Samsung Galaxy S25
Geekbench AI Score
443
Single Precision Score
438
Half Precision Score
905
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | September 02 2025 04:39 AM |
| Views | 2 |
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-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% |
368
68.4 IPS |
|
|
Image Classification (HP)
|
100% |
374
69.5 IPS |
|
|
Image Classification (Q)
|
99% |
919
171.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
488
7.91 IPS |
|
|
Image Segmentation (HP)
|
100% |
489
7.93 IPS |
|
|
Image Segmentation (Q)
|
98% |
954
15.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
620
0.72 IPS |
|
|
Pose Estimation (HP)
|
100% |
428
0.50 IPS |
|
|
Pose Estimation (Q)
|
98% |
1381
1.62 IPS |
|
|
Object Detection (SP)
|
100% |
205
16.3 IPS |
|
|
Object Detection (HP)
|
100% |
206
16.4 IPS |
|
|
Object Detection (Q)
|
87% |
546
43.8 IPS |
|
|
Face Detection (SP)
|
100% |
562
6.68 IPS |
|
|
Face Detection (HP)
|
100% |
564
6.70 IPS |
|
|
Face Detection (Q)
|
97% |
1231
14.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
485
3.74 IPS |
|
|
Depth Estimation (HP)
|
99% |
489
3.77 IPS |
|
|
Depth Estimation (Q)
|
64% |
1016
9.22 IPS |
|
|
Style Transfer (SP)
|
100% |
891
1.15 IPS |
|
|
Style Transfer (HP)
|
100% |
899
1.16 IPS |
|
|
Style Transfer (Q)
|
98% |
2327
3.00 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
243
8.98 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
286
10.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1016
37.6 IPS |
|
|
Text Classification (SP)
|
100% |
316
422.2 IPS |
|
|
Text Classification (HP)
|
100% |
320
427.3 IPS |
|
|
Text Classification (Q)
|
91% |
491
660.5 IPS |
|
|
Machine Translation (SP)
|
100% |
698
12.0 IPS |
|
|
Machine Translation (HP)
|
100% |
725
12.5 IPS |
|
|
Machine Translation (Q)
|
57% |
387
9.46 IPS |
