Samsung Galaxy S25 Ultra
Geekbench AI Score
2637
Single Precision Score
2563
Half Precision Score
4780
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | ixhayabusa |
| Upload Date | January 18 2026 08:28 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1975
367.2 IPS |
|
|
Image Classification (HP)
|
100% |
1806
335.9 IPS |
|
|
Image Classification (Q)
|
100% |
4297
799.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1966
31.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2324
37.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
5049
82.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
4916
5.74 IPS |
|
|
Pose Estimation (HP)
|
100% |
3784
4.42 IPS |
|
|
Pose Estimation (Q)
|
84% |
9313
11.0 IPS |
|
|
Object Detection (SP)
|
98% |
1508
120.0 IPS |
|
|
Object Detection (HP)
|
98% |
1636
130.2 IPS |
|
|
Object Detection (Q)
|
83% |
3747
302.7 IPS |
|
|
Face Detection (SP)
|
100% |
4171
49.6 IPS |
|
|
Face Detection (HP)
|
100% |
4252
50.5 IPS |
|
|
Face Detection (Q)
|
95% |
9815
117.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
4416
34.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
4164
32.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
10121
92.7 IPS |
|
|
Style Transfer (SP)
|
89% |
11121
14.4 IPS |
|
|
Style Transfer (HP)
|
89% |
11181
14.5 IPS |
|
|
Style Transfer (Q)
|
98% |
23227
30.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2281
84.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2038
75.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6369
236.0 IPS |
|
|
Text Classification (SP)
|
100% |
923
1.23 KIPS |
|
|
Text Classification (HP)
|
99% |
915
1.22 KIPS |
|
|
Text Classification (Q)
|
88% |
1053
1.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
1313
22.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1277
22.0 IPS |
|
|
Machine Translation (Q)
|
50% |
532
18.9 IPS |
