samsung SM-S938B
Geekbench AI Score
2705
Single Precision Score
2777
Half Precision Score
4252
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 13 2025 12:42 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
2081
387.0 IPS |
|
|
Image Classification (HP)
|
100% |
2069
384.7 IPS |
|
|
Image Classification (Q)
|
100% |
4657
866.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2423
39.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2493
40.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
5231
85.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
5599
6.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
5609
6.54 IPS |
|
|
Pose Estimation (Q)
|
84% |
13967
16.6 IPS |
|
|
Object Detection (SP)
|
98% |
1610
128.1 IPS |
|
|
Object Detection (HP)
|
98% |
1612
128.3 IPS |
|
|
Object Detection (Q)
|
83% |
1328
107.3 IPS |
|
|
Face Detection (SP)
|
100% |
3783
44.9 IPS |
|
|
Face Detection (HP)
|
100% |
3986
47.4 IPS |
|
|
Face Detection (Q)
|
95% |
7831
93.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
4215
32.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
4887
37.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
11056
101.3 IPS |
|
|
Style Transfer (SP)
|
89% |
11776
15.3 IPS |
|
|
Style Transfer (HP)
|
89% |
11499
14.9 IPS |
|
|
Style Transfer (Q)
|
98% |
26019
33.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2303
85.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2305
85.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4908
181.9 IPS |
|
|
Text Classification (SP)
|
100% |
775
1.03 KIPS |
|
|
Text Classification (HP)
|
99% |
808
1.08 KIPS |
|
|
Text Classification (Q)
|
88% |
672
906.9 IPS |
|
|
Machine Translation (SP)
|
100% |
1378
23.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1406
24.2 IPS |
|
|
Machine Translation (Q)
|
50% |
576
20.4 IPS |
