samsung SM-S938B
Geekbench AI Score
1205
Single Precision Score
2005
Half Precision Score
1792
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | norti |
| Upload Date | January 25 2025 03:30 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938B |
| Model ID | samsung SM-S938B |
| 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% |
723
134.4 IPS |
|
|
Image Classification (HP)
|
100% |
987
183.6 IPS |
|
|
Image Classification (Q)
|
99% |
949
177.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1638
26.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2022
32.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1178
19.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1651
1.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
2442
2.85 IPS |
|
|
Pose Estimation (Q)
|
96% |
2165
2.54 IPS |
|
|
Object Detection (SP)
|
100% |
433
34.4 IPS |
|
|
Object Detection (HP)
|
100% |
1023
81.1 IPS |
|
|
Object Detection (Q)
|
86% |
1154
92.7 IPS |
|
|
Face Detection (SP)
|
100% |
2742
32.6 IPS |
|
|
Face Detection (HP)
|
100% |
3938
46.8 IPS |
|
|
Face Detection (Q)
|
97% |
3718
44.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1493
11.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
4168
32.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
3295
30.6 IPS |
|
|
Style Transfer (SP)
|
100% |
4685
6.02 IPS |
|
|
Style Transfer (HP)
|
100% |
10693
13.7 IPS |
|
|
Style Transfer (Q)
|
98% |
10153
13.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
602
22.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1799
66.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1662
61.6 IPS |
|
|
Text Classification (SP)
|
100% |
660
881.6 IPS |
|
|
Text Classification (HP)
|
100% |
671
895.3 IPS |
|
|
Text Classification (Q)
|
91% |
1064
1.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
1007
17.3 IPS |
|
|
Machine Translation (HP)
|
100% |
994
17.1 IPS |
|
|
Machine Translation (Q)
|
57% |
557
13.6 IPS |
