Samsung Galaxy S25
Geekbench AI Score
588
Single Precision Score
572
Half Precision Score
1251
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | September 22 2025 10:46 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Elite |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S25 |
| 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% |
339
63.0 IPS |
|
|
Image Classification (HP)
|
100% |
353
65.7 IPS |
|
|
Image Classification (Q)
|
99% |
874
163.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
462
7.48 IPS |
|
|
Image Segmentation (HP)
|
100% |
461
7.47 IPS |
|
|
Image Segmentation (Q)
|
98% |
908
14.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
646
0.75 IPS |
|
|
Pose Estimation (HP)
|
100% |
618
0.72 IPS |
|
|
Pose Estimation (Q)
|
98% |
2503
2.93 IPS |
|
|
Object Detection (SP)
|
100% |
355
28.2 IPS |
|
|
Object Detection (HP)
|
100% |
356
28.3 IPS |
|
|
Object Detection (Q)
|
87% |
887
71.2 IPS |
|
|
Face Detection (SP)
|
100% |
830
9.86 IPS |
|
|
Face Detection (HP)
|
100% |
829
9.85 IPS |
|
|
Face Detection (Q)
|
97% |
1913
22.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
749
5.77 IPS |
|
|
Depth Estimation (HP)
|
99% |
695
5.36 IPS |
|
|
Depth Estimation (Q)
|
64% |
1573
14.3 IPS |
|
|
Style Transfer (SP)
|
100% |
1348
1.73 IPS |
|
|
Style Transfer (HP)
|
100% |
1110
1.43 IPS |
|
|
Style Transfer (Q)
|
98% |
3144
4.05 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
401
14.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
401
14.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1288
47.7 IPS |
|
|
Text Classification (SP)
|
100% |
467
623.0 IPS |
|
|
Text Classification (HP)
|
100% |
468
624.1 IPS |
|
|
Text Classification (Q)
|
91% |
719
966.8 IPS |
|
|
Machine Translation (SP)
|
100% |
877
15.1 IPS |
|
|
Machine Translation (HP)
|
100% |
885
15.2 IPS |
|
|
Machine Translation (Q)
|
57% |
613
15.0 IPS |
