samsung SM-S938B
Geekbench AI Score
2635
Single Precision Score
2650
Half Precision Score
4656
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 04 2025 01:25 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% |
1904
354.1 IPS |
|
|
Image Classification (HP)
|
100% |
1880
349.7 IPS |
|
|
Image Classification (Q)
|
100% |
4193
779.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2331
37.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2361
38.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
4822
78.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
5153
6.01 IPS |
|
|
Pose Estimation (HP)
|
100% |
5090
5.94 IPS |
|
|
Pose Estimation (Q)
|
84% |
12507
14.8 IPS |
|
|
Object Detection (SP)
|
98% |
1583
126.0 IPS |
|
|
Object Detection (HP)
|
98% |
1643
130.7 IPS |
|
|
Object Detection (Q)
|
83% |
3922
316.8 IPS |
|
|
Face Detection (SP)
|
100% |
4171
49.6 IPS |
|
|
Face Detection (HP)
|
100% |
4345
51.6 IPS |
|
|
Face Detection (Q)
|
95% |
8637
103.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
4181
32.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
4271
33.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
9346
85.6 IPS |
|
|
Style Transfer (SP)
|
89% |
11179
14.5 IPS |
|
|
Style Transfer (HP)
|
89% |
10707
13.9 IPS |
|
|
Style Transfer (Q)
|
98% |
24386
31.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2175
80.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2189
80.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5690
210.8 IPS |
|
|
Text Classification (SP)
|
100% |
822
1.10 KIPS |
|
|
Text Classification (HP)
|
99% |
799
1.07 KIPS |
|
|
Text Classification (Q)
|
88% |
808
1.09 KIPS |
|
|
Machine Translation (SP)
|
100% |
1282
22.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1324
22.8 IPS |
|
|
Machine Translation (Q)
|
50% |
534
18.9 IPS |
