Samsung Galaxy S25 Ultra
Geekbench AI Score
2529
Single Precision Score
3590
Half Precision Score
4720
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | DanielStr |
| Upload Date | March 01 2026 12:03 AM |
| Views | 10 |
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% |
1450
269.6 IPS |
|
|
Image Classification (HP)
|
100% |
2529
470.3 IPS |
|
|
Image Classification (Q)
|
99% |
4603
858.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2449
39.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
3244
52.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
5343
86.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
5414
6.32 IPS |
|
|
Pose Estimation (HP)
|
92% |
9884
11.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
12160
14.2 IPS |
|
|
Object Detection (SP)
|
98% |
1604
127.7 IPS |
|
|
Object Detection (HP)
|
97% |
2062
164.1 IPS |
|
|
Object Detection (Q)
|
85% |
3621
291.7 IPS |
|
|
Face Detection (SP)
|
100% |
4039
48.0 IPS |
|
|
Face Detection (HP)
|
100% |
5755
68.4 IPS |
|
|
Face Detection (Q)
|
97% |
9310
111.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
4125
31.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
6514
50.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
9414
86.9 IPS |
|
|
Style Transfer (SP)
|
89% |
10826
14.1 IPS |
|
|
Style Transfer (HP)
|
88% |
12498
16.2 IPS |
|
|
Style Transfer (Q)
|
98% |
23241
30.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1808
66.8 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
3569
132.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4403
163.2 IPS |
|
|
Text Classification (SP)
|
100% |
755
1.01 KIPS |
|
|
Text Classification (HP)
|
100% |
857
1.14 KIPS |
|
|
Text Classification (Q)
|
93% |
721
967.7 IPS |
|
|
Machine Translation (SP)
|
100% |
1415
24.4 IPS |
|
|
Machine Translation (HP)
|
96% |
1486
25.7 IPS |
|
|
Machine Translation (Q)
|
55% |
785
21.1 IPS |
