samsung SM-S731B
Geekbench AI Score
3537
Single Precision Score
24384
Half Precision Score
46388
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Azeno42 |
| Upload Date | December 18 2025 06:58 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-S731B |
| Model ID | samsung SM-S731B |
| 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% |
1623
301.9 IPS |
|
|
Image Classification (HP)
|
100% |
16640
3.09 KIPS |
|
|
Image Classification (Q)
|
100% |
30969
5.76 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3014
48.9 IPS |
|
|
Image Segmentation (HP)
|
97% |
12035
195.8 IPS |
|
|
Image Segmentation (Q)
|
96% |
27791
452.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
14427
16.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
87009
101.5 IPS |
|
|
Pose Estimation (Q)
|
97% |
299212
350.4 IPS |
|
|
Object Detection (SP)
|
100% |
1597
126.7 IPS |
|
|
Object Detection (HP)
|
100% |
14055
1.11 KIPS |
|
|
Object Detection (Q)
|
90% |
23417
1.87 KIPS |
|
|
Face Detection (SP)
|
100% |
5034
59.8 IPS |
|
|
Face Detection (HP)
|
100% |
38019
451.7 IPS |
|
|
Face Detection (Q)
|
97% |
99230
1.18 KIPS |
|
|
Depth Estimation (SP)
|
100% |
5609
43.2 IPS |
|
|
Depth Estimation (HP)
|
79% |
53686
426.3 IPS |
|
|
Depth Estimation (Q)
|
62% |
105786
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
28886
37.1 IPS |
|
|
Style Transfer (HP)
|
99% |
162127
208.4 IPS |
|
|
Style Transfer (Q)
|
98% |
268703
346.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4174
154.1 IPS |
|
|
Image Super-Resolution (HP)
|
82% |
21944
828.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
59164
2.19 KIPS |
|
|
Text Classification (SP)
|
100% |
633
845.2 IPS |
|
|
Text Classification (HP)
|
100% |
6870
9.17 KIPS |
|
|
Text Classification (Q)
|
93% |
8062
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1262
21.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6084
104.8 IPS |
|
|
Machine Translation (Q)
|
56% |
5687
145.9 IPS |
