Samsung Galaxy S25 Ultra
Geekbench AI Score
2120
Single Precision Score
3322
Half Precision Score
2752
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | DPOUND |
| Upload Date | February 08 2026 02:07 AM |
| 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% |
1314
244.4 IPS |
|
|
Image Classification (HP)
|
100% |
1821
338.6 IPS |
|
|
Image Classification (Q)
|
100% |
1887
350.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2421
39.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
5213
84.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
4127
67.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
10092
11.8 IPS |
|
|
Pose Estimation (HP)
|
99% |
18103
21.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
17933
21.0 IPS |
|
|
Object Detection (SP)
|
100% |
1248
99.0 IPS |
|
|
Object Detection (HP)
|
99% |
1549
122.9 IPS |
|
|
Object Detection (Q)
|
85% |
1496
120.4 IPS |
|
|
Face Detection (SP)
|
100% |
4408
52.4 IPS |
|
|
Face Detection (HP)
|
100% |
7830
93.0 IPS |
|
|
Face Detection (Q)
|
97% |
6728
80.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
5365
41.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
7395
57.2 IPS |
|
|
Depth Estimation (Q)
|
61% |
5737
55.9 IPS |
|
|
Style Transfer (SP)
|
100% |
12824
16.5 IPS |
|
|
Style Transfer (HP)
|
100% |
28020
36.0 IPS |
|
|
Style Transfer (Q)
|
98% |
28445
36.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2812
103.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4406
162.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4352
161.3 IPS |
|
|
Text Classification (SP)
|
35% |
66
645.7 IPS |
|
|
Text Classification (HP)
|
35% |
71
643.0 IPS |
|
|
Text Classification (Q)
|
33% |
52
585.3 IPS |
|
|
Machine Translation (SP)
|
100% |
817
14.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1214
20.9 IPS |
|
|
Machine Translation (Q)
|
48% |
481
18.5 IPS |
