50 IPS |
|
|
Depth Estimation (HP)
|
99% |
84835
653.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
146553
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1594
2.05 IPS |
|
|
Style Transfer (HP)
|
98% |
98846
127.5 IPS |
|
|
Style Transfer (Q)
|
98% |
495489
638.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
510
18.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54076
2.00 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
135005
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
659
879.6 IPS |
|
|
Text Classification (HP)
|
100% |
3912
5.22 KIPS |
|
|
Text Classification (Q)
|
93% |
8033
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1086
18.7 IPS |
|
|
Machine Translation (HP)
|
100% |
4867
83.8 IPS |
|
|
Machine Translation (Q)
|
56% |
3265
84.1 IPS |
