samsung SM-S711N
Geekbench AI Score
1397
Single Precision Score
1418
Half Precision Score
2078
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 12 2025 11:58 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S711N |
| Model ID | samsung SM-S711N |
| 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% |
1224
227.6 IPS |
|
|
Image Classification (HP)
|
100% |
1256
233.7 IPS |
|
|
Image Classification (Q)
|
100% |
2083
387.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1318
21.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1363
22.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
2233
36.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2427
2.83 IPS |
|
|
Pose Estimation (HP)
|
100% |
2004
2.34 IPS |
|
|
Pose Estimation (Q)
|
84% |
3896
4.62 IPS |
|
|
Object Detection (SP)
|
98% |
834
66.3 IPS |
|
|
Object Detection (HP)
|
98% |
1024
81.5 IPS |
|
|
Object Detection (Q)
|
83% |
1174
94.9 IPS |
|
|
Face Detection (SP)
|
100% |
1882
22.4 IPS |
|
|
Face Detection (HP)
|
100% |
1907
22.7 IPS |
|
|
Face Detection (Q)
|
95% |
3185
38.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
1942
15.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
2273
17.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
3261
29.9 IPS |
|
|
Style Transfer (SP)
|
89% |
4814
6.25 IPS |
|
|
Style Transfer (HP)
|
89% |
4742
6.16 IPS |
|
|
Style Transfer (Q)
|
98% |
8103
10.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1102
40.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1047
38.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2227
82.5 IPS |
|
|
Text Classification (SP)
|
100% |
394
525.7 IPS |
|
|
Text Classification (HP)
|
99% |
475
633.6 IPS |
|
|
Text Classification (Q)
|
88% |
866
1.17 KIPS |
|
|
Machine Translation (SP)
|
100% |
1142
19.7 IPS |
|
|
Machine Translation (HP)
|
100% |
917
15.8 IPS |
|
|
Machine Translation (Q)
|
50% |
435
15.4 IPS |
