samsung SM-S931B
Geekbench AI Score
2667
Single Precision Score
2646
Half Precision Score
4503
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 27 2025 10:15 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S931B |
| Model ID | samsung SM-S931B |
| 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% |
1798
334.4 IPS |
|
|
Image Classification (HP)
|
100% |
2040
379.3 IPS |
|
|
Image Classification (Q)
|
100% |
4373
813.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2425
39.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2425
39.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
5341
86.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
5522
6.44 IPS |
|
|
Pose Estimation (HP)
|
100% |
5397
6.30 IPS |
|
|
Pose Estimation (Q)
|
84% |
13083
15.5 IPS |
|
|
Object Detection (SP)
|
98% |
1610
128.2 IPS |
|
|
Object Detection (HP)
|
98% |
1316
104.7 IPS |
|
|
Object Detection (Q)
|
83% |
3264
263.7 IPS |
|
|
Face Detection (SP)
|
100% |
4414
52.4 IPS |
|
|
Face Detection (HP)
|
100% |
4421
52.5 IPS |
|
|
Face Detection (Q)
|
95% |
9577
114.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
4716
36.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
4609
35.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
10682
97.8 IPS |
|
|
Style Transfer (SP)
|
89% |
8751
11.4 IPS |
|
|
Style Transfer (HP)
|
89% |
9890
12.8 IPS |
|
|
Style Transfer (Q)
|
98% |
22960
29.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2127
78.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2016
74.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4828
178.9 IPS |
|
|
Text Classification (SP)
|
100% |
876
1.17 KIPS |
|
|
Text Classification (HP)
|
99% |
841
1.12 KIPS |
|
|
Text Classification (Q)
|
88% |
569
767.0 IPS |
|
|
Machine Translation (SP)
|
100% |
1384
23.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1403
24.2 IPS |
|
|
Machine Translation (Q)
|
50% |
533
18.9 IPS |
