Samsung Galaxy S25 Ultra
Geekbench AI Score
574
Single Precision Score
27070
Half Precision Score
60966
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 14 2025 11:20 AM |
| Views | 12 |
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% |
432
80.3 IPS |
|
|
Image Classification (HP)
|
100% |
21332
3.97 KIPS |
|
|
Image Classification (Q)
|
97% |
49691
9.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
537
8.70 IPS |
|
|
Image Segmentation (HP)
|
100% |
13585
220.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
41653
677.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
592
0.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
119632
139.6 IPS |
|
|
Pose Estimation (Q)
|
98% |
476584
557.8 IPS |
|
|
Object Detection (SP)
|
100% |
288
22.8 IPS |
|
|
Object Detection (HP)
|
100% |
18632
1.48 KIPS |
|
|
Object Detection (Q)
|
85% |
21473
1.73 KIPS |
|
|
Face Detection (SP)
|
100% |
806
9.58 IPS |
|
|
Face Detection (HP)
|
100% |
41385
491.7 IPS |
|
|
Face Detection (Q)
|
97% |
140151
1.67 KIPS |
|
|
Depth Estimation (SP)
|
100% |
698
5.38 IPS |
|
|
Depth Estimation (HP)
|
99% |
83221
641.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
144013
1.33 KIPS |
|
|
Style Transfer (SP)
|
100% |
1233
1.58 IPS |
|
|
Style Transfer (HP)
|
98% |
98856
127.5 IPS |
|
|
Style Transfer (Q)
|
98% |
491708
634.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
366
13.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
53862
1.99 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
135199
5.01 KIPS |
|
|
Text Classification (SP)
|
100% |
460
613.4 IPS |
|
|
Text Classification (HP)
|
100% |
3915
5.23 KIPS |
|
|
Text Classification (Q)
|
93% |
8063
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
845
14.6 IPS |
|
|
Machine Translation (HP)
|
100% |
4557
78.5 IPS |
|
|
Machine Translation (Q)
|
56% |
3096
79.8 IPS |
