Samsung Galaxy S25 Ultra
Geekbench AI Score
2320
Single Precision Score
3872
Half Precision Score
3167
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | ixhayabusa |
| Upload Date | January 18 2026 08:32 PM |
| Views | 4 |
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% |
1575
292.9 IPS |
|
|
Image Classification (HP)
|
100% |
2523
469.2 IPS |
|
|
Image Classification (Q)
|
100% |
3205
596.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
3406
55.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
6830
110.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
5869
95.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
13681
16.0 IPS |
|
|
Pose Estimation (HP)
|
99% |
25027
29.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
24239
28.4 IPS |
|
|
Object Detection (SP)
|
100% |
1585
125.7 IPS |
|
|
Object Detection (HP)
|
99% |
2222
176.3 IPS |
|
|
Object Detection (Q)
|
85% |
1132
91.2 IPS |
|
|
Face Detection (SP)
|
100% |
3250
38.6 IPS |
|
|
Face Detection (HP)
|
100% |
5003
59.4 IPS |
|
|
Face Detection (Q)
|
97% |
5301
63.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
3238
24.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
7379
57.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
5759
56.1 IPS |
|
|
Style Transfer (SP)
|
100% |
14532
18.7 IPS |
|
|
Style Transfer (HP)
|
100% |
32231
41.4 IPS |
|
|
Style Transfer (Q)
|
98% |
33199
42.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3333
123.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5203
192.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4749
176.0 IPS |
|
|
Text Classification (SP)
|
35% |
70
677.3 IPS |
|
|
Text Classification (HP)
|
35% |
72
655.4 IPS |
|
|
Text Classification (Q)
|
33% |
62
698.7 IPS |
|
|
Machine Translation (SP)
|
100% |
1093
18.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1777
30.6 IPS |
|
|
Machine Translation (Q)
|
48% |
660
25.3 IPS |
