Samsung Galaxy S25 Ultra
Geekbench AI Score
2742
Single Precision Score
4358
Half Precision Score
3660
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | DanielStr |
| Upload Date | March 01 2026 12:05 AM |
| Views | 7 |
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% |
1856
345.1 IPS |
|
|
Image Classification (HP)
|
100% |
2630
489.1 IPS |
|
|
Image Classification (Q)
|
100% |
2794
519.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
3139
50.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
6687
108.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
5401
87.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
13695
16.0 IPS |
|
|
Pose Estimation (HP)
|
99% |
23199
27.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
22932
26.9 IPS |
|
|
Object Detection (SP)
|
100% |
1478
117.2 IPS |
|
|
Object Detection (HP)
|
99% |
1876
148.8 IPS |
|
|
Object Detection (Q)
|
85% |
1973
158.9 IPS |
|
|
Face Detection (SP)
|
100% |
4992
59.3 IPS |
|
|
Face Detection (HP)
|
100% |
10480
124.5 IPS |
|
|
Face Detection (Q)
|
97% |
8424
100.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6660
51.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
9000
69.6 IPS |
|
|
Depth Estimation (Q)
|
61% |
7408
72.2 IPS |
|
|
Style Transfer (SP)
|
100% |
17315
22.3 IPS |
|
|
Style Transfer (HP)
|
100% |
37709
48.5 IPS |
|
|
Style Transfer (Q)
|
98% |
38312
49.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3705
136.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5839
215.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5476
203.0 IPS |
|
|
Text Classification (SP)
|
35% |
88
858.0 IPS |
|
|
Text Classification (HP)
|
35% |
84
759.4 IPS |
|
|
Text Classification (Q)
|
33% |
68
764.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1086
18.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1854
31.9 IPS |
|
|
Machine Translation (Q)
|
48% |
710
27.2 IPS |
