samsung SM-S731U
Geekbench AI Score
2107
Single Precision Score
24452
Half Precision Score
43893
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| Upload Date | March 05 2026 09:21 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-S731U |
| Model ID | samsung SM-S731U |
| Motherboard | s5e9945 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.59 GHz |
| Cluster 3 | 2 Cores @ 2.90 GHz |
| Cluster 4 | 1 Core @ 3.21 GHz |
| Memory Information | |
|---|---|
| Size | 7.04 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1598
297.2 IPS |
|
|
Image Classification (HP)
|
100% |
18107
3.37 KIPS |
|
|
Image Classification (Q)
|
100% |
34610
6.44 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3071
49.8 IPS |
|
|
Image Segmentation (HP)
|
97% |
10289
167.4 IPS |
|
|
Image Segmentation (Q)
|
97% |
29082
473.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
14015
16.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
84644
98.8 IPS |
|
|
Pose Estimation (Q)
|
97% |
323101
378.4 IPS |
|
|
Object Detection (SP)
|
100% |
1590
126.1 IPS |
|
|
Object Detection (HP)
|
100% |
14735
1.17 KIPS |
|
|
Object Detection (Q)
|
90% |
25286
2.02 KIPS |
|
|
Face Detection (SP)
|
100% |
5193
61.7 IPS |
|
|
Face Detection (HP)
|
100% |
41883
497.7 IPS |
|
|
Face Detection (Q)
|
97% |
66169
789.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
2358
18.2 IPS |
|
|
Depth Estimation (HP)
|
79% |
62745
498.3 IPS |
|
|
Depth Estimation (Q)
|
62% |
101479
973.5 IPS |
|
|
Style Transfer (SP)
|
100% |
9791
12.6 IPS |
|
|
Style Transfer (HP)
|
99% |
167236
215.0 IPS |
|
|
Style Transfer (Q)
|
98% |
272915
352.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1763
65.1 IPS |
|
|
Image Super-Resolution (HP)
|
83% |
22294
839.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
36484
1.35 KIPS |
|
|
Text Classification (SP)
|
100% |
202
270.0 IPS |
|
|
Text Classification (HP)
|
100% |
5592
7.46 KIPS |
|
|
Text Classification (Q)
|
93% |
6435
8.64 KIPS |
|
|
Machine Translation (SP)
|
100% |
370
6.37 IPS |
|
|
Machine Translation (HP)
|
100% |
6004
103.4 IPS |
|
|
Machine Translation (Q)
|
61% |
7503
165.0 IPS |
