samsung SM-S936N
Geekbench AI Score
2788
Single Precision Score
2816
Half Precision Score
5088
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 17 2025 05:05 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-S936N |
| Model ID | samsung SM-S936N |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2020
375.7 IPS |
|
|
Image Classification (HP)
|
100% |
2089
388.5 IPS |
|
|
Image Classification (Q)
|
100% |
4672
868.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2301
37.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2409
39.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
5289
86.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
5390
6.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
5299
6.18 IPS |
|
|
Pose Estimation (Q)
|
84% |
13170
15.6 IPS |
|
|
Object Detection (SP)
|
98% |
1740
138.5 IPS |
|
|
Object Detection (HP)
|
98% |
1738
138.3 IPS |
|
|
Object Detection (Q)
|
83% |
3988
322.1 IPS |
|
|
Face Detection (SP)
|
100% |
4314
51.3 IPS |
|
|
Face Detection (HP)
|
100% |
4307
51.2 IPS |
|
|
Face Detection (Q)
|
95% |
9198
109.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
4635
35.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
4652
35.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
10552
96.6 IPS |
|
|
Style Transfer (SP)
|
89% |
11212
14.6 IPS |
|
|
Style Transfer (HP)
|
89% |
11011
14.3 IPS |
|
|
Style Transfer (Q)
|
98% |
25083
32.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2315
85.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2351
86.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6687
247.8 IPS |
|
|
Text Classification (SP)
|
100% |
920
1.23 KIPS |
|
|
Text Classification (HP)
|
99% |
971
1.30 KIPS |
|
|
Text Classification (Q)
|
88% |
1057
1.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
1367
23.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1344
23.1 IPS |
|
|
Machine Translation (Q)
|
50% |
521
18.5 IPS |
