Samsung Galaxy S25 Ultra
Geekbench AI Score
2835
Single Precision Score
4325
Half Precision Score
3639
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | jkovacs87 |
| Upload Date | July 19 2025 04:57 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Elite |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S25 Ultra |
| Model ID | samsung SM-S938U1 |
| 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% |
1689
314.1 IPS |
|
|
Image Classification (HP)
|
100% |
2901
539.5 IPS |
|
|
Image Classification (Q)
|
100% |
2905
540.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
3877
62.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
5183
84.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4926
80.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
13791
16.1 IPS |
|
|
Pose Estimation (HP)
|
99% |
24842
29.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
24205
28.4 IPS |
|
|
Object Detection (SP)
|
100% |
1540
122.1 IPS |
|
|
Object Detection (HP)
|
99% |
1990
157.8 IPS |
|
|
Object Detection (Q)
|
85% |
1937
155.9 IPS |
|
|
Face Detection (SP)
|
100% |
5453
64.8 IPS |
|
|
Face Detection (HP)
|
100% |
9538
113.3 IPS |
|
|
Face Detection (Q)
|
97% |
8371
99.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7265
56.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
9564
73.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
7409
72.2 IPS |
|
|
Style Transfer (SP)
|
100% |
17361
22.3 IPS |
|
|
Style Transfer (HP)
|
100% |
38044
48.9 IPS |
|
|
Style Transfer (Q)
|
98% |
37883
48.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3727
137.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5744
212.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5629
208.6 IPS |
|
|
Text Classification (SP)
|
35% |
93
901.3 IPS |
|
|
Text Classification (HP)
|
35% |
87
794.4 IPS |
|
|
Text Classification (Q)
|
33% |
72
806.3 IPS |
|
|
Machine Translation (SP)
|
100% |
1015
17.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1778
30.6 IPS |
|
|
Machine Translation (Q)
|
48% |
639
24.5 IPS |
