Samsung Galaxy S25 Ultra
Geekbench AI Score
2829
Single Precision Score
2773
Half Precision Score
4820
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | gsidedgdb |
| Upload Date | July 10 2025 09:23 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Elite |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S25 Ultra |
| Model ID | samsung SM-S938U |
| 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% |
2019
375.5 IPS |
|
|
Image Classification (HP)
|
100% |
2006
373.0 IPS |
|
|
Image Classification (Q)
|
100% |
4683
870.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2511
40.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2508
40.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
5321
86.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5657
6.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
5360
6.25 IPS |
|
|
Pose Estimation (Q)
|
84% |
13519
16.0 IPS |
|
|
Object Detection (SP)
|
98% |
1706
135.8 IPS |
|
|
Object Detection (HP)
|
98% |
1790
142.4 IPS |
|
|
Object Detection (Q)
|
83% |
3939
318.2 IPS |
|
|
Face Detection (SP)
|
100% |
4444
52.8 IPS |
|
|
Face Detection (HP)
|
100% |
4064
48.3 IPS |
|
|
Face Detection (Q)
|
95% |
9863
117.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
4391
33.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
4564
35.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
10569
96.8 IPS |
|
|
Style Transfer (SP)
|
89% |
11688
15.2 IPS |
|
|
Style Transfer (HP)
|
89% |
11335
14.7 IPS |
|
|
Style Transfer (Q)
|
98% |
25032
32.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2399
88.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2414
89.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6213
230.2 IPS |
|
|
Text Classification (SP)
|
100% |
884
1.18 KIPS |
|
|
Text Classification (HP)
|
99% |
782
1.04 KIPS |
|
|
Text Classification (Q)
|
88% |
547
737.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1391
24.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1404
24.2 IPS |
|
|
Machine Translation (Q)
|
50% |
576
20.4 IPS |
