Samsung Galaxy S25
Geekbench AI Score
615
Single Precision Score
602
Half Precision Score
1299
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 16 2026 06:58 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Elite |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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 | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
420
78.0 IPS |
|
|
Image Classification (HP)
|
100% |
411
76.5 IPS |
|
|
Image Classification (Q)
|
99% |
1002
186.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
448
7.27 IPS |
|
|
Image Segmentation (HP)
|
100% |
464
7.52 IPS |
|
|
Image Segmentation (Q)
|
98% |
924
15.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
667
0.78 IPS |
|
|
Pose Estimation (HP)
|
100% |
598
0.70 IPS |
|
|
Pose Estimation (Q)
|
98% |
2478
2.90 IPS |
|
|
Object Detection (SP)
|
100% |
355
28.2 IPS |
|
|
Object Detection (HP)
|
100% |
369
29.2 IPS |
|
|
Object Detection (Q)
|
87% |
921
73.9 IPS |
|
|
Face Detection (SP)
|
100% |
952
11.3 IPS |
|
|
Face Detection (HP)
|
100% |
996
11.8 IPS |
|
|
Face Detection (Q)
|
97% |
2104
25.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
697
5.37 IPS |
|
|
Depth Estimation (HP)
|
99% |
698
5.37 IPS |
|
|
Depth Estimation (Q)
|
64% |
1572
14.3 IPS |
|
|
Style Transfer (SP)
|
100% |
1430
1.84 IPS |
|
|
Style Transfer (HP)
|
100% |
1229
1.58 IPS |
|
|
Style Transfer (Q)
|
98% |
3112
4.01 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
363
13.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
403
14.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1402
51.9 IPS |
|
|
Text Classification (SP)
|
100% |
503
671.9 IPS |
|
|
Text Classification (HP)
|
100% |
467
623.0 IPS |
|
|
Text Classification (Q)
|
91% |
776
1.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
1004
17.3 IPS |
|
|
Machine Translation (HP)
|
100% |
932
16.1 IPS |
|
|
Machine Translation (Q)
|
57% |
580
14.2 IPS |
