Samsung Galaxy S25 Ultra
Geekbench AI Score
660
Single Precision Score
27432
Half Precision Score
61756
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | DPOUND |
| Upload Date | February 08 2026 02:05 AM |
| Views | 8 |
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-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% |
382
71.1 IPS |
|
|
Image Classification (HP)
|
100% |
20970
3.90 KIPS |
|
|
Image Classification (Q)
|
97% |
48553
9.06 KIPS |
|
|
Image Segmentation (SP)
|
100% |
505
8.18 IPS |
|
|
Image Segmentation (HP)
|
100% |
13515
219.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
42138
685.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
686
0.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
123781
144.4 IPS |
|
|
Pose Estimation (Q)
|
98% |
478987
560.6 IPS |
|
|
Object Detection (SP)
|
100% |
388
30.8 IPS |
|
|
Object Detection (HP)
|
100% |
19207
1.52 KIPS |
|
|
Object Detection (Q)
|
85% |
22463
1.81 KIPS |
|
|
Face Detection (SP)
|
100% |
988
11.7 IPS |
|
|
Face Detection (HP)
|
100% |
43006
511.0 IPS |
|
|
Face Detection (Q)
|
97% |
150699
1.80 KIPS |
|
|
Depth Estimation (SP)
|
100% |
854
6.58 IPS |
|
|
Depth Estimation (HP)
|
99% |
83763
645.3 IPS |
|
|
Depth Estimation (Q)
|
63% |
144293
1.34 KIPS |
|
|
Style Transfer (SP)
|
100% |
1471
1.89 IPS |
|
|
Style Transfer (HP)
|
98% |
98910
127.5 IPS |
|
|
Style Transfer (Q)
|
98% |
493829
636.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
459
16.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54821
2.02 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
135414
5.02 KIPS |
|
|
Text Classification (SP)
|
100% |
569
759.3 IPS |
|
|
Text Classification (HP)
|
100% |
3934
5.25 KIPS |
|
|
Text Classification (Q)
|
93% |
8171
11.0 KIPS |
|
|
Machine Translation (SP)
|
100% |
948
16.3 IPS |
|
|
Machine Translation (HP)
|
100% |
4662
80.3 IPS |
|
|
Machine Translation (Q)
|
56% |
3085
79.5 IPS |
