samsung SM-S711B
Geekbench AI Score
1408
Single Precision Score
1355
Half Precision Score
2103
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | July 01 2025 07:57 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S711B |
| Model ID | samsung SM-S711B |
| Motherboard | s5e9925 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.82 GHz |
| Cluster 1 | 4 Cores @ 1.82 GHz |
| Cluster 2 | 3 Cores @ 2.52 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.12 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1320
245.4 IPS |
|
|
Image Classification (HP)
|
100% |
1224
227.6 IPS |
|
|
Image Classification (Q)
|
100% |
2022
376.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1285
20.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1337
21.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
2230
36.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2437
2.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
1912
2.23 IPS |
|
|
Pose Estimation (Q)
|
84% |
3770
4.47 IPS |
|
|
Object Detection (SP)
|
98% |
872
69.4 IPS |
|
|
Object Detection (HP)
|
98% |
841
66.9 IPS |
|
|
Object Detection (Q)
|
83% |
1246
100.6 IPS |
|
|
Face Detection (SP)
|
100% |
1895
22.5 IPS |
|
|
Face Detection (HP)
|
100% |
1863
22.1 IPS |
|
|
Face Detection (Q)
|
95% |
3310
39.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
2285
17.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2283
17.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
3421
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
4783
6.21 IPS |
|
|
Style Transfer (HP)
|
89% |
4780
6.21 IPS |
|
|
Style Transfer (Q)
|
98% |
8682
11.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1043
38.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
920
34.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2126
78.8 IPS |
|
|
Text Classification (SP)
|
100% |
417
556.2 IPS |
|
|
Text Classification (HP)
|
99% |
470
627.7 IPS |
|
|
Text Classification (Q)
|
88% |
848
1.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
948
16.3 IPS |
|
|
Machine Translation (HP)
|
100% |
903
15.6 IPS |
|
|
Machine Translation (Q)
|
50% |
452
16.0 IPS |
