Samsung Galaxy S25 Ultra
Geekbench AI Score
2520
Single Precision Score
3598
Half Precision Score
4807
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | DanielStr |
| Upload Date | March 01 2026 05:47 AM |
| Views | 9 |
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% |
2023
376.3 IPS |
|
|
Image Classification (HP)
|
100% |
2223
413.4 IPS |
|
|
Image Classification (Q)
|
99% |
4502
839.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2478
40.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
3335
54.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
5477
89.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
5232
6.10 IPS |
|
|
Pose Estimation (HP)
|
92% |
10266
12.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
12354
14.5 IPS |
|
|
Object Detection (SP)
|
98% |
1614
128.4 IPS |
|
|
Object Detection (HP)
|
97% |
2011
160.1 IPS |
|
|
Object Detection (Q)
|
85% |
3664
295.2 IPS |
|
|
Face Detection (SP)
|
100% |
3863
45.9 IPS |
|
|
Face Detection (HP)
|
100% |
6384
75.8 IPS |
|
|
Face Detection (Q)
|
97% |
9247
110.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
4156
32.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
7198
55.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
10171
93.9 IPS |
|
|
Style Transfer (SP)
|
89% |
11391
14.8 IPS |
|
|
Style Transfer (HP)
|
88% |
13111
17.0 IPS |
|
|
Style Transfer (Q)
|
98% |
23568
30.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2008
74.1 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
3584
133.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4605
170.7 IPS |
|
|
Text Classification (SP)
|
100% |
494
658.8 IPS |
|
|
Text Classification (HP)
|
100% |
754
1.01 KIPS |
|
|
Text Classification (Q)
|
93% |
735
986.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1347
23.2 IPS |
|
|
Machine Translation (HP)
|
96% |
1461
25.3 IPS |
|
|
Machine Translation (Q)
|
55% |
787
21.1 IPS |
