samsung SM-S938U1
Geekbench AI Score
745
Single Precision Score
27880
Half Precision Score
62990
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 21 2025 03:50 AM |
| Views | 14 |
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% |
476
88.5 IPS |
|
|
Image Classification (HP)
|
100% |
21574
4.01 KIPS |
|
|
Image Classification (Q)
|
97% |
49641
9.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
609
9.87 IPS |
|
|
Image Segmentation (HP)
|
100% |
13686
221.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
42577
692.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
780
0.91 IPS |
|
|
Pose Estimation (HP)
|
100% |
124021
144.7 IPS |
|
|
Pose Estimation (Q)
|
98% |
478338
559.9 IPS |
|
|
Object Detection (SP)
|
100% |
368
29.2 IPS |
|
|
Object Detection (HP)
|
100% |
19696
1.56 KIPS |
|
|
Object Detection (Q)
|
85% |
23254
1.87 KIPS |
|
|
Face Detection (SP)
|
100% |
1125
13.4 IPS |
|
|
Face Detection (HP)
|
100% |
44451
528.2 IPS |
|
|
Face Detection (Q)
|
97% |
163609
1.95 KIPS |
|
|
Depth Estimation (SP)
|
100% |
966
7.44 IPS |
|
|
Depth Estimation (HP)
|
99% |
84791
653.3 IPS |
|
|
Depth Estimation (Q)
|
63% |
146182
1.35 KIPS |
|
|
Style Transfer (SP)
|
100% |
1610
2.07 IPS |
|
|
Style Transfer (HP)
|
98% |
99040
127.7 IPS |
|
|
Style Transfer (Q)
|
98% |
492622
635.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
511
18.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
55033
2.03 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134899
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
660
881.1 IPS |
|
|
Text Classification (HP)
|
100% |
3912
5.22 KIPS |
|
|
Text Classification (Q)
|
93% |
8027
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1085
18.7 IPS |
|
|
Machine Translation (HP)
|
100% |
4896
84.3 IPS |
|
|
Machine Translation (Q)
|
56% |
3279
84.5 IPS |
