Samsung Galaxy S25 Ultra
Geekbench AI Score
541
Single Precision Score
27075
Half Precision Score
61206
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 14 2025 05:52 PM |
| Views | 14 |
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-S938N |
| 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% |
265
49.3 IPS |
|
|
Image Classification (HP)
|
100% |
20194
3.76 KIPS |
|
|
Image Classification (Q)
|
97% |
49064
9.16 KIPS |
|
|
Image Segmentation (SP)
|
100% |
351
5.69 IPS |
|
|
Image Segmentation (HP)
|
100% |
13596
220.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
41011
666.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
624
0.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
119280
139.2 IPS |
|
|
Pose Estimation (Q)
|
98% |
478290
559.8 IPS |
|
|
Object Detection (SP)
|
100% |
305
24.2 IPS |
|
|
Object Detection (HP)
|
100% |
18859
1.50 KIPS |
|
|
Object Detection (Q)
|
85% |
22458
1.81 KIPS |
|
|
Face Detection (SP)
|
100% |
961
11.4 IPS |
|
|
Face Detection (HP)
|
100% |
42578
505.9 IPS |
|
|
Face Detection (Q)
|
97% |
143589
1.71 KIPS |
|
|
Depth Estimation (SP)
|
100% |
776
5.98 IPS |
|
|
Depth Estimation (HP)
|
99% |
83932
646.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
144426
1.34 KIPS |
|
|
Style Transfer (SP)
|
100% |
1232
1.58 IPS |
|
|
Style Transfer (HP)
|
98% |
98781
127.4 IPS |
|
|
Style Transfer (Q)
|
98% |
491485
633.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
342
12.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54187
2.00 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
135613
5.03 KIPS |
|
|
Text Classification (SP)
|
100% |
498
664.8 IPS |
|
|
Text Classification (HP)
|
100% |
3945
5.27 KIPS |
|
|
Text Classification (Q)
|
93% |
8133
10.9 KIPS |
|
|
Machine Translation (SP)
|
100% |
777
13.4 IPS |
|
|
Machine Translation (HP)
|
100% |
4542
78.2 IPS |
|
|
Machine Translation (Q)
|
56% |
3037
78.2 IPS |
