samsung SM-S901B
Geekbench AI Score
418
Single Precision Score
420
Half Precision Score
607
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 29 2025 01:34 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S901B |
| Model ID | samsung SM-S901B |
| Motherboard | exynos9820 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 1 part 3 revision 0 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 Cores @ 1.95 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Cluster 3 | 2 Cores @ 2.81 GHz |
| Memory Information | |
|---|---|
| Size | 7.24 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
212
39.4 IPS |
|
|
Image Classification (HP)
|
100% |
198
36.9 IPS |
|
|
Image Classification (Q)
|
100% |
564
104.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
234
3.79 IPS |
|
|
Image Segmentation (HP)
|
100% |
233
3.78 IPS |
|
|
Image Segmentation (Q)
|
98% |
520
8.46 IPS |
|
|
Pose Estimation (SP)
|
100% |
905
1.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
889
1.04 IPS |
|
|
Pose Estimation (Q)
|
84% |
775
0.92 IPS |
|
|
Object Detection (SP)
|
100% |
180
14.3 IPS |
|
|
Object Detection (HP)
|
100% |
174
13.8 IPS |
|
|
Object Detection (Q)
|
83% |
391
31.6 IPS |
|
|
Face Detection (SP)
|
100% |
619
7.36 IPS |
|
|
Face Detection (HP)
|
100% |
603
7.17 IPS |
|
|
Face Detection (Q)
|
95% |
1058
12.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
782
6.02 IPS |
|
|
Depth Estimation (HP)
|
99% |
785
6.05 IPS |
|
|
Depth Estimation (Q)
|
64% |
844
7.73 IPS |
|
|
Style Transfer (SP)
|
89% |
1454
1.89 IPS |
|
|
Style Transfer (HP)
|
89% |
1475
1.92 IPS |
|
|
Style Transfer (Q)
|
98% |
2015
2.60 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
451
16.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
462
17.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
721
26.7 IPS |
|
|
Text Classification (SP)
|
100% |
183
243.6 IPS |
|
|
Text Classification (HP)
|
100% |
217
289.6 IPS |
|
|
Text Classification (Q)
|
88% |
293
395.0 IPS |
|
|
Machine Translation (SP)
|
100% |
354
6.09 IPS |
|
|
Machine Translation (HP)
|
100% |
348
5.99 IPS |
|
|
Machine Translation (Q)
|
50% |
203
7.21 IPS |
