samsung SM-S931N
Geekbench AI Score
2480
Single Precision Score
2250
Half Precision Score
3566
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 13 2025 03:12 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S931N |
| Model ID | samsung SM-S931N |
| 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 | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1994
370.8 IPS |
|
|
Image Classification (HP)
|
100% |
1797
334.3 IPS |
|
|
Image Classification (Q)
|
100% |
4437
825.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2371
38.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2277
36.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
2361
38.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
5413
6.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
3753
4.38 IPS |
|
|
Pose Estimation (Q)
|
84% |
9522
11.3 IPS |
|
|
Object Detection (SP)
|
98% |
1293
102.9 IPS |
|
|
Object Detection (HP)
|
98% |
1397
111.1 IPS |
|
|
Object Detection (Q)
|
83% |
2617
211.4 IPS |
|
|
Face Detection (SP)
|
100% |
3661
43.5 IPS |
|
|
Face Detection (HP)
|
100% |
3976
47.2 IPS |
|
|
Face Detection (Q)
|
95% |
7710
92.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
4478
34.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
4491
34.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
8848
81.0 IPS |
|
|
Style Transfer (SP)
|
89% |
9316
12.1 IPS |
|
|
Style Transfer (HP)
|
89% |
8392
10.9 IPS |
|
|
Style Transfer (Q)
|
98% |
16435
21.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1668
61.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1671
61.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4641
172.0 IPS |
|
|
Text Classification (SP)
|
100% |
767
1.02 KIPS |
|
|
Text Classification (HP)
|
99% |
546
728.6 IPS |
|
|
Text Classification (Q)
|
88% |
676
911.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1366
23.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1137
19.6 IPS |
|
|
Machine Translation (Q)
|
50% |
363
12.9 IPS |
