samsung SM-S938Q
Geekbench AI Score
681
Single Precision Score
674
Half Precision Score
1473
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | mamiyoshi |
| Upload Date | April 28 2025 02:09 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938Q |
| Model ID | samsung SM-S938Q |
| 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% |
439
81.7 IPS |
|
|
Image Classification (HP)
|
100% |
435
80.9 IPS |
|
|
Image Classification (Q)
|
99% |
1091
203.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
554
8.98 IPS |
|
|
Image Segmentation (HP)
|
100% |
556
9.01 IPS |
|
|
Image Segmentation (Q)
|
98% |
1127
18.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
732
0.85 IPS |
|
|
Pose Estimation (HP)
|
100% |
711
0.83 IPS |
|
|
Pose Estimation (Q)
|
98% |
2275
2.66 IPS |
|
|
Object Detection (SP)
|
100% |
407
32.3 IPS |
|
|
Object Detection (HP)
|
100% |
411
32.6 IPS |
|
|
Object Detection (Q)
|
87% |
1129
90.6 IPS |
|
|
Face Detection (SP)
|
100% |
1001
11.9 IPS |
|
|
Face Detection (HP)
|
100% |
899
10.7 IPS |
|
|
Face Detection (Q)
|
97% |
2078
24.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
759
5.85 IPS |
|
|
Depth Estimation (HP)
|
99% |
838
6.46 IPS |
|
|
Depth Estimation (Q)
|
64% |
1929
17.5 IPS |
|
|
Style Transfer (SP)
|
100% |
1479
1.90 IPS |
|
|
Style Transfer (HP)
|
100% |
1407
1.81 IPS |
|
|
Style Transfer (Q)
|
98% |
3991
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
456
16.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
443
16.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1602
59.4 IPS |
|
|
Text Classification (SP)
|
100% |
576
769.5 IPS |
|
|
Text Classification (HP)
|
100% |
577
770.1 IPS |
|
|
Text Classification (Q)
|
91% |
888
1.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
1013
17.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1019
17.6 IPS |
|
|
Machine Translation (Q)
|
57% |
670
16.4 IPS |
