samsung SM-S711B
Geekbench AI Score
1412
Single Precision Score
1418
Half Precision Score
2111
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Namelessmint |
| Upload Date | January 16 2025 11:41 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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% |
1440
267.8 IPS |
|
|
Image Classification (HP)
|
100% |
1353
251.6 IPS |
|
|
Image Classification (Q)
|
100% |
2123
394.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1317
21.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1381
22.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
2297
37.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2566
2.99 IPS |
|
|
Pose Estimation (HP)
|
100% |
1943
2.27 IPS |
|
|
Pose Estimation (Q)
|
84% |
3697
4.38 IPS |
|
|
Object Detection (SP)
|
98% |
888
70.6 IPS |
|
|
Object Detection (HP)
|
98% |
945
75.2 IPS |
|
|
Object Detection (Q)
|
83% |
1252
101.1 IPS |
|
|
Face Detection (SP)
|
100% |
1899
22.6 IPS |
|
|
Face Detection (HP)
|
100% |
1863
22.1 IPS |
|
|
Face Detection (Q)
|
95% |
3198
38.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
1977
15.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2362
18.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
3215
29.4 IPS |
|
|
Style Transfer (SP)
|
89% |
4808
6.24 IPS |
|
|
Style Transfer (HP)
|
89% |
4815
6.25 IPS |
|
|
Style Transfer (Q)
|
98% |
9375
12.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1102
40.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1099
40.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2325
86.2 IPS |
|
|
Text Classification (SP)
|
100% |
453
604.4 IPS |
|
|
Text Classification (HP)
|
99% |
442
589.7 IPS |
|
|
Text Classification (Q)
|
88% |
792
1.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
812
14.0 IPS |
|
|
Machine Translation (HP)
|
100% |
931
16.0 IPS |
|
|
Machine Translation (Q)
|
50% |
440
15.6 IPS |
