Samsung Galaxy S25 Ultra
Geekbench AI Score
2689
Single Precision Score
4229
Half Precision Score
3585
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | rennsport |
| Upload Date | October 20 2025 12:18 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Elite |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S25 Ultra |
| Model ID | samsung SM-S938B |
| 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% |
1601
297.7 IPS |
|
|
Image Classification (HP)
|
100% |
2857
531.3 IPS |
|
|
Image Classification (Q)
|
100% |
2823
525.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
3330
54.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
5868
95.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
5451
88.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
13828
16.1 IPS |
|
|
Pose Estimation (HP)
|
99% |
24681
28.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
24095
28.2 IPS |
|
|
Object Detection (SP)
|
100% |
1542
122.3 IPS |
|
|
Object Detection (HP)
|
99% |
2027
160.8 IPS |
|
|
Object Detection (Q)
|
85% |
2001
161.1 IPS |
|
|
Face Detection (SP)
|
100% |
5145
61.1 IPS |
|
|
Face Detection (HP)
|
100% |
9410
111.8 IPS |
|
|
Face Detection (Q)
|
97% |
8420
100.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
7057
54.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
9127
70.5 IPS |
|
|
Depth Estimation (Q)
|
61% |
7117
69.3 IPS |
|
|
Style Transfer (SP)
|
100% |
16294
20.9 IPS |
|
|
Style Transfer (HP)
|
100% |
35681
45.9 IPS |
|
|
Style Transfer (Q)
|
98% |
35312
45.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3517
129.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5421
200.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5318
197.1 IPS |
|
|
Text Classification (SP)
|
35% |
79
764.9 IPS |
|
|
Text Classification (HP)
|
35% |
80
730.5 IPS |
|
|
Text Classification (Q)
|
33% |
69
772.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1060
18.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1645
28.3 IPS |
|
|
Machine Translation (Q)
|
48% |
609
23.4 IPS |
