Samsung Galaxy S25 Ultra
Geekbench AI Score
2653
Single Precision Score
4063
Half Precision Score
3492
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | DanielStr |
| Upload Date | March 01 2026 05:49 AM |
| Views | 3 |
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% |
1187
220.7 IPS |
|
|
Image Classification (HP)
|
100% |
1686
313.5 IPS |
|
|
Image Classification (Q)
|
100% |
1756
326.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
3192
51.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
5453
88.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
5713
92.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
13729
16.0 IPS |
|
|
Pose Estimation (HP)
|
99% |
24643
28.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
24154
28.3 IPS |
|
|
Object Detection (SP)
|
100% |
1483
117.7 IPS |
|
|
Object Detection (HP)
|
99% |
1941
153.9 IPS |
|
|
Object Detection (Q)
|
85% |
1965
158.2 IPS |
|
|
Face Detection (SP)
|
100% |
5722
68.0 IPS |
|
|
Face Detection (HP)
|
100% |
9205
109.4 IPS |
|
|
Face Detection (Q)
|
97% |
8087
96.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6598
50.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
9579
74.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
7715
75.2 IPS |
|
|
Style Transfer (SP)
|
100% |
17281
22.2 IPS |
|
|
Style Transfer (HP)
|
100% |
35694
45.9 IPS |
|
|
Style Transfer (Q)
|
98% |
35001
45.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3508
129.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5388
199.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5604
207.7 IPS |
|
|
Text Classification (SP)
|
35% |
91
882.6 IPS |
|
|
Text Classification (HP)
|
35% |
88
804.0 IPS |
|
|
Text Classification (Q)
|
33% |
69
775.5 IPS |
|
|
Machine Translation (SP)
|
100% |
1077
18.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1871
32.2 IPS |
|
|
Machine Translation (Q)
|
48% |
671
25.7 IPS |
