Samsung Galaxy S25 Ultra
Geekbench AI Score
633
Single Precision Score
27563
Half Precision Score
68068
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 11 2026 04:02 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-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% |
414
76.9 IPS |
|
|
Image Classification (HP)
|
100% |
21259
3.95 KIPS |
|
|
Image Classification (Q)
|
96% |
50747
9.48 KIPS |
|
|
Image Segmentation (SP)
|
100% |
527
8.54 IPS |
|
|
Image Segmentation (HP)
|
100% |
13695
222.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
53165
864.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
689
0.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
111917
130.6 IPS |
|
|
Pose Estimation (Q)
|
98% |
436534
510.9 IPS |
|
|
Object Detection (SP)
|
100% |
377
29.9 IPS |
|
|
Object Detection (HP)
|
100% |
18292
1.45 KIPS |
|
|
Object Detection (Q)
|
85% |
27814
2.24 KIPS |
|
|
Face Detection (SP)
|
100% |
813
9.66 IPS |
|
|
Face Detection (HP)
|
100% |
37576
446.5 IPS |
|
|
Face Detection (Q)
|
97% |
132362
1.58 KIPS |
|
|
Depth Estimation (SP)
|
100% |
830
6.39 IPS |
|
|
Depth Estimation (HP)
|
99% |
82271
633.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
176227
1.64 KIPS |
|
|
Style Transfer (SP)
|
100% |
1465
1.88 IPS |
|
|
Style Transfer (HP)
|
100% |
89359
114.9 IPS |
|
|
Style Transfer (Q)
|
98% |
447903
577.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
366
13.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
53904
1.99 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
136793
5.07 KIPS |
|
|
Text Classification (SP)
|
100% |
532
710.4 IPS |
|
|
Text Classification (HP)
|
100% |
4465
5.96 KIPS |
|
|
Text Classification (Q)
|
93% |
11397
15.3 KIPS |
|
|
Machine Translation (SP)
|
100% |
952
16.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6387
110.0 IPS |
|
|
Machine Translation (Q)
|
56% |
4002
103.1 IPS |
