Samsung Galaxy S25 Ultra
Geekbench AI Score
733
Single Precision Score
27875
Half Precision Score
63067
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 27 2025 06:02 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 8 Elite |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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 | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
436
81.1 IPS |
|
|
Image Classification (HP)
|
100% |
21631
4.02 KIPS |
|
|
Image Classification (Q)
|
97% |
50256
9.38 KIPS |
|
|
Image Segmentation (SP)
|
100% |
577
9.36 IPS |
|
|
Image Segmentation (HP)
|
100% |
13653
221.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
42690
694.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
743
0.87 IPS |
|
|
Pose Estimation (HP)
|
100% |
123729
144.4 IPS |
|
|
Pose Estimation (Q)
|
98% |
479564
561.3 IPS |
|
|
Object Detection (SP)
|
100% |
392
31.1 IPS |
|
|
Object Detection (HP)
|
100% |
19706
1.56 KIPS |
|
|
Object Detection (Q)
|
85% |
23254
1.87 KIPS |
|
|
Face Detection (SP)
|
100% |
1127
13.4 IPS |
|
|
Face Detection (HP)
|
100% |
44132
524.4 IPS |
|
|
Face Detection (Q)
|
97% |
157804
1.88 KIPS |
|
|
Depth Estimation (SP)
|
100% |
957
7.37 IPS |
|
|
Depth Estimation (HP)
|
99% |
84783
653.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
146938
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1604
2.06 IPS |
|
|
Style Transfer (HP)
|
98% |
99073
127.8 IPS |
|
|
Style Transfer (Q)
|
98% |
495832
639.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
503
18.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
55150
2.04 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
135506
5.02 KIPS |
|
|
Text Classification (SP)
|
100% |
657
877.5 IPS |
|
|
Text Classification (HP)
|
100% |
3938
5.26 KIPS |
|
|
Text Classification (Q)
|
93% |
8200
11.0 KIPS |
|
|
Machine Translation (SP)
|
100% |
1083
18.7 IPS |
|
|
Machine Translation (HP)
|
100% |
4887
84.2 IPS |
|
|
Machine Translation (Q)
|
56% |
3257
83.9 IPS |
